A user-friendly platform for yeast two-hybrid library screening using next generation sequencing

Massively parallel measurement of protein-protein interactions by sequencing using MP3-seq

Protein-protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.

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.

Exploring the potential role of four Rhizophagus irregularis nuclear effectors: opportunities and technical limitations

Arbuscular mycorrhizal fungi (AMF) are obligate symbionts that interact with the roots of most land plants. The genome of the AMF model species Rhizophagus irregularis contains hundreds of predicted small effector proteins that are secreted extracellularly but also into the plant cells to suppress plant immunity and modify plant physiology to establish a niche for growth. Here, we investigated the role of four nuclear-localized putative effectors, i.e., GLOIN707, GLOIN781, GLOIN261, and RiSP749, in mycorrhization and plant growth. We initially intended to execute the functional studies in Solanum lycopersicum, a host plant of economic interest not previously used for AMF effector biology, but extended our studies to the model host Medicago truncatula as well as the non-host Arabidopsis thaliana because of the technical advantages of working with these models. Furthermore, for three effectors, the implementation of reverse genetic tools, yeast two-hybrid screening and whole-genome transcriptome analysis revealed potential host plant nuclear targets and the downstream triggered transcriptional responses. We identified and validated a host protein interactors participating in mycorrhization in the host.S. lycopersicum and demonstrated by transcriptomics the effectors possible involvement in different molecular processes, i.e., the regulation of DNA replication, methylglyoxal detoxification, and RNA splicing. We conclude that R. irregularis nuclear-localized effector proteins may act on different pathways to modulate symbiosis and plant physiology and discuss the pros and cons of the tools used.

Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

Determination of Key Components in the Bombyx mori p53 Apoptosis Regulation Network Using Y2H-Seq

The apoptosis pathway is highly conserved between invertebrates and mammals. Although genes encoding the classical apoptosis pathway can be found in the silkworm genome, the regulatory pathway and other apoptotic network genes have yet to be confirmed. Consequently, characterizing these genes and their underlying mechanisms could provide critical insights into the molecular basis of organ apoptosis and remodeling. A homolog of p53, a key apoptosis regulator in vertebrates, has been identified and cloned from Bombyx mori (Bmp53). This study confirmed via gene knockdown and overexpression that Bmp53 directly induces cell apoptosis and regulates the morphology and development of individuals during the metamorphosis stage. Furthermore, yeast two-hybrid sequencing (Y2H-Seq) identified several potential apoptotic regulatory interacting proteins, including the MDM2-like ubiquitination regulatory protein, which may represent an apoptosis factor unique to Bmp53 and which differs from that in other Lepidoptera. These results provide a theoretical basis for analyzing the various biological processes regulated by Bmp53 interaction groups and thus provide insight into the regulation of apoptosis in silkworms. The global interaction set identified in this study also provides a basic framework for future studies on apoptosis-dependent pupation in Lepidoptera.

From prediction to function: Current practices and challenges towards the functional characterization of type III effectors

The type III secretion system (T3SS) is a well-studied pathogenicity determinant of many bacteria through which effectors (T3Es) are translocated into the host cell, where they exercise a wide range of functions to deceive the host cell's immunity and to establish a niche. Here we look at the different approaches that are used to functionally characterize a T3E. Such approaches include host localization studies, virulence screenings, biochemical activity assays, and large-scale omics, such as transcriptomics, interactomics, and metabolomics, among others. By means of the phytopathogenic Ralstonia solanacearum species complex (RSSC) as a case study, the current advances of these methods will be explored, alongside the progress made in understanding effector biology. Data obtained by such complementary methods provide crucial information to comprehend the entire function of the effectome and will eventually lead to a better understanding of the phytopathogen, opening opportunities to tackle it.

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.

Cataloguing Protein Complexes In Planta Using TurboID-Catalyzed Proximity Labeling

Mapping protein-protein interactions is crucial to understand protein function. Recent advances in proximity-dependent biotinylation (BioID) coupled to mass spectrometry (MS) allow the characterization of protein complexes in diverse plant models. Here, we describe the use of BioID in hairy root cultures of tomato and provide detailed information on how to analyze the data obtained by MS.

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.

Fine Mapping of a Vigor QTL in Chickpea (Cicer arietinum L.) Reveals a Potential Role for Ca4_TIFY4B in Regulating Leaf and Seed Size

Plant vigor is a complex trait for which the underlying molecular control mechanisms remain unclear. Vigorous plants tend to derive from larger seeds and have greater early canopy cover, often with bigger leaves. In this study, we delimited the size of a major vigor quantitative trait locus (QTL) on chickpea chromosome 4-104.4 kb, using recombinant association analysis in 15 different heterogeneous inbred families, derived from a Rupali/Genesis836 recombinant inbred line population. The phenotypic and molecular genetic analysis provided evidence for a role of the gene Ca4_TIFY4B, in determining leaf and seed size in chickpea. A non-synonymous single-nucleotide polymorphism (SNP) in the high-vigor parent was located inside the core motif TIFYCG, resulting in a residue change T[I/S]FYCG. Complexes formed by orthologs of Ca4_TIFY4B (PEAPOD in Arabidopsis), Novel Interactor of JAZ (CaNINJA), and other protein partners are reported to act as repressors regulating the transcription of downstream genes that control plant organ size. When tested in a yeast 2-hybrid (Y2H) assay, this residue change suppressed the interaction between Ca4_TIFY4B and CaNINJA. This is the first report of a naturally occurring variant of the TIFY family in plants. A robust gene-derived molecular marker is available for selection in chickpea for seed and plant organ size, i.e., key component traits of vigor.

Unraveling Protein Interactions between the Temperate Virus Bam35 and Its Bacillus Host Using an Integrative Yeast Two Hybrid-High Throughput Sequencing Approach

Bacillus virus Bam35 is the model Betatectivirus and member of the family Tectiviridae, which is composed of tailless, icosahedral, and membrane-containing bacteriophages. Interest in these viruses has greatly increased in recent years as they are thought to be an evolutionary link between diverse groups of prokaryotic and eukaryotic viruses. Additionally, betatectiviruses infect bacteria of the Bacillus cereus group, which are known for their applications in industry and notorious since it contains many pathogens. Here, we present the first protein–protein interactions (PPIs) network for a tectivirus–host system by studying the Bam35–Bacillus thuringiensis model using a novel approach that integrates the traditional yeast two-hybrid system and high-throughput sequencing (Y2H-HTS). We generated and thoroughly analyzed a genomic library of Bam35′s host B. thuringiensis HER1410 and screened interactions with all the viral proteins using different combinations of bait–prey couples. Initial analysis of the raw data enabled the identification of over 4000 candidate interactions, which were sequentially filtered to produce 182 high-confidence interactions that were defined as part of the core virus–host interactome. Overall, host metabolism proteins and peptidases were particularly enriched within the detected interactions, distinguishing this host–phage system from the other reported host–phage PPIs. Our approach also suggested biological roles for several Bam35 proteins of unknown function, including the membrane structural protein P25, which may be a viral hub with a role in host membrane modification during viral particle morphogenesis. This work resulted in a better understanding of the Bam35–B. thuringiensis interaction at the molecular level and holds great potential for the generalization of the Y2H-HTS approach for other virus–host models.

Transcription Factors Interact with ABA through Gene Expression and Signaling Pathways to Mitigate Drought and Salinity Stress

Among abiotic stressors, drought and salinity seriously affect crop growth worldwide. In plants, research has aimed to increase stress-responsive protein synthesis upstream or downstream of the various transcription factors (TFs) that alleviate drought and salinity stress. TFs play diverse roles in controlling gene expression in plants, which is necessary to regulate biological processes, such as development and environmental stress responses. In general, plant responses to different stress conditions may be either abscisic acid (ABA)-dependent or ABA-independent. A detailed understanding of how TF pathways and ABA interact to cause stress responses is essential to improve tolerance to drought and salinity stress. Despite previous progress, more active approaches based on TFs are the current focus. Therefore, the present review emphasizes the recent advancements in complex cascades of gene expression during drought and salinity responses, especially identifying the specificity and crosstalk in ABA-dependent and -independent signaling pathways. This review also highlights the transcriptional regulation of gene expression governed by various key TF pathways, including AP2/ERF, bHLH, bZIP, DREB, GATA, HD-Zip, Homeo-box, MADS-box, MYB, NAC, Tri-helix, WHIRLY, WOX, WRKY, YABBY, and zinc finger, operating in ABA-dependent and -independent signaling pathways.

Pathogen Effectors: Exploiting the Promiscuity of Plant Signaling Hubs

Pathogens produce effectors to overcome plant immunity, thereby threatening crop yields and global food security. Large-scale interactomic studies have revealed that pathogens from different kingdoms of life target common plant proteins during infection, the so-called effector hubs. These hubs often play central roles in numerous plant processes through their ability to interact with multiple plant proteins. This ability arises partly from the presence of intrinsically disordered domains (IDDs) in their structure. Here, we highlight the role of the TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) and JASMONATE-ZIM DOMAIN (JAZ) transcription regulator families as plant signaling and effector hubs. We consider different evolutionary hypotheses to rationalize the existence of diverse effectors sharing common targets and the possible role of IDDs in this interaction.

Labour-saving construction of a target protein interaction network by selective culture and high-throughput sequencing

Yeast two-hybrid (Y2H) is a classic method of screening for protein-protein interactions. However, the operation process is labor intensive and time consuming, and there is a high possibility of false positives and false negatives. Combined with wet lab operation and bioinformatics analysis, we developed a novel method of Y2H library screening using Chrysanthemum morifolium CmMPK3 as an example. The protocol can not only greatly simplify the steps of traditional Y2H library screening but also identify as many interacting proteins as possible. Furthermore, this protocol is applicable to any species, even if no genomic information is available yet.

Advances and perspectives in discovery and functional analysis of small secreted proteins in plants

Small secreted proteins (SSPs) are less than 250 amino acids in length and are actively transported out of cells through conventional protein secretion pathways or unconventional protein secretion pathways. In plants, SSPs have been found to play important roles in various processes, including plant growth and development, plant response to abiotic and biotic stresses, and beneficial plant-microbe interactions. Over the past 10 years, substantial progress has been made in the identification and functional characterization of SSPs in several plant species relevant to agriculture, bioenergy, and horticulture. Yet, there are potentially a lot of SSPs that have not been discovered in plant genomes, which is largely due to limitations of existing computational algorithms. Recent advances in genomics, transcriptomics, and proteomics research, as well as the development of new computational algorithms based on machine learning, provide unprecedented capabilities for genome-wide discovery of novel SSPs in plants. In this review, we summarize known SSPs and their functions in various plant species. Then we provide an update on the computational and experimental approaches that can be used to discover new SSPs. Finally, we discuss strategies for elucidating the biological functions of SSPs in plants.

Visualizing protein-protein interactions in plants by rapamycin-dependent delocalization

Identifying protein-protein interactions (PPIs) is crucial for understanding biological processes. Many PPI tools are available, yet only some function within the context of a plant cell. Narrowing down even further, only a few tools allow complex multi-protein interactions to be visualized. Here, we present a conditional in vivo PPI tool for plant research that meets these criteria. Knocksideways in plants (KSP) is based on the ability of rapamycin to alter the localization of a bait protein and its interactors via the heterodimerization of FKBP and FRB domains. KSP is inherently free from many limitations of other PPI systems. This in vivo tool does not require spatial proximity of the bait and prey fluorophores and it is compatible with a broad range of fluorophores. KSP is also a conditional tool and therefore the visualization of the proteins in the absence of rapamycin acts as an internal control. We used KSP to confirm previously identified interactions in Nicotiana benthamiana leaf epidermal cells. Furthermore, the scripts that we generated allow the interactions to be quantified at high throughput. Finally, we demonstrate that KSP can easily be used to visualize complex multi-protein interactions. KSP is therefore a versatile tool with unique characteristics and applications that complements other plant PPI methods.

High-throughput insertional mutagenesis reveals novel targets for enhancing lipid accumulation in Nannochloropsis oceanica

The microalga Nannochloropsis oceanica is considered a promising platform for the sustainable production of high-value lipids and biofuel feedstocks. However, current lipid yields of N. oceanica are too low for economic feasibility. Gaining fundamental insights into the lipid metabolism of N. oceanica could open up various possibilities for the optimization of this species through genetic engineering. Therefore, the aim of this study was to discover novel genes associated with an elevated neutral lipid content. We constructed an insertional mutagenesis library of N. oceanica, selected high lipid mutants by five rounds of fluorescence-activated cell sorting, and identified disrupted genes using a novel implementation of a rapid genotyping procedure. One particularly promising mutant (HLM23) was disrupted in a putative APETALA2-like transcription factor gene. HLM23 showed a 40%-increased neutral lipid content, increased photosynthetic performance, and no growth impairment. Furthermore, transcriptome analysis revealed an upregulation of genes related to plastidial fatty acid biosynthesis, glycolysis and the Calvin-Benson-Bassham cycle in HLM23. Insights gained in this work can be used in future genetic engineering strategies for increased lipid productivity of Nannochloropsis.

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.

DoMY-Seq: A yeast two-hybrid-based technique for precision mapping of protein-protein interaction motifs

Interactions between proteins are fundamental for every biological process and especially important in cell signaling pathways. Biochemical techniques that evaluate these protein-protein interactions (PPIs), such as in vitro pull downs and coimmunoprecipitations, have become popular in most laboratories and are essential to identify and validate novel protein binding partners. Most PPIs occur through small domains or motifs, which are challenging and laborious to map by using standard biochemical approaches because they generally require the cloning of several truncation mutants. Moreover, these classical methodologies provide limited resolution of the interacting interface. Here, we describe the development of an alternative technique to overcome these limitations termed "Protein Domain mapping using Yeast 2 Hybrid-Next Generation Sequencing" (DoMY-Seq), which leverages both yeast two-hybrid and next-generation sequencing techniques. In brief, our approach involves creating a library of fragments derived from an open reading frame of interest and enriching for the interacting fragments using a yeast two-hybrid reporter system. Next-generation sequencing is then subsequently employed to read and map the sequence of the interacting fragment, yielding a high-resolution plot of the binding interface. We optimized DoMY-Seq by taking advantage of the well-described and high-affinity interaction between KRAS and CRAF, and we provide high-resolution domain mapping on this and other protein-interacting pairs, including CRAF-MEK1, RIT1-RGL3, and p53-MDM2. Thus, DoMY-Seq provides an unbiased alternative method to rapidly identify the domains involved in PPIs by advancing the use of yeast two-hybrid technology.

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.

Keeping in Touch with Type-III Secretion System Effectors: Mass Spectrometry-Based Proteomics to Study Effector-Host Protein-Protein Interactions

Manipulation of host cellular processes by translocated bacterial effectors is key to the success of bacterial pathogens and some symbionts. Therefore, a comprehensive understanding of effectors is of critical importance to understand infection biology. It has become increasingly clear that the identification of host protein targets contributes invaluable knowledge to the characterization of effector function during pathogenesis. Recent advances in mapping protein-protein interaction networks by means of mass spectrometry-based interactomics have enabled the identification of host targets at large-scale. In this review, we highlight mass spectrometry-driven proteomics strategies and recent advances to elucidate type-III secretion system effector-host protein-protein interactions. Furthermore, we highlight approaches for defining spatial and temporal effector-host interactions, and discuss possible avenues for studying natively delivered effectors in the context of infection. Overall, the knowledge gained when unravelling effector complexation with host factors will provide novel opportunities to control infectious disease outcomes.

A Novel Germline MLH1 In-Frame Deletion in a Slovenian Lynch Syndrome Family Associated with Uncommon Isolated PMS2 Loss in Tumor Tissue

The diagnostics of Lynch syndrome (LS) is focused on the detection of DNA mismatch repair (MMR) system deficiency. MMR deficiency can be detected on tumor tissue by microsatellite instability (MSI) using molecular genetic test or by loss of expression of one of the four proteins (MLH1, MSH2, MSH6, and PMS2) involved in the MMR system using immunohistochemistry (IHC) staining. According to the National Comprehensive Cancer Network (NCCN) guidelines, definitive diagnosis of LS requires the identification of the germline pathogenic variant in one of the MMR genes. In the report, we are presenting interesting novel MLH1 in-frame deletion LRG_216t1:c.2236_2247delCTGCCTGATCTA p.(Leu746_Leu749del) associated with LS. The variant appears to be associated with uncommon isolated loss of PMS2 immunohistochemistry protein staining (expression) in tumor tissue instead of MLH1 and PMS2 protein loss, which is commonly seen with pathogenic variants in MLH1. The variant was classified as likely pathogenic, based on segregation analysis and molecular characterization of blood and tumor samples. According to the American College of Medical Genetics (ACMG) guidelines, the following evidence categories of PM1, PM2, PM4, and PP1 moderate have been used for classification of the novel variant. By detecting and classifying the novel MLH1 variant as likely pathogenic, we confirmed the LS in this family.

A Phage-Assisted Continuous Selection Approach for Deep Mutational Scanning of Protein-Protein Interactions

Protein-protein interactions (PPIs) are critical for organizing molecules in a cell and mediating signaling pathways. Dysregulation of PPIs is often a key driver of disease. To better understand the biophysical basis of such disease processes-and to potentially target them-it is critical to understand the molecular determinants of PPIs. Deep mutational scanning (DMS) facilitates the acquisition of large amounts of biochemical data by coupling selection with high throughput sequencing (HTS). The challenging and labor-intensive design and optimization of a relevant selection platform for DMS, however, limits the use of powerful directed evolution and selection approaches. To address this limitation, we designed a versatile new phage-assisted continuous selection (PACS) system using our previously reported proximity-dependent split RNA polymerase (RNAP) biosensors, with the aim of greatly simplifying and streamlining the design of a new selection platform for PPIs. After characterization and validation using the model KRAS/RAF PPI, we generated a library of RAF variants and subjected them to PACS and DMS. Our HTS data revealed positions along the binding interface that are both tolerant and intolerant to mutations, as well as which substitutions are tolerated at each position. Critically, the "functional scores" obtained from enrichment data through continuous selection for individual variants correlated with K_D values measured in vitro, indicating that biochemical data can be extrapolated from sequencing using our new system. Due to the plug and play nature of RNAP biosensors, this method can likely be extended to a variety of other PPIs. More broadly, this, and other methods under development support the continued development of evolutionary and high-throughput approaches to address biochemical problems, moving toward a more comprehensive understanding of sequence-function relationships in proteins.

SH3Ps-Evolution and Diversity of a Family of Proteins Engaged in Plant Cytokinesis

SH3P2 (At4g34660), an Arabidopsis thaliana SH3 and Bin/amphiphysin/Rvs (BAR) domain-containing protein, was reported to have a specific role in cell plate assembly, unlike its paralogs SH3P1 (At1g31440) and SH3P3 (At4g18060). SH3P family members were also predicted to interact with formins—evolutionarily conserved actin nucleators that participate in microtubule organization and in membrane–cytoskeleton interactions. To trace the origin of functional specialization of plant SH3Ps, we performed phylogenetic analysis of SH3P sequences from selected plant lineages. SH3Ps are present in charophytes, liverworts, mosses, lycophytes, gymnosperms, and angiosperms, but not in volvocal algae, suggesting association of these proteins with phragmoplast-, but not phycoplast-based cell division. Separation of three SH3P clades, represented by SH3P1, SH3P2, and SH3P3 of A. thaliana, appears to be a seed plant synapomorphy. In the yeast two hybrid system, Arabidopsis SH3P3, but not SH3P2, binds the FH1 and FH2 domains of the formin FH5 (At5g54650), known to participate in cytokinesis, while an opposite binding specificity was found for the dynamin homolog DRP1A (At5g42080), confirming earlier findings. This suggests that the cytokinetic role of SH3P2 is not due to its interaction with FH5. Possible determinants of interaction specificity of SH3P2 and SH3P3 were identified bioinformatically.