Unsuspected Clonal Spread of Methicillin-Resistant Staphylococcus aureus Causing Bloodstream Infections in Hospitalized Adults Detected Using Whole Genome Sequencing.
Unsuspected Clonal Spread of Methicillin-Resistant Staphylococcus aureus Causing Bloodstream Infections in Hospitalized Adults Detected Using Whole Genome Sequencing.
复制标题
使用全基因组测序检测出耐甲氧西林金黄色葡萄球菌的意外克隆传播，导致住院成人血流感染。
DOI：
10.1093/cid/ciac339
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
David,MichaelZ
中科院分区：
文献类型：
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作者：
Talbot,BrookeM;Jacko,NatasiaF;Petit,RobertA;Pegues,DavidA;Shumaker,MargotJ;Read,TimothyD;David,MichaelZ
背景虽然检测耐甲氧西林金黄色葡萄球菌(MRSA)感染的传播群是医院感染控制人员的首要任务，但MRSA在住院血液感染(BSI)患者中的传播动力学尚未得到深入研究。MRSA监测分离株全基因组测序(WGS)对医院暴发疫情的监测具有重要意义，但生物信息学方法多种多样，难以比较。方法对2所医院12个月来收集的106株MRSA BSI进行全基因组测序，结合其基因分型、表型和流行病学特征。临床资料和住院史均从电子病历中提取。我们比较了3种基因组序列比对策略，以评估聚类确定中的相似性。结果3种比对方法检测结果相似，但表现出一定的差异。基于基因家族的比对管道在所有MRSA克隆性复合体中最一致。我们鉴定了9个独特的亲缘关系密切的BSI分离物。大多数BSI与医疗保健和社区发病有关。我们的Logistic模型显示，在13个单核苷酸多态性的情况下，同一群中的任何2名患者在一家医院重叠的可能性为50%。结论利用WGS可以在2家医院的BSI培养的菌株中鉴定出多群密切相关的MRSA分离株。这些感染的基因组聚集性表明，传播是在BSI诊断之前很久就由社区传播和医疗保健暴露的混合造成的。
BackgroundThough detection of transmission clusters of methicillin-resistantStaphylococcus 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.MethodsWe 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.ResultsWhile 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%.ConclusionsMultiple 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.