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      Metaproteome plasticity sheds light on the ecology of the rumen microbiome and its connection to host traits

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          Abstract

          The arsenal of genes that microbes express reflect the way in which they sense their environment. We have previously reported that the rumen microbiome composition and its coding capacity are different in animals having distinct feed efficiency states, even when fed an identical diet. Here, we reveal that many microbial populations belonging to the bacteria and archaea domains show divergent proteome production in function of the feed efficiency state. Thus, proteomic data serve as a strong indicator of host feed efficiency state phenotype, overpowering predictions based on genomic and taxonomic information. We highlight protein production of specific phylogenies associated with each of the feed efficiency states. We also find remarkable plasticity of the proteome both in the individual population and at the community level, driven by niche partitioning and competition. These mechanisms result in protein production patterns that exhibit functional redundancy and checkerboard distribution that are tightly linked to the host feed efficiency phenotype. By linking microbial protein production and the ecological mechanisms that act within the microbiome feed efficiency states, our present work reveals a layer of complexity that bears immense importance to the current global challenges of food security and sustainability.

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          Most cited references51

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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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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                Author and article information

                Contributors
                imizrahi@bgu.ac.il
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                16 August 2022
                16 August 2022
                November 2022
                : 16
                : 11
                : 2610-2621
                Affiliations
                [1 ]GRID grid.7489.2, ISNI 0000 0004 1937 0511, Faculty of Natural Sciences, , Ben-Gurion University of the Negev, ; Beer-Sheva, 8499000 Israel
                [2 ]GRID grid.5603.0, Institute of Microbiology, Department of Microbial Proteomics, , (Center for Functional Genomics of Microbes), University of Greifswald, ; Greifswald, 17489 Germany
                [3 ]GRID grid.410498.0, ISNI 0000 0001 0465 9329, Department of Ruminant Science, Institute of Animal Sciences, , Agricultural Research Organization, Volcani Center, ; Rishon LeZion, 7505101 Israel
                [4 ]GRID grid.13992.30, ISNI 0000 0004 0604 7563, Department of Biomolecular Sciences, , The Weizmann Institute of Science, ; Rehovot, 7610001 Israel
                [5 ]GRID grid.4818.5, ISNI 0000 0001 0791 5666, Present Address: Aquaculture and Fisheries Group, Department of Animal Sciences, , Wageningen University, ; 6700AH Wageningen, The Netherlands
                Author information
                http://orcid.org/0000-0003-3272-5746
                http://orcid.org/0000-0002-2839-0843
                http://orcid.org/0000-0001-6636-8818
                Article
                1295
                10.1038/s41396-022-01295-8
                9563048
                35974086
                2b6c8786-2989-47a9-a683-99be6e41068e
                © The Author(s) 2022

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 November 2021
                : 8 June 2022
                : 12 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: 64084
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003977, Israel Science Foundation (ISF);
                Award ID: 1947/19
                Award ID: 1947/19
                Award Recipient :
                Categories
                Article
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                © International Society for Microbial Ecology 2022

                Microbiology & Virology
                microbial ecology,microbiome
                Microbiology & Virology
                microbial ecology, microbiome

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