Table 1 Primers Primer Sequence Reference 27 F 5′AGAGTTTGATCMTGGCTCAG-3′ [13] 341 5′-CCTAYGGGRBGCASCAG-3′ [14, 15] 806 5′-GGACTACNNGGGTATCTAAT-3′ [14, 15] TitA_341F 5′-CGTATCGCCTCCCTCGCGCCATCAG-TAG-CCTAYGGGRBGCASCAG-3′ [16] TitB_806R 5′-CTATGCGCCTTGCCAGCCCGCTCAG-GGACTACNNGGGTATCTAAT-3′ [16] 1492R 5′-GGTTACCTTGTTACGACTT-3′

[13] In the second PCR the adaptors were attached to the amplicon library elongating the fragment towards 526 bp with the primer TitA_341F and TitB_806R. The same reaction conditions of PCR I were applied in PCR II with a reduced cycle number of 15. Initially we tried to apply the same www.selleckchem.com/products/sn-38.html procedure for the lung tissue selleck chemicals samples but unspecific bands after gel-electrophoresis made it impossible to select the correct fragment size. To overcome this problem we chose the primer 27 F and 1492R amplifying A-769662 ic50 the entire 16S rRNA gene which appeared to be more specific. The PCR I conditions were the same as mentioned above except that the annealing temperature was reduced to 55°C and the cycle number to 40. In this perspective the Tag-PCR reaction with TitA_341F and TitB_806R provided the selection for V3 and V4 as well as attaching the adaptors to the amplicons. Statistical analysis and bioinformatics The 16S rRNA gene sequences obtained from one half a plate of a 454 – Roche

– Titanium pyrosequencing run were quality filtered, trimmed and split into the corresponding animal samples with the Qiime pipeline version 1.6.0 using the default settings [17]. We considered only sequences with a minimum

length of 250 bp. Chimeras were removed by UCHIME [18]. The operational taxonomic units (OTU) were picked de novo and clustered at 97% sequence similarity. AZD9291 The taxonomy was assigned using RDP classifier (bootstrap threshold 0.8) greengenes as reference database [19]. For statistical analysis, raw data were transferred into the open source statistical program “R” [20]. The non-parametric Wilcoxon test (W) evaluated variations of alpha diversity between two variables. We used the non-parametric Kruskal-Wallis-test when comparing more than 2 variables (KW). Dissimilarities in OTUs abundance between the samples were explained by KW and the sample clustering of the OTU count based Bray-Curtis distance metric were examined by the analysis of similarity (anosim). Results To determine the airway bacterial microbiota of the BALB/cJ mouse model based on 16S rDNA gene sequencing, we have compared sequences found in the lungs with three different approaches, to sequences found in corresponding vaginal and caecal samples. Over all sequence quality and results from all sample types We generated a total of 908256 sequences. After quality filtering and chimera check, 27% of sequences were removed and 660319 sequences were further processed for OTU picking (sequences ranged between 3530 up to 31638 per animal sample).