Microbial community-scale metabolic modelling predicts personalized short-chain fatty acid production profiles in the human gut.

Microbially derived short-chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. Here we use a microbial community-scale metabolic modelling (MCMM) approach to predict individual-specific SCFA production profiles to assess the impact of different dietary, prebiotic and probiotic inputs. We evaluate the quantitative accuracy of our MCMMs using in vitro and ex vivo data, plus published human cohort data. We find that MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic and probiotic interventions aimed at optimizing SCFA production in the gut. Our model represents an approach to direct gut microbiome engineering for precision health and nutrition.

Microbial community-scale metabolic modeling predicts personalized short chain fatty acid production profiles in the human gut.

Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we show how MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.

Differential cell adhesion to vocal fold extracellular matrix constituents.

The human vocal folds are a complex layering of cells and extracellular matrix. Vocal fold extracellular matrix uniquely contributes to the biomechanical viscoelasticity required for human phonation. We investigated the adhesion of vocal fold stellate cells, a novel cell type first cultured by our laboratory, and fibroblasts to eight vocal fold extracellular matrix components: elastin, decorin, fibronectin, hyaluronic acid, laminin and collagen types I, III and IV. Our data demonstrate that these cells adhere differentially to said substrates at 5 to 120 min. Cells were treated with hyaluronidase and Y-27632, a p160ROCK-specific inhibitor, to test the role of pericellular hyaluronan and Rho-ROCK activation in early and mature adhesion. Reduced adhesion resulted; greater inhibition of fibroblast adhesion was observed. We modulated the fibronectin affinity exhibited by both cell types using Nimesulide, an inhibitor of fibronectin integrin receptors alpha5beta1 and alphavbeta3. Our results are important in understanding vocal fold pathologies, wound healing, scarring, and in developing an accurate organotypic model of the vocal folds.