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细菌全基因组关联研究(bGWAS)和转录组学鉴定了……中的隐性抗菌耐药机制

Bacterial Genome Wide Association Studies (bGWAS) and Transcriptomics Identifies Cryptic Antimicrobial Resistance Mechanisms in .

作者信息

Roe Chandler, Williamson Charles H D, Vazquez Adam J, Kyger Kristen, Valentine Michael, Bowers Jolene R, Phillips Paul D, Harrison Veronica, Driebe Elizabeth, Engelthaler David M, Sahl Jason W

机构信息

Northern Arizona University, Flagstaff, AZ, United States.

Translational Genomics Research Institute, Flagstaff, AZ, United States.

出版信息

Front Public Health. 2020 Sep 2;8:451. doi: 10.3389/fpubh.2020.00451. eCollection 2020.

Abstract

Antimicrobial resistance (AMR) in the nosocomial pathogen, , is becoming a serious public health threat. While some mechanisms of AMR have been reported, understanding novel mechanisms of resistance is critical for identifying emerging resistance. One of the first steps in identifying novel AMR mechanisms is performing genotype/phenotype association studies; however, performing these studies is complicated by the plastic nature of the pan-genome. In this study, we compared the antibiograms of 12 antimicrobials associated with multiple drug families for 84 isolates, many isolated in Arizona, USA. screening of these genomes for known AMR mechanisms failed to identify clear correlations for most drugs. We then performed a bacterial genome wide association study (bGWAS) looking for associations between all possible 21-mers; this approach generally failed to identify mechanisms that explained the resistance phenotype. In order to decrease the genomic noise associated with population stratification, we compared four phylogenetically-related pairs of isolates with differing susceptibility profiles. RNA-Sequencing (RNA-Seq) was performed on paired isolates and differentially-expressed genes were identified. In these isolate pairs, five different potential mechanisms were identified, highlighting the difficulty of broad AMR surveillance in this species. To verify and validate differential expression, amplicon sequencing was performed. These results suggest that a diagnostic platform based on gene expression rather than genomics alone may be beneficial in certain surveillance efforts. The implementation of such advanced diagnostics coupled with increased AMR surveillance will potentially improve infection treatment and patient outcomes.

摘要

医院病原体中的抗菌药物耐药性(AMR)正成为严重的公共卫生威胁。虽然已经报道了一些AMR机制,但了解新的耐药机制对于识别新出现的耐药性至关重要。识别新的AMR机制的第一步是进行基因型/表型关联研究;然而,由于泛基因组的可塑性,进行这些研究变得复杂。在本研究中,我们比较了84株分离株对12种与多个药物家族相关的抗菌药物的抗菌谱,其中许多分离株来自美国亚利桑那州。对这些基因组进行已知AMR机制的筛选未能发现大多数药物的明确相关性。然后,我们进行了细菌全基因组关联研究(bGWAS),寻找所有可能的21聚体之间的关联;这种方法通常未能识别出解释耐药表型的机制。为了减少与群体分层相关的基因组噪声,我们比较了四对系统发育相关的分离株,它们具有不同的药敏谱。对配对的分离株进行了RNA测序(RNA-Seq),并鉴定了差异表达基因。在这些分离株对中,确定了五种不同的潜在机制,突出了该物种广泛AMR监测的难度。为了验证差异表达,进行了扩增子测序。这些结果表明,基于基因表达而非仅基于基因组学的诊断平台在某些监测工作中可能是有益的。实施这种先进的诊断方法并加强AMR监测可能会改善感染治疗和患者预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d95/7493718/71e4c288b860/fpubh-08-00451-g0001.jpg

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