Mass Spectrometry in Food Safety. Paul Zavitsanos Global Food Safety Marketing Manager

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Mass Spectrometry in Food Safety Paul Zavitsanos Global Food Safety Marketing Manager

Agilent s Lab-bench to Lab-bench Market Development Model Create local research/technical development teams in Europe, the Americas, China, and India Identify key chemical and biological applications (unmet needs) Collaborate with respected researchers to make these applications a reality Support researchers world wide on specific applications Communicate our findings worldwide Commercialize successful applications

Existing Core Chemical Applications GC/MS, LC/MS, GC/QQQ, LC/QQQ, LC/Q-TOF, LC/TOF, ICP/MS Pesticides Quantification of known pesticides Identification/quantification of new pesticides and metabolites Veterinary drugs Identification/quantification of antibiotics, steroids, and other growth hormones Trace metals Identification/quantification of elements such as lead and mercury The challenge: increase speed and sensitivity while decreasing cost

Emerging Chemical Applications Mycotoxins (over 3,000 known; immediate toxic effects) Typically LC/MS Steroid hormones (difficult to measure through conventional techniques) GC/QQQ Dramatic success in 2010 Winter Olympics Dioxins in food (traditionally requires high-res equipment/specialized skills) GC/QQQ Fast, simple, more sensitive than conventional GC approaches Marine toxins (small-molecule compounds produced by shellfish) LC/QQQ (quantification of known targets) LC/TOF (discovery of unknowns) Allergens (chemical aspects to identification) LC/MS, LC/Q-TOF, GC/QQQ Small-molecule allergens

Emerging Biological Applications Allergens (biological aspects to identification) LC/MS, LC/Q-TOF Intact protein discovery with bio-confirm software can determine the exact sequence of molecule in question Measurement by biological reagents Species identification (accidental contamination vs. intentional fraud) PCR, bioanalyzer, specialty bioreagents Identify biological compounds at the DNA level; Manipulate genetic information Pathogen identification (serotype) Mass Codes PCR with MS detection Identification at the DNA level DNA manipulation Tag and recognize dangerous bacteria Serotype determination At what point in manufacturing process is contamination taking place?

DISCOVERY of unknown chemical containments TOF techniques Visualize and differentiate compounds that were previously hidden under one peak Modern TOF instruments: 10x greater mass discrimination. Can determine empirical formula based on the mass of the compound in question. Novel data mining techniques (such as DRS, MFE, PCD) Discover more compounds/ contaminants, faster, and with greater precision Data review and processing: weeks vs. minutes

MYCOTOXINS

Determination of Aflatoxins (B 1, B 2, G 1, G 2 ) in Food Matrices using Triple Quadrupole LC/MS/MS Presented by Peter Stone, Agilent Technologies, Santa Clara, CA. Experimental Work and Data provided by: Yang Chen and Jack Cappozzo National Center for Food Safety and Technology

Chromatography G2 aflatoxins Overlaid EICs Quant ion & 2 x Qualifiers (1ppb) B1 B2 G1 G2 Isotopically labelled aflatoxins B1 B2 G1 Overlaid EICs Quant ion & Qualifier ion (2.5ppb)

Spiked Peanut Samples Recovery Studies (% Recovery, ± RSD, N=7) No Internal Standard: Aflatoxin Internal Standard: Peanut spiked at 5 ng/g C18 clean-up Peanut spiked at 25 ng/g C18 clean-up Peanut spiked at 5 ng/g MycoSep#226 Peanut spiked at 25 ng/g Mycosep#226 B 1 96.7 ± 3.4 97.0 ± 4.6 112.0 ± 8.4 104.9 ± 1.7 B 2 98.3 ± 4.7 97.4 ± 2.9 108.0 ± 4.6 104.5 ± 2.0 G 1 95.0 ± 5.6 95.0 ± 4.9 109.9 ± 2.1 105.7 ± 3.4 G 2 100.0 ± 2.3 100.0 ± 2.0 114.7 ± 3.2 106.3 ± 1.1 Aflatoxin Peanut spiked at 5 ng/g C18 clean-up Peanut spiked at 25 ng/g C18 clean-up Peanut spiked at 5 ng/g MycoSep#226 Peanut spiked at 25 ng/g Mycosep#226 B 1 101.8 ± 3.6 96.1 ± 2.0 100.0 ± 6.8 103.0 ± 3.5 B 2 102.5 ± 5.5 100.2 ± 5.0 99.4 ± 4.1 102.9 ± 2.7 G 1 105.7 ± 7.3 99.2 ± 2.2 105.2 ± 4.3 101.7 ± 5.2 G 2 107.5 ± 10.9 104.9 ± 6.7 109.3 ± 8.7 102.4 ± 3.1

Acknowledgements: Experimental Work and Data provided by: Yang Chen and Jack Cappozzo (National Center for Food Safety and Technology, IIT) Photo: Rima Juskelis, Jianwen Xu, Katie Banaszewski, Haoshi Feng, Niranjen Kalle, Fadwa Al-Taher, Jack Cappozzo, Yang Chen

Mycotoxin Screening by LC/QQQ Dr. Robert Voyksner Dr. Jennifer Voyksner LC/MS Limited, NC. USA

Comparison of pos and neg ESI LC/MS/MS analysis of 31 mycotoxins Conditions: poroshell 120 2.1x50 mm 2.7 um particles gradient 5-95% ACN 12 min(0.025% TFA for pos esi, 20 mm am Act neg esi), 0.3 ml/min Positive ESI MRM transitions Negative ESI MRM transitions

Recovery for 31 Mycotoxins from spiked corn using 3 different LC/MS/MS gradient analysis conditions Conditions: 1 g corn spiked with 20-160 ng/g of each mycotoxins, extracted with 2 ml of 80% ACN in water with 0.025% TFA for 10 min, centrifuged and filtered (30K MWCO filter), then diluted with 1.5 ml of water and 10 ul injected onto the LC/MS/MS. Separation used poroshell 120 2.1x50 mm 2.7 um particles gradient 5-95% ACN in 3, 12 and 28 min, 0.3 ml/min, ESI pos ion detection used 0.025% TFA and ESI neg ion detection used 20 mm AM Act.

Analysis of mycotoxins in food Agilent 1290 Infinity HPLC / G6460A QQQ system Dr. Thomas Glauner LC-MS Food Application Scientist European Food Group Page 15

Sample preparation 0.5 g cereal sample (ground and homogenized) Extraction with 2 ml solvent (CH 3 CN/H 2 O/HAc 79 + 20 + 1) Shaking (90 min) and centrifugation (2 min @ 3000 Umin -1 ) Dilution (0.5 ml sample + 0.5 ml solvent) (CH 3 CN/H 2 O/HAc 20 + 79 + 1) LC-MS/MS M. Sulyok, F. Berthiller, R. Kruska, R. Schuhmacher, Rapid Commun Mass Spectrom 2006, 20(18): 2649-2659 Page 16

Mycotoxins acquired in negative ion mode In negative mode most abundant precursor ions of mycotoxins have been [M-H] - and [M+COOH - ] -, respectively. Nivalenol Deoxynivalenol Fusarenon-X 3-Acetyldeoxynivalenol Zearalenon Page 17

Mycotoxins acquired in positive ion mode In positive mode most abundant precursor ions of mycotoxins have been [M+H] +, [M+NH 4+ ] +, and [M+Na + ] +, respectively. Neosolaniol Aflatoxin B2 Aflatoxin B1 Diacetoxyscirpenol HT2-Toxin 15-Acetyldeoxynivalenol Fumonisin B2 Fumonisin B3 T2-Toxin Fumonisin B1 Page 18

PLANT HORMONES

Plant Growth Regulators(PGRs) Plant hormones or Phytohormones are chemicals which regulates plant growth Manmade compounds are called PGRs and basically used to regulate growth of cultivated plants, weeds and in vitro grown plants and plant cells Major five classes of plant hormones 1-Abscisic acid 2-Auxins 3-Cytokinins 4-Ethylene 5-Gibberellins Other known hormones are like salicylic acid,jasmonates,plant peptide hormones,polyamines,nitric oxide,strigolactones and Karikins Page 20

Sample clean up for PGRs quantitation 1g of homogenized grapes sample Spiked with mixture of STD PGRs (final cone 5ppb in sample and 50ppb in blank) Sample extracted in 40ml Methanol Water (50:50) 30 min/ambient/shaking 1.0 ml supernatant transferred to 1.7 ml centrifuge tube and Centrifuge @ 14,000 rpm, 5min

Methodology Sample Preparation continued. Solid phase dispersive Clean-up 0.8 ml supernatant transferred to 1.7ml micro-centrifuge tubes Add 200mg of C18 ODS SPE bulk Sorbent, Agilent (p/n 5982-1182) Vortex for 1 min & centrifuge @ 14,000 rpm, 3min 0.4ml supernatant diluted with 0.6ml Methanol for LC/MS

Zeatin 6-Benzyladenine Chlormequat Kinetin IAA IBA Ferchlorfenuron Paclobutrazole

Sample study

Sample spiked with STD (5ppb)

Response for 0.5ppb STD Chlormequat

DIOXINS, FURANS and PCBs

Determination of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzo-p-furans (PCDFs) in Foodstuffs using the 7000B Tandem Quadrupole GC- MS/MS System Chris Sandy EMEA GC-MS Food Segment Scientist Agilent Technologies UK April 2010

Acknowledgements Dr Karl Petitt, Ms Karolina Songin Marchwood Scientific Services, UK Prof. Peter Fuerst, Dr Thorsten Bernsmann CVUA-MEL, Munster, Germany

Native PCDD and PCDF Isomers Tetra Penta Hexa Hepta Octa

2378-TCDD in Poultry Egg (1.66 pg TEQ /g Fat)

2378-TCDD in Beef Sample (0.28 pg TEQ /g Fat)

Difference between GC-HRMS results and GC-MS/MS results TEQ (Upper bound) PCDD/F-TEQ pg/g LOD animal feed: GC-HRMS: 0.01-0.06 pg/g; GC-MS/MS: 0.02-0.08 pg/g Source : CVUA-MEL

Difference between GC-HRMS results and GC-MS/MS results TEQ (Upper bound) ~< 3 pg/g Poultry meat AL ML Organic Hen s eggs from Germany May 2010 Hens fed on feed manufactured in Holland from maize imported from Ukraine AL ML PCDD/F-TEQ pg/g AL ML LOD animal feed: GC-HRMS: 0.01-0.06 pg/g; GC-MS/MS: 0.02-0.08 pg/g

Dioxins / DBFs Total TEQ* for Bovine meat extract Analyte Analytical result TEF Value TEQ pg/g Fat pg/g Fat Dioxins 2378-TCDD 0.281 1 0.281 12378-PCDD 0.237 1 0.237 123478-HxCDD 0.001 0.1 0.0001 123678-HxCDD 0.575 0.1 0.0575 123789-HxCDD 0.040 0.1 0.004 1234678-HpCDD 0.663 0.01 0.00663 OCDD 0.209 0.0001 0.000021 Dioxins Total TEQ pg/g fat 0.586 Furans 2378-TCDF 0.037 0.1 0.0037 12378-PCDF 0.009 0.05 0.00045 23478-PCDF 3.289 0.5 1.6445 123478-HxCDF 1.475 0.1 0.1475 123678-HxCDF 1.539 0.1 0.1539 234678-HxCDF 1.584 0.1 0.1584 123789-HxCDF 0.002 0.1 0.0002 1234678-HpCDF 0.439 0.01 0.00439 1234789-HpCDF 0.108 0.01 0.00108 OCDF 0.356 0.0001 0.000036 Furans Total TEQ pg/g fat 2.114 Total (Dioxins + Furans)TEQ pg/g fat Max permitted level TEQ pg/g fat 2.70 3 *TEQ = Toxic Equivalent Concentration Total TEQ = Sum of analytical results for 17 Dx/DBFs, expressed as pg-teq/g Fat

ANABOLIC STEROIDS and other VETERINARY DRUGS

Application of the Agilent 7000B to the Determination of Anabolic Steroids in Veterinary Samples Dr Bruno Le Bizec School of Veterinary Medicine Nantes, France

Agilent 7000 TQ /LABERCA GROWTH PROMOTERS IN TISSUE - DETECTION AND IDENTIFICATION OF ANABOLIC STEROIDS BY GAS CHROMATOGRAPHY COUPLED TO TANDEM MASS SPECTROMETRY Some anabolic steroïds detected Molecules Type Transition 1 Collision T1 (ev) Transition 2 Collision T2 (ev) T R (min)* Estradiol-zeranol fraction 17a-estradiol AR 416.3>285.2 12 416.3>129.1 15 14.78 17ß-estradiol-d 3 EI 419.3>285.2 12 15.17 17ß-estradiol AR 416.3>285.2 12 416.3>129.1 15 15.20 Norgestrel EE 456.3>301.3 25 16.98 Zeranol-d 4 EI 437.3>295.2 25 16.57 Zeranol AR 433.3>295.2 25 523.4>433.3 25 16.60 Taleranol-d 4 EI 437.3>295.2 25 16.73 Taleranol AR 433.3>295.2 25 523.4>433.3 25 16.76 Molecules Type Transition 1 Collision T1 (ev) Transition 2 Collision T2 (ev) T R (min)* Trenbolone fraction 17a-trenbolone AR 380.3>323.3 20 449.3>307.3 20 16.00 17ß-trenbolone-d 2 EI 444.3>309.3 20 16.15 17ß-trenbolone AR 380.3>323.3 20 442.3>295.3 25 16.17

Molecules Type Transition 1 Collision T1 (ev) Transition 2 Collision T2 (ev) T R (min)* Faq Fraction androgènes-progestagènes 17a-nandrolone AR 418.3>194.1 20 418.3>182.1 15 14.45 1 17a-testosterone AR 432.3>209.2 18 432.3>247.2 18 14.82 1 17ß-nandrolone-d 3 EI 421.3>194.1 20 14.88 1 17ß-nandrolone AR 418.3>194.1 20 418.3>182.1 15 14.90 1 17ß-testosterone-d 2 EI 434.3>211.2 15 15.32 1 17ß-testosterone AR 432.3>209.2 15 432.3>247.2 25 15.33 1 Methyltestosterone-d 3 EI 449.3>301.3 25 16.24 2 Methyltestosterone AR 446.3>301.3 20 446.3>340.9 15 16.27 2 Progesterone AR 458.3>157.1 25 443.3>157.1 15 17.53 et 17.86 2 Megestrol-d 3 EI 561.4>224.2 25 18.60 3 Megestrol AR 558.4>236.2 25 558.4>453.3 25 18.63 3 Melengestrol-d 3 EI 573.4>73.0 25 18.84 3 Melengestrol AR 570.4>73.0 25 570.4>243.2 25 18.86 3 Medroxyprogesterone-d 3 EI 563.4>333.3 25 18.90 3 Medroxyprogesterone AR 560.4>315.3 25 560.4>328.3 25 18.92 3 Chlormadinone AR 578.4>143.1 25 578.4>473.3 25 21.03 3 Chromatographic conditions: column 30m 0.25µm 0.25 mm, splitless mode

Good repeatability on Tissue NTd3 10 injections Nortestosterone d3 Concentration 0.5 ppb

Good repeatability on Tissue NTd3 after10 injections more Nortestosterone d3

COMPOUND DISCOVERY APPROACHES

Screening 105 Veterinaries in Meat using Agilent 6530 RRLC-QTOF System Shanghai AQSIQ Lab Dr. XiaoJun DENG 2010-11-4 44

Results TIC of Standards and real samples Standards (5ng/mL) Meat sample (5ug/kg) 2010-11-4 2010-11-4 45 45

Result EIC 标品 5ng/mL 样品 5ug/kg 2010-11-4 2010-11-4 46 46

Results Accurate Mass 8.00 7.00 6.00 5.00 4.00 3.00 Error distribution plot of matrix sample -2ppm < 92% compounds < 2ppm Error (ppm) 2.00 1.00 0.00-1.00-2.00-3.00-4.00-5.00-6.00-7.00-8.00 Compound 2010-11-4 2010-11-4 47 47

PATHOGEN IDENTIFICATION

MultiMaTCH Genotyping (applied to food safety) Greg Richmond Molecular Preparation Team Agilent Laboratories Confidentiality Label

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