Genomic insights into the evolution and adaptation of Listeria monocytogenes in poultry production systems.
Li Zhang, Satoshi Ishii, Michael J Rothrock, Adelumola Oladeinde, Xiang Li
Food research international (Ottawa, Ont.)
Abstract
Listeria monocytogenes (Lm) is a significant foodborne pathogen whose evolution has been shaped by the expansion of industrial food systems. To investigate these adaptive dynamics, we conducted a comprehensive genomic analysis of 1788 poultry-associated Lm isolates collected between 1940 and 2024. We integrated phylogenomic, demographic modeling, and pangenome analyses to reconstruct the pathogen's evolutionary history in response to anthropogenic pressures. Our pangenome analysis revealed an open pangenome with an extensive accessory genome (65.17% cloud genes), indicating remarkable genomic plasticity. Demographic reconstruction identified a five-fold increase in effective population size from 1940 to a peak around 1980, coinciding with the industrialization of poultry production. This expansion was followed by a sharp decline, likely reflecting the implementation of modern food safety interventions. Genome-wide association studies identified distinct sets of accessory genes significantly associated with specific isolation sources, including chicken, egg, and pet food, with pet food isolates showing exceptional genetic distinctiveness. Despite this extensive environmental adaptation, key virulence determinants were highly conserved across all isolates, confirming the maintenance of pathogenic potential. Collectively, these findings demonstrate that industrial food systems are the primary driver of Lm evolution, promoting niche specialization while preserving virulence. This research underscores that integrating pangenome-based surveillance into food safety frameworks complements traditional typing methods (e.g., wgMLST/cgMLST) by monitoring accessory genes driving niche adaptation. This approach aids in identifying persistence mechanisms and tracking down sources of cross-contamination, thereby better anticipating and mitigating risks.