Name of the tool MLST Tool homepage or repository https://github.com/tseemann/mlst Tool description Scan contig files against PubMLST typing schemes Tool output example files Acinetobacter_GCF_0086...

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Introduction. Histoplasma capsulatum is an important fungal pathogen of humans, especially in immunocompromised patients, and the World Health Organisation has listed Histoplasma as a High Priority fungal pathogen. The taxonomy of the genus Histoplasma is still under development, but its only species H. capsulatum has at least of seven lineages, and a range of sublineages. Gap Statement. Allelic multilocus sequence typing (MLST) has been very successfully applied for typing and epidemiology of pathogenic bacteria, but its adoption for fungal pathogens is more limited. Genome sequence-based MLST approaches promise much a higher resolution for comparative phylogenetics, but there are only a small number of genome assemblies available for H. capsulatum. Aim. To develop and validate genome-based MLST typing for H. capsulatum. Methodology. A total of 406 genome assemblies were generated from publicly available Illumina short-read sequencing samples. Selected genome assemblies were subsequently used to generate MLST schemes with chewBBACA, based on whole genome sequences (wgMLST), NCBI-obtained annotations (annMLST) and annotations obtained with Funannotate (fanMLST), and used for lineage identification, and comparative analyses of population structure. Results. Genome assemblies were successfully generated for 406 H. capsulatum samples, with BUSCO completeness scores of over 98%. A subset of 60 genome assemblies was used to generate and validate MLST schemes based on the 60 genome assemblies, 5 genome annotations obtained from Genbank, and 13 genome annotations generated using Funannotate, resulting in schemes with > 8,000 markers. Each of the MLST schemes allowed reproducible separation of all 7 lineages and 6 H. capsulatum Suramericanum sublineages, without the need for high-performance clusters or powerful computing equipment. Comparison of the different schemes using tanglegrams and scatter plots showed good reproducibility (r2 values of 0.8-1.0). Comparison of total sizes of genome assemblies showed significant lineage-dependent size differences, with the Suramericanum, LAmB, India, Capsulatum and Mississippiense lineages averaging a total genome size of 30-33 million bp, and the Africa and Ohiense lineages averaging at 39 million bp. Conclusion. Genome sequence- and especially genome annotation-based MLST analyses are a promising approach that can be adapted as a rapid, high-throughput method for genomic clustering and epidemiological tracing of pathogenic fungi. ### Competing Interest Statement The authors have declared no competing interest.

BSR-Based Allele Calling Algorithm. Contribute to B-UMMI/chewBBACA development by creating an account on GitHub.

Podcast Episode · Machine Learning Street Talk (MLST) · 30 September · 1hr 14min