16S Metabarcode Sequence Data Processing
The resulting FASTQ file was analyzed using the Quantitative Insights Into Microbial Ecology (QIIME2-2020.11) platform (Bolyen et al., 2019) (details of the QIIME analysis is presented in the supplementary file). A total of 8,820,568 sequences with 19,776 ASVs were obtained for the 267 samples (195 gut samples, 68 water samples, and 4 negative controls). The four negative controls had 1 to 7 reads and were excluded from the rest of the study. Using a taxon filter-table, ASVs related to eukaryotes, mitochondria, chloroplasts (combined ~ 1%), and unassigned (1%), were removed, resulting in a total of 8,655,659 (98%) sequences remaining. Furthermore, samples with low sequence depth (less than 3000 reads), low abundance taxa (less than 10 ASVs) and ASVs that showed up in only one sample were removed. This decreased the total number of samples to 255 samples (189 gut samples, 66 water samples) with 8,217,478 sequences and 2888 ASVs. The 8 deleted samples were not related to specific treatment type or family (antibiotic treatment (one water sample), probiotic treatment (4 gut samples, and one water sample), control (two gut samples)). Alpha diversity indices (Chao1 and Faith’s phylogenetic diversity (PD)) of BCs were calculated using the QIIME2 alpha diversity plugin. The ASV table was rarefied to 3000 reads per sample for the alpha diversity estimation (rarefaction curves plateaued at 3000 reads). A Bray-Curtis dissimilarity matrix was calculated to estimate β-diversity.