in

Prolonged drought imparts lasting compositional changes to the rice root microbiome

  • 1.

    Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).

    CAS 

    Google Scholar 

  • 2.

    Zhang, J. et al. Effect of drought on agronomic traits of rice and wheat: a meta-analysis. Int. J. Environ. Res. Public Health 15, 839 (2018).

  • 3.

    Hirasawa, T., in Genetic Improvement of Rice for Water-Limited Environments (eds Ito, O, O’Toole, J. C. & Hardy, B.) 89–98 (International Rice Research Institute, 1999).

  • 4.

    Pandey, V. & Shukla, A. Acclimation and tolerance strategies of rice under drought stress. Rice Sci. 22, 147–161 (2015).

    Google Scholar 

  • 5.

    Compant, S., van der Heijden, M. G. A. & Sessitsch, A. Climate change effects on beneficial plant-microorganism interactions. FEMS Microbiol. Ecol. 73, 197–214 (2010).

    CAS 

    Google Scholar 

  • 6.

    de Vries, F. T., Griffiths, R. I., Knight, C. G., Nicolitch, O. & Williams, A. Harnessing rhizosphere microbiomes for drought-resilient crop production. Science 368, 270–274 (2020).

    Google Scholar 

  • 7.

    Busby, P. E. et al. Research priorities for harnessing plant microbiomes in sustainable agriculture. PLoS Biol. 15, e2001793 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 8.

    Santos-Medellín, C., Edwards, J., Liechty, Z., Nguyen, B. & Sundaresan, V. Drought stress results in a compartment-specific restructuring of the rice root-associated microbiomes. mBio 8, e00764-17 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 9.

    Naylor, D., DeGraaf, S., Purdom, E. & Coleman-Derr, D. Drought and host selection influence bacterial community dynamics in the grass root microbiome. ISME J. https://doi.org/10.1038/ismej.2017.118 (2017).

  • 10.

    Fitzpatrick, C. R. et al. Assembly and ecological function of the root microbiome across angiosperm plant species. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1717617115 (2018).

  • 11.

    Edwards, J. A. et al. Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice. PLoS Biol. 16, e2003862 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 12.

    Zhang, J. et al. Root microbiota shift in rice correlates with resident time in the field and developmental stage. Sci. China Life Sci. 61, 613–621 (2018).

    Google Scholar 

  • 13.

    Xu, L. et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proc. Natl Acad. Sci. USA 115, E4284–E4293 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 14.

    Liechty, Z. et al. Comparative analysis of root microbiomes of rice cultivars with high and low methane emissions reveals differences in abundance of methanogenic archaea and putative upstream fermenters. mSystems 5, e00897-19 (2020).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 15.

    Rong, X. & Huang, Y. Taxonomic evaluation of the Streptomyces griseus clade using multilocus sequence analysis and DNA–DNA hybridization, with proposal to combine 29 species and three subspecies as 11 genomic species. Int. J. Syst. Evol. Microbiol. 60, 696–703 (2010).

    CAS 

    Google Scholar 

  • 16.

    Lin, L. & Xu, X. Indole-3-acetic acid production by endophytic Streptomyces sp. En-1 isolated from medicinal plants. Curr. Microbiol. 67, 209–217 (2013).

    CAS 

    Google Scholar 

  • 17.

    Legault, G. S., Lerat, S., Nicolas, P. & Beaulieu, C. Tryptophan regulates thaxtomin A and indole-3-acetic acid production in Streptomyces scabiei and modifies its interactions with radish seedlings. Phytopathology 101, 1045–1051 (2011).

    CAS 

    Google Scholar 

  • 18.

    Guo, J. et al. Seed-borne, endospheric and rhizospheric core microbiota as predictor for plant functional traits across rice cultivars are dominated by deterministic processes. New Phytol. https://doi.org/10.1111/nph.17297 (2021).

  • 19.

    de Vries, F. T. et al. Soil bacterial networks are less stable under drought than fungal networks. Nat. Commun. 9, 3033 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 20.

    de Vries, F. T. & Shade, A. Controls on soil microbial community stability under climate change. Front. Microbiol. 4, 265 (2013).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 21.

    Borken, W. & Matzner, E. Reappraisal of drying and wetting effects on C and N mineralization and fluxes in soils. Glob. Change Biol. 15, 808–824 (2009).

    Google Scholar 

  • 22.

    Lueders, T. & Friedrich, M. W. Effects of amendment with ferrihydrite and gypsum on the structure and activity of methanogenic populations in rice field soil. Appl. Environ. Microbiol. 68, 2484–2494 (2002).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 23.

    Linquist, B. A. et al. Reducing greenhouse gas emissions, water use, and grain arsenic levels in rice systems. Glob. Change Biol. 21, 407–417 (2015).

    Google Scholar 

  • 24.

    Speirs, L. B. M., Rice, D. T. F., Petrovski, S. & Seviour, R. J. The phylogeny, biodiversity, and ecology of the chloroflexi in activated sludge. Front. Microbiol. 10, 2015 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 25.

    Thomas, S. H. et al. The mosaic genome of Anaeromyxobacter dehalogenans strain 2CP-C suggests an aerobic common ancestor to the delta-proteobacteria. PLoS ONE 3, e2103 (2008).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 26.

    Yang, T. H., Coppi, M. V., Lovley, D. R. & Sun, J. Metabolic response of Geobacter sulfurreducens towards electron donor/acceptor variation. Microb. Cell Fact. 9, 90 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 27.

    Keller, K. L. & Wall, J. D. Genetics and molecular biology of the electron flow for sulfate respiration in desulfovibrio. Front. Microbiol. 2, 135 (2011).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 28.

    Zhalnina, K. et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat. Microbiol. https://doi.org/10.1038/s41564-018-0129-3 (2018).

  • 29.

    Williams, A. & de Vries, F. T. Plant root exudation under drought: implications for ecosystem functioning. New Phytol. 225, 1899–1905 (2020).

    Google Scholar 

  • 30.

    Vries, F. T. et al. Changes in root-exudate-induced respiration reveal a novel mechanism through which drought affects ecosystem carbon cycling. New Phytol. 224, 132–145 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 31.

    Casartelli, A. et al. Exploring traditional aus-type rice for metabolites conferring drought tolerance. Rice 11, 9 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 32.

    Pérez-Jaramillo, J. E. et al. Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. ISME J. https://doi.org/10.1038/ismej.2017.85 (2017).

  • 33.

    Kang, D.-J. & Futakuchi, K. Effect of moderate drought-stress on flowering time of interspecific hybrid progenies (Oryza sativa L. × Oryza glaberrima Steud.). J. Crop Sci. Biotechnol. 22, 75–81 (2019).

    Google Scholar 

  • 34.

    Guo, X. et al. Host-associated quantitative abundance profiling reveals the microbial load variation of root microbiome. Plant Commun. 1, 100003 (2020).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 35.

    Varoquaux, N. et al. Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1907500116 (2019).

  • 36.

    Li, P. et al. Physiological and transcriptome analyses reveal short-term responses and formation of memory under drought stress in rice. Front. Genet. 10, 55 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 37.

    Vandenkoornhuyse, P., Quaiser, A., Duhamel, M., Le Van, A. & Dufresne, A. The importance of the microbiome of the plant holobiont. New Phytol. 206, 1196–1206 (2015).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 38.

    Toju, H. et al. Core microbiomes for sustainable agroecosystems. Nat. Plants 4, 247–257 (2018).

    Google Scholar 

  • 39.

    Shade, A. & Stopnisek, N. Abundance-occupancy distributions to prioritize plant core microbiome membership. Curr. Opin. Microbiol. 49, 50–58 (2019).

    Google Scholar 

  • 40.

    Suralta, R. R. et al. Plasticity in nodal root elongation through the hardpan triggered by rewatering during soil moisture fluctuation stress in rice. Sci. Rep. 8, 4341 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 41.

    Hamedi, J. & Mohammadipanah, F. Biotechnological application and taxonomical distribution of plant growth promoting actinobacteria. J. Ind. Microbiol. Biotechnol. 42, 157–171 (2015).

    CAS 

    Google Scholar 

  • 42.

    Vurukonda, S. S. K. P., Vardharajula, S., Shrivastava, M. & SkZ, A. Enhancement of drought stress tolerance in crops by plant growth promoting rhizobacteria. Microbiol. Res. 184, 13–24 (2016).

    Google Scholar 

  • 43.

    Aznar, A. & Dellagi, A. New insights into the role of siderophores as triggers of plant immunity: what can we learn from animals? J. Exp. Bot. 66, 3001–3010 (2015).

    CAS 

    Google Scholar 

  • 44.

    Viaene, T., Langendries, S., Beirinckx, S., Maes, M. & Goormachtig, S. Streptomyces as a plant’s best friend? FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiw119 (2016).

  • 45.

    Meena, K. K. et al. Abiotic stress responses and microbe-mediated mitigation in plants: the omics strategies. Front. Plant Sci. 8, 172 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 46.

    Mukamuhirwa, A. et al. Effect of intermittent drought on grain yield and quality of rice (Oryza sativa L.) grown in Rwanda. J. Agro Crop Sci. 206, 252–262 (2020).

    CAS 

    Google Scholar 

  • 47.

    Fleta-Soriano, E. & Munné-Bosch, S. Stress memory and the inevitable effects of drought: a physiological perspective. Front. Plant Sci. 7, 143 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 48.

    Ding, Y., Fromm, M. & Avramova, Z. Multiple exposures to drought ‘train’ transcriptional responses in Arabidopsis. Nat. Commun. 3, 740 (2012).

    Google Scholar 

  • 49.

    de la Fuente Cantó, C. et al. An extended root phenotype: the rhizosphere, its formation and impacts on plant fitness. Plant J. 103, 951–964 (2020).

    Google Scholar 

  • 50.

    Kittas, C., Bartzanas, T. & Jaffrin, A. Temperature gradients in a partially shaded large greenhouse equipped with evaporative cooling pads. Biosyst. Eng. 85, 87–94 (2003).

    Google Scholar 

  • 51.

    Edwards, J. et al. Soil domestication by rice cultivation results in plant–soil feedback through shifts in soil microbiota. Genome Biol. 20, 221 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 52.

    Edwards, J., Santos-Medellín, C. & Sundaresan, V. Extraction and 16S rRNA sequence analysis of microbiomes associated with rice roots. Bio. Protoc. 8, e2884 (2018).

  • 53.

    Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108, 4516–4522 (2011).

    CAS 

    Google Scholar 

  • 54.

    Masella, A. P., Bartram, A. K., Truszkowski, J. M., Brown, D. G. & Neufeld, J. D. PANDAseq: paired-end assembler for illumina sequences. BMC Bioinform. 13, 31 (2012).

    CAS 

    Google Scholar 

  • 55.

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

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 56.

    Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 57.

    DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 58.

    Weimer, B. C. 100K Pathogen Genome Project. Genome Announc. 5, e00594-17 (2017).

  • 59.

    Kong, N. et al. Draft genome sequences of 1,183 Salmonella strains from the 100K Pathogen Genome Project. Genome Announc. 5, e00518–17 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 60.

    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 

  • 61.

    Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 62.

    Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

    CAS 

    Google Scholar 

  • 63.

    Medema, M. H. et al. antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences. Nucleic Acids Res. 39, W339–W346 (2011).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 64.

    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018); https://www.R-project.org/

  • 65.

    McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 66.

    Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 67.

    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 

  • 68.

    McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 69.

    Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 70.

    Oksanen, J. et al. vegan: Community Ecology Package (2018).

  • 71.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).

  • 72.

    Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 13 (2017).

    Google Scholar 

  • 73.

    Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. Emmeans: estimated marginal means, aka least-squares means. R package v.1, 3 (R Foundation for Statistical Computing, 2018).

  • 74.

    Kassambara, A. Rstatix: pipe-friendly framework for basic statistical tests. R package v.0.6.0 (R Foundation for Statistical Computing, 2020).

  • 75.

    Graves, S., Piepho, H.-P., Selzer, L. & Dorai-Raj, S. multcompView: visualizations of paired comparisons. R package v.0.1-7 (R Foundation for Statistical Computing, 2015).

  • 76.

    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 77.

    Liaw, A. & Wiener, M. Classification and regression by randomForest. R. News 2, 18–22 (2002).

    Google Scholar 

  • 78.

    Subramanian, S. et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature 510, 417–421 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 


  • Source: Ecology - nature.com

    Reducing emissions by decarbonizing industry

    Quality assessment of Urochloa (syn. Brachiaria) seeds produced in Cameroon