Song Hokyung, Jeon Dabin, Unno Tatsuya
Subtropical/Tropical Organism Gene Bank, Jeju National University, Jeju 63243, Korea.
Faculty of Biotechnology, School of Life Sciences, Sustainable Agriculture Research Institute (SARI), Jeju National University, Jeju 63243, Korea.
Foods. 2022 Aug 17;11(16):2490. doi: 10.3390/foods11162490.
Prebiotics are non-digestible food ingredients that promote the growth of beneficial gut microorganisms and foster their activities. The performance of prebiotics has often been tested in mouse models in which the gut ecology differs from that of humans. In this study, we instead performed an in vitro gastrointestinal digestion and fecal fermentation experiment to evaluate the efficiency of eight different prebiotics. Feces obtained from 11 different individuals were used to ferment digested prebiotics. The total DNA from each sample was extracted and sequenced through Illumina MiSeq for microbial community analysis. The amount of short-chain fatty acids was assessed through gas chromatography. We found links between community shifts and the increased amount of short-chain fatty acids after prebiotics treatment. The results from differential abundance analysis showed increases in beneficial gut microorganisms, such as , , and , after prebiotics treatment. We were also able to construct well-performing machine-learning models that could predict the amount of short-chain fatty acids based on the gut microbial community structure. Finally, we provide an idea for further implementation of machine-learning techniques to find customized prebiotics.
益生元是不可消化的食物成分，可促进有益肠道微生物的生长并增强其活性。益生元的性能通常在肠道生态与人类不同的小鼠模型中进行测试。在本研究中，我们进行了体外胃肠道消化和粪便发酵实验，以评估八种不同益生元的效率。使用从11个不同个体获得的粪便来发酵消化后的益生元。提取每个样品的总DNA，并通过Illumina MiSeq进行测序以进行微生物群落分析。通过气相色谱法评估短链脂肪酸的含量。我们发现益生元处理后群落变化与短链脂肪酸含量增加之间存在联系。差异丰度分析结果显示，益生元处理后有益肠道微生物（如 、 和 ）数量增加。我们还能够构建性能良好的机器学习模型，该模型可以根据肠道微生物群落结构预测短链脂肪酸的含量。最后，我们为进一步应用机器学习技术寻找定制益生元提供了思路。
