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Updated: Nov 20, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Long-term dietary intake from infancy to late adolescence is associated with gut microbiota composition in young
Kolade Oluwagbemigun1, Aoife N O'Donovan2,3,4, Kirsten Berding2
1Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.
Background:
Gut microbiota composition as influenced by long-term diet may be associated with the risk of adult chronic diseases. Thus, establishing the relation of long-term diet, particularly starting from early life, with adult microbiota composition would be an important research advance.
Objective:
We aimed to investigate the association of long-term intake of energy, carbohydrate, fiber, protein, and fat from infancy to late adolescence with microbiota composition in adulthood.
Methods:
Within the prospective DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study, we sampled stool 1 or 2 times within 1 y from 128 adults (median age: 29 y). Microbiota composition was profiled by 16S ribosomal RNA sequencing. Annual dietary records from age 1 to 18 y were retrieved. We estimated trajectories of energy, energy-adjusted carbohydrate, fiber, protein, and fat intake with multilevel models, producing predicted intake at age 1 y and rates of change in intake. A multivariate, zero-inflated, logistic-normal model was used to model the association between intake trajectories and the composition of 158 genera in single-sampled individuals. Associations found in this model were confirmed in double-sampled individuals using a zero-inflated Beta regression model.
Results:
Adjusting for covariates and temporal differences in microbiota composition, long-term carbohydrate intake was associated with 3 genera. Specifically, carbohydrate intake at age 1 y was negatively associated with Phascolarctobacterium [coefficient = -4.31; false discovery rate (FDR)-adjusted P = 0.006] and positively associated with Dialister (coefficient = 3.06; FDR-adjusted P = 0.003), and the rate of change in carbohydrate intake was positively associated with Desulfovibrio (coefficient = 13.16; FDR-adjusted P = 0.00039). Energy and other macronutrients were not associated with any genus.
Conclusions:
This work links long-term carbohydrate intake to microbiota composition. Considering the associations of high carbohydrate intake and microbiota composition with some diseases, these findings could inform the development of gut microbiota-targeted dietary recommendations for disease prevention.
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