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      Integrative visual omics of the white-rot fungus Polyporus brumalis exposes the biotechnological potential of its oxidative enzymes for delignifying raw plant biomass

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          Abstract

          Background

          Plant biomass conversion for green chemistry and bio-energy is a current challenge for a modern sustainable bioeconomy. The complex polyaromatic lignin polymers in raw biomass feedstocks (i.e., agriculture and forestry by-products) are major obstacles for biomass conversions. White-rot fungi are wood decayers able to degrade all polymers from lignocellulosic biomass including cellulose, hemicelluloses, and lignin. The white-rot fungus Polyporus brumalis efficiently breaks down lignin and is regarded as having a high potential for the initial treatment of plant biomass in its conversion to bio-energy. Here, we describe the extraordinary ability of P. brumalis for lignin degradation using its enzymatic arsenal to break down wheat straw, a lignocellulosic substrate that is considered as a biomass feedstock worldwide.

          Results

          We performed integrative multi-omics analyses by combining data from the fungal genome, transcriptomes, and secretomes. We found that the fungus possessed an unexpectedly large set of genes coding for Class II peroxidases involved in lignin degradation (19 genes) and GMC oxidoreductases/dehydrogenases involved in generating the hydrogen peroxide required for lignin peroxidase activity and promoting redox cycling of the fungal enzymes involved in oxidative cleavage of lignocellulose polymers (36 genes). The examination of interrelated multi-omics patterns revealed that eleven Class II Peroxidases were secreted by the fungus during fermentation and eight of them where tightly co-regulated with redox cycling enzymatic partners.

          Conclusion

          As a peculiar feature of P. brumalis, we observed gene family extension, up-regulation and secretion of an abundant set of versatile peroxidases and manganese peroxidases, compared with other Polyporales species. The orchestrated secretion of an abundant set of these delignifying enzymes and redox cycling enzymatic partners could contribute to the delignification capabilities of the fungus. Our findings highlight the diversity of wood decay mechanisms present in Polyporales and the potentiality of further exploring this taxonomic order for enzymatic functions of biotechnological interest.

          Electronic supplementary material

          The online version of this article (10.1186/s13068-018-1198-5) contains supplementary material, which is available to authorized users.

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          Most cited references48

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          Expansion of the enzymatic repertoire of the CAZy database to integrate auxiliary redox enzymes

          Background Since its inception, the carbohydrate-active enzymes database (CAZy; http://www.cazy.org) has described the families of enzymes that cleave or build complex carbohydrates, namely the glycoside hydrolases (GH), the polysaccharide lyases (PL), the carbohydrate esterases (CE), the glycosyltransferases (GT) and their appended non-catalytic carbohydrate-binding modules (CBM). The recent discovery that members of families CBM33 and family GH61 are in fact lytic polysaccharide monooxygenases (LPMO), demands a reclassification of these families into a suitable category. Results Because lignin is invariably found together with polysaccharides in the plant cell wall and because lignin fragments are likely to act in concert with (LPMO), we have decided to join the families of lignin degradation enzymes to the LPMO families and launch a new CAZy class that we name “Auxiliary Activities” in order to accommodate a range of enzyme mechanisms and substrates related to lignocellulose conversion. Comparative analyses of these auxiliary activities in 41 fungal genomes reveal a pertinent division of several fungal groups and subgroups combining their phylogenetic origin and their nutritional mode (white vs. brown rot). Conclusions The new class introduced in the CAZy database extends the traditional CAZy families, and provides a better coverage of the full extent of the lignocellulose breakdown machinery.
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            Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3.

            Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.
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              Protein structure homology modeling using SWISS-MODEL workspace.

              Homology modeling aims to build three-dimensional protein structure models using experimentally determined structures of related family members as templates. SWISS-MODEL workspace is an integrated Web-based modeling expert system. For a given target protein, a library of experimental protein structures is searched to identify suitable templates. On the basis of a sequence alignment between the target protein and the template structure, a three-dimensional model for the target protein is generated. Model quality assessment tools are used to estimate the reliability of the resulting models. Homology modeling is currently the most accurate computational method to generate reliable structural models and is routinely used in many biological applications. Typically, the computational effort for a modeling project is less than 2 h. However, this does not include the time required for visualization and interpretation of the model, which may vary depending on personal experience working with protein structures.
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                Author and article information

                Contributors
                Shingo.Miyauchi@inra.fr
                anais.rancon@gmail.com
                elodie.drula@afmb.univ-mrs.fr
                hayat.hage@etu.univ-amu.fr
                delphine.chaduli@inra.fr
                anne.favel@univ-amu.fr
                sacha.grisel@inra.fr
                Bernard.Henrissat@afmb.univ-mrs.fr
                isabelle.gimbert@univ-amu.fr
                fjruiz@cib.csic.es
                didier.chevret@inra.fr
                hmadmatt@gmail.com
                junyanlin@lbl.gov
                mwang@lbl.gov
                JLPangilinan@lbl.gov
                alipzen@lbl.gov
                laurence.lesage-meessen@inra.fr
                david.navarro@inra.fr
                rwriley@lbl.gov
                IVGrigoriev@lbl.gov
                simeng.zhou@univ-amu.fr
                sana.raouche@univ-amu.fr
                marie-noelle.rosso@inra.fr
                Journal
                Biotechnol Biofuels
                Biotechnol Biofuels
                Biotechnology for Biofuels
                BioMed Central (London )
                1754-6834
                23 July 2018
                23 July 2018
                2018
                : 11
                : 201
                Affiliations
                [1 ]ISNI 0000 0001 2176 4817, GRID grid.5399.6, Aix Marseille Univ, INRA, UMR 1163, Biodiversité et Biotechnologie Fongiques, BBF, ; Marseille, France
                [2 ]ISNI 0000 0001 2176 4817, GRID grid.5399.6, CIRM-CF, UMR1163, INRA, Aix-Marseille Univ, ; Marseille, France
                [3 ]ISNI 0000 0004 1798 275X, GRID grid.463764.4, UMR 7257, CNRS, Aix-Marseille Univ, ; Marseille, France
                [4 ]ISNI 0000 0004 1798 275X, GRID grid.463764.4, INRA, USC 1408, AFMB, ; Marseille, France
                [5 ]ISNI 0000 0001 0619 1117, GRID grid.412125.1, Department of Biological Sciences, , King Abdulaziz University, ; Jeddah, Saudi Arabia
                [6 ]ISNI 0000 0004 1794 0752, GRID grid.418281.6, Centro de Investigaciones Biológicas, CSIC, ; Madrid, Spain
                [7 ]GRID grid.417961.c, INRA, UMR1319, Micalis, Plateforme d’Analyse Protéomique de Paris Sud-Ouest, ; Jouy-en-Josas, France
                [8 ]ISNI 0000 0004 0449 479X, GRID grid.451309.a, US Department of Energy Joint Genome Institute, ; Walnut Creek, CA USA
                [9 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Department of Plant and Microbial Biology, , University of California Berkeley, ; Berkeley, CA USA
                [10 ]ISNI 0000 0001 2194 6418, GRID grid.29172.3f, Present Address: Laboratoire d’Excellence ARBRE, , UMR 1136, INRA-Université de Lorraine ‘Interactions Arbres/Microorganismes’, ; Champenoux, France
                [11 ]ISNI 0000 0004 1759 7798, GRID grid.450959.4, Present Address: Institut des Sciences Moléculaires de Marseille, UMR 7313, CNRS, Aix-Marseille Université, ; Marseille, France
                Author information
                http://orcid.org/0000-0001-8317-7220
                Article
                1198
                10.1186/s13068-018-1198-5
                6055342
                30061923
                315d38de-3bd5-4263-a2d9-6e7a8f139ab8
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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.

                History
                : 16 April 2018
                : 6 July 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-14-CE06-0020-01
                Award ID: ANR-12-BIME-0009
                Award ID: ANR-10-EQPX-29-01
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000015, U.S. Department of Energy;
                Award ID: DE-AC02-05CH11231
                Funded by: Spanish Ministry of Economy, Industry and Competitiveness
                Award ID: BIO2017-86559-R
                Funded by: FundRef http://dx.doi.org/10.13039/501100010076, Conseil Régional Provence-Alpes-Côte d'Azur;
                Award ID: 2017_05836
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100006488, Institut National de la Recherche Agronomique;
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Biotechnology
                solid-state fermentation,lignin degradation,polyporus brumalis,plant biomass transformation

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