TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization - 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; et al. (Frontiers in Public Health, 2023)
Clinical incidence of antimicrobial-resistant fungal infections have increased dramatically in recent years. Certain fungal pathogens colonize various body cavities and cause life-threatening bloodstream infections. However, laboratory identification and characterization of fungal isolates remains a significant diagnostic challenge in medicinemediceal and public health. Here we introduce TheiaEuk_Illumina_PE_PHB (TheiaEuk), a cloud-native bioinformatics workflow that accepts paired-end next generation sequencing data generated on an Illumina platform as input and performs read quality assessment and trimming, de novo genome assembly, and taxon identification for fungal pathogens. This workflow performs taxon identification using the GAMBIT tool with a novel, curated fungal database containing 5,667 unique genomes representing 245 species. While the core components of TheiaEuk are species-agnostic, the workflow will automatically launch taxon-specific submodules for specific species, including clade-typing for Candida auris (C. auris). For several fungal species it will also perform dynamic reference genome selection and variant calling, then report mutations found in genes currently known to be associated with antifungal resistance (FKS1, ERG11, FUR1). This workflow is open source and available on the Theiagen Genomics GitHub page