Genome-scale metabolic modeling-driven design of synbiotics for methane mitigation and quality improvement in...

Methane is a major greenhouse gas with a global warming potential 28 times greater than that of carbon dioxide, making reduction of livestock emissions a critical challenge. Current mitigation strategies, such as feed management, chemical additives, and algae supplementation, face limitations related to safety, supply instability, and economic feasibility. To address these issues, we investigated the development of methane-reducing feeds utilizing synbiotics. In a preliminary study, we evaluated the methane reduction potential of Komagataeibacter intermedius and Zygosaccharomyces parabailii (KZ), two SCOBY-derived strains, and identified prebiotics that promote their colonization. Genome-scale metabolic (GSM) models were constructed for three hydrogen-producing bacteria, five methanogens, and the KZ strain, and their metabolic networks were compared. Five prebiotics (glycerol, oleic acid, menaquinone-7, Gly-Leu, and Gly-Asn-L) were identified as substrates utilized by KZ but not by hydrogen-producing bacteria or methanogens. Coculture experiments confirmed that combined prebiotic treatment significantly enhanced KZ growth. In vitro rumen fermentation assays demonstrated reduced methane emissions in synbiotic-treated groups, with the combined prebiotic treatment resulting in the strongest inhibition. Based on these findings, a synbiotic-based fermented total mixed ration (FTMR) was developed. Synbiotic supplementation alleviated acidification, increased acetic acid production, and enriched bacterial and fungal populations. Microbial community analysis revealed higher abundance of lactic acid bacteria and non-Saccharomyces yeasts, indicating improved fermentation and enhanced feed quality. In conclusion, the synbiotic-based FTMR stabilized pH, altered organic acid profiles, and reshaped microbial communities, with synergistic interactions between lactic acid bacteria and yeast supporting a more stable fermentation environment. These results demonstrate that GSM modeling is effective for designing synbiotic-based feeds and that the newly developed synbiotic FTMR improves fermentation quality. Notably, this study focused on prebiotic identification, synbiotic formulation, are fermentation characterization; direct evaluation of the methane reduction efficacy of FTMR under in vitro and in vivo conditions remains a subject for future investigation.