Wu Xuangao, Yang Hee-Jong, Ryu Myeong-Seon, Jung Su-Jin, Ha Kwangsu, Jeong Do-Yeon, Park Sunmin
Department of Bioconvergence, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, Asan 31499, ChungNam-do, Republic of Korea.
Department of R&D, Microbial Institute for Fermentation Industry, 61-27 Minsokmaeul-gil, Sunchang-gun 56048, Republic of Korea.
Nutrients. 2024 Dec 31;17(1):138. doi: 10.3390/nu17010138.
The relationship between gut microbiota composition, lifestyles, and colonic transit time (CTT) remains poorly understood. This study investigated associations among gut microbiota profiles, diet, lifestyles, and CTT in individuals with subjective constipation.
We conducted a secondary analysis of data from our randomized clinical trial, examining gut microbiota composition, CTT, and dietary intake in baseline and final assessments of 94 participants with subjective constipation. Participants were categorized into normal-transit (<36 h) and slow-transit (≥36 h) groups based on CTT at baseline. Gut microbiota composition was measured using 16S rRNA sequencing, and dietary patterns were assessed through semi-quantitative food frequency questionnaires. Enterotype analysis, machine learning approaches, and metabolic modeling were employed to investigate microbiota-diet interactions. The constipated participants primarily belonged to Lachnospiraceae (ET-L).
The slow-transit group showed higher alpha diversity than the normal-transit group. was abundant in the normal-transit group, while , , and were abundant in the slow-transit group, which also had a higher abundance of mucin-degrading bacteria. Metabolic modeling predicted increased N-acetyl-D-glucosamine (GlcNAc), a mucin-derived metabolite, in the slow-transit group. Network analysis identified two microbial co-abundance groups (CAG3 and CAG9) significantly associated with transit time and dietary patterns. Six mucin-degrading species showed differential correlations with GlcNAc and a plant-based diet, particularly, including rice, bread, fruits and vegetables, and fermented beans. In conclusion, an increased abundance of mucin-degrading bacteria and their predicted metabolic products were associated with delayed CTT.
These findings suggest dietary modulation of these bacterial populations as a potential therapeutic strategy for constipation. Moreover, our results reveal a potential immunometabolic mechanism where mucin-degrading bacteria and their metabolic interactions may influence intestinal transit, mucosal barrier function, and immune response.
肠道微生物群组成、生活方式与结肠传输时间（CTT）之间的关系仍知之甚少。本研究调查了主观便秘患者的肠道微生物群谱、饮食、生活方式与CTT之间的关联。
我们对随机临床试验的数据进行了二次分析，在94名主观便秘参与者的基线和最终评估中检查肠道微生物群组成、CTT和饮食摄入量。根据基线时的CTT将参与者分为正常传输（<36小时）和慢速传输（≥36小时）组。使用16S rRNA测序测量肠道微生物群组成，并通过半定量食物频率问卷评估饮食模式。采用肠型分析、机器学习方法和代谢建模来研究微生物群与饮食的相互作用。便秘参与者主要属于毛螺菌科（ET-L）。
慢速传输组的α多样性高于正常传输组。在正常传输组中丰富，而在慢速传输组中丰富，且慢速传输组中黏蛋白降解菌的丰度也更高。代谢建模预测慢速传输组中黏蛋白衍生代谢物N-乙酰-D-葡萄糖胺（GlcNAc）增加。网络分析确定了两个与传输时间和饮食模式显著相关的微生物共丰度组（CAG3和CAG9）。六种黏蛋白降解菌与GlcNAc和植物性饮食表现出不同的相关性，特别是包括大米、面包、水果和蔬菜以及发酵豆类。总之，黏蛋白降解菌丰度增加及其预测的代谢产物与CTT延迟有关。
这些发现表明对这些细菌群体进行饮食调节是便秘的一种潜在治疗策略。此外，我们的结果揭示了一种潜在的免疫代谢机制，其中黏蛋白降解菌及其代谢相互作用可能影响肠道传输、黏膜屏障功能和免疫反应。
