Metagenomes, metatranscriptomes and microbiomes of naturally decomposing deadwood
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu dataset, časopisecké články, práce podpořená grantem
PubMed
34344895
PubMed Central
PMC8333335
DOI
10.1038/s41597-021-00987-8
PII: 10.1038/s41597-021-00987-8
Knihovny.cz E-zdroje
- MeSH
- Bacteria klasifikace MeSH
- buk (rod) mikrobiologie MeSH
- dřevo mikrobiologie MeSH
- ekosystém MeSH
- houby klasifikace MeSH
- lesy MeSH
- metagenom * MeSH
- mezerníky ribozomální DNA genetika MeSH
- mikrobiota * MeSH
- RNA ribozomální 16S genetika MeSH
- stromy mikrobiologie MeSH
- taxonomické DNA čárové kódování MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
- Názvy látek
- mezerníky ribozomální DNA MeSH
- RNA ribozomální 16S MeSH
Deadwood represents significant carbon (C) stock in a temperate forests. Its decomposition and C mobilization is accomplished by decomposer microorganisms - fungi and bacteria - who also supply the foodweb of commensalist microbes. Due to the ecosystem-level importance of deadwood habitat as a C and nutrient stock with significant nitrogen fixation, the deadwood microbiome composition and function are critical to understanding the microbial processes related to its decomposition. We present a comprehensive suite of data packages obtained through environmental DNA and RNA sequencing from natural deadwood. Data provide a complex picture of the composition and function of microbiome on decomposing trunks of European beech (Fagus sylvatica L.) in a natural forest. Packages include deadwood metagenomes, metatranscriptomes, sequences of total RNA, bacterial genomes resolved from metagenomic data and the 16S rRNA gene and ITS2 metabarcoding markers to characterize the bacterial and fungal communities. This project will be of use to microbiologists, environmental biologists and biogeochemists interested in the microbial processes associated with the transformation of recalcitrant plant biomass.
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Luyssaert S, et al. Old-growth forests as global carbon sinks. Nature. 2008;455:213–215. doi: 10.1038/nature07276. PubMed DOI
Pan Y, et al. A large and persistent carbon sink in the world’s forests. Science. 2011;333:988–993. doi: 10.1126/science.1201609. PubMed DOI
Rinne-Garmston KT, et al. Carbon flux from decomposing wood and its dependency on temperature, wood N2 fixation rate, moisture and fungal composition in a Norway spruce forest. Glob. Chang. Biol. 2019;25:1852–1867. doi: 10.1111/gcb.14594. PubMed DOI PMC
Šamonil P, et al. Convergence, divergence or chaos? Consequences of tree trunk decay for pedogenesis and the soil microbiome in a temperate natural forest. Geoderma. 2020;376:114499. doi: 10.1016/j.geoderma.2020.114499. DOI
Tláskal V, et al. Complementary roles of wood-inhabiting fungi and bacteria facilitate deadwood decomposition. mSystems. 2021;6:e01078–20. doi: 10.1128/mSystems.01078-20. PubMed DOI PMC
Odriozola I, et al. Fungal communities are important determinants of bacterial community composition in deadwood. mSystems. 2021;6:e01017–20. doi: 10.1128/mSystems.01017-20. PubMed DOI PMC
Valášková V, de Boer W, Gunnewiek PJAK, Pospíšek M, Baldrian P. Phylogenetic composition and properties of bacteria coexisting with the fungus Hypholoma fasciculare in decaying wood. ISME J. 2009;3:1218–1221. doi: 10.1038/ismej.2009.64. PubMed DOI
Brunner A, Kimmins JP. Nitrogen fixation in coarse woody debris of Thuja plicata and Tsuga heterophylla forests on northern Vancouver Island. Can. J. For. Res. 2003;33:1670–1682. doi: 10.1139/x03-085. DOI
Rinne KT, et al. Accumulation rates and sources of external nitrogen in decaying wood in a Norway spruce dominated forest. Funct. Ecol. 2016;31:530–541. doi: 10.1111/1365-2435.12734. DOI
Põlme S, et al. FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles. Fungal Divers. 2020;105:1–16. doi: 10.1007/s13225-020-00466-2. DOI
Tláskal V, Baldrian P. Deadwood-inhabiting bacteria show adaptations to changing carbon and nitrogen availability during decomposition. Front. Microbiol. 2021;12:685303. doi: 10.3389/fmicb.2021.685303. PubMed DOI PMC
Lemos LN, Mendes LW, Baldrian P, Pylro VS. Genome-resolved metagenomics is essential for unlocking the microbial black box of the soil. Trends Microbiol. 2021;29:279–282. doi: 10.1016/j.tim.2021.01.013. PubMed DOI
Větrovský T, et al. GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies. Sci. Data. 2020;7:228. doi: 10.1038/s41597-020-0567-7. PubMed DOI PMC
Thompson LR, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551:457–463. doi: 10.1038/nature24621. PubMed DOI PMC
Anderson-Teixeira KJ, Davies SJ, Bennett AC, Muller-landau HC, Wright SJ. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Chang. Biol. 2015;21:528–549. doi: 10.1111/gcb.12712. PubMed DOI
Baldrian P, et al. Fungi associated with decomposing deadwood in a natural beech-dominated forest. Fungal Ecol. 2016;23:109–122. doi: 10.1016/j.funeco.2016.07.001. DOI
Smyth CE, et al. Patterns of carbon, nitrogen and phosphorus dynamics in decomposing wood blocks in Canadian forests. Plant Soil. 2016;9:46–62.
Král K, et al. Local variability of stand structural features in beech dominated natural forests of Central Europe: Implications for sampling. For. Ecol. Manage. 2010;260:2196–2203. doi: 10.1016/j.foreco.2010.09.020. DOI
Caporaso JG, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–1624. doi: 10.1038/ismej.2012.8. PubMed DOI PMC
Lanzén A, et al. CREST – Classification resources for environmental sequence tags. PLoS One. 2012;7:e49334. doi: 10.1371/journal.pone.0049334. PubMed DOI PMC
Quast C, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–D596. doi: 10.1093/nar/gks1219. PubMed DOI PMC
Žifčáková L, Větrovský T, Howe A, Baldrian P. Microbial activity in forest soil reflects the changes in ecosystem properties between summer and winter. Environ. Microbiol. 2016;18:288–301. doi: 10.1111/1462-2920.13026. PubMed DOI
Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–2120. doi: 10.1093/bioinformatics/btu170. PubMed DOI PMC
Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–1676. doi: 10.1093/bioinformatics/btv033. PubMed DOI
Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165. doi: 10.7717/peerj.1165. PubMed DOI PMC
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–1055. doi: 10.1101/gr.186072.114. PubMed DOI PMC
Parks DH, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat. Microbiol. 2017;2:1533–1542. doi: 10.1038/s41564-017-0012-7. PubMed DOI
Parks DH, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 2018;36:996–1004. doi: 10.1038/nbt.4229. PubMed DOI
Lee MD. GToTree: A user-friendly workflow for phylogenomics. Bioinformatics. 2019;35:4162–4164. doi: 10.1093/bioinformatics/btz188. PubMed DOI PMC
Hyatt D, et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. doi: 10.1186/1471-2105-11-119. PubMed DOI PMC
Eddy SR. Accelerated profile HMM searches. PLoS Comput. Biol. 2011;7:e1002195. doi: 10.1371/journal.pcbi.1002195. PubMed DOI PMC
Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–1797. doi: 10.1093/nar/gkh340. PubMed DOI PMC
Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25:1972–1973. doi: 10.1093/bioinformatics/btp348. PubMed DOI PMC
Price MN, Dehal PS, Arkin AP. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5:e9490. doi: 10.1371/journal.pone.0009490. PubMed DOI PMC
Ihrmark K, et al. New primers to amplify the fungal ITS2 region – evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiol. Ecol. 2012;82:666–677. doi: 10.1111/j.1574-6941.2012.01437.x. PubMed DOI
Větrovský T, Baldrian P, Morais D. SEED 2: A user-friendly platform for amplicon high-throughput sequencing data analyses. Bioinformatics. 2018;34:2292–2294. doi: 10.1093/bioinformatics/bty071. PubMed DOI PMC
Aronesty E. Comparison of sequencing utility programs. Open Bioinforma. J. 2013;7:1–8. doi: 10.2174/1875036201307010001. DOI
Nilsson RH, et al. An open source software package for automated extraction of ITS1 and ITS2 from fungal ITS sequences for use in high-throughput community assays and molecular ecology. Fungal Ecol. 2010;3:284–287. doi: 10.1016/j.funeco.2010.05.002. DOI
Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460–2461. doi: 10.1093/bioinformatics/btq461. PubMed DOI
Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods. 2013;10:996–998. doi: 10.1038/nmeth.2604. PubMed DOI
Nilsson RH, et al. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classification. Nucleic Acids Res. 2018;47:D259–D264. doi: 10.1093/nar/gky1022. PubMed DOI PMC
Wright ES. Using DECIPHER v2.0 to analyze big biological sequence data in R. R J. 2016;8:352–359. doi: 10.32614/RJ-2016-025. DOI
Murali A, Bhargava A, Wright ES. IDTAXA: A novel approach for accurate taxonomic classification of microbiome sequences. Microbiome. 2018;6:140. doi: 10.1186/s40168-018-0521-5. PubMed DOI PMC
2020. NCBI BioProject. PRJNA603240
2020. NCBI Sequence Read Archive. PRJNA672674
Sutela S, Poimala A, Vainio EJ. Viruses of fungi and oomycetes in the soil environment. FEMS Microbiol. Ecol. 2019;95:fiz119. doi: 10.1093/femsec/fiz119. PubMed DOI
Woodcroft BJ, et al. Genome-centric view of carbon processing in thawing permafrost. Nature. 2018;560:49–54. doi: 10.1038/s41586-018-0338-1. PubMed DOI
Mackelprang R, et al. Microbial community structure and functional potential in cultivated and native tallgrass prairie soils of the Midwestern United States. Front. Microbiol. 2018;9:1775. doi: 10.3389/fmicb.2018.01775. PubMed DOI PMC
Hervé V, et al. Phylogenomic analysis of 589 metagenome-assembled genomes encompassing all major prokaryotic lineages from the gut of higher termites. PeerJ. 2020;8:e8614. doi: 10.7717/peerj.8614. PubMed DOI PMC
Clissmann F, et al. First insight into dead wood protistan diversity: a molecular sampling of bright-spored Myxomycetes (Amoebozoa, slime-moulds) in decaying beech logs. FEMS Microbiol. Ecol. 2015;91:fiv050. doi: 10.1093/femsec/fiv050. PubMed DOI
Urich T, et al. Simultaneous assessment of soil microbial community structure and function through analysis of the meta-transcriptome. PLoS One. 2008;3:e2527. doi: 10.1371/journal.pone.0002527. PubMed DOI PMC
Geisen S, et al. Metatranscriptomic census of active protists in soils. ISME J. 2015;9:2178–2190. doi: 10.1038/ismej.2015.30. PubMed DOI PMC
Tláskal V, Zrůstová P, Vrška T, Baldrian P. Bacteria associated with decomposing dead wood in a natural temperate forest. FEMS Microbiol. Ecol. 2017;93:fix157. doi: 10.1093/femsec/fix157. PubMed DOI
Moll J, et al. Bacteria inhabiting deadwood of 13 tree species reveal great heterogeneous distribution between sapwood and heartwood. Environ. Microbiol. 2018;20:3744–3756. doi: 10.1111/1462-2920.14376. PubMed DOI
Christofides SR, Hiscox J, Savoury M, Boddy L, Weightman AJ. Fungal control of early-stage bacterial community development in decomposing wood. Fungal Ecol. 2019;42:100868. doi: 10.1016/j.funeco.2019.100868. DOI
Nayfach S, et al. A genomic catalog of Earth’s microbiomes. Nat. Biotechnol. 2021;39:499–509. doi: 10.1038/s41587-020-0718-6. PubMed DOI PMC
Seibold S, et al. Experimental studies of dead-wood biodiversity — A review identifying global gaps in knowledge. Biol. Conserv. 2015;191:139–149. doi: 10.1016/j.biocon.2015.06.006. DOI
Long-read sequencing sheds light on key bacteria contributing to deadwood decomposition processes