Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

被引：125

作者：

Kavvas, Erol S. ^{[1
]}

Catoiu, Edward ^{[1
]}

Mih, Nathan ^{[1
,2
]}

Yurkovich, James T. ^{[1
,2
]}

Seif, Yara ^{[1
]}

Dillon, Nicholas ^{[3
,4
]}

Heckmann, David ^{[1
]}

Anand, Amitesh ^{[1
]}

Yang, Laurence ^{[1
]}

Nizet, Victor ^{[3
,4
]}

Monk, Jonathan M. ^{[1
]}

Palsson, Bernhard O. ^{[1
,2
,3
]}

机构：

[1] Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA

[2] Univ Calif San Diego, Bioinformat & Syst Biol Program, La Jolla, CA 92093 USA

[3] Univ Calif San Diego, Dept Pediat, La Jolla, CA 92093 USA

[4] Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 USA

来源：

NATURE COMMUNICATIONS | 2018年 / 9卷

关键词：

PARA-AMINOSALICYLIC ACID; DRUG-RESISTANT; STREPTOMYCIN RESISTANCE; RIFAMPIN-RESISTANT; WIDE ASSOCIATION; EFFLUX PUMP; MUTATIONS; STRAINS; PROTEIN; INHA;

D O I：

10.1038/s41467-018-06634-y

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many publicly available datasets describing its AMR characteristics demand disparate data-type analyses. Here, we develop a reference strain-agnostic computational platform that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics. This platform is applied to 1595 sequenced strains to yield four key results. First, a pan-genome analysis shows that M. tuberculosis is highly conserved with sequenced variation concentrated in PE/PPE/PGRS genes. Second, the platform corroborates 33 genes known to confer resistance and identifies 24 new genetic signatures of AMR. Third, 97 epistatic interactions across 10 resistance classes are revealed. Fourth, detailed structural analysis of these genes yields mechanistic bases for their selection. The platform can be used to study other human pathogens.

引用

页数：9

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