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

Abstract

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.

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

“…Both AVR A1 and BEC1016 interact with barley J-domain protein, HvERdj3B To identify barley targets for AVR A1 and BEC1016, batch Y2H-NGIS was performed according to Velásquez-Zapata et al (2021). The screens involved parallel histidine selection vs. non-selection and bait specificity to enrich for yeast cells expressing interacting bait and prey proteins.…”

“…NGPINT facilitates the identification of GAL4 AD-prey in-frame coding sequence fusion reads. Then Y2H-SCORES uses count data to build a set of ranking scores to predict three properties expected from true interactors, i.e ., enrichment in selection vs. non-selection conditions, specificity to a bait screening, and in-frame selection of the prey (Velásquez-Zapata et al, 2021). Prey proteins that interact with the selected baits, as indicated by significant enrichment under selection, are reconstituted in silico with their mapped fusion reads to identify the complete prey sequence containing the PPI domain for further studies.…”

“…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).…”

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

“…We used yeast-two-hybrid, next-generation-interaction-screening (Y2H-NGIS) to identify interacting partners for the MLA6 resistance protein, split into three baits corresponding to the main domains of the NLR: amino acids 1-161 for the coil-coiled (CC) domain, amino acids 1-225 for CC and the nucleotide binding (NB) domain (CC+NB), and amino acids 550-976 for the leucine rich repeat (LRR) domain (Velásquez-Zapata et al, 2021). Using the recently developed NGPINT (Banerjee et al, 2021) and Y2H-SCORES (Velásquez-Zapata et al, 2021) software, we obtained a list of high-confidence interactors for each of the MLA6 fragments and validated them using binary Y2H (Dreze et al, 2010).…”

“…Three MLA6 fragments (MLA6 aa 1-161 for the CC domain, MLA6 aa 1-225 for CC and NB domains, and MLA6 aa 550-956 for the LRR domain) were tested as baits using Y2H-NGIS, and a three-frame cDNA prey library of 1.1 x 10 7 primary clones generated from the infection time course experiment (Hunt et al, 2019;Surana, 2017;Velásquez-Zapata et al, 2021). Y2H-NGIS data from these baits were analyzed using the NGPINT and Y2H-SCORES pipelines (Banerjee et al, 2021;Velásquez-Zapata et al, 2021). Using the Borda ensemble provided by Y2H-SCORES, we predicted a top list of candidate interactors to be validated.…”