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      Abundance, classification and genetic potential of Thaumarchaeota in metagenomes of European agricultural soils: a meta-analysis

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          Abstract

          Background

          For a sustainable production of food, research on agricultural soil microbial communities is inevitable. Due to its immense complexity, soil is still some kind of black box. Soil study designs for identifying microbiome members of relevance have various scopes and focus on particular environmental factors. To identify common features of soil microbiomes, data from multiple studies should be compiled and processed. Taxonomic compositions and functional capabilities of microbial communities associated with soils and plants have been identified and characterized in the past few decades. From a fertile Loess–Chernozem-type soil located in Germany, metagenomically assembled genomes (MAGs) classified as members of the phylum Thaumarchaeota/Thermoproteota were obtained. These possibly represent keystone agricultural soil community members encoding functions of relevance for soil fertility and plant health. Their importance for the analyzed microbiomes is corroborated by the fact that they were predicted to contribute to the cycling of nitrogen, feature the genetic potential to fix carbon dioxide and possess genes with predicted functions in plant-growth-promotion (PGP). To expand the knowledge on soil community members belonging to the phylum Thaumarchaeota, we conducted a meta-analysis integrating primary studies on European agricultural soil microbiomes.

          Results

          Taxonomic classification of the selected soil metagenomes revealed the shared agricultural soil core microbiome of European soils from 19 locations. Metadata reporting was heterogeneous between the different studies. According to the available metadata, we separated the data into 68 treatments. The phylum Thaumarchaeota is part of the core microbiome and represents a major constituent of the archaeal subcommunities in all European agricultural soils. At a higher taxonomic resolution, 2074 genera constituted the core microbiome. We observed that viral genera strongly contribute to variation in taxonomic profiles. By binning of metagenomically assembled contigs, Thaumarchaeota MAGs could be recovered from several European soil metagenomes. Notably, many of them were classified as members of the family Nitrososphaeraceae, highlighting the importance of this family for agricultural soils. The specific Loess-Chernozem Thaumarchaeota MAGs were most abundant in their original soil, but also seem to be of importance in other agricultural soil microbial communities. Metabolic reconstruction of Switzerland_1_MAG_2 revealed its genetic potential i.a. regarding carbon dioxide (CO \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_2$$\end{document} ) fixation, ammonia oxidation, exopolysaccharide production and a beneficial effect on plant growth. Similar genetic features were also present in other reconstructed MAGs. Three Nitrososphaeraceae MAGs are all most likely members of a so far unknown genus.

          Conclusions

          On a broad view, European agricultural soil microbiomes are similarly structured. Differences in community structure were observable, although analysis was complicated by heterogeneity in metadata recording. Our study highlights the need for standardized metadata reporting and the benefits of networking open data. Future soil sequencing studies should also consider high sequencing depths in order to enable reconstruction of genome bins. Intriguingly, the family Nitrososphaeraceae commonly seems to be of importance in agricultural microbiomes.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40793-023-00479-9.

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          Most cited references56

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          Fast and sensitive protein alignment using DIAMOND.

          The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.
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            CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

            Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.
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              Embracing the unknown: disentangling the complexities of the soil microbiome

              Soil contains a vast diversity of microorganisms that can directly or indirectly modulate soil processes and terrestrial ecosystems. In this Review, Fierer summarizes the challenges in characterizing the composition and functions of the soil microbiome, and discusses key future research directions.
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                Author and article information

                Contributors
                jnelkner@cebitec.uni-bielefeld.de
                huanglr@cebitec.uni-bielefeld.de
                lin@uni-mainz.de
                aschulz@techfak.uni-bielefeld.de
                benedikt@cebitec.uni-bielefeld.de
                christian@cebitec.uni-bielefeld.de
                jochen.blom@computational.bio.uni-giessen.de
                puehler@cebitec.uni-bielefeld.de
                asczyrba@cebitec.uni-bielefeld.de
                aschluet@cebitec.uni-bielefeld.de
                Journal
                Environ Microbiome
                Environ Microbiome
                Environmental Microbiome
                BioMed Central (London )
                2524-6372
                30 March 2023
                30 March 2023
                2023
                : 18
                : 26
                Affiliations
                [1 ]GRID grid.7491.b, ISNI 0000 0001 0944 9128, Genome Research of Industrial Microorganisms, CeBiTec - Center for Biotechnology, , Bielefeld University, ; Bielefeld, Germany
                [2 ]GRID grid.7491.b, ISNI 0000 0001 0944 9128, Computational Metagenomics Group, CeBiTec - Center for Biotechnology, , Bielefeld University, ; Bielefeld, Germany
                [3 ]GRID grid.7491.b, ISNI 0000 0001 0944 9128, Machine Learning Group, CITEC - Cognitive Interaction Technology, , Bielefeld University, ; Bielefeld, Germany
                [4 ]GRID grid.8664.c, ISNI 0000 0001 2165 8627, Bioinformatics and Systems Biology, , Justus-Liebig-University, ; Gießen, Germany
                [5 ]GRID grid.5802.f, ISNI 0000 0001 1941 7111, Nucleic Acids Core Facility, Faculty of Biology, , Johannes Gutenberg University Mainz, ; Germany Mainz,
                Author information
                https://orcid.org/0000-0001-9441-0403
                https://orcid.org/0000-0003-4729-837X
                https://orcid.org/0000-0002-3872-1706
                https://orcid.org/0000-0002-0739-612X
                https://orcid.org/0000-0002-2912-4950
                https://orcid.org/0000-0001-6455-3622
                https://orcid.org/0000-0003-4723-2960
                https://orcid.org/0000-0002-4405-3847
                https://orcid.org/0000-0003-4830-310X
                Article
                479
                10.1186/s40793-023-00479-9
                10064710
                36998097
                1aa14701-39a7-4102-9851-e91be13baa52
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 September 2022
                : 9 March 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A
                Award ID: 031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
                Award ID: 818431
                Award ID: 818431
                Award ID: 818431
                Award ID: 818431
                Award Recipient :
                Funded by: Universität Bielefeld (3146)
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                european soil,agricultural microbiome,open metagenome data analysis,metagenomically assembled genomes,soil health,thaumarchaeota,soil microbial diversity

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