Network-based genetic investigation of virulence-associated phenotypes in methicillin-resistant Staphylococcus aureus

Chan Yeong Kim, Muyoung Lee, Keehoon Lee, Sang Sun Yoon, Insuk Lee

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5 Citations (Scopus)


Staphylococcus aureus is a gram-positive bacterium that causes a wide range of infections. Recently, the spread of methicillin-resistant S. aureus (MRSA) strains has seriously reduced antibiotic treatment options. Anti-virulence strategies, the objective of which is to target the virulence instead of the viability of the pathogen, have become widely accepted as a means of avoiding the emergence of new antibiotic-resistant strains. To increase the number of anti-virulence therapeutic options, it is necessary to identify as many novel virulence-associated genes as possible in MRSA. Co-functional networks have proved useful for mapping gene-to-phenotype associations in various organisms. Herein, we present StaphNet (, a genome-scale co-functional network for an MRSA strain, S. aureus subsp. USA300-FPR3757. StaphNet, which was constructed by the integration of seven distinct types of genomics data within a Bayesian statistics framework, covers approximately 94% of the coding genome with a high degree of accuracy. We implemented a companion web server for network-based gene prioritization of the phenotypes of 31 different S. aureus strains. We demonstrated that StaphNet can effectively identify genes for virulence-associated phenotypes in MRSA. These results suggest that StaphNet can facilitate target discovery for the development of anti-virulence drugs to treat MRSA infection.

Original languageEnglish
Article number10796
JournalScientific reports
Issue number1
Publication statusPublished - 2018 Dec 1

Bibliographical note

Funding Information:
This work was supported by grants from the National Research Foundation of Korea (2017R1A2A2A05019987).

Publisher Copyright:
© 2018 The Author(s).

All Science Journal Classification (ASJC) codes

  • General


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