{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T05:57:14Z","timestamp":1790575034792,"version":"4.1.0"},"reference-count":78,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"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                    Fermentation is an effective strategy to prolong the shelf life of soybean residue and improve its value as an animal feed resource. To investigate the influence of differing fermentation conditions on the microbial community and metabolite profile of fermented soybean residue, fresh soybean residue was fermented in sealed anaerobic bag using a mixed inoculum comprising\n                    <jats:italic>Bacillus subtili<\/jats:italic>\n                    s,\n                    <jats:italic>Lacticaseibacillus rhamnosus<\/jats:italic>\n                    ,\n                    <jats:italic>Limosilactobacillus reuteri<\/jats:italic>\n                    , and\n                    <jats:italic>Lactiplantibacillus plantarum<\/jats:italic>\n                    , with varying levels of wheat bran supplementation (0\u201315%), fermentation temperatures (24\u201337 \u00b0C), and durations (24\u201372 h). The microbial community and metabolite profiles were analyzed after fermentation. The results indicated that wheat bran supplementation was the primary factor driving microbial community shift (explaining 49.1% of the axes contributions,\n                    <jats:italic>P<\/jats:italic>\n                    = 0.002), inducing a transition from Proteobacteria-dominated to Firmicutes-dominated communities. The shift was characterized by targeted enrichment of\n                    <jats:italic>Bacillus<\/jats:italic>\n                    and multiple genera of lactic acid bacteria, alongside suppression of potential pathogens, such as Enterobacteriaceae and\n                    <jats:italic>Pseudomonas<\/jats:italic>\n                    . Concurrently, the process of fermentation resulted in a substantial increase in the levels of functional metabolites, including tryptophan, indolelactic acid, and various phenolic acids, accompanied by a reduction in flavonoid content. Fermentation temperature was the primary factor influencing metabolite distribution, explaining 18.1% of the axes contributions (\n                    <jats:italic>P<\/jats:italic>\n                    = 0.002). Network analysis revealed close correlations between specific microbiota (e.g.,\n                    <jats:italic>Lactobacillus<\/jats:italic>\n                    ,\n                    <jats:italic>Limosilactobacillus<\/jats:italic>\n                    ) and key metabolites, including aromatic lactic acid metabolites. The findings presented herein provide insights into substrate-driven microbial modulation during soybean residue fermentation, thus establishing a foundation for optimizing fermentation conditions to enhance feed quality for animal health applications.\n                  <\/jats:p>","DOI":"10.3389\/fmicb.2026.1919307","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T05:44:45Z","timestamp":1790574285000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Substrate-driven shifts in microbial communities reshape metabolite profiles during soybean residue fermentation"],"prefix":"10.3389","volume":"17","author":[{"given":"Gaorui","family":"Bian","sequence":"first","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]},{"name":"Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yamei","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaoxing","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaidong","family":"Deng","sequence":"additional","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minyang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Animal Nutrition and Feed Science, College of Animal Science and Food Engineering, Jinling Institute of Technology","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiyun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyang","family":"Yin","sequence":"additional","affiliation":[{"name":"Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University","place":["Nanjing, China"]},{"name":"Huzhou Academy of Agricultural Sciences","place":["Huzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1039\/c2fo10241b","article-title":"Optimizing the bioactive potential of wheat bran by processing.","volume":"3","author":"Anson","year":"2012","journal-title":"Food Funct."},{"key":"B2","doi-asserted-by":"publisher","first-page":"124284","DOI":"10.1016\/j.fuel.2022.124284","article-title":"Valorization of agro-industrial residues for production of commercial biorefinery products.","volume":"322","author":"Arpit Singh","year":"2022","journal-title":"Fuel"},{"key":"B3","doi-asserted-by":"publisher","first-page":"697","DOI":"10.3390\/microorganisms9040697","article-title":"The role of Enterobacteriaceae in gut microbiota dysbiosis in inflammatory bowel diseases.","volume":"9","author":"Baldelli","year":"2021","journal-title":"Microorganisms"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.1093\/bioinformatics\/btx012","article-title":"Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.","volume":"33","author":"Basu","year":"2017","journal-title":"Bioinformatics"},{"key":"B5","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1038\/s41587-019-0209-9","article-title":"Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.","volume":"37","author":"Bolyen","year":"2019","journal-title":"Nat. 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