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Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.
Nature Medicine ( IF 58.7 ) Pub Date : 2019-11-25 , DOI: 10.1038/s41591-019-0650-9
Roby P Bhattacharyya 1, 2 , Nirmalya Bandyopadhyay 1 , Peijun Ma 1 , Sophie S Son 1 , Jamin Liu 1 , Lorrie L He 1 , Lidan Wu 3 , Rustem Khafizov 3 , Rich Boykin 3 , Gustavo C Cerqueira 1, 4 , Alejandro Pironti 1 , Robert F Rudy 1 , Milesh M Patel 1 , Rui Yang 1 , Jennifer Skerry 5 , Elizabeth Nazarian 6 , Kimberly A Musser 6 , Jill Taylor 6 , Virginia M Pierce 5 , Ashlee M Earl 1 , Lisa A Cosimi 7 , Noam Shoresh 1 , Joseph Beechem 3 , Jonathan Livny 1 , Deborah T Hung 1, 8, 9
Affiliation  

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.

中文翻译:

同时检测基因型和表型可以快速准确地确定抗生素敏感性。

耐多药生物是对人类健康的严重威胁1,2。快速、准确的抗生素敏感性测试 (AST) 是解决不断升级的抗生素耐药性的关键需求,因为延迟识别多重耐药菌会增加死亡率 3,4 和广谱抗生素的使用,从而进一步选择耐药菌。然而,当前基于生长的 AST 检测,例如微量肉汤稀释法,需要几天时间才能为关键的临床决策提供信息。Rapid AST 将改变感染患者的护理方式,同时确保我们的抗生素库尽可能有效地部署。基于生长的检测从根本上受到病原体加倍时间的限制,而基因型检测受到细菌抗生素耐药机制不断增长的多样性和复杂性的限制。在这里,我们描述了一种通过 RNA 检测对组合基因型和表型 AST 进行快速测定,GoPhAST-R,通过将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因素相结合,以 94-99% 的准确度对菌株进行分类提高耐药性检测的准确性,促进分子流行病学并能够及早发现新出现的耐药性机制。这种双管齐下的方法比标准工作流程更快地提供表型 AST 24-36 小时,在用于直接从阳性血培养物中实施的基于杂交的多重 RNA 检测的试验仪器上的测定时间小于 4 小时。通过将早期抗生素诱导的转录变化的机器学习分析与关键遗传抗性决定因素的同时检测相结合,以 94-99% 的准确度对菌株进行分类,以提高抗性检测的准确性,促进分子流行病学并能够早期检测新兴的抗性机制。这种双管齐下的方法比标准工作流程更快地提供表型 AST 24-36 小时,在用于直接从阳性血培养物中实施的基于杂交的多重 RNA 检测的试验仪器上的测定时间小于 4 小时。通过将早期抗生素诱导的转录变化的机器学习分析与关键遗传抗性决定因素的同时检测相结合,以 94-99% 的准确度对菌株进行分类,以提高抗性检测的准确性,促进分子流行病学并能够早期检测新兴的抗性机制。这种双管齐下的方法比标准工作流程更快地提供表型 AST 24-36 小时,在用于直接从阳性血培养物中实施的基于杂交的多重 RNA 检测的试验仪器上的测定时间小于 4 小时。
更新日期:2019-11-26
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