Global diversity and Azithromycin resistance of Salmonella enterica serovar London: a genomic epidemiology study

Global diversity and Azithromycin resistance of Salmonella enterica serovar London: a genomic epidemiology study | 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 Article Global diversity and Azithromycin resistance of Salmonella enterica serovar London: a genomic epidemiology study Zhenzhou Huang, Zhibei Zheng, Hua Yu, Wei Zheng, Xiuqin Lou, Pan Zhao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9203063/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 Non-typhoidal Salmonella enterica serovar London (S. London) represents an emerging zoonotic threat with escalating azithromycin resistance, yet its global population structure and evolutionary dynamics remain poorly characterized. Here we present a genomic epidemiology analysis of 946 global isolates from 1984–2024, revealing four major clades (C1–C4) and eight sub-clades, with distinct geographical distributions and host adaptations. Notably, sub-clade C1.1 was predominantly endemic to China, while C3.1 demonstrated cosmopolitan distribution. The C1.1 exhibited alarming azithromycin resistance (62.1%, 123/198) driven by mphA-harboring multidrug resistance cassettes located on IncFIB(K) plasmids. These super-resistance islands, mobilized by transposable elements, facilitate horizontal transmission across animal-food-human interfaces. Distinct sub-clades exhibited specialized virulence–resistance co-evolutionary strategies. Analysis revealed a farm-to-fork transmission trajectory, with pork production systems as the primary conduit for dissemination. Our findings highlight the urgent need for integrated One Health surveillance to contain the global dissemination of high-risk MDR clones and preserve last-resort antimicrobial therapies. Biological sciences/Microbiology/Bacteria/Infectious-disease epidemiology Biological sciences/Microbiology/Antimicrobials/Antimicrobial resistance Biological sciences/Microbiology/Bacteria/Bacterial genomics Salmonella enterica serovar London Global dissemination Azithromycin resistance mphA gene Genomic epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Non-typhoidal Salmonella (NTS) represents a preeminent etiologic agent of acute gastroenteritis and constitutes a paradigmatic zoonotic pathogen of global public health significance. Responsible for an estimated 138 million human infections and 57,000 fatalities annually, NTS ranks as the fourth leading cause of diarrheal mortality worldwide 1 . Transmission occurs predominantly via the fecal-oral route, with consumption of contaminated animal-derived products, particularly pork and poultry eggs 2 . The global trade networks and the modern food supply chains have catalyzed the emergence of NTS as a trans-boundary threat 3 . Salmonella enterica serovar London ( S. London) (antigenic formula 3,10:l,v:1,6) 4 exemplifies a generalist serovar capable of colonizing diverse hosts including humans, swine, and avian species. While S . Typhimurium and S . Enteritidis have garnered substantial research attention due to their association with invasive non-typhoidal salmonellosis (iNTS) and epidemic potential in sub-Saharan Africa 5 , S. London remains comparatively understudied, despite its documented implication in invasive disease outbreaks and considerable clinical burden 6 . Epidemiological investigations have documented a marked upsurge in the prevalence of S. London within porcine production systems and pork products. In the United Kingdom, S. London accounts for 2.6% of swine-derived Salmonella isolates 7 . Whereas positive rate of S. London from pork and chicken sausages was 20.8% detected in France 8 , establishing it as a co-dominant serovar alongside S . Typhimurium and S . Derby. Similarly, through a municipal market surveillance in Guangzhou, China, S. London was identified in 15.3% of pork-associated isolates 9 , underscoring its emergence as a predominant foodborne hazard. Fluoroquinolones and third-generation cephalosporins have historically constituted the cornerstone of antimicrobial therapy for iNTS infections 10 . However, the rapid dissemination of resistance determinants against these agents has precipitated a therapeutic crisis, compelling the adoption of azithromycin 11 , a macrolide antibiotic, as the primary alternative for managing severe iNTS and complicated gastroenteritis 12,13 . Alarmingly, global surveillance indicates escalating azithromycin resistance among NTS isolates. Data from the United States National Antimicrobial Resistance Monitoring System (NARMS) revealed that resistance prevalence increased from <0.5% in 2018 to 1.6–1.8% during 2020–2023 14 . In China, multicenter studies have documented azithromycin resistance rates of 3.08% among NTS isolates 15 , while regional surveillance in Zhejiang Province (2016–2021) reported a striking 32.1% resistance rate among S . London and S . Kentucky isolates from clinical and food sources 16 . The molecular architecture of azithromycin resistance in NTS encompasses phosphotransferase-mediated inactivation, 23S rRNA methylation by methyltransferases, ribosomal protein modifications, and efflux pump overexpression 11 . Among these mechanisms, the phosphotransferase encoded by the mph A gene predominates and has demonstrated capacity for rapid plasmid-mediated horizontal dissemination 17 . The global emergence of mph A-harboring MDR Salmonella has been reported across the Middle East 18 , Europe 19,20 , and Southeast Asia 17,21 . Octavia et al. recently reported a clinical isolate of S . London harboring both bla NDM-1 and mph A in Singapore 22 , exemplifying the propensity for acquiring and transmitting high-risk resistance determinants. Despite these concerning epidemiological trends, a comprehensive genomic investigation elucidating the evolutionary dynamics and transmission networks of S . London remains conspicuously absent. Herein, we systematically assemble the largest scale of S . London genome dataset to date. Our findings provide critical insights into the global population structure, azithromycin-resistant landscape within this clinically significant serovar, thereby informing targeted surveillance and evidence-based strategies of this emerging pathogen. Materials and Methods Isolate Collection During 2017–2023, 918 Salmonella isolates were collected from 16 sentinel hospitals in Hangzhou, Zhejiang Province, China, through the National Surveillance for Foodborne Diseases and Chinese Pathogen Identification Net. Common serovars included S Typhimurium (4,5,12:i:1,2), S Enteritidis (9,12:g,m:-) and monophasic Typhimurium (I 4,[5],12:i:-), but S. London (3,10:l,v:1,6) represented the fourth most prevalent (n = 137). Despite its lower prevalence relative to I 4,[5],12:i:- (14.9% versus 24.9%), S. London exhibited a significantly elevated mphA -positive rate (45.9% versus 3.1%; 15-fold higher), surpassing the overall surveillance average of 11.11% (102/918). Thus, S. London accounted for the majority of azithromycin-resistant isolates in our collection. Also, a corpus of >1,050,000 Salmonella genomes was retrieved from the GenBank and EnteroBase repositories (accessed December 1, 2025). Subsequent in silico serotyping was analyzed by two methods, SeqSero2 v1.3.1 (https://github.com/denglab/SeqSero2) 23 and SISTR v1.1.1 ( Salmonella in silico typing resource, https://lfz.corefacility.ca/sistr-app/) 24 , and finally identified 809 isolates exhibiting the antigenic determinants of 3,10:l,v:1,6. A total of 946 S. London isolates were analyzed in this study, including 809 public isolates and 137 newly sequenced strains (Table S1). Isolation sources included human clinical samples (n=236), food (n=471), environmental samples (n=27), and animal (n=202). Bacterial Culture and Identification Isolates were cultured on Salmonella - Shigella (SS) agar at 37°C for 18–24 hours. Species confirmation was validated by both VITEK®2 Compact system (bioMérieux, France) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS; Bruker, Germany). Serotyping was performed using slide agglutination with specific antisera (Statens Serum Institut, Copenhagen, Denmark) according to the Kauffmann-White scheme 25 . Antimicrobial Susceptibility Testing Antimicrobial susceptibility testing was performed using broth microdilution panels ( Enterobacteriaceae susceptibility kits; Shandong Xinke, China) to determine the minimum inhibitory concentrations (MICs) of 14 antimicrobial agents. The panel comprised ampicillin (2–64 μg/mL), ampicillin/sulbactam (2/1–64/32 μg/mL), cefotaxime (0.25–8 μg/mL), ceftazidime (0.5–16 μg/mL), meropenem (0.06–4 μg/mL), nalidixic acid (2–64 μg/mL), ciprofloxacin (0.03–32 μg/mL), azithromycin (2–64 μg/mL), streptomycin (4–32 μg/mL), amikacin (4–128 μg/mL), tetracycline (1–32 μg/mL), chloramphenicol (2–64 μg/mL), trimethoprim-sulfamethoxazole (0.25/4.75–8/152 μg/mL), colistin (polymyxin E; 0.5–16 μg/mL). Resistance breakpoints were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines (2024 edition) 26 . For streptomycin, which lacks CLSI-established breakpoints, interpretive criteria were adopted from the United States National Antimicrobial Resistance Monitoring System (NARMS) 27 . Isolates resistant to three or more antibiotic classes were classified as MDR 28 . Whole-Genome Sequencing Our 137 isolates were subjected to whole-genome sequencing. Genomic DNA was extracted using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) and quantified by Qubit 4.0 (Thermo Fisher Scientific, Waltham, MA, USA). Libraries were constructed using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) and sequenced on the Illumina NextSeq 2000 platform with the scheme of 150-bp paired-end reads. Thirteen S. London isolates were sequenced on a GridION (Oxford Nanopore Technologies, Oxford, UK). The mean coverage depth across all isolates was 130×. Raw reads were trimmed with Trimmomatic v0.36 29 and assembled de novo using SPAdes v3.15.5 30 . Phylogenetic Analysis Core-genome multilocus sequence typing (cgMLST) was performed employing a curated schema of 3,002 core genes to establish high-resolution genotypic relationships 31 . For phylogenomic reconstruction, core-genome single nucleotide polymorphisms (cgSNPs) were identified by mapping quality-filtered reads against a S. London reference genome (accession No. GCA_018338335.1) using Snippy v4.6.0 (https://github.com/tseemann/snippy). Gubbins v2.4.1 32 was used to remove recombinant regions and spurious variants. Population structure was elucidated using fastBAPS v1.0.6 hierarchical Bayesian clustering 33 . Maximum-likelihood phylogenetic trees were subsequently inferred using IQ-TREE v2.2.0 by 1,000 bootstrap replicates 34 , and visualized using ggtree R package 35 . Functional genomic surveys of virulence determinants and antimicrobial resistance (AMR) were searched against the Virulence Factor Database (VFDB 2024 release) 36 and the Comprehensive Antibiotic Resistance Database (CARD v3.2.9) 37 , respectively. Identification of plasmid replicons was performed using PlasmidFinder v2.1 38 , thereby illuminating potential vectors for horizontal mphA gene transfer. Statistical Analysis Statistical analyses were performed using SPSS Statistics v21.0 (IBM Corp., Armonk, NY, USA) and R v4.2.0. Categorical variables were presented as absolute counts and relative frequencies. Comparisons of proportions between groups were conducted using Pearson’s χ² test or two-tailed Fisher’s exact test, where appropriate, followed by Benjamini-Hochberg correction for multiple testing. Distribution disparities across sub-clades were assessed using the Kruskal–Wallis test. Ethics Statement All human isolates were obtained from routine clinical diagnostics, with ethical approval from Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution) Ethics Committee. Food and environmental isolates were collected as part of national surveillance programs, with permission from relevant authorities. Results Genomic Dataset of S. London This study assembled the largest S. London genome dataset to date, comprising 946 globally distributed isolates. We newly sequenced 137 surveillance isolates and integrated 809 publicly available genomes from GenBank and EnteroBase database. ANI analysis of all 946 genomes yielded values ranging from 97.7 to 100. Multilocus sequence typing (MLST) identified 10 distinct sequence types (STs), with ST155 representing the overwhelming majority (n = 907, 95.8%), reflecting the global epidemic predominance of ST155 among S. London populations. Global Distribution of S. London Globally, S. London isolates were collected from multiple regions, with the high prevalence observed in North America (n = 636, 67.2%), Asia (n = 203, 21.5%) and Europe (n = 92, 9.7%). The United States accounted for the largest proportion (n = 597, 63.1%), followed by China (n = 197, 20.8%) and the United Kingdom (n = 92, 9.7%). Minor were isolated from Mexico (n = 27, 2.9%), Canada (n = 12, 1.3%), Australia (n = 8, 0.8%), Viet Nam (n = 4, 0.4%), and Ireland (n = 1, 0.1%), while another eight isolates remained unknown (Figure 1A, Table S1). The overall distribution pattern indicated that North America, East Asia, and Western Europe constituted the primary endemic regions. Temporally, the collection period spanned from 1984 to 2024, covering more than four decades and reflecting the long-term persistence and continuous global surveillance of this serovar. Sequencing efforts increased markedly around 2014, with 765 isolates (80.9%) collected during the most recent decade (2014–2024). Two prominent peaks in isolation numbers were observed in 2017 and 2022 (Figure 1B, Table S1). The present study contributed 137 isolates from national surveillance (collected between 2017 and 2023), representing 14.5% of the global S. London genome collection. Isolation sources were highly diverse, encompassing four core categories: human clinical (n = 236, 24.9%), food (n = 471, 49.8%), environment (n = 27, 2.8%), and animal (n = 202, 21.4%), alongside unknown sources (n = 10, 1.1%) (Figure 1C). Clinical specimens included feces (n = 127, 13.4%), blood (n = 9, 1.0%), urine (n = 7, 0.7%), and unspecified clinical samples (n = 93, 9.8%). Food samples primarily comprised pork (n = 382, 40.4%), followed by chicken (n = 40, 4.2%), beef (n = 40, 4.2%), aquatic products (n = 3, 0.3%), duck meat (n = 1, 0.1%), and other food (n = 5, 0.5%). Environmental samples were derived from living/residential environments (n = 17, 1.8%) and breeding/production environments (n = 4, 0.4%), while animal sources were predominantly swine (n = 198, 20.9%). These findings indicate that S. London possesses a broad host niche. Population Structure of S. London Preliminary cgMLST based minimum spanning tree (MST) topology exhibited clear genetic clusters that correlated closely with geographic origins among the S. London isolates (Figure S2). Isolates from North America (United States), Asia (China), and Europe (United Kingdom) served as primary reservoirs. The 597 United States isolates represented the dominant lineage, constituting the backbone of the major clades, whereas isolates originating from China (n = 197) and the United Kingdom (n = 92) constituted relatively independent subgroups. We next investigated the delineation of the population structure of S. London. Following exclusion of 12 outlier isolates based on cgMLST results, phylogenomic reconstruction of 934 S. London genomes delineated four distinct clades (C1–C4) and eight sub-clades (C1.1, C2.1, C2.2, C3.1, C3.2, C4.1, C4.2, C4.3) (Figure 2A). The stability of the inferred population clustering, as verified by Bootstrap, is presented in Figure S3. Importantly, the 137 newly sequenced isolates from China exclusively clustered within C1.1, constituting a unique Asian lineage. The continental distribution of S. London revealed a dual pattern of global dispersion and regional endemism across the eight sub-clades (Figure 2B). Sub-clade C1.1 was endemic to Asia, whereas C2.2, C4.2, and C4.3 were concentrated in North America (>80% of sub-clade isolates). While isolates from Oceania, Mexico, and Viet Nam were phylogenetically restricted and sparsely distributed, consistent with localized epidemics. In marked contrast, C3.1 exhibited a cosmopolitan distribution (present in Asia, Europe, North America and Oceania) and multiple host categories (human, food, environment, animal), consistent with a generalist lifestyle and potent transboundary spread capacity. Notably, ecological niche partitioning was observed among the sub-clades (Figure 2C, 2D). The predominance of patient-derived isolates (primarily fecal, with minor involvement of blood and urine) among C1.1, C3.1, and C4.1 underscores the clinical significance of these sub-clades, indicating efficient gastrointestinal colonization and potential for fecal-oral transmission. In contrast, C2.2 and C3.2 constituted the dominant lineages among foodborne isolates, serving as core vectors for foodborne transmission. These sub-clades were primarily linked to common meat products including pork, chicken, and beef, with occasional detection in aquatic products and duck meat. And animal-derived isolates were highly enriched in C4.2 and C4.3, predominantly corresponding to livestock such as swine and bovine. The strong association of C2.2 with both pork products and swine, coupled with its overlap with breeding/production environments (Figure 2D), indicates a potential "farm-to-fork" transmission trajectory. Environmental isolates were rare, primarily from human living conditions, and dispersed across multiple sub-clades (C3.1, C4.1, C2.1), indicating their role as intermediary reservoirs. Evolutionary Characteristics of Sub-lineages in S. London Genomic architecture analysis revealed that genome sizes ranged from 4.5 to 5.5 Mbp across sub-clades (Figure 3A). Sub-clade C3.1 exhibited a broader distribution range and higher median genome size. In contrast, C2.2, C4.2, and C4.3 displayed relatively uniform and slightly reduced genome sizes, reflecting genome reduction trends associated with niche specialization. Significant differences were observed among sub-clades in the frequencies of six mutagenesis types (C>T/G>A, C>G/G>C, C>A/G>T, A>T/T>A, A>C/T>G, A>G/T>C) (Figure 3B). The sub-clade specificity of transition-to-transversion (Ti/Tv) ratios likely reflect differential selective pressures or variations in DNA repair system efficiency 39 . For instance, elevated frequencies of C>T mutations in C2.2 and C4.2 may be associated with reactive oxygen species (ROS) stress or adaptive evolution to specific host environments (e.g., food chain niches). Mantel tests revealed sub-clade C3.1 exhibited a significant positive correlation between genetic and geographic distances (positive slope), conforming to an Isolation by Distance (IBD) model and supporting the hypothesis of intercontinental spread via stepwise migration as a global clone (Figure 3C). Conversely, C1.1 and C2.1 displayed negative correlations, suggesting genetic homogenization resulting from recent clonal expansion or long-distance dispersal, consistent with sporadic endemicity in Asia. In contrast, C4.1–C4.3 reflected long-term endemic circulation and frequent gene flow within North America and Europe. Virulence Gene Repertoire of S. London Core virulence genes , including adhesion factors ( csg family), long polar fimbriae ( lpfA ), type III secretion system 1 (T3SS-1; invF ), T3SS-2 ( sspH ), type I fimbriae ( fimH ), and immune modulation genes ( ssaB , sse family), were highly conserved across all sub-clades, underpinning the fundamental enteropathogenic capacity of S. London (Figure 3D). Sub-clade-specific virulence determinants were predominantly enriched in the two clinically relevant sub-clades, C1.1 and C4.1. Specifically, C1.1 harbored the heat-stable enterotoxin ( astA ), the immune evasion-associated regulator ( grvA ), and superoxide dismutase ( sodCI ), potentially augmenting intestinal colonization and pathogenicity. Also, C4.1 was distinguished by a signature virulence marker, the adhesive fimbriae ( fae family), likely contributing to human gut colonization 40 . Significant differences in virulence gene profiles were observed between human and food/environmental isolates (χ²=82.1, OR (95%CI) =5.72 [3.83-11.37], P < 0.001). Antimicrobial Resistance Landscape of S. London Antimicrobial resistance (AMR) gene profiling revealed marked sub-clade stratification in S. London against ten antibiotic classes, including aminoglycosides, β-lactams, quinolones, fosfomycins, macrolides, trimethoprim, sulfonamides, tetracyclines, efflux pump-associated agents, and others (Figure 3E). Overall, 938 (99.2%) isolates harbored at least one resistance gene, with multidrug resistance (MDR) detected in 235 (24.8%) of strains. High rates of resistance genes were observed against aminoglycosides (99.2%), sulfonamides (24.0%), β-lactams (22.6%), quinolones (20.2%), macrolides (13.4%), and tetracyclines (8.6%). The mphA gene was highly enriched in sub-clade C1.1 (indicated by dark red arrows) (Figure 3E), directly associated with azithromycin resistance in these clinically relevant clades. Meanwhile, C1.1 harbored abundant resistance genes against aminoglycosides, β-lactams, fluoroquinolones, macrolides, and sulfonamides (upper red dashed box) (Figure 3E, 4A, 4B). Similarly, C3.1 and C4.1 carried resistance genes against aminoglycosides, β-lactams, and tetracyclines (lower red dashed box) (Figure 3E), likely mediated by specific efflux pump genes (e.g., oqxA , oqxB , cmlA6 ). In contrast, food-related lineages (C2.2 and C3.2) were enriched for aac (6')-Iaa , tetA , and tetD , reflecting selection pressures from aminoglycosides and tetracyclines in the food chain (Figure 4C). The Asian sub-clade (C1.1) exhibited high resistance rates to macrolides, sulfonamides, aminoglycosides, β-lactams, and quinolones (ranging from 80% to 100%), whereas North American (mainly the United States) and European (mainly the United Kingdom) lineages were predominantly resistant to tetracyclines, aminoglycosides, β-lactams, and sulfonamides (Figure 4B). The MDR rate among Chinese isolates (156/197, 79.2%) was significantly higher than that observed in Mexican (9/27, 33.3%), United Kingdom (11/92, 12.0%), and the United States (39/597, 6.5%) isolates. Although all isolates from Viet Nam exhibited MDR (4/4, 100%), the limited sample size warrants continued surveillance. Collectively, these findings suggest that S. London sub-clades have evolved specialized virulence-resistance co-evolutionary strategies adapted to their specific ecological niches and geographic dissemination patterns. Azithromycin Resistance Mechanisms Importantly, the azithromycin resistance rate among S. London isolates in this study was 50.5% (69/137), with MIC values ranging from 32 to >256 μg/mL. The corresponding mphA gene detection rate was 53.3% (73/137), showing high concordance with phenotypic resistance. This resistance rate exceeded that reported for other Salmonella serovar Derby and Typhimurium 14,15 . Among all 946 genomes, 125 (13.2%) were mphA -positive. Sankey diagram analysis revealed that mphA -positive isolates exhibited significant dual characteristics of sub-clade enrichment (predominantly in C1.1) and geographic clustering (primarily China) (Figure 4D). Those isolates were most prevalent among clinical patient samples (55.2%, 69/125), followed by food (43.2%, 54/125) and animal sources (1.6%, 2/125). They were significantly more common in human feces (46.4%, 58/125) and pork samples (36.0%, 45/125) than in other sources (<4.0%, <5/125) ( P < 0.001) (Figure 4D). The high positivity rates in clinical settings (patient feces) and food products (pork) suggest that mphA -positive clones may have undergone active local transmission and adaptive evolution within China. MDR cassette-Mediated Azithromycin Resistance Transmission The mphA gene does not exist in isolation but is embedded within six distinct multidrug resistance (MDR) cassettes, forming the complex core elements mediating high-risk MDR (Figure 4E). In addition to mphA , these cassettes harbored tandem arrays of resistance genes conferring resistance to aminoglycosides ( aadA , aac(6')-Ib , aac(3)-IIa , aph(3'')-Ib ), β-lactams ( TEM , CTX-M ), quinolones ( qnrB ), sulfonamides ( sul ), and tetracyclines ( tetR ), alongside mercuric resistance operons. Third-generation sequencing of 13 complete genomes subsequently revealed that these MDR cassettes have formed a super-resistance island within the borne by IncFIB(K) plasmids (detected in 1 1 strains, 84.6 %), rather than being integrated into the chromosome. Concomitantly, these cassettes are flanked by mobile genetic elements (MGEs), including transposases, transposons (e.g., Tn 621 family), integrons ( IntI1 ), and insertion sequences ( IS1 ), which facilitate horizontal gene transfer between different strains and plasmids, providing the molecular basis for the rapid cross-regional and cross-host dissemination of mphA . Analysis of host and source flow patterns (Figure 4D) reveals a clear "animal-food-patient" transmission chain, with cross-associations observed among isolates from patient, food, and animal sources in the United Kingdom, Canada, Australia, and the United States, suggesting that mphA -positive clones may have initiated global spread. This cassette architecture confers rapid horizontal transferability, resulting not only in azithromycin resistance but also in an MDR phenotype characterized by combined resistance to macrolides and multiple additional antibiotic classes. Discussion Through large-scale whole-genome sequencing, we systematically delineate the global phylogeographic architecture and population genomic features of S. London , providing unprecedented resolution into the evolutionary dynamics of this emerging foodborne pathogen. Our analysis of 946 globally distributed genomes, spanning four decades (1984–2024) and encompassing major endemic regions across North America, Asia, and Europe, reveals a striking pattern of ST155 clonal dominance (95.8%, 907/946), suggesting ST155 possesses enhanced environmental adaptability and competitive fitness within diverse ecological niches. This epidemiological pattern mirrors the global dissemination of S Kentucky ST198 19 , which similarly achieved pandemic spread through a single dominant clone, underscoring how specific Salmonella sequence types can achieve transcontinental establishment through anthropogenic selective pressures 41 . The One Health paradigm 42 , recognizing the inextricable linkages between human, animal, and environmental health, provides an essential framework for interpreting the complex transmission ecology of S. London . Phylogenomic reconstruction resolved four principal clades (C1–C4) and eight sub-clades exhibiting divergent epidemiological strategies. While some demonstrate strict host and geographic fidelity (specialist lineages), others display cosmopolitan distributions across continents and reservoirs (generalist lineages) (Figure 2A, 2B). The food chain, particularly pork production systems, constitutes the primary conduit for dissemination, with elevated frequencies of clinical isolates in specific sub-clades (C1.1, C3.1, C4.1) suggesting substantial human-to-human transmission potential. Remarkably, sub-clade C1.1 represents a China-specific lineage comprising nearly all Chinese isolates, forming a phylogenetically distinct Asian clade likely shaped by regional livestock trade networks and localized supply chain dynamics. In contrast, Clade C3 exhibits the most extensive global dissemination, spanning Asia, Europe, North America, and Oceania, consistent with a generalist lifestyle facilitated by broad host permissivity and enhanced transmissibility. Genomic interrogation reveals distinct evolutionary trajectories among these sub-clades. C3.1 exhibited significantly elevated genome size variability and larger median genome dimensions compared to the streamlined genomes of C2.2, C4.2, and C4.3, suggesting acquisition of accessory genetic elements through horizontal gene transfer (HGT) 17 . Mantel testing demonstrates that C3.1 conforms to an isolation-by-distance model of neutral microevolution, consistent with stepwise intercontinental migration via continuous transmission chains rather than long-distance dispersal events. This phylogeographic signature, combined with its predominance in clinical specimens, supports the hypothesis that C3.1 represents a global clone with enhanced pathogenic potential, analogous to internationally disseminated Typhimurium monophasic variants 43 . The antimicrobial resistance landscape in S. London presents a sobering therapeutic challenge. With 99.2% (938/946) of isolates harboring resistance determinants and 24.8% (235/946) exhibiting multidrug resistance (MDR), the prevalence of resistance substantially exceeded the ~10% MDR rate reported by the NARMS for NTS 14 . The elevated rates of sulfonamide (24.0%), β-lactam (22.6%), and quinolone (20.2%) resistance, reflected intense selection pressure exerted by prophylactic and growth-promoting antibiotic use in livestock production systems 44 . The ubiquitous carriage of the aac(6')-Iaa gene (aminoglycoside resistance, 99.2%) reflects its status as a chromosomal housekeeping gene intrinsic to Salmonella rather than a horizontally acquired resistance determinant 45,46 . Remarkably, Chinese isolates exhibit an alarmingly high MDR rate of 79.2% (156/197) compared to Mexico (33.3%), the United Kingdom (12.0%), and the United States (6.5%), likely indicating differential regulatory enforcement and agricultural antibiotic stewardship practices. As the world's largest producer and consumer of antimicrobial agents, China's intensive farming sector appears to have driven the emergence of hyper-resistant lineages through sustained evolutionary selection 47 . Strikingly, distinct sub-clades exhibit specialized virulence-resistance co-evolutionary strategies indicative of ecological niche partitioning. Clinical-associated sub-clades (C1.1) were enriched for enterotoxins ( astA ), immune evasion determinants ( grvA ), and oxidative stress resistance genes ( sodCI ), facilitating enhanced intestinal colonization and invasive potential. Also, C1.1 represented a clonal complex harboring mphA -MDR composite cassettes. Conversely, food-chain-associated lineages (C2.2, C3.2) predominantly harbor resistance cassettes conferring aminoglycoside and tetracycline resistance ( aac(6')-Iaa , tetA , tetD ), reflecting the selective milieu of agricultural production environments. The strong association of C2.2 with porcine sources and breeding facilities suggests a farm-to-fork transmission trajectory 48 , wherein livestock serve as reservoirs for MDR strains that subsequently contaminate the food supply. The azithromycin resistance crisis in S. London warrants particular clinical concern. Among our 137 newly sequenced Chinese isolates, we document a phenotypic resistance rate of 50.5% (69/137) and mph A gene carriage in 53.3% (73/137). The mph A gene was embedded within six distinct MDR cassettes forming super-resistance islands 49 , physically linked to determinants conferring resistance to aminoglycosides ( aadA , aac(6')-Ib ), β-lactams ( TEM , CTX-M ), quinolones ( qnrB ), sulfonamides ( sul ), and tetracyclines ( tetR ). These cassettes are mobilized by transposases (Tn 621 family), integrons ( IntI1 ), and insertion sequences ( IS1 ) within IncFIB(K) plasmids, providing the molecular machinery for rapid horizontal dissemination. The convergent enrichment of these cassettes in C1.1 suggests this lineage has undergone intense antibiotic selection in Chinese agricultural and clinical environments, establishing it as a high-risk epidemic clone requiring urgent surveillance. From clinical and public health perspectives, the high prevalence of azithromycin resistance in S. London , particularly within the C1.1, threatened to severely compromise the therapeutic armamentarium for invasive salmonellosis. With fluoroquinolones and third-generation cephalosporins already compromised by widespread resistance, the emergence of macrolide resistance eliminates one of the last remaining first-line options for severe infections. The co-localization of resistance determinants on conjugative plasmids and transposable elements suggests these MDR clones possess high epidemic potential, capable of rapid transnational dissemination through food trade networks. Viewed through the One Health lens, the S. London resistance crisis exemplifies the anthropogenic selection of antimicrobial resistance at the human-animal-environment interface. Our data revealed a clear transmission nexus spanning livestock reservoirs, food products, and clinical infections, underscoring the futility of intervention strategies targeting single sectors. Effective mitigation necessitates stringent antimicrobial stewardship in agricultural production 5 0 , rigorous withdrawal period enforcement, and the establishment of genomic surveillance sentinel sites to monitor the global dissemination of high-risk clones such as mph A-positive C1.1. Only through integrated, transdisciplinary approaches can we hope to contain the emergence of pan-resistant Salmonella lineages capable of undermining decades of therapeutic progress. Declarations Data availability The datasets of newly sequenced S. London isolates analyzed in the current study are available in the GenBank repository in the BioProject PRJNA1440902. 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Global clonal spread of mcr-3-carrying MDR ST34 Salmonella enterica serotype Typhimurium and monophasic 1,4,[5],12:i:- variants from clinical isolates. The Journal of antimicrobial chemotherapy 75 , 1756-1765 (2020). Wang, Y. , et al. Changes in colistin resistance and mcr-1 abundance in Escherichia coli of animal and human origins following the ban of colistin-positive additives in China: an epidemiological comparative study. The Lancet. Infectious diseases 20 , 1161-1171 (2020). Magnet, S., Courvalin, P. & Lambert, T. Activation of the cryptic aac(6')-Iy aminoglycoside resistance gene of Salmonella by a chromosomal deletion generating a transcriptional fusion. Journal of bacteriology 181 , 6650-6655 (1999). Salipante, S.J. & Hall, B.G. Determining the limits of the evolutionary potential of an antibiotic resistance gene. Molecular biology and evolution 20 , 653-659 (2003). Zhu, Y.G. , et al. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proceedings of the National Academy of Sciences of the United States of America 110 , 3435-3440 (2013). Hald, T., Vose, D., Wegener, H.C. & Koupeev, T. A Bayesian approach to quantify the contribution of animal-food sources to human salmonellosis. Risk analysis : an official publication of the Society for Risk Analysis 24 , 255-269 (2004). Zhao, X. , et al. Characterization of integrons and antimicrobial resistance in Salmonella from broilers in Shandong, China. Poultry science 99 , 7046-7054 (2020). Ho, C.S. , et al. Antimicrobial resistance: a concise update. The Lancet. Microbe 6 , 100947 (2025). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryFigureandTable.docx Extended Data Fig. 1, Extended Data Fig. 2, Extended Data Fig. 3, Extended Data Fig. 1, Extended Data Fig. 2 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-9203063","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":611379194,"identity":"bd056315-c0ae-4ef2-924e-bb8e893abaa5","order_by":0,"name":"Zhenzhou Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYBACAwh1AIh5gLgCxEggScsZkrUwthGhxVwi+dnDL3/uyJnznz34mHfeHXv+9uQHDD8qtjHwz27AqsVyRpq5sQzPM2PLhnPJxrzbnjFLnHlmwNhz5jaDxJ0D2B12I8FMWkLicOKGgz1m0rzbDrMZSOQwMDO23WYwkMDuQoMb6d+kJQwO1284zAPUMucwDxFacswkPyQcTjA4BtLScFiCsJYzb8qkGQ4cNtxwhsfYcM6xwwYgvxwE+oVH4gYOLcfTt0n++HNY3uD8GcMHb2oOg0Ls4YMfFbfl+Gdg1wICzDzoIgcYIDGLEzD+wCc7CkbBKBgFowAA26FiIvo41MYAAAAASUVORK5CYII=","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":true,"prefix":"","firstName":"Zhenzhou","middleName":"","lastName":"Huang","suffix":""},{"id":611379195,"identity":"f4ef983f-027c-4435-94f9-f40f267bd57b","order_by":1,"name":"Zhibei Zheng","email":"","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":false,"prefix":"","firstName":"Zhibei","middleName":"","lastName":"Zheng","suffix":""},{"id":611379196,"identity":"f6ff4893-cbb8-42c1-b378-c59f3164c74b","order_by":2,"name":"Hua Yu","email":"","orcid":"","institution":"Microbiology Laboratory, Hangzhou Center for Disease Control and Prevention, Hangzhou, Zhejiang Province","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Yu","suffix":""},{"id":611379197,"identity":"e3b8d458-c5db-4dea-978a-0b2bab631156","order_by":3,"name":"Wei Zheng","email":"","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zheng","suffix":""},{"id":611379198,"identity":"388341eb-1c41-40c2-ba43-3882865417e0","order_by":4,"name":"Xiuqin Lou","email":"","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":false,"prefix":"","firstName":"Xiuqin","middleName":"","lastName":"Lou","suffix":""},{"id":611379199,"identity":"a6c5c61b-8e85-4667-a766-4db393da88c7","order_by":5,"name":"Pan Zhao","email":"","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":false,"prefix":"","firstName":"Pan","middleName":"","lastName":"Zhao","suffix":""},{"id":611379200,"identity":"18d4720a-6231-41c5-858d-7e70bd4e3e60","order_by":6,"name":"Lingyi Zeng","email":"","orcid":"","institution":"Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution)","correspondingAuthor":false,"prefix":"","firstName":"Lingyi","middleName":"","lastName":"Zeng","suffix":""},{"id":611379201,"identity":"b2501ce4-309f-4b16-9819-7e945b307858","order_by":7,"name":"Shuojia Gu","email":"","orcid":"","institution":"Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Shuojia","middleName":"","lastName":"Gu","suffix":""},{"id":611379202,"identity":"160d571e-3e3a-4cf0-bc63-804cbd330d9e","order_by":8,"name":"Jun Li","email":"","orcid":"","institution":"Hangzhou Centre for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-03-23 16:41:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9203063/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9203063/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105564622,"identity":"6b75119a-cd2b-426f-8492-3c7feb29c2e3","added_by":"auto","created_at":"2026-03-27 12:50:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1332291,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal Distribution of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSalmonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e London genome dataset collected in this study.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e The geographic distribution of \u003cem\u003eS. \u003c/em\u003eLondon isolates in various countries or regions. Colors ranging from white to dark blue indicate a gradual increase in the number of isolates.\u003cstrong\u003e (B) \u003c/strong\u003eNumber of isolates per year collected from the national surveillance and public databases. NA indicates the data is unavailable. \u003cstrong\u003e(C)\u003c/strong\u003e Distribution of isolation by four major categories: patient, food, environment, and animal.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/e51f9e569d1fc0613b266868.png"},{"id":105348908,"identity":"4f9c9a6e-e5a0-4645-9fde-cfa59e124f2f","added_by":"auto","created_at":"2026-03-25 05:21:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1068789,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenomic structure and epidemiological characteristics of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eLondon. (A)\u003c/strong\u003e Maximum likelihood phylogenetic tree of 934 isolates based on 6,103 core-genome single nucleotide polymorphisms (cgSNPs). Four major clades (C1–C4) and eight sub-clades (C1.1; C2.1, C2.2; C3.1, C3.2; C4.1, C4.2, C4.3) were identified using fastBAPs by a hierarchical Bayesian clustering analysis. Metadata including inferred origin, sequence type (ST), and isolation host were labelled in columns 3-5. \u003cstrong\u003e(B)\u003c/strong\u003e Geographic distribution of isolates across the eight sub-clades, stratified by continent. \u003cstrong\u003e(C)\u003c/strong\u003eProportional distribution of isolation sources (animal, environment, food, and patient) within each sub-clade. \u003cstrong\u003e(D)\u003c/strong\u003e Number of isolates across detailed source categories.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/baa2378a2dbfdb60d551354c.png"},{"id":105348909,"identity":"aabe236f-986e-4a2e-af81-5e64a55f1a2e","added_by":"auto","created_at":"2026-03-25 05:21:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1608528,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenomic divergence, virulence repertoire, and antimicrobial resistance profiles among the eight \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eLondon\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e sub-clades.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Violin plots comparing genome sizes across sub-clades. \u003cstrong\u003e(B)\u003c/strong\u003eComparison of the ratios of six mutagenesis types among sub-clades. \u003cstrong\u003e(C)\u003c/strong\u003e Mantel test results indicating correlations between genetic distance and geographic distance within each sub-clade. \u003cstrong\u003e(D)\u003c/strong\u003e Distribution of virulence genes mapped onto the \u003cem\u003eS. London\u003c/em\u003ephylogenetic tree. Virulence genes shown from left to right include: \u003cem\u003eastA\u003c/em\u003e, \u003cem\u003ecdtB\u003c/em\u003e, \u003cem\u003ecsg\u003c/em\u003e family, \u003cem\u003eentA\u003c/em\u003e, \u003cem\u003efae\u003c/em\u003e family, \u003cem\u003efimH\u003c/em\u003e, \u003cem\u003egrvA\u003c/em\u003e, \u003cem\u003einvF\u003c/em\u003e, \u003cem\u003elpfA\u003c/em\u003e, \u003cem\u003emgtC\u003c/em\u003e, T3SS-1, T3SS-2, \u003cem\u003esodCI\u003c/em\u003e, and \u003cem\u003esspH\u003c/em\u003e. \u003cstrong\u003e(E)\u003c/strong\u003e Antimicrobial resistance (AMR) gene profiles. Red arrows indicate the positions of macrolide (azithromycin) resistance genes. Dashed boxes highlight two antimicrobial resistance gene-enriched regions. AMI, aminoglycoside; β-LA, β-lactam; QUI, quinolone; FOS, fosfomycin; MAC, macrolide; TRI, trimethoprim; SUL, sulfonamide; TET, tetracycline; EFP, efflux pump; OTH, other.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/ea76cf4c3f92cbf91b5add1d.png"},{"id":105564623,"identity":"147c14b0-c694-48de-a803-65ffb438ccd9","added_by":"auto","created_at":"2026-03-27 12:50:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":807781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of azithromycin resistance in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSalmonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e London.\u003c/strong\u003e \u003cstrong\u003e(A) \u003c/strong\u003eDistribution of the top six antimicrobial resistance classes across sub-clades, \u003cstrong\u003e(B)\u003c/strong\u003e inferred geographical regions, \u003cstrong\u003e(C) \u003c/strong\u003eisolation hosts. \u003cstrong\u003e(D)\u003c/strong\u003e Sankey diagram tracking the epidemiological flow of 125 \u003cem\u003emphA\u003c/em\u003e-positive isolates across sub-clades, geographical origins, isolation hosts, and specific sources. \u003cstrong\u003e(E)\u003c/strong\u003e Genetic organization of the six multidrug resistance cassettes harboring \u003cem\u003emphA\u003c/em\u003e. Arrows are colored according to distinct antimicrobial resistance functions.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/275d98ecf762c7d0a9cb6a06.png"},{"id":106724288,"identity":"b0680b20-ce24-40af-9273-1885d35f2f25","added_by":"auto","created_at":"2026-04-12 18:27:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5588875,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/981b25ee-f496-477f-8313-630907911a58.pdf"},{"id":105565182,"identity":"9f87f7ea-3dae-4736-b170-6d5121bf028f","added_by":"auto","created_at":"2026-03-27 12:52:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4844819,"visible":true,"origin":"","legend":"Extended Data Fig. 1, Extended Data Fig. 2, Extended Data Fig. 3, Extended Data Fig. 1, Extended Data Fig. 2","description":"","filename":"SupplementaryFigureandTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-9203063/v1/f0f56824315525f8c783e9c5.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Global diversity and Azithromycin resistance of Salmonella enterica serovar London: a genomic epidemiology study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNon-typhoidal \u003cem\u003eSalmonella\u003c/em\u003e (NTS) represents a preeminent etiologic agent of acute gastroenteritis and constitutes a paradigmatic zoonotic pathogen of global public health significance. Responsible for an estimated 138 million human infections and 57,000 fatalities annually, NTS ranks as the fourth leading cause of diarrheal mortality worldwide\u003csup\u003e1\u003c/sup\u003e. Transmission occurs predominantly via the fecal-oral route, with consumption of contaminated animal-derived products, particularly pork and poultry eggs\u003csup\u003e2\u003c/sup\u003e. The global trade networks and the modern food supply chains have catalyzed the emergence of NTS as a trans-boundary threat\u003csup\u003e3\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSalmonella\u003c/em\u003e \u003cem\u003eenterica\u003c/em\u003e serovar London (\u003cem\u003eS.\u003c/em\u003e London) (antigenic formula 3,10:l,v:1,6)\u003csup\u003e4\u003c/sup\u003e exemplifies a generalist serovar capable of colonizing diverse hosts including humans, swine, and avian species. While \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Typhimurium and \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Enteritidis have garnered substantial research attention due to their association with invasive non-typhoidal salmonellosis (iNTS) and epidemic potential in sub-Saharan Africa\u003csup\u003e5\u003c/sup\u003e, \u003cem\u003eS.\u0026nbsp;London\u003c/em\u003e remains comparatively understudied, despite its documented implication in invasive disease outbreaks and considerable clinical burden\u003csup\u003e6\u003c/sup\u003e. Epidemiological investigations have documented a marked upsurge in the prevalence of \u003cem\u003eS.\u0026nbsp;London\u003c/em\u003e within porcine production systems and pork products. In the United Kingdom, \u003cem\u003eS.\u0026nbsp;London\u003c/em\u003e accounts for 2.6% of swine-derived \u003cem\u003eSalmonella\u003c/em\u003e isolates\u003csup\u003e7\u003c/sup\u003e. Whereas positive rate of \u003cem\u003eS.\u0026nbsp;London\u003c/em\u003e from pork and chicken sausages was 20.8% detected in France\u003csup\u003e8\u003c/sup\u003e, establishing it as a co-dominant serovar alongside \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Typhimurium and \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Derby. Similarly, through a municipal market surveillance in Guangzhou, China, \u003cem\u003eS.\u0026nbsp;London\u003c/em\u003e was identified in 15.3% of pork-associated isolates\u003csup\u003e9\u003c/sup\u003e, underscoring its emergence as a predominant foodborne hazard.\u003c/p\u003e\n\u003cp\u003eFluoroquinolones and third-generation cephalosporins have historically constituted the cornerstone of antimicrobial therapy for iNTS infections\u003csup\u003e10\u003c/sup\u003e. However, the rapid dissemination of resistance determinants against these agents has precipitated a therapeutic crisis, compelling the adoption of azithromycin\u003csup\u003e11\u003c/sup\u003e, a macrolide antibiotic, as the primary alternative for managing severe iNTS and complicated gastroenteritis\u003csup\u003e12,13\u003c/sup\u003e. Alarmingly, global surveillance indicates escalating azithromycin resistance among NTS isolates. Data from the United States National Antimicrobial Resistance Monitoring System (NARMS) revealed that resistance prevalence increased from \u0026lt;0.5% in 2018 to 1.6\u0026ndash;1.8% during 2020\u0026ndash;2023\u003csup\u003e14\u003c/sup\u003e. In China, multicenter studies have documented azithromycin resistance rates of 3.08% among NTS isolates\u003csup\u003e15\u003c/sup\u003e, while regional surveillance in Zhejiang Province (2016\u0026ndash;2021) reported a striking 32.1% resistance rate among \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e London and \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Kentucky isolates from clinical and food sources\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe molecular architecture of azithromycin resistance in NTS encompasses phosphotransferase-mediated inactivation, 23S rRNA methylation by methyltransferases, ribosomal protein modifications, and efflux pump overexpression\u003csup\u003e11\u003c/sup\u003e. Among these mechanisms, the phosphotransferase encoded by the \u003cem\u003emph\u003c/em\u003eA gene predominates and has demonstrated capacity for rapid plasmid-mediated horizontal dissemination\u003csup\u003e17\u003c/sup\u003e. The global emergence of \u003cem\u003emph\u003c/em\u003eA-harboring MDR \u003cem\u003eSalmonella\u003c/em\u003e has been reported across the Middle East\u003csup\u003e18\u003c/sup\u003e, Europe\u003csup\u003e19,20\u003c/sup\u003e, and Southeast Asia\u003csup\u003e17,21\u003c/sup\u003e. Octavia et al. recently reported a clinical isolate of \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e London harboring both \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eNDM-1\u003c/sub\u003e and \u003cem\u003emph\u003c/em\u003eA in Singapore\u003csup\u003e22\u003c/sup\u003e, exemplifying the propensity for acquiring and transmitting high-risk resistance determinants.\u003c/p\u003e\n\u003cp\u003eDespite these concerning epidemiological trends, a comprehensive genomic investigation elucidating the evolutionary dynamics and transmission networks of \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e London remains conspicuously absent. Herein, we systematically assemble the largest scale of \u003cem\u003eS\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e London genome dataset to date. Our findings provide critical insights into the global population structure, azithromycin-resistant landscape within this clinically significant serovar, thereby informing targeted surveillance and evidence-based strategies of this emerging pathogen.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eIsolate Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring 2017\u0026ndash;2023, 918 \u003cem\u003eSalmonella\u003c/em\u003e isolates were collected from 16 sentinel hospitals in Hangzhou, Zhejiang Province, China, through the National Surveillance for Foodborne Diseases and Chinese Pathogen Identification Net. Common\u0026nbsp;serovars included \u003cem\u003eS\u003c/em\u003e Typhimurium (4,5,12:i:1,2), \u003cem\u003eS\u003c/em\u003e Enteritidis (9,12:g,m:-) and monophasic Typhimurium (I 4,[5],12:i:-), but \u003cem\u003eS.\u003c/em\u003e London (3,10:l,v:1,6) represented the fourth most prevalent (n = 137). Despite its lower prevalence relative to I 4,[5],12:i:- (14.9% versus 24.9%), \u003cem\u003eS.\u003c/em\u003e London exhibited a significantly elevated \u003cem\u003emphA\u003c/em\u003e-positive rate (45.9% versus 3.1%; 15-fold higher), surpassing the overall surveillance average of 11.11% (102/918). Thus, \u003cem\u003eS.\u003c/em\u003e London accounted for the majority of azithromycin-resistant isolates in our collection.\u003c/p\u003e\n\u003cp\u003eAlso, a corpus of \u0026gt;1,050,000 \u003cem\u003eSalmonella\u003c/em\u003e genomes was retrieved from the GenBank and EnteroBase repositories (accessed December 1, 2025). Subsequent \u003cem\u003ein silico\u003c/em\u003e serotyping was analyzed by two methods, SeqSero2 v1.3.1 (https://github.com/denglab/SeqSero2)\u003csup\u003e23\u003c/sup\u003e and SISTR v1.1.1 (\u003cem\u003eSalmonella in silico\u003c/em\u003e typing resource, https://lfz.corefacility.ca/sistr-app/)\u003csup\u003e24\u003c/sup\u003e, and finally identified 809 isolates exhibiting the antigenic determinants of 3,10:l,v:1,6.\u003c/p\u003e\n\u003cp\u003eA total of 946 \u003cem\u003eS.\u003c/em\u003e London isolates were analyzed in this study, including 809 public isolates and 137 newly sequenced strains (Table S1). Isolation sources included human clinical samples (n=236), food (n=471), environmental samples (n=27), and animal (n=202).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBacterial Culture and Identification\u003c/p\u003e\n\u003cp\u003eIsolates were cultured on \u003cem\u003eSalmonella\u003c/em\u003e-\u003cem\u003eShigella\u003c/em\u003e (SS) agar at 37\u0026deg;C for 18\u0026ndash;24 hours. Species confirmation was validated by both VITEK\u0026reg;2 Compact system (bioM\u0026eacute;rieux, France) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS; Bruker, Germany). Serotyping was performed using slide agglutination with specific antisera (Statens Serum Institut, Copenhagen, Denmark) according to the Kauffmann-White scheme\u003csup\u003e25\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAntimicrobial Susceptibility Testing\u003c/p\u003e\n\u003cp\u003eAntimicrobial susceptibility testing was performed using broth microdilution panels (\u003cem\u003eEnterobacteriaceae\u0026nbsp;\u003c/em\u003esusceptibility kits; Shandong Xinke, China) to determine the minimum inhibitory concentrations (MICs) of 14 antimicrobial agents. The panel comprised ampicillin (2\u0026ndash;64 \u0026mu;g/mL), ampicillin/sulbactam (2/1\u0026ndash;64/32 \u0026mu;g/mL), cefotaxime (0.25\u0026ndash;8 \u0026mu;g/mL), ceftazidime (0.5\u0026ndash;16 \u0026mu;g/mL), meropenem (0.06\u0026ndash;4 \u0026mu;g/mL), nalidixic acid (2\u0026ndash;64 \u0026mu;g/mL), ciprofloxacin (0.03\u0026ndash;32 \u0026mu;g/mL), azithromycin (2\u0026ndash;64 \u0026mu;g/mL), streptomycin (4\u0026ndash;32 \u0026mu;g/mL), amikacin (4\u0026ndash;128 \u0026mu;g/mL), tetracycline (1\u0026ndash;32 \u0026mu;g/mL), chloramphenicol (2\u0026ndash;64 \u0026mu;g/mL), trimethoprim-sulfamethoxazole (0.25/4.75\u0026ndash;8/152 \u0026mu;g/mL), colistin (polymyxin E; 0.5\u0026ndash;16 \u0026mu;g/mL). Resistance breakpoints were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines (2024 edition)\u003csup\u003e26\u003c/sup\u003e. For streptomycin, which lacks CLSI-established breakpoints, interpretive criteria were adopted from the United States National Antimicrobial Resistance Monitoring System (NARMS)\u003csup\u003e27\u003c/sup\u003e. Isolates resistant to three or more antibiotic classes were classified as MDR\u003csup\u003e28\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWhole-Genome Sequencing\u003c/p\u003e\n\u003cp\u003eOur 137 isolates were subjected to whole-genome sequencing. Genomic DNA was extracted using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) and quantified by Qubit 4.0 (Thermo Fisher Scientific, Waltham, MA, USA). Libraries were constructed using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) and sequenced on the Illumina NextSeq 2000 platform with the scheme of 150-bp paired-end reads. Thirteen \u003cem\u003eS.\u003c/em\u003e London isolates were sequenced on a GridION (Oxford Nanopore Technologies, Oxford, UK). The mean coverage depth across all isolates was 130\u0026times;. Raw reads were trimmed with Trimmomatic v0.36\u003csup\u003e29\u003c/sup\u003e and assembled \u003cem\u003ede novo\u003c/em\u003e using SPAdes v3.15.5\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCore-genome multilocus sequence typing (cgMLST) was performed employing a curated schema of 3,002 core genes to establish high-resolution genotypic relationships\u003csup\u003e31\u003c/sup\u003e. For phylogenomic reconstruction, core-genome single nucleotide polymorphisms (cgSNPs) were identified by mapping quality-filtered reads against a \u003cem\u003eS.\u003c/em\u003e London reference genome (accession No. GCA_018338335.1) using Snippy v4.6.0 (https://github.com/tseemann/snippy). Gubbins v2.4.1\u003csup\u003e32\u003c/sup\u003e was used to remove recombinant regions and spurious variants. Population structure was elucidated using fastBAPS v1.0.6 hierarchical Bayesian clustering\u003csup\u003e33\u003c/sup\u003e. Maximum-likelihood phylogenetic trees were subsequently inferred using IQ-TREE v2.2.0 by 1,000 bootstrap replicates\u003csup\u003e34\u003c/sup\u003e, and visualized using ggtree R package\u003csup\u003e35\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunctional genomic surveys of virulence determinants and antimicrobial resistance (AMR) were searched against the Virulence Factor Database (VFDB 2024 release)\u003csup\u003e36\u003c/sup\u003e and the Comprehensive Antibiotic Resistance Database (CARD v3.2.9)\u003csup\u003e37\u003c/sup\u003e, respectively. Identification of plasmid replicons was performed using PlasmidFinder v2.1\u003csup\u003e38\u003c/sup\u003e, thereby illuminating potential vectors for horizontal \u003cem\u003emphA\u003c/em\u003e gene transfer.\u003c/p\u003e\n\u003cp\u003eStatistical Analysis\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS Statistics v21.0 (IBM Corp., Armonk, NY, USA) and R v4.2.0. Categorical variables were presented as absolute counts and relative frequencies. Comparisons of proportions between groups were conducted using Pearson\u0026rsquo;s \u0026chi;\u0026sup2; test or two-tailed Fisher\u0026rsquo;s exact test, where appropriate, followed by Benjamini-Hochberg correction for multiple testing. Distribution disparities across sub-clades were assessed using the Kruskal\u0026ndash;Wallis test.\u003c/p\u003e\n\u003cp\u003eEthics Statement\u003c/p\u003e\n\u003cp\u003eAll human isolates were obtained from routine clinical diagnostics, with ethical approval from Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution) Ethics Committee. Food and environmental isolates were collected as part of national surveillance programs, with permission from relevant authorities.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eGenomic Dataset of \u003cem\u003eS.\u003c/em\u003e London\u003c/p\u003e\n\u003cp\u003eThis study assembled the largest \u003cem\u003eS.\u003c/em\u003e London genome dataset to date, comprising 946 globally distributed isolates. We newly sequenced 137 surveillance isolates and integrated 809 publicly available genomes from GenBank and EnteroBase database. ANI analysis of all 946 genomes yielded values ranging from 97.7 to 100. Multilocus sequence typing (MLST) identified 10 distinct sequence types (STs), with ST155 representing the overwhelming majority (n = 907, 95.8%), reflecting the global epidemic predominance of ST155 among \u003cem\u003eS.\u003c/em\u003e London populations.\u003c/p\u003e\n\u003cp\u003eGlobal Distribution of \u003cem\u003eS.\u003c/em\u003e London\u003c/p\u003e\n\u003cp\u003eGlobally, \u003cem\u003eS.\u003c/em\u003e London isolates were collected from multiple regions, with the high prevalence observed in North America (n = 636, 67.2%), Asia (n = 203, 21.5%) and Europe (n = 92, 9.7%). The United States accounted for the largest proportion (n = 597, 63.1%), followed by China (n = 197, 20.8%) and the United Kingdom (n = 92, 9.7%). Minor were isolated from Mexico (n = 27, 2.9%), Canada (n = 12, 1.3%), Australia (n = 8, 0.8%), Viet Nam (n = 4, 0.4%), and Ireland (n = 1, 0.1%), while another eight isolates remained unknown (Figure 1A, Table S1). The overall distribution pattern indicated that North America, East Asia, and Western Europe constituted the primary endemic regions.\u003c/p\u003e\n\u003cp\u003eTemporally, the collection period spanned from 1984 to 2024, covering more than four decades and reflecting the long-term persistence and continuous global surveillance of this serovar. Sequencing efforts increased markedly around 2014, with 765 isolates (80.9%) collected during the most recent decade (2014\u0026ndash;2024). Two prominent peaks in isolation numbers were observed in 2017 and 2022 (Figure 1B, Table S1). The present study contributed 137 isolates from national surveillance (collected between 2017 and 2023), representing 14.5% of the global \u003cem\u003eS.\u003c/em\u003e London genome collection.\u003c/p\u003e\n\u003cp\u003eIsolation sources were highly diverse, encompassing four core categories: human clinical (n = 236, 24.9%), food (n = 471, 49.8%), environment (n = 27, 2.8%), and animal (n = 202, 21.4%), alongside unknown sources (n = 10, 1.1%) (Figure 1C). Clinical specimens included feces (n = 127, 13.4%), blood (n = 9, 1.0%), urine (n = 7, 0.7%), and unspecified clinical samples (n = 93, 9.8%). Food samples primarily comprised pork (n = 382, 40.4%), followed by chicken (n = 40, 4.2%), beef (n = 40, 4.2%), aquatic products (n = 3, 0.3%), duck meat (n = 1, 0.1%), and other food (n = 5, 0.5%). Environmental samples were derived from living/residential environments (n = 17, 1.8%) and breeding/production environments (n = 4, 0.4%), while animal sources were predominantly swine (n = 198, 20.9%). These findings indicate that \u003cem\u003eS.\u003c/em\u003e London possesses a broad host niche.\u003c/p\u003e\n\u003cp\u003ePopulation Structure of \u003cem\u003eS.\u0026nbsp;\u003c/em\u003eLondon\u003c/p\u003e\n\u003cp\u003ePreliminary cgMLST based minimum spanning tree (MST) topology exhibited clear genetic clusters that correlated closely with geographic origins among the \u003cem\u003eS.\u0026nbsp;\u003c/em\u003eLondon isolates (Figure S2). Isolates from North America (United States), Asia (China), and Europe (United Kingdom) served as primary reservoirs. The 597 United States isolates represented the dominant lineage, constituting the backbone of the major clades, whereas isolates originating from China (n = 197) and the United Kingdom (n = 92) constituted relatively independent subgroups.\u003c/p\u003e\n\u003cp\u003eWe next investigated the delineation of the population structure of \u003cem\u003eS.\u0026nbsp;\u003c/em\u003eLondon. Following exclusion of 12 outlier isolates based on cgMLST results, phylogenomic reconstruction of 934 \u003cem\u003eS.\u003c/em\u003e London genomes delineated four distinct clades (C1\u0026ndash;C4) and eight sub-clades (C1.1, C2.1, C2.2, C3.1, C3.2, C4.1, C4.2, C4.3) (Figure 2A). The stability of the inferred population clustering, as verified by Bootstrap, is presented in Figure S3. Importantly, the 137 newly sequenced isolates from China exclusively clustered within C1.1, constituting a unique Asian lineage.\u003c/p\u003e\n\u003cp\u003eThe continental distribution of \u003cem\u003eS.\u003c/em\u003e London revealed a dual pattern of global dispersion and regional endemism across the eight sub-clades (Figure 2B). Sub-clade C1.1 was endemic to Asia, whereas C2.2, C4.2, and C4.3 were concentrated in North America (\u0026gt;80% of sub-clade isolates). While isolates from Oceania, Mexico, and Viet Nam were phylogenetically restricted and sparsely distributed, consistent with localized epidemics. In marked contrast, C3.1 exhibited a cosmopolitan distribution (present in Asia, Europe, North America and Oceania) and multiple host categories (human, food, environment, animal), consistent with a generalist lifestyle and potent transboundary spread capacity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNotably, ecological niche partitioning was observed among the sub-clades (Figure 2C, 2D). The predominance of patient-derived isolates (primarily fecal, with minor involvement of blood and urine) among C1.1, C3.1, and C4.1 underscores the clinical significance of these sub-clades, indicating efficient gastrointestinal colonization and potential for fecal-oral transmission. In contrast, C2.2 and C3.2 constituted the dominant lineages among foodborne isolates, serving as core vectors for foodborne transmission. These sub-clades were primarily linked to common meat products including pork, chicken, and beef, with occasional detection in aquatic products and duck meat. And animal-derived isolates were highly enriched in C4.2 and C4.3, predominantly corresponding to livestock such as swine and bovine. The strong association of C2.2 with both pork products and swine, coupled with its overlap with breeding/production environments (Figure 2D), indicates a potential \u0026quot;farm-to-fork\u0026quot; transmission trajectory. Environmental isolates were rare, primarily from human living conditions, and dispersed across multiple sub-clades (C3.1, C4.1, C2.1), indicating their role as intermediary reservoirs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvolutionary Characteristics of Sub-lineages in \u003cem\u003eS.\u003c/em\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eLondon\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic architecture analysis revealed that genome sizes ranged from 4.5 to 5.5 Mbp across sub-clades (Figure 3A). Sub-clade C3.1 exhibited a broader distribution range and higher median genome size. In contrast, C2.2, C4.2, and C4.3 displayed relatively uniform and slightly reduced genome sizes, reflecting genome reduction trends associated with niche specialization.\u003c/p\u003e\n\u003cp\u003eSignificant differences were observed among sub-clades in the frequencies of six mutagenesis types (C\u0026gt;T/G\u0026gt;A, C\u0026gt;G/G\u0026gt;C, C\u0026gt;A/G\u0026gt;T, A\u0026gt;T/T\u0026gt;A, A\u0026gt;C/T\u0026gt;G, A\u0026gt;G/T\u0026gt;C) (Figure 3B). The sub-clade specificity of transition-to-transversion (Ti/Tv) ratios likely reflect differential selective pressures or variations in DNA repair system efficiency\u003csup\u003e39\u003c/sup\u003e. For instance, elevated frequencies of C\u0026gt;T mutations in C2.2 and C4.2 may be associated with reactive oxygen species (ROS) stress or adaptive evolution to specific host environments (e.g., food chain niches).\u003c/p\u003e\n\u003cp\u003eMantel tests revealed sub-clade C3.1 exhibited a significant positive correlation between genetic and geographic distances (positive slope), conforming to an Isolation by Distance (IBD) model and supporting the hypothesis of intercontinental spread via stepwise migration as a global clone (Figure 3C). Conversely, C1.1 and C2.1 displayed negative correlations, suggesting genetic homogenization resulting from recent clonal expansion or long-distance dispersal, consistent with sporadic endemicity in Asia. In contrast, C4.1\u0026ndash;C4.3 reflected long-term endemic circulation and frequent gene flow within North America and Europe.\u003c/p\u003e\n\u003cp\u003eVirulence Gene Repertoire of \u003cem\u003eS.\u003c/em\u003e London\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCore virulence genes\u003c/strong\u003e, including adhesion factors (\u003cem\u003ecsg\u003c/em\u003e family), long polar fimbriae (\u003cem\u003elpfA\u003c/em\u003e), type III secretion system 1 (T3SS-1; \u003cem\u003einvF\u003c/em\u003e), T3SS-2 (\u003cem\u003esspH\u003c/em\u003e), type I fimbriae (\u003cem\u003efimH\u003c/em\u003e), and immune modulation genes (\u003cem\u003essaB\u003c/em\u003e, \u003cem\u003esse\u003c/em\u003e family), were highly conserved across all sub-clades, underpinning the fundamental enteropathogenic capacity of \u003cem\u003eS. London\u003c/em\u003e (Figure 3D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSub-clade-specific virulence determinants\u003c/strong\u003e were predominantly enriched in the two clinically relevant sub-clades, C1.1 and C4.1. Specifically, C1.1 harbored the heat-stable enterotoxin (\u003cem\u003eastA\u003c/em\u003e), the immune evasion-associated regulator (\u003cem\u003egrvA\u003c/em\u003e), and superoxide dismutase (\u003cem\u003esodCI\u003c/em\u003e), potentially augmenting intestinal colonization and pathogenicity. Also, C4.1 was distinguished by a signature virulence marker, the adhesive fimbriae (\u003cem\u003efae\u003c/em\u003e family), likely contributing to human gut colonization\u003csup\u003e40\u003c/sup\u003e.\u0026nbsp;Significant differences in virulence gene profiles were observed between human and food/environmental isolates (\u0026chi;\u0026sup2;=82.1, OR (95%CI) =5.72 [3.83-11.37],\u0026nbsp;\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntimicrobial Resistance Landscape of \u003cem\u003eS.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eLondon\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntimicrobial resistance (AMR) gene profiling revealed marked sub-clade stratification in \u003cem\u003eS. London\u003c/em\u003e against ten antibiotic classes, including aminoglycosides, \u0026beta;-lactams, quinolones, fosfomycins, macrolides, trimethoprim, sulfonamides, tetracyclines, efflux pump-associated agents, and others\u0026nbsp;(Figure 3E). Overall, 938 (99.2%) isolates\u0026nbsp;harbored\u0026nbsp;at least one resistance\u0026nbsp;gene, with multidrug resistance (MDR) detected in 235 (24.8%)\u0026nbsp;of strains. High rates\u0026nbsp;of\u0026nbsp;resistance\u0026nbsp;genes\u0026nbsp;were observed\u0026nbsp;against\u0026nbsp;aminoglycosides (99.2%), sulfonamides (24.0%), \u0026beta;-lactams (22.6%), quinolones (20.2%), macrolides (13.4%), and tetracyclines (8.6%). The \u003cem\u003emphA\u003c/em\u003e gene was highly enriched in sub-clade C1.1 (indicated by dark red arrows)\u0026nbsp;(Figure 3E), directly associated with azithromycin resistance in these clinically relevant\u0026nbsp;clades.\u003c/p\u003e\n\u003cp\u003eMeanwhile, C1.1 harbored abundant resistance genes against aminoglycosides, \u0026beta;-lactams, fluoroquinolones, macrolides, and sulfonamides (upper red dashed box)\u0026nbsp;(Figure 3E, 4A, 4B). Similarly, C3.1 and C4.1 carried resistance genes against aminoglycosides, \u0026beta;-lactams, and tetracyclines (lower red dashed box)\u0026nbsp;(Figure 3E), likely mediated by specific efflux pump genes (e.g., \u003cem\u003eoqxA\u003c/em\u003e, \u003cem\u003eoqxB\u003c/em\u003e, \u003cem\u003ecmlA6\u003c/em\u003e). In contrast, food-related lineages (C2.2 and C3.2) were enriched for\u0026nbsp;\u003cem\u003eaac\u003c/em\u003e\u003cem\u003e(6\u0026apos;)-Iaa\u003c/em\u003e, \u003cem\u003etetA\u003c/em\u003e, and \u003cem\u003etetD\u003c/em\u003e, reflecting selection pressures from aminoglycosides and tetracyclines in the food chain\u0026nbsp;(Figure 4C).\u003c/p\u003e\n\u003cp\u003eThe Asian sub-clade (C1.1) exhibited high resistance rates to macrolides, sulfonamides, aminoglycosides, \u0026beta;-lactams, and quinolones (ranging from 80% to 100%), whereas North American (mainly the United States) and European (mainly the United Kingdom) lineages were predominantly resistant to tetracyclines, aminoglycosides, \u0026beta;-lactams, and sulfonamides\u0026nbsp;(Figure 4B). The MDR rate among Chinese isolates (156/197, 79.2%) was significantly higher than that observed in Mexican (9/27, 33.3%), United Kingdom (11/92, 12.0%), and\u0026nbsp;the\u0026nbsp;United States (39/597, 6.5%) isolates. Although all isolates from Viet Nam exhibited MDR (4/4, 100%), the limited sample size warrants continued surveillance. Collectively, these findings suggest that \u003cem\u003eS. London\u003c/em\u003e sub-clades have evolved specialized virulence-resistance co-evolutionary strategies adapted to their specific ecological niches and geographic dissemination patterns.\u003c/p\u003e\n\u003cp\u003eAzithromycin Resistance Mechanisms\u003c/p\u003e\n\u003cp\u003eImportantly, the azithromycin resistance rate among \u003cem\u003eS.\u0026nbsp;\u003c/em\u003eLondon isolates in this study was 50.5% (69/137), with MIC values ranging from 32 to \u0026gt;256 \u0026mu;g/mL. The corresponding \u003cem\u003emphA\u003c/em\u003e gene detection rate was 53.3% (73/137), showing high concordance with phenotypic resistance. This resistance rate exceeded that reported for other \u003cem\u003eSalmonella\u003c/em\u003e serovar Derby and Typhimurium\u003csup\u003e14,15\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAmong all 946 genomes, 125 (13.2%) were \u003cem\u003emphA\u003c/em\u003e-positive. Sankey diagram analysis revealed that \u003cem\u003emphA\u003c/em\u003e-positive isolates exhibited significant dual characteristics of sub-clade enrichment (predominantly in C1.1) and geographic clustering (primarily China) (Figure 4D). Those isolates were most prevalent among clinical patient samples (55.2%, 69/125), followed by food (43.2%, 54/125) and animal sources (1.6%, 2/125). They were significantly more common in human feces (46.4%, 58/125) and pork samples (36.0%, 45/125) than in other sources (\u0026lt;4.0%, \u0026lt;5/125) (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) (Figure 4D). The high positivity rates in clinical settings (patient feces) and food products (pork) suggest that \u003cem\u003emphA\u003c/em\u003e-positive clones may have undergone active local transmission and adaptive evolution within China.\u003c/p\u003e\n\u003cp\u003eMDR cassette-Mediated Azithromycin Resistance Transmission\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003emphA\u003c/em\u003e gene does not exist in isolation but is embedded within six distinct multidrug resistance (MDR) cassettes, forming the complex core elements mediating high-risk MDR (Figure 4E). In addition to \u003cem\u003emphA\u003c/em\u003e, these cassettes harbored tandem arrays of resistance genes conferring resistance to aminoglycosides (\u003cem\u003eaadA\u003c/em\u003e, \u003cem\u003eaac(6\u0026apos;)-Ib\u003c/em\u003e, \u003cem\u003eaac(3)-IIa\u003c/em\u003e, \u003cem\u003eaph(3\u0026apos;\u0026apos;)-Ib\u003c/em\u003e), \u0026beta;-lactams (\u003cem\u003eTEM\u003c/em\u003e, \u003cem\u003eCTX-M\u003c/em\u003e), quinolones (\u003cem\u003eqnrB\u003c/em\u003e), sulfonamides (\u003cem\u003esul\u003c/em\u003e), and tetracyclines (\u003cem\u003etetR\u003c/em\u003e), alongside mercuric resistance operons. \u003cem\u003eThird-generation sequencing of 13 complete genomes subsequently revealed that\u0026nbsp;\u003c/em\u003ethese MDR cassettes have formed a super-resistance island within the \u003cem\u003eborne by IncFIB(K) plasmids\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e(detected in 1\u003c/em\u003e\u003cem\u003e1\u003c/em\u003e\u003cem\u003e\u0026nbsp;strains,\u0026nbsp;\u003c/em\u003e\u003cem\u003e84.6\u003c/em\u003e\u003cem\u003e%), rather than being integrated into the chromosome.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConcomitantly, these cassettes are flanked by mobile genetic elements (MGEs), including transposases, transposons (e.g., Tn\u003cem\u003e621\u003c/em\u003e family), integrons (\u003cem\u003eIntI1\u003c/em\u003e), and insertion sequences (\u003cem\u003eIS1\u003c/em\u003e), which facilitate horizontal gene transfer between different strains and plasmids, providing the molecular basis for the rapid cross-regional and cross-host dissemination of \u003cem\u003emphA\u003c/em\u003e. Analysis of host and source flow patterns (Figure 4D) reveals a clear \u0026quot;animal-food-patient\u0026quot; transmission chain, with cross-associations observed among isolates from patient, food, and animal sources in the United Kingdom, Canada, Australia, and the United States, suggesting that \u003cem\u003emphA\u003c/em\u003e-positive clones may have initiated global spread. This cassette architecture confers rapid horizontal transferability, resulting not only in azithromycin resistance but also in an MDR phenotype characterized by combined resistance to macrolides and multiple additional antibiotic classes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThrough large-scale whole-genome sequencing, we systematically delineate the global phylogeographic architecture and population genomic features of \u003cem\u003eS. London\u003c/em\u003e, providing unprecedented resolution into the evolutionary dynamics of this emerging foodborne pathogen. Our analysis of 946 globally distributed genomes, spanning four decades (1984\u0026ndash;2024) and encompassing major endemic regions across North America, Asia, and Europe, reveals a striking pattern of ST155 clonal dominance (95.8%, 907/946), suggesting ST155 possesses enhanced environmental adaptability and competitive fitness within diverse ecological niches. This epidemiological pattern mirrors the global dissemination of \u003cem\u003eS\u003c/em\u003e Kentucky ST198\u003csup\u003e19\u003c/sup\u003e, which similarly achieved pandemic spread through a single dominant clone, underscoring how specific \u003cem\u003eSalmonella\u003c/em\u003e sequence types can achieve transcontinental establishment through anthropogenic selective pressures\u003csup\u003e41\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003eOne Health\u003c/strong\u003e paradigm\u003csup\u003e42\u003c/sup\u003e, recognizing the inextricable linkages between human, animal, and environmental health, provides an essential framework for interpreting the complex transmission ecology of \u003cem\u003eS. London\u003c/em\u003e.\u0026nbsp;Phylogenomic reconstruction resolved four principal clades (C1\u0026ndash;C4) and eight sub-clades exhibiting divergent epidemiological strategies. While some demonstrate strict host and geographic fidelity (specialist lineages), others display cosmopolitan distributions across continents and reservoirs (generalist lineages)\u0026nbsp;(Figure 2A, 2B). The food chain, particularly\u0026nbsp;pork production systems, constitutes the primary conduit for dissemination, with elevated frequencies of clinical isolates in specific sub-clades (C1.1, C3.1, C4.1) suggesting substantial human-to-human transmission potential. Remarkably, sub-clade C1.1 represents a China-specific lineage comprising nearly all Chinese isolates, forming a phylogenetically distinct Asian clade likely shaped by regional livestock trade networks and localized supply chain dynamics. In contrast, Clade C3 exhibits the most extensive global dissemination, spanning Asia, Europe, North America, and Oceania, consistent with a \u003cstrong\u003egeneralist\u003c/strong\u003e lifestyle facilitated by broad host permissivity and enhanced transmissibility.\u003c/p\u003e\n\u003cp\u003eGenomic interrogation reveals distinct evolutionary trajectories among these sub-clades. C3.1 exhibited significantly elevated genome size variability and larger median genome dimensions compared to the streamlined genomes of C2.2, C4.2, and C4.3, suggesting acquisition of accessory genetic elements through horizontal gene transfer (HGT)\u003csup\u003e17\u003c/sup\u003e. Mantel testing demonstrates that C3.1 conforms to an \u003cstrong\u003eisolation-by-distance\u003c/strong\u003e model of neutral microevolution, consistent with stepwise intercontinental migration via continuous transmission chains rather than long-distance dispersal events. This phylogeographic signature, combined with its predominance in clinical specimens, supports the hypothesis that C3.1 represents a \u003cstrong\u003eglobal clone\u003c/strong\u003e with enhanced pathogenic potential, analogous to internationally disseminated Typhimurium monophasic variants\u003csup\u003e43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe antimicrobial resistance landscape in \u003cem\u003eS. London\u003c/em\u003e presents a sobering therapeutic challenge. With 99.2% (938/946) of isolates harboring resistance determinants and 24.8% (235/946) exhibiting multidrug resistance (MDR), the prevalence of resistance substantially exceeded the ~10% MDR rate reported by the NARMS for NTS\u003csup\u003e14\u003c/sup\u003e. The elevated rates of sulfonamide (24.0%), \u0026beta;-lactam (22.6%), and quinolone (20.2%) resistance, reflected intense selection pressure exerted by prophylactic and growth-promoting antibiotic use in livestock production systems\u003csup\u003e44\u003c/sup\u003e.\u0026nbsp;The ubiquitous carriage of the \u003cem\u003eaac(6\u0026apos;)-Iaa\u003c/em\u003e gene (aminoglycoside resistance, 99.2%) reflects its status as a chromosomal housekeeping gene intrinsic to \u003cem\u003eSalmonella\u003c/em\u003e rather than a horizontally acquired resistance determinant\u003csup\u003e45,46\u003c/sup\u003e.\u0026nbsp;Remarkably,\u0026nbsp;Chinese isolates exhibit an alarmingly high MDR rate of 79.2% (156/197) compared to Mexico (33.3%), the United Kingdom (12.0%), and the United States (6.5%), likely indicating differential regulatory enforcement and agricultural antibiotic stewardship practices. As the world\u0026apos;s largest producer and consumer of antimicrobial agents, China\u0026apos;s intensive farming sector appears to have driven the emergence of hyper-resistant lineages through sustained evolutionary selection\u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eStrikingly,\u0026nbsp;distinct sub-clades exhibit specialized virulence-resistance co-evolutionary strategies indicative of ecological niche partitioning. Clinical-associated sub-clades (C1.1) were enriched for enterotoxins (\u003cem\u003eastA\u003c/em\u003e), immune evasion determinants (\u003cem\u003egrvA\u003c/em\u003e), and oxidative stress resistance genes (\u003cem\u003esodCI\u003c/em\u003e), facilitating enhanced intestinal colonization and invasive potential.\u0026nbsp;Also, C1.1 represented a clonal complex harboring \u003cem\u003emphA\u003c/em\u003e-MDR composite cassettes.\u0026nbsp;Conversely, food-chain-associated lineages (C2.2, C3.2) predominantly harbor resistance cassettes conferring aminoglycoside and tetracycline resistance (\u003cem\u003eaac(6\u0026apos;)-Iaa\u003c/em\u003e, \u003cem\u003etetA\u003c/em\u003e, \u003cem\u003etetD\u003c/em\u003e), reflecting the selective milieu of agricultural production environments. The strong association of C2.2 with porcine sources and breeding facilities suggests a \u003cstrong\u003efarm-to-fork\u003c/strong\u003e transmission trajectory\u003csup\u003e48\u003c/sup\u003e, wherein livestock serve as reservoirs for MDR strains that subsequently contaminate the food supply.\u003c/p\u003e\n\u003cp\u003eThe azithromycin resistance crisis in \u003cem\u003eS. London\u003c/em\u003e warrants particular clinical concern. Among our 137 newly sequenced Chinese isolates, we document a phenotypic resistance rate of 50.5% (69/137) and \u003cem\u003emph\u003c/em\u003eA gene carriage in 53.3% (73/137). The \u003cem\u003emph\u003c/em\u003eA gene was embedded within six distinct MDR cassettes forming \u003cstrong\u003esuper-resistance islands\u003c/strong\u003e\u003csup\u003e49\u003c/sup\u003e, physically linked to determinants conferring resistance to aminoglycosides (\u003cem\u003eaadA\u003c/em\u003e, \u003cem\u003eaac(6\u0026apos;)-Ib\u003c/em\u003e), \u0026beta;-lactams (\u003cem\u003eTEM\u003c/em\u003e, \u003cem\u003eCTX-M\u003c/em\u003e), quinolones (\u003cem\u003eqnrB\u003c/em\u003e), sulfonamides (\u003cem\u003esul\u003c/em\u003e), and tetracyclines (\u003cem\u003etetR\u003c/em\u003e). These cassettes are mobilized by transposases (Tn\u003cem\u003e621\u003c/em\u003e family), integrons (\u003cem\u003eIntI1\u003c/em\u003e), and insertion sequences (\u003cem\u003eIS1\u003c/em\u003e)\u0026nbsp;within\u0026nbsp;IncFIB(K) plasmids,\u0026nbsp;providing the molecular machinery for rapid horizontal dissemination. The convergent enrichment of these cassettes in C1.1 suggests this lineage has undergone intense antibiotic selection in Chinese agricultural and clinical environments, establishing it as a high-risk epidemic clone requiring urgent surveillance.\u003c/p\u003e\n\u003cp\u003eFrom clinical and public health perspectives, the high prevalence of azithromycin resistance in \u003cem\u003eS. London\u003c/em\u003e, particularly within the C1.1, threatened to severely compromise the therapeutic armamentarium for invasive salmonellosis. With fluoroquinolones and third-generation cephalosporins already compromised by widespread resistance, the emergence of macrolide resistance eliminates one of the last remaining first-line options for severe infections. The co-localization of resistance determinants on conjugative plasmids and transposable elements suggests these MDR clones possess high epidemic potential, capable of rapid transnational dissemination through food trade networks.\u003c/p\u003e\n\u003cp\u003eViewed through the \u003cstrong\u003eOne Health\u003c/strong\u003e lens, the \u003cem\u003eS. London\u003c/em\u003e resistance crisis exemplifies the anthropogenic selection of antimicrobial resistance at the human-animal-environment interface. Our data revealed a clear transmission nexus spanning livestock reservoirs, food products, and clinical infections, underscoring the futility of intervention strategies targeting single sectors. Effective mitigation necessitates stringent antimicrobial stewardship in agricultural production\u003csup\u003e5\u003c/sup\u003e\u003csup\u003e0\u003c/sup\u003e, rigorous withdrawal period enforcement, and the establishment of genomic surveillance sentinel sites to monitor the global dissemination of high-risk clones such as \u003cem\u003emph\u003c/em\u003eA-positive C1.1. Only through integrated, transdisciplinary approaches can we hope to contain the emergence of pan-resistant \u003cem\u003eSalmonella\u003c/em\u003e lineages capable of undermining decades of therapeutic progress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets of newly sequenced \u003cem\u003eS.\u0026nbsp;\u003c/em\u003eLondon isolates analyzed in the current study are available in the GenBank repository in the BioProject PRJNA1440902.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExtended data is available for this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e(WHO), W.H.O. 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Microbe\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 100947 (2025).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Salmonella enterica serovar London, Global dissemination, Azithromycin resistance, mphA gene, Genomic epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-9203063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9203063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Non-typhoidal Salmonella enterica serovar London (S. London) represents an emerging zoonotic threat with escalating azithromycin resistance, yet its global population structure and evolutionary dynamics remain poorly characterized. Here we present a genomic epidemiology analysis of 946 global isolates from 1984–2024, revealing four major clades (C1–C4) and eight sub-clades, with distinct geographical distributions and host adaptations. Notably, sub-clade C1.1 was predominantly endemic to China, while C3.1 demonstrated cosmopolitan distribution. The C1.1 exhibited alarming azithromycin resistance (62.1%, 123/198) driven by mphA-harboring multidrug resistance cassettes located on IncFIB(K) plasmids. These super-resistance islands, mobilized by transposable elements, facilitate horizontal transmission across animal-food-human interfaces. Distinct sub-clades exhibited specialized virulence–resistance co-evolutionary strategies. Analysis revealed a farm-to-fork transmission trajectory, with pork production systems as the primary conduit for dissemination. Our findings highlight the urgent need for integrated One Health surveillance to contain the global dissemination of high-risk MDR clones and preserve last-resort antimicrobial therapies.","manuscriptTitle":"Global diversity and Azithromycin resistance of Salmonella enterica serovar London: a genomic epidemiology study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-25 05:21:28","doi":"10.21203/rs.3.rs-9203063/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":"20aad3f5-289f-4269-a67b-e3c775a6fa99","owner":[],"postedDate":"March 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65051189,"name":"Biological sciences/Microbiology/Bacteria/Infectious-disease epidemiology"},{"id":65051190,"name":"Biological sciences/Microbiology/Antimicrobials/Antimicrobial resistance"},{"id":65051191,"name":"Biological sciences/Microbiology/Bacteria/Bacterial genomics"}],"tags":[],"updatedAt":"2026-03-31T17:26:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-25 05:21:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9203063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9203063","identity":"rs-9203063","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}