2022 ESA Annual Meeting (August 14 - 19)

COS 227-2 Directed plant-microbiome evolution to improve crop performance under drought

10:15 AM-10:30 AM
513B
Sanna Sevanto, Earth and Environmental Sciences Division, Los Alamos National Laboratory;Dea Musa,Los Alamos National Laboratory;Kelsey R. Carter, PhD,Los Alamos National Laboratory;Eric R. Moore, n/a,Los Alamos National Laboratory;Abigael Nachtsheim,Los Alamos National Laboratory;Anastasiia Kim,Los Alamos National Laboratory;Joshua Mitchell,Los Alamos National Laboratory;Jack Heneghan,Los Alamos National Laboratory;L. Turin Dickman,Los Alamos National Laboratory;Anthony Sabella,Los Alamos National Laboratory;Estella Gomez,Los Alamos National Laboratory;Eliana Rodriguez,Los Alamos National Laboratory;Sangeeta Negi,Los Alamos National Laboratory;George Perkins,Los Alamos National Laboratory;Rose Harris,Los Alamos National Laboratory;Oana Marina,Los Alamos National Laboratory;Brent Newman,Los Alamos National Laboratory;Jeffrey Heikoop,Los Alamos National Laboratory;Christine Anderson-Cook,Los Alamos National Laboratory;Nicholas Lubbers,Los Alamos National Laboratory;
Background/Question/Methods

Microbiome optimization could improve the performance of biological systems, from humans to plants and ecosystems. Yet, owing to challenges in finding and cultivating microbiomes that maintain their function in field conditions, use of microbes to improve plant productivity and crop stress tolerance has not become widespread despite years of trials. Based on the strong interactions and interdependency of rhizosphere microbes and plants, directed plant-microbiome evolution has been suggested as a means for developing microbiomes for these purposes. To test the feasibility of this method in developing microbial communities that improve plant performance under reduced irrigation, we cultivated Zea mays from seed in an artificial soil inoculated with soil microbiomes originating from a pine forest or a historically-droughted maize field. In the initial generation, water use efficiency (WUE) and stomatal closure point (SCP) were measured once the plants grew 10 leaves. The microbiomes of three plants demonstrating the best or worst WUE or SCP values for each microbiome source were selected for propagation to the next generation, and the process was repeated for two additional generations. Microbiome composition was analyzed after each generation using Illumina MiSeq sequencing, and microbial groups affecting plant performance were identified using Latent Dirichlet Allocation.

Results/Conclusions

Our results show that, in three generations, the microbiome originating from the forest soil was able to consistently influence plant SCP, while the microbiome from the agricultural field had no significant effect on either WUE or SCP. The forest and agricultural microbiomes remained distinct from one another throughout the evolutionary process, but the microbiomes adapted to the greenhouse experiment such that the parent and offspring microbiomes became progressively more similar in subsequent generations. Interestingly, we also found that the microbiome originating from forest soil consistently produced faster growing plants than the microbiome from the agricultural field. This microbiome contained more bacteria related to the nitrogen cycle than the agricultural microbiome, while the agricultural microbiome had a higher abundance of bacteria commonly found in dry soils. We were able to consistently identify consortia of bacteria related to different plant traits using a dimension reduction method called Latent Dirichlet Allocation (LDA). Our experiment demonstrates that, in only a few generations (3 as opposed to 6-10 in previous studies), directed evolution can produce soil microbiomes that influence important functional drought tolerance traits in maize, but not all soils may have the microbial diversity or species structure needed to optimize plant traits.