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Mass spectrometry- based proteomics Jeff Johnson Feb 19, 2014

Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

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Page 1: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Mass spectrometry-based proteomics

Jeff JohnsonFeb 19, 2014

Page 2: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MS Proteomics in a Nutshell

• Ionization– Delivering macromolecules to the MS

• Ion Manipulation– Trapping and ejecting analytes of interest

• Fragmentation– Breaking apart for more information

• Mass analysis and detection– Measuring masses and quantifying intensities

Page 3: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MS Proteomics in a Nutshell

• Ionization– Delivering macromolecules to the MS

• Ion Manipulation– Trapping and ejecting analytes of interest

• Fragmentation– Breaking apart for more information

• Mass analysis and detection– Measuring masses and quantifying intensities

Page 4: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Macromolecular Ionization for MS

• Analyte must be in the gas phase for mass analysis• Analyte must be charged in order to be

manipulated by electric and magnetic fields– All mass analyzers measure mass-to-charge ratios (m/z)

• Two predominant approaches (shared the Nobel prize in 2002)– Matrix assisted laser desorption ionization– Electrospray ionization

Page 5: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MALDI Ionization• Sample is spotted in a matrix that

readily absorbs UV/IR light and is vaporized by a laser– Common matrix: 2,5-dihydroxybenzoic

acid (DHB) • Advantages

– Fast and easy– Spots can be reanalyzed later– Most analytes get one +ive charge

makes it easy to deconvolute• Disadvantages

– Harsh. Often breaks analytes apart (e.g., breaks phosphorylation)

– Not easily combined with online HPLC separations

Page 6: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Electrospray Ionization• Sample is dissolved in liquid and pushed through

a charged needle and sprayed into an evaporation chamber

– Droplets pulled into the MS source by electric potential between the needle and the MS

– Heated ion transfer tube evaporates water molecules in droplets leaving +ively charged analytes in the gas phase

• Advantages– Compatible with online HPLC separations– “Soft” ionization maintains label and non-covalent

interactions• Disadvantages

– Analytes can have different numbers of charges, can be difficult to deconvolute without high mass accuracy

– Different samples going through the same electrospray tip causes carryover problems

• Especially bad with online HPLCs

Page 7: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Ionization is Nearly Impossible to Predict

2x

A B

A B

X

• Different molecules ionize with different efficiencies and are very difficult to predict

• MS intensity ratios between different molecules do not reflect ratios in the sample from which they were derived

• Most quantification by MS is relative

Page 8: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Ionization is Nearly Impossible to Predict

• Different molecules ionize with different efficiencies and are very difficult to predict

• MS intensity ratios between different molecules do not reflect ratios in the sample from which they were derived

• Most quantification by MS is relative

A A

A A

Sample 1 Sample 2

Sample 1 Sample 2

* Assumption: MS run 1 = MS run 2

Page 9: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MS Proteomics in a Nutshell

• Ionization– Delivering macromolecules to the MS

• Ion Manipulation– Trapping and ejecting analytes of interest

• Fragmentation– Breaking apart for more information

• Mass analysis and detection– Measuring masses and quantifying intensities

Page 10: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Ion Manipulation

• We need a way to select only ions of interest– Most detectors are just electron multipliers that don’t

measure mass but just detect a thing hitting the multiplier– We can manipulate ions to deliver defined mass ranges to

the detector to get a mass spectrum• Two common tools:

– Ion traps– Quadrupoles– Both use electric and magnetic fields to select ions of a

particular m/z range

Page 11: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Ion Trap

• Ions are trapped by 3D electric field by DC and AC applied to the electrodes

• An ion trap can accumulate ions as they come in from the source and store them

• Low resolution: +/- 1 Da

Page 12: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Quadrupole

• Can be thought as a mass filter• DC and AC fields applied that stabilize a trajectory for ions in

a desired mass range, undesired ions are ejected• Quadrupole operate with a continuous flow of ions• Low resolution (+/- 1 Da)

Page 13: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MS Proteomics in a Nutshell

• Ionization– Delivering macromolecules to the MS

• Ion Manipulation– Trapping and ejecting analytes of interest

• Fragmentation– Breaking apart for more information

• Mass analysis and detection– Measuring masses and quantifying intensities

Page 14: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Fragmentation

• Usually measuring the mass of an analyte is not enough to conclusively identify it

• By fragmenting an analyte and measuring the masses of the fragments we can obtain further information to identify the analyte

• There are many types of fragmentation but collision-induced dissociation (CID) is the most common– Fastest and most generally successful for the widest

variety of proteins and peptides

Page 15: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Collision-Induced Dissociation

• Give ions kinetic energy and collide with gas molecules (He)• Collisions build up potential energy until a fragmentation

event can occur• Ideally potential energy is strong enough to break a single

peptide bond but not strong enough to fragment further• Can be done in an ion trap or a quadrupole

Page 16: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Collision Induced Dissociation

A E P T I R H2O

Fragment (somewhat) randomly along the peptide backbone

Page 17: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

M/z

Inte

nsity

A E P

A

A E

A E P T

72.0201.1

298.1399.2

B-type Ions

Page 18: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

M/z

Inte

nsity

R I T P E AH2O

Y-type Ions

Page 19: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

M/z

Inte

nsity

R I T P E AH2O

B-type, A-type, Y-type Ions

Page 20: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

MS Proteomics in a Nutshell

• Ionization– Delivering macromolecules to the MS

• Ion Manipulation– Trapping and ejecting analytes of interest

• Fragmentation– Breaking apart for more information

• Mass analysis and detection– Measuring masses and quantifying intensities

Page 21: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Mass Analysis and Detection

Magnetic Sector MS

• All mass analyzers achieve the same thing: physical separation based on mass:charge

• Magnetic sector is the simplest and one of the earliest types

Page 22: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

FT-ICR MS

• FT-ICR = Fourier transform – ion cyclotron resonance• Ion injected in line with a strong magnetic field that

induces a cyclical motion• Radius of the cyclotron motion is proportional to m/z

Page 23: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Time-of-flight MS

Medium / High Resolution

Page 24: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Quadrupole and Ion Trap MS

Electron multiplier

• You can use a quadrupoles or ion traps to “scan out” ions across an entire mass range to a detector by gradually ramping voltages

• Low resolution but electron multipliers make these very sensitive

Page 25: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Orbitrap MS

22

R

Rmzr

12

2

R

Rmz

zm

kz /

• Characteristic frequencies:– Frequency of rotation ωφ

– Frequency of radial oscillations ωr

– Frequency of axial oscillations ωz

r

)/ln(2/2

),( 222mm RrRrz

kzrU

z

φ

Page 26: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Power of Fourier Transforms

• FTs convert from time domain to freq domain

• Instead of a single measurement the m/z is measured over a period of time and the FT essentially averages all those measurements

• Resulting data is very high resolution

Page 27: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014
Page 28: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Chromatography to Simplify Complexity

• Complexity hurts sensitivity• A constant, defined number of ions can be analyzed in

each MS scan• Sensitivity is constant (around 1 fmol)• A scan with fewer ions is more sensitive than a scan with

many

ComplexSample

MS

Page 29: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Chromatography to Simplify Complexity

C18 RP column

ACN gradient

AB

C

D

A

B

C

D

Complex Sample HPLC MS

Page 30: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Chromatography to Simplify Complexity

VeryComplexSample

Online HPLC (RP) MS

Offline HPLC(e.g., SCX) SCX Fractions

SCX FractionsInjected individually

Page 31: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Acquiring MS Data

• Data acquisition depends on experimental goals– Data-dependent acquisition

• MS attempts to acquire data to allow you to identify a maximum number of unknowns

• Commonly used for analyses where you don’t know what you’re looking for

– Targeted acquisition• MS only acquires data for what you tell it to acquire• Much more sensitive than data-dependent, but also more

limited in scope

Page 32: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Data-Dependent Acquisition

Page 33: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Data-Dependent Acquisition

High resolution survey scan(<5 ppm mass accuracy)

1

23

Page 34: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Data-Dependent Acquisition

Low resolution MS/MS scan 1

Page 35: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Data-Dependent Acquisition

Low resolution MS/MS scan 2

Page 36: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Data-Dependent Acquisition

Low resolution MS/MS scan 3

Page 37: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Peptide IdentificationAA sequence DB(Species UniProt)

Page 38: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Peptide Identification

1

2

3

AA DBsrestrictedby parent ion mass measured in survey scan

AA sequence DB(Species UniProt)

Page 39: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Peptide Identification

MS/MS 1

MS/MS 2

MS/MS 3

1

2

3

AA DBsrestrictedby parent ion mass measured in survey scan

AA sequence DB(Species UniProt)

Page 40: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Probabilistic Matching (X!Tandem)

by-Score= Sum of intensities of peaks matchingB-type or Y-type ions

HyperScore=Hyper Score

# of

Mat

ches

Best HitSecond

Best

Page 41: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Model spectrum comparisons

Page 42: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Pattern Matching (Sequest)

Page 43: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Sequest XCorr

Cross Correlation(direct comparison)

Auto Correlation(background)

XCorr =

Offset (AMU)

Corr

elati

on S

core

Page 44: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Targeted Acquisition with a QQQ

A priori knowledge required:SRM assay development for a list of proteins/peptides of interest Information derived from label-free unbiased

proteomic analysis

SRM Assay

Page 45: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

“Sensitivity”• Sensitivity of a MS is well defined, but the ability to

identify something is a very different concept– Ability to detect depends on:

• Sample complexity• MS sensitivity• MS speed

– A faster MS can collect go deeper in each survey scan– Think “top 10” vs. “top 50”

• MS mass accuracy– Better mass accuracy improves the ability to identify peptides but

sacrifices speed and MS sensitivity– Especially important for variable modifications

– The “best” method is very dependent on the experimental goals

Page 46: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Database SearchingIon trap+/- 1 Da

Orbitrap+/- 0.002 Da

Database“search space”

Page 47: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Database SearchingIon trap+/- 1 Da

Orbitrap+/- 0.002 Da

Database“search space”

+S/T/Y phosphorylation

Page 48: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Database SearchingIon trap+/- 1 Da

Orbitrap+/- 0.002 Da

Database“search space”

+S/T/Y phosphorylation

Page 49: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Protein Quantification

• A mass spectrometer is an inherently quantitative device but the ionization source is not– Different peptides/proteins are ionized with drastically

different efficiencies– Absolute abundances in a mass spectrometer are not

precisely indicative of abundance in a sample• Solution: stable isotope labeling

– Compare samples that have been labeled with stable isotopes (13C, 15N, 2H)

– ‘Heavy’ isotopes behave chemically identically to their ‘light’ counterparts but are separated in the MS

Page 50: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Isotope Coded Affinity Tag (ICAT)

Page 51: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014
Page 52: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014
Page 53: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Stable Isotope Labeling of Amino Acids in Culture (SILAC)

• Grow cells in media supplemented with stable isotope-labeled amino acids

• Combine samples at the level of cells and process as one sample• Minimize variability

between samples for lysis and digestion

• Different samples separated by mass in the MS

Page 54: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Absolute Quantification (AQUA)

Page 55: Mass spectrometry-based proteomics Jeff Johnson Feb 19, 2014

Absolute Quantification (AQUA)