Chemometric Strategy for Modeling Metabolic Biological Space along the Gastrointestinal Tract and Assessing Microbial Influences

摘要

Over the past decade, the analysis of metabolic data withnadvanced chemometric techniques has offered the potentialnto explore functional relationships among biologicalncompartments in relation to the structure and function ofnthe intestine. However, the employed methodologies,ngenerally based on regression modeling techniques, havengiven emphasis to region-specific metabolic patterns,nwhile providing only limited insights into the spatiotemporalnmetabolic features of the complex gastrointestinalnsystem. Hence, novel approaches are needed to analyzenmetabolic data to reconstruct the metabolic biologicalnspace associated with the evolving structures and functionsnof an organ such as the gastrointestinal tract. Here,nwe report the application of multivariate curve resolutionn(MCR) methodology to model metabolic relationshipsnalong the gastrointestinal compartments in relation to itsnstructure and function using data from our previousnmetabonomic analysis. The method simultaneously summarizesnmetabolite occurrence and contribution to continuousnmetabolic signatures of the different biologicalncompartments of the gut tract. This methodology shedsnnew light onto the complex web of metabolic interactionsnwith gut symbionts that modulate host cell metabolismnin surrounding gut tissues. In the future, such annapproach will be key to provide new insights into thendynamic onset of metabolic deregulations involved innregion-specific gastrointestinal disorders, such as Crohn’sndisease or ulcerative colitis.