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PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains.
Her, Hsuan-Lin; Lin, Po-Ting; Wu, Yu-Wei.
Afiliación
  • Her HL; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, 92093, USA.
  • Lin PT; Department of Mechanical Engineering, National Taiwan University of Science and Technology, No.43, Keelung Rd., Sec.4, Da'an Dist., Taipei City, 10609, Taiwan. potinglin@mail.ntust.edu.tw.
  • Wu YW; Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei, 10609, Taiwan. potinglin@mail.ntust.edu.tw.
BMC Bioinformatics ; 22(1): 548, 2021 Nov 10.
Article en En | MEDLINE | ID: mdl-34758735
ABSTRACT

BACKGROUND:

Discerning genes crucial to antimicrobial resistance (AMR) mechanisms is becoming more and more important to accurately and swiftly identify AMR pathogenic strains. Pangenome-wide association studies (e.g. Scoary) identified numerous putative AMR genes. However, only a tiny proportion of the putative resistance genes are annotated by AMR databases or Gene Ontology. In addition, many putative resistance genes are of unknown function (termed hypothetical proteins). An annotation tool is crucially needed in order to reveal the functional organization of the resistome and expand our knowledge of the AMR gene repertoire.

RESULTS:

We developed an approach (PangenomeNet) for building co-functional networks from pan-genomes to infer functions for hypothetical genes. Using Escherichia coli as an example, we demonstrated that it is possible to build co-functional network from its pan-genome using co-inheritance, domain-sharing, and protein-protein-interaction information. The investigation of the network revealed that it fits the characteristics of biological networks and can be used for functional inferences. The subgraph consisting of putative meropenem resistance genes consists of clusters of stress response genes and resistance gene acquisition pathways. Resistome subgraphs also demonstrate drug-specific AMR genes such as beta-lactamase, as well as functional roles shared among multiple classes of drugs, mostly in the stress-related pathways.

CONCLUSIONS:

By demonstrating the idea of pan-genome-based co-functional network on the E. coli species, we showed that the network can infer functional roles of the genes, including those without functional annotations, and provides holistic views on the putative antimicrobial resistomes. We hope that the pan-genome network idea can help formulate hypothesis for targeted experimental works.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escherichia coli / Infecciones por Escherichia coli Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escherichia coli / Infecciones por Escherichia coli Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos