Artificial selection of stable rhizosphere microbiota leads to heritable plant phenotype changes.
evolution
group selection
heritability
interaction
microbiota
plant-microbe interaction
stability
Journal
Ecology letters
ISSN: 1461-0248
Titre abrégé: Ecol Lett
Pays: England
ID NLM: 101121949
Informations de publication
Date de publication:
Jan 2022
Jan 2022
Historique:
revised:
07
09
2021
received:
20
04
2021
accepted:
27
09
2021
pubmed:
9
11
2021
medline:
15
12
2021
entrez:
8
11
2021
Statut:
ppublish
Résumé
Artificial selection of microbiota opens new avenues for improving plants. However, reported results lack consistency. We hypothesised that the success in artificial selection of microbiota depends on the stabilisation of community structure. In a ten-generation experiment involving 1,800 plants, we selected rhizosphere microbiota of Brachypodium distachyon associated with high or low leaf greenness, a proxy of plant performance. The microbiota structure showed strong fluctuations during an initial transitory phase, with no detectable leaf greenness heritability. After five generations, the microbiota structure stabilised, concomitantly with heritability in leaf greenness. Selection, initially ineffective, did successfully alter the selected property as intended, especially for high selection. We show a remarkable correlation between the variability in plant traits and selected microbiota structures, revealing two distinct sub-communities associated with high or low leaf greenness, whose abundance was significantly steered by directional selection. Understanding microbiota structure stabilisation will improve the reliability of artificial microbiota selection.
Types de publication
Letter
Langues
eng
Sous-ensembles de citation
IM
Pagination
189-201Subventions
Organisme : FABER project
ID : 2017-9201AAO049S01302
Informations de copyright
© 2021 John Wiley & Sons Ltd.
Références
Akmouche, Y., Cheneby, J., Lamboeuf, M., Elie, N., Laperche, A., Bertheloot, J. et al. (2019) Do nitrogen- and sulphur-remobilization-related parameters measured at the onset of the reproductive stage provide early indicators to adjust N and S fertilization in oilseed rape (Brassica napus L.) grown under N- and/or S-limiting supplies? Planta, 250, 2047-2062.
Arias-Sánchez, F.I., Vessman, B. & Mitri, S. (2019) Artificially selecting microbial communities: if we can breed dogs, why not microbiomes? PLoS Biology, 17, e3000356.
Baker, G.C., Smith, J.J. & Cowan, D.A. (2003) Review and re-analysis of domain-specific 16S primers. Journal of Microbiol Methods, 55, 541-555.
Blouin, M., Karimi, B., Mathieu, J. & Lerch, T.Z. (2015) Levels and limits in artificial selection of communities. Ecology Letters, 18, 1040-1048.
Chang, C.Y., Osborne, M.L., Bajic, D. & Sanchez, A. (2020) Artificially selecting bacterial communities using propagule strategies. Evolution, 74, 2392-2403.
Conner, J.K. (2003) Artificial selection: a powerful tool for ecologists. Ecology, 84, 1650-1660.
Dixon, P. (2003) VEGAN, a package of R functions for community ecology. Journal of Vegetation Science, 14, 927-930.
Draper, J., Mur, L.A.J., Jenkins, G., Ghosh-Biswas, G.C., Bablak, P., Hasterok, R. et al. (2001) Brachypodium distachyon. A new model system for functional genomics in grasses. Plant Physiology, 127, 1539-1555.
Estensmo, E.L.F., Sundy, M., Morgado, L., Martin-Sanchez, P.M., Skrede, I. & Kauserud, H. (2021) The influence of intraspecific sequence variation during DNA metabarcoding: a case study of eleven fungal species. Molecular Ecology Resources, 21, 1141-1148.
Girin, T., David, L.C., Chardin, C., Sibout, R., Krapp, A., Ferrario-Méry, S. et al. (2014) Brachypodium: a promising hub between model species and cereals. Journal of Experimental Botany, 65, 5683-5696.
Herlemann, D.P., Labrenz, M., Jurgens, K., Bertilsson, S., Waniek, J.J. & Andersson, A.F. (2011) Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. The ISME Journal, 5, 1571-1579.
Ihrmark, K., Bödeker, I.T.M., Cruz-Martinez, K., Friberg, H., Kubartova, A., Schenck, J. et al. (2012) New primers to amplify the fungal ITS2 region - evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiology Ecology, 82, 666-677.
Kalacska, M., Lalonde, M. & Moore, T.R. (2015) Estimation of foliar chlorophyll and nitrogen content in an ombrotrophic bog from hyperspectral data: scaling from leaf to image. Remote Sensing of Environment, 169, 270-279.
Komsta, L. & Novomestky, F. (2011) Moments: moments, cumulants, skewness, kurtosis and related tests R package version 0.12.
Lau, J.A. & Lennon, J.T. (2012) Rapid responses of soil microorganisms improve plant fitness in novel environments. Proceedings of the National Academy of Sciences of the United States of America, 109, 14058-14062.
Lemanceau, P., Blouin, M., Muller, D. & Moënne-Loccoz, Y. (2017) Let the core microbiota be functional. Trends in Plant Science, 22, 583-595.
Lewontin, R.C. (1970) The units of selection. Annual Review of Ecology Evolution and Systematics, 1, 1-18.
Luo, Y., Wang, F., Huang, Y., Zhou, M., Gao, J., Yan, T. et al. (2019) Sphingomonas sp. Cra20 increases plant growth rate and alters rhizosphere microbial community structure of arabidopsis thaliana under drought stress. Frontiers in Microbiology, 10, 1221.
Marín, I. & Arahal, D.R. (2014) The Family Beijerinckiaceae. In: Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, E. & Thompson, F. (Eds.) The Prokaryotes. Springer, Berlin, Heidelberg.
May, M.R. (1972). Qualitative stability in model ecosystems. Ecology, 54, 638-641.
Milcu, A., Puga-Freitas, R., Ellison, A.M., Blouin, M., Scheu, S., Freschet, G.T. et al. (2018) Genotypic variability enhances the reproducibility of an ecological study. Nature Ecology and Evolution, 2, 279-287.
Millard, P. (1988) The accumulation and storage of nitrogen by herbaceous plants. Plant, Cell and Environment, 11, 1-8.
Mueller, U.G., Juenger, T.E., Kardish, M.R., Carlson, A.L., Burns, K., Smith, C.C. et al. (2016) Artificial microbiome selection to engineer microbiomes that confer salt-tolerance to plants. BioRxiv, https://doi.org/10.1101/081521.
Mueller, U.G. & Sachs, J.L. (2015) Engineering Microbiomes to Improve Plant and Animal Health. Trends in Microbiology, 23, 606-617.
Muggeo, V. & Muggeo, R. (2008) Segmented: an R package to fit regression models with broken-line relationships. R News, 8(1), 20-25.
Muyzer, G., De Waal, E.C. & Uitterlinden, A.G. (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Applied and Environment Microbiology, 59, 695-700.
Pagé, A.P., Tremblay, J., Masson, L. & Greer, C.W. (2019) Nitrogen- and phosphorus-starved Triticum aestivum show distinct belowground microbiome profiles. PLoS One, 14, e0210538.
Panke-Buisse, K., Poole, A.C., Goodrich, J.K., Ley, R.E. & Kao-Kniffin, J. (2015) Selection on soil microbiomes reveals reproducible impacts on plant function. The ISME J, 9, 980-989.
Penn, A. (2003). Modelling Artificial Ecosystem Selection: A Preliminary Investigation. In Advances in Artificial Life, ECAL, Lecture Notes in Computer Science, vol. 2801. Springer, Berlin, Heidelberg.
Penn, A. & Harvey, I. (2004). The role of non-genetic change in the heritability, variation and response to selection of artificially selected ecosystems. In Proceedings of the ninth international conference on artificial life. MIT Press, pp. 352-357.
Philippot, L., Raaijmakers, J.M., Lemanceau, P. & van der Putten, W. (2013) Going back to the roots: the microbial ecology of the rhizosphere. Nature Reviews Microbiology, 11, 789-799.
R core Team. (2020) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing, http://www.R-project.org/
Raynaud, T., Devers, M., Spor, A. & Blouin, M. (2019) Effect of the reproduction method in an artificial selection experiment at the community level. Frontiers in Ecology and Evolution, 7, 416.
Rohart, F., Gautier, B., Singh, A. & Lê Cao, K. A. (2017) mixOmics: an R package for ‘omics’ feature selection and multiple data integration. PLoS Computational Biology, 13, e1005752.
Salon, C. (2012) PPHD: a platform for phenotyping. Biofutur, 338, 61-64.
Sanchez, A., Vila, J.C.C., Chang, C., Diaz-Colunga, J., Estrela, S. & Rebolleda-Gomez, M. (2020) Directed evolution of microbial communities. Annual Review of Biophysics, 50, 323-341.
Schöler, A., Jacquiod, S., Vestergaard, G., Schulz, S. & Schloter, M. (2017) Analysis of soil microbial communities based on amplicon sequencing of marker genes. Biology and Fertility of Soils, 53, 485.
Spor, A., Roucou, A., Mounier, A., Bru, D., Breuil, M.-C., Fort, F. et al. (2020) Domestication-driven changes in plant traits associated with changes in the assembly of the rhizosphere microbiota in tetraploid wheat. Scientific Reports, 10, 12234.
Swenson, W., Arendt, J. & Sloan-Wilson, D. (2000) Artificial selection of microbial ecosystems for 3-chloroaniline biodegradation. Environmental Microbiology, 2, 564-571.
Swenson, W., Wilson, D.S. & Elias, R. (2000) Artificial ecosystem selection. Proceedings of the National Academy of Sciences of the United States of America, 97, 9110-9114.
Tilman, D. & Downing, J. (1994) Biodiversity and stability in grasslands. Nature, 367, 363-365.
van der Heijden, M.G.A., Bardgett, R.D. & Van Straalen, N.M. (2008) The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecology Letters, 11, 296-310.
Wade, M.J. (1976) Group selection among laboratory populations of Tribolium. Proceedings of the National Academy of Sciences of the United States of America, 73, 4604-4607.
Warren, C.R., Adams, M.A. & Chen, Z. (2000) Is photosynthesis related to concentrations of nitrogen and Rubisco in leaves of Australian native plants? Functional Plant Biology, 27, 407-416.
Watt, M., Schneebeli, K., Dong, P. & Wilson, I.W. (2009) The shoot and root growth of Brachypodium and its potential as a model for wheat and other cereal crops. Functional Plant Biology, 36, 960-969.
Wei, Z. & Jousset, A. (2017) Plant Breeding Goes Microbial. Trends in Plant Science, 22, 555-558.
White, T., Bruns, T., Lee, S., Taylor, F., White, T.J., Lee, S.H. et al. (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR protocols: a guide to methods and applications, 18 ed. London: Academic Press, pp. 315-322.
Xie, L., Yuan, A.E. & Wenying, S. (2019) Simulations reveal challenges to artificial community selection and possible strategies for success. PLoS Biology, 17, e3000295.
Xiong, D., Chen, J., Yu, T., Gao, W., Ling, X., Li, Y. et al. (2015) SPAD-based leaf nitrogen estimation is impacted by environmental factors and crop leaf characteristics. Scientific Reports, 5, 1-12.