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Pathogens. 2014 Apr 15;3(2):356-76. doi: 10.3390/pathogens3020356.

Characterization of Antimicrobial Resistance Dissemination across Plasmid Communities Classified by Network Analysis.

Author information

1
Pathogen Genomics Center, National institute of infectious diseases, 1-23-1 Toyama, Shinjuku-ku, Tokyo 162-8640, Japan. uhmin@niid.go.jp.
2
Pathogen Genomics Center, National institute of infectious diseases, 1-23-1 Toyama, Shinjuku-ku, Tokyo 162-8640, Japan. sekizuka@niid.go.jp.
3
Pathogen Genomics Center, National institute of infectious diseases, 1-23-1 Toyama, Shinjuku-ku, Tokyo 162-8640, Japan. makokuro@niid.go.jp.

Abstract

The global clustering of gene families through network analysis has been demonstrated in whole genome, plasmid, and microbiome analyses. In this study, we carried out a plasmidome network analysis of all available complete bacterial plasmids to determine plasmid associations. A blastp clustering search at 100% aa identity cut-off and sharing at least one gene between plasmids, followed by a multilevel community network analysis revealed that a surprisingly large number of the plasmids were connected by one largest connected component (LCC), with dozens of community sub-groupings. The LCC consisted mainly of Bacilli and Gammaproteobacteria plasmids. Intriguingly, horizontal gene transfer (HGT) was noted between different phyla (i.e., Staphylococcus and Pasteurellaceae), suggesting that Pasteurellaceae can acquire antimicrobial resistance (AMR) genes from closely contacting Staphylococcus spp., which produce the external supplement of V-factor (NAD). Such community network analysis facilitate displaying possible recent HGTs like a class 1 integron, str and tet resistance markers between communities. Furthermore, the distribution of the Inc replicon type and AMR genes, such as the extended-spectrum ß-lactamase (ESBL) CTX-M or the carbapenemases KPC NDM-1, implies that such genes generally circulate within limited communities belonging to typical bacterial genera. Thus, plasmidome network analysis provides a remarkable discriminatory power for plasmid-related HGT and evolution.

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