Evolutionary dynamics of proteinaceous MAMPs reveals intrabacterial antagonism of plant immune perception

Abstract

Plants and animals detect biomolecules termed Microbe-Associated Molecular Patterns (MAMPs) and induce immunity. Agricultural production is severely impacted by pathogens which can be controlled by transferring immune receptors. However, most studies use a single MAMP epitope and the impact of diverse multi-copy MAMPs on immune induction is unknown. Here we characterized the epitope landscape from five proteinaceous MAMPs across 4,228 plant-associated bacterial genomes. Despite the diversity sampled, natural variation was constrained and experimentally testable. Immune perception in both Arabidopsis and tomato depended on both epitope sequence and copy number variation. For example, Elongation Factor Tu is predominantly single copy and 92% of its epitopes are immunogenic. Conversely, 99.9% of bacterial genomes contain multiple Cold Shock Proteins and 46% carry a non-immunogenic form. We uncovered a new mechanism for immune evasion, intrabacterial antagonism, where a non-immunogenic Cold Shock Protein blocks perception of immunogenic forms encoded in the same genome. These data will lay the foundation for immune receptor deployment and engineering based on natural variation. Significance StatementPlants recognize pathogens as non-self using innate immune receptors. Receptors on the cell surface can recognize amino acid epitopes present in pathogen proteins. Despite many papers investigating receptor signaling, the vast majority use a single epitope. Here, we analyzed the natural variation across five different epitopes and experimentally characterized their perception in plants. We highlight the importance of analyzing all epitope copies within a pathogen genome. Through genetic and biochemical analyses, we revealed a mechanism for immune evasion, intrabacterial antagonism, where a non-immunogenic epitope blocks perception of immunogenic forms encoded in a single genome. These data can directly inform disease control strategies by enabling prediction of receptor utility and deployment for current and emerging pathogens.