TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities.
TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities.
复制标题
DOI：
10.1371/journal.ppat.1006939
复制
发表时间：
2018-03
期刊：
影响因子：
6.7
通讯作者：
Fortune SM
中科院分区：
文献类型：
--
作者：
Carey AF;Rock JM;Krieger IV;Chase MR;Fernandez-Suarez M;Gagneux S;Sacchettini JC;Ioerger TR;Fortune SM
一旦被认为是一种表型单态性细菌，就有越来越多的工作证明结核分枝杆菌（Mtb）菌株在临床相关特征（包括毒力和对抗生素的反应）中的异质性。然而，Mtb菌株之间大多数表型差异的遗传和分子基础仍然未知。为了研究Mtb菌株变异的基础，我们对一组Mtb临床分离株和参考菌株H37 Rv进行了全基因组转座子突变并结合下一代测序（TnSeq），以比较这些菌株体外生长的遗传要求。我们开发了一种分析方法，以确定这些遗传多样性菌株之间的遗传要求的定量差异，这些菌株在基因组结构和基因含量上各不相同。使用这种方法，我们发现菌株之间的差异，在他们的要求基因参与基本的细胞过程，包括氧化还原稳态和中央碳代谢。在具有不同要求的基因中，有katG，它编码一线抗结核药物异烟肼的激活剂，和glcB，它编码苹果酸合酶，一种新的小分子抑制剂的靶点。不同菌株对katG和glcB的需求差异预测了它们对这些抗菌剂的反应差异。重要的是，抗生素反应的这些菌株特异性差异不能通过全基因组测序或基因表达分析鉴定的遗传变异来预测。我们的研究结果为Mtb菌株之间的变异基础提供了新的见解，并证明TnSeq是一种可扩展的方法来预测Mtb菌株之间临床上重要的表型差异。由结核分枝杆菌（Mycobacterium tuberculosis，Mtb）引起的结核病仍然是严重的全球健康问题，每年在全世界造成约150万人死亡。与其他细菌病原体一样，结核分枝杆菌菌株之间的多样性导致感染结果、疫苗有效性和对抗生素治疗反应的差异。目前，导致结核分枝杆菌菌株变异的重要遗传差异仍然知之甚少。在这项研究中，我们应用了一种称为TnSeq的功能基因组学技术来研究结核分枝杆菌临床菌株的遗传基础。我们确定了一些基因的差异，需要在这些菌株的文化中的增长。其中一些基因与抗生素的反应有关，包括一线抗结核药物异烟肼和目前正在开发的一种新型抗结核药物。我们发现TnSeq发现的菌株之间的遗传差异预测了对这些抗生素的反应。我们的结果证明了TnSeq用于鉴定Mtb菌株之间的临床相关差异的实用性。
Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains. Tuberculosis, caused by the bacterium Mycobacterium tuberculosis (Mtb), remains a serious global health problem, causing ~1.5 million deaths a year world-wide. Like other bacterial pathogens, diversity among strains of Mtb contributes to differences in infection outcomes, vaccine efficacy, and response to antibiotic treatment. Currently, the important genetic differences that contribute to variation among Mtb strains remain poorly understood. In this study, we applied a functional genomics technique called TnSeq to a panel of Mtb clinical strains to investigate the genetic basis of strain diversity. We identified a number of genes that are differentially required for growth in culture among these strains. Some of these genes are involved in the response to antibiotics, including the first-line antitubercular agent isoniazid and a novel antitubercular drug currently in development. We found that the genetic differences between strains uncovered by TnSeq predicted responses to these antibiotics. Our results demonstrate the utility of TnSeq for identifying clinically relevant differences among Mtb strains.