Colon samples The colon samples contained a total of 658 OTUs; 248 Firmicutes, 194 Proteobacteria and 46 Bacteroidetes. The colon samples ranged from 307 to 597 OTUs/sample, with an average of 413 OTUs/sample (Table 2). There were 235 OTUs that were found across all six colon samples, and of these, 71 OTUs were exclusive to the colon, representing 22 families (Figure 3). Again, the OTUs with unclassified families were assigned by phyla (Figure 2c), with the dominant phyla being Firmicutes,

Proteobacteria and Unclassified, 16% each; Gemmatimonadetes and Chloroflexi, 11% each, and Bacteroidetes, 10%. All other phyla represented 10% or less of OTUs with selleck kinase inhibitor unclassified families (Figure 2c). Again, many unidentified sequences were listed as uncultured clones by location found. The unidentified sequences found exclusively in the colon were related to52 “termite gut clone” OTUs, 20 “marine, wetland, or waterway sediment clone” OTUs, 10 “soil clone” OTUs, eight “fecal/colon clone” OTUs, eight

“sludge clone” OTUs and five “rumen LCL161 manufacturer clone” OTUs. UniFrac analysis P-test significance was run using all 14 samples together and 100 permutations, resulting in a corrected p-value of < 0.01, designating that each sample was significantly different from each other. Environment clusters and jackknife values are provided (Figure 4), showing a statistical measurement of the correctness of the tree created. The weighted algorithm accounted for the relative abundance of sequences

in a sample, which is typical for Dipeptidyl peptidase environmental samples. UniFrac and PhyloTrac both clustered the rumen and colon samples into two distinct groups: the first node was present 100% of the time in the unweighted and weighted UniFrac clusters. The branching pattern for the rumen group is different between UniFrac algorithm (Figure 4) and between programs (Figure 5). However, the branching pattern for the colon group is identical between PhyloTrac, and the unweighted and weighted UniFrac outputs. A principal component analysis (PCA) scatterplot (Figure 5) was also created using the weighted algorithm, which grouped the rumen and colon samples separately. Figure 4 Jackknife environment clustering in UniFrac, by sample. (a) An unweighted UniFrac algorithm and (b) a weighted UniFrac algorithm were used, and were not normalized as different evolutionary rates of gene did not need to be accounted for. Jackknife counts for each are provided for each node. The weighted UniFrac algorithm takes into account abundance of sequences, and is better suited to analysis of mixed bacterial samples. Samples are labeled by individual moose (1–8) and sample type (rumen, R or colon, C), and gender, weight and age information is provided in the legend. Figure 5 Principal component analysis (PCA) scatterplot of the environments using the weighted UniFrac algorithm.