Probing Early Stage Aggregates of Amyloidogenic Proteins

Probing Early Stage Aggregates of Amyloidogenic Proteins using Mass Spectrometry Based

Methods

A thesis submitted to the University of Manchester for the degree of

Doctor of Philosophy in the Faculty of Science and Engineering

2016

Ashley S. Phillips

School of Chemistry

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Table of Contents

Table of Contents .................................................................................................................... 2

List of Figures .......................................................................................................................... 6

List of Tables ......................................................................................................................... 11

List of Equations .................................................................................................................... 13

Abbreviations ........................................................................................................................ 14

Abstract ................................................................................................................................. 16

Declaration ............................................................................................................................ 17

Copyright Statement ............................................................................................................. 17

Acknowledgements ............................................................................................................... 19

1. Chapter 1 - Introduction ................................................................................................ 21

1.1. Proteins ................................................................................................................. 22

1.2. Intrinsically Disordered Proteins and Disease ....................................................... 22

1.3. Aggregation ........................................................................................................... 24

1.4. Parkinson’s Disease and α-Synuclein ..................................................................... 25

1.5. Alzheimer’s Disease and the Amyloid-β peptides ................................................. 29

1.6. Disruption of Amyloid Formation .......................................................................... 34

1.7. Biophysical Techniques for the Structural Analysis of Proteins ............................. 36

1.8. Transmission Electron Microscopy ........................................................................ 37

1.9. Mass Spectrometry ............................................................................................... 38

1.10. Tandem Mass Spectrometry ............................................................................. 46

1.11. Cross-linking ...................................................................................................... 50

1.12. Hydrogen Deuterium Exchange Mass Spectrometry ......................................... 50

1.13. Ion Mobility - Mass Spectrometry ..................................................................... 51

1.14. Biological Mass Spectrometry and Ion Mobility – Mass Spectrometry ............. 53

1.15. Summary ........................................................................................................... 57

1.16. References ......................................................................................................... 58

2. Chapter 2 - Experimental ............................................................................................... 73

2.1. Reagents ................................................................................................................ 74

2.2. α-Synuclein Expression and Purification................................................................ 74

2.3. α-Synuclein Aggregation ....................................................................................... 75

2.4. Amyloid-β peptide Sample Preparation ................................................................ 76

2.5. Mass Spectrometry ............................................................................................... 76

2.6. Ion Mobility - Mass Spectrometry ......................................................................... 80

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2.7. Collision Induced Unfolding –Travelling Wave Ion Mobility Mass Spectrometry .. 92

2.8. Electron Transfer Dissociation ............................................................................... 92

2.9. Surface Induced Dissociation ................................................................................ 93

2.10. Cross-linking Ion Mobility - Mass Spectrometry ................................................ 96

2.11. Hydrogen Deuterium Exchange Mass Spectrometry ......................................... 97

2.12. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Electron

Capture Dissociation ......................................................................................................... 97

2.13. Transmission Electron Microscopy .................................................................... 98

2.14. References ......................................................................................................... 99

3. Chapter 3 - Investigating the Structure of α-Synuclein ............................................... 101

3.1. Introduction ........................................................................................................ 102

3.2. Experimental ....................................................................................................... 103

3.2.1. Sample preparation ..................................................................................... 103

3.2.2. Mass Spectrometry ..................................................................................... 103

3.2.3. Ion Mobility - Mass Spectrometry ............................................................... 103

3.2.4. Electron Capture Dissociation - Fourier Transform - Ion Cyclotron Resonance

Mass Spectrometry ..................................................................................................... 103

3.3. Results and Discussion ........................................................................................ 104

3.3.1. The Effect of Solution pH modification ........................................................ 104

3.3.2. The Effect of Ionisation mode ..................................................................... 110


3.3.4. Cross-linking Ion Mobility - Mass Spectrometry .......................................... 115

3.3.5. Investigating α-Synuclein Structure using ECD-FT-ICR MS ........................... 120

3.4. Summary ............................................................................................................. 127

3.5. References........................................................................................................... 128

4. Chapter 4 - Following the Early Stages of α-Synuclein Aggregation ........................... 132

4.1. Introduction ........................................................................................................ 133

4.2. Experimental ....................................................................................................... 135

4.2.1. Sample Preparation ..................................................................................... 135

4.2.2. Aggregation Method ................................................................................... 135



4.2.5. Hydrogen Deuterium Exchange Mass Spectrometry ................................... 135


4.3.1. Following Aggregation via Mass Spectrometry ........................................... 136

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4.3.2. TEM of Aggregates Prepared under Mass Spectrometry Compatible

Conditions ................................................................................................................... 138

4.3.3. In Tip Aggregation ....................................................................................... 139

4.3.4. Probing the Conformational Changes during Aggregation by Ion Mobility -

Mass Spectrometry ..................................................................................................... 142

4.3.5. Probing Conformational Changes during Aggregation by HDX-MS.............. 145

4.4. Summary ............................................................................................................. 148

4.5. References........................................................................................................... 150

5. Chapter 5 - Structure and Interactions of Aβ(1-42) and Aβ(1-40) ............................... 154

5.1. Introduction ........................................................................................................ 155

5.2. Experimental ....................................................................................................... 157

5.2.1. Sample Preparation ..................................................................................... 157


5.2.3. Travelling Wave Ion Mobility Mass Spectrometry ....................................... 157

5.2.4. Electron Transfer Dissociation ..................................................................... 158

5.2.5. Surface Induced Dissociation ....................................................................... 158

5.2.6. Data Analysis ............................................................................................... 158


5.3.1. The Effect of Concentration, Solution Conditions and Ionisation Polarity ... 159

5.3.2. The Effect of Salt Concentration on Structure ............................................. 160

5.3.3. Conformational Stability of Aβ(1-42) probed by CIU-TWIMS ...................... 163

5.3.4. ETD, ETnoD and ETcaD ................................................................................ 165

5.3.5. Surface Induced Dissociation ....................................................................... 169

5.3.5.1. Fragmentation ..................................................................................... 169

5.3.5.2. The Effect of SID on the Conformation Exhibited by Amyloid Species . 173

5.3.6. The Interactions of Aβ(1-42) with Small Molecule Anti-Aggregation Drug

Candidates .................................................................................................................. 177

5.4. Summary ............................................................................................................. 183

5.5. References........................................................................................................... 185

6. Chapter 6 - Conclusions and Future Work ................................................................... 191

6.1. Conclusions and Future Work ............................................................................. 192

6.2. References........................................................................................................... 199

7. Appendices ................................................................................................................... 200

Appendix 1 - Amino Acid Abbreviations .......................................................................... 201

Appendix 2 – Investigating the Structure of α-Synuclein ................................................ 203

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Appendix 3 – Following the Early Stages of α-Synuclein Aggregation ............................. 206

Appendix 3.1 - Following Aggregation via Mass Spectrometry ................................... 209

Appendix 3.2 - In Tip Aggregation ............................................................................... 210

Appendix 3.3 - Probing Conformational Changes during Aggregation by HDX-MS. .... 213

Appendix 4 – Structure and Interactions of Aβ(1-42) and Aβ(1-40) ................................ 214

Appendix 4.1 - The Effect of Concentration, Solution Conditions and Ionisation Polarity

.................................................................................................................................... 215

Appendix 4.2 - Conformational Stability of Aβ(1-42) probed by CIU-TWIMS .............. 217

Appendix 4.3 – Surface Induced Dissociation .............................................................. 219

Appendix 4.3.1 - Preparation of the SID Surface ..................................................... 219

Appendix 4.3.2 - Effect of SID on the Conformation Exhibited by Amyloid species 219

Appendix 4.3.3 - The Absence of Precursor Activation by SID ................................. 223

Appendix 4.4 - The Interactions of Aβ(1-42) with Small Molecule Anti-Aggregation Drug

Candidates .................................................................................................................. 223

References ...................................................................................................................... 231

Final Word Count: 64,490

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List of Figures

Chapter 1 - Introduction

Figure 1.1 - Peptide bond formation……………………………………………………………… 22

Figure 1.2 - The four levels of protein structure……………………………………………. 22

Figure 1.3 - The Protein Quartet Model………………………………………………………… 23

Figure 1.4 - Schematic of the potential species adopted by proteins during

the aggregation process……………………………………………………………… 25

Figure 1.5 - α-Synuclein primary sequence……………………………………………………. 26

Figure 1.6 - The three domains of α-Synuclein……………………………………………… 27

Figure 1.7 - The amyloidogenic and non-amyloidogenic processing pathways

of APP………………………………………………………………………………………… 30

Figure 1.8 - Aβ(1-42) primary sequence………………………………………………………… 30

Figure 1.9 - Overview of the Aβ aggregation process……………………………………. 31

Figure 1.10 - Bernstein mechanism for the oligomerization and fibril

formation of Aβ(1-40) and Aβ(1-42)…………………………………………… 31

Figure 1.11 - Structure of the monomer unit of Aβ(1-40) and Aβ(1-42) fibrils…. 33

Figure 1.12 - The amyloid cascade………………………………………………………………….. 34

Figure 1.13 - RI-OR2 structure………………………………………………………………………… 35

Figure 1.14 - Rutin structure…………………………………………………………………………… 36

Figure 1.15 - The nESI process………………………………………………………………………… 40

Figure 1.16 - Ion trajectories within a quadrupole………………………………………….. 41

Figure 1.17 - Schematic of two ToF geometries………………………………………………. 43

Figure 1.18 - FT-ICR MS cell schematic………………………………..………………………….. 44

Figure 1.19 - The simplified path of cyclotron and magnetron motion imposed

on ions within an FT-ICR MS cell…………………………………………………. 45

Figure 1.20 - MCPs and electron multiplication within a channel……………………. 46

Figure 1.21 - Peptide fragmentation notation…………………………………………………. 46

Figure 1.22 - Workflow of a typical cross-linking-MS experiment……………………. 50

Figure 1.23 - Mobility separation in the IMS region of the Triwave device……… 53

Chapter 2 - Experimental

Figure 2.1 - SDS-PAGE of lysed E. coli cell pellet……………………………………………. 75

Figure 2.2 - QToF schematic………………………………………………………………………….. 78

Figure 2.3 - MoQToF DT-IM-MS instrument schematic…………………………………. 81

Figure 2.4 - Drift cell and lens schematic………………………………………………………. 82

Figure 2.5 - IM-MS experimental workflow example…………………………………….. 84

Figure 2.6 - Waters Synapt G2 instrument schematic……………………………………. 86

Figure 2.7 - Waters Synapt G2S/G2Si instrument schematic…………………………. 87

Figure 2.8 - Synapt Triwave region schematic featuring three TWIGS…………… 87

Figure 2.9 - TWIG/SRIG schematic………………………………………………………………… 87

Figure 2.10 - Example TWIMS CCS calibration plots………………………………………… 92

Figure 2.11 - Structure of 1,3-dicyanobenzene.………………………………………………. 93

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Figure 2.12 - Waters Synapt G2 instrument schematic with SID device

modification…………………………………………………………………............... 94

Figure 2.13 - The position of the SID device within the Waters Synapt G2

instrument…………………………………………………………………………………. 94

Figure 2.14 - SID cell schematic………………………………………………………………………. 95

Figure 2.15 - Structure of the BS3 cross-linking reagent.…………………………………. 96

Chapter 3 – Investigating the Structure of α-Synuclein

Figure 3.1 - α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 6.8,

positive ionisation mode).………………………………………………………….. 104

Figure 3.2 - α-Synuclein mass spectra (70 µM, 50 mM AmAc, pH 6.8, positive

ionisation mode) recorded under the same conditions at

different times………….………………………………………………………………… 106






negative ionisation mode).…………………………………………………………. 110


negative ionisation mode).…………………………………………………………. 111

Figure 3.7 - α-Synuclein (70 µM, 50 mM AmAc, pH 6.8, positive ionisation

mode) A. m/z vs. CCS plot, B. Mass spectrum and C. Charge state

vs. CCS plot………………………………………………………………………………… 114

Figure 3.8 - α-Synuclein mass spectrum (100 µM, 50 mM AmAc) following

cross-linking at pH 4 and pH 8……………………………………………………. 116

Figure 3.9 - α-Synuclein CCSDs with and without cross-linking……………………… 119

Figure 3.10 - α-Synuclein mass spectrum (30 µM, 50 mM AmAc) recorded on a Bruker Solarix 12T FT-ICR MS instrument prior to ECD…………….. 120

Figure 3.11 - ECD fragmentation maps of the α-Synuclein monomer species

investigated at pH 6.8 and pH 3.5.……………………………………………… 122

Figure 3.12 - The annotated mass spectrum of [aSyn+9H]9+ following ECD

fragmentation of α-Synuclein (30 µM, 50 mM AmAc, pH 6.8)……. 123





Chapter 4 – Following the Early Stages of α-Synuclein Aggregation

Figure 4.1 - α-Synuclein MS aggregation time course with an instrument

cone voltage of 60 V…………………………………………………………………… 137

Figure 4.2 - TEM images of oligomers and fibrils formed in MS compatible

buffer…………………………………………………………………………………………. 138

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Figure 4.3 - α-Synuclein in tip aggregation time course spectra……………………. 141

Figure 4.4 - Mass spectra recorded during the α-Synuclein IM-MS

aggregation time course…………………………………………………………….. 142

Figure 4.5 - α-Synuclein CCSDs recorded during a 120 hour IM-MS

aggregation time course…………………………………………………………….. 144

Figure 4.6 - α-Synuclein peptides RFU plots at the 0 hour, 24 hour and 120

hour time points of the HDX-MS aggregation time course…………. 146

Chapter 5 – Structure and Interactions of Aβ(1-42) and Aβ(1-40)

Figure 5.1 - Aβ(1-42) mass spectra at 20 or 50 µM in H2O (pH 2) or 20 mM

AmAc (pH 7.4) collected in positive or negative ionisation mode.. 160

Figure 5.2 - [Aβ42+4H]4+ and [Aβ42+3H]3+ ATDs at 20 µM, pH 7.4 at

increasing AmAc salt concentration, collected in positive

ionisation mode…………………………………………………………………………. 162

Figure 5.3 - [Aβ42-4H]4- and [Aβ42-3H]3- ATDs at 20 µM, pH 7.4 at increasing

AmAc salt concentration, collected in negative ionisation mode… 162

Figure 5.4 - Normalised CIU fingerprint plots of A. [Aβ42+4H]4+ and C.

[Aβ42+3H]3+ in H2O (pH 2) and B. [Aβ42+4H]4+ and D.

[Aβ42+3H]3+ in 20 mM AmAc (pH 7.4)………………………………………… 163

Figure 5.5 - CID fragmentation maps of [Aβ42+4H]4+ in H2O (pH 2) at

increasing collision voltage…………………………………………………………. 164

Figure 5.6 - CID fragmentation maps of [Aβ42+4H]4+ in 20 mM AmAc (pH 7.4)

at increasing collision voltage…………………………………………………….. 164

Figure 5.7 - Spectra of the isolated [Aβ42+4H]4+ (20 µM, 20 mM AmAc, pH

7.4), following incremental reduction of the trap wave height

charge reduction is observed……………………………………………………… 166

Figure 5.8 - Aβ(1-42) monomer absolute intensity divided by the TIC plotted

against the trap region wave height…………………………………………… 166

Figure 5.9 - A comparison of ETD and ETcaD fragmentation and location…….. 168

Figure 5.10 - ETcaD fragmentation map for [Aβ42+4H]4+ in 20 mM AmAc (pH

7.4). ETD with supplemental collisional activation (25 V)……………. 169

Figure 5.11 - SID fragmentation map for [Aβ42+4H]4+ in 20 mM AmAc (pH

7.4). SID collision voltage: 40 V…………………………………………………… 170

Figure 5.12 - SID fragmentation map for [Aβ40+4H]4+ in 20 mM AmAc (pH

7.4). SID collision voltage: 40 V…………………………………………………… 171

Figure 5.13 - Comparison of CID vs SID fragmentation of [Aβ42+4H]4+ in 20

mM AmAc (pH 7.4). A. CID: 50 V, B. CID/SID: 0 V C. SID: 40 V……… 172

Figure 5.14 - [Aβ42+4H]4+ C-terminal SID b- fragment ion ATDs in 20 mM

AmAc (pH 7.4). SID collision voltage: 40V…………………………………… 173

Figure 5.15 - [Aβ40+4H]4+ C-terminal SID b- fragment ion ATDs in 20 mM

AmAc (pH 7.4). SID collision voltage: 40 V………………………………….. 175

Figure 5.16 - ATDs of the charge reduced [Aβ40+3H]3+ central region SID b-

fragment ions in 20 mM AmAc (pH 7.4). SID collision voltage: 40

V………………………………………………………………………………………………… 177

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Figure 5.17 - Mass spectra of Aβ(1-42) at 20 µM in H2O (pH 2) at increasing

Aβ(1-42):RI-OR2 ratio…………………………………………………………………. 179

Figure 5.18 - Absolute intensity of all observed species plotted against Aβ(1-

42):RI-OR2 ratio in H2O (pH 2)……………………………………………………. 179

Figure 5.19 - ATDs and calculated CCS values of ligand bound Aβ(1-42),

[(Aβ42:Ligand)±4H]4± at a ratio of 1:1 (1:5, Figure 4.19D) in H2O

(pH 2) or 20 mM AmAc (pH 7.4) at 20 µM in positive or negative

ionisation mode…………………………………………………………………………. 182

Appendices

Appendix 3 – Following the Early Stages of α-Synuclein Aggregation

Figure A3.1 - α-Synuclein MS aggregation time course with an instrument

cone voltage of 60 V normalised to the 0 hour spectrum base

peak intensity…………………………………………………………………………….. 209

Figure A3.2 - Microscope image of the nESI tip used to spray the sample

recorded in Figure 4.3 and Figure A3.3………………………………………. 210

Figure A3.3 - α-Synuclein in tip aggregation time course spectra (Figure 4.3),

normalised to the 0-5 minute spectrum base peak intensity……… 211

Figure A3.4 - α-Synuclein in tip aggregation time course replicate spectra,

normalised to the 0-5 minute spectrum base peak intensity……… 212

Figure A3.5 - Plot of the α-Synuclein peptides RFU at the 0 hour and 120 hour

time points analysed together within DynamX…………………………… 213

Figure A3.6 - Plot of the α-Synuclein peptides RFU at the 0 hour and 120 hour

time points analysed independently within DynamX………………….. 213

Appendix 4 – Structure and Interactions of Aβ(1-42) and Aβ(1-40)

Figure A4.1 - Aβ(1-42) mass spectra in H2O (pH 2) collected using different

instruments and using different source conditions…………………….. 216

Figure A4.2 - Aβ(1-42) mass spectra in 20 mM AmAc (pH 7.4) collected under

different source conditions and on different instruments………….. 217

Figure A4.3 - CIU-TWIMS ATDs of [Aβ42+4H]4+ and [Aβ42+3H]3+ in H2O (pH 2)

at increasing collision voltage…………………………………………………….. 218

Figure A4.4 - CIU-TWIMS ATDs of [Aβ42+4H]4+ and [Aβ42+3H]3+ in 20 mM

AmAc (pH 7.4) at increasing collision voltage……………………………… 218

Figure A4.5 - ATDs of [Aβ42+4H]4+ b- fragment ions in 20mM AmAc (pH 7.4),

observed during CIU-TWIMS experiment. Collision voltage: 40 V. 220

Figure A4.6 - C-terminal SID b- fragment ion ATDs of the charge reduced

[Aβ42+3H]3+ (20 mM AmAc, pH 7.4). SID collision voltage: 40 V…. 221

Figure A4.7 - C-terminal SID b- fragment ion ATDs of the charge reduced

[Aβ40+3H]3+ (20 mM AmAc, pH 7.4). SID collision voltage: 40 V…. 222

10

Figure A4.8 - ATDs of the isolated [Aβ42+4H]4+ (A to E) and [Aβ40+4H]4+ (F to

J) precursor ions in 20 mM AmAc (pH 7.4), following the

application of increasing SID collision voltage…………………………….. 223

Figure A4.9 - Aβ(1-42) mass spectra at increasing Aβ(1-42):Bradykinin ratio in

H2O (pH 2)………………………………………………………………………………….. 224

Figure A4.10 - ATDs and calculated CCS values of [Aβ42+4H]4+ and [Aβ42+3H]3+

in the absence and presence of RI-OR2/Rutin/Bradykinin at a 1:1

ratio in H2O (pH 2)……………………………………………………………………… 226

Figure A4.11 - ATDs and calculated CCS values of [Aβ42±4H]4± and [Aβ42±3H]3±

in the absence and presence of Rutin or Bradykinin at 1:1 (Aβ(1-

42) and Rutin, negative ionisation mode: ratio 1:5) in 20 mM

AmAc (pH7.4)…………………………………………………………………………….. 226

Figure A4.12 - ATDs and calculated CCS values of [(Aβ42:Bradykinin)+4H]4+ at a

ratio of 1:1 in H2O (pH 2) or 20 mM AmAc (pH 7.4), collected in

positive ionisation mode……………………………………………………………. 227

Figure A4.13 - The ATD and calculated CCS value of [RI-OR2+2H]2+ in H2O (pH 2)

collected in positive ionisation mode…………………………………………. 227

Figure A4.14 - The ATD and calculated CCS value of [BK+H]1+ in H2O (pH 2)


Figure A4.15 - The ATD and calculated CCS values of [BK+H]1+ and [BK+2H]2+ in

20 mM AmAc (pH 7.4) collected in positive ionisation mode……… 228

Figure A4.16 - The ATD and calculated CCS value of [Rutin+1H]1+ in H2O (pH 2)


Figure A4.17 - The ATD and calculated CCS value of [Rutin+1H]1+ in 20 mM

AmAc (pH 7.4) collected in positive ionisation mode…………………. 229

Figure A4.18 - Mass spectra and ATDs of the main and shoulders of isotopic

peaks of the Aβ(1-42):Rutin bound species in Figure 5.19C………… 230

Figure A4.19 - Aβ(1-42) mass spectra (20 mM AmAc, pH 7.4) in the absence (A)

and presence (B & C) of Rutin at a 1:5 ratio collected in negative

ionisation mode…………………………………………………………………………. 230

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List of Tables

Chapter 1 - Introduction

Table 1.1 - Summary of advantages and disadvantages of biophysical

techniques for the structural analysis of IDPs………………………………. 56

Chapter 2 - Experimental

Table 2.1 - Typical operating parameters for MS experiments performed on a

QToF Ultima / Ultima Global instrument with MS Vision high mass

upgrade………………………………………………………………………………………… 79

Table 2.2 - Typical operating parameters for DT-IM-MS experiments in

positive ionisation mode performed on the MoQToF IM-MS

instrument…………………………………………………………………………………… 82

Table 2.3 - The voltage ranges and typical drift cell lens voltages for the

MoQToF in positive ionisation mode……………………………………………. 83

Table 2.4 - Typical operating parameters for TWIMS experiments performed

on Waters Synapt instrument operated in positive ionisation

mode……………………………………………………………………………………………. 88

Table 2.5 - Typical operating parameters for TWIMS experiments performed

on Waters Synapt instrument operated in negative ionisation

mode……………………………………………………………………………………………. 90

Table 2.6 - Supplemental typical instrument parameters for ETD

experiments…………………………………………………………………………………. 93

Table 2.7 - Typical operating parameters for the SID cell lenses in flythrough

and SID modes……………………………………………………………………………… 96

Chapter 3 - Investigating the Structure of α-Synuclein

Table 3.1 - The fragments identified of α-Synuclein dimers, [(aSyn)2+13H]13+,

[(aSyn)2+15H]15+ and [(aSyn)2+17H]17+ at pH 6.8 and pH 3.5

following ECD……………………………………………………………………………….. 125

Chapter 5 – Structure and Interactions of Aβ(1-42) and Aβ(1-40)

Table 5.1 - Calculated CCS values of the unbound [Aβ42+4H]4+ and

[Aβ42+3H]3+ in the absence and presence of RI-OR2, Rutin and

Bradykinin in H2O (pH 2) or 20mM AmAc (pH 7.4)………………………… 182

12

Appendices

Appendix 1 – Amino Acid Abbreviations

Table A1.1 - Amino acid structures and properties…………………………………………… 201

Appendix 2 – Investigating the Structure of α-Synuclein

Table A2.1 - Complete list of α-Synuclein species observed in Chapter 3

figures………………………………………………………………………………………….. 204

Table A2.2 - Experimental CCS values for α-Synuclein (70µM, 50mM AmAc, pH

6.8) collected in positive ionisation mode…………………………………….. 205


Table A3.1 - Complete list of α-Synuclein species observed in Chapter 4

figures………………………………………………………………………………………….. 207

Table A3.2 - Complete list of α-Synuclein species observed in Appendix 3

figures………………………………………………………………………………………….. 208


Table A4.1 - Complete list of Aβ(1-42), bound complexes and small molecule

drug candidate species observed in Chapter 5 figures………………….. 214

Table A4.2 - Complete list of Aβ(1-42), bound complexes and small drug

molecule candidate species observed in Appendix 4 figures………… 214

Table A4.3 - Instrument parameters and source conditions applied during

collection of the spectra in Figure A4.1A to A4.1C………………………… 215

Table A4.4 - Instrument parameters and solution conditions applied during

the collection of the spectra in Figure A4.2………………………………….. 217

Table A4.5 - Instrument parameters and solution conditions used for Aβ(1-42)

binding experiments…………………………………………………………………….. 225

13

List of Equations

Chapter 1 – Introduction

Equation 1.1 - ±𝜙0 = ±(𝑈 − 𝑉 cos 𝜔𝑡) ………………………………………………………. 41

Equation 1.2 - 𝐸𝑘 = 𝑚𝑣2

2= 𝑧𝑒𝑉𝑠 ……………………………………………………………………. 42

Equation 1.3 - 𝑣 = (2𝑧𝑒 𝑉𝑠 𝑚⁄ )1 2⁄ …………………………………………………….............. 42

Equation 1.4 - 𝑡 = 𝐿

𝑣 ……………………………………………………………………………………… 42

Equation 1.5 - 𝑡2 = 𝑚

𝑧 (

𝐿2

2𝑒𝑉𝑠) ………………………………………………………………………… 42

Equation 1.6 - 𝑧𝐵 = 𝑚𝑣

𝑟 ………………………………………………………………………………… 43

Equation 1.7 - 𝑓 = 𝑣

2𝜋𝑟 ………………………………………………………………………………….. 44

Equation 1.8 - 𝜔 = 2𝜋𝑓 = 𝑣

𝑟=

𝑧

𝑚𝐵 ……………………………………………………………… 44

Equation 1.9 - 𝑣𝑑 = 𝐾𝐸 …………………………………………………………………………………. 51

Equation 1.10 - 𝐾 = 3𝑧𝑒

16𝑁 (

2𝜋

𝜇𝑘𝐵𝑇)

1 2⁄ 1

𝛺 ……………………………………………………………. 51

Equation 1.11 - 𝐾0 = 𝐾𝑇𝑜𝑃

𝑃𝑜𝑇 ………………………………………………………………….............. 52

Chapter 2 – Experimental

Equation 2.1 - 𝑦 = 𝑦0 + 𝐴

𝑤√𝜋

2 𝑒

−2(𝑥−𝑥𝑐)2

𝑤2 ……………………………………………………… 84

Equation 2.2 - 𝑡𝑎 = 𝑡𝑑 + 𝑡0 …………………………………………………………………………. 85

Equation 2.3 - 𝐾 = 𝐿2

𝑡𝑑𝑉 …………………………………………………………………………………. 85

Equation 2.4 - 𝐾0 = 𝐾𝑇0

𝑇

𝑃

𝑃0 …………………………………………………………………………… 85

Equation 2.5 - 𝑡𝑑 = 𝑡𝑎 − 𝑡𝑜 = 𝐿2𝑇0𝑃

𝐾0𝑇𝑃0𝑉 ………………………………………………………… 85

Equation 2.6 - 𝛺 = 3𝑧𝑒

16𝑁 (

2𝜋

µ𝑘𝐵𝑇)

1

2 1

𝐾0 ……………………………………………………………….. 85

Equation 2.7 - 𝑡′𝑑 = 𝑡𝑑 − [𝑐√𝑚/𝑧

1000] ……………………………………………………………….. 91

Equation 2.8 - 𝛺′ = 𝛺

𝑧 (1 µ⁄ )1/2 ………………………………………………………………………… 91

Equation 2.9 - ln 𝛺′ = 𝑥 ln 𝑡′𝑑 + ln 𝐴 …………………………………………………………… 92

Equation 2.10 - 𝑡′′𝑑 = 𝑡′𝑑𝑥

𝑧 (1 µ⁄ )1 2⁄ ……………………………………………………………. 92

14

Abbreviations

aSyn α-Synuclein

AFM Atomic Force Microscopy

AmAc Ammonium Acetate

ANS 8-Anilinonapthalene-1-sulfonic acid

AS Alternative Splicing

ATD Arrival Time Distribution

Aβ / Aβ40 / Aβ42 Amyloid-β / Amyloid-β (1-40) / Amyloid-β (1-42)

BEH Ethylene Bridged Hybrid

BK Bradykinin

CAD Collisional Activation Dissociation

CCD Charge Coupled Device

CCS Collision Cross Section

CCSD Collision Cross Section Distribution

CD Circular Dichroism

CEM Chain Ejection Model

CHC Central Hydrophobic Cluster

CID Collision Induced Dissociation

CIU-TWIMS Collision Induced Unfolding – Travelling Wave Ion Mobility Mass

Spectrometry

CRM Charge Reduction Model

Cryo-EM Cryo- Electron Microscopy

CSD Charge State Distribution

Da Dalton

DC Direct Current

DI Deionised

DLS Dynamic Light Scattering

DT-IM-MS Drift Time Ion Mobility Mass Spectrometry

DTT Dithiothreitol

E. coli Escherichia coli

ECD Electron Capture Dissociation

EDTA Ethylenediaminetetraacetic acid

EGCG Epigallocatechin Gallate

EOM Ensemble Optimisation Model

ESI ElectroSpray Ionisation

ETcaD Electron Transfer Collisional Activation Dissociation

ETD Electron Transfer Dissociation

FRET Förster Resonance Energy Transfer

FT-ICR MS Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

FTIR Fourier Transform Infrared Spectroscopy

HDX Hydrogen Deuterium Exchange

HFIP Hexafluoroisopropanol

ID Inner Diameter

IDP/R Intrinsically Disordered Protein/Region

15

IEM Ion Ejection Model

IM-MS Ion Mobility Mass Spectrometry

LB Luria Broth

LC Liquid Chromatography

m/z Mass to Charge ratio

MALDI Matrix Assisted Laser Desorption Ionisation

MAP Microtubule-Associated Protein

MCPs Multichannel Plates

mRNA Messenger Ribonucleic acid

MS Mass Spectrometry

MS/MS Tandem Mass Spectrometry

MW Molecular Weight

MWCO Molecular Weight Cut Off

nESI Nano ElectroSpray Ionisation

NFT Neurofibrillary Tangle

NMR Nuclear Magnetic Resonance Microscopy

NOE Nuclear Overhauser Effect

OD Outer Diameter

PBS Phosphate Buffer Solution

PD Parkinson’s Disease

PHFs Paired Helicoidal Filaments

PLGS ProteinLynx Global Server

PTM Post-Translational Modification

QToF Quadrupole Time of Flight

RF Radio Frequency

RFU Relative Fractional Uptake

ROS Reactive Oxygen Species

rpm Revolutions per minute

SAXS Small Angle X-ray Scattering

SDS-PAGE Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis

SID Surface Induced Dissociation

SRIG Stacked Ring Ion Guide

TDC Time-to-Digital Converter

TEM Transmission Electron Microscopy

ThT Thioflavin T

TIC Total Ion Current

ToF Time of Flight

Tris Tris(hydroxymethyl)aminoamethane

TWIG Travelling Wave Ion Guide

TWIMS Travelling Wave Ion Mobility Mass Spectrometry

UPLC Ultra High Pressure Liquid Chromatography

UV Ultraviolet

wt Wildtype

16

Abstract

The University of Manchester

Candidate’s name: Ashley Sean Phillips

Degree title: Doctor of Philosophy

Thesis title: Probing Early Stage Aggregates of Amyloidogenic Proteins using Mass

Spectrometry Based Methods

Date: 14 December 2016

Mass Spectrometry (MS) and Ion Mobility – Mass Spectrometry (IM-MS) can be used to investigate protein structure and dynamics and are ideally positioned to study intrinsically disordered and amyloidogenic proteins, whose diverse conformational space and/or oligomeric state is hard to track accurately. This thesis uses hybrid MS approaches including IM-MS, Cross-linking IM-MS and ECD-FT-ICR MS to probe the structure of α-Synuclein and Amyloid-β (Aβ).

For α-Synuclein, the effect of solution pH and ionisation polarity on the species observed by MS and IM-MS is investigated. Conformational families observed by Cross-linking IM-MS provides a link between the solution and gas phase structures of α-Synuclein observed here and our data correlates with that reported by other groups. MS, IM-MS and HDX-MS are used to probe α-Synuclein during the early stages of aggregation. A specific aggregation competent conformer is not observed suggesting that the solution constituents remain conformationally dynamic. We observe shifts in the species observed by MS and IM-MS between samples and our data contributes to an array of conflicting structural studies indicating that α-Synuclein adopts a diverse range of species with significant variation.

For Aβ(1-42) and Aβ(1-40) Collision Induced Unfolding and ETD/ETcaD demonstrate that Aβ(1-42) adopts a compact conformation bound by intramolecular interactions. Changes to the Aβ(1-42) and Aβ(1-40) ATDs following SID are correlated to known structure influencing intermolecular interactions and demonstrate the large structural difference between Aβ(1-42) and Aβ(1-40) despite differing by only two C-terminal amino acids. IM-MS is used to classify the mode of action of anti-aggregation drug candidates on Aβ(1-42). The anti-aggregation capacity of the retro-inverso peptide, RI-OR2 is shown to result from inducing the compaction or extension of Aβ(1-42), preventing the adoption of an aggregation competent structure. In contrast, the flavonoid Rutin is shown to act solely through inducing Aβ(1-42) compaction.

This thesis demonstrates the power of MS based methods to investigate the diverse range of structures of intrinsically disordered aggregating proteins implicated in disease.

17

Declaration

No portion of the work referred to in the thesis has been submitted in support of an

application for another degree or qualification of this or any other university or other

institute of learning.

Copyright Statement

i. The author of this thesis (including any appendices and/or schedules to this thesis)

owns certain copyright or related rights in it (the “Copyright”) and s/he has given

The University of Manchester certain rights to use such Copyright, including for

administrative purposes.

ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic

copy, may be made only in accordance with the Copyright, Designs and Patents Act

1988 (as amended) and regulations issued under it or, where appropriate, in

accordance with licensing agreements which the University has from time to time.

This page must form part of any such copies made.

iii. The ownership of certain Copyright, patents, designs, trade marks and other

intellectual property (the “Intellectual Property”) and any reproductions of

copyright works in the thesis, for example graphs and tables (“Reproductions”),

which may be described in this thesis, may not be owned by the author and may be

owned by third parties. Such Intellectual Property and Reproductions cannot and

must not be made available for use without the prior written permission of the

owner(s) of the relevant Intellectual Property and/or Reproductions.

iv. Further information on the conditions under which disclosure, publication and

commercialisation of this thesis, the Copyright and any Intellectual Property and/or

Reproductions described in it may take place is available in the University IP Policy

(see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any

relevant Thesis restriction declarations deposited in the University Library, The

University Library’s regulations (see

http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s

policy on Presentation of Theses

http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487

http://www.manchester.ac.uk/library/aboutus/regulations

18

“Even the knowledge of my own fallibility cannot keep me from making mistakes. Only when I fall do I get up again” Vincent van Gogh

“What is a scientist after all? It is a curious man looking through a keyhole, the keyhole of nature,

trying to know what’s going on.” Jacques Cousteau

19

Acknowledgements

I would not have made it to the end of this adventure without the knowledge and advice of

many colleagues, advisors, friends and family. I would like to thank my supervisor, Perdita

Barran, my secondary supervisors Tilo Kunath, Cait MacPhee (in Edinburgh, but not

forgotten) and Roy Goodacre for their words of advice during this rocky roller coaster. My

collaborators, Garth Cooper, Isabel Riba Garcia and David Allsop. Ewa Jurneczko, you

guided me through my first steps into the wonderful world of mass spectrometry and I will

be forever grateful. Alex Gomes, your passion for mass spectrometry is unrivalled and you

are an inspiration, thanks for your help with the cross-linking and ECD experiments. Jay

Gillam for late night protein expression, which made all of this possible. Jason Kalapothakis

and my project students Jonas Gasparavicious and Hassan Saleem thanks for your help with

the α-Synuclein time course experiments. Steve Mitchell for your help with TEM. Jon

Williams for your help with ETD. Bruno Bellina for your help with ETD and SID. Logan

MacKay and SIRCAMS for your help with ECD. Sophie Harvey for your help with ECD and

SID. Ben Allsop for your help with Aβ(1-42) binding experiments and being an

overwhelmingly cheerful chap. The DTC in Glasgow for having the initial faith in me and for

a brilliant Masters year. I would like to thank the support staff at the University of

Edinburgh and the University of Manchester, without your help my experiments would

never have made the leap from ideas into reality. Thanks to MIB stores, you made buying

gloves fun, but sadly only until midday on Fridays.

Thanks to PBRGroup old and new. Thanks to: Fellow Dr Triathlete Bex Beveridge, you beat

me in this race. Chris Nortcliffe for whisky lessons and mammoth games sessions. Ellie

Dickinson, first of her name, for reminding me of the Leu Enk lock mass every time I needed

it. Jakub, the best flat mate I have ever had, even though you left the hob on. Kamila, road

trip buddy, gym buddy and Wagakamas head chef (Chica, you are fabulous!). Rosie, thanks

for late night chats, pizza and cycling with me in the snow and hail. Alina, for proofreading

everything, thanks for making me sound human. Chris G for putting me in his

acknowledgments. Jacky for the maple syrup. Naza, my desk and squash partner, rematch?

Maria, the mother hen, thanks for adopting me. Thanks to Lukasz, Claire, Pancake and

Crumpet, for housing a stray scientist in the last stressful months of my sentence. Nick

O’Meara for some great cycling adventures. I have made some truly wonderful friends in

Glasgow, Edinburgh and Manchester, I cannot mention everyone here, but you have all

made my PhD four unforgettable years!

20

Thanks to my entire family for their support. To Ell for his brutal brotherly support and to

Inka for keeping me company. Finally, Mum and Dad, thanks for putting up with all my

grumbles, for the pick me up chats when I was feeling down and for supplying my coffee,

biscuit and foam banana addictions.

21

1 Introduction

Intrinsically disordered proteins challenge the traditional structure = function paradigm,

exhibiting regions of complete disorder while still performing essential biological functions.

As a result, these proteins are implicated in many diseases. The aggregation of these

proteins is complex and features a diverse array of species.

Analysis of the structure and formation of the early species in the aggregation process is

critical for understanding the disease and designing therapeutics. Mass Spectrometry and

Ion Mobility - Mass Spectrometry represent a solution where other biophysical methods

falter providing valuable insights into the species present and their structure.

22

1.1. Proteins

Proteins are the building blocks and work horses of the cellular environment. Peptides and

proteins are polymers of amino acids linked by an amide or peptide bond (Figure 1.1).

Amino acids are small organic molecules consisting of an amino group (-NH2), a carboxyl

group (-COOH), a hydrogen atom and a variable R group.

Figure 1.1 – Peptide bond formation.

The properties of the twenty common amino acids which make up eukaryotic proteins, are

defined by the variable R group, see Appendix Table A1.1. There are four levels of protein

structure (Figure 1.2). A proteins primary structure is the order of amino acids which make

up the polypeptide chain of the protein. A proteins secondary structure is the assumption

of structural elements including α-helices and β-sheets. A proteins tertiary structure is the

three dimensional arrangement of these structural elements with turns and regions of

disorder. A proteins quaternary structure is the three dimensional arrangement of protein

subunits which may possess tertiary structure.

Figure 1.2 - The four levels of protein structure.

1.2. Intrinsically Disordered Proteins and Disease

Intrinsically Disordered Proteins (IDPs) are biologically active despite the possession of

sometimes substantial regions that lack stable secondary structure and challenge the

traditional structure = function paradigm. IDPs are not rare; more than 50% of eukaryotic

proteins contain significant regions of disorder (IDRs), rising to 70% of signalling proteins [1,

2]. Due to their abundance, it is logical that IDPs perform important biological functions.

23

IDPs have been shown to be involved in a range of biological functions, from acting as

chaperones to acting as hubs in signalling networks [2]. In general, IDPs feature few

hydrophobic residues and a high proportion of charged residues [3, 4]. An IDPs primary

structure is enriched for disorder promoting residues (Pro, Arg, Gly, Gln, Ser, Glu, Lys, Ala)

and depleted of order promoting residues (Cys, Trp, Tyr, Phe, Ile, Leu, Val and Asn) [5]. The

Protein Trinity model proposed by Dunker and Obradovic [6] and extended by Uversky into

the Protein Quartet model [7] (Figure 1.3), rationalises IDP functionality as arising from one

of four states or the transition between two [2].

Figure 1.3 - The Protein Quartet Model. The model suggests that function results from the assumption of one state or the transition between two. Based on a figure in [7].

Many IDPs undergo a disorder to order transition on binding, giving a high specificity but

low affinity property [2]. This has led to IDPs being defined as promiscuous proteins, having

multiple interaction partners and serving as hubs of signalling networks [2]. Post-

Translational Modifications (PTMs), known to be involved in controlling the function of

many proteins, occur preferentially in IDRs as many of the modifiable residues are also

classified as disorder promoting residues [5].

The involvement of IDPs in many important biological functions has led to their implication

in a range of diseases and the creation of the Disorder in Diseases or D2 concept [2, 8]. The

properties of IDPs which lead to their use within many important biological processes are

also the reason for their implication in many diseases. Alternative Splicing (AS) enables the

production of multiple mRNAs from a single precursor premRNA. Regions of AS correlate

well with IDRs meaning abnormal AS, which has been implicated in disease, can interfere

with protein-protein interactions [8]. In addition, the preference for protein function

regulating PTMs in IDRs and the position of IDPs as signalling network hubs due to their

24

promiscuous binding, further links IDPs to disease, as their alteration can lead to

deleterious effects [2].

1.3. Aggregation

Protein aggregation is commonly exploited in nature. Functional amyloids are present in up

to 40% of biofilm producing bacteria [9, 10]. Functional amyloids are also found in animals

such as the Silkmoth. Chorion is a functional amyloid and a major component of the

Silkmoth eggshell, which protects the oocyte and developing embryo [10, 11].

The Protein Misfolding Diseases are a range of human diseases arising from a protein or

peptides inability to retain its native conformation [12]. Many neurodegenerative diseases

including Parkinson’s disease and Alzheimer’s disease form a disease subset, which result

from a proteins aggregation and the formation of intra or extra-cellular amyloid deposits

[12-14]. The proteins implicated in these diseases are commonly disordered and a study of

the proteins implicated in three major neurodegenerative diseases, Huntington’s disease,

Parkinson’s disease and Alzheimer’s disease found levels of disorder of >81%, >75% and

>80%, respectively [15]. The D2 concept has recently been expanded into the D3

concept,

Disorder in neuroDegenerative Disease [14].

Understanding the aggregation process of the proteins involved in the aforementioned

diseases is an important step in designing therapeutics and much of this work is conducted

in vitro. The in vitro aggregation of proteins falls into two categories, firstly IDPs which

feature elements in their primary sequences which predispose them to aggregation [16].

The second category are globular proteins which must be subjected to specific conditions

such as heat, low pH or shaking [16]. The in vitro aggregation of proteins is very susceptible

to modification by environmental conditions including the initial concentration, pH,

aggregation temperature and the presence of contaminants [17, 18].

Aggregation in vivo on the other hand can be the result of mutations such as in Parkinson’s

disease. Aggregation may also result from an errant enzymatic cleavage mechanism such as

the Aβ peptides in Alzheimer’s disease [17] or by a defect in protein homeostasis such as

where the misfolded protein concentration exceeds the capabilities of the cell to deal with

it [16]. An example of this is the accumulation of α-Synuclein as a result of duplication and

triplication mutations in Parkinson’s disease [19-21]. In vivo aggregation can also result

from environmental stress triggers such as Reactive Oxygen Species (ROS) [16].

25

The aggregation process is not a simple switch from monomer to amyloid fibril and features

multiple stages and species, as demonstrated in Figure 1.4. The aggregation pathways of

proteins are highly diverse. Frieden discusses two aggregation mechanisms for protein

aggregation, isodesmic and the nucleation-elongation mechanism and how the

characteristics of IDPs, complicate the definition of their assembly mechanism [22]. Both α-

Synuclein and the Aβ peptides aggregate via a version of the nucleation-elongation

mechanism [17, 23]. Aggregation via this mechanism can be divided into three phases, the

initial lag phase during which the aggregation nuclei form [10, 22]. The aggregation nucleus

varies and growth results via the addition of subunits [22]. The lag phase is followed by the

log phase in which the nuclei are extended into fibrils and other species [10]. Finally, the

saturation phase in which the supply of monomer units is exhausted [10].

Figure 1.4 - Schematic of the potential species adopted by proteins during the aggregation process. Figure reproduced from [10].

The log phase of aggregation is populated by a range of oligomeric species including

spherical [24], ring-like [25] and tubular [26]. The amyloid fibril is the most recognisable

species of the aggregation cascade. Fibrils have been characterised in vitro and typically

consist of several protofilaments, twisted together to form the rope-like fibril, typically 7 to

13 nm wide [12]. The protofilaments are arranged so that the β-strands run perpendicular

to the long axis of the fibril in a cross-β structure (Figure 1.4) [12].

1.4. Parkinson’s Disease and α-Synuclein

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder

worldwide, affecting 2% of the world population over the age of 65 [27]. PD and other age

related neurodegenerative disorders are poised to put extra stress on healthcare machinery

worldwide as the number of people aged 60 and over is predicted to rise from 11% (2011)

to 22% by 2050 [28].

26

James Parkinson first described PD in 1817 [29] and it is characterised clinically by tremor,

bradykinesia, rigidity and a loss of postural reflexes [30, 31]. Neuropathologically, PD is

characterised by the presence of proteinaceous Lewy Body inclusions in, and the selective

degeneration of, the dopaminergic neurons of the Substantia nigra pars compacta [31, 32].

This neuronal loss is the cause of PD’s motor symptoms and is only evident following the

loss of 50% of the neurons [33]. Lewy Bodies were first described as a feature of specific PD

nigral pathology by Tretiakoff [31, 34, 35]. Phase and Electron microscopy studies by Duffy

and Tennyson demonstrated that Lewy bodies are composed of filamentous structures,

which were subsequently found to be composed primarily of α-Synuclein [32, 35, 36].

α-Synuclein is a 140 residue, 14.5kDa IDP member of the Synuclein family (Figure 1.5). The

function of α-Synuclein is currently unknown; however, evidence that α-Synuclein localises

at the synapse [37] and co-localises with synaptic vesicles [38, 39] suggests that it has a role

in synaptic transmission [40]. α-Synuclein has also been demonstrated to interact with over

fifty different ligands and has previously been observed in the nucleus of the cell, although

its role is not yet known [40-44]. The discovery of six point substitution mutations (A30P

[45], E46K [46], H50Q [47], G51D [48], A53E [49] and A53T [50]) and duplication [20, 21]

and triplication [19] mutations of the α-Synuclein encoding SNCA gene, leading to the

presentation of idiopathic resembling and early onset PD, respectively further implicate α-

Synuclein in PD aetiology.

Figure 1.5 - α-Synuclein primary sequence.

α-Synuclein can be divided into three domains (Figure 1.6), the N-terminal amphipathic

domain, the central NAC domain and the acidic C-terminal domain. The classification of

these domains varies. The N-terminal domain of α-Synuclein features four of seven

27

imperfect KTKEGV repeats which confer the domains α-helical propensity [40, 43]. The N-

terminal domain is important for lipid binding and assumes a helical structure upon binding

lipid micelles [43, 51, 52]. The central NAC domain is highly hydrophobic and features three

imperfect KTKEGV repeats [41]. The NAC domain is highly amyloidogenic and extensive

evidence demonstrates that it is responsible for the aggregation of α-Synuclein [43, 53].

The deletion of the amino acid residues 71 to 82, located in the NAC region of α-Synuclein,

prevents aggregation in vitro [54] and in vivo [55]. In addition, β-Synuclein and α-Synuclein

exhibit significant sequence homology (78%), similar biological properties and subcellular

localisation [54, 56]. However, β-Synuclein differs from α-Synuclein in the NAC region and

as a result, does not aggregate and is not found in Lewy inclusions [54-56]. The central

domain (residues 30 – 100) is slightly positive charged (+3 net charge, 9 positive, 6 negative

charges) [41]. The acidic C-terminal domain of α-Synuclein is highly negatively charged (-8

net charge, no positive residues) which explains the long-range interactions observed

between the central and C-terminal domains [41]. The proline enriched C-terminal domain

remains flexible and unstructured and is home to many protein-protein and protein-small

molecule interaction sites [41, 57].

The native state of α-Synuclein is an issue of debate; the accepted structure is a natively

unfolded monomer, driven by its low hydrophobicity and high net charge [41, 58]. This was

challenged by Bartels et al. who suggested that it occurs physiologically as a helically folded

tetramer [59] and that the monomer phenotype is a result of expression protocols. These

results are highly contested [60-63].

α-Synuclein purified from ex vivo brain samples has a mass of 14681 Da (nominal mass,

14460 Da) which suggests α-Synuclein undergoes some form of PTM [64, 65]. A review of

extensive α-Synuclein PTMs and their effects can be found in [66].

Figure 1.6 - The three domains of α-Synuclein. Figure based on [33, 41, 43, 67].

α-Synuclein follows a nucleation dependent aggregation process and displays characteristic

sigmoidal growth kinetics with a distinct lag phase [23, 68-71]. The aggregation nucleus is a

dimer, which displays no stable secondary structure [23, 72, 73]. The formation of the

28

nucleus is the rate limiting step in the aggregation process [74]. Following the formation of

the aggregation nuclei, the log phase of exponential growth occurs during which oligomeric

protofibrillar and fibril species are formed. These oligomers are both on and off-pathway

species and a wide range of morphologies have been identified [75]. Oligomer morphology

is influenced by the aggregation conditions used and the presence of small molecules.

Curcumin, for instance, stabilises large oligomers and elongated protofibrils whilst metal

ions induce annular, ring-like oligomers [75-79]. Spherical [24], spheroidal [80] and tubular

[26] oligomers have also been identified. The secondary structure component of the

oligomers is highly diverse and varies from α-helical to β-sheet [75, 80, 81]. The amyloid

fibrils found in Lewy Bodies have a β-sheet rich structure and exhibit the characteristic

cross-β diffraction pattern [82]. Fibrils range in width but typically have a diameter between

5 and 10 nm and vary in length, up to 10 µm [31, 83-85]. The core of the fibril is composed

of the central region of α-Synuclein, spanning residues 30 to 110, although the exact limits

of this region are disputed [86-88]. These residues are arranged into five β-strands

separated by several loops [84, 89]. The N- and C- terminal regions remain unstructured

[88, 90]. A variety of fibril morphologies have been observed including twisted and

untwisted, curved and straight, periodic and non-periodic [31, 75, 82, 86, 91, 92]. Fibril

morphology is influenced by the experimental aggregation conditions including

concentration, pH and the presence of metal ions [18, 75, 83].

Fibrils are traditionally considered the toxic species; however, therapeutic strategies which

promote inclusion formation lead to reduced α-Synuclein mediated toxicity [93]. Increasing

evidence including toxicity in the absence of fibrils in animal models [94], toxicity from

partially aggregated α-Synuclein [95] and the absence of neurodegeneration in the

presence of fibrillary inclusions [96], point to the oligomeric species being the toxic form

[41]. In contrast, oligomeric species have also been shown to have a protective effect,

Baicalein-induced α-Synuclein oligomers have been shown to inhibit fibrillation of

untreated α-Synuclein [97, 98]. The aggregation of α-Synuclein is a complex process and

without consensus on which species is toxic, or whether there is a single toxic species, it is

important to characterise all species in the early stages of the aggregation process, as these

are likely the druggable species [23]. To date, a host of techniques have been applied to

characterise the structure of α-Synuclein including Nuclear Magnetic Resonance

spectroscopy (NMR) [57], in-cell NMR [63], Fourier Transform Infrared Spectroscopy (FTIR)

[58, 69], Circular Dichroism (CD) [69, 99, 100] and Small Angle X-ray Scattering (SAXS) [69].

29

1.5. Alzheimer’s Disease and the Amyloid-β peptides

Alzheimer’s disease was first described by Alois Alzheimer in 1907 and is a member of a

large group of diseases known as the dementias [101]. Alzheimer’s disease accounts for

80% of dementia cases [102]. In 2015, 5.2% of people aged 60 and above worldwide

suffered from a form of dementia, with a new case diagnosed every three seconds [103]. It

is projected that by 2050, the number of people living with dementia worldwide will

increase by 181% [103]. The prevalence of dementia is strongly linked to age, with

worldwide prevalence doubling for every 6 year increment in age [103].

Alzheimer’s disease is a chronic condition for which there is no cure. Sufferers require daily

care for an extended period of time and the cost of this care was estimated to be $818

billion in 2015 [103]. As the disease progresses, patients suffer increasing cognitive

impairment, presenting clinically in three ways, a decrease in cognitive function causing

amnesia, aphasia (language impairment) and apraxia (inability to conduct motor tasks,

despite no motor deficit) [101]. Secondly, patients display various psychiatric symptoms

including depression and hallucinations [101]. Thirdly, there is a decline in the ability to

conduct daily activities which progresses until the loss of basic activities including feeding

[101]. Alzheimer’s disease is characterised neuropathologically by the presence of amyloid

plaques and NeuroFibrillary Tangles (NFTs).

Two intrinsically disordered aggregating proteins are implicated in the pathology of

Alzheimer’s disease, Amyloid-β and Tau. The Amyloid-β (Aβ) peptides are derived from the

enzymatic degradation of the APP protein. The APP protein is a transmembrane, type-1,

integral glycoprotein and is expressed in all human tissues [104]. Enzymatic degradation of

APP occurs via two pathways, the amyloidogenic and the non-amyloidogenic (Figure 1.7).

During the non-amyloidogenic pathway, APP is cleaved by an α-secretase enzyme

generating a soluble α-APP (APPsα) fragment which is released extracellularly. Cleavage by

γ-secretase yields the p3 fragment which is degraded and the APP intracellular domain

(AICD), which may act as a transcriptional regulator [17]. During the amyloidogenic

pathway, APP is cleaved by a β-secretase. This generates the APP-β fragment (APPsβ) and

the C99 fragment. The C99 fragment is cleaved by γ-secretase to generate an Aβ peptide

and the AICD domain [17, 104]. The cleavage by γ-Secretase is not perfect and the Aβ

peptides generated vary in length from 37 to 43 amino acids [17, 105]. These Aβ peptides

are subsequently involved in an aggregation cascade, resulting in the formation of

oligomers and fibrils.

30

Figure 1.7 - The amyloidogenic and non-amyloidogenic processing pathways of APP. Sites of

enzymatic cleavage are highlighted by a dashed line. Figure is modified from [17] and [106].

Despite differing by only two amino acids, the structure and properties of the monomeric

Aβ(1-40) and Aβ(1-42) peptides differ substantially (Figure 1.8). The Aβ(1-40) peptide is the

most abundant, accounting for up to 90% of all Aβ peptides whilst Aβ(1-42) accounts for

approximately 10% [105]. Aβ(1-42) is significantly more neurotoxic than Aβ(1-40), is highly

amyloidogenic and is the predominant constituent of amyloid plaques [107-110].

Figure 1.8 - Aβ(1-42) primary sequence.

Aβ follows a nucleation-polymerization mechanism with a characteristic lag phase, during

which the aggregation nuclei are formed, followed by the rapid growth phase [111]. This

31

mechanism is shown in Figure 1.9 which demonstrates the on and off-pathway nature of

oligomeric species.

Figure 1.9 – Overview of the Aβ aggregation process. Figure reproduced from [111].

A mechanism for the early stages of the aggregation of the Aβ(1-40) and Aβ(1-42) peptides

has been proposed by Bernstein et al. [25] (Figure 1.10). For Aβ(1-40), a key step in the

fibril formation mechanism is the generation of a tetramer which resists monomer or dimer

addition [25]. This results in a slow rate of fibril formation. For Aβ(1-42), the key step

follows the formation of a hexameric paranucleus from an open tetramer [25]. Two

paranuclei combine to form a dodecamer species from which the pathway splits, resisting

addition or undergoing a slow α to β-sheet transition to form protofibrils which are on

pathway for fibril formation [25].

Figure 1.10 – Bernstein mechanism for the oligomerization and fibril formation of Aβ(1-40) and Aβ(1-42). Figure reproduced from [25].

To date, a consensus on the aggregation process for Aβ(1-42) and Aβ(1-40) has not been

reached. Pujol-Pina et al. report that the hexameric species observed by PICUP experiments

32

and referenced by Bernstein et al. are an artefact of the PICUP process and induced by the

presence of SDS [25, 108, 112]. In addition, Cohen et al. report an alternative aggregation

process featuring a positive feedback mechanism [113]. They report that after the initial

formation of oligomers and fibrils, further Aβ(1-42) oligomeric species are formed from

monomers in a secondary nucleation process involving fibrils [113]. The mechanism for

Aβ(1-40) aggregation proposed by Bernstein et al. [25] is contested by the work of Kloniecki

et al. [114] and Sitkiewicz et al. [115]. Kloniecki et al. propose a mechanism which features

two distinct oligomeric species, an open and an extended form, which lead to two

competing pathways for oligomer formation [114, 115]. Kloniecki et al. in positive

ionisation mode and Sitkiewicz et al. in negative ionisation mode demonstrate that the two

features of the drift time profile of [(Aβ40)2-5H]5- are not a mixture of dimers and

tetramers, but two conformationally distinct dimers on the basis of the ATD peaks featuring

the same isotopic spacing [114, 115]. These results are supported by Pujol-Pina et al. [112].

In addition, the higher order oligomers observed are not limited to the tetrameric species

reported by Bernstein et al. and include heptamer and tetradecamer species [25, 114, 115].

A wide array of Aβ oligomeric species have been identified from soluble dimers and trimers

to annular pore-like oligomers and protofibrils [111, 116]. Extensive evidence suggests that

these soluble oligomers are the toxic form of Aβ as the levels of soluble oligomeric species,

specifically soluble fibrillar oligomers, correlate with cognitive dysfunction [117-120]. The

mechanisms of oligomer toxicity are diverse and include receptor disruption to altering the

conductivity of lipid membranes [118].

Aβ fibrils feature a typical cross-β diffraction pattern; however, they also display significant

polymorphism [17, 121]. This polymorphism depends on the aggregation conditions and

several morphologies have been reported for both Aβ(1-40) and Aβ(1-42) [17].

Morphologies observed include twisted fibrils [122], hollow twisted fibrils [123] and ribbons

[124, 125]. Fibril morphology studies are conducted primarily on Aβ(1-40); however,

multiple Aβ(1-42) fibril morphologies have been observed [121, 123]. Cryo-EM has also

demonstrated that Aβ(1-40) fibrils grown under the same conditions exhibit morphologies

with different twists [122]. Extensive research has been conducted into the structure of the

fibril subunits and the intramolecular bonds which exist. In general, the monomeric units

adopt a β-strand-turn-β-strand (β-turn-β) structure, with a disordered N-terminus; see

Figure 1.11 [126]. The structure of the monomer subunits and in particular the intra and

inter-molecular bonding of Aβ(1-40) and Aβ(1-42) subunits are a region of debate and likely

differ between the various morphologies observed [17, 124, 126].

33

Figure 1.11 - Structure of the monomer unit of Aβ(1-40) and Aβ(1-42) fibrils. NMR has shown residues 1-10 are unstructured and 11-40 adopt a β-turn-β structure in Aβ(1-40). Residues 1-17 are

unstructured and 18-42 adopt a β-turn-β structure in Aβ(1-42). Intramolecular interactions are shown by dashed lines (Aβ(1-40): blue, Aβ(1-42): red and orange). In both, hydrophobic interactions

between green residues and a salt bridge between Asp23 and Lys28 stabilise the β-turn-β structure. Figure and caption reproduced from [126].

Tau is a Microtubule-Associated Protein (MAP) involved in the organisation of microtubule

growth and shrinking cycles and is found in most tissues, although it is predominantly

distributed in the neurons of the brain [104, 127, 128]. Tau hyperphosphorylation leads to

the destabilisation of microtubules by affecting Tau’s ability to bind tubulin [104, 129].

Hyperphosphorylated Tau can also sequester unmodified Tau [104, 129]. Aberrant

hyperphosphorylation of Tau leads to the formation of Paired Helicoidal Filaments (PHFs)

which form the characteristic NFTs of Alzheimer’s disease [104, 129, 130]. Tau is important

for neuronal stability and homeostasis, the disruption of this function leads to cellular

dysfunction and death [104].

According to the amyloid cascade hypothesis, proposed by Hardy and Higgins in 1992,

Alzheimer’s disease is a result of an imbalance in Aβ production and clearance [104, 131-

133]. Figure 1.12 highlights the sequence of events that lead to the development of

Alzheimer’s disease according to the amyloid cascade hypothesis. This leads to the

aggregation of Aβ including the formation of toxic oligomers [104, 118]. The accumulation

and aggregation of Aβ also results in a host of downstream deleterious processes including

Tau hyperphosphorylation [104]. The endpoint of the amyloid cascade is the development

of dementia [104]. Acceptance of the amyloid cascade hypothesis is not universal and there

are several weaknesses of the hypothesis including patients who have substantial amyloid

deposits in their brains yet exhibit few clinical symptoms [134]. These issues and

alternatives to the hypothesis are currently issues of debate [132, 134]. An alternative to

the amyloid cascade hypothesis, implicates the protein kinase GSK3 in the pathogenesis of

34

AD, acting upstream of other mechanisms it can increase Aβ production and Tau

hyperphosphorylation [104, 130, 135].

Figure 1.12 - The amyloid cascade. This flowchart describes the sequence of events leading from the rise in Aβ(1-42) levels to dementia. Figure reproduced from [132].

1.6. Disruption of Amyloid Formation

There is currently no cure for Parkinson’s or Alzheimer’s disease. The complex aggregation

process and the disordered nature and ambiguity of the toxic species continue to frustrate

the development of therapeutics. Numerous approaches exist from preventing the

production of the aggregating protein to inhibiting the aggregation of the protein itself

[136]. Aggregation modification approaches vary, curcumin stabilises large oligomers and

elongated protofibrils of α-Synuclein [79] whilst β-sheet breaker peptides bind Aβ and

prevent aggregation [137].

35

Due to their key position in the amyloid cascade, the Aβ peptides have been a focus of anti-

amyloid drug research. Approaches vary from the reduction of Aβ production, oligomer and

fibril formation inhibitors to fibril extension inhibitors [138, 139]. The use of peptides to

disrupt self-aggregation and small molecule assembly inhibitors, based on natural products,

are two key areas of drug development [139, 140].

RI-OR2 is a retro-inverso peptide, based on the established Aβ oligomerisation inhibitor

peptide, OR2 [141, 142]. Figure 1.13 is the primary sequence of RI-OR2, it features the

central KLVFF motif, designed to mimic the Aβ peptide central region (Figure 1.8) [142]. The

retro-inverso nature of the peptide denotes the replacement of L-enantiomers for D-

enantiomers and the reversal of the peptide bond direction [142]. This approach is

designed to prevent the proteolytic cleavage of the peptide, improving therapeutic

potential [142]. The peptide features arginine resides at both termini to prevent self-

aggregation and an amidated N-terminus, previously shown to improve inhibition of

oligomer formation [142].

Figure 1.13 - RI-OR2 structure. L-Amino acids are in upper case and D-Amino acids are in lower case. Peptide bond orientation is indicated by arrows. Figure modified from [142].

RI-OR2 inhibits the formation of Aβ(1-42) oligomers and fibrils in vitro [142, 143]. Recently,

a modified RI-OR2 peptide with a TAT domain designed to target the peptide to the brain,

was shown to inhibit oligomer and fibril formation. In addition, it has been shown to

decrease brain Aβ oligomer levels, microglial activation, oxidative stress levels and to

promote neurogenesis in transgenic mice [143]. Development of the peptide is ongoing

[144].

Figure 1.14 is the structure of Rutin, a flavonoid composed of quercetin and the

disaccharide rutinose [145]. Rutin is found in plants, fruits and vegetables and possesses

anti-carcinogenic, cytoprotective, antioxidant and anti-inflammatory properties [145].

36

Figure 1.14 – Rutin structure.

Rutin has been demonstrated to inhibit Aβ(1-42) fibrillization, to reduce Aβ(1-42) mediated

cytotoxicity and ROS production in vitro [145]. Rutin has been shown to reduce Aβ(1-42)

oligomer levels, decrease ROS levels, reduce neuro-inflammation and cytokine production

in Alzheimer’s disease transgenic mice [146].

1.7. Biophysical Techniques for the Structural Analysis of Proteins

X-ray crystallography is considered the gold standard for generating high resolution atomic

level structural information of proteins. The technique relies on the analysis of an electron

density map derived from a diffraction pattern recorded on a Charge Coupled Device (CCD),

following the irradiation of a protein crystal with a monochromatic, collimated X-ray beam

[147, 148]. An in depth discussion of the technique may be found in [149]. The requirement

for a crystal is a major limitation of X-ray crystallography; crystallisation trials require large

amounts of pure protein and may not even be possible. The crystal produced may not

reflect solution structure. The flexibility of IDPs results in non-coherent X-ray scattering and

blind spots in the electron density map [150]. It is possible to correlate a high B-factor, the

measure of uncertainty of atom positions in the model, with regions of disorder; however,

these regions are composed of flexible but ordered regions and IDRs [150].

Nuclear Magnetic Resonance (NMR) spectroscopy is based on the resonance (chemical

shift) of certain nuclei (1H, 13C, 15N) in response to exposure to strong magnetic fields and

Radio Frequency (RF) signals. The chemical shift depends on the local molecular

environment [151]. J couplings can be analysed to provide information on the peptide

backbone and side chain conformation and the Nuclear Overhauser Effect (NOE) can be

used to determine the proximity of nuclei to each other [151]. Due to the large number of

atoms in a protein there is significant signal overlap, requiring multi-dimensional

experiments [152]. Despite the spectral overlap issue, NMR has been applied to obtain

37

atomistic detail of proteins in the Mega Dalton range. NMR has certain drawbacks, a high

sample concentration (~0.1-1 mM) and large volume of very pure protein is required; this

poses additional problems with aggregating proteins, whose aggregation is concentration

dependent [153]. NMR approaches have been developed for the analysis of IDPs; however,

as IDP size increases so does difficulty and experimental complexity [154]. An in-cell NMR

approach has been developed to probe the structure of proteins in the cellular

environment and has been recently applied to study the structure of α-Synuclein

monomers following their recombinant overexpression in E. coli [63].

Small Angle X-ray Scattering (SAXS) yields low resolution data on protein shape and

conformation. In a typical SAXS experiment, a solution of the protein of interest is

illuminated by a collimated monochromatic X-ray beam [155]. The X-ray photons scatter

elastically off the sample, the intensity of the photon scattering as a function of scattering

angle is recorded on a CCD detector [156]. An in depth technical background may be found

in [155]. SAXS benefits from the ability to analyse solution phase samples in contrast to X-

ray crystallography and higher molecular weight limits than other methods such as NMR

[156]. The lack of widespread availability to beam sources including Synchrotrons, the

requirement for the protein of interest to remain soluble at high concentration and the

potential radiation damage suffered by proteins, limits the application of the technique

[157]. SAXS may be used for the analysis of IDPs and equilibrium systems such as those

which exist in an aggregating protein sample [150, 155]. Data analysis methods such as the

Ensemble Optimization Method (EOM) have been developed for the analysis of IDPs [150,

155]. SAXS is typically used in combination with other biophysical techniques to determine

structural information [150, 157].

1.8. Transmission Electron Microscopy

Transmission Electron Microscopy (TEM) is analogous to traditional light microscopy.

However, the increased resolution of TEM enables the imaging of cellular organelles,

aggregated proteins and viruses. Electrons are emitted by an electron gun by applying a

high voltage to a tungsten filament (the cathode). Electrons are then accelerated towards

the anode, a metal plate with a central aperture, creating the electron beam. The electrons

are focussed using a series of electromagnetic lenses prior to passing through the sample.

TEM imaging is based on electron scattering. Electrons will be scattered by interaction with

the sample and these scattered electrons are focussed by a series of post-sample

electromagnetic lenses prior to detection. Multiple detection methods exist, details of

38

these can be found in [158]. The TEM instrument used in this study featured a CCD camera.

Prior to detection by the CCD camera, electrons must be converted to photons by a

scintillator before passing through a light optical tandem objective or fiber plate [158].

The imaging of proteins can be enhanced by using a staining protocol such as Negative

staining. Negative staining greatly increases the contrast of images by embedding the

sample in a layer of heavy metal solution such as uranyl acetate, as the probability of

electron scattering, which is dependent on the coulomb interaction, is greater for heavier

elements [159, 160].

1.9. Mass Spectrometry

Modern Mass Spectrometry (MS) is based on the pioneering work of Thomson and Aston in

the development of the Mass Spectrograph [161-163]. Since this time, MS has undergone

many developments and found applications in many fields. MS can be broken down into

three parts. Firstly, the production of gaseous ions, followed by their separation according

to their mass to charge ratio (m/z) and finally the detection of their abundance.

1.9.1. Ionisation Methods

Sample ionisation is the first step in any MS experiment. Soft ionisation methods such as

Matrix Assisted Laser Desorption Ionisation (MALDI) and ElectroSpray Ionisation (ESI)

enable the analysis of a wide range of molecules from nucleic acids to proteins and

peptides [164]. ESI was pioneered by the work of Dole et al. [165] and developed as an

ionisation method for MS by Fenn and coworkers [166, 167].

Bruins, 1998 splits the ESI process into three steps, firstly, nebulization and the formation of

electrically charged droplets [168]. Secondly, the transition from droplets to ions and

thirdly, the transport of these ions from atmospheric pressure into the vacuum

environment of the instrument [168]. In ESI, the sample solution is fed through a capillary

held at more positive potential than the counter electrode, when operated in positive

ionisation mode [168]. A high electric field at the top of the capillary pulls positive charges

towards the tip of the capillary [168]. Polarization of the solvent leads to the formation of a

taylor cone, from which charged droplets are emitted (Figure 1.15A) [164]. The emitted

droplets are reduced in size by solvent evaporation and the shear forces from moving

through the dense gas environment of the source region [168, 169]. As the droplets shrink,

charge density builds on the outside of the droplet until it reaches an upper limit, the

39

Rayleigh limit [168, 169]. At this point, highly charged smaller droplets are emitted [168,

169]. Ion emission from these droplets occurs via three different mechanisms, the Ion

Ejection Model (IEM), proposed by Iribarne and Thomson [170], the Charge Reduction

Model (CRM), proposed by Dole et al. [165] and the Chain Ejection Model (CEM), proposed

by Ahadi et al. [171] (Figure 1.15B). IEM is appropriate for low molecular weight pre-formed

solution phase ions and is based on the electric field of the Rayleigh-charged droplet being

high enough to eject the charged analyte ions [169]. Ion formation via the CRM model is

due to the evaporation of a Rayleigh-charged droplet containing a single analyte. As the

solvent shell disappears, charge is transferred to the analyte [169]. This is the model

proposed for large globular species such as natively folded proteins [169]. CEM is proposed

for unfolded proteins and is based on the hydrophobic nature of the unfolded protein

causing it to migrate to the surface of the Rayleigh-charged droplet [169]. At the droplet

surface, one end of the unfolded protein chain is first ejected and is followed sequentially

by the rest of the protein chain [169]. This process leads to the high charge states observed

for these proteins [169]. A series of salt adduction experiments by Yue et al. have recently

demonstrated that the CRM and CEM models are responsible for folded and unfolded

protein ion formation, respectively [172].

NanoElectroSpray Ionisation (nESI) is a version of conventional ESI developed by Wilm and

Mann [173]. In addition to much lower sample consumption, nESI is a softer ionisation

mechanism than ESI requiring lower capillary voltages and gas flows. The initial nESI droplet

size is much smaller than ESI and droplets undergo fewer evaporation and fission cycles

prior to ion production [169, 174]. nESI is more tolerant of solvents with higher surface

tensions such as water and of the presence of salt ions, as the initial smaller droplet size

means fewer salt ions will be transferred to the analyte [174, 175]. nESI also offers

improvements on sensitivity and ionisation efficiency [169, 174].

40

Figure 1.15 - The nESI process. A. The generation of droplets from a nESI tip, this example features a globular protein. B. The three ion emission models, Ion Ejection Model (IEM), Charged Residue Model (CRM) and the Chain Ejection Model (CEM). Structure: 1GB2 [176]. Figure based on a figure in [169].

1.9.2. Mass Analysers

A mass analyser measures the mass to charge ratio and may be used alone, in multiples or

in combination with other mass analysers.

1.9.2.1. Quadrupoles

Quadrupoles are composed of four parallel circular or hyperbolic rods. The rods are

arranged in pairs and a fixed Direct Current (DC) voltage and an alternating RF are applied

to the rod pairs. At one time, one pair of rods has an in-phase RF potential, or positive

polarity and the other pair has an out of phase RF potential or negative polarity. This

41

creates an oscillating electric field, described by Equation 1.1, where ϕo is the potential

applied to the rods, U is the direct potential, V is the zero-to-peak amplitude of the RF

potential, ω is the angular frequency of the RF potential (in radians per second, which is

equal to 2πv, where v is the RF frequency) and t is time [177].

±𝜙0 = ±(𝑈 − 𝑉 cos 𝜔𝑡) Equation 1.1

An ion entering the quadrupole will be attracted to a rod of the opposite polarity. As an

alternating RF potential is applied to the pairs of rods, the rod polarity is constantly

alternating. If the rod switches polarity before the ion strikes it, the trajectory of the ion will

change, see Figure 1.16.

Figure 1.16 – Ion trajectories within a quadrupole. Note the stable trajectory (orange) resulting in ion transmission and the unstable trajectory (green), resulting in the impact of the ion on the quadrupole

rods. Based on a figure in [178].

Ions in the quadrupole travel in an oscillating path which is defined by the values of U, V

and ω. Quadrupoles can be used in two modes, firstly as a transmission device; by scanning

through values of V, ions of different m/z values may be transmitted. Secondly, the

quadrupole may be used as a mass filter. For an ion, specific values of U, V and ω will

provide a stable trajectory, by fixing the quadrupole at these values only the ion of interest

will be transmitted, all other ions have a unstable trajectory and collide with the rods. The

quadrupole is used in this mode during an MS/MS experiment, enabling selection of an ion

prior to fragmentation. The principles of the quadrupole are reflected in the operation of

hexapoles and octapoles. Examples of these multipoles are used in the QToF instruments

described in Chapter 2 and used for data collection in Chapters 3 to 5. In general, as the

number of rods increases, the mass range for ion transmission increases but the focussing

power of the device decreases [177].

42

1.9.2.2. Time of Flight

A Time of Flight (ToF) analyser accelerates an ion into the field-free region of the flight

tube. The velocity of the ion in this field-free region is dependent on the m/z ratio. The m/z

of ion is determined by measuring the time taken for the ion to travel the length of the

field-free region to the detector. Equation 1.2 demonstrates how the kinetic energy, Ek of

an ion accelerated into the field-free region can be determined, where m is the ions mass, v

is the ions velocity, ze is the total charge of the ion and Vs is the potential [177].

𝐸𝑘 = 𝑚𝑣2

2= 𝑧𝑒𝑉𝑠 Equation 1.2

Equation 1.3 demonstrates how the velocity of an ion can be determined.

𝑣 = (2𝑧𝑒 𝑉𝑠 𝑚⁄ )1 2⁄ Equation 1.3

After the ion is accelerated into the field-free region it travels at a constant velocity to the

detector. The time (t) an ion takes to travel the length (L) of the field free region is

dependent on its velocity (v), see Equation 1.4.

𝑡 = 𝐿

𝑣 Equation 1.4

Equation 1.5, a combination of Equation 1.3 and 1.4, demonstrates how the m/z ratio of an

ion is determined by the time taken for the ion to travel the length of the field-free region.

𝑡2 = 𝑚

𝑧 (

𝐿2

2𝑒𝑉𝑠) Equation 1.5

Figure 1.17 is a schematic of two common ToF geometries, a linear ToF (Figure 1.17A) and

an orthogonal acceleration reflectron ToF (Figure 1.17B). The QToF instruments described

in Chapter 2 and used in Chapters 3 to 5, all feature orthogonal acceleration reflectron ToF

geometries.

43

Figure 1.17 - Schematic of two ToF geometries. A. The linear ToF and B. The orthogonal acceleration reflectron ToF.

The use of a reflectron to improve mass resolution was proposed by Mamyrin et al. in 1973

[179]. A reflectron is an ion mirror, created by stacking ring electrodes and grids and acts by

deflecting ions back along the flight tube (Figure 1.17B) [177]. A reflectron increases the

resolution of a ToF mass analyser by increasing the length of the flight tube, as well as

correcting the kinetic energy dispersion of ions [177]. ToF mass analysers have a high upper

mass limit, very high sensitivity and high analysis speed, all beneficial for the analysis of

proteins especially, aggregating species [177].

1.9.2.3. Fourier Transform Ion Cyclotron Resonance Mass

Spectrometry

An ions trajectory is curved in a magnetic field and if the field is intense and the velocity

low, the radius of the trajectory is small [177]. Based on this principle, an ion can be

trapped in a circular trajectory in a magnetic field. This stable circular trajectory is a

balance of centripetal and centrifugal forces experienced by an ion and described by

Equation 1.6, where z is charge, B is magnetic field, m is mass, v is velocity and r is radius.

𝑧𝐵 = 𝑚𝑣

𝑟 Equation 1.6

The frequency (ƒ) of the ions circular trajectory is defined by Equation 1.7 and the angular

velocity (ω) by Equation 1.8.

44

𝑓 = 𝑣

2𝜋𝑟 Equation 1.7

𝜔 = 2𝜋𝑓 = 𝑣

𝑟=

𝑧

𝑚𝐵 Equation 1.8

According to Equations 1.7 and 1.8, an ions frequency and angular velocity is dependent on

the m/z and the magnetic field strength but independent of its velocity. Irradiating an ion

with an electromagnetic wave which has the same frequency as the ion, allows resonance

absorption of the wave and energy transfer. An increase in energy results in an increase in

the radius of the ions trajectory [177].

Figure 1.18 is a schematic of a basic Fourier Transform Ion Cyclotron Resonance Mass

Spectrometry (FT-ICR MS) cell, ions are trapped in the x and y axis by the magnetic field and

along the z axis through the application of a voltage to the trapping plates [177]. Ions within

the cell orbit around the z axis due to the cyclotron motion and along the z axis between

the trapping plates, known as trapping oscillation [177, 180].

Figure 1.18 – FT-ICR MS cell schematic [177, 178, 180].

Figure 1.19 demonstrates the simplified path of an ion in an FT-ICR MS cell, the cyclotron

motion is the result of the magnetic field whilst the magnetron motion is a result of the

45

drift of the centre of the cyclotron motion centre along the electrical equipotential lines,

which run perpendicular to the magnetic field direction [181].

Figure 1.19 - The simplified path of cyclotron and magnetron motion imposed on ions within an FT-ICR MS cell. The trapping oscillation is omitted from this figure for clarity [180, 182].

FT-ICR MS simultaneously excites all ions by scanning rapidly through a large frequency

range, by applying a waveform calculated by an inverse fourier transform. This broadband

excitation causes all ions to adopt the same radius but at frequencies (of the same voltage)

depending on the m/z ratio of the ion. Excitation of the ions induces a trajectory which

brings the ions close enough to the detection plates to induce a current (Figure 1.18); this

alternating current is amplified and then digitised [177, 180]. Excitement also brings the

ions into phase enabling the use of a fourier transform to convert the complex wave

detected from a time-dependent to a frequency-dependent intensity function [177, 180].

The high sensitivity and resolution of an FT-ICR MS instrument coupled with fragmentation

techniques including Electron Capture Dissociation (ECD) enables proteomics studies,

protein structure elucidation and PTM locations to be defined [183].

1.9.3. Detectors

Detection is the final stage of an ions passage through the instrument. Detectors generate

an electrical current proportional to the abundance of the ion. This method of detection

differs to the previously described method of detection applied in FT-ICR instruments.

Microchannel Plates (MCPs) are commonly used in conjunction with ToF instruments as

they enable the collection of precise arrival times with narrow pulse widths. An MCP is a

type of continuous dynode electron multiplier and is composed of a series of parallel

cylindrical channels, coated with a semi-conductor (Figure 1.20). The ion input side is held

46

at a negative potential of ~1 kV compared to the output side [177]. Electron multiplication

is achieved by ions impacting the wall of the channel and generating secondary electrons,

shown in Figure 1.20. The process is repeated along the length of the channel, initiating a

cascade of electrons, accelerated through the channel by the potential gradient present,

the electron cascade is then measured as current [177]. A single plate arrangement can

result in an amplification of up to 104, the use of multiple plate arrangements can result in

an amplification of 108 [177].

Figure 1.20 - MCPs and electron multiplication within a channel. Figure reproduced from [184].

1.10. Tandem Mass Spectrometry

Tandem mass spectrometry (MS/MS) involves two stages of mass analysis and typically

involves a fragmentation process [177]. Fragmentation methods are one of the most

fruitful areas of instrument development. Figure 1.21 is the common nomenclature for

peptide fragmentation notation proposed by Roepstorff and Fohlmann in 1984 [185] and

modified by Biemann [186].

Figure 1.21 - Peptide fragmentation notation [187, 188].

47

1.10.1. Collision Induced Dissociation

Collision Induced Dissociation (CID) is the most widespread fragmentation technique and a

feature of most modern MS instruments. The CID process relies on the activation of the

selected species by collision with neutral gas molecules and is described as a two-step

process [189, 190]. The first step is the activation of the fast moving ion by collision with

the slow moving neutral gas molecule, which transfers a portion of the ions kinetic energy

to the internal modes [190, 191]. The second step is the dissociation of the excited ion

[190]. CID is a multi-collision process and occurs over tens of microseconds [192]. CID is

most commonly associated with the generation of b- and y- ions [193]. CID is conducted in

the collision cell of the QToF instruments and in the Trap and Transfer regions of the

Triwave device of the Synapt instruments, described in Chapter 2.

1.10.2. Electron Capture/ Transfer Dissociation

Electron Capture Dissociation (ECD) and Electron Transfer Dissociation (ETD) are electron

based fragmentation techniques. ECD was developed in the McLafferty lab by Zubarev et al.

[193]. ECD was initially limited to use with ICR instruments; however, it has now been

applied in most types of instrumentation [194]. During the ECD process, a multiply charged

protein ion captures electrons forming a charge reduced species and begins the ion-radical

fragmentation process [194-196]. Fragmentation occurs through cleavage of the N-Cα

bond. ECD also results in the cleavage of disulphide bonds. The exact process is an ongoing

debate and descriptions of the three proposed mechanisms can be found in [194]. The

Utah-Washington mechanism is the most widely accepted mechanism. In this mechanism,

the electron is captured by the π orbital of the positive charge site, the electron is then

transferred to the amide π* (or S-S δ* orbitals, in the case of disulphide bond cleavage)

which causes N-Cα bond cleavage [194, 197-200]. Cleavage can also occur by direct capture

of the electron by the amide π* or disulphide δ* orbital [194]. During ECD-FT-ICR MS

experiments, electrons are produced by heating a filament outside the magnet, prior to

interaction with ions isolated in the FT-ICR MS cell [193].

ETD was developed to overcome the difficulty of trapping electrons in ion traps, in the Hunt

lab by Syka and Coon, using anions as electron donors in place of an electron source [194,

201]. The mechanism for ETD fragmentation is theorised to be similar to that described for

ECD [202]. ETD can be applied in the Trap region of a modified Synapt instrument using 1,3-

48

dicyanobenzene as a radical anion electron donor. Both, ECD and ETD are associated with

the generation of c- and z- ions [193].

1.10.3. Electron Transfer Collisional Activation Dissociation

ECD and ETD fragmentation does not dissociate non-covalent interactions, as a result

fragment ions may not be resolved for a species with strong intramolecular non-covalent

interactions [194]. This issue is overcome by the combination of ECD or ETD with a

vibrational activation process such as CID, in a process known as Activated Ion Electron

Capture/Transfer Dissociation (AI-ECD/AI-ETD) [194]. Electron Transfer Collisional

Activation Dissociation (ETcaD) developed by the Coon lab can be easily applied in the

Triwave cell of a Synapt instrument modified to conduct ETD [203].

1.10.4. Surface Induced Dissociation

Surface Induced Dissociation (SID) was pioneered by the Cooks group and is analogous to

CID as fragmentation is governed by interaction with a neutral target, the SID surface

replacing the neutral gas molecule of CID [191, 204, 205]. SID has been applied in multiple

instrument geometries including tandem quadrupoles [206], FT-ICR MS instruments [207],

ToF instruments [208] and within QToF instruments [209]. SID has also been coupled to IM-

MS by the Russell Group [210]. Recently, the Wysocki group has developed an SID cell for

use within a commercial Synapt instrument, increasing the potential SID-IM-MS user

market [211]. Although SID is described as analogous to CID, this connection is limited to

the interaction of the ion with an inert target and in reality; the two fragmentation

techniques are very different. SID is described as a fast single step process in which the

internal energy deposited by impact with the surface occurs within picoseconds [212, 213].

This internal energy is much higher than that deposited by multiple collisions as in CID and

is one aspect of the different fragmentation processes seen by SID [213].

SID has been applied to small molecules [214], peptides [206, 207], proteins [215] and

recently to protein complexes [216]. In contrast to the highly charged monomer ejected by

CID, SID fragmentation leads to a more equal charge partitioning and the retention of a

more native-like compact conformer [212, 217]. Studies including the use of SID-IMS

experiments have demonstrated that SID product ions are more folded than their CID

counterparts [216, 218, 219]. SID is sensitive to the conformation of the precursor, it is

therefore possible to infer structural information [218]. SID is associated with the

production of b- and y- type ions [220].

49

1.10.5. Fragmentation Techniques for the Analysis of Protein Structure

The analysis of protein structure is a common application of gas phase fragmentation

techniques such as CID and ECD. The structural information gathered depends on the

technique applied and each technique has distinct advantages and disadvantages. The

analysis of structure by fragmentation is a very rapid technique with a low sample

requirement and it is possible to select a specific charged species or a specific conformer

with IM-MS prior to analysis. However, it is only possible to investigate ionisable species

and the ionisable species may not be representative of a complex sample. In addition,

experimental conditions must be carefully chosen to maintain biological relevance. For

example, instrument conditions may alter solution phase structure [221] and following

ionisation, the age of the ion can dictate the preservation of solution phase intramolecular

interactions [222].

CID is the most widely available fragmentation technique and is easily applied. However,

structural information is limited to primary structure and general structural information,

such as number of subunits. The technique is a multiple collision process and removes

higher order structural information [223]. Electron based fragmentation mechanisms such

as ECD and ETD, can probe the 3D structure of a protein, as the fragmentation mechanism

does not disrupt non-covalent interactions [224, 225]. ECD/ETD can provide primary

structure information like CID; however, the location of CID-labile PTMs such as

phosphorylation can also be determined [226]. In contrast to CID, the technique is limited

to specialised instruments and experiments are typically longer and more complex. For

instance, ETD requires the tuning of the anion reagent ionisation prior to fragmentation. In

addition, non-covalent interactions can prevent the dissociation of fragment ions,

preventing their observation and reducing sequence coverage; however, experimental

methods exist to combat this problem. Due to its single step, high energy fragmentation

process, SID has been applied to study the substructure of protein complexes and the

fragments which result can be used to investigate gas phase structure [227, 228]. However,

there are a limited number of instruments capable of conducting SID. In addition, the

process is not as user friendly as techniques such as CID or ECD/ETD and the current design

requires instrument disassembly to change the SID surface.

50

1.11. Cross-linking

Cross-linking uses a cross-linking reagent to preserve non-covalent interactions or residues

within a certain proximity prior to mapping their location [229]. Cross-linking-MS has been

applied to study the structure of Bovine Serum Albumin [230], RNA Polymerase II [231] and

a protein phosphatase 2A network [232]. A traditional cross-linking-MS experiment involves

cross-linking the protein using a cross-linker reagent (Figure 1.22A-B). A cross-linker reagent

typically features two reactive groups separated by a spacer. A wide range of cross-linkers

featuring different reactive groups have been developed for example, a cross-linker

featuring amino groups is commonly applied for protein or peptide cross-linking [229].

Structure is preserved by the formation of covalent bonds between the reactive groups of

the cross-linking reagent and the protein or protein complex. The cross-linked proteins are

then subjected to a trypsin digest (Figure 1.22C) before being separated by LC-MS/MS

(Figure 1.22D). The spectra are then compared to a database to identify cross-linked

peptides and decipher structural elements (Figure 1.22E) [229].

Figure 1.22 - Workflow of a typical cross-linking-MS experiment. Based on a figure in [229].

1.12. Hydrogen Deuterium Exchange Mass Spectrometry

Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS) exploits the fact that

hydrogen atoms in O-H, N-H and S-H are able to exchange with the surrounding water

[233]. By replacing the water with deuterium oxide, it is possible to monitor this exchange

by MS. Exchange is related to the protection of the hydrogen atom, with regions of

structure possessing slower exchange rates. HDX occurs for both the backbone amide

hydrogens and those of the side chains of the amino acids of the protein. The structure of

51

the entire protein can be probed for example; HDX-MS has been applied to study the effect

of mutations on antibody structure [233, 234].

1.13. Ion Mobility - Mass Spectrometry

Ion Mobility - Mass Spectrometry (IM-MS) is a gas phase electrophoretic technique which

enables the separation of ions on the basis of their mobility (K) in a given buffer gas, which

is related to an ions size and shape, in addition to the mass (m) and charge (z) separation

achieved by traditional MS. This two dimensional approach enables the separation of

species which possess coincident m/z values but differ in terms of oligomeric order or

conformation. An excellent review of current IM-MS approaches may be found in [235],

[236] and [237]. The two approaches applied in this thesis, Drift Time Ion Mobility Mass

Spectrometry (DT-IM-MS) and Travelling Wave Ion Mobility Mass Spectrometry (TWIMS)

are described here.

1.13.1. Drift Time Ion Mobility - Mass Spectrometry

DT-IM-MS is the simplest form of IM-MS but is the gold standard for Collision Cross Section

(CCS) measurement. Early experimental and theoretical investigations into the movement

of ions in gases are the basis of modern DT-IM-MS [238-240]. Based on this early work,

McDaniel constructed linear drift time ion mobility instruments [241]. This work was built

on by Kebarle [242] and led to the development of the first IMS-MS hybrid instrument by

hyphenating a linear drift tube with a magnetic sector mass spectrometer [243, 244].

The behaviour of an ion passing through a gas under the influence of an electric field is

dependent on the ratio of electric field strength (E) and the number gas density (N). At high

E/N, ions may align with the field and their motion becomes dependent on E [245]. At low

E/N ratios, known as the Low Field Limit, the motion of ions can be described in simpler

terms and ions have low velocities independent of E [246]. At the low field limit, mobility

(K) is the constant of proportionality between drift velocity and the electric field (E), see

Equation 1.9.

𝑣𝑑 = 𝐾𝐸 Equation 1.9

An ions mobility (K) is dependent on its mass (m), charge (z) and shape, which can be

defined as its rotationally averaged CCS (Ω), described by Equation 1.10:

𝐾 = 3𝑧𝑒

16𝑁 (

2𝜋

𝜇𝑘𝐵𝑇)

1 2⁄ 1

𝛺 Equation 1.10

52

where K is the mobility, e is the elementary charge, N is the gas number density, µ is the

reduced mass of the ion–neutral pair, kB is the Boltzmann constant and T is the gas

temperature. The reduced mobility, the measured mobility at standard temperature and

pressure (273.15 K and 760 Torr) is calculated to aid in the comparison of values between

laboratories, see Equation 1.11.

𝐾0 = 𝐾𝑇𝑜𝑃

𝑃𝑜𝑇 Equation 1.11

DT-IM-MS instruments enable the direct measurement of an ions CCS and until the recent

development of the Agilent DT-IMS-MS instrument, they were largely limited to instrument

development laboratories.

1.13.2. Travelling Wave Ion Mobility Mass Spectrometry

The Waters Synapt instruments are the first commercial integrated IM-MS instruments and

are based on Travelling Wave Ion Mobility Mass Spectrometry (TWIMS). Synapt

instruments use a Stacked Ring Ion Guide (SRIG) variant, the Travelling Wave Ion Guide

(TWIG) in which a periodic travelling wave is superimposed to propel ions through the

guide [247]. TWIMS mobility separation is achieved in the presence of an inert buffer gas

(Figure 1.23), two ions of different mobilities surf the wave created by the TWIG. The ion

with a lower mobility rolls over the wave and takes a longer time to travel the length of the

IMS region. The higher mobility ion does not roll over the wave and travels the length of

the IMS region in a shorter time [248].

It is not possible to determine CCS values directly from the drift time data of TWIMS

instruments. Instead, a calibration curve is generated from a set of protein standards,

whose CCS values have been measured on DT-IM-MS instruments. This approach has

shortcomings including the effect of the buffer gas. TWIMS CCS measurements are

conducted in nitrogen whereas DT-IM-MS instruments are usually conducted in helium;

calculation of CCS values from TWIMS data therefore requires converting the value from

one gas to another. The buffer gas is known to have an impact on the CCS of small

molecules and to a lesser extent on large biomolecules such as proteins [247, 249]. In

addition, Ridenour et al. have demonstrated that the choice of calibrant and ionisation

source can affect calibration quality [250]. Therefore, the calibrant ions chosen must be

similar to the subject of investigation and the experimental conditions must be identical.

Evidence of ion heating in TWIMS instruments also means that instrument conditions must

be carefully considered and controlled to avoid disruption of protein structure [221, 251].

53

Figure 1.23 - Mobility separation in the IMS region of the Triwave device. Separation is achieved by low mobility ions rolling over the wave whilst high mobility ions do not. Figure is adapted from [248].

1.14. Biological Mass Spectrometry and Ion Mobility – Mass

Spectrometry

The study of proteins and protein complexes by MS and IM-MS was enabled by the

development of ESI, enabling the transfer of intact proteins and protein complexes into the

gas phase. Since this development MS has been applied to study protein subunit

stoichiometry, PTMs and substrate binding [252]. The application of MS based methods to

study protein structure relies on the retention of structure following the transition into the

gas phase. Growing evidence demonstrates the retention of structure in the gas phase.

Studies have shown the retention of α-helices [253, 254] and to a lesser extent, the

retention of β-sheet structure [255]. It is also possible to preserve weak non-covalent

interactions [256]. In addition, Ouyang et al. observe the retention of biological activity of

two enzymes following soft landing, demonstrating the retention of structure following

transition into the gas phase [257]. A recent study by Chen and Russell, demonstrate that

careful consideration of the instrumental conditions is required to preserve native

structure [221].

In solution, protein structure is mediated by non-covalent interactions including hydrogen

bonding, electrostatic and hydrophobic interactions and van der Waals forces. The

transition from the solution to the gas phase is a dramatic shift in the environment of the

protein. Breuker and McLafferty examine the transition from solution to gas phase

following the creation of charged droplets during the electrospray process [222]. The

54

retention of solution phase structure in the gas phase is dependent on the experimental

conditions; the collapse of charged side chains in the picoseconds following desolvation can

preserve native solution phase structure [222]. However, milliseconds after desolvation,

the structure may lose hydrophobic and electrostatic interactions and undergo unfolding

and refolding [222]. Minutes after desolvation, new non-covalent bonds may be formed,

stabilising alternative structures [222]. Careful consideration of experimental design is

therefore required to maintain solution phase structure.

It is possible from MS alone to infer general structural information and conformational

changes on the basis of the width of a proteins Charge State Distribution (CSD). More

compact conformers or proteins have fewer exposed ionisable sites and therefore present

fewer charge states. On the other hand, more unfolded or disordered proteins such as α-

Synuclein, in general feature greater numbers of exposed ionisable sites and so present

much wider CSDs. MS can be applied in this manner to track the effect of solution

conditions such as pH on conformation [258-260]. Gaussian fitting of the charge state

envelopes enables the tracking of different conformers in relation to changes in conditions

such as exposure to alcohols or metal ions [259, 260]. This is particularly beneficial for

aggregating systems in which a wide range of conformational species are present at one

time. However, the analysis of structure or conformational changes by MS alone is

hampered by the presence of charge coincident species, either of overlapping

conformational families or oligomeric species.

IM-MS emerged in the mid-1990’s as an alternative to X-ray crystallography and NMR for

the characterisation of protein structure [261]. A summary of the advantages and

disadvantages of each biophysical technique can be found in Table 1.1. Although IM-MS

cannot offer the same atomistic resolution, it instead offers the ability to study the

conformational dynamics of the protein, enabling the separation and interrogation of

multiple overlapping conformers or oligomeric species, which are frequently lost in other

techniques. This can be expanded into analysing the effect of binding of inhibitors or small

molecules on protein conformation to decipher their mechanism of action. For example,

the effect of RNA binding to trp RNA-binding attenuation protein (TRAP) [262] or the

binding of EGCG to α-Synuclein [263].

In contrast to NMR and X-ray crystallography in which large sample volumes and

concentrations are typically required, the sample requirements for MS and IM-MS analysis

are much lower, requiring µL volumes of µM concentrations. NMR and X-ray

55

crystallography are non-destructive processes as it is possible to recover or preserve the

protein or protein crystals. On the other hand, ionisation of the protein by MS based

methods is destructive, although this downside is mediated by the lower sample volume

requirements. In addition, the lower sample concentrations required compared to NMR

and X-ray crystallography are beneficial for the study of rare proteins and aggregating

systems, where concentration is known to affect aggregation. As a result, MS and IM-MS

have been applied to study a range of aggregating proteins and peptides. β2-microglobulin,

implicated in the aetiology of dialysis-related amyloidosis, has been extensively studied by

MS and IM-MS. The Vachet group have applied MS to locate the binding site of copper ions

[264] and in conjunction with a covalent labelling approach, they have probed the structure

of pre-fibrillar structures [265, 266]. MS and IM-MS have been applied extensively to probe

the structure and aggregation of β2-microglobulin by the Heck, Grandori, Radford and

Ashcroft groups [267-274].

MS based methods have been applied to other aggregating systems including amylin [275-

279], insulin [280] and prion proteins [281, 282]. The application of MS and IM-MS

approaches to study α-Synuclein and the Amyloid-β peptides is covered in subsequent

chapters.

56

Table 1.1 – Summary of advantages and disadvantages of biophysical techniques for the structural analysis of IDPs [235].

MS IM-MS X-ray Crystallography NMR Spectroscopy SAXS

Phase of analyte Gas Gas Solid Liquid (or Solid) Liquid

Advantages - Rapid analysis time - Can analyse mixtures - Very low sample requirements - Ligand binding analysis - General structural information (compact/extended) - CID-MS: primary structure analysis - ECD/ETD-MS: 3D structure - Cross-linking/HDX-MS: Solution structure analysis

- Fast analysis time - Can analyse mixtures - Very low sample requirements - Measures protein structural dynamics - Ligand binding analysis - SID-IMMS can be applied to determine subunit stoichiometry

- Non-destructive - Atomic level structure determination - Stereo-chemical information, bond lengths and angles can be determined

- Non-destructive - Stereo-chemical information, bond lengths and angles can be determined - Solution phase analysis is more biologically relevant/native-like - Can be conducted in-cell

- Non-destructive - Methods developed for analysis of IDPs (EOM) - Can be used to study systems in equilibrium e.g. Aggregation - High MW limit

Disadvantages - Analyte must be ionisable - Destructive - Detailed 3D structural information difficult to determine directly from spectra - Limited tolerance to contaminants e.g. metal ions

- Analyte must be ionisable - Destructive - Modelling required for precise structural information. Difficulty scales with MW - Limited tolerance to contaminants e.g. metal ions

- Crystallisation requires large volume of pure, concentrated sample. May not be possible - One conformation of a heterogenous sample - X-ray sample damage - Non-coherent X-ray scattering of IDPs creates electron density map blind spots

- Requires large volume of pure, concentrated sample. - As protein size increases, experimental complexity and difficulty increases

- X-ray sample damage - Limited beam sources - Protein must remain soluble at high concentrations

57

1.15. Summary

MS and IM-MS have previously been shown to be excellent tools for examining the

structure and aggregation of proteins and peptides implicated in disease. This thesis

investigates the use of MS based methods including IM-MS and a range of fragmentation

techniques to probe the structure, aggregation and interactions of proteins and peptides of

medical relevance in the gas phase. Firstly, the structure and aggregation of α-Synuclein,

which has been implicated in the development of Parkinson’s disease, is probed using a

combination of MS and IM-MS hyphenated with the structure interrogating techniques

including HDX and ECD (Chapters 3 and 4). Secondly, the structure of the aggregating

Amyloid-β peptides, implicated in the aetiology of Alzheimer’s disease is probed by a range

of gas phase fragmentation techniques. The alteration of this structure, as a result of the

interaction of the peptide with anti-amyloid therapeutic candidates is also studied by

TWIMS (Chapter 5). Finally, the ability of these MS based methods to study the structure of

intrinsically disordered aggregating protein systems and the scope for further investigation

is discussed.

58

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2 Experimental

This chapter contains descriptions of the instruments used for data collection, instrument

schematics and typical tuning parameters. Examples of data acquisition and processing for

Drift Time - Ion Mobility - Mass Spectrometry are also included. Details of recombinant

protein expression and purification, Nano-ElectroSpray Ionisation, solution preparation and

fragmentation techniques are provided.

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2.1. Reagents

All organic solvents used for buffer or sample preparation were of LC grade or higher and

purchased from Fisher Scientific or Sigma Aldrich, UK. High purity water (resistivity: 18.2

MΩ) was produced using an Arium 611 (Sartorius, Germany) or Milli-Q A10 (Millipore,

Germany) water purification system or LC grade water was purchased from Fisher Scientific

or Sigma Aldrich, UK for the preparation of buffers and samples. Ammonium Acetate

(AmAc), purity ≥ 99%, was purchased from Fisher Scientific, UK.

Reagents used for pH alteration were of the highest quality obtainable. Ammonium

hydroxide, Acetic acid and Formic acid were purchased from Sigma Aldrich, UK.

Hydrochloric acid was purchased from Fisher Scientific, UK. Solution pH measurements

were conducted using a Jenway 2505 pH meter (Jenway Scientific Equipment, UK).

Poly-L-lysine and ubiquitin for Travelling Wave Ion Mobility Mass Spectrometry (TWIMS)

Collision Cross Section (CCS) calibration and sodium iodide and caesium iodide for mass

calibration were purchased from Sigma Aldrich, UK.

2.2. α-Synuclein Expression and Purification

The method used for α-Synuclein expression and purification was based on the method

published by Woods et al. [1]. A pT7-7 vector containing the human wildtype α-Synuclein

gene, provided by Professor Chris Rochet, Purdue University was transformed into

competent BL21(DE3) E. coli. 10 µL plasmid DNA was incubated with 200 µL of competent

cell suspension on ice for 1 hour before heat shocking for 1 minute 45 seconds at 42°C and

returning to ice for 2 - 3 minutes. 800 µL LB media was added and each sample was shaken

for 1 hour at 37°C. Cells were then centrifuged for 4 minutes at 13,000 rpm and

resuspended in 200 µL. LB agar and ampicillin plates were inoculated with the cell

suspension and incubated at 37°C overnight. 5 mL LB Media (with 50 µM ampicillin) was

inoculated with a single colony and incubated overnight with shaking at 37°C. LB media

(with ampicillin) was inoculated with the overnight culture (5%) and induced with 0.1 mM

IPTG once growth to an OD600 = 0.3-0.4 had been achieved. After 5 hours of induction, cells

were pelleted at 5545 rpm for 15 minutes at 4°C, resuspended in PBS and pelleted again.

Cell pellets were resuspended in lysis buffer (20 mM Tris-HCl, pH 7.5, 1 mM EDTA, 1 mM

DTT and Roche protease inhibitor tablets, 1 per 250 mL buffer). Cells were lysed with a Cell

Disrupter (Constant Systems Ltd., UK). Expression was confirmed by SDS-PAGE (Figure 2.1).

75

Figure 2.1 - SDS-PAGE of lysed E. coli cell pellet. The arrow head indicates the presence of a large α-Synuclein band in duplicate lanes. Lane 3 is a custom MW ladder.

The lysate was clarified by centrifugation at 18,000g for 45 minutes at 4°C. The supernatant

was collected, adjusted to pH 3.5 and stirred at room temperature for 20 to 30 minutes,

centrifuged at 27,000g for 1 hour at 4°C and the supernatant collected. Prior to application

to the column, the supernatant was adjusted to pH 7.5. The supernatant was applied to a

Resource Q (6 mL) column (GE Healthcare Life Sciences, UK), pre-equilibrated with 20 mM

Tris-HCl (pH 7.5) on an Äkta Liquid Chromatography system in a temperature controlled

cabinet held between 6 and 6.5°C. α-Synuclein was eluted with a NaCl gradient (0 – 1 M)

with 1 mM DTT in 20 mM Tris-HCl and a flow rate of 20 mL/min. Fractions with high α-

Synuclein concentrations, determined by absorbance at 260/280 nm and SDS-PAGE were

pooled and concentrated with Vivaspin 6 centrifugal sample concentrators, MWCO: 10,000

Da (GE Healthcare Life Sciences Ltd., UK). The concentrated α-Synuclein was buffer

exchanged into 100 mM AmAc using a HiPrep 26/10 desalting column (GE Healthcare Life

Sciences Ltd., UK), pre-equilibrated with 100 mM AmAc and a flow rate 10 mL/min. The

eluent was flash frozen in a thin film in a freeze-drier flask, lyophilised (Christ Alpha 2-4

LDplus) and stored at -80°C.

2.3. α-Synuclein Aggregation

The aggregation method employed is based on the work of Hashimoto et al. [2] and Fink et

al. [3], modified for Mass Spectrometry (MS) compatibility. For long term aggregation MS

and Ion Mobility - Mass Spectrometry (IM-MS) experiments, 70 µM α-Synuclein in 50 mM

AmAc (pH 7) was incubated at 37°C with agitation (200 rpm) in an incubator shaker.

Samples were incubated individually, removed from the incubator at each time point and

analysed immediately. The time from incubator to instrument was minimised and never

more than 3 minutes. For TEM, samples were aggregated in the same fashion, snap frozen

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and stored at -80°C until TEM grid preparation. All samples endured the same number of

freeze-thaw cycles.

2.4. Amyloid-β peptide Sample Preparation

For all experiments, Aβ(1-42) and Aβ(1-40), pre-treated with Hexafluoro-2-propanol (HFIP),

was purchased from rPeptide (Bogart, USA) and stored as films at -20°C until required. HFIP

treatment produces unaggregated Aβ peptide [4]. In order to prepare a solution of Aβ(1-42)

in H2O (pH 2), Aβ(1-42) was deseeded by Professor David Allsop, University of Lancaster

first by dissolving the film in trichloroacetic acid and thioanisole and incubating for one

hour. The liquid was then removed under a nitrogen stream, prior to dissolving in HFIP and

evaporating twice before aliquoting. Prior to analysis, Aβ(1-42) was dissolved in H2O

adjusted to pH 2 with Hydrochloric acid (HCl) to a concentration of 100 µM, aliquoted, snap

frozen in liquid nitrogen and stored at -20°C until required. To prepare a solution of Aβ(1-

42) or Aβ(1-40) in 20 mM AmAc (pH 7.4), a film was dissolved in 20 mM AmAc to a

concentration of 100 µM and sonicated for 1 minute. The peptide solution was then

aliquoted, snap frozen and stored at -20°C, until required. Deseeded Aβ(1-42) was a gift

from Professor David Allsop, University of Lancaster.

2.5. Mass Spectrometry

All MS experiments with the exception of ECD-FT-ICR MS were conducted on QToF

geometry instruments.

2.5.1. Nano-ElectroSpray Ionisation

Nano-ElectroSpray Ionisation (nESI) was used for all experiments except the HDX-MS

experiments which required an ElectroSpray Ionisation (ESI) source for automation and the

ECD-FT-ICR MS experiments which used an Advion Nanomate nESI source.

nESI tips were prepared in-house from thin wall glass capillaries (ID: 0.69 mm, OD: 1.2 mm,

World Precision Instruments, USA). Capillaries were pulled using a Flaming/Brown

micropipette puller (Sutter Instrument Company, USA). nESI tips were filled using gel

microloader tips (Eppendorf, Germany) or a Hamilton Syringe (Hamilton, USA). The sample

is charged by inserting a small piece of platinum wire (0.125 mm diameter, purity: 99.99%

Goodfellows, UK) into the sample in the nESI tip. The capillary voltage applied differs

between samples and can differ between nESI tips, the lowest capillary voltage possible is

77

applied to the sample in all cases. The position of the nESI tip relative to the external cone

is also important. Both parameters are tuned for maximum intensity and spray stability.

2.5.2. QToF: ion transfer, mass analysis and detection

Figure 2.2 is a schematic of a typical QToF instrument, following ionisation, ions pass

through two skimmers, the cone and the extractor cone (Figure 2.2A and B). The

orientation of these two cones improves sensitivity by guiding the ions into the instrument

along a potential gradient and removing uncharged species and other spray contaminants.

This region is held at 80°C to aid desolvation. The ions then pass through the RF lens (Figure

2.2C) which transfers the ions to the quadrupole analyser region. In this region, the ions

pass through the quadrupole analyser (Figure 2.2D), this may be set to transmit all ions in

MS mode, or to select a specific ion in MS/MS mode, acting as a mass filter. In MS mode,

the ions pass through the collision cell (Figure 2.2E) and transfer lens (Figure 2.2F) into the

ToF region. In MS/MS mode, the selected ion is transferred into the hexapole collision cell.

The collision cell is filled with an inert gas, Argon (BOC speciality gases, UK). The energy at

which the ion is injected into this region can be increased to initiate CID. Upon entry into

the collision cell, the ion undergoes multiple collisions with the argon gas, generating

fragment ions which are transferred into the ToF region by the hexapole transfer lens. In

MS and MS/MS mode, ions are focussed and accelerated into the ToF region by a stack of

lenses. In the ToF region, the pusher (Figure 2.2G) accelerates the ions down the length of

the flight tube. The reflectron (Figure 2.2I), positioned at the base of the flight tube, acts as

an ion mirror and the ions are slowed and reflected towards the MCP detector (Figure 2.2J).

The reflectron also corrects the kinetic energy dispersion of ions of the same m/z, by

causing more energetic ions to take a longer path to the MCP detector [5, 6]. More

energetic ions penetrate deeper into the reflectron than less energetic ions and therefore

take longer to reach the detector [6]. The point detector, a photomultiplier may also be

used for detection (Figure 2.2H), in this configuration, the pusher is inactive and the flight

tube unused. The signal generated by the MCP detector is converted by a Time-to-Digital

Converter (TDC) generating a Total Ion Count (TIC) chromatogram, which can be

deconvoluted into a mass spectrum using the MassLynx software (Waters, UK).

78

Figure 2.2 - QToF schematic.

2.5.3. QToF Ultima/ Ultima Global High Mass Upgrade

High resolution MS was conducted on QToF Ultima and QToF Ultima Global mass

spectrometers (Waters, Manchester, UK) using nESI source units. The QToF Ultima and

Ultima Global used in the following chapters have been fitted with a high mass upgrade kit

from MS Vision, Netherlands. The modifications to the instrument include the installation

of a speedivalve on the source pumping line, enabling fine control of source pressure. A

pressure sleeve is also fitted around the RF lens to aid transmission of high mass species.

The quadrupole mass range has been altered to > m/z 30,000 enabling selection of high

m/z ions. The collision cell has been modified to feature smaller apertures and the argon

inlet line diameter has been increased from 75 µm to 100 µm, increasing argon pressure

and signal intensity. The instrument has also been modified to enable the application of a

collision voltage of 200 V. The typical instrument parameters applied during operation in

positive and negative ionisation mode are listed in Table 2.1. Typical pressures in each

region are: source ~2 x 10-1 mBar, analyser ~7 x 10-3 mBar and ToF ~3 x 10-7 mBar.

79

Table 2.1 - Typical operating parameters for MS experiments performed on a QToF Ultima / Ultima Global instrument with MS Vision high mass upgrade.

Instrument parameter

Value

QToF Ultima

QToF Ultima Global

Comments

Ionisation Polarity + + -

Capillary (kV) ~1.6 Minimised for soft ionisation or tuned for experimental objective Cone (V) 20 - 120

RF Lens 1 (V) 2.5 26 25

Aperture 1 (V) 1 0 0

RF Lens 2 (V) 0 0 0

Source Temperature (°C)

80

LM Resolution (V) Tuned according to experimental objective

HM Resolution (V)

Collision Energy (V) 5 6 10

Ion Energy (V) 1.4 1.3 3

Steering (V) 0 -1 0

Entrance (V) 65 80 71

Pre-filter (V) 6 4 5

Transport (V) 3.7 5 10

Aperture 3 (V) 8.0 7 5

Acceleration (V) 200 200 200

Focus (V) 0 0 0

Tube Lens (V) 200 200 80

Offset 1 (V) -0.8 -2.4 -3.5

Offset 2 (V) 0 0 0

Pusher (kV) 980 980 970

TOF (kV) 9.10 9.10 9.10

Reflectron (V) 34.66 35.00 35.00

Pusher Cycle Time (µS)

70 - 160 Adjusted according to m/z

range

Multiplier (V) 650 550 650

MCP (V) 1800 – 2300

TDC Start (mV) 650 800 700

TDC Stop (mV) 45 60 60

TDC Threshold 0 0 0

80

2.5.3.1. Mass Calibration

Instrument calibration was conducted when required using 2 mg/mL sodium iodide for

mass calibration ≤ m/z 3000 and caesium iodide for mass calibration ≥ m/z 3000, both were

prepared in 50:50 isopropanol:water. Both generate reproducible salt clusters enabling

external instrument mass calibration.

2.6. Ion Mobility - Mass Spectrometry

DT-IM-MS measurements were conducted on the MoQToF, an in-house modified QToF 1

instrument (Micromass, UK). TWIMS measurements were conducted on Waters Synapt G2,

G2S and G2Si instruments (Waters/ Micromass, UK).

2.6.1. MoQToF

The MoQToF instrument has been adapted to perform variable temperature IM-MS

experiments via the addition of a drift cell and supplementary ion optics [7]. These

modifications include an additional drift chamber which holds the pre-cell einzel lenses (L1

to L3), drift cell, post-cell lens (L4) and the post-cell hexapole (Figures 2.3 and 2.4). The drift

cell is 5.1 cm in length and is made from a copper block; the copper end cap is separated by

a ceramic ring [7]. Details of the variable temperature capabilities of the instrument can be

found in [7]. A 500 L/s TMH520 turbomolecular pump (Pfeiffer Vacuum Ltd., UK) is fitted to

the drift chamber, in addition to the three 250 L/s turbomolecular pumps on the standard

instrument [7]. This additional turbomolecular pump is backed by a dual stage rotary pump

(Edwards Vacuum, UK). For IM-MS experiments, the drift cell is filled with helium (99.999%,

BOC speciality gases, UK) to a pressure of 3 to 4 Torr at ~300 K. The pressure is measured

using a Baratron (MKS Instruments, USA) attached to the top of the cell. To enable fine

control of source pressure, an argon inlet into the source block and a speedivalve in the

source pumping line between the source block and the backing rotary pump are fitted.

Figure 2.4 is a schematic of the additional lenses; the drift field is created between the cell

body (C1) and the end cap (C2). TH1 is used to apply a stopping voltage, enabling storage of

ions in the pre-cell hexapole, H1. The pre-cell Einzel lens is used to focus ions into the drift

cell and is composed of three lenses (L1 to L3). The L2 lens is split into four segments

enabling x/y steering. The post cell lens, L4 focuses ions into the post cell hexapole (H2).

81

Figure 2.3 - MoQToF DT-IM-MS instrument schematic.

In an IM-MS experiment, ions are produced in the nESI source and pass through two

skimmers, the cone and the extractor cone, prior to being transferred into the pre-cell

hexapole. Application of a stopping voltage to the top hat lens, TH1 acts as an ion gate,

storing ions in the pre-cell hexapole, see Figure 2.3C. A bipolar pulser, manufactured in-

house is controlled by a Stanford DG535 digital delay generator (Stanford Research Systems

Inc., USA), lowering the top hat lens voltage allows ions into the drift region, beginning the

IM-MS experiment, and also triggers the mobility clock. Ions are focussed into the drift cell

via L1 to L3 (Figure 2.3D). After exiting the drift cell, ions are focussed into the post-cell

hexapole using L4, Figure 2.3E. Ions then travel through the quadrupole analyser region

(Figure 2.3F to H). Ions are then detected using either the point detector or the ToF

detector (Figure 2.3K to M). The MCP detector signal is converted via a 4 GHz TDC card into

the total arrival time distribution and relative ion intensities are binned according to drift

time [7]. Typical operating parameters for a DT-IM-MS experiment can be found in Table

2.2. Typical drift cell lens settings can be found in Table 2.3. Typical pressures in each region

with helium in the drift cell are: source ~3 x 10-1 mBar, analyser ~3 x 10-3 mBar and ToF ~5 x

10-7 mBar.

82

Figure 2.4 - Drift cell and lens schematic. H1: pre-cell hexapole, H2: post-cell hexapole, TH1 & TH2: pre- and post- cell top hat lenses, L1 to L3: pre-cell lenses, L4: post cell lens, C1 & C2: Cell body 1 and 2.

Table 2.2 - Typical operating parameters for DT-IM-MS experiments in positive ionisation mode performed on the MoQToF IM-MS instrument.

Instrument parameter Value Comments

Capillary (kV) ~1.6 Minimised for soft ionisation and tuned

for ion intensity Cone (V) 85 - 190

Extractor (V) 70 - 110

RF Lens 2 (V) 2.4

Source Temperature (°C) 80


HM Resolution (V)

Collision Energy (V) 4

Ion Energy (V) 0.5

Steering (V) -2

Entrance (V) 45

Pre-filter (V) 5

Transport (V) 3

Aperture 2 (V) 3.4

Acceleration (V) 200

Focus (V) 0

Tube Lens (V) 90

Guard (V) 44.1

TOF (kV) 7.2

Reflectron (V) 35

Pusher Cycle Time (µS) 105 - 119 Adjusted according to m/z range

Multiplier (Hz) 650

MCP (V) 2400

TDC Start (mV) 300

TDC Stop (mV) 40

TDC Threshold 0

83

Table 2.3 – The voltage ranges and typical drift cell lens voltages for the MoQToF in positive ionisation mode. All voltages float above the collision cell voltage (CV).

Lens Voltage Range (V) Potential

wrt. C1/C2* (V)

Actual Voltage (V)

H1 0 to 200 31 C1 + H1 = 101

TH1 0 to 200 4 C1 + TH1 = 74

L1 0 to -350 -56 C1 + L1 = 14

L2 0 to -350 -154 C1 + L2 = -84

L3 +50 to -50 23 C1 + L3 = 93

C1 0 to 200 70 C1

C2 0 to 75 10* C2

L4 +50 to -50 -13* C2 + L4 = -3

2.6.1.1. Example Experimental Workflow

The following section details the acquisition and analysis of IM-MS data on the MoQToF

instrument. Firstly source conditions including capillary and cone voltages, source pressure

and drift cell optics are optimised in MS mode. A reference mass spectrum is then acquired

(Figure 2.5A), [aSyn+10H]10+ is highlighted in blue and is used as an example. Then in IM-MS

mode, using a drift voltage of 60 V, a total ion Arrival Time Distribution (ATD) is collected

(Figure 2.5B). The same number of total ion ATDs is collected for each drift voltage, typically

ten or fifteen, although for low intensity species, this number may be increased. Data is

acquired for more than six drift voltages ≤ 60 V. The drift voltage applied is altered by

lowering the potential applied to C1, see Figure 2.4. The temperature and pressure at the

start and end of each drift voltage acquisition is recorded. These values are then averaged

to provide an average temperature and pressure for each drift voltage. By using the

reference spectrum (Figure 2.5A) for guidance within Masslynx and combining over a m/z

region of interest, it is possible to generate an extracted ion ATD such as the one of

[aSyn+10H]10+ at a drift voltage of 45 V shown in Figure 2.5C. This process is repeated for

each distinct charged species observed in the reference spectrum, for each drift voltage

collected. The extracted ion ATDs are summed using an excel spreadsheet. For extracted

ion ATDs featuring a single peak, the peak centre is determined by fitting a single Gaussian

peak. At lower drift voltages, the time the ions spend travelling through the drift region

increases and additional conformational families or oligomeric species may be observed.

The low resolution of the instrument typically yields overlapping species.

84

Figure 2.5 - IM-MS experimental workflow example. A. α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 6.8) B. Total ion ATD at a drift voltage of 45 V in helium, each peak is 200 collated scans. C.

ATD of the [aSyn+10H]10+ species taken at a drift voltage of 45 V, Experimental ATD: black line, Guassian fits: red, green and dark blue lines, Cumulative fit peak: light blue. D. P/V plotted against

arrival time of the red species in Figure 2.5C for seven drift voltages.

For ATDs in which multiple overlapping peaks are present, such as in Figure 2.5C, the peak

centre is derived by one of two ways. Either by fitting each ATD with a Gaussian function

using Origin (OriginLab, USA) as demonstrated in Figure 2.5C or using a Weibull distribution

function in an Excel spreadsheet created by Dr. J. Ujma [8]. The Gaussian function in the

first method is stated in Equation 2.1, where y0 is the offset, A is the area, xc is the centre of

the fitted peak and w is the peak width.

𝑦 = 𝑦0 + 𝐴

𝑤√𝜋

2 𝑒

−2(𝑥−𝑥𝑐)2

𝑤2 Equation 2.1

For each fitted overlapping conformer, such as those present in Figure 2.5C, if the

conformer is present in a minimum of five drift voltages, it is reported. Multiplying the

output of either method for deriving average scan number by the MS pusher time yields

the average arrival time, ta. The average arrival time of a specific ion is the time taken to

travel in this case, between H1 and the ToF pusher and is therefore a combination of the

time taken by an ion to traverse the length of the drift region, td and the time taken for the

ion to travel the rest of the instrument, known as the dead time, t0 (Equation 2.2).

10 12 14 16 18 20

Arrival time / scans

0.05 0.10 0.15 0.20 0.25

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

Arr

ival ti

me /

S

P/V / TorrVolt-1

0 500 1000 1500 2000 2500

Inte

nsit

y / a

rbit

rary

un

its

Scan number

A B

C D

500 1000 1500 2000 2500 3000 3500 4000

m/z

85

𝑡𝑎 = 𝑡𝑑 + 𝑡0 Equation 2.2

An ions behaviour moving through a gas under the influence of an electric field (E) is

dependent on its energy. This energy is determined by the ratio of electric field strength to

buffer gas number density (N), E/N [9, 10]. At the low field limit, defined as a low ratio of

E/N, ions have low velocities, independent of field strength. The low field mobility (K) is

inversely proportional to its drift time (td) and drift voltage (V) and where L is the drift

region length, see Equation 2.3

𝐾 = 𝐿2

𝑡𝑑𝑉 Equation 2.3

An ions mobility is dependent on the temperature and pressure at which the experiment is

conducted. Therefore to normalise for differences in temperature (T) and pressure (P) and

aid data comparison between laboratories, the reduced mobility or K0 is calculated, see

Equation 2.4, where T0 and P0 are the reduced temperature (273.15 K) and pressure (760

Torr), respectively [11].

𝐾0 = 𝐾𝑇0

𝑇

𝑃

𝑃0 Equation 2.4

The average arrival times as determined in Figure 2.5C, are plotted against the pressure/

drift voltage or P/V, using the temperature and pressure values recorded during each drift

voltage experiment, creating a linear plot (Figure 2.5D). The intercept of this plot is equal to

the dead time and the gradient is inversely proportional to the reduced mobility of the ion.

A minimum of five points or drift voltages are required and the R2 value of this line is used

to gauge the quality of the data, an R2 value of ≥ 0.999 is required. The drift time can be

calculated using Equation 2.5.

𝑡𝑑 = 𝑡𝑎 − 𝑡𝑜 = 𝐿2𝑇0𝑃

𝐾0𝑇𝑃0𝑉 Equation 2.5

The gradient of Figure 2.5D and Equation 2.6, can be used to determine the rotationally

averaged CCS, where z is the nominal ion charge state, e is the elementary charge, N is the

number density of the buffer gas, µ is the reduced mass of the ion neutral pair, kB is the

Boltzmann constant, T is the drift gas temperature and Ko is the reduced ion mobility.

𝛺 = 3𝑧𝑒

16𝑁 (

2𝜋

𝜇𝑘𝐵𝑇)

1

2 1

𝐾0 Equation 2.6

86

In all cases, three repeats of each sample are conducted, with repeats spread across a

number of days. Between repeats, the source conditions are tuned and an average CCS

value is reported.

The IDPs investigated in the following chapters do not typically present as distinct resolved

conformers, instead large conformational families of many similar species are observed. In

order to compare data without defining specific CCS values, Collision Cross Section

Distribution (CCSD) plots are generated. Experimental data points are converted to CCS

using the above equations and are plotted normalised to spectral intensity. An example of

this plot can be found in Chapter 4, Figure 4.5.

2.6.2. Synapt

Synapt instrument geometry resembles traditional QToF instruments, see Figure 2.6 and

2.7. Upgrades between the G2 and G2S/Si instruments include the StepWave ion guide. The

StepWave device improves ion transmission and MS sensitivity, its principles and operation

are discussed in [12]. Synapt instruments employ a different IMS methodology, TWIMS. In

contrast to DT-IM-MS, CCS values derived from TWIMS experiments are estimated by

external calibration. The relationship between CCS and an ions mobility within the TWIMS

device has been explored by Shvartsburg and Smith [13]. The TWIMS capabilities of the

Synapt instrument are derived from the Triwave device, located between the pre-Triwave

ion optics and the ToF analyser. The Triwave device is composed of three TWIGs (Figure

2.8).

Figure 2.6 - Waters Synapt G2 instrument schematic. Figure reproduced from [14].

87

Figure 2.7 - Waters Synapt G2S/G2Si instrument schematic. Figure reproduced from [15].

.

Figure 2.8 - Synapt Triwave region schematic featuring three TWIGS. The position of the helium cell is highlighted in yellow. The nitrogen filled IMS region is highlighted in green.

Figure 2.9 is a schematic of the TWIG, each consists of a series of planar ring electrodes

oriented orthogonally to the ion path. Further information on TWIG geometry can be found

in [16]. As in a Stacked Ring Ion Guide (SRIG), to adjacent electrodes, opposite phases of an

RF voltage are applied to radially confine ions (Figure 2.9) [16]. A transient Direct Current

(DC) voltage is then superimposed, sequentially to pairs of adjacent electrodes, creating a

wave (T-wave) to propel ions through the device [16, 17].

Figure 2.9 - TWIG/SRIG schematic. Figure adapted from [16].

88

In a typical TWIMS experiment, ions are generated using the nESI source unit. These ions

are then transferred using the pre-Triwave ion optics, see Figures 2.6 to 2.7. Ions are stored

in the Trap region and released in packets into the IMS region. The transfer TWIG is then

used to transfer ions to the ToF region for mass analysis. Synchronising ToF acquisition with

the release of the ion packet from the Trap enables the ATD to be recorded [16].

Acquisition time is varied according to signal intensity. The typical acquisition time is 5

minutes (scan time: 1 s), this can be increased for low intensity species. Typical operating

parameters used during a TWIMS experiment can be found in Table 2.4 and 2.5.

Table 2.4 - Typical operating parameters for TWIMS experiments performed on Waters Synapt instruments operated in positive ionisation mode.

Value

Instrument parameter Synapt

G2 Synapt

G2S Synapt

G2Si Comments

Capillary (kV) ~1.6 Minimised for soft ionisation and tuned for ion

intensity

Cone (V) 40 - 60 15 - 30

Extractor / Offset (V) 0.6 – 1.4 45 – 80

Source temperature (°C) 80


HM Resolution (V)

Aperture 1 0 0 0


Ion energy (V) 1 1 1

Trap Collision Energy (V) 2 - 4 *

Transfer Collision Energy (V) 0 – 2.5 †

Source gas flow (mL/min) 0

Trap gas flow (mL/min) 0 - 3

He gas flow (mL/min) 120 120 120

IMS gas flow (mL/min) 60 60 60

Detector 2800 2425 2375


Acceleration 1 70 70 70


Aperture 2 70 70 70

Transport 1 70 70 70


Steering 0 -0.9 0

Tube Lens 75 85 75

Pusher 1900 1900 1900

Puller 1370 1370 1370

Collector 50 50 50

Collector Pulse 10 10 10

Entrance 62 62 62

Flight Tube (kV) 10 10 10

89

Reflectron (kV) 3.780 3.780 3.780

Trap DC Entrance 0 5 0

Voltages are tuned for greater ion

intensity

Trap DC Bias 45 45 45

Trap DC 0 3 0

Trap DC Exit 3 5 3

IMS DC Entrance 25 30 20

He Cell DC 35 55 50

He Cell Exit -5 -20 -20

IMS Bias 3 3 3

IMS DC Exit 0 0 0

Transfer DC Entrance 4 5 4

Transfer DC Exit 15 15 15

Trap Wave Velocity (m/s) 508 311 150

Trap Wave Height (V) 4.2 6 4

IMS Wave Velocity (m/s) 800 800 900 Tuned according to sample IMS Wave Height (V) 40 40 40

Transfer Wave Velocity (m/s) 508 175 85

Transfer Wave Height (V) 2.1 4 5.3

Step Wave 1 In Velocity (m/s) N/A 300 300

Step Wave 1 In Height (V) N/A 10 10

Step Wave 1 Out Velocity (m/s)

N/A 300 300

Step Wave 1 Out Height (V) N/A 0 0

Step Wave 2 Velocity (m/s) N/A 300 300

Step Wave 2 Height (V) N/A 0 0

Backing Pressure (mBar) 2.60 3.79 3.27

Source Pressure (mBar) 1.3e-3 6.69e-3 7.95e-3

Trap Pressure (mBar) 1.24e-2 2.11e-2 1.81e-2

He Cell Pressure (mBar) 1.38e3 1.78e1 2.53

IMS Pressure (mBar) 2.6 2.4 2.0

Transfer Pressure (mBar) 2.0e-2 2.0e-2 1.9e-2

ToF Pressure (mBar) 8.06e-7 8.30e-7 5.76e-7

*The Trap Collision Energy is raised incrementally in CIU-TWIMS and CID experiments.

† The Transfer Collision Energy is raised for ETcaD experiments.

90

Table 2.5 - Typical operating parameters for TWIMS experiments performed on Waters Synapt instruments operated in negative ionisation mode

Value

Instrument parameter Synapt

G2 Synapt

G2S Synapt

G2Si Comments

Capillary (kV) ~1.6 Minimised for soft ionisation and tuned for ion

intensity

Cone (V) 60 – 90 30

Extractor / Offset (V) 1.5 - 3 60 - 75

Source temperature (°C) 80


HM Resolution (V)

Aperture 1 0 0 0


Ion energy (V) 1 1 1

Trap Collision Energy (V) 2 - 4

Transfer Collision Energy (V) 0.5 – 2.5

Source gas flow (mL/min) 0

Trap gas flow (mL/min) 1 – 3.5

He gas flow (mL/min) 120 120 120

IMS gas flow (mL/min) 60 60 60

Detector 2350 2775 2675




Aperture 2 70 32 70



Steering 0 0.4 0

Tube Lens 75 35 72

Pusher 1900 1900 1900

Puller 1500 1370 1370

Collector 50 50 60

Collector Pulse 10 10 10

Entrance 62 62 62

Flight Tube (kV) 10 10 10

Reflectron (kV) 3.780 3.780 3.780

Trap DC Entrance 0 0 0

Voltages are tuned for greater ion

intensity

Trap DC Bias 45 45 45

Trap DC -2 0 0

Trap DC Exit 3 3 3

IMS DC Entrance 25 20 25

He Cell DC 35 50 35

He Cell Exit -5 -20 -5

IMS Bias 3 3 3

IMS DC Exit 0 0 0

Transfer DC Entrance 4 4 4

91

Transfer DC Exit 5 15 15

Trap Wave Velocity (m/s) 311 311 311

Trap Wave Height (V) 6 4 4

IMS Wave Velocity (m/s) 350 475 800 Tuned according to sample IMS Wave Height (V) 15 20 25

Transfer Wave Velocity (m/s) 311 191 380

Transfer Wave Height (V) 6 0.1 4

Step Wave 1 In Velocity (m/s) N/A 300 300

Step Wave 1 In Height (V) N/A 10 10

Step Wave 1 Out Velocity (m/s)

N/A 300 300

Step Wave 1 Out Height (V) N/A 0 0

Step Wave 2 Velocity (m/s) N/A 300 300

Step Wave 2 Height (V) N/A 0 0

Backing Pressure (mBar) 2.6 3.6 3.33

Source Pressure (mBar) 1.28e-3 6.4e-3 8.1e-3

Trap Pressure (mBar) 1.4e-2 2.6e-2 1.4e-2

He Cell Pressure (mBar) 1.4e3 1.4e3 1.4e3

IMS Pressure (mBar) 2.6 2.4 1.9

Transfer Pressure (mBar) 1.6e-2 2.4e-2 1.6e-2

ToF Pressure (mBar) 7.3e-7 1.1e-6 4.8e-7

2.6.2.1. CCS calibration

CCS values are calculated for TWIMS experiments by calibration to known values obtained

on a DT-IM-MS instrument, the Ruotolo et al. method is applied in this thesis [18]. In all

experiments, Poly-L-lysine and ubiquitin (1:1, 49.5:49.5:1 Water:Acetonitrile:Formic Acid, 1

mg/mL) were chosen as calibrant ions and the Bush CCS database values were used [19,

20]. Calibrant ions were analysed immediately following binding study experiments,

simultaneously and using identical source conditions. CCS calibration was conducted using

MassLynx v4.1 (Waters, USA), Origin v9 (OriginLab, USA) and Excel (Microsoft Corporation,

USA). The drift times for calibrant ions are corrected for mass-dependent flight times, using

Equation 2.7, where td is drift time, t’d is corrected drift time (both in ms) and c is the

Enhanced Duty Cycle, a constant.

𝑡′𝑑 = 𝑡𝑑 − [𝑐√𝑚/𝑧

1000] Equation 2.7

Calibrant cross sections (Ω) are corrected for charge state, z and reduced mass, µ, using

Equation 2.8, yielding Ω’.

𝛺′ = 𝛺

𝑧 (1 µ⁄ )1/2 Equation 2.8

92

Fitting a plot of ln t’d against ln Ω’, with the linear relationship in Equation 2.9 yields A, a fit-

determined constant and X, an exponential factor. The R2 value of this relationship must be

> 0.98. Figure 2.10A is an example of this plot.

ln 𝛺′ = 𝑥 ln 𝑡′𝑑 + ln 𝐴 Equation 2.9

CCS values for ions of interest can be calculated by plotting Ω against the product of

Equation 2.10. The R2 value of this relationship must be > 0.98. Figure 2.10B is an example

of this plot.

𝑡′′𝑑 = 𝑡′𝑑𝑥

𝑧 (1 µ⁄ )1 2⁄ Equation 2.10

Figure 2.10 - Example TWIMS CCS calibration plots.

2.7. Collision Induced Unfolding –Travelling Wave Ion Mobility Mass

Spectrometry

All Collision Induced Unfolding – TWIMS (CIU-TWIMS) experiments were conducted on a

Synapt G2 instrument (Waters, UK) using a nESI source unit. To conduct CIU-TWIMS

experiments, the collision voltage in the Trap region of the Triwave device, see Figure 2.6,

was raised incrementally.

2.8. Electron Transfer Dissociation

All Electron Transfer Dissociation (ETD) and Electron Transfer Collision Activation

Dissociation (ETcaD) experiments were conducted on a Synapt G2Si instrument (Waters,

UK) fitted with a Glow discharge source block and nESI source unit. 1,3-dicyanobenzene

was used as the ETD reagent for all experiments (Figure 2.11). The glow discharge source

block enables the generation of radical reagent anions. These anions are stored in the Trap

region of the Triwave device, see Figure 2.8. Prior to conducting an ETD experiment, the

1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9

7.0

7.1

ln

'

ln t'D

R2: 0.9897

0 2 4 6 8 10

0

500

1000

1500

2000

2500

3000

R2: 0.9997

t''D

A B

93

intensity of the radical anion is tuned to at least 1x106. Radical intensity is increased by

tuning the glow discharge source voltages or increasing the make up gas flow. The make up

gas flow is the nitrogen gas flow rate across the reagent vial, situated prior to glow

discharge needle, increasing this flow rate increases reagent density. ETD system

maintenance including ETD reagent replacement or cleaning the glow discharge needle,

source block or reagent supply lines can also improve intensity.

Figure 2.11 - Structure of 1,3-dicyanobenzene. ETD electron donor reagent used in all ETD experiments.

During an ETD experiment, the instrument source cycles between two modes, firstly using

the negative ionisation mode glow discharge source, which generates the negative radical,

refilling the Trap region. Secondly, in positive ionisation mode, the nESI source generates

the positive sample cations. The reagent anion and sample cations are separated by

imposing a high T-Wave voltage. Lowering this voltage permits interaction and the ETD

process. Supplemental activation can be applied by raising the collision voltage in the

Transfer TWIG. Instrument parameters are as listed in Table 2.4, additional ETD specific

supplemental instrument parameters are listed in Table 2.6. Acquisition time is varied

according to ion intensity. For Aβ(1-42) experiments (Chapter 5), data was acquired for 1

minute (Scan time: 1 s).

Table 2.6 – Supplemental typical instrument parameters for ETD experiments

Instrument parameter Value

Discharge voltage (kV) 0.9

Discharge Current (µA) 50

Make up gas flow (mL/min) 30

Trap gas flow (mL/min) 18.2

2.9. Surface Induced Dissociation

All Surface Induced Dissociation (SID) experiments were conducted on a Waters Synapt G2

instrument modified to include a prototype SID device designed by the Wysocki group in

94

collaboration with Waters Corporation. The SID device is described in detail in [21] and

details of the preparation of the SID surface can be found in Appendix Section 4.3.1. The

SID device is positioned prior to the IMS region of the Triwave device to enable SID-IMS-MS

experiments, see Figure 2.12 and 2.13. A truncated version of the Trap region is installed to

enable the SID cell to fit within the Triwave region. The additional SID cell ion optics are

powered by an external power supply and controlled by the external Tempus Data System

software (both, Ardara Technologies, USA).

Figure 2.12 - Waters Synapt G2 instrument schematic with SID device modification. Figure modified from [14].

Figure 2.13 - The position of the SID device within the Waters Synapt G2 instrument. The truncated trap TWIG is visible to the left of the SID device within the Triwave device enclosure.

The SID cell can be operated in two modes, the first is denoted ‘flythrough’, in which there

is no interaction with the surface and the second ‘SID’ mode (Figure 2.14). In a typical SID

experiment, the ion intensity is tuned whilst operating the instrument and the SID cell in

MS mode as it is easier to achieve successful flythrough settings in MS mode than in TWIMS

mode. The instrument and the SID cell are then switched into TWIMS mode. To increase ion

95

intensity, the SID cell lenses are tuned, see Figure 2.14. The lenses are tuned in the follow

order: Entrance 1 > Entrance 2 > Front bottom deflector > Front top deflector > Rear

bottom deflector > Rear top deflector > Exit 1 > Exit 2. This process is cycled until no further

increase in ion intensity is achieved. The SID cell tuning parameters for MS and TWIMS

modes are not compatible, as the voltages applied in the Triwave region differ between the

two modes. The voltages applied to the SID cell are modified to reflect this and are listed in

Table 2.7. Special attention is paid to the voltages applied in the Triwave region to ensure

transmission of the ions from the Trap region through the SID device and into the IMS

region. The Trap gas flow is typically set to 2 mL/min to prevent CID. SID is initiated by

increasing the Trap DC bias; this accelerates the ion into the SID device. The Entrance 1

voltage is adjusted to remain within 5-10 V of the Trap exit. The front bottom deflector is

used to steer ions into the surface. The SID fragment intensity may be improved by tuning

of the voltages applied to the optics located post-surface interaction. Tuning of the rear top

and bottom deflectors has the greatest effect on signal intensity. To compensate for low

fragment ion intensity, data was acquired for 10 to 15 minutes per SID collision voltage. The

SID collision voltage is defined as the difference between the Trap exit and the surface. The

injection energy is defined as the difference between the helium cell entrance and the SID

surface.

Figure 2.14 - SID cell schematic. The surface (5) is composed of the surface holder and the gold SID surface.

96

Table 2.7 - Typical operating parameters for the SID cell lenses in flythrough and SID modes.

Parameter

Flythrough SID 40 V

Value (V) Value (V) Value (V)

MS IM-MS

Entrance 1 -117 -35 -5

Entrance 2 -150 -36 -36

Front Top Deflector -132 -40 -40

Front Bottom Deflector -132 -40 -80

Surface -129 -39 -39

Middle Bottom -131 -38 -38

Rear Top Deflector -127 -37 -62

Rear Bottom Deflector -126 -39 -39

Exit 1 -133 -43 -43

Exit 2 -137 -44 -44

2.10. Cross-linking Ion Mobility - Mass Spectrometry

The conditions used for cross-linking experiments are based primarily on the work of

Iglesias et al. [22] and Chen et al. [23]. The BS3 cross-linker (Figure 2.15) was purchased

from Thermo Scientific Pierce, UK.

Figure 2.15 - Structure of the BS3 cross-linking reagent. Note the identical amine reactive functional groups.

Lyophilised α-Synuclein was reconstituted in each buffer solution, to which BS3 cross-linker

was added at a 50:1 molar excess, final α-Synuclein concentration, 100 µM. Reaction

mixtures were incubated at room temperature for 1 hour and quenched by the addition of

1 M AmAc. Samples were desalted via buffer exchange into 50 mM AmAc using Amicon

Ultra centrifuge filters, MWCO: 10 kDa (Millipore, Germany) prior to analysis. Altering the

solution pH away from the ideal working range of the BS3 reagent enables the modulation

of the number of cross-linker reactions. Four buffer conditions were used, each at 50 mM,

sodium acetate (pH 4), sodium phosphate (pH 6), HEPES (pH 8) and sodium carbonate (pH

10), all purchased from Sigma Aldrich, UK. The HEPES buffer pH was modified with KOH

(Sigma Aldrich, UK). Following cross-linking, DT-IM-MS measurements were conducted on

the MoQToF.

97

2.11. Hydrogen Deuterium Exchange Mass Spectrometry

All sample handling including Hydrogen Deuterium Exchange (HDX) labelling and quenching

was automated using a CTC PAL sample manager (LEAP Technologies, Carrboro, NC, USA).

Sample aggregation was conducted as described in Section 2.3 and time points coincided

with the beginning of sample runs. Prior to placing the sample in the PAL sample manager,

α-Synuclein was diluted to 20 µM with 10 mM phosphate buffer. α-Synuclein was then

diluted 20-fold with 10 mM phosphate buffer in 99.99% deuterium oxide (Sigma Aldrich,

UK), pH 6.6/ pD 7.0. Labelling was quenched with an equal volume of chilled 100 mM

phosphate buffer (pH 2.5). 50 µL of the labelled sample was injected onto a nanoACQUITY

UPLCTM system with HDX technology (Waters, USA). A Waters EnzymateTM immobilised BEH

pepsin column (2.1 x 30 mm) was used for in-line pepsin digestion. Digestion was

conducted for 1 minute at 20°C in the presence of 0.1% Formic acid. Peptides were

separated on a UPLC BEH C18 column (Waters, USA) at 0°C. A 7 minute linear acetonitrile

gradient (8-35%) with 0.1% Formic acid and a flow rate of 40 µL/min was used. Mass

spectra were acquired using a Synapt G2Si HDMS instrument (Waters, UK), a m/z range of

50-2000 was used. Analysis was conducted in triplicate. Typical operating parameters can

be found in Table 2.4. Data was analysed with MassLynx v4.1, Protein Lynx Global Server

(PLGS) v3.1 and DynamX v3.0 (Waters, USA). Both PLGS and DynamX require human input,

in PLGS to design peptide filtering criteria including threshold intensity and in DynamX to

curate the matched peptides, as a quality control measure. The DynamX software

automatically produces uptake plots; the raw data of these plots is exported and replotted

for clarity in Origin v9 (OriginLab, USA).

2.12. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and

Electron Capture Dissociation

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) with Electron

Capture Dissociation (ECD) was performed on a 12 Tesla solariX Fourier Transform Ion

Cyclotron Resonance Mass Spectrometer (Bruker Daltronics, Bremen, Germany) with a

NanoMate nESI source (Advion Biosciences, Ithaca, NY, USA) using a capillary voltage of

0.56 kV. Following ionisation, ions pass through a set of focussing lenses prior to a

quadrupole analyser in which they can be mass selected. Ions are then refocussed prior to

transfer into the ICR cell for ECD and mass analysis. A native mass spectrum was acquired

prior to ECD by tuning source optics. Specific ion species were then isolated using the mass

resolving quadrupole and subjected to ECD. For ECD, 1.7 A was applied to the cathode

98

filament, 22 V to the lens and 1.2 V to the bias. The pulse length employed was varied

between 15 and 20 ms, depending on ease of fragmentation. Fragmentation data is the

sum of 70 acquisitions. Data analysis was performed using Data Analysis (Bruker Daltronics,

Bremen, Germany). The SNAP 2.0 algorithm in Data Analysis was used for peak picking

using the following parameters: signal to noise ratio, 0.0001, relative intensity threshold,

0.0001 and quality factor threshold, 0.001. Prosight PTM (v1.0) was used to match

fragment peaks to calculated fragment masses, prior to a final curation by hand [24].

2.13. Transmission Electron Microscopy

All Transmission Electron Microscopy (TEM) experiments were conducted on a Philips

CM120 Transmission Electron Microscope (Philips, Netherlands). To prepare samples for

TEM, 4 µL of sample was spotted onto a 200 mesh formvar and carbon coated copper grid

(TAAB, Aldermaston, UK). Grids were incubated at room temperature for 5 minutes before

any excess was removed by the peripheral application of filter paper. Grids were rinsed by

spotting Deionised (DI) water on the grids and removing the excess with filter paper. 4 µL of

Uranyl acetate (1% working solution) was applied to each grid for negative staining and

incubated at room temperature for 35 seconds with any excess removed by filter paper.

Grids were allowed to dry for a minimum of 5 minutes prior to storage and 12 hours prior

to analysis. Grids were stored at room temperature in petri dishes lined with filter paper.

99

2.14. References

1. Wood, S.J., et al., alpha-synuclein fibrillogenesis is nucleation-dependent - Implications for the pathogenesis of Parkinson's disease. Journal of Biological Chemistry, 1999. 274(28): p. 19509-19512.

2. Hashimoto, M., et al., Human recombinant NACP/alpha-synuclein is aggregated and fibrillated in vitro: Relevance for Lewy body disease. Brain Research, 1998. 799(2): p. 301-306.


4. Stine, W.B., et al., In vitro characterization of conditions for amyloid-beta peptide oligomerization and fibrillogenesis. Journal of Biological Chemistry, 2003. 278(13): p. 11612-11622.

5. Mamyrin, B.A., et al., Mass-Reflectron A New Nonmagnetic Time-Of-Flight- High-Resolution Mass-Spectrometer. Zhurnal Eksperimentalnoi I Teoreticheskoi Fiziki, 1973. 64(1): p. 82-89.

6. Guilhaus, M., Principles And Instrumentation In Time-Of-Flight Mass-Spectrometry - Physical And Instrumental Concepts. Journal of Mass Spectrometry, 1995. 30(11): p. 1519-1532.

7. McCullough, B.J., et al., Development of an ion mobility quadrupole time of flight mass spectrometer. Analytical Chemistry, 2008. 80(16): p. 6336-6344.

8. Chepelin, O., et al., Luminescent, Enantiopure, Phenylatopyridine Iridium-Based Coordination Capsules. Journal of the American Chemical Society, 2012. 134(47): p. 19334-19337.

9. Jurneczko, E. and P.E. Barran, How useful is ion mobility mass spectrometry for structural biology? The relationship between protein crystal structures and their collision cross sections in the gas phase. Analyst, 2011. 136(1): p. 20-28.

10. Mason, E.A. and E.W. McDaniel, Transport properties of ions in gases. 1988, New York: Wiley.

11. Matz, L.M., et al., Investigation of drift gas selectivity in high resolution ion mobility spectrometry with mass spectrometry detection. Journal of the American Society for Mass Spectrometry, 2002. 13(4): p. 300-307.

12. WatersCorporation, Stepwave Enhancing MS Sensitivity and Robustness (white paper). 2012.

13. Shvartsburg, A.A. and R.D. Smith, Fundamentals of Traveling Wave Ion Mobility Spectrometry. Analytical Chemistry, 2008. 80(24): p. 9689-9699.

14. WatersCorporation, Waters Synapt G2 Mass Spectrometry System Operator's Overview and Maintenance Guide. 2009.

15. WatersCorporation, Waters Synapt G2-S HDMS Mass Spectrometer Overview and Maintenance Guide. 2014.

16. Pringle, S.D., et al., An investigation of the mobility separation of some peptide and protein ions using a new hybrid quadrupole/travelling wave IMS/oa-ToF instrument. International Journal of Mass Spectrometry, 2007. 261(1): p. 1-12.

17. Giles, K., et al., Applications of a travelling wave-based radio-frequencyonly stacked ring ion guide. Rapid Communications in Mass Spectrometry, 2004. 18(20): p. 2401-2414.

18. Ruotolo, B.T., et al., Ion mobility-mass spectrometry analysis of large protein complexes. Nature Protocols, 2008. 3(7): p. 1139-1152.

19. Bush, M.F., et al., Collision Cross Sections of Proteins and Their Complexes: A Calibration Framework and Database for Gas-Phase Structural Biology. Analytical Chemistry, 2010. 82(22): p. 9557-9565.

100

20. Bush, M.F., I.D.G. Campuzano, and C.V. Robinson, Ion Mobility Mass Spectrometry of Peptide Ions: Effects of Drift Gas and Calibration Strategies. Analytical Chemistry, 2012. 84(16): p. 7124-7130.


22. Iglesias, A.H., L.F.A. Santos, and F.C. Gozzo, Identification of Cross-Linked Peptides by High-Resolution Precursor Ion Scan. Analytical Chemistry, 2010. 82(3): p. 909-916.

23. Chen, Z.A., et al., Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry. Embo Journal, 2010. 29(4): p. 717-726.

24. LeDuc, R.D., et al., ProSight PTM: an integrated environment for protein identification and characterization by top-down mass spectrometry. Nucleic Acids Research, 2004. 32: p. W340-W345.

101

3 Investigating the Structure of

α-Synuclein

α-Synuclein is heavily implicated in the aetiology of Parkinson’s disease. An amyloidogenic

protein, its native state is an unfolded monomer; however, aggregation end points vary

from oligomers to fibrils and are heavy influenced by the environment.

In this chapter, the conformational and structural dynamics of α-Synuclein are probed by MS

based methods. Gas phase structures are interrogated by MS, IM-MS and ECD-FT-ICR MS

whilst cross-linking IM-MS is employed to investigate solution phase structures.

102

3.1. Introduction

α-Synuclein has been previously studied by MS based methods. The effect of solution

conditions has been previously investigated, the effect of acidic pHs by the Bowers [1] and

Kaltashov [2] groups and the effect of basic pHs by the Grandori group [3]. All note the

coexistence of multiple conformational families, both compact and extended species.

Additionally, the effect of the addition of organic solvents has also been investigated by the

Kaltashov [2], Grandori [3] and Smith groups [4]. The effect of metal ion binding on

conformation has also been the subject of much research [3, 5-7].

To date, the focus of most IM-MS research has been to characterise the effect of small

molecule binding including dopamine [8, 9], gallic acid [10], spermine [11] and the green

tea extract, epigallocatechin gallate (EGCG) [12, 13]. Efforts have also been made to

characterise the effect of lipid binding [14], which has previously been shown to induce

structure by NMR [15]. In addition, Vlad et al. have investigated autoproteolytic fragments

identified during the aggregation of α-Synuclein [16, 17]. IM-MS has also been employed to

characterise the structure of α-Synuclein. Bernstein et al. highlight the effect of pH on α-

Synuclein structure using DT-IM-MS [1] whilst Illes-Toth et al. observe a subpopulation

shown to induce intracellular aggregation using TWIMS [4]. These studies highlight the wide

conformational spread of α-Synuclein. This structural diversity is also reflected by the wide

ATDs, multiple conformational families and co-existing populations reported by all groups,

irrespective of the purpose of the published work.

The aim of the experiments presented in this chapter is to apply MS based methods to

probe the structure of α-Synuclein. In particular, to investigate the effects of ionisation

polarity and solution conditions on the species observed and to compare the solution phase

and gas phase conformations exhibited by α-Synuclein. This chapter is composed of work

published by Phillips et al. in Analyst [18] in which we highlight the conformational

heterogeneity and inter-day variation observed when studying α-Synuclein structure and

aggregation using an unbiased method of analysis. The effect of pH and ionisation polarity

on α-Synuclein structure is investigated by MS. The conformational diversity observed is

further investigated using IM-MS to probe the gas phase structure whilst cross-linking IM-

MS is applied to investigate solution phase structure. ECD-FT-ICR MS is also used to probe

the effect of pH on the gas phase structure of α-Synuclein.

103

3.2. Experimental

3.2.1. Sample preparation

Lyophilised α-Synuclein was reconstituted in 50 mM AmAc at a concentration of 70 µM, at

pH 6.8 or pH 3.5, aliquoted, snap-frozen and stored at -80°C until required.

Aliquots remained frozen until time of analysis. The time from thawing to introduction to

the instrument was minimised.

3.2.2. Mass Spectrometry

nESI-MS experiments were conducted in both positive and negative ionisation modes on

QToF Ultima and QToF Ultima Global instruments (Waters, Manchester, UK). The tuning of

source parameters for soft ionisation to prevent the disruption of higher order oligomers

was tempered by the requirement for sufficient ion intensity. Instrument parameters are

listed in Chapter 2 Table 2.1.

3.2.3. Ion Mobility - Mass Spectrometry

DT-IM-MS experiments were conducted in positive ionisation mode on the MoQTOF [19],

an in-house modified QToF 1 mass spectrometer (Waters, Manchester, UK) equipped with a

nESI source unit. Source parameters were modified to enable soft ionisation, preventing

the disruption of higher order oligomers but to maintain sufficient ion intensity. Instrument

parameters are listed in Chapter 2 Table 2.2. Experiments were conducted in triplicate on

different days.

The voltage applied across the cell was varied during the experiment, between 60 V and 10

V. ATDs were recorded for at least 6 drift voltages and processed as described in Chapter 2

Section 2.6.1.1.

Cross-linking was conducted prior to analysis as described in Chapter 2 Section 2.10.

3.2.4. Electron Capture Dissociation - Fourier Transform - Ion Cyclotron

Resonance Mass Spectrometry

Lyophilised α-Synuclein was reconstituted in 50 mM AmAc at a concentration of 30 µM.

Samples were prepared at pH 6.8 and pH 3.5. pH was adjusted by the addition of acetic

acid. Experiments were conducted as described in Chapter 2 Section 2.12.

104

3.3. Results and Discussion

3.3.1. The Effect of Solution pH modification

Figure 3.1 is the mass spectrum acquired for α-Synuclein (70 µM, 50 mM AmAc) at pH 6.8 in

positive ionisation mode. As expected for an aggregating protein, a range of oligomeric

species are observed ranging from the most intense monomeric species to low abundance

pentameric species. A wide Charge State Distribution (CSD) is observed for monomeric α-

Synuclein and spans from [aSyn+4H]4+ to [aSyn+19H]19+ (Figure 3.1). Presenting over a wide

range of charge states, weighted for the amino acid composition of the protein, is a well-

known characteristic of Intrinsically Disordered Proteins (IDPs) and suggests that α-

Synuclein is a dynamic and flexible protein [20]. This concurs with the opinion of the wider

α-Synuclein community, as highlighted in [21, 22]. The α-Synuclein dimer is also observed

over a wide range of charge states, from [(aSyn)2+7H]7+ to [(aSyn)2+29H]29+, suggesting that

the dimer species is similarly dynamic and flexible. This CSD pattern is also observed for the

α-Synuclein trimers observed, [(aSyn)3+11H]11+ to [(aSyn)3+26H]26+. As expected, as

oligomeric order increases, the intensity of the species decreases. An additional

complication is a rising baseline, indicative of unresolved higher order oligomeric species,

which obscures low intensity species by increasing with the longer acquisition times often

required to observe higher order oligomeric species.

Figure 3.1 - α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 6.8, positive ionisation mode). CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes

oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-multimer (inset) 20x Zoom of low intensity high m/z species. See Appendix Table A2.1 for a list of all species observed.

105

The α-Synuclein mass spectrum in Figure 3.1 has a bi-modal distribution with modes

centred on [aSyn+10H]10+ and [aSyn+7H]7+ and is shifted in favour of higher charged

monomeric species. The presence of m/z coincident species, i.e. [aSyn+5H]5+ and

[(aSyn)2+10H]10+ which present at the same m/z complicates mode association.

α-Synuclein is a highly dynamic species which presents as a large degree of conformational

flux, it is possible to observe this dynamic nature due to the unbiased sampling of MS based

methods. Figure 3.2 is three mass spectra of α-Synuclein (70 µM, 50 mM AmAc, pH 6.8)

recorded under similar source conditions with clear differences in the CSDs. The spectra are

predominantly composed of the monomeric form of α-Synuclein with higher order

oligomers also present. Both Figure 3.2A and B feature the wide CSD of an IDP, spanning 4 ≤

z ≤ 20 (Figure 3.2A) and 5 ≤ z ≤ 19 (Figure 3.2B) for the monomeric species [aSyn+zH]z+.

Similar CSDs, which differ in terms of relative intensity, are also observed for dimeric and

trimeric species. Figure 3.2A presents a multimodal distribution, with modes centred on

[aSyn+17H]17+, [aSyn+14H]14+ and [aSyn+11H]11+. In contrast, Figure 3.2B presents as a

predominantly monomodal distribution, with a single mode centred on [aSyn+14H]14+. The

monomodal distribution highlights the lower intensity of dimeric and trimeric species.

Additionally, the most intense species shifts from [aSyn+17H]17+ in Figure 3.2A to

[aSyn+14H]14+ in Figure 3.2B and there is a dramatic shift in the relative intensity of some

species, for example the intensity of [aSyn+10H]10+ is significantly lower in Figure 3.2B

compared to Figure 3.2A. The shift in intensity of these species indicates changes to the

solution phase conformers. The multimodal distribution of sample A (Figure 3.2A), suggests

the sample is enriched for multiple conformational families of monomeric and low order

oligomeric species and that the protein has occupied a preferential state, competent of

acquiring 10 charges. In comparison, the distribution of Figure 3.2B suggests that the

species observed are from a sample enriched for elongated monomeric species, whose

greater solvent accessibility leads to increased charging, resulting in a higher intensity of

highly charged monomeric species. The Figure 3.2C CSD is very different in comparison with

Figure 3.2A or B despite being acquired using the same source sample. Although the

spectrum was collected at a later date on the same model instrument, with modifications

to the source and post-source ion optics, using a MALDI competent source unit and a SRIG

instead of a quadrupole ion guide. Figure 3.2C presents a similarly wide CSD (4 ≤ z ≤ 19) and

the presence of low order oligomers including dimeric and trimeric species. Tetramers are

not observed; however, low intensity pentamers are observed. Figure 3.2C features a

bimodal distribution (mode centres: [aSyn+10H]10+ and [aSyn+7H]7+) and a lower most

106

intense species ([aSyn+10H]10+). This suggests the sample is enriched for compact

conformational families, whose lower solvent accessibility leads to the presentation of

lower charge states. This suggests that the low order oligomeric species present in the

sample vary in their presentation to the gas phase even under similar, highly controlled

experimental conditions. This inter-sample variation highlights the difficulty of studying

aggregating species and the need to characterise all these species in an unbiased manner,

to understand the complex aggregation process and prevent the targeting of a non-toxic

species or the accumulation of a toxic species.

Figure 3.2 – α-Synuclein mass spectra (70 µM, 50 mM AmAc, pH 6.8, positive ionisation mode) recorded under the same conditions at different times. A and B were collected 1 month apart on the same instrument, C (Figure 3.1) was collected later on the same model instrument and is included for

comparison. CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-

multimer. (inset) Zoom of low intensity high m/z species. A. 1000x B. 120x C. 65x. See Appendix Table A2.1 for a list of all species observed.

107

Figure 3.3 – α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 3.5, positive ionisation mode). CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes

oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-multimer. (inset) 250x zoom of low intensity high m/z species. See Appendix Table 2.1 for a list of all species observed.

Protein structure and conformation can be affected by the solution environment. Solution

pH has a large effect and within the lifetime of a protein it will be exposed to multiple pH

environments. Some proteins may be located in an environment in a natural constant state

of pH flux or a disease-related pH flux such as that exhibited by neurons in Parkinson’s

disease [23]. The solution conditions present prior to ionisation are known to have a large

impact on the charge states and conformations observed [4, 24]. The conformational flux

observed at pH 6.8 (Figure 3.1 & 3.2) is also observed with a lower solution pH. Figure 3.3

and 3.4 are mass spectra of α-Synuclein (70 µM, 50 mM AmAc, positive ionisation mode)

with the solution pH reduced to 3.5. Again, a wide range of charge states is observed,

spanning 4 ≤ z ≤ 17 and 3 ≤ z ≤ 12 for the monomeric species in Figures 3.3 and 3.4,

respectively. The Figure 3.4 monomer CSD is narrower than Figure 3.3, suggesting the

sample used for Figure 3.4 is enriched for more compact species, which are less solvent

accessible and therefore display lower charge states. Figure 3.3 displays a multimodal

distribution dominated by highly charged monomeric species with [aSyn+10H]10+, the most

intense species. Figure 3.4 in comparison, which also features a multimodal distribution,

displays a more complicated overlapping distribution, dominated by [aSyn+7H]7+ (m/z

2066). There is significant intensity in higher charged monomeric species and a further

mode is centred on [aSyn+10H]10+ (m/z 1447), the most intense species in Figure 3.3. These

108

changes to the intensity distribution are indicative of differences in the solution

components.

Figure 3.4 – α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 3.5, positive ionisation mode). CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes

oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-multimer. (inset) 100x zoom of low intensity high m/z species. See Appendix Table A2.1 for a list of all species

observed.

The clarity of the entire CSD including higher order oligomers is greater in Figure 3.3, but

the species observed are of a lower oligomeric order than those of Figure 3.4. Hexameric

and septameric species are observed in Figure 3.4; however, the CSD width of these higher

order oligomeric species is obscured by their low intensity and a higher baseline. This

suggests that changes to the source conditions are breaking up larger aggregates leading to

a greater intensity of these oligomeric species [25], despite tuning of source parameters to

minimise this or that this change is a result of the inter-day variation demonstrated by α-

Synuclein.

Figure 3.2A and Figure 3.4 were acquired on the same instrument, under both solution

conditions (pH 6.8 and pH 3.5). α-Synuclein presents a wide CSD at both pHs, monomeric

species span 4 ≤ z ≤ 20 at pH 6.8 (Figure 3.2A) whilst at pH 3.5 the CSD has shifted to the

dominance of lower charge states (3 ≤ z ≤ 12, Figure 3.4). This shift is replicated in the CSD

of the higher oligomeric species, the dimer and trimer populations dropping from 10 ≤ z ≤

23 and 19 ≤ z ≤ 22 to 7 ≤ z ≤ 13 and 8 ≤ z ≤ 17, for pH 6.8 and pH 3.5, respectively. This

change is also observed when Figure 3.1/3.2C and Figure 3.3 are compared, but the change

109

is not as dramatic. Frimpong et al. observed a similar shift in the CSD when solution pH was

dropped to pH 2.5 [2]. The drop in charge state suggests that the protein has adopted a

more compact conformation, thus reducing the solvent accessibility of protonatable sites.

This hypothesis concurs with other biophysical techniques. Both Far UV CD, by the increase

in negative intensity at 220 nm and FTIR, by the appearance of a band at 1626 cm-1, both

infer the induction of structure following a decrease in solution pH [26]. SAXS data also

points to a switch from a predominantly random coil conformation to the development of a

protein with a tightly packed core [26]. Bernstein et al. also report a Collision Cross Section

(CCS) decrease, when solution pH is dropped [1].

An interesting feature of spectra recorded from samples with a lower solution pH is the

greater intensity of higher order oligomeric species, ranging from dimer to septamer. The

lower sample pH (pH 3.5) combined with the low pI of α-Synuclein (pI 4.67), results in less

protein-protein repulsion and is therefore an environment conducive to oligomer formation

[27].

The large increase in baseline noise which is attributed to the presence of multiple low

intensity unresolved higher order aggregates, supports the theory that the higher order

oligomers resolved are the result of aggregation [28] rather than an artefact of the ESI

process and are not simply non-specifically bound monomers. This hypothesis is also

supported by the depletion of overall signal intensity, a similar effect is observed under

aggregating conditions, as low order oligomers are sequestered into higher order oligomers

which are beyond the range of the instrument, see Appendix Figure A3.1 and A3.2.

110

3.3.2. The Effect of Ionisation mode

The choice of ionisation mode either positive or negative, purely in terms of generating ions

is of greater importance for small molecules, whose acidic or basic nature must be taken

into account to optimise ionisation. This is not the case for peptides and proteins, which in

most cases will have both, acidic and basic residues, as well as the chargeable N-terminal

amine and the C-terminal acid groups. For instance, α-Synuclein has 24 acidic residues (Asp

and Glu) and 16 basic residues (Arg, Lys and His), a net charge of -8. For proteins the choice

is based on which polarity is more ‘native’. The ‘correct’ ionisation polarity for α-Synuclein

is a matter of contention with groups favouring positive ionisation mode [2, 4, 8-10, 12, 14,

16, 17, 29, 30] and groups favouring negative ionisation mode [1, 3, 11, 31].

Figure 3.5 – α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 6.8, negative ionisation mode). CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes

oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-multimer. (inset) 50x zoom of low intensity high m/z species. See Appendix Table A2.1 for a list of all species observed.

Figure 3.5 is the mass spectrum of α-Synuclein (70 µM, 50 mM AmAc, pH 6.8) recorded in

negative ionisation mode. The spectrum features a wide CSD, previously observed in

positive ionisation mode and indicative of an IDP; however, the relative intensity

distribution is shifted across the range of charge states observed. There is negligible change

to monomer CSD width, spanning 4 ≤ z ≤ 19 and 3 ≤ z ≤ 17, in positive and negative mode

respectively (Figure 3.1 vs. Figure 3.5). A multimodal distribution is observed for both

ionisation polarities. In negative mode, the spectrum is dominated by a very intense [aSyn-

111

6H]6- (m/z 2411) peak and a low intensity [aSyn-7H]7- (m/z 2066) peak. This occurs at a

similar level of charging as the large CCS increase observed by Bernstein et al. [1]. An

additional mode is also centred on [aSyn-11H]11-. The modes of the higher order oligomeric

species are difficult to assign due to the observation of isolated species, the result of a

raised baseline obscuring these low intensity species. The observation of higher order

oligomeric species and the shift in relative intensity to lower charged species following the

polarity change mimics the effect observed when the solution pH is lowered (Figure 3.2A vs

3.4).

Figure 3.6 – α-Synuclein mass spectrum (70 µM, 50 mM AmAc, pH 3.5, negative ionisation mode). CSD extremes and species of interest are labelled oligomeric order/ charge. Marker colour denotes oligomeric order: red-monomer, blue-dimer, yellow-trimer, purple-tetramer, green-multimer. See

Appendix Table A2.1 for complete list of species resolved.

Figure 3.6 is the mass spectrum of α-Synuclein (70 µM, 50 mM AmAc) recorded in negative

ionisation mode following the lowering of solution pH to 3.5, despite the use of similar

source parameters the spectra differs from that observed in Figure 3.5. The wide

monomeric CSD observed is shifted to lower charged species and spans 4 ≤ z ≤ 14 (3 ≤ z ≤

17, Figure 3.5). The CSD of higher order oligomeric species is also narrower. The overall

relative intensity distribution is similar to positive ionisation mode (Figure 3.1); however,

there is a much higher baseline suggesting a greater intensity of low intensity unresolved

higher order oligomeric species. This suggests that negative ion mode may transfer a

greater intensity of higher order oligomeric species into the gas phase; however, they

remain unresolved. As observed in positive ionisation mode, the charge states of higher

112

order oligomers observed following the lowering of solution pH are lower. In negative

ionisation mode, the effect is enhanced as only the [(aSyn)2-5H]5- to [(aSyn)2-7H]7- dimer

and [(aSyn)3-10H]10- and [(aSyn)3-14H]14- trimers are observed.

From this data it is clear that the ionisation polarity has an effect on the species exhibited

by α-Synuclein. Interestingly, this effect is reduced at lower solution pHs suggesting the

environmental structural modifications are in competition with, and have a larger effect

than coloumbic effects. MS has demonstrated a large degree of variation in the α-Synuclein

signal from nESI, irrespective of the solution pH or ionisation polarity.


IM-MS can be used for the structural analysis of a given protein which presents as a

heterogeneous mixture of conformational families and oligomeric species, such as α-

Synuclein. IM-MS cannot provide the atomistic resolution of X-ray crystallography or NMR.

However, these techniques fall short of truly representing the conformational space

occupied by IDPs. X-ray crystallography requires the pinning of a single conformation in a

crystal lattice and NMR struggles to define the regions of disorder in IDPs. NMR strategies

have been developed for the analysis of IDPs; however, experimental difficulty and

complexity increases with IDP size [32].

α-Synucleins characteristic wide monomer CSD is present in m/z vs. CCS plot (Figure 3.7A)

spanning 5 ≤ z ≤ 16. Additional species are visible in the mass spectrum (Figure 3.7B);

however, only species with sufficient signal intensity for IM-MS analysis are included. The

CCS range covered by the CSD is large, spanning 937.53 to 3093.17 Å2 which is

characteristic of an IDP. Appendix Table 2.2 contains the experimental CCS values for all

charge states and conformational families observed. Multiple conformational species are

observed for each charge state (Figure 3.7A & 3.7C), a feature also observed in IM-MS

aggregation experiments (Chapter 4, Figure 4.5). This concurs with the multiple species

observed by Illes-Toth et al. [8] and Lee et al. [14]. The Illes-Toth et al. CCS values are in

good agreement; however, the Lee et al. values are slightly larger, this may be a result of

the use of harsher source parameters, including the use of an ESI source unit and very

different instrumental parameters.

As expected CCS increases with charge, this trend has been reported previously for many

proteins [33, 34]. Despite the use of positive mode rather than negative mode used by

Bernstein et al., the CCS values of the lower charge species are in good agreement [1].

113

However, the molecule does not undergo the large CCS increase observed between the

[aSyn-8H]8- and [aSyn-9H]9- charge states (Figure 3.7C) and following this the CCS values

derived for the numerically equivalent but opposite polarity charge states are much lower

[1]. Grabenauer et al. report similar CCS values for the lower charge states [11], without the

large change in CCS reported in [1]. This suggests that the larger CCS values seen in negative

ionisation mode are driven mainly by the location of chargeable residues and the coulombic

repulsion which results from their charging. The large error bars present for most species

highlight the large variation observed between samples prepared and analysed under

strictly controlled conditions. The same diversity is highlighted by Illes-Toth et al. [8] and in

the lower charged species reported by Grabenauer et al. significant variation is observed

[11].

114

Figure 3.7 – α-Synuclein (70 µM, 50 mM AmAc, pH 6.8, positive ionisation mode) A. m/z vs. CCS plot B. Mass spectrum, monomer and dimer CSD extremes and species of interest are labelled. Species are

labelled oligomeric order/ charge. Red labelled species are present in mass spectrum but not of sufficient intensity for IM-MS. See Appendix Table A2.1 for a list of all species observed. C. Charge

state vs. CCS plot. Error bars where present are associated with values which are the average of three repeats and represent the standard deviation.

115

3.3.4. Cross-linking Ion Mobility - Mass Spectrometry

The phase transition from liquid to solid and the trapping of a protein conformation from a

heterogenous distribution of protein conformers in a crystal lattice is widely accepted and

the basis of X-ray crystallography. The other major biophysical structural technique, NMR

has the ability to analyse samples in the liquid phase. MS and IM-MS require the phase

transition from liquid to gas and the ability to retain solution structure is an issue of

constant debate. This is despite the development of soft ionisation sources including nESI

which has enabled the transfer of large intact biomolecules into the gas phase [35] and

evidence for the retention of α-helices and β-sheet structures in the gas phase [36-38].

Chemical cross-linking has many applications and is a well-known technique for the

characterisation of protein conformation and protein-protein interactions. Cross-linking is

usually followed by an enzymatic digestion step; however, in this application enzymatic

digestion was omitted to ‘trap’ solution phase structures and transfer them to the gas

phase for IM-MS analysis.

The presence of the chemical cross-linker in solution causes some additional hurdles for

structural analysis. The BS3 cross-linking reagent used in this study is a homobifunctional

amine reactive non-targeted cross-linker and will react with all possible lysine residues and

N-termini. This uncontrolled reactivity means charge state peaks are broadened by multiple

tailing peaks, each representing n+1 crosslink modifications. The spectrum generated

resembles a spectrum contaminated with a salt such as NaCl, see Figure 3.8A and B. It was

not possible to obtain dimer or higher order oligomer CCS data, due to the peak broadening

observed. The extent of cross-linking can be modified by altering the working conditions

such as the solution pH. The CSDs of the crosslinked α-Synuclein samples are narrower than

those recorded prior to cross-linking, the monomer CSD width has decreased from 5 ≤ z ≤

18 (Figure 3.7B) to 5 ≤ z ≤ 16 for the pH 4 (Figure 3.8A) and 6 ≤ z ≤ 10 for the pH 8 (Figure

3.8B) conditions. The narrowing of the CSD is an indicator of the action of the cross-linker

modification to ‘pin’ conformations, restricting the flexibility of the protein. This effect is

clear when the Collision Cross Section Distributions (CCSDs) of the modified and unmodified

protein are compared (Figure 3.9). This effect is most obvious in the [aSyn+7H]7+ CCSD

(Figure 3.9Bi) whereby it is clear narrowing of the CCSD is occurring with the addition of as

few as four crosslink modifications and the effect is dramatically enhanced with the

addition of eleven crosslink modifications (Figure 3.9Biv). This narrowing suggests that the

cross-linker is a) decreasing the population of conformers sampled and b) preventing the

adoption of the extreme compact CCS values displayed in the unmodified distributions. This

116

is also evident in the [aSyn+6H]6+ and [aSyn+8H]8+ CCSDs and in the higher charged species.

The highest charged species examined ([aSyn+10H]10+) exhibits the same most collapsed

state (~1200 Å2), this suggests that coulombic repulsion in these species is preventing the

complete collapse of the protein, which has been previously predicted to be 873.4 Å2 [20].

To predict the smallest CCS measureable, the volume of the protein sphere is calculated

according to molecular weight [20]. The radius of this sphere is then used to calculate the

CCS and a scaling factor is applied to match experimentally determined CCS values [20].

Figure 3.8 - α-Synuclein mass spectrum (100 µM, 50 mM AmAc) following cross-linking at pH 4 (A) and pH 8 (B). Note the peak broadening with additional modifications. Figure reproduced from [18].

Extensive cross-linking is apparent from Figure 3.8A&B and analysis of the CCSDs obtained

highlights three distinct conformational families (Figure 3.9). The first conformational family

identified, designated C1 and highlighted in red in Figure 3.9Ai, is the most compact family

and is centred on a CCS of ~1200 Å2. It is most clearly seen in the [aSyn+6H]6+ CCSD (Figure

3.9Ai) and is retained even following the addition of eleven crosslink modifications (Figure

3.9Aiv). This species is also present in the CCSDs of the higher charged species analysed at

very low intensity.

The second conformational family, centred on ~1500 Å2 and designated E1, is highlighted in

orange in Figure 3.9Aiv and is slightly more extended than the first family. This

conformational family emerges following the addition of 10 crosslink modifications to the

[aSyn+6H]6+ species and their presence further stabilises this extended species, see Figure

117

3.9Aiii and Figure 3.9Aiv. The co-stabilisation of this extended conformational family

suggests that in solution α-Synuclein is in a state of flux and the additional cross-linker

modifications act like molecular pins holding the structure during the transition from the

solution to the gas phase. This extended conformational family, E1 is dominant for charge

states [aSyn+7H]7+ to [aSyn+10H]10+, see Figure 3.9Bi to Figure 3.9Eiv. This conformational

family matches the CCS value reported by Bernstein et al. for the α-Synuclein [aSyn-8H]8- -

species [1]. Interestingly, this set of CCSDs are noticeably broader and show considerably

more tailing than the [aSyn+7H]7+ species upon comparison of both the unmodified and the

crosslink modified α-Synuclein CCSDs. This increased level of conformational diversity could

be the result of the greater levels of coulombic repulsion suffered by this species in

comparison with other lower charge species but interestingly, Bernstein et al. report a large

CCS increase between the [aSyn-8H]8- and [aSyn-9H]9- species, this follows the resolution of

multiple conformers for [aSyn-8H]8-, whereas lower charge states present as single or

multiple conformations with only a small CCS difference [1]. This conformational diversity is

also reported by Illes-Toth et al. [8] and Grabenauer et al. [11].

The third conformational family, U1, represents a more unfolded conformational ensemble,

is centred on ~2350 Å2 and highlighted in green in Figure 3.9Diii. The presence of additional

crosslink modifications progressively stabilises this unfolded conformational family. It is

highly likely that this conformational family is present in the CCSD of lower charged species

at a much lower intensity, particularly the [aSyn+8H]8+ species, although in this case the

width of the CCSD prevents assignment. This family closely matches the CCS value reported

by Bernstein et al. for the [aSyn-9H]9- species and is in good agreement with the radius of

gyration calculated from pH 7 SAXS data [1, 26]. The incremental changes in the CCS values

between the charge states are the result of the additional coulombic repulsion suffered by

the higher charge states.

Another interesting feature is the transmission of both the extended and unfolded

conformational families at higher charge states; see Figure 3.9Diii to Figure 3.9Eiv shown by

the wide CCSD of the unmodified samples and observation of the family even with few

crosslinker modifications. This suggests α-Synuclein is present in an ensemble of dynamic

conformational families and the crosslinker is able to pin multiple conformational families

in solution. This concurs with single molecule Atomic Force Microscopy (AFM) data which

highlights the co-presence of multiple monomeric α-Synuclein morphologies [39].

118

This data demonstrates that cross-linking prior to IM-MS enables the analysis of solution

phase structures in the gas phase. The BS3 cross-linker used in this study has a spacer arm

length of 11.4 Å and although untargeted, cross-linker reactivity is limited to primary

amines. Due to the disordered and flexible nature of α-Synuclein in solution, it is possible

that the cross-linking reaction may select for or be biased towards cross-linking conducive

structures such as those with exposed lysine residues or lysine residues within close

proximity, which may represent a subpopulation of solution structures. A range of cross-

linking reagents with different reactivity terminals and spacer arm lengths are commercially

available. Further experiments, using a range of these reagents should be conducted to

determine whether the conformational families observed reflect the full range of solution

structures.

119

Figure 3.9 – α-Synuclein CCSDs with and without cross-linking. Dashed black line: un-modified α-Synuclein CCSD. Solid line: Crosslinked α-Synuclein CCSD. The CCSDs are arranged in order of increasing number of modifications i) four modifications to iv) 11 modifications. The number of modifications is composed of a mixture of complete crosslinks and dead end crosslinks. These CCSDs highlight the modification to the CCSD of α-Synuclein and the trapping of three distinct conformational families. All data

was taken with 30 V across the drift cell. Figure reproduced from [18].

120

3.3.5. Investigating α-Synuclein Structure using ECD-FT-ICR MS

Electron Capture Dissociation (ECD) is routinely applied for protein and peptide sequencing

and to establish the location of post-translational modifications. In addition to its routine

applications, the presence of higher order structure can also be probed due to the

fragmentation mechanism [40, 41]. Here, ECD has been applied to probe the effect of pH

on the structure of α-Synuclein. ECD efficiency is known to increase with charge state [42].

However, the structural information which can be gained from fragmentation of these

charge states is impaired by the increased levels of gas phase coulombic distortion they

suffer from. Therefore, lower charge states than previously studied [43] were selected in

this study, as they are less affected by gas phase coulombic distortion and fragments may

be related to a solvated structure. As expected, this results in a lower fragmentation

efficiency. Figure 3.10 highlights the charge states selected and their position within the

overall α-Synuclein CSD.

Figure 3.10 – α-Synuclein mass spectrum (30 µM, 50 mM AmAc) recorded on a Bruker Solarix 12T FT-ICR MS instrument prior to ECD. The CSDs observed at each pH are similar to those observed on ToF

instruments. Species analysed by ECD are labelled. The dashed lines highlight charge states not analysed at pH 3.5. See Appendix Table A2.1 for a list of all species observed. Figure reproduced from

[18].

121

The spectra obtained are similar to those obtained using ToF instruments (Figure 3.2A-C vs

3.10), at pH 6.8 a wide CSD is observed spanning 5 ≤ z ≤ 18 and 11 ≤ z ≤23 for the

monomers and dimers, respectively. The spectrum at pH 6.8 differs in terms of the overall

intensity distribution, significant intensity remains centred on the highly charged monomer

species with a mode centred on [aSyn+14H]14+ and there is a greater intensity of lower

charged species with an additional mode is centred on [aSyn+8H]8+ (Figure 3.10 bottom).

The monomer and dimer CSD widths remain similar after the solution pH is lowered and as

observed on ToF instruments, the intensity distribution shifts to lower charge states. The

most intense species of the monomer distribution shifts to [aSyn+7H]7+ and a lower

abundance of highly charged monomers is observed (Figure 3.10 top). Interestingly, higher

order oligomeric species such as trimers and tetramers are not observed. This may be due

to the lower sample concentration used generating a lower abundance of these species,

which are subsequently obscured by the raised baseline [44] or due to the use of the

Nanomate source compared to the nESI source of the ToF instruments, which may disrupt

higher order oligomers. The clarity of the spectrum and lack of peak broadening in the pH

3.5 spectrum are likely the result of the disruption of salt adducts due to the different ion

optic geometry of the FT-ICR MS instrument. Species were chosen on the basis of their

compliance with fragmentation and of being of high enough intensity to observe fragments.

Figure 3.11 are the α-Synuclein ECD fragmentation maps at pH 6.8 and pH 3.5. The

fragmentation observed at both pHs appears equal based on inspection of the

fragmentation maps; however, the coverage observed for pH 6.8 is heavily influenced by a

large increase in fragmentation observed for [aSyn+10H]10+ (Figure 3.12 vs. 3.13). The

increase in fragmentation observed can be explained by the increased coulombic unfolding

suffered by a higher charged species resulting in the adoption of a more fragmentation

conducive structure [42, 45]. This charge state has been demonstrated by IM-MS to exhibit

an extended and therefore fragmentation competent conformation [42, 45].

122

Figure 3.11 - ECD fragmentation maps of the α-Synuclein monomer species investigated at pH 6.8

and pH 3.5. Figure reproduced from [18].

Lowering the solution pH from 6.8 to 3.5 led to an overall increase in fragmentation for

both the monomer and dimer species investigated. This effect is clear when comparing the

[aSyn+9H]9+ monomer at pH 3.5 with the respective charge state at pH 6.8 (Figure 3.12 vs

3.14). This suggests the protein has adopted a less compact form, with fewer non-covalent

interactions making the species more susceptible to ECD. This is at odds with reported data,

firstly the CSD shift to lower charge states suggests compaction of the protein, the lower

charge states a result of a less solvent accessible solution structure. Secondly, published IM-

MS data describes the partial collapse of the protein when the solution pH is reduced to 2.5

[1], theorised to be the result of the C-terminus collapsing following protonation. In

addition, this does not concur with other biophysical techniques including far-UV CD, FTIR,

ANS fluorescence and SAXS which all demonstrate an increase in structure following a

decrease in solution pH, which would result in reduced fragmentation [26]. The increase in

fragmentation observed could be the result of the extension of the N-terminus of the

protein, which has been shown by NMR to adopt a more extended conformation at lower

pH [46], in contrast to the structural collapse experienced by the C-terminus at low pH.

123

Figure 3.12 – The annotated mass spectrum of [aSyn+9H]9+

following ECD fragmentation of α-Synuclein (30 µM, 50 mM AmAc, pH 6.8).

Figure 3.13 - The annotated mass spectrum of [aSyn+10H]10+ following ECD fragmentation of α-Synuclein (30 µM, 50 mM AmAc, pH 6.8). Note the complexity of the spectrum following

fragmentation including the large number of c- fragment ions and unidentified fragment ions. Figure reproduced from [18].

124

Figure 3.14 - The annotated mass spectrum of [aSyn+9H]9+ following ECD fragmentation of α-Synuclein (30 µM, 50 mM AmAc, pH 3.5). Note the complexity of the spectrum including the large

number of c- fragment ions and unidentified fragment ions. A greater number of z- fragment ions are identified compared to pH 6.8 (Figure 3.12). Figure reproduced from [18].

Lowering the solution pH also resulted in an increase in fragmentation for the dimer species

investigated, highlighted by the large increase in fragments identified, see Table 3.1.

125

Table 3.1 – The fragments identified of α-Synuclein dimers [(aSyn)2+13H]13+, [(aSyn)2+15H]15+ and

[(aSyn)2+17H]17+ at pH 6.8 and pH 3.5 following ECD. 13+ fragments are underlined, 15+ fragments are in brackets and 17+ fragments are in bold. Resolution of the fragment from multiple charge states is identified by combining the typography emphasis styles. Table reproduced from [18].

pH 6.8 pH 3.5

13+ / (15+) / 17+ 13+ / (15+) / 17+

C ion Z ion C ion Z ion (C115) (C57) C35 (C6)

C279 C149 C98 C75 C50 C47

(C46) C39

(C38) C37 C35 C34

(C27) (C24) (C23) (C22) (C21) C11 (C9) (C6)

(Z274)

Fragmentation is limited to the N-terminus of the protein at pH 6.8 and pH 3.5. If the

[aSyn+9H]9+ fragmentation maps are compared, fragmentation is limited from between

Gly47 and Ala140 at pH 6.8 and between Ala76 and Ala140 at pH 3.5. This pattern is

replicated for the dimer species investigated. This concurs with the N-terminus unfolding at

low pH, the hypothesis suggested for the increase in fragmentation observed following the

reduction of solution pH. The limited C-terminal fragmentation suggests under these

conditions the C-terminus is involved in a stable protected core region. This correlates well

with paramagnetic relaxation enhancement and NMR dipolar coupling experiments [47,

48], which establish interactions between a C-terminal hydrophobic cluster and the central

NAC region, a highly hydrophobic region itself; this would decrease ECD efficiency [49]. This

also concurs with single molecule Förster Resonance Energy Transfer (FRET) experiments

which highlight the compaction of the C-terminus at lower pH and the closer interaction of

the C-terminus with the NAC core domain [50]. Additionally the termini are found to be in

close proximity at both pH conditions tested, although these values are from solution

126

conditions including salt concentrations far in excess of those achievable via MS based

methods [50].

The location of the α-Synuclein dimer interface is an area of interest. The NAC domain of α-

Synuclein is necessary for the aggregation pathway leading to fibrils [51]. However, the N-

terminus of α-Synuclein is the location of the interface of dopamine-mediated dimers,

suggesting the existence of multiple distinct formation pathways [9, 52]. The lack of C-

terminal fragments observed for the dimer species suggests that the C-terminal region is

involved in the dimer interface and the lack of fragmentation observed is the result of

protective protein-protein interactions. This hypothesis is supported by single molecule

AFM force spectroscopy data, which demonstrates that the central NAC domain of α-

Synuclein is not solely the location of the dimer interface and that the C-terminal region is

involved [53]. However, a similar lack of fragmentation is also observed from the C-

terminus of the α-Synuclein monomer (Figure 3.11). This suggests that whilst the C-

terminus may be involved in the interface, the lack of fragmentation may also be due to the

dimer being composed of two monomers with fragmentation resistant C-termini.

These findings for both the monomer and dimer species do not correlate with previously

published CD and FTIR data [22] which did not detect regions of secondary structure or

hydrophobic protein core regions and with in-cell NMR experiments which concluded that

α-Synuclein is largely monomeric and disordered [54]. Additionally, our data does not

correlate with previously published HDX-MS studies. Del mar et al., Lee et al. and Mysling et

al. establish an unprotected and therefore disordered C-terminal region in monomeric α-

Synuclein [14, 55, 56]. Interestingly, despite transient C-terminal protection in assembled

amyloid structures highlighted by Del Mar et al. [55]. Del Mar et al. and Mysling et al. both

conclude that the C-terminal region of the assembled amyloid is unprotected, this lack of

structure should be conducive to ECD fragmentation [55, 56]. This degree of uncertainty of

C-terminal protection again highlights the conformational heterogeneity of α-Synuclein, as

previously highlighted by MS, IM-MS and Cross-linking IM-MS.

127

3.4. Summary

The aim of the experiments in this chapter was to apply MS based methods to probe the

structure of α-Synuclein. MS demonstrates that both the solution pH and ionisation polarity

have an effect on the species observed. α-Synuclein presents a wide CSD at both pHs;

however, following the lowering of the solution pH, the CSD is shifted to lower charge

states, indicating that the protein has adopted a more compact conformation, this concurs

with other biophysical techniques. MS also demonstrates that ionisation polarity has an

effect on the species observed, with the CSD shifting to lower charge states at both solution

pHs tested. The wide CCS range covered by the CSD and the multiple conformations

observed for all species, highlights α-Synucleins disordered nature. The CCS values are in

good agreement with published work including values recorded in negative ionisation mode

and the differences observed can be explained by the change in location of chargeable

residues between ionisation modes. MS and IM-MS both provide compelling evidence

supporting the conformational diversity of α-Synuclein and highlight large scale day to day

variation. This day to day variation is present following the modification of solution

conditions and ionisation polarity and concurs with the control results of previously

published data. The aim of the cross-linking IM-MS experiments was to probe the solution

phase structures of α-Synuclein in the gas phase. The three conformational families

observed following cross-linking IM-MS closely match previously published CCS values,

providing a link between the solution and gas phase structures observed. However,

additional work is required to probe the effect of the cross-linking reagent on the

conformations observed. ECD-FT-ICR MS was applied to probe the effect of pH on the

structure of α-Synuclein. The increase in fragmentation observed following the reduction of

solution pH, can be explained by conformational changes previously observed by other

biophysical techniques. The lack of fragmentation observed in the C-terminus in

combination with data published from other biophysical techniques, suggests the

involvement of the C-terminus in the dimer interface. However, this can also be explained

by the dimer being composed of two monomers with fragmentation resistant C-termini.

The fact that our ECD-FT-ICR MS results are at odds with other published MS based work,

including HDX-MS data, also concurs with the large scale variation previously highlighted.

These results demonstrate that MS based methods are ideally situated to characterise

conformationally dynamic proteins such as α-Synuclein. However, care must be taken in the

application of these techniques to disordered species to ensure there is no omission of

transient species.

128

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52. Yamaguchi, Y., et al., Characterization of Inhibitor-Bound alpha-Synuclein Dimer: Role of alpha-Synuclein N-Terminal Region in Dimerization and Inhibitor Binding. Journal of Molecular Biology, 2010. 395(3): p. 445-456.

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53. Krasnoslobodtsev, A.V., et al., alpha-Synuclein Misfolding Assessed with Single Molecule AFM Force Spectroscopy: Effect of Pathogenic Mutations. Biochemistry, 2013. 52(42): p. 7377-7386.

54. Binolfi, A., F.X. Theillet, and P. Selenko, Bacterial in-cell NMR of human alpha-synuclein: a disordered monomer by nature? Biochemical Society Transactions, 2012. 40: p. 950-U292.

55. Del Mar, C., et al., Structure and properties of alpha-synuclein and other amyloids determined at the amino acid level. Proceedings of the National Academy of Sciences of the United States of America, 2005. 102(43): p. 15477-15482.

56. Mysling, S., et al., Characterizing the Dynamics of a-Synuclein Oligomers Using Hydrogen/Deuterium Exchange Monitored by Mass Spectrometry. Biochemistry, 2013. 52(51): p. 9097-9103.

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4 Following the Early Stages of

α-Synuclein Aggregation

The aggregation of α-Synuclein is key to its implication in the aetiology of Parkinson’s

disease. The aggregation process is complex and the species present diverse. It is important

to characterise the species present during the early stages of aggregation, rather than large

fibrillar aggregates, as they are likely to be the ‘druggable’ species

Here, Mass Spectrometry based methods have been applied to monitor the species present

during the early stages of aggregation. IM-MS and HDX-MS have been applied to probe the

conformation of these structures and the aggregation of α-Synuclein under Mass

Spectrometry compatible conditions has been demonstrated by TEM.

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4.1. Introduction

The aggregation of α-Synuclein has previously been studied by a variety of techniques

including Fluorescence based assays such as the ThT assay [1], Dynamic Light Scattering

(DLS) [2], Small Angle X-ray Scattering (SAXS) [3], TEM [4], and Atomic Force Microscopy

(AFM) [5] amongst others, these references highlight excellent examples of each

techniques use. Common pitfalls of these methods include their low throughput nature, the

inherent biased nature of the test such as the reliance on the presence of β-sheet structure

of the ThT assay and low sensitivity, requiring high sample concentrations [6]. Mass

Spectrometry (MS) based methods offer a high throughput, low consumption, unbiased

method to characterise the species present during the early stages of aggregation. MS

based methods have been applied to investigate the aggregation of other amyloidogenic

proteins. A large body of work has been conducted by MS and Ion Mobility-Mass

Spectrometry (IM-MS) on the aggregation of β2-microglobulin, which is linked to dialysis-

related amyloidosis [7-23]. Amyloid-β [24-27] and Tau [28], two amyloidogenic proteins

implicated in Alzheimer’s disease have been previously investigated by MS and IM-MS.

Amylin [29-31] and the amyloid disease related, Transthyretin (TTR) [32] have also been

investigated.

The aggregation of α-Synuclein has been previously studied by MS based methods. Metal

ion binding has been demonstrated to have a large influence on aggregation. Copper has

been shown to influence α-Synuclein aggregation and MS has played a crucial role in

determining the interactions and effects, including the adoption of an aggregation

competent conformer [33-36]. Primarily, MS based methods have been applied to study the

effect of small molecules on α-Synuclein structure and aggregation. MS and IM-MS has

been used to investigate the effect of flavonoids including Baicalein [37, 38] and EGCG [39]

and the phenolic acid, gallic acid on α-Synuclein [40]. MS and IM-MS have also been applied

to investigate the effect of dopamine [41] and spermine [42] on α-Synuclein aggregation.

IM-MS has been previously utilised to investigate the effect of α-Synuclein fragments on

the aggregation of α-Synuclein [43, 44], whilst Illes-Toth et al. investigated the species

present [45] and Bernstein et al. investigated the impact of solution conditions [46]. A gas

phase solution for investigating solution phase conformers, Hydrogen Deuterium Exchange

Mass Spectrometry (HDX-MS) has been applied to probe the oligomeric species of the α-

Synuclein aggregation cascade [47-50].

134

The aim of the experiments in this chapter is to investigate the species present during the

early stages of α-Synuclein aggregation and to use gas phase and solution phase MS based

methods to probe the structure of these species, with a view to developing a method to

test drug candidates to aid the drug discovery process. The aggregation process is followed

on two time scales, a 96 hour time course and the aggregation in tip during a nESI-MS

experiment. The formation of fibrils under MS compatible conditions is demonstrated by

TEM. IM-MS is applied to probe the gas phase structure of species observed during

aggregation and the solution phase structures present during the early stages of

aggregation are investigated by HDX-MS.

The aggregation MS and IM-MS work has been published in part in Phillips et al. [51] and

the HDX-MS data has been published in part in Beveridge et al. [52].

135

4.2. Experimental

4.2.1. Sample Preparation

α-Synuclein samples remained frozen until time of analysis or incubation. The time from

thawing to introduction to the instrument was minimised. For the in tip aggregation

experiments, a freeze dryer (Heto LyoLab 3000) was used to alter sample concentration to

70 µM.

4.2.2. Aggregation Method

Samples were aggregated as described in Chapter 2 Section 2.3 for up to 120 hours. For in

tip aggregation, the sample was thawed, loaded into the nESI tip and presented to the

instrument. Aggregation was allowed to proceed without supplementary heating or

agitation. Samples for TEM were snap frozen at each aggregation time point and stored at -

80°C, prior to TEM grid preparation as described in Chapter 2 Section 2.13.


High resolution MS was conducted on QToF Ultima and QToF Ultima Global instruments

(Waters, Manchester, UK) with MS Vision high mass upgrade, operated in positive

ionisation mode. The source conditions were tuned to prevent the disruption of higher

order oligomers, tempered by the requirement for sufficient ion intensity. Instrument

parameters are listed in Chapter 2 Table 2.1.


IM-MS measurements were conducted on an in-house modified QToF instrument, the

MoQToF detailed in [53], operated in positive ionisation mode. Instrument parameters are

listed in Chapter 2 Table 2.2 and 2.3. The voltage applied across the cell was varied during

the experiment, between 60 V and 10 V. ATDs were recorded for at least 6 drift voltages

and processed as described in Chapter 2 Section 2.6.1.1. Time points were analysed in

triplicate.

4.2.5. Hydrogen Deuterium Exchange Mass Spectrometry

HDX analysis was conducted as described in Chapter 2 Section 2.11. Aggregation time

points were analysed in the same DynamX workflow and independently.

136


4.3.1. Following Aggregation via Mass Spectrometry

Figure 4.1 is the mass spectra of the 0 hour, 72 hour and 96 hour time points of a 96 hour in

vitro α-Synuclein aggregation time course. The 0 hour spectrum displays the same

characteristics described in Chapter 3 (Figure 3.1), wide CSDs and low order oligomeric

species ranging from dimers to tetramers are observed (Figure 4.1A). The monomer CSD

spans 5 ≤ z ≤ 27 and the spectra features a multimodal distribution with modes centred on

[aSyn+17H]17+ and [(aSyn)2+20H]20+. At later time points, the monomer CSD narrows (72 and

96 hours, 5 ≤ z ≤ 19) and the multimodal distribution shifts to favour lower charged states,

centred on [aSyn+14H]14+ for the monomer CSD at 72 hours and 96 hours (Figure 4.1B and

C). This suggests as the time course progresses extended α-Synuclein monomers in solution

are depleted, as these species would present as the highly charged species observed at the

0 hour time point due to their higher solvent accessibility. The depletion of these species

and their extended conformation suggests they are more amenable to aggregation.

Alternatively, the extended conformation may be in equilibrium with a fast aggregating

compact form. The loss of highly charged monomer intensity with time course progression

can be explained by the collapse of these extended species to form a compact species,

which rapidly aggregates to form higher order oligomers beyond the scope of the

experiment. This mechanism concurs with previously published data which demonstrates a

link between the assumption of a compact conformation and aggregation progression [42,

46, 54, 55].

Small changes are observed in the contribution of higher order oligomeric species to the

mass spectrum as the time course progresses. From 0 hours to 72 hours, there is a small

increase in the trimers observed, as the CSD increases from 0 hours: 19 ≤ z ≤ 26 to 72 hours:

16 ≤ z ≤ 29 (Figure 4.1A and B). Tetramers are the largest species observed during the time

course and are only observed in the 0 hour spectrum (Figure 4.1A). Larger oligomeric

species are expected and this suggests these low order oligomeric species which persist at

the later time points are potentially slow aggregating off pathway species. Their continued

presence and the presence of monomers following 96 hours under conditions shown to

form fibrils, suggests these species are in addition to a solution component which may be in

equilibrium with higher order species outside the scope of the technique.

It becomes increasingly difficult to achieve a stable nESI spray from the later time point

samples, indicating the presence of aggregates and as the time course progresses; the TIC

137

decreases (Appendix Figure A3.1). This is indicative of aggregation, as lower order species

are sequestered from solution to form higher order aggregates not observable by MS.

Although, this may also be attributed to off pathway effects depleting the ion current, here

it correlates with fibrillation as seen by TEM (Figure 4.2).

Figure 4.1 – α-Synuclein MS aggregation time course with an instrument cone voltage of 60 V. A. 0 hours, B. 72 hours and C. 96 hours. (insets) 100x zoom to highlight low intensity species. CSD

extremes and species of interest are labelled oligomeric order/ charge. Marker colour indicates oligomeric order. Monomeric: red, dimeric: blue, trimeric: yellow and tetrameric: purple. See

Appendix Table A3.1 for a list of all species observed.

The changes to the mass spectra indicate that it is possible to follow the aggregation of α-

Synuclein using MS. We are only able to observe a narrow window of the aggregation

process and changes to the solution phase components. As MS is not biased to a certain

species or structure such as the β-sheet rich structures of the ThT assay [56], except for the

requirement for the species to be ionisable, the effect of the incubation of a drug candidate

1000 2000 3000 4000

1000 2000 3000 4000

1000 2000 3000 4000

m/z

2200 2400 2600 2800 3000

2200 2400 2600 2800 3000

2200 2400 2600 2800 3000

1660 1665 1670 1675 1680

1485 1490 1495 1500 1505

1540 1545 1550 1555 1560

19

+

3/2

8+

2/2

3+

5+

19

+

27

+

3/1

9+

2/1

1+

2/11+

5+

2/2

3+ 3/1

6+

3/1

9+3

/26

+

2/11+

4/2

5+

3/29+

2/2

7+

5+

17

+1

6+

16

+

12

+1

2+

10

+1

0+

14

+1

4+

12

+

10

+

14

+

A

B

C 6+

6+

6+

2/1

3+

2/1

3+

2/1

3+

138

designed to prevent aggregation or to disaggregate could be investigated based on the

change in species observed.

4.3.2. TEM of Aggregates Prepared under Mass Spectrometry Compatible

Conditions

The solution conditions used for in vitro aggregation studies of α-Synuclein vary widely.

Phosphate-buffered saline [57], 100 mM sodium acetate [58] or the inclusion of 150 mM

sodium chloride in solution [4], have all been used for the characterisation of oligomeric

species and fibrils. These solution conditions are not compatible with MS for instance, the

ion suppression caused by the inclusion of 150 mM sodium chloride would distort the mass

spectrum and prevent the observation of any α-Synuclein species [4].

Figure 4.2 - TEM images of oligomers and fibrils formed in MS compatible buffer. A. 0 hours B. 24 hours C. 48 hours D. 72 hours E. 96 hours F. 120 hours. Scale bars represent 10 nm. Images A and F

are reproduced from [51].

Fibrils are not present in the sample prior to aggregation (Figure 4.2A). Following 24 hours

aggregation, short worm-like fibrils, 10 nm wide are observed (Figure 4.2B). Following 48

hours aggregation, elongated 10 nm wide fibrils are observed (Figure 4.2C). At 72 hours, no

fibrils are observed; however, small non-fibrillar species are observed following 24 and 72

139

hours of aggregation. Short 10 nm wide fibrils are observed following 96 hours aggregation,

whilst more abundant long 10 nm wide fibrils are observed following 120 hours (Figure

4.2F). These fibrils match the typical morphology exhibited by the α-Synuclein fibrils

characterised by TEM by Spillantini et al. [59], El-Agnaf et al. [57], Conway et al. [60], and

Hashimoto et al. [58]. The characterisation of these fibrils also concurs with those

characterised by Fink using AFM [5]. These images demonstrate it is possible to form fibrils

under MS compatible conditions and validates the time points chosen for the MS

aggregation time courses.

4.3.3. In Tip Aggregation

α-Synuclein aggregation kinetics can follow a typical sigmoidal growth curve, characterised

by a short lag phase [61]. The lag phase is populated by lower order oligomeric species,

present prior to their sequestration into higher order species. Small aggregates were

observed by TEM following 24 hours under MS compatible aggregation conducive

conditions (Figure 4.2B) and it is possible to observe the presence of aggregates in the end

of the nESI tip following a long MS experiment (Appendix Figure A3.2). Figure 4.3A to H are

the spectra collected during an extended nESI in tip aggregation experiment.

Figure 4.3A is the spectrum of the first five minutes of acquisition and as observed

previously (Chapter 3 and Figure 4.1), wide CSDs and low order oligomeric species ranging

from dimers to tetramers are observed. The samples used in the in tip experiments are not

incubated or agitated; however, there are indicators that aggregation is occurring and

aggregates are observed in the end of tip used to spray the sample of Figure 4.3 (Appendix

Figure A3.2). As the time course progresses, fewer higher order oligomeric species are

observed. Tetramers are no longer observed after 35 minutes (Figure 4.3D), trimers are no

longer observed following 45 minutes (Figure 4.3E) and only monomers are observed

following 55 minutes (Figure 4.3F). The narrowing of the CSDs is indicative of aggregation as

species are depleted from solution by sequestration into higher order aggregates not visible

by MS. The raised baseline observed at later time points is also indicative of aggregation

and the presence of unresolved higher order oligomers. The TIC falls with time course

progression, as observed during the 96 hour time course, as lower order species are

sequestered from solution (Appendix Figure A3.3). As observed during the long term

aggregation time course, higher charged monomeric species are depleted with time course

progression (see Figure 4.3D to F). In addition, lower charged monomeric species are also

depleted (see Figure 4.3B vs. E vs. H). The depletion of the lower charged species in

140

combination with the loss of higher charged monomeric species suggests that the extended

species may be equilibrium with a fast aggregating compact form. As observed in the long

term aggregation time course (Figure 4.1), the loss of the extended, higher charged

monomeric species can be explained by their collapse to form compact species, which

rapidly aggregate to form species beyond the scope of the technique. This concurs with

previously published data which demonstrates the importance of the compact species in

the aggregation process [42, 46, 54, 55].

In a replicate of this experiment, the changes to the CSDs and the species observed is not

reproduced (Appendix Figure A3.4). The CSDs remain similar throughout the time course

and the TIC fluctuates with time course progression but a significant decrease is not

observed (Appendix Figure A3.3 vs A3.4). α-Synuclein aggregation is highly dependent on

the environmental conditions including protein concentration, temperature, agitation, the

presence of contaminants and the initial state of the protein, alteration of these factors

may explain the variation observed [58]. The decrease in the TIC with time course

progression and loss of higher order oligomers during the first in tip aggregation time

course is greater than that observed during the long term aggregation time course (Figure

4.1 and Appendix Figure A3.1). This suggests that during this experiment, which features

time points earlier in the aggregation process, that aggregation is occurring quickly. The

spectra of the long term aggregation time course are of time points later in the aggregation

cascade (Figure 4.1 and Appendix Figures A3.1) and may represent an established solution

populated by slower aggregating species and those in equilibrium with higher order

aggregates not observable by MS. The spectra of the second in tip aggregation experiment

(Appendix Figure A3.4) are similar to the spectra recorded at the later time points of the

long term aggregation experiment. This suggests that the aggregation process is occurring

very quickly and the part of the process we can observe and sample includes the formation

of a sub-population of solution constituents including slower aggregating species and those

in equilibrium with higher order aggregates.

141

Figure 4.3 – α-Synuclein in tip aggregation time course spectra. The arrows highlight CSD width. See Appendix Table A3.1 for a list of all species observed. The narrowing of the CSDs, the loss of higher order oligomeric species and a raised baseline can be observed as aggregation proceeds.

142

4.3.4. Probing the Conformational Changes during Aggregation by Ion

Mobility - Mass Spectrometry

IM-MS is applied to probe conformational changes exhibited by α-Synuclein monomer and

dimer species during the aggregation process. Figure 4.4 and 4.5 show the mass spectra

and corresponding Collision Cross Section Distributions (CCSDs) generated following the in

vitro aggregation of α-Synuclein using the MoQToF. In this work, we focus on three

monomeric and two dimeric charge states.

Figure 4.4 - Mass spectra recorded during the α-Synuclein IM-MS aggregation time course. See Appendix Table A3.1 for a list of all species observed. Image reproduced from [51].

[aSyn+6H]6+ displays a narrow CCSD is centred on 1400 Å2, similar to that reported in the

cross-linking IM-MS experiments (Chapter 3, Figure 3.9) for the entire time course. At Day 0

(Figure 4.5Ai), there is a small shoulder which is attributed to the mass-coincident

[(aSyn)2+12H]12+ species. The large error bars indicate that these species are transient and

the absence in the Day 3 and Day 5 CCSDs highlight α-Synucleins conformationally dynamic

143

nature. The [aSyn+10H]10+ CCSD (Figure 4.5B) presents a much wider distribution than

[aSyn+6H]6+, attributed in part to the greater levels of coulombic repulsion suffered by a

higher charged species. The presence of an unfolded conformational family highlighted by

cross-linking IM-MS data in Chapter 3 Figure 3.9, also accounts for the broad CCSD. The

CCSD is centred on 1800 Å2, with a small shoulder at all time points, centred on ~2300 Å2. In

comparison with Bernstein et al. despite the use of different ionisation polarities, the CCSs

derived are in good general agreement. There is a discrepancy in the CCS values derived

from the [aSyn+10H]10+ species. The major species defined by Bernstein et al. is ~2500 Å2

(Figure 4, [46]), whereas the major peak in the CCSD in Figure 4.5B is centred on ~1800 Å2,

the persistent shoulder being centred on ~2300 Å2. This may be explained by our

instrument having a ‘cooler’ source, resulting in less protein unfolding during the ionisation

and desolvation process or by a difference resulting from different charge location, due to

the switch of ionisation polarity. The CCSD of [aSyn+13H]13+ is similarly broad and centred

on ~3000 Å2 for the entire time course. A shoulder is also present and attributed to a

compact conformer, the large errors bars highlight this species is transient and it is absent

from the later time point CCSDs (Figure 4.5Cii and Ciii).

The day 0 [(aSyn)2+13H]13+ dimer CCSD (Figure 4.5Di), presents a broad distribution, centred

on ~3000 Å2 with a small shoulder centred on ~3600 Å2. This shoulder becomes more

intense in the day 3 CCSD and is present in the day 5 CCSD; however, is obscured by

broadening of the ~3000 Å2 peak (Figure 4.5Diii). The CCSD of [(aSyn)2+17H]17+, the highest

charged dimer examined, is again broad and centred on ~3900 Å2 with a shoulder centred

on ~3200 Å2. The large errors bars of the CCSDs indicate the presence of several lowly

populated conformational dynamic species and again highlight the variation exhibited by α-

Synuclein.

As expected the CCS exhibited increases with charge state. The large spread in CCS across

the CSD (ΔCCS ~1600 Å2) and the large spread in CCS seen for each charge state indicates

that the protein is flexible in solution and able to adopt multiple conformations in the

solution and gas phase. The large error bars present on some CCSDs highlight the

conformational variation exhibited by α-Synuclein. This is even more evident in the CCSDs

of the dimer species investigated (Figure 4.5D and E). This large variation in the dimer CCS

concurs with the work of Illes-Toth et al. [45] and Ray et al. [62].

144

Figure 4.5 – α-Synuclein CCSDs recorded during a 120 hour IM-MS aggregation time course. Monomer species, A: [aSyn+6H]6+ B: [aSyn+10H]10+ C: [aSyn+13H]13+ and Dimer species, D:

[(aSyn)2+13H]13+ and E: [(aSyn)2+17H]17+. Data was recorded with 35 V across the drift cell. Image reproduced from [51].

There is a notable lack of change in the CCS across the aggregation time course (Figure 4.5),

this is despite the observation of fibrils by TEM under MS compatible conditions (Figure

4.2). The [aSyn+6H]6+ CCSD remains centred on ~1400 Å2 from day 0 until day 5. This is also

true for the higher charged species including [aSyn+13H]13+, which remains centred on

~3000 Å2. There is no evidence of CCSD alteration including CCSD narrowing, which would

suggest the adoption of an aggregation specific conformation. This is also true for the

dimer species (See Figure 4.5D and E). This lack of conformational modification even

following long term aggregation, suggests the solution constituents remain

conformationally dynamic and potentially in an equilibrium with higher order species, prior

145

to their sequestration into higher order oligomeric species or are off pathway species

which aggregate on different time scales.

The monomer and dimer CSD width does not change with aggregation time; however, the

relative monomer intensity fluctuates with time course progression (Figure 4.4), this

concurs with the lack of change in structure observed. The oligomers or fibrils observed by

TEM (Figure 4.2) could disassemble during desolvation. However, as the samples become

progressively harder to spray with time course progression, indicating the presence of

aggregates, this is not considered the source of the low order oligomers.

In comparison, the [aSyn+6H]6+ monomer and [(aSyn)2+13H]13+ dimer CCSDs do not show a

significant decrease in the CCSD with dimer formation. These species were chosen on the

basis of their similar charging and mass, limiting any CCS difference resulting from different

levels of coulombic repulsion. The lack of a CCS decrease suggests that the dimer remains

largely unstructured with a small interface. This concurs with the force spectroscopy

studies of Neupane et al. who report the lack of discrete cooperative unfolding events for

most dimers indicating a lack of structure [63]. In ~15% cases, they report multiple

unfolding transitions which are indicative of structure and concurs with the day to day

variation previously highlighted by MS and IM-MS [63].

4.3.5. Probing Conformational Changes during Aggregation by HDX-MS.

We have used IM-MS to investigate the conformation of α-Synuclein species observed

during an MS compatible aggregation time course in the gas phase. Here, the conformation

exhibited by α-Synuclein during aggregation is investigated using HDX-MS. The process of

deciphering conformational information from HDX-MS data does not rely on the gas phase

interrogation of structure but the solution phase, non-destructive labelling of protein

structure, prior to analysis of these structures in the gas phase. α-Synuclein monomer and

oligomer structure has been previously interrogated by HDX-MS [47-50] and all groups

unanimously describe the monomer as disordered. The description of the oligomeric

species is an area of debate with regions of protection observed [47-50].

Data can be analysed in two fashions within the DynamX program, as different states

within a file and independently. As the number of states within a file increases, the number

of fragments identified can decrease, as the filtering criteria applied can omit relevant

peptides. This has an averaging type effect on the data and reduces site specific

information, see Appendix Figure A3.5 and A3.6. This effect may be less noticeable in a

146

much larger protein. It is also important to consider that in a changeable sample such as

aggregating α-Synuclein, the regions which are susceptible to pepsin digestion or

deuterium labelling are likely to change, all time points are therefore analysed separately.

Previous investigations have focused on the aggregation of α-Synuclein followed by the

separation of the monomeric solution component from oligomeric species. In order to

compare this study with previous work, α-Synuclein was aggregated in vitro (see Section

2.3) and the supernatant of the aggregated sample was analysed without any further

processing at the 0 hour, 24 hour and 120 hour time points. The Relative Fractional

deuterium Uptake (RFU) of the α-Synuclein peptides at all time points, are broadly similar

(Figure 4.6). All three, in general, demonstrate a transition to complete deuteration within

the first labelling time point of 15 seconds, indicating an absence of protective structure.

The lack of specific regions of RFU correlation throughout the time course (Figure 4.6)

suggest the presence of transient structural elements, as observed during the IM-MS time

course (Figure 4.5). This may also be the result of an averaging effect due to the lack of a

pre-processing step following aggregation.

Figure 4.6 - α-Synuclein peptides RFU plots at the 0 hour, 24 hour and 120 hour time points of the HDX-MS aggregation time course. All time points analysed separately in DynamX.

147

The C- terminal region of α-Synuclein exhibits some protection at the 0 hour and 120 hour

time points, highlighted by the increase in RFU as a function of labelling time (Figure 4.6,

top and bottom). This concurs with previously identified protective C- terminal interactions

with other regions of the protein via ECD-FT-ICR MS (Chapter 3). The C- terminal region also

displays a much greater variation in RFU, this is contrast to the data of Mysling et al. who

report a uniform RFU of 1.0, which suggests the absence of structure [48] and supports the

earlier findings of Del Mar et al. [47]. The central protected region reported by Del Mar et

al. and Mysling et al. is also not observed [47, 48]. Mysling et al. report a protected region

in the N-terminus (residues 4-17), following 120 hours under aggregation conducive

conditions, a partially overlapping-protected region (residues 9-21) is observed.

The oscillating RFU highlights the presence of transient structure elements, indicating that

the solution component of α-Synuclein aggregated in vitro remains conformationally

diverse and an aggregation competent structure is not adopted, as reported by IM-MS. The

untargeted approach used, may explain the poor correlation between our findings and

those reported by Mysling et al. and Del Mar et al. [47, 48].Our findings demonstrate that

the solution component is populated by a range of species and demonstrates significant

variation as previously observed.

148

4.4. Summary

One of the aims of the experiments in this chapter was to investigate the species present

during the early stages of α-Synuclein aggregation using MS based methods. It is possible to

observe a wide range of species during the short term and long term in vitro aggregation

time course experiments and it is possible to relate the changes in species observed to

possible aggregation mechanisms. The loss of highly charged monomeric species with

aggregation progression during the long term aggregation time course, highlighted in Figure

4.1, suggests these species are amenable to aggregation. The loss of the highly charged,

extended monomeric species may also be the result of this species being in equilibrium

with a compact, fast aggregating species, which rapidly aggregates beyond the scope of the

technique. The loss of the extended species resulting from its collapse to form the compact.

This mechanism correlates with the loss of lower charged, compact species with time

course progression during the in tip aggregation time course experiments, highlighted in

Figure 4.3, during which the loss of higher charged, extended monomeric species is also

observed. This also concurs with previously published data, which highlights the importance

of the compact conformer to aggregation progression. The observation of fibrils via TEM

from samples aggregated under MS compatible conditions demonstrates that the species

observed are part of the aggregation process. In addition, the variation in the species

observed correlates with the variation discussed in Chapter 3 and complicates the process.

The aim of the IM-MS and HDX-MS experiments was to probe the structure of the species

observed in the gas and solution phase, respectively. As highlighted in Chapter 3, the large

spread in CCS across the CSD and in the CCSs for each charge state indicates that α-

Synuclein is flexible in solution and able to adopt multiple conformations. The transient

species and the large error bars highlight α-Synucleins conformationally dynamic nature.

The lack of a CCS decrease when comparing a similarly charged monomer and dimer

suggests that the α-Synuclein dimer remains unstructured, this concurs with previous force

spectroscopy studies [63]. The lack of distinct regions of protection observed by HDX-MS

demonstrates that the solution component of the α-Synuclein sample remains

conformationally diverse. The poor correlation between these results and previously

published data may be explained by the different sample preparation techniques.

Importantly, IM-MS and HDX-MS are unable to identify a single aggregation prone

conformer following the in vitro aggregation of α-Synuclein.

149

Based on these experiments, there is further scope for the application of MS and IM-MS to

follow the aggregation of α-Synuclein and other amyloidogenic proteins including

investigating the effect of small molecules on the species observed and their conformation,

with a view to aiding drug discovery.

150

4.5. References

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5 Structure and Interactions of

Aβ(1-42) and Aβ(1-40)

The Amyloid-β peptides derived from the Amyloid Precursor Protein are linked to the

progression of Alzheimer’s disease. Mass spectrometry is used here to examine two

variants, Aβ(1-42) and Aβ(1-40). Although they differ in length by only two amino acids,

they differ dramatically in terms of other characteristics including aggregation propensity.

Here, mass spectrometry probes both the structure and aggregation of Aβ(1-42) and Aβ(1-

40) as well as interactions with proposed inhibitors.

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5.1. Introduction

The Amyloid-β (Aβ) peptides are derived through the proteolytic cleavage of the Amyloid

Precursor Protein (APP) and differ in terms of length and characteristics including structure

and aggregation propensity, see Chapter 1 Section 1.5 and Figures 1.7 to 1.11 [1]. Their

implication in the development of Alzheimer’s disease has led to their widespread study

including the use of MS based methods [1]. Aβ(1-42) and Aβ(1-40) are the two most

commonly studied peptides. MS and IM-MS have been used to study the aggregation of

Aβ(1-40) inferring conformational modifications based on charge state analysis [2]. Young

et al. used Travelling Wave Ion Mobility Mass Spectrometry (TWIMS) to study the co-

assembly of Aβ(1-40) and hIAPP, comparing homo- and heterodimers and their properties

[3]. Immuno-precipitation MS has highlighted the preferential incorporation of Aβ(1-42)

into fibrils from the co-incubation of Aβ(1-40) and Aβ(1-42) monomers [4]. The Bowers

group is a major contributor to the study of the Aβ peptides, frequently employing both

molecular modelling and IM-MS to investigate monomeric [5-7] and oligomeric structure

[8]. They have used this data to propose an assembly mechanism from monomer through

oligomeric species to fibrils [9-11]. Bernstein et al. hypothesised that following the

formation of an open tetramer, hexamer paranucleus and paranuclear dimer, the Aβ(1-42)

aggregation pathway diverges to form oligomers, β-sheet rich oligomers, protofibrils and

fibrils [10]. In contrast, the Aβ(1-40) aggregation pathway is less complex and features a

slow transition from tetramer to fibril [10]. The Bowers group have investigated, the effect

of familial mutations [12-15], the effect of Aβ(1-40) on Aβ(1-42) aggregation [16] and the

effect of Aβ fragments on the structure or oligomerisation of Aβ peptides [17] and Tau,

another intrinsically disordered aggregating protein implicated in Alzheimer’s disease [18].

In addition, in combination with cell based toxicity assays, the neurotoxicity of different

Aβ(1-42) aggregates has been investigated [19]. Kloniecki et al. applied a combination of

TWIMS and molecular modelling to investigate the aggregation of Aβ(1-40) and the

resulting oligomeric species. They demonstrate the presence of two distinct species

representing on- and off- pathway oligomers and propose an alternative aggregation

pathway to that proposed by Bernstein et al. [10, 20]. This mechanism is supported by the

work of Sitkiewicz et al. [21] and Pujol-Pina et al. [22].

HDX-MS has also been applied to study the Aβ(1-42) aggregation pathway; however, a lot

of work has focussed on the aggregation of Aβ(1-40). Low hydrogen deuterium exchange

levels indicate the presence of structure, which protects residues from exchange, a

decrease/ increase in HDX indicates a modification to local structure. A decrease in

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hydrogen exchange has been reported following the transition from monomer to fibril [23,

24]. The transition from proto-fibril to fibril was also accompanied by an increase in

protection from exchange, in the central region spanning residues Phe20 to Met35 [25-27].

Zhang et al. also demonstrate an increase in the protection of peptides spanning the

residues Phe20 to Leu34 for fibrils compared to low and high molecular weight oligomers

[28].

Zhang et al. compare the effect of incubation temperature, agitation and the presence of

copper on structural changes occurring during the aggregation of Aβ(1-40) and Aβ(1-42)

[29]. They report no significant change in the level of protection/ structure of Aβ(1-40)

compared to Aβ(1-42) [29]. Serra-Vidal et al. apply HDX-MS to track the shift in intensity

from unprotected monomers and oligomers to protected oligomers and fibrils during the

aggregation of Aβ(1-40) and Aβ(1-42) [30]. In experiments analogous to HDX-MS, Ramos et

al. apply reductive alkylation, using the reducing agent sodium cyanoborohydride and

formaldehyde to determine the solvent accessibility of primary amines in different

aggregated states of Aβ(1-40) [31]. They demonstrate an increase in protection between

monomers and fibrils and report that Leu16 in fibrils is most protected from solvent

exchange [31]. The increase in protection observed and its location concurs with HDX-MS

studies.

Due perhaps to its rapid aggregation, there have been few reports on the interaction of

Aβ(1-42) with anti-amyloid agents [32] but Aβ(1-40) has been widely used as a target for

small molecules of therapeutic potential including melatonin [33], oleuropein [34] and β-

sheet breaker peptides [35]. MS has also been applied to understand the mechanism of

aggregation inhibitors such as the C-terminal domain of proSP-C to aid drug design [36].

The work of Young et al. is of note in which they screen and classify small molecule

aggregation inhibitor binding using TWIMS [37].

The aim of the experiments in this chapter is to apply a combination of MS, IM-MS and gas

phase fragmentation techniques to examine the structure of primarily, Aβ(1-42) and Aβ(1-

40) to probe the effects of sample concentration, solution condition modification and

ionisation polarity. The aim of the TWIMS ligand binding experiments is to demonstrate the

ability to classify ligand induced conformational changes in Aβ(1-42) according to the mode

of action, to aid drug design.

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5.2. Experimental

5.2.1. Sample Preparation

For all experiments, Aβ(1-42)/Aβ(1-40) concentration was 20 µM, unless stated otherwise.

RI-OR2, Rutin and Bradykinin were reconstituted in H2O (pH 2) or 20 mM AmAc (pH 7.4) at a

concentration of 100 µM, aliquoted, snap frozen and stored at -20°C, until required. For MS

ratio experiments, additional concentration solutions were produced as required and

subject to the same storage procedure. RI-OR2 was a gift from Professor David Allsop,

University of Lancaster. Rutin was a gift from Professor Garth Cooper, University of

Manchester.


Samples for solution condition experiments were prepared in H2O (pH 2) or 20 mM AmAc

(pH 7.4) at a concentration of 20 µM or 50 µM from frozen aliquots. Experiments were

conducted using a Waters Synapt G2, G2S or G2Si instrument, operated in positive

ionisation or negative ionisation mode. Instrument parameters are listed in Chapter 2 Table

2.4 and 2.5.

MS ratio experiments were conducted on a Waters Synapt G2 operated in positive

ionisation mode, instrument parameters can be found in Chapter 2 Table 2.4. Protein:

ligand ratios of 1:0, 1:0.1, 1:0.5, 1:1 and 1:2 using a protein concentration of 20 µM were

prepared immediately prior to analysis.

5.2.3. Travelling Wave Ion Mobility Mass Spectrometry

To prepare samples at different buffer concentrations, 100 µM aliquots were diluted to 20

µM with AmAc, immediately prior to analysis. Experiments were conducted on a Waters

Synapt G2Si instrument operated in positive ionisation mode. Instrument parameters are

listed in Chapter 2 Table 2.4.

Samples for ligand binding experiments were prepared immediately prior to analysis to

minimise Aβ(1-42) aggregation and tip clogging. Equimolar concentrations were used in all

instances with the exception of Aβ(1-42) and Rutin in 20 mM AmAc (pH 7.4) in negative

ionisation mode, for which a ratio of 1:5 was required to observe the bound species. Source

conditions were modified to improve resolution of the bound complex and differed

between samples, see Appendix Table A4.5. In each case, the same source conditions were

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applied to Aβ(1-42) in the presence and the absence of the ligand and to the selected CCS

calibrants. Experiments were conducted on a Waters Synapt G2, G2S or G2Si instrument

operated in either positive or negative ionisation mode. Instrument parameters are listed in

Chapter 2 Table 2.4 and 2.5.

CIU-TWIMS experiments were conducted on a Waters Synapt G2 instrument operated in

positive ionisation mode. Instrument parameters are listed in Chapter 2 Table 2.4. The

charge state of interest was isolated prior to CIU-TWIMS. The collision voltage was ramped

in the trap region from 4/5 V to 60 V.

For all TWIMS experiments in which CCS values are quoted, CCS calibration was conducted

as described in Chapter 2 Section 2.6.2.1 [38].

5.2.4. Electron Transfer Dissociation

Electron Transfer Dissociation (ETD) and Electron Transfer Collision Activation Dissociation

(ETcaD) experiments were conducted on a Waters Synapt G2Si instrument, fitted with a

glow discharge source and nESI source unit. Instrument parameters can be found in

Chapter 2 Table 2.4 and 2.6. Supplementary activation was applied in the transfer region of

the Triwave device. A collision voltage of 25 V was applied.


All SID experiments were conducted on a modified Waters Synapt G2 instrument [39]

operated in positive ionisation mode. Instrument parameters can be found in Chapter 2

Table 2.4 and 2.7. Trap gas flow was increased to 3 mL/min to improve SID fragmentation.

SID fragmentation was conducted at a range of SID voltages.

5.2.6. Data Analysis

For CID, ETD/ETcaD and SID fragmentation analysis, the output from the Protein Prospector

MS product tool was compared with measured peak lists [40]. Fragmentation maps were

created in Powerpoint (Microsoft Corporation, USA). All data analysis (MS and TWIMS) in

this chapter was conducted using Masslynx v4.1 (Waters, USA), Origin v9 and OriginPro

2015 (OriginLab, USA), Excel and Powerpoint (Microsoft Corporation, USA). CIU fingerprint

plots were created using CIUSuite [41].

159


5.3.1. The Effect of Concentration, Solution Conditions and Ionisation

Polarity

Figure 5.1A to D are mass spectra of Aβ(1-42) in H2O (pH 2). By increasing the sample

concentration from 20 µM to 50 µM (Figure 5.1A vs. C, B vs. D), it is possible to observe

additional species in both positive and negative ionisation mode. [Aβ42±4H]4± is the most

intense species regardless of sample concentration and these newly observed species are

low intensity and at the extremes of the CSD and therefore are the result of the

concentration increase.

The Bowers group commonly work in negative ionisation mode, as the net charge on Aβ(1-

42) at neutral pH is -3 [6]. Here, on switching the polarity of the instrument, we observe a

spectrum which is highly similar to that of positive ionisation mode (Figure 5.1 A & C vs B &

D). In contrast to the work of the Bowers group, neither the commonly observed [(Aβ42)2-

5H]5- species [5, 6, 9, 10, 13, 14, 16, 17, 19], nor dimeric/ higher order oligomeric species

are observed. The insets of Figure 5.1E and F are examples of the lack of m/z-coincident

dimer species observed for all conditions. The lack of higher order aggregates can be

explained by the harsher source conditions in the Synapt instruments compared to the

Bowers Group instrument or by further aggregation of these samples. In positive ionisation

mode, it is possible to observe the [(Aβ42)2+5H]5+ dimer (m/z 1806), this is the result of a

higher sample concentration (Figure 5.1C). Alteration of source conditions such as the cone

voltage may alter the intensity of species observed but does not affect the CSD width, see

Appendix Figure A4.1.

Solution conditions have an effect on protein charge states and conformations in the gas

phase, Figure 5.1E to F are representative spectra for Aβ(1-42) in 20 mM AmAc (pH 7.4)

[42]. The CSD intensity is shifted to lower charge states and no dimeric species are

observed. In Figure 5.1F, the intensity distribution is shifted towards [Aβ42-3H]3- in AmAc

(pH 7.4). This mimics the CSD observed by the Bowers group and published in multiple

instances [5, 6, 9, 13, 14, 16, 17, 19]; however, the commonly observed [Aβ42-2H]2- and

[(Aβ42)2-5H]5- are absent. In general, regardless of solution condition, the CSD is shifted to

lower charge states in negative ionisation mode.

The higher charged [Aβ42±5H]5± is observed, at both concentrations in both ionisation

modes in H2O (pH 2) with the exception of 20 µM Aβ(1-42) in negative mode (Figure 5.1B),

160

this absence can be explained by the lower protein concentration. Bernstein et al. report

observation of [Aβ42-5H]5- in 20 mM AmAc (pH 7.2) and attribute the greater intensity of

the higher charged species to excess charging during the ESI process [6]. [Aβ42±5H]5± is not

observed in Figure 5.1E or F. [Aβ42+5H]5+ is observed in 20 mM AmAc (pH 7.4) with a slight

modification to the source conditions at a very low intensity, see Appendix Figure A4.2. The

higher intensity of [Aβ42±5H]5± in H2O (pH 2) is likely due to the unfolding of the peptide

due to the low solution pH.

The absence of the higher order aggregates observed by the Bowers group may be the

result of the sample preparation protocol applied. The Bowers group does not include a

pre-treatment step such as HFIP treatment to deseed the sample, which may account for

the presence of higher order aggregates [43-46].

Figure 5.1 – A to D - Aβ(1-42) mass spectra in H2O (pH 2), collected in positive ionisation mode at a concentration of 20 µM (A) and 50 µM (C) and in negative ionisation mode at 20 µM (B) and 50 µM (D). (C inset) Zoom to highlight [(Aβ42)2+5H]5+ (D inset) Zoom to highlight [Aβ42-5H]5- and [Aβ42-

2H]2-

. E to F - Aβ(1-42) mass spectra in 20 mM AmAc (pH 7.4) collected in positive (E) and negative (F)

ionisation mode. (E and F insets) Zoom to highlight the isotopic distribution and absence of m/z coincident dimer species, observed under all conditions (data not shown). Species are labelled using the Bowers group format of oligomeric order/ charge. 0.3% AmOH was added to the sample in (F) to

aid desolvation and does not effect the CSD.

5.3.2. The Effect of Salt Concentration on Structure

AmAc concentration was increased to assess any effects on the aggregation and structure

of Aβ(1-42) in both positive and negative ionisation modes. There were no significant

161

changes to the CSD and no observable aggregates are present in positive or negative

ionisation mode as a function of salt concentration (data not shown). ATDs of [Aβ42+4H]4+

and [Aβ42+3H]3+ in AmAc (pH 7.4) are shown in Figure 5.2, accompanied by the calculated

CCS values. A single conformer (Calculated CCS: 630 Å2) is observed at all salt

concentrations for [Aβ42+4H]4+. In 20 mM AmAc, a single conformer is observed in most

cases; however, two conformers were observed for [Aβ42+4H]4+ when conducting CIU-

TWIMS experiments (see Appendix Figures A4.3 and A4.4), similar to that reported by

Bernstein et al. in negative ionisation mode [6]. This inter-day variation is a common

feature of intrinsically disordered aggregating species, see Chapters 3 and 4. In contrast,

two conformers are consistently observed for [Aβ42+3H]3+, see Figure 5.2 and Appendix

Figures A4.3 and A4.4. The intensity of the later arriving [Aβ42+3H]3+ species decreases in

intensity with increasing buffer concentration, see Figure 5.2D to F. Teplow et al. suggest

this early arriving conformer is a solvent-free species, whilst the later arriving conformer is

either a dehydrated or hydrated conformer [9]. As the salt concentration increases, the

solution vapour pressure decreases, aiding in the creation of solvent-free structures.

As observed in positive ionisation mode, [Aβ42-4H]4- presents as a single conformer and

[Aβ42-3H]3- as two conformers at all salt concentrations, see Figure 5.3. The two

overlapping conformers observed for [Aβ42-3H]3- mimics the ATD published by the Bowers

group [5, 6, 19]. The drift time of the two species does not alter with increasing salt

concentration; however, the intensity distribution of the two conformers differs. As the salt

concentration increases from 20 mM to 100 mM, the intensity distribution shifts in favour

of the later arriving species. Interestingly, as the concentration is increased further from

100 mM to 200 mM, the intensity distribution shifts in favour of early arriving compact

species with the observation of a new intermediate species, see Figure 5.3F.

Stabilisation of compact conformers as a function of increasing buffer concentration

therefore differs between ionisation modes. The presence of two conformers for

[Aβ42±3H]3± concurs with previous publications, whereas the observation of a single

conformer for [Aβ42±4H]4± does not, as Bernstein et al. report two conformers for [Aβ42-

4H]4- [6]. The differences observed between the ATDs in positive and negative ionisation

mode suggest the location of positively and negatively charged groups influence the gas

phase structure.

162

Figure 5.2 – [Aβ42+4H]4+ and [Aβ42+3H]3+ ATDs at 20 µM, pH 7.4 at increasing AmAc salt concentration, collected in positive ionisation mode. A & D. 20 mM, B & E. 100 mM, C & F. 200 mM.

CCS values are calculated using the method described in [38].

Figure 5.3 - [Aβ42-4H]4- and [Aβ42-3H]3- ATDs at 20 µM, pH 7.4 at increasing AmAc salt concentration, collected in negative ionisation mode. A & D. 20 mM, B & E. 100 mM, C & F. 200 mM.

163

5.3.3. Conformational Stability of Aβ(1-42) probed by CIU-TWIMS

Figure 5.4A to D are the CIU fingerprint plots of the m/z selected [Aβ42+4H]4+ and

[Aβ42+3H]3+ from H2O (pH 2) and 20 mM AmAc (pH 7.4). As the collision voltage is ramped,

the selected precursor is depleted, see Figure 5.4A to D. Under both solution conditions, for

both charge states, there is no large scale modification to the ATD i.e. ATD shift or

widening, which would suggest unfolding of the peptide prior to dissociation to a distinct

pre-activated conformer. The observed b- and y- fragment ions of [Aβ42+4H]4+ in H2O (pH

2) and 20 mM AmAc (pH 7.4) are shown in Figure 5.5 and 5.6. The CIU fingerprint plots

show how the dissociation of the selected precursor occurs at slightly lower energies in H2O

(pH 2) than in 20 mM AmAc (pH 7.4).

Figure 5.4 – Normalised CIU fingerprint plots of A. [Aβ42+4H]4+ and C. [Aβ42+3H]3+ in H2O (pH 2) and B. [Aβ42+4H]4+ and D. [Aβ42+3H]3+ in 20 mM AmAc (pH 7.4).

Figure 5.5 and 5.6 are the CID fragmentation maps of [Aβ42+4H]4+ in H2O (pH 2) and 20 mM

AmAc (pH 7.4). As expected, fragmentation increases with collision voltage under both

conditions. There is a greater increase in sequence coverage at lower collision voltages and

at the highest collision voltage applied (60 V), the sequence coverage is greater in H2O (pH

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2), see Figure 5.5/6 A to E and G. This suggests that under these solution conditions, a

conformer more conducive to fragmentation is prevalent.

Figure 5.5 – CID fragmentation maps of [Aβ42+4H]4+

in H2O (pH 2) at increasing collision voltage.

Figure 5.6 - CID fragmentation maps of [Aβ42+4H]4+ in 20 mM AmAc (pH 7.4) at increasing collision voltage.

At lower collision voltages fragmentation is limited to the C-terminal region; however,

fragments are identified from the central region as collision voltage is ramped. The absence

of fragments from the N-terminus of Aβ(1-42) can be explained by the cluster of basic

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residues in this region. Protonated peptides which are activated under low-energy collision

conditions fragment mainly by a charge-directed mechanism, requiring a proton at the

cleavage site [47, 48]. The mobile proton model proposed by Dongré et al., 1996 states that

the proton(s) migrate to various protonation sites following activation unless sequestered

by basic amino acid side chains [47, 49]. If the proton(s) are sequestered by the basic amino

acid side chain(s), energy is required to mobilize the proton(s) to the peptide back bone to

induce dissociation; increasing the energy required for fragmentation, this energy threshold

can be more than required to initiate charge-remote fragmentation pathways [48, 50-54].

The CIU fingerprint plots and fragmentation maps demonstrate that Aβ(1-42) in H2O (pH 2)

is more conducive to fragmentation, it can be hypothesized that the intramolecular

interactions of the peptide in AmAc (pH 7.4) may hold the conformer intact to higher

energies than those present in H2O (pH 2).

5.3.4. ETD, ETnoD and ETcaD

Electron Transfer Dissociation (ETD) is commonly used for the top down fragmentation of

peptides and proteins to determine primary sequence and Post-Translational Modification

(PTM) location. ETD can be used to probe secondary and tertiary structure, analogous to

ECD, see Chapter 3 [55]. Following interaction with the ETD reagent, 1,3-dicyanobenzene,

no ETD specific c- and z- fragment ions were observed. Figure 5.7 is the mass spectra of

Aβ(1-42) following the incremental reduction of the trap wave height. [Aβ42+4H]4+, the

selected precursor ion is highlighted in yellow (Figure 5.7A). Following the lowering of the

trap region wave height to 0.5 V to allow increased interaction, the dominant reaction is

charge reduction as [Aβ42+3H]3+ (green) and [Aβ42+2H]2+(orange) are observed, see Figure

5.7C. [Aβ42+H]1+ highlighted in blue, is observed when the trap region wave height is

lowered to 0.4 V (Figure 5.7D). This becomes the most intense species following the

reduction of trap region wave height to 0.3 V (Figure 5.7E) and 0.1 V (Figure 5.7F). Figure

5.8 highlights the rise and fall in intensity of the charge reduced species as a function of

trap region wave height. Figure 5.7E and F feature significant peaks which appear to be

fragment ions; however, positive identification was not possible. [Aβ42+4H]4+ and

[Aβ42+2H]2+ are present as salt ion adducted species, but are not labelled in Figure 5.7E and

F. [Aβ42+3H]3+ is not observed following the reduction of the wave height to <0.4 V,

suggesting this species is more susceptible to charge reduction.

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Figure 5.7 – Spectra of the isolated [Aβ42+4H]4+ (20 µM, 20 mM AmAc, pH 7.4), following incremental reduction of the trap wave height charge reduction is observed. The peaks which appear

to be the 4+ species in the WH 0.3 V and 0.1 V spectra are very stable [Aβ42+3H+Na]4+.

Figure 5.8 – Aβ(1-42) monomer absolute intensity divided by the TIC plotted against the trap region wave height. Note the change in dominant species with trap wave height reduction.

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The presence of three histidine residues in the disordered N-terminal region of Aβ(1-42),

which have been shown to act as stable electron traps and the presence of strong intra-

molecular interactions preventing the loss of fragmented regions, explains the preference

for charge reduction over fragmentation observed [56]. ETD with supplemental activation

has been previously employed by the Coon group [57] and the Sobott group [55], to

improve the production of fragment ions by disrupting the intra-molecular interactions

holding the electron transfer based fragments together. Supplemental collisional activation

can be applied in the transfer region of the Synapt Triwave device and the effect is clear in

Figure 5.9. Again no significant fragmentation is observed with a raised trap wave height

without supplemental collisional activation (Figure 5.9A). A single z- fragment ion is

observed after the wave height is lowered to 0.5 V to enable interaction with the ETD

reagent (Figure 5.9B). Following the lowering of the trap wave height to 0.5 V with

supplemental collisional activation, multiple c- and z- fragment ions are observed, as well as

b- and y- fragment ions in the C-terminal region (Figure 5.9D). These b- and y- fragment

ions are attributed to post drift fragmentation as a raised trap wave height preventing ETD

with supplemental collisional activation yields b- and y- fragment ions of a similar efficiency

to those seen with a reduced wave height (Figure 5.9C vs. D).

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Figure 5.9 – A comparison of ETD and ETcaD fragmentation and location. Normalised c-, z-, b- and y- fragment ion intensities plotted against the location within the primary sequence of Aβ(1-42). A. no ETD no CAD B. ETD without CAD C. CAD without ETD D. ETD with CAD. Note the increase in c- and z- fragment ion intensity with CAD.

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Figure 5.10 – ETcaD fragmentation map for [Aβ42+4H]4+ in 20 mM AmAc (pH 7.4). ETD with supplemental collisional activation (25 V).

Figure 5.10 is the ETcaD fragmentation map for the selected Aβ(1-42) precursor ion,

[Aβ42+4H]4+. C- and z- fragment ions resulting from the ETcaD process are located primarily

in the N-terminal region of the protein. The Aβ(1-42) monomer has been described as

intrinsically disordered and assumes a collapsed structure in water composed of loops,

strands and turns [58, 59]. In addition, the Central Hydrophobic Cluster (CHC) interacts with

the C-terminus, which isolates the N-terminus [58, 59]. This lack of evidence for structural

elements explains the N-terminal fragmentation observed.

The b- and y- fragment ions, a product of the supplemental collisional activation process

are located primarily in the C-terminal region. This concurs with previous CID analysis of

Aβ(1-42), see Figure 5.6. ETcaD experiments were conducted on a Synapt G2Si instrument

which offers increased sensitivity over the Synapt G2 instrument used for the pH effect

experiments, this can be seen by comparing Figure 5.10 and Figure 5.6.


5.3.5.1. Fragmentation

Surface Induced Dissociation (SID) has been employed to study a wide range of molecular

ions including organic ions [60], fullerenes [61] and dendrimers [62] amongst other species

[63, 64]. SID has been previously demonstrated to be as effective as CAD for the

sequencing and structural characterization of peptides and proteins [65-69]. A wide range

of biomolecules has been studied by SID, ranging from peptides such as leucine enkephalin

[70], melittin [65], bradykinin [67] and substance P [71] to proteins including cytochrome C

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[72, 73], tryptophan synthase [74] and C-reactive protein [75]. To date, SID has not been

applied to amyloidogenic peptides and has been applied here to study Aβ(1-42) in

comparison with Aβ(1-40).

Figure 5.11 – SID fragmentation map for [Aβ42+4H]4+ in 20 mM AmAc (pH 7.4). SID collision voltage: 40 V.

Figure 5.11 is the SID fragmentation map of [Aβ42+4H]4+ using a collision voltage of 40 V.

The fragments observed are limited to b- and y- fragment ions and are primarily located in

the C-terminal region of the peptide. Fragments not located in the C-terminal region are

located in the extreme N-terminal region and no fragments are observed in the central

region between Ser7 and Ala30. The low levels of fragmentation observed in the N-

terminus can be explained by the presence of a cluster of basic residues, previously shown

to decrease fragmentation [49, 69, 70, 76] and as observed for CID experiments, see Figure

5.6 and 5.10. The lack of fragmentation from the central domain is interesting; this region

includes the CHC, spanning residues Leu17 to Ala21, a region of high β-turn propensity and

a salt bridge between the residues Lys28 and Asp23 [7, 59, 77-80]. The lack of

fragmentation suggests a dependence on precursor structure. The three solvation states

proposed by Bernstein et al. and Teplow et al. may be represented in the Aβ(1-42) ATDs

collected; however, it is not possible to determine which states are present [6, 9].

Molecular modelling by Bernstein et al. has indicated that following the transition of the

peptide from the solution phase to the gas phase, in the case of the solvent free model, the

hydrophobic core region is exposed [6]. The core is also exposed in the hydrated and

dehydrated models but to a lesser extent [6]. This exposure of the hydrophobic regions

presents an explanation for the fragmentation observed from the central region.

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Charge reduction is observed following SID of Aβ(1-42) [66, 67], attributed to charge

transfer with the surface [67]. Complimentary charge reduced C-terminal fragment ions, in

addition to a single N-terminal y-ion and a b-ion located in the central domain, although

not in the CHC are also observed.

Figure 5.12 – SID fragmentation map for [Aβ40+4H]4+ in 20 mM AmAc (pH 7.4). SID collision voltage: 40 V.

Aβ(1-42) is ten times less abundant, aggregates faster, forms distinct oligomeric species

and is significantly more neurotoxic than Aβ(1-40) [16, 17]. However, as the name suggests

it only differs in sequence by two C-terminal amino acids. SID collision voltage was ramped

following the isolation of [Aβ40+4H]4+ and Figure 5.12 is the SID fragmentation map at a SID

collision voltage of 40 V. Again, the C-terminus fragments more readily than any other part

of the peptide and the lack of fragmentation in the N-terminal region is again attributed to

the cluster of basic residues, which remain unchanged. Interestingly, greater sequence

coverage is achieved with both b- and y- C-terminal fragment ions observed. It is known

that the Aβ(1-40) C-terminus is more flexible and therefore may provide more

fragmentation conducive structures [17, 81]. The main differences between the

fragmentation maps of Aβ(1-42) and Aβ(1-40) are the fragments from the CHC and the

greater coverage of complimentary charge reduced fragment ions observed, see Figure

5.12. Differences in the interactions of the CHC with the C-terminal region of Aβ(1-40) and

Aβ(1-42) may explain this disparity. The C-terminal region of Aβ(1-42) has been shown to

interact with the CHC forming an anti-parallel β-hairpin which is rarely present in the more

flexible Aβ(1-40) [59, 81].

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Figure 5.13 are spectra following CID (Figure 5.13A) or SID (Figure 5.13C) of [Aβ42+4H]4+.

Although analogous to CID on the basis that both induce fragmentation via collision with an

inert target in contrast, SID is a single step process lasting picoseconds during which a

higher internal energy than that of a multiple collision process is deposited in a highly

tuneable manner [68, 82]. The difference between the two fragmentation techniques is

clear. The b- fragment ions generated by SID are of greater relative intensity and compared

to the complex CID spectrum, the SID fragmentation map is much ‘cleaner’, one of the

advantages that the fast single energy deposition of SID offers over the slow heating

mechanism of CID, in which multiple rearrangement products may be generated [82].

Figure 5.13 – Comparison of CID vs SID fragmentation of [Aβ42+4H]4+ in 20 mM AmAc (pH 7.4). A. CID: 50 V, B. CID/SID: 0 V C. SID: 40 V

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5.3.5.2. The Effect of SID on the Conformation Exhibited by Amyloid

Species

Installation of the SID cell prior to the TWIMS region of the Synapt instrument enables SID

fragment ions to be analysed by TWIMS. Here, SID-TWIMS is used to probe the

conformation of the SID fragment ions of Aβ(1-42) and Aβ(1-40). The C-terminus of Aβ(1-

42) and Aβ(1-40) readily fragments in contrast to the sparse fragmentation observed from

the central and N-terminal regions. During ETD experiments Aβ(1-42) was demonstrated to

present a ETD resistant structure, bound by strong intramolecular interactions (Figure 5.7-

5.10).

Figure 5.14 - [Aβ42+4H]4+ C-terminal SID b- fragment ion ATDs in 20 mM AmAc (pH 7.4). SID collision voltage: 40 V

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Figure 5.14A to I are the ATDs of the precursor and C-terminal b- fragment ions of

[Aβ42+4H]4+ following SID at 40 V. A single wide distribution without shoulders is observed

for the precursor ion, as previously documented (see Figure 5.2). There is no observable

modification to the ATD of the [b41+4H]4+ to [b37+4H]4+ fragment ions. The ATD of the

[b36+4H]4+ fragment ion is significantly different, see Figure 5.14E. Two overlapping

conformers are present, the newly observed conformer occupying a longer drift time. This

suggests the fragment has adopted a less compact conformation. A β-hairpin involving the

CHC and the Gly29 to Val36 residues has been observed by Ball et al., disruption of this

structure due to the loss of C-terminal residues explains the observation of the extended

conformer [59]. This extended conformer may also be the result of a loss of self-solvation

of the peptide ion [83]. An additional later arriving conformer is also observed in the

[b36+4H]4+ fragment ion resulting from CID. The ATD recorded is less defined and the

species of lower intensity, see Appendix Figure A4.5. The [b35+4H]4+, [b34+4H]4+ and

[b32+4H]4+ fragment ions also exhibit two conformers, the presence of the later arriving

species in Figure 5.14H is based on the width of the ATD; however, a single conformer is

observed for the [b31+4H]4+ fragment ion.

Figure 5.15A to I are the ATDs of the precursor [Aβ40+4H]4+ and b- fragment ions following

SID at 40 V. The less rigid and structured C-terminal region of Aβ(1-40) demonstrated by

solution NMR is reflected in the fragment ion ATDs [17, 81]. Aβ(1-40) has also been

demonstrated to exhibit conformational changes prior to aggregation and the presence of

an aggregation intermediate conformer [80, 84]. Compared to the parent ion (Figure

5.15A), two broad conformers of equal intensity are observed for the [b39+4H]4+ fragment

ion (Figure 5.15B). The earlier arriving conformer is observed at a much higher intensity for

the [b39+4H]4+ fragment ion, and represents a more compact conformer as charge and MW

are identical. The loss of this residue will remove the contribution to the fold of any

interactions it has. An interaction between His13 and Val40 has been reported, although

this is in a modelled Aβ(1-40) fibril [80]. The [b38+4H]4+ fragment ion also presents two

conformers, see Figure 5.15C.

The [b37+4H]4+ fragment ion exhibits three conformers (Figure 5.15D), two compact species

and one extended conformer on the basis of the longer drift time. The [b36+4H]4+ fragment

ion exhibits multiple overlapping conformers, including a dominant extended conformer,

see Figure 5.15E. A series of low intensity overlapping conformers and a dominant

extended conformer are also observed for the [b35+4H]4+ and [b34+4H]4+ fragment ions

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(Figure 5.15F to G). One explanation for this dominating extended conformer is the

disruption of a region of high β-sheet probability in the C-terminus of Aβ(1-40). The

disruption of a reported interaction between Gln15 and Val36 may also be a contributing

factor [80]. The [b33+4H]4+ and [b32+4H]4+ fragment ions present similar ATDs with a series

of overlapping more compact conformers, of a greater intensity compared to the [b34+4H]4+

to [b36+4H]4+ fragment ions, and an extended conformer, see Figure 5.15H and I. The loss of

the C-terminal hydrophobic cluster enabling the rearrangement and adoption of compact

structure is one explanation for the compact conformers whilst a loss of self-solvation

explains the extended conformer. The loss of the Leu34 residue also disrupts a reported

interaction with the Phe19 residue [80].

Figure 5.15 – [Aβ40+4H]4+ C-terminal SID b- fragment ion ATDs in 20 mM AmAc (pH 7.4). SID collision voltage: 40 V.

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In contrast to the fragment ions of [Aβ42+4H]4+, a single conformer is observed in the ATDs

of the charge reduced [Aβ42+3H]3+ and C-terminal b- fragment ions, see Appendix Figure

A4.6A to J. The only ATD modification is a small decrease in drift time with C-terminal

residue loss. This is also observed for the charge reduced [Aβ40+3H]3+ precursor and

fragment ions. With the exception of the [b39+3H]3+ and [b38+3H]3+ fragment ions, a single

conformer is observed for all fragment ions, see Appendix Figure A4.7A to K. A second

more compact conformer is observed for the [b39+3H]3+ and [b38+3H]3+ fragment ions, see

Appendix Figure A4.7B and C. This suggests the Aβ(1-42) and Aβ(1-40) fragments readily

adopt a compact conformation and there is no loss of self-solvation or extended conformer

adoption with C-terminal residue loss, this may be the result of the reduced coulombic

repulsion suffered by the charge reduced species or the result of a conformational

rearrangement resulting from interaction with the surface during the charge reduction

event.

Figure 5.16 shows the ATDs of the fragment ions observed from the central region of Aβ(1-

40). A single conformer is observed for the [b30+3H]3+, [b24+3H]3+ and [b23+3H]3+ fragment

ions, see Figure 5.16A to C. In contrast, a compact and an extended conformer are

observed in the ATDs of the [b21+3H]3+ to [b19+3H]3+ fragment ions, see Figure 5.16D to F.

The loss of further residues from the CHC correlates with an increase in intensity of the

more extended conformer. This shift in favour of the extended conformer suggests the loss

of these residues leads to the disruption of the CHC and enables the remaining peptide

including the disordered N-terminal region to adopt more extended conformations [80].

SID and CID are both collision based fragmentation techniques; however, the time scale for

the energy deposition process differs significantly, from picoseconds (SID) to microseconds

(CID) [73, 85]. CID is a multi-collision process; typically involving 103 to 105 collisions and

pre-activation of the precursor [86]. SID on the other hand is characterised as a single step

process with no pre-activation of the precursor [64, 85, 87, 88]. Following the application of

increasing SID collision voltage, the ATDs of the selected precursor ions [Aβ42+4H]4+ and

[Aβ40+4H]4+ display no change to the drift time profile, indicating a lack of pre-activation

prior to fragmentation, see Appendix Figure A4.8. This suggests the changes to the ATDs

observed, represent changes to the conformation of the peptide following the disruption of

intramolecular interactions on the loss of C-terminal residues.

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Figure 5.16 – ATDs of the charge reduced [Aβ40+3H]3+ central region SID b- fragment ions in 20 mM AmAc (pH 7.4). SID collision voltage: 40 V.

5.3.6. The Interactions of Aβ(1-42) with Small Molecule Anti-Aggregation

Drug Candidates

Measuring the binding of small drug candidates to proteins is a common application of

biological MS. Here, the binding of Aβ(1-42) and the aggregation inhibiting peptide, RI-OR2

is assessed, in comparison with a control peptide, Bradykinin (BK). Figure 5.17 shows the

mass spectra of Aβ(1-42) at an increasing ratio of Aβ(1-42) to RI-OR2 in H2O (pH 2). In the

absence of RI-OR2, only monomeric species are observed (3 ≤ z ≤ 5). At a 1:0.1 ratio,

[Aβ42+6H]6+ is observed at low intensity, expanding the monomer CSD width, in addition,

the [(Aβ42)2+5H]5+ and [(Aβ42)2+7H]7+ dimers are observed. Significant tailing attributed to

sodium adducts is observed in Figure 5.17A and Figure 5.17B, although at a much lower

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intensity. The difference in the salt adduction between the two samples may be the result

of a larger nESI tip orifice, increasing the initial droplet size and the probability of sodium

ion presence in the initial droplet. The reduction in salt adducts may also be the result of

RI-OR2 sequestering some of the sodium contaminant ions, which are subsequently lost

during the desolvation process or the presence of RI-OR2 leads to a rearrangement of Aβ(1-

42) surface accessible residues lowering the potential partners for sodium ion pair

formation [89]. The cleaner spectrum in Figure 5.17B also explains the observation of the

low intensity dimer species. In addition, a bound 1:1 complex [(Aβ42:RI-OR2)+4H]4+ (m/z:

1409) is observed at a low intensity. As the ratio of Aβ(1-42):RI-OR2 is increased, the

intensity of the bound species increases (Figure 5.17C to E). At a ratio of 1:0.5 and above,

the [(Aβ42)2+5H]5+ dimer is not observed, this is attributed to an increase in baseline noise.

The unbound [RI-OR2+3H]3+ and [RI-OR2+2H]2+ are observed at all ratios tested and as the

Aβ(1-42):RI-OR2 ratio is increased, [RI-OR2+3H]3+ and the unbound RI-OR2 species in

general become the dominant species of each spectrum. Although the monomer and dimer

species observed are similar, a greater ratio of Aβ(1-42):ligand is required to observe the

Aβ(1-42):BK complex, 1:0.5 compared to 1:0.1, see Appendix Figure A4.9, demonstrating

RI-OR2s greater affinity for Aβ(1-42). Figure 5.18 is a plot of the absolute intensity for the

observed species at each ratio tested, there is no suppression of the Aβ(1-42) signal with

increasing RI-OR2 intensity. RI-OR2 ionises more readily than Aβ(1-42) and the intensity of

the unbound RI-OR2 peaks may be supplemented by the dissociation of Aβ(1-42):RI-OR2

during the ionisation process. Difficulties achieving a stable spray of Aβ(1-42) and

aggregation of the sample, negatively affect the intensity of the Aβ(1-42) peaks observed.

This experiment demonstrates that the interaction between RI-OR2 and Aβ(1-42) is

observable by MS. The peptide:ligand samples were prepared immediately prior to analysis

to minimise aggregation. In order to test the anti-aggregation properties of RI-OR2, longer

incubation periods before analysis are required. Following incubation, the absence of

dimers and higher order oligomers will confirm the anti-aggregation properties of RI-OR2.

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Figure 5.17 - Mass spectra of Aβ(1-42) at 20 µM in H2O (pH 2) at increasing Aβ(1-42):RI-OR2 ratio. Observed species are annotated in the first instance and labelled oligomeric order / charge. Marker denotes species and oligomeric order. Red triangle: RI-OR2, Green square: Aβ(1-42) monomer, Blue

square: Aβ(1-42) dimer, Yellow circle: Aβ(1-42):RI-OR2 bound species. (inset) Zoom of regions of interest, required due to the high intensity unbound ligand species.

Figure 5.18 - Absolute intensity of all observed species plotted against Aβ(1-42):RI-OR2 ratio in H2O (pH 2).

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TWIMS has been previously applied to categorise the binding of small drug candidates to

Aβ(1-40) in a screening type experiment [37]. Here, TWIMS is used to investigate the

impact of small drug candidates on Aβ(1-42):ligand complex conformation in comparison

with the control peptide, Bradykinin. Figure 5.19 are the ATDs and calculated CCS values of

the Aβ(1-42):ligand complexes observed. For all ligands tested, there was no evidence of

templating or effects of the presence of the ligand in solution under all solution conditions

and ionisation polarities tested. The calculated CCS values of the unbound species differ by

<±1% in all cases (Table 5.1) and there is no observable change to the ATDs recorded, see

Appendix Figure A4.10 and A4.11. In all cases, a single conformer is observed for

[Aβ42+4H]4+ as previously observed (Figure 5.2, Appendix Figures A4.10 and A4.11 and

Table 5.1). Two conformers are observed for [Aβ42+3H]3+ (Figure 5.2, Appendix Figure

A4.10 and A4.11 and Table 5.1), with the exception of the experiments in the presence and

absence of rutin in 20 mM AmAc in positive ionisation mode (Appendix Figure A4.11A to E

and Table 5.1). This difference is likely due to the instrumental conditions applied, which

were tuned for observation of the complex, being unable to separate the two conformers.

The ATD of the Aβ(1-42):RI-OR2 complex, [(Aβ42:RI-OR2)+4H]4+ in H2O (pH 2) is more

complex. Both compact (646 Å2, 689 Å2 and 721 Å2) and extended (816 Å2) conformers are

observed (Figure 5.19A). The calculated CCS of RI-OR2 ([RI-OR2+2H]2+) is 259 Å2 (Appendix

Figure A4.13), a larger increase in CCS is expected following the binding of a ligand which is

~1/4 of the MW of Aβ(1-42) (4514 Da) and which presents a CCS which is equivalent to

~1/2 of Aβ(1-42), see Table 5.1. The compact conformers are therefore the result of RI-OR2

binding, followed by the collapse of the Aβ(1-42) around it. The observation of multiple

compact conformers suggests that there are either multiple binding sites or energy

minimised conformers. The extended conformer observed is the result of RI-OR2 binding

Aβ(1-42) and holding it in an extended conformer or is the result of non-specific binding.

Bradykinin (BK) was chosen as a control peptide due its similar molecular weight to RI-OR2

(MW: 1060 Da) and absence of known anti-aggregation properties. In contrast, in both H2O

(pH 2) and 20 mM AmAc (pH 7.4), the Aβ(1-42):BK bound species exhibits a longer drift

time than the unbound species. A single extended conformer is observed with a calculated

CCS of 803 Å2 in H2O (pH 2), see Appendix Figure A4.12A. In contrast, two extended

conformers are observed in 20 mM AmAc (pH 7.4) with calculated CCSs of 771 Å2 and 792

Å2 (Appendix Figure A4.12B). The additional conformer observed in AmAc is an earlier

arriving, more compact species and suggests the single conformer observed in H2O is the

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result of the solution conditions unfolding the bound conformer. The ATDs and calculated

CCS values of BK in H2O (pH 2) and AmAc (pH 7.4) are shown in Appendix Figure A4.14 and

A4.15. The increase in calculated CCS suggests BK is binding to an extended form of Aβ(1-

42) and is not inducing a compaction.

A single conformer with a shorter drift time and a calculated CCS of 660 Å2 is observed for

the Rutin bound Aβ(1-42) in contrast to RI-OR2 and BK in H2O (pH 2), see Figure 5.19B. A

single conformer with a calculated CCS of 651 Å2 is also observed in 20 mM AmAc (pH 7.4),

see Figure 5.19C. In both cases, the CCS of the bound complex is only slightly larger than

the unbound species (Table 5.1), and when the CCS of unbound Rutin is considered, 170 Å2

in H2O (pH 2) and 169 Å2 in 20 mM AmAc (pH 7.4) (Appendix Figures A4.16 and A4.17), a

larger increase in CCS is expected upon binding. These results suggest in contrast to RI-OR2,

Rutin exerts its inhibitory action solely by inducing a compaction of Aβ(1-42). Several

studies have shown that small molecules composed of an aromatic core and polyhydroxyl

groups have anti-aggregation properties based on interaction with the residues of the CHC,

interaction with the hydrophobic channels created by fibrillization or via disruption of

hydrogen bonding by acting as electron donors [90-93]. Rutin features an aromatic core

and polyhydroxyl groups, this data suggests that Rutin binds to the central hydrophobic

region of Aβ(1-42) and the compact conformer which results from binding is via collapse of

the protein around the molecule [93]. The blue highlighted region in Figure 5.19C is

composed of contaminant m/z coincident species co-transmitted with the isolated

precursor, see Appendix Figure A4.18.

Ionisation polarity was switched to negative mode to assess the impact of ionisation on the

conformers of Aβ(1-42) observed in the presence of rutin. The CSD and relative intensity

distribution of the mass spectrum in the absence of rutin is similar to that observed

previously (Appendix Figure A4.19A vs. Figure 5.1). To observe the low intensity bound

species, data collection was extended to 20 minutes and the ratio of Aβ(1-42):Rutin

increased to 1:5 (Appendix Figure A4.19B & C). As observed in positive ionisation mode, the

presence of rutin in solution did not have an observable effect on the ATD of the unbound

species, see Appendix Figure A4.11. Figure 5.19D is the ATD of [(Aβ42:Rutin)-4H]4- in 20

mM AmAc (pH 7.4), due to the absence of a negative ion calibration database, the CCS

values could not be calculated. As observed in positive ionisation mode, the ATD shifts to

an earlier arrival time indicative of a compaction. In contrast to the single peak observed in

positive mode, the ATD is much more complex and is composed of multiple overlapping

182

peaks. The choice of ionisation mode is therefore resulting in a modification of the bound

complex conformers observed.

Figure 5.19 - ATDs and calculated CCS values of ligand bound Aβ(1-42), [(Aβ42:Ligand)±4H]4± at a ratio of 1:1 (1:5, Figure 5.19D) in H2O (pH 2) or 20 mM AmAc (pH 7.4) at 20 µM in positive or

negative ionisation mode.

Table 5.1 - Calculated CCS values of the unbound [Aβ42+4H]4+ and [Aβ42+3H]3+ in the absence and presence of RI-OR2, Rutin and Bradykinin in H2O (pH 2) or 20 mM AmAc (pH 7.4).

TWCCSN2 (Å2)

Buffer H2O (pH 2) 20 mM AmAc (pH 7.4)

Un

bo

un

d A

β(1

-42

)

Ligand RI-OR2 Rutin Bradykinin Rutin Bradykinin

[Aβ42+4H]4+ in absence

635 643 646 642 648

[Aβ42+4H]4+ in presence

635 648 644 642 639

[Aβ42+3H]3+ in absence

566 589 568 588 571 588 574 569 586

[Aβ42+3H]3+ in presence

566 592 573 593 571 591 574 563 582

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5.4. Summary

The aim of the experiments in this chapter was to apply MS based methods to probe the

structure of Aβ(1-42) and Aβ(1-40). MS and IM-MS were applied to probe the effect of

solution condition modification and ionisation polarity on Aβ(1-42). Shifts in the CSD

intensity are observed with alteration of solution conditions and ionisation polarity,

demonstrating that both have an effect on the species observed. The difference in the

Aβ(1-42) ATDs at increasing AmAc salt concentrations between ionisation polarities

suggests that the location of charged groups influences the gas phase structure. As

previously demonstrated for α-Synuclein in Chapters 3 and 4, it is possible to observe day

to day variation in the species observed via MS and IM-MS. This observation highlights the

benefit of MS based methods for analysis, as the unbiased nature and the lack of an

averaging effect are common pitfalls of traditional biophysical techniques and can mask

these variations. In order to probe the structure Aβ(1-42) and Aβ(1-40) and fulfil the aim of

the experiments in this chapter, a range of gas phase fragmentation techniques including

CID, ETD and SID were applied. CIU-TWIMS and analysis of the CID fragments, highlights the

overall structural stability of Aβ(1-42) and its alteration following modification of solution

conditions. In addition, the CIU-TWIMS data demonstrates the day to day variation

previously observed. The primary sequence of Aβ(1-42) has a pronounced effect on the CID

fragments observed, with the cluster of basic residues in the N-terminus preventing

fragmentation in this region (Figures 5.5, 5.6 and 5.10). Previous MS based approaches

including HDX-MS [23-30], have reported the lack of defined structure within the

monomeric Aβ(1-40) and Aβ(1-42) and increases in structure following the transition to

higher order oligomers and fibrils. The absence of fragmentation via ETD alone and the

requirement for supplemental collisional activation, in combination with IM-MS,

demonstrates that monomeric Aβ(1-42) is a compact species bound by intramolecular

interactions. The comparison of the fragmentation of Aβ(1-42) by CID and SID is the first of

its kind for an amyloidogenic protein. SID has been previously demonstrated to be

comparable to CID for the analysis of primary structure [65-69]. The differences between

the two fragmentation processes are clear following comparison of the MS/MS spectra

(Figure 5.13), one of the key benefits of SID being the much ‘cleaner’ spectrum. In addition,

significant charge reduction is observed, a relic of the interaction with the surface during

SID, both features are beneficial for fragment identification and primary sequence

determination. As observed following CID, fragmentation is limited primarily to the C-

terminal region of Aβ(1-42) and Aβ(1-40) (Figure 5.12 and 5.13). SID has been previously

184

used to characterise the subunit architecture of protein oligomers [88, 94, 95]. As SID is a

single step, high energy deposition process without precursor activation (Appendix Figure

A4.8), changes observed in the ATDs of the fragment ions can be correlated with known

structural elements, demonstrated by other biophysical techniques [96] and used to infer

structural details of the precursor ion.

The final aim of the experiments in this chapter was to classify the mode of action of two

drug candidates based on the ligand induced conformational changes in Aβ(1-42) using

TWIMS. We expand on the work of Young et al. in classifying the binding of small drug

candidates to Aβ(1-40) using TWIMS [37]. Based on the calculated CCS of the RI-OR2:Aβ(1-

42) complex, RI-OR2 exerts its inhibitory effect by the collapse of the peptide around it

following binding or by binding and holding Aβ(1-42) in an extended conformation. In

contrast, Rutin exerts its inhibitory effect solely by binding to Aβ(1-42), followed by the

collapse of the peptide around it. Aβ(1-42) is notably more difficult to work with than Aβ(1-

40), on the basis of its aggregation propensity. However, we have demonstrated that

applying IM-MS in this manner has the potential to act as a secondary filter in a high

throughput screen of thousands of small molecule drug candidates.

185

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6 Conclusions and Future Work

Mass spectrometry based methods have been applied to probe the structure and

aggregation of amyloidogenic proteins. In this chapter, the key findings are summarised and

avenues for further investigation are detailed.

192

6.1. Conclusions and Future Work

Understanding the structures adopted by proteins during their lifecycle and in response to

changes in their environment is a crucial step towards understanding the biological

processes which rely on their correct function and the effects when these processes

breakdown in disease. In addition, understanding protein structure in healthy and disease

states can inform the drug design process to prevent or potentially correct the adoption of

a disease state. A wide spectrum of techniques exists for the analysis of protein structure

ranging from the atomistic detail of X-ray crystallography and NMR to the study of protein

dynamics via IM-MS. Although atomistic detail can give a definitive answer to the structure

adopted by a protein, this structure is potentially one of many and the averaging, biased

nature of techniques such as X-ray crystallography and NMR cannot give the full picture. In

contrast, although protein structure can be determined by IM-MS in combination with

molecular modelling, the true strength of MS and IM-MS is that the structure of multiple

species can be investigated at the same time in a unstable sample, in an unbiased manner

with far lower sample requirements.

Chapter 3 is the first chapter concerning α-Synuclein and focuses on the structure of this

IDP and the effect of changes to solution pH and ionisation polarity on the structures

observed. As expected from an IDP, α-Synuclein presents a wide CSD regardless of the

solution pH or ionisation polarity used. The amyloidogenic nature of α-Synuclein can also be

observed by the presence of dimers and other higher order oligomeric species and by the

raised baseline in some spectra, attributed to the presence of low intensity unresolved

higher order aggregates. Lowering the solution pH from 6.8 to 3.5, in positive and negative

mode resulted in a narrowing of the CSD and a shift to lower charge states of monomers

and higher order oligomers. This response is indicative of the induction of structure and

concurs with other biophysical techniques including IM-MS [1]. It is clear from the MS data

that ionisation polarity does have an effect on the species observed, and is likely due to the

location of chargeable residues. However, solution pH has a greater effect on the species

observed. The day to day variation of α-Synuclein is an overarching theme observed by MS.

This is evident by the shifts in the relative intensity distribution of the CSDs and in the

species observed in replicates, despite the strict control of experimental conditions.

IM-MS highlights the disordered nature of α-Synuclein. At pH 6.8, multiple conformational

species are observed for each charge state of α-Synucleins wide CSD, which spans a CCS

range of 938 Å2 to 3093 Å2. These CCS values are in good agreement with those reported by

193

Illes-Toth et al. [2]. Despite the use of positive ionisation mode, the CCS values are also in

good agreement with those reported by Bernstein et al. and Grabenauer et al. in negative

mode for the lower charged species [1, 3]. However, higher charge states exhibit

significantly larger CCS values and the large CCS increase between [aSyn-8H]8- and [aSyn-

9H]9- is not replicated in positive ionisation mode [1]. This suggests the location of

chargeable residues is driving the larger CCS values observed in negative ionisation mode.

The day to day variation and conformational diversity observed in the MS data is again

evident in the IM-MS data, as the large error bars for most species demonstrate the large

variation observed between samples prepared under strictly controlled conditions. This

diversity is also highlighted by Illes-Toth et al. [2] and in the lower charge states reported by

Grabenauer et al. in negative mode [3].

Cross-linking IM-MS enables the gas phase analysis of solution phase structures by trapping

conformations via covalent modification prior to ionisation. The addition of the cross-linker

influences the conformational space that α-Synuclein is able to inhabit. The conformation

pinning action of the cross-linker on the protein is clearly shown by the narrowing of the α-

Synuclein CSD and CCSD and the stabilisation of conformational families with additional

cross-linker modifications. However, the addition of the cross-linker can also prevent the

adoption of the most compact conformers in lower charged species. MS, IM-MS and AFM

observe multiple α-Synuclein morphologies at one time; this is reflected in the cross-linking

IM-MS data by the co-transmission of combinations of the three cross-linker pinned

conformational families. Of the three conformational families observed, the extended and

unfolded species CCS values are in good agreement with values reported by Bernstein et al.

[1] and reflect the conformational diversity observed by Illes-Toth et al. [2] and Grabenauer

et al. [3]. The data further demonstrates the conformational diversity of α-Synuclein and

highlights a link between the solution phase and the gas phase structures observed by MS

based methods. The cross-linking process creates some additional hurdles for analysis, as

the uncontrolled cross-linking reaction leads to peak broadening. Additional sample

preparation steps to clean up the spectra to enable further analysis of higher order

oligomers is the clear next step. The effect of the cross-linking reagent on the species

observed must also be investigated. Following this cross-linking IM-MS could be applied to

examine the effect of ligands on solution phase conformation.

ECD was applied to investigate the effect of solution pH on the gas phase structure of α-

Synuclein. The spectra obtained on the FT-ICR MS instrument are similar to those obtained

on ToF geometry instruments and display the characteristic wide CSD and shift in intensity

194

to lower charge states following a reduction of the solution pH. A wide variety of low order

oligomers are observed on ToF instruments; however, only monomers and dimers are

observed on the FT-ICR instrument. These changes to the CSD may result from the use of a

different ionisation source. Further analysis will focus on tuning experimental conditions to

observe higher order oligomers prior to ECD. As expected, the fragmentation observed

increases with charge state, this clearly visible in the annotated spectra of the [aSyn+9H]9+

and [aSyn+10H]10+ monomers (Figure 3.12 and 3.13) and is also observed for the dimer

species investigated. Interestingly, a reduction in the solution pH from 6.8 to 3.5 results in

the observation of greater fragmentation for α-Synuclein monomers and dimers. This is at

odds with MS data from ToF and FT-ICR instruments which indicate the protein has adopted

a less solvent accessible structure; with IM-MS which reports a reduction in CCS at pH 2.5

[1] and with other biophysical techniques [4] which indicate an increase in structure at low

pH, which should reduce fragmentation. The fragmentation observed is limited primarily to

the N-terminal region of both monomers and dimers, which has been shown by NMR to

adopt a more extended conformation at lower pH. The lack of fragmentation observed

from the C-terminal region suggests the C-terminus forms part of a stable protected core

region. This hypothesis is supported by IM-MS data which suggests the CCS decrease is the

result of the collapse of the C-terminal region at low pH [1] and by FRET experiments which

demonstrate a compaction of the C-terminus [5]. This also concurs with PRE and NMR

dipolar coupling experiments which establish interactions between C-terminal hydrophobic

clusters and the central NAC domain [6]. AFM force spectroscopy data suggests the C-

terminus is involved in the dimer interface, which explains the lack of fragmentation

observed in this region [7]. However, the lack of fragmentation also observed from the C-

terminal region of the monomer species investigated, suggests that the lack of

fragmentation observed from the dimer species may be a result of them being composed of

two monomers with fragmentation resistant C-termini. In addition, CD [8], FTIR [8], and

HDX-MS [9, 10] do not detect regions of stable C-terminal secondary structure, these

conflicting reports highlight the conformational heterogeneity and variation of α-Synuclein.

Chapter 4 builds on the work of Chapter 3 and focuses on examining the early stages of α-

Synuclein aggregation using MS based methods. The observation of fibrils via TEM following

aggregation under MS compatible conditions, which exhibit previously reported

morphologies, validates the time points chosen and demonstrate that it is possible to

follow aggregation in an MS compatible buffer. The variety of morphologies observed

during the TEM time course highlights the diversity of the species of the α-Synuclein

195

aggregation cascade. As seen in Chapter 3, wide CSDs and a range of low order oligomeric

species ranging from dimers to tetramers are observed for α-Synuclein. The α-Syuclein

aggregation process can be observed by MS, as the depletion of the TIC with time course

progression and the increasing difficulty in achieving a stable nESI spray from the samples

of the later time points, indicate that aggregation is taking place. However, we are only able

to observe a small window of the process. At the later time points of the 96 hour in vitro

aggregation time course the intensity distribution shifts to favour lower charged

monomeric species, as highly charged monomers are depleted from solution. These highly

charged monomeric species represent the extended α-Synuclein monomers in solution,

which become highly charged upon ionisation, due to their greater solvent accessibility.

This suggests these extended monomers are more amenable to aggregation. The depletion

of higher charged monomeric species with time course progression may also be the result

of an equilibrium between the extended species and a rapidly aggregating compact species.

The depletion of the extended species results from collapse of the protein to form a

compact species, which rapidly aggregates beyond the scope of the technique. This concurs

with previously published data which demonstrates the link between the assumption of a

compact conformation and aggregation progression [1, 3, 11, 12]. The contribution to the

spectra of higher order species including trimers increases as the time course progresses.

However, higher order species are expected and again suggests the low order oligomeric

species observed are off-pathway slower aggregating species. When aggregation is

assessed on a shorter time scale during a nESI experiment, this same narrowing of the CSDs

and falling TIC is observed. In addition, a raised baseline, indicative of low intensity, poorly

resolved, higher order oligomeric species is observed at later time points and higher order

species are depleted as they are sequestered into higher order aggregates not observable

by MS. In addition to the depletion of highly charged monomers, as previously observed in

the long term aggregation time course, lower charged monomers are also depleted with

time course progression. Again, this suggests the presence of an aggregation mechanism in

which the extended species are in equilibrium with a fast aggregating compact species.

Despite these indicators of aggregation, the lack of CSD modification and TIC depletion in a

replicate of the in tip aggregation experiment demonstrates that the aggregation process is

highly complex and influenced heavily by environmental conditions. This also suggests that

the initial aggregation process is occurring very quickly and the species observed via MS are

a sub-population of slower aggregating species and those in equilibrium with higher order

aggregates. The variation in higher order oligomers observed between the 96 hour MS

time course, the in tip aggregation time course and the mass spectra of the IM-MS

196

aggregation time course, in comparison with the figures of Chapter 3 demonstrate that a

variable diverse range of species is present during the aggregation process. Despite the

variation observed, MS at both short and long aggregation time scales has the potential to

be used as a screen for small molecules able to prevent aggregation or to disaggregate α-

Synuclein based on the species observed. The absence of the variation of species observed

here would indicate that a population of homogenous species had been achieved.

IM-MS of a 120 hour in vitro α-Synuclein time course again observes wide CSDs and CCSDs

throughout the aggregation time course, similar to those observed following cross-linking

(Chapter 3) and the CCSs recorded are similar to those reported by Bernstein et al. despite

the use of positive ionisation mode in place of negative ionisation mode [1]. Evidence such

as CCSD narrowing to suggest the adoption of an aggregation prone structure is not

observed in either the monomer or dimer species investigated. The large spread in CCS

across the CSD (Δ ~1600 Å2), the large spread in CCS for each charge state analysed, the

CCSD error bars and transient species observed, all indicate that the protein remains

flexible in solution. This again highlights the diverse range of species present during the

aggregation process, as observed by MS. Significant variation is observed for the α-

Synuclein dimers investigated and concurs with the work of Illes-Toth et al. [13] and Ray et

al. [14]. The wide CCSDs and the lack of a CCS decrease with dimer formation suggest the α-

Synuclein dimer has a small interface and the dimer itself remains unstructured, which

concurs with the force spectroscopy studies of Neupane et al. [15]. The next step is to

investigate the effect of pre-treatment with or the presence of anti-aggregation drug

candidates on α-Synuclein aggregation and the species observed. IM-MS has the potential

to act as a secondary screen, in combination with less labour intensive methods including

MS to screen small molecule libraries for drug candidates.

An aggregation specific conformer or distinct regions of protection, which would indicate

an aggregation induced conformational change, is not observed by HDX-MS. The oscillating

RFU with time course progression highlights the presence of transient structures, which

concurs with our IM-MS results. The differences in the small regions of protection between

our results and those published by Del Mar et al. and Mysling et al. demonstrates that the

α-Synuclein species observed by MS based methods from the solution component of the in

vitro aggregated sample remain conformationally diverse [9, 10]. The untargeted approach

used here may account for some differences in the RFU observed, as previous studies have

included processing steps to remove monomeric α-Synuclein from the sample. The PAL

sample manager and HDX manager system used in this study permits the analysis of a large

197

panel of candidates with minimal human input, HDX-MS could therefore be used to screen

libraries of anti-aggregation drug candidates. However, changes to the data analysis

method are required to prevent the degradation of the data.

Chapter 5 focussed on investigating the structure and interactions of primarily, Aβ(1-42)

and Aβ(1-40). As observed with α-Synuclein, alteration of the solution conditions led to

changes in the CSD and is hypothesised to be the result of the conditions causing a change

in protein solution structure. The choice of ionisation polarity also has an effect on the CSD

observed, with the CSD shifting to lower charge states regardless of solution conditions.

The overwhelming majority of species observed are monomeric and the commonly

observed [(Aβ42)2-5H]5- dimer is not observed. The Bowers group state the observation of

this dimer is the result of a sample preparation step involving a spin column. However,

replication of the Bowers preparation method, using recombinant Aβ(1-42) in place of

FMOC synthetic Aβ(1-42), did not yield a useable sample [16]. In addition, the Bowers

group do not include a pre-treatment step such as HFIP treatment to deseed the sample,

this provides an explanation for the higher order aggregates observed. TWIMS experiments

probing the effect of salt concentration demonstrate a correlation between higher salt

concentration and the formation of more compact, solvent-free conformations. Again, the

choice of ionisation polarity and the location of the respective charged groups influences

the gas phase conformers observed.

The combination of the fragmentation techniques, CID, ETD and SID with MS and IM-MS

enable the investigation of the gas phase structures exhibited by the Amyloid-β peptides.

CIU-TWIMS of Aβ(1-42) highlights the destabilising effect of the change of buffer between

H2O (pH 2) and 20 mM AmAc (pH 7.4). The greater fragmentation observed at low pH is

hypothesised to be the result of a destabilisation of intramolecular interactions. The lack of

fragmentation observed following ETD suggests that Aβ(1-42) adopts a compact structure

bound by strong intramolecular interactions. This is confirmed by the ETcaD experiments,

which disrupt the non-covalent interactions of Aβ(1-42) enabling the detection of ETD

specific fragments. The observation of CID specific fragment ions, the location of which

concurs with the CID fragments observed during CIU-TWIMS experiments, are by-products

of the ETcaD process and can be reduced with further optimisation of the ETcaD process.

SID has a vastly different fragmentation mechanism to CID and ETD. Despite the presence

of the N-terminal basic residue cluster hampering fragmentation in this region, the

different fragmentation channels of SID and CID are observed. It is also possible to observe

a link to precursor structure, on the basis of the lack of fragmentation observed from the

198

central region of Aβ(1-42) and the greater sequence coverage observed following SID of

Aβ(1-40), known to feature fewer intramolecular interactions and to adopt a more flexible

conformation. SID-TWIMS of Aβ(1-42) and Aβ(1-40) fragment ions present vastly different

ATD profiles and it is possible to correlate the changes observed in the ATDs with known

intramolecular interactions and highlight the different structures and interactions of the

two proteins. Building on this work, the next steps for the SID-TWIMS work include a CCS

calibration to enable fragment ion CCS calculation and investigating the effect of ionisation

polarity.

Finally, the binding of the anti-aggregation peptide, RI-OR2 to Aβ(1-42) is observed via MS

and building on this, TWIMS demonstrates the anti-aggregation properties of RI-OR2 stem

from either the compaction of Aβ(1-42) or via holding the protein in an extended

conformation. In contrast, TWIMS demonstrates that the anti-aggregation properties of

rutin result solely from compaction of the protein. There is a wide scope for further TWIMS

profiling work and it should be expanded to investigate the effect of longer term incubation

on Aβ(1-42) and Aβ(1-40) protein structure and other drug candidates. In addition, the

effect of rutin binding on other amyloidogenic proteins such as α-Synuclein should be

investigated to determine whether the method of action is conserved.

MS and IM-MS based methods including ECD-FT-ICR MS, HDX-MS and SID-TWIMS are

genuine alternatives to the traditional biophysical methods of studying protein structure.

IDPs are challenging targets for structural analysis via traditional methods. This is

complicated further when the target is prone to aggregation, a process which generates a

diverse range of species, often presenting a range of structures. The unbiased and rapid

nature of analysis and the ability to study all species present simultaneously make MS and

IM-MS the methods of choice for investigating the structure of the wide range of species

present during the aggregation cascade.

199

6.2. References





5. Trexler, A.J. and E. Rhoades, Single Molecule Characterization of alpha-Synuclein in Aggregation-Prone States. Biophysical Journal, 2010. 99(9): p. 3048-3055.

6. Bertoncini, C.W., et al., Release of long-range tertiary interactions potentiates aggregation of natively unstructured alpha-synuclein. Proceedings of the National Academy of Sciences of the United States of America, 2005. 102(5): p. 1430-1435.

7. Krasnoslobodtsev, A.V., et al., alpha-Synuclein Misfolding Assessed with Single Molecule AFM Force Spectroscopy: Effect of Pathogenic Mutations. Biochemistry, 2013. 52(42): p. 7377-7386.




11. Mason, R.J., et al., Copper Binding and Subsequent Aggregation of alpha-Synuclein Are Modulated by N-Terminal Acetylation and Ablated by the H50Q Missense Mutation. Biochemistry, 2016. 55(34): p. 4737-4741.



14. Ray, C. and B.B. Akhremitchev, Conformational heterogeneity of surface-grafted amyloidogenic fragments of alpha-synuclein dimers detected by atomic force microscopy. Journal of the American Chemical Society, 2005. 127(42): p. 14739-14744.

15. Neupane, K., et al., Diverse Metastable Structures Formed by Small Oligomers of alpha-Synuclein Probed by Force Spectroscopy. Plos One, 2014. 9(1).


200

Appendices

This chapter contains supplementary information and data to support conclusions proposed

in previous chapters. This chapter also contains details of all species observed during mass

spectrometry experiments presented in the previous chapters.

201

Appendix 1 - Amino Acid Abbreviations

Table A1.1 lists the abbreviations, structure, characteristics and molecular weights

of the 20 common amino acids.

Table A1.1 - Amino acid structures and properties [1, 2].

Aspartic Acid Asp / D

Glutamic Acid Glu / E

Acidic C4H5NO3

Acidic C5H7NO3

M: 115.027 A: 115.087

M: 129.043 A: 129.114

Lysine Lys / K

Arginine Arg / R

Basic C6H12N2O

Basic C6H12N40

M: 128.095 A: 128.172

M: 156.101 A: 156.186

Histidine His / H

Asparagine Asn / N

Basic C6H7N3O

Polar C4H6N2O2

M: 137.059 A: 137.139

M: 114.043 A: 114.103

Glutamine Gln / Q

Serine Ser / S

Polar C5H8N2O2

Polar C3H5NO2

M: 128.059 A: 128.129

M: 87.032 A: 87.077

Threonine Thr / T

Tyrosine Tyr / Y

Polar C4H7NO2

Polar/Hydrophobic C9H9NO2

M: 101.048 A: 101.104

M: 163.063 A: 163.173

202

Alanine Ala / A

Valine Val / V

Nonpolar/Hydrophobic C3H5NO


M: 71.037 A: 71.078

M: 99.068 A: 99.131

Leucine Leu / L

Isoleucine Ile / I



M: 113.084 A: 113.158

M: 113.084 A: 113.158

Proline Pro / P

Phenylalanine Phe / F

Nonpolar C5H7NO


M: 97.053 A: 97.115

M: 147.068 A: 147.174

Methionine Met / M

Tryptophan Trp / W

Nonpolar C5H9NOS

Nonpolar/Hydrophobic C11H10N2O

M: 131.040 A: 131.196

M: 186.079 A: 186.210

Glycine Gly / G

Cysteine Cys / C

Nonpolar C2H3NO

Nonpolar C3H5NOS

M: 57.021 A: 57.051

M: 103.009 A: 103.143

203

Appendix 2 – Investigating the Structure of α-Synuclein

Due to the wide CSDs and the range of oligomeric species observed in the mass spectra of

α-Synuclein, only the extremes of the CSDs and species of interest have been annotated in

the figures of Chapter 3. Table A2.1 details all species observed in the figures of Chapter 3.

Table A2.2 details the experimental CCS values for α-Synuclein, used for the production of

Figures 3.7A and C.

204

Table A2.1 – Complete list of α-Synuclein species observed in Chapter 3 figures. A: monomer, B: dimer, C: trimer, D: tetramer, E: pentamer, F: hexamer, G: septamer and H: octamer.

Charge state (z)

Figure

no.

[x±3

H]3

±

[x±4

H]4

±

[x±5

H]5

±

[x±6

H]6

±

[x±7

H]7

±

[x±8

H]8

±

[x±9

H]9

±

[x±1

0H

]10

±

[x±1

1H

]11

±

[x±1

2H

]12

±

[x±1

3H

]13

±

[x±1

4H

]14

±

[x±1

5H

]15

±

[x±1

6H

]16

±

[x±1

7H

]17

±

[x±1

8H

]18

±

[x±1

9H

]19

±

[x±2

0H

]20

±

[x±2

1H

]21

±

[x±2

2H

]22

±

[x±2

3H

]23

±

[x±2

4H

]24

±

[x±2

5H

]25

±

[x±2

6H

]26

±

[x±2

7H

]27

±

[x±2

8H

]28

±

[x±2

9H

]29

±

[x±3

0H

]30

±

[x±3

1H

]31

±

[x±3

2H

]32

±

[x±3

3H

]33

±

[x±3

4H

]34

±

[x±3

5H

]35

±

3.1/3.2C

3.2A

3.2B

3.3

3.4

3.5

3.6

3.7B

3.10(top)

3.10(bot)

205

Table A2.2 – Experimental CCS values for α-Synuclein (70 µM, 50 mM AmAc, pH 6.8) collected in

positive ionisation mode. * CCS value is the product of two or fewer repeats.

Monomer Dimer

Charge state

(z)

Average CCS

(Å2)

Standard

Deviation

Charge state

(z)

Average CCS

(Å2)

Standard

Deviation

5 937.53*

11

2196.38*

1168.88 117.72 2286.60 76.77

6

1040.56* 2610.29* 39.07

1256.19 93.10 2816.74*

1474.62 111.63

13

2322.08* 80.46

7 1380.76 87.47 2583.86 36.96

1475.66 124.31 2792.18* 136.31

8 1381.03 17.87

15

2614.92 94.59

1490.29 25.60 2868.00 103.00

9 1402.72 25.20 3032.96 163.08

1630.95 81.96

17

2607.62 155.13

10 1486.41 63.87 3068.10 146.28

1751.19 47.56 3407.70 90.70

11 1675.26 81.85

19

2952.39 124.29

2014.85 67.78 3493.55 34.87

12 1698.10 31.17 3741.71 43.53

2313.64 210.45

21

2927.58 249.13

13

1902.42* 3413.47 470.38

2297.16 125.91 4009.22 222.38

2584.92 78.87

23

3250.67 70.73

14

2125.14* 3724.16 188.47

2247.87 45.02 4205.86 196.17

2628.71 43.68

15

2455.31 176.25

2767.84 47.33

16 2677.50 70.30

2872.25 194.45

206


Due to the wide CSDs and the range of oligomeric species observed only the extremes of

the CSDs and species of interest have been annotated in the figures of Chapter 4. Table

A3.1 details the species observed in the figures of Chapter 4.

Table A3.2 details the species observed in the figures of Appendix 3.

207

Table A3.1 – Complete list of α-Synuclein species observed in Chapter 4 figures. A: monomer, B: dimer, C: trimer, D: tetramer, E: pentamer, F: hexamer, G: septamer and H:

octamer.

Charge state (z)

Figure

no.

[x+3

H]3

+

[x+4

H]4

+

[x+5

H]5

+

[x+6

H]6

+

[x+7

H]7

+

[x+8

H]8

+

[x+9

H]9

+

[x+1

0H

]10

+

[x+1

1H

]11

+

[x+1

2H

]12

+

[x+1

3H

]13

+

[x+1

4H

]14

+

[x+1

5H

]15

+

[x+1

6H

]16

+

[x+1

7H

]17

+

[x+1

8H

]18

+

[x+1

9H

]19

+

[x+2

0H

]20

+

[x+2

1H

]21

+

[x+2

2H

]22

+

[x+2

3H

]23

+

[x+2

4H

]24

+

[x+2

5H

]25

+

[x+2

6H

]26

+

[x+2

7H

]27

+

[x+2

8H

]28

+

[x+2

9H

]29

+

[x+3

0H

]30

+

[x+3

1H

]31

+

[x+3

2H

]32

+

[x+3

3H

]33

+

[x+3

4H

]34

+

[x+3

5H

]35

+

4.1A

4.1B

4.1C

4.3A

4.3B

4.3C

4.3D

4.3E

4.3F

4.3G

4.3H

4.4

208

Table A3.2 – Complete list of α-Synuclein species observed in Appendix 3 figures. A: monomer, B: dimer, C: trimer, D: tetramer, E: pentamer, F: hexamer, G: septamer and H: octamer.

Charge state (z)

Figure no.

[x+3

H]3

+

[x+4

H]4

+

[x+5

H]5

+

[x+6

H]6

+

[x+7

H]7

+

[x+8

H]8

+

[x+9

H]9

+

[x+1

0H

]10

+

[x+1

1H

]11

+

[x+1

2H

]12

+

[x+1

3H

]13

+

[x+1

4H

]14

+

[x+1

5H

]15

+

[x+1

6H

]16

+

[x+1

7H

]17

+

[x+1

8H

]18

+

[x+1

9H

]19

+

[x+2

0H

]20

+

[x+2

1H

]21

+

[x+2

2H

]22

+

[x+2

3H

]23

+

[x+2

4H

]24

+

[x+2

5H

]25

+

[x+2

6H

]26

+

[x+2

7H

]27

+

[x+2

8H

]28

+

[x+2

9H

]29

+

[x+3

0H

]30

+

[x+3

1H

]31

+

[x+3

2H

]32

+

[x+3

3H

]33

+

[x+3

4H

]34

+

[x+3

5H

]35

+

A3.1A

A3.1B

A3.1C

A3.3A

A3.3B

A3.3C

A3.3D

A3.3E

A3.3F

A3.3G

A3.3H

A3.4A-H

209

Appendix 3.1 - Following Aggregation via Mass Spectrometry

Figure A3.1 are the mass spectra of the 0 hour, 72 hour and 96 hour time points of a 96

hour in vitro α-Synuclein aggregation time course, normalised to the base peak intensity of

the 0 hour spectrum, collected using a cone voltage of 60 V. Instrument parameters and

source conditions are as detailed in Table 2.1. The TIC decreases as the time course

progresses, this is indicative of aggregation.

Figure A3.1 - α-Synuclein MS aggregation time course with an instrument cone voltage of 60 V normalised to the 0 hour spectrum base peak intensity. A. 0 hours, B. 72 hours C. 96 hours. See

Appendix Table A3.2 for a list of all species observed.

500 1000 1500 2000 2500 3000 3500 4000

500 1000 1500 2000 2500 3000 3500 4000

500 1000 1500 2000 2500 3000 3500 4000

500 1000 1500 2000 2500 3000 3500 4000

500 1000 1500 2000 2500 3000 3500 4000

m/z

A

B

C

1000 2000 3000 4000

1000 2000 3000 4000

1000 2000 3000 4000

m/z

210

Appendix 3.2 - In Tip Aggregation

Figure A3.2 is a microscope image of the nESi tip used for the in tip aggregation experiment

shown in Figure 4.3 and Appendix Figure A3.3. Aggregates are clearly visible at the end of

the nESI tip.

Figure A3.2 - Microscope image of the nESI tip used to spray the sample recorded in Figure 4.3 and Figure A3.3

Figure A3.3 are the mass spectra of Figure 4.3 normalised to the base peak of the 0-5

minute spectrum. Experimental parameters are as described for Figure 4.3. Species

observed are detailed in Table A3.2. It is clear that with time course progression the TIC

decreases.

Figure A3.4 are the mass spectra of a second α-Synuclein in tip aggregation experiment.

Instrument parameters are as described for Figure 4.3. Species observed are detailed in

Table A3.2. In contrast to Figure 4.3, with time course progression the observed CSDs do

not narrow and tetrameric species are not observed. The spectra are normalised to the

base peak of Figure A3.4A, general intensity fluctuates but does not significantly decrease

as observed in Figure A3.3.

211

Figure A3.3 – α-Synuclein in tip aggregation time course spectra (Figure 4.3), normalised to the 0-5 minute spectrum base peak intensity. See Appendix Table A3.2 for a list of all species observed. Note the depletion of species intensity with time course progression.

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

A B C

D E F

G H

0-5

min

20

-25

min

60

-65

min

30

-35

min

40

-45

min

50

-55

min

70

-75

min

10

-15

min

212

Figure A3.4 – α-Synuclein in tip aggregation time course replicate spectra, normalised to the 0-5 minute spectrum base peak intensity. The widths of the CSDs are highlighted. See Appendix Table A3.2 for a list of all species observed. Note the persistent CSD width throughout the time course.

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

500 1000 1500 2000 2500 3000 3500 4000

m/z

0-5

min

20

-25

min

60

-65

min

30

-35

min

40

-45

min

50

-55

min

70

-75

min

10

-15

min

monomerdimer

trimer

Charge State Distribution

A B C

D E F

G H

213

Appendix 3.3 - Probing Conformational Changes during Aggregation by HDX-MS.

Figure A3.5 and A3.6 are plots of α-Synuclein peptide RFU at the 0 hour and 120 hour time

points of the α-Synuclein HDX time course analysed in the same DynamX file (A3.5) and

independently (A3.6). Experimental parameters are as described in Section 2.11 and Table

2.4. There is a clear averaging effect incurred through analysing both aggregation time

points within the same DynamX file.

Figure A3.5 – Plot of the α-Synuclein peptides RFU at the 0 hour and 120 hour time points analysed together within DynamX.

Figure A3.6 – Plot of the α-Synuclein peptides RFU at the 0 hour and 120 hour time points analysed independently within DynamX.

214


Table A4.1 is a list of all Aβ(1-42), bound complexes and small molecule drug candidate

species observed in the figures of Chapter 5.

Table A4.2 is a list of all Aβ(1-42), bound complexes and small molecule drug candidate

species observed in the figures of Appendix 4.

Table A4.1 – Complete list of all Aβ(1-42), bound complexes and small molecule drug candidate species observed in Chapter 5 figures.

5

.1A

5.1

B

5.1

C

5.1

D

5.1

E

5.1

F

5.7

A

5.7

B

5.7

C

5.7

D

5.7

E

5.7

F

5.1

7A

5.1

7B

5.1

7C

5.1

7D

5.1

7E

[Aβ42±H]1± X X X

[Aβ42±2H]2± X X X X

[Aβ42±3H]3± X X X X X X X X X X X X X

[Aβ42±4H]4± X X X X X X X X X X X X X X X

[Aβ42±5H]5± X X X X X X X X

[Aβ42±6H]6± X X X X X

[(Aβ42)2±5H]5± X X

[(Aβ42)2±7H]7± X X X X

[(Aβ42:RI-OR2)+4H]4+ X X X X

[RI-OR2+2H]2+ X X X X

[RI-OR2+3H]3+ X X X X

Table A4.2 – Complete list of all Aβ(1-42), bound complexes and small drug molecule candidate species observed in Appendix 4 figures.

A4

.1A

A4

.1B

A4

.1C

A4

.2A

A4

.2B

A4

.9A

A4

.9B

A4

.9C

A4

.9D

A4

.9E

A4

.19

A

A4

.19

B

A4

.19

C

[Aβ42±H]1±

[Aβ42±2H]2± X

[Aβ42±3H]3± X X X X X X X X X X X X X

[Aβ42±4H]4± X X X X X X X X X X X X

[Aβ42±5H]5± X X X X X X X X X

[Aβ42±6H]6± X X X X X X X

[(Aβ42)2±5H]5± X X

[(Aβ42)2±7H]7± X X

[(Aβ42:BK)+3H]3+ X X

[(Aβ42:BK)+4H]4+ X X X

[(Aβ42:Rutin)-4]4- X

[BK+H]1+ X X X

[BK+2H]2+ X X X X

[Rutin+H]1+ X X

215

Appendix 4.1 - The Effect of Concentration, Solution Conditions and Ionisation

Polarity

Figure A4.1 are mass spectra of Aβ(1-42) in H2O (pH 2), collected on different instruments

and under different source conditions but using the same source sample. Instrument

parameters and solution conditions are detailed in Table A4.3, in addition to Chapter 2

Table 2.4. The species observed are detailed in Table A4.2. The spectra in Figure A4.1

demonstrate that the observed CSD width does not alter dramatically between instruments

and source conditions tuned on both instruments to preserve native structure. Day to day

variation previously observed in the spectra of IDPs can be observed by comparison of

Figure A4.1A and A4.1B, which despite the application of very similar source conditions

display a shift in the intensity distribution towards higher charged monomers, as well as the

observation of the lower charged [Aβ42+2H]2+ species. The most intense species shifts to

[Aβ42+4H]4+ in Figure A4.1C; however, the CSD width is the same as Figure A4.1A, despite

the use of a different instrument and different source conditions.

Table A4.3 - Instrument parameters and solution conditions applied during collection of the spectra in Figure A4.1A to 4.1C.

Figure number

Solution conditions A4.1A A4.1B A4.1C

pH 2 2 2

Buffer H2O H2O H2O

Instrumental parameters

Instrument Synapt G2 Synapt G2 Synapt G2Si

Ionisation polarity Positive Positive Positive

Capillary voltage (kV) 1.7 1.6 1.54

Cone voltage (V) 40 40 20

Extractor Cone voltage/ offset (V) 1.4 1.4 80

Source temperature (°C) 80 80 80

216

Figure A4.1 – Aβ(1-42) mass spectra in H2O (pH 2) collected using different instruments and using different source conditions, see Table A4.3.

Figure A4.2 are mass spectra of Aβ(1-42) in 20 mM AmAc (pH 7.4) collected on different

instruments using the same source sample. The experimental parameters applied are

detailed in Table A4.4, in addition to Chapter 2 Table 2.4. The species observed are detailed

in Table A4.2. [Aβ42+4H]4+ remains the most intense species; however, it is possible to

observe [Aβ42+5H]5+ with a modification to the source parameters.

217

Table A4.4 - Instrument parameters and solution conditions applied during the collection of the spectra in Figure A4.2.

Figure number

Solution conditions A4.2A A4.2B

pH 7.4 7.4

Buffer 20 mM AmAc 20 mM AmAc

Instrumental parameters

Instrument Synapt G2Si Synapt G2

Ionisation polarity Positive Positive

Capillary voltage (kV) 1.44 1.69

Cone voltage (V) 15 40

Extractor cone voltage / offset (V) 45 0.6

Source temperature (°C) 80 80

Figure A4.2 – Aβ(1-42) mass spectra in 20 mM AmAc (pH 7.4) collected under different source conditions and on different instruments.

Appendix 4.2 - Conformational Stability of Aβ(1-42) probed by CIU-TWIMS

Figure A4.3 and A4.4 are the ATDs of [Aβ42+4H]4+ and [Aβ42+3H]3+in H2O (pH 2) and 20 mM

AmAc following application of increasing collision voltage. Experimental details can be

found in Chapter 5 Section 5.2.3 in addition to Chapter 2 Table 2.4. Two conformers are

observed for both charge states under both solution conditions. As the collision voltage is

raised, there is no observable modification to the ATD and the precursor is depleted. The b-

218

and y- fragment ions generated from the [Aβ42+4H]4+ are shown in Chapter 5 Figure 5.5

and 5.6.

Figure A4.3 – CIU-TWIMS ATDs of [Aβ42+4H]4+ and [Aβ42+3H]3+ in H2O (pH 2) at increasing collision voltage.

Figure A4.4 – CIU-TWIMS ATDs of [Aβ42+4H]4+ and [Aβ42+3H]3+ in 20 mM AmAc (pH 7.4) at increasing collision voltage.

219

Appendix 4.3 – Surface Induced Dissociation

Appendix 4.3.1 - Preparation of the SID Surface

A single SID surface prepared as per the method in [3] was used for all SID experiments. The

gold surface slides (EMF Corp. 17x13x0.5mm, 1000 Å of gold on 50 Å titanium on glass) and

1H,1H,2H,2H-Perfluorododecanethiol (FC12) was provided by Professor Vicki Wysocki, Ohio

State University. Ethanol was purchased from Sigma Aldrich, UK or Fisher Scientific, UK.

Using high precision, anti-magnetic stainless steel fine tweezers (TAAB, Aldermaston, UK) a

gold surface slide was cleaned in ethanol and dried thoroughly under a nitrogen stream.

The surface was then placed under a UV cleaner for 15 minutes prior to submersion, gold

surface up, in a beaker of 1 mM FC12. The vial was wrapped in aluminium foil and incubated

for 24 hours at room temperature. Prior to installation, the surface was cleaned by

sonicating in ethanol for 1 minute. This process was repeated six times, using fresh ethanol

for each wash. The surface was then installed in the Surface holder and inserted into the

SID cell prior to installation.

Appendix 4.3.2 - Effect of SID on the Conformation Exhibited by Amyloid species

Figure A4.5 is the ATDs of b- fragment ions observed during the CIU-TWIMS experiment.

Experimental parameters applied can be found in Chapter 5 Section 5.2.3 in addition to

Chapter 2 Table 2.4. Two conformers are observed for [Aβ42+4H]4+ in contrast to a single

conformer observed in Figure 5.2. This may be the result of the different instrumental

conditions applied or a result of the previously observed day to day variation. Interestingly,

an additional later arriving conformer is observed in the [b36+4H]4+ and [b35+4H]4+ fragment

ion ATDs, as observed in the ATDs of the same b- fragment ions generated by SID. The ATDs

are noticeably less defined, the result of much lower signal intensity. The signal intensity of

the other C-terminal b- fragment ions was too low to generate ATDs.

220

Figure A4.5 - ATDs of [Aβ42+4H]4+ b- fragment ions in 20 mM AmAc (pH 7.4), observed during CIU-TWIMS experiment. Collision voltage: 40 V.

221

Figure A4.6 and A4.7 are the ATDs of the charge reduced C-terminal fragment ions

observed following SID of [Aβ42+4H]4+ and [Aβ40+4H]4+. Experimental parameters can be

found in Chapter 5 Section 5.2.5 in addition to Chapter 2 Table 2.4 and 2.7. The ATDs of the

fragments of both the charge reduced [Aβ42+3H]3+ and [Aβ40+3H]3+ and their fragments

present a single conformer, with the exception of the [b39+3H]3+ and [b38+3H]3+ b- fragment

ions of [Aβ40+3H]3+, in contrast to the multiple conformers present in the ATDs of the b-

fragment ions of [Aβ42+4H]4+ and [Aβ40+4H]4+.

Figure A4.6 - C-terminal SID b- fragment ion ATDs of the charge reduced [Aβ42+3H]3+ (20 mM AmAc, pH 7.4). SID collision voltage: 40 V.

222

Figure A4.7 - C-terminal SID b- fragment ion ATDs of the charge reduced [Aβ40+3H]3+ (20 mM AmAc, pH 7.4). SID collision voltage: 40 V.

223

Appendix 4.3.3 - The Absence of Precursor Activation by SID

Figure A4.8 are the ATDs of the selected precursor ions following the application of

increasing SID collision voltage. There is no modification to the ATD with increasing collision

voltage for either [Aβ42+4H]4+ or [Aβ40+4H]4+ due to the high energy, single step

deposition mechanism of SID compared to the slow heating, multiple collision mechanism

of CID.

Figure A4.8 - ATDs of the isolated [Aβ42+4H]4+ (A to E) and [Aβ40+4H]4+ (F to J) precursor ions in 20 mM AmAc (pH 7.4), following the application of increasing SID collision voltage.

Appendix 4.4 - The Interactions of Aβ(1-42) with Small Molecule Anti-Aggregation

Drug Candidates

The mass spectra of Aβ(1-42) in the presence of an increasing ratio of Bradykinin (BK) are

shown in Figure A4.9. Experimental parameters can be found in Chapter 5 Section 5.2.3 in

addition to Chapter 2 Table 2.4. As the ratio of Aβ(1-42) to Bradykinin is increased, the

intensity of the Aβ(1-42):Bradykinin bound species increases, see Figure A4.9B to A4.9E. In

contrast to RI-OR2, a much higher ratio of protein:ligand is required to observe the

224

complex, 0.5 compared to 0.1, see Chapter 5 Figure 5.17. At a ratio of 1:0.5 to 1:2, the

unbound [BK+2H]2+ is the most abundant species. As the protein:ligand ratio is increased to

1:2, the intensity of the bound complex decreases and the Aβ(1-42) dimer species are no

longer observed. This is likely the result of ion suppression due to the preferential

ionisation of bradykinin.

Figure A4.9 - Aβ(1-42) mass spectra at increasing Aβ(1-42):Bradykinin ratio in H2O (pH 2). Observed species are annotated in the first instance and labelled oligomeric order / charge. Marker denotes

species and oligomeric order. Red triangle: Bradykinin, Green square: Aβ(1-42) monomer, Blue square: Aβ(1-42) dimer, Yellow circle: Aβ(1-42):Bradykinin bound species. (inset) Zoom of regions of

interest, required due to the high intensity unbound ligand species.

Instrument source parameters were tuned to maximise the intensity of the bound species

during Aβ(1-42) binding studies. The source conditions applied differ between ligands and

are detailed in Table A4.5 in addition to the instrument parameters detailed in Chapter 2

Table 2.4 and 2.5.

225

Table A4.5 – Instrument parameters and solution conditions used for Aβ(1-42) binding experiments.

Ligand

RI-

OR

2

Bra

dyk

inin

Bra

dyk

inin

Ru

tin

Ru

tin

Ru

tin

pH 2 2 7.4 2 7.4 7.4

Buffer H2O H2O 20 mM AmAc

H2O 20 mM AmAc

20 mM AmAc

Instrument parameters

Instrument Synapt

G2 Synapt

G2Si Synapt

G2Si Synapt

G2 Synapt

G2S Synapt

G2S

Ionisation Polarity + + + + + -

Capillary voltage (kV) 1.70 1.57 1.40 1.54 1.80 1.57

Cone voltage (V) 40 20 15 20 30 30

Extractor Cone voltage/ offset (V)

1.4 80 45 80 75 60

Source temperature (°C) 80 80 80 80 80 80

Helium gas flow (mL/min)

180 120 120 120 120 120

IMS gas flow (mL/min) 90 60 60 60 60 60

Wave height (V) 40 40 25 40 40 20

Wave velocity (m/s) 800 900 900 900 800 475

Figure A4.10 is the ATDs and calculated CCS of [Aβ42+4H]4+ and [Aβ42+3H]3+ in the absence

and the presence of RI-OR2, Rutin and Bradykinin at a 1:1 ratio in H2O (pH 2), collected in

positive ionisation mode. Figure A4.11A to H are the ATDs and calculated CCS [Aβ42+4H]4+

and [Aβ42+3H]3+ in the absence and the presence of Rutin and Bradykinin at a 1:1 ratio in

20 mM AmAc (pH 7.4), collected in positive ionisation mode. Figure A4.11I to L are the ATDs

of [Aβ42-4H]4- and [Aβ42-3H]3- in the absence and presence of Rutin at a ratio of 1:5 in 20

mM AmAc (pH 7.4), collected in negative ionisation mode. In all cases, the presence of the

ligand in solution does not have an observable effect on the ATD or the calculated CCS of

[Aβ42±4H]4± and [Aβ42±3H]3±. Interestingly, a single conformer is observed for [Aβ42+3H]3+

in contrast to the two conformers previously observed, see Chapter 5 Figure 5.2. This may

be the result of the instrument parameters applied to observe the bound species being

unable to separate the two conformers, as the calculated CCS is bracketed by the two

conformers observed in Figure A4.11G. In addition, two conformers are observed for

[Aβ42-4H]4- in contrast to the single conformer observed in Chapter 5 Figure 5.3, this may

also be a result of the instrument parameters applied.

226

Figure A4.10 – ATDs and calculated CCS values of the unbound Aβ(1-42) [Aβ42+4H]4+ and [Aβ42+3H]3+ charge states in the absence and presence of RI-OR2/ Rutin/ Bradykinin at a 1:1 ratio in

H2O (pH 2).

Figure A4.11 – ATDs and calculated CCS values of the unbound Aβ(1-42) [Aβ42±4H]4± and [Aβ42±3H]

3± charge states in the absence and presence of Rutin or Bradykinin at 1:1 (Aβ(1-42) and

Rutin, negative ionisation mode: ratio 1:5) in 20 mM AmAc (pH 7.4).

TWCCSN2TWCCSN2

TWCCSN2

635 Å2

635 Å2

566 Å2

566 Å2

589 Å2

592 Å2

643 Å2

648 Å2

646 Å2

644 Å2

568 Å2

573 Å2

588 Å2

593 Å2

571 Å2

571 Å2

588 Å2

591 Å2

[Aβ42+4H]4+ [Aβ42+4H]4+[Aβ42+4H]4+

[Aβ42+3H]3+[Aβ42+3H]3+[Aβ42+3H]3+

[Aβ42+3H]3+

in presence of RI-OR2[Aβ42+3H]3+

in presence of Rutin[Aβ42+3H]3+

in presence of BK

[Aβ42+4H]4+

in presence of BK

[Aβ42+4H]4+

in presence of Rutin[Aβ42+4H]4+

in presence of RI-OR2

A

B

C

D

E

F

G

H

I

J

K

L

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

Drift time (ms) Drift time (ms) Drift time (ms)

TWCCSN2TWCCSN2

642 Å2

642 Å2

574 Å2

574 Å2

642 Å2

642 Å2

572 Å2

573 Å2

593 Å2

594 Å2

[Aβ42+4H]4+ [Aβ42-4H]4-[Aβ42+4H]4+

[Aβ42-3H]3-[Aβ42+3H]3+[Aβ42+3H]3+

[Aβ42+3H]3+

in presence of Rutin

[Aβ42+3H]3+

in presence of BK

[Aβ42-3H]3-


[Aβ42-4H]4-


[Aβ42+4H]4+

in presence of BK[Aβ42+4H]4+


A

B

C

D

E

F

G

H

I

J

K

L

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

0 5 10 15 20

Drift time (ms) Drift time (ms) Drift time (ms)

227

Figure A4.12 are the ATDs and calculated CCS values for [(Aβ42:BK)+4H]4+ in H2O (Figure

A4.12A) and 20 mM AmAc (Figure A4.12B), collected in positive ionisation mode. Both

bound species present extended conformers.

Figure A4.12 - ATDs and calculated CCS values of [(Aβ42:Bradykinin)+4H]4+ at a ratio of 1:1 in H2O (pH 2) or 20 mM AmAc (pH 7.4), collected in positive ionisation mode.

To aid comparison between bound and unbound species, the CCS values of the unbound

ligand species have been calculated. Experimental parameters for all ligands are as used for

the bound and unbound species and can be found in Chapter 5 Section 5.2.3, Chapter 2

Table 2.4 and in Appendix Table A4.5. CCS values are calculated as described in Section

2.6.2.1 [4-6]. Figure A4.13 is the ATD and calculated CCS value for the [RI-OR2+2H]2+ species

in H2O (pH 2). The ATD displays a single narrow intensity distribution, which highlights the

lack of conformational diversity of the RI-OR2 peptide.

Figure A4.13 – The ATD and calculated CCS value of [RI-OR2+2H]2+ in H2O (pH 2) collected in positive ionisation mode.

228

Figure A4.14 is the ATD and calculated CCS for [BK+H]1+ in H2O (pH 2). A single conformer is

present with a calculated CCS of 231 Å2. Figure A4.15 are the ATDs and calculated CCSs for

[BK+H]1+ and [BK+2H]2+ in 20 mM AmAc (pH 7.4). A single conformer is observed for both

charge states. The calculated CCS of 217 Å2 for [BK+H]1+ in AmAc (pH 7.4) is slightly smaller

than in H2O (pH 2). As expected, [BK+2H]2+ has a larger CCS of 251 Å2.

Figure A4.14 – The ATD and calculated CCS value of [BK+H]1+ in H2O (pH 2) collected in positive ionisation mode.

Figure A4.15 - The ATD and calculated CCS values of [BK+H]1+ and [BK+2H]2+ in 20 mM AmAc (pH 7.4) collected in positive ionisation mode.

Figure A4.16 and A4.17 are the ATDs and calculated CCS values of [Rutin+H]1+ in H2O (pH 2)

and 20 mM AmAc (pH 7.4), respectively. Both ATDs feature a single narrow peak and the

calculated CCSs are 170 Å2 and 169 Å2, respectively. The alteration of solution conditions

does not result in a observable modification to the ATD or the calculated CCS value.

229

Figure A4.16 – The ATD and calculated CCS value of [Rutin+1H]1+ in H2O (pH 2) collected in positive ionisation mode.

Figure A4.17 – The ATD and calculated CCS value of [Rutin+1H]1+ in 20 mM AmAc (pH 7.4) collected in positive ionisation mode.

The ATD of [(Aβ42:Rutin)+4H]4+ in Figure 5.19C, features a single peak for the bound species

and a shoulder. Figure A4.18 is the mass spectra of the bound species and the ATDs of two

peaks of the isotopic distribution and their respective shoulders. The ATDs of both peaks

from the isotopic distribution feature a dominant peak and a low intensity satellite peak.

The ATDs of the shoulders of the peaks selected from the isotopic distribution, do not

feature the bound species peak but feature the previously observed shoulder peak species.

This demonstrates that the shoulder observed in Figure 5.19C, is the result of a m/z

coincident contaminant species and not the result of an extended conformer of the Aβ(1-

42):Rutin bound species.

230

Figure A4.18– Mass spectra and ATDs of the main and shoulders of isotopic peaks of the Aβ(1-42): Rutin bound species in Figure 5.19C. The coloured regions of the zoom of the mass spectra

correspond to the coloured ATDs.

Figure A4.19 are mass spectra of Aβ(1-42) in the absence (Figure A4.19A) and presence

(A4.19B and C) of Rutin at a ratio of 1:5 in 20 mM AmAc (pH 7.4), collected in negative

ionisation mode. The CSD of Figure A4.19A is similar to that observed previously, see

Chapter 5 Figure 5.1F. Figure A4.19B is the mass spectrum acquired in the presence of

rutin, the complex is very low intensity and required mass selection with a longer

acquisition time of 20 minutes (Figure A4.19C).

Figure A4.19 - Aβ(1-42) (20 mM AmAc, pH 7.4) in the absence (A) and presence (B & C) of Rutin at a 1:5 ratio, collected in negative ionisation mode. (inset) Zoom of region of interest, required due to high intensity unbound species. Species are labelled oligomeric order/ charge. The marker denotes

species. Red triangle: Rutin unbound, Green square: Aβ(1-42) monomer and Yellow circle: Aβ(1-42):Rutin bound species.

231

References

1. Alberts, B., et al., Molecular biology of the cell. 5th ed. 2008, Abingdon, UK: Garland Science.

2. Science, M. Amino acid reference data. 2016 [cited 2016 12/07/2016]; Available from: http://www.matrixscience.com/help/aa_help.html.

3. Group, W., Installation Guide for Incorporating SID Device into Synapt Instruments. 2014.


5. Bush, M.F., et al., Collision Cross Sections of Proteins and Their Complexes: A Calibration Framework and Database for Gas-Phase Structural Biology. Analytical Chemistry, 2010. 82(22): p. 9557-9565.

6. Bush, M.F., I.D.G. Campuzano, and C.V. Robinson, Ion Mobility Mass Spectrometry of Peptide Ions: Effects of Drift Gas and Calibration Strategies. Analytical Chemistry, 2012. 84(16): p. 7124-7130.

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