The Analysis of Allergens in Raw and Roasted Peanuts using Nanoscale UPLC & Time of-Flight Mass...

©2015 Waters Corporation 1

The Analysis Of Allergens in Raw and

Roasted Peanuts using nanoscale UPLC &

Time-of-Flight Mass Spectrometry


Presentation Overview

Allergens Background

Technologies for Allergen Analysis

Experimental Workflow

– Sample Prep

– Instrument set-up

– Software

Results

Conclusions


Background: Allergens Overview

Incidence of food allergy in industrialised populations is

increasing

Effects for suffers can be fatal

Food Regulations WW

– Reduce cross-contamination in factory

– Food Labelling


Background: Allergens Type of Food Categories


Analysis of Allergens Technologies

ELISA

PCR

MS

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Workflow

SAMPLE PREPARATION (1) Protein extraction (2) Tryptic digest

DATA ACQUISITION Acquire data-independent MSE Data

SOFTWARE PROCESSING PLGS

INSTRUMENT SET-UP (1) nanoACQUITY UPLC ® (2) XevoTM QTof MS


Workflow (1)

SAMPLE PREPARATION

PART 1:

— Ara h1 protein extraction from raw and roasted peanut

PART 2:

— Tryptic digest of raw and roasted Ara h1 extract (RapiGest™ SF)

(PART 3:)

— Ara h1 identification and quantification in matrix (additional use

of ADH)


nanoACQUITY UPLC

Column:

– nanoACQUITY™ BEH C18, 75 mm x

150 mm

Flow Rate:

– 300 nL/min

Mobile Phase:

– A: 0.1% FA in Water

– B: 0.1% FA in Acetonitrile

Gradient:

Workflow (2)



nanoACQUITY data Raw peanut sample


Xevo QTof MS

Ionisation Mode:

– Electrospray Positive Ion

Capillary:

– 3.3 V

Cone:

– 25 V

Source Temperature:

– 100oC

LC/MSE Conditions:

– MS scan (Low CE): 6 V

– MSE scan (High CE ): 15 – 40 V

– Scan time: 0.6 sec

Workflow (2)



UPLC-MSE provides ‘all the data, all the time’

– More information from a single analysis

UPLC-MSE employs a simple methodology which

– Uses generic methods of acquisition

– Uses relevant Application Manager to mine data set

– ‘Acquire your data, Ask questions later!’

Workflow

DATA ACQUISITION Acquire data-independent MSE Data


Advantages of MSE with PLGS Time-aligned spectra

Low energy fragmentation

High energy fragmentation *


Workflow

SOFTWARE PROCESSING PLGS (ProteinLynx Global SERVER™ )

Databank: SwissProt

False Positive Rate: 4%

Fixed modification: Carbamidomethyl C

Variable modification: Acetyl N-Term, Deamidation N, Deamidation Q, Met-Oxidation, Hydroxy P

N-Linked Glycosylation

~10 ppm window for precursor ions;

~25 ppm window for fragment ions


ProteinLynx Global SERVER™ Parameters

•Data preparation

Default parameters were used. Lock mass correction: 785.8426.

•Work flow

Databank: SwissProt

False Positive Rate: 4%

Fixed modification: Carbamidomethyl C

Variable modification: Acetyl N-Term, Deamidation N, Deamidation Q, Met-Oxidation, Hydroxy P

N-Linked Glycosylation

~10 ppm window for precursor ions;

~25 ppm window for fragment ions


Peptide Sequence Identification: GSEEDITNPINLR


Peptide sequences observed in both raw & roasted samples


Relative intensities of peptide sequences present in both samples


Peptide Coverage Raw and Roasted Samples

Signal peptide: 1-25

Raw Sample Roasted Sample


Quantification of Ara H1

in Matrix


Experimental Overview

Aim:

– To identify and quantify Ara H1 in complex

matrix

Samples:

Two samples investigated – different

concentrations:

– Sample A – 1 : 3 (v/v) Sample 1 vs Standard

solution

– Sample B – 1 : 200 (v/v) Sample 1 vs Standard

solution


Workflow

SAMPLE PREPARATION

PART 1:

— Ara h1 protein extraction from raw and roasted peanut

PART 2:

— Tryptic digest of raw and roasted Ara h1 extract (RapiGest™ SF)

(PART 3:)

— Ara h1 identification and quantification in matrix (additional use

of ADH)


Sample A – 1 : 3 dilution

MS – Low collision energy data

MSE – High collision energy data


Sample B – 1 : 200 dilution

MS – Low collision energy data

MSE – High collision energy data


Sample B – 1 : 200 dilution Peptide Coverage


Summary

Challenges for analysis of allergenic proteins – many different

approaches already used

– Complexity added – Typical food processing (e.g. food processing)

can alter the markers peptides present / amount that they are

present in the samples

Analytical tools and software can support confidence in the

results obtained

– ProteinLynx Global Server (PLGS) with intelligent filtering and

scoring routines minimizes occurrence of false positive results

– UPLC-MSE fragment ion exact mass data provides greater

confidence in protein identification in food samples

The Analysis of Allergens in Raw and Roasted Peanuts using Nanoscale UPLC & Time of-Flight Mass...

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