chewBBACA: A complete suite for gene-by-gene schema creation and strain identification

Abstract

Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.

Keywords: allele calling; chewBBACA; gene-by-gene; multilocus sequence typing; schema.

Fig. 1.

chewBBACA workflow from schema definition to schema evaluation

Fig. 2.

(a) chewBBACA pairwise comparison for schema creation algorithm (b) chewBBACA allele calling algorithm.

Fig. 3.

chewBBACA allele definition outputs. (a) Size exclusion of alleles 20 % smaller or larger than the allele length mode for the loci (b) Detection of loci duplication on the draft genome (c) Detection of locus identified on the 5′ or 3′ ends of the contig (d) Detection of paralogous loci

Fig. 4.

Benchmarking of chewBBACA's allele-calling algorithm for bacterial genome assemblies (approximately 2 Mb) using a cgMLST schema of 1264 loci on a HPC cluster and two laptops with different storage devices. The allele calling was executed five times for each CPU data point.