Whole-Genome Sequencing and Bioinformatics Analysis of Apiotrichum mycotoxinivorans: Predicting Putative Zearalenone-Degradation Enzymes.
Identifieur interne : 000009 ( Main/Exploration ); précédent : 000008; suivant : 000010Whole-Genome Sequencing and Bioinformatics Analysis of Apiotrichum mycotoxinivorans: Predicting Putative Zearalenone-Degradation Enzymes.
Auteurs : Jinyuan Sun [République populaire de Chine] ; Yan Xia [République populaire de Chine] ; Dengming Ming [République populaire de Chine]Source :
- Frontiers in microbiology [ 1664-302X ] ; 2020.
Abstract
Biological detoxification techniques have been developed by using microorganisms such as bacteria, yeast, and fungi to eliminate mycotoxin contamination. However, due to the lack of molecular details of related enzymes, the underlying mechanism of detoxification of many mycotoxins remain unclear. On the other hand, the next generation sequencing technology provides a large number of genomic data of microorganisms that can degrade mycotoxins, which makes it possible to use bioinformatics technology to study the molecular details of relevant enzymes. In this paper, we report the whole-genome sequencing of Apiotrichum mycotoxinivorans (Trichosporon mycotoxinivorans in old taxonomy) and the putative Baeyer-Villiger monooxygenases (BVMOs) and carboxylester hydrolases for zearalenone (ZEA) degradation through bioinformatic analysis. In particular, we developed a working pipeline for genome-scaled prediction of substrate-specific enzyme (GPSE, available at https://github.com/JinyuanSun/GPSE), which ultimately builds homologous structural and molecular docking models to demonstrate how the relevant degrading enzymes work. We expect that the enzyme-prediction woroflow process GPSE developed in this study might help accelerate the discovery of new detoxification enzymes.
DOI: 10.3389/fmicb.2020.01866
PubMed: 32849454
PubMed Central: PMC7416605
Affiliations:
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However, due to the lack of molecular details of related enzymes, the underlying mechanism of detoxification of many mycotoxins remain unclear. On the other hand, the next generation sequencing technology provides a large number of genomic data of microorganisms that can degrade mycotoxins, which makes it possible to use bioinformatics technology to study the molecular details of relevant enzymes. In this paper, we report the whole-genome sequencing of <i>Apiotrichum mycotoxinivorans</i> (<i>Trichosporon mycotoxinivorans</i> in old taxonomy) and the putative Baeyer-Villiger monooxygenases (BVMOs) and carboxylester hydrolases for zearalenone (ZEA) degradation through bioinformatic analysis. In particular, we developed a working pipeline for genome-scaled prediction of substrate-specific enzyme (GPSE, available at https://github.com/JinyuanSun/GPSE), which ultimately builds homologous structural and molecular docking models to demonstrate how the relevant degrading enzymes work. We expect that the enzyme-prediction woroflow process GPSE developed in this study might help accelerate the discovery of new detoxification enzymes.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32849454</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>28</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1664-302X</ISSN><JournalIssue CitedMedium="Print"><Volume>11</Volume><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>Frontiers in microbiology</Title><ISOAbbreviation>Front Microbiol</ISOAbbreviation></Journal><ArticleTitle>Whole-Genome Sequencing and Bioinformatics Analysis of <i>Apiotrichum mycotoxinivorans</i>: Predicting Putative Zearalenone-Degradation Enzymes.</ArticleTitle><Pagination><MedlinePgn>1866</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3389/fmicb.2020.01866</ELocationID><Abstract><AbstractText>Biological detoxification techniques have been developed by using microorganisms such as bacteria, yeast, and fungi to eliminate mycotoxin contamination. However, due to the lack of molecular details of related enzymes, the underlying mechanism of detoxification of many mycotoxins remain unclear. On the other hand, the next generation sequencing technology provides a large number of genomic data of microorganisms that can degrade mycotoxins, which makes it possible to use bioinformatics technology to study the molecular details of relevant enzymes. In this paper, we report the whole-genome sequencing of <i>Apiotrichum mycotoxinivorans</i> (<i>Trichosporon mycotoxinivorans</i> in old taxonomy) and the putative Baeyer-Villiger monooxygenases (BVMOs) and carboxylester hydrolases for zearalenone (ZEA) degradation through bioinformatic analysis. In particular, we developed a working pipeline for genome-scaled prediction of substrate-specific enzyme (GPSE, available at https://github.com/JinyuanSun/GPSE), which ultimately builds homologous structural and molecular docking models to demonstrate how the relevant degrading enzymes work. We expect that the enzyme-prediction woroflow process GPSE developed in this study might help accelerate the discovery of new detoxification enzymes.</AbstractText><CopyrightInformation>Copyright © 2020 Sun, Xia and Ming.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sun</LastName><ForeName>Jinyuan</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Xia</LastName><ForeName>Yan</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ming</LastName><ForeName>Dengming</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>03</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front Microbiol</MedlineTA><NlmUniqueID>101548977</NlmUniqueID><ISSNLinking>1664-302X</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Apiotrichum mycotoxinivorans</Keyword><Keyword MajorTopicYN="N">BVMO</Keyword><Keyword MajorTopicYN="N">carboxylesterase</Keyword><Keyword MajorTopicYN="N">genome-scaled prediction of substrate-specific enzyme (GPSE)</Keyword><Keyword MajorTopicYN="N">mycotoxin detoxification</Keyword><Keyword MajorTopicYN="N">whole-genome sequencing</Keyword><Keyword MajorTopicYN="N">zearalenone 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