Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing
Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing
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DOI：
10.1038/s41564-019-0656-6
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发表时间：
2020-02-10
影响因子：
28.3
通讯作者：
Hanage, William P.
中科院分区：
文献类型：
--
作者：
Brinda, Karel;Callendrello, Alanna;Hanage, William P.
基因组近邻分型可用于基于最近亲缘的基因组推断细菌样品的抗微生物剂敏感性和抗性。结合MinION测序，它可以在4小时内快速确定临床样本的微生物耐药性。监测耐药菌对于医疗保健提供者提供有效的经验性抗生素治疗至关重要。然而，传统的分子流行病学通常不会在可能影响患者治疗和结局的时间尺度上发生。在这里，我们提出了一种称为“基因组邻居分型”的方法，用于通过在具有元数据的基因组数据库中识别其最近的亲属来推断细菌样品的表型。我们表明，这种技术可以推断抗生素敏感性和耐药性的肺炎链球菌和淋病奈瑟菌。我们通过快速k-mer匹配实现了这一点，当用于Oxford Nanopore MinION数据时，可以真实的运行。这导致在10分钟内测定耐药性（对S.肺炎奈瑟氏菌的敏感性为81%，特异性为100%。从具有代表性数据库的分离株获得的淋病），并在样品收集的4小时内（对S. pneumoniae）用于临床宏基因组痰样品。这种灵活的方法在病原体监测中具有广泛的应用，并可用于大大加速适当的经验性抗生素治疗。
Genomic neighbour typing can be used to infer the antimicrobial susceptibility and resistance of a bacterial sample based on the genomes of closest relatives. Combined with MinION sequencing, it can rapidly determine microbial resistance for clinical samples within 4 h.Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.