Subramanian Devika, Natarajan Jeyakumar
Department of Bioinformatics, Data Mining and Text Mining Laboratory, Bharathiar University, Coimbatore, Tamil Nadu, India.
Indian J Med Microbiol. 2019 Apr-Jun;37(2):173-185. doi: 10.4103/ijmm.IJMM_18_311.
Vancomycin-intermediate Staphylococcus aureus remains one of the most prevalent multidrug-resistant pathogens causing healthcare infections that are difficult to treat.
This study uses a comprehensive computational analysis to systematically investigate various gene expression profiles of resistant and sensitive S. aureus strains on exposure to antibiotics.
The transcriptional changes leading to the development of multiple antibiotic resistance were examined by an integrative analysis of nine differential expression experiments under selected conditions of vancomycin-intermediate and -sensitive strains for four different antibiotics using publicly available RNA-Seq datasets.
For each antibiotic, three experimental conditions for expression analysis were selected to identify those genes that are particularly involved in the development of resistance. The results were further scrutinised to generate a resistome that can be analysed for their role in the development or adaptation to antibiotic resistance.
The 99 genes in the resistome are then compiled to create a multiple drug resistome of 25 known and novel genes identified to play a part in antibiotic resistance. The inclusion of agr genes and associated virulence factors in the identified resistome supports the role of agr quorum sensing system in multiple drug resistance. In addition, enrichment analysis also identified the kyoto encyclopedia of genes and genomes (KEGG) pathways - quorum sensing and two-component system pathways - in the resistome gene set.
Further studies on understanding the role of the identified molecular targets such as SAA6008_00181, SAA6008_01127, agrA, agrC and coa in adapting to the pressure of antibiotics at sub-inhibitory concentrations can help in learning the molecular mechanisms causing resistance to the pathogens as well as finding other potential therapeutics.
万古霉素中介金黄色葡萄球菌仍然是引起难以治疗的医疗保健感染的最普遍的多重耐药病原体之一。
本研究使用全面的计算分析系统地研究耐药和敏感金黄色葡萄球菌菌株在接触抗生素时的各种基因表达谱。
通过对公开可用的RNA-Seq数据集在万古霉素中介和敏感菌株针对四种不同抗生素的选定条件下的九个差异表达实验进行综合分析,研究导致多重抗生素耐药性产生的转录变化。
对于每种抗生素,选择三个用于表达分析的实验条件,以鉴定那些特别参与耐药性产生的基因。对结果进行进一步审查以生成一个耐药基因组,可分析其在抗生素耐药性产生或适应中的作用。
然后汇编耐药基因组中的99个基因,以创建一个包含25个已知和新发现基因的多重耐药基因组,这些基因被确定在抗生素耐药性中起作用。在鉴定出的耐药基因组中纳入agr基因和相关毒力因子支持了agr群体感应系统在多重耐药性中的作用。此外,富集分析还在耐药基因组基因集中鉴定出京都基因与基因组百科全书(KEGG)途径——群体感应和双组分系统途径。
进一步研究理解已鉴定的分子靶点如SAA6008_00181、SAA6008_01127、agrA、agrC和coa在适应亚抑菌浓度抗生素压力中的作用,有助于了解病原体产生耐药性的分子机制以及寻找其他潜在治疗方法。