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

Abstract

The barley MLA nucleotide-binding, leucine-rich-repeat (NLR) receptor and its orthologs confer recognition specificity to many cereal diseases, including powdery mildew, stem and stripe rust, Victoria blight, and rice blast. We used interolog inference to construct a barley protein interactome (HvInt) comprising 66133 edges and 7181 nodes, as a foundation to explore signaling networks associated with MLA. HvInt was compared to the experimentally validated Arabidopsis interactome of 11253 proteins and 73960 interactions, verifying that the two networks share scale-free properties, including a power-law distribution and small-world network. Then, by successive layering of defense-specific ‘omics’ datasets, HvInt was customized to model cellular response to powdery mildew infection. Integration of HvInt with expression quantitative trait loci (eQTL) enabled us to infer disease modules and responses associated with fungal penetration and haustorial development. Next, using HvInt and an infection-time-course transcriptome, we assembled resistant (R) and susceptible (S) subnetworks. The resulting differentially co-expressed (R-S) interactome is essential to barley immunity, facilitates the flow of signaling pathways and is linked to Mla through trans eQTL associations. Lastly, next-generation, yeast-two-hybrid screens identified fifteen novel MLA interactors, which were incorporated into HvInt, to predict receptor localization, and signaling response. These results link genomic, transcriptomic, and physical interactions during MLA-specified immunity.AUTHOR SUMMARYPowdery mildew fungi infect more than 9,500 agronomic and horticultural plant species. In order to prevent economic loss due to diseases caused by pathogens, plant breeders incorporate resistance genes into varieties that are grown for food, feed, fuel and fiber. One of these resistance genes encodes the barley MLA immune receptor, an ancestral cereal protein that confers recognition to powdery mildew, stem and stripe rust, rice blast and Victoria blight. However, in order to function properly, these immune receptors must interact with additional proteins and protein complexes during the different stages of fungal infection and plant defense. We used a combination of computational- and laboratory-based methods to predict over 66,000 possible protein-protein interactions in barley. This network of proteins was then integrated with various defense-specific datasets to assemble the molecular building blocks associated with resistance to the powdery mildew pathogen, in addition to those proteins that interact with the MLA immune receptor. Our application of genome-scale, protein-protein interaction data provides a foundation to decipher the complex molecular components that control immune responses in crops.

Powdery mildew effectors AVRA1and BEC1016 target the ER J-domain proteinHvERdj3B required for immunity in barley

“…To identify host-pathogen PPI, three independent replications of batch Y2H-NGIS were performed according to Elmore et al (2023) and Velásquez-Zapata et al (2021, 2023a. The screens involved parallel histidine selection (for enrichment of yeast cells with bait and prey interactions) vs. non-selected controls (selection for bait and prey, but not their interactions).…”

“…Deep Illumina sequencing was performed across the GAL4 activation domain (AD) and into the prey protein coding sequences for all cultures. Two complementary software packages, designated NGPINT and Y2H-SCORES, were used to quantify the outcome of Y2H-NGIS (Banerjee et al, 2021;Velásquez-Zapata et al, 2021, 2023a. NGPINT facilitates the identification of GAL4 AD-prey inframe coding sequence fusion reads.…”

“…The Bh effectors AVRA1 and BEC1016 were used as baits in Y2H-NGIS to mine for novel PPI (Elmore et al, 2023;Velásquez-Zapata et al, 2023a). Bait sequences (w/o signal peptides) were fused with the GAL4 transcription factor binding domain (GAL4-BD) in the p97-BD, Leu2p vector and transformed into Saccharomyces cerevisiae strain Y8930 (Dreze et al, 2010).…”

“…Bait sequences (w/o signal peptides) were fused with the GAL4 transcription factor binding domain (GAL4-BD) in the p97-BD, Leu2p vector and transformed into Saccharomyces cerevisiae strain Y8930 (Dreze et al, 2010). For the prey library, first seedling leaves from an infection time course of the resistant barley line CI 16151 (Mla6) and four fast-neutron-derived immune mutants were sampled from a split-plot design at 0, 16, 20, 24, 32, and 48 hours after inoculation (HAI) with Bh isolate 5874 (AVRa1, AVRa3, AVRa6, AVRa12) (Chapman et al, 2021;Surana, 2017;Velásquez-Zapata et al, 2022). mRNA isolated from the 90 experimental units (5 genotypes × 6 time points × 3 biological replications) was used for RNA-Sequencing (data at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101304), small RNA sequencing (Hunt et al 2019), and was also pooled to prepare a three-frame cDNA prey library in the Gateway-compatible ARS4/CEN6 GAL4 activation domain (AD) vector, p86-AD, Trp1p (Dreze et al 2010;Velásquez-Zapata et al, 2021;Yu et al 2015).…”

“…These approaches facilitate a quantitative measure of which preys interact with each bait protein (Suter et al 2015) and identify reproducible p rotein- p rotein i nteractions (PPI) with 70-90% accuracy (Pashkova et al, 2016; Trigg et al, 2017; Weimann et al, 2013; Velásquez-Zapata et al, 2021). This then allows functional PPI to be positioned within interactome networks (Mukhtar et al, 2011; Weßling et al, 2014; Velásquez-Zapata et al, 2021; 2022).…”