Diet-microbiome relationships are often evaluated using isolated nutrients, yet microbes encounter complex food matrices in which nutrient accessibility and baseline microbial community context jointly shape gut fermentation outcomes. This study integrated an in vitro digestion and gut fermentation to examine the nutrient-baseline microbiota interaction to modulate community diversity. Nutrient-defined matrix classes were grouped using free saccharides, free amino acids, and free fatty acids content in food digesta. Two machine learning models—a classification model that predicted nutrient-defined matrix class from genus-level relative abundance changes (0-12 h) and regression models that predicted α-diversity change using nutrient and baseline (0 h) community features—were developed. SHAP-based feature attribution revealed that three nutrient-defined matrix classes exhibited distinct microbial response signatures (Turicibacter/Alistipes/Staphylococcus-centered), suggesting post-digestion nutrient associations with gut microbial restructuring patterns. However, α-diversity shifts within the same nutrient class were bidirectional, and inclusion of baseline microbiota features improved model performance for predicting diversity change from R2 = 0.34 to R2 = 0.72, consistent with a role for baseline-nutrient interactions. Fermented food matrices further illustrated that food-associated microbial contexts can modify restructuring trajectories beyond nutrient profiles. Overall, these findings propose that diversity outcomes during fermentation may depend on baseline-conditioned responses to bioaccessible nutrients, highlighting a matrix-specific but context-dependent diet-microbiome effects.
Hwang et al. (Thu,) studied this question.