72, p = 0 001) The separation is clearly shown in PCoA1 (Figure 

72, p = 0.001). The separation is clearly shown in PCoA1 (Figure 1C) and PCoA3 (Additional file 4: Figure S4). Those samples that grouped into S1 were found to be less similar to caecum and lung communities, whereas samples grouping into S2 appeared more closely related to the lung microbiota. A more detailed Autophagy inhibitor description of the taxa responsible for distinguishing bacterial communities in the lung, caecum and vagina is demonstrated using a heatmap dendrogram (Figure 1D). We removed from the subsampled OTU table all observations accounting for less than 0.5% of the generated sequences to visualize the taxa with main impact

on the community profile. This method provides maximal taxonomic resolution of each individual animal sample and selleck screening library directly reflects the PCoA plots since both analyses are based on OTU find more count dissimilarities. For the caecum samples, 27% could be assigned to a taxonomic genus as mentioned before and the sequences belonged to Alistipes (16%) Anaeroplasma (1.5%) and a 22 genera listed in Additional file 3: Table S4. We observed a better taxonomic resolution on the family level, were 77% of the reads were successful assigned. The three major families in the caecum were Lachnospiraceae

(33.8%), Ruminococcaceae (15.3%) and Porphyromonadaceae (7.9%). Vaginal samples within S1 contained between 56-97% of Streptococcus, over while vaginal samples within S2 only had 0.2 – 10% of the gram-positive bacterium, explaining why here appears to be such a distinction between the S1 and S2 groups. In addition to Streptococcus, notable contributions from Acinetobacter (6.2%), Sphinogmonas (3.3%), Enterococcus (3.1%), and Polaromonas (1.8%) were also observed in the vaginal community. All

lung samples had representative sequences from genera including Staphylococcus (8.3%) Massilia (2.6%), Corynebacterium (2.2%), Pseudomonas (2.53%), Streptococcus (2.3%) and Sphingomonas (1.7%) without significant variation (KW, p > 0.05). Even though the beta diversity measure indicated that there were minimal differences between the lung communities sampled using different methods, six major genera varied significantly (KW, p < 0.05). Acinetobacter, Pelomonas, and Schlegella were more abundant in the BAL-plus samples in comparison to the BAL-minus or the lung tissue samples. Arcobacter, and Polaromonas were highly associated with BAL-minus, whereas Brochothrix was only found in the lung tissue samples. Richness and diversity of sample type (Alpha diversity) To compare the OTU diversity between sample approaches and sampling sites, we have calculated the alpha diversity index. There were two key points we were interested in. First, we wanted to know if the alpha diversity of the BAL samples was higher or lower than the diversity of the lung tissue samples.

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