Lee Dong Hyeon, Seong Hyunbin, Chang Daniel, Gupta Vinod K, Kim Jiseung, Cheon Seongwon, Kim Geonhee, Sung Jaeyun, Han Nam Soo
Brain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, 55455, USA.
NPJ Sci Food. 2023 May 9;7(1):18. doi: 10.1038/s41538-023-00195-1.
We previously proposed the Gut Microbiome Wellness Index (GMWI), a predictor of disease presence based on a gut microbiome taxonomic profile. As an application of this index for food science research, we applied GMWI as a quantitative tool for measuring the prebiotic effect of oligosaccharides. Mainly, in an in vitro anaerobic batch fermentation system, fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2'-fucosyllactose (2FL), were mixed separately with fecal samples obtained from healthy adult volunteers. To find out how 24 h prebiotic fermentation influenced the GMWI values in their respective microbial communities, changes in species-level relative abundances were analyzed in the five prebiotics groups, as well as in two control groups (no substrate addition at 0 h and for 24 h). The GMWI of fecal microbiomes treated with any of the five prebiotics (IN (0.48 ± 0.06) > FOS (0.47 ± 0.03) > XOS (0.33 ± 0.02) > GOS (0.26 ± 0.02) > 2FL (0.16 ± 0.06)) were positive, which indicates an increase of relative abundances of microbial species previously found to be associated with a healthy, disease-free state. In contrast, the GMWI of samples without substrate addition for 24 h (-0.60 ± 0.05) reflected a non-healthy, disease-harboring microbiome state. Compared to the original prebiotic index (PI) and α-diversity metrics, GMWI provides a more data-driven, evidence-based indexing system for evaluating the prebiotic effect of food components. This study demonstrates how GMWI can be applied as a novel PI in dietary intervention studies, with wider implications for designing personalized diets based on their impact on gut microbiome wellness.
我们之前提出了肠道微生物群健康指数（GMWI），这是一种基于肠道微生物群分类学特征来预测疾病存在的指标。作为该指数在食品科学研究中的一项应用，我们将GMWI用作一种定量工具来衡量低聚糖的益生元效应。具体而言，在体外厌氧分批发酵系统中，将低聚果糖（FOS）、低聚半乳糖（GOS）、低聚木糖（XOS）、菊粉（IN）和2'-岩藻糖基乳糖（2FL）分别与从健康成年志愿者获得的粪便样本混合。为了探究24小时的益生元发酵如何影响其各自微生物群落中的GMWI值，我们分析了五个益生元组以及两个对照组（0小时和24小时均不添加底物）中物种水平相对丰度的变化。用五种益生元中的任何一种处理的粪便微生物群的GMWI（IN（0.48±0.06）>FOS（0.47±0.03）>XOS（0.33±0.02）>GOS（0.26±0.02）>2FL（0.16±0.06））均为正值，这表明先前发现与健康、无疾病状态相关的微生物物种的相对丰度有所增加。相比之下，24小时不添加底物的样本的GMWI（-0.60±0.05）反映出一种不健康、携带疾病的微生物群状态。与原始的益生元指数（PI）和α-多样性指标相比，GMWI为评估食品成分的益生元效应提供了一个更具数据驱动性、基于证据的索引系统。这项研究展示了GMWI如何在饮食干预研究中作为一种新型PI应用，对基于其对肠道微生物群健康的影响来设计个性化饮食具有更广泛的意义。
