{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T12:59:40Z","timestamp":1790773180610,"version":"4.1.0"},"posted":{"date-parts":[[2026,9,25]]},"group-title":"Microbiology","reference-count":92,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.biorxiv.org\/about\/FAQ#license"}],"funder":[{"name":"National Science Foundation","award":["OIA-2418752"],"award-info":[{"award-number":["OIA-2418752"]}]},{"name":"NIH","award":["P20GM103443"],"award-info":[{"award-number":["P20GM103443"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,9,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Antibiotic resistance genes (ARGs) travel from cities into rivers and coastal waters through wastewater treatment plants. Monitoring them normally requires metagenomic sequencing, which is sufficiently costly that most utilities can sample only occasionally. Weather and location data are freely available on a daily basis for virtually any location worldwide, making them attractive predictors for identifying where limited sequencing resources should be prioritized. However, whether such models generalize to previously unseen cities remains largely untested, as most published studies train and evaluate models within the same catchments, thereby assessing interpolation rather than geographic transferability. To address this gap, we paired 235 wastewater metagenomes collected from five European cities with 23 abiotic predictors spanning geospatial, meteorological, hydrological, radiative, and temporal domains. Model performance was evaluated using leave-one-group-out (LOGO) cross-validation, in which all samples from one city were withheld for testing while the remaining cities were used for training. Cat-Boost achieved a median LOGO ROC\u2013AUC of 0.929 and a median F1-score of 0.750. Using freely available environmental reanalysis predictors (meteorological, hydrological, radiative, geospatial, and temporal) \u2014 without any metagenomic sequencing \u2014 CatBoost achieved a mean ROC-AUC of 0.722, recovering 78% of the predictive performance of the full omics-integrated model. Removing latitude and longitude reduced ROC\u2013AUC by only 0.003, whereas replacing random cross-validation with city-wise validation reduced ROC\u2013AUC by 0.052. Predictive performance varied across ARG classes, ranging from a ROC\u2013AUC of 0.981 for\n                  <jats:italic>\u03b2<\/jats:italic>\n                  -lactam resistance genes to 0.762 for glycopeptide resistance genes. These findings demonstrate that freely available environmental reanalysis predictors \u2014 spanning meteorological, hydrological, radiative, geospatial, and temporal domains \u2014 recover 78% of the predictive signal for antibiotic resistance gene occurrence in urban wastewater, allowing scarce sequencing capacity to be directed to the catchments where it changes a decision.\n                <\/jats:p>\n                <jats:sec>\n                  <jats:title>Highlights<\/jats:title>\n                  <jats:list list-type=\"bullet\">\n                    <jats:list-item>\n                      <jats:p>Environmental features predict wastewater ARG risk without deep sequencing (ROC-AUC 0.722)<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>CatBoost generalizes to unseen cities, reaching a LOGO ROC-AUC of 0.929<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Geographic transferability exceeds coordinate contribution (cost 0.052 vs 0.003)<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>The framework prioritizes sequencing resources in data-poor regions at low cost<\/jats:p>\n                    <\/jats:list-item>\n                  <\/jats:list>\n                <\/jats:sec>","DOI":"10.64898\/2026.09.24.753270","type":"posted-content","created":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T03:30:18Z","timestamp":1790393418000},"source":"Crossref","is-referenced-by-count":0,"title":["Predictors Recover Most of the Metagenomic Signal for Antibiotic Resistance Gene Occurrence: A Cross-City Test of Geographic Transferability in Urban Wastewater"],"prefix":"10.64898","author":[{"given":"Somayeh","family":"Falahati Khanaman","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering South Dakota Mines Rapid City SD 57701 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bichar Dip","family":"Shrestha Gurung","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering University of South Dakota Sioux Falls SD 57107 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiva","family":"Aryal","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering University of South Dakota Sioux Falls SD 57107 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengistu","family":"Geza Nisrani","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering South Dakota Mines Rapid City SD 57701 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Venkataramana","family":"Gadhamshetty","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering South Dakota Mines Rapid City SD 57701 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5338-084X","authenticated-orcid":false,"given":"Etienne Z.","family":"Gnimpieba","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering University of South Dakota Sioux Falls SD 57107 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026093005250692000_2026.09.24.753270v1.1","doi-asserted-by":"crossref","unstructured":"T. N. Sheikh , V. P. Bhange , M. A. Soni , Antibiotic resistance in solid waste systems: Environmental and human health threats, Environmental Engineering Science (2025).","DOI":"10.1177\/15579018251389686"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.2","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1007\/s44169-025-00096-2","article-title":"Antimicrobial resistance transmission in environmental matrices: Current prospects and future directions","volume":"263","year":"2025","journal-title":"Reviews of Environmental Contamination and Toxicology"},{"key":"2026093005250692000_2026.09.24.753270v1.3","unstructured":"J. O\u2019Neill , et al., Tackling drug-resistant infections globally: final report and recommendations. 2016 (2018)."},{"key":"2026093005250692000_2026.09.24.753270v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(21)02724-0"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.5","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.1038\/s41467-022-29283-8","article-title":"Assessment of global health risk of antibiotic resistance genes","volume":"13","year":"2022","journal-title":"Nature communications"},{"issue":"8","key":"2026093005250692000_2026.09.24.753270v1.6","doi-asserted-by":"crossref","first-page":"763","DOI":"10.3390\/antibiotics14080763","article-title":"The role of water as a reservoir for antibiotic-resistant bacteria","volume":"14","year":"2025","journal-title":"Antibiotics"},{"key":"2026093005250692000_2026.09.24.753270v1.7","doi-asserted-by":"crossref","first-page":"119241","DOI":"10.1016\/j.ecoenv.2025.119241","article-title":"Environmental emissions of antibiotics and args in china: Trends, regional variability, and the role of socioeconomic factors","volume":"305","year":"2025","journal-title":"Ecotoxicology and Environmental Safety"},{"key":"2026093005250692000_2026.09.24.753270v1.8","doi-asserted-by":"crossref","first-page":"1673343","DOI":"10.3389\/fmicb.2025.1673343","article-title":"Detecting antibiotic resistance: classical, molecular, advanced bioengineering, and ai-enhanced approaches","volume":"16","year":"2025","journal-title":"Frontiers in Microbiology"},{"key":"2026093005250692000_2026.09.24.753270v1.9","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-024-01805-0"},{"key":"2026093005250692000_2026.09.24.753270v1.10","doi-asserted-by":"crossref","unstructured":"S. F. Khanaman , E. Gnimpieba , M. G. Nisrani , V. Gadhamshetty , Aidriven sensor\u2013omics framework for detecting antibiotic resistance in environmental engineering systems, in: 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, 2025, pp. 7574\u20137578.","DOI":"10.1109\/BIBM66473.2025.11356047"},{"key":"2026093005250692000_2026.09.24.753270v1.11","doi-asserted-by":"crossref","first-page":"126252","DOI":"10.1016\/j.jenvman.2025.126252","article-title":"Machine learning approaches for predicting antibiotic resistance genes abundance changes during biological nitrogen removal process","volume":"390","year":"2025","journal-title":"Journal of Environmental Management"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.12","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s13213-025-01814-w","article-title":"The interplay between antimicrobial resistance genes and emerging contaminants in wastewater treatment plants: Key players in one health","volume":"75","year":"2025","journal-title":"Annals of Microbiology"},{"issue":"4","key":"2026093005250692000_2026.09.24.753270v1.13","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1080\/10643389.2020.1835124","article-title":"Removal of antibiotic resistance genes (args) in various wastewater treatment processes: An overview","volume":"52","year":"2022","journal-title":"Critical Reviews in Environmental Science and Technology"},{"key":"2026093005250692000_2026.09.24.753270v1.14","doi-asserted-by":"crossref","unstructured":"M. Zarean , S. H. Dave , S. K. Brar , R. W. Kwong , Environmental drivers of antibiotic resistance: Synergistic effects of climate change, copollutants, and microplastics, Journal of Hazardous Materials Advances (2025) 100768.","DOI":"10.1016\/j.hazadv.2025.100768"},{"key":"2026093005250692000_2026.09.24.753270v1.15","doi-asserted-by":"crossref","unstructured":"L. Wang , X. Gu , K. Hui , T. Yu , Y. Yuan , G. Chen , W. Tan , Interactions between antibiotic resistance genes and soil environmental factors: Coupling, antagonism, and synergism, Emerging Contaminants (2025) 100578.","DOI":"10.1016\/j.emcon.2025.100578"},{"key":"2026093005250692000_2026.09.24.753270v1.16","doi-asserted-by":"crossref","unstructured":"N. T. Zulkifle , M. I. A Wahab , H.-m. Neoh , S. S. Zulfakar , Environmental factors attributed on dissemination of antibiotic-resistant bacteria (arb) and antibiotic resistance genes (args) through pm2. 5 and pm10, Aerobiologia (2025) 1\u201322.","DOI":"10.1007\/s10453-025-09870-0"},{"key":"2026093005250692000_2026.09.24.753270v1.17","doi-asserted-by":"crossref","first-page":"120814","DOI":"10.1016\/j.envres.2025.120814","article-title":"Investigating the antibiotic resistance genes and mobile genetic elements in water systems impacted with anthropogenic pollutants","volume":"269","year":"2025","journal-title":"Environmental Research"},{"issue":"9","key":"2026093005250692000_2026.09.24.753270v1.18","doi-asserted-by":"crossref","first-page":"986","DOI":"10.3390\/mi16090986","article-title":"Electrochemical biosensing for antibiotic-resistant bacteria: Advances, challenges, and future directions","volume":"16","year":"2025","journal-title":"Micromachines"},{"key":"2026093005250692000_2026.09.24.753270v1.19","doi-asserted-by":"publisher","DOI":"10.1111\/j.1574-6941.2008.00629.x"},{"key":"2026093005250692000_2026.09.24.753270v1.20","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2022.153360"},{"key":"2026093005250692000_2026.09.24.753270v1.21","unstructured":"A. A. Zubair , Antibiotic resistance in marine and coastal environments: A systematic review, unpublished or incomplete reference (n.d.)."},{"issue":"4","key":"2026093005250692000_2026.09.24.753270v1.22","doi-asserted-by":"crossref","first-page":"218","DOI":"10.34172\/jaehr.1407","article-title":"Tracking antimicrobial resistance beyond healthcare: Role of environmental monitoring","volume":"13","year":"2025","journal-title":"Journal of Advances in Environmental Health Research"},{"key":"2026093005250692000_2026.09.24.753270v1.23","doi-asserted-by":"crossref","first-page":"140199","DOI":"10.1016\/j.scitotenv.2020.140199","article-title":"Fate of antibiotics and antibiotic resistance genes during conventional and additional treatment technologies in wastewater treatment plants","volume":"741","year":"2020","journal-title":"Science of the Total Environment"},{"key":"2026093005250692000_2026.09.24.753270v1.24","doi-asserted-by":"crossref","unstructured":"E. Buelow , J. R. Bayjanov , E. Majoor , R. J. Willems , M. J. Bonten , H. Schmitt , W. van Schaik , Limited influence of hospital wastewater on the microbiome and resistome of wastewater in a community sewerage system, FEMS microbiology ecology 94 (7) (2018) fiy087.","DOI":"10.1093\/femsec\/fiy087"},{"key":"2026093005250692000_2026.09.24.753270v1.25","doi-asserted-by":"crossref","first-page":"133368","DOI":"10.1016\/j.jhazmat.2023.133368","article-title":"Occurrence and source identification of antibiotics and antibiotic resistance genes in groundwater surrounding urban hospitals","volume":"465","year":"2024","journal-title":"Journal of hazardous materials"},{"key":"2026093005250692000_2026.09.24.753270v1.26","doi-asserted-by":"crossref","first-page":"1492128","DOI":"10.3389\/fmicb.2025.1492128","article-title":"Sludge water: a potential pathway for the spread of antibiotic resistance and pathogenic bacteria from hospitals to the environment","volume":"16","year":"2025","journal-title":"Frontiers in Microbiology"},{"key":"2026093005250692000_2026.09.24.753270v1.27","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0252691"},{"key":"2026093005250692000_2026.09.24.753270v1.28","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-021-14178-w"},{"key":"2026093005250692000_2026.09.24.753270v1.29","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.136001"},{"key":"2026093005250692000_2026.09.24.753270v1.30","doi-asserted-by":"crossref","first-page":"107714","DOI":"10.1016\/j.envint.2022.107714","article-title":"Industrial effluents boosted antibiotic resistome risk in coastal environments","volume":"171","year":"2023","journal-title":"Environment International"},{"issue":"11","key":"2026093005250692000_2026.09.24.753270v1.31","doi-asserted-by":"crossref","first-page":"5723","DOI":"10.3390\/ijerph18115723","article-title":"Antibiotic-resistant bacteria in aquaculture and climate change: A challenge for health in the mediterranean area","volume":"18","year":"2021","journal-title":"International journal of environmental research and public health"},{"issue":"8","key":"2026093005250692000_2026.09.24.753270v1.32","first-page":"001384","article-title":"Cultivating antimicrobial resistance: how intensive agriculture ploughs the way for antibiotic resistance","volume":"169","year":"2023","journal-title":"Microbiology"},{"key":"2026093005250692000_2026.09.24.753270v1.33","doi-asserted-by":"crossref","unstructured":"Y. Sun , R. Chen , S. van den Broek , J. Wen , Y. Li , X. Zeng , S. Su , G. Garland , Transmission and migration of antibiotic resistance genes following agricultural fertilization in sloping croplands, Journal of Hazardous Materials (2026) 141666.","DOI":"10.1016\/j.jhazmat.2026.141666"},{"key":"2026093005250692000_2026.09.24.753270v1.34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoenv.2021.112328"},{"key":"2026093005250692000_2026.09.24.753270v1.35","doi-asserted-by":"publisher","DOI":"10.2134\/jeq2015.06.0317"},{"issue":"2","key":"2026093005250692000_2026.09.24.753270v1.36","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3390\/antibiotics10020209","article-title":"Rapid methods for antimicrobial resistance diagnostics","volume":"10","year":"2021","journal-title":"Antibiotics"},{"issue":"8","key":"2026093005250692000_2026.09.24.753270v1.37","doi-asserted-by":"crossref","first-page":"786","DOI":"10.3390\/antibiotics13080786","article-title":"Rapid phenotypic and genotypic antimicrobial susceptibility testing approaches for use in the clinical laboratory","volume":"13","year":"2024","journal-title":"Antibiotics"},{"key":"2026093005250692000_2026.09.24.753270v1.38","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.coesh.2020.02.004","article-title":"Quantification of antibiotic resistance genes for environmental monitoring: current methods and future directions","volume":"16","year":"2020","journal-title":"Current Opinion in Environmental Science & Health"},{"key":"2026093005250692000_2026.09.24.753270v1.39","doi-asserted-by":"publisher","DOI":"10.1007\/s00248-016-0866-x"},{"key":"2026093005250692000_2026.09.24.753270v1.40","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkad384"},{"key":"2026093005250692000_2026.09.24.753270v1.41","doi-asserted-by":"publisher","DOI":"10.4161\/viru.28196"},{"key":"2026093005250692000_2026.09.24.753270v1.42","doi-asserted-by":"publisher","DOI":"10.1128\/AAC.01310-13"},{"key":"2026093005250692000_2026.09.24.753270v1.43","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3176"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.44","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1038\/ismej.2014.106","article-title":"Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology","volume":"9","year":"2015","journal-title":"The ISME journal"},{"key":"2026093005250692000_2026.09.24.753270v1.45","doi-asserted-by":"publisher","DOI":"10.1093\/NAR\/GKAC920"},{"key":"2026093005250692000_2026.09.24.753270v1.46","doi-asserted-by":"publisher","DOI":"10.1093\/jac\/dks261"},{"key":"2026093005250692000_2026.09.24.753270v1.47","doi-asserted-by":"crossref","first-page":"1437602","DOI":"10.3389\/fmicb.2024.1437602","article-title":"Artificial intelligence tools for the identification of antibiotic resistance genes","volume":"15","year":"2024","journal-title":"Frontiers in Microbiology"},{"issue":"3","key":"2026093005250692000_2026.09.24.753270v1.48","doi-asserted-by":"crossref","first-page":"e1007608","DOI":"10.1371\/journal.pcbi.1007608","article-title":"Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens","volume":"16","year":"2020","journal-title":"PLoS computational biology"},{"key":"2026093005250692000_2026.09.24.753270v1.49","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkw1009"},{"key":"2026093005250692000_2026.09.24.753270v1.50","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-018-0401-z"},{"key":"2026093005250692000_2026.09.24.753270v1.51","doi-asserted-by":"crossref","unstructured":"Q. Wang , X. Yu , S. Han , G. Hu , N. Wu , X. Wang , X. Xu , Predicting changes in antibiotic resistance genes during the anaerobic digestion of swine manure using machine learning, Journal of Environmental Chemical Engineering (2025) 118604.","DOI":"10.1016\/j.jece.2025.118604"},{"key":"2026093005250692000_2026.09.24.753270v1.52","doi-asserted-by":"crossref","unstructured":"Y. Li , J. Ma , X. Li , T. Ling , Y. Zhang , X. Xia , Integrating metagenomics analysis and machine learning to identify drivers of antibiotic resistance genes abundance in microplastic-contaminated soil, Journal of Hazardous Materials (2025) 140886.","DOI":"10.1016\/j.jhazmat.2025.140886"},{"issue":"5","key":"2026093005250692000_2026.09.24.753270v1.53","first-page":"1","article-title":"Artificial intelligence in drug resistance management","volume":"3","year":"2025","journal-title":"Biotech"},{"key":"2026093005250692000_2026.09.24.753270v1.54","doi-asserted-by":"crossref","unstructured":"Z.-C. Zhou , L. Teng , X.-Y. Geng , L. Wang , X. Meng , M. Qiao , K.-Q. Xiao , Z. Zhao , X.-L. Ba , C. Achi , et al., Association of climate change with the spread of antimicrobial resistance genes in salmonella: a longitudinal ecological and modelling study, The Lancet Planetary Health 10 (4) (2026).","DOI":"10.1016\/j.lanplh.2026.101445"},{"key":"2026093005250692000_2026.09.24.753270v1.55","doi-asserted-by":"crossref","first-page":"976657","DOI":"10.3389\/fmicb.2022.976657","article-title":"The source, fate and prospect of antibiotic resistance genes in soil: A review","volume":"13","year":"2022","journal-title":"Frontiers in microbiology"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.56","doi-asserted-by":"crossref","first-page":"7141","DOI":"10.1038\/s41467-025-61606-3","article-title":"Global soil antibiotic resistance genes are associated with increasing risk and connectivity to human resistome","volume":"16","year":"2025","journal-title":"Nature Communications"},{"key":"2026093005250692000_2026.09.24.753270v1.57","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1016\/j.biortech.2017.08.016","article-title":"Effects of superabsorbent polymers on the abundances of antibiotic resistance genes, mobile genetic elements, and the bacterial community during swine manure composting","volume":"244","year":"2017","journal-title":"Bioresource technology"},{"issue":"12","key":"2026093005250692000_2026.09.24.753270v1.58","doi-asserted-by":"crossref","first-page":"7661","DOI":"10.1111\/1462-2920.15631","article-title":"Termite mound formation reduces the abundance and diversity of soil resistomes","volume":"23","year":"2021","journal-title":"Environmental Microbiology"},{"key":"2026093005250692000_2026.09.24.753270v1.59","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2018.02.039"},{"key":"2026093005250692000_2026.09.24.753270v1.60","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2021.149260"},{"key":"2026093005250692000_2026.09.24.753270v1.61","doi-asserted-by":"crossref","unstructured":"C. Yang , Y. Qin , Y. Zhang , A. Farhadi , S. Wang , X. Diao , J. Xie , Distribution and occurrence of antibiotic resistance genes and microbial diversity in western hainan\u2019s inshore seawaters: A seasonal study, Emerging Contaminants (2025) 100550.","DOI":"10.1016\/j.emcon.2025.100550"},{"key":"2026093005250692000_2026.09.24.753270v1.62","doi-asserted-by":"crossref","first-page":"100642","DOI":"10.1016\/j.onehlt.2023.100642","article-title":"Antibiotic resistance genes prevalence prediction and interpretation in beaches affected by urban wastewater discharge","volume":"17","year":"2023","journal-title":"One Health"},{"key":"2026093005250692000_2026.09.24.753270v1.63","doi-asserted-by":"crossref","first-page":"125695","DOI":"10.1016\/j.envpol.2025.125695","article-title":"Antibiotic resistance genes in the coastal atmosphere under varied weather conditions: Distribution, influencing factors, and transmission mechanisms","volume":"368","year":"2025","journal-title":"Environmental Pollution"},{"key":"2026093005250692000_2026.09.24.753270v1.64","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-022-01405-w"},{"key":"2026093005250692000_2026.09.24.753270v1.65","doi-asserted-by":"crossref","unstructured":"J. Bengtsson-Palme , E. Kristiansson , D. J. Larsson , Environmental factors influencing the development and spread of antibiotic resistance, FEMS microbiology reviews 42 (1) (2018) fux053.","DOI":"10.1093\/femsre\/fux053"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.66","doi-asserted-by":"crossref","first-page":"7551","DOI":"10.1038\/s41467-024-51957-8","article-title":"Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance","volume":"15","year":"2024","journal-title":"Nature communications"},{"key":"2026093005250692000_2026.09.24.753270v1.67","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw354"},{"key":"2026093005250692000_2026.09.24.753270v1.68","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty560"},{"key":"2026093005250692000_2026.09.24.753270v1.69","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btv033"},{"key":"2026093005250692000_2026.09.24.753270v1.70","unstructured":"Comune di Bologna, Official website of the city of bologna, accessed July 18, 2026 (2026). URL https:\/\/www.comune.bologna.it"},{"key":"2026093005250692000_2026.09.24.753270v1.71","unstructured":"Municipality of Budapest, Official website of budapest (2024). URL https:\/\/budapest.hu\/en"},{"key":"2026093005250692000_2026.09.24.753270v1.72","unstructured":"City of Copenhagen, City of copenhagen (2026). URL https:\/\/international.kk.dk"},{"key":"2026093005250692000_2026.09.24.753270v1.73","unstructured":"Roma Capitale, Roma capitale \u2013 official website (2026). URL https:\/\/www.comune.roma.it\/web\/en\/home.page"},{"key":"2026093005250692000_2026.09.24.753270v1.74","unstructured":"Rotterdam Partners, Invest in rotterdam (2026). URL https:\/\/www.rotterdam.info\/en\/invest"},{"key":"2026093005250692000_2026.09.24.753270v1.75","unstructured":"L. Prokhorenkova , G. Gusev , A. Vorobev , A. V. Dorogush , A. Gulin , Catboost: unbiased boosting with categorical features, Advances in neural information processing systems 31 (2018)."},{"key":"2026093005250692000_2026.09.24.753270v1.76","first-page":"507","article-title":"Why do tree-based models still outperform deep learning on typical tabular data?","volume":"35","year":"2022","journal-title":"Advances in neural information processing systems"},{"key":"2026093005250692000_2026.09.24.753270v1.77","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2024.100843"},{"key":"2026093005250692000_2026.09.24.753270v1.78","doi-asserted-by":"publisher","DOI":"10.1111\/cts.70056"},{"key":"2026093005250692000_2026.09.24.753270v1.79","doi-asserted-by":"crossref","first-page":"1054316","DOI":"10.3389\/fvets.2022.1054316","article-title":"Removal of antibiotic resistance genes during livestock wastewater treatment processes: Review and prospects","volume":"9","year":"2022","journal-title":"Frontiers in Veterinary Science"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.80","first-page":"e01019","article-title":"Dissemination routes of carbapenem and pan-aminoglycoside resistance mechanisms in hospital and urban wastewater canalizations of ghana","volume":"7","year":"2022","journal-title":"Msystems"},{"key":"2026093005250692000_2026.09.24.753270v1.81","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2018.04.041"},{"issue":"1","key":"2026093005250692000_2026.09.24.753270v1.82","doi-asserted-by":"crossref","first-page":"14847","DOI":"10.1038\/s41598-019-51421-4","article-title":"Occurrence of bacterial markers and antibiotic resistance genes in sub-saharan rivers receiving animal farm wastewaters","volume":"9","year":"2019","journal-title":"Scientific reports"},{"key":"2026093005250692000_2026.09.24.753270v1.83","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2018.03.044"},{"key":"2026093005250692000_2026.09.24.753270v1.84","doi-asserted-by":"publisher","DOI":"10.1038\/s41579-021-00649-x"},{"key":"2026093005250692000_2026.09.24.753270v1.85","doi-asserted-by":"publisher","DOI":"10.1038\/nrmicro2761"},{"key":"2026093005250692000_2026.09.24.753270v1.86","doi-asserted-by":"crossref","first-page":"663","DOI":"10.3389\/fbioe.2020.00663","article-title":"Genomic characterization of mcr-1-carrying salmonella enterica serovar 4,[5], 12: i:-st 34 clone isolated from pigs in china","volume":"8","year":"2020","journal-title":"Frontiers in bioengineering and biotechnology"},{"key":"2026093005250692000_2026.09.24.753270v1.87","doi-asserted-by":"publisher","DOI":"10.1093\/NAR\/GKAC958"},{"key":"2026093005250692000_2026.09.24.753270v1.88","doi-asserted-by":"publisher","DOI":"10.1038\/nrmicro3439"},{"key":"2026093005250692000_2026.09.24.753270v1.89","doi-asserted-by":"publisher","DOI":"10.1289\/ehp.1206446"},{"issue":"4","key":"2026093005250692000_2026.09.24.753270v1.90","first-page":"10","article-title":"Mobile genetic elements associated with antimicrobial resistance","volume":"31","year":"2018","journal-title":"Clinical microbiology reviews"},{"issue":"6","key":"2026093005250692000_2026.09.24.753270v1.91","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1038\/ismej.2014.226","article-title":"Using the class 1 integron-integrase gene as a proxy for anthropogenic pollution","volume":"9","year":"2015","journal-title":"The ISME journal"},{"key":"2026093005250692000_2026.09.24.753270v1.92","unstructured":"NASA POWER Project, Nasa power parameter dictionary, https:\/\/power.larc.nasa.gov\/parameters\/, accessed: 2026-07-25 (2026)."}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.09.24.753270","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T12:25:25Z","timestamp":1790771125000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.64898\/2026.09.24.753270"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,25]]},"references-count":92,"URL":"https:\/\/doi.org\/10.64898\/2026.09.24.753270","relation":{},"subject":[],"published":{"date-parts":[[2026,9,25]]},"subtype":"preprint"}}