Metabolomics identifies 208 discriminative features in wheat digestate digestion, suggesting its relevance to diagnostic biomarkers.
Metabolomics is a powerful approach for investigating mechanisms linked to specific diseases or for exploring nutrition and health interaction. It is also recognized as a mature phenotyping tool for identifying diagnostic or prognostic biomarkers. In contrast to extensively studied biological matrices like biological fluids, a notable gap exists in the scientific literature regarding comprehensive, untargeted metabolomic analyses of in vitro digestate matrices. The objectives of this work were to explore the metabolic response associated with an in vitro digestion and identify the metabolic profiles from the artificial gastric digestion of different breads. To reach these objectives, yeast and sourdough breads made with four wheat varieties were digested thanks to a dynamic digester (DIDGIⓇ) mimicking the physiology of the adult gastrointestinal tract. In vitro gastric samples were collected at four temporal stages. An untargeted mass spectrometry-based approach produced 1,343 robust features. Their analysis showed a clear discrimination based on digestion time on the principal component analysis (PCA), independent of the wheat varieties and breadmaking processes. The results also revealed that metabolites can discriminate between the process (with 20 significantly modulated features) and the wheat variety (with 208 significantly modulated features). This study emphasizes the necessity of deepening our understanding of in vitro digestion outcomes, shedding light on novel insights into metabolic transformations and potential applications across diverse scientific disciplines.
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Centeno et al. (2025) studied this question.
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