27
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Unravelling the gut bacteriome of Ips (Coleoptera: Curculionidae: Scolytinae): identifying core bacterial assemblage and their ecological relevance

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Bark beetles often serve as forest damaging agents, causing landscape-level mortality. Understanding the biology and ecology of beetles are important for both, gathering knowledge about important forest insects and forest protection. Knowledge about the bark beetle gut-associated bacteria is one of the crucial yet surprisingly neglected areas of research with European tree-killing bark beetles. Hence, in this study, we survey the gut bacteriome from five Ips and one non- Ips bark beetles from Scolytinae. Results reveal 69 core bacterial genera among five Ips beetles that may perform conserved functions within the bark beetle holobiont. The most abundant bacterial genera from different bark beetle gut include Erwinia, Sodalis, Serratia, Tyzzerella, Raoultella, Rahnella, Wolbachia, Spiroplasma, Vibrio, and Pseudoxanthomonas. Notable differences in gut-associated bacterial community richness and diversity among the beetle species are observed. Furthermore, the impact of sampling location on the overall bark beetle gut bacterial community assemblage is also documented, which warrants further investigations. Nevertheless, our data expanded the current knowledge about core gut bacterial communities in Ips bark beetles and their putative function such as cellulose degradation, nitrogen fixation, detoxification of defensive plant compounds, and inhibition of pathogens, which could serve as a basis for further metatranscriptomics and metaproteomics investigations.

          Related collections

          Most cited references97

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              QIIME allows analysis of high-throughput community sequencing data.

                Bookmark

                Author and article information

                Contributors
                Roy@fld.czu.cz
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 October 2020
                29 October 2020
                2020
                : 10
                : 18572
                Affiliations
                [1 ]GRID grid.15866.3c, ISNI 0000 0001 2238 631X, EVA 4.0 Unit, Faculty of Forestry and Wood Sciences, , Czech University of Life Sciences Prague, ; Kamýcká 129, Suchdol, 165 21 Prague 6, Czech Republic
                [2 ]GRID grid.15866.3c, ISNI 0000 0001 2238 631X, Excellent Team for Mitigation (ETM), Faculty of Forestry and Wood Sciences, , Czech University of Life Sciences Prague, ; Kamýcká 129, Suchdol, 165 21 Prague 6, Czech Republic
                [3 ]GRID grid.6341.0, ISNI 0000 0000 8578 2742, Department of Plant Protection Biology, , Swedish University of Agricultural Sciences, ; 230 53 Alnarp, Sweden
                Article
                75203
                10.1038/s41598-020-75203-5
                7596566
                33122700
                142f026d-aca2-4bfd-9a06-c556b27aa58f
                © The Author(s) 2020

                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 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/.

                History
                : 30 April 2020
                : 7 October 2020
                Funding
                Funded by: OP RDE
                Award ID: EVA 4.0”, No. CZ.02.1.01/0.0 /0.0/16_019 /0000803
                Award ID: EXTEMIT-K, CZ.02.1.01/0.0/0.0/15_003/0000433
                Award Recipient :
                Funded by: Fakulta Lesnická a Drevarská, Česká Zemědělská Univerzita v Praze
                Award ID: IGA
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                microbial ecology,microbial communities
                Uncategorized
                microbial ecology, microbial communities

                Comments

                Comment on this article