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Artificial Microbiome-Selection to Engineer Microbiomes That Confer Salt-Tolerance to Plants

View ORCID ProfileUlrich G Mueller, View ORCID ProfileThomas E Juenger, Melissa R Kardish, Alexis L Carlson, Kathleen Burns, Joseph A Edwards, Chad C Smith, Chi-Chun Fang, David L Des Marais
doi: https://doi.org/10.1101/081521
Ulrich G Mueller
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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  • For correspondence: umueller@austin.utexas.edu
Thomas E Juenger
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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Melissa R Kardish
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
2Center for Population Biology, University of California, Davis, CA, USA
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Alexis L Carlson
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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Kathleen Burns
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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Joseph A Edwards
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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Chad C Smith
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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Chi-Chun Fang
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
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David L Des Marais
1Department of Integrative Biology, University of Texas at Austin, 1 University Station #C0990, Austin TX 78712, USA
2Center for Population Biology, University of California, Davis, CA, USA
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Abstract

We develop a method to artificially select for rhizosphere microbiomes that confer salt-tolerance to the model grass Brachypodium distachyon. We differentially propagate microbiomes within the background of a non-evolving, highly-inbred plant population, and therefore only microbiomes evolve in our experiment, but not the plants. To optimize methods, we conceptualize artificial microbiome-selection as a special case of indirect selection: We do not measure microbiome properties directly, but we use host performance (e.g., biomass; seed set) as an indicator to infer association with rhizosphere microbiomes that confer salt-tolerance to a plant. We previously called this indirect-selection scheme host-mediated indirect selection on microbiomes (Mueller & Sachs 2015). Our methods aim to maximize evolutionary changes due to differential microbiome-propagation, while minimizing some (but not all) ecological processes affecting microbiome composition. Specifically, our methods aim to maximize microbiome perpetuation between selection-cycles and maximize response to artificial microbiome-selection by (a) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (b) using low-carbon soil to enhance host-control mediated by carbon secretions of plants during initial microbiome assembly and subsequent microbiome persistence; (c) fractionating microbiomes before transfer between plants to perpetuate and select only on bacterial and viral (but not fungal) microbiome components; and (d) ramping of salt-stress between selection-cycles to minimize the chance of over-stressing plants. Our selection protocol generates microbiomes that enhance plant fitness after only 1-3 rounds of artificial selection on rhizosphere microbiomes. Relative to fallow-soil control treatments, artificially-selected microbiomes increase plant fitness by 75% under sodium-sulfate stress, and by 38% under aluminum-sulfate stress. Relative to null control treatments, artificially-selected microbiomes increase plant fitness by 13% under sodium-sulfate stress, and by 12% under aluminum-sulfate stress. When testing microbiomes after nine rounds of differential microbiome propagation, the effect of bacterial microbiomes selected to confer tolerance to sodium-sulfate stress appears specific (these microbiomes do not confer tolerance to aluminum-sulfate stress), but the effect of microbiomes selected to confer tolerance to aluminum-sulfate stress appears non-specific (selected microbiomes ameliorate both sodium- and aluminum-sulfate stresses). Complementary metagenomic analyses of the artificially selected microbiomes will help elucidate metabolic properties of microbiomes that confer specific versus non-specific salt-tolerance to plants.

Footnotes

  • Many thanks to the bioRxiv community for constructive comments. We have expanded the Supplemental Information to describe some methods in greater detail. We revised the main text for greater clarification and updated references. We also tested whether it could be possible to use parametric tests after transforming the seed-weight data of Generation 9 (page 32 in Supplemental Information), but we found no transformation that would permit parametric tests (new Figure S5 on page 32), and we therefore present the non-parametric tests as already described in our original bioRxiv version.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 11, 2019.
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Artificial Microbiome-Selection to Engineer Microbiomes That Confer Salt-Tolerance to Plants
Ulrich G Mueller, Thomas E Juenger, Melissa R Kardish, Alexis L Carlson, Kathleen Burns, Joseph A Edwards, Chad C Smith, Chi-Chun Fang, David L Des Marais
bioRxiv 081521; doi: https://doi.org/10.1101/081521
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Artificial Microbiome-Selection to Engineer Microbiomes That Confer Salt-Tolerance to Plants
Ulrich G Mueller, Thomas E Juenger, Melissa R Kardish, Alexis L Carlson, Kathleen Burns, Joseph A Edwards, Chad C Smith, Chi-Chun Fang, David L Des Marais
bioRxiv 081521; doi: https://doi.org/10.1101/081521

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