Computational protocol: Microbial diversity in the hypersaline Lake Meyghan, Iran

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[…] Genomic DNA was extracted from colonies grown on the agar medium from which the strain was isolated, using the Genomic-DNA extraction kit (Roche, Diagnostic, Mannheim, Germany) and according to the manufacturer’s recommendations. The DNA concentration and purity were assayed using the Nanodrop 1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and were confirmed by visualization on a 1% agarose gel. The 16S rRNA genes from the isolates were amplified using either the Bacteria specific primers 27F and 1492R or the Archaea specific primers 20F and 1530R (Table ). The PCR conditions were as follows for Bacteria: 94 °C for 3 min, followed by 25 cycles of 95 °C for 45S, 55 °C for 45S and 72 °C for 90S and a final 10 min extension at 72 °C and for Archaea: 94 °C for 3 min, followed by 30 cycles of 94 °C for 15S, 52 °C for 30S and 72 °C for 50S and a final 7 min extension at 72 °C. Sanger sequencing was performed on an ABI 3730XL DNA sequencer at Macrogen (Seoul, South Korea) generating on average 900 bp sequences using bacterial 27F or the archaeal 20F oligonucleotides as sequencing primers. Neighboring taxa were identified using the BLASTN program and analysed by pairwise sequence alignment to calculate sequence similarity using the EzBioCloud server ( The sequences were considered to belong to an operational taxonomic unit (OTU) when sharing ≥97% sequence identity. For metagenomic analysis, multiple filters were pooled for DNA extraction using a phenol-chloroform based protocol. Metagenome sequencing was performed using a paired-end protocol with an average read size of 100 bp (PE100) on Illumina HiSeq 4000 (BGI, Hong Kong) on randomly sheared 170–500 bp DNA fragments. [...] Taxonomic and functional profiling of raw sequencing reads was performed on the MG-RAST pipeline that contains its own quality control algorhythm. Taxonomic profiles of the microbial community were extracted from the MG-RAST annotation pipeline focusing on sequences annotated as small subunit ribosomal (SSU) RNA using the Silva SSU database as a reference. For further in house analysis, low quality reads were removed using Trimmomatic. The filtering cutoffs were: minimum length 100 bp, average quality score 20, sliding window 4:20, maximum info 100:0.8.Metagenomic contigs were annotated using a collection of in house bioinformatics scripts (supplementary material ). The pipeline included: the identification of ORFs with Prodigal, tRNAs with tRNAscan-SE and functional annotation using BLAST implemented in USEARCH and HMMER-3. The databases used for taxonomical and functional annotation were: Silva SSU release 123, COG, TIGRFAM and NCBI non-redundant RefSeq release 75. Comparative metagenomic analysis of the three samples was applied in order to overcome the shallow sequencing of the metagenome and to identify sequences that appear in all samples and those that are sample specific. Quality filtered reads were co-assembled using MEGAHIT with a minimum contig length of 1,000 bp. Reads from each metagenome were mapped back to the contigs using bowtie-2. Anvi’o pipeline metagenomics workflow was applied to build a contigs database and to analyze the distribution of functional annotation of open reading frames and GC% across the individual samples. Briefly, reads of each sample were mapped to the co-assembled contigs and bins of clustered contigs were generated and stored in a phylogenetic tree applying the default settings of CONCOCT. Hierarchical clustering was done by combining the sequence alignments with the differential coverage of relative abundance of individual sample reads. The individual sample reads were aligned to the sequences in the contig bins using Euclidean distance with a maximum contig length of 20,000 bp. […]

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