An interolog-based barley interactome as an integration framework for immune signaling

Powdery mildew effectors AVRA1 and BEC1016 target the ER J-domain protein HvERdj3B required for immunity in barley

The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide-binding leucine-rich-repeat (NLR) receptor MLA1 and therefore is designated AVRA1. Here, we show that AVRA1 and the sequence-unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two-hybrid next-generation interaction screens (Y2H-NGIS), followed by binary Y2H and in planta protein-protein interactions studies, and identified a common barley target of AVRA1 and BEC1016, the endoplasmic reticulum (ER)-localized J-domain protein HvERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. HvERdj3B is ER luminal, and we showed using split GFP that AVRA1 and BEC1016 translocate into the ER signal peptide-independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of HvERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J-domain protein HvERdj3B appears to be essential and can be regulated by AVRA1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVRA1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVRA1 J-domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

Bioinformatic Analysis of Yeast Two-Hybrid Next-Generation Interaction Screen Data

Yeast two-hybrid next-generation interaction screening (Y2H-NGIS) uses the output of next-generation sequencing to mine for novel protein-protein interactions. Here, we outline the analytics underlying Y2H-NGIS datasets. Different systems, libraries, and experimental designs comprise Y2H-NGIS methodologies. We summarize the analysis in several layers that comprise the characterization of baits and preys, quantification, and identification of true interactions for subsequent secondary validation. We present two software designed for this purpose, NGPINT and Y2H-SCORES, which are used as front-end and back-end tools in the analysis. Y2H-SCORES software can be used and adapted to analyze different datasets not only from Y2H-NGIS but from other techniques ruled by similar biological principles.