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确定食物和营养成分作为定植预测指标。

Identification of food and nutrient components as predictors of colonization.

作者信息

Thompson Sharon C, Ford Amanda L, Moothedan Elijah J, Stafford Lauren S, Garrett Timothy J, Dahl Wendy J, Conesa Ana, Gonzalez Claudio F, Lorca Graciela L

机构信息

Department of Microbiology and Cell Science, Genetics Institute, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, United States.

Department of Food Science and Human Nutrition, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, United States.

出版信息

Front Nutr. 2023 Apr 21;10:1118679. doi: 10.3389/fnut.2023.1118679. eCollection 2023.

Abstract

A previous double-blind, randomized clinical trial of 42 healthy individuals conducted with N6.2 found that the probiotic's mechanistic tryptophan pathway was significantly modified when the data was stratified based on the individuals' lactic acid bacteria (LAB) stool content. These results suggest that confounding factors such as dietary intake which impact stool LAB content may affect the response to the probiotic treatment. Using dietary intake, serum metabolite, and stool LAB colony forming unit (CFU) data from a previous clinical trial, the relationships between diet, metabolic response, and fecal LAB were assessed. The diets of subject groups with high vs. low CFUs of LAB/g of wet stool differed in their intakes of monounsaturated fatty acids, vegetables, proteins, and dairy. Individuals with high LAB consumed greater amounts of cheese, fermented meats, soy, nuts and seeds, alcoholic beverages, and oils whereas individuals with low LAB consumed higher amounts of tomatoes, starchy vegetables, and poultry. Several dietary variables correlated with LAB counts; positive correlations were determined for nuts and seeds, fish high in N-3 fatty acids, soy, and processed meats, and negative correlations to consumption of vegetables including tomatoes. Using machine learning, predictors of LAB count included cheese, nuts and seeds, fish high in N-3 fatty acids, and erucic acid. Erucic acid alone accurately predicted LAB categorization, and was shown to be utilized as a sole fatty acid source by several species regardless of their mode of fermentation. Several metabolites were significantly upregulated in each group based on LAB titers, notably polypropylene glycol, caproic acid, pyrazine, and chondroitin sulfate; however, none were correlated with the dietary intake variables. These findings suggest that dietary variables may drive the presence of LAB in the human gastrointestinal tract and potentially impact response to probiotic interventions.

摘要

此前一项针对42名健康个体开展的双盲随机临床试验使用N6.2发现,当根据个体的乳酸菌(LAB)粪便含量对数据进行分层时,益生菌的机制性色氨酸途径发生了显著改变。这些结果表明,影响粪便LAB含量的饮食摄入等混杂因素可能会影响对益生菌治疗的反应。利用先前一项临床试验中的饮食摄入、血清代谢物和粪便LAB菌落形成单位(CFU)数据,评估了饮食、代谢反应和粪便LAB之间的关系。每克湿粪便中LAB的CFU高的受试者组和低的受试者组的饮食在单不饱和脂肪酸、蔬菜、蛋白质和乳制品的摄入量上有所不同。LAB含量高的个体食用了更多的奶酪、发酵肉类、大豆、坚果和种子、酒精饮料及油类,而LAB含量低的个体食用了更多的西红柿、淀粉类蔬菜和家禽。几个饮食变量与LAB计数相关;确定了坚果和种子、富含N-3脂肪酸的鱼类、大豆和加工肉类呈正相关,与包括西红柿在内的蔬菜消费呈负相关。使用机器学习,LAB计数的预测因素包括奶酪、坚果和种子、富含N-3脂肪酸的鱼类和芥酸。单独的芥酸能准确预测LAB分类,并且已证明它被几种菌种用作唯一的脂肪酸来源,无论其发酵模式如何。基于LAB滴度,每组中有几种代谢物显著上调,特别是聚丙二醇、己酸、吡嗪和硫酸软骨素;然而,没有一种与饮食摄入变量相关。这些发现表明,饮食变量可能驱动LAB在人类胃肠道中的存在,并可能影响对益生菌干预的反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2347/10160632/b687d53aceda/fnut-10-1118679-g001.jpg

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