工作流程
抗生素耐药性
分子诊断学
临床微生物学
计算生物学
生物
数据科学
医学
抗生素
生物信息学
微生物学
遗传学
计算机科学
数据库
作者
Eric M. Ransom,Robert F. Potter,Gautam Dantas,Carey Ann D. Burnham
出处
期刊:Clinical Chemistry
[Oxford University Press]
日期:2020-09-12
卷期号:66 (10): 1278-1289
被引量:23
标识
DOI:10.1093/clinchem/hvaa172
摘要
Abstract Background Next-generation sequencing (NGS) technologies are being used to predict antimicrobial resistance. The field is evolving rapidly and transitioning out of the research setting into clinical use. Clinical laboratories are evaluating the accuracy and utility of genomic resistance prediction, including methods for NGS, downstream bioinformatic pipeline components, and the clinical settings in which this type of testing should be offered. Content We describe genomic sequencing as it pertains to predicting antimicrobial resistance in clinical isolates and samples. We elaborate on current methodologies and workflows to perform this testing and summarize the current state of genomic resistance prediction in clinical settings. To highlight this aspect, we include 3 medically relevant microorganism exemplars: Mycobacterium tuberculosis, Staphylococcus aureus, and Neisseria gonorrhoeae. Last, we discuss the future of genomic-based resistance detection in clinical microbiology laboratories. Summary Antimicrobial resistance prediction by genomic approaches is in its infancy for routine patient care. Genomic approaches have already added value to the current diagnostic testing landscape in specific circumstances and will play an increasingly important role in diagnostic microbiology. Future advancements will shorten turnaround time, reduce costs, and improve our analysis and interpretation of clinically actionable results.
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