Department of Medicine and Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, USA.
Department of Medicine and Department of Anatomic and Clinical Pathology, Tufts University School of Medicine, Boston, Massachusetts, USA.
Antimicrob Agents Chemother. 2024 May 2;68(5):e0118523. doi: 10.1128/aac.01185-23. Epub 2024 Apr 8.
Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in (Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.
抗生素暴露后细菌的转录反应为了解抗生素作用机制、细菌反应和抗菌药物耐药性特征提供了线索。我们旨在通过汇集和分析 Mtb 微阵列和 RNA-seq 数据集,定义临床相关药物中 (Mtb) 分离株的转录抗生素反应(TAR)。我们生成了 17 种抗生素的 99 种抗生素转录谱,其中 76%的谱使用 3-24 小时的抗生素暴露生成,49%的谱在世界卫生组织抗生素临界浓度的一个倍增期内生成。TAR 基因具有时间依赖性,并且主要与抗生素作用机制特异性相关。TAR 特征在预测抗生素暴露方面表现良好,上调基因的接受者操作特征曲线(AUC)范围为 0.84-1.00(TAR <6 小时的抗生素暴露)和 0.76-1.00(>6 小时的抗生素暴露),下调基因的 AUC 范围分别为 0.57-0.90 和 0.87-1.00。这项工作表明,转录组学可以在 Mtb 暴露 6 小时内评估抗生素的活性。