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Identification of Meat Species in Processed Foods using Mass Spectrometry - Waters Corporation Food Research

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Identification of Meat Species in Processed Foods using Mass Spectrometry - Waters Corporation Food Research

  1. 1. ©2015 Waters Corporation 1 Identification of Meat Species in Processed Foods using Mass Spectrometry
  2. 2. ©2015 Waters Corporation 2 Presentation Overview  Background – Food labelling regulations – Water retaining agents in chicken products – Use of gelatine  Research Objectives  Proposed solution – Sample preparation procedure – LC-MS approach – Data interpretation  Results – Identification of potential peptide markers – Quantification of markers  Future work using Xevo TQ-S  Conclusions
  3. 3. ©2015 Waters Corporation 3 Meat speciation – regulatory requirements  Authenticity of food and the accuracy of package labeling is important to both consumers and food producers  Within the EC food labeling regulations exist – ~5 M people in UK have preferences concerning consumption of certain species  Composition of injection powders? – Undeclared water-retaining hydrolysed proteins from pork and beef used in chicken products – Some chicken products potentially unsuitable for consumers  Need to verify the species of gelatine used in food
  4. 4. ©2015 Waters Corporation 4 Injection powders - gelatine  What is it? – Bi-product from the meat / fish industry – partial hydrolysis of collagen extracted from skin, bones, connective tissue  Properties of gelatine – Gelling agent – Semi-solid colloid gel – Texture enhancer  Approx annual production: – Europe: 117kt (70% used in food)  What is it used for? – Food and Beverages – Drugs and capsules – Cosmetics – Photographic film – Fertilisers…
  5. 5. ©2015 Waters Corporation 5 Research objectives and aims  Develop a method to detect species and tissue origin of meat ingredients present in meat products 1. To identify unequivocal markers that can indicate the presence of bovine or porcine gelatine 2. To determine whether chicken products have been adulterated with proteins from other animal species 3. To develop a robust and transferable method  Current limitations… – Paper trail is not sufficient – FSA concluded that PCR / IA based strategies are not reliable • DNA markers damaged by processing conditions • False negative rate  Possible Solutions? – LC-MS/MS using a proteomic workflow
  6. 6. ©2015 Waters Corporation 6 Alternative strategy = proteomic based analytical strategy to identify peptide markers using HR-MS
  7. 7. ©2015 Waters Corporation 7 Bottom-up proteomic experiment 1. Enzyme digestion 2. UPLC separation Precursor ions MSE product ions 3. MS analysis 4. Data interpretation
  8. 8. ©2015 Waters Corporation 8 Meat Speciation Workflow SAMPLE PREPARATION (1) Tryptic digest (2) ADH addition DATA ACQUISITION Acquire data-independent MSE Data SOFTWARE PROCESSING IdentityE and gelatine database (BioArch) ANALYTICAL SYSTEMS (1) nanoACQUITY UPLC ® (2) XevoTM QTof MS Nano-scale separations •Resolution •Peak shape •Number of components / analytical run Full scan, accurate mass
  9. 9. ©2015 Waters Corporation 9 Meat Speciation Workflow Sample Preparation  Samples – Protein tryptic digests; o pork gelatine o beef gelatine o pork & beef gelatine mix  Tryptic digest – 250 μg of porcine and bovine gelatine were hydrolysed with 5 μg of sequence grade trypsin for 16hr  ADH addition – Quench reaction with formic acid – 10 fmol of yeast alcohol dehydrogenase (internal standard) added tryptic digest SAMPLE PREPARATION (1) Tryptic digest (2) ADH addition
  10. 10. ©2015 Waters Corporation 10 UPLC Conditions  System – NanoACQUITY® UPLC  Column: – 75 µm x 15 cm BEH C18 column  Gradient: – 1 to 40% acetonitrile – 90 min  Flow rate: – 300 nL/min  Triplicate analysis MS Conditions  System – Xevo QTof MS  Mass range: – m/z 50-1990  Data Acquisition: – MSE  Collision energy: – Low energy - 4 eV – High energy - 12-35 eV  Acquisition scan time: – 0.9 s/function Meat Speciation Workflow UPLC-MS conditions OPTIMISED ANALYTICAL PARAMETERS (1) nanoACQUITY UPLC ® (2) XevoTM QTof MS
  11. 11. ©2015 Waters Corporation 11 Meat Speciation Workflow MSE  UPLC-MSE is a data independent parallel process that occurs in the collision cell  The instrument is operated in an alternative scanning mode providing two MS scan functions for data acquisition in one analytical run – Function 1 = low collision energy (precursor ions) Function 2 = high energy (fragment ions) DATA ACQUISITION Acquire data-independent MSE Data
  12. 12. ©2015 Waters Corporation 12 Meat Speciation Workflow Software processing SOFTWARE PROCESSING PLGS and IdentityE Positive matches referenced to database library Increasing confidence in assignment of peptides
  13. 13. ©2015 Waters Corporation 13 Results and Discussion
  14. 14. ©2015 Waters Corporation 14 nanoACQUITY replicate injections (n=3) Beef gelatine Repeatable results Overlay low energy MSE chromatograms
  15. 15. ©2015 Waters Corporation 15 Meat Speciation Workflow Software processing High energy product ion data gives increased confidence in peptide sequence identification Low energy data can be displayed as a mass spectrum or a chromatogram Markers originated from a SINGLE protein Unique marker peptides sequences listed here
  16. 16. ©2015 Waters Corporation 16 Discovery & Identification Total Marker Peptides Aim to obtain a peptide marker that is unmodified (if possible)  Over 60 collagen peptides were identified in samples of both bovine and porcine gelatines  IdentityE did not identify peptides from any other proteins – Collagen – Yeast ADH  Indicates the samples were 100% gelatine Multiple forms of the peptides identified Species peptide Peptide mass Type of peptide modification Bovine GYPGNPGPAGAAGAP 1235.58 Non-tryptic cleavage product GYPGNPGPAGAAGAPGPQGAVGPAGK 2173.08 Unmodified peptide GYPGNPGPAGAAGAPGPQGAVGPAGK 2189.07 Hydroxyl of single proline GYPGNPGPAGAAGAPGPQGAVGPAGK 2205.07 Hydroxylation of prolines 3 and 15 GYPGNPGPAGAAGAPGPQGAVGPAGK 2221.06 Three hydroxyprolines GYPGNPGPAGAAGAPGPQGAVGPAGKHGNR 2653.3 Missed tryptic cleavage hydroxylation of proline 29 GYPGNPGPAGAAGAPGPQGAVGPAGKHGNR 2669.29 Missed cleavage plus two proline hydroxylations Porcine IGQPGAVGPAGIR 1192.68 Deamidation + Q3 IGQPGAVGPAGIR 1193.66 Hydroxyl + DKNP 4 IGQPGAVGPAGIR 1208.67 IGQPGAVGPAGIR 1209.66 Deamidation +Q3; Hydroxyl+DKNP9
  17. 17. ©2015 Waters Corporation 17 Discovery & Identification Unique Unmodified Marker Peptides Bovine peptide marker IGQPGAVAPAGIR Porcine peptide marker TGQPGAVAPAGIR Comparison of high energy MSE fragment ion spectra Differences in b and y ions formed
  18. 18. ©2015 Waters Corporation 18 Quantification Porcine and bovine gelatine  Use of ADH enabled quantification of proteins in sample Removes need to use labelling systems for peptide and protein quantification Test mix was prepared Addition of 15%(w/w) bovine gelatine in porcine gelatine Results Three bovine and porcine peptides were selected - relative bovine gelatine content of ~ 16.8%
  19. 19. ©2015 Waters Corporation 19 Conclusions  Highly processed food proteins, such as gelatine, that are devoid of DNA signature can be speciated using LC-MS  Protein sequence database analysis identified peptide sequences within the protein that are species specific  Waters Xevo Qtof MS was able to identify these sequences, even after significant modification of the amino acids  The interrogation of the total protein complement of the sample also provided potential information on non-gelatine proteins in the samples
  20. 20. ©2015 Waters Corporation 20 Further Work Preliminary data suggests the method can be used to quantify the species in mixtures of gelatines  Investigate the contribution that type III collagen (from skin and connective tissue) might make to the quantitative analysis of gelatines
  21. 21. ©2015 Waters Corporation 21 Future Work Method transfer to routine analysis using tandem quad MS/MS
  22. 22. ©2015 Waters Corporation 22 Acknowledgments Helen Grundy - Food and Environment Research Agency, York, UK BioArCh, University of York, UK Thank you for your attention Any Questions?

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