2.11. Statistical analysis

Data were analyzed in SPSS software version 24 (IBM Corp.). All datasets were checked for the normality with Shapiro–Wilk test and homogeneity of variance with Levene's test. Outliers were removed following Grubbs's test (significance level = 0.05).

Changes in body weight gain and FITC permeability overtime were analyzed by a two‐way repeated‐measures analysis of variance (ANOVA; diet and ABX as independent factors and time as a repeated‐measure factor) followed by Bonferroni's post hoc pairwise comparisons at each timepoint. Tissue and organ weights, intestinal length, gene expression, plasma leptin, insulin, inflammatory markers, and lipopolysaccharide binding protein levels, and total FITC flux data were compared with two‐way ANOVA followed by pairwise comparison using Bonferroni's post hoc test. Non‐parametric data were compared with Kruskal–Wallis test followed by Mann–Whitney U test. Caecum metabolomics pairwise comparisons were performed with independent Student's t test and expressed as Log2 ratios. Benjamin Hochberg (BH) procedure with false discovery rate (FDR) set at 0.05 was used to correct p values for multiple comparisons. p < 0.05 was deemed significant in all cases. Data are expressed as mean + SEM.

A complete description of statistical analysis is detailed in “Supplementary Statistic” and Figures S4–S7.

All statistical analyses of the gut microbiota data were performed with R version 3.6.0. Normality of the data was evaluated with Shapiro–Wilk test. Microbiota and study variables were included in the estimation of alpha‐diversity richness (Shannon, Simpson and total Richness indexes) by the Vegan and Phyloseq R packages (McMurdie & Holmes, 2013). Therefore, potential differences in richness of factors included in the study were estimated by repeated measures ANOVA. Statistically significant differences in beta‐diversity were assessed by PERmutational Multivariate Analyses Of Variance (PERMANOVA) using a Bray‐Curtis dissimilarity measure. Specific differences between groups were assessed by post hoc comparisons with Adonis pairwise comparisons. Principal Coordinates Analysis (PCoA) plots based on Bray–Curtis dissimilarity measure were used to visualize beta‐diversity plot (Bray & Curtis, 1957). Differences in taxa abundance for experimental groups were analyzed by non‐parametric Kruskal–Wallis test and Pairwise Wilcoxon Rank Sum tests for multiple comparisons and Benjamin–Hochberg p‐value correction with a threshold of 0.05.