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      Paired metagenomic and chemical evaluation of aflatoxin-contaminated dog kibble

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          Abstract

          Introduction

          Identification of chemical toxins from complex or highly processed foods can present ‘needle in the haystack’ challenges for chemists. Metagenomic data can be used to guide chemical toxicity evaluations by providing DNA-based description of the wholistic composition (eukaryotic, bacterial, protozoal, viral, and antimicrobial resistance) of foods suspected to harbor toxins, allergens, or pathogens. This type of information can focus chemistry-based diagnostics, improve hazard characterization and risk assessment, and address data gaps. Additionally, there is increasing recognition that simultaneously co-occurring mycotoxins, either from single or multiple species, can impact dietary toxicity exposure. Metagenomic data provides a way to address data gaps related to co-occurrence of multiple fungal species.

          Methods

          Paired metagenomic and chemical data were used to evaluate aflatoxin-contaminated kibble with known levels of specific mycotoxins. Kibble was ground to a fine powder for both chemical and molecular analyses. Chemical analyses were performed with Liquid Chromatography Mass Spectrometry (LCMS) and according to the AOAC Official method 2005.08: Aflatoxins in Corn, Raw Peanuts, and Peanut Butter using Liquid Chromatography with Post-Column Photochemical Derivatization. Metagenomes were created from DNA extracted from ground kibble and sequenced on an Illumina NextSeq 2000 with an average sequence depth of 180 million reads per replicate.

          Results and discussion

          Metagenomic data demonstrated that the abundance of DNA from putative aflatoxigenic Aspergillus spp. correlated with the levels of aflatoxin quantified by LCMS. Metagenomic data also identified an expansive range of co-occurring fungal taxa which may produce additional mycotoxins. DNA data paired with chemical data provides a novel modality to address current data gaps surrounding dietary mycotoxin exposure, toxigenic fungal taxonomy, and mycotoxins of emerging concern.

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          Most cited references36

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Anthony M. Bolger, Marc Lohse, Bjoern Usadel (2014)
          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Use of Ranks in One-Criterion Variance Analysis

            William H. Kruskal, W. Wallis (1952)
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              Sensitive protein alignments at tree-of-life scale using DIAMOND

              Benjamin Buchfink, Klaus Reuter, Hajk-Georg Drost (2021)
              We are at the beginning of a genomic revolution in which all known species are planned to be sequenced. Accessing such data for comparative analyses is crucial in this new age of data-driven biology. Here, we introduce an improved version of DIAMOND that greatly exceeds previous search performances and harnesses supercomputing to perform tree-of-life scale protein alignments in hours, while matching the sensitivity of the gold standard BLASTP. An updated version of DIAMOND uses improved algorithmic procedures and a customized high-performance computing framework to make seemingly prohibitive large-scale protein sequence alignments feasible.
              Article 0 comments Cited 677 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Andrea Ottesen: URI : https://loop.frontiersin.org/people/1945926/overviewRole: Role: Role: Role: Role: Role: Role: Role: Role:
                Brandon Kocurek: URI : https://loop.frontiersin.org/people/2637542/overviewRole: Role: Role: Role: Role: Role:
                Elizabeth Reed: URI : https://loop.frontiersin.org/people/565959/overviewRole: Role: Role: Role:
                Seth Commichaux: Role: Role: Role:
                Mark Mammel: URI : https://loop.frontiersin.org/people/345956/overviewRole: Role: Role:
                Padmini Ramachandran: URI : https://loop.frontiersin.org/people/626945/overviewRole:
                Patrick McDermott: URI : https://loop.frontiersin.org/people/456558/overviewRole:
                Brenna M. Flannery: URI : https://loop.frontiersin.org/people/1165773/overviewRole:
                Errol Strain: URI : https://loop.frontiersin.org/people/580047/overviewRole:
                Journal
                Journal ID (nlm-ta): Front Vet Sci
                Journal ID (iso-abbrev): Front Vet Sci
                Journal ID (publisher-id): Front. Vet. Sci.
                Title: Frontiers in Veterinary Science
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2297-1769
                Publication date (Electronic): 11 April 2024
                Publication date Collection: 2024
                Volume: 11
                Electronic Location Identifier: 1374839
                Affiliations
                [1] 1Center for Veterinary Medicine (CVM), U.S. Food and Drug Administration , Laurel, MD, United States
                [2] 2Center for Food Safety and Applied Nutrition (CFSAN), U.S. Food and Drug Administration , College Park, MD, United States
                Author notes

                Edited by: Kai Wang, Chinese Academy of Agricultural Sciences, China

                Reviewed by: Aisha Khatoon, University of Agriculture, Faisalabad, Pakistan

                Bishwo Adhikari, Animal and Plant Health Inspection Service (USDA), United States

                *Correspondence: Andrea Ottesen, Andrea.Ottesen@ 123456fda.hhs.gov
                Article
                DOI: 10.3389/fvets.2024.1374839
                PMC ID: 11043538
                PubMed ID: 38665771
                SO-VID: 8ef0c38c-518f-4e8d-9a8b-889f5d566cbc
                Copyright © Copyright © 2024 Ottesen, Kocurek, Reed, Commichaux, Mammel, Ramachandran, McDermott, Flannery and Strain.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 22 January 2024
                Date accepted : 25 March 2024
                Page count
                Figures: 6, Tables: 2, Equations: 0, References: 43, Pages: 9, Words: 5818
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Subject: Veterinary Science
                Subject: Original Research
                Custom metadata
                section-at-acceptance Animal Nutrition and Metabolism

                Keywords: metagenome,metagenomic,chemical,aflatoxin,kibble,aspergillus
                Data availability:
                Keywords: metagenome, metagenomic, chemical, aflatoxin, kibble, aspergillus

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