Graduate School of Biological and Biomedical Sciences, Emory University, Atlanta, Georgia, USA.
Division of Infectious Diseases, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Clin Infect Dis. 2022 Dec 19;75(12):2104-2112. doi: 10.1093/cid/ciac339.
Though detection of transmission clusters of methicillin-resistant Staphylococcus aureus (MRSA) infections is a priority for infection control personnel in hospitals, the transmission dynamics of MRSA among hospitalized patients with bloodstream infections (BSIs) has not been thoroughly studied. Whole genome sequencing (WGS) of MRSA isolates for surveillance is valuable for detecting outbreaks in hospitals, but the bioinformatic approaches used are diverse and difficult to compare.
We combined short-read WGS with genotypic, phenotypic, and epidemiological characteristics of 106 MRSA BSI isolates collected for routine microbiological diagnosis from inpatients in 2 hospitals over 12 months. Clinical data and hospitalization history were abstracted from electronic medical records. We compared 3 genome sequence alignment strategies to assess similarity in cluster ascertainment. We conducted logistic regression to measure the probability of predicting prior hospital overlap between clustered patient isolates by the genetic distance of their isolates.
While the 3 alignment approaches detected similar results, they showed some variation. A gene family-based alignment pipeline was most consistent across MRSA clonal complexes. We identified 9 unique clusters of closely related BSI isolates. Most BSIs were healthcare associated and community onset. Our logistic model showed that with 13 single-nucleotide polymorphisms, the likelihood that any 2 patients in a cluster had overlapped in a hospital was 50%.
Multiple clusters of closely related MRSA isolates can be identified using WGS among strains cultured from BSI in 2 hospitals. Genomic clustering of these infections suggests that transmission resulted from a mix of community spread and healthcare exposures long before BSI diagnosis.
虽然检测耐甲氧西林金黄色葡萄球菌（MRSA）感染的传播集群是医院感染控制人员的首要任务，但住院血流感染（BSI）患者中 MRSA 的传播动态尚未得到充分研究。对 MRSA 分离株进行全基因组测序（WGS）监测对于检测医院内的暴发非常有价值，但使用的生物信息学方法多种多样，难以比较。
我们将短读 WGS 与来自 2 家医院 12 个月内常规微生物学诊断收集的 106 株 MRSA BSI 分离株的基因型、表型和流行病学特征相结合。从电子病历中提取临床数据和住院史。我们比较了 3 种基因组序列比对策略，以评估在聚类确定方面的相似性。我们进行了逻辑回归，以衡量通过分离株的遗传距离预测聚类患者分离株之间先前医院重叠的概率。
虽然这 3 种对齐方法检测到了相似的结果，但它们也存在一些差异。基于基因家族的对齐管道在 MRSA 克隆复合体中最为一致。我们确定了 9 个独特的密切相关 BSI 分离株簇。大多数 BSI 与医疗保健相关，社区发病。我们的逻辑模型显示，在 13 个单核苷酸多态性的情况下，任何 2 个集群患者在医院重叠的可能性为 50%。
使用 WGS 可以从 2 家医院培养的 BSI 中鉴定出多个密切相关的 MRSA 分离株簇。这些感染的基因组聚类表明，传播是由社区传播和医疗保健暴露混合引起的，远在 BSI 诊断之前。
