Threshold-free genomic cluster detection to track transmission pathways in healthcare settings

Abstract

Background Carbapenem-resistant Enterobacteriaceae have been recognized as an urgent antibiotic resistance threat for more than a decade. Despite this attention, their prevalence has remained steady or increased in some settings, suggesting that transmission pathways remain uncontrolled by current prevention strategies. We hypothesized that these transmission pathways, and hence targets for improved prevention, could be elucidated through comprehensive patient sampling, followed by integration of whole-genome sequencing (WGS) and epidemiological data. Methods Longitudinal KPC+ Klebsiella pneumoniae (KPC-Kp) surveillance cultures were collected from 94% of patients in a long-term acute care hospital (LTACH) during a one-year bundled intervention to reduce KPC-Kp prevalence. WGS of 462 KPC-Kp isolates from 256 patients, and associated surveillance data were integrated using a distance threshold-free approach to identify transmission clusters that grouped patients acquiring KPC-Kp in the LTACH with the admission-positive "index" patients that imported their strain into the facility. Plausible transmission pathways within clusters were identified using patient location data. Findings Transmission clusters (N=49) had between 2-14 patients, capturing KPC-Kp acquisitions from 100 (80%) patients who first acquired KPC-Kp in the LTACH. Within-cluster genetic diversity varied from 0-154 (median 9) single-nucleotide variants (SNVs), with elevated diversity being driven by prolonged asymptomatic colonization and evolution of hypermutator strains. Transmission between patients in clusters could be explained by spatiotemporal overlap in patient rooms (14%), wards (66%), or facility (81%). Sequential exposure to the same patient room was the only epidemiological link for one patient, indicating that residual environmental contamination of rooms after patient discharge contributed little to transmission. Persistent, modifiable routes of transmission were associated with lapses in patient cohorting, transmission between cohort and non-cohort locations and clusters propagating due to false-negative surveillance. Interpretation Integration of comprehensive surveillance and WGS data using a SNV threshold-free approach disclosed specific instances where improved patient and healthcare worker cohorting, reducing exposures to common locations outside of patient rooms, and improved KPC-Kp colonization detection could reduce transmission. Overall, results highlight the potential for WGS to monitor and improve infection prevention and the importance of combining rigorous sampling with appropriate analytical strategies to generate actionable hypotheses.

regentrans: a framework and R package for using genomics to study regional pathogen transmission

“…Several of the methods discussed below rely on interpreting, comparing, or thresholding pairwise SNV distances between isolates to make inferences. It is generally understood that small pairwise SNV distances between isolates implies recent transmission [14][15][16], but that this method is not entirely accurate due to within-host evolution and variable mutation rates [17,18]. To identify recent transmission pairs using pairwise SNV distances, investigators must choose a threshold to determine what pairs are considered closely related [14][15][16].…”