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김동혁

Kim, Donghyuk
Systems Biology and Machine Learning Lab.
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dc.citation.endPage 3049 -
dc.citation.startPage 3040 -
dc.citation.title COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL -
dc.citation.volume 23 -
dc.contributor.author Ko, Seyoung -
dc.contributor.author Nguyen, Huynh Minh Triet -
dc.contributor.author Lee, Woojung -
dc.contributor.author Kim, Donghyuk -
dc.date.accessioned 2024-08-21T09:35:07Z -
dc.date.available 2024-08-21T09:35:07Z -
dc.date.created 2024-08-19 -
dc.date.issued 2024-12 -
dc.description.abstract Pathogenic Escherichia coli (E. coli) strains are distinguished by their diverse virulence factors, which contribute to a wide spectrum of diseases. These pathogens evolve through the horizontal transfer of virulence factors, resulting in the emergence of hybrid pathotypes with complex and heterogeneous characteristics. Recognizing their profound impact on public health, this study introduces the PIP-eco pipeline, a comprehensive analytical tool designed for the precise identification and characterization of E. coli pathotypes. This PIP-eco pipeline advances beyond traditional molecular techniques by facilitating detailed analysis of both single and hybrid pathotypes. It integrates targeted marker gene analysis, virulence factor-based phylogenetic analysis, and pathogenicity islands (PAIs) profiling to elucidate the genetic diversity of E. coli pathotypes and support their accurate classification. This integrative approach enables PIP-eco to uncover connections among various E. coli pathotypes, highlight shared virulence factors, and provide insights into their evolutionary trajectories. By utilizing experimentally validated marker genes, the pipeline ensures robust identification of pathotypes, particularly those of hybrid pathotypes. Additionally, PAI analysis offers comprehensive genetic investigations, revealing strain-specific variations and potential virulence mechanisms. As a result, the PIP-eco pipeline emerges as a useful tool for dissecting the evolutionary dynamics of E. coli and characterizing complex pathotypes, addressing the critical need for accurate detection and understanding of hybrid pathotypes. -
dc.identifier.bibliographicCitation COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, v.23, pp.3040 - 3049 -
dc.identifier.doi 10.1016/j.csbj.2024.07.017 -
dc.identifier.issn 2001-0370 -
dc.identifier.scopusid 2-s2.0-85199977058 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/83537 -
dc.identifier.wosid 001283972300001 -
dc.language 영어 -
dc.publisher ELSEVIER -
dc.title Developing the PIP-eco: An integrated genomic pipeline for identification and characterization of Escherichia coli pathotypes encompassing hybrid forms -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology -
dc.relation.journalResearchArea Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Escherichia coli -
dc.subject.keywordAuthor Hybrid pathotype -
dc.subject.keywordAuthor Classification tool -
dc.subject.keywordAuthor Comprehensive analysis -
dc.subject.keywordPlus MULTIPLE SEQUENCE ALIGNMENT -
dc.subject.keywordPlus PATHOGENICITY ISLANDS -
dc.subject.keywordPlus VIRULENCE -
dc.subject.keywordPlus EVOLUTION -
dc.subject.keywordPlus GENES -
dc.subject.keywordPlus RESISTANCE -
dc.subject.keywordPlus STRAIN -
dc.subject.keywordPlus MODEL -
dc.subject.keywordPlus PANEL -
dc.subject.keywordPlus IBEA -

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