小柯机器人

美国哈佛大学-麻省理工学院博德研究所Deborah T. Hung研究组开发出能够同时检测基因型和表型的快速、准确抗生素敏感性测定方法。2019年11月25日，《自然—医学》在线发表了这一成果。

研究人员表示，多耐药性生物严重威胁人类健康。快速、准确的抗生素药敏试验（AST）是解决不断增长的抗生素耐药性的关键需求，因为延迟发现具有多重耐药性的生物会增加死亡率，并且使用广谱抗生素，从而进一步选择耐药菌。然而，当前的基于生长的AST分析（如肉汤微量稀释）需要几天的时间才能提供关键的临床决策。快速AST将改变感染患者的护理方式，同时确保尽可能有效地部署现有的抗生素库。由于病原体的倍增时间，从根本上限制了基于生长的分析的速度，而基因型分析受到细菌抗生素抗药性机制不断增长的多样性和复杂性的限制。

研究人员报道了通过RNA检测GoPhAST-R对基因型和表型AST进行组合的快速测定方法，该方法通过对早期抗生素诱导的转录变化的机器学习分析与同时检测关键遗传抗性决定子的结合来对菌株进行94-99％的准确度分类。

这一方法能够提高耐药性检测的准确性，促进分子流行病学的发展，并能够及早发现新兴的耐药性机制。这种双管齐下的方法提供了比标准工作流程快24到36小时的表型AST，并且能够直接从阳性血液培养物中实施的基于杂交的多重RNA检测，从而使得分析时间少于4小时。

附：英文原文

 

Title:Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination

 

Author:Roby P. Bhattacharyya, Nirmalya Bandyopadhyay, Peijun Ma, Sophie S. Son, Jamin Liu, Lorrie L. He, Lidan Wu, Rustem Khafizov, Rich Boykin, Gustavo C. Cerqueira, Alejandro Pironti, Robert F. Rudy, Milesh M. Patel, Rui Yang, Jennifer Skerry, Elizabeth Nazarian, Kimberly A. Musser, Jill Taylor, Virginia M. Pierce, Ashlee M. Earl, Lisa A. Cosimi, Noam Shoresh, Joseph Beechem, Jonathan Livny & Deborah T. Hung 

 

Issue&Volume:2019-11-25

 

Abstract: Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, 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.

 

DOI:10.1038/s41591-019-0650-9

 

Source: https://www.nature.com/articles/s41591-019-0650-9