CAREER: Investigating the molecular rules of legume partner selection

This project promotes the progress of science by addressing a fundamental challenge in agriculture: how do plants select beneficial soil bacteria that can replace the need for synthetic nitrogen-based fertilizers? Nitrogen fertilizers are costly to produce and using too much can hurt human health, creating an urgent need for sustainable alternatives. Legume crops such as soybean and alfalfa naturally partner with soil bacteria to obtain nitrogen, but the molecular rules governing how plants choose the most effective partners remain poorly understood. This project will address three key questions. First, it will identify the chemical signals that plants and bacteria use to communicate during the establishment of this symbiosis. Second, it will determine the plant genes required to respond to these signals, by using artificial intelligence to predict candidate receptors and specific residues involved in signal recognition. Third, we will uncover how plants select bacterial partners that maximize nitrogen acquisition. In parallel, this project also advances national prosperity and welfare by developing a highly skilled workforce in plant biotechnology. Undergraduate, graduate, and postdoctoral researchers will be trained through integrated research and classroom activities that provide hands-on experience in modern genetic and genomic approaches. This project will also support the development of a regional biotechnology network that seeks to connect trainees with industry professionals ultimately contributing to local economic development. This project aims to define the molecular rules that govern how legumes differentiate between and select symbiotic nitrogen-fixing bacterial partners. Maximizing biological nitrogen fixation in legume-rhizobia associations offers a sustainable strategy to reduce reliance on synthetic fertilizers. Although legumes form mutually beneficial relationships with rhizobia, the mechanisms by which host plants distinguish and preferentially select the most effective nitrogen-fixing strains remain poorly understood. This research addresses this gap using the model legume Medicago truncatula through three objectives. First, the project will identify plant-derived peptide signals from the PAMP INDUCED SECRETED PEPTIDES (PIP) family that regulate nodule formation and rhizobial partner selection. Transcriptomic analyses combined with CRISPR-generated mutants will be used to determine how these peptides integrate symbiosis and immune signaling pathways and influence microbial occupancy within nodules. Second, the project will define the structural basis of peptide-receptor specificity using machine learning-based protein structure prediction via AlphaFold, to model interactions between peptides and candidate leucine-rich repeat receptor kinases (LRR-RLKs). Functional validation using receptor variants will identify key residues that determine signal recognition and downstream physiological responses. Third, the project will quantify how plant receptors influence competition among rhizobial strains using a barcoded diversity panel of Sinorhizobium strains tagged with Plasmid ID barcodes. These strains will be evaluated in populations of Medicago lrr-rlk mutants to measure strain occupancy and nitrogen fixation efficiency in a high-throughput manner. This approach will reveal both plant and microbial genetic contributions to symbiotic partner selection. Together, these studies will establish principles for how legumes evaluate, and select microbial partners. This work will advance fundamental understanding of plant-microbe interactions and provide a foundation for improving biological nitrogen use in agriculture. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2544620 | Program: 01003031DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Sonali Roy | Institution: Tennessee State University, NASHVILLE, TN | Award Amount: $1,088,069 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2544620 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2544620.html