{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T23:59:25Z","timestamp":1785110365121,"version":"3.55.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":60,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"the Key Research and Development Project of Sichuan Provincial Science and Technology Program","award":["2024YFFK0071"],"award-info":[{"award-number":["2024YFFK0071"]}]},{"name":"the National Natural Science Foundation of the China Joint Fund for Regional Innovation and Development","award":["No. U21A20333"],"award-info":[{"award-number":["No. U21A20333"]}]},{"name":"Sichuan Science and Technology Program","award":["No.2023NSFSC0530"],"award-info":[{"award-number":["No.2023NSFSC0530"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Microbiol"],"DOI":"10.1186\/s12866-026-05228-9","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T07:15:34Z","timestamp":1779952534000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrated analysis of human-mouse gut microbiota in RSV infection based on machine learning"],"prefix":"10.1186","volume":"26","author":[{"given":"You","family":"Duan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4633-911X","authenticated-orcid":false,"given":"Hanmin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4626-3618","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,28]]},"reference":[{"key":"5228_CR1","doi-asserted-by":"publisher","first-page":"2047","DOI":"10.1016\/S0140-6736(22)00478-0","volume":"399","author":"Y Li","year":"2022","unstructured":"Li Y, et al. Global, regional, and national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus in children younger than 5 years in 2019: a systematic analysis. Lancet Lond Engl. 2022;399:2047\u201364.","journal-title":"Lancet Lond Engl"},{"key":"5228_CR2","doi-asserted-by":"crossref","unstructured":"Marsland BJ, Trompette A, Gollwitzer ES. The Gut\u2013Lung Axis in Respiratory Disease. 12, (2015).","DOI":"10.1513\/AnnalsATS.201503-133AW"},{"key":"5228_CR3","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1038\/s41385-020-00361-8","volume":"14","author":"V Sencio","year":"2021","unstructured":"Sencio V, Machado MG, Trottein F. The lung\u2013gut axis during viral respiratory infections: the impact of gut dysbiosis on secondary disease outcomes. Mucosal Immunol. 2021;14:296\u2013304.","journal-title":"Mucosal Immunol"},{"key":"5228_CR4","doi-asserted-by":"publisher","first-page":"3440","DOI":"10.1016\/j.celrep.2018.03.001","volume":"22","author":"LB Thackray","year":"2018","unstructured":"Thackray LB, et al. Oral Antibiotic Treatment of Mice Exacerbates the Disease Severity of Multiple Flavivirus Infections. Cell Rep. 2018;22:3440\u2013e34536.","journal-title":"Cell Rep"},{"key":"5228_CR5","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.celrep.2019.05.105","volume":"28","author":"KC Bradley","year":"2019","unstructured":"Bradley KC, et al. Microbiota-Driven Tonic Interferon Signals in Lung Stromal Cells Protect from Influenza Virus Infection. Cell Rep. 2019;28:245\u2013e2564.","journal-title":"Cell Rep"},{"key":"5228_CR6","doi-asserted-by":"publisher","first-page":"3273","DOI":"10.1038\/s41467-019-11152-6","volume":"10","author":"KH Antunes","year":"2019","unstructured":"Antunes KH, et al. Microbiota-derived acetate protects against respiratory syncytial virus infection through a GPR43-type 1 interferon response. Nat Commun. 2019;10:3273.","journal-title":"Nat Commun"},{"key":"5228_CR7","doi-asserted-by":"publisher","first-page":"1630","DOI":"10.1038\/s41401-020-00573-5","volume":"42","author":"J Ji","year":"2021","unstructured":"Ji J, et al. Probiotics protect against RSV infection by modulating the microbiota-alveolar-macrophage axis. Acta Pharmacol Sin. 2021;42:1630\u201341.","journal-title":"Acta Pharmacol Sin"},{"key":"5228_CR8","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1186\/s12866-020-01816-5","volume":"20","author":"JN Harding","year":"2020","unstructured":"Harding JN, et al. Altered gut microbiota in infants is associated with respiratory syncytial virus disease severity. BMC Microbiol. 2020;20:140.","journal-title":"BMC Microbiol"},{"key":"5228_CR9","doi-asserted-by":"publisher","first-page":"1193113","DOI":"10.3389\/fcimb.2023.1193113","volume":"13","author":"S Roggiani","year":"2023","unstructured":"Roggiani S, et al. Gut, oral, and nasopharyngeal microbiota dynamics in the clinical course of hospitalized infants with respiratory syncytial virus bronchiolitis. Front Cell Infect Microbiol. 2023;13:1193113.","journal-title":"Front Cell Infect Microbiol"},{"key":"5228_CR10","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1038\/nature11550","volume":"489","author":"CA Lozupone","year":"2012","unstructured":"Lozupone CA, Stombaugh JI, Gordon JI, Jansson JK, Knight R. Diversity, stability and resilience of the human gut microbiota. Nature. 2012;489:220\u201330.","journal-title":"Nature"},{"key":"5228_CR11","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1038\/nbt.3353","volume":"33","author":"L Xiao","year":"2015","unstructured":"Xiao L, et al. A catalog of the mouse gut metagenome. Nat Biotechnol. 2015;33:1103\u20138.","journal-title":"Nat Biotechnol"},{"key":"5228_CR12","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1038\/s41579-023-00984-1","volume":"22","author":"F Asnicar","year":"2024","unstructured":"Asnicar F, Thomas AM, Passerini A, Waldron L. Segata, N. Machine learning for microbiologists. Nat Rev Microbiol. 2024;22:191\u2013205.","journal-title":"Nat Rev Microbiol"},{"key":"5228_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s43705-022-00182-9","volume":"2","author":"R Hern\u00e1ndez Medina","year":"2022","unstructured":"Hern\u00e1ndez Medina R, et al. Machine learning and deep learning applications in microbiome research. ISME Commun. 2022;2:1\u20137.","journal-title":"ISME Commun"},{"key":"5228_CR14","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1038\/s41587-019-0209-9","volume":"37","author":"E Bolyen","year":"2019","unstructured":"Bolyen E, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852\u20137.","journal-title":"Nat Biotechnol"},{"key":"5228_CR15","doi-asserted-by":"publisher","first-page":"1335112","DOI":"10.3389\/fimmu.2024.1335112","volume":"15","author":"H Wang","year":"2024","unstructured":"Wang H, et al. Integrative analysis identifies oxidative stress biomarkers in non-alcoholic fatty liver disease via machine learning and weighted gene co-expression network analysis. Front Immunol. 2024;15:1335112.","journal-title":"Front Immunol"},{"key":"5228_CR16","doi-asserted-by":"publisher","first-page":"e2266","DOI":"10.1002\/hsr2.2266","volume":"7","author":"BS Gharehhasani","year":"2024","unstructured":"Gharehhasani BS, et al. The most important variables associated with death due to COVID-19 disease, based on three data mining models Decision Tree, AdaBoost, and Support Vector Machine: A cross\u2010sectional study. Health Sci Rep. 2024;7:e2266.","journal-title":"Health Sci Rep"},{"key":"5228_CR17","doi-asserted-by":"publisher","unstructured":"Chen T, Guestrin C, XGBoost:. A Scalable Tree Boosting System. in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 785\u2013794ACM, San Francisco California USA, (2016). https:\/\/doi.org\/10.1145\/2939672.2939785.","DOI":"10.1145\/2939672.2939785"},{"key":"5228_CR18","doi-asserted-by":"publisher","first-page":"3034","DOI":"10.1007\/s10278-024-01172-0","volume":"37","author":"W Wang","year":"2024","unstructured":"Wang W, et al. LightGBM is an Effective Predictive Model for Postoperative Complications in Gastric Cancer: A Study Integrating Radiomics with Ensemble Learning. J Imaging Inf Med. 2024;37:3034\u201348.","journal-title":"J Imaging Inf Med"},{"key":"5228_CR19","doi-asserted-by":"publisher","first-page":"e108","DOI":"10.1371\/journal.pbio.0020108","volume":"2","author":"E Bair","year":"2004","unstructured":"Bair E, Tibshirani R. Semi-Supervised Methods to Predict Patient Survival from Gene Expression Data. PLoS Biol. 2004;2:e108.","journal-title":"PLoS Biol"},{"key":"5228_CR20","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.11363","author":"AV Dorogush","year":"2018","unstructured":"Dorogush AV, Ershov V, Gulin A. CatBoost: gradient boosting with categorical features support. Preprint at. 2018. https:\/\/doi.org\/10.48550\/arXiv.1810.11363.","journal-title":"Preprint at"},{"key":"5228_CR21","doi-asserted-by":"publisher","unstructured":"Beck MW. NeuralNetTools: Visualization and Analysis Tools for Neural Networks. J Stat Softw. 85;(2018). https:\/\/doi.org\/10.18637\/jss.v085.i11.","DOI":"10.18637\/jss.v085.i11"},{"key":"5228_CR22","doi-asserted-by":"crossref","unstructured":"Friedman J, Hastie T, Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw. 33, (2010).","DOI":"10.18637\/jss.v033.i01"},{"key":"5228_CR23","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1186\/1471-2105-12-77","volume":"12","author":"X Robin","year":"2011","unstructured":"Robin X, et al. pROC: an open-source package for R and S\u2009+\u2009to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.","journal-title":"BMC Bioinformatics"},{"key":"5228_CR24","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1038\/s41587-020-0548-6","volume":"38","author":"GM Douglas","year":"2020","unstructured":"Douglas GM, et al. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol. 2020;38:685\u20138.","journal-title":"Nat Biotechnol"},{"key":"5228_CR25","doi-asserted-by":"publisher","unstructured":"Yang C et al. ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization. https:\/\/doi.org\/10.1093\/bioinformatics\/btad470.","DOI":"10.1093\/bioinformatics\/btad470"},{"key":"5228_CR26","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/2049-2618-2-15","volume":"2","author":"AD Fernandes","year":"2014","unstructured":"Fernandes AD, et al. Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis. Microbiome. 2014;2:15.","journal-title":"Microbiome"},{"key":"5228_CR27","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.chom.2021.12.003","volume":"30","author":"BS Beresford-Jones","year":"2022","unstructured":"Beresford-Jones BS, et al. The Mouse Gastrointestinal Bacteria Catalogue enables translation between the mouse and human gut microbiotas via functional mapping. Cell Host Microbe. 2022;30:124\u2013e1388.","journal-title":"Cell Host Microbe"},{"key":"5228_CR28","doi-asserted-by":"publisher","first-page":"810","DOI":"10.1016\/S2213-2600(24)00246-7","volume":"12","author":"HJ Zar","year":"2024","unstructured":"Zar HJ, et al. Early-life respiratory syncytial virus disease and long-term respiratory health. Lancet Respir Med. 2024;12:810\u201321.","journal-title":"Lancet Respir Med"},{"key":"5228_CR29","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1038\/nature07540","volume":"457","author":"PJ Turnbaugh","year":"2009","unstructured":"Turnbaugh PJ, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480\u20134.","journal-title":"Nature"},{"key":"5228_CR30","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1038\/nbt.3353","volume":"33","author":"L Xiao","year":"2015","unstructured":"Xiao L, et al. A catalog of the mouse gut metagenome. Nat Biotechnol. 2015;33:1103\u20138.","journal-title":"Nat Biotechnol"},{"key":"5228_CR31","doi-asserted-by":"publisher","first-page":"104062","DOI":"10.1016\/j.micpath.2020.104062","volume":"142","author":"X Ren","year":"2020","unstructured":"Ren X, et al. The distribution characteristics of intestinal microbiota in children with community-acquired pneumonia under five Years of age. Microb Pathog. 2020;142:104062.","journal-title":"Microb Pathog"},{"key":"5228_CR32","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1186\/s40168-023-01472-7","volume":"11","author":"L de Nies","year":"2023","unstructured":"de Nies L, et al. Altered infective competence of the human gut microbiome in COVID-19. Microbiome. 2023;11:46.","journal-title":"Microbiome"},{"key":"5228_CR33","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1038\/nm.3871","volume":"21","author":"D Fan","year":"2015","unstructured":"Fan D, et al. Activation of HIF-1\u03b1 and LL-37 by commensal bacteria inhibits Candida albicans colonization. Nat Med. 2015;21:808\u201314.","journal-title":"Nat Med"},{"key":"5228_CR34","doi-asserted-by":"publisher","first-page":"2934","DOI":"10.1016\/j.celrep.2020.02.013","volume":"30","author":"V Sencio","year":"2020","unstructured":"Sencio V, et al. Gut Dysbiosis during Influenza Contributes to Pulmonary Pneumococcal Superinfection through Altered Short-Chain Fatty Acid Production. Cell Rep. 2020;30:2934\u2013e29476.","journal-title":"Cell Rep"},{"key":"5228_CR35","first-page":"e29927","volume":"14","author":"SS Naik","year":"2022","unstructured":"Naik SS, et al. Association of Gut Microbial Dysbiosis and Hypertension: A Systematic Review. Cureus. 2022;14:e29927.","journal-title":"Cureus"},{"key":"5228_CR36","doi-asserted-by":"publisher","first-page":"2009","DOI":"10.3390\/microorganisms10102009","volume":"10","author":"M Soltysova","year":"2022","unstructured":"Soltysova M, Tomova A, Ostatnikova D. Gut Microbiota Profiles in Children and Adolescents with Psychiatric Disorders. Microorganisms. 2022;10:2009.","journal-title":"Microorganisms"},{"key":"5228_CR37","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1038\/s41398-023-02670-5","volume":"13","author":"M Gao","year":"2023","unstructured":"Gao M, et al. Gut microbiota composition in depressive disorder: a systematic review, meta-analysis, and meta-regression. Transl Psychiatry. 2023;13:379.","journal-title":"Transl Psychiatry"},{"key":"5228_CR38","doi-asserted-by":"publisher","first-page":"2669","DOI":"10.1093\/cid\/ciaa709","volume":"71","author":"S Gu","year":"2020","unstructured":"Gu S, et al. Alterations of the Gut Microbiota in Patients With Coronavirus Disease 2019 or H1N1 Influenza. Clin Infect Dis Off Publ Infect Dis Soc Am. 2020;71:2669\u201378.","journal-title":"Clin Infect Dis Off Publ Infect Dis Soc Am"},{"key":"5228_CR39","doi-asserted-by":"publisher","first-page":"11755","DOI":"10.2147\/JIR.S525880","volume":"18","author":"N Chen","year":"2025","unstructured":"Chen N, Li L, Han Y, Chen Z. The Role of Gut Microbiota in the Modulation of Pulmonary Immune Response to Viral Infection Through the Gut-Lung Axis. J Inflamm Res. 2025;18:11755\u201381.","journal-title":"J Inflamm Res"},{"key":"5228_CR40","doi-asserted-by":"publisher","first-page":"1001313","DOI":"10.3389\/fmicb.2022.1001313","volume":"13","author":"Q Wang","year":"2022","unstructured":"Wang Q, et al. Lactobacillus mucosae exerted different antiviral effects on respiratory syncytial virus infection in mice. Front Microbiol. 2022;13:1001313.","journal-title":"Front Microbiol"},{"key":"5228_CR41","doi-asserted-by":"publisher","first-page":"1197092","DOI":"10.3389\/fmicb.2023.1197092","volume":"14","author":"X Wu","year":"2023","unstructured":"Wu X, Wang J, Tang Y, Jiang J, Li X. Altered intestinal microbiota in children with bronchiolitis. Front Microbiol. 2023;14:1197092.","journal-title":"Front Microbiol"},{"key":"5228_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/19490976.2019.1613124","volume":"11","author":"C Lordan","year":"2020","unstructured":"Lordan C, Thapa D, Ross RP, Cotter PD. Potential for enriching next-generation health-promoting gut bacteria through prebiotics and other dietary components. Gut Microbes. 2020;11:1\u201320.","journal-title":"Gut Microbes"},{"key":"5228_CR43","doi-asserted-by":"publisher","first-page":"5110","DOI":"10.1038\/s41598-023-32227-x","volume":"13","author":"J An","year":"2023","unstructured":"An J, et al. Prediction of breast cancer using blood microbiome and identification of foods for breast cancer prevention. Sci Rep. 2023;13:5110.","journal-title":"Sci Rep"},{"key":"5228_CR44","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.1038\/s12276-022-00846-5","volume":"54","author":"A McDowell","year":"2022","unstructured":"McDowell A, et al. Machine-learning algorithms for asthma, COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects. Exp Mol Med. 2022;54:1586\u201395.","journal-title":"Exp Mol Med"}],"container-title":["BMC Microbiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12866-026-05228-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12866-026-05228-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12866-026-05228-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T23:28:09Z","timestamp":1785108489000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12866-026-05228-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,28]]},"references-count":44,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["5228"],"URL":"https:\/\/doi.org\/10.1186\/s12866-026-05228-9","relation":{},"ISSN":["1471-2180"],"issn-type":[{"value":"1471-2180","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,28]]},"assertion":[{"value":"19 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"not applicable.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"672"}}