Identifying Candida auris transmission in a hospital outbreak investigation using whole-genome sequencing and SNP phylogenetic analysis.
Brooks I MitchellKendall KlingMaureen K BolonShardul N RathodMichael MalczynskiJavier RuizWanda PolancoKevin FritzSarah MaaliValentina StosorTeresa R ZembowerChao QiPublished in: Journal of clinical microbiology (2024)
Candida auris poses a global public health challenge, causing multiple outbreaks within healthcare facilities. Despite advancements in strain typing for various infectious diseases, a consensus on the genetic relatedness threshold for identifying C. auris transmission in local hospital outbreaks remains elusive. We investigated genetic variations within our local isolate collection using whole-genome-based single nucleotide polymorphism (SNP) phylogenetic analysis. A total of 74 C . auris isolates were subjected to whole-genome sequencing (WGS) and SNP phylogenetic analysis via the QIAGEN CLC Genomics Workbench. Isolates included known related strains from the same patient, strains from different hospitals, strains from our hospital patients with no epidemiological link, and 19 patient isolates from a recent C. auris outbreak. All but three isolates were identified to be Clade IV. By examining the genetic diversities of C. auris within patients and between patients, we identified a SNP variation range of 0-13 for identifying related isolates. During an outbreak investigation, utilizing this range, maximum likelihood phylogenetic analysis revealed two distinct clusters that aligned with the epidemiological links. Determining a SNP variation range to delineate genetic relatedness among isolates is crucial for the application of WGS and SNP phylogenetic analysis in identifying C. auris transmission during hospital outbreak investigations. The use of WGS SNP phylogenetic analysis via the CLC Genomics Workbench has emerged as a valuable method for typing C. auris in clinical microbiology laboratories.
Keyphrases
- genome wide
- genetic diversity
- healthcare
- infectious diseases
- dna methylation
- end stage renal disease
- public health
- high density
- escherichia coli
- newly diagnosed
- chronic kidney disease
- copy number
- prognostic factors
- single cell
- peritoneal dialysis
- gene expression
- acute care
- adverse drug
- emergency department
- patient reported outcomes
- high resolution
- clinical practice
- candida albicans
- mass spectrometry
- biofilm formation
- patient reported
- single molecule
- electronic health record
- global health
- health insurance