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      Soil depth matters: shift in composition and inter-kingdom co-occurrence patterns of microorganisms in forest soils

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          ABSTRACT

          Soil depth represents a strong physiochemical gradient that greatly affects soil-dwelling microorganisms. Fungal communities are typically structured by soil depth, but how other microorganisms are structured is less known. Here, we tested whether depth-dependent variation in soil chemistry affects the distribution and co-occurrence patterns of soil microbial communities. This was investigated by DNA metabarcoding in conjunction with network analyses of bacteria, fungi, as well as other micro-eukaryotes, sampled in four different soil depths in Norwegian birch forests. Strong compositional turnover in microbial assemblages with soil depth was detected for all organismal groups. Significantly greater microbial diversity and fungal biomass appeared in the nutrient-rich organic layer, with sharp decrease towards the less nutrient-rich mineral zones. The proportions of copiotrophic bacteria, Arthropoda and Apicomplexa were markedly higher in the organic layer, while patterns were opposite for oligotrophic bacteria, Cercozoa, Ascomycota and ectomycorrhizal fungi. Network analyses indicated more intensive inter-kingdom co-occurrence patterns in the upper mineral layer (0–5 cm) compared to the above organic and the lower mineral soil, signifying substantial influence of soil depth on biotic interactions. This study supports the view that different microbial groups are adapted to different forest soil strata, with varying level of interactions along the depth gradient.

          Abstract

          This study highlights the importance of different soil horizons as well as a combination of markers when assessing microorganisms in forest soil and provide hypotheses about depth-dependent biotic interactions.

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          UCHIME improves sensitivity and speed of chimera detection

          Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: robert@drive5.com Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information: Supplementary data are available at Bioinformatics online.
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            VSEARCH: a versatile open source tool for metagenomics

            Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
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              Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB

              A 16S rRNA gene database ( http://greengenes.lbl.gov ) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria .
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                Author and article information

                Contributors
                Journal
                FEMS Microbiol Ecol
                FEMS Microbiol Ecol
                femsec
                FEMS Microbiology Ecology
                Oxford University Press
                0168-6496
                1574-6941
                06 February 2021
                March 2021
                06 February 2021
                : 97
                : 3
                : fiab022
                Affiliations
                Section for Genetics and Evolutionary Biology (EvoGene), Department of Biosciences, University of Oslo , NO-0316 Oslo, Norway
                Department of Biology, College of Science, United Arab Emirates University , Al-Ain, Abu-Dhabi, UAE
                NIBIO, Department of Terrestrial Ecology , NO-1431 Ås, Norway
                Section for Genetics and Evolutionary Biology (EvoGene), Department of Biosciences, University of Oslo , NO-0316 Oslo, Norway
                Naturalis Biodiversity Center , 2300 RA Leiden, the Netherlands
                Section for Genetics and Evolutionary Biology (EvoGene), Department of Biosciences, University of Oslo , NO-0316 Oslo, Norway
                Faculty of Environmental and Natural Resource Management, Norwegian University of Life Sciences , NO-1432 Ås, Norway
                Section for Genetics and Evolutionary Biology (EvoGene), Department of Biosciences, University of Oslo , NO-0316 Oslo, Norway
                Author notes
                Corresponding author: Department of Biology, College of Science, United Arab Emirates University, Al-Ain, Abu-Dhabi, UAE. Tel: +47 92510337; E-mail: sunilm@ 123456ibv.uio.no ; sunilmundra@ 123456hotmail.com
                Author information
                https://orcid.org/0000-0002-0535-118X
                https://orcid.org/0000-0002-0782-0584
                Article
                fiab022
                10.1093/femsec/fiab022
                7948073
                33547899
                0b794aac-7142-4108-8b9d-39baed71d2e8
                © The Author(s) 2021. Published by Oxford University Press on behalf of FEMS.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 December 2020
                : 04 February 2021
                Page count
                Pages: 15
                Funding
                Funded by: Research Council of Norway, DOI 10.13039/501100005416;
                Award ID: 255307
                Award ID: 240859
                Categories
                Research Article
                AcademicSubjects/SCI01150

                Microbiology & Virology
                co-occurrences patterns,metabarcoding,microbial communities,microbial interactions,betula pubescens,boreal birch forest

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