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Network-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa

DC Field Value Language
dc.contributor.author윤상선-
dc.date.accessioned2017-02-27T07:30:37Z-
dc.date.available2017-02-27T07:30:37Z-
dc.date.issued2016-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/146899-
dc.description.abstractPseudomonas aeruginosa is a Gram-negative bacterium of clinical significance. Although the genome of PAO1, a prototype strain of P. aeruginosa, has been extensively studied, approximately one-third of the functional genome remains unknown. With the emergence of antibiotic-resistant strains of P. aeruginosa, there is an urgent need to develop novel antibiotic and anti-virulence strategies, which may be facilitated by an approach that explores P. aeruginosa gene function in systems-level models. Here, we present a genome-wide functional network of P. aeruginosa genes, PseudomonasNet, which covers 98% of the coding genome, and a companion web server to generate functional hypotheses using various network-search algorithms. We demonstrate that PseudomonasNet-assisted predictions can effectively identify novel genes involved in virulence and antibiotic resistance. Moreover, an antibiotic-resistance network based on PseudomonasNet reveals that P. aeruginosa has common modular genetic organisations that confer increased or decreased resistance to diverse antibiotics, which accounts for the pervasiveness of cross-resistance across multiple drugs. The same network also suggests that P. aeruginosa has developed mechanism of trade-off in resistance across drugs by altering genetic interactions. Taken together, these results clearly demonstrate the usefulness of a genome-scale functional network to investigate pathogenic systems in P. aeruginosa.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherNature Publishing Group-
dc.relation.isPartOfSCIENTIFIC REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHComputational Biology-
dc.subject.MESHDrug Resistance, Bacterial*-
dc.subject.MESHGene Regulatory Networks-
dc.subject.MESHGenes, Bacterial-
dc.subject.MESHPseudomonas aeruginosa/drug effects*-
dc.subject.MESHPseudomonas aeruginosa/pathogenicity*-
dc.subject.MESHSystems Biology-
dc.subject.MESHVirulence Factors/analysis*-
dc.titleNetwork-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa-
dc.typeArticle-
dc.publisher.locationEngland-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Microbiology-
dc.contributor.googleauthorSohyun Hwang-
dc.contributor.googleauthorChan Yeong Kim-
dc.contributor.googleauthorSun-Gou Ji-
dc.contributor.googleauthorJunhyeok Go-
dc.contributor.googleauthorHanhae Kim-
dc.contributor.googleauthorSunmo Yang-
dc.contributor.googleauthorHye Jin Kim-
dc.contributor.googleauthorAra Cho-
dc.contributor.googleauthorSang Sun Yoon-
dc.contributor.googleauthorInsuk Lee-
dc.identifier.doi10.1038/srep26223-
dc.contributor.localIdA02558-
dc.relation.journalcodeJ02646-
dc.identifier.eissn2045-2322-
dc.identifier.pmid27194047-
dc.contributor.alternativeNameYoon, Sang Sun-
dc.contributor.affiliatedAuthorYoon, Sang Sun-
dc.citation.volume6-
dc.citation.startPage26223-
dc.identifier.bibliographicCitationSCIENTIFIC REPORTS, Vol.6 : 26223, 2016-
dc.date.modified2017-02-24-
dc.identifier.rimsid46465-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Microbiology (미생물학교실) > 1. Journal Papers

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