The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
Clin Pharmacol Ther. 2019 Sep;106(3):512-524. doi: 10.1002/cpt.1535. Epub 2019 Jul 22.
Antibiotic-resistant organisms (AROs) are a major concern to public health worldwide. While antibiotics have been naturally produced by environmental bacteria for millions of years, modern widespread use of antibiotics has enriched resistance mechanisms in human-impacted bacterial environments. Antibiotic resistance genes (ARGs) continue to emerge and spread rapidly. To combat the global threat of antibiotic resistance, researchers must develop methods to rapidly characterize AROs and ARGs, monitor their spread across space and time, and identify novel ARGs and resistance pathways. We review how high-throughput sequencing-based methods can be combined with classic culture-based assays to characterize, monitor, and track AROs and ARGs. Then, we evaluate genomic and metagenomic methods for identifying ARGs and biosynthetic pathways for novel antibiotics from genomic data sets. Together, these genomic analyses can improve surveillance and prediction of emerging resistance threats and accelerate the development of new antibiotic therapies to combat resistance.
抗药性生物体(AROs)是全球公共卫生的主要关注点。尽管抗生素已经在环境细菌中自然产生了数百万年,但现代抗生素的广泛使用已经在人类影响的细菌环境中丰富了耐药机制。抗生素耐药基因(ARGs)不断出现并迅速传播。为了应对抗生素耐药性的全球威胁,研究人员必须开发快速鉴定 AROs 和 ARGs 的方法,监测它们在空间和时间上的传播,并识别新的 ARGs 和耐药途径。我们回顾了基于高通量测序的方法如何与经典的基于培养的检测方法相结合,以对 AROs 和 ARGs 进行鉴定、监测和跟踪。然后,我们评估了基因组和宏基因组方法,以从基因组数据集中鉴定 ARGs 和新型抗生素的生物合成途径。这些基因组分析可以共同提高对新兴耐药威胁的监测和预测,并加速开发新的抗生素疗法以对抗耐药性。