The American journal of clinical nutrition · 2026
Genome-scale modeling of the influence of microbiota-derived butyrate on the regulation of human metabolism by the histone deacetylase sirtuin 1.
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Roma Pi Jordi, Alberto Jean-Marc, Paoli Justine, Baspinar Okan, Guéant-Rodriguez Rosa-Maria, Guéant Jean-Louis, Heinken Almut
Аннотация
BACKGROUND: Genome-scale metabolic models predict metabolic flux distributions but typically lack explicit transcriptional regulation, limiting their ability to simulate graded effects of epigenetic modulators such as Sirtuin1.
OBJECTIVES: This study aims to develop and validate a continuous regulatory-metabolic framework integrating sirtuin 1-dependent transcriptional control into human genome-scale metabolism and to quantify the metabolic impact of microbiome-derived butyrate in intestinal epithelial cells.
METHODS: A curated Sirtuin1-centered regulatory network comprising 8 transcriptional regulators, 487 metabolic genes, and 2296 reactions (∼22% of Recon3D) was integrated into the Recon3D reconstruction to generate iSirtuin1_HumanMet. Continuous regulatory logic was implemented within steady-state regulatory flux balance analysis. Tissue-specific models were derived from genotype-tissue expression transcriptomic data using FASTCORE. Human Caco-2 intestinal epithelial cells were treated with 0 to 9 mM sodium butyrate for 72 h. Sirtuin1 protein expression was quantified by Western blot and modeled using an inverse exponential regression (R2 = 0.669). Predicted maximal intracellular production capacities were compared with independent metabolomics data using Spearman correlation.
RESULTS: Simulated Sirtuin1 activation (0.0-1.0) modulated 2296 reactions, with 34.2% of upregulated reactions belonging to fatty acid oxidation. Increasing Sirtuin1 promoted gluconeogenesis and lipid utilization while repressing glycolysis and nucleotide interconversion. Tissue-specific simulations across 54 tissues revealed distinct clustering of metabolic responses. Incorporation of experimentally derived butyrate-Sirtuin1 inhibition resulted in concordant monotonic trends between predicted and measured intracellular metabolites for 10 of 12 metabolites (83%), with Spearman ρ ranging from -0.64 to 0.85 (median ρ ≈ 0.69). Integration of microbiome-predicted butyrate fluxes showed strong host metabolic associations, including correlations as strong as ρ = -0.92 (P = 8.77 × 10-22).
CONCLUSIONS: In Caco-2 intestinal epithelial cells and tissue-specific human metabolic models, continuous integration of Sirtuin1 regulation enables quantitative simulation of graded transcriptional control and microbiome-derived metabolic modulation, providing a systems-level framework to study diet-microbiome-host metabolic interactions.
OBJECTIVES: This study aims to develop and validate a continuous regulatory-metabolic framework integrating sirtuin 1-dependent transcriptional control into human genome-scale metabolism and to quantify the metabolic impact of microbiome-derived butyrate in intestinal epithelial cells.
METHODS: A curated Sirtuin1-centered regulatory network comprising 8 transcriptional regulators, 487 metabolic genes, and 2296 reactions (∼22% of Recon3D) was integrated into the Recon3D reconstruction to generate iSirtuin1_HumanMet. Continuous regulatory logic was implemented within steady-state regulatory flux balance analysis. Tissue-specific models were derived from genotype-tissue expression transcriptomic data using FASTCORE. Human Caco-2 intestinal epithelial cells were treated with 0 to 9 mM sodium butyrate for 72 h. Sirtuin1 protein expression was quantified by Western blot and modeled using an inverse exponential regression (R2 = 0.669). Predicted maximal intracellular production capacities were compared with independent metabolomics data using Spearman correlation.
RESULTS: Simulated Sirtuin1 activation (0.0-1.0) modulated 2296 reactions, with 34.2% of upregulated reactions belonging to fatty acid oxidation. Increasing Sirtuin1 promoted gluconeogenesis and lipid utilization while repressing glycolysis and nucleotide interconversion. Tissue-specific simulations across 54 tissues revealed distinct clustering of metabolic responses. Incorporation of experimentally derived butyrate-Sirtuin1 inhibition resulted in concordant monotonic trends between predicted and measured intracellular metabolites for 10 of 12 metabolites (83%), with Spearman ρ ranging from -0.64 to 0.85 (median ρ ≈ 0.69). Integration of microbiome-predicted butyrate fluxes showed strong host metabolic associations, including correlations as strong as ρ = -0.92 (P = 8.77 × 10-22).
CONCLUSIONS: In Caco-2 intestinal epithelial cells and tissue-specific human metabolic models, continuous integration of Sirtuin1 regulation enables quantitative simulation of graded transcriptional control and microbiome-derived metabolic modulation, providing a systems-level framework to study diet-microbiome-host metabolic interactions.