Shestov Maksim, Ontañón Santiago, Tozeren Aydin
School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA.
College of Computing and Informatics, Drexel University, Philadelphia, PA, USA.
BMC Genomics. 2015 Oct 13;16:773. doi: 10.1186/s12864-015-1957-7.
Bacterial infections comprise a global health challenge as the incidences of antibiotic resistance increase. Pathogenic potential of bacteria has been shown to be context dependent, varying in response to environment and even within the strains of the same genus.
We used the KEGG repository and extensive literature searches to identify among the 2527 bacterial genomes in the literature those implicated as pathogenic to the host, including those which show pathogenicity in a context dependent manner. Using data on the gene contents of these genomes, we identified sets of genes highly abundant in pathogenic but relatively absent in commensal strains and vice versa. In addition, we carried out genome comparison within a genus for the seventeen largest genera in our genome collection. We projected the resultant lists of ortholog genes onto KEGG bacterial pathways to identify clusters and circuits, which can be linked to either pathogenicity or synergy. Gene circuits relatively abundant in nonpathogenic bacteria often mediated biosynthesis of antibiotics. Other synergy-linked circuits reduced drug-induced toxicity. Pathogen-abundant gene circuits included modules in one-carbon folate, two-component system, type-3 secretion system, and peptidoglycan biosynthesis. Antibiotics-resistant bacterial strains possessed genes modulating phagocytosis, vesicle trafficking, cytoskeletal reorganization, and regulation of the inflammatory response. Our study also identified bacterial genera containing a circuit, elements of which were previously linked to Alzheimer's disease.
Present study produces for the first time, a signature, in the form of a robust list of gene circuitry whose presence or absence could potentially define the pathogenicity of a microbiome. Extensive literature search substantiated a bulk majority of the commensal and pathogenic circuitry in our predicted list. Scanning microbiome libraries for these circuitry motifs will provide further insights into the complex and context dependent pathogenicity of bacteria.
随着抗生素耐药性发生率的增加,细菌感染构成了一项全球性的健康挑战。已表明细菌的致病潜力取决于环境,会因环境甚至同一属内的菌株不同而有所变化。
我们利用KEGG数据库和广泛的文献检索,在文献中的2527个细菌基因组中,识别出那些对宿主致病的基因组,包括那些以环境依赖方式表现出致病性的基因组。利用这些基因组的基因内容数据,我们识别出在致病菌株中高度丰富但在共生菌株中相对缺乏的基因集,反之亦然。此外,我们对基因组集合中17个最大的属进行了属内基因组比较。我们将直系同源基因的结果列表投射到KEGG细菌通路中,以识别可与致病性或协同作用相关联的簇和回路。在非致病细菌中相对丰富的基因回路通常介导抗生素的生物合成。其他与协同作用相关的回路降低了药物诱导的毒性。富含病原体的基因回路包括一碳叶酸、双组分系统、III型分泌系统和肽聚糖生物合成中的模块。抗生素耐药细菌菌株拥有调节吞噬作用、囊泡运输、细胞骨架重组和炎症反应调节的基因。我们的研究还识别出含有一个回路的细菌属,其部分元件先前与阿尔茨海默病有关。
本研究首次产生了一种特征,以一份强大的基因回路列表的形式呈现,其存在与否可能潜在地定义微生物群的致病性。广泛的文献检索证实了我们预测列表中大部分的共生和致病回路。扫描微生物组文库中的这些回路基序将为细菌复杂且依赖环境的致病性提供进一步的见解。