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Establishing Genotype-to-Phenotype Relationships in Bacteria Causing Hospital-Acquired Pneumonia: A Prelude to the Application of Clinical Metagenomics

机译:建立细菌引起医院获得性肺炎的基因型与表型之间的关系:临床元基因组学应用的前奏。

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摘要

Clinical metagenomics (CMg), referred to as the application of next-generation sequencing (NGS) to clinical samples, is a promising tool for the diagnosis of hospital-acquired pneumonia (HAP). Indeed, CMg allows identifying pathogens and antibiotic resistance genes (ARGs), thereby providing the information required for the optimization of the antibiotic regimen. Hence, provided that CMg would be faster than conventional culture, the probabilistic regimen used in HAP could be tailored faster, which should lead to an expected decrease of mortality and morbidity. While the inference of the antibiotic susceptibility testing from metagenomic or even genomic data is challenging, a limited number of antibiotics are used in the probabilistic regimen of HAP (namely beta-lactams, aminoglycosides, fluoroquinolones, glycopeptides and oxazolidinones). Accordingly, based on the perspective of applying CMg to the early diagnostic of HAP, we aimed at reviewing the performances of whole genomic sequencing (WGS) of the main HAP-causing bacteria (Enterobacteriaceae, Pseudomonas aeruginosa, Acinetobacter baumannii, Stenotrophomonas maltophilia and Staphylococcus aureus) for the prediction of susceptibility to the antibiotic families advocated in the probabilistic regimen of HAP.
机译:临床宏基因组学(CMg),被称为下一代测序(NGS)对临床样品的应用,是诊断医院获得性肺炎(HAP)的有前途的工具。实际上,CMg可以识别病原体和抗生素抗性基因(ARG),从而提供优化抗生素方案所需的信息。因此,如果CMg比常规培养更快,则可以更快地调整HAP中使用的概率方案,这将导致预期的死亡率和发病率降低。虽然从宏基因组甚至基因组数据推断抗生素药敏试验具有挑战性,但在HAP的概率方案中使用了数量有限的抗生素(即β-内酰胺类,氨基糖苷类,氟喹诺酮类,糖肽类和恶唑烷酮类)。因此,基于将CMg应用于HAP的早期诊断的观点,我们旨在综述引起HAP的主要细菌(肠杆菌科,铜绿假单胞菌,鲍曼不动杆菌,嗜麦芽窄食单胞菌和金黄色葡萄球菌)的全基因组测序(WGS)的性能。 )用于预测HAP概率方案中倡导的抗生素家族的易感性。

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