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Record W7020821333

Multi-Class Liquid Chromatography-High Resolution Mass Spectrometry Methods for Monitoring of Mycotoxins and Metabolites in Human Plasma for Exposure Studies

2020· dissertation· en· W7020821333 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2020
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
Fundersnot available
KeywordsMycotoxinOchratoxin AFumonisinAflatoxinFumonisin B1OchratoxinZeranolMass spectrometryProtein precipitationBioanalysis
DOInot available

Abstract

fetched live from OpenAlex

Mycotoxins are secondary metabolites produced by fungi that can pose a serious threat to human and animal health due to their toxicity. The assessment of human chronic exposure to mycotoxins requires reliable and highly sensitive multi-analyte assay(s) enabling simultaneous measurements of common toxicologically important mycotoxins and their metabolites in human plasma. \nThe first goal of the thesis was to develop sensitive liquid chromatography – high-resolution mass spectrometry (LC-HRMS) multi-mycotoxin method(s) for the detection and quantification of common toxicologically important mycotoxins frequently occurring in Canada and emerging mycotoxins of interest. Based on the results of extraction recoveries and chromatographic separation, two LC-HRMS methods were required to cover the full mycotoxin panel of interest. The first method combined liquid-liquid extraction with pentafluorophenyl reversed-phase LC-HRMS for the quantification of 17 mycotoxins, aflatoxins B1, B2, G1 and G2, zearalenone, 7-α-hydroxy-zearalenol (α-ZOL), 7-β-hydroxy-zearalenol, zearalanone, 7-α-hydroxy-zearalanol, 7-β-hydroxy-zearalanol, T-2 toxin, HT-2 toxin, deoxynivalenol, nivalenol, 15-acetyldeoxynivalenol, 3-acetyldeoxynivalenol and fusarenon X. The method was validated using procedures described in the Food and Drug Administration (FDA) guidance for Industry Bioanalytical Method Validation. Lower limits of quantification (LLOQs) ranged from 0.1 to 0.5 ng/ml, except for nivalenol (3 ng/ml). The method (intra-day and inter-day) accuracy and precision ranged from 85.6% to 116.4% and from 1.6% to 15.6% RSD, respectively, excluding α-ZOL for which an accuracy of 72.9 % to 97.2% was observed. The second method covered ten mycotoxins, fumonisin B1, fumonisin B2, ochratoxin α (OTα), citrinin, ochratoxin A, beauvericin, enniatin A, enniatin A1 (ENNA1), enniatin B (ENNB) and enniatin B1, and combined methanol protein precipitation with C18 reversed-phase chromatography and polarity-switching LC-HRMS. LLOQs ranged from 1.25 to 4 ng/ml. Absolute recovery ranged from 86.6% to 127.7% in individual plasma samples. Significant matrix effects were observed for OTα (77.5%) in one out of ten individual plasma samples and fumonisins (134.8% to 167.8%), ENNB (69.7% to 79.4%) and ENNA (69.3% to 79.2%) in all individual plasma samples. The rest of the mycotoxins showed negligible matrix effects ranging from 87.2% to 112.2% in all lots of plasma tested. \nExcellent LLOQs, negligible matrix effects and accurate quantitation capability of the first method coupled with the lower cost of analysis per sample make the method suitable for large-scale analysis of human plasma samples. The second method is also simple and low cost but requires additional modification to further improve LLOQs and reduce the matrix effect before full validation and implementation. Both methods are versatile and can be applied for retrospective analysis and other applications such as metabolism studies due to the use of HRMS and superior chromatographic separation. To show this capability, the first method was successfully applied for the in-depth metabolism studies of 17 mycotoxins. The method showed excellent suitability and advantages for the detection of various mycotoxin metabolites from Phase I metabolism and glucuronidation obtained from human microsomal incubations. Two ppm mass accuracy with internal mass calibration reduced the number of possible elemental formulas for a measured m/z value. Data-dependent acquisition in combination with collision-induced dissociation or higher energy collisional dissociation was used to ensure adequate fragmentation and to study the structure of the mycotoxin metabolites. The Compound Discoverer 2.1 software, which contains extensive libraries of common metabolic pathways and mass spectral libraries, was used to streamline the identification and the characterization of the metabolites. In total, 188 mycotoxin metabolites were generated, characterized and used to build an extensive in-house library of human mycotoxin metabolites. One hundred metabolites were reported for the first time, showing the power and sensitivity of the approach. For these 17 mycotoxins, 92 metabolites were previously described in literature, and among these known metabolites only four could not be generated using our approach. Currently, this is the most comprehensive LC-MS library of human mycotoxin metabolites. \nIn conclusion, both LC-MS methods and the in-house mycotoxin metabolite library will allow the monitoring of 27 mycotoxins and their 188 metabolites in large-scale biomonitoring studies. In the long-term, this will help to prioritize metabolites that should be routinely included during exposure monitoring studies and will provide important new data on mycotoxin exposure of the Canadian population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.333
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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