Candida auris Whole-Genome Sequence Benchmark Dataset for Phylogenomic Pipelines

Abstract

Candida auris is a multidrug-resistant pathogen that represents a serious public health threat due to its rapid global emergence, increasing incidence of healthcare-associated outbreaks, and high rates of antifungal resistance. Whole-genome sequencing and genomic surveillance have the potential to bolster C. auris surveillance networks moving forward. Laboratories conducting genomic surveillance need to be able to compare analyses from various national and international surveillance partners to ensure that results are mutually trusted and understood. Therefore, we established an empirical outbreak benchmark dataset consisting of 23 C. auris genomes to help validate comparisons of genomic analyses and facilitate communication among surveillance networks. Our outbreak benchmark dataset represents a polyclonal phylogeny with three subclades. The genomes in this dataset are from well-vetted studies that are supported by multiple lines of evidence, which demonstrate that the whole-genome sequencing data, phylogenetic tree, and epidemiological data are all in agreement. This C. auris benchmark set allows for standardized comparisons of phylogenomic pipelines, ultimately promoting effective C. auris collaborations.

Emergence of Clonally-Related South Asian Clade I Clinical Isolates of Candida auris in a Greek COVID-19 Intensive Care Unit

“…However, a standardized dataset to allow for comparisons of these molecular typing and phylogenomic pipelines has not been established for C. auris . Recently, a genomic benchmark dataset has been developed to serve as a resource to facilitate global efforts to collaborate and rapidly validate sequence analysis tools, which should be able to differentiate between the geographic clades, hospital transmission, colonization and the extent of carriage in the community [ 41 , 42 ].…”

Optimization and Validation of Candida auris Short Tandem Repeat Analysis

“…As for any method, there are various parameters affecting its outcome, including input sequence quality, coverage, and the choice of sequence assembly tool, read mapping tool, and single-nucleotide polymorphism (SNP) pipeline ( 4 , 5 ). In 2021, a WGS benchmark data set was published, allowing standardized comparisons of phylogenomic pipelines ( 6 ). The disadvantages of WGS analysis include long turnaround time, high costs, and required bioinformatic expertise.…”

Description and Genome Characterization of Three Novel Fungal Strains Isolated from Mars 2020 Mission-Associated Spacecraft Assembly Facility Surfaces—Recommendations for Two New Genera and One Species

“…We used traditional fungal characterization via colony morphology and microscopy, and, in addition, performed multi-locus sequence typing (MLST) of up to six loci, internal transcribed spacer ( ITS) , large subunit ribosomal ribonucleic acid ( LSU) , small subunit ribosomal ribonucleic acid ( SSU ), RNA polymerase II gene ( RPB ), tubulin ( TUB) , and translation elongation factor 1 alpha ( TEF 1). The WGS-based methods have increasingly been used to detect and characterize outbreaks for fungal pathogens [ 15 , 16 , 17 ], however, their efficacy on novel fungal strains is not well tested yet. Thus, the second objective was to clarify the phylogenetic relationship of the novel fungal genera with other closely related fungi using available WGS.…”