Computational protocol: Pika Population Density Is Associated with the Composition and Diversity of Gut Microbiota

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Protocol publication

[…] The Ezup genomic DNA extraction kit for soil (Sangon Biotech, China) was used to extract total DNA of gut contents. DNA concentration and purity were determined using the Nanodrop 2000 Spectrophotometer. The extracted DNA was diluted to 10 ng/μL for PCR amplification. In order to amplify the V4–V5 hypervariable region of the microbial 16S rRNA gene, the universal primers 515F (5′-GTGYCAGCMGCCGCGGTA-3′) and 909R (5′-CCCCGYCAATTCMTTTRAGT-3′) with 12 nt unique barcode at 5′-end of 515F (Tamaki et al., ) were used. PCR amplifications were performed in duplicate with 25 μL reaction mix containing 1 × PCR buffer, 1.5 mM MgCl2, each deoxynucleoside triphosphate at 0.2 mM, each primer at 1.0 μM and 0.25 U of Ex Taq (TaKaRa, Dalian) and 10 ng genomic DNA. The thermal cycling procedure consisted of an initial denaturation step at 94°C for 3 min, followed by 30 cycles of 94°C for 40 s, 56°C for 60 s, and 72°C for 60 s, and a final extension at 72°C for 10 min. After PCR amplification, the two PCR products were mingled together and subjected to electrophoresis using 1.2% agarose gel. The correct band (~400 bp) was excised and purified using SanPrep DNA Gel Extraction Kit (Sangon Biotech, China) and quantified with the Nanodrop 2000 Spectrophotometer. All samples were pooled together with an equal molar amount from each sample. The sequencing samples were prepared using the TruSeq DNA kit according to the manufacturer's instruction. The purified library was diluted, denatured, re-diluted, mixed with PhiX (equal to 30% of final DNA amount), as described in the Illumina library preparation protocols, and then applied to an Illumina Miseq platform for sequencing (Reagent Kit V2) at the Environmental Genome Platform of Chengdu Institute of Biology.The raw sequence data were processed using QIIME Pipeline-Version 1.7.0 (http://qiime.org/tutorials/tutorial.html). All sequences were trimmed and assigned to each sample based on their barcodes (barcode mismatches = 0). The overlapping paired-end reads were merged using the FLASH-1.2.8 software (Magoc and Salzberg, ). The merged sequences with high quality (reads length >300 bp, without ambiguous base “N,” and average base quality score >30) were used for further analysis. Due to possible contamination of chloroplast sequences in PCR amplification, we employed the Metaxa2 software tool to remove chloroplast sequences from our large sequencing datasets (Bengtsson-Palme et al., ). The aligned 16S rRNA gene sequences were used for a chimera check using the Uchime algorithm (Edgar et al., ). All sequences were clustered into operational taxonomic units (OTUs) at a 97% identity threshold using CD-HIT (Li and Godzik, ). Singleton OTUs were filtered out. To compare samples with different sequencing depths, each sample was rarefied to the same number of reads (8234 sequences). The alpha diversity indices, including observed species and Shannon diversity, were calculated. To assess beta diversity, the unweighted and weighted UniFrac distance metrics, which use phylogenetic information to calculate community similarity (Lozupone and Knight, ), were produced through the QIIME pipeline. In addition, in order to compare community similarity based on the presence/absence of OTUs, the Jaccard index was used; to compare community similarity based on OTU abundance, the Bray-Curtis dissimilarity matric was used with Hellinger transformed data (Dixon, ). The rarefaction curves were generated from the Goods coverage at the OTU level. Taxonomy was assigned using the Ribosomal Database Project classifier (Wang et al., ).The original sequence data are available at the European Nucleotide Archive by accession number PRJEB11203 (http://www.ebi.ac.uk/ena/data/view/PRJEB11203). [...] Because the sample size was uneven in each group, an analysis of similarity (ANOSIM), which does not allow for interaction terms (Dill-McFarland et al., ), was applied to evaluate if microbial communities were significantly different across groups. ANOSIM analysis was implemented using the procedure “anosim” in the R “vegan” package (Warton et al., ). We calculated the average weighted UniFrac dissimilarity within each group. In order to explore the relationship between host density and the average weighted UniFrac dissimilarity, the Spearman correlation analysis was tested. Differences in the levels of variation within each group were tested with permutational tests of multivariate dispersions (PERMDISP). The Spearman correlations between the mean relative abundance (>0.05%) of microbial taxa at phylum, family and genus levels, and host population density were analyzed using SPSS 13.0 software. False discovery rate (FDR) values were evaluated using the Benjamini-Yekutieli method (Benjamini and Yekutieli, ). […]

Pipeline specifications

Software tools MINGLeD, QIIME, metaxa, UCHIME, CD-HIT, UniFrac, RDP Classifier, vegan
Databases ENA
Application 16S rRNA-seq analysis
Organisms Ochotona curzoniae