Winter migratory birds may carry diverse antimicrobial resistance genes into Japan

Winter migratory birds may carry diverse antimicrobial resistance genes into Japan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Winter migratory birds may carry diverse antimicrobial resistance genes into Japan Kei Nabeshima, Manabu Onuma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8905247/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Environmental surveillance of antimicrobial resistance (AMR) in wildlife remains limited, despite increasing recognition that resistance determinants can circulate across human, livestock, and natural ecosystems. Migratory waterbirds move long distances and aggregate at shared stopover and wintering sites, potentially facilitating the acquisition and redistribution of antimicrobial resistance genes (ARGs) across regions. However, nationwide evidence describing the breadth of ARGs carried by winter migratory birds in Japan is scarce. We assessed the diversity and distribution of ARGs in pooled fecal samples from winter migratory birds across Japan. Methods We analyzed pooled fecal DNA collected at migratory bird habitats across 12 local governments during the 2021–2022 and 2022–2023 winter seasons (24 pools). Avian host origin was inferred by amplicon sequencing, and ARGs were profiled by probe-based target enrichment with read-based detection (ARG detected at ≥ 10 reads). Results Ducks ( Anas spp.) were the predominant inferred host. ARGs were detected in all areas and included genes associated with resistance to multiple antibiotic classes used in livestock production. Across the two seasons, genes associated with resistance to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in all 12 areas in at least one season. Genes associated with resistance to agents restricted for use in Japanese livestock production, including colistin, erythromycin, chloramphenicol, and rifampicin, were also detected in all 24 pools. Isoniazid-, gentamicin-, meropenem-, and tigecycline-associated genes were detected in 23/24, 20/24, 11/24, and 9/24 pools, respectively. Conclusions These data indicate widespread environmental occurrence of diverse ARGs and support the possibility that migratory birds could contribute to long-distance dispersal of ARGs. Culture-based isolation, phenotypic testing, and quantitative analyses will be needed to identify host bacteria and assess clinical relevance. Migratory birds antimicrobial resistance (AMR) antimicrobial resistance genes (ARGs) target enrichment sequencing fecal microbiome environmental DNA Figures Figure 1 Background Antimicrobial resistance (AMR) has been reported worldwide. The World Health Organization (WHO) has highlighted priority bacterial pathogens and emphasized the urgent need to address antimicrobial resistance through coordinated action [1]. Active surveillance of AMR in medicine and veterinary medicine is currently being promoted, as well as the appropriate use of antibiotics in many countries, including Japan [2], EU [3], USA [4], China [5], India [6], Africa [7], and Australia [8]. By contrast, surveillance of AMR in the environment remains limited, particularly in wildlife. Limitations have been identified regarding isolation and targeting specific antimicrobial resistance genes (ARGs) when conducting AMR surveillance in the environment and wildlife. In the case of isolation-based methods, only indicator bacteria, e.g. Escherichia coli , can be targeted from a diverse range of bacteria, and may therefore miss resistance present in non-target or uncultivable taxa. In contrast, molecular methods targeting predefined ARGs may underestimate the diversity of resistance genes in complex samples. Migratory birds have long attracted significant attention as hosts of avian influenza (AI). Migratory birds migrate long distances without being influenced by national borders, and furthermore, it has been shown that they share their lives with several migratory birds in different areas within their migration routes, thus sharing AI at the same time. Subtypes of AI isolated from migratory birds that flew to Japan were closely related to AI from continental Europe and northern Africa, suggesting that migratory birds from these regions crossed the Eurasian continent to reach Japan while possessing AI [9–11]. In recent years, there have been some reports of migratory birds carrying AMR. Jarma et al . extracted DNA from the feces of waterbirds ( Ciconia ciconia , Larus fuscus , Anser anser , and Grus grus ) in Spain and evaluated the diversity of ARGs [12]. They pointed out that waterbirds are reservoirs of ARGs and may spread ARGs from human environments, such as waste disposal sites, to aquatic environments. Smith et al . conducted a survey of drug-resistant E. coli , Salmonella sp., and Enterococcus spp. in 12 species of birds in Australia and reported that 42% of E. coli , 85% of Enterococcus spp., and 10% of Salmonella sp. were drug-resistant, with many of them resistant to erythromycin, ciprofloxacin, and streptomycin [13]. The report also noted that resident birds were more likely to carry AMR than migratory birds, suggesting that bird populations themselves may serve as reservoirs for AMR. E. coli and Staphylococcus spp. resistant to penicillins, sulfonamide, aminoglycoside, and tetracycline antibiotics have been isolated from migratory birds in Saudi Arabia, which is a stopover point for many migratory birds [14]. Here too, wild birds have been pointed out as a possible reservoir for AMR [15]. Surprisingly, it has been reported that penguins, which are resident birds in the south polar regions where human activity is restricted, carry AMR, and it has been pointed out that southern gulls are spreading this AMR from Indian Ocean area [16,17]. In addition, AMR has been isolated from Arctic terns, which are migratory birds that utilize the north polar regions [18]. These reports indicate that AMR determinants can be widely distributed and may be transported over long distances by avian hosts. Previous reports on AMR in wild birds have mainly used isolation-based methods or methods targeting limited genes, and methods for broadly detecting drug resistance genes have been less commonly applied. In recent years, a method has been developed to selectively concentrate ARGs in the environment using probes and analyze various ARGs using next-generation sequencing, and its use in environmental samples is becoming widespread. This method has high concentration efficiency and is more sensitive than meta-DNA-seq, and has been reported to be an excellent method for tracking ARGs in the environment. In this study, we analyzed ARGs from wild bird feces throughout Japan using target sequences concentrated by probes, and assessed the potential for migratory birds to carry diverse ARGs into Japan. Materials and methods Sample collection This study used fecal samples collected during the 2021-2022 and 2022-2023 avian influenza surveillance seasons (September-March) under Japan’s Avian Influenza Surveillance Project. Migratory bird feces were collected by 12 local governments at migratory bird habitats located along major flyways in Japan (Fig. 1; Table 1). For each local government and season, 100 fecal samples were collected. Equal amounts of fecal material from each sample were pooled to generate one composite sample per local government per season, yielding 24 pooled samples in total. Across the two seasons, 2,400 fecal samples were collected. Ethics approval was not required for this study because samples were non-invasive fecal droppings collected from the environment without handling animals. Table 1. Sampling area, number of reads, and number of detected ARGs Area 2021-2022 season 2022-2023 season Number of reads Number of detected ARGs Number of reads Number of detected ARGs Hokkaido 11971334 327 16602590 233 Akita 77314220 236 32536122 366 Miyagi 29598514 415 13446672 413 Saitama 44560846 250 39490192 489 Shiga 38359012 293 46179402 372 Wakayama 3336806 224 4008526 137 Tottori 3963406 323 7437060 371 Hiroshima 3843542 173 7179072 299 Tokushima 28272724 247 57711776 577 Nagasaki 32571050 492 2925706 297 Kagoshima 45566592 411 8663194 491 Okinawa 28264442 638 121724076 676 Methods DNA extraction Each fecal sample was suspended in phosphate-buffered saline at a 1:1 dilution and homogenized. For each local government and season, equal volumes of the diluted fecal suspensions were combined to generate one pooled suspension. DNA was extracted from 500 μL of each pooled suspension using the QIAamp PowerFecal Pro DNA Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Molecular bird species identification The extracted DNA was used to infer the avian host species from fecal DNA. For bird host inference, amplicon sequencing was performed using modified BirT primers (Table 2) [19] to detect avian DNA from environmental DNA. The 1st PCR was performed in 50 μl reaction mixtures containing, 25 μl of Superfi II premix, 2 μL of DNA sample, 1 μl of each primer (25 μM), and 21 μl of nuclease-free water (Thermo Fisher Scientific, Waltham, MA). The 1st PCR conditions were as follows: 98°C for 30 seconds, followed by 35 cycles at 98 °C for 10 s, 60 °C for 10 s, and 72 °C for 15 s, and the final cycle was followed by extension at 72°C for 5 min. The 1st PCR amplicons were electrophoresed and visualized by E-Gel 2% Agarose Gels (Thermo Fisher Scientific). A band showing the expected size for modified BirT primers (approximately 380 bp) was considered positive and the amplicons were purified by using the AMpure XP beads (Beckman Coulter, Inc, Brea, CA) following the manufacturer’s instructions. The purified PCR products were applied to index PCR using Nextera XT adapters. Index PCR was performed in 50 μl reaction mixtures containing, 25 μl of Superfi II premix, 2 μL of purified DNA, 5 μl of each index primer (Nextera XT Index Kit v2; Illumina, San Diego, CA), and 13 μl of nuclease-free water. The index PCR conditions were as follows: 98°C for 30 seconds, followed by 8 cycles at 98 °C for 10 s, 60 °C for 10 s, and 72 °C for 15 s, and the final cycle was followed by extension at 72°C for 5 min. Index PCR products were purified by using the AMpure XP beads (Beckman Coulter, Inc) following the manufacturer’s instructions. Then, library concentrations were measured by Qubit (Thermo Fisher Scientific). All libraries were adjusted to the same concentration and mixed in equal volumes. Indexed libraries were prepared for each pooled sample (n=24) and sequenced as independent libraries on an Illumina MiSeq run with a 30% PhiX spike-in, following the manufacturer’s instructions. In the analysis, reads were merged, quality-filtered, and formatted using flash2 (v2.2.00), fastp (v1.1.0), and seqkit (v2.12.0), respectively [20-22]. Then, bird species were determined by local BLASTn (v2.17.0) [23] against RefSeq avian mitochondrial genomes for the formatted reads. In addition, the host taxa of birds in feces was estimated by integrating the BLAST results with migratory bird arrivals at various locations that were visually confirmed by Migratory Bird Survey in 2021-2022 and 2022-2023 seasons [24]. Table 2. Primers used in this study Name Sequence Notes BirT-F-adapter TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG YGGTAAATCYTGTGCCAGC A Nextera XT adaptor was added to the end of each primer for use in amplicon sequencing. The parts that correspond to Nextera adaptors are underlined. BirT-R-adapter GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG AAGTCCTTAGAGTTTYAAGCGTT Capture sequencing of ARGs using QIAseq xHYB AMR panels and bioinformatics analysis using GeneGlobe Libraries for antimicrobial resistance gene (ARG) profiling were prepared using the QIAseq xHYB AMR panel (Qiagen) according to the manufacturer’s instructions, with 30 ng of input DNA per pooled sample. Sequencing was performed on an Illumina NovaSeq X platform with 2×150 bp paired-end sequencing outsourced to Macrogen Japan. A minimum of 2 million reads was required; the achieved depth per pool is summarized in Table 1. The fastq files generated in this analysis were deposited in DDBJ Sequence Read Archive under accession number PRJDB40359. The fastq files were uploaded to Qiagen GeneGlobe and analyzed using the Antimicrobial Resistance Analysis workflow (accessed on 25 December 2023). The GeneGlobe pipeline analyses were run using the platform’s default settings. The analysis results file is provided as Additional file 1 (Supplementary Table 1). We defined an ARG as “detected” when ≥10 reads were assigned to the corresponding target. ARGs corresponding to clinically important antibiotics were summarized with reference to the WHO list of Critically Important Antimicrobials for Human Medicine (6th revision) [25] and Japanese veterinary antimicrobial sales statistics [26]. Large language models (ChatGPT, OpenAI) were used for English grammar and phrasing only; all scientific content was verified by the authors. Results Bird species identification Amplicon sequencing with modified BirT primers was performed on DNA extracted from pooled fecal samples (n=24). In total, 1.65M reads were generated, and 68k reads per pooled sample (mean) were retained after quality filtering for downstream analyses. Based on BLASTn assignments, we detected avian genetic signatures corresponding to 13 avian taxa (Table 3). All detected taxa had also been recorded in the same seasons and regions by the Ministry of the Environment’s migratory bird arrival survey [24], supporting the molecular host assignments. Ducks ( Anas spp.) were the predominant inferred hosts across pooled samples. Table 3 . Estimated host origin of samples by season and area Area 2021-2022 season 2022-2023 season Hokkaido AA, AC, AF, AP, Anas clypeata , Anser sp., Branta sp. Cygnus columbianus AA, AC, AF, AP, MS, Anser sp., Anas clypeata , Branta sp., Cygnus columbianus Akita AA, AC, AP, MS, FA, Cygnus columbianus AA, AC, AF,AP, MS Miyagi AA, AC, AF, AP AA, AC, AF, AP, FA, MS Saitama AA, AF, AP, MS, FA, Ardea sp., Cygnus columbianus , Melanitta sp. AA, AC, AF, AP, FA, MS, Anser sp. Shiga AA, AC, AF, AP, MS, Ardea sp. Anas clypeata AA, AF, AP, FA, MS, Ardea sp. Wakayama AA, AC, AF, AP, FA, MS, Anas clypeata AA, AC, AP, MS, Anas clypeata Tottori AA, AC, AF, AP, FA, MS, Branta sp., Aythya sp., Cygnus columbianus , Anser sp. AA, AC, AF, AP Hiroshima AA, AC, AF, AP, FA, MS, Anas clypeata AA, AP, AC, AF, MS, FA, Anas clypeata Tokushima AA, AC, AF, AP, MS AA, AP, AF, MS Nagasaki AA, AF, AP, MS, FA, Ardea sp. AA, AP, AC, AF, MS, Anas clypeata Kagoshima AA, AP, AF, AC, MS, Ardea sp., AA, AP, AC, AF, MS FA Anas clypeata Okinawa AA, AP, AC, AF, Ardea sp., Gallinula sp. AA, AP, AC, AF, MS, FA Abbreviation: AA: Anas acuta , AC: Anas crecca , AF: Anas falcata , AP: Anas platyrhynchos , MS: Mareca strepera , FA: Fulica atra Sequencing output and ARG detection overview A total of 704 million sequencing reads were analyzed. For the 2021-2022 season, 347 million reads were analyzed in total, with a mean of 28.9 million reads per pool (median 28.9 million). The number of detected ARG targets per pool ranged from 173 to 638 (median 280.5; mean 331.2). For the 2022–2023 season, 357 million reads were analyzed in total, with a mean of 29.8 million reads per pool (median 15.0 million), indicating substantial between-pool variability in sequencing depth. The number of ARG targets detected per pool ranged from 137 to 676 (median 346.5; mean 364.6). Sequencing depth explained a limited fraction of the variability in detected ARG counts (linear regression; R² = 0.2676). We therefore focused on presence/absence summaries using the ≥10-reads threshold. ARG targets were grouped by the antibiotics to which they confer resistance, and the presence/absence of ARG targets for 23 antibiotics (Table 4) was summarized for each pooled sample with reference to Critically Important Antimicrobials for Human Medicine (6th revision) [25] and Japanese veterinary antimicrobial sales statistics [26]. ARG targets corresponding to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in all 12 areas in at least one of the two seasons. In addition, ARG targets associated with meropenem and tigecycline were detected in 11/24 and 9/24 pooled samples, respectively, corresponding to 7/12 areas with detection in at least one season for each agent. ARG targets corresponding to veterinary antibiotics with high sales volumes in Japan were detected in all pooled samples. Moreover, ARG targets associated with antibiotics restricted for use in Japanese livestock production (colistin, erythromycin, and chloramphenicol) as well as agents primarily used in human medicine (rifampicin and isoniazid) were detected across a broad geographic range. Table 4. Antibiotic categories screened and detection of associated resistance genes across pooled samples (≥10 reads). Antibiotics Detected from (Number of detected pools) Use in livestock production. Sales volumes in the livestock production （ kg ） Gentamicin All areas (20/24) 〇（mainly in cow） 39 Cephalosporins All areas (24/24) 〇 8027 Macrolides All areas (24/24) 〇 157721 Tetracyclines All areas (24/24) 〇 305751 Fosfomycin All areas (24/24) 〇 373 Clindamycin All areas (24/24) 〇 151 Penicillins All areas (24/24) 〇 89024 Streptogramins All areas (24/24) 〇 No data Sulfonamides/Trimethoprim All areas (24/24) 〇 81959 Colistin All areas (24/24) 〇 (only in treatment) 266357 Erythromycin All areas (24/24) 〇(mainly in fish) 84692 Chloramphenicol All areas (24/24) 〇(mainly in companion animal) 0.4 Rifampicin All areas (24/24) - - Isoniazid All areas (23/24) - - Meropenem A part of areas* (11/24) - - Tigecycline A part of areas** (9/24) - - Aztreonam - - - *: 2021-2022: Hokkaido, Tokushima, Tottori, Wakayama, 2022-2023: Hiroshima, Hokkaido, Kagoshima, Okinawa, Tokushima, Tottori, Wakayama **: 2021-2022: Hiroshima, Nagasaki, Okinawa, Wakayama, 2022-2023: Hiroshima, Kagoshima, Miyagi, Okinawa, Tokushima Discussion Amplicon sequencing of fecal DNA was used to infer the host taxa of the fecal pools, and the predominant hosts were identified as Anatidae (ducks and geese; Anas spp. and Mareca strepera ) and Rallidae ( Fulica atra ) based on both molecular results and field observations. Tundra swans ( Cygnus columbianus ) were observed in Hokkaido and Saitama, and their DNA was also detected in the corresponding fecal pools. These findings support that the fecal samples used in this study originated from winter migratory birds arriving in Japan. Among the detected ARGs, we summarized ARG targets annotated as conferring resistance to 23 antibiotics with reference to the WHO list of Critically Important Antimicrobials for Human Medicine: 6th revision [25] and Sales Values of Veterinary Antimicrobials in Japan[26]. ARG targets linked to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in pools from all areas in at least one season. Because gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, and sulfonamides/trimethoprim are widely used in livestock production in Japan, these results suggest that bacteria carrying corresponding resistance genes may have disseminated into the environment and subsequently been acquired by migratory birds. Except for isoniazid, multiple resistance genes were detected for each antimicrobial category, indicating a diverse resistome rather than reliance on a single determinant. This pattern suggests that resistance may be supported by multiple genetic factors and potentially heterogeneous mechanisms within the microbial community. In contrast, colistin, erythromycin, and chloramphenicol are not commonly used in livestock production in Japan under current practice. Colistin has been prohibited for use as a feed additive since 2018. Erythromycin is used primarily in aquaculture rather than in terrestrial livestock, and high erythromycin resistance rates have been reported in bacteria isolated from Japanese fishery products [2]. Chloramphenicol is generally avoided due to toxicity concerns and is largely restricted to limited applications in companion animals. For colistin, it remains unclear whether migratory birds retained resistance genes acquired before 2018 or acquired colistin resistance outside Japan during migration. For erythromycin, given its frequent use in aquatic environments and the reported high resistance rates in aquatic bacteria, acquisition of erythromycin-associated ARGs by migratory birds may occur. For chloramphenicol, reports of chloramphenicol-resistant bacteria are rare in Japan, whereas a high prevalence has been reported in pig farms in China [27] (82.04%; 1535/1871), raising the possibility that migratory birds may acquire chloramphenicol-resistant bacteria from livestock-associated environments outside Japan and transport them to Japan. Rifampicin and isoniazid are not approved as veterinary medicinal products in Japan and are primarily used as anti-tuberculosis drugs. In Japan, resistance to rifampicin and isoniazid has not been confirmed in livestock, and resistance rates in human tuberculosis are also low (approximately 5.6% and 1.1%, respectively) [2]. Therefore, these resistance genes may reflect acquisition outside Japan. Similarly, meropenem and tigecycline are not used in livestock in Japan; however, resistance genes to these agents have been reported from farms in other countries [28,29], suggesting that at least a subset of these detections may reflect acquisition outside Japan. Conclusion Our findings are consistent with the potential for migratory birds, particularly ducks, to contribute to the long-distance transport of ARGs. The detection of resistance genes that are not typically associated with Japanese livestock settings highlights the need for broader, international surveillance of ARG dynamics in environmental and wildlife reservoirs. Our findings suggest that diverse ARGs are widespread in the sampled environments. This study has several limitations. First, we did not perform bacterial isolation, and therefore it remains unclear whether bacteria harboring the detected ARGs exhibit phenotypic antimicrobial resistance. Second, because the samples were collected within the framework of avian influenza surveillance, we were unable to evaluate summer samples or resident bird populations. Continued and expanded surveillance will be required to address these gaps. Third, because we used a probe-based enrichment panel, detection is limited to targeted ARGs and may not capture the full resistome. Nevertheless, by comprehensively targeting ARGs using probe-based enrichment sequencing, this approach enables relatively straightforward detection of potentially high-risk resistance determinants compared with culture-based methods. Therefore, this method may be useful for future environmental and wildlife-focused ARGs surveillance studies. Abbreviations AMR Antimicrobial resistance ARGs Antimicrobial resistance genes Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and materials: All data are publicly available from the DDBJ Sequence Read Archive under BioProject PRJDB40359 (https://ddbj.nig.ac.jp/resource/bioproject/PRJDB40359). Supplementary outputs are provided as Additional file 1. Competing interests: The authors declare that they have no competing interests. Funding: This work was supported by National Institute for Environmental Studies (NIES) Research Funding (Type B). Authors' contributions: KN performed the molecular experiments, analyzed the data, and drafted the manuscript. MO conceived and designed the study, coordinated sample collection, supervised the study, and critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgements: Language editing assistance was provided using large language models (ChatGPT, OpenAI) for grammar and phrasing; all scientific content was verified by the authors. Authors’ information: Not applicable. References World Health Organization. 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Supplementary Files Additionalfile1.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Mar, 2026 Reviews received at journal 20 Mar, 2026 Reviews received at journal 12 Mar, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 23 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 20 Feb, 2026 First submitted to journal 17 Feb, 2026 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8905247","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598007293,"identity":"63ca3a64-47b8-4111-b483-7c86d9bd8858","order_by":0,"name":"Kei Nabeshima","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYFACHgYGxgYJIIONgSGhAsQFAzZitZwhXgtUEWMbEc4yZz978OHPHRbR/A1siQ8ezrsjw89/gPnFBwa+PFxaLHvyko15z0jkzjjAdtggcdszHskZCWyWMxjYinFpMTiQYybN2CaR23CAvU0icdthHoMbDGzGPAxsiQ24tJx/Y/7zJ1DL/APs7T8S5xzmsT9/gICWGzlmDLxALRsOsB1jSGwA2sKQwPwYv5Z3ydIgLRsPsyVLJBw7zCNxI7GNcYYBHr+czz348WdbXe68422GH3/UHLbn7z98+MOHimM4QwwBmOEsYGgwGBxLIKwFWfcHBoYa0rSMglEwCkbBcAYAlAZYmCZyfRAAAAAASUVORK5CYII=","orcid":"","institution":"National Institute for Environmental Studies","correspondingAuthor":true,"prefix":"","firstName":"Kei","middleName":"","lastName":"Nabeshima","suffix":""},{"id":598007297,"identity":"5d1088fc-fe08-4cf6-960a-8a78a9e53d69","order_by":1,"name":"Manabu Onuma","email":"","orcid":"","institution":"National Institute for Environmental Studies","correspondingAuthor":false,"prefix":"","firstName":"Manabu","middleName":"","lastName":"Onuma","suffix":""}],"badges":[],"createdAt":"2026-02-18 02:53:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8905247/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8905247/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103711259,"identity":"0c072a68-70d3-45b7-80c6-02cc2a8aabc5","added_by":"auto","created_at":"2026-03-02 03:46:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":691328,"visible":true,"origin":"","legend":"\u003cp\u003eSampling areas by local government\u003c/p\u003e\n\u003cp\u003eMap of Japan showing sampling areas by local government. Sampling areas are shown in orange.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8905247/v1/1699345246cbbfbccb3b557d.png"},{"id":103711261,"identity":"2fc2244a-e657-4546-964f-0046730bb912","added_by":"auto","created_at":"2026-03-02 03:46:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1346510,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8905247/v1/ec6185bf-48ee-41ba-be15-fa3f8390bbb5.pdf"},{"id":103711260,"identity":"21ee33bf-d684-48e8-828e-13cd0964e932","added_by":"auto","created_at":"2026-03-02 03:46:27","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":783400,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8905247/v1/aee75c21dcd0d067825e3bb9.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Winter migratory birds may carry diverse antimicrobial resistance genes into Japan","fulltext":[{"header":"Background","content":"\u003cp\u003eAntimicrobial resistance (AMR) has been reported worldwide. The World Health Organization (WHO) has highlighted priority bacterial pathogens and emphasized the urgent need to address antimicrobial resistance through coordinated action [1]. Active surveillance of AMR in medicine and veterinary medicine is currently being promoted, as well as the appropriate use of antibiotics in many countries, including Japan [2], EU [3], USA [4], China [5], India [6], Africa [7], and Australia [8]. By contrast, surveillance of AMR in the environment remains limited, particularly in wildlife. Limitations have been identified regarding isolation and targeting specific antimicrobial resistance genes (ARGs) when conducting AMR surveillance in the environment and wildlife. In the case of isolation-based methods, only indicator bacteria, e.g. \u003cem\u003eEscherichia coli\u003c/em\u003e, can be targeted from a diverse range of bacteria, and may therefore miss resistance present in non-target or uncultivable taxa. In contrast, molecular methods targeting predefined ARGs may underestimate the diversity of resistance genes in complex samples.\u003c/p\u003e \u003cp\u003eMigratory birds have long attracted significant attention as hosts of avian influenza (AI). Migratory birds migrate long distances without being influenced by national borders, and furthermore, it has been shown that they share their lives with several migratory birds in different areas within their migration routes, thus sharing AI at the same time. Subtypes of AI isolated from migratory birds that flew to Japan were closely related to AI from continental Europe and northern Africa, suggesting that migratory birds from these regions crossed the Eurasian continent to reach Japan while possessing AI [9\u0026ndash;11].\u003c/p\u003e \u003cp\u003eIn recent years, there have been some reports of migratory birds carrying AMR. Jarma \u003cem\u003eet al\u003c/em\u003e. extracted DNA from the feces of waterbirds (\u003cem\u003eCiconia ciconia\u003c/em\u003e, \u003cem\u003eLarus fuscus\u003c/em\u003e, \u003cem\u003eAnser anser\u003c/em\u003e, and \u003cem\u003eGrus grus\u003c/em\u003e) in Spain and evaluated the diversity of ARGs [12]. They pointed out that waterbirds are reservoirs of ARGs and may spread ARGs from human environments, such as waste disposal sites, to aquatic environments. Smith \u003cem\u003eet al\u003c/em\u003e. conducted a survey of drug-resistant \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eSalmonella\u003c/em\u003e sp., and \u003cem\u003eEnterococcus\u003c/em\u003e spp. in 12 species of birds in Australia and reported that 42% of \u003cem\u003eE. coli\u003c/em\u003e, 85% of \u003cem\u003eEnterococcus\u003c/em\u003e spp., and 10% of \u003cem\u003eSalmonella\u003c/em\u003e sp. were drug-resistant, with many of them resistant to erythromycin, ciprofloxacin, and streptomycin [13]. The report also noted that resident birds were more likely to carry AMR than migratory birds, suggesting that bird populations themselves may serve as reservoirs for AMR. \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eStaphylococcus\u003c/em\u003e spp. resistant to penicillins, sulfonamide, aminoglycoside, and tetracycline antibiotics have been isolated from migratory birds in Saudi Arabia, which is a stopover point for many migratory birds [14]. Here too, wild birds have been pointed out as a possible reservoir for AMR [15]. Surprisingly, it has been reported that penguins, which are resident birds in the south polar regions where human activity is restricted, carry AMR, and it has been pointed out that southern gulls are spreading this AMR from Indian Ocean area [16,17]. In addition, AMR has been isolated from Arctic terns, which are migratory birds that utilize the north polar regions [18]. These reports indicate that AMR determinants can be widely distributed and may be transported over long distances by avian hosts.\u003c/p\u003e \u003cp\u003ePrevious reports on AMR in wild birds have mainly used isolation-based methods or methods targeting limited genes, and methods for broadly detecting drug resistance genes have been less commonly applied. In recent years, a method has been developed to selectively concentrate ARGs in the environment using probes and analyze various ARGs using next-generation sequencing, and its use in environmental samples is becoming widespread. This method has high concentration efficiency and is more sensitive than meta-DNA-seq, and has been reported to be an excellent method for tracking ARGs in the environment. In this study, we analyzed ARGs from wild bird feces throughout Japan using target sequences concentrated by probes, and assessed the potential for migratory birds to carry diverse ARGs into Japan.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eSample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used fecal samples collected during the 2021-2022 and 2022-2023 avian influenza surveillance seasons (September-March) under Japan\u0026rsquo;s Avian Influenza Surveillance Project. Migratory bird feces were collected by 12 local governments at migratory bird habitats located along major flyways in Japan (Fig. 1; Table 1). For each local government and season, 100 fecal samples were collected. Equal amounts of fecal material from each sample were pooled to generate one composite sample per local government per season, yielding 24 pooled samples in total. Across the two seasons, 2,400 fecal samples were collected. Ethics approval was not required for this study because samples were non-invasive fecal droppings collected from the environment without handling animals.\u003c/p\u003e\n\u003cp\u003eTable 1. Sampling area, number of reads, and number of detected ARGs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003eArea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 226px;\"\u003e\n \u003cp\u003e2021-2022 season\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 227px;\"\u003e\n \u003cp\u003e2022-2023 season\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNumber of reads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNumber of detected ARGs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNumber of reads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNumber of detected ARGs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eHokkaido\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e11971334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e16602590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAkita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e77314220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e32536122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eMiyagi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e29598514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e13446672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e413\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eSaitama\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e44560846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e39490192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e489\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eShiga\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e38359012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e46179402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eWakayama\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3336806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4008526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eTottori\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3963406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e7437060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eHiroshima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3843542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e7179072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eTokushima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e28272724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e57711776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNagasaki\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e32571050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2925706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eKagoshima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e45566592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e8663194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e491\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eOkinawa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e28264442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e121724076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach fecal sample was suspended in phosphate-buffered saline at a 1:1 dilution and homogenized. For each local government and season, equal volumes of the diluted fecal suspensions were combined to generate one pooled suspension. DNA was extracted from 500 \u0026mu;L of each pooled suspension using the QIAamp PowerFecal Pro DNA Kit (Qiagen, Hilden, Germany) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular bird species identification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe extracted DNA was used to infer the avian host species from fecal DNA. For bird host inference, amplicon sequencing was performed using modified BirT primers (Table 2) [19] to detect avian DNA from environmental DNA. The 1st PCR was performed in 50 \u0026mu;l reaction mixtures containing, 25 \u0026mu;l of Superfi II premix, 2 \u0026mu;L of DNA sample, 1 \u0026mu;l of each primer (25 \u0026mu;M), and 21 \u0026mu;l of nuclease-free water (Thermo Fisher Scientific, Waltham, MA). The 1st PCR conditions were as follows: 98\u0026deg;C for 30 seconds, followed by 35 cycles at 98 \u0026deg;C for 10 s, 60 \u0026deg;C for 10 s, and 72 \u0026deg;C for 15 s, and the final cycle was followed by extension at 72\u0026deg;C for 5 min. The 1st PCR amplicons were electrophoresed and visualized by E-Gel 2% Agarose Gels (Thermo Fisher Scientific). A band showing the expected size for modified BirT primers (approximately 380 bp) was considered positive and the amplicons were purified by using the AMpure XP beads (Beckman Coulter, Inc, Brea, CA) following the manufacturer\u0026rsquo;s instructions. The purified PCR products were applied to index PCR using Nextera XT adapters. Index PCR was performed in 50 \u0026mu;l reaction mixtures containing, 25 \u0026mu;l of Superfi II premix, 2 \u0026mu;L of purified DNA, 5 \u0026mu;l of each index primer (Nextera XT Index Kit v2; Illumina, San Diego, CA), and 13 \u0026mu;l of nuclease-free water. The index PCR conditions were as follows: 98\u0026deg;C for 30 seconds, followed by 8 cycles at 98 \u0026deg;C for 10 s, 60 \u0026deg;C for 10 s, and 72 \u0026deg;C for 15 s, and the final cycle was followed by extension at 72\u0026deg;C for 5 min. Index PCR products were purified by using the AMpure XP beads (Beckman Coulter, Inc) following the manufacturer\u0026rsquo;s instructions. Then, library concentrations were measured by Qubit (Thermo Fisher Scientific).\u003c/p\u003e\n\u003cp\u003eAll libraries were adjusted to the same concentration and mixed in equal volumes. Indexed libraries were prepared for each pooled sample (n=24) and sequenced as independent libraries on an Illumina MiSeq run with a 30% PhiX spike-in, following the manufacturer\u0026rsquo;s instructions. In the analysis, reads were merged, quality-filtered, and formatted using flash2 (v2.2.00), fastp (v1.1.0), and seqkit (v2.12.0), respectively [20-22]. Then, bird species were determined by local BLASTn (v2.17.0) [23] against RefSeq avian mitochondrial genomes for the formatted reads. In addition, the host taxa of birds in feces was estimated by integrating the BLAST results with migratory bird arrivals at various locations that were visually confirmed by Migratory Bird Survey in 2021-2022 and 2022-2023 seasons [24].\u003c/p\u003e\n\u003cp\u003eTable 2. Primers used in this study\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"577\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 342px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirT-F-adapter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 342px;\"\u003e\n \u003cp\u003e\u003cu\u003eTCGTCGGCAGCGTCAGATGTGTATAAGAGACAG\u003c/u\u003e\u003c/p\u003e\n \u003cp\u003eYGGTAAATCYTGTGCCAGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eA Nextera XT adaptor was added to the end of each primer for use in amplicon sequencing. The parts that correspond to Nextera adaptors are underlined.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirT-R-adapter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 342px;\"\u003e\n \u003cp\u003e\u003cu\u003eGTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG\u003c/u\u003e\u003c/p\u003e\n \u003cp\u003eAAGTCCTTAGAGTTTYAAGCGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eCapture sequencing of ARGs using QIAseq xHYB AMR panels and bioinformatics analysis using GeneGlobe\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLibraries for antimicrobial resistance gene (ARG) profiling were prepared using the QIAseq xHYB AMR panel (Qiagen) according to the manufacturer\u0026rsquo;s instructions, with 30 ng of input DNA per pooled sample. Sequencing was performed on an Illumina NovaSeq X platform with 2\u0026times;150 bp paired-end sequencing outsourced to Macrogen Japan. A minimum of 2 million reads was required; the achieved depth per pool is summarized in Table 1. The fastq files generated in this analysis were deposited in DDBJ Sequence Read Archive under accession number PRJDB40359.\u003c/p\u003e\n\u003cp\u003eThe fastq files were uploaded to Qiagen GeneGlobe and analyzed using the Antimicrobial Resistance Analysis workflow (accessed on 25 December 2023). The GeneGlobe pipeline analyses were run using the platform\u0026rsquo;s default settings. The analysis results file is provided as Additional file 1 (Supplementary Table 1). We defined an ARG as \u0026ldquo;detected\u0026rdquo; when \u0026ge;10 reads were assigned to the corresponding target. ARGs corresponding to clinically important antibiotics were summarized with reference to the WHO list of Critically Important Antimicrobials for Human Medicine (6th revision) [25] and Japanese veterinary antimicrobial sales statistics [26].\u003c/p\u003e\n\u003cp\u003eLarge language models (ChatGPT, OpenAI) were used for English grammar and phrasing only; all scientific content was verified by the authors.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBird species identification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmplicon sequencing with modified BirT primers was performed on DNA extracted from pooled fecal samples (n=24). In total, 1.65M reads were generated, and 68k reads per pooled sample (mean) were retained after quality filtering for downstream analyses. Based on BLASTn assignments, we detected avian genetic signatures corresponding to 13 avian taxa (Table 3). All detected taxa had also been recorded in the same seasons and regions by the Ministry of the Environment\u0026rsquo;s migratory bird arrival survey [24], supporting the molecular host assignments. Ducks (\u003cem\u003eAnas\u003c/em\u003e spp.) were the predominant inferred hosts across pooled samples.\u003c/p\u003e\n\u003cp\u003eTable 3 . Estimated host origin of samples by season and area\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eArea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021-2022 season\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022-2023 season\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eHokkaido\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e, \u003cem\u003eAnser\u003c/em\u003e sp., \u003cem\u003eBranta\u003c/em\u003e sp. \u003cem\u003eCygnus columbianus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, MS, \u003cem\u003eAnser\u003c/em\u003e sp., \u003cem\u003eAnas clypeata\u003c/em\u003e, \u003cem\u003eBranta\u003c/em\u003e sp., \u003cem\u003eCygnus columbianus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAkita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AP, MS, FA,\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCygnus columbianus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF,AP, MS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eMiyagi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC,\u0026nbsp;AF, AP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, FA, MS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eSaitama\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AF, AP, MS, FA, \u003cem\u003eArdea\u003c/em\u003e sp., \u003cem\u003eCygnus columbianus\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMelanitta\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, FA, MS, \u003cem\u003eAnser\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eShiga\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, MS,\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eArdea\u003c/em\u003e sp. \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AF, AP, FA, MS, \u003cem\u003eArdea\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eWakayama\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, FA, MS, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AP, MS, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eTottori\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, FA, MS, \u003cem\u003eBranta\u003c/em\u003e sp., \u003cem\u003eAythya\u003c/em\u003e sp.,\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCygnus columbianus\u003c/em\u003e, \u003cem\u003eAnser\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eHiroshima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, FA, MS, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AC, AF, MS, FA, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eTokushima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AC, AF, AP, MS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AF, MS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eNagasaki\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AF, AP, MS, FA, \u003cem\u003eArdea\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AC, AF, MS, \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eKagoshima\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AF, AC,\u0026nbsp;MS,\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eArdea\u003c/em\u003e sp.,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AC, AF, MS FA \u003cem\u003eAnas\u0026nbsp;clypeata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eOkinawa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AC, AF, \u003cem\u003eArdea\u003c/em\u003e sp., \u003cem\u003eGallinula\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eAA, AP, AC, AF, MS, FA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: AA: \u003cem\u003eAnas acuta\u003c/em\u003e, AC: \u003cem\u003eAnas crecca\u003c/em\u003e, AF: \u003cem\u003eAnas falcata\u003c/em\u003e, AP: \u003cem\u003eAnas platyrhynchos\u003c/em\u003e, MS: \u003cem\u003eMareca strepera\u003c/em\u003e, FA: \u003cem\u003eFulica atra\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequencing output and ARG detection overview\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 704 million sequencing reads were analyzed. For the 2021-2022 season, 347 million reads were analyzed in total, with a mean of 28.9 million reads per pool (median 28.9 million). The number of detected ARG targets per pool ranged from 173 to 638 (median 280.5; mean 331.2). For the 2022\u0026ndash;2023 season, 357 million reads were analyzed in total, with a mean of 29.8 million reads per pool (median 15.0 million), indicating substantial between-pool variability in sequencing depth. The number of ARG targets detected per pool ranged from 137 to 676 (median 346.5; mean 364.6). Sequencing depth explained a limited fraction of the variability in detected ARG counts (linear regression; R\u0026sup2; = 0.2676). We therefore focused on presence/absence summaries using the \u0026ge;10-reads threshold.\u003c/p\u003e\n\u003cp\u003eARG targets were grouped by the antibiotics to which they confer resistance, and the presence/absence of ARG targets for 23 antibiotics (Table 4) was summarized for each pooled sample with reference to Critically Important Antimicrobials for Human Medicine (6th revision) [25] and Japanese veterinary antimicrobial sales statistics [26]. ARG targets corresponding to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in all 12 areas in at least one of the two seasons. In addition, ARG targets associated with meropenem and tigecycline were detected in 11/24 and 9/24 pooled samples, respectively, corresponding to 7/12 areas with detection in at least one season for each agent. ARG targets corresponding to veterinary antibiotics with high sales volumes in Japan were detected in all pooled samples. Moreover, ARG targets associated with antibiotics restricted for use in Japanese livestock production (colistin, erythromycin, and chloramphenicol) as well as agents primarily used in human medicine (rifampicin and isoniazid) were detected across a broad geographic range.\u003c/p\u003e\n\u003cp\u003eTable 4. Antibiotic categories screened and detection of associated resistance genes across pooled samples (\u0026ge;10 reads).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDetected from\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Number of detected pools)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse in livestock production.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSales volumes in the livestock production\u003c/strong\u003e\u003cstrong\u003e （\u003c/strong\u003e\u003cstrong\u003ekg\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGentamicin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (20/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇（mainly in cow）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCephalosporins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e8027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMacrolides\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e157721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTetracyclines\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e305751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFosfomycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e373\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClindamycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePenicillins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e89024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStreptogramins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eNo data\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSulfonamides/Trimethoprim\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e81959\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eColistin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇\u0026nbsp;(only in treatment)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e266357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eErythromycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇(mainly in fish)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e84692\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChloramphenicol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e〇(mainly in companion animal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRifampicin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (24/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsoniazid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eAll areas (23/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeropenem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eA part of areas* (11/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTigecycline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eA part of areas** (9/24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAztreonam\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*: \u0026nbsp;2021-2022: Hokkaido, Tokushima, Tottori, Wakayama, 2022-2023: Hiroshima, Hokkaido, Kagoshima, Okinawa, Tokushima, Tottori, Wakayama\u003c/p\u003e\n\u003cp\u003e**: 2021-2022: Hiroshima, Nagasaki, Okinawa, Wakayama, 2022-2023: Hiroshima, Kagoshima, Miyagi, Okinawa, Tokushima\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAmplicon sequencing of fecal DNA was used to infer the host taxa of the fecal pools, and the predominant hosts were identified as Anatidae (ducks and geese; \u003cem\u003eAnas\u003c/em\u003e spp. and \u003cem\u003eMareca strepera\u003c/em\u003e) and Rallidae (\u003cem\u003eFulica atra\u003c/em\u003e) based on both molecular results and field observations. Tundra swans (\u003cem\u003eCygnus columbianus\u003c/em\u003e) were observed in Hokkaido and Saitama, and their DNA was also detected in the corresponding fecal pools. These findings support that the fecal samples used in this study originated from winter migratory birds arriving in Japan.\u003c/p\u003e\n\u003cp\u003eAmong the detected ARGs, we summarized ARG targets annotated as conferring resistance to 23 antibiotics with reference to the WHO list of Critically Important Antimicrobials for Human Medicine: 6th revision [25] and Sales Values of Veterinary Antimicrobials in Japan[26]. ARG targets linked to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in pools from all areas in at least one season. Because gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, and sulfonamides/trimethoprim are widely used in livestock production in Japan, these results suggest that bacteria carrying corresponding resistance genes may have disseminated into the environment and subsequently been acquired by migratory birds. Except for isoniazid, multiple resistance genes were detected for each antimicrobial category, indicating a diverse resistome rather than reliance on a single determinant. This pattern suggests that resistance may be supported by multiple genetic factors and potentially heterogeneous mechanisms within the microbial community.\u003c/p\u003e\n\u003cp\u003eIn contrast, colistin, erythromycin, and chloramphenicol are not commonly used in livestock production in Japan under current practice. Colistin has been prohibited for use as a feed additive since 2018. Erythromycin is used primarily in aquaculture rather than in terrestrial livestock, and high erythromycin resistance rates have been reported in bacteria isolated from Japanese fishery products [2]. Chloramphenicol is generally avoided due to toxicity concerns and is largely restricted to limited applications in companion animals. For colistin, it remains unclear whether migratory birds retained resistance genes acquired before 2018 or acquired colistin resistance outside Japan during migration. For erythromycin, given its frequent use in aquatic environments and the reported high resistance rates in aquatic bacteria, acquisition of erythromycin-associated ARGs by migratory birds may occur. For chloramphenicol, reports of chloramphenicol-resistant bacteria are rare in Japan, whereas a high prevalence has been reported in pig farms in China [27] (82.04%; 1535/1871), raising the possibility that migratory birds may acquire chloramphenicol-resistant bacteria from livestock-associated environments outside Japan and transport them to Japan.\u003c/p\u003e\n\u003cp\u003eRifampicin and isoniazid are not approved as veterinary medicinal products in Japan and are primarily used as anti-tuberculosis drugs. In Japan, resistance to rifampicin and isoniazid has not been confirmed in livestock, and resistance rates in human tuberculosis are also low (approximately 5.6% and 1.1%, respectively) [2]. Therefore, these resistance genes may reflect acquisition outside Japan. Similarly, meropenem and tigecycline are not used in livestock in Japan; however, resistance genes to these agents have been reported from farms in other countries [28,29], suggesting that at least a subset of these detections may reflect acquisition outside Japan.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings are consistent with the potential for migratory birds, particularly ducks, to contribute to the long-distance transport of ARGs. The detection of resistance genes that are not typically associated with Japanese livestock settings highlights the need for broader, international surveillance of ARG dynamics in environmental and wildlife reservoirs. Our findings suggest that diverse ARGs are widespread in the sampled environments. This study has several limitations. First, we did not perform bacterial isolation, and therefore it remains unclear whether bacteria harboring the detected ARGs exhibit phenotypic antimicrobial resistance. Second, because the samples were collected within the framework of avian influenza surveillance, we were unable to evaluate summer samples or resident bird populations. Continued and expanded surveillance will be required to address these gaps. Third, because we used a probe-based enrichment panel, detection is limited to targeted ARGs and may not capture the full resistome. Nevertheless, by comprehensively targeting ARGs using probe-based enrichment sequencing, this approach enables relatively straightforward detection of potentially high-risk resistance determinants compared with culture-based methods. Therefore, this method may be useful for future environmental and wildlife-focused ARGs surveillance studies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntimicrobial resistance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARGs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntimicrobial resistance genes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eAll data are publicly available from the DDBJ Sequence Read Archive under BioProject PRJDB40359 (https://ddbj.nig.ac.jp/resource/bioproject/PRJDB40359). Supplementary outputs are provided as Additional file 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by National Institute for Environmental Studies (NIES) Research Funding (Type B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003eKN performed the molecular experiments, analyzed the data, and drafted the manuscript. MO conceived and designed the study, coordinated sample collection, supervised the study, and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eLanguage editing assistance was provided using large language models (ChatGPT, OpenAI) for grammar and phrasing; all scientific content was verified by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ information:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. WHO\u0026apos;s list of medically important antimicrobials: a risk management tool for mitigating antimicrobial resistance due to non-human use. Geneva: World Health Organization; 2024.\u003c/li\u003e\n \u003cli\u003eThe AMR One Health Surveillance Committee. Nippon AMR One Health Report (NAOR) 2024. Tokyo: Division of Infectious Diseases Prevention and Control, Department of Infectious Disease Prevention and Control, Public Health Bureau, Ministry of Health, Labour and Welfare; 2024.\u003c/li\u003e\n \u003cli\u003eEuropean Centre for Disease Prevention and Control; WHO Regional Office for Europe. Surveillance of antimicrobial resistance in Europe, 2023 data: executive summary. Stockholm: European Centre for Disease Prevention and Control; 2024.\u003c/li\u003e\n \u003cli\u003eCenters for Disease Control and Prevention. Antimicrobial resistance. https://www.cdc.gov/antimicrobial-resistance/index.html Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eChina Antimicrobial Surveillance Network (CHINET). Institute of Antibiotics, Huashan Hospital, Fudan University. http://www.chinets.com/ Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eNational Centre for Disease Control (India). National programme on AMR containment. https://ncdc.mohfw.gov.in/national-programme-on-amr-containment/ Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eWHO, Regional Office for Africa. (2025) iAHO. https://aho.afro.who.int/ Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eAustralian Government. Surveillance of antimicrobial use and resistance in human health. https://www.amr.gov.au/australias-response/objective-5-integrated-surveillance-and-response-resistance-and-usage/surveillance-antimicrobial-use-and-resistance-human-health Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eNabeshima K, Takadate Y, Soda K, Hiono T, Isoda N, Sakoda Y, et al. Detection of H5N1 high pathogenicity avian influenza viruses in four raptors and two geese in Japan in the fall of 2022. Viruses. 2023;15(9):1865. doi:10.3390/v15091865.\u003c/li\u003e\n \u003cli\u003eEsaki M, Okuya K, Tokorozaki K, Haraguchi Y, Hasegawa T, Ozawa M. Highly pathogenic avian influenza A(H5N1) outbreak in endangered cranes, Izumi Plain, Japan, 2022-23. Emerging Infectious Diseases. 2025;31(5):937-947. doi:10.3201/eid3105.241410.\u003c/li\u003e\n \u003cli\u003eHew YL, Hiono T, Monne I, Nabeshima K, Sakuma S, Kumagai A, et al. Cocirculation of genetically distinct highly pathogenic avian influenza H5N5 and H5N1 viruses in crows, Hokkaido, Japan. Emerging Infectious Diseases. 2024;30(9):1912-1917. doi:10.3201/eid3009.240356.\u003c/li\u003e\n \u003cli\u003eJarma D, S\u0026aacute;nchez MI, Green AJ, Peralta-S\u0026aacute;nchez JM, Hortas F, S\u0026aacute;nchez-Melsi\u0026oacute; A, et al. Faecal microbiota and antibiotic resistance genes in migratory waterbirds with contrasting habitat use. The Science of the Total Environment. 2021;783:146872. doi:10.1016/j.scitotenv.2021.146872.\u003c/li\u003e\n \u003cli\u003eSmith HG, Bean DC, Clarke RH, Loyn R, Larkins JA, Hassell C, Greenhill AR. Presence and antimicrobial resistance profiles of Escherichia coli, Enterococcus spp. and Salmonella sp. in 12 species of Australian shorebirds and terns. Zoonoses and Public Health. 2022;69(6):615-624. doi:10.1111/zph.12950.\u003c/li\u003e\n \u003cli\u003eBegum R, Asha NA, Dipu DCC, Roy M, Rahman A, Chowdhury MSR, et al. Virulence and antimicrobial resistance patterns of Salmonella spp. recovered from migratory and captive wild birds. Veterinary Medicine and Science. 2024;10(6):e70102. doi:10.1002/vms3.70102.\u003c/li\u003e\n \u003cli\u003eElsohaby I, Samy A, Elmoslemany A, Alorabi M, Alkafafy M, Aldoweriej A, et al. Migratory wild birds as a potential disseminator of antimicrobial-resistant bacteria around Al-Asfar Lake, Eastern Saudi Arabia. Antibiotics (Basel). 2021;10(3):260. doi:10.3390/antibiotics10030260.\u003c/li\u003e\n \u003cli\u003eMiller RV, Gammon K, Day MJ. Antibiotic resistance among bacteria isolated from seawater and penguin fecal samples collected near Palmer Station, Antarctica. Canadian Journal of Microbiology. 2009;55(1):37-45. doi:10.1139/W08-119.\u003c/li\u003e\n \u003cli\u003eSegawa T, Takahashi A, Kokubun N, Ishii S. Spread of antibiotic resistance genes to Antarctica by migratory birds. The Science of the Total Environment. 2024;923:171345. doi:10.1016/j.scitotenv.2024.171345.\u003c/li\u003e\n \u003cli\u003ePrakash EA, Hrom\u0026aacute;dkov\u0026aacute; T, Jabir T, Vipindas PV, Krishnan KP, Mohamed Hatha AA, et al. Dissemination of multidrug resistant bacteria to the polar environment - role of the longest migratory bird Arctic tern (Sterna paradisaea). The Science of the Total Environment. 2022;815:152727. doi:10.1016/j.scitotenv.2021.152727.\u003c/li\u003e\n \u003cli\u003eThalinger B, Empey R, Cowperthwaite M, Coveny K, Steinke D. 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Migratory Bird Survey. https://www.env.go.jp/nature/dobutsu/bird_flu/migratory/ap_wr_transit/index.html Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Critically important antimicrobials for human medicine, 6th revision. Geneva: World Health Organization; 2019.\u003c/li\u003e\n \u003cli\u003eNational Veterinary Assay Laboratory. Sales values of veterinary antimicrobials. https://www.maff.go.jp/nval/yakuzai/yakuzai_p3_6.html Accessed 29 Jan 2025.\u003c/li\u003e\n \u003cli\u003ePeng Z, Hu Z, Li Z, Zhang X, Jia C, Li T, et al. Antimicrobial resistance and population genomics of multidrug-resistant Escherichia coli in pig farms in mainland China. Nature Communications. 2022;13(1):1116. doi:10.1038/s41467-022-28750-6.\u003c/li\u003e\n \u003cli\u003eYu Y, Shao C, Gong X, Quan H, Liu D, Chen Q, Chu Y. Antimicrobial resistance surveillance of tigecycline-resistant strains isolated from herbivores in Northwest China. Microorganisms. 2022;10(12):2432. doi:10.3390/microorganisms10122432.\u003c/li\u003e\n \u003cli\u003eYang Y, Sun Y, Zhou Z, Song Y, Zhu Y, Zhou W, et al. Surveillance of Escherichia coli antimicrobial resistance in pig farms in Zhejiang province, China: high prevalence of multidrug resistance and risk-associated genes. Microbial Pathogenesis. 2025;204:107598. doi:10.1016/j.micpath.2025.107598.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"one-health-outlook","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oneh","sideBox":"Learn more about [One Health Outlook](https://onehealthoutlook.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/oneh/default.aspx","title":"One Health Outlook","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Migratory birds, antimicrobial resistance (AMR), antimicrobial resistance genes (ARGs), target enrichment sequencing, fecal microbiome, environmental DNA","lastPublishedDoi":"10.21203/rs.3.rs-8905247/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8905247/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEnvironmental surveillance of antimicrobial resistance (AMR) in wildlife remains limited, despite increasing recognition that resistance determinants can circulate across human, livestock, and natural ecosystems. Migratory waterbirds move long distances and aggregate at shared stopover and wintering sites, potentially facilitating the acquisition and redistribution of antimicrobial resistance genes (ARGs) across regions. However, nationwide evidence describing the breadth of ARGs carried by winter migratory birds in Japan is scarce. We assessed the diversity and distribution of ARGs in pooled fecal samples from winter migratory birds across Japan.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe analyzed pooled fecal DNA collected at migratory bird habitats across 12 local governments during the 2021\u0026ndash;2022 and 2022\u0026ndash;2023 winter seasons (24 pools). Avian host origin was inferred by amplicon sequencing, and ARGs were profiled by probe-based target enrichment with read-based detection (ARG detected at \u0026ge;\u0026thinsp;10 reads).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDucks (\u003cem\u003eAnas\u003c/em\u003e spp.) were the predominant inferred host. ARGs were detected in all areas and included genes associated with resistance to multiple antibiotic classes used in livestock production. Across the two seasons, genes associated with resistance to gentamicin, cephalosporins, macrolides, tetracyclines, fosfomycin, clindamycin, penicillins, streptogramins, sulfonamides/trimethoprim, colistin, erythromycin, chloramphenicol, rifampicin, and isoniazid were detected in all 12 areas in at least one season. Genes associated with resistance to agents restricted for use in Japanese livestock production, including colistin, erythromycin, chloramphenicol, and rifampicin, were also detected in all 24 pools. Isoniazid-, gentamicin-, meropenem-, and tigecycline-associated genes were detected in 23/24, 20/24, 11/24, and 9/24 pools, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThese data indicate widespread environmental occurrence of diverse ARGs and support the possibility that migratory birds could contribute to long-distance dispersal of ARGs. Culture-based isolation, phenotypic testing, and quantitative analyses will be needed to identify host bacteria and assess clinical relevance.\u003c/p\u003e","manuscriptTitle":"Winter migratory birds may carry diverse antimicrobial resistance genes into Japan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 03:46:17","doi":"10.21203/rs.3.rs-8905247/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-23T18:36:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T22:24:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-12T09:13:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"131872333913243898351178793261099488230","date":"2026-02-27T08:28:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35269135287291703608074912041585497382","date":"2026-02-24T11:42:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-23T14:41:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T12:47:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T09:48:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"One Health Outlook","date":"2026-02-18T02:47:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"one-health-outlook","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oneh","sideBox":"Learn more about [One Health Outlook](https://onehealthoutlook.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/oneh/default.aspx","title":"One Health Outlook","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1442c14c-85c9-4458-bbb3-df7b9bc3b696","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T14:23:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 03:46:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8905247","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8905247","identity":"rs-8905247","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}