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Updated: May 31, 2025

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota
Published on: July 31, 2019
Advances in understanding dietary fiber: Classification, structural characterization, modification, and gut
Yiming Feng1,2, Qing Jin1,3, Xuanbo Liu1
1Department of Food Science and Technology, Virginia Tech, Blacksburg, Virginia, USA.
Abstract:
Gut microbiota and their metabolites profoundly impact host physiology. Targeted modulation of gut microbiota has been a long-term interest in the scientific community. Numerous studies have investigated the feasibility of utilizing dietary fibers (DFs) to modulate gut microbiota and promote the production of health-beneficial bacterial metabolites. However, the complexity of fiber structures, microbiota composition, and their dynamic interactions have hindered the precise prediction of the impact of DF on the gut microbiome. We address this issue with a new perspective, focusing on the inherent chemical and structural complexity of DFs and their interaction with gut microbiota. The chemical and structural complexity of fibers was thoroughly elaborated, encompassing the fibers' molecular composition, polymorphism, mesoscopic structures, porosity, and particle size. Advanced characterization techniques to investigate fiber structural properties were discussed. Additionally, we examined the interactions between DFs and gut microbiota. Finally, we summarized processing techniques to modify fiber structures for improving the fermentability of DF by gut microbiota. The structure of fibers, such as their crystallinity, porosity, degree of branching, and pore wettability, significantly impacts their interactions with gut microbiota. These structural differences also substantially affect fiber's fermentability and capability to modulate the composition of gut microbiota. Conventional approaches are not capable of investigating complex fiber properties and their influences on the gut microbiome; therefore, it is of the essence to involve advanced material characterization techniques and artificial intelligence to unveil more comprehensive information on this topic.
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