Abstract

The file MICODE_Multiunit-In-Vitro-Colon-Model-and-Prebiotic-Prototypes.ods contains a comprehensive collection of raw data, statistical analyses, and Next Generation Sequencing (NGS) information from a study investigating the modulation of gut microbiota by a prebiotic hemp by-product. The dataset provides valuable insights into microbial quantification, metabolite profiling, and multivariate statistical analyses. The file contains the following data: (1) data on microbial quantifications obtained from the in vitro colon model. The data provides detailed measurements of microbial populations, allowing researchers to assess the impact of the prebiotic hemp by-product on gut microbiota composition and dynamics. These quantifications are essential for evaluating microbial shifts and understanding how the prebiotic intervention influences different bacterial taxa; (2) data on metabolite quantifications at baseline. The data serve as a reference point for assessing metabolic changes over time, offering insights into the initial conditions before the prebiotic intervention. By analyzing these metabolites, researchers can explore the biochemical environment of the gut and its potential interactions with microbial activity; (3) data from a multivariate analysis of metabolite data, highlighting complex relationships between different metabolites and microbial communities. The use of MANOVA (Multivariate Analysis of Variance) allows for the identification of statistically significant patterns and variations in metabolite concentrations, helping to determine the effects of the prebiotic hemp by-product on gut metabolism; (3) data from a second multivariate analysis of metabolite data, possibly using a different set of variables or experimental conditions. This additional analysis offers a broader perspective on metabolic shifts, allowing for a more refined understanding of the interactions between gut microbiota and prebiotic supplementation. This dataset is a valuable resource for researchers studying the effects of prebiotic interventions on gut microbiota and metabolic processes. The data enable a detailed exploration of microbial community changes, metabolite fluctuations, and their potential health implications, contributing to a deeper understanding of gut microbiome modulation.