A general life-death selection strategy for dissecting protein functions

Intra-FCY1: a novel system to identify mutations that cause protein misfolding

Protein misfolding is a common intracellular occurrence. Most mutations to coding sequences increase the propensity of the encoded protein to misfold. These misfolded molecules can have devastating effects on cells. Despite the importance of protein misfolding in human disease and protein evolution, there are fundamental questions that remain unanswered, such as, which mutations cause the most misfolding? These questions are difficult to answer partially because we lack high-throughput methods to compare the destabilizing effects of different mutations. Commonly used systems to assess the stability of mutant proteins in vivo often rely upon essential proteins as sensors, but misfolded proteins can disrupt the function of the essential protein enough to kill the cell. This makes it difficult to identify and compare mutations that cause protein misfolding using these systems. Here, we present a novel in vivo system named Intra-FCY1 that we use to identify mutations that cause misfolding of a model protein [yellow fluorescent protein (YFP)] in Saccharomyces cerevisiae. The Intra-FCY1 system utilizes two complementary fragments of the yeast cytosine deaminase Fcy1, a toxic protein, into which YFP is inserted. When YFP folds, the Fcy1 fragments associate together to reconstitute their function, conferring toxicity in media containing 5-fluorocytosine and hindering growth. But mutations that make YFP misfold abrogate Fcy1 toxicity, thus strains possessing misfolded YFP variants rise to high frequency in growth competition experiments. This makes such strains easier to study. The Intra-FCY1 system cancels localization of the protein of interest, thus can be applied to study the relative stability of mutant versions of diverse cellular proteins. Here, we confirm this method can identify novel mutations that cause misfolding, highlighting the potential for Intra-FCY1 to illuminate the relationship between protein sequence and stability.

Controllable genome editing with split-engineered base editors

DNA deaminase enzymes play key roles in immunity and have recently been harnessed for their biotechnological applications. In base editors (BEs), the combination of DNA deaminase mutator activity with CRISPR-Cas localization confers the powerful ability to directly convert one target DNA base into another. While efforts have been made to improve targeting efficiency and precision, all BEs so far use a constitutively active DNA deaminase. The absence of regulatory control over promiscuous deaminase activity remains a major limitation to accessing the widespread potential of BEs. Here, we reveal sites that permit splitting of DNA cytosine deaminases into two inactive fragments, whose reapproximation reconstitutes activity. These findings allow for the development of split-engineered BEs (seBEs), which newly enable small-molecule control over targeted mutator activity. We show that the seBE strategy facilitates robust regulated editing with BE scaffolds containing diverse deaminases, offering a generalizable solution for temporally controlling precision genome editing.

Protein-fragment complementation assays for large-scale analysis of protein-protein interactions

Protein-protein interactions (PPIs) orchestrate nearly all biological processes. They are also considered attractive drug targets for treating many human diseases, including cancers and neurodegenerative disorders. Protein-fragment complementation assays (PCAs) provide a direct and straightforward way to study PPIs in living cells or multicellular organisms. Importantly, PCAs can be used to detect the interaction of proteins expressed at endogenous levels in their native cellular environment. In this review, we present the principle of PCAs and discuss some of their advantages and limitations. We describe their application in large-scale experiments to investigate PPI networks and to screen or profile PPI targeting compounds.

Identification of Putative Interactors of Arabidopsis Sugar Transporters

Hexoses and disaccharides are the key carbon sources for essentially all physiological processes across kingdoms. In plants, sucrose, and in some cases raffinose and stachyose, are transported from the site of synthesis in leaves, the sources, to all other organs that depend on import, the sinks. Sugars also play key roles in interactions with beneficial and pathogenic microbes. Sugar transport is mediated by transport proteins that fall into super-families. Sugar transporter (ST) activity is tuned at different levels, including transcriptional and posttranslational levels. Understanding the ST interactome has a great potential to uncover important players in biologically and physiologically relevant processes, including, but not limited to Arabidopsis thaliana. Here, we combined ST interactions and coexpression studies to identify potentially relevant interaction networks.

Genetics' Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome-Wide Protein-Protein Interaction Dynamics

How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein-protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment.

FRETting about the affinity of bimolecular protein-protein interactions

Fluorescence resonance energy transfer (FRET) is a powerful tool to study macromolecular interactions such as protein-protein interactions (PPIs). Fluorescent protein (FP) fusions enable FRET-based PPI analysis of signaling pathways and molecular structure in living cells. Despite FRET's importance in PPI studies, FRET has seen limited use in quantifying the affinities of PPIs in living cells. Here, we have explored the relationship between FRET efficiency and PPI affinity over a wide range when expressed from a single plasmid system in Escherichia coli. Using live-cell microscopy and a set of 20 pairs of small interacting proteins, belonging to different structural folds and interaction affinities, we demonstrate that FRET efficiency can reliably measure the dissociation constant (K_D ) over a range of mM to nM. A 10-fold increase in the interaction affinity results in 0.05 unit increase in FRET efficiency, providing sufficient resolution to quantify large affinity differences (> 10-fold) using live-cell FRET. This approach provides a rapid and simple strategy for assessment of PPI affinities over a wide range and will have utility for high-throughput analysis of protein interactions.

Extended Linkers Improve the Detection of Protein-protein Interactions (PPIs) by Dihydrofolate Reductase Protein-fragment Complementation Assay (DHFR PCA) in Living Cells

Understanding the function of cellular systems requires describing how proteins assemble with each other into transient and stable complexes and to determine their spatial relationships. Among the tools available to perform these analyses on a large scale is Protein-fragment Complementation Assay based on the dihydrofolate reductase (DHFR PCA). Here we test how longer linkers between the fusion proteins and the reporter fragments affect the performance of this assay. We investigate the architecture of the RNA polymerases, the proteasome and the conserved oligomeric Golgi (COG) complexes in living cells and performed large-scale screens with these extended linkers. We show that longer linkers significantly improve the detection of protein-protein interactions and allow to measure interactions further in space than the standard ones. We identify new interactions, for instance between the retromer complex and proteins related to autophagy and endocytosis. Longer linkers thus contribute an enhanced additional tool to the existing toolsets for the detection and measurements of protein-protein interactions and protein proximity in living cells.

EC-tagging allows cell type-specific RNA analysis

Purification of cell type-specific RNAs remains a significant challenge. One solution involves biosynthetic tagging of target RNAs. RNA tagging via incorporation of 4-thiouracil (TU) in cells expressing transgenic uracil phosphoribosyltransferase (UPRT), a method known as TU-tagging, has been used in multiple systems but can have limited specificity due to endogenous pathways of TU incorporation. Here, we describe an alternative method that requires the activity of two enzymes: cytosine deaminase (CD) and UPRT. We found that the sequential activity of these enzymes converts 5-ethynylcytosine (EC) to 5-ethynyluridine monophosphate that is subsequently incorporated into nascent RNAs. The ethynyl group allows efficient detection and purification of tagged RNAs. We show that ‘EC-tagging’ occurs in tissue culture cells and Drosophila engineered to express CD and UPRT. Additional control can be achieved through a split-CD approach in which functional CD is reconstituted from independently expressed fragments. We demonstrate the sensitivity and specificity of EC-tagging by obtaining cell type-specific gene expression data from intact Drosophila larvae, including transcriptome measurements from a small population of central brain neurons. EC-tagging provides several advantages over existing techniques and should be broadly useful for investigating the role of differential RNA expression in cell identity, physiology and pathology.

Protein interaction perturbation profiling at amino-acid resolution

The identification of genomic variants in healthy and diseased individuals continues to rapidly outpace our ability to functionally annotate these variants. Techniques that both systematically assay the functional consequences of nucleotide-resolution variation and can scale to hundreds of genes are urgently required. We designed a sensitive yeast two-hybrid-based 'off switch' for positive selection of interaction-disruptive variants from complex genetic libraries. Combined with massively parallel programmed mutagenesis and a sequencing readout, this method enables systematic profiling of protein-interaction determinants at amino-acid resolution. We defined >1,000 interaction-disrupting amino acid mutations across eight subunits of the BBSome, the major human cilia protein complex associated with the pleiotropic genetic disorder Bardet-Biedl syndrome. These high-resolution interaction-perturbation profiles provide a framework for interpreting patient-derived mutations across the entire protein complex and thus highlight how the impact of disease variation on interactome networks can be systematically assessed.

Yeast-based assays for detecting protein-protein/drug interactions and their inhibitors

Understanding cellular processes at molecular levels in health and disease requires the knowledge of protein-protein interactions (PPIs). In line with this, identification of PPIs at genome-wide scale is highly valuable to understand how different cellular pathways are interconnected, and it eventually facilitates designing effective drugs against certain PPIs. Furthermore, investigating PPIs at a small laboratory scale for deciphering certain biochemical pathways has been demanded for years. In this regard, yeast two hybrid system (Y2HS) has proven an extremely useful tool to discover novel PPIs, while Y2HS derivatives and novel yeast-based assays are contributing significantly to identification of protein-drug/inhibitor interaction at both large- and small-scale set-ups. These methods have been evolving over time to provide more accurate, reproducible and quantitative results. Here we briefly describe different yeast-based assays for identification of various protein-protein/drug/inhibitor interactions and their specific applications, advantages, shortcomings, and improvements. The broad range of yeast-based assays facilitates application of the most suitable method(s) for each specific need.

A method for high-throughput production of sequence-verified DNA libraries and strain collections

The low costs of array‐synthesized oligonucleotide libraries are empowering rapid advances in quantitative and synthetic biology. However, high synthesis error rates, uneven representation, and lack of access to individual oligonucleotides limit the true potential of these libraries. We have developed a cost‐effective method called Recombinase Directed Indexing (REDI), which involves integration of a complex library into yeast, site‐specific recombination to index library DNA, and next‐generation sequencing to identify desired clones. We used REDI to generate a library of ~3,300 DNA probes that exhibited > 96% purity and remarkable uniformity (> 95% of probes within twofold of the median abundance). Additionally, we created a collection of ~9,000 individually accessible CRISPR interference yeast strains for > 99% of genes required for either fermentative or respiratory growth, demonstrating the utility of REDI for rapid and cost‐effective creation of strain collections from oligonucleotide pools. Our approach is adaptable to any complex DNA library, and fundamentally changes how these libraries can be parsed, maintained, propagated, and characterized.

Protein-Fragment Complementation Assays for Large-Scale Analysis, Functional Dissection, and Spatiotemporal Dynamic Studies of Protein-Protein Interactions in Living Cells

Protein-fragment complementation assays (PCAs) comprise a family of assays that can be used to study protein-protein interactions (PPIs), conformation changes, and protein complex dimensions. We developed PCAs to provide simple and direct methods for the study of PPIs in any living cell, subcellular compartments or membranes, multicellular organisms, or in vitro. Because they are complete assays, requiring no cell-specific components other than reporter fragments, they can be applied in any context. PCAs provide a general strategy for the detection of proteins expressed at endogenous levels within appropriate subcellular compartments and with normal posttranslational modifications, in virtually any cell type or organism under any conditions. Here we introduce a number of applications of PCAs in budding yeast, Saccharomyces cerevisiae These applications represent the full range of PPI characteristics that might be studied, from simple detection on a large scale to visualization of spatiotemporal dynamics.

Dissecting the Contingent Interactions of Protein Complexes with the Optimized Yeast Cytosine Deaminase Protein-Fragment Complementation Assay

Here, we present a detailed protocol for studying in yeast cells the contingent interaction between a substrate and its multisubunit enzyme complex by using a death selection technique known as the optimized yeast cytosine deaminase protein-fragment complementation assay (OyCD PCA). In yeast, the enzyme cytosine deaminase (encoded by FCY1) is involved in pyrimidine metabolism. The PCA is based on an engineered form of yeast cytosine deaminase optimized by directed evolution for maximum activity (OyCD), which acts as a reporter converting the pro-drug 5-fluorocytosine (5-FC) to 5-fluorouracil (5-FU), a toxic compound that kills the cell. Cells that have OyCD PCA activity convert 5-FC to 5-FU and die. Using this assay, it is possible to assess how regulatory subunits of an enzyme contribute to the overall interaction between the catalytic subunit and the potential substrates. Furthermore, OyCD PCA can be used to dissect different functions of mutant forms of a protein as a mutant can disrupt interaction with one partner, while retaining interaction with others. As it is scalable to a medium- or high-throughput format, OyCD PCA can be used to study hundreds to thousands of pairwise protein-protein interactions in different deletion strains. In addition, OyCD PCA vectors (pAG413GAL1-ccdB-OyCD-F[1] and pAG415GAL1-ccdB-OyCD-F[2]) have been designed to be compatible with the proprietary Gateway technology. It is therefore easy to generate fusion genes with the OyCD reporter fragments. As an example, we will focus on the yeast cyclin-dependent protein kinase 1 (Cdk1, encoded by CDC28), its regulatory cyclin subunits, and its substrates or binding partners.

A Split-Ubiquitin Based Strategy Selecting for Protein Complex-Interfering Mutations

Understanding the topologies and functions of protein interaction networks requires the selective removal of single interactions. We introduce a selection strategy that enriches among a random library of alleles for mutations that impair the binding to a given partner protein. The selection makes use of a split-ubiquitin based protein interaction assay. This assay provides yeast cells that carry protein complex disturbing mutations with the advantage of being able to survive on uracil-lacking media. Applied to the exemplary interaction between the PB domains of the yeast proteins Bem1 and Cdc24, we performed two independent selections. The selections were either analyzed by Sanger sequencing of isolated clones or by next generation sequencing (NGS) of pools of clones. Both screens enriched for the same mutation in position 833 of Cdc24. Biochemical analysis confirmed that this mutation disturbs the interaction with Bem1 but not the fold of the protein. The larger dataset obtained by NGS achieved a more complete representation of the bipartite interaction interface of Cdc24.

Current Experimental Methods for Characterizing Protein-Protein Interactions

Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.

Current Experimental Methods for Characterizing Protein-Protein Interactions

Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.

Combining the Optimized Yeast Cytosine Deaminase Protein Fragment Complementation Assay and an In Vitro Cdk1 Targeting Assay to Study the Regulation of the γ-Tubulin Complex

Cdk1 is the essential cyclin-dependent kinase in the budding yeast Saccharomyces cerevisiae. Cdk1 orchestrates cell cycle control by phosphorylating target proteins with extraordinary temporal and spatial specificity by complexing with one of the nine cyclin regulatory subunits. The identification of the cyclin required for targeting Cdk1 to a substrate can help to place the regulation of that protein at a specific time point during the cell cycle and reveal information needed to elucidate the biological significance of the regulation. Here, we describe a combination of strategies to identify interaction partners of Cdk1, and associate these complexes to the appropriate cyclins using a cell-based protein-fragment complementation assay. Validation of the specific reliance of the OyCD interaction between Cdk1 and budding yeast γ-tubulin on the Clb3 cyclin, relative to the mitotic Clb2 cyclin, was performed by an in vitro kinase assay using the γ-tubulin complex as a substrate.

Multi-scale perturbations of protein interactomes reveal their mechanisms of regulation, robustness and insights into genotype-phenotype maps

Cellular architectures and signaling machineries are organized through protein-protein interactions (PPIs). High-throughput methods to study PPIs in yeast have opened a new perspective on the organization of the cell by allowing the study of whole protein interactomes. Recent investigations have moved from the description of this organization to the analysis of its dynamics by experimenting how protein interaction networks (PINs) are rewired in response to perturbations. Here we review studies that have used the budding yeast as an experimental system to explore these altered networks. Given the large space of possible PPIs and the diversity of potential genetic and environmental perturbations, high-throughput methods are an essential requirement to survey PIN perturbations on a large scale. Network perturbations are typically conceptualized as the removal of entire proteins (nodes), the modification of single PPIs (edges) or changes in growth conditions. These studies have revealed mechanisms of PPI regulation, PIN architectural organization, robustness and sensitivity to perturbations. Despite these major advances, there are still inherent limits to current technologies that lead to a trade-off between the number of perturbations and the number of PPIs that can be considered simultaneously. Nevertheless, as we exemplify here, targeted approaches combined with the existing resources remain extremely powerful to explore the inner organization of cells and their responses to perturbations.

SPLIFF: A Single-Cell Method to Map Protein-Protein Interactions in Time and Space

Protein interactions occur at certain times and at specific cellular places. The past years have seen a massive accumulation of binary protein-protein interaction data. The rapid increase of this context-free information necessitates robust methods to monitor protein interactions with temporal and spatial resolution in single cells. We have developed a simple split-ubiquitin-based method (SPLIFF) that uses the ratio of two fluorescent reporters as a signal for protein-protein interactions. One protein of the pair of interest is attached to the linear fusion of mCherry, the C-terminal half of ubiquitin, and GFP (mCherry-Cub-GFP). The other potential binding partner is expressed as a C-terminal fusion to the N-terminal half of ubiquitin (Nub). Upon co-expression the interaction between the two proteins of interest induces the reassociation of Nub and Cub to the native-like ubiquitin. GFP is subsequently cleaved from the C-terminus of Cub and degraded whereas the red-fluorescent mCherry stays attached to the Cub-fusion protein. We first implemented this method in the model yeast Saccharomyces cerevisiae. One fusion protein is expressed in cells of the a-mating type and the complementary fusion protein in cells of the α-mating type. Upon mixing, both cell types fuse and the Nub- and Cub-fusion proteins are free to interact. The red and green fluorescence is monitored by two-channel fluorescence time-lapse microcopy. The moment of cell fusion defines the start of the analysis. The calculated ratio of green to red fluorescence allows mapping the spatiotemporal interaction profiles of the investigated proteins in single cells.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks

Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden dynamics within protein interaction networks.

Cells are complex dynamic systems, and a central challenge in modern cell biology is to capture information about interactions between the molecules underlying cellular processes. Proteins rarely act alone; more often they form functional partnerships that can specify the timing and/or location of activity. These partnerships are subject to dynamic changes, and thus protein interactions within complexes undergo continuous transitions. Genetic and biochemical evidence suggest that regulation or depletion of a single protein can alter the stability and activity of an entire protein complex. Experimental approaches that detect interactions within living cells provide critical information for the dynamical system that protein complexes represent; yet complexes are often depicted as static 2-dimensional networks. We have built a system that projects in vivo protein interaction datasets as 3-dimensional virtual protein complexes. By using this method to approximate the diffusion of complex components, we can predict transient conformational states and estimate their abundance in living cells. Our method offers biologists a framework to correlate experimental phenotypes with predicted complex dynamics such as short or long-range effects of a single perturbation to the function of the whole ensemble.

An infrared reporter to detect spatiotemporal dynamics of protein-protein interactions

We report a protein-fragment complementation assay (PCA) based on the engineered Deinococcus radiodurans infrared fluorescent protein IFP1.4. Unlike previous fluorescent protein PCAs, the IFP PCA is reversible, allowing analysis of spatiotemporal dynamics of hormone-induced signaling complexes in living yeast and mammalian cells at nanometer resolution. The inherently low background of infrared fluorescence permitted detection of subcellular reorganization of a signaling complex expressed at low abundance.

A 3C(pro)-dependent bioluminescence imaging assay for in vivo evaluation of anti-enterovirus 71 agents

Enterovirus 71 (EV71), a member of Picornaviridae, is one of the major pathogens of human hand, foot and mouth disease. EV71 mainly infects children and causes severe neurological complications and even death. The pathogenesis of EV71 infection is largely unknown, and no clinically approved vaccine or effective treatment is available to date. Here we described a novel bioluminescence imaging approach for EV71 detection. In this approach, a plasmid-based reporter was constructed to express the fusion protein AmN(Q/G)BC, a split firefly luciferase mutant, which can be specifically cleaved by EV71 protease 3C(pro). Upon cleavage, the splitting fusion protein restores luciferase activity. Our test confirmed that AmN(Q/G)BC was specifically cleaved by 3C(pro) and EV71 and restored the luciferase activity to a degree that corresponds to the 3C(pro) and virus doses in cells and mice. The anti-EV71 effect of GW5074 and U0126, two mitogen-activated protein kinase (MAPK) inhibitors, was evaluated using this approach to validate its application of screening anti-EV71 agents. We found that the AmN(Q/G)BC reporter efficiently monitored the inhibitory effect of GW5074 and U0126 on EV71 infection under in vitro and in vivo conditions. The data from AmN(Q/G)BC reporter were consistent with Western blotting and histopathology examination. Taken together, this real-time imaging approach can quantitatively monitor the efficacy of anti-EV71 agents and is valuable for anti-EV71 drug screening and evaluation, especially, under in vivo conditions.

All or nothing: protein complexes flip essentiality between distantly related eukaryotes

In the budding yeast Saccharomyces cerevisiae, the subunits of any given protein complex are either mostly essential or mostly nonessential, suggesting that essentiality is a property of molecular machines rather than individual components. There are exceptions to this rule, however, that is, nonessential genes in largely essential complexes and essential genes in largely nonessential complexes. Here, we provide explanations for these exceptions, showing that redundancy within complexes, as revealed by genetic interactions, can explain many of the former cases, whereas “moonlighting,” as revealed by membership of multiple complexes, can explain the latter. Surprisingly, we find that redundancy within complexes cannot usually be explained by gene duplication, suggesting alternate buffering mechanisms. In the distantly related Schizosaccharomyces pombe, we observe the same phenomenon of modular essentiality, suggesting that it may be a general feature of eukaryotes. Furthermore, we show that complexes flip essentiality in a cohesive fashion between the two species, that is, they tend to change from mostly essential to mostly nonessential, or vice versa, but not to mixed patterns. We show that these flips in essentiality can be explained by differing lifestyles of the two yeasts. Collectively, our results support a previously proposed model where proteins are essential because of their involvement in essential functional modules rather than because of specific topological features such as degree or centrality.

Dissection of Cdk1-cyclin complexes in vivo

Cyclin-dependent kinases (Cdks) are regulatory enzymes with temporal and spatial selectivity for their protein substrates that are governed by cell cycle-regulated cyclin subunits. Specific cyclin-Cdk complexes bind to and phosphorylate target proteins, coupling their activity to cell cycle states. The identification of specific cyclin-Cdk substrates is challenging and so far, has largely been achieved through indirect correlation or use of in vitro techniques. Here, we use a protein-fragment complementation assay based on the optimized yeast cytosine deaminase to systematically identify candidate substrates of budding yeast Saccharomyces cerevisiae Cdk1 and show dependency on one or more regulatory cyclins. We identified known and candidate cyclin dependencies for many predicted protein kinase Cdk1 targets and showed elusory Clb3-Cdk1-specific phosphorylation of γ-tubulin, thus establishing the timing of this event in controlling assembly of the mitotic spindle. Our strategy can be generally applied to identify substrates and accessory subunits of multisubunit protein complexes.

Evidence for the robustness of protein complexes to inter-species hybridization

Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein-protein interactions (PPIs) among closely related species and their hybrids. We examine in vivo the architecture of protein complexes in two yeast species (Saccharomyces cerevisiae and Saccharomyces kudriavzevii) that diverged 5-20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC), which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.

qPCA: a scalable assay to measure the perturbation of protein-protein interactions in living cells

One of the most important challenges in systems biology is to understand how cells respond to genetic and environmental perturbations. Here we show that the yeast DHFR-PCA, coupled with high-resolution growth profiling (DHFR-qPCA), is a straightforward assay to study the modulation of protein-protein interactions (PPIs) in vivo as a response to genetic, metabolic and drug perturbations. Using the canonical Protein Kinase A (PKA) pathway as a test system, we show that changes in PKA activity can be measured in living cells as a modulation of the interaction between its regulatory (Bcy1) and catalytic (Tpk1 and Tpk2) subunits in response to changes in carbon metabolism, caffeine and methyl methanesulfonate (MMS) treatments and to modifications in the dosage of its enzymatic regulators, the phosphodiesterases. Our results show that the DHFR-qPCA is easily implementable and amenable to high-throughput. The DHFR-qPCA will pave the way to the study of the effects of drug, genetic and environmental perturbations on in vivo PPI networks, thus allowing the exploration of new spaces of the eukaryotic interactome.

Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system

The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays.

Systematic functional prioritization of protein posttranslational modifications

Protein function is often regulated by posttranslational modifications (PTMs), and recent advances in mass spectrometry have resulted in an exponential increase in PTM identification. However, the functional significance of the vast majority of these modifications remains unknown. To address this problem, we compiled nearly 200,000 phosphorylation, acetylation, and ubiquitination sites from 11 eukaryotic species, including 2,500 newly identified ubiquitylation sites for Saccharomyces cerevisiae. We developed methods to prioritize the functional relevance of these PTMs by predicting those that likely participate in cross-regulatory events, regulate domain activity, or mediate protein-protein interactions. PTM conservation within domain families identifies regulatory "hot spots" that overlap with functionally important regions, a concept that we experimentally validated on the HSP70 domain family. Finally, our analysis of the evolution of PTM regulation highlights potential routes for neutral drift in regulatory interactions and suggests that only a fraction of modification sites are likely to have a significant biological role.

Annotator: postprocessing software for generating function-based signatures from quantitative mass spectrometry

Mass spectrometry is used to investigate global changes in protein abundance in cell lysates. Increasingly powerful methods of data collection have emerged over the past decade, but this has left researchers with the task of sifting through mountains of data for biologically significant results. Often, the end result is a list of proteins with no obvious quantitative relationships to define the larger context of changes in cell behavior. Researchers are often forced to perform a manual analysis from this list or to fall back on a range of disparate tools, which can hinder the communication of results and their reproducibility. To address these methodological problems, we developed Annotator, an application that filters validated mass spectrometry data and applies a battery of standardized heuristic and statistical tests to determine significance. To address systems-level interpretations, we incorporated UniProt and Gene Ontology keywords as statistical units of analysis, yielding quantitative information about changes in abundance for an entire functional category. This provides a consistent and quantitative method for formulating conclusions about cellular behavior, independent of network models or standard enrichment analyses. Annotator allows for "bottom-up" annotations that are based on experimental data and not inferred by comparison to external or hypothetical models. Annotator was developed as an independent postprocessing platform that runs on all common operating systems, thereby providing a useful tool for establishing the inherently dynamic nature of functional annotations, which depend on results from ongoing proteomic experiments. Annotator is available for download at http://people.cs.uchicago.edu/∼tyler/annotator/annotator_desktop_0.1.tar.gz .

Manipulating cellular processes using optical control of protein-protein interactions

Tools for optical control of proteins offer an unprecedented level of spatiotemporal control over biological processes, adding a new layer of experimental opportunity. While use of light-activated cation channels and anion pumps has already revolutionized neurobiology, an emerging class of more general optogenetic tools may have similar transformative effects. These tools consist of light-dependent protein interaction modules that allow control of target protein interactions and localization with light. Such tools are modular and can be applied to regulate a wide variety of biological activities. This chapter reviews the different properties of light-induced dimerization systems, based on plant phytochromes, cryptochromes, and light-oxygen-voltage domain proteins, exploring advantages and limitations of the different systems and practical considerations related to their use. Potential applications of these tools within the neurobiology field, including light control of various signaling pathways, neuronal activity, and DNA recombination and transcription, are discussed.

PKA regulatory subunits mediate synergy among conserved G-protein-coupled receptor cascades

G-protein-coupled receptors sense extracellular chemical or physical stimuli and transmit these signals to distinct trimeric G-proteins. Activated Gα-proteins route signals to interconnected effector cascades, thus regulating thresholds, amplitudes and durations of signalling. Gαs- or Gαi-coupled receptor cascades are mechanistically conserved and mediate many sensory processes, including synaptic transmission, cell proliferation and chemotaxis. Here we show that a central, conserved component of Gαs-coupled receptor cascades, the regulatory subunit type-II (RII) of protein kinase A undergoes adenosine 3′-5′-cyclic monophosphate (cAMP)-dependent binding to Gαi. Stimulation of a mammalian Gαi-coupled receptor and concomitant cAMP-RII binding to Gαi, augments the sensitivity, amplitude and duration of Gαi:βγ activity and downstream mitogen-activated protein kinase signalling, independent of protein kinase A kinase activity. The mechanism is conserved in budding yeast, causing nutrient-dependent modulation of a pheromone response. These findings suggest a direct mechanism by which coincident activation of Gαs-coupled receptors controls the precision of adaptive responses of activated Gαi-coupled receptor cascades.

G-protein-coupled receptors sense extracellular cues and transmit the signal to distinct trimeric G-proteins. Stefan et al. show that in response to cAMP, a central and conserved component of the Gαs-coupled receptor cascade, the RII subunit of PKA, specifically binds to and participates in Gαi signaling.

Protein-fragment complementation assays for large-scale analysis, functional dissection and dynamic studies of protein-protein interactions in living cells

Protein-fragment Complementation Assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism, or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Assays can be performed in any cell type or model organism that can be transformed or transfected with gene expression DNA constructs. Here we focus on recent applications of PCA in the budding yeast, Saccharomyces cerevisiae, that cover the gamut of applications one could envision for studying any aspect of PPIs. We present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR), reporter PCA, and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present methods to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs.

Design, selection, and characterization of a split chorismate mutase

Split proteins are versatile tools for detecting protein-protein interactions and studying protein folding. Here, we report a new, particularly small split enzyme, engineered from a thermostable chorismate mutase (CM). Upon dissecting the helical-bundle CM from Methanococcus jannaschii into a short N-terminal helix and a 3-helix segment and attaching an antiparallel leucine zipper dimerization domain to the individual fragments, we obtained a weakly active heterodimeric mutase. Using combinatorial mutagenesis and in vivo selection, we optimized the short linker sequences connecting the leucine zipper to the enzyme domain. One of the selected CMs was characterized in detail. It spontaneously assembles from the separately inactive fragments and exhibits wild-type like CM activity. Owing to the availability of a well characterized selection system, the simple 4-helix bundle topology, and the small size of the N-terminal helix, the heterodimeric CM could be a valuable scaffold for enzyme engineering efforts and as a split sensor for specifically oriented protein-protein interactions.

A toolkit of protein-fragment complementation assays for studying and dissecting large-scale and dynamic protein-protein interactions in living cells

Protein-fragment complementation assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Applications of PCAs in yeast have been limited until recently, simply because appropriate expression plasmids or cassettes had not been developed. However, we have now developed and reported on several PCAs in Saccharomyces cerevisiae that cover the gamut of applications one could envision for studying any aspect of PPIs. Here, we present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR) reporter PCA and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present a method to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs and finally, two luciferase reporter PCAs that have proved useful for studies of dynamics of PPIs.