{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T05:09:36Z","timestamp":1779426576724,"version":"3.53.1"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:00:00Z","timestamp":1779408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>\n                    Secondary bacterial pneumonia is a severe complication of influenza;howeve the biological determinants that distinguish progression from uncomplicated infection remain poorly understood. We investigated the oropharyngeal microbiome and plasma metabolome as potential discriminators of pneumonia development. In this study, we report a cross-sectional case\u2013control study conducted during the 2022\u20132023 influenza season to identify and internally validate a microbiome-metabolite profile that characterizes pneumonia cases from uncomplicated influenza. We enrolled 236 consecutive influenza patients from Jiangsu Province, China (October 2023\u2013December 2024): 59 with secondary pneumonia and 177 uncomplicated controls. Oropharyngeal swabs were subjected to 16S rRNA V3-V4 sequencing; plasma metabolomics was performed by UPLC-MS\/MS in both ion modes. Seven machine-learning algorithms were compared; Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression was selected because it yielded the highest cross-validated discrimination. Microbial composition distinguished groups, not richness. Pneumonia cases showed enrichment of\n                    <jats:italic>Synergistota<\/jats:italic>\n                    and\n                    <jats:italic>Bifidobacteriaceae<\/jats:italic>\n                    with depletion of\n                    <jats:italic>Bacillaceae<\/jats:italic>\n                    (\u03b2-diversity\n                    <jats:italic>p<\/jats:italic>\n                    \u202f=\u202f0.057). Controls exhibited enriched glycolysis and lipid metabolism pathways; pneumonia cases showed elevated degradation pathways (GLUCARDEG and GALLATE-DEGRADATION). Plasma metabolomics revealed a lipid depletion signature: phospholipids PC(O-16:0\/0:0) and PS(14:0\/18:3(9Z,12Z,15Z)) were significantly reduced (area under the (receiver operating characteristic) curves (AUCs)\u202f=\u202f0.69\u20130.71). Small Molecule Pathway Database (SMPDB) pathway analysis demonstrated suppressed anabolic (tyrosine, steroid, and purine metabolism) and enhanced catabolic (beta-oxidation of very long-chain fatty acids) pathways. Machine learning identified\n                    <jats:italic>Peptococcus<\/jats:italic>\n                    as the top indicator (LASSO AUC\u202f=\u202f0.65); Shapley Additive Explanation (SHAP) analysis revealed a monotonic risk increase with abundance. Oropharyngeal dysbiosis and systemic metabolic reprogramming characterize influenza cases that progress to secondary pneumonia.\n                    <jats:italic>Peptococcus<\/jats:italic>\n                    and four metabolites form an internally validated exploratory profile associated with secondary pneumonia; external validation and performance optimization are warranted.\n                  <\/jats:p>","DOI":"10.3389\/fmicb.2026.1824965","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T04:52:03Z","timestamp":1779425523000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A multi-omics case\u2013control study identifying oropharyngeal microbiome\u2013metabolite patterns that characterize secondary bacterial pneumonia among influenza patients"],"prefix":"10.3389","volume":"17","author":[{"given":"Hong","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongbin","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"102143","DOI":"10.1016\/j.econedurev.2021.102143","article-title":"What is at stake without high-stakes exams? 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