Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes

Abstract

Background: Recurrence of methicillin-resistant Staphylococcus aureus (MRSA) bacteremia is a high risk complication for patients. Distinguishing persistent lineages from new infections is not standardized across clinical studies.

Methods: We investigated factors contributing to recurrence of MRSA bacteremia among subjects in Philadelphia, Pennsylvania. Subject demographics and clinical history were collected and paired with whole-genome sequences of infection isolates. Recurrent bacteremia episodes were recorded and defined as relapse infections (same lineage) or new infections by genomic criteria, where a relapse contains isolates <=25 single nucleotide polymorphisms (SNP) different, and by clinical criteria. All isolates were assessed for pairwise SNP distances, common mutations, and signatures of within-host adaptation using the McDonald-Kreitman test. Clusters of transmission between relapse-associated isolates and other subject lineages were identified.

Results: Among 411 sequential subjects with MRSA bacteremia, 32 experienced recurrent bacteremia episodes, with 24 subjects having exclusively relapse infections, six with infections exclusively from a new strain, and two patients with both relapse and new infections. No concordance between a genomic and a clinical definition of relapse was evident (Cohen's Kappa = 0.18, CI: -0.41). Recurrence-associated lineages exhibited signatures of positive selection(G-test:<0.01). Genes with SNPs occurring in multiple relapse lineages have roles in antibiotic resistance and virulence, including 5 lineages with mutations in mprF and 3 lineages with mutations in rpoB, which corresponded with evolved phenotypic changes in daptomycin and rifampin resistance.

Conclusions: Recurrent infections have a diverse strain background. Relapses can be readily distinguished from newly acquired infections using genomic sequencing but not clinical criteria.

Keywords: antibiotic resistance; genomic epidemiology; hospital epidemiology; infection prevention.

Figure 1:. Recurrent MRSAB isolates share a similar phylogenetic distribution to non-recurrent MRSAB episodes.

A core pangenome tree of 411 MRSA bloodstream isolates was constructed and rooted using MSSA strain Newman (GCF_020985245.1). Whether or not an isolate was associated with a recurrent episode and molecular characteristics are shown in the heat map including, from left to right, the presence or absence of mecA, mecA type, clonal complex, and mutlilocus sequence type (ST). Blue dots indicated nodes where Shimodaira-Hasegawa approximate likelihood ratio test and ultrafast bootstrap values were >70).

Figure 2:. Relapsing infections and new infections within a patient are genomically distinguishable.

Subsequent isolate pairs among recurrences episodes (n=45) were separated into relapse-associated (n=37) or new infections (n=8) based on pairwise single nucleotide polymorphism (SNP) distance and distance to last common ancestor between isolates within the subject (A) Difference in time between subsequent episodes for genomically new infections and relapse associated infections were compared using the Kruskal-Wallice test (p=0.17). (B) Counts of the pairwise SNP distances between all isolate pairs from the same host were quantified (N=73). The inset display demonstrates counts where the SNP distance between isolates was between 0 and 350 SNPs. The dotted line represents the 25 SNP threshold.

Figure 3:. Clinical and genomic definitions of relapse are discordant.

Pairs of isolates from all recurrent infections were compared and identified as relapse (filled black rectangle) or new infections (white rectangles) based on a genomic definition or clinical definition, for a total of 45 pairs. The suspected source type of each infection within the episode was identified, with the least recent isolate associated with the “First Source” and the most recent isolate associated with the “Second Source.” Clinical source type was additionally assessed to determine if the first and second source were anatomically from the same source.

Figure 4:. Commonly mutated genes among relapse lineages are associated with antibiotic resistance phenotypes.

(A) Unique non-synonymous (NS) 354]mutations in coding regions of the genome were quantified by gene from isolates of relapse-associated infections and summarized relative to the subject from which the isolate was collected. Each unique mutation was annotated with the clonal background of the lineage from which the set of relapses were derived. For lineages with rpoB mutations (B) and mprF mutations (C), a timeline (days since index infection) was created for each set of relapsing infections by the subject experiencing that set of relapses. Individual episodes were annotated with the amino acid changes detected in the respective genes, the clinical assay used to assess minimum inhibitory concentration (MIC) and the corresponding MIC, and whether the patient was exposed to rifampin (RIF)(B) or daptomycin (DAP)(C). Dots are colored based on the clinical assay determination of drug susceptibility to RIF or DAP.

Figure 5:. Non-relapse associated isolates cluster separately from relapse-associated isolates.

A tree based on core genes was generated using the unequal transition/transversion rate plus empirical base frequencies model to investigate branching positions. Clusters were investigated when at least one relapse-associated isolate genome differed by 25 SNPs or fewer from an isolate from a different subject. Subtrees were extracted based on the most-recent common ancestor shared by relapse subject isolates and the clustered additional subjects. Nodes denoted with a blue dot indicate ultrafast bootstrap values and Shimodaira-Hasegawa approximate likelihood ratio test values that are greater than 70. Bolded tip labels indicate an isolate that is part of a relapse. Tips are annotated with the patient subject IDs and the number of days at which the isolate was collected relative to the earliest isolate in the cluster. Branch lengths are scaled in substitutions per site.