in

Genetic determinants of endophytism in the Arabidopsis root mycobiome

[adace-ad id="91168"]
  • 1.

    Hou, S. et al. A microbiota–root–shoot circuit favours Arabidopsis growth over defence under suboptimal light. Nat. Plants 7, 1078–1092 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 2.

    Durán, P. et al. Microbial interkingdom interactions in roots promote Arabidopsis survival. Cell 175, 973–983.e14 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 3.

    van der Heijden, M. G., Bruin, S., de, Luckerhoff, L., van Logtestijn, R. S. & Schlaeppi, K. A widespread plant-fungal-bacterial symbiosis promotes plant biodiversity, plant nutrition and seedling recruitment. ISME J. 10, 389–399 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 4.

    Carrión, V. J. et al. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 366, 606–612 (2019).

    ADS 
    PubMed 

    Google Scholar 

  • 5.

    Wagg, C., Schlaeppi, K., Banerjee, S., Kuramae, E. E. & van der Heijden, M. G. A. Fungal-bacterial diversity and microbiome complexity predict ecosystem functioning. Nat. Commun. 10, 1–10 (2019).

    CAS 

    Google Scholar 

  • 6.

    Martin, F. M., Uroz, S. & Barker, D. G. Ancestral alliances: Plant mutualistic symbioses with fungi and bacteria. Science 356 (2017).

  • 7.

    Nagy, L. G. et al. in The Fungal Kingdom 35–56 (ASM Press, 2017). https://doi.org/10.1128/9781555819583.ch2.

  • 8.

    Brundrett, M. C. & Tedersoo, L. Evolutionary history of mycorrhizal symbioses and global host plant diversity. N. Phytol. 220, 1108–1115 (2018).

    Google Scholar 

  • 9.

    Delavaux, C. S. et al. Mycorrhizal fungi influence global plant biogeography. Nat. Ecol. Evol. 3, 424–429 (2019).

    PubMed 

    Google Scholar 

  • 10.

    Soudzilovskaia, N. A. et al. Global mycorrhizal plant distribution linked to terrestrial carbon stocks. Nat. Commun. 10, 1–10 (2019).

    CAS 

    Google Scholar 

  • 11.

    Steidinger, B. S. et al. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 569, 404–408 (2019).

    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • 12.

    Trivedi, P., Leach, J. E., Tringe, S. G., Sa, T. & Singh, B. K. Plant–microbiome interactions: from community assembly to plant health. Nat. Rev. Microbiol. 18, 607–621 (2020).

    CAS 
    PubMed 

    Google Scholar 

  • 13.

    Lugtenberg, B. J. J., Caradus, J. R. & Johnson, L. J. Fungal endophytes for sustainable crop production. FEMS Microbiol. Ecol. 92, fiw194 (2016).

    PubMed 

    Google Scholar 

  • 14.

    Glynou, K. et al. The local environment determines the assembly of root endophytic fungi at a continental scale. Environ. Microbiol. 18, 2418–2434 (2016).

    CAS 
    PubMed 

    Google Scholar 

  • 15.

    Glynou, K., Nam, B., Thines, M. & Maciá-Vicente, J. G. Facultative root-colonizing fungi dominate endophytic assemblages in roots of nonmycorrhizal Microthlaspi species. N. Phytol. 217, 1190–1202 (2018).

    Google Scholar 

  • 16.

    U’Ren, J. M. et al. Host availability drives distributions of fungal endophytes in the imperilled boreal realm. Nat. Ecol. Evol. 3, 1430–1437 (2019).

    PubMed 

    Google Scholar 

  • 17.

    Maciá-Vicente, J. G., Piepenbring, M. & Koukol, O. Brassicaceous roots as an unexpected diversity hot-spot of helotialean endophytes. IMA Fungus 11, 1–23 (2020).

    Google Scholar 

  • 18.

    Thiergart, T. et al. Root microbiota assembly and adaptive differentiation among European Arabidopsis populations. Nat. Ecol. Evol. 4, 122–131 (2020).

    PubMed 

    Google Scholar 

  • 19.

    Oita, S. et al. Climate and seasonality drive the richness and composition of tropical fungal endophytes at a landscape scale. Commun. Biol. 4, 1–11 (2021).

    Google Scholar 

  • 20.

    Vannier, N., Bittebiere, A. K., Mony, C. & Vandenkoornhuyse, P. Root endophytic fungi impact host plant biomass and respond to plant composition at varying spatio-temporal scales. Fungal Ecol. 44, 100907 (2020).

    Google Scholar 

  • 21.

    Jumpponen, A., Herrera, J., Porras-Alfaro, A. & Rudgers, J. Biogeography of root-associated fungal endophytes. Biogeography of Mycorrhizal Symbiosis 195–222. https://doi.org/10.1007/978-3-319-56363-3_10 (2017).

  • 22.

    Bokati, D., Herrera, J. & Poudel, R. Soil influences colonization of root-associated fungal endophyte communities of maize, wheat, and their progenitors. J. Mycol. 2016, 1–9 (2016).

    Google Scholar 

  • 23.

    Card, S. D. et al. Beneficial endophytic microorganisms of Brassica – A review. Biol. Control 90, 102–112 (2015).

    Google Scholar 

  • 24.

    Junker, C., Draeger, S. & Schulz, B. A fine line – endophytes or pathogens in Arabidopsis thaliana. Fungal Ecol. 5, 657–662 (2012).

    Google Scholar 

  • 25.

    Fesel, P. H. & Zuccaro, A. Dissecting endophytic lifestyle along the parasitism/mutualism continuum in Arabidopsis. Curr. Opin. Microbiol. 32, 103–112 (2016).

    PubMed 

    Google Scholar 

  • 26.

    Kia, S. H. et al. Influence of phylogenetic conservatism and trait convergence on the interactions between fungal root endophytes and plants. ISME J. 11, 777–790 (2017).

    PubMed 

    Google Scholar 

  • 27.

    Lahrmann, U. et al. Mutualistic root endophytism is not associated with the reduction of saprotrophic traits and requires a noncompromised plant innate immunity. N. Phytol. 207, 841–857 (2015).

    CAS 

    Google Scholar 

  • 28.

    Hacquard, S. et al. Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi. Nat. Commun. 7, 1–13 (2016).

    Google Scholar 

  • 29.

    Hiruma, K. et al. Root endophyte Colletotrichum tofieldiae confers plant fitness benefits that are phosphate status dependent. Cell 165, 464–474 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 30.

    Almario, J. et al. Root-associated fungal microbiota of nonmycorrhizal Arabis alpina and its contribution to plant phosphorus nutrition. Proc. Natl Acad. Sci. USA 114, E9403–E9412 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 31.

    Kohler, A. et al. Convergent losses of decay mechanisms and rapid turnover of symbiosis genes in mycorrhizal mutualists. Nat. Genet. 47, 410–415 (2015).

    CAS 
    PubMed 

    Google Scholar 

  • 32.

    Miyauchi, S. et al. Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits. Nat. Commun. 11, 1–17 (2020).

    Google Scholar 

  • 33.

    Spatafora, J. W., Sung, G. H. J. M. S., Hywel-Jones, N. L. & White, J. F. Phylogenetic evidence for an animal pathogen origin of ergot and the grass endophytes. Mol. Ecol. 16, 1701–1711 (2007).

    CAS 
    PubMed 

    Google Scholar 

  • 34.

    Xu, X. H. et al. The rice endophyte Harpophora oryzae genome reveals evolution from a pathogen to a mutualistic endophyte. Sci. Rep. 4, 1–9 (2014).

    CAS 

    Google Scholar 

  • 35.

    Weiß, M., Waller, F., Zuccaro, A. & Selosse, M. Sebacinales – one thousand and one interactions with land plants. N. Phytol. 211, 20–40 (2016).

    Google Scholar 

  • 36.

    Knapp, D. G. et al. Comparative genomics provides insights into the lifestyle and reveals functional heterogeneity of dark septate endophytic fungi. Sci. Rep. 8, 6321 (2018).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 37.

    Hettiarachchige, I. K. et al. Global changes in asexual Epichloë transcriptomes during the early stages, from seed to seedling, of symbiotum establishment. Microorg 9, 991 (2021).

    Google Scholar 

  • 38.

    Větrovský, T. et al. GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies. Sci. Data 7, 1–14 (2020).

    Google Scholar 

  • 39.

    Agler, M. T. et al. Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 14, e1002352 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 40.

    Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).

    Google Scholar 

  • 41.

    Selosse, M.-A., Schneider-Maunoury, L. & Martos, F. Time to re-think fungal ecology? Fungal ecological niches are often prejudged. N. Phytol. 217, 968–972 (2018).

    Google Scholar 

  • 42.

    Zuccaro, A. et al. Endophytic life strategies decoded by genome and transcriptome analyses of the mutualistic root symbiont Piriformospora indica. PLoS Pathog. 7, e1002290 (2011).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 43.

    David, A. S. et al. Draft genome sequence of Microdochium bolleyi, a dark septate fungal endophyte of beach grass. Genome Announc. 4, e00270-16 (2016).

  • 44.

    Walker, A. K. et al. Full genome of Phialocephala scopiformis DAOMC 229536, a fungal endophyte of spruce producing the potent anti-insectan compound rugulosin. Genome Announc. 4, e01768-15 (2016).

  • 45.

    Wu, W. et al. Characterization of four endophytic fungi as potential consolidated bioprocessing hosts for conversion of lignocellulose into advanced biofuels. Appl. Microbiol. Biotechnol. 101.6, 2603–2618 (2017).

    Google Scholar 

  • 46.

    Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 1–14 (2019).

    Google Scholar 

  • 47.

    Csűös, M. Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood. Bioinformatics 26, 1910–1912 (2010).

    Google Scholar 

  • 48.

    Shah, F. et al. Ectomycorrhizal fungi decompose soil organic matter using oxidative mechanisms adapted from saprotrophic ancestors. N. Phytol. 209, 1705–1719 (2016).

    CAS 

    Google Scholar 

  • 49.

    Pellegrin, C., Morin, E., Martin, F. M. & Veneault-Fourrey, C. Comparative analysis of secretomes from ectomycorrhizal fungi with an emphasis on small-secreted proteins. Front. Microbiol. 6, 1278 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 50.

    Tung Ho, L. S. & Ané, C. A linear-time algorithm for gaussian and non-gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).

    Google Scholar 

  • 51.

    Klopfenstein, D. V. et al. GOATOOLS: A Python library for Gene Ontology analyses. Sci. Rep. 8, 1–17 (2018).

    CAS 

    Google Scholar 

  • 52.

    Szklarczyk, D. et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 53.

    Schulz, B. & Boyle, C. The endophytic continuum. Mycol. Res. 109, 661–686 (2005).

    PubMed 

    Google Scholar 

  • 54.

    Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 55.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 56.

    Curran, D. M., Gilleard, J. S. & Wasmuth, J. D. MIPhy: identify and quantify rapidly evolving members of large gene fam. PeerJ 2018, e4873 (2018).

    Google Scholar 

  • 57.

    Atanasova, L. et al. Evolution and functional characterization of pectate lyase PEL12, a member of a highly expanded Clonostachys rosea polysaccharide lyase 1 family. BMC Microbiol. 18, 1–19 (2018).

    Google Scholar 

  • 58.

    Keim, J., Mishra, B., Sharma, R., Ploch, S. & Thines, M. Root-associated fungi of Arabidopsis thaliana and Microthlaspi perfoliatum. Fungal Divers 66, 99–111 (2014).

    Google Scholar 

  • 59.

    Vannier, N., Agler, M. & Hacquard, S. Microbiota-mediated disease resistance in plants. PLoS Pathog. 15, e1007740 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 60.

    Hassani, M. A., Durán, P. & Hacquard, S. Microbial interactions within the plant holobiont. Microbiome 6, 1–17 (2018).

    Google Scholar 

  • 61.

    Getzke, F., Thiergart, T. & Hacquard, S. Contribution of bacterial-fungal balance to plant and animal health. Curr. Opin. Microbiol. 49, 66–72 (2019).

    CAS 
    PubMed 

    Google Scholar 

  • 62.

    Wolinska, K. W. et al. Tryptophan metabolism and bacterial commensals prevent fungal dysbiosis in Arabidopsis roots. Proc. Natl Acad Sci USA. 118, e2111521118 (2021).

    PubMed 

    Google Scholar 

  • 63.

    Lofgren, L. A. et al. Genome-based estimates of fungal rDNA copy number variation across phylogenetic scales and ecological lifestyles. Mol. Ecol. 28, 721–730 (2019).

    PubMed 

    Google Scholar 

  • 64.

    Karasov, T. L. et al. Arabidopsis thaliana and Pseudomonas pathogens exhibit stable associations over evolutionary timescales. Cell Host Microbe 24, 168–179.e4 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 65.

    Karasov, T. L. et al. The relationship between microbial population size and disease in the Arabidopsis thaliana phyllosphere. Preprint at https://doi.org/10.1101/828814 (2020).

  • 66.

    Benen, J. A. E., Kester, H. C. M., Pařenicová, L. & Visser, J. Characterization of Aspergillus niger pectate lyase A. Biochemistry 39, 15563–15569 (2000).

    CAS 
    PubMed 

    Google Scholar 

  • 67.

    Bauer, S., Vasu, P., Persson, S., Mort, A. J. & Somerville, C. R. Development and application of a suite of polysaccharide-degrading enzymes for analyzing plant cell walls. Proc. Natl Acad. Sci. USA 103, 11417–11422 (2006).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 68.

    Bacic, A. Breaking an impasse in pectin biosynthesis. Proc. Natl Acad. Sci. USA 103, 5639–5640 (2006).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 69.

    Vogel, J. Unique aspects of the grass cell wall. Curr. Opin. Plant Biol. 11, 301–307 (2008).

    CAS 
    PubMed 

    Google Scholar 

  • 70.

    Bacete, L. et al. Arabidopsis response reGUlator 6 (ARR6) modulates plant cell-wall composition and disease resistance. Mol. Plant-Microbe Interact. 33, 767–780 (2020).

    CAS 
    PubMed 

    Google Scholar 

  • 71.

    Molina, A. et al. Arabidopsis cell wall composition determines disease resistance specificity and fitness. Proc. Natl Acad. Sci. USA 118, 2021 (2021).

    Google Scholar 

  • 72.

    Sun, Z.-B. et al. Biology and applications of Clonostachys rosea. J. Appl. Microbiol. 129, 486–495 (2020).

    PubMed 

    Google Scholar 

  • 73.

    Broberg, M. et al. Comparative genomics highlights the importance of drug efflux transporters during evolution of mycoparasitism in Clonostachys subgenus Bionectria (Fungi, Ascomycota, Hypocreales). Evol. Appl. 14, 476–497 (2021).

    CAS 
    PubMed 

    Google Scholar 

  • 74.

    Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 75.

    Chin, C. S. et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods 13, 1050–1054 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 76.

    Grabherr, M. G. et al. Trinity: Reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat. Biotechnol. 29, 644 (2011).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 77.

    Grigoriev, I. V. et al. MycoCosm portal: gearing up for 1000 fungal genomes. Nucleic Acids Res. 42, D699–D704 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 78.

    Nilsson, R. H. et al. The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 47, D259–D264 (2019).

    CAS 
    PubMed 

    Google Scholar 

  • 79.

    Solovyev, V., Kosarev, P., Seledsov, I. & Vorobyev, D. Automatic annotation of eukaryotic genes, pseudogenes and promoters. Genome Biol. 7, S10 (2006).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 80.

    Cohen, O., Ashkenazy, H., Belinky, F., Huchon, D. & Pupko, T. GLOOME: gain-loss mapping engine. Bioinformatics 26, 2914–2915 (2010).

    CAS 
    PubMed 

    Google Scholar 

  • 81.

    Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Machine Learning Res. http://scikit-learn.sourceforge.net. (2011).

  • 82.

    Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: Assessing genome assembly and annotation completeness. In Methods in Molecular Biology vol. 1962, 227–245 (Humana Press Inc., 2019).

  • 83.

    Morin, E. et al. Comparative genomics of Rhizophagus irregularis, R. cerebriforme, R. diaphanus and Gigaspora rosea highlights specific genetic features in Glomeromycotina. N. Phytol. 222, 1584–1598 (2019).

    CAS 

    Google Scholar 

  • 84.

    Cantarel, B. I. et al. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res. 37, 233–238 (2009).

    Google Scholar 

  • 85.

    Rawlings, N. D., Barrett, A. J. & Finn, R. Twenty years of the MEROPS database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res. 44, D343–D350 (2016).

    CAS 
    PubMed 

    Google Scholar 

  • 86.

    Fischer, M. & Pleiss, J. The Lipase Engineering Database: a navigation and analysis tool for protein families. Nucleic Acids Res. 31, 319–321 (2003).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 87.

    Cock, P. J. A. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 88.

    Deorowicz, S., Debudaj-Grabysz, A. & Gudys, A. FAMSA: Fast and accurate multiple sequence alignment of huge protein families. Sci. Rep. 6, 1–13 (2016).

    Google Scholar 

  • 89.

    Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).

  • 90.

    Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 91.

    Morris, J. H. et al. ClusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC Bioinforma. 12, 436 (2011).

    CAS 

    Google Scholar 

  • 92.

    Gruber, B. D., Giehl, R. F. H., Friedel, S. & von Wirén, N. Plasticity of the Arabidopsis root system under nutrient deficiencies. Plant Physiol. 163, 161–179 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 93.

    Hedges, L. V. Distribution Theory for Glass’s estimator of effect size and related estimators. J. Educ. Stat. 6, 107–128 (1981).

    Google Scholar 

  • 94.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 95.

    Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    CAS 

    Google Scholar 

  • 96.

    Zhu, A., Ibrahim, J. G. & Love, M. I. Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinformatics 35, 2084–2092 (2019).

    CAS 
    PubMed 

    Google Scholar 

  • 97.

    Mesny, F. Genomic determinants of endophytism in the Arabidopsis root mycobiome. GitHub https://doi.org/10.5281/zenodo.5642698 (2021).


  • Source: Ecology - nature.com

    A tool to speed development of new solar cells

    Commensal Pseudomonas protect Arabidopsis thaliana from a coexisting pathogen via multiple lineage-dependent mechanisms