82 Chapter 3 clustered by taxonomy and relative abundance using the R package phyloseq (McMurdie & Holmes, 2013) and plotted with ggplot2. Metagenomics analysis Samples were sequenced by Macrogen Europe VB (Amsterdam, The Netherlands) with a TruSeq DNA PCR free library using an insert size of 350 bp on a NovaSeq6000 Illumina platform, producing 2x151bp paired-end read (10Gbp/ sample). Metagenomic data were analyzed as follows. Read quality was assessed with FASTQC v0.11.8 before and after quality trimming, adapter removal, and contaminant filtering, performed with BBDuk (BBTools v38.75). Trimmed reads were co-assembled de novo using metaSPAdes v3.14.1 (Nurk et al., 2017) and mapped to assembled contigs using BBMap (BBTools v38.75) (Bushnell, 2014). Sequence mapping files were handled and converted using SAMtools v1.10. Contigs at least 1,000-bp long were used for binning with CONCOCT v1.1.0 (Alneberg et al., 2014), MaxBin2 v2.2.7 (Wu et al., 2016), and MetaBAT2 v2.1512 (Kang et al., 2019). Resulting metagenome-assembled genomes (MAGs) were dereplicated with DAS Tool v1.1.213 (Sieber et al., 2018) and taxonomically classified with the Genome Taxonomy Database Toolkit GTDB-Tk v1.3.0 (Chaumeil et al., 2019) release 9514. MAG completeness and contamination was estimated with CheckM v1.1.2 (Parks et al., 2015). MAGs were renamed to their lowest GTDB-Tk category (Supplementary Table 1). MAGs were annotated with DRAM v1.0 (Shaffer et al., 2020) with default options, except min_contig_size at 1,000 bp, and genes of interest were searched in annotation files as well as via BLASTP and HMM analyses. Gene-based metagenomic analysis was resolved using CoverM v0.6.1 (https://github.com/wwood/CoverM) with -contig flag, minimum of 95% identity and aligned read length of 75% for each read. Here, KEGG-curated HMM profiles of selected functional marker genes were mapped against our metagenome and corrected for read and contig size. The motivation to employ certain genes for sulfide detoxification/oxidation (sulfide: quinone oxidoreductase, sqr), DNRA (nitrite:ammonium oxidoreductase, nrfA) and denitrification (nitrate reductase [narG, napA], nitrite reductase [nirS, nirK], nitric oxide reductase [norB] and nitrous oxide reductase [nosZ]) was based on pathway specificity, well-curated genes (KEGG-based) with known directionality, except for nitrate reductase/nitrite oxidoreductase (narG/nxrA), which was put in context with downstream denitrification genes.
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