The TSC22D, WNK, and NRBP gene families exhibit functional buffering and evolved with Metazoa for cell volume regulation.

The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. We used gene co-essentiality analysis to identify an unappreciated relationship between TSC22D2, WNK1, and NRBP1 in regulating cell volume homeostasis. All of these genes have paralogs and are functionally buffered for osmo-sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK, and NRBP family members physically associate into biomolecular condensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans revealed that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is accompanied by rapid IDR length expansion in WNK-family kinases. Our study reveals that TSC22D, WNK, and NRBP genes evolved in metazoans to co-regulate rapid cell volume changes in response to osmolarity.

High-resolution electron cryomicroscopy of V-ATPase in native synaptic vesicles.

Intercellular communication in the nervous system occurs through the release of neurotransmitters into the synaptic cleft between neurons. In the presynaptic neuron, the proton pumping vesicular- or vacuolar-type ATPase (V-ATPase) powers neurotransmitter loading into synaptic vesicles (SVs), with the V1 complex dissociating from the membrane region of the enzyme before exocytosis. We isolated SVs from rat brain using SidK, a V-ATPase-binding bacterial effector protein. Single-particle electron cryomicroscopy allowed high-resolution structure determination of V-ATPase within the native SV membrane. In the structure, regularly spaced cholesterol molecules decorate the enzyme's rotor and the abundant SV protein synaptophysin binds the complex stoichiometrically. ATP hydrolysis during vesicle loading results in a loss of the V1 region of V-ATPase from the SV membrane, suggesting that loading is sufficient to induce dissociation of the enzyme.

Exploring Options for Proximity-Dependent Biotinylation Experiments: Comparative Analysis of Labeling Enzymes and Affinity Purification Resins.

Proximity-dependent biotinylation (PDB) techniques provide information about the molecular neighborhood of a protein of interest, yielding insights into its function and localization. Here, we assessed how different labeling enzymes and streptavidin resins influence PDB results. We compared the high-confidence interactors of the DNA/RNA-binding protein transactive response DNA-binding protein 43 kDa (TDP-43) identified using either miniTurbo (biotin ligase) or APEX2 (peroxidase) enzymes. We also evaluated two commercial affinity resins for purification of biotinylated proteins: conventional streptavidin sepharose versus a new trypsin-resistant streptavidin conjugated to magnetic resin, which significantly reduces the level of contamination by streptavidin peptides following on-bead trypsin digestion. Downstream analyses involved liquid chromatography coupled to mass spectrometry in data-dependent acquisition mode, database searching, and statistical analysis of high-confidence interactors using SAINTexpress. The APEX2-TDP-43 experiment identified more interactors than miniTurbo-TDP-43, although miniTurbo provided greater overlap with previously documented TDP-43 interactors. Purifications on sepharose resin yielded more interactors than magnetic resin in small-scale experiments using a range of magnetic resin volumes. We suggest that resin-specific background protein binding profiles and different lysate-to-resin ratios cumulatively affect the distributions of prey protein abundance in experimental and control samples, which impact statistical confidence scores. Overall, we highlight key experimental variables to consider for the empirical optimization of PDB experiments.

A New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules.

Stress granules (SGs) are cytosolic biomolecular condensates that form in response to cellular stress. Weak, multivalent interactions between their protein and RNA constituents drive their rapid, dynamic assembly through phase separation coupled to percolation. Though a consensus model of SG function has yet to be determined, their perceived implication in cytoprotective processes (e.g., antiviral responses and inhibition of apoptosis) and possible role in the pathogenesis of various neurodegenerative diseases (e.g., amyotrophic lateral sclerosis and frontotemporal dementia) have drawn great interest. Consequently, new studies using numerous cell biological, genetic, and proteomic methods have been performed to unravel the mechanisms underlying SG formation, organization, and function and, with them, a more clearly defined SG proteome. Here, we provide a consensus SG proteome through literature curation and an update of the user-friendly database RNAgranuleDB to version 2.0 (http://rnagranuledb.lunenfeld.ca/). With this updated SG proteome, we use next-generation phase separation prediction tools to assess the predisposition of SG proteins for phase separation and aggregation. Next, we analyze the primary sequence features of intrinsically disordered regions (IDRs) within SG-resident proteins. Finally, we review the protein- and RNA-level determinants, including post-translational modifications (PTMs), that regulate SG composition and assembly/disassembly dynamics.

Mapping Protein-Protein Interactions Using Data-Dependent Acquisition without Dynamic Exclusion.

Systematic analysis of affinity-purified samples by liquid chromatography coupled to mass spectrometry (LC-MS) requires high coverage, reproducibility, and sensitivity. While data-independent acquisition (DIA) approaches improve the reproducibility of protein-protein interaction detection as compared to standard data-dependent acquisition approaches, the need for library generation reduces their throughput, and analysis pipelines are still being optimized. In this study, we report the development of a simple and robust approach, termed turboDDA, to improve interactome analysis using spectral counting and data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step and optimizing the acquisition parameters. Using representative interaction and proximity proteomics samples, we detected increases in identified interactors of 18-71% compared to all samples analyzed by standard DDA with dynamic exclusion and for most samples analyzed by DIA with the MSPLIT-DIA spectral counting approach. In summary, turboDDA provides better sensitivity and identifies more high-confident interactors than the optimized DDA with DE and comparable or better sensitivity than DIA spectral counting approaches.

A proximity-dependent biotinylation map of a human cell.

Compartmentalization is a defining characteristic of eukaryotic cells, and partitions distinct biochemical processes into discrete subcellular locations. Microscopy1 and biochemical fractionation coupled with mass spectrometry2-4 have defined the proteomes of a variety of different organelles, but many intracellular compartments have remained refractory to such approaches. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach to define the composition of cellular compartments in living cells5-7. Here we present a BioID-based map of a human cell on the basis of 192 subcellular markers, and define the intracellular locations of 4,145 unique proteins in HEK293 cells. Our localization predictions exceed the specificity of previous approaches, and enabled the discovery of proteins at the interface between the mitochondrial outer membrane and the endoplasmic reticulum that are crucial for mitochondrial homeostasis. On the basis of this dataset, we created humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to understand BioID results better.

Properties of Stress Granule and P-Body Proteomes.

Stress granules and P-bodies are cytosolic biomolecular condensates that dynamically form by the phase separation of RNAs and proteins. They participate in translational control and buffer the proteome. Upon stress, global translation halts and mRNAs bound to the translational machinery and other proteins coalesce to form stress granules (SGs). Similarly, translationally stalled mRNAs devoid of translation initiation factors shuttle to P-bodies (PBs). Here, we review the cumulative progress made in defining the protein components that associate with mammalian SGs and PBs. We discuss the composition of SG and PB proteomes, supported by a new user-friendly database (http://rnagranuledb.lunenfeld.ca/) that curates current literature evidence for genes or proteins associated with SGs or PBs. As previously observed, the SG and PB proteomes are biased toward intrinsically disordered regions and have a high propensity to contain primary sequence features favoring phase separation. We also provide an outlook on how the various components of SGs and PBs may cooperate to organize and form membraneless organelles.

Identifying Pseudomonas syringae Type III Secreted Effector Function via a Yeast Genomic Screen.

Gram-negative bacterial pathogens inject type III secreted effectors (T3SEs) directly into host cells to promote pathogen fitness by manipulating host cellular processes. Despite their crucial role in promoting virulence, relatively few T3SEs have well-characterized enzymatic activities or host targets. This is in part due to functional redundancy within pathogen T3SE repertoires as well as the promiscuity of individual T3SEs that can have multiple host targets. To overcome these challenges, we generated and characterized a collection of yeast strains stably expressing 75 T3SE constructs from the plant pathogen Pseudomonas syringae This collection is devised to facilitate heterologous genetic screens in yeast, a non-host organism, to identify T3SEs that target conserved eukaryotic processes. Among 75 T3SEs tested, we identified 16 that inhibited yeast growth on rich media and eight that inhibited growth on stress-inducing media. We utilized Pathogenic Genetic Array (PGA) screens to identify potential host targets of P. syringae T3SEs. We focused on the acetyltransferase, HopZ1a, which interacts with plant tubulin and alters microtubule networks. To uncover putative HopZ1a host targets, we identified yeast genes with genetic interaction profiles most similar (i.e., congruent) to the PGA profile of HopZ1a and performed a functional enrichment analysis of these HopZ1a-congruent genes. We compared the congruence analyses above to previously described HopZ physical interaction datasets and identified kinesins as potential HopZ1a targets. Finally, we demonstrated that HopZ1a can target kinesins by acetylating the plant kinesins HINKEL and MKRP1, illustrating the utility of our T3SE-expressing yeast library to characterize T3SE functions.

Human MARF1 is an endoribonuclease that interacts with the DCP1:2 decapping complex and degrades target mRNAs.

Meiosis arrest female 1 (MARF1) is a cytoplasmic RNA binding protein that is essential for meiotic progression of mouse oocytes, in part by limiting retrotransposon expression. MARF1 is also expressed in somatic cells and tissues; however, its mechanism of action has yet to be investigated. Human MARF1 contains a NYN-like domain, two RRMs and eight LOTUS domains. Here we provide evidence that MARF1 post-transcriptionally silences targeted mRNAs. MARF1 physically interacts with the DCP1:DCP2 mRNA decapping complex but not with deadenylation machineries. Importantly, we provide a 1.7 Å resolution crystal structure of the human MARF1 NYN domain, which we demonstrate is a bona fide endoribonuclease, the activity of which is essential for the repression of MARF1-targeted mRNAs. Thus, MARF1 post-transcriptionally represses gene expression by serving as both an endoribonuclease and as a platform that recruits the DCP1:DCP2 decapping complex to targeted mRNAs.

In planta proximity dependent biotin identification (BioID).

Proximity dependent biotin identification (BioID) has emerged as a powerful tool for studies of proteome architecture, including insoluble or membrane-associated proteins. The technique has been well established in mammalian cells but has yet to be applied to whole plant systems. Here we demonstrate the application of BioID on leaf tissues of the model plant Arabidopsis thaliana, thereby expanding the versatility of this important technique and providing a powerful proteomics tool for plant biologists.

Molecular architecture of LSM14 interactions involved in the assembly of mRNA silencing complexes.

The LSM domain-containing protein LSM14/Rap55 plays a role in mRNA decapping, translational repression, and RNA granule (P-body) assembly. How LSM14 interacts with the mRNA silencing machinery, including the eIF4E-binding protein 4E-T and the DEAD-box helicase DDX6, is poorly understood. Here we report the crystal structure of the LSM domain of LSM14 bound to a highly conserved C-terminal fragment of 4E-T. The 4E-T C-terminus forms a bi-partite motif that wraps around the N-terminal LSM domain of LSM14. We also determined the crystal structure of LSM14 bound to the C-terminal RecA-like domain of DDX6. LSM14 binds DDX6 via a unique non-contiguous motif with distinct directionality as compared to other DDX6-interacting proteins. Together with mutational and proteomic studies, the LSM14-DDX6 structure reveals that LSM14 has adopted a divergent mode of binding DDX6 in order to support the formation of mRNA silencing complexes and P-body assembly.

High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.

mRNA processing, transport, translation, and ultimately degradation involve a series of dedicated protein complexes that often assemble into large membraneless structures such as stress granules (SGs) and processing bodies (PBs). Here, systematic in vivo proximity-dependent biotinylation (BioID) analysis of 119 human proteins associated with different aspects of mRNA biology uncovers 7424 unique proximity interactions with 1,792 proteins. Classical bait-prey analysis reveals connections of hundreds of proteins to distinct mRNA-associated processes or complexes, including the splicing and transcriptional elongation machineries (protein phosphatase 4) and the CCR4-NOT deadenylase complex (CEP85, RNF219, and KIAA0355). Analysis of correlated patterns between endogenous preys uncovers the spatial organization of RNA regulatory structures and enables the definition of 144 core components of SGs and PBs. We report preexisting contacts between most core SG proteins under normal growth conditions and demonstrate that several core SG proteins (UBAP2L, CSDE1, and PRRC2C) are critical for the formation of microscopically visible SGs.

C. elegans SUP-46, an HNRNPM family RNA-binding protein that prevents paternally-mediated epigenetic sterility.

BACKGROUND: In addition to DNA, gametes contribute epigenetic information in the form of histones and non-coding RNA. Epigenetic programs often respond to stressful environmental conditions and provide a heritable history of ancestral stress that allows for adaptation and propagation of the species. In the nematode C. elegans, defective epigenetic transmission often manifests as progressive germline mortality. We previously isolated sup-46 in a screen for suppressors of the hexosamine pathway gene mutant, gna-2(qa705). In this study, we examine the role of SUP-46 in stress resistance and progressive germline mortality. RESULTS: We identified SUP-46 as an HNRNPM family RNA-binding protein, and uncovered a highly novel role for SUP-46 in preventing paternally-mediated progressive germline mortality following mating. Proximity biotinylation profiling of human homologs (HNRNPM, MYEF2) identified proteins of ribonucleoprotein complexes previously shown to contain non-coding RNA. Like HNRNPM and MYEF2, SUP-46 was associated with multiple RNA granules, including stress granules, and also formed granules on active chromatin. SUP-46 depletion disrupted germ RNA granules and caused ectopic sperm, increased sperm transcripts, and chronic heat stress sensitivity. SUP-46 was also required for resistance to acute heat stress, and a conserved "MYEF2" motif was identified that was needed for stress resistance. CONCLUSIONS: In mammals, non-coding RNA from the sperm of stressed males has been shown to recapitulate paternal stress phenotypes in the offspring. Our results suggest that HNRNPM family proteins enable stress resistance and paternally-mediated epigenetic transmission that may be conserved across species.

Parallel Exploration of Interaction Space by BioID and Affinity Purification Coupled to Mass Spectrometry.

Complete understanding of cellular function requires knowledge of the composition and dynamics of protein interaction networks, the importance of which spans all molecular cell biology fields. Mass spectrometry-based proteomics approaches are instrumental in this process, with affinity purification coupled to mass spectrometry (AP-MS) now widely used for defining interaction landscapes. Traditional AP-MS methods are well suited to providing information regarding the temporal aspects of soluble protein-protein interactions, but the requirement to maintain protein-protein interactions during cell lysis and AP means that both weak-affinity interactions and spatial information is lost. A more recently developed method called BioID employs the expression of bait proteins fused to a nonspecific biotin ligase, BirA*, that induces in vivo biotinylation of proximal proteins. Coupling this method to biotin affinity enrichment and mass spectrometry negates many of the solubility and interaction strength issues inherent in traditional AP-MS methods, and provides unparalleled spatial context for protein interactions. Here we describe the parallel implementation of both BioID and FLAG AP-MS allowing simultaneous exploration of both spatial and temporal aspects of protein interaction networks.

Functional Analysis of Kinases and Transcription Factors in Saccharomyces cerevisiae Using an Integrated Overexpression Library.

Kinases and transcription factors (TFs) are key modulators of important signaling pathways and their activities underlie the proper function of many basic cellular processes such as cell division, differentiation, and development. Changes in kinase and TF dosage are often associated with disease, yet a systematic assessment of the cellular phenotypes caused by the combined perturbation of kinases and TFs has not been undertaken. We used a reverse-genetics approach to study the phenotypic consequences of kinase and TF overexpression (OE) in the budding yeast, Saccharomyces cerevisiae We constructed a collection of strains expressing stably integrated inducible alleles of kinases and TFs and used a variety of assays to characterize the phenotypes caused by TF and kinase OE. We used the Synthetic Genetic Array (SGA) method to examine dosage-dependent genetic interactions (GIs) between 239 gain-of-function (OE) alleles of TFs and six loss-of-function (LOF) and seven OE kinase alleles, the former identifying Synthetic Dosage Lethal (SDL) interactions and the latter testing a GI we call Double Dosage Lethality (DDL). We identified and confirmed 94 GIs between 65 OE alleles of TFs and 9 kinase alleles. Follow-up experiments validated regulatory relationships between genetically interacting pairs (Cdc28-Stb1 and Pho85-Pdr1), suggesting that GI studies involving OE alleles of regulatory proteins will be a rich source of new functional information.

Exploring genetic suppression interactions on a global scale.

Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

A mesoscale abscisic acid hormone interactome reveals a dynamic signaling landscape in Arabidopsis.

The sesquiterpenoid abscisic acid (ABA) mediates an assortment of responses across a variety of kingdoms including both higher plants and animals. In plants, where most is known, a linear core ABA signaling pathway has been identified. However, the complexity of ABA-dependent gene expression suggests that ABA functions through an intricate network. Here, using systems biology approaches that focused on genes transcriptionally regulated by ABA, we defined an ABA signaling network of over 500 interactions among 138 proteins. This map greatly expanded ABA core signaling but was still manageable for systematic analysis. For example, functional analysis was used to identify an ABA module centered on two sucrose nonfermenting (SNF)-like kinases. We also used coexpression analysis of interacting partners within the network to uncover dynamic subnetwork structures in response to different abiotic stresses. This comprehensive ABA resource allows for application of approaches to understanding ABA functions in higher plants.

The Arabidopsis ZED1 pseudokinase is required for ZAR1-mediated immunity induced by the Pseudomonas syringae type III effector HopZ1a.

Plant and animal pathogenic bacteria can suppress host immunity by injecting type III secreted effector (T3SE) proteins into host cells. However, T3SEs can also elicit host immunity if the host has evolved a means to recognize the presence or activity of specific T3SEs. The diverse YopJ/HopZ/AvrRxv T3SE superfamily, which is found in both animal and plant pathogens, provides examples of T3SEs playing this dual role. The T3SE HopZ1a is an acetyltransferase carried by the phytopathogen Pseudomonas syringae that elicits effector-triggered immunity (ETI) when recognized in Arabidopsis thaliana by the nucleotide-binding leucine-rich repeat (NB-LRR) protein ZAR1. However, recognition of HopZ1a does not require any known ETI-related genes. Using a forward genetics approach, we identify a unique ETI-associated gene that is essential for ZAR1-mediated immunity. The hopZ-ETI-deficient1 (zed1) mutant is specifically impaired in the recognition of HopZ1a, but not the recognition of other unrelated T3SEs or in pattern recognition receptor (PRR)-triggered immunity. ZED1 directly interacts with both HopZ1a and ZAR1 and is acetylated on threonines 125 and 177 by HopZ1a. ZED1 is a nonfunctional kinase that forms part of small genomic cluster of kinases in Arabidopsis. We hypothesize that ZED1 acts as a decoy to lure HopZ1a to the ZAR1-resistance complex, resulting in ETI activation.

Functional genomics in the study of yeast cell polarity: moving in the right direction.

The budding yeast Saccharomyces cerevisiae has been used extensively for the study of cell polarity, owing to both its experimental tractability and the high conservation of cell polarity and other basic biological processes among eukaryotes. The budding yeast has also served as a pioneer model organism for virtually all genome-scale approaches, including functional genomics, which aims to define gene function and biological pathways systematically through the analysis of high-throughput experimental data. Here, we outline the contributions of functional genomics and high-throughput methodologies to the study of cell polarity in the budding yeast. We integrate data from published genetic screens that use a variety of functional genomics approaches to query different aspects of polarity. Our integrated dataset is enriched for polarity processes, as well as some processes that are not intrinsically linked to cell polarity, and may provide new areas for future study.