Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations

被引:4
|
作者
Green, Anna G. [1 ]
Vargas Jr, Roger [1 ,2 ]
Marin, Maximillian G. [1 ]
Freschi, Luca [1 ]
Xie, Jiaqi [3 ]
Farhat, Maha R. [1 ,4 ]
机构
[1] Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA
[2] Harvard Med Sch, Ctr Computat Biomed, Boston, MA USA
[3] Johns Hopkins Sch Med, Dept Genet, Baltimore, MD USA
[4] Massachusetts Gen Hosp, Div Pulm & Crit Care Med, Boston, MA 02114 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
computational biology; microbiology; mycobacterium; microbial genomics; microbial evolution; ACETYLTRANSFERASE EIS; ANTIBIOTIC-RESISTANCE; GENE CONVERSION; SEQUENCE; EPISTASIS; EMERGENCE; EVOLUTION; RECOMBINATION; SELECTION; REVEALS;
D O I
10.1093/molbev/msad131
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Pathogenic microorganisms are in a perpetual struggle for survival in changing host environments, where host pressures necessitate changes in pathogen virulence, antibiotic resistance, or transmissibility. The genetic basis of phenotypic adaptation by pathogens is difficult to study in vivo. In this work, we develop a phylogenetic method to detect genetic dependencies that promote pathogen adaptation using 31,428 in vivo sampled Mycobacterium tuberculosis genomes, a globally prevalent bacterial pathogen with increasing levels of antibiotic resistance. We find that dependencies between mutations are enriched in antigenic and antibiotic resistance functions and discover 23 mutations that potentiate the development of antibiotic resistance. Between 11% and 92% of resistant strains harbor a dependent mutation acquired after a resistance-conferring variant. We demonstrate the pervasiveness of genetic dependency in adaptation of naturally evolving populations and the utility of the proposed computational approach.
引用
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页数:16
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