Global population genomics of Salmonella enterica serotype Napoli, an emerging pathogen with an unusual epidemiologic pattern

Global population genomics of Salmonella enterica serotype Napoli, an emerging pathogen with an unusual epidemiologic pattern | 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 population genomics of Salmonella enterica serotype Napoli, an emerging pathogen with an unusual epidemiologic pattern Lise Frézal, Laura Villa, Guido Bloemberg, Laetitia Bonifait, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8608855/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 We characterised the population structure of Salmonella enterica serotype Napoli ( S. Napoli), an emerging European pathogen. We assembled a collection of 1,320 isolates obtained between 1945 and 2022 from diverse biological sources in Italy, Switzerland, France (regions of known endemicity) and a newly identified endemic area, Spain. Whole-genome analyses linked the rising incidence of S. Napoli to a monophyletic serotype from core genome multilocus typing (cgMLST) superlineage HC2000_1289. The S. Napoli population has considerable genetic diversity, strong spatial structuring, and a very low frequency of antimicrobial resistance determinants. Unlike successful non-typhoidal Salmonella serotypes, for which globalisation has had a homogenising effect, S. Napoli forms at least 15 distinct lineages isolated by geographic distance, each probably subject to local ecological adaptation. This comprehensive description of S. Napoli populations complemented by 12 representative complete genomes provides a valuable resource for future source attribution and surveillance of this serotype. Biological sciences/Evolution/Population genetics/Genetic variation Biological sciences/Microbiology/Bacteria/Bacterial genomics Biological sciences/Microbiology/Policy and public health in microbiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Salmonella enterica serotype Napoli (hereafter referred to as S. Napoli) was first isolated by Captain W.H. Ewing of the Section of Bacteriology, 15th Medical General Laboratory of the United States (US) Army stationed in Naples during the Italian campaign of World War II 1 . Between November 21st, 1943 and October 25th 1945, this laboratory identified 31 S. Napoli isolates from stool samples from Italian civilian food-handlers — all apparently healthy carriers — and then US soldiers, most of whom were suffering from gastroenteritis 1 , 2 . Since the mid-1990s, the number of human infections caused by S. Napoli has progressively increased in Europe 3 , 4 . Between 2000 and 2006, a 140% rise in the number of reported cases (from 122 to 283 cases) was observed in 18 European countries, with over 87% of these cases originating from three countries: France, Italy, and Switzerland. More recently, between 2020 and 2024, the countries of the European Economic Area (EEA) reported annual numbers of S. Napoli cases fluctuating between 359 and 457, with two countries, France and Italy (Switzerland being not an EEA member), accounting for 71.8% and 91.3% of the cases, respectively ( https://atlas.ecdc.europa.eu/public ). In France, Italy and Switzerland, animal health, environmental, and food production surveillance programmes have reported a similar upward trend 4 , with frequent isolations of S . Napoli from plant-based foods, poultry farming environments 4 , surface waters 4 – 6 , and wildlife, including lizards 7 , 8 , boars 9 , 10 and birds 11 . Within the last five years, the European Union (EU) Rapid Alert for Feed and Food (RASFF; https://food.ec.europa.eu/food-safety/rasff_en ) system has issued alerts concerning the presence of S . Napoli in rocket leaves from Italy (notification number 2024.8347), thyme from Italy (2022.3666) and oysters from France (2020.0435). Since the widely reported 1982 outbreak in England and Wales, which was linked to Italian-manufactured chocolate bars 12 – 14 , foodborne outbreaks of S . Napoli infection have remained rare and have often involved the consumption of plant products (essentially fresh herbs, rocket leaves or beetroot) produced in Italy or France 4 , 6 , 15 . The presence of S . Napoli in surface waters used for irrigation was identified as the most significant risk factor for food crop contamination 6 , 16 . Unlike most non-typhoidal Salmonella (NTS) infections, those caused by S . Napoli are predominantly sporadic and of unknown origin, affecting individuals at the extremes of the human age range — under the age of two years or over the age of 65 years — more frequently than is generally observed for the principal NTS infections 4 – 6 , 17 . Furthermore, the seasonal peaks of S . Napoli isolations from humans and the environment coincide, typically during the period from June to October, with case numbers falling to particularly low levels during cold months 3 , 4 , 6 . Pulsed-field gel electrophoresis (PFGE) analyses have identified genetic clusters containing both human and non-human isolates 4 , 6 , 15 . Collectively, this evidence indicates that S . Napoli may be transmitted to humans primarily through contact with the environment (e.g., consumption of contaminated greens irrigated with contaminated water; outdoor activities involving water 5 , 6 , 16 ) rather than via the consumption of commercially available animal products. S . Napoli can, therefore, reasonably be described as an emerging pathogen of environmental origin 4 – 6 , 15 , 17 , 18 . However, despite extensive research, the natural reservoirs of this serotype remain unidentified. For sporadic diseases, effective source attribution and surveillance depend heavily on both a clear description of the pathogen population structure and the availability of robust laboratory tools for linking cases. S. Napoli has been shown to be phylogenetically close to the Typhi and Paratyphi A serotypes within a clade — defined as section Typhi — in the S. enterica phylogeny, but different from these serotypes 19 , 20 . However, the global S . Napoli population is currently poorly characterised. Previous assessments of the genetic diversity of S . Napoli based on PFGE, multilocus sequence typing (MLST7), and/or whole-genome sequencing (WGS) revealed a high degree of genetic heterogeneity both within Italy and throughout the known endemic regions in Europe 4 , 6 , 15 , 17 . However, none of these studies was able to establish clear phylogenetic relationships between the isolates or provide a comprehensive phylogeographic description of the population. This gap in our knowledge obscures the links between human infection and potential sources of exposure, making source attribution for S. Napoli a major challenge. As a first step towards understanding the natural ecology of S . Napoli, we investigated the genetic diversity of S . Napoli populations in multiple countries, including Italy, Switzerland, and France — where this serotype has increasingly been reported over the last 35 years — and Spain, which we identify here, for the first time as a zone of endemicity for S. Napoli. Our findings emphasize the need for the collection of medium-to-long-term international data and genomic data to elucidate the relationships between sporadic autochthonous infections of both human and non-human origin. RESULTS Phylogenetic position of S . Napoli The phylogeny of S. enterica subsp. enterica established by Zhou and coworkers 19 (redrawn in Supplementary Fig. 1) demonstrated that S. Napoli belongs to a clade closely related to serotypes Typhi and Paratyphi A. Notably, this clade also contains isolates of two environmental serotypes, Veneziana and Mississippi (clade A for the latter 20 ), and all members of this clade belong to EnteroBase core genome MLST (cgMLST) hierarchical cluster HC2600_104. An analysis of all cgMLST HC2600_104 genomes in EnteroBase on April 2024 ( n = 3,991; workspace:110633), confirmed the monophyly of S . Napoli, as all isolates ( n = 2,145) of this serotype (identified with the in silico serotype prediction tool SISTR 21 and/or clustering within MLST eBurst group eBG60 (ref. 22 ), both approaches implemented in EnteroBase) grouped together exclusively in the HC2000_1289 superlineage (Fig. 1 A, Supplementary Data 1). Other S. enterica serotypes belonging to HC2600_104, such as Lomalinda, Veneziana, Mississippi (clade A), Blijdorp, Itami, and Woodinville, all identified by SISTR, were grouped in other HC2000 clusters (Fig. 1 A). Genetic diversity and structure of S . Napoli We studied the population structure of S . Napoli by assembling a set of 1,320 genomes (all present in EnteroBase) sampled between 1945 and 2022 in four European countries (France, Italy, Switzerland, and Spain) and originating from human and non-human sources (Fig. 2 , Supplementary Table 1, Supplementary Data 1). These 1,320 genomes included 1,145 generated in this study, 174 previously published genomes 17 , 18 , and one unpublished genome (isolate 142214) (Supplementary Fig. 2A). Conventional serotyping and/or in silico typing confirmed the antigenic formula ( 1 ,9,12:l,z13:e,n,x) for all these genomes (Supplementary Data 1). Our cgMLST analysis on all HC2600_104 genomes (see above) confirmed that our set of 1,320 genomes was, indeed, representative of the known global diversity of S . Napoli (Fig. 1 C). Salmonella serotype delineation is often based on cgMLST HC900 clusters (one HC900 cluster corresponds generally to one serotype) 23 . Intriguingly, we identified 12 HC900 clusters for S . Napoli in both the initial dataset of 2,145 genomes (Fig. 1 B) and the final dataset of 1,320 genomes (Fig. 3 A). The HC900 diversity detected for S . Napoli in these four neighbouring European countries was 2.5 times higher than that of serotype Mississippi clade A in Oceania and the US (Fig. 1 B; https://enterobase.warwick.ac.uk/ms_tree/125256 ). The 12 cgMLST HC900 clusters were subdivided into 31 HC400 and 55 HC200 clusters (Supplementary Fig. 2B, 2C). Phylogenetic analyses with both cgMLST (EnteroBase cgMLSTv2 scheme using NINJA neighbour-joining and HierCCv1; Fig. 3 B) and single-nucleotide variant (SNV)-based clustering (RAxML; Generalised time reversible Gamma — GTRGamma — model; 1,000 bootstrap replicates; Fig. 3 A) approaches subdivided the S . Napoli population into two clades (N1 and N2), which could be further subdivided into 15 lineages. Eleven of these lineages exactly matched the established cgMLST HC900 clusters, the exception being HC900_1543 (clade N2), which was differentiated into four distinct subclades by SNV-based phylogeny analysis: HC900_1543a, HC900_1543b, HC900_1543ab, and HC900_1543c. Lineage HC900_1543ab, consisting of only three isolates, was basal and ancestral to lineages HC900_1543a and HC900_1543b. Lineage HC900_1543c displayed the highest degree of genetic divergence. Before this study, only one complete genome of S . Napoli of good quality, 16-174478 (GenBank accession no. CP063140.1) was available 24 . This genome, from an extended-spectrum beta-lactamase (ESBL)-producing isolate collected in Italy, belonged to cluster HC900_1450. As a means of improving this and future genomic analyses of S . Napoli populations, we generated 12 additional complete genome sequences to obtain a set of 13 complete genomes representative of the major lineages (12 of the 15 phylogenetic lineages; Supplementary Data 1 and 2). Strong phylogeographic pattern of S . Napoli lineages Differential geographic partitioning of the seven most prominent S . Napoli lineages was observed across Italy, Switzerland, France, and Spain (Fig. 3 B), with Italy hosting five lineages. The HC900_20879 lineage predominated in northern/central Italy and Switzerland, whereas HC900_1450, HC900_7673 and HC900_107023 were prevalent in southern Italy. Interestingly, the HC900_1450 lineage, isolated principally from Campania and Lazio (central Italy), includes the historical first isolate described in Naples (Campania) in 1945 (ref. 1 ). The other lineages also had strongly regionalised distributions, with HC900_1543b highly prevalent across northern Italy, Switzerland (Ticino and Zürich Großregions ) and eastern France (Haut-Rhin and Alpes-Maritimes départements ); HC900_1543c was confined to Spain, mainly in the northern coast (Asturias and Cantabria comunidades autónomas ); and HC900_1543a was largely restricted to western France. For minor lineages, the limited sample sizes prevented robust spatial analysis, but metadata analysis indicated a tendency of HC900_107120 to be associated with Sicily (Supplementary Data 1). Furthermore, the observed geographic structure was not associated with the source of the isolate, as human and non-human isolates from the same lineage had similar distributions (Supplementary Fig. 3). We further analysed the spatial structuring of the major genetic cluster HC900_1543, transforming postcode centroids into Global Positioning System (GPS) co-ordinates (in mainland France, the 5,896 postcodes have a median area of about 11 km²; in Switzerland the 3,194 postcodes - PLZ4 - have a median area of 7–8 km²). Even at a finer phylogenetic scale, we observed clear and discrete geographic clustering with minimal overlap. The HC900_1543a lineage could be subdivided into distinct HC400 clusters: HC400_204873, geographically concentrated in north/north-western Switzerland and the neighbouring French region of Alsace, and HC400_140575, localised in south-western and central France (Supplementary Fig. 4). The widespread HC400_27729 cluster could be subdivided into three HC200 clusters, one of which (HC200_140623) was tightly concentrated around La Rochelle and the island of Ré (Supplementary Fig. 4). The other two clusters (HC200_27729 and HC200_27733) could themselves be subdivided into geographically clustered HC50 genetic clusters (Fig. 4 ). Finally, despite the limited GPS data available for Italian samples, we also observed a geographic clustering of HC900_1543b sublineages, with HC100_107035 localised in central Switzerland, HC50_137319 in Ticino, and HC20_140601 in Alsace/north and north-western Switzerland (Supplementary Fig. 5). Inefficacy of MSLT typing for identifying S . Napoli lineages MLST7 sequence types (STs) and eBurst Groups (eBG) are widely used to track Salmonella lineages, but the phylogenetic resolution of MLST7 was limited for S . Napoli. We found that eBG60 perfectly identified S . Napoli, but we observed 50 different STs with disorganised distributions across serotype S . Napoli HC900 clusters (Supplementary Fig. 6). In particular, the predominant ST (ST474) was observed in isolates from three different clusters, HC900_1543, HC900_107023, and HC900_1289. ST2019 occurred in two different clusters, HC900_7673 and HC900_63054, whereas a single cluster, HC900_7673 contained isolates from five different STs (ST2008, ST2019, ST2101, ST4936, ST7210) (Supplementary Fig. 6). However, we observed limited congruence between MLST7 STs and cgMLST clusters, with five specific associations: one with minor HC900 clusters (ST4354 and HC900_94001) and four with HC400 clusters (ST1853 and HC400_106990; ST4550 and HC400_107080; ST4277 and HC400_88024; and ST8183 and HC400_247522) (Supplementary Data 1). Low nucleotide diversity of the flagellin gene sequences of S. Napoli A unique one-to-one relationship between a serotype and a cgMLST HC2000 cluster (super-lineage) — as observed between S . Napoli and HC2000_1289 — is rather unusual for most NTS, for which relationships are generally observed between a serotype and an HC900 cluster. We investigated the maintenance of a similar antigenic formula ( 1 ,9,12:l,z23:e,n:x) ) across the 15 lineages of S . Napoli, by analysing the genetic polymorphism of the fliC (encoding H1 flagellin l,z13) and fljB (encoding H2 flagellin e,n,x) genes in our dataset. Full fliC l,z13 (1,503 bp) and fljB _e,n,x (1,506 bp) sequences could be retrieved for 1,294 and 1,229 isolates, respectively (Supplementary Table 2). An identical fliC allele, fliC 1, was found in 92.4% (1,196/1,294) of the S . Napoli isolates distributed across 11 lineages; two fljB alleles — fljB 1 and fljB 2 (differentiated by a single synonymous SNV) — were found in 86.6% (1,064/1,229) of the isolates, with fljB 2 distributed across 10 lineages. Despite the identification of 18 and 22 alleles for fliC and fljB genes, respectively, there was little nucleotide variation between these alleles, with a maximum of two SNVs resulting in two amino-acid changes for fliC (with fliC 1 as the reference) and a maximum of three SNVs resulting in a single amino-acid change for fljB (with fljB 1 as the reference). The presence of similar flagellin antigens in S . Napoli is, therefore, linked to a strong conservation of fliC and fljB nucleotide sequences across one HC2000 cluster and its 15 derived lineages. Antimicrobial, metal and biocide resistance gene content of S . Napoli populations Antimicrobial resistance (AMR) genes were rare in S . Napoli, occurring in only 2% (27/1,320) of the isolates (Supplementary Data 1). Transmission was horizontal (carried by a plasmid) for 22 of the 23 AMR genes, and vertically transmitted via chromosomal mutation for the remaining AMR gene ( gyrA _D87G in isolate UZH_N16-0214). Most AMR-positive isolates (16/27; 60%) harboured multiple plasmid-borne AMR genes (Supplementary Data 1). Notable resistance phenotypes included one carbapenemase-producing isolate ( bla OXA−48 in clinical isolate 201805020) and three ESBL-producing isolates ( bla CTX−M−1 in clinical isolates 16-174478 (ref. 24 ) and 201606260; bla CTX−M−15 in clinical isolate LC0541/17 (ref. 25 )). We screened for metal and biocide resistance gene repertoires with the BacMet database, which contains 753 experimentally validated resistance genes 26 . The screening of 1,191 S . Napoli genome assemblies (further included in the pan-genome analysis) identified 115 genes, 109 of which were present in at least 95% of the assemblies (Supplementary Data 3). This analysis defined a core metal‑/biocide‑resistome of 109 genes for S . Napoli, and an accessory resistome composed of six arsenic-resistant ( arsABCDRH ) genes detected in 3 to 9% of the isolates. For comparison, we screened 779 NCBI reference genomes for three additional S. enterica serotypes: Enteritidis ( n = 327), Typhimurium ( n = 289) and Typhi ( n = 165). The core resistomes of these serotypes contained 117 genes for Enteritidis, 116 genes for Typhimurium, and 103 genes for Typhi. The four serotypes had a subset of 102 genes in common. The ges and gol operons, conferring tolerance to gold (Au) and copper (Cu), were absent from both Napoli and Typhi; the mercury ( mer ), quaternary‑ammonium‑compound ( oqx ), copper ( pco ), silver ( sil ) and tellurium ( ter ) resistance operons were detected in 9–34% of the Typhimurium genomes, but in less than 0.5% of S . Napoli genomes. Finally, arsenic resistance ( ars ) genes, were detected in 25% of Typhimurium genomes but were absent from the Enteritidis and Typhi serotypes (Supplementary Data 4). Pan-genome composition across S . Napoli lineages Analyses of genome content were facilitated by our access to 13 complete genomes representative of S . Napoli diversity. The pan-genome analysis was performed on 1,191 genome assemblies of fewer than 200 contigs and included 13 of the 15 S . Napoli lineages (Supplementary Fig. 7; Supplementary Data 5), with HC900_1543a and HC900_1543b accounting for 53.6% and 26.5%, respectively, of these genomes. Despite the overrepresentation of the HC900_1543a and 1543b lineages in the dataset, our pan-genome analysis identified a closed pan-genome (Heap’s α = 1.0555 > 1) containing 10,739 genes, including 3,898 core genes (≥ 99% isolates), 146 soft core genes (95–99% isolates), 721 shell genes (15–95% isolates) and 6,120 cloud genes (< 15% isolates) (Supplementary Fig. 8A, B). We searched for enrichment in any gene functions (cluster of orthologous categories, COG) in either the core or accessory genome. The pan-genome analysis detected 10,739 coding DNA sequences (CDSs), 2,156 of which lacked eggNOG-mapper annotations (Supplementary Data 6). The functional enrichment analysis of the annotated 8,583 CDSs revealed that 78% of the 3,813 poorly characterised/uncharacterised genes belonged to the accessory genome (Fisher’s exact test, p < 0.0001). For the 4,770 genes with assigned functions, a strong enrichment in replication, recombination and repair (L) genes was observed in the accessory genome, together with genes involved in transcription (K) and intracellular trafficking, secretion and vesicular transport (U) (Supplementary Fig. 8C, D). By contrast, the core genome was enriched in seven functions — translation, ribosomal structure and biogenesis functions (J) — plus six metabolic categories — nucleotide transport (F); coenzyme transport (H); amino-acid transport (E); energy production and conversion (C); carbohydrate transport (G); and inorganic ion transport (P) (Supplementary Fig. 8C, D). Accessory gene content was itself structured by phylogeny. Pan-genome-based neighbour networks revealed a lineage-specific clustering of cgMLST HC900 clusters (excluding HC900_1543) or, for HC900_1543, of HC400 and HC200 clustering levels, indicating that pan-genome divergence increased with core genome phylogenetic distance (Supplementary Fig. 9A-C; Supplementary Data 5). The country of origin within genetic clusters and the isolation source had no effect on pan-genome clustering patterns (Supplementary Fig. 9D, E), consistent with the absence of source-associated phylogenetic clustering (Supplementary Fig. 3). Pathogenicity island and virulence factor analysis SPI-finder detected seven pathogenicity islands (SPI-1, -2, -3, -4, -5, -9, and − 12) in the 13 complete S . Napoli genomes and the SPI-13 island in 12 of these genomes. The SPI coverage analysis (including Illumina reads for 1,320 S . Napoli) confirmed the presence of these islands (complete SPI-1, -2, -4, -9, and − 12; partial SPI-3, -5, and − 13) and detected three additional islands (complete SPI-18; partial SPI-6, and − 11; very incomplete SPI-7) (Supplementary Figs. 10 and 11). Contrary to these initial database hits, we found that S . Napoli lacked the canonical 134 kb SPI-7 island of S. enterica serotype Typhi 27 — including, in particular, the locus for the production and export of Vi antigen and a sopE prophage — with observed kma hits matching solely the sopE gene and diverse prophage genes. The distribution of several SPIs displayed striking lineage specificity. Two of the five major SPI-3 components, mgtB and mgtC , were detected in all S . Napoli genomes; the other three were detected exclusively in clade N2: marT/cadC1 , rhuM , and misL (either complete 2853 bp or partial 663 bp) (Supplementary Fig. 11A). Furthermore, SPI-5 was complete in HC900_1543, or almost complete in other HC900 clusters, but insertions of transposases and prophages were repeatedly observed between tRNA-ser and pipA and, between sigE and sopB genes, especially in clade N1 (Supplementary Fig. 11B). The type VI secretion system (T6SS) encoded by SPI-6 was detected exclusively in the Spanish lineage (HC900_1543c) and one western French sublineage (HC200_27729). The other sublineages carried only incomplete versions (Supplementary Fig. 11C). The SPI-11 of S . Napoli was similar to that of the S. enterica serotype Typhi CT18 genome, with a conserved region from tRNA-Arg to cdtB , with or without the pltA , pltB , and sopF genes (Supplementary Fig. 11D). Finally, S . Napoli genomes carried an SPI-13 island (~ 35.7 kb in most genomes) significantly larger than that in the S. enterica serotype Typhimurium LT2 reference sequence (19.5 kb) (Supplementary Fig. 11E). A comparative analysis of virulence factors (VFDB 28 , 29 ) in the 13 complete genomes and the 1,191 pan-genomes revealed a uniform composition in terms of the genes of pathogenicity islands SPI-1 and SPI-2, which encode the type III secretion systems TTSS-1 and TTSS-2, respectively (Supplementary Data 7). Key determinants of magnesium uptake ( mgtB, mgtC ) and regulation ( phoP , phoQ ), and the macrophage-inducible gene mig-14 were also conserved. Seven of the TTSS-1 translocated effectors were encoded by all genomes, two ( sopE2 and sopE ) were present in more than 95% of the genomes, and four ( avrA, sopD2 , spvC , spvD ) absent from all genomes (Supplementary Data 7). The sopE gene is carried by an Edward-GF2 prophage of the Caudoviricetes phage family. Eight of the TTSS-2 effectors were widely detected ( pipB2 , pipB , sifA , sifB , spiC/ssaB , sseF , sseG , sseJ , sseK1 , sseL, sspH2; ≥94% pan-genomes), whereas three were detected in a more variable manner: gogB (12 genomes and 77% of the pan-genomes), sseI/srfH (exclusive to HC900_1450) and sseK2 (8 of 13 genomes and 23% of the pan-genomes) (Supplementary Data 7). An adhesion system analysis showed that six fimbrial operons were ubiquitous ( csg , fim , peg , sta , stf , sth ), 10 were undetected ( pef , sef , stb, stc, ste, sti , stj , stk , lpf , tcf ) and six varied in terms of their presence or completeness ( bcf operon complete in 8 genomes, 91% of the pan-genomes; near-complete std and sth operons in 13 genomes; safB/C/ D exclusive to HC900_1543c) (Supplementary Fig. 11C; Supplementary Data 7). The nonfimbrial adhesion determinants ratB , shdA , and sinH were conserved, whereas misL was restricted to HC900_1543b, HC900_1543c, HC900_20879 and HC400_140575 within clade N2. Finally, despite the absence of SPI-7, the S. enterica serotype Typhi Vi-encoding pathogenicity island, three other Typhi determinants were detected in the vicinity of SPI-11 in S . Napoli (Supplementary Fig. 11D; Supplementary Data 7): cdtB was present in all genomes, and pltA and/or pltB were found in six genomes (in 14% and 42% of the pan-genomes respectively). Recombining regions, CRISPR system and spacer diversity Recombining regions, CRISPR system and spacer diversity A Gubbins software analysis of 1,317 genomes aligned with the S . Napoli Nap72-2 genome (GenBank accession no. CP163475) identified three major recombining regions (Supplementary Fig. 12). The gene content of these regions was inspected within complete genomes: 13 S . Napoli and one S. enterica serotype Veneziana (the closest serotype to Napoli in Europe, hereafter referred to as S. Veneziana), 164K (GenBank accession no. CP063140) (Supplementary Data 1). Recombining region 1 (RR1: 30,549 bp) included part of the SPI-6 pathogenicity island ( TssD /sTM0276 to pagN ) and displayed a high level of SNV diversity in the HC900_1543b lineage. Recombining region 2 (RR2: 188,605 bp) contained the SPI-5 pathogenicity island, the csg (curli) operon, and the flg (flagellar) gene cluster and displayed marked SNV density in the HC900_1543a/b/c/a-b, HC900_20879 and HC900_1289 lineages. Recombining region 3 (RR3: 218,909 bp) contained the SPI-1 pathogenicity island and the CRISPR-Cas system components, including the associated spacers. A high level of SNV density was observed in RR3 in lineages HC900_1543b and HC900_20879. Subsequent phylogenetic analyses of RR2 and RR3, taking either the S . Napoli Nap72-2 or the S. Veneziana 164K genome as a reference, revealed hallmarks of genetic introgression (Supplementary Figs. 13 and 14). At RR2, S . Veneziana branched together with the S . Napoli clade N1 lineages. At RR3, S . Veneziana branched with two major lineages from Switzerland, northern Italy and eastern France (HC900_1543b and HC900_20879). Comparative analysis of the CRISPR-Cas encoding region revealed unexpected diversity across S . Napoli lineages. Most S . Napoli lineages harboured the CRISPR LT2-type structure 30 , either intact or with a partial deletion, but the HC900_1543b and HC900_20879 lineages harboured a deleted Ty2-type CRISPR structure 30 (Fig. 5 , Supplementary Table 3). In line with the introgression signal detected in RR3, spacer content divergence mirrored CRISPR-Cas structural partitioning: HC900_1543b and HC900_20879 had no spacer in common with other S . Napoli lineages but displayed 100% spacer identity to S . Veneziana (Supplementary Table 3). By contrast, S . Napoli genomes harbouring an LT2-type CRISPR structure had a maximum of 64% of spacers in common (29% of CR1; 100% of CR2; Supplementary Table 3) with other HC2600_104 members, and spacer content followed the phylogenetic structure (Fig. 5 ). DISCUSSION The heterogeneity of the S . Napoli population had already been described in Italy 15 , 17 and Europe 4 , but our whole-genome sequencing analysis of a representative set of isolates provides a clearer picture of the phylogeography of the Napoli serotype across its endemic zone, constituting a solid baseline for epidemiological investigations. The S . Napoli population can be split into two clades (N1 and N2), further divided into 15 lineages, seven of which are prominent. The S . Napoli population displayed a remarkable pattern of geographic segregation in Europe, evident from the 15 basal lineages down to the finest phylogenetic resolution. The sample studied here is the most comprehensive collection of S . Napoli ever assembled, from various sources and covering the entire known genetic diversity for this serotype. Nevertheless, it remains challenging to delineate the endemic zone of any micro-organism, including S . Napoli. In 2009, the Enter-net international surveillance network (an EU-funded dedicated surveillance network for enteric pathogens) showed that 87.5% of human S . Napoli infections occurred in Switzerland, Italy, and France, three countries in which the presence of S . Napoli in the environment had been previously documented 4 , 31 . Our work expands this endemic zone to include Spain, where the isolates form a newly identified distinct clade, phylogenetically different from those already detected in other endemic regions in Europe (France, Italy and Switzerland). However, we cannot rule out the possibility that S . Napoli has a greater genetic diversity or wider geographic distribution extending beyond the four countries identified to date. Indeed, our work is based on published findings, surveillance data from the European Centre for Disease Prevention and Control (ECDC), genomic data available from EnteroBase, and information obtained through contacts with numerous European reference laboratories for Salmonella . Nevertheless, the capacity for salmonellosis surveillance varies across the European continent, potentially masking both new lineages and unrecognised foci of infection. In the seminal paper for the cgMLST scheme 32 , Zhou and collaborators considered the cgMLST HC200 and HC100 clustering levels to correspond to a long-term endemic persistence of Salmonella clones. In the study reported here, access to location data (GPS co-ordinates of postcode centroids) for the sources of the French and Swiss isolates made it possible to refine the geographic distributions of the HC200 and HC100 clusters. Most of the isolates were obtained from cases of human infection, but the observed spatial distribution was consistent with long-term endemic persistence and limited migration between subpopulations. This finding provides direct evidence that different S . Napoli phylogenetic clades establish stable, local endemic populations. Furthermore, our phylogeographic analyses confirmed that S . Napoli lineages circulate locally between animals, humans, and the environment, consistent with an environmental origin (i.e., wildlife) of S . Napoli salmonellosis. These findings suggest that the natural niche of S. Napoli consists of many local and isolated patches. The local environment appears to be a key determinant of the transmission of this enteric pathogen to humans. In addition, despite the observed high level of genetic diversity, AMR determinants were found to be rare in S. Napoli and the ESBL or carbapenemase resistance traits did not seem to spread in the S. Napoli local population. The carbapenemase-producing isolate ( bla OXA−48 ) is noteworthy, as carbapenemase production has rarely been reported in Salmonella 33 . The presence of the bla OXA−48 resistance gene could be linked to the patient’s clinical history. The repertoire of metal-and-biocide tolerance genes consists of 109 core genes and only six accessory genes underlying arsenic tolerance. The S . Napoli core metal-and-biocide resistome is similar to those of serotypes Enteritidis, Typhimurium and Typhi, but S . Napoli does not harbour any of the other accessory resistome genes detected in Typhimurium or Typhi ( mer , oqx, pco , sil, ter ). Overall, resistance gene content is therefore consistent with an environmental origin of the S . Napoli population, relatively spared from the influence of the agrifood supply chain, with its antibiotic-, biocide-, or metal-enriched environments. Our comparative analysis revealed that pan-genome structure primarily mirrored phylogenetic clustering rather than the source from which the isolate was acquired. Thus, any detectable molecular signature of adaptation would be more likely to be related to the local ecosystem than the biological source of the isolate. The repertoire of pathogenicity islands and virulence factors — including fimbrial and non-fimbrial adhesins, toxins and secretion systems — provides an initial indication of the potential local adaptation of lineages and sublineages to their specific environmental niches. For instance, S . Napoli harbors six core pathogenicity islands (SPI-1, -2, -4, -9, -12, -18), five accessory pathogenicity islands (SPI-3, -5, -6, -11 and − 13), and 151 virulence factors (VFDB), 88% of which are core determinants. Only a few candidate genes for adaptation to the local environment were identified in our pan-genome analysis: the absence of the bcf operon encoding fimbrial adhesion determinants from the HC900_1450 and HC900_107023 lineages, the presence of SPI-6 and the saf operon in HC900_1543c, and the presence of sseI and absence of stdB and stbC in HC900_1450. The cgMLST hierarchical clustering analysis confirmed that S. Napoli was a monophyletic serotype belonging to section Typhi of subspecies S. enterica enterica clade A 17,19,20 . Surprisingly, S . Napoli was identified at superlineage cgMLST HC2000_1289 clustering level rather than the usual cgMLST HC900 clustering level for serotypes 34 , which is coherent with a vastly distributed environmental niche from which animal and human cases emerge sporadically, rather than localised farms or healthcare foci. Moreover, S. Napoli is closely related to two environmentally sourced serotypes also identified at superlineage clustering level: Veneziana (HC2000_12926), present in Spain, France, Italy ( https://atlas.ecdc.europa.eu/public/ ) and Switzerland 35 , and Mississippi (clade A; HC2000_4338). This last serotype is of increasing public health concern in the US, Australia and New Zealand 20 , 36 , 37 . The Mississippi and Napoli serotypes also have a number of epidemiological and genetic features in common, such as the scarcity of AMR determinants 38 , presence in non-urban environments and in wild fauna, and marked seasonality 39 associated with a pronounced phylogeographic pattern 20 , 37 . Furthermore, the population structure of S. Napoli observed in neighbouring European countries resembles that described for the Mississippi serotype in the southeastern US, and this strong phylogeographic profile may be a remnant of the natural ecology of Salmonella (i.e., that which prevailed before the era of agribusiness). In Europe, the geographic distributions of S. Napoli and S. Veneziana partly overlap, as demonstrated by the isolation of both serotypes from Italian wild boars 9 , 10 and from the intestinal contents of Italian lizards 7 , 8 (five S . Napoli isolates sequenced in the framework of this study were from these lizards). Consistent with this spatial overlap, our genomic analyses revealed multiple, independent horizontal gene transfer events for determinants of pathogenicity (SPI-1, SPI-5) and immunity (CRISPR system) between S . Napoli and S . Veneziana, suggesting that these European serotypes either currently occupy or have historically occupied overlapping ecological niches. Finally, the broadly used MLST7 scheme does not capture the diversity of the S . Napoli population. As illustrated by the paraphyly of ST474 within the Italian diversity of S . Napoli in a previous study 17 , our analysis confirmed that ST subdivisions coincide poorly with cgMLST HC900 or HC400 phylogenetic divisions. The use of STs to distinguish between S . Napoli lineages should therefore be strongly discouraged; instead, we recommend using the cgMLST scheme or establishing specific phylogenies including the 13 complete genomes representative of S . Napoli. In conclusion, source attribution for S . Napoli infections is essential for the development of effective prevention and control measures for this infection, which remains an emerging enigma, as first described by Fisher et al. 4 in 2009. Improving our understanding of the epidemiology of S . Napoli and its recent rise in Europe will require a One-Health approach. Case-control studies and substantial sampling of potential sources, such as the wildlife, in a defined geographic area with a high prevalence of the disease and well-characterised ecosystems are required to identify the risk factors associated with the disease and the nature of the bacterial reservoirs, respectively. In addition, the accumulation of international data over the medium and long term, and the acquisition of genomic data, will provide greater insight into the geographic distribution of this infection and the diversity and genetic evolution of the pathogen. By clarifying the population structure and phylogeographic characteristics of this transborder pathogen, and by providing analytical tools, this work constitutes a first step towards elucidating the relationships between sporadic indigenous infections of human origin and the environment. METHODS Ethics statement This study was based exclusively on bacterial isolates and associated metadata, including, in particular, 989 isolates of human origin obtained from national reference laboratories for Salmonella at the following institutions: Institut Pasteur ( n = 684, including one S. Veneziana), Instituto de Salud Carlos III ( n = 34), Istituto Superiore di Sanità of Rome ( n = 103), and University of Zurich ( n = 169). The Institut Pasteur isolates were collected and stored by the French National Reference Centre for Escherichia coli , Shigella and Salmonella (FNRC-ESS) with the approval of the French National Commission for Data Protection and Liberties (‘ Commission Nationale Informatique et Libertés (CNIL )’; approval number 1474659). The isolates from all the other institutions were acquired under the corresponding national mandates for laboratory-based surveillance of salmonellosis in line with local laws and regulations. Metadata anonymity was strictly maintained: data were limited to year/country/postcode of the laboratory performing the isolation (together with the postcode of the place of residence for the patient in 80% of cases) and international travel history, with no information allowing identification of the person included. As a result, neither informed consent nor approval from an ethics committee was required, given that this was not a study performed on human participants. Bacterial isolates and metadata We analysed 1,320 S . Napoli isolates from human ( n = 1,088), animal ( n = 60, including 28 mammals, 16 gastropods and 5 reptiles), food ( n = 25), environmental ( n = 139) and unknown ( n = 8) sources. These isolates were collected in France ( n = 771, including 2 from Monaco and 2 from travellers returning from Italy), Italy ( n = 319), Switzerland ( n = 181), and Spain ( n = 48) (Supplementary Data 1). These isolates were obtained by the FNRC-ESS, Institut Pasteur, Paris, France ( n = 699), Laboratorio de Referencia e Investigación en Enfermedades Bacterianas Transmitidas por Alimentos, Instituto de Salud Carlos III, Madrid, Spain ( n = 48), Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy ( n = 135), and National Reference Laboratory (NRL) for Enteropathogens and Listeria , Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Switzerland ( n = 181), French National Reference Laboratory (NRL) for Salmonella, Anses, Ploufragan, France ( n = 51), and Salmonella and Listeria Unit (SEL), Anses, Maisons-Alfort, France ( n = 31). We included two additional isolates: isolate 142214 from the UK Health Security Agency (UKHSA; ENA Biosample accession no SAMN04600129) as it was the only representative of cgMLST HC900_1289, and isolate 202208589 provided after the study period by the FNRC-ESS as a representative of the rare HC900_63054 cluster, for which we performed long-read sequencing (see the corresponding section). For each isolate, detailed metadata are provided in Supplementary Data 1, including isolation date, geographic origin (country, region, subregion, postcode), biological sample type, and travelling information, when available. All French isolates from humans were obtained via the national surveillance programme, which operates through a voluntary network of clinical laboratories located throughout France (mainland France and overseas regions) . Each isolate and the basic related metadata were sent to the FNRC-ESS. Short-read sequencing, analysis and de novo assemblies In total, 1,145 genome sequences of S . Napoli were generated in this study. Sequencing libraries were prepared with the Nextera XT DNA library preparation kit (Illumina, San Diego, CA, USA) and sequenced on the NextSeq 500 platform ( Illumina ) as 2x150 bp paired-end reads. Raw read quality was assessed with FastQC 40 v.0.11.9 (https://github.com/s-andrews/FastQC) and we checked for the absence of contamination with Kraken2 (ref. 41 ) v.2.1.1 (https://github.com/DerrickWood/kraken2) (> 95% of reads originated from Salmonella enterica). Reads passing the initial quality control steps were filtered and quality-trimmed with FqCleanER v21.06 (https://gitlab.pasteur.fr/GIPhy/fqCleanER; options: -q 15 -l 50 -p 50). De novo assemblies were generated from raw reads with fq2dna/21.06 (at https://gitlab.pasteur.fr/GIPhy/fq2dna; strategy B; default settings). Serotyping Isolates ( n = 713) obtained in Spain, Italy, Switzerland and before 2017 in France were serotyped using the conventional serotyping method ( S. Napoli antigenic formula 1 ,9,12:l,z13:e,n,x). The other isolates ( n = 607) were only typed with an in silico serotyping procedure: the O-antigen was determined using a fast kmer-alignment (kma v.1.4.14, https://github.com/genomicepidemiology/kma; coverage ≥65% and identity ≥98%) of Illumina reads against theO9 reference sequence within the rfb cluster ( S . enterica serotype Enteritidis strain P125109; GenBank accession no. AM933172.1; co-ordinates 2,162,790-2,184,501); the H1 ( fliC ) and H2 ( fljB ) flagellins were determined with the BLASTN algorithm 42 (blast+ v.2.16.0; query coverage ≥75%, nucleic acid sequence identity ≥99%) on assemblies against S . Napoli Nap72-2 reference sequences for fliC (GenBank accession no. CP163475; co-ordinates 2866177-2867679) and fljB (GenBank accession no. CP163475; co-ordinates 3,242,735-3,244,240). This in silico serotyping procedure was applied to the 1,320 isolates of our dataset. For the analyses of fliC and fljB sequences, we performed an in silico PCR on short-read assemblies and aligned sequences with Mega12 (ref. 43 ). MLST and core genome MLST (cgMLST) analysis Newly generated raw Illumina paired-end reads ( n = 1,145) from S . Napoli were uploaded to EnteroBase (https://enterobase.warwick.ac.uk), which already contained the published genomes. The platform’s automated pipeline assigned sequence types (STs) and eBurst groups (eBGs) to each genome according to the Achtman MLST7 scheme ( aroC , dnaN , hemD , hisD , purE , sucA , thrA ) 22 . The pipeline also determined core genome MLST (cgMLST) profiles with the Hierarchical Clustering (HierCC V1 (ref. 44 ); https://github.com/zheminzhou/pHierCC) algorithm and allele diversity at the 3,002 loci of Salmonella cgMLST scheme V2 (ref. 23 ) (https://www.cgmlst.org/ncs/1000/schema/Senterica2035/). This EnteroBase Salmonella cgMLST scheme assigns bacterial genomes to single-linkage hierarchical clusters (HCs) at 13 fixed levels of resolution (HC0 HC2, HC5, HC10, HC20, HC50, HC100, HC200, HC400, HC900, HC2000, HC2600 and HC2850) from high-resolution clusters (with no allelic differences for HC0) to low-resolution clusters (with up to 2,850 allelic differences for HC2850). If a genome is equidistant from two existing genotypes, EnteroBase cluster assignment prioritises the earliest database entry. The cgMLST trees were generated from via the EnteroBase website, with the NINJA 45 neighbour-joining algorithm (https://wheelerlab.org/software/ninja/). Complete genome circularisation Complete circular genomes were generated for 13 isolates representative of the observed genetic diversity. Bacterial cultures were grown from single colonies in 10 mL of Trypto-casein soy broth (Bio-Rad 355345B) incubated overnight at 37°C with shaking at 200 rpm . Genomic DNA was extracted from cell pellets with Genomic-tip 100/G columns and the Genomic DNA Buffer set (Qiagen), in accordance with the manufacturer’s instructions. For the S. Napoli Nap72-2isolate, GATC Biotech (now part of Eurofins Scientific) generated PacBio RSII long-read sequences and performed de novo assembly according to the hierarchical genome-assembly process (HGAP; https://github.com/jtchien0925/PacBio_HGAP_assembly) 46 . We subsequently polished the assembly, using Illumina short reads and polypolish 47 (https://github.com/rrwick/Polypolish) then pilon 48 v1.23 (https://github.com/broadinstitute/pilon) software. For the remaining 12 isolates (11 S. Napoli and 1 S. Veneziana; Supplementary Data 1), Oxford Nanopore Technology (ONT) libraries were generated from total DNA with the SQK-LSK109 and EXP-NBD104/114 kits, according to the ONT procedure “ Native Barcoding Amplicons protocol” version 14 Aug 2019 (dx.doi.org/10.17504/protocols.io.bgzxjx7n). Libraries were sequenced on R9.4.1 flow cells with a Mk1C MinION TM device and bases were called for the reads with Guppy 3 (v5.0.13 or v6.4.2; https://nanoporetech.com/software/other/guppy). Long reads underwent filtering for quality with filtlong v0.2.1 (https://github.com/rrwick/Filtlong/) and d e novo genome assemblies were generated with Trycycler 49 v0.5.0 (https://github.com/rrwick/Trycycler), using the default parameters. For each genome, long reads were subsampled into 12 sets. Four sets were assembled with Flye 50 v2.9 (https://github.com/mikolmogorov/Flye), four with raven 51 v1.6.0 (https://github.com/lbcb-sci/raven) and four with miniasm v0.3 (https://github.com/lh3/miniasm) followed by Minipolish 47 v0.1.3 (https://github.com/rrwick/Minipolish). Consensus assemblies underwent three sequential polishing steps: one ONT read polishing with medaka v1.4.4 (https://github.com/nanoporetech/medaka), followed by a primary Illumina read polishing with polypolish 47 v0.5.0 and a final Illumina read polishing with pilon 48 v1.23. Phylogenetic analyses Phylogenetic analyses were performed independently with two reference chromosomes: Nap72-2 ( S . Napoli, GenBank accession no. CP163475) and 164K ( S. Veneziana, GenBank accession no. CP163496). Core genome alignments were generated by mapping Illumina paired-end reads to each reference genome with Snippy v4.6.0 (https://github.com/tseemann/snippy), using the following parameters: minimum mapping quality of 60, minimum base quality of 13, minimum read coverage of 4, and minimum allele proportion of 75%. Repetitive regions, including insertion sequence (IS) elements, prophages and rRNA, were identified in the reference genome and masked in the corresponding alignments. Recombinant regions were subsequently identified and masked with Gubbins 52 v3.2.0 (https://github.com/nickjcroucher/gubbins) The resulting alignments were used to infer maximum likelihood (ML) phylogenies with RAxML 53 v8.2.12 (https://github.com/stamatak/standard-RAxML) under the GTRGAMMA model with 1,000 bootstrap replicates. The tree containing the 164K outgroup was used to establish the root and clade structure for S . Napoli, guiding the rooting of the final ML tree comprising exclusively S . Napoli genomes. We built ML trees for specific genomic segments by selecting the corresponding genomic positions in the SNIPPY alignments before running RAxML v8.2.12 as described above. All trees were visualized and annotated with Interactive Tree of Life (iTOL 54 v6; https://itol.embl.de/). Resistance gene and plasmid analysis ResFinder 55 v4.0.1 (https://github.com/genomicepidemiology/resfinder) was used to identify acquired antibiotic resistance genes (ARGs), and to detect mutations in chromosomal genes encoding antimicrobial resistance in de novo genome assemblies. Plasmid replicons were identified with PlasmidFinder 56 v2.1.1 (https://github.com/genomicepidemiology/plasmidfinder). Results were filtered with >90% identity and >80% coverage thresholds. Six of the 13 complete genomes carried one or two plasmids, none harbouring ARG. BacMet analysis For the identification of genes conferring resistance to biocides and metals, protein sequences from 13 complete S . Napoli genomes (annotated with Bakta 57 v1.5.0; https://github.com/oschwengers/bakta) were used to query the BacMet 26 v2.0 database (https://github.com/ZhihaoXie/BacMet), a curated repository of 753 experimentally confirmed resistance genes (including 125 genes identified in Escherichia coli), with the BLASTP algorithm (BLAST+ 58 v2.16.0). We retained hits meeting the following criteria: minimum query coverage of 84% and amino-acid sequence identity of 75%. When multiple hits were obtained for the same subject protein, only the best hit was retained. We assessed the distribution of resistance genes across S . Napoli lineages by searching for genes identified in the complete genomes within the Panaroo pan-genome output. Pan-genome analysis As the quality of genome assemblies can significantly affect pan-genome description, we excluded genome assemblies of more than 200 contigs from the analysis. Pan-genome analysis was performed with Panaroo 59 v1.3.0 (https://github.com/gtonkinhill/panaroo), using the default parameters (sequence identity threshold of 0.98; length difference cutoff of 0.98) on assemblies previously annotated with Bakta v.1.5.0 (Supplementary Fig. 7, Supplementary Data 1). This analysis encompassed 1,191 isolates and accounted for 11 of the 12 S . Napoli cgMLST HC900 clusters. Pan-genome openness was evaluated by calculating the Heap’s law alpha coefficient (alpha ≤ 1, open; alpha > 1, closed) from a gene presence-absence matrix with 2,000 permutations (micropan 60 v.2.1 R package; https://CRAN.R-project.org/package=micropan). We improved the assignment of accessory genes with prophages or plasmids by performing pan-genome analysis on 13 complete S . Napoli genomes annotated with Bakta. Prophages were delineated with PHASTEST 61 (https://phastest.ca/). Gene content variation was further investigated to determine whether isolates from the same source, geographic origin, or cgMLST cluster had similar accessory gene contents. Pairwise distances between the gene contents of all 1,191 genomes (10,666 genes) were calculated with the Barnes-Hut t-SNE algorithm with a gradient accuracy of 0.5 (PANINI 62 ; https://gitlab.com/cgps/panini/bhtsne). Pathogenicity island (SPI) and virulence factor analysis Virulence factors were initially identified in the 13 complete S . Napoli genomes with VFanalyzer, the online tool provided by the virulence Factors DataBase (VFDB 28,29 (https://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi). Virulence factor distribution (presence/absence) was subsequently analysed across S . Napoli populations (1,191 genomes) during pan-genome analysis (see dedicated section). We first screened for Salmonella pathogenicity islands (SPIs) in the 13 complete S . Napoli genomes, using the SPIFinder v2.0 database (https://cge.food.dtu.dk/services/SPIFinder/). We then used the 1,320 Illumina paired-end reads and kma 63 v1.4.14 (https://github.com/genomicepidemiology/kma; option 1t1, to force the retention of one match per query sequence) to assess the coverage of PAIDB 64 (http://www.paidb.re.kr/) sequences in the total set of isolates. SPI-18 (ref. 65 ) ( S. Napoli strain Nap72-2; GenBank accession no CP163475; co-ordinates 1,455,055–1,456,801), and SPI-13 (ref. 66 ) ( S. Napoli strain Nap72-2; GenBank accession no CP163475; co-ordinates 3,592,799-3,628,491) were added to the selected set of PAIDB sequences. Kma results were filtered to retain SPIs with at least three isolates with ≥50% template coverage and 70% nucleotide identity. The gene architecture of incomplete SPIs was investigated in the complete genomes from annotations or in the annotated genome assemblies when the SPI was not detected in the incomplete genomes. Type VI secretion system (T6SS) identity was confirmed with the SecreT6 web platform 67 (https://bioinfo-mml.sjtu.edu.cn/SecReT6/index.php). Clusters of Orthologous Groups (COG) classification The 10,666 CDS identified during pan-genome analysis were submitted to the eggNOG-mapper-2.1 web interface 68 (http://eggnog-mapper.embl.de/). These CDS included 2,156 corresponding to genes with no known annotations. The remaining 8,583 genes were assigned to COG categories and analysed further. The enrichment index was calculated as the percentage of the core genome (core and soft) consisting of a COG divided by the percentage of the entire genome consisting of the same COG. Two-tailed Fisher’s exact tests were performed to determine the significance of differences. The log 2 fold-enrichment in core genes was calculated across COG functional categories, with a positive value implying that the core genome contained a larger than expected number of genes corresponding to the COG category concerned. CRISPR system and spacer analysis A published Salmonella CRISPR genomic array 30 and the BLASTN algorithm 42 were used to investigate CRISPR-associated gene content. The analysis was performed in two stages: first on the 13 complete S . Napoli genomes and the 1 complete S . Veneziana genome, with subsequent extension to the 1,320 S . Napoli genome assemblies. Spacer content was determined for the 1,320 S . Napoli genome assemblies with the Salmonella -CRISPR-Typing 30 pipeline (https://github.com/C3BI-pasteur-fr/Salmonella-CRISPR-Typing/). The Napoli spacers were designated Nap j for the CR1 array and NapB j for the CR2 array, where j represents a sequential number. A spacer differing by one or two nucleotides from an existing spacer was classified as a variant and designated Nap(B) j var. We also investigated the CRISPR-gene and spacer content of cgMLST HC2600_104 with a set of 38 assemblies downloaded from EnteroBase (Supplementary Table 3) and corresponding to 19 serotypes. Maps and other graphic illustrations The postcode of residence for human cases and the postcode of sampling location for all non-human sources (for five human cases on the islands of Noirmoutier or Ré for the postcode of residence was unknown, we used the postcode of the clinical laboratory) were available for 175 Swiss (95% human and 5% non-human) and 558 French (90% human and 10% non-human) isolates. The postcodes were transformed into Global Positioning System (GPS) co-ordinates based on the centroid of postcode area (GPS data; https://www.data.gouv.fr/datasets/base-officielle-des-codes-postaux/; https://www.swisstopo.admin.ch/fr/repertoire-officiel-des-localites). GPS metadata for the 43 northern Italian isolates were publicly available 18 . Maps and choropleth maps were drawn with the “maps” 69 and “ggplot2” 70 packages of R software and the official EU spatial delineation for basic regions (NUTS level 2, for Italian regione and Swiss Großregions ) and small regions (NUTS level 3: French départements and Spanish provincias ) (https://ec.europa.eu/eurostat/fr/web/nuts). All figures were finalised with the open-source scalable vector graphics editor, Inkscape v0.92.5. (https://inkscape.org/release/inkscape-0.92.5/). Local genome architecture (CDS content) was visualised with the gggenes 71 v0.5.0 https://github.com/wilkox/gggenes and ggplot2 (ref. 72 ) v3.4.2 packages of R93 v.4.1.2 (R Core Team, 2021). RAxML-NG phylogenies were visualised with Interactive Tree of Life (iTOL 54 v6; https://itol.embl.de/). Declarations DATA AVAILABILITY The Illumina sequence reads generated in this study were submitted to EnteroBase(available from: https://enterobase.warwick.ac.uk/species/senterica) and the European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena/) under study numbers PRJEB68323, PRJEB71958, PRJEB49424, PRJEB105765, PRJEB106318, PRJEB106484. All ENA accession numbers and EnteroBase barcodes are listed in Supplementary Data 1. The 13 complete genomes generated in this study were submitted to the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1052634 (Supplementary Data 1 and 2). An interactive version of the cgMLST GrapeTrees output shown in Figure 3 is available from https://enterobase.warwick.ac.uk/ms_tree/133265. CODE AVAILABILITY The FqCleanER script (paired-end FASTQ files cleaning) can be found at https://gitlab.pasteur.fr/GIPhy/fqCleanER. The fq2dna script (genome de novo assembly from raw paired-end FASTQ files) can be found at https://gitlab.pasteur.fr/GIPhy/fq2dna . ACKNOWLEDGEMENTS We thank Magali Ravel, Véronique Guibert, Estelle Serre, Sylvie Issenhuth-Jeanjean, Louise Baugé, Claire Yvon, Annaelle Kerouanton, Herbert Hächler and all participating laboratories of the French, Swiss and Spanish Salmonella surveillance networks. We thank Henriette de Valk, Nathalie Jourdan-Da Silva, Jean-Louis Pinsard, Alexandre Boissinot, Matthieu Berroneau, Roger Meek, Gilles Salvat for discussions. We thank Nigel Dyer and all the other EnteroBase curators. This research was funded by the Fondation Le Roch-Les Mousquetaires (to F.-X.W); Institut Pasteur (to F.-X.W); Santé publique France (to F.-X.W); by the French Government’s Investissement d’Avenir programme, Laboratoire d’Excellence ‘Integrative Biology of Emerging Infectious Diseases’ (grant no. ANR-10-LABX-62-IBEID to F.-X.W); and by the Institute of Health Carlos III (project Acción Estratégica de Salud Intramural (AESI); PI21CIII/00029)). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CONTRIBUTIONS S.H.-L., R.S., A.C., and F.-X.W designed the study. F.-X.W oversaw the study. L.V., G.B., L.B., V.L., L.FA., S.C.-S., M.C., M.P.G., S.H.-L., R.S., A.C., and F.-X.W selected and provided isolates or genomes with their basic metadata. M.A.-D., L.V., G.B., L.B., H.A., S. P-R, S.C.-S. subcultured the bacteria, performed phenotypic experiments, and extracted DNA. L.FR, L.FA., and F.-X.W. analysed and/or interpreted the data. L.FR. wrote the manuscript, with a major contribution from F.-X.W. All the authors contributed to the editing of the manuscript. References Bruner, D. W. & Edwards, P. R. Two New Salmonella Types Belonging to Somatic Group D. Experimental Biology and Medicine 58 , 289–290 (1945). 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13:26:23","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":217324,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/6e7cbda269f22f8abcd4e2e5.html"},{"id":100418251,"identity":"2f17ce6d-ef3f-4409-b5a6-1db5ad321906","added_by":"auto","created_at":"2026-01-16 13:25:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":334545,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic positioning of\u0026nbsp;\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS.\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eNapoli within cgMLST HC2600_104\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;\u003cbr\u003e\n\u0026nbsp;(A)\u0026nbsp;\u003c/strong\u003eGrapeTree\u003csup\u003e73\u003c/sup\u003e\u0026nbsp;visualisation of the NINJA neighbour-joining\u0026nbsp;tree of 3,167 genomes belonging to the cgMLST HC2600_104 cluster including our set of 1,320\u0026nbsp;\u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli genomes (HierCCv1 (ref.\u003csup\u003e44\u003c/sup\u003e)\u0026nbsp;and NINJA algorithms\u003csup\u003e45\u003c/sup\u003e;\u0026nbsp;\u003cem\u003eSalmonella\u003c/em\u003e\u0026nbsp;cgMLSTv2 scheme available at https://enterobase.warwick.ac.uk/). Node colour corresponds to\u003cem\u003e\u0026nbsp;\u003c/em\u003ecgMLST HC2000 cluster and node size is proportional to genome count (kurtosis = 30%). The scale bar indicates allelic differences. The interactive version of this tree is available from https://enterobase.warwick.ac.uk/ms_tree/125256).\u0026nbsp;\u003cstrong\u003e(B)\u0026nbsp;\u003c/strong\u003eNINJA neighbour-joining GrapeTree visualisation of cgMLST HC2600_104 showing cgMLST HC900 clusters for serotypes Napoli and Mississippi (see legend inset). Scale bars indicate the number of cgMLST allelic differences.\u0026nbsp;\u003cstrong\u003e(C)\u0026nbsp;\u003c/strong\u003eFocus on\u0026nbsp;\u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli (cgMLST HC2000_1289) with node colour corresponding to genome providers, illustrating how our set of 1,320 genomes is representative of known\u0026nbsp;\u003cem\u003eS\u003c/em\u003e. Napoli diversity. Source Data file 1.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/440a4e5d3e8cddb7de402180.png"},{"id":100418280,"identity":"b6ced3bf-99fa-4cd2-8f16-120c7248c70a","added_by":"auto","created_at":"2026-01-16 13:25:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70299,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTemporal, geographic and source composition of the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eNapoli study collection.\u003c/strong\u003e A dataset of 1,320 \u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli isolates was analysed, including 1,145 newly sequenced and 174 previously published isolates\u003csup\u003e15,17\u003c/sup\u003e. Metadata were available for 1,319 isolates. The single isolate without associated metadata (UKHSA isolate no. 142214) was retained because it was the sole representative of cluster HC900_1289. \u003cstrong\u003e(A) \u003c/strong\u003eTemporal distribution of isolates obtained from 1945-2022, by geographic origin. The numbers above the bars are the total number of isolates per time period. \u003cstrong\u003e(B) \u003c/strong\u003eDistribution of isolates by country of isolation and source category. Source Data file 2.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/df2f3424c4953f955f72536f.png"},{"id":100418165,"identity":"648f0669-7013-44d2-8634-8acd0e4dbe0a","added_by":"auto","created_at":"2026-01-16 13:25:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":215230,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic structure and geographic distribution of\u0026nbsp;\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS.\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eNapoli in four European countries. (A)\u0026nbsp;\u003c/strong\u003eMaximum likelihood phylogeny based on 1,317\u0026nbsp;\u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli genomes (66,487 non-repetitive SNVs; RAxML-NG\u003csup\u003e53\u003c/sup\u003e; GTRgamma model; 1,000 bootstrap replicates). The columns below the phylogeny indicate the cgMLST HC900 cluster (HC900), geographic origin (GEO) and source of isolates, see inset legend. The scale bar indicates the number of nucleotide differences.\u0026nbsp;\u003cstrong\u003e(B)\u003c/strong\u003e\u0026nbsp;Centre:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eGrapeTree\u003csup\u003e73\u003c/sup\u003e\u0026nbsp;visualisation of the neighbour-joining tree of 1,320\u0026nbsp;\u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli genomes (HierCCv1 (ref.\u003csup\u003e44\u003c/sup\u003e) and NINJA\u003csup\u003e45\u003c/sup\u003e\u0026nbsp;algorithms;\u0026nbsp;\u003cem\u003eSalmonella\u003c/em\u003e\u0026nbsp;cgMLSTv2 scheme (https://enterobase.warwick.ac.uk/). Node colours correspond to\u003cem\u003e\u0026nbsp;\u003c/em\u003ecgMLST HC900 clusters and node size is proportional to genome count (kurtosis = 30%). The scale bar indicates allelic differences. An asterisk (*) indicates isolate LC0541/17, which is distant in the cgMLST analysis due to the presence in EnteroBase of a problematic genome (GCF_003296145, now suppressed from GenBank due to many frameshifted proteins) for this isolate. Interactive tree version: https://enterobase.warwick.ac.uk/ms_tree/133265. Periphery:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eChoropleth maps of cgMLST HC900 distribution across Spanish\u0026nbsp;\u003cem\u003eprovincias\u003c/em\u003e, French\u0026nbsp;\u003cem\u003edépartements\u003c/em\u003e, and Italian\u0026nbsp;\u003cem\u003eregione\u003c/em\u003e\u0026nbsp;and Swiss\u0026nbsp;\u003cem\u003eGroßregions\u003c/em\u003e. The percentage of isolates in each HC900 is colour-coded from white (0%) to red (60 %). Maps were generated with the “maps”\u003csup\u003e69\u003c/sup\u003e\u0026nbsp;and “ggplot2”\u003csup\u003e72\u003c/sup\u003e\u0026nbsp;packages of R. Source Data file 3.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/a66d3fd1d46bb044fc9a8e0d.png"},{"id":100421895,"identity":"81b7c60c-647b-4fe3-b627-0c9922c6527d","added_by":"auto","created_at":"2026-01-16 14:01:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":95849,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogeography of two major \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u0026nbsp;Napoli cgMLST HC200 clusters in Western France.\u0026nbsp;\u003c/strong\u003e(\u003cstrong\u003eLeft\u003c/strong\u003e) Maximum likelihood phylogeny of HC900_1543a isolates (detail from Fig. 1A). The columns to the right of the phylogeny indicate, in order, geographic origin (GEO), the availability of postcode metadata (GPS, here the Global Positioning System co-ordinate of the postcode centroid), and cgMLST clusters (HC400, HC200, HC100, HC50; hierarchical clustering thresholds shown inset). The scale bar indicates the number of nucleotide differences. (\u003cstrong\u003eRight\u003c/strong\u003e) Geographic distribution of major HC50 clusters within HC200_27729 (\u003cstrong\u003etop\u003c/strong\u003e) and HC200_27733 (\u003cstrong\u003ebottom\u003c/strong\u003e). Source Data file 4.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/d8a507d7870cab62d827e4b4.png"},{"id":100418686,"identity":"1c0ffbac-8692-4e54-b939-860a0db3f7ef","added_by":"auto","created_at":"2026-01-16 13:26:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64174,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCRISPR-Cas architecture and spacer diversity in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS.\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eNapoli.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eTwo type I-E CRISPR-Cas architectures found between the \u003cem\u003eiap\u003c/em\u003e and \u003cem\u003eeno\u003c/em\u003e genes in \u003cem\u003eS\u003c/em\u003e.\u0026nbsp;Napoli: LT2-like (matches architecture previously described for \u003cem\u003eS. enterica \u003c/em\u003eserotype\u003cem\u003e \u003c/em\u003eTyphimurium strain LT2) and Ty2-like (resembles type\u003cem\u003e \u003c/em\u003edescribed for\u003cem\u003e S. enterica \u003c/em\u003eserotype\u003cem\u003e \u003c/em\u003eTyphi strain Ty2)\u003csup\u003e30\u003c/sup\u003e. Gene maps were generated with gggenes v0.5.0 and ggplot2 v3.4.2 in R v4.1.2. \u003cstrong\u003e(B) \u003c/strong\u003eMaximum likelihood phylogeny (RAxML-NG\u003csup\u003e53\u003c/sup\u003e, 66,487 non-repetitive SNVs; 1,317 isolates) from Fig. 1A with identical HC900 branch colours. CRISPR architecture is shown on the right of the tree, see inset legend. Scale bar represents 200 cgMLST allelic differences. The asterisk (*) marks the clade with a \u003cem\u003ecasA/cse1\u003c/em\u003e premature stop codon (pTyr110stop). The binary matrix indicates spacer presence (black)/absence (white), with spacers ordered by age of acquisition, left (oldest) to right (youngest), per site (CR1, CR2), and per architecture type. Spacer colours indicate BLASTN hits (word size 7; \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005), orange (prophage/phage; NCBI: taxid10239), green (\u003cem\u003eSalmonella\u003c/em\u003e gene; NCBI:txid590), and black (no hit). Spacer annotations and isolate metadata are provided in Source Data file 5.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/8ece2a7349ef7a3e92822cf7.png"},{"id":101202401,"identity":"0b73ee7b-4492-4f0f-beed-94e8726f3f15","added_by":"auto","created_at":"2026-01-27 09:30:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2081221,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/244372ad-6d89-476d-a067-60899e6fa3d7.pdf"},{"id":100418137,"identity":"e802cc80-8816-44e2-ba0b-3d0496b1187a","added_by":"auto","created_at":"2026-01-16 13:25:11","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":468237,"visible":true,"origin":"","legend":"Supplementary Dataset 1","description":"","filename":"SupplementaryData1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/c17af2831812f006043733e0.xlsx"},{"id":100418350,"identity":"cb516be9-f9a6-4738-8d44-2e6bb767b1b3","added_by":"auto","created_at":"2026-01-16 13:25:41","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15663,"visible":true,"origin":"","legend":"Supplementary Dataset 2","description":"","filename":"SupplementaryData2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/24f33807b5677963a7406b6f.xlsx"},{"id":100418272,"identity":"6b461658-9e41-4595-9220-7a3475b38539","added_by":"auto","created_at":"2026-01-16 13:25:26","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":39334,"visible":true,"origin":"","legend":"Supplementary Dataset 3","description":"","filename":"SupplementaryData3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/bbb27c996f0cbd6cfd56ddb9.xlsx"},{"id":100418361,"identity":"f87132f6-f49f-42cd-857b-c08dcdb675c5","added_by":"auto","created_at":"2026-01-16 13:25:44","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1812886,"visible":true,"origin":"","legend":"Supplementary Dataset 4","description":"","filename":"SupplementaryData4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/120d61fe9fd9e70415990047.xlsx"},{"id":100418136,"identity":"238b0071-88a1-42e4-9785-38dc164475a6","added_by":"auto","created_at":"2026-01-16 13:25:10","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":38769115,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Dataset 5\u003c/p\u003e","description":"","filename":"SupplementaryData5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/27f82d8543f090e12f190937.xlsx"},{"id":100418452,"identity":"bdf4b993-6068-4c2d-b0af-9819dc6cab57","added_by":"auto","created_at":"2026-01-16 13:25:46","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1774076,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Dataset 6\u003c/p\u003e","description":"","filename":"SupplementaryData6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/4492a7595ed60f673cb19d7b.xlsx"},{"id":100418171,"identity":"1888b6d6-5667-41e0-86fb-c98f0a342d15","added_by":"auto","created_at":"2026-01-16 13:25:13","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":38756,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Dataset 7\u003c/p\u003e","description":"","filename":"SupplementaryData7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/c2ceb68e2ef6de713698aa87.xlsx"},{"id":100418654,"identity":"d48dc653-388d-4409-9926-9a9cf099b4c5","added_by":"auto","created_at":"2026-01-16 13:25:59","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":23327,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Dataset 8\u003c/p\u003e","description":"","filename":"SupplementaryData8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/f9559d41da97276b3ff15415.xlsx"},{"id":100417868,"identity":"16fe30f1-48d9-4234-88a6-c4f0267f3237","added_by":"auto","created_at":"2026-01-16 13:24:47","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":15748265,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementaryInformation\u003c/p\u003e","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8608855/v1/52607847f96adab3ed00992d.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Global population genomics of Salmonella enterica serotype Napoli, an emerging pathogen with an unusual epidemiologic pattern","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e \u003cem\u003eSalmonella enterica\u003c/em\u003e serotype Napoli (hereafter referred to as \u003cem\u003eS.\u003c/em\u003e Napoli) was first isolated by Captain W.H. Ewing of the Section of Bacteriology, 15th Medical General Laboratory of the United States (US) Army stationed in Naples during the Italian campaign of World War II\u003csup\u003e1\u003c/sup\u003e. Between November 21st, 1943 and October 25th 1945, this laboratory identified 31 \u003cem\u003eS.\u003c/em\u003e Napoli isolates from stool samples from Italian civilian food-handlers \u0026mdash; all apparently healthy carriers \u0026mdash; and then US soldiers, most of whom were suffering from gastroenteritis\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Since the mid-1990s, the number of human infections caused by \u003cem\u003eS.\u003c/em\u003e Napoli has progressively increased in Europe\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Between 2000 and 2006, a 140% rise in the number of reported cases (from 122 to 283 cases) was observed in 18 European countries, with over 87% of these cases originating from three countries: France, Italy, and Switzerland. More recently, between 2020 and 2024, the countries of the European Economic Area (EEA) reported annual numbers of \u003cem\u003eS.\u003c/em\u003e Napoli cases fluctuating between 359 and 457, with two countries, France and Italy (Switzerland being not an EEA member), accounting for 71.8% and 91.3% of the cases, respectively (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://atlas.ecdc.europa.eu/public\u003c/span\u003e\u003cspan address=\"https://atlas.ecdc.europa.eu/public\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In France, Italy and Switzerland, animal health, environmental, and food production surveillance programmes have reported a similar upward trend\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, with frequent isolations of \u003cem\u003eS\u003c/em\u003e. Napoli from plant-based foods, poultry farming environments\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, surface waters\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, and wildlife, including lizards\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, boars\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and birds\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Within the last five years, the European Union (EU) Rapid Alert for Feed and Food (RASFF; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://food.ec.europa.eu/food-safety/rasff_en\u003c/span\u003e\u003cspan address=\"https://food.ec.europa.eu/food-safety/rasff_en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) system has issued alerts concerning the presence of \u003cem\u003eS\u003c/em\u003e. Napoli in rocket leaves from Italy (notification number 2024.8347), thyme from Italy (2022.3666) and oysters from France (2020.0435). Since the widely reported 1982 outbreak in England and Wales, which was linked to Italian-manufactured chocolate bars\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, foodborne outbreaks of \u003cem\u003eS\u003c/em\u003e. Napoli infection have remained rare and have often involved the consumption of plant products (essentially fresh herbs, rocket leaves or beetroot) produced in Italy or France\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The presence of \u003cem\u003eS\u003c/em\u003e. Napoli in surface waters used for irrigation was identified as the most significant risk factor for food crop contamination\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUnlike most non-typhoidal \u003cem\u003eSalmonella\u003c/em\u003e (NTS) infections, those caused by \u003cem\u003eS\u003c/em\u003e. Napoli are predominantly sporadic and of unknown origin, affecting individuals at the extremes of the human age range \u0026mdash; under the age of two years or over the age of 65 years \u0026mdash; more frequently than is generally observed for the principal NTS infections\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Furthermore, the seasonal peaks of \u003cem\u003eS\u003c/em\u003e. Napoli isolations from humans and the environment coincide, typically during the period from June to October, with case numbers falling to particularly low levels during cold months\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Pulsed-field gel electrophoresis (PFGE) analyses have identified genetic clusters containing both human and non-human isolates\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Collectively, this evidence indicates that \u003cem\u003eS\u003c/em\u003e. Napoli may be transmitted to humans primarily through contact with the environment (e.g., consumption of contaminated greens irrigated with contaminated water; outdoor activities involving water\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e) rather than via the consumption of commercially available animal products. \u003cem\u003eS\u003c/em\u003e. Napoli can, therefore, reasonably be described as an emerging pathogen of environmental origin\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, despite extensive research, the natural reservoirs of this serotype remain unidentified.\u003c/p\u003e \u003cp\u003eFor sporadic diseases, effective source attribution and surveillance depend heavily on both a clear description of the pathogen population structure and the availability of robust laboratory tools for linking cases. \u003cem\u003eS.\u003c/em\u003e Napoli has been shown to be phylogenetically close to the Typhi and Paratyphi A serotypes within a clade \u0026mdash; defined as section Typhi \u0026mdash; in the \u003cem\u003eS. enterica\u003c/em\u003e phylogeny, but different from these serotypes\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, the global \u003cem\u003eS\u003c/em\u003e. Napoli population is currently poorly characterised. Previous assessments of the genetic diversity of \u003cem\u003eS\u003c/em\u003e. Napoli based on PFGE, multilocus sequence typing (MLST7), and/or whole-genome sequencing (WGS) revealed a high degree of genetic heterogeneity both within Italy and throughout the known endemic regions in Europe\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, none of these studies was able to establish clear phylogenetic relationships between the isolates or provide a comprehensive phylogeographic description of the population. This gap in our knowledge obscures the links between human infection and potential sources of exposure, making source attribution for \u003cem\u003eS.\u003c/em\u003e Napoli a major challenge.\u003c/p\u003e \u003cp\u003eAs a first step towards understanding the natural ecology of \u003cem\u003eS\u003c/em\u003e. Napoli, we investigated the genetic diversity of \u003cem\u003eS\u003c/em\u003e. Napoli populations in multiple countries, including Italy, Switzerland, and France \u0026mdash; where this serotype has increasingly been reported over the last 35 years \u0026mdash; and Spain, which we identify here, for the first time as a zone of endemicity for \u003cem\u003eS.\u003c/em\u003e Napoli. Our findings emphasize the need for the collection of medium-to-long-term international data and genomic data to elucidate the relationships between sporadic autochthonous infections of both human and non-human origin.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cb\u003ePhylogenetic position of\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe phylogeny of \u003cem\u003eS. enterica\u003c/em\u003e subsp. \u003cem\u003eenterica\u003c/em\u003e established by Zhou and coworkers\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e (redrawn in Supplementary Fig.\u0026nbsp;1) demonstrated that \u003cem\u003eS.\u003c/em\u003e Napoli belongs to a clade closely related to serotypes Typhi and Paratyphi A. Notably, this clade also contains isolates of two environmental serotypes, Veneziana and Mississippi (clade A for the latter\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e), and all members of this clade belong to EnteroBase core genome MLST (cgMLST) hierarchical cluster HC2600_104. An analysis of all cgMLST HC2600_104 genomes in EnteroBase on April 2024 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3,991; workspace:110633), confirmed the monophyly of \u003cem\u003eS\u003c/em\u003e. Napoli, as all isolates (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2,145) of this serotype (identified with the \u003cem\u003ein silico\u003c/em\u003e serotype prediction tool SISTR\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and/or clustering within MLST eBurst group eBG60 (ref.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e), both approaches implemented in EnteroBase) grouped together exclusively in the HC2000_1289 superlineage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, Supplementary Data 1). Other \u003cem\u003eS. enterica\u003c/em\u003e serotypes belonging to HC2600_104, such as Lomalinda, Veneziana, Mississippi (clade A), Blijdorp, Itami, and Woodinville, all identified by SISTR, were grouped in other HC2000 clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGenetic diversity and structure of\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe studied the population structure of \u003cem\u003eS\u003c/em\u003e. Napoli by assembling a set of 1,320 genomes (all present in EnteroBase) sampled between 1945 and 2022 in four European countries (France, Italy, Switzerland, and Spain) and originating from human and non-human sources (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Table\u0026nbsp;1, Supplementary Data 1). These 1,320 genomes included 1,145 generated in this study, 174 previously published genomes\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and one unpublished genome (isolate 142214) (Supplementary Fig.\u0026nbsp;2A). Conventional serotyping and/or \u003cem\u003ein silico\u003c/em\u003e typing confirmed the antigenic formula (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e1\u003c/span\u003e,9,12:l,z13:e,n,x) for all these genomes (Supplementary Data 1). Our cgMLST analysis on all HC2600_104 genomes (see above) confirmed that our set of 1,320 genomes was, indeed, representative of the known global diversity of \u003cem\u003eS\u003c/em\u003e. Napoli (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSalmonella\u003c/em\u003e serotype delineation is often based on cgMLST HC900 clusters (one HC900 cluster corresponds generally to one serotype)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Intriguingly, we identified 12 HC900 clusters for \u003cem\u003eS\u003c/em\u003e. Napoli in both the initial dataset of 2,145 genomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) and the final dataset of 1,320 genomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The HC900 diversity detected for \u003cem\u003eS\u003c/em\u003e. Napoli in these four neighbouring European countries was 2.5 times higher than that of serotype Mississippi clade A in Oceania and the US (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://enterobase.warwick.ac.uk/ms_tree/125256\u003c/span\u003e\u003cspan address=\"https://enterobase.warwick.ac.uk/ms_tree/125256\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The 12 cgMLST HC900 clusters were subdivided into 31 HC400 and 55 HC200 clusters (Supplementary Fig.\u0026nbsp;2B, 2C). Phylogenetic analyses with both cgMLST (EnteroBase cgMLSTv2 scheme using NINJA neighbour-joining and HierCCv1; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and single-nucleotide variant (SNV)-based clustering (RAxML; Generalised time reversible Gamma \u0026mdash; GTRGamma \u0026mdash; model; 1,000 bootstrap replicates; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) approaches subdivided the \u003cem\u003eS\u003c/em\u003e. Napoli population into two clades (N1 and N2), which could be further subdivided into 15 lineages. Eleven of these lineages exactly matched the established cgMLST HC900 clusters, the exception being HC900_1543 (clade N2), which was differentiated into four distinct subclades by SNV-based phylogeny analysis: HC900_1543a, HC900_1543b, HC900_1543ab, and HC900_1543c. Lineage HC900_1543ab, consisting of only three isolates, was basal and ancestral to lineages HC900_1543a and HC900_1543b. Lineage HC900_1543c displayed the highest degree of genetic divergence.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBefore this study, only one complete genome of \u003cem\u003eS\u003c/em\u003e. Napoli of good quality, 16-174478 (GenBank accession no. CP063140.1) was available\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This genome, from an extended-spectrum beta-lactamase (ESBL)-producing isolate collected in Italy, belonged to cluster HC900_1450. As a means of improving this and future genomic analyses of \u003cem\u003eS\u003c/em\u003e. Napoli populations, we generated 12 additional complete genome sequences to obtain a set of 13 complete genomes representative of the major lineages (12 of the 15 phylogenetic lineages; Supplementary Data 1 and 2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eStrong phylogeographic pattern of\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli lineages\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDifferential geographic partitioning of the seven most prominent \u003cem\u003eS\u003c/em\u003e. Napoli lineages was observed across Italy, Switzerland, France, and Spain (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), with Italy hosting five lineages. The HC900_20879 lineage predominated in northern/central Italy and Switzerland, whereas HC900_1450, HC900_7673 and HC900_107023 were prevalent in southern Italy. Interestingly, the HC900_1450 lineage, isolated principally from Campania and Lazio (central Italy), includes the historical first isolate described in Naples (Campania) in 1945 (ref.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e). The other lineages also had strongly regionalised distributions, with HC900_1543b highly prevalent across northern Italy, Switzerland (Ticino and Z\u0026uuml;rich \u003cem\u003eGro\u0026szlig;regions\u003c/em\u003e) and eastern France (Haut-Rhin and Alpes-Maritimes \u003cem\u003ed\u0026eacute;partements\u003c/em\u003e); HC900_1543c was confined to Spain, mainly in the northern coast (Asturias and Cantabria \u003cem\u003ecomunidades aut\u0026oacute;nomas\u003c/em\u003e); and HC900_1543a was largely restricted to western France. For minor lineages, the limited sample sizes prevented robust spatial analysis, but metadata analysis indicated a tendency of HC900_107120 to be associated with Sicily (Supplementary Data 1). Furthermore, the observed geographic structure was not associated with the source of the isolate, as human and non-human isolates from the same lineage had similar distributions (Supplementary Fig.\u0026nbsp;3). We further analysed the spatial structuring of the major genetic cluster HC900_1543, transforming postcode centroids into Global Positioning System (GPS) co-ordinates (in mainland France, the 5,896 postcodes have a median area of about 11 km\u0026sup2;; in Switzerland the 3,194 postcodes - PLZ4 - have a median area of 7\u0026ndash;8 km\u0026sup2;). Even at a finer phylogenetic scale, we observed clear and discrete geographic clustering with minimal overlap. The HC900_1543a lineage could be subdivided into distinct HC400 clusters: HC400_204873, geographically concentrated in north/north-western Switzerland and the neighbouring French region of Alsace, and HC400_140575, localised in south-western and central France (Supplementary Fig.\u0026nbsp;4). The widespread HC400_27729 cluster could be subdivided into three HC200 clusters, one of which (HC200_140623) was tightly concentrated around La Rochelle and the island of R\u0026eacute; (Supplementary Fig.\u0026nbsp;4). The other two clusters (HC200_27729 and HC200_27733) could themselves be subdivided into geographically clustered HC50 genetic clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Finally, despite the limited GPS data available for Italian samples, we also observed a geographic clustering of HC900_1543b sublineages, with HC100_107035 localised in central Switzerland, HC50_137319 in Ticino, and HC20_140601 in Alsace/north and north-western Switzerland (Supplementary Fig.\u0026nbsp;5).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInefficacy of MSLT typing for identifying\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli lineages\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMLST7 sequence types (STs) and eBurst Groups (eBG) are widely used to track \u003cem\u003eSalmonella\u003c/em\u003e lineages, but the phylogenetic resolution of MLST7 was limited for \u003cem\u003eS\u003c/em\u003e. Napoli. We found that eBG60 perfectly identified \u003cem\u003eS\u003c/em\u003e. Napoli, but we observed 50 different STs with disorganised distributions across serotype \u003cem\u003eS\u003c/em\u003e. Napoli HC900 clusters (Supplementary Fig.\u0026nbsp;6). In particular, the predominant ST (ST474) was observed in isolates from three different clusters, HC900_1543, HC900_107023, and HC900_1289. ST2019 occurred in two different clusters, HC900_7673 and HC900_63054, whereas a single cluster, HC900_7673 contained isolates from five different STs (ST2008, ST2019, ST2101, ST4936, ST7210) (Supplementary Fig.\u0026nbsp;6). However, we observed limited congruence between MLST7 STs and cgMLST clusters, with five specific associations: one with minor HC900 clusters (ST4354 and HC900_94001) and four with HC400 clusters (ST1853 and HC400_106990; ST4550 and HC400_107080; ST4277 and HC400_88024; and ST8183 and HC400_247522) (Supplementary Data 1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLow nucleotide diversity of the flagellin gene sequences of\u003c/b\u003e \u003cb\u003eS.\u003c/b\u003e \u003cb\u003eNapoli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA unique one-to-one relationship between a serotype and a cgMLST HC2000 cluster (super-lineage) \u0026mdash; as observed between \u003cem\u003eS\u003c/em\u003e. Napoli and HC2000_1289 \u0026mdash; is rather unusual for most NTS, for which relationships are generally observed between a serotype and an HC900 cluster. We investigated the maintenance of a similar antigenic formula (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e1\u003c/span\u003e,9,12:l,z23:e,n:x) ) across the 15 lineages of \u003cem\u003eS\u003c/em\u003e. Napoli, by analysing the genetic polymorphism of the \u003cem\u003efliC\u003c/em\u003e (encoding H1 flagellin l,z13) and \u003cem\u003efljB\u003c/em\u003e (encoding H2 flagellin e,n,x) genes in our dataset. Full \u003cem\u003efliC\u003c/em\u003e l,z13 (1,503 bp) and \u003cem\u003efljB\u003c/em\u003e_e,n,x (1,506 bp) sequences could be retrieved for 1,294 and 1,229 isolates, respectively (Supplementary Table\u0026nbsp;2). An identical \u003cem\u003efliC\u003c/em\u003e allele, \u003cem\u003efliC\u003c/em\u003e1, was found in 92.4% (1,196/1,294) of the \u003cem\u003eS\u003c/em\u003e. Napoli isolates distributed across 11 lineages; two \u003cem\u003efljB\u003c/em\u003e alleles \u0026mdash; \u003cem\u003efljB\u003c/em\u003e1 and \u003cem\u003efljB\u003c/em\u003e2 (differentiated by a single synonymous SNV) \u0026mdash; were found in 86.6% (1,064/1,229) of the isolates, with \u003cem\u003efljB\u003c/em\u003e2 distributed across 10 lineages. Despite the identification of 18 and 22 alleles for \u003cem\u003efliC\u003c/em\u003e and \u003cem\u003efljB\u003c/em\u003e genes, respectively, there was little nucleotide variation between these alleles, with a maximum of two SNVs resulting in two amino-acid changes for \u003cem\u003efliC\u003c/em\u003e (with \u003cem\u003efliC\u003c/em\u003e1 as the reference) and a maximum of three SNVs resulting in a single amino-acid change for \u003cem\u003efljB\u003c/em\u003e (with \u003cem\u003efljB\u003c/em\u003e1 as the reference). The presence of similar flagellin antigens in \u003cem\u003eS\u003c/em\u003e. Napoli is, therefore, linked to a strong conservation of \u003cem\u003efliC\u003c/em\u003e and \u003cem\u003efljB\u003c/em\u003e nucleotide sequences across one HC2000 cluster and its 15 derived lineages.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAntimicrobial, metal and biocide resistance gene content of\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli populations\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAntimicrobial resistance (AMR) genes were rare in \u003cem\u003eS\u003c/em\u003e. Napoli, occurring in only 2% (27/1,320) of the isolates (Supplementary Data 1). Transmission was horizontal (carried by a plasmid) for 22 of the 23 AMR genes, and vertically transmitted via chromosomal mutation for the remaining AMR gene (\u003cem\u003egyrA\u003c/em\u003e_D87G in isolate UZH_N16-0214). Most AMR-positive isolates (16/27; 60%) harboured multiple plasmid-borne AMR genes (Supplementary Data 1). Notable resistance phenotypes included one carbapenemase-producing isolate (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e in clinical isolate 201805020) and three ESBL-producing isolates (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u0026minus;1\u003c/sub\u003e in clinical isolates 16-174478 (ref.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e) and 201606260; \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u0026minus;15\u003c/sub\u003e in clinical isolate LC0541/17 (ref.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e)).\u003c/p\u003e \u003cp\u003eWe screened for metal and biocide resistance gene repertoires with the BacMet database, which contains 753 experimentally validated resistance genes\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The screening of 1,191 \u003cem\u003eS\u003c/em\u003e. Napoli genome assemblies (further included in the pan-genome analysis) identified 115 genes, 109 of which were present in at least 95% of the assemblies (Supplementary Data 3). This analysis defined a core metal‑/biocide‑resistome of 109 genes for \u003cem\u003eS\u003c/em\u003e. Napoli, and an accessory resistome composed of six arsenic-resistant (\u003cem\u003earsABCDRH\u003c/em\u003e) genes detected in 3 to 9% of the isolates. For comparison, we screened 779 NCBI reference genomes for three additional \u003cem\u003eS. enterica\u003c/em\u003e serotypes: Enteritidis (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;327), Typhimurium (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;289) and Typhi (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;165). The core resistomes of these serotypes contained 117 genes for Enteritidis, 116 genes for Typhimurium, and 103 genes for Typhi. The four serotypes had a subset of 102 genes in common. The \u003cem\u003eges\u003c/em\u003e and \u003cem\u003egol\u003c/em\u003e operons, conferring tolerance to gold (Au) and copper (Cu), were absent from both Napoli and Typhi; the mercury (\u003cem\u003emer\u003c/em\u003e), quaternary‑ammonium‑compound (\u003cem\u003eoqx\u003c/em\u003e), copper (\u003cem\u003epco\u003c/em\u003e), silver (\u003cem\u003esil\u003c/em\u003e) and tellurium (\u003cem\u003eter\u003c/em\u003e) resistance operons were detected in 9\u0026ndash;34% of the Typhimurium genomes, but in less than 0.5% of \u003cem\u003eS\u003c/em\u003e. Napoli genomes. Finally, arsenic resistance (\u003cem\u003ears\u003c/em\u003e) genes, were detected in 25% of Typhimurium genomes but were absent from the Enteritidis and Typhi serotypes (Supplementary Data 4).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePan-genome composition across\u003c/b\u003e \u003cb\u003eS\u003c/b\u003e. \u003cb\u003eNapoli lineages\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnalyses of genome content were facilitated by our access to 13 complete genomes representative of \u003cem\u003eS\u003c/em\u003e. Napoli diversity. The pan-genome analysis was performed on 1,191 genome assemblies of fewer than 200 contigs and included 13 of the 15 \u003cem\u003eS\u003c/em\u003e. Napoli lineages (Supplementary Fig.\u0026nbsp;7; Supplementary Data 5), with HC900_1543a and HC900_1543b accounting for 53.6% and 26.5%, respectively, of these genomes. Despite the overrepresentation of the HC900_1543a and 1543b lineages in the dataset, our pan-genome analysis identified a closed pan-genome (Heap\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;1.0555\u0026thinsp;\u0026gt;\u0026thinsp;1) containing 10,739 genes, including 3,898 core genes (\u0026ge;\u0026thinsp;99% isolates), 146 soft core genes (95\u0026ndash;99% isolates), 721 shell genes (15\u0026ndash;95% isolates) and 6,120 cloud genes (\u0026lt;\u0026thinsp;15% isolates) (Supplementary Fig.\u0026nbsp;8A, B).\u003c/p\u003e \u003cp\u003eWe searched for enrichment in any gene functions (cluster of orthologous categories, COG) in either the core or accessory genome. The pan-genome analysis detected 10,739 coding DNA sequences (CDSs), 2,156 of which lacked eggNOG-mapper annotations (Supplementary Data 6). The functional enrichment analysis of the annotated 8,583 CDSs revealed that 78% of the 3,813 poorly characterised/uncharacterised genes belonged to the accessory genome (Fisher\u0026rsquo;s exact test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). For the 4,770 genes with assigned functions, a strong enrichment in replication, recombination and repair (L) genes was observed in the accessory genome, together with genes involved in transcription (K) and intracellular trafficking, secretion and vesicular transport (U) (Supplementary Fig.\u0026nbsp;8C, D). By contrast, the core genome was enriched in seven functions \u0026mdash; translation, ribosomal structure and biogenesis functions (J) \u0026mdash; plus six metabolic categories \u0026mdash; nucleotide transport (F); coenzyme transport (H); amino-acid transport (E); energy production and conversion (C); carbohydrate transport (G); and inorganic ion transport (P) (Supplementary Fig.\u0026nbsp;8C, D).\u003c/p\u003e \u003cp\u003eAccessory gene content was itself structured by phylogeny. Pan-genome-based neighbour networks revealed a lineage-specific clustering of cgMLST HC900 clusters (excluding HC900_1543) or, for HC900_1543, of HC400 and HC200 clustering levels, indicating that pan-genome divergence increased with core genome phylogenetic distance (Supplementary Fig.\u0026nbsp;9A-C; Supplementary Data 5). The country of origin within genetic clusters and the isolation source had no effect on pan-genome clustering patterns (Supplementary Fig.\u0026nbsp;9D, E), consistent with the absence of source-associated phylogenetic clustering (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePathogenicity island and virulence factor analysis\u003c/h2\u003e \u003cp\u003eSPI-finder detected seven pathogenicity islands (SPI-1, -2, -3, -4, -5, -9, and \u0026minus;\u0026thinsp;12) in the 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes and the SPI-13 island in 12 of these genomes. The SPI coverage analysis (including Illumina reads for 1,320 \u003cem\u003eS\u003c/em\u003e. Napoli) confirmed the presence of these islands (complete SPI-1, -2, -4, -9, and \u0026minus;\u0026thinsp;12; partial SPI-3, -5, and \u0026minus;\u0026thinsp;13) and detected three additional islands (complete SPI-18; partial SPI-6, and \u0026minus;\u0026thinsp;11; very incomplete SPI-7) (Supplementary Figs.\u0026nbsp;10 and 11). Contrary to these initial database hits, we found that \u003cem\u003eS\u003c/em\u003e. Napoli lacked the canonical 134 kb SPI-7 island of \u003cem\u003eS. enterica\u003c/em\u003e serotype Typhi\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e \u0026mdash; including, in particular, the locus for the production and export of Vi antigen and a \u003cem\u003esopE\u003c/em\u003e prophage \u0026mdash; with observed kma hits matching solely the \u003cem\u003esopE\u003c/em\u003e gene and diverse prophage genes. The distribution of several SPIs displayed striking lineage specificity. Two of the five major SPI-3 components, \u003cem\u003emgtB\u003c/em\u003e and \u003cem\u003emgtC\u003c/em\u003e, were detected in all \u003cem\u003eS\u003c/em\u003e. Napoli genomes; the other three were detected exclusively in clade N2: \u003cem\u003emarT/cadC1\u003c/em\u003e, \u003cem\u003erhuM\u003c/em\u003e, and \u003cem\u003emisL\u003c/em\u003e (either complete 2853 bp or partial 663 bp) (Supplementary Fig.\u0026nbsp;11A). Furthermore, SPI-5 was complete in HC900_1543, or almost complete in other HC900 clusters, but insertions of transposases and prophages were repeatedly observed between tRNA-ser and \u003cem\u003epipA\u003c/em\u003e and, between \u003cem\u003esigE\u003c/em\u003e and \u003cem\u003esopB\u003c/em\u003e genes, especially in clade N1 (Supplementary Fig.\u0026nbsp;11B). The type VI secretion system (T6SS) encoded by SPI-6 was detected exclusively in the Spanish lineage (HC900_1543c) and one western French sublineage (HC200_27729). The other sublineages carried only incomplete versions (Supplementary Fig.\u0026nbsp;11C). The SPI-11 of \u003cem\u003eS\u003c/em\u003e. Napoli was similar to that of the \u003cem\u003eS. enterica\u003c/em\u003e serotype Typhi CT18 genome, with a conserved region from tRNA-Arg to \u003cem\u003ecdtB\u003c/em\u003e, with or without the \u003cem\u003epltA\u003c/em\u003e, \u003cem\u003epltB\u003c/em\u003e, and \u003cem\u003esopF\u003c/em\u003e genes (Supplementary Fig.\u0026nbsp;11D). Finally, \u003cem\u003eS\u003c/em\u003e. Napoli genomes carried an SPI-13 island (~\u0026thinsp;35.7 kb in most genomes) significantly larger than that in the \u003cem\u003eS. enterica\u003c/em\u003e serotype Typhimurium LT2 reference sequence (19.5 kb) (Supplementary Fig.\u0026nbsp;11E).\u003c/p\u003e \u003cp\u003eA comparative analysis of virulence factors (VFDB\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e) in the 13 complete genomes and the 1,191 pan-genomes revealed a uniform composition in terms of the genes of pathogenicity islands SPI-1 and SPI-2, which encode the type III secretion systems TTSS-1 and TTSS-2, respectively (Supplementary Data 7). Key determinants of magnesium uptake (\u003cem\u003emgtB, mgtC\u003c/em\u003e) and regulation (\u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoQ\u003c/em\u003e), and the macrophage-inducible gene \u003cem\u003emig-14\u003c/em\u003e were also conserved. Seven of the TTSS-1 translocated effectors were encoded by all genomes, two (\u003cem\u003esopE2\u003c/em\u003e and \u003cem\u003esopE\u003c/em\u003e) were present in more than 95% of the genomes, and four (\u003cem\u003eavrA, sopD2\u003c/em\u003e, \u003cem\u003espvC\u003c/em\u003e, \u003cem\u003espvD\u003c/em\u003e) absent from all genomes (Supplementary Data 7). The \u003cem\u003esopE\u003c/em\u003e gene is carried by an Edward-GF2 prophage of the Caudoviricetes phage family.\u003c/p\u003e \u003cp\u003eEight of the TTSS-2 effectors were widely detected (\u003cem\u003epipB2\u003c/em\u003e, \u003cem\u003epipB\u003c/em\u003e, \u003cem\u003esifA\u003c/em\u003e, \u003cem\u003esifB\u003c/em\u003e, \u003cem\u003espiC/ssaB\u003c/em\u003e, \u003cem\u003esseF\u003c/em\u003e, \u003cem\u003esseG\u003c/em\u003e, \u003cem\u003esseJ\u003c/em\u003e, \u003cem\u003esseK1\u003c/em\u003e, \u003cem\u003esseL, sspH2;\u003c/em\u003e \u0026ge;94% pan-genomes), whereas three were detected in a more variable manner: \u003cem\u003egogB\u003c/em\u003e (12 genomes and 77% of the pan-genomes), \u003cem\u003esseI/srfH\u003c/em\u003e (exclusive to HC900_1450) and \u003cem\u003esseK2\u003c/em\u003e (8 of 13 genomes and 23% of the pan-genomes) (Supplementary Data 7). An adhesion system analysis showed that six fimbrial operons were ubiquitous (\u003cem\u003ecsg\u003c/em\u003e, \u003cem\u003efim\u003c/em\u003e, \u003cem\u003epeg\u003c/em\u003e, \u003cem\u003esta\u003c/em\u003e, \u003cem\u003estf\u003c/em\u003e, \u003cem\u003esth\u003c/em\u003e), 10 were undetected (\u003cem\u003epef\u003c/em\u003e, \u003cem\u003esef\u003c/em\u003e, \u003cem\u003estb, stc, ste, sti\u003c/em\u003e, \u003cem\u003estj\u003c/em\u003e, \u003cem\u003estk\u003c/em\u003e, \u003cem\u003elpf\u003c/em\u003e, \u003cem\u003etcf\u003c/em\u003e) and six varied in terms of their presence or completeness (\u003cem\u003ebcf\u003c/em\u003e operon complete in 8 genomes, 91% of the pan-genomes; near-complete \u003cem\u003estd\u003c/em\u003e and \u003cem\u003esth\u003c/em\u003e operons in 13 genomes; \u003cem\u003esafB/C/\u003c/em\u003eD exclusive to HC900_1543c) (Supplementary Fig.\u0026nbsp;11C; Supplementary Data 7). The nonfimbrial adhesion determinants \u003cem\u003eratB\u003c/em\u003e, \u003cem\u003eshdA\u003c/em\u003e, and \u003cem\u003esinH\u003c/em\u003e were conserved, whereas \u003cem\u003emisL\u003c/em\u003e was restricted to HC900_1543b, HC900_1543c, HC900_20879 and HC400_140575 within clade N2. Finally, despite the absence of SPI-7, the \u003cem\u003eS. enterica\u003c/em\u003e serotype Typhi Vi-encoding pathogenicity island, three other Typhi determinants were detected in the vicinity of SPI-11 in \u003cem\u003eS\u003c/em\u003e. Napoli (Supplementary Fig.\u0026nbsp;11D; Supplementary Data 7): \u003cem\u003ecdtB\u003c/em\u003e was present in all genomes, and \u003cem\u003epltA\u003c/em\u003e and/or \u003cem\u003epltB\u003c/em\u003e were found in six genomes (in 14% and 42% of the pan-genomes respectively).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRecombining regions, CRISPR system and spacer diversity\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eRecombining regions, CRISPR system and spacer diversity\u003c/div\u003e \u003cp\u003eA Gubbins software analysis of 1,317 genomes aligned with the \u003cem\u003eS\u003c/em\u003e. Napoli Nap72-2 genome (GenBank accession no. CP163475) identified three major recombining regions (Supplementary Fig.\u0026nbsp;12). The gene content of these regions was inspected within complete genomes: 13 \u003cem\u003eS\u003c/em\u003e. Napoli and one \u003cem\u003eS. enterica\u003c/em\u003e serotype Veneziana (the closest serotype to Napoli in Europe, hereafter referred to as \u003cem\u003eS.\u003c/em\u003e Veneziana), 164K (GenBank accession no. CP063140) (Supplementary Data 1). Recombining region 1 (RR1: 30,549 bp) included part of the SPI-6 pathogenicity island (\u003cem\u003eTssD\u003c/em\u003e/sTM0276 to \u003cem\u003epagN\u003c/em\u003e) and displayed a high level of SNV diversity in the HC900_1543b lineage. Recombining region 2 (RR2: 188,605 bp) contained the SPI-5 pathogenicity island, the \u003cem\u003ecsg\u003c/em\u003e (curli) operon, and the \u003cem\u003eflg\u003c/em\u003e (flagellar) gene cluster and displayed marked SNV density in the HC900_1543a/b/c/a-b, HC900_20879 and HC900_1289 lineages. Recombining region 3 (RR3: 218,909 bp) contained the SPI-1 pathogenicity island and the CRISPR-Cas system components, including the associated spacers. A high level of SNV density was observed in RR3 in lineages HC900_1543b and HC900_20879. Subsequent phylogenetic analyses of RR2 and RR3, taking either the \u003cem\u003eS\u003c/em\u003e. Napoli Nap72-2 or the \u003cem\u003eS.\u003c/em\u003e Veneziana 164K genome as a reference, revealed hallmarks of genetic introgression (Supplementary Figs.\u0026nbsp;13 and 14). At RR2, \u003cem\u003eS\u003c/em\u003e. Veneziana branched together with the \u003cem\u003eS\u003c/em\u003e. Napoli clade N1 lineages. At RR3, \u003cem\u003eS\u003c/em\u003e. Veneziana branched with two major lineages from Switzerland, northern Italy and eastern France (HC900_1543b and HC900_20879).\u003c/p\u003e \u003cp\u003eComparative analysis of the CRISPR-Cas encoding region revealed unexpected diversity across \u003cem\u003eS\u003c/em\u003e. Napoli lineages. Most \u003cem\u003eS\u003c/em\u003e. Napoli lineages harboured the CRISPR LT2-type structure\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, either intact or with a partial deletion, but the HC900_1543b and HC900_20879 lineages harboured a deleted Ty2-type CRISPR structure\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Supplementary Table\u0026nbsp;3). In line with the introgression signal detected in RR3, spacer content divergence mirrored CRISPR-Cas structural partitioning: HC900_1543b and HC900_20879 had no spacer in common with other \u003cem\u003eS\u003c/em\u003e. Napoli lineages but displayed 100% spacer identity to \u003cem\u003eS\u003c/em\u003e. Veneziana (Supplementary Table\u0026nbsp;3). By contrast, \u003cem\u003eS\u003c/em\u003e. Napoli genomes harbouring an LT2-type CRISPR structure had a maximum of 64% of spacers in common (29% of CR1; 100% of CR2; Supplementary Table\u0026nbsp;3) with other HC2600_104 members, and spacer content followed the phylogenetic structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe heterogeneity of the \u003cem\u003eS\u003c/em\u003e. Napoli population had already been described in Italy\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e and Europe\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, but our whole-genome sequencing analysis of a representative set of isolates provides a clearer picture of the phylogeography of the Napoli serotype across its endemic zone, constituting a solid baseline for epidemiological investigations. The \u003cem\u003eS\u003c/em\u003e. Napoli population can be split into two clades (N1 and N2), further divided into 15 lineages, seven of which are prominent. The \u003cem\u003eS\u003c/em\u003e. Napoli population displayed a remarkable pattern of geographic segregation in Europe, evident from the 15 basal lineages down to the finest phylogenetic resolution.\u003c/p\u003e \u003cp\u003eThe sample studied here is the most comprehensive collection of \u003cem\u003eS\u003c/em\u003e. Napoli ever assembled, from various sources and covering the entire known genetic diversity for this serotype. Nevertheless, it remains challenging to delineate the endemic zone of any micro-organism, including \u003cem\u003eS\u003c/em\u003e. Napoli. In 2009, the Enter-net international surveillance network (an EU-funded dedicated surveillance network for enteric pathogens) showed that 87.5% of human \u003cem\u003eS\u003c/em\u003e. Napoli infections occurred in Switzerland, Italy, and France, three countries in which the presence of \u003cem\u003eS\u003c/em\u003e. Napoli in the environment had been previously documented\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Our work expands this endemic zone to include Spain, where the isolates form a newly identified distinct clade, phylogenetically different from those already detected in other endemic regions in Europe (France, Italy and Switzerland). However, we cannot rule out the possibility that \u003cem\u003eS\u003c/em\u003e. Napoli has a greater genetic diversity or wider geographic distribution extending beyond the four countries identified to date. Indeed, our work is based on published findings, surveillance data from the European Centre for Disease Prevention and Control (ECDC), genomic data available from EnteroBase, and information obtained through contacts with numerous European reference laboratories for \u003cem\u003eSalmonella\u003c/em\u003e. Nevertheless, the capacity for salmonellosis surveillance varies across the European continent, potentially masking both new lineages and unrecognised foci of infection.\u003c/p\u003e \u003cp\u003eIn the seminal paper for the cgMLST scheme\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, Zhou and collaborators considered the cgMLST HC200 and HC100 clustering levels to correspond to a long-term endemic persistence of \u003cem\u003eSalmonella\u003c/em\u003e clones. In the study reported here, access to location data (GPS co-ordinates of postcode centroids) for the sources of the French and Swiss isolates made it possible to refine the geographic distributions of the HC200 and HC100 clusters. Most of the isolates were obtained from cases of human infection, but the observed spatial distribution was consistent with long-term endemic persistence and limited migration between subpopulations. This finding provides direct evidence that different \u003cem\u003eS\u003c/em\u003e. Napoli phylogenetic clades establish stable, local endemic populations. Furthermore, our phylogeographic analyses confirmed that \u003cem\u003eS\u003c/em\u003e. Napoli lineages circulate locally between animals, humans, and the environment, consistent with an environmental origin (i.e., wildlife) of \u003cem\u003eS\u003c/em\u003e. Napoli salmonellosis. These findings suggest that the natural niche of \u003cem\u003eS.\u003c/em\u003e Napoli consists of many local and isolated patches. The local environment appears to be a key determinant of the transmission of this enteric pathogen to humans.\u003c/p\u003e \u003cp\u003eIn addition, despite the observed high level of genetic diversity, AMR determinants were found to be rare in \u003cem\u003eS.\u003c/em\u003e Napoli and the ESBL or carbapenemase resistance traits did not seem to spread in the \u003cem\u003eS.\u003c/em\u003e Napoli local population. The carbapenemase-producing isolate (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e) is noteworthy, as carbapenemase production has rarely been reported in \u003cem\u003eSalmonella\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The presence of the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e resistance gene could be linked to the patient\u0026rsquo;s clinical history. The repertoire of metal-and-biocide tolerance genes consists of 109 core genes and only six accessory genes underlying arsenic tolerance. The \u003cem\u003eS\u003c/em\u003e. Napoli core metal-and-biocide resistome is similar to those of serotypes Enteritidis, Typhimurium and Typhi, but \u003cem\u003eS\u003c/em\u003e. Napoli does not harbour any of the other accessory resistome genes detected in Typhimurium or Typhi (\u003cem\u003emer\u003c/em\u003e, \u003cem\u003eoqx, pco\u003c/em\u003e, \u003cem\u003esil, ter\u003c/em\u003e). Overall, resistance gene content is therefore consistent with an environmental origin of the \u003cem\u003eS\u003c/em\u003e. Napoli population, relatively spared from the influence of the agrifood supply chain, with its antibiotic-, biocide-, or metal-enriched environments.\u003c/p\u003e \u003cp\u003eOur comparative analysis revealed that pan-genome structure primarily mirrored phylogenetic clustering rather than the source from which the isolate was acquired. Thus, any detectable molecular signature of adaptation would be more likely to be related to the local ecosystem than the biological source of the isolate. The repertoire of pathogenicity islands and virulence factors \u0026mdash; including fimbrial and non-fimbrial adhesins, toxins and secretion systems \u0026mdash; provides an initial indication of the potential local adaptation of lineages and sublineages to their specific environmental niches. For instance, \u003cem\u003eS\u003c/em\u003e. Napoli harbors six core pathogenicity islands (SPI-1, -2, -4, -9, -12, -18), five accessory pathogenicity islands (SPI-3, -5, -6, -11 and \u0026minus;\u0026thinsp;13), and 151 virulence factors (VFDB), 88% of which are core determinants. Only a few candidate genes for adaptation to the local environment were identified in our pan-genome analysis: the absence of the \u003cem\u003ebcf\u003c/em\u003e operon encoding fimbrial adhesion determinants from the HC900_1450 and HC900_107023 lineages, the presence of SPI-6 and the \u003cem\u003esaf\u003c/em\u003e operon in HC900_1543c, and the presence of \u003cem\u003esseI\u003c/em\u003e and absence of \u003cem\u003estdB and stbC\u003c/em\u003e in HC900_1450.\u003c/p\u003e \u003cp\u003eThe cgMLST hierarchical clustering analysis confirmed that \u003cem\u003eS.\u003c/em\u003e Napoli was a monophyletic serotype belonging to section Typhi of subspecies \u003cem\u003eS. enterica enterica\u003c/em\u003e clade A\u003csup\u003e17,19,20\u003c/sup\u003e. Surprisingly, \u003cem\u003eS\u003c/em\u003e. Napoli was identified at superlineage cgMLST HC2000_1289 clustering level rather than the usual cgMLST HC900 clustering level for serotypes\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, which is coherent with a vastly distributed environmental niche from which animal and human cases emerge sporadically, rather than localised farms or healthcare foci. Moreover, \u003cem\u003eS.\u003c/em\u003e Napoli is closely related to two environmentally sourced serotypes also identified at superlineage clustering level: Veneziana (HC2000_12926), present in Spain, France, Italy (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://atlas.ecdc.europa.eu/public/\u003c/span\u003e\u003cspan address=\"https://atlas.ecdc.europa.eu/public/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Switzerland\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and Mississippi (clade A; HC2000_4338). This last serotype is of increasing public health concern in the US, Australia and New Zealand\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The Mississippi and Napoli serotypes also have a number of epidemiological and genetic features in common, such as the scarcity of AMR determinants\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, presence in non-urban environments and in wild fauna, and marked seasonality\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e associated with a pronounced phylogeographic pattern\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Furthermore, the population structure of \u003cem\u003eS.\u003c/em\u003e Napoli observed in neighbouring European countries resembles that described for the Mississippi serotype in the southeastern US, and this strong phylogeographic profile may be a remnant of the natural ecology of \u003cem\u003eSalmonella\u003c/em\u003e (i.e., that which prevailed before the era of agribusiness).\u003c/p\u003e \u003cp\u003eIn Europe, the geographic distributions of \u003cem\u003eS.\u003c/em\u003e Napoli and \u003cem\u003eS.\u003c/em\u003e Veneziana partly overlap, as demonstrated by the isolation of both serotypes from Italian wild boars\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and from the intestinal contents of Italian lizards\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (five \u003cem\u003eS\u003c/em\u003e. Napoli isolates sequenced in the framework of this study were from these lizards). Consistent with this spatial overlap, our genomic analyses revealed multiple, independent horizontal gene transfer events for determinants of pathogenicity (SPI-1, SPI-5) and immunity (CRISPR system) between \u003cem\u003eS\u003c/em\u003e. Napoli and \u003cem\u003eS\u003c/em\u003e. Veneziana, suggesting that these European serotypes either currently occupy or have historically occupied overlapping ecological niches.\u003c/p\u003e \u003cp\u003eFinally, the broadly used MLST7 scheme does not capture the diversity of the \u003cem\u003eS\u003c/em\u003e. Napoli population. As illustrated by the paraphyly of ST474 within the Italian diversity of \u003cem\u003eS\u003c/em\u003e. Napoli in a previous study\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, our analysis confirmed that ST subdivisions coincide poorly with cgMLST HC900 or HC400 phylogenetic divisions. The use of STs to distinguish between \u003cem\u003eS\u003c/em\u003e. Napoli lineages should therefore be strongly discouraged; instead, we recommend using the cgMLST scheme or establishing specific phylogenies including the 13 complete genomes representative of \u003cem\u003eS\u003c/em\u003e. Napoli.\u003c/p\u003e \u003cp\u003eIn conclusion, source attribution for \u003cem\u003eS\u003c/em\u003e. Napoli infections is essential for the development of effective prevention and control measures for this infection, which remains an emerging enigma, as first described by Fisher \u003cem\u003eet al.\u003c/em\u003e\u003csup\u003e4\u003c/sup\u003e in 2009. Improving our understanding of the epidemiology of \u003cem\u003eS\u003c/em\u003e. Napoli and its recent rise in Europe will require a One-Health approach. Case-control studies and substantial sampling of potential sources, such as the wildlife, in a defined geographic area with a high prevalence of the disease and well-characterised ecosystems are required to identify the risk factors associated with the disease and the nature of the bacterial reservoirs, respectively. In addition, the accumulation of international data over the medium and long term, and the acquisition of genomic data, will provide greater insight into the geographic distribution of this infection and the diversity and genetic evolution of the pathogen. By clarifying the population structure and phylogeographic characteristics of this transborder pathogen, and by providing analytical tools, this work constitutes a first step towards elucidating the relationships between sporadic indigenous infections of human origin and the environment.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was based exclusively on bacterial isolates and associated metadata, including, in particular, 989 isolates of human origin obtained from national reference laboratories for \u003cem\u003eSalmonella\u003c/em\u003e at the following institutions: Institut Pasteur (\u003cem\u003en\u003c/em\u003e = 684, including one \u003cem\u003eS.\u003c/em\u003e Veneziana), Instituto de Salud Carlos III (\u003cem\u003en\u003c/em\u003e = 34), Istituto Superiore di Sanità of Rome (\u003cem\u003en\u003c/em\u003e = 103), and University of Zurich (\u003cem\u003en \u003c/em\u003e= 169). The Institut Pasteur isolates were collected and stored by the French National Reference Centre for \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eShigella\u003c/em\u003e and \u003cem\u003eSalmonella \u003c/em\u003e(FNRC-ESS) with the approval of the French National Commission for Data Protection and Liberties (‘\u003cem\u003eCommission Nationale Informatique et Libertés (CNIL\u003c/em\u003e)’; approval number 1474659). The isolates from all the other institutions were acquired under the corresponding national mandates for laboratory-based surveillance of salmonellosis in line with local laws and regulations. Metadata anonymity was strictly maintained: data were limited to year/country/postcode of the laboratory performing the isolation (together with the postcode of the place of residence for the patient in 80% of cases) and international travel history, with no information allowing identification of the person included. As a result, neither informed consent nor approval from an ethics committee was required, given that this was not a study performed on human participants. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial isolates and metadata\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analysed 1,320 \u003cem\u003eS\u003c/em\u003e. Napoli isolates from human (\u003cem\u003en\u003c/em\u003e = 1,088), animal (\u003cem\u003en\u003c/em\u003e = 60, including 28 mammals, 16 gastropods and 5 reptiles), food (\u003cem\u003en\u003c/em\u003e = 25), environmental (\u003cem\u003en\u003c/em\u003e = 139) and unknown (\u003cem\u003en\u003c/em\u003e = 8) sources. These isolates were collected in France (\u003cem\u003en\u003c/em\u003e = 771, including 2 from Monaco and 2 from travellers returning from Italy), Italy (\u003cem\u003en\u003c/em\u003e = 319), Switzerland (\u003cem\u003en\u003c/em\u003e = 181), and Spain (\u003cem\u003en\u003c/em\u003e = 48) (Supplementary Data 1). These isolates were obtained by the FNRC-ESS, Institut Pasteur, Paris, France (\u003cem\u003en\u003c/em\u003e = 699), Laboratorio de Referencia e Investigación en Enfermedades Bacterianas Transmitidas por Alimentos, Instituto de Salud Carlos III, Madrid, Spain (\u003cem\u003en\u003c/em\u003e = 48), Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy (\u003cem\u003en\u003c/em\u003e = 135), and National Reference Laboratory (NRL) for Enteropathogens and \u003cem\u003eListeria\u003c/em\u003e, Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Switzerland (\u003cem\u003en \u003c/em\u003e= 181), French National Reference Laboratory (NRL) for Salmonella, Anses, Ploufragan, France (\u003cem\u003en \u003c/em\u003e= 51), and \u003cem\u003eSalmonella\u003c/em\u003e and \u003cem\u003eListeria\u003c/em\u003e Unit (SEL), Anses, Maisons-Alfort, France (\u003cem\u003en \u003c/em\u003e= 31). We included two additional isolates: isolate 142214 from the UK Health Security Agency (UKHSA; ENA Biosample accession no SAMN04600129) as it was the only representative of cgMLST HC900_1289, and isolate 202208589 provided after the study period by the FNRC-ESS as a representative of the rare HC900_63054 cluster, for which we performed long-read sequencing (see the corresponding section). For each isolate, detailed metadata are provided in Supplementary Data 1, including isolation date, geographic origin (country, region, subregion, postcode), biological sample type, and travelling information, when available. All French isolates from humans were obtained via the national surveillance programme, which operates through a voluntary network of clinical laboratories located throughout France (mainland France and overseas regions)\u003cem\u003e. \u003c/em\u003eEach isolate and the basic related metadata were sent to the FNRC-ESS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShort-read sequencing, analysis and \u003cem\u003ede novo\u003c/em\u003e assemblies \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 1,145 genome sequences of \u003cem\u003eS\u003c/em\u003e. Napoli were generated in this study. Sequencing libraries were prepared with the Nextera XT DNA library preparation kit (Illumina, San Diego, CA, USA) and sequenced on the NextSeq 500 platform (\u003cem\u003eIllumina\u003c/em\u003e) as 2x150 bp paired-end reads. Raw read quality was assessed with FastQC\u003csup\u003e40\u003c/sup\u003e v.0.11.9 (https://github.com/s-andrews/FastQC) and we checked for the absence of contamination with Kraken2 (ref.\u003csup\u003e41\u003c/sup\u003e) v.2.1.1 (https://github.com/DerrickWood/kraken2) (\u0026gt; 95% of reads originated from \u003cem\u003eSalmonella\u003c/em\u003e enterica). Reads passing the initial quality control steps were filtered and quality-trimmed with FqCleanER v21.06 (https://gitlab.pasteur.fr/GIPhy/fqCleanER; options: -q 15 -l 50 -p 50). \u003cem\u003eDe novo\u003c/em\u003e assemblies were generated from raw reads with fq2dna/21.06 (at https://gitlab.pasteur.fr/GIPhy/fq2dna; strategy B; default settings). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerotyping \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIsolates (\u003cem\u003en\u003c/em\u003e = 713) obtained in Spain, Italy, Switzerland and before 2017 in France were serotyped using the conventional serotyping method (\u003cem\u003eS.\u003c/em\u003e Napoli antigenic formula \u003cu\u003e1\u003c/u\u003e,9,12:l,z13:e,n,x). The other isolates (\u003cem\u003en\u003c/em\u003e = 607) were only typed with an \u003cem\u003ein silico\u003c/em\u003e serotyping procedure: the O-antigen was determined using a fast kmer-alignment (kma v.1.4.14, https://github.com/genomicepidemiology/kma; coverage ≥65% and identity ≥98%) of Illumina reads against theO9 reference sequence within the \u003cem\u003erfb \u003c/em\u003ecluster (\u003cem\u003eS\u003c/em\u003e. \u003cem\u003eenterica\u003c/em\u003e serotype Enteritidis strain P125109; GenBank accession no. AM933172.1; co-ordinates 2,162,790-2,184,501); the H1 (\u003cem\u003efliC\u003c/em\u003e) and H2 (\u003cem\u003efljB\u003c/em\u003e) flagellins were determined with the BLASTN algorithm\u003csup\u003e42\u003c/sup\u003e (blast+ v.2.16.0; query coverage ≥75%, nucleic acid sequence identity ≥99%) on assemblies against \u003cem\u003eS\u003c/em\u003e. Napoli Nap72-2 reference sequences for \u003cem\u003efliC\u003c/em\u003e (GenBank accession no. CP163475; co-ordinates 2866177-2867679) and \u003cem\u003efljB\u003c/em\u003e (GenBank accession no. CP163475; co-ordinates 3,242,735-3,244,240). This \u003cem\u003ein silico\u003c/em\u003e serotyping procedure was applied to the 1,320 isolates of our dataset. For the analyses of \u003cem\u003efliC\u003c/em\u003e and \u003cem\u003efljB\u003c/em\u003e sequences, we performed an \u003cem\u003ein silico\u003c/em\u003e PCR on short-read assemblies and aligned sequences with Mega12 (ref.\u003csup\u003e43\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMLST and core genome MLST (cgMLST) analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNewly generated raw Illumina paired-end reads (\u003cem\u003en\u003c/em\u003e = 1,145) from \u003cem\u003eS\u003c/em\u003e. Napoli were uploaded to EnteroBase (https://enterobase.warwick.ac.uk), which already contained the published genomes. The platform’s automated pipeline assigned sequence types (STs) and eBurst groups (eBGs) to each genome according to the Achtman MLST7 scheme (\u003cem\u003earoC\u003c/em\u003e,\u003cem\u003e dnaN\u003c/em\u003e,\u003cem\u003e hemD\u003c/em\u003e,\u003cem\u003e hisD\u003c/em\u003e,\u003cem\u003e purE\u003c/em\u003e,\u003cem\u003e sucA\u003c/em\u003e,\u003cem\u003e thrA\u003c/em\u003e)\u003csup\u003e22\u003c/sup\u003e. The pipeline also determined core genome MLST (cgMLST) profiles with the Hierarchical Clustering (HierCC V1 (ref.\u003csup\u003e44\u003c/sup\u003e); https://github.com/zheminzhou/pHierCC) algorithm and allele diversity at the 3,002 loci of \u003cem\u003eSalmonella\u003c/em\u003e cgMLST scheme V2 (ref.\u003csup\u003e23\u003c/sup\u003e) (https://www.cgmlst.org/ncs/1000/schema/Senterica2035/). This EnteroBase \u003cem\u003eSalmonella \u003c/em\u003ecgMLST scheme assigns bacterial genomes to single-linkage hierarchical clusters (HCs) at 13 fixed levels of resolution (HC0 HC2, HC5, HC10, HC20, HC50, HC100, HC200, HC400, HC900, HC2000, HC2600 and HC2850) from high-resolution clusters (with no allelic differences for HC0) to low-resolution clusters (with up to 2,850 allelic differences for HC2850). If a genome is equidistant from two existing genotypes, EnteroBase cluster assignment prioritises the earliest database entry. The cgMLST trees were generated from via the EnteroBase website, with the NINJA\u003csup\u003e45\u003c/sup\u003e neighbour-joining algorithm (https://wheelerlab.org/software/ninja/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComplete genome circularisation \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplete circular genomes were generated for 13 isolates representative of the observed genetic diversity. Bacterial cultures were grown from single colonies in 10 mL of Trypto-casein soy broth (Bio-Rad 355345B) incubated overnight at 37°C with shaking at 200 rpm\u003cem\u003e. \u003c/em\u003eGenomic DNA was extracted from cell pellets with Genomic-tip 100/G columns and the Genomic DNA Buffer set (Qiagen), in accordance with the manufacturer’s instructions. For the \u003cem\u003eS.\u003c/em\u003e Napoli Nap72-2isolate, GATC Biotech (now part of Eurofins Scientific) generated PacBio RSII long-read sequences and performed \u003cem\u003ede novo\u003c/em\u003e assembly according to the hierarchical genome-assembly process (HGAP; https://github.com/jtchien0925/PacBio_HGAP_assembly)\u003csup\u003e46\u003c/sup\u003e. We subsequently polished the assembly, using Illumina short reads and polypolish\u003csup\u003e47\u003c/sup\u003e (https://github.com/rrwick/Polypolish) then pilon\u003csup\u003e48\u003c/sup\u003e v1.23 (https://github.com/broadinstitute/pilon) software. For the remaining 12 isolates (11\u003cem\u003e S.\u003c/em\u003e Napoli and 1\u003cem\u003e S. \u003c/em\u003eVeneziana; Supplementary Data 1), Oxford Nanopore Technology (ONT) libraries were generated from total DNA with the SQK-LSK109 and EXP-NBD104/114 kits, according to the ONT procedure “\u003cem\u003eNative Barcoding Amplicons protocol” \u003c/em\u003eversion 14 Aug 2019 (dx.doi.org/10.17504/protocols.io.bgzxjx7n). Libraries were sequenced on R9.4.1 flow cells with a Mk1C MinION\u003csup\u003eTM\u003c/sup\u003e device and bases were called for the reads with Guppy\u003csup\u003e3 \u003c/sup\u003e(v5.0.13 or v6.4.2; https://nanoporetech.com/software/other/guppy). Long reads underwent filtering for quality with filtlong v0.2.1 (https://github.com/rrwick/Filtlong/) and \u003cem\u003ed\u003c/em\u003e\u003cem\u003ee novo\u003c/em\u003e genome assemblies were generated with Trycycler\u003csup\u003e49\u003c/sup\u003e v0.5.0 (https://github.com/rrwick/Trycycler), using the default parameters. For each genome, long reads were subsampled into 12 sets. Four sets were assembled with Flye\u003csup\u003e50\u003c/sup\u003e v2.9 (https://github.com/mikolmogorov/Flye), four with raven\u003csup\u003e51\u003c/sup\u003e v1.6.0 (https://github.com/lbcb-sci/raven) and four with miniasm v0.3 (https://github.com/lh3/miniasm) followed by Minipolish\u003csup\u003e47\u003c/sup\u003e v0.1.3 (https://github.com/rrwick/Minipolish). Consensus assemblies underwent three sequential polishing steps: one ONT read polishing with medaka v1.4.4 (https://github.com/nanoporetech/medaka), followed by a primary Illumina read polishing with polypolish\u003csup\u003e47\u003c/sup\u003e v0.5.0 and a final Illumina read polishing with pilon\u003csup\u003e48\u003c/sup\u003e v1.23. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic analyses \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhylogenetic analyses were performed independently with two reference chromosomes: Nap72-2 (\u003cem\u003eS\u003c/em\u003e. Napoli, GenBank accession no. CP163475) and 164K (\u003cem\u003eS.\u003c/em\u003e Veneziana, GenBank accession no. CP163496). Core genome alignments were generated by mapping Illumina paired-end reads to each reference genome with Snippy v4.6.0 (https://github.com/tseemann/snippy), using the following parameters: minimum mapping quality of 60, minimum base quality of 13, minimum read coverage of 4, and minimum allele proportion of 75%. Repetitive regions, including insertion sequence (IS) elements, prophages and rRNA, were identified in the reference genome and masked in the corresponding alignments. Recombinant regions were subsequently identified and masked with Gubbins\u003csup\u003e52\u003c/sup\u003e v3.2.0 (https://github.com/nickjcroucher/gubbins) The resulting alignments were used to infer maximum likelihood (ML) phylogenies with RAxML\u003csup\u003e53\u003c/sup\u003e v8.2.12 (https://github.com/stamatak/standard-RAxML) under the GTRGAMMA model with 1,000 bootstrap replicates. The tree containing the 164K outgroup was used to establish the root and clade structure for \u003cem\u003eS\u003c/em\u003e. Napoli, guiding the rooting of the final ML tree comprising exclusively \u003cem\u003eS\u003c/em\u003e. Napoli genomes. We built ML trees for specific genomic segments by selecting the corresponding genomic positions in the SNIPPY alignments before running RAxML v8.2.12 as described above. All trees were visualized and annotated with Interactive Tree of Life (iTOL\u003csup\u003e54\u003c/sup\u003e v6; https://itol.embl.de/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResistance gene and plasmid analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResFinder\u003csup\u003e55\u003c/sup\u003e v4.0.1 (https://github.com/genomicepidemiology/resfinder) was used to identify acquired antibiotic resistance genes (ARGs), and to detect mutations in chromosomal genes encoding antimicrobial resistance in \u003cem\u003ede novo\u003c/em\u003e genome assemblies. Plasmid replicons were identified with PlasmidFinder\u003csup\u003e56\u003c/sup\u003ev2.1.1 (https://github.com/genomicepidemiology/plasmidfinder). Results were filtered with \u0026gt;90% identity and \u0026gt;80% coverage thresholds. Six of the 13 complete genomes carried one or two plasmids, none harbouring ARG. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacMet analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the identification of genes conferring resistance to biocides and metals, protein sequences from 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes (annotated with Bakta\u003csup\u003e57\u003c/sup\u003e v1.5.0; https://github.com/oschwengers/bakta) were used to query the BacMet\u003csup\u003e26\u003c/sup\u003e v2.0 database (https://github.com/ZhihaoXie/BacMet), a curated repository of 753 experimentally confirmed resistance genes (including 125 genes identified in \u003cem\u003eEscherichia\u003c/em\u003e coli), with the BLASTP algorithm (BLAST+\u003csup\u003e58\u003c/sup\u003e v2.16.0). We retained hits meeting the following criteria: minimum query coverage of 84% and amino-acid sequence identity of 75%. When multiple hits were obtained for the same subject protein, only the best hit was retained. We assessed the distribution of resistance genes across \u003cem\u003eS\u003c/em\u003e. Napoli lineages by searching for genes identified in the complete genomes within the Panaroo pan-genome output. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePan-genome analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs the quality of genome assemblies can significantly affect pan-genome description, we excluded genome assemblies of more than 200 contigs from the analysis. Pan-genome analysis was performed with Panaroo\u003csup\u003e59\u003c/sup\u003e v1.3.0 (https://github.com/gtonkinhill/panaroo), using the default parameters (sequence identity threshold of 0.98; length difference cutoff of 0.98) on assemblies previously annotated with Bakta v.1.5.0 (Supplementary Fig. 7, Supplementary Data 1). This analysis encompassed 1,191 isolates and accounted for 11 of the 12 \u003cem\u003eS\u003c/em\u003e. Napoli cgMLST HC900 clusters. Pan-genome openness was evaluated by calculating the Heap’s law alpha coefficient (alpha ≤ 1, open; alpha \u0026gt; 1, closed) from a gene presence-absence matrix with 2,000 permutations (micropan\u003csup\u003e60\u003c/sup\u003e v.2.1 R package; https://CRAN.R-project.org/package=micropan). We improved the assignment of accessory genes with prophages or plasmids by performing pan-genome analysis on 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes annotated with Bakta. Prophages were delineated with PHASTEST\u003csup\u003e61\u003c/sup\u003e (https://phastest.ca/). Gene content variation was further investigated to determine whether isolates from the same source, geographic origin, or cgMLST cluster had similar accessory gene contents. Pairwise distances between the gene contents of all 1,191 genomes (10,666 genes) were calculated with the Barnes-Hut t-SNE algorithm with a gradient accuracy of 0.5 (PANINI\u003csup\u003e62\u003c/sup\u003e; https://gitlab.com/cgps/panini/bhtsne). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePathogenicity island (SPI) and virulence factor analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVirulence factors were initially identified in the 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes with VFanalyzer, the online tool provided by the virulence Factors DataBase (VFDB\u003csup\u003e28,29\u003c/sup\u003e (https://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi). Virulence factor distribution (presence/absence) was subsequently analysed across \u003cem\u003eS\u003c/em\u003e. Napoli populations (1,191 genomes) during pan-genome analysis (see dedicated section). We first screened for \u003cem\u003eSalmonella\u003c/em\u003e pathogenicity islands (SPIs) in the 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes, using the SPIFinder v2.0 database (https://cge.food.dtu.dk/services/SPIFinder/). We then used the 1,320 Illumina paired-end reads and kma\u003csup\u003e63\u003c/sup\u003e v1.4.14 (https://github.com/genomicepidemiology/kma; option 1t1, to force the retention of one match per query sequence) to assess the coverage of PAIDB\u003csup\u003e64\u003c/sup\u003e(http://www.paidb.re.kr/) sequences in the total set of isolates. SPI-18 (ref.\u003csup\u003e65\u003c/sup\u003e) (\u003cem\u003eS. \u003c/em\u003eNapoli strain Nap72-2; GenBank accession no CP163475; co-ordinates 1,455,055–1,456,801), and SPI-13 (ref.\u003csup\u003e66\u003c/sup\u003e) (\u003cem\u003eS. \u003c/em\u003eNapoli strain Nap72-2; GenBank accession no CP163475; co-ordinates 3,592,799-3,628,491) were added to the selected set of PAIDB sequences. Kma results were filtered to retain SPIs with at least three isolates with ≥50% template coverage and 70% nucleotide identity. The gene architecture of incomplete SPIs was investigated in the complete genomes from annotations or in the annotated genome assemblies when the SPI was not detected in the incomplete genomes. Type VI secretion system (T6SS) identity was confirmed with the SecreT6 web platform\u003csup\u003e67\u003c/sup\u003e (https://bioinfo-mml.sjtu.edu.cn/SecReT6/index.php).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClusters of Orthologous Groups (COG) classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 10,666 CDS identified during pan-genome analysis were submitted to the eggNOG-mapper-2.1 web interface\u003csup\u003e68\u003c/sup\u003e (http://eggnog-mapper.embl.de/). These CDS included 2,156 corresponding to genes with no known annotations. The remaining 8,583 genes were assigned to COG categories and analysed further. The enrichment index was calculated as the percentage of the core genome (core and soft) consisting of a COG divided by the percentage of the entire genome consisting of the same COG. Two-tailed Fisher’s exact tests were performed to determine the significance of differences. The log\u003csub\u003e2\u003c/sub\u003e fold-enrichment in core genes was calculated across COG functional categories, with a positive value implying that the core genome contained a larger than expected number of genes corresponding to the COG category concerned. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRISPR system and spacer analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA published \u003cem\u003eSalmonella\u003c/em\u003e CRISPR genomic array\u003csup\u003e30\u003c/sup\u003e and the BLASTN algorithm\u003csup\u003e42\u003c/sup\u003e were used to investigate CRISPR-associated gene content. The analysis was performed in two stages: first on the 13 complete \u003cem\u003eS\u003c/em\u003e. Napoli genomes and the 1 complete \u003cem\u003eS\u003c/em\u003e. Veneziana genome, with subsequent extension to the 1,320 \u003cem\u003eS\u003c/em\u003e. Napoli genome assemblies. Spacer content was determined for the 1,320 \u003cem\u003eS\u003c/em\u003e. Napoli genome assemblies with the \u003cem\u003eSalmonella\u003c/em\u003e-CRISPR-Typing\u003csup\u003e30\u003c/sup\u003e pipeline (https://github.com/C3BI-pasteur-fr/Salmonella-CRISPR-Typing/). The Napoli spacers were designated Nap\u003cem\u003ej\u003c/em\u003e for the CR1 array and NapB\u003cem\u003ej\u003c/em\u003e for the CR2 array, where \u003cem\u003ej\u003c/em\u003e represents a sequential number. A spacer differing by one or two nucleotides from an existing spacer was classified as a variant and designated Nap(B)\u003cem\u003ej\u003c/em\u003evar. We also investigated the CRISPR-gene and spacer content of cgMLST HC2600_104 with a set of 38 assemblies downloaded from EnteroBase (Supplementary Table 3) and corresponding to 19 serotypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaps and other graphic illustrations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe postcode of residence for human cases and the postcode of sampling location for all non-human sources (for five human cases on the islands of Noirmoutier or Ré for the postcode of residence was unknown, we used the postcode of the clinical laboratory) were available for 175 Swiss (95% human and 5% non-human) and 558 French (90% human and 10% non-human) isolates. The postcodes were transformed into Global Positioning System (GPS) co-ordinates based on the centroid of postcode area (GPS data; https://www.data.gouv.fr/datasets/base-officielle-des-codes-postaux/; https://www.swisstopo.admin.ch/fr/repertoire-officiel-des-localites). GPS metadata for the 43 northern Italian isolates were publicly available\u003csup\u003e18\u003c/sup\u003e. Maps and choropleth maps were drawn with the “maps”\u003csup\u003e69\u003c/sup\u003e and “ggplot2”\u003csup\u003e70\u003c/sup\u003e packages of R software and the official EU spatial delineation for basic regions (NUTS level 2, for Italian \u003cem\u003eregione\u003c/em\u003e and Swiss \u003cem\u003eGroßregions\u003c/em\u003e) and small regions (NUTS level 3: French \u003cem\u003edépartements\u003c/em\u003e and Spanish \u003cem\u003eprovincias\u003c/em\u003e) (https://ec.europa.eu/eurostat/fr/web/nuts). All figures were finalised with the open-source scalable vector graphics editor, Inkscape v0.92.5. (https://inkscape.org/release/inkscape-0.92.5/). Local genome architecture (CDS content) was visualised with the gggenes\u003csup\u003e71\u003c/sup\u003e v0.5.0 https://github.com/wilkox/gggenes and ggplot2 (ref.\u003csup\u003e72\u003c/sup\u003e) v3.4.2 packages of R93 v.4.1.2 (R Core Team, 2021). RAxML-NG phylogenies were visualised with Interactive Tree of Life (iTOL\u003csup\u003e54\u003c/sup\u003e v6; https://itol.embl.de/). \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Illumina sequence reads generated in this study were submitted to EnteroBase(available from: https://enterobase.warwick.ac.uk/species/senterica) and the European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena/) under study numbers PRJEB68323, PRJEB71958, PRJEB49424, PRJEB105765, PRJEB106318, PRJEB106484. All ENA accession numbers and EnteroBase barcodes are listed in Supplementary Data 1. The 13 complete genomes generated in this study were submitted to the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1052634 (Supplementary Data 1 and 2). An interactive version of the cgMLST GrapeTrees output shown in Figure 3 is available from https://enterobase.warwick.ac.uk/ms_tree/133265.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCODE AVAILABILITY \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe FqCleanER script (paired-end FASTQ files cleaning) can be found at https://gitlab.pasteur.fr/GIPhy/fqCleanER. The fq2dna script (genome \u003cem\u003ede novo\u003c/em\u003e assembly from raw paired-end FASTQ files) can be found at https://gitlab.pasteur.fr/GIPhy/fq2dna .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Magali Ravel, Véronique Guibert, Estelle Serre, Sylvie Issenhuth-Jeanjean, Louise Baugé, Claire Yvon, Annaelle Kerouanton, Herbert Hächler and all participating laboratories of the French, Swiss and Spanish \u003cem\u003eSalmonella\u003c/em\u003e surveillance networks. We thank Henriette de Valk, Nathalie Jourdan-Da Silva, Jean-Louis Pinsard, Alexandre Boissinot, Matthieu Berroneau, Roger Meek, Gilles Salvat for discussions. We thank Nigel Dyer and all the other EnteroBase curators.\u003c/p\u003e\n\u003cp\u003eThis research was funded by the \u003cem\u003eFondation Le Roch-Les Mousquetaires\u003c/em\u003e (to F.-X.W); \u003cem\u003eInstitut Pasteur\u003c/em\u003e (to F.-X.W); \u003cem\u003eSanté publique France\u003c/em\u003e (to F.-X.W); by the French Government’s \u003cem\u003eInvestissement d’Avenir\u003c/em\u003e programme, \u003cem\u003eLaboratoire d’Excellence\u003c/em\u003e ‘Integrative Biology of Emerging Infectious Diseases’ (grant no. ANR-10-LABX-62-IBEID to F.-X.W); and by the Institute of Health Carlos III (project Acción Estratégica de Salud Intramural (AESI); PI21CIII/00029)).\u003c/p\u003e\n\u003cp\u003eThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.H.-L., R.S., A.C., and F.-X.W designed the study. F.-X.W oversaw the study. L.V., G.B., L.B., V.L., L.FA., S.C.-S., M.C., M.P.G., S.H.-L., R.S., A.C., and F.-X.W selected and provided isolates or genomes with their basic metadata. M.A.-D., L.V., G.B., L.B., H.A., S. P-R, S.C.-S. subcultured the bacteria, performed phenotypic experiments, and extracted DNA. L.FR, L.FA., and F.-X.W. analysed and/or interpreted the data. L.FR. wrote the manuscript, with a major contribution from F.-X.W. All the authors contributed to the editing of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBruner, D. W. \u0026amp; Edwards, P. R. Two New Salmonella Types Belonging to Somatic Group D. \u003cem\u003eExperimental Biology and Medicine\u003c/em\u003e \u003cstrong\u003e58\u003c/strong\u003e, 289\u0026ndash;290 (1945).\u003c/li\u003e\n\u003cli\u003eBruner, D. W. \u0026amp; Joyce, B. J. 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(2023).\u003c/li\u003e\n\u003cli\u003eWickham, H. ggplot2: Elegant Graphics for Data Analysis. in (Springer-Verlag, New York, 2009).\u003c/li\u003e\n\u003cli\u003eZhou, Z. \u003cem\u003eet al.\u003c/em\u003e GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. \u003cem\u003eGenome Res.\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 1395\u0026ndash;1404 (2018).\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":"","lastPublishedDoi":"10.21203/rs.3.rs-8608855/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8608855/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe characterised the population structure of \u003cem\u003eSalmonella enterica\u003c/em\u003e serotype Napoli (\u003cem\u003eS.\u003c/em\u003e Napoli), an emerging European pathogen. We assembled a collection of 1,320 isolates obtained between 1945 and 2022 from diverse biological sources in Italy, Switzerland, France (regions of known endemicity) and a newly identified endemic area, Spain. Whole-genome analyses linked the rising incidence of \u003cem\u003eS.\u003c/em\u003e Napoli to a monophyletic serotype from core genome multilocus typing (cgMLST) superlineage HC2000_1289. The \u003cem\u003eS.\u003c/em\u003e Napoli population has considerable genetic diversity, strong spatial structuring, and a very low frequency of antimicrobial resistance determinants. Unlike successful non-typhoidal \u003cem\u003eSalmonella\u003c/em\u003e serotypes, for which globalisation has had a homogenising effect, \u003cem\u003eS.\u003c/em\u003e Napoli forms at least 15 distinct lineages isolated by geographic distance, each probably subject to local ecological adaptation. This comprehensive description of \u003cem\u003eS.\u003c/em\u003e Napoli populations complemented by 12 representative complete genomes provides a valuable resource for future source attribution and surveillance of this serotype.\u003c/p\u003e","manuscriptTitle":"Global population genomics of Salmonella enterica serotype Napoli, an emerging pathogen with an unusual epidemiologic pattern","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 13:06:17","doi":"10.21203/rs.3.rs-8608855/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":"b91b6855-0f35-4662-9f78-9fd70397dc13","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61238453,"name":"Biological sciences/Evolution/Population genetics/Genetic variation"},{"id":61238454,"name":"Biological sciences/Microbiology/Bacteria/Bacterial genomics"},{"id":61238455,"name":"Biological sciences/Microbiology/Policy and public health in microbiology"}],"tags":[],"updatedAt":"2026-01-21T11:42:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 13:06:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8608855","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8608855","identity":"rs-8608855","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}