chewBBACA 3: lowering the barrier for scalable and detailed whole- and core-genome multilocus sequence typing

The wide adoption of whole genome sequencing has enabled the implementation of genomics-based systems, which provide unparalleled resolution for the surveillance and outbreak investigation of bacterial pathogens. To fully exploit the wealth and complexity of genomics data, bioinformatics methods need to be highly scalable, provide accurate and extensive data for potential downstream analyses, as well as analytic capabilities. Here, we present chewBBACA 3, a suite of modules for scalable and comprehensive bacterial whole- and core-genome multilocus sequence typing (wg/cgMLST) with built-in features to create new schemas, evaluate loci diversity and strain similarity. chewBBACA 3 enables faster and more accurate schema creation and allele calling by complementing an alignment-based approach with alignment-free methods, including hash-based comparisons and minimizer-based clustering. Schema creation is up to 55-fold faster and identifies up to 10% more loci than its predecessor, chewBBACA 2. Furthermore, chewBBACA 3 can quickly adapt or import schemas available on external wg/cgMLST platforms or Chewie-NS, promoting interoperability. The efficiency of allele calling allows processing larger genome collections, from thousands to tens of thousands of genomes, at the whole- and core-genome levels without requiring high computational resources and being up to 52-fold faster than similar tools. chewBBACA 3’s enhanced sensitivity allows it to identify and classify more schema loci and coding sequences than the compared methods, resulting in higher resolution for strain comparison. Moreover, the allelic profiles, classification statistics and associated sequence data produced by chewBBACA 3 can be the basis for detailed analyses that provide added value in surveillance and outbreak investigation settings. New modules leverage the potential of the schema and allele call results data to create interactive reports that enable an intuitive and in-depth analysis of allele diversity in loci of interest and allow assessing strain similarity based on loci presence, allelic distances and phylogenetic analysis. chewBBACA 3 provides functionalities for complete wg/cgMLST analysis at scale, lowering the barrier for the use of wg/cgMLST and offering extensive results and analytic capabilities for streamlined, comprehensive, and local analyses. chewBBACA 3 is freely available at https://github.com/B-UMMI/chewBBACA.