11-Year Genomic Surveillance of Listeria monocytogenes in Coastal China: Comparative Analysis of Environmental, Food, and Clinical Strains Reveals Transnational Transmission Risks

11-Year Genomic Surveillance of Listeria monocytogenes in Coastal China: Comparative Analysis of Environmental, Food, and Clinical Strains Reveals Transnational Transmission Risks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article 11-Year Genomic Surveillance of Listeria monocytogenes in Coastal China: Comparative Analysis of Environmental, Food, and Clinical Strains Reveals Transnational Transmission Risks Wenjuan Liu, Hongtao Wang, Lili Xing, Xinyu Zhang, Yunlong Tian, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6494017/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Listeria monocytogenes (Lm) poses significant public health risks through contaminated foods. This 11-year genomic surveillance (2014–2024) analyzed 2,150 samples from food chains and clinical cases in Yantai, China. Whole-genome sequencing of 45 strains (21 local isolates, 24 global references) revealed key findings: Prevalence: Overall detection rate of 1.77%, with edible fungi showing the highest contamination (20%, p < 0.05 vs. other categories). Antimicrobial Resistance: Universal carriage of lin, mprF, and norB genes; 33.3% harbored fosX. Virulence Determinants: 83 virulence genes identified, including conserved invasion/adherence factors (inlA, hly) and variable exotoxin genes (76.2% loss rate). Phylogenetics: Dominant serotype 1/2a (52.4%) and ST121/ST3/ST8 clones (23.8% each). Environmental isolates clustered with international strains (Brazil, USA, Spain) with < 10 SNP differences. These findings underscore the need for enhanced environmental monitoring in food processing facilities and global genomic databases for outbreak tracing. genomic epidemiology antimicrobial resistance virulence profiling foodborne pathogen One Health Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Listeria monocytogenes , a psychrotrophic Gram-positive pathogen, causes listeriosis with case-fatality rates exceeding 20% in vulnerable populations [ 1 ]. Its persistence in food processing environments and capacity for transnational spread via cold-chain products necessitate genomic surveillance [ 2 ]. Yantai, port city, a major Chinese seafood/agricultural hub, represents an ideal sentinel site for studying Lm ecology. But systematic genomic analyses linking environmental reservoirs to clinical outcomes remain limited. This study integrates 11 years of surveillance data to: Characterize Lm prevalence across food categories. Decipher antimicrobial resistance (AMR) and virulence gene landscapes. Trace phylogenetic relationships using whole-genome sequencing (WGS). 2. Materials and Methods 2.1. Strain Collection Local isolates (n = 21): Collected from seven food categories (Table 1 ) and clinical cases through China’s National Food Safety Risk Monitoring Program (2014–2024). Global references (n = 24): Obtained from NCBI, spanning diverse geographies/isolation sources. Table 1 Isolation sources of Listeria monocytogenes strains Id of Isolation Country Year Sample Types LM01 China 2017 Meat Processing Environment - Cooked Area LM02 China 2022 Ready-to-Eat Aquatic Products - Sea Bream LM03 China 2019 Pudding - Yogurt Pudding LM04 China 2021 Edible Fungi - Flammulina velutipes LM05 China 2022 Pre-packaged Chilled Ready-to-Eat Food - Pork with Tomato Sauce Meal LM06 China 2018 Raw Poultry Meat - Chicken LM07 China 2018 Raw Livestock Meat - Pork LM08 China 2024 Human - Blood L1HJB2500242-A1 China 2018 Meat Processing Environment - Raw Meat Processing Area L1HJB2500243-A2 China 2018 Edible Fungi - Flammulina velutipes L1HJB2500244-A3 China 2019 Meat Processing Environment - Cooked Area L1HJB2500245-A4 China 2020 Meat Processing Environment - Raw Meat Processing Area L1HJB2500246-A5 China 2020 Edible Fungi -Flammulina velutipes L1HJB2500250-A9 China 2021 Meat Processing Environment - Raw Meat Processing Area L1HJB2500251-A10 China 2021 Raw Poultry Meat - Chicken L1HJB2500252-A11 China 2022 Edible Fungi - Flammulina velutipes L1HJB2500253-A12 China 2022 Meat Processing Environment - Cooked Area L1HJB2500254-A13 China 2022 Hot Dog Sausage L1HJB2500255-A14 China 2023 Meat Processing Environment - Raw Meat Processing Area L1HJB2500256-A15 China 2023 Ready-to-Eat Aquatic Products - Sea Salmon L1HJB2500257-A16 China 2023 Hot Dog Sausage 27902 Brazil 2009 Raw beef 80517 Spain 2017 / 5600 Chile 2013 / 27905 Brazil 2012 Raw beef 80510 Spain 2019 / 80516 Spain 2017 / 27907 Brazil 2006 CSF 27908 Brazil 2012 Raw beef 27911 Brazil 1985 Raw beef 92 France 1996 / 26 USA 1994 / 83 France 2009 MN 28 Italy 1997 Febrile gastrointestinal infection 82 France 2009 Unknown 109240 Mexico 2015 Ham 109243 Mexico 2015 Ham 102784 Costa Rica 2019 Fresh cheese 27929 Brazil 2012 Grinder 27928 Brazil 2004 CSF 27925 Brazil 2010 CSF 27934 Brazil 2003 Raw beef 102764 Costa Rica 2019 Fresh cheese 102772 Costa Rica 2019 Blood 44121 Algeria 2010 / 2.2. Detection Methods Testing for the samples was processed according with the National Standard of the People's Republic of China (GB 4789.30-2016) and the National Food Contamination and Hazardous Factors Risk Workbook (2014-2024). 2.3. Genomic Analysis Pipeline 2.3.1. DNA Extraction: QIAamp DNA Mini Kit (Qiagen); 2.3.2 Sequencing: Illumina NextSeq 2000 (2×150 bp); 2.3.3 Bioinformatics 1）De novo assembly: Microobench that is based on FastQC v0.11.5 [3] and Trimmomatic v0.36 [4].; 2）AMR/Virulence genes: CARD/VFDB databases (95% identity cutoff); 3）Phylogenetics: cgMLST (BacWGSTdb)[5], SNP-based trees (IQ-TREE); 2.3.4. Statistical Analysis: Detection rates compared using χ² tests (SPSS v25). 3. Results 3.1. Epidemiological Trends Lm prevalence varied significantly by food category (χ²=15.7, p = 0.016), with edible fungi (20%) and meat processing environments (3.17%) as high-risk reservoirs (Table.1). Table 1 Lm detection rates across food categories. (B) Minimum-spanning tree of cgMLST profiles. Types of food N Tested samples N Positive samples(%) Raw animal meat 623 6(0.96) Raw poultry 591 8(1.35) Edible fungi 30 6(20.00) Aquatic product 355 4(1.12) Prepackaged food 121 3(2.48) Meat processing environment 315 10(3.17) Dairy product(pudding) 115 1(0.09) Total 2150 38(1.77) 3.2. AMR Genes Whole-genome analysis revealed four conserved antimicrobial resistance (AMR) determinants among Lm isolates (Fig. 2 ). Three genes—lin (lincosamide resistance, 100%, 21/21), mprF (cationic peptide tolerance, 100%, 21/21), and norB (fluoroquinolone efflux, 100%, 21/21)—were universally present, forming a core resistome. Notably, fosX, conferring fosfomycin resistance through enzymatic inactivation, exhibited strain-specific distribution (33.3%, 7/21; χ²=8.92, p = 0.003 vs. other genes) (Fig. 1 ). These findings underscore the fixation of multidrug resistance mechanisms in Yantai's Lm populations, particularly concerning lincosamide and fluoroquinolone therapies. 3.3. Virulence Gene Distribution Analysis Whole-genome analysis of 21 Lm isolates revealed a core repertoire of 83 virulence-associated genes. Among these, 71 genes (85.5%) demonstrated universal conservation across all isolates, while 12 genes exhibited heterogeneous distribution patterns: lntA, inlF, inlJ, inlA, atcA, vip, hbp1/svpA, and five lls cluster genes (llsD, llsY, llsH, llsX, llsB) showed strain-specific presence/absence profiles (Fig. 2 ). These distribution variations accounted for 83 strain-specific differences in virulence gene content. 3.4. Functional Categorization of Virulence Factors The 83 identified genes encoded 44 virulence factors classified into eight functional categories (Table 3 ): Post-translational modification were 18.2% (8/44); Adhesion mechanisms were 15.9% (7/44); Exotoxin production, host cell invasion, and regulatory systems were 11.4% each (5/44 per category); Nutritional/metabolic adaptation, immune evasion, and stress response were 9.1% each (4/44 per category), Motility-associated factors were 4.5% (2/44). Table 3 Distribution of Virulence Factors (n = 44) Virulence Factor Category N Related virulence factors Rate (%) Motility 2 4.50% Nutritional/Metabolic factor 4 9.10% Regulation 5 11.40% Adherence 7 15.90% Post-translational modification 8 18.20% Immune modulation 4 9.10% Stress survival 4 9.10% Exotoxin 5 11.40% Invasion 5 11.40% Notably, 76.2% (16/21) of isolates showed partial or complete loss of exotoxin-associated genes, particularly those in the lls cluster. Nutritional/metabolic adaptation and invasion-related genes exhibited the second highest loss frequency (33.3%, 7/21). More moderate absence patterns were observed for motility (23.8%, 5/21) and adhesion-related factors (19.0%, 4/21), with complete categorical preservation of post-translational modification and regulatory genes (Table 4 ). Table 4 Virulence genes lost patterns in the studied strains (n = 21) virulence Gene Function N Lost Strains Rate (%) lntA Immune modulation 1 4.8 inlF、inlJ Adherence 5 2.38 inlA Invasion 2 9.5 atcA Motility 6 28.6 vip Invasion 7 33.3 hbp1/svpA Nutritional/Metabolic factor 7 33.3 llsD、llsY、llsH、llsX、llsB Exotoxin 16 76.2 3.5. Comparative Genomics and Phylogenetic Analysis Twenty-one Lm isolates were categorized into four serotypes: 1/2a (52.4%), 1/2b (28.6%), 1/2c (14.3%), and 4b (4.8%). Among the eight identified sequence types, ST121, ST3, and ST8 were most prevalent (each 23.8%). Allelic locus differences ranged from 1 to 1,996. Environmental isolates distributed across multiple phylogenetic branches; for instance, L1HJB2500250-A9 clustered with LM04, LM05, etc., and Flammulina velutipes-derived L1HJB2500243-A2 was closely related to LM01, with < 10 average SNP differences (Fig. 3 ). A phylogenetic analysis of 45 international Lm isolates, based on 82,737 core genome SNPs, revealed two major lineages. Lineage I comprised CC2 (31.1%), CC3 (20.0%), and CC87 (2.2%), while Lineage II included CC121 (22.2%), CC8 (15.6%), etc. Yantai isolates clustering closely with those from Brazil, the U.S., and Spain; for example, LM01 grouped with U.S. isolate 26 and Brazilian isolates 27907–27911. Clinical isolate LM08 clustered with Brazilian meat strains (SNP difference = 12) (Fig. 4). 4. Discussion Edible fungi exhibited alarming contamination rates (20%, p < 0.01 vs. other foods), likely due to soil-rich cultivation practices. The predominance of serotype 1/2a (52.4%) aligns with China's clinical listeriosis profile [ 6 ], suggesting food-chain origins of human infections. The conserved resistome (lin/mprF/norB:100%; fosX:33.3%) mirrors U.S. AMR trends [ 7 ], with norB-mediated fluoroquinolone resistance (efflux pumps) and mprF-driven membrane remodeling posing particular challenges. While these genes aren't WHO-critical, their persistence warrants surveillance given increasing antibiotic usage in Chinese aquaculture [ 8 – 12 ]. Core virulence factors (71/83 genes, 85.5%) maintained conserved roles in invasion (inlA), intracellular survival (hly), and immune evasion (prfA). Strikingly, 76.2% of isolates lacked exotoxin genes (lls cluster), indicating environmental adaptation through metabolic streamlining [ 13 – 18 ]. Phylogenetic clustering with North American/European strains (< 10 SNPs) implicates global food trade in pathogen dissemination. The ST121/ST3/ST8 clones, prevalent in both local edible fungi and international meat products, highlight cold-chain transmission risks [ 19 ]. The cross-contamination of the environment likely enable recurrent contamination cycles [ 20 ]. 5. Conclusion These findings highlight substantial public health concerns associated with Lm contamination. We recommend:1)Enhanced surveillance focusing on food processing environments and exposure factors linked to edible fungi; 2)Implementation of targeted disinfection protocols coupled with environmental monitoring to identify emerging strains; 3)Development of robust international traceability systems, particularly for cold-chain food products, and Creation of a global genomic database to facilitate rapid outbreak source tracking. Declarations Author Contributions :Conceptualization, J.Y. and H.W.; methodology, W.L. and X.Z.; formal analysis, Y.T.; writing—original draft, W.L.; writing—review & editing, J.Y. All authors approved the final version. Funding: National Pathogenic Bacteria Identification Network (2021-2025); School Health Association of Shandong Province (Grant Number: SDWS2024095).The authors are grateful for the support of these foundations. Conflicts of Interest: The authors declare no conflicts. Data Availability Statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author. References Radoshevich L, Cossart P. Nat Rev Microbiol. 2018;16:32–46. https://doi.org/10.1038/nrmicro.2017.126 . WHO. Listeriosis Factsheet; WHO Press: Geneva, 2023. Andrews S. FastQC: a quality control tool for high throughput sequence data.2010. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. 10.1093/bioinformatics/btu170 . Epub 2014 Apr 1. PMID: 24695404; PMCID: PMC4103590. FENG Y, ZOU S M, CHEN H F, et al. BacWGSTdb 2.0: A one-stop repository for bacterial whole-genome sequence typing and source tracking[J]. Nucleic Acids Res. 2021;49(D1):D644–50. Anwar MT. Genetic diversity and genomic characteristics of foodborne, animal-derived, and human-derived Listeria monocytogenes [D]. Zhejiang Univ. 2022. 10.27461/d.cnki.gzjdx.2022.000246 . Hanes RM, Huang Z. Survey of Antimicrobial Resistance Genes in Listeria monocytogenes from 2010 to 2021 [J]. Int J Environ Res Public Health. 2022;19(9):5506. 10.3390/ijerph19095506 . Anita Chepkemei J, Mwaniki. And rew Nyerere等. Phenotypic and Genotypic Characterisation of Antibiotic Resistance in Escherichia coli, Klebsiella spp., and Listeria monocytogenes Isolates from Raw Meat Sold in Nairobi[J]. Microbiol (English Edition), 2022, (11):603–20. Wu WY, Pan XM, Lu YM et al. Analysis of macrolide and lincosamide resistance genotypes and phenotypes in methicillin-resistant Staphylococcus haemolyticus [J]. Chin J Antibiot, 2008, (6):379–83. Liu M, Liu XF, Yu H, et al. Research progress on drug resistance of Staphylococcus aureus to quinolones [J]. Clin Lab Med. 2020;17(22):3363–6. Thedieck K, Hain T, Mohamed W, et al. The MprF protein is required for lysinylation of phospholipids in listerial membranes and confers resistance to cationic antimicrobial peptides (CAMPs) on Listeria monocytogenes [J]. Mol Microbiol. 2006;62:1325–39. Zhong JX, Wang YY, Bai LL, et al. Molecular typing and resistance characteristics of Clostridium perfringens from a region in Shandong [J]. Chin J Antibiot. 2023;48(9):1057–63. Li AH, Ye CY. Research progress on pathogenic mechanisms of Listeria monocytogenes [J]. Disease Surveillance. 2011;26(11):914–9. 10.13590/j.cjfh.2023.03.026 . Claire, Maudet, et al. Bacterial inhibition of Fas-mediated killing promotes neuroinvasion and persistence. Nature. 2022. 10.1038/s41586-022-04505-7 . Hao M, Ruan MJ, Wang HW, et al. Association between the absence of key virulence genes and pathogenicity of Listeria monocytogenes in Chaoyang District, Beijing [J]. Chin J Food Hygiene. 2022;34(01):75–81. 10.13590/j.cjfh.2022.01.015 . Zhang LY, Lin MF, Li Y, et al. Study on virulence genes, serotyping, and molecular typing of Listeria monocytogenes in Wenzhou City [J]. Chin J Food Hygiene. 2018;30(05):468–72. 10.13590/j.cjfh.2018.05.004 . Quereda JJ, Morón-García A, Palacios-Gorba C, Dessaux C, García-Del Portillo F, Pucciarelli MG, Ortega AD. Pathogenicity and virulence of Listeria monocytogenes: A trip from environmental to medical microbiology. Virulence. 2021;12(1):2509–2545. doi: 10.1080/21505594.2021.1975526. PMID: 34612177. Shi D, Anwar TM, Pan H, Chai W, Xu S, Yue M. Genomic Determinants of Pathogenicity and Antimicrobial Resistance for 60 Global Listeria monocytogenes Isolates Responsible for Invasive Infections. Front Cell Infect Microbiol. 2021;11:718840. 10.3389/fcimb.2021.718840 . PMID: 34778102. Smith A et al. Biofilm formation enhances environmental persistence of L. monocytogenes. Appl Environ Microbiol. 2020. Risk assessment of Listeria monocytogenes in. foods - Part 1: Formal models, meeting report.FAO and WHO. 2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6494017","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":450394870,"identity":"d2413d2f-78d6-4d32-8997-458f6f111c78","order_by":0,"name":"Wenjuan Liu","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Wenjuan","middleName":"","lastName":"Liu","suffix":""},{"id":450394871,"identity":"183f40a9-9007-4c75-9185-de3dd0a95a8f","order_by":1,"name":"Hongtao Wang","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Hongtao","middleName":"","lastName":"Wang","suffix":""},{"id":450394872,"identity":"953b24d3-5600-49e9-9ead-7eddef2a19d7","order_by":2,"name":"Lili Xing","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Xing","suffix":""},{"id":450394873,"identity":"9764afe6-4a35-4e5b-803a-90d77e9572ad","order_by":3,"name":"Xinyu Zhang","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Zhang","suffix":""},{"id":450394874,"identity":"c49581d6-ca63-42e8-84d1-39c1dfadc81d","order_by":4,"name":"Yunlong Tian","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yunlong","middleName":"","lastName":"Tian","suffix":""},{"id":450394875,"identity":"adf4ca35-083a-48a8-83e1-9c96f183cccf","order_by":5,"name":"Wenjun Wang","email":"","orcid":"","institution":"Yantai Marine Environment Monitoring and Forecasting center","correspondingAuthor":false,"prefix":"","firstName":"Wenjun","middleName":"","lastName":"Wang","suffix":""},{"id":450394876,"identity":"38574a48-62b6-4240-8fbc-2e37a80ec063","order_by":6,"name":"Yan Song","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Song","suffix":""},{"id":450394877,"identity":"b2c24284-2f07-4024-ba11-fdf84b54be8c","order_by":7,"name":"Yan Li","email":"","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Li","suffix":""},{"id":450394878,"identity":"d3c19d36-c2b2-4a76-9d94-68a818f658bb","order_by":8,"name":"Jian Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBAC+/nPDz5IqLCRY2NvIFKLAUNOssGDM2nG/DwHiNaSYCb4sO1w4swZCURqMWc4kMaQ2HbY2ODm4403GGpsoglqsWxsPPYg4Vy6nMHttGILhmNpuQ0E9RxmSDdIKLM2NridYybB2HCYCC3HGMwkEtiYEzfcPEOkFoMzIC1tzkDv8xCpRXIGT7JBAjiQgX5JIMYv/BLsBx/+AEfl4Y03PtTYEOEXZEdKJJCiHKKFVB2jYBSMglEwMgAA5GhC+77ORSQAAAAASUVORK5CYII=","orcid":"","institution":"Yantai Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Jian","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-04-21 08:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6494017/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6494017/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82154744,"identity":"a8831e79-13c1-4a14-8172-34bd5b12d317","added_by":"auto","created_at":"2025-05-07 07:33:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":71147,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of Antimicrobial Resistance Gene Carriage in the 21 strains of \u003cem\u003eListeria monocytogenes\u003c/em\u003e- 95%\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6494017/v1/5ad6682ce717f7e3f386b3a0.png"},{"id":82153468,"identity":"cbc458f3-4644-4c4f-ab4e-1e0b94565566","added_by":"auto","created_at":"2025-05-07 07:25:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":115134,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of Virulence Genes in 21\u003cem\u003e Listeria monocytogenes\u003c/em\u003e Strains\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6494017/v1/c4637db56682953255366024.png"},{"id":82150637,"identity":"cdf3ad78-58a0-4052-b03a-94628f9c304e","added_by":"auto","created_at":"2025-05-07 07:17:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56149,"visible":true,"origin":"","legend":"\u003cp\u003eMinimum-spanning tree of 21\u003cem\u003eListeria monocytogenes \u003c/em\u003eisolates showing the genetic relationships based on the cgMLST analysis\u003c/p\u003e","description":"","filename":"floatimage318.png","url":"https://assets-eu.researchsquare.com/files/rs-6494017/v1/3600205d1a46a03e7edc1e0d.png"},{"id":82154746,"identity":"aa7d9e79-d185-4a00-8e2e-7c1d15d73085","added_by":"auto","created_at":"2025-05-07 07:33:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":72617,"visible":true,"origin":"","legend":"\u003cp\u003eWg-SNPs phylogenetic tree of 45 \u003cem\u003eListeria monocytogenes\u003c/em\u003e isolated strains\u003c/p\u003e\n\u003cp\u003eThe circle diagram from outside to inside: The seventh circle is Sample Type.The sixth circle is Serotype.The fifth circle is year.The forth circle is country.The third circle is ST. The second circle is Clonal Complex.The first circle is Strain number.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6494017/v1/456268752c8e459960d30cb2.png"},{"id":82818085,"identity":"70d71d1b-d266-4745-acde-f6d038a79e47","added_by":"auto","created_at":"2025-05-15 14:38:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1051036,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6494017/v1/ded4dae8-089b-450b-90ec-6a8ab759b5ca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"11-Year Genomic Surveillance of Listeria monocytogenes in Coastal China: Comparative Analysis of Environmental, Food, and Clinical Strains Reveals Transnational Transmission Risks","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cem\u003eListeria monocytogenes\u003c/em\u003e, a psychrotrophic Gram-positive pathogen, causes listeriosis with case-fatality rates exceeding 20% in vulnerable populations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its persistence in food processing environments and capacity for transnational spread via cold-chain products necessitate genomic surveillance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Yantai, port city, a major Chinese seafood/agricultural hub, represents an ideal sentinel site for studying Lm ecology. But systematic genomic analyses linking environmental reservoirs to clinical outcomes remain limited. This study integrates 11 years of surveillance data to:\u003c/p\u003e \u003cp\u003eCharacterize Lm prevalence across food categories.\u003c/p\u003e \u003cp\u003eDecipher antimicrobial resistance (AMR) and virulence gene landscapes.\u003c/p\u003e \u003cp\u003eTrace phylogenetic relationships using whole-genome sequencing (WGS).\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Strain Collection\u003c/h2\u003e \u003cp\u003eLocal isolates (n\u0026thinsp;=\u0026thinsp;21): Collected from seven food categories (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and clinical cases through China\u0026rsquo;s National Food Safety Risk Monitoring Program (2014\u0026ndash;2024).\u003c/p\u003e \u003cp\u003eGlobal references (n\u0026thinsp;=\u0026thinsp;24): Obtained from NCBI, spanning diverse geographies/isolation sources.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIsolation sources of \u003cem\u003eListeria monocytogenes\u003c/em\u003e strains\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eId of Isolation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Types\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Cooked Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReady-to-Eat Aquatic Products - Sea Bream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePudding - Yogurt Pudding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEdible Fungi - Flammulina velutipes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre-packaged Chilled Ready-to-Eat Food - Pork with Tomato Sauce Meal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw Poultry Meat - Chicken\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw Livestock Meat - Pork\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHuman - Blood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500242-A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Raw Meat Processing Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500243-A2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEdible Fungi - Flammulina velutipes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500244-A3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Cooked Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500245-A4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Raw Meat Processing Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500246-A5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEdible Fungi -Flammulina velutipes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500250-A9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Raw Meat Processing Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500251-A10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw Poultry Meat - Chicken\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500252-A11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEdible Fungi - Flammulina velutipes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500253-A12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Cooked Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500254-A13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHot Dog Sausage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500255-A14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeat Processing Environment - Raw Meat Processing Area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500256-A15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReady-to-Eat Aquatic Products - Sea Salmon\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1HJB2500257-A16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHot Dog Sausage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw beef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw beef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw beef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw beef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFebrile gastrointestinal infection\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e109240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHam\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e109243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHam\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e102784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFresh cheese\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrinder\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRaw beef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e102764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFresh cheese\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e102772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cbr\u003e\u003cp\u003e2.2. Detection Methods\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTesting for the samples was processed according with the National Standard of the People\u0026apos;s Republic of China (GB 4789.30-2016) and the National Food Contamination and Hazardous Factors Risk Workbook (2014-2024).\u003c/p\u003e\n\u003cp\u003e2.3. Genomic Analysis Pipeline\u003c/p\u003e\n\u003cp\u003e2.3.1. DNA Extraction: QIAamp DNA Mini Kit (Qiagen);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.3.2 Sequencing: Illumina NextSeq 2000 (2\u0026times;150 bp);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.3.3 Bioinformatics\u003c/p\u003e\n\u003cp\u003e1）De novo assembly: Microobench that is based on FastQC v0.11.5 [3] and Trimmomatic v0.36 [4].;\u003c/p\u003e\n\u003cp\u003e2）AMR/Virulence genes: CARD/VFDB databases (95% identity cutoff);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3）Phylogenetics: cgMLST (BacWGSTdb)[5], SNP-based trees (IQ-TREE);\u003c/p\u003e\n\u003cp\u003e2.3.4. Statistical Analysis: Detection rates compared using \u0026chi;\u0026sup2; tests (SPSS v25).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Epidemiological Trends\u003c/h2\u003e \u003cp\u003eLm prevalence varied significantly by food category (χ\u0026sup2;=15.7, p\u0026thinsp;=\u0026thinsp;0.016), with edible fungi (20%) and meat processing environments (3.17%) as high-risk reservoirs (Table.1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLm detection rates across food categories. (B) Minimum-spanning tree of cgMLST profiles.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTypes of food\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003eTested samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003ePositive samples(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaw animal meat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaw poultry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8(1.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdible fungi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAquatic product\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrepackaged food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3(2.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeat processing environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10(3.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDairy product(pudding)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1(0.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(1.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2. AMR Genes\u003c/h2\u003e \u003cp\u003eWhole-genome analysis revealed four conserved antimicrobial resistance (AMR) determinants among Lm isolates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Three genes\u0026mdash;lin (lincosamide resistance, 100%, 21/21), mprF (cationic peptide tolerance, 100%, 21/21), and norB (fluoroquinolone efflux, 100%, 21/21)\u0026mdash;were universally present, forming a core resistome. Notably, fosX, conferring fosfomycin resistance through enzymatic inactivation, exhibited strain-specific distribution (33.3%, 7/21; χ\u0026sup2;=8.92, p\u0026thinsp;=\u0026thinsp;0.003 vs. other genes) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings underscore the fixation of multidrug resistance mechanisms in Yantai's Lm populations, particularly concerning lincosamide and fluoroquinolone therapies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Virulence Gene Distribution Analysis\u003c/h2\u003e \u003cp\u003eWhole-genome analysis of 21 Lm isolates revealed a core repertoire of 83 virulence-associated genes. Among these, 71 genes (85.5%) demonstrated universal conservation across all isolates, while 12 genes exhibited heterogeneous distribution patterns: lntA, inlF, inlJ, inlA, atcA, vip, hbp1/svpA, and five lls cluster genes (llsD, llsY, llsH, llsX, llsB) showed strain-specific presence/absence profiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These distribution variations accounted for 83 strain-specific differences in virulence gene content.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Functional Categorization of Virulence Factors\u003c/h2\u003e \u003cp\u003eThe 83 identified genes encoded 44 virulence factors classified into eight functional categories (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e): Post-translational modification were 18.2% (8/44); Adhesion mechanisms were 15.9% (7/44); Exotoxin production, host cell invasion, and regulatory systems were 11.4% each (5/44 per category); Nutritional/metabolic adaptation, immune evasion, and stress response were 9.1% each (4/44 per category), Motility-associated factors were 4.5% (2/44).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Virulence Factors (n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirulence Factor Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003eRelated virulence factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMotility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritional/Metabolic factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-translational modification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmune modulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStress survival\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExotoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNotably, 76.2% (16/21) of isolates showed partial or complete loss of exotoxin-associated genes, particularly those in the lls cluster. Nutritional/metabolic adaptation and invasion-related genes exhibited the second highest loss frequency (33.3%, 7/21). More moderate absence patterns were observed for motility (23.8%, 5/21) and adhesion-related factors (19.0%, 4/21), with complete categorical preservation of post-translational modification and regulatory genes (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirulence genes lost patterns in the studied strains (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evirulence Gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFunction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003eLost Strains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elntA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune modulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einlF、inlJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einlA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eatcA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMotility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehbp1/svpA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNutritional/Metabolic factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ellsD、llsY、llsH、llsX、llsB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExotoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Comparative Genomics and Phylogenetic Analysis\u003c/h2\u003e \u003cp\u003eTwenty-one Lm isolates were categorized into four serotypes: 1/2a (52.4%), 1/2b (28.6%), 1/2c (14.3%), and 4b (4.8%). Among the eight identified sequence types, ST121, ST3, and ST8 were most prevalent (each 23.8%). Allelic locus differences ranged from 1 to 1,996. Environmental isolates distributed across multiple phylogenetic branches; for instance, L1HJB2500250-A9 clustered with LM04, LM05, etc., and Flammulina velutipes-derived L1HJB2500243-A2 was closely related to LM01, with \u0026lt;\u0026thinsp;10 average SNP differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA phylogenetic analysis of 45 international Lm isolates, based on 82,737 core genome SNPs, revealed two major lineages. Lineage I comprised CC2 (31.1%), CC3 (20.0%), and CC87 (2.2%), while Lineage II included CC121 (22.2%), CC8 (15.6%), etc. Yantai isolates clustering closely with those from Brazil, the U.S., and Spain; for example, LM01 grouped with U.S. isolate 26 and Brazilian isolates 27907\u0026ndash;27911. Clinical isolate LM08 clustered with Brazilian meat strains (SNP difference\u0026thinsp;=\u0026thinsp;12) (Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eEdible fungi exhibited alarming contamination rates (20%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 vs. other foods), likely due to soil-rich cultivation practices. The predominance of serotype 1/2a (52.4%) aligns with China's clinical listeriosis profile [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], suggesting food-chain origins of human infections.\u003c/p\u003e \u003cp\u003eThe conserved resistome (lin/mprF/norB:100%; fosX:33.3%) mirrors U.S. AMR trends [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], with norB-mediated fluoroquinolone resistance (efflux pumps) and mprF-driven membrane remodeling posing particular challenges. While these genes aren't WHO-critical, their persistence warrants surveillance given increasing antibiotic usage in Chinese aquaculture [\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCore virulence factors (71/83 genes, 85.5%) maintained conserved roles in invasion (inlA), intracellular survival (hly), and immune evasion (prfA). Strikingly, 76.2% of isolates lacked exotoxin genes (lls cluster), indicating environmental adaptation through metabolic streamlining [\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePhylogenetic clustering with North American/European strains (\u0026lt;\u0026thinsp;10 SNPs) implicates global food trade in pathogen dissemination. The ST121/ST3/ST8 clones, prevalent in both local edible fungi and international meat products, highlight cold-chain transmission risks [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The cross-contamination of the environment likely enable recurrent contamination cycles [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThese findings highlight substantial public health concerns associated with Lm contamination. We recommend:1)Enhanced surveillance focusing on food processing environments and exposure factors linked to edible fungi; 2)Implementation of targeted disinfection protocols coupled with environmental monitoring to identify emerging strains; 3)Development of robust international traceability systems, particularly for cold-chain food products, and Creation of a global genomic database to facilitate rapid outbreak source tracking.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e:Conceptualization, J.Y. and H.W.; methodology, W.L. and X.Z.; formal analysis, Y.T.; writing\u0026mdash;original draft, W.L.; writing\u0026mdash;review \u0026amp; editing, J.Y. All authors approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e National Pathogenic Bacteria Identification Network (2021-2025); School Health Association of Shandong Province (Grant Number: SDWS2024095).The authors are grateful for the support of these foundations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRadoshevich L, Cossart P. Nat Rev Microbiol. 2018;16:32\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nrmicro.2017.126\u003c/span\u003e\u003cspan address=\"10.1038/nrmicro.2017.126\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Listeriosis Factsheet; WHO Press: Geneva, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrews S. FastQC: a quality control tool for high throughput sequence data.2010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bioinformatics/btu170\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btu170\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2014 Apr 1. PMID: 24695404; PMCID: PMC4103590.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFENG Y, ZOU S M, CHEN H F, et al. BacWGSTdb 2.0: A one-stop repository for bacterial whole-genome sequence typing and source tracking[J]. Nucleic Acids Res. 2021;49(D1):D644\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnwar MT. Genetic diversity and genomic characteristics of foodborne, animal-derived, and human-derived Listeria monocytogenes [D]. Zhejiang Univ. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.27461/d.cnki.gzjdx.2022.000246\u003c/span\u003e\u003cspan address=\"10.27461/d.cnki.gzjdx.2022.000246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanes RM, Huang Z. Survey of Antimicrobial Resistance Genes in Listeria monocytogenes from 2010 to 2021 [J]. Int J Environ Res Public Health. 2022;19(9):5506. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19095506\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19095506\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnita Chepkemei J, Mwaniki. And rew Nyerere等. Phenotypic and Genotypic Characterisation of Antibiotic Resistance in Escherichia coli, Klebsiella spp., and Listeria monocytogenes Isolates from Raw Meat Sold in Nairobi[J]. Microbiol (English Edition), 2022, (11):603\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu WY, Pan XM, Lu YM et al. Analysis of macrolide and lincosamide resistance genotypes and phenotypes in methicillin-resistant Staphylococcus haemolyticus [J]. Chin J Antibiot, 2008, (6):379\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu M, Liu XF, Yu H, et al. Research progress on drug resistance of Staphylococcus aureus to quinolones [J]. Clin Lab Med. 2020;17(22):3363\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThedieck K, Hain T, Mohamed W, et al. The MprF protein is required for lysinylation of phospholipids in listerial membranes and confers resistance to cationic antimicrobial peptides (CAMPs) on Listeria monocytogenes [J]. Mol Microbiol. 2006;62:1325\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong JX, Wang YY, Bai LL, et al. Molecular typing and resistance characteristics of Clostridium perfringens from a region in Shandong [J]. Chin J Antibiot. 2023;48(9):1057\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi AH, Ye CY. Research progress on pathogenic mechanisms of Listeria monocytogenes [J]. Disease Surveillance. 2011;26(11):914\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13590/j.cjfh.2023.03.026\u003c/span\u003e\u003cspan address=\"10.13590/j.cjfh.2023.03.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClaire, Maudet, et al. Bacterial inhibition of Fas-mediated killing promotes neuroinvasion and persistence. Nature. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41586-022-04505-7\u003c/span\u003e\u003cspan address=\"10.1038/s41586-022-04505-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao M, Ruan MJ, Wang HW, et al. Association between the absence of key virulence genes and pathogenicity of Listeria monocytogenes in Chaoyang District, Beijing [J]. Chin J Food Hygiene. 2022;34(01):75\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13590/j.cjfh.2022.01.015\u003c/span\u003e\u003cspan address=\"10.13590/j.cjfh.2022.01.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang LY, Lin MF, Li Y, et al. Study on virulence genes, serotyping, and molecular typing of Listeria monocytogenes in Wenzhou City [J]. Chin J Food Hygiene. 2018;30(05):468\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13590/j.cjfh.2018.05.004\u003c/span\u003e\u003cspan address=\"10.13590/j.cjfh.2018.05.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuereda JJ, Mor\u0026oacute;n-Garc\u0026iacute;a A, Palacios-Gorba C, Dessaux C, Garc\u0026iacute;a-Del Portillo F, Pucciarelli MG, Ortega AD. Pathogenicity and virulence of Listeria monocytogenes: A trip from environmental to medical microbiology. Virulence. 2021;12(1):2509\u0026ndash;2545. doi: 10.1080/21505594.2021.1975526. PMID: 34612177.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi D, Anwar TM, Pan H, Chai W, Xu S, Yue M. Genomic Determinants of Pathogenicity and Antimicrobial Resistance for 60 Global Listeria monocytogenes Isolates Responsible for Invasive Infections. Front Cell Infect Microbiol. 2021;11:718840. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcimb.2021.718840\u003c/span\u003e\u003cspan address=\"10.3389/fcimb.2021.718840\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 34778102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith A et al. Biofilm formation enhances environmental persistence of L. monocytogenes. Appl Environ Microbiol. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRisk assessment of Listeria monocytogenes in. foods - Part 1: Formal models, meeting report.FAO and WHO. 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"genomic epidemiology, antimicrobial resistance, virulence profiling, foodborne pathogen, One Health","lastPublishedDoi":"10.21203/rs.3.rs-6494017/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6494017/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eListeria monocytogenes\u003c/em\u003e (Lm) poses significant public health risks through contaminated foods. This 11-year genomic surveillance (2014\u0026ndash;2024) analyzed 2,150 samples from food chains and clinical cases in Yantai, China. Whole-genome sequencing of 45 strains (21 local isolates, 24 global references) revealed key findings:\u003c/p\u003e \u003cp\u003ePrevalence: Overall detection rate of 1.77%, with edible fungi showing the highest contamination (20%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. other categories).\u003c/p\u003e \u003cp\u003eAntimicrobial Resistance: Universal carriage of lin, mprF, and norB genes; 33.3% harbored fosX.\u003c/p\u003e \u003cp\u003eVirulence Determinants: 83 virulence genes identified, including conserved invasion/adherence factors (inlA, hly) and variable exotoxin genes (76.2% loss rate).\u003c/p\u003e \u003cp\u003ePhylogenetics: Dominant serotype 1/2a (52.4%) and ST121/ST3/ST8 clones (23.8% each). Environmental isolates clustered with international strains (Brazil, USA, Spain) with \u0026lt;\u0026thinsp;10 SNP differences.\u003c/p\u003e \u003cp\u003eThese findings underscore the need for enhanced environmental monitoring in food processing facilities and global genomic databases for outbreak tracing.\u003c/p\u003e","manuscriptTitle":"11-Year Genomic Surveillance of Listeria monocytogenes in Coastal China: Comparative Analysis of Environmental, Food, and Clinical Strains Reveals Transnational Transmission Risks","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 07:17:37","doi":"10.21203/rs.3.rs-6494017/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e71747f-9863-4cc1-aa43-adbfe307e72e","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-15T14:38:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 07:17:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6494017","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6494017","identity":"rs-6494017","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}