Infectious Disease and Microbiome Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Infectious Diseases Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Nat Med. 2019 Dec;25(12):1858-1864. doi: 10.1038/s41591-019-0650-9. Epub 2019 Nov 25.
Multidrug resistant organisms are a serious threat to human health. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94-99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24-36 h faster than standard workflows, with <4 h assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.
多药耐药菌对人类健康构成严重威胁。快速、准确的抗生素药敏试验（AST）是应对不断升级的抗生素耐药性的关键需求，因为延迟确定多药耐药菌会增加死亡率和广谱抗生素的使用，从而进一步选择耐药菌。然而，目前基于生长的 AST 检测方法，如肉汤微量稀释法，需要数天时间才能为关键的临床决策提供信息。快速 AST 将改变感染患者的治疗方式，同时确保我们的抗生素武器库尽可能有效地部署。基于生长的检测方法在速度上受到病原体倍增时间的根本限制，而基因型检测方法则受到细菌抗生素耐药机制的不断增长的多样性和复杂性的限制。在这里，我们通过 RNA 检测描述了一种用于联合基因型和表型 AST 的快速检测方法 GoPhAST-R，该方法通过将抗生素诱导的早期转录变化的机器学习分析与关键遗传耐药决定因素的同时检测相结合，以 94-99%的准确率对菌株进行分类，从而提高耐药检测的准确性，促进分子流行病学，并能够早期检测新兴的耐药机制。这种双管齐下的方法比标准工作流程提供了 24-36 小时更快的表型 AST，对于基于杂交的 RNA 检测的先导仪器，其检测时间<4 小时，可直接从阳性血培养物中实现。
