Fig. S8. Percent distribution of prophage and DNA recombination genes from gut metagenomes available within the MG-RAST pipeline. Using the “”Metabolic
Analysis”" tool within MG-RAST, the available gut metagenomes were searched against the SEED database using the BLASTx algorithm. Percentage contribution of each gut metagenome assigned to functional classes within “”Prophage/DNA recombination”" SEED Subsystem is shown. The e-value cutoff for metagenomic sequences matches to this SEED Subsystem was 1×10-5 with a minimum alignment length of 30 bp. Fig. S9. Hierarchical clustering of gut metagenomes available within MG-RAST based on the relative abundance of cell wall and capsule genes. A matrix consisting selleck of the number of reads assigned to genes within the “”Cell wall and Capsule”" SEED Subsystem from each gut metagenome was generated using the “”Metabolic Analysis”" tool within MG-RAST. The e-value cutoff for metagenomic sequences matches to this SEED Subsystem was 1×10-5 with a minimum alignment length of CUDC-907 30 bp. Resemblance matrices were calculated using Bray- Curtis dissimilarities within PRIMER v6 software [41]. Clustering was performed using the complete linkage algorithm. Dotted branches denote that
no statistical difference in similarity profiles could be identified for these respective nodes, using the SIMPROF test within PRMERv6 software. Fig. S10. Transposases derived from gut metagenomes available within JGI’s IMG/M database. The percent of total CP-690550 manufacturer annotated tranposase gene families from pig, mouse, human, and termite gut metagenomes is shown. The percentage of each transposase family from swine, human, and mouse gut metagenomes were each averaged since there was more than one metagenome for each of these hosts within the JGI’s IMG/M database. Metagenomic sequences were assigned to transposase Nintedanib (BIBF 1120) gene families using the IMG 2.8 pipeline. Fig. S11. Composition of resistance genes present with the swine fecal metagenome. The percent of swine fecal metagenomic sequences assigned to the “”Resistance to Antibiotics and Toxic
Compounds”" SEED Subsystem is shown. The number of GS20 and FLX assigned to genes within this SEED Subsystem were combined. The e-value cutoff for metagenomic sequence matches to this SEED Subsystem database was 1×10-5 with a minimum alignment length of 30 bp. Fig. S12. Differential functions within the swine fecal metagenome. A list of significantly different SEED Subsystems and their relative abundance are shown for pair-wise comparisons of the pig fecal metagenome versus other available gut metagenomes within the MG-RAST database. A matrix of the abundance of sequences assigned to each SEED Subsystem from each gut metagenome was generated using the “”Metabolic Analysis”" tool in MG-RAST. The number of reads from each individual pig, human infant, and human adult metagenomes were each combined since there was more than one metagenome for each of these hosts within the MG-RAST database.