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An Open-Source Program (Haplo-ST) for Whole-Genome Sequence Typing Shows Extensive Diversity among Listeria monocytogenes Isolates in Outdoor Environments and Poultry Processing Plants.


ABSTRACT: A reliable and standardized classification of Listeria monocytogenes is important for accurate strain identification during outbreak investigations. Current whole-genome sequencing (WGS)-based approaches for strain characterization are either difficult to standardize, rendering them less suitable for data exchange, or are not freely available. Thus, we developed a portable and open-source tool, Haplo-ST, to improve standardization and provide maximum discriminatory potential to WGS data tied to a multilocus sequence typing (MLST) framework. Haplo-ST performs whole-genome MLST (wgMLST) for L. monocytogenes while allowing for data exchangeability worldwide. This tool takes in (i) raw WGS reads as input, (ii) cleans the raw data according to user-specified parameters, (iii) assembles genes across loci by mapping to genes from reference strains, and (iv) assigns allelic profiles to assembled genes and provides a wgMLST subtyping for each isolate. Data exchangeability relies on the tool assigning allelic profiles based on a centralized nomenclature defined by the widely used BIGSdb-Lm database. Tests of Haplo-ST's performance with simulated reads from L. monocytogenes reference strains demonstrated high sensitivity (97.5%), and coverage depths of ?20× were found to be sufficient for wgMLST profiling. We then used Haplo-ST to characterize and differentiate between two groups of L. monocytogenes isolates derived from the natural environment and poultry processing plants. Phylogenetic reconstruction identified lineages within each group, and no lineage specificity was observed with isolate phenotypes (transient versus persistent) or origins. Genetic differentiation analyses between isolate groups identified 21 significantly differentiated loci, potentially enriched for adaptation and persistence of L. monocytogenes within poultry processing plants.IMPORTANCE We have developed an open-source tool (https://github.com/swarnalilouha/Haplo-ST) that provides allele-based subtyping of L. monocytogenes isolates at the whole-genome level. Along with allelic profiles, this tool also generates allele sequences and identifies paralogs, which is useful for phylogenetic tree reconstruction and deciphering relationships between closely related isolates. More broadly, Haplo-ST is flexible and can be adapted to characterize the genome of any haploid organism simply by installing an organism-specific gene database. Haplo-ST also allows for scalable subtyping of isolates; fewer reference genes can be used for low-resolution typing, whereas higher resolution can be achieved by increasing the number of genes used in the analysis. Our tool enabled clustering of L. monocytogenes isolates into lineages and detection of potential loci for adaptation and persistence in food processing environments. Findings from these analyses highlight the effectiveness of Haplo-ST in subtyping and evaluating relationships among isolates in studies of bacterial population genetics.

SUBMITTER: Louha S 

PROVIDER: S-EPMC7755245 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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An Open-Source Program (Haplo-ST) for Whole-Genome Sequence Typing Shows Extensive Diversity among Listeria monocytogenes Isolates in Outdoor Environments and Poultry Processing Plants.

Louha Swarnali S   Meinersmann Richard J RJ   Abdo Zaid Z   Berrang Mark E ME   Glenn Travis C TC  

Applied and environmental microbiology 20201217 1


A reliable and standardized classification of <i>Listeria monocytogenes</i> is important for accurate strain identification during outbreak investigations. Current whole-genome sequencing (WGS)-based approaches for strain characterization are either difficult to standardize, rendering them less suitable for data exchange, or are not freely available. Thus, we developed a portable and open-source tool, Haplo-ST, to improve standardization and provide maximum discriminatory potential to WGS data t  ...[more]

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