Metagenomics & microbiome

Environmental DNA (eDNA) is extracted with a CTAB / phenol–chloroform–isoamyl alcohol (PCI) protocol with minor modifications. Water samples (100 mL) are first filtered through a 0.22 µm membrane (Whatman); sediment and soil (about 0.25–0.5 g) are processed directly. Cells are lysed in pre-warmed CTAB buffer (100 mM Tris-HCl pH 8.0, 20 mM EDTA, 1.5 M NaCl, 2% CTAB) with β-mercaptoethanol and 0.5 mm glass beads (10 min vortexing), then digested with proteinase K at 55–65 °C and treated with RNase A at 37 °C. DNA is purified with phenol:chloroform:isoamyl alcohol (25:24:1) and chloroform:isoamyl alcohol (24:1), precipitated with cold isopropanol, washed with ethanol and dissolved in TE buffer. Purity is measured with a NanoDrop spectrophotometer (A260/A280 about 1.8–2.0) and integrity on a 1% agarose gel.

The hypervariable V3–V4 region of the bacterial 16S rRNA gene is amplified with barcoded primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) in 30 µL reactions with Promega G2 Green Master Mix: 98 °C for 1 min; 30 cycles of 98 °C for 10 s, 50 °C for 30 s and 72 °C for 30 s; and a final extension at 72 °C for 5 min. Products are checked on a 2% agarose gel, purified with the GeneJET Gel Extraction Kit and quantified with a Qubit fluorometer. Equimolar amplicons are pooled into libraries following the Illumina TruSeq protocol and sequenced on an Illumina NovaSeq 6000 (paired-end, 2 × 250 bp).

Reads are demultiplexed by their 12 bp sample barcodes (custom Python script). Adapters and short reads are removed with Cutadapt, and paired reads are merged with FLASH. Fastp removes low-quality reads (Phred below Q19), and VSEARCH removes chimeric sequences (Rognes et al. 2016). Clean reads are denoised with DADA2 in QIIME2 to obtain amplicon sequence variants (ASVs) (Bolyen et al. 2019). A phylogenetic tree is built in QIIME2, and ASVs are classified with a naïve Bayesian classifier (Wang et al. 2007) trained on the SILVA 138 database (Quast et al. 2013).

Alpha diversity (Chao1 richness, Shannon and Simpson diversity, Pielou’s evenness, dominance and Good’s coverage) is calculated in QIIME2 and plotted in R (ggplot2, vegan, reshape2). Beta diversity is based on weighted and unweighted UniFrac distances, shown with Principal Coordinates Analysis (PCoA), Principal Component Analysis (PCA) and non-metric multidimensional scaling (NMDS). Differences between groups are tested with PERMANOVA (Adonis), ANOSIM and MRPP (Anderson 2001).

Differentially abundant taxa are identified with metagenomeSeq, and potential biomarkers with LEfSe (LDA score above 4). Community functions are predicted with PICRUSt2 (Douglas et al. 2020), phenotypes with BugBase, and ecological guilds with FAPROTAX and FUNGuild. Relationships between communities and environmental variables are explored with canonical correspondence analysis (CCA) and distance-based redundancy analysis (db-RDA) in R (vegan, psych).

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2. Bolyen E, Rideout JR, Dillon MR, et al. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37: 852–857. https://doi.org/10.1038/s41587-019-0209-9
3. Douglas GM, Maffei VJ, Zaneveld JR, et al. (2020). PICRUSt2 for prediction of metagenome functions. Nature Biotechnology 38: 685–688. https://doi.org/10.1038/s41587-020-0548-6
4. Quast C, Pruesse E, Yilmaz P, et al. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 41(D1): D590–D596. https://doi.org/10.1093/nar/gks1219
5. Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016). VSEARCH: a versatile open source tool for metagenomics. PeerJ 4: e2584. https://doi.org/10.7717/peerj.2584
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