Overview of Food Allergen Detection using Mass Spectrometry - Waters Corporation Food Safety & Research

©2015 Waters Corporation 1

The Advantages of LC-MS/MS analysis

for Food Allergen Detection

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Overview

Food allergens – background & regulatory status

– Major classifications (within EU) & threshold dose establishment

Current detection strategies?

What information can MS provide?

LC-MS/MS strategy

– Discovery phase (proteomic based)

– Translation to routine quantitation (tandem quadrupole)

– Recommendations for MS based allergen analysis

Summary and future prospects?

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Immunological Aspects of Food Allergy

Food allergic reaction is an IgE mediated reaction to specific

food proteins

– Prevalent in c. 2% of the adult and 8% of child population

– Symptoms can range from mild to severe (life-threatening)


Food Allergy – avoidance & preventative actions?

No curative treatment is available for food allergy

Accidental ingestion of the culprit food can lead to severe clinical

symptoms

– Elimination diet

o Reduce the risk of allergic reactions

o Disadvantages: deficiencies, eating disorders, growth retardation

– Emergency medication

o Antihistamines (H1 blockers)

o EpiPen (adrenaline-autoinjector)

o Corticosteroids

Preventative actions?

Effective tools for detection & quantitation are

needed for effective labelling

http://guangdonginspection.com/blog/wp-content/uploads/2013/09/Preventive-corrective-action.png


EU perspective – Statutory Food Labelling Laws

The rules for pre-packed foods establish a list of 14 food

allergens, which must be indicated by reference to the source

allergen whenever they, or ingredients made from them, are used at

any level in pre-packed foods, including alcoholic drinks

Labelling rules in European Directives 2003/89/EC & 2006/142/EC

ensure that all consumers are given comprehensive ingredient

listing information and make it easier for people with food

allergies to identify ingredients they need to avoid

Food Information for Consumers Regulation (EU) No. 1169/2011 builds

on current allergen labelling provisions for pre-packed foods &

introduces a new requirement for allergen information to be provided

for foods sold non-packed or pre-packed for direct sale

– Allergen labelling rules will be changing in December 2014


Allergen Classification EU 14 major priorities

Cereals containing gluten, crustaceans, molluscs, eggs, fish, peanuts, nuts, soybeans, milk, celery, mustard, sesame, lupin and sulfur dioxide (at levels >10mg/kg or 10

mg/litre, expressed as SO2 )


Establishment of Threshold Doses

Threshold dose establishment – ongoing research activity

– Safety assessment LOAEL or NOAEL

Commission Regulation (EC) No. 41/2009 established levels of

gluten for foods claiming to be either 'gluten-free' or 'very low

gluten‘ (January 2012)

– 'gluten-free': at 20 parts per million of gluten or less

– 'very low gluten': at 100 parts per million of gluten or less -

however, only foods with cereal ingredients that have been specially

processed to remove the gluten may make a 'very low gluten' claim

These regulations apply to all foods, pre-packed or sold loose,

such as in health food stores or in catering establishments


Analysis of Allergens Current detection strategies

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ELISA IgG antibody based recognition of

whole protein or peptides

PCR Determination of

allergic protein DNA

MS

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Effect of food processing?

The majority of allergen testing is performed on processed

foods

The effect of cooking procedures on the target protein analytes

need to be considered along with the effects of the matrix

components (other proteins; carbohydrates; oils etc.)

Processing-induced modifications also affect analyte extraction

– May compromise immuno-based methods as processing induced

changes may affect antibody reactivity & specificity

– For PCR based methods it is often the case that no DNA can be

extracted from highly processed products or protein concentrates

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LC-MS/MS Advantage?

Specificity

• MRM acquisition mode

• Multiple transitions & ion ratios (selectivity)

Robustness

• Matrix effect reduction

• Good S:N in complex matrices

• Repeatability (r) & reproducibility (R)

Sensitivity

• Trace level detection (sub ppb LoDs)

• Use of labeled internal standards

• Simultaneous analysis of multiple allergens in processed foodstuffs

Ideal for routine quantitative method


What information can MS detection provide?

MS technologies allow a broad range of different types of protein analysis to be conducted e.g. protein identification; characterisation & quantitation

Analyse peptide markers of the protein causing the allergic

reaction

Targeted and specific (m/z) analysis

Quantifiable technique

Potential to use a multi-allergen approach

Capability to modify / optimise routine methods for challenging matrices (without additional cost)


Discovery of peptide markers of allergenic

proteins

QTof & ion mobility enabled QTof


Which type of MS technology is applicable for discovery?

Time-of-flight MS analysers (Tof; QTof; ion mobility enabled

QTof)

The inherent characteristics of Tof MS are extreme sensitivity (all

ions are detected), almost unlimited mass range, speed of analysis

(>10 full spectra / s) and >>5ppm mass accuracy

Confirmation of elemental composition

– Identification of unknown compounds

Additional dimension of specificity

– Quantitation in accurate mass MS mode (rather than MS/MS) mode

to reduce chemical interferences

– Differentiation of nominal isobars in combinatorial libraries

– Improved protein database search results

– Improved de novo protein sequencing results


Waters Accurate Mass Instrument Portfolio

Xevo G2-XS Q-ToF

Xevo G2-XS MS

SYNAPT G2-Si HDMS

SYNAPT G2-Si MS

Ion mobility enabled QTof


“Discovery phase” Bottom-up proteomic based approach

1. Enzyme digestion

2. UPLC separation

Precursor ions

MSE product ions

3. MS analysis

4. Data interpretation


“Discovery phase” HRMS workflow

SAMPLE PREPARATION (1) Tryptic digest (2) ADH addition

DATA ACQUISITION Acquire data-independent MSE or HDMSE Data

SOFTWARE PROCESSING PLGS & IdentityE and Proteomic database (e.g. UniProt)

ANALYTICAL SYSTEMS (1) ACQUITY M-Class UPLC ® (2) XevoTM G2-XS QTof or Synapt G2-Si


Food Proteomic Workflow Software processing

SOFTWARE PROCESSING PLGS and IdentityE

Positive matches referenced to database library

Increasing confidence in peptide assignment - - >


Progenesis™ software


Progenesis™ Workflow to Aid the Discovery Process

alignment

peak detection

identification

protein quantitation

statistics

meta

bolo

mic

s/l

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om

ics

pro

teom

ics

peptide quantitation

alignment

peak detection

compound quantitation

identification

statistics

deconvolution


Ion mobility enables QTof HDMSE acquisition mode


Ion mobility enabled QTof additional peak capacity

3 Dimensions of resolution

X = m/z Y = Intensity Z = Drift time

OVT peptide m/z 878.7726 AIANNEADAISLDGG


Ion mobility enabled QTof discover more peptides…


“In Silico” Approach

Software-based strategy to identify peptide

markers


Scientific publications Major allergens from

milk, soy and egg

“In silico” digestion Theoretical peptides

Specific peptides

STE

P 1

Extraction and purification from a reference material

Suitable sample preparation method

Xevo TQ-S Analytical method for peptides from STEP 1

STE

P 2

“In silico” Workflow Strategy Combination of observed & theoretical peptides


Sample Preparation Strategy

Solubilise and extract protein using aq buffer (PBS) from complex matrix

Protein denaturation using detergents (RapiGest™ or SDS) to linearise the 3D structure

Proteolytic digestion using trypsin to cleave the protein into reproducible and peptide sequences (6 – 12 amino acids)

Additional sample clean-up & enrichment

– Immuno-affinity column using specific anti-peptide IgG

– Ultra-filtration or SPE?

Filtration & dilution in mobile phase A prior to LC-MS analysis


Allergic food

Number of allergens

Reference protein for method development

Number of specific petpides (Skyline© - literature)

Egg white 3 Ovalbumin 4 - 14

Egg yolk 3 Phosvitin 30 - 3

Milk 6 Casein αS1 3 - 3

Soy 11 Kunitz Tripsin Inhibitor 4 - 2

Selection of the optimum protein & peptide sequences

Ovalbumin

Peptide from literature Source Comment Skyline matching

AFKDEDTQAMPFR Faeste et al., 2011 Review OK

ISQAVHAAHAEINEAGR Faeste et al., 2011 et

Lee et al., 2010 OK

HIATNAVLFFGR

Heick et al., 2011 Multi-allergen

method

OK

YPILPEYLQCVK OK

DILNQITKPNDVYSFSLASR OK

ELINSWVESQTNGIIR OK

DVYSFSLA

Azarnia et al., 2013 Heat proof

OK

ISQAVHAAHAEINEAGR OK

HIATNAVLFFGR OK

GGLEPINFQTAADQAR OK

LTEWTSSNVMEER OK

VTEQESKPVQMMYQIGLFR OK

EVVGSAEAGVDAASVSEEFRA OK

Determine robustness of the peptides to thermal processing (commercial baking

conditions 200o C for 20 mins)


Skyline Experimental Design

Peptide settings

Transition settings

MRM generation


Translation to routine quantitative analysis

using tandem quadrupole

TQ-S


Acquisition Mode Multiple Reaction Monitoring (MRM)

Quadrupole 1 Collision

Cell

Static (m/z 821.5)

Static (m/z 768.5)

Ar (2.5 – 3.0e-3mBar)

Precursor(s) Product(s)

Quadrupole 1


MRM transition development process

Reference samples may be used to determine & optimise the

MRM’s for each of the peptide sequences

Information from Skyline is used to predict the parents &

fragments for each peptide sequence

Step 1

• Full Scan MS

• Determine precursor m/z & charge state

• N.B. 2+& 3+ ions give better fragmentation

Step 2

• Product ion scan

• Determine selective products of precursor (minimum number of 3 per peptide)

Step 3

• In the presence of matrix

• Optimise cone voltage(s)

• Optimise collision energies


Method Parameters ACQUITY UPLC conditions

LC system ACQUITY UPLC I-Class

Column ACQUITY BEH300 C18, 2.1 x 150 mm, 1.7 µm

Column temp 40°C

Solvent A Water + 0.1% formic acid

Solvent B ACN 0.1% formic acid

Injection volume 2 μl

Time (min)

Flow rate (mL/min)

% A % B Curve

0.0 0.5 98 2 -

30 0.5 60 40 6

30.1 0.5 10 90 6

32.1 0.5 10 90 6

32.2 0.5 98 2 6

35 0.5 98 2 6


Peanut allergens Targeted peptides & MRMs

Peptide Protein Precursor Product Cone Voltage (V) Collision Energy (eV)

930.45 25 24

1077.52 25 24

1148.55 25 24

804.35 25 28

1247.51 25 28

1360.6 25 28

587.3 30 30

1219.53 30 30

1347.58 30 30

175.12 30 19

505.26 30 19

761.37 30 19

660.31 25 31

807.37 25 31

1050.46 25 31

147.11 25 18

656.35 25 18

275.17 25 18

672.35 25 18

1186.53 25 18

147.11 30 27

299.8 30 27

404.25 30 27

809.37 30 27

923.42 30 27

1181.5 30 27

473.58 25 15

695.16 25 15

750.91 25 15

376.19 30 17

475.26 30 17

590.29 30 17

653.28 25 19

781.34 25 19

878.39 25 19

Arah 2 N Term

Arah2 C Term1

Arah2 C Term2

Arah1 N Term Prepro

Arah1 N Term

Arah1 C Term

553.26Arah7.1

Arah6 Uni

Arah6 1

Arah3 4 Acidic

Arah3 4 Basic

543.02

547.00

695.17

767.84

582.92

489.53

SPDIYNPQAGSLK

QQPEENACQFQR

IMGEQEQYDSYDIR

CDLDVSGGR

NLPQNCGFR

688.83

786.87

809.95

543.02

863.57

DLAFPGSGEQVEK

VLLEENAGGEQEER

CLQSCQQEPDDLK

NLPQQCGLR

CCNELNEFENNQR

ANLRPCEQHLMQK


Milk allergens Targeted peptides & MRMs

Peptide Precursor

(m/z) Product (m/z)

YLGYLEQLLR (casein S1) 423.2 529.3

634.4 658.4

634.4 771.5

634.4 934.5

VPQLEIVPNSAEER (casein S1) 527.6 802.4

790.9 779.5

790.9 802.4

790.9 1014.5

FFVAPFPEVFGK (casein S1) 692.9 465.2

692.9 676.4

692.9 920.5

692.9 991.5

ALNEINQFYQK (casein S2) 456.6 827.4

684.3 713.4

684.3 827.4

684.3 940.5

FALPQYLK (casein S2) 490.2 332.2

490.2 551.3

490.2 648.4

490.2 761.5


Egg white allergen Targeted peptides & MRMs

Peptide Precursor (m/z)

Product (m/z)

DILNQITKPNDVYSFSLASR (ovalbumin) 761.0 767.4

761.0 930.5

761.0 1355.7

1141.1 1355.7

GGLEPINFQTAADQAR (ovalbumin) 563.3 732.4

844.4 860.4

844.4 1007.5

844.4 1121.5

844.4 1331.7

ELINSWVESQTNGIIR (ovalbumin) 620.3 673.4

620.3 888.5

930.0 1017.5

930.0 1116.6

EVVGSAEAGVDAASVSEEFR (ovalbumin) 670.3 853.4

670.3 924.4

1005.0 1110.5

1005.0 1266.6


Compound name: YLGYLEQLLR (casein S1)

Correlation coefficient: r = 0.995512, r^2 = 0.991045

Calibration curve: 59440.7 * x + -3078.23

Response type: External Std, Area

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

1000000

2000000

3000000

4000000

5000001

Compound name: ALNEINQFYQK (casein S2)





Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

100000

200000

300000

Compound name: FALPQYLK (casein S2)


Calibration curve: 62929.5 * x + 567.125



Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

1000000

2000000

3000000

4000000

5000001

Compound name: GGLEPINFQTAADQAR (ovalbumin)





Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

500000

1000000

1500000

2000000

2500000

Quantitative performance - linearity Matrix matched calibration standards


Peptide Identification & Confirmation Using ACQUITY UPLC & Xevo TQ-S

1. Retention time

2. Standard MRM transitions


Peptide Identification & Confirmation Using ACQUITY UPLC & Xevo TQ-S

1. Retention time

2. Standard MRM transitions

3. Standard MRM transitions & full scan data

4. Product ion scanning confirmation

(PICs)


Method Development with Skyline Use of RADAR for Food Matrices

- Parallel MRM with full scan data acquisition

}


Method Development with Skyline Use of RADAR for Food Matrices

Once the most selective, and then the most sensitive MRMs have been selected for a subset of

food matrices, RADAR can be used to support routine analysis

Casein

S1-

YLG

Casein

S1-

FFV

Ovalb

um

in-

EVV O

valb

um

in-

GG

L

Ovalb

um

in-

DIL

O

valb

um

in-

ELI

Casein

S2-

FAL

Casein

S1 -

VPQ

Casein

S2-

ALN

4

3

2 1

6

5

Full scan

MRMs


Summary Practical Considerations?

Choice of analyte?

– MS analysis presents the opportunity to directly analyze for the presence of the molecules that cause allergic reactions

Choice of MS Marker Peptides?

– not all proteins & peptides are stable after common processing steps in the food industry like heating, baking, roasting, or pressure treatment

Choice of Standard?

– Isotopically labelled (proteins) or peptides

Optimization of Protease Digestion

– Quant protein MS requires reproducible & effective protease digestion, optimised for each matrix / target combination

Harmonization of Methods & Results

– Development of naturally incurred reference materials & validation protocols & inter-lab trials


AOAC recommendations for Allergen Analysis by LC-MS

Johnson et al.: Journal of AOAC International vol. 94, no. 4, 2011


Acknowledgements

University of Manchester, UK

Prof Claire Mills

Phil Johnson

CER, Marloie, Belgium

Nathalie Gillard

Samuel Nemes

Technology Strategy Board funding for

“Allergen analysis developing integrated approaches” (13045-83259)

http://www.manchester.ac.uk/

Science

Overview of Food Allergen Detection using Mass Spectrometry - Waters Corporation Food Safety & Research