The Dose-Dependent Influence of Type 2 Resistant Starch on Gut Microbial Communities and Metabolic Outputs: An In Vitro Simulation

This study systematically investigated the dose-response relationship of resistant starch type 2 (RS2; Hi-maize 260; 0-15 g/L) on gut microbial composition, short-chain fatty acid (SCFA)/gas output, and tryptophan catabolism using an in vitro fermentation model. The highest RS2 concentration (15 g/L) elicited optimal metabolic outcomes, including maximal SCFA production; significant H<sub>2</sub>S reduction; and redirected tryptophan metabolism from potentially detrimental indoles toward neuroprotective metabolites. Microbial profiling revealed dose-dependent enrichment of saccharolytic taxa (<i>Bifidobacterium</i>, <i>Lactobacillus</i>) with concomitant suppression of proteolytic pathobionts (e.g., <i>Escherichia-Shigella</i>). Correlation analyses revealed strong positive associations between beneficial microbes and both SCFAs and neuroprotective metabolites, whereas pathogenic taxa correlated inversely with these compounds. Collectively, these findings establish that functionally relevant microbiome modulation requires a sufficiently high, dose-tailored intake of RS2, providing a rational basis for precision dietary strategies aimed at improving host metabolic and gut health.

Authors

Institutions

Publication Details

Journal
Foods
Published
2025-09-19
DOI
https://doi.org/10.3390/foods14183255
Citations
2
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
1.61
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Dose-Dependent Influence of Type 2 Resistant Starch on Gut Microbial Communities and Metabolic Outputs: An In Vitro Simulation

Xiangyu Bian, Hongyuan Zheng, Fang‐Shu Shi, Xiaoqiong Li et al.
2 citations
Foods
Gut microbiota and health
1.61
article

The Dose-Dependent Influence of Type 2 Resistant Starch on Gut Microbial Communities and Metabolic Outputs: An In Vitro Simulation

Xiangyu Bian, Hongyuan Zheng, Fang‐Shu Shi, Xiaoqiong Li, Shuisheng Wu, Jinjun Li
article en
2 citations

Abstract

This study systematically investigated the dose-response relationship of resistant starch type 2 (RS2; Hi-maize 260; 0-15 g/L) on gut microbial composition, short-chain fatty acid (SCFA)/gas output, and tryptophan catabolism using an in vitro fermentation model. The highest RS2 concentration (15 g/L) elicited optimal metabolic outcomes, including maximal SCFA production; significant H<sub>2</sub>S reduction; and redirected tryptophan metabolism from potentially detrimental indoles toward neuroprotective metabolites. Microbial profiling revealed dose-dependent enrichment of saccharolytic taxa (<i>Bifidobacterium</i>, <i>Lactobacillus</i>) with concomitant suppression of proteolytic pathobionts (e.g., <i>Escherichia-Shigella</i>). Correlation analyses revealed strong positive associations between beneficial microbes and both SCFAs and neuroprotective metabolites, whereas pathogenic taxa correlated inversely with these compounds. Collectively, these findings establish that functionally relevant microbiome modulation requires a sufficiently high, dose-tailored intake of RS2, providing a rational basis for precision dietary strategies aimed at improving host metabolic and gut health.

FoodsVol. 14(18)
Fujian University of Traditional Chinese Medicine (CN), ZheJiang Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 15%
Gut microbiota and health
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Dose-Dependent Influence of Type 2 Resistant Starch on Gut Microbial Communities and Metabolic Outputs: An In Vitro Simulation — Xiangyu Bian, Hongyuan Zheng, et al. · Foods (2025) | TGRS Research Map | TGRS