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Liao J, Guo X, Li S, Anupoju SMB, Cheng RA, Weller DL, Sullivan G, Zhang H, Deng X, Wiedmann M. Comparative genomics unveils extensive genomic variation between populations of Listeria species in natural and food-associated environments. ISME Commun 2023; 3:85. [PMID: 37598265 PMCID: PMC10439904 DOI: 10.1038/s43705-023-00293-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 08/21/2023]
Abstract
Comprehending bacterial genomic variation linked to distinct environments can yield novel insights into mechanisms underlying differential adaptation and transmission of microbes across environments. Gaining such insights is particularly crucial for pathogens as it benefits public health surveillance. However, the understanding of bacterial genomic variation is limited by a scarcity of investigations in genomic variation coupled with different ecological contexts. To address this limitation, we focused on Listeria, an important bacterial genus for food safety that includes the human pathogen L. monocytogenes, and analyzed a large-scale genomic dataset collected by us from natural and food-associated environments across the United States. Through comparative genomics analyses on 449 isolates from the soil and 390 isolates from agricultural water and produce processing facilities representing L. monocytogenes, L. seeligeri, L. innocua, and L. welshimeri, we find that the genomic profiles strongly differ by environments within each species. This is supported by the environment-associated subclades and differential presence of plasmids, stress islands, and accessory genes involved in cell envelope biogenesis and carbohydrate transport and metabolism. Core genomes of Listeria species are also strongly associated with environments and can accurately predict isolation sources at the lineage level in L. monocytogenes using machine learning. We find that the large environment-associated genomic variation in Listeria appears to be jointly driven by soil property, climate, land use, and accompanying bacterial species, chiefly representing Actinobacteria and Proteobacteria. Collectively, our data suggest that populations of Listeria species have genetically adapted to different environments, which may limit their transmission from natural to food-associated environments.
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Affiliation(s)
- Jingqiu Liao
- Department of Food Science, Cornell University, Ithaca, NY, USA.
- Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
| | - Xiaodong Guo
- Department of Food Science, Cornell University, Ithaca, NY, USA
| | - Shaoting Li
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou, Guangdong, China
| | | | - Rachel A Cheng
- Department of Food Science and Technology, Virginia Tech, Blacksburg, VA, USA
| | - Daniel L Weller
- Department of Food Science and Technology, Virginia Tech, Blacksburg, VA, USA
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Hailong Zhang
- Department of Business Information Technology, Virginia Tech, Blacksburg, VA, USA
| | - Xiangyu Deng
- Center for Food Safety, University of Georgia, Griffin, GA, USA
| | - Martin Wiedmann
- Department of Food Science, Cornell University, Ithaca, NY, USA
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