Identifying the effect of patient sharing on between-hospital genetic differentiation of methicillin-resistant Staphylococcus aureus. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Chang, Hsiao-Han; Dordel, Janina; Donker, Tjibbe; Worby, Colin; Feil, Edward; Hanage, William; Bentley, Stephen; Huang, Susan; Lipsitch, Marc
• Is Part Of: Genome medicine. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-12
• Subjects: Genetic differentiation -- Patient sharing -- Gene flow -- Transmission -- Staphylococcus aureus; Genomics -- Periodicals; Medical genetics -- Periodicals; 616.042
• DOI: 10.1186/s13073-016-0274-3
• Languages: English
• ISSNs: 1756-994X

Abstract

Abstract Background Methicillin-resistantStaphylococcus aureus (MRSA) is one of the most common healthcare-associated pathogens. To examine the role of inter-hospital patient sharing on MRSA transmission, a previous study collected 2, 214 samples from 30 hospitals in Orange County, California and showed byspa typing that genetic differentiation decreased significantly with increased patient sharing. In the current study, we focused on the 986 samples withspa type t008 from the same population. Methods We used genome sequencing to determine the effect of patient sharing on genetic differentiation between hospitals. Genetic differentiation was measured by between-hospital genetic diversity, F ST, and the proportion of nearly identical isolates between hospitals. Results Surprisingly, we found very similar genetic diversity within and between hospitals, and no significant association between patient sharing and genetic differentiation measured byF ST . However, in contrast toF ST, there was a significant association between patient sharing and the proportion of nearly identical isolates between hospitals. We propose that the proportion of nearly identical isolates is more powerful at determining transmission dynamics than traditional estimators of genetic differentiation (F ST ) when gene flow between populations is high, since it is more responsive to recent transmission events. Our hypothesis was supported by the results from coalescent simulations. Conclusions Our results suggested that there was a high level of gene flow between hospitals facilitated by patient sharing, and that the proportion of nearly identical isolates is more sensitive to population structure thanF ST when gene flow is high.