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.

Improved super-resolution ribosome profiling reveals prevalent translation of upstream ORFs and small ORFs in Arabidopsis.

A crucial step in functional genomics is identifying actively translated ORFs and linking them to biological functions. The challenge lies in identifying short ORFs, as their identification is greatly influenced by data quality and depth. Here, we improved the coverage of super-resolution Ribo-seq in Arabidopsis (Arabidopsis thaliana), revealing uncharacterized translation events for nuclear, chloroplastic, and mitochondrial genes. Assisted by a transcriptome assembly, we identified 7,751 unconventional translation events, comprising 6,996 upstream ORFs (uORFs) and 209 downstream ORFs on annotated protein-coding genes, as well as 546 ORFs in presumed noncoding RNAs. Proteomic data confirmed the production of stable proteins from some of these unannotated translation events. We present evidence of active translation from primary transcripts of trans-acting small interfering RNAs (TAS1-4) and microRNAs (pri-MIR163 and pri-MIR169) and periodic ribosome stalling supporting cotranslational decay. Additionally, we developed a method for identifying extremely short uORFs, including 370 minimum uORFs (AUG-stop), and 2,921 tiny uORFs (2 to 10 amino acids) and 681 uORFs that overlap with each other. Remarkably, these short uORFs exhibit strong translational repression as do longer uORFs. We also systematically discovered 594 uORFs regulated by alternative splicing, suggesting widespread isoform-specific translational control. Finally, these prevalent uORFs are associated with numerous important pathways. In summary, our improved Arabidopsis translational landscape provides valuable resources to study gene expression regulation.

Next-Generation Yeast Two-Hybrid Screening to Discover Protein-Protein Interactions.

Yeast two-hybrid is a powerful approach to discover new protein-protein interactions. Traditional methods involve screening a target protein against a cDNA expression library and assaying individual positive colonies to identify interacting partners. Here we describe a simple approach to perform yeast two-hybrid screens of a cDNA expression library in batch liquid culture. Positive yeast cell populations are enriched under selection and then harvested en masse. Prey cDNAs are amplified and used as input for next-generation sequencing libraries for identification, quantification, and ranking.

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.

The Fusarium graminearum Transporters Abc1 and Abc6 Are Important for Xenobiotic Resistance, Trichothecene Accumulation, and Virulence to Wheat.

The plant pathogenic fungus Fusarium graminearum is the causal agent of Fusarium head blight (FHB) disease on small-grain cereals. F. graminearum produces trichothecene mycotoxins such as deoxynivalenol (DON) that are required for full virulence. DON must be exported outside the cell to cause FHB disease, a process that may require the involvement of membrane-bound transporters. In this study, we show that the deletion of membrane-bound transporters results in reduced DON accumulation as well as reduced FHB symptoms on wheat. Deletion of the ATP-binding cassette (ABC) transporter gene Abc1 results in the greatest reduction in DON accumulation and virulence. Deletion of another ABC transporter gene, Abc6, also reduces FHB symptoms to a lesser degree. Combining deletions fails to reduce DON accumulation or virulence in an additive fashion, even when a ∆abc1 deletion is included. Heterologous expression of F. graminearum transporters in a DON-sensitive strain of yeast confirms Abc1 as a major DON resistance mechanism; furthermore, it suggests that Abc1 is directly participating in DON transport rather than facilitating DON transport though other means. Yeast expression further indicates that multiple transporters, including Abc1, play an important role in resistance to the wheat phytoalexin 2-benzoxazolinone (BOA) and other xenobiotics. Thus, Abc1 may contribute to virulence on wheat both by facilitating export of DON and by providing resistance to the wheat phytoalexin BOA. This research provides useful information that may aid in designing novel management techniques of FHB or other destructive plant diseases.

Integration of multi-omics data reveals interplay between brassinosteroid and Target of Rapamycin Complex signaling in Arabidopsis.

Brassinosteroids (BRs) and Target of Rapamycin Complex (TORC) are two major actors coordinating plant growth and stress responses. Brassinosteroids function through a signaling pathway to extensively regulate gene expression and TORC is known to regulate translation and autophagy. Recent studies have revealed connections between these two pathways, but a system-wide view of their interplay is still missing. We quantified the level of 23 975 transcripts, 11 183 proteins, and 27 887 phosphorylation sites in wild-type Arabidopsis thaliana and in mutants with altered levels of either BRASSINOSTEROID INSENSITIVE 2 (BIN2) or REGULATORY ASSOCIATED PROTEIN OF TOR 1B (RAPTOR1B), two key players in BR and TORC signaling, respectively. We found that perturbation of BIN2 or RAPTOR1B levels affects a common set of gene-products involved in growth and stress responses. Furthermore, we used the multi-omic data to reconstruct an integrated signaling network. We screened 41 candidate genes identified from the reconstructed network and found that loss of function mutants of many of these proteins led to an altered BR response and/or modulated autophagy activity. Altogether, these results establish a predictive network that defines different layers of molecular interactions between BR- or TORC-regulated growth and autophagy.

SGT1-Specific Domain Mutations Impair Interactions with the Barley MLA6 Immune Receptor in Association with Loss of NLR Protein.

The Mla (Mildew resistance locus a) of barley (Hordeum vulgare L.) is an effective model for cereal immunity against fungal pathogens. Like many resistance proteins, variants of the MLA coiled-coil nucleotide-binding leucine-rich repeat (CC-NLR) receptor often require the HRS complex (HSP90, RAR1, and SGT1) to function. However, functional analysis of Sgt1 has been particularly difficult, as deletions are often lethal. Recently, we identified rar3 (required for Mla6 resistance 3), an in-frame Sgt1ΔKL308-309 mutation in the SGT1-specific domain, that alters resistance conferred by MLA but without lethality. Here, we use autoactive MLA6 and recombinant yeast-two-hybrid strains with stably integrated HvRar1 and HvHsp90 to determine that this mutation weakens but does not entirely disrupt the interaction between SGT1 and MLA. This causes a concomitant reduction in MLA6 protein accumulation below the apparent threshold required for effective resistance. The ΔKL308-309 deletion had a lesser effect on intramolecular interactions than alanine or arginine substitutions, and MLA variants that display diminished interactions with SGT1 appear to be disproportionately affected by the SGT1ΔKL308-309 mutation. We hypothesize that those dimeric plant CC-NLRs that appear unaffected by Sgt1 silencing are those with the strongest intermolecular interactions with it. Combining our data with recent work in CC-NLRs, we propose a cyclical model of the MLA-HRS resistosome interactions.[Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor.

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

NGPINT: a next-generation protein-protein interaction software.

Mapping protein-protein interactions at a proteome scale is critical to understanding how cellular signaling networks respond to stimuli. Since eukaryotic genomes encode thousands of proteins, testing their interactions one-by-one is a challenging prospect. High-throughput yeast-two hybrid (Y2H) assays that employ next-generation sequencing to interrogate complementary DNA (cDNA) libraries represent an alternative approach that optimizes scale, cost and effort. We present NGPINT, a robust and scalable software to identify all putative interactors of a protein using Y2H in batch culture. NGPINT combines diverse tools to align sequence reads to target genomes, reconstruct prey fragments and compute gene enrichment under reporter selection. Central to this pipeline is the identification of fusion reads containing sequences derived from both the Y2H expression plasmid and the cDNA of interest. To reduce false positives, these fusion reads are evaluated as to whether the cDNA fragment forms an in-frame translational fusion with the Y2H transcription factor. NGPINT successfully recognized 95% of interactions in simulated test runs. As proof of concept, NGPINT was tested using published data sets and it recognized all validated interactions. NGPINT can process interaction data from any biosystem with an available genome or transcriptome reference, thus facilitating the discovery of protein-protein interactions in model and non-model organisms.

Advancements in the analysis of the Arabidopsis plasma membrane proteome.

The plasma membrane (PM) regulates diverse processes essential to plant growth, development, and survival in an ever-changing environment. In addition to maintaining normal cellular homeostasis and plant nutrient status, PM proteins perceive and respond to a myriad of environmental cues. Here we review recent advances in the analysis of the plant PM proteome with a focus on the model plant Arabidopsis thaliana. Due to membrane heterogeneity, hydrophobicity, and low relative abundance, analysis of the PM proteome has been a special challenge. Various experimental techniques to enrich PM proteins and different protein and peptide separation strategies have facilitated the identification of thousands of integral and membrane-associated proteins. Numerous classes of proteins are present at the PM with diverse biological functions. PM microdomains have attracted much attention. However, it still remains a challenge to characterize these cell membrane compartments. Dynamic changes in the PM proteome in response to different biotic and abiotic stimuli are highlighted. Future prospects for PM proteomics research are also discussed.