1230. Identification of Subclinical Healthcare-Associated Clusters of Staphylococcus epidermidis in an Orthopedic Patient Population.
Authors: Simon Samantha , Simon Samantha , Sater Mohamad , Herriott Ian C , Huntley Miriam H , Hollenbeck Brian L 
Published: December 2022

Background

Prosthetic joint infections (PJIs) cause increased morbidity and mortality for patients. Staphylococcus epidermidis (S. epidermidis) can readily form biofilm on implanted medical devices, making this typically commensal species a common cause of PJIs. This study investigates genetic, epidemiologic, and environmental factors contributing to positive S. epidermidis joint cultures.

Methods

We identified S. epidermidis isolates from hip or knee cultures obtained between 2017-20 in patients with one or more prior corresponding intraarticular procedure at our hospital. Whole genome sequencing and single nucleotide polymorphism (SNP) based clonality analysis was performed using the epiXact® service at Day Zero Diagnostics, including species identification, in silico multi-locus sequence typing (MLST), phylogenomic analysis, along with genotypic assessment of the prevalence of specific antibiotic resistance and virulence genes. Additional epidemiologic review was performed to compare cluster and noncluster cases.

Results

Sixty phenotypically distinct S. epidermidis joint isolates were identified from 44 patients. After removal of duplicates and impure samples, 46 samples were used for genomic sequencing, and 45 were used for MLST. Four S. epidermidis strains showed phenotypic susceptibility to oxacillin yet harbored mecA, and two showed phenotypic resistance despite not having mecA (Figure 1). Notably, smr was found in all isolates. MupA positivity was not observed. We also identified six clonal clusters, all with SNP distances &lt; 10 (Figure 2). Each cluster consisted of between 2-4 patients. Cluster isolates accounted for 14/45 (31.1%) of S. epidermidis isolates sequenced. Further epidemiologic investigation showed ties to common aspirations or operative procedures although no specific common source was identified. These subclinical clusters appear to be self-limited, suggesting benefit to common infection control practices.

Phylogenetic tree of S. epidermidis population and heatmap showing the presence/absence of specific genomic features.

Circle color on node tip corresponds to sequence type (MLST). Color strips (right panel) showing genomic feature (gene or marker) presence/absence inferred from WGS de novo assemblies. Green cells correspond to a full match found, and gray cells to no match found. Empty rows correspond to external reference genomes used as controls.

*AMR: antimicrobial resistance; ST: sequence type;

SNP distance values for all pairs of samples of matching multi-locus sequence types.

Only samples belonging to matching multi-locus sequence types (MLSTs) with more than one sample are shown. Blue cells correspond to pairwise distance of &lt; 25 SNPs indicating clonality. 13 isolates with unique MLSTs are not shown. 10 isolates were not included due to having multi-strain or multi-species contamination.

*ST: sequence type; SNP: single-nucleotide polymorphism;

Univariate analysis of clonal isolates versus non-clonal isolates.

Samples not included in the multi-locus sequence type analysis due to contamination were excluded from the univariate analysis.

*PJI: prosthetic joint infection; MSIS: Musculoskeletal Infection Society;

Conclusion

The majority of S. epidermidis isolated from clinical joint samples are diverse in origin, but we identified an important subset of 31% that belonged to subclinical healthcare-associated clusters. Clusters appeared to resolve spontaneously over time, suggesting benefit to routine infection control practices.

Diagram of clonal isolate clusters

Potential relationships and modes of transmission between clonal isolates in each cluster.

*PJI: prosthetic joint infection; MSIS: Musculoskeletal Infection Society; SNP: single-nucleotide polymorphism;

Disclosures

Mohamad Sater, PhD, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Stocks/Bonds Ian C. Herriott, Bachelor's of Science, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Stocks/Bonds Miriam H. Huntley, PhD, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Ownership Interest.