Unsuspected Clonal Spread of Methicillin-Resistant Staphylococcus aureus Causing Bloodstream Infections in Hospitalized Adults Detected Using Whole Genome Sequencing

Abstract

Background: 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.

Methods: 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.

Results: 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%.

Conclusions: 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.

Keywords: Staphylococcus aureus; bloodstream infections; hospital epidemiology; infection prevention; outbreak detection.

Figure 1.

Frequencies and distribution of single-nucleotide polymorphism (SNP) distances between isolates vary by alignment tool. The frequency of pairwise distances between isolates from clonal complexes (CC) 8 and 5 were quantified from distance matrices derived from alignments generated from 2 groupings of isolate input: the total number of isolates in the investigation (blue) or CC-specific isolates only (red). Isolate inputs were aligned using each of the 3 alignment pipelines, the gene-family pipeline (A and B), assembly pipeline (C and D), and pseudoread pipeline (E and F).

Figure 2.

Suspected transmission clusters fall into distinct clonal groups. Maximum likelihood trees were generated from the PIRATE alignment of 104 isolates and visualized using ggtree. A, Tree indicating clades containing individual clonal complexes (CCs). B, Subtrees from the complete maximum likelihood trees for the 2 most abundant CCs. Nodes with bootstrap values ≥70 are marked in red. Heat maps show strain type (ST), SCCmec element type, and resistance phenotype for indicated antibiotics per sequence, infection setting (healthcare-associated [HA], community-associated [CA], and healthcare-associated community-onset [HACO]), admission hospital, and transmission cluster at a threshold of 35 single-nucleotide polymorphisms (SNPs) or 15 SNPs.

Figure 3.

Hospitalization history among patients in genomic bloodstream infection (BSI) clusters. Hospitalization history at 4 study hospitals (A, B, C, and D) up to 365 days before the date of the earliest methicillin-resistant Staphylococcus aureus (MRSA) bloodstream isolate culture in each cluster (relative day 0) and up to 365 days after the latest MRSA bloodstream isolate in the cluster. Note that BSIs were only included at hospitals A and B. Rows represent the hospitalization history of each patient associated with a sequenced cluster isolate. Colored rectangles and circular marks represent individual hospitalization durations (rectangles) or 1-day admissions (circles); the color indicates hospital A, B, C, or D. Black outlined boxes represent areas where 2 or more patients overlapped in the same hospital at the same time. Stars indicate the date of collection of the sequenced BSI isolate for each patient. Triangles indicate a hospitalization where 2 or more patients overlapped in the same hospital unit.

Figure 4.

Higher single-nucleotide polymorphism (SNP) distances trend toward ruling out hospital overlaps between clustering patients. A, Logistic regression model indicating the relationship between patient pairs overlapping in the same hospital at the same time (prior to the diagnosis of an index methicillin-resistant Staphylococcus aureus bloodstream infection) and the pairwise SNP distance. Points indicate the true result for each pair as overlapping (1.0) or not overlapping (0). The color of the points indicates whether hospital overlap patient pairs also overlapped (black) or did not overlap (gray) in the same hospital unit. Gray ribbon indicates the 95% confidence interval. B, Receiver operating characteristic (ROC) curve of the logistic model in A. Area under the curve (AUC) = 0.662.