Antimicrobial susceptibility associations in Acinetobacter baumannii based on genomic and transcriptomic analyses

 描述（由申请方提供）：鲍曼不动杆菌是一种危险的医院内病原体，与临床感染中的抗菌药物耐药性相关。虽然传统的抗菌素耐药性表征依赖于研究或临床实验室的敏感性测试，但基于全基因组序列（WGS）数据的分析，现在可以使用耐药相关基因数据库来表征耐药谱。在这项研究中，我们建议对100株目前具有相关耐药性数据的分离株进行测序，以便更好地了解与耐药性相关的机制。将根据共享的系统发育史，比较成对耐药/敏感分离株的WGS数据，以确定与耐药表型相关的单核苷酸多态性（SNP）和编码区。本研究将采用全基因组关联研究（GWAS）来鉴定与抗菌素耐药表型相关的SNP和基因。除了对这些分离株进行测序外，我们还建议全面表征抗菌素耐药性谱，以将特定的抗菌素与特定的遗传特征相关联。预计这些结果将产生比目前存在的更准确和描述性的基因型/表型关联。除了基因组学方法外，还提出了转录组学方法，以更好地了解基因表达对抗菌素耐药表型的贡献。我们将对在含和不含亚抑制浓度抗菌剂的培养基中生长的成对耐药/敏感分离株提取的RNA进行测序。将在成对分离株之间鉴定差异基因表达，以发现抗菌素耐药性和基因表达之间的相关性。将采用定量逆转录酶聚合酶链反应（qRT-PCR）检测其他抗菌剂，以确定观察到的转录差异是否与多种抗菌剂相关。总的来说，这项拟议的工作预计将确定与抗菌素耐药性相关的新机制，并增加先前相关机制的靶特异性。这些目标不仅有助于设计更有信息量的诊断方法，而且还有助于准确检测抗菌素耐药性，这也将有助于更及时和更有针对性地治疗耐药的临床感染。

 DESCRIPTION (provided by applicant): Acinetobacter baumannii is a dangerous nosocomial pathogen associated with antimicrobial resistance in clinical infections. Although traditional antimicrobial resistance characterization relies on susceptibility testing in research or clinical laboratories, databases of resistance-associated genes are now available to characterize resistance profiles, based on the analysis of whole-genome sequence (WGS) data. In this study, we propose to sequence 100 isolates that currently have associated antimicrobial resistance data in order to better understand mechanisms associated with antimicrobial resistance. WGS data from paired resistant/susceptible isolates, based on a shared phylogenetic history, will be compared to identify both single nucleotide polymorphisms (SNPs) and coding regions associated with the resistance phenotype. A genome-wide association study (GWAS) will be employed in this study to identify SNPs and genes associated with the antimicrobial resistance phenotype. In addition to sequencing these isolates, we also propose to comprehensively characterize the antimicrobial resistance profile to associate specific antimicrobials with specific genetic features. These results are expected to generate more accurate and descriptive genotype/phenotype associations than currently exist. In addition to genomics approaches, transcriptomic methods are proposed to better understand the contribution of gene expression to the antimicrobial resistance phenotype. We will sequence extracted RNA from paired resistant/susceptible isolates grown in media with and without sub-inhibitory concentrations of antimicrobials. Differential gene expression will be identified between paired isolates to find correlations between antimicrobial resistance and gene expression. Additional antimicrobials will be tested with quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) to identify if observed transcriptional differences are associated with multiple classes of antimicrobials. In general, this proposed work is anticipated to identify novel mechanisms associated with antimicrobial resistance as well as increase the target specificity of previously associated mechanisms. These goals will not only help in the design of more informative diagnostics, but will also aid in accurate detection of antimicrobial resistance, which will also help in the more timely and focused treatment of resistant clinical infections.