Bioinformatics analysis
We performed quality checks on raw sequences from all fecal samples using FastQC. Shotgun metagenomic sequencing data were then processed through an analysis workflow that utilizes Huttenhower Biobakery pipeline, including Kneaddata, MetaPhlAn3 and HUMAnN3 to obtain species, genes and pathways abundance matrix. Briefly, quality filtering and host genome decontamination (human) was performed using Trimmomatic and Bowtie2 via Kneaddata wrapper program with following parameters: ILLUMINACLIP:/NexteraPE-PE.fa:2:30:10, SLIDINGWINDOW:5:25, MINLEN:60, LEADING:3, TRAILING:3. Taxonomic and functional profiling of the microbial community was performed using MetaPhlan3 and HUMAnN3 using default parameters. Next, gene abundance matrix was further collapsed by Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology term and Gene Ontology term mapping via “humann_regroup_table” function provided within HUMAnN3.Further microbiome data-handling was done in R (version 4.1.2) with the Rstudio GUI (version 1.4.1717). The iNEXT library was used to compute alpha diversity for the first three hill numbers (Chao1, Shannon entropy and Simpson Index). Differences in alpha diversity were assessed using linear mixed effect models using the lme4 package. Principal component analysis was performed on centered log-ratio transformed (clr) values as a visual companion to the beta diversity analysis. Zeroes were imputed using the “unif” method. Beta diversity was computed in terms of Aitchison distance (Euclidean distance of clr-transformed counts) and differences in beta diversity were assessed using the PERMANOVA implementation from the vegan library using 10,000 permutations. Microbial volatility was measured as the Aitchison distance between pre- and post-intervention [Gut-brain modules (GBMs) and gut-metabolic modules (GMMs) were calculated using the R version of the Gomixer tool [