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      Phylogenomic analysis of 589 metagenome-assembled genomes encompassing all major prokaryotic lineages from the gut of higher termites

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          Abstract

          “Higher” termites have been able to colonize all tropical and subtropical regions because of their ability to digest lignocellulose with the aid of their prokaryotic gut microbiota. Over the last decade, numerous studies based on 16S rRNA gene amplicon libraries have largely described both the taxonomy and structure of the prokaryotic communities associated with termite guts. Host diet and microenvironmental conditions have emerged as the main factors structuring the microbial assemblages in the different gut compartments. Additionally, these molecular inventories have revealed the existence of termite-specific clusters that indicate coevolutionary processes in numerous prokaryotic lineages. However, for lack of representative isolates, the functional role of most lineages remains unclear. We reconstructed 589 metagenome-assembled genomes (MAGs) from the different gut compartments of eight higher termite species that encompass 17 prokaryotic phyla. By iteratively building genome trees for each clade, we significantly improved the initial automated assignment, frequently up to the genus level. We recovered MAGs from most of the termite-specific clusters in the radiation of, for example, Planctomycetes, Fibrobacteres, Bacteroidetes, Euryarchaeota, Bathyarchaeota, Spirochaetes, Saccharibacteria, and Firmicutes, which to date contained only few or no representative genomes. Moreover, the MAGs included abundant members of the termite gut microbiota. This dataset represents the largest genomic resource for arthropod-associated microorganisms available to date and contributes substantially to populating the tree of life. More importantly, it provides a backbone for studying the metabolic potential of the termite gut microbiota, including the key members involved in carbon and nitrogen biogeochemical cycles, and important clues that may help cultivating representatives of these understudied clades.

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          Most cited references78

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          IMG 4 version of the integrated microbial genomes comparative analysis system

          The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).
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            Symbiotic digestion of lignocellulose in termite guts.

            Their ability to degrade lignocellulose gives termites an important place in the carbon cycle. This ability relies on their partnership with a diverse community of bacterial, archaeal and eukaryotic gut symbionts, which break down the plant fibre and ferment the products to acetate and variable amounts of methane, with hydrogen as a central intermediate. In addition, termites rely on the biosynthetic capacities of their gut microbiota as a nutritional resource. The mineralization of humus components in the guts of soil-feeding species also contributes to nitrogen cycling in tropical soils. Lastly, the high efficiency of their minute intestinal bioreactors makes termites promising models for the industrial conversion of lignocellulose into microbial products and the production of biofuels.
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              Lignocellulose degradation mechanisms across the Tree of Life

              Organisms use diverse mechanisms involving multiple complementary enzymes, particularly glycoside hydrolases (GHs), to deconstruct lignocellulose. Lytic polysaccharide monooxygenases (LPMOs) produced by bacteria and fungi facilitate deconstruction as does the Fenton chemistry of brown-rot fungi. Lignin depolymerisation is achieved by white-rot fungi and certain bacteria, using peroxidases and laccases. Meta-omics is now revealing the complexity of prokaryotic degradative activity in lignocellulose-rich environments. Protists from termite guts and some oomycetes produce multiple lignocellulolytic enzymes. Lignocellulose-consuming animals secrete some GHs, but most harbour a diverse enzyme-secreting gut microflora in a mutualism that is particularly complex in termites. Shipworms however, house GH-secreting and LPMO-secreting bacteria separate from the site of digestion and the isopod Limnoria relies on endogenous enzymes alone. The omics revolution is identifying many novel enzymes and paradigms for biomass deconstruction, but more emphasis on function is required, particularly for enzyme cocktails, in which LPMOs may play an important role.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                13 February 2020
                2020
                : 8
                : e8614
                Affiliations
                [1 ]Research Group Insect Gut Microbiology and Symbiosis, Max Planck Institute for Terrestrial Microbiology , Marburg, Germany
                [2 ]Laboratory of Experimental and Comparative Ethology EA 4443, Université Paris 13 , Villetaneuse, France
                [3 ]Faculty of Forestry and Wood Sciences, Czech University of Life Sciences , Prague, Czech Republic
                Author information
                http://orcid.org/0000-0002-3495-561X
                http://orcid.org/0000-0001-6141-5603
                http://orcid.org/0000-0002-2667-4391
                Article
                8614
                10.7717/peerj.8614
                7024585
                32095380
                3ff8ab91-5353-47e6-8f51-e411e55a7ed7
                © 2020 Hervé et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 29 August 2019
                : 21 January 2020
                Funding
                Funded by: Deutsche Forschungsgemeinschaft in the collaborative research center SFB 987 (Microbial Diversity in Environmental Signal Response)
                Funded by: Max-Planck-Gesellschaft
                Funded by: U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility
                Funded by: Office of Science of the U.S. Department of Energy
                Award ID: DE-AC02-05CH11231
                Funded by: OP RDE “EVA4.0”
                Award ID: CZ.02.1.01/0.0/0.0/16_019/0000803
                This study was funded by the Deutsche Forschungsgemeinschaft in the collaborative research center SFB 987 (Microbial Diversity in Environmental Signal Response) and by the Max-Planck-Gesellschaft. The work conducted by the U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Petr Stiblik and Jan Šobotník were supported by grant “EVA4.0,” No. CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Ecology
                Genomics
                Microbiology

                metagenome-assembled genomes,gut microbiology,higher termites,bacteria,archaea,phylogenomics,metagenomics,spirochaetes,fibrobacteres,bathyarchaeota

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