Recent emergence of a multidrug-resistant Campylobacter coli lineage linked to poultry intensification in the Peruvian Amazon

Recent emergence of a multidrug-resistant Campylobacter coli lineage linked to poultry intensification in the Peruvian Amazon | 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 Recent emergence of a multidrug-resistant Campylobacter coli lineage linked to poultry intensification in the Peruvian Amazon Ben Pascoe, Evangelos Mourkas, Francesca Schiaffino, Maribel Olortegui, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8865396/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Campylobacter is a leading cause of bacterial gastroenteritis worldwide, with the highest burden among children in low- and middle-income countries (LMICs). Despite global significance, Campylobacter coli remains comparatively under-studied. Here we combine population genomics and phylodynamic analysis of 460 C. coli genomes from the Peruvian Amazon to investigate the emergence of a locally dominant, multidrug-resistant lineage. Genomes were obtained from children with gastroenteritis (n = 136) and asymptomatic carriage (n = 163) in Iquitos, Peru, alongside isolates from poultry in backyard (n = 29) and industrial systems (n = 60), pigs (n = 36), cattle (n = 15), and a small reference collection (n = 21). These genomes represented 102 multilocus sequence types (STs) spanning five distinct clonal complexes (CCs). The globally distributed ST-828 clonal complex accounted for most isolates, whereas a distinct lineage, ST-1150 CC, was significantly over-represented in paediatric diarrhoeal cases yet rare elsewhere globally. Time-scaled phylogenies showed that ST-1150 CC emerged and expanded rapidly from the 1980s, coinciding with intensification of poultry production in the region. Genomic antimicrobial-resistance profiling identified extensive acquired resistance to fluoroquinolones, macrolides, and tetracyclines, underpinned by conserved cmeB efflux-pump variants. Collectively, these findings strongly suggest that agricultural intensification and antimicrobial exposure have driven the ecological emergence and clonal success of a highly adapted C. coli lineage. This work illustrates how regional farming practices can shape bacterial evolution and resistance trajectories, underscoring the need for integrated One Health genomic surveillance to mitigate the spread of zoonotic pathogens that are global in scope. Health sciences/Diseases/Gastrointestinal diseases/Gastroenteritis Biological sciences/Microbiology/Bacteria/Bacterial genomics Biological sciences/Evolution/Phylogenetics Biological sciences/Ecology/Microbial ecology Campylobacter coli diarrhoea child health One health poultry intensification Figures Figure 1 Figure 2 Figure 3 Plain English Summary Campylobacter coli is an important cause of diarrhoea, especially among children in low- and middle-income countries. We discovered a bacterial lineage, ST-1150, that is common in the Peruvian Amazon but rarely seen elsewhere. By analysing hundreds of genomes, we show that this lineage emerged and expanded rapidly from the 1980s onwards, coinciding with the intensification of poultry farming. It carries multiple genes that make it resistant to several antibiotic classes, suggesting that agricultural antibiotic use has shaped its evolution. Our findings reveal how local farming practices and antimicrobial exposure can drive the emergence of new resistant bacterial lineages, underscoring the need for integrated surveillance of human and animal infections. Introduction Campylobacter species are among the leading causes of gastroenteritis worldwide, with the highest burden in low- and middle-income countries (LMICs), where repeated early-life infections contribute to malnutrition, stunting and impaired child development 1 – 9 . While Campylobacter jejuni dominates reported infections in high-income countries (HIC), Campylobacter coli accounts for a substantial proportion of cases in LMICs 10 – 16 . Despite its clinical and epidemiological importance, C. coli remains comparatively under-studied, and the ecological and evolutionary processes shaping its persistence in endemic regions are poorly understood. The World Health Organization’s Foodborne Disease Burden Epidemiology Reference Group estimates that bacterial foodborne pathogens impose an annual economic burden exceeding $ 95 billion USD in LMICs 1 , underscoring the need to elucidate how local agricultural and antimicrobial practices influence the emergence of pathogenic lineages. Most Campylobacter genome datasets originate from HICs and may not capture the diversity and dynamics circulating in tropical, high-transmission environments 11 , 17 – 19 . Recent surveillance in LMICs has revealed an increasing prevalence of multidrug-resistant (MDR) C. coli , often associated with unregulated antibiotic use in livestock production and limited biosecurity 15 , 16 , 20 – 22 . These pressures can generate ecological niches favouring the evolution and persistence of locally adapted clones. Understanding how such lineages arise and disseminate is essential to designing effective One Health interventions. The Peruvian Amazon provides a powerful model for investigating these processes. Community-based surveillance in Iquitos has shown that Campylobacter carriage among children is nearly universal by two years of age, frequently asymptomatic yet associated with enteropathy – 25 . Over recent decades, the region has experienced rapid urban expansion 23 , 24 , increased poultry consumption 25 , and the growth of both backyard and industrial poultry systems, accompanied by widespread antimicrobial use 26 , 27 . Such conditions provide ideal ecological opportunities for bacterial adaptation and transmission between humans and livestock. Domestic chickens across South America are genetically diverse, reflecting historical admixture between European and Asian domestic lineages introduced through trade and colonial expansion 28 . Although backyard poultry production remains largely informal in Iquitos, there is mixing between breeds cohabiting in open environments and sharing feed and water sources with other livestock species. These conditions provide fertile ground for bacterial exchange and selection, shaping the genetic structure of circulating Campylobacter lineages. At a global scale, C. coli is composed of three deeply rooted clades that have undergone extensive introgression with C. jejuni , particularly within the ST-828 clonal complex (CC828) 29 – 32 . This clonal complex comprises host-generalist lineages capable of colonising livestock, poultry, and humans, enabling frequent interspecies transmission 33 – 36 . However, the extent to which local agricultural intensification and antimicrobial selection pressures drive the emergence of novel C. coli lineages in endemic LMIC settings remains unclear. Here, we integrate population-genomic and phylodynamic analyses of 460 C. coli genomes from the Peruvian Amazon to investigate the ecological and evolutionary drivers of lineage emergence. Our dataset includes isolates from children with gastroenteritis and asymptomatic carriage, alongside samples from poultry, pigs, and cattle, providing a comprehensive view of the local C. coli gene pool. We identify a distinct lineage, ST-1150 CC, that is significantly over-represented in paediatric diarrhoeal cases yet rare globally. Time-scaled phylogenies reveal that this lineage emerged and expanded rapidly from the 1980s coinciding with intensification of poultry production and antibiotic use in the region. Genomic antimicrobial-resistance profiling demonstrates extensive acquired resistance, underpinned by conserved cmeB efflux-pump variants. Together, these findings provide a mechanistic view of how agricultural intensification and antimicrobial exposure can drive the ecological emergence and clonal success of multidrug-resistant Campylobacter lineages. By linking local environmental change to pathogen evolution, this study highlights the need for integrated One Health genomic surveillance to detect and mitigate the emergence of zoonotic pathogens in rapidly changing food production systems. Results Peruvian C. coli isolates cluster within agriculture-associated clades and reveal a locally dominant lineage We analysed 460 C. coli genomes collected from the Peruvian Amazon, comprising isolates from children with gastroenteritis (n = 136), asymptomatic carriage (n = 163), poultry (backyard = 29; commercial = 60), pigs (n = 36), cattle (n = 15), and a small reference panel (n = 21; Fig. 1 A; Supplementary table S1 ). Comparison with global reference genomes 29 , 31 – 33 , 37 , 38 revealed that all Peruvian isolates clustered within the agriculture-associated C. coli clade 1, with no representatives of the ancestral, unintrogressed clades 2 or 3 (Fig. 1 B) We identified 102 multilocus sequence types (ST) spanning five clonal complexes (CC), dominated by ST-828 CC (n = 343, 75%) and the locally prevalent ST-1150 CC (n = 96, 21%; Supplementary table S1 ). Although ST-1150 CC is globally rare, detected in 25,000 C. coli genomes in PubMLST (accessed 09/2024), it accounted for 23% (69/299) of human isolates in this study and was significantly enriched in diarrhoeal cases compared to asymptomatic carriage (47/136 [35%] vs 22/163 [14%]; χ² = 17.36, p = 3.1 × 10⁻⁵; Fig. 1CD ). Within ST-828 CC many individual STs were not monophyletic, often clustering in two or more distinct parts of the phylogeny (e.g. ST-825 and ST-10234; Supplementary figure S1 ). Peruvian C. coli isolates represent a distinct local gene pool Across the full dataset, C. coli exhibited extensive accessory genome plasticity, consistent with frequent horizontal gene transfer ( Supplementary Tables S3-4 ). However, ST-1150 CC isolates formed a tight, well-supported cluster distinct from the more heterogeneous ST-828 CC ( Supplementary Figure S2 A ). Pangenome accumulation analyses stratified by host source revealed broadly similar trajectories across reservoirs, indicating that differences in accessory genome structure reflected lineage-specific clustering rather than host-exclusive gene acquisition ( Supplementary Figure S2 B ). Accessory genome clustering showed that ST-1150 CC isolates grouped almost exclusively with poultry-derived isolates, whereas ST-828 CC genomes shared accessory gene content with both poultry- and swine-associated isolates ( Supplementary Figure S2 C ). These findings support the existence of a locally structured C. coli gene pool in the Peruvian Amazon and indicate a strong epidemiological association between ST-1150 CC and poultry production systems, with limited recent gene flow from other livestock reservoirs. Phylodynamic reconstruction indicates recent emergence and rapid expansion of ST-1150 CC Time-scaled phylogenetic reconstruction of ST-1150 CC revealed a relatively recent common ancestry, with most diversification occurring during the late 20th century (Fig. 2 A). Root-to-tip regression revealed a significant positive association between genetic divergence and sampling time (R² = 0.28, p < 1 × 10⁻⁴), indicating sufficient temporal signal to support molecular-clock inference ( Supplementary Fig. 3A ). Under a mixed-gamma relaxed molecular clock, the most recent common ancestor (MRCA) of ST-1150 CC was dated to a posterior median of 1974 (95% highest posterior density [HPD]: 1952–1990), placing its emergence in the latter half of the twentieth century. While uncertainty around the MRCA date was substantial ( Supplementary Fig. 3B ), the inferred timing consistently preceded a period of major demographic and agricultural change in the Peruvian Amazon 23 ( Supplementary Tables S5-6 ). Skyline-based phylodynamic analyses indicated a sustained increase in effective population size beginning approximately in the 1980s and continuing into the early 2000s (Fig. 2 B), coinciding with periods of rapid growth in regional poultry production. (Fig. 2 C). Notably, the inferred demographic history was characterised by gradual and sustained population growth rather than sharp, punctuated expansions. Consistent with this, CaveDive analyses showed highest posterior support for models with no discrete expansion events (posterior probability ≈ 70%), with moderate support for a single expansion (≈ 30%) and negligible support for multiple expansion events ( Supplementary 3BCD ). Together, these results support a model in which ST-1150 CC underwent progressive demographic expansion associated with agricultural intensification, rather than abrupt population bursts driven by single introduction events. Consistent with this interpretation, global contextualisation using PubMLST revealed that non-human ST-1150 CC isolates have been almost exclusively sampled from poultry sources, predominantly from commercial production systems, whereas ST-828 CC displays a much broader host range spanning poultry, swine, cattle, and humans (Fig. 2 D). ST-1150 CC exhibits a dense and conserved multidrug-resistance architecture Phenotypic antimicrobial susceptibility testing revealed high levels of resistance across the dataset, with particularly elevated multidrug resistance (MDR) in ST-1150 CC ( Supplementary Table S7 ). Resistance to ciprofloxacin was common in both ST-1150 CC (72.6%) and ST-828 CC (81.4%), while azithromycin resistance was detected in approximately 30% of isolates from both clades (Fig. 3 A). However, multidrug-resistance (MDR), defined as non-susceptibility to ≥ 3 antibiotic classes, was significantly more frequent in ST-1150 CC (56.1%) than in ST-828 CC (40.1%; χ² = 5.99, p = 0.014) (Fig. 3 B). Genomic screening corroborated these findings: 96% of ST-1150 CC isolates carried determinants for resistance to at least one antibiotic class, and 71% met the genomic MDR definition ( Supplementary Table S8 ). Common determinants included the tetracycline resistance gene tet(O) (95%), β-lactamase bla OXA−61 (92%), the aminoglycoside cluster aadE-sat4-aphA3 (68%), and the gyrA T86I mutation (> 80%) (Fig. 3 C; Supplementary Figure S5 ). Macrolide resistance was linked to the 23S rRNA A2075G mutation and the cmeABC efflux operon, which was present in all isolates. Notably, ST-1150 CC exhibited markedly reduced allelic diversity in cmeB compared with ST-828 CC, with fixation of a resistance-enhanced cmeB variant previously linked to increased efflux efficiency ( Supplementary Figure S6 ). This pattern is consistent with strong selection acting on a multidrug-resistance phenotype during lineage expansion and suggests consolidation of resistance determinants within a clonal genomic background. Virulence gene content does not indicate lineage-specific increases in intrinsic pathogenicity Screening against the Virulence Factors Database (VFDB) showed that both ST-1150 CC and ST-828 CC carried the canonical Campylobacter virulence determinants, including cdtABC , flagellar motility genes ( flaA/B ), and iron-acquisition loci ( Supplementary Table S9 ). ST-1150 CC exhibited a narrower but more conserved virulence gene repertoire relative to the genetically diverse ST-828 CC ( Supplementary Figure S7 A ), consistent with reduced genomic diversity following recent clonal expansion. Integration of clinical metadata revealed that ST-1150 CC was significantly over-represented among isolates from children with diarrhoeal disease; however, no evidence of increased disease severity was observed based on MAL-ED diarrhoeal severity scores ( Supplementary Figure S7 BC ). Together, these findings indicate that the elevated contribution of ST-1150 CC to paediatric diarrhoeal disease reflects its local ecological dominance and exposure frequency rather than the acquisition of novel virulence determinants or enhanced intrinsic pathogenicity. Discussion This study reveals how ecological change and antimicrobial exposure can drive the rapid emergence of a multidrug-resistant Campylobacter coli lineage in a LMIC setting. The locally dominant ST-1150 CC was rare in global collections but accounted for over one-fifth of C. coli isolates in the Peruvian Amazon, with a disproportionate association with paediatric diarrhoeal disease. Phylodynamic reconstruction indicates that ST-1150 CC arose in the late 20th century and underwent a rapid expansion from the 1980s onwards, coinciding with increased poultry production and widespread antibiotic use in the region. These results demonstrate that agricultural intensification can generate ecological opportunities for zoonotic pathogens to evolve, adapt, and establish persistent transmission cycles in human populations. The evolutionary success of ST-1150 CC appears to have been reinforced by strong antimicrobial selection. Genomic analyses revealed high levels of acquired resistance to fluoroquinolones, macrolides, and tetracyclines, supported by fixation of a conserved cmeB efflux-pump variant predicted to enhance multidrug-resistance 4 , 39 – 42 . This pattern suggests a selective sweep within an already adapted lineage, in which antimicrobial exposure consolidated resistance determinants and promoted clonal dominance. Similar mechanisms have been reported for C. jejuni lineages associated with industrialised poultry systems in Brazil and Europe 43 – 45 , but ST-1150 CC represents an independent, LMIC-derived example of convergent evolution towards a host-associated, multidrug-resistant state. The Peruvian Amazon provides a compelling case study of how local ecological and socio-economic factors shape bacterial evolution. Rapid demographic growth, unregulated antimicrobial use, and the expansion of both backyard and commercial poultry systems have created an environment favouring pathogen adaptation. Importantly, domestic poultry populations across South America exhibit substantial genetic heterogeneity, derived from historical admixture of European and Asian lineages 26 – 28 . In mixed backyard systems, this diversity likely provides a mosaic of host environments that sustain parallel Campylobacter lineages and facilitate genetic exchange. The persistence of ST-1150 CC across human and poultry hosts underscores the permeability of boundaries between livestock and human infection cycles in regions with limited biosecurity and high environmental exposure 32 – 35 . These findings align with broader evidence that Campylobacter transmission in endemic settings often originates from locally maintained reservoirs rather than repeated introductions of globally dominant lineages 15 , 19 , 46 – 49 . Our results also highlight the evolutionary constraints acting on C. coli populations. Despite its genomic plasticity and capacity for recombination, ST-1150 CC exhibits marked genomic conservation, particularly across AMR-associated loci, suggesting a recent clonal expansion from a well-adapted ancestor rather than gradual diversification through horizontal gene transfer 50 , 51 . The balance between recombination-driven diversity and selective fixation of advantageous alleles likely determines the long-term success of emergent Campylobacter lineages 18 . Beyond Campylobacter , these findings illustrate a broader mechanism of pathogen emergence in LMIC settings. Agricultural intensification and antimicrobial selection can accelerate bacterial adaptation, enabling the rise of novel, multidrug-resistant lineages that may later disseminate globally through trade, travel, or movement of animals or animal products 52 – 56 . Recent debate about the removal of fluoroquinolone-resistant Campylobacter from the 2024 WHO Bacterial Priority Pathogen List 57 – 59 underscores that such lineages continue to represent an ongoing global threat. Integrating genomic surveillance into agricultural and public health systems is essential to detect and characterise these emergent lineages before they become globally established. This work reinforces the importance of a One Health framework for tackling AMR 60 , 61 . Interventions confined to clinical or veterinary domains are unlikely to succeed without addressing the underlying ecological and evolutionary processes that enable resistance selection and transmission. Linking genomic data with antimicrobial usage records, animal husbandry practices, and environmental exposures will be crucial for developing evidence-based strategies to limit resistance spread and safeguard antimicrobial efficacy. Methods Study design and sampling Between 2002 and 2024, Campylobacter coli isolates were collected from paediatric faecal samples as part of five observational studies conducted in Iquitos, Peru, encompassing both health-care–based surveillance and community-based sampling 5 , 40 , 62 – 65 . Additional isolates were obtained from poultry, pigs, cattle, goats, and ducks through ongoing zoonotic surveillance between 2019 and 2024. In total, 460 C. coli genomes were included in this study (children with gastroenteritis, n = 136; asymptomatic carriage, n = 163; poultry, n = 89; pigs, n = 36; cattle, n = 15; reference panel, n = 21). Faecal samples were collected using sterile cotton swabs and placed in Cary-Blair transport medium. Samples were transported at ambient temperature and processed within 12 h of collection. Ethical approvals All studies were approved by the respective Institutional Review Boards: Asociación Benéfica Prisma (Lima, Peru), Johns Hopkins Bloomberg School of Public Health (Baltimore, USA), and the University of Virginia (Charlottesville, USA). Written informed consent was obtained from the parents or legal guardians of participating children. Animal sampling was approved by the Institutional Ethics Committee on the Use of Animals in Research of Universidad Peruana Cayetano Heredia (Lima, Peru). Bacterial isolation and phenotypic testing Faecal samples were cultured on Campylobacter Blood-Free Selective Agar Base (Oxoid, Thermo Fisher Scientific) supplemented with CCDA Selective Supplement or on Columbia Blood Agar containing 5% lysed horse blood. Filter plates (0.45 µm, 47 mm, Merck Millipore) were incubated under microaerophilic conditions (1% O₂ + 10% CO₂ + 10% H₂, balance N₂). Mammalian isolates were grown at 37°C for 48–72 h; avian isolates at 42°C for 48–72 h 66,67 . Antimicrobial susceptibility testing was performed on Mueller-Hinton agar with 5% laked horse blood using the Kirby–Bauer disk-diffusion method for ciprofloxacin, erythromycin, azithromycin, tetracycline, imipenem, gentamicin, amoxicillin–clavulanic acid, and chloramphenicol. Zone-diameter breakpoints followed CLSI M45 for Campylobacter spp.; for agents without established breakpoints, Enterobacteriaceae thresholds were applied. Whole-genome sequencing and assembly Genomic DNA was extracted using the Qiagen DNeasy Blood & Tissue Kit, as previously described 4 , 40 . Libraries were prepared with either the Nextera XT or Illumina DNA Prep (Tagmentation) kits and sequenced on an Illumina MiSeq platform using 2 × 250 bp chemistry to achieve ≥ 80× coverage. Read quality was assessed with fastp v0.23.2 68 , trimmed using parameters “-l 50 -g”, and assembled de novo with SPAdes v3.13.0 69,70 . Genome quality was verified with CheckM v1.1.3 71 ; assemblies with > 4 % contaminaton or mixed species detected by Kraken2 v2.1.3 72 were excluded. Final acceptance thresholds were N50 > 20 kb, total length 1.5–2.0 Mb, ≤ 400 contigs, and mean depth ≥ 20×. Assemblies were annotated using PROKKA v1.14.6 73 . Genotyping and population structure Seven-locus MLST sequence types (STs) and clonal complexes (CCs; ≥ 5 shared alleles) were assigned through the PubMLST Campylobacter database 74 , 75 . Novel allelic profiles were submitted for curation. Population clustering was assessed using hierarchical Bayesian Analysis of Population Structure (BAPS) implemented in rhierBAPS v1.1.3 76,77 . Core and accessory genomes were defined with PIRATE v1.0.4 using amino-acid identity thresholds from 45% to 98% 78 . Core genes (≥ 95 %of genomes) were concatenated to build a maximum-likelihood phylogeny with IQ-TREE2 v1.6.8 under a GTR + I + G model and 1,000 ultrafast bootstraps 79 , 80 . Gene-presence matrices were visualised in Phandango 81 and accessory-genome clustering examined with PANINI 82 , 83 . Recombination analysis and phylogenetic reconstruction Whole-genome alignments for CC828 and CC1150 were generated by mapping reads to reference genome JV20 (NZ_AEER00000000.1) using Snippy v4.6.0 84 . Recombination was detected and masked with Gubbins v3.2.1 85 , and recombination-free trees inferred using IQ-TREE2 79 . Rooting employed isolate CAMP3311 from unintrogressed C. coli clade 1 as outgroup 29 , 32 . Temporal signal and phylodynamic inference To investigate the timing and demographic history of the locally dominant ST-1150 clonal complex, we performed phylodynamic inference using BactDating v1.1.1 on a recombination-filtered core genome alignment. Temporal signal was assessed by regressing root-to-tip genetic distances against sampling dates, with significance evaluated by randomisation testing 86 . Time-scaled phylogenies were inferred under a mixed-gamma relaxed molecular clock model, which allows branch-specific rate variation while sharing information across the tree. Analyses were run for 10⁸ Markov chain Monte Carlo (MCMC) iterations, sampling every 100 iterations, with the first 50% discarded as burn-in. Convergence and effective sample sizes (Gelman–Rubin 200) were assessed using the coda package in R (v0.19-4.1). Changes in effective population size (Ne) through time were reconstructed using Skygrowth v1.0 87 , which estimates piecewise-constant growth rates from dated phylogenies under a Bayesian framework. Posterior median estimates and 95% highest posterior density (HPD) intervals were summarised and visualised. Discrete clonal expansion events were identified using CaveDive v0.1.1 88 , which infers shifts in population growth dynamics from posterior distributions of dated trees. CaveDive analyses were run using BactDating posterior samples as input, and expansion events were considered supported when posterior probabilities exceeded 70%. Trace plots and posterior distributions were inspected to confirm convergence and stability of inferred expansion dynamics. Antimicrobial-resistance and virulence-gene profiling Acquired and chromosomal AMR determinants were identified using AMRFinderPlus v3.10.30 and confirmed by targeted BLASTn searches for C. coli -specific resistance mutations, including gyrA T86I and 23S rRNA A2075G 4 , 39 , 40 , 89 , 90 . Plasmid reconstruction and typing employed MOB-suite v3.0.3 91,92 . Virulence-associated genes were screened against the Virulence Factors Database (VFDB, 2023 release) 93 . Presence/absence matrices were visualised with phandango and correlated with clinical metadata (diarrhoea severity scores from MAL-ED study 94 ) to explore genotype–phenotype associations. Historical data acquisition Census data was retrieved for the estimated human population of Iquitos between 1980 and 2023 95 and combined with historical estimates. In addition, poultry farming estimates were also retrieved for between 1999 and 2025 96 . These were plotted and compared with bacterial effective population sizes of the emerging ST-1150 CC lineage. Declarations Data availability All assembled genomes and associated metadata are publicly available on PubMLST (individual IDs in Table S1 ). Raw sequence reads for previously unpublished isolates are deposited in NCBI SRA under BioProject PRJNA912682. Processed datasets, including AMR profiles, phylogenetic trees, recombination-filtered alignments, and BactDating outputs, are archived on Figshare (doi: 10.6084/m9.figshare.29891339). Interactive visualisations of key phylogenies are available on Microreact: Full dataset: https://microreact.org/project/uz2vcaYGnrvjPcC5xp2PLV-peru-ccoli-dataset ST-1150 CC: https://microreact.org/project/i9BCoHKBx1Dus1FkAvSSke-peru-ccoli-cc1150 ST-828 CC: https://microreact.org/project/hFfnn1GQNisKqBTPgUbazB-peru-ccoli-cc828 Acknowledgements We thank the participating children, parents, and community health workers in Iquitos, Peru, for their contribution to this study. We gratefully acknowledge the technical assistance of Steven Huynh at USDA-ARS, and Madison P. Goforth and Evangelos Antonios Dimopoulos at the University of Oxford for helpful discussions. Bioinformatics analysis was conducted using high-performance computing infrastructure managed by the University of Arizona. We also thank the PubMLST development team for curating Campylobacter datasets (curated by Frances M. Colles). Author contributions B.P., E.M., F.S., C.T.P., K.K.C. and M.N.K. conceived and designed the study. M.P.O. , P.P.Y. , P.F.G.B. , and M.N.K. coordinated fieldwork, sample collection, and microbiological processing in Iquitos, Peru. P.F.G.B. , K.M.V. , L.R.C. , L.F.Z.P. , W.V.S.L. , T.P.V. , A.C. , J.N. performed fieldwork, sample collection, and microbiological processing in Iquitos, Peru. V.O. , C.S. and M.D.H. sequenced genomes used in the study; and C.T.P. and K.K.C. performed genome assembly, annotation, and quality control. B.P., F.S. and E.M. conducted the population genomic, pangenome, and phylodynamic analyses with input from M.N.K. , and C.T.P.; K.K.C. , C.T.P. and S.K.S. contributed to metadata curation and contextual interpretation of the epidemiological data. B.P., E.M., F.S., C.T.P., K.K.C. and M.N.K. wrote the initial draft of the manuscript. All authors reviewed, edited, and approved the final version of the manuscript. Competing interests The authors declare no competing interests. Funding This work was supported by grants from the US National Institutes of Health RO1AI158576 and R21AI63801 (MNK, CTP) , 5D43TW010913 (MNK and MPO), K43TW012298 (FS) and Gates Foundation (INV-031791). Additional support was obtained by the United States Department of Agriculture-Agricultural Research Service Current Research Information System project 2030-42000-055-00D (to CTP), Ineos Oxford Institute for Antimicrobial Research, and the MRC (BP, SKS). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. References Organization WH (2015) WHO Estimates of the Global Burden of Foodborne Diseases. World Health OrganiZation 254 (2020) Goddard MR et al (2022) A restatement of the natural science evidence base regarding the source, spread and control of Campylobacter species causing human disease. 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Supplementary Files FigureS1genome.size.pdf Supplementary Figure 1 FigureS3BacDating.pdf Supplementary Figure 3 FigureS4Expansions.pdf Supplementary Figure 4 FigureS7virulence.pdf Supplementary Figure 7 FigureS6cmeBmatrix.pdf Supplementary Figure 6 FigureS2accessory.pdf Supplementary Figure 2 FigureS5AMRmatrix.pdf Supplementary Figure 5 Supplementarytables.xlsx Supplementary Tables SupplementaryFiguresCaptions.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Kosek","email":"","orcid":"","institution":"University of Virginia","correspondingAuthor":false,"prefix":"","firstName":"Margaret","middleName":"N.","lastName":"Kosek","suffix":""}],"badges":[],"createdAt":"2026-02-12 20:21:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8865396/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8865396/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103441011,"identity":"f02acf1a-56d3-4ef8-9855-21a37f017421","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":229290,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePopulation structure and local dominance of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e ST-1150 CC in the Peruvian Amazon.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Maximum likelihood phylogeny of 468 \u003cem\u003eC. coli\u003c/em\u003e genomes (439 from Iquitos, Peru; 29 global references), inferred from the core genome and mid-point rooted. Tips are coloured by isolation source: red = human gastroenteritis case; blue = asymptomatic human surveillance; yellow = commercial chicken; orange = backyard chicken; pink = pig; green = cattle/goat; grey = reference genome. Peruvian isolates are restricted to agriculture-associated clade 1, forming two major groups: the globally distributed ST-828 CC and the locally dominant ST-1150 CC. Scale bar indicates substitutions per site. (B) Distribution of STs within the Peruvian collection, coloured by source. Several STs (e.g. ST-825, ST-10234) are paraphyletic in the core genome phylogeny and indicated with an asterisk (*). (C) Comparison of ST prevalence in human clinical isolates from Peru (y-axis) versus global prevalence in the PubMLST database (x-axis; accessed 09-09-2024). ST-1150 CC sequence types, including ST-11961 and ST-11963, are rare globally but common locally, with some significantly enriched in Peruvian human infections. (D) Proportion of isolates within each CC from diarrhoeal cases (orange) versus asymptomatic carriage (grey). ST-1150 CC is significantly over-represented in diarrhoeal cases (χ² = 17.36, p = 3.1 × 10⁻⁵).\u003c/p\u003e","description":"","filename":"Figure1population.png","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/b44f60069109fac87121c26a.png"},{"id":103441022,"identity":"c924d3eb-ca3d-4d64-bc15-6ef47e19777b","added_by":"auto","created_at":"2026-02-25 17:16:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":239455,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylodynamic reconstruction of ST-1150 CC emergence and expansion in the Peruvian Amazon.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Time-scaled phylogeny of ST-1150 CC isolates inferred using BactDating from a recombination-filtered core genome alignment. Tip points are coloured by isolation source: red, human gastroenteritis cases; blue, asymptomatic human surveillance; yellow, commercial chicken; orange, backyard chicken; pink, pig; green, ruminant (cattle/goat). Key historical events relevant to the Amazon region are indicated along the x-axis for temporal context. (B) Bayesian skyline reconstruction of effective population size (Ne) for ST-1150 CC through time. The solid black line indicates the posterior median Ne estimate, with shaded grey regions representing the 95% highest posterior density (HPD) interval. Overlaid in red is the historical growth of the human population of Iquitos based on census data. (C) Estimated annual poultry production in Loreto Department, Peru, from 2000 to 2020, illustrating rapid growth in commercial poultry production during the late twentieth and early twenty-first centuries. Together, panels (B) and (C) show a marked (\u0026gt;1,000-fold) increase in inferred Ne between approximately 1980 and 2005 that is temporally congruent with regional demographic growth and poultry intensification. (D) Proportion of isolates from non-human sources within ST-1150 CC and ST-828 CC, highlighting the strong association of ST-1150 CC with poultry compared with the broader host range observed for ST-828 CC.\u003c/p\u003e","description":"","filename":"Figure2dating.png","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/b86928e6593e90a0bff626d0.png"},{"id":103441014,"identity":"37cb5f92-bd5e-4a2a-8f01-8150b330fe5d","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":207496,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAMR phenotypes and genotypes of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates from Iquitos, Peru.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Phylogeny-ordered matrix summarising AMR genotypes and corresponding phenotypic susceptibility profiles across \u003cem\u003eC. coli\u003c/em\u003e isolates. The maximum-likelihood phylogeny is mid-point rooted, and tips are coloured by isolation source as in Figure 1. Rows represent individual isolates ordered by phylogeny, and columns represent the presence or absence of AMR determinants (black, present; white, absent) and phenotypic susceptibility outcomes. AMR determinants were identified using AMRFinderPlus and include genes and mutations conferring resistance to aminoglycosides (e.g. \u003cem\u003eaadE\u003c/em\u003e, \u003cem\u003esat4\u003c/em\u003e, \u003cem\u003eaphA3\u003c/em\u003e), β-lactams (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA-61\u003c/sub\u003e), macrolides (\u003cem\u003eerm(B)\u003c/em\u003e and 23S rRNA A2075G), fluoroquinolones (\u003cem\u003egyrA\u003c/em\u003e T86I), and tetracyclines (\u003cem\u003etet(O)\u003c/em\u003e, \u003cem\u003etet(O/32/O)\u003c/em\u003e). Phenotypic resistance is shown in dark orange, susceptibility in grey, and multidrug resistance (MDR) in purple. (B) Boxplot showing the number of AMR determinants identified per isolate across major \u003cem\u003eC. coli\u003c/em\u003e clades. ST-1150 CC isolates harbour a significantly higher number of resistance determinants compared with ST-828 CC and other clades (****, p \u0026lt; 0.0001; Wilcoxon rank-sum test).\u003cstrong\u003e \u003c/strong\u003e(C) Pairwise similarity of AMR profiles within ST-1150 CC and ST-828 CC, calculated as the proportion of shared resistance determinants between isolate pairs. ST-1150 CC exhibits significantly higher within-lineage similarity, consistent with a conserved multidrug-resistance architecture.\u003cstrong\u003e \u003c/strong\u003eIsolates were classified as multidrug resistant (MDR) if they were non-susceptible to three or more antibiotic classes.\u003c/p\u003e","description":"","filename":"Figure3AMRfinal.png","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/9f3e6479c8cc467bf0883805.png"},{"id":104398203,"identity":"6e83be98-bbf1-49d9-9783-f61f77d81a34","added_by":"auto","created_at":"2026-03-11 12:00:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2009751,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/8df3afd5-afdd-44b7-af26-548c68a26de0.pdf"},{"id":103507465,"identity":"54922900-8233-4297-bc93-51411cf93f14","added_by":"auto","created_at":"2026-02-26 13:41:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":122895,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"FigureS1genome.size.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/88e84b399828e98d63d5e429.pdf"},{"id":103441013,"identity":"3164a9df-c8c3-4ec6-8105-a8a3924cc413","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":430028,"visible":true,"origin":"","legend":"Supplementary Figure 3","description":"","filename":"FigureS3BacDating.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/20ed28526612a2e962792428.pdf"},{"id":103441018,"identity":"0018abd1-99be-42fb-937d-febe4db5cefa","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":428579,"visible":true,"origin":"","legend":"Supplementary Figure 4","description":"","filename":"FigureS4Expansions.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/3cfd5039723db85a3e9f4df5.pdf"},{"id":103441017,"identity":"5585779e-3806-4e3d-8854-27e49db0ed9e","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":177816,"visible":true,"origin":"","legend":"Supplementary Figure 7","description":"","filename":"FigureS7virulence.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/9c5d64dfb6a15b182823fb72.pdf"},{"id":103507509,"identity":"79583bb9-06ed-4ef8-b381-7d00bb441529","added_by":"auto","created_at":"2026-02-26 13:41:38","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":903803,"visible":true,"origin":"","legend":"Supplementary Figure 6","description":"","filename":"FigureS6cmeBmatrix.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/bdc49489cf846a3ebc0b9e70.pdf"},{"id":103441016,"identity":"efedf12d-8c1e-44d8-b962-e8d3cca1d5c8","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":717782,"visible":true,"origin":"","legend":"Supplementary Figure 2","description":"","filename":"FigureS2accessory.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/587eaa0a381e1d76084642f0.pdf"},{"id":103441019,"identity":"b08a5f37-3366-450b-a402-bc2884e9d0a6","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":181611,"visible":true,"origin":"","legend":"Supplementary Figure 5","description":"","filename":"FigureS5AMRmatrix.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/61a866e95ca75abd23556974.pdf"},{"id":103441020,"identity":"e6a553ce-23e0-4dca-a647-598d365f2719","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":17482560,"visible":true,"origin":"","legend":"Supplementary Tables","description":"","filename":"Supplementarytables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/487826487ab252be3f709bf1.xlsx"},{"id":103441021,"identity":"24012bbc-e5ec-468a-926a-d2a3f8479804","added_by":"auto","created_at":"2026-02-25 17:16:06","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":17717,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiguresCaptions.docx","url":"https://assets-eu.researchsquare.com/files/rs-8865396/v1/40c5d1255c9cd83cf7d84c13.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Recent emergence of a multidrug-resistant Campylobacter coli lineage linked to poultry intensification in the Peruvian Amazon","fulltext":[{"header":"Plain English Summary","content":"\u003cp\u003e\u003cem\u003eCampylobacter coli\u0026nbsp;\u003c/em\u003eis an important cause of diarrhoea, especially among children in low- and middle-income countries. We discovered a bacterial lineage, ST-1150, that is common in the Peruvian Amazon but rarely seen elsewhere. By analysing hundreds of genomes, we show that this lineage emerged and expanded rapidly from the 1980s onwards, coinciding with the intensification of poultry farming. It carries multiple genes that make it resistant to several antibiotic classes, suggesting that agricultural antibiotic use has shaped its evolution. Our findings reveal how local farming practices and antimicrobial exposure can drive the emergence of new resistant bacterial lineages, underscoring the need for integrated surveillance of human and animal infections.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eCampylobacter\u003c/em\u003e species are among the leading causes of gastroenteritis worldwide, with the highest burden in low- and middle-income countries (LMICs), where repeated early-life infections contribute to malnutrition, stunting and impaired child development\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. While \u003cem\u003eCampylobacter jejuni\u003c/em\u003e dominates reported infections in high-income countries (HIC), \u003cem\u003eCampylobacter coli\u003c/em\u003e accounts for a substantial proportion of cases in LMICs\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Despite its clinical and epidemiological importance, \u003cem\u003eC. coli\u003c/em\u003e remains comparatively under-studied, and the ecological and evolutionary processes shaping its persistence in endemic regions are poorly understood. The World Health Organization\u0026rsquo;s Foodborne Disease Burden Epidemiology Reference Group estimates that bacterial foodborne pathogens impose an annual economic burden exceeding \u003cspan\u003e$\u003c/span\u003e95\u0026nbsp;billion USD in LMICs \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, underscoring the need to elucidate how local agricultural and antimicrobial practices influence the emergence of pathogenic lineages.\u003c/p\u003e \u003cp\u003eMost \u003cem\u003eCampylobacter\u003c/em\u003e genome datasets originate from HICs and may not capture the diversity and dynamics circulating in tropical, high-transmission environments\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Recent surveillance in LMICs has revealed an increasing prevalence of multidrug-resistant (MDR) \u003cem\u003eC. coli\u003c/em\u003e, often associated with unregulated antibiotic use in livestock production and limited biosecurity\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. These pressures can generate ecological niches favouring the evolution and persistence of locally adapted clones. Understanding how such lineages arise and disseminate is essential to designing effective One Health interventions.\u003c/p\u003e \u003cp\u003eThe Peruvian Amazon provides a powerful model for investigating these processes. Community-based surveillance in Iquitos has shown that \u003cem\u003eCampylobacter\u003c/em\u003e carriage among children is nearly universal by two years of age, frequently asymptomatic yet associated with enteropathy\u003csup\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Over recent decades, the region has experienced rapid urban expansion\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, increased poultry consumption\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and the growth of both backyard and industrial poultry systems, accompanied by widespread antimicrobial use\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Such conditions provide ideal ecological opportunities for bacterial adaptation and transmission between humans and livestock.\u003c/p\u003e \u003cp\u003eDomestic chickens across South America are genetically diverse, reflecting historical admixture between European and Asian domestic lineages introduced through trade and colonial expansion\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Although backyard poultry production remains largely informal in Iquitos, there is mixing between breeds cohabiting in open environments and sharing feed and water sources with other livestock species. These conditions provide fertile ground for bacterial exchange and selection, shaping the genetic structure of circulating \u003cem\u003eCampylobacter\u003c/em\u003e lineages. At a global scale, \u003cem\u003eC. coli\u003c/em\u003e is composed of three deeply rooted clades that have undergone extensive introgression with \u003cem\u003eC. jejuni\u003c/em\u003e, particularly within the ST-828 clonal complex (CC828)\u003csup\u003e\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. This clonal complex comprises host-generalist lineages capable of colonising livestock, poultry, and humans, enabling frequent interspecies transmission\u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. However, the extent to which local agricultural intensification and antimicrobial selection pressures drive the emergence of novel \u003cem\u003eC. coli\u003c/em\u003e lineages in endemic LMIC settings remains unclear.\u003c/p\u003e \u003cp\u003eHere, we integrate population-genomic and phylodynamic analyses of 460 \u003cem\u003eC. coli\u003c/em\u003e genomes from the Peruvian Amazon to investigate the ecological and evolutionary drivers of lineage emergence. Our dataset includes isolates from children with gastroenteritis and asymptomatic carriage, alongside samples from poultry, pigs, and cattle, providing a comprehensive view of the local \u003cem\u003eC. coli\u003c/em\u003e gene pool. We identify a distinct lineage, ST-1150 CC, that is significantly over-represented in paediatric diarrhoeal cases yet rare globally. Time-scaled phylogenies reveal that this lineage emerged and expanded rapidly from the 1980s coinciding with intensification of poultry production and antibiotic use in the region. Genomic antimicrobial-resistance profiling demonstrates extensive acquired resistance, underpinned by conserved \u003cem\u003ecmeB\u003c/em\u003e efflux-pump variants. Together, these findings provide a mechanistic view of how agricultural intensification and antimicrobial exposure can drive the ecological emergence and clonal success of multidrug-resistant \u003cem\u003eCampylobacter\u003c/em\u003e lineages. By linking local environmental change to pathogen evolution, this study highlights the need for integrated One Health genomic surveillance to detect and mitigate the emergence of zoonotic pathogens in rapidly changing food production systems.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePeruvian C. coli isolates cluster within agriculture-associated clades and reveal a locally dominant lineage\u003c/h2\u003e \u003cp\u003eWe analysed 460 \u003cem\u003eC. coli\u003c/em\u003e genomes collected from the Peruvian Amazon, comprising isolates from children with gastroenteritis (n\u0026thinsp;=\u0026thinsp;136), asymptomatic carriage (n\u0026thinsp;=\u0026thinsp;163), poultry (backyard\u0026thinsp;=\u0026thinsp;29; commercial\u0026thinsp;=\u0026thinsp;60), pigs (n\u0026thinsp;=\u0026thinsp;36), cattle (n\u0026thinsp;=\u0026thinsp;15), and a small reference panel (n\u0026thinsp;=\u0026thinsp;21; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Comparison with global reference genomes\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e revealed that all Peruvian isolates clustered within the agriculture-associated \u003cem\u003eC. coli\u003c/em\u003e clade 1, with no representatives of the ancestral, unintrogressed clades 2 or 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe identified 102 multilocus sequence types (ST) spanning five clonal complexes (CC), dominated by ST-828 CC (n\u0026thinsp;=\u0026thinsp;343, 75%) and the locally prevalent ST-1150 CC (n\u0026thinsp;=\u0026thinsp;96, 21%; \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Although ST-1150 CC is globally rare, detected in \u0026lt;\u0026thinsp;0.1% of \u0026gt;\u0026thinsp;25,000 \u003cem\u003eC. coli\u003c/em\u003e genomes in PubMLST (accessed 09/2024), it accounted for 23% (69/299) of human isolates in this study and was significantly enriched in diarrhoeal cases compared to asymptomatic carriage (47/136 [35%] vs 22/163 [14%]; χ\u0026sup2; = 17.36, p\u0026thinsp;=\u0026thinsp;3.1 \u0026times; 10⁻⁵; \u003cb\u003eFig.\u0026nbsp;1CD\u003c/b\u003e). Within ST-828 CC many individual STs were not monophyletic, often clustering in two or more distinct parts of the phylogeny (e.g. ST-825 and ST-10234; \u003cb\u003eSupplementary figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePeruvian C. coli isolates represent a distinct local gene pool\u003c/h3\u003e\n\u003cp\u003eAcross the full dataset, \u003cem\u003eC. coli\u003c/em\u003e exhibited extensive accessory genome plasticity, consistent with frequent horizontal gene transfer (\u003cb\u003eSupplementary Tables S3-4\u003c/b\u003e). However, ST-1150 CC isolates formed a tight, well-supported cluster distinct from the more heterogeneous ST-828 CC (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA\u003c/b\u003e). Pangenome accumulation analyses stratified by host source revealed broadly similar trajectories across reservoirs, indicating that differences in accessory genome structure reflected lineage-specific clustering rather than host-exclusive gene acquisition (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB\u003c/b\u003e). Accessory genome clustering showed that ST-1150 CC isolates grouped almost exclusively with poultry-derived isolates, whereas ST-828 CC genomes shared accessory gene content with both poultry- and swine-associated isolates (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC\u003c/b\u003e). These findings support the existence of a locally structured \u003cem\u003eC. coli\u003c/em\u003e gene pool in the Peruvian Amazon and indicate a strong epidemiological association between ST-1150 CC and poultry production systems, with limited recent gene flow from other livestock reservoirs.\u003c/p\u003e\n\u003ch3\u003ePhylodynamic reconstruction indicates recent emergence and rapid expansion of ST-1150 CC\u003c/h3\u003e\n\u003cp\u003eTime-scaled phylogenetic reconstruction of ST-1150 CC revealed a relatively recent common ancestry, with most diversification occurring during the late 20th century (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Root-to-tip regression revealed a significant positive association between genetic divergence and sampling time (R\u0026sup2; = 0.28, p\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10⁻⁴), indicating sufficient temporal signal to support molecular-clock inference (\u003cb\u003eSupplementary Fig.\u0026nbsp;3A\u003c/b\u003e). Under a mixed-gamma relaxed molecular clock, the most recent common ancestor (MRCA) of ST-1150 CC was dated to a posterior median of 1974 (95% highest posterior density [HPD]: 1952\u0026ndash;1990), placing its emergence in the latter half of the twentieth century. While uncertainty around the MRCA date was substantial (\u003cb\u003eSupplementary Fig.\u0026nbsp;3B\u003c/b\u003e), the inferred timing consistently preceded a period of major demographic and agricultural change in the Peruvian Amazon\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (\u003cb\u003eSupplementary Tables S5-6\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSkyline-based phylodynamic analyses indicated a sustained increase in effective population size beginning approximately in the 1980s and continuing into the early 2000s (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), coinciding with periods of rapid growth in regional poultry production. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Notably, the inferred demographic history was characterised by gradual and sustained population growth rather than sharp, punctuated expansions. Consistent with this, CaveDive analyses showed highest posterior support for models with no discrete expansion events (posterior probability\u0026thinsp;\u0026asymp;\u0026thinsp;70%), with moderate support for a single expansion (\u0026asymp;\u0026thinsp;30%) and negligible support for multiple expansion events (\u003cb\u003eSupplementary 3BCD\u003c/b\u003e). Together, these results support a model in which ST-1150 CC underwent progressive demographic expansion associated with agricultural intensification, rather than abrupt population bursts driven by single introduction events. Consistent with this interpretation, global contextualisation using PubMLST revealed that non-human ST-1150 CC isolates have been almost exclusively sampled from poultry sources, predominantly from commercial production systems, whereas ST-828 CC displays a much broader host range spanning poultry, swine, cattle, and humans (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\n\u003ch3\u003eST-1150 CC exhibits a dense and conserved multidrug-resistance architecture\u003c/h3\u003e\n\u003cp\u003ePhenotypic antimicrobial susceptibility testing revealed high levels of resistance across the dataset, with particularly elevated multidrug resistance (MDR) in ST-1150 CC (\u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003e\u003c/b\u003e). Resistance to ciprofloxacin was common in both ST-1150 CC (72.6%) and ST-828 CC (81.4%), while azithromycin resistance was detected in approximately 30% of isolates from both clades (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). However, multidrug-resistance (MDR), defined as non-susceptibility to \u0026ge;\u0026thinsp;3 antibiotic classes, was significantly more frequent in ST-1150 CC (56.1%) than in ST-828 CC (40.1%; χ\u0026sup2; = 5.99, p\u0026thinsp;=\u0026thinsp;0.014) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Genomic screening corroborated these findings: 96% of ST-1150 CC isolates carried determinants for resistance to at least one antibiotic class, and 71% met the genomic MDR definition (\u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM8\" class=\"InternalRef\"\u003eS8\u003c/span\u003e\u003c/b\u003e). Common determinants included the tetracycline resistance gene \u003cem\u003etet(O)\u003c/em\u003e (95%), β-lactamase \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eOXA\u0026minus;61\u003c/em\u003e\u003c/sub\u003e (92%), the aminoglycoside cluster \u003cem\u003eaadE-sat4-aphA3\u003c/em\u003e (68%), and the \u003cem\u003egyrA\u003c/em\u003e T86I mutation (\u0026gt;\u0026thinsp;80%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC; \u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e\u003c/b\u003e). Macrolide resistance was linked to the 23S rRNA A2075G mutation and the \u003cem\u003ecmeABC\u003c/em\u003e efflux operon, which was present in all isolates. Notably, ST-1150 CC exhibited markedly reduced allelic diversity in \u003cem\u003ecmeB\u003c/em\u003e compared with ST-828 CC, with fixation of a resistance-enhanced \u003cem\u003ecmeB\u003c/em\u003e variant previously linked to increased efflux efficiency (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003e\u003c/b\u003e). This pattern is consistent with strong selection acting on a multidrug-resistance phenotype during lineage expansion and suggests consolidation of resistance determinants within a clonal genomic background.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eVirulence gene content does not indicate lineage-specific increases in intrinsic pathogenicity\u003c/h3\u003e\n\u003cp\u003eScreening against the Virulence Factors Database (VFDB) showed that both ST-1150 CC and ST-828 CC carried the canonical \u003cem\u003eCampylobacter\u003c/em\u003e virulence determinants, including \u003cem\u003ecdtABC\u003c/em\u003e, flagellar motility genes (\u003cem\u003eflaA/B\u003c/em\u003e), and iron-acquisition loci (\u003cb\u003eSupplementary Table S9\u003c/b\u003e). ST-1150 CC exhibited a narrower but more conserved virulence gene repertoire relative to the genetically diverse ST-828 CC (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003eA\u003c/b\u003e), consistent with reduced genomic diversity following recent clonal expansion. Integration of clinical metadata revealed that ST-1150 CC was significantly over-represented among isolates from children with diarrhoeal disease; however, no evidence of increased disease severity was observed based on MAL-ED diarrhoeal severity scores (\u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003eBC\u003c/b\u003e). Together, these findings indicate that the elevated contribution of ST-1150 CC to paediatric diarrhoeal disease reflects its local ecological dominance and exposure frequency rather than the acquisition of novel virulence determinants or enhanced intrinsic pathogenicity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study reveals how ecological change and antimicrobial exposure can drive the rapid emergence of a multidrug-resistant \u003cem\u003eCampylobacter coli\u003c/em\u003e lineage in a LMIC setting. The locally dominant ST-1150 CC was rare in global collections but accounted for over one-fifth of \u003cem\u003eC. coli\u003c/em\u003e isolates in the Peruvian Amazon, with a disproportionate association with paediatric diarrhoeal disease. Phylodynamic reconstruction indicates that ST-1150 CC arose in the late 20th century and underwent a rapid expansion from the 1980s onwards, coinciding with increased poultry production and widespread antibiotic use in the region. These results demonstrate that agricultural intensification can generate ecological opportunities for zoonotic pathogens to evolve, adapt, and establish persistent transmission cycles in human populations.\u003c/p\u003e \u003cp\u003eThe evolutionary success of ST-1150 CC appears to have been reinforced by strong antimicrobial selection. Genomic analyses revealed high levels of acquired resistance to fluoroquinolones, macrolides, and tetracyclines, supported by fixation of a conserved \u003cem\u003ecmeB\u003c/em\u003e efflux-pump variant predicted to enhance multidrug-resistance\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. This pattern suggests a selective sweep within an already adapted lineage, in which antimicrobial exposure consolidated resistance determinants and promoted clonal dominance. Similar mechanisms have been reported for \u003cem\u003eC. jejuni\u003c/em\u003e lineages associated with industrialised poultry systems in Brazil and Europe\u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, but ST-1150 CC represents an independent, LMIC-derived example of convergent evolution towards a host-associated, multidrug-resistant state.\u003c/p\u003e \u003cp\u003eThe Peruvian Amazon provides a compelling case study of how local ecological and socio-economic factors shape bacterial evolution. Rapid demographic growth, unregulated antimicrobial use, and the expansion of both backyard and commercial poultry systems have created an environment favouring pathogen adaptation. Importantly, domestic poultry populations across South America exhibit substantial genetic heterogeneity, derived from historical admixture of European and Asian lineages\u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In mixed backyard systems, this diversity likely provides a mosaic of host environments that sustain parallel \u003cem\u003eCampylobacter\u003c/em\u003e lineages and facilitate genetic exchange. The persistence of ST-1150 CC across human and poultry hosts underscores the permeability of boundaries between livestock and human infection cycles in regions with limited biosecurity and high environmental exposure\u003csup\u003e\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. These findings align with broader evidence that \u003cem\u003eCampylobacter\u003c/em\u003e transmission in endemic settings often originates from locally maintained reservoirs rather than repeated introductions of globally dominant lineages\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan additionalcitationids=\"CR47 CR48\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur results also highlight the evolutionary constraints acting on \u003cem\u003eC. coli\u003c/em\u003e populations. Despite its genomic plasticity and capacity for recombination, ST-1150 CC exhibits marked genomic conservation, particularly across AMR-associated loci, suggesting a recent clonal expansion from a well-adapted ancestor rather than gradual diversification through horizontal gene transfer\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. The balance between recombination-driven diversity and selective fixation of advantageous alleles likely determines the long-term success of emergent \u003cem\u003eCampylobacter\u003c/em\u003e lineages\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Beyond \u003cem\u003eCampylobacter\u003c/em\u003e, these findings illustrate a broader mechanism of pathogen emergence in LMIC settings. Agricultural intensification and antimicrobial selection can accelerate bacterial adaptation, enabling the rise of novel, multidrug-resistant lineages that may later disseminate globally through trade, travel, or movement of animals or animal products\u003csup\u003e\u003cspan additionalcitationids=\"CR53 CR54 CR55\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Recent debate about the removal of fluoroquinolone-resistant \u003cem\u003eCampylobacter\u003c/em\u003e from the 2024 WHO Bacterial Priority Pathogen List\u003csup\u003e\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e underscores that such lineages continue to represent an ongoing global threat. Integrating genomic surveillance into agricultural and public health systems is essential to detect and characterise these emergent lineages before they become globally established.\u003c/p\u003e \u003cp\u003eThis work reinforces the importance of a One Health framework for tackling AMR\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Interventions confined to clinical or veterinary domains are unlikely to succeed without addressing the underlying ecological and evolutionary processes that enable resistance selection and transmission. Linking genomic data with antimicrobial usage records, animal husbandry practices, and environmental exposures will be crucial for developing evidence-based strategies to limit resistance spread and safeguard antimicrobial efficacy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and sampling\u003c/h2\u003e \u003cp\u003eBetween 2002 and 2024, \u003cem\u003eCampylobacter coli\u003c/em\u003e isolates were collected from paediatric faecal samples as part of five observational studies conducted in Iquitos, Peru, encompassing both health-care\u0026ndash;based surveillance and community-based sampling\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Additional isolates were obtained from poultry, pigs, cattle, goats, and ducks through ongoing zoonotic surveillance between 2019 and 2024. In total, 460 C. coli genomes were included in this study (children with gastroenteritis, n\u0026thinsp;=\u0026thinsp;136; asymptomatic carriage, n\u0026thinsp;=\u0026thinsp;163; poultry, n\u0026thinsp;=\u0026thinsp;89; pigs, n\u0026thinsp;=\u0026thinsp;36; cattle, n\u0026thinsp;=\u0026thinsp;15; reference panel, n\u0026thinsp;=\u0026thinsp;21).\u003c/p\u003e \u003cp\u003eFaecal samples were collected using sterile cotton swabs and placed in Cary-Blair transport medium. Samples were transported at ambient temperature and processed within 12 h of collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEthical approvals\u003c/h2\u003e \u003cp\u003eAll studies were approved by the respective Institutional Review Boards: Asociaci\u0026oacute;n Ben\u0026eacute;fica Prisma (Lima, Peru), Johns Hopkins Bloomberg School of Public Health (Baltimore, USA), and the University of Virginia (Charlottesville, USA). Written informed consent was obtained from the parents or legal guardians of participating children. Animal sampling was approved by the Institutional Ethics Committee on the Use of Animals in Research of Universidad Peruana Cayetano Heredia (Lima, Peru).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBacterial isolation and phenotypic testing\u003c/h2\u003e \u003cp\u003eFaecal samples were cultured on \u003cem\u003eCampylobacter\u003c/em\u003e Blood-Free Selective Agar Base (Oxoid, Thermo Fisher Scientific) supplemented with CCDA Selective Supplement or on Columbia Blood Agar containing 5% lysed horse blood. Filter plates (0.45 \u0026micro;m, 47 mm, Merck Millipore) were incubated under microaerophilic conditions (1% O₂ + 10% CO₂ + 10% H₂, balance N₂). Mammalian isolates were grown at 37\u0026deg;C for 48\u0026ndash;72 h; avian isolates at 42\u0026deg;C for 48\u0026ndash;72 h\u003csup\u003e66,67\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAntimicrobial susceptibility testing was performed on Mueller-Hinton agar with 5% laked horse blood using the Kirby\u0026ndash;Bauer disk-diffusion method for ciprofloxacin, erythromycin, azithromycin, tetracycline, imipenem, gentamicin, amoxicillin\u0026ndash;clavulanic acid, and chloramphenicol. Zone-diameter breakpoints followed CLSI M45 for Campylobacter spp.; for agents without established breakpoints, Enterobacteriaceae thresholds were applied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWhole-genome sequencing and assembly\u003c/h2\u003e \u003cp\u003eGenomic DNA was extracted using the Qiagen DNeasy Blood \u0026amp; Tissue Kit, as previously described\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Libraries were prepared with either the Nextera XT or Illumina DNA Prep (Tagmentation) kits and sequenced on an Illumina MiSeq platform using 2 \u0026times; 250 bp chemistry to achieve\u0026thinsp;\u0026ge;\u0026thinsp;80\u0026times; coverage. Read quality was assessed with fastp v0.23.2\u003csup\u003e68\u003c/sup\u003e, trimmed using parameters \u0026ldquo;-l 50 -g\u0026rdquo;, and assembled \u003cem\u003ede novo\u003c/em\u003e with SPAdes v3.13.0\u003csup\u003e69,70\u003c/sup\u003e. Genome quality was verified with CheckM v1.1.3\u003csup\u003e71\u003c/sup\u003e; assemblies with \u0026gt;\u0026thinsp;4 % contaminaton or mixed species detected by Kraken2 v2.1.3\u003csup\u003e72\u003c/sup\u003e were excluded. Final acceptance thresholds were N50\u0026thinsp;\u0026gt;\u0026thinsp;20 kb, total length 1.5\u0026ndash;2.0 Mb, \u0026le; 400 contigs, and mean depth\u0026thinsp;\u0026ge;\u0026thinsp;20\u0026times;. Assemblies were annotated using PROKKA v1.14.6\u003csup\u003e73\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGenotyping and population structure\u003c/h2\u003e \u003cp\u003eSeven-locus MLST sequence types (STs) and clonal complexes (CCs; \u0026ge; 5 shared alleles) were assigned through the PubMLST \u003cem\u003eCampylobacter\u003c/em\u003e database\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Novel allelic profiles were submitted for curation. Population clustering was assessed using hierarchical Bayesian Analysis of Population Structure (BAPS) implemented in rhierBAPS v1.1.3\u003csup\u003e76,77\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCore and accessory genomes were defined with PIRATE v1.0.4 using amino-acid identity thresholds from 45% to 98%\u003csup\u003e78\u003c/sup\u003e. Core genes (\u0026ge;\u0026thinsp;95 %of genomes) were concatenated to build a maximum-likelihood phylogeny with IQ-TREE2 v1.6.8 under a GTR\u0026thinsp;+\u0026thinsp;I + G model and 1,000 ultrafast bootstraps\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. Gene-presence matrices were visualised in Phandango\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e and accessory-genome clustering examined with PANINI\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRecombination analysis and phylogenetic reconstruction\u003c/h2\u003e \u003cp\u003eWhole-genome alignments for CC828 and CC1150 were generated by mapping reads to reference genome JV20 (NZ_AEER00000000.1) using Snippy v4.6.0\u003csup\u003e84\u003c/sup\u003e. Recombination was detected and masked with Gubbins v3.2.1\u003csup\u003e85\u003c/sup\u003e, and recombination-free trees inferred using IQ-TREE2\u003csup\u003e79\u003c/sup\u003e. Rooting employed isolate CAMP3311 from unintrogressed \u003cem\u003eC. coli\u003c/em\u003e clade 1 as outgroup\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTemporal signal and phylodynamic inference\u003c/h2\u003e \u003cp\u003eTo investigate the timing and demographic history of the locally dominant ST-1150 clonal complex, we performed phylodynamic inference using BactDating v1.1.1 on a recombination-filtered core genome alignment. Temporal signal was assessed by regressing root-to-tip genetic distances against sampling dates, with significance evaluated by randomisation testing\u003csup\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e. Time-scaled phylogenies were inferred under a mixed-gamma relaxed molecular clock model, which allows branch-specific rate variation while sharing information across the tree. Analyses were run for 10⁸ Markov chain Monte Carlo (MCMC) iterations, sampling every 100 iterations, with the first 50% discarded as burn-in. Convergence and effective sample sizes (Gelman\u0026ndash;Rubin\u0026thinsp;\u0026lt;\u0026thinsp;1.1, ESS\u0026thinsp;\u0026gt;\u0026thinsp;200) were assessed using the \u003cem\u003ecoda\u003c/em\u003e package in R (v0.19-4.1).\u003c/p\u003e \u003cp\u003eChanges in effective population size (Ne) through time were reconstructed using Skygrowth v1.0\u003csup\u003e87\u003c/sup\u003e, which estimates piecewise-constant growth rates from dated phylogenies under a Bayesian framework. Posterior median estimates and 95% highest posterior density (HPD) intervals were summarised and visualised. Discrete clonal expansion events were identified using CaveDive v0.1.1\u003csup\u003e88\u003c/sup\u003e, which infers shifts in population growth dynamics from posterior distributions of dated trees. CaveDive analyses were run using BactDating posterior samples as input, and expansion events were considered supported when posterior probabilities exceeded 70%. Trace plots and posterior distributions were inspected to confirm convergence and stability of inferred expansion dynamics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAntimicrobial-resistance and virulence-gene profiling\u003c/h2\u003e \u003cp\u003eAcquired and chromosomal AMR determinants were identified using AMRFinderPlus v3.10.30 and confirmed by targeted BLASTn searches for \u003cem\u003eC. coli\u003c/em\u003e-specific resistance mutations, including \u003cem\u003egyrA\u003c/em\u003e T86I and 23S rRNA A2075G\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e,\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e. Plasmid reconstruction and typing employed MOB-suite v3.0.3\u003csup\u003e91,92\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eVirulence-associated genes were screened against the Virulence Factors Database (VFDB, 2023 release)\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e. Presence/absence matrices were visualised with phandango and correlated with clinical metadata (diarrhoea severity scores from MAL-ED study\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e) to explore genotype\u0026ndash;phenotype associations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eHistorical data acquisition\u003c/h2\u003e \u003cp\u003eCensus data was retrieved for the estimated human population of Iquitos between 1980 and 2023\u003csup\u003e95\u003c/sup\u003e and combined with historical estimates. In addition, poultry farming estimates were also retrieved for between 1999 and 2025\u003csup\u003e96\u003c/sup\u003e. These were plotted and compared with bacterial effective population sizes of the emerging ST-1150 CC lineage.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData availability\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll assembled genomes and associated metadata are publicly available on PubMLST (individual IDs in \u003cstrong\u003eTable S1\u003c/strong\u003e). Raw sequence reads for previously unpublished isolates are deposited in NCBI SRA under BioProject PRJNA912682. Processed datasets, including AMR profiles, phylogenetic trees, recombination-filtered alignments, and BactDating outputs, are archived on Figshare (doi: 10.6084/m9.figshare.29891339).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInteractive visualisations of key phylogenies are available on Microreact:\u003c/p\u003e\n\u003cp\u003eFull dataset: https://microreact.org/project/uz2vcaYGnrvjPcC5xp2PLV-peru-ccoli-dataset\u003c/p\u003e\n\u003cp\u003eST-1150 CC: https://microreact.org/project/i9BCoHKBx1Dus1FkAvSSke-peru-ccoli-cc1150\u003c/p\u003e\n\u003cp\u003eST-828 CC: https://microreact.org/project/hFfnn1GQNisKqBTPgUbazB-peru-ccoli-cc828\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the participating children, parents, and community health workers in Iquitos, Peru, for their contribution to this study. We gratefully acknowledge the technical assistance of Steven Huynh at USDA-ARS, and Madison P. Goforth and Evangelos Antonios Dimopoulos at the University of Oxford for helpful discussions. Bioinformatics analysis was conducted using high-performance computing infrastructure managed by the University of Arizona. We also thank the PubMLST development team for curating \u003cem\u003eCampylobacter\u003c/em\u003e datasets (curated by Frances M. Colles).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.P., E.M., F.S., C.T.P., K.K.C.\u003c/strong\u003e and \u003cstrong\u003eM.N.K.\u003c/strong\u003e conceived and designed the study. \u003cstrong\u003eM.P.O.\u003c/strong\u003e, \u003cstrong\u003eP.P.Y.\u003c/strong\u003e, \u003cstrong\u003eP.F.G.B.\u003c/strong\u003e, and \u003cstrong\u003eM.N.K.\u003c/strong\u003e coordinated fieldwork, sample collection, and microbiological processing in Iquitos, Peru. \u003cstrong\u003eP.F.G.B.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eK.M.V.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eL.R.C.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eL.F.Z.P.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eW.V.S.L.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eT.P.V.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eA.C.\u003c/strong\u003e,\u0026nbsp;\u003cstrong\u003eJ.N. performed\u0026nbsp;\u003c/strong\u003efieldwork, sample collection, and microbiological processing in Iquitos, Peru.\u0026nbsp;\u003cstrong\u003eV.O.\u003c/strong\u003e, \u003cstrong\u003eC.S.\u003c/strong\u003e and \u003cstrong\u003eM.D.H.\u003c/strong\u003e sequenced genomes used in the study; and\u0026nbsp;\u003cstrong\u003eC.T.P.\u0026nbsp;\u003c/strong\u003eand \u003cstrong\u003eK.K.C.\u003c/strong\u003e performed genome assembly, annotation, and quality control. \u003cstrong\u003eB.P., F.S.\u003c/strong\u003e and \u003cstrong\u003eE.M.\u003c/strong\u003e conducted the population genomic, pangenome, and phylodynamic analyses with input from \u003cstrong\u003eM.N.K.\u003c/strong\u003e, and \u003cstrong\u003eC.T.P.; K.K.C.\u003c/strong\u003e,\u003cstrong\u003eC.T.P.\u0026nbsp;\u003c/strong\u003eand \u003cstrong\u003eS.K.S.\u003c/strong\u003e contributed to metadata curation and contextual interpretation of the epidemiological data. \u003cstrong\u003eB.P., E.M., F.S., C.T.P., K.K.C. and M.N.K.\u003c/strong\u003e wrote the initial draft of the manuscript. All authors reviewed, edited, and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the US National Institutes of Health RO1AI158576 and R21AI63801 (MNK, CTP)\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e5D43TW010913 (MNK and MPO), K43TW012298 (FS) and Gates Foundation (INV-031791). Additional support was obtained by the United States Department of Agriculture-Agricultural Research Service Current Research Information System project 2030-42000-055-00D (to CTP), Ineos Oxford Institute for Antimicrobial Research, and the MRC (BP, SKS). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganization WH (2015) WHO Estimates of the Global Burden of Foodborne Diseases. \u003cem\u003eWorld Health OrganiZation\u003c/em\u003e 254 (2020)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoddard MR et al (2022) A restatement of the natural science evidence base regarding the source, spread and control of Campylobacter species causing human disease. \u003cem\u003eProceedings of the Royal Society B\u003c/em\u003e 289\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmour C et al (2016) Epidemiology and Impact of Campylobacter Infection in Children in 8 Low-Resource Settings: Results from the MAL-ED Study. 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J Pediatr Gastroenterol Nutr 63:466\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Population Prospects \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://population.un.org/wpp/\u003c/span\u003e\u003cspan address=\"https://population.un.org/wpp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHome | Global Agricultural Information Network \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gain.fas.usda.gov/#/home\u003c/span\u003e\u003cspan address=\"https://gain.fas.usda.gov/#/home\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"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":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Campylobacter coli, diarrhoea, child health, One health, poultry intensification","lastPublishedDoi":"10.21203/rs.3.rs-8865396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8865396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eCampylobacter\u003c/em\u003e is a leading cause of bacterial gastroenteritis worldwide, with the highest burden among children in low- and middle-income countries (LMICs). Despite global significance, \u003cem\u003eCampylobacter coli\u003c/em\u003e remains comparatively under-studied. Here we combine population genomics and phylodynamic analysis of 460 \u003cem\u003eC. coli\u003c/em\u003e genomes from the Peruvian Amazon to investigate the emergence of a locally dominant, multidrug-resistant lineage. Genomes were obtained from children with gastroenteritis (n\u0026thinsp;=\u0026thinsp;136) and asymptomatic carriage (n\u0026thinsp;=\u0026thinsp;163) in Iquitos, Peru, alongside isolates from poultry in backyard (n\u0026thinsp;=\u0026thinsp;29) and industrial systems (n\u0026thinsp;=\u0026thinsp;60), pigs (n\u0026thinsp;=\u0026thinsp;36), cattle (n\u0026thinsp;=\u0026thinsp;15), and a small reference collection (n\u0026thinsp;=\u0026thinsp;21). These genomes represented 102 multilocus sequence types (STs) spanning five distinct clonal complexes (CCs). The globally distributed ST-828 clonal complex accounted for most isolates, whereas a distinct lineage, ST-1150 CC, was significantly over-represented in paediatric diarrhoeal cases yet rare elsewhere globally. Time-scaled phylogenies showed that ST-1150 CC emerged and expanded rapidly from the 1980s, coinciding with intensification of poultry production in the region. Genomic antimicrobial-resistance profiling identified extensive acquired resistance to fluoroquinolones, macrolides, and tetracyclines, underpinned by conserved \u003cem\u003ecmeB\u003c/em\u003e efflux-pump variants. Collectively, these findings strongly suggest that agricultural intensification and antimicrobial exposure have driven the ecological emergence and clonal success of a highly adapted \u003cem\u003eC. coli\u003c/em\u003e lineage. This work illustrates how regional farming practices can shape bacterial evolution and resistance trajectories, underscoring the need for integrated One Health genomic surveillance to mitigate the spread of zoonotic pathogens that are global in scope.\u003c/p\u003e","manuscriptTitle":"Recent emergence of a multidrug-resistant Campylobacter coli lineage linked to poultry intensification in the Peruvian Amazon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 17:16:01","doi":"10.21203/rs.3.rs-8865396/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e3257ff0-a7c3-41ff-8ac6-7c8c5b941f6a","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"revise","date":"2026-05-11T20:38:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-08T20:05:07+00:00","index":3,"fulltext":"This content is not available."}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63004417,"name":"Health sciences/Diseases/Gastrointestinal diseases/Gastroenteritis"},{"id":63004418,"name":"Biological sciences/Microbiology/Bacteria/Bacterial genomics"},{"id":63004419,"name":"Biological sciences/Evolution/Phylogenetics"},{"id":63004420,"name":"Biological sciences/Ecology/Microbial ecology"}],"tags":[],"updatedAt":"2026-05-11T20:40:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 17:16:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8865396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8865396","identity":"rs-8865396","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}