Antimicrobial susceptibility prediction from genomes: a dream come true?

IF 14 1区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Trends in Microbiology Pub Date : 2024-04-01 Epub Date: 2024-03-03 DOI:10.1016/j.tim.2024.02.012

Guido Werner, Hege Vangstein Aamot, Natacha Couto

引用次数: 0

Abstract

Genome-based diagnostics provides relevant information to guide patient treatment and support pathogen and resistance surveillance. Recently, Coll et al. introduced a curated database for predicting antimicrobial resistance (AMR) from Enterococcus faecium genomics data, offering excellent predictive values for susceptibility to important antimicrobials. Challenges to predict resistance to last-resort antimicrobials remain.

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从基因组预测抗菌药敏感性：梦想成真？

基于基因组的诊断为指导患者治疗和支持病原体及耐药性监测提供了相关信息。最近，Coll 等人从粪肠球菌基因组学数据中引入了一个用于预测抗菌药耐药性（AMR）的编辑数据库，为重要抗菌药的敏感性提供了极好的预测值。预测对最后一种抗菌药物的耐药性仍面临挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Trends in Microbiology 生物-生化与分子生物学

CiteScore

25.30

自引率

0.60%

发文量

193

审稿时长

6-12 weeks

期刊介绍： Trends in Microbiology serves as a comprehensive, multidisciplinary forum for discussing various aspects of microbiology, spanning cell biology, immunology, genetics, evolution, virology, bacteriology, protozoology, and mycology. In the rapidly evolving field of microbiology, technological advancements, especially in genome sequencing, impact prokaryote biology from pathogens to extremophiles, influencing developments in drugs, vaccines, and industrial enzyme research.