Additional file 5 - scripts for microbiota analysis

Microbiota analysis was carried out in R using the DADA2 pipeline (Callahan et al., 2016), and taxonomic categories were assigned using the Silva Database (release 138.1) as a reference for the assignment (Quast et al., 2012). Alpha (Shannon, Chao1, and Simpson indices) and Beta diversity (calculated as Bray Curtis distance matrix), as well as the abundance of taxonomic categories, were calculated and analysed with R software 3.6, using the PhyloSeq (McMurdie et al., 2013), Vegan (Dixon, 2003), and microbiomeMarker (Cao et al., 2022) packages. Differences between groups regarding Alpha diversity indices were tested using a linear mixed model that included category (IUGR, NORM), time (T1, T2, T3, T4), and their interaction as fixed factors, with the litter of origin considered as a random factor. Then, a separate model within each time point was performed including only the category as a fixed factor and the litter of origin as a random factor. For Beta diversity, a dissimilarity matrix was constructed using the Bray–Curtis distance matrix as metrics, and the results were plotted using a non-metric multidimensional scaling (NMDS) plot. Furthermore, the betadisper test was conducted to test differences in the samples’ dispersion among the groups. Differences were tested using a PERMANOVA (Adonis) model with 9,999 permutations, including category, time, and their interaction, and litter of origin as factors. A second PERMANOVA model was then performed within each time point, including the category as a factor. For the differential analysis of taxa, the LEfSe algorithm was used at the genus level. Specifically, taxa were considered significant if they possessed a Linear Discriminant Analysis (LDA) score > 4 and a Padj < 0.05 within each time point, including the category as a factor.References:Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP: DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 2016, 13:581-583.Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO: The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 2012, 41:D590-D596.McMurdie PJ, Holmes S: phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PloS One 2013, 8:e61217.Dixon P: VEGAN, a package of R functions for community ecology. Journal of Vegetation Science 2003, 14:927-930.Cao Y, Dong Q, Wang D, Zhang P, Liu Y, Niu C: microbiomeMarker: an R/Bioconductor package for microbiome marker identification and visualization. Bioinformatics 2022, 38:4027-4029.