Infectious Disease Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Infection Control Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
J Clin Microbiol. 2021 Jan 21;59(2). doi: 10.1128/JCM.01955-20.
Multilocus sequence typing (MLST) is a low-resolution but rapid genotyping method for Whole-genome sequencing (WGS) has emerged as the new gold standard for typing, but cost and lack of standardization still limit broad utilization. In this study, we evaluated the potential to combine the portability of MLST with the increased resolution of WGS for a cost-saving approach to routine typing. strains from two New York City hospitals (hospital A and hospital B) were selected. WGS single-nucleotide polymorphism (wgSNP) was performed using established methods. Sequence types (ST) were determined using PubMLST, while wgSNP analysis was performed using the Bionumerics software. An additional analysis of a subset of data (hospital A) was made comparing the Bionumerics software to the CosmosID pipeline. Cost and turnaround time to results were compared for the algorithmic approach of MLST followed by wgSNP versus direct wgSNP. Among the 202 isolates typed, 91% ( = 185/203) clustered within the representative ST, showing a high agreement between MLST and wgSNP. While clustering was similar between the Bionumerics and CosmosID pipelines, large differences in the overall number of SNPs were noted. A two-step algorithm for routine typing results in significantly lower cost than routine use of WGS. Our results suggest that using MLST as a first step in routine typing of followed by WGS for MLST concordant strains is a less technically demanding, cost-saving approach for performing typing than WGS alone without loss of discriminatory power.
多位点序列分型（MLST）是一种低分辨率但快速的全基因组测序（WGS）基因分型方法，已经成为新的金标准，但成本和缺乏标准化仍然限制了广泛应用。在这项研究中，我们评估了将 MLST 的便携性与 WGS 的分辨率提高相结合的潜力，以实现一种节省成本的常规分型方法。从纽约市的两家医院（医院 A 和医院 B）选择了菌株。使用已建立的方法进行 WGS 单核苷酸多态性（wgSNP）分析。使用 PubMLST 确定序列类型（ST），而 wgSNP 分析使用 Bionumerics 软件进行。对医院 A 的部分数据进行了额外的分析，比较了 Bionumerics 软件和 CosmosID 管道。比较了 MLST 算法和直接 wgSNP 与直接 wgSNP 的成本和结果周转时间。在 202 株被分型的分离株中，91%（=185/203）在代表性 ST 内聚类，表明 MLST 和 wgSNP 之间具有高度一致性。虽然 Bionumerics 和 CosmosID 管道的聚类相似，但总 SNP 数量存在较大差异。常规分型的两步算法的成本明显低于常规使用 WGS。我们的结果表明，使用 MLST 作为常规 分型的第一步，然后对 MLST 一致的菌株进行 WGS，是一种比单独使用 WGS 更具技术挑战性、节省成本的方法，而不会降低鉴别力。
