AUTHOR=Ambrosio Frank J. , Scribner Michelle R. , Wright Sage M. , Otieno James R. , Doughty Emma L. , Gorzalski Andrew , Siao Danielle Denise , Killian Steve , Hua Chi , Schneider Emily , Tran Michael , Varghese Vici , Libuit Kevin G. , Pandori Mark , Sevinsky Joel R. , Hess David 

TITLE=TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization

JOURNAL=Frontiers in Public Health

VOLUME=11

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1198213

DOI=10.3389/fpubh.2023.1198213

ISSN=2296-2565

ABSTRACT=<sec><title>Introduction</title><p>The clinical incidence of antimicrobial-resistant fungal infections has dramatically increased in recent years. Certain fungal pathogens colonize various body cavities, leading to life-threatening bloodstream infections. However, the identification and characterization of fungal isolates in laboratories remain a significant diagnostic challenge in medicine and public health. Whole-genome sequencing provides an unbiased and uniform identification pipeline for fungal pathogens but most bioinformatic analysis pipelines focus on prokaryotic species. To this end, TheiaEuk_Illumina_PE_PHB (TheiaEuk) was designed to focus on genomic analysis specialized to fungal pathogens.</p></sec><sec><title>Methods</title><p>TheiaEuk was designed using containerized components and written in the workflow description language (WDL) to facilitate deployment on the cloud-based open bioinformatics platform Terra. This species-agnostic workflow enables the analysis of fungal genomes without requiring coding, thereby reducing the entry barrier for laboratory scientists. To demonstrate the usefulness of this pipeline, an ongoing outbreak of <italic>C. auris</italic> in southern Nevada was investigated. We performed whole-genome sequence analysis of 752 new <italic>C. auris</italic> isolates from this outbreak. Furthermore, TheiaEuk was utilized to observe the accumulation of mutations in the FKS1 gene over the course of the outbreak, highlighting the utility of TheiaEuk as a monitor of emerging public health threats when combined with whole-genome sequencing surveillance of fungal pathogens.</p></sec><sec><title>Results</title><p>A primary result of this work is a curated fungal database containing 5,667 unique genomes representing 245 species. TheiaEuk also incorporates taxon-specific submodules for specific species, including clade-typing for <italic>Candida auris (C. auris)</italic>. In addition, for several fungal species, it performs dynamic reference genome selection and variant calling, reporting mutations found in genes currently associated with antifungal resistance (<italic>FKS1</italic>, <italic>ERG11</italic>, <italic>FUR1</italic>). Using genome assemblies from the ATCC Mycology collection, the taxonomic identification module used by TheiaEuk correctly assigned genomes to the species level in 126/135 (93.3%) instances and to the genus level in 131/135 (97%) of instances, and provided zero false calls. Application of TheiaEuk to actual specimens obtained in the course of work at a local public health laboratory resulted in 13/15 (86.7%) correct calls at the species level, with 2/15 called at the genus level. It made zero incorrect calls. TheiaEuk accurately assessed clade type of <italic>Candida auris</italic> in 297/302 (98.3%) of instances.</p></sec><sec><title>Discussion</title><p>TheiaEuk demonstrated effectiveness in identifying fungal species from whole genome sequence. It further showed accuracy in both clade-typing of <italic>C. auris</italic> and in the identification of mutations known to associate with drug resistance in that organism.</p></sec>