Computational protocol: RNA Based Stable Isotope Probing Suggests Allobaculum spp. as Particularly Active Glucose Assimilators in a Complex Murine Microbiota Cultured In Vitro

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Protocol publication

[…] The sequencing data were processed with QIIME 1.8 []. Overlapping paired-end Illumina fastq files were merged using the join_paired_ends.py script with default settings. Assembled sequences were quality filtered using a Q30 base call accuracy cut-off and allocated to their respective samples according to their unique barcode sequence. The demultiplexed sequences were then chimera checked using the USEARCH method against the Greengenes alignment (release GG_13_8). Sequences identified as chimeric were removed from subsequent analyses. Sequence reads were clustered into operational taxonomic units (OTUs) at 97% or greater similarity using the USEARCH method []. Representative sequences were aligned with PyNAST against the Greengenes database (release GG_13_8) and assigned taxonomies using the Ribosomal Database Project (RDP) classifier []. Alpha and beta diversity analyses were performed using the core_diversity_analyses.py script in QIIME 1.8. Alpha diversity was calculated through the phylogenetic metric PD_whole_tree (Faith's phylogenetic diversity estimate) using the value of the minimum number of reads (1008) across 10 iterations. Beta diversity was visualized using principal coordinate analysis (PCoA) of unweighted UniFrac phylogenetic distances.Statistical analyses of the microbiota sequencing data were performed in R 3.0.2 []. The results on the community composition and the corresponding statistical analysis were based on relative abundances averaged from the sequencing replicates for each fraction (except for fraction 3 of the 2 h incubation, where only one sample was usable for sequencing). The differences in the mean relative abundance of bacterial taxa found in “heavy” and “medium” RNA-SIP fractions were assessed using one-way ANOVA. Differences in alpha diversity between “heavy” and “medium” fractions were analyzed using two-way ANOVA with time and density as factors. Differences with a p value < 0.05 were considered significant, while trends were defined as p > 0.05 but <0.10.All sequencing data were submitted to GenBank and are publicly available under the accession number PRJNA340187. […]

Pipeline specifications

Software tools QIIME, USEARCH, PyNAST, RDP Classifier, UniFrac
Databases Greengenes
Applications Phylogenetics, 16S rRNA-seq analysis
Organisms Mus musculus
Chemicals Carbohydrates, Glucose, Lactic Acid