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      Microbial community of the geothermal soils of Pantelleria

      Creators
      Hogendoorn, C.
      Picone, N.
      Hout, F van
      Vijverberg, S.
      Poghosyan, L.
      Alen, T. van
      Frank, J.
      Pol, A.
      Gagliano, A.L.
      Jetten, M.S.M.
      D'Alessandro, W.
      Quatrini, P.
      Camp, H.J.M. op den
      Date of Archiving
      2020
      Archive
      NCBI
      Related links
      https://www.ncbi.nlm.nih.gov/bioproject/PRJEB36447
      DOI
      http://dx.doi.org/10.1007/s10482-021-01525-7
      Related publications
      Draft genome of a novel methanotrophic Methylobacter sp. from the volcanic soils of Pantelleria Island  
      Publication type
      Dataset
      Access level
      Open access
      Please use this identifier to cite or link to this item: https://hdl.handle.net/2066/239524   https://hdl.handle.net/2066/239524
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      Organization
      Ecological Microbiology
      Audience(s)
      Biology
      Key words
      methane; methanotroph; volcanic soil; metabolic potential
      Abstract
      In this stujdy, we try to describe a geothermal microbial community by means of metagenomics and genomics of isolated microorganisms. Sampling location and DNA isolation Samples were collected at Favara Grande, Pantelleria, Italy 2017 (FAV1, 36° 50′ 80″ N; 11° 57′ 170″ E) and (FAV2, 36° 50′ 77″ N; 11°57′ 160″ E) during a field campaign in June 2017 (Picone et al. 2020). Soil samples (1–10, 10–15 and 12–20 cm depth) were taken using a core sampler (diameter 1.5 cm), stored in sterile 50 mL tubes and kept at 4 °C until DNA was extracted. In situ pH values were 4–4.5 with temperatures from 60 to 67 °C. Two different DNA extraction methods were used, namely Fast DNA Spin kit for soil (MP Biomedicals, Santa Ana, California), according to manufacturer’s instructions, and the CTAB method (Allen et al. 2006). DNA extraction was only successful from the FAV2 sampling site and the reads from the different depths and different extraction methods were combined for assembly and binning. For more detail see Picone et al. (2020). Genome sequencing, assembly and binning The metagenome was sequenced on the Illumina sequencing platform. For library preparation the Nextera XT kit (Illumina, San Diego, California) was used according to the manufacturer’s instructions. Enzymatic tagmentation was performed starting with 1 ng of DNA, followed by incorporation of the indexed adapters and amplification of the library. After purification of the amplified library using AMPure XP beads (Beckman Coulter, Indianapolis), libraries were checked for quality and size distribution using the Agilent 2100 Bioanalyzer and the High sensitivity DNA kit. Quantitation of the library was performed by Qubit using the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, Massachusetts). The libraries were pooled, denatured and sequenced with the Illumina Miseq sequence machine (San Diego, California). Paired end sequencing of 2 × 300 base pairs was performed using the MiSeq Reagent Kit v3 (Illumina, San Diego, California) according the manufacturers protocol. Reads were trimmed using BBDuk (BBMap), assembled by MEGAHIT v1.0.3 (Li et al. 2015) and binned using an in-house pipeline, using different binning algorithms, including BinSanity (Graham et al. 2017), COCACOLA (Lu et al. 2017), CONCOCT (Alneberg et al. 2014), MaxBin 2.0 (Wu et al. 2016), and MetaBAT 2 (Kang et al. 2019). DAS Tool 1.0 was used for consensus binning (Sieber et al. 2018) and CheckM was used to assess the MAG quality (Parks et al. 2015). The average nucleotide identity using BLAST (ANIb) is calculated using JSpeciesWS software with standard settings (Richter et al. 2016). An up-to-date Bacterial Core Gene (UBCG) phylogenetic tree was constructed using RAxML (Stamatakis 2014) on CIPRES Science Gateway V. 3.3 platform (Miller et al. 2012). PROKKA and the MicroScope platform were used to automatically annotate the draft genome (Seemann 2014; Vallenet et al. 2013) and genomic features were manually checked.
      This item appears in the following Collection(s)
      • Datasets [1528]
      • Faculty of Science [34950]
       
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