A systematic approach for the genetic dissection of protein complexes in living cells

Co-translational Assembly Pathways of Nuclear Multiprotein Complexes Involved in the Regulation of Gene Transcription

Most factors that regulate gene transcription in eukaryotic cells are multimeric, often large, protein complexes. The understanding of the biogenesis pathways of such large and heterogeneous protein assemblies, as well as the dimerization partner choice among transcription factors, is crucial to interpret and control gene expression programs and consequent cell fate decisions. Co-translational assembly (Co-TA) is thought to play key roles in the biogenesis of protein complexes by directing complex formation during protein synthesis. In this review we discuss the principles of Co-TA with a special focus for the assembly of transcription regulatory complexes. We outline the expected molecular advantages of establishing co-translational interactions, pointing at the available, or missing, evidence for each of them. We hypothesize different molecular mechanisms based on Co-TA to explain the allocation "dilemma" of paralog proteins and subunits shared by different transcription complexes. By taking as a paradigm the different assembly pathways employed by three related transcription regulatory complexes (TFIID, SAGA and ATAC), we discuss alternative Co-TA strategies for nuclear multiprotein complexes and the widespread - yet specific - use of Co-TA for the formation of nuclear complexes involved in gene transcription. Ultimately, we outlined a series of open questions which demand well-defined lines of research to investigate the principles of gene regulation that rely on the coordinated assembly of protein complexes.

Tackling redundancy: genetic mechanisms underlying paralog compensation in plants

Gene duplication is a powerful source of biological innovation giving rise to paralogous genes that undergo diverse fates. Redundancy between paralogous genes is an intriguing outcome of duplicate gene evolution, and its maintenance over evolutionary time has long been considered a paradox. Redundancy can also be dubbed 'a geneticist's nightmare': It hinders the predictability of genome editing outcomes and limits our ability to link genotypes to phenotypes. Genetic studies in yeast and plants have suggested that the ability of ancient redundant duplicates to compensate for dosage perturbations resulting from a loss of function depends on the reprogramming of gene expression, a phenomenon known as active compensation. Starting from considerations on the stoichiometric constraints that drive the evolutionary stability of redundancy, this review aims to provide insights into the mechanisms of active compensation between duplicates that could be targeted for breaking paralog dependencies - the next frontier in plant functional studies.

Multilayered regulation of proteome stoichiometry

Cellular systems depend on multiprotein complexes whose functionalities require defined stoichiometries of subunit proteins. Proper stoichiometry is achieved by controlling the amount of protein synthesis and degradation even in the presence of genetic perturbations caused by changes in gene dosage. As a consequence of increased gene copy number, excess subunits unassembled into the complex are synthesized and rapidly degraded by the ubiquitin–proteasome system. This mechanism, called protein-level dosage compensation, is widely observed not only under such perturbed conditions but also in unperturbed physiological cells. Recent studies have shown that recognition of unassembled subunits and their selective degradation are intricately regulated. This review summarizes the nature, strategies, and increasing complexity of protein-level dosage compensation and discusses possible mechanisms for controlling proteome stoichiometry in multiple layers of biological processes.

Expression attenuation as a mechanism of robustness against gene duplication

Gene duplication is ubiquitous and a major driver of phenotypic diversity across the tree of life, but its immediate consequences are not fully understood. Deleterious effects would decrease the probability of retention of duplicates and prevent their contribution to long-term evolution. One possible detrimental effect of duplication is the perturbation of the stoichiometry of protein complexes. Here, we measured the fitness effects of the duplication of 899 essential genes in the budding yeast using high-resolution competition assays. At least 10% of genes caused a fitness disadvantage when duplicated. Intriguingly, the duplication of most protein complex subunits had small to nondetectable effects on fitness, with few exceptions. We selected four complexes with subunits that had an impact on fitness when duplicated and measured the impact of individual gene duplications on their protein-protein interactions. We found that very few duplications affect both fitness and interactions. Furthermore, large complexes such as the 26S proteasome are protected from gene duplication by attenuation of protein abundance. Regulatory mechanisms that maintain the stoichiometric balance of protein complexes may protect from the immediate effects of gene duplication. Our results show that a better understanding of protein regulation and assembly in complexes is required for the refinement of current models of gene duplication.

Exploring the Complexity of Protein-Level Dosage Compensation that Fine-Tunes Stoichiometry of Multiprotein Complexes

Proper control of gene expression levels upon various perturbations is a fundamental aspect of cellular robustness. Protein-level dosage compensation is one mechanism buffering perturbations to stoichiometry of multiprotein complexes through accelerated proteolysis of unassembled subunits. Although N-terminal acetylation- and ubiquitin-mediated proteasomal degradation by the Ac/N-end rule pathway enables selective compensation of excess subunits, it is unclear how widespread this pathway contributes to stoichiometry control. Here we report that dosage compensation depends only partially on the Ac/N-end rule pathway. Our analysis of genetic interactions between 18 subunits and 12 quality control factors in budding yeast demonstrated that multiple E3 ubiquitin ligases and N-acetyltransferases are involved in dosage compensation. We find that N-acetyltransferases-mediated compensation is not simply predictable from N-terminal sequence despite their sequence specificity for N-acetylation. We also find that the compensation of Pop3 and Bet4 is due in large part to a minor N-acetyltransferase NatD. Furthermore, canonical NatD substrates histone H2A/H4 were compensated even in its absence, suggesting N-acetylation-independent stoichiometry control. Our study reveals the complexity and robustness of the stoichiometry control system.

Quality control of multiprotein complexes is important for maintaining homeostasis in cellular systems that are based on functional complexes. Proper stoichiometry of multiprotein complexes is achieved by the balance between protein synthesis and degradation. Recent studies showed that translation efficiency tends to scale with stoichiometry of their subunits. On the other hand, although protein N-terminal acetylation- and ubiquitin-mediated proteolysis pathway is involved in selective degradation of excess subunits, it is unclear how widespread this pathway contributes to stoichiometry control due to the lack of a systematic investigation using endogenous proteins. To better understand the landscape of the stoichiometry control system, we examined genetic interactions between 18 subunits and 12 quality control factors (E3 ubiquitin ligases and N-acetyltransferases), in total 114 combinations. Our data suggest that N-acetyltransferases are partially responsible for stoichiometry control and that N-acetylation-independent pathway is also involved in selective degradation of excess subunits. Therefore, this study reveals the complexity and robustness of the stoichiometry control system. Further dissection of this complexity will help to understand the mechanisms buffering gene expression perturbations and shaping proteome stoichiometry.

Evolutionary coupling analysis identifies the impact of disease-associated variants at less-conserved sites

Genome-wide association studies have discovered a large number of genetic variants in human patients with the disease. Thus, predicting the impact of these variants is important for sorting disease-associated variants (DVs) from neutral variants. Current methods to predict the mutational impacts depend on evolutionary conservation at the mutation site, which is determined using homologous sequences and based on the assumption that variants at well-conserved sites have high impacts. However, many DVs at less-conserved but functionally important sites cannot be predicted by the current methods. Here, we present a method to find DVs at less-conserved sites by predicting the mutational impacts using evolutionary coupling analysis. Functionally important and evolutionarily coupled sites often have compensatory variants on cooperative sites to avoid loss of function. We found that our method identified known intolerant variants in a diverse group of proteins. Furthermore, at less-conserved sites, we identified DVs that were not identified using conservation-based methods. These newly identified DVs were frequently found at protein interaction interfaces, where species-specific mutations often alter interaction specificity. This work presents a means to identify less-conserved DVs and provides insight into the relationship between evolutionarily coupled sites and human DVs.

Paralog dependency indirectly affects the robustness of human cells

The protective redundancy of paralogous genes partly relies on the fact that they carry their functions independently. However, a significant fraction of paralogous proteins may form functionally dependent pairs, for instance, through heteromerization. As a consequence, one could expect these heteromeric paralogs to be less protective against deleterious mutations. To test this hypothesis, we examined the robustness landscape of gene loss-of-function by CRISPR-Cas9 in more than 450 human cell lines. This landscape shows regions of greater deleteriousness to gene inactivation as a function of key paralog properties. Heteromeric paralogs are more likely to occupy such regions owing to their high expression and large number of protein-protein interaction partners. Further investigation revealed that heteromers may also be under stricter dosage balance, which may also contribute to the higher deleteriousness upon gene inactivation. Finally, we suggest that physical dependency may contribute to the deleteriousness upon loss-of-function as revealed by the correlation between the strength of interactions between paralogs and their higher deleteriousness upon loss of function.

A collection of barcoded natural isolates of Saccharomyces paradoxus to study microbial evolutionary ecology

While the use of barcoded collections of laboratory microorganisms and the development of barcode-based cell tracking are rapidly developing in genetics and genomics research, tools to track natural populations are still lacking. The yeast Saccharomyces paradoxus is an emergent microbial model in ecology and evolution. More than five allopatric and sympatric lineages have been identified and hundreds of strains have been isolated for this species, allowing to assess the impact of natural diversity on complex traits. We constructed a collection of 550 barcoded and traceable strains of S. paradoxus, including all three North American lineages SpB, SpC, and SpC*. These strains are diploid, many have their genome fully sequenced and are barcoded with a unique 20 bp sequence that allows their identification and quantification. This yeast collection is functional for competitive experiments in pools as the barcodes allow to measure each lineage's and individual strains' fitness in common conditions. We used this tool to demonstrate that in the tested conditions, there are extensive genotype-by-environment interactions for fitness among S. paradoxus strains, which reveals complex evolutionary potential in variable environments. This barcoded collection provides a valuable resource for ecological genomics studies that will allow gaining a better understanding of S. paradoxus evolution and fitness-related traits.

Mitochondrial Recombination Reveals Mito-Mito Epistasis in Yeast

Genetic variation in mitochondrial DNA (mtDNA) provides adaptive potential although the underlying genetic architecture of fitness components within mtDNAs is not known. To dissect functional variation within mtDNAs, we first identified naturally occurring mtDNAs that conferred high or low fitness in Saccharomyces cerevisiae by comparing growth in strains containing identical nuclear genotypes but different mtDNAs. During respiratory growth under temperature and oxidative stress conditions, mitotype effects were largely independent of nuclear genotypes even in the presence of mito-nuclear interactions. Recombinant mtDNAs were generated to determine fitness components within high- and low-fitness mtDNAs. Based on phenotypic distributions of isogenic strains containing recombinant mtDNAs, we found that multiple loci contributed to mitotype fitness differences. These mitochondrial loci interacted in epistatic, nonadditive ways in certain environmental conditions. Mito-mito epistasis (i.e., nonadditive interactions between mitochondrial loci) influenced fitness in progeny from four different crosses, suggesting that mito-mito epistasis is a widespread phenomenon in yeast and other systems with recombining mtDNAs. Furthermore, we found that interruption of coadapted mito-mito interactions produced recombinant mtDNAs with lower fitness. Our results demonstrate that mito-mito epistasis results in functional variation through mitochondrial recombination in fungi, providing modes for adaptive evolution and the generation of mito-mito incompatibilities.

Mitochondrial Recombination and Introgression during Speciation by Hybridization

Genome recombination is a major source of genotypic diversity and contributes to adaptation and speciation following interspecies hybridization. The contribution of recombination in these processes has been thought to be largely limited to the nuclear genome because organelles are mostly uniparentally inherited in animals and plants, which prevents recombination. Unicellular eukaryotes such as budding yeasts do, however, transmit mitochondria biparentally, suggesting that during hybridization, both parents could provide alleles that contribute to mitochondrial functions such as respiration and metabolism in hybrid populations or hybrid species. We examined the dynamics of mitochondrial genome transmission and evolution during speciation by hybridization in the natural budding yeast Saccharomyces paradoxus. Using population-scale mitochondrial genome sequencing in two endemic North American incipient species SpB and SpC and their hybrid species SpC*, we found that both parental species contributed to the hybrid mitochondrial genome through recombination. We support our findings by showing that mitochondrial recombination between parental types is frequent in experimental crosses that recreate the early step of this speciation event. In these artificial hybrids, we observed that mitochondrial genome recombination enhances phenotypic variation among diploid hybrids, suggesting that it could play a role in the phenotypic differentiation of hybrid species. Like the nuclear genome, the mitochondrial genome can, therefore, also play a role in hybrid speciation.

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.

No evidence for extrinsic post-zygotic isolation in a wild Saccharomyces yeast system

Although microorganisms account for the largest fraction of Earth's biodiversity, we know little about how their reproductive barriers evolve. Sexual microorganisms such as Saccharomyces yeasts rapidly develop strong intrinsic post-zygotic isolation, but the role of extrinsic isolation in the early speciation process remains to be investigated. We measured the growth of F₁ hybrids between two incipient species of Saccharomyces paradoxus to assess the presence of extrinsic post-zygotic isolation across 32 environments. More than 80% of hybrids showed either partial dominance of the best parent or over-dominance for growth, revealing no fitness defects in F₁ hybrids. Extrinsic reproductive isolation therefore likely plays little role in limiting gene flow between incipient yeast species and is not a requirement for speciation.

The Rapid Evolution of an Ohnolog Contributes to the Ecological Specialization of Incipient Yeast Species

Identifying the molecular changes that lead to ecological specialization during speciation is one of the major goals of molecular evolution. One question that remains to be thoroughly investigated is whether ecological specialization derives strictly from adaptive changes and their associated trade-offs, or from conditionally neutral mutations that accumulate under relaxed selection. We used whole-genome sequencing, genome annotation and computational analyses to identify genes that have rapidly diverged between two incipient species of Saccharomyces paradoxus that occupy different climatic regions along a south-west to north-east gradient. As candidate loci for ecological specialization, we identified genes that show signatures of adaptation and accelerated rates of amino acid substitutions, causing asymmetric evolution between lineages. This set of genes includes a glycyl-tRNA-synthetase, GRS2, which is known to be transcriptionally induced under heat stress in the model and sister species S. cerevisiae. Molecular modelling, expression analysis and fitness assays suggest that the accelerated evolution of this gene in the Northern lineage may be caused by relaxed selection. GRS2 arose during the whole-genome duplication (WGD) that occurred 100 million years ago in the yeast lineage. While its ohnolog GRS1 has been preserved in all post-WGD species, GRS2 has frequently been lost and is evolving rapidly, suggesting that the fate of this ohnolog is still to be resolved. Our results suggest that the asymmetric evolution of GRS2 between the two incipient S. paradoxus species contributes to their restricted climatic distributions and thus that ecological specialization derives at least partly from relaxed selection rather than a molecular trade-off resulting from adaptive evolution.

Gene duplication can impart fragility, not robustness, in the yeast protein interaction network

The maintenance of duplicated genes is thought to protect cells from genetic perturbations, but the molecular basis of this robustness is largely unknown. By measuring the interaction of yeast proteins with their partners in wild-type cells and in cells lacking a paralog, we found that 22 out of 56 paralog pairs compensate for the lost interactions. An equivalent number of pairs exhibit the opposite behavior and require each other's presence for maintaining their interactions. These dependent paralogs generally interact physically, regulate each other's abundance, and derive from ancestral self-interacting proteins. This reveals that gene duplication may actually increase mutational fragility instead of robustness in a large number of cases.

Quantitative analysis of protein interaction network dynamics in yeast

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.

Identification of the fitness determinants of budding yeast on a natural substrate

The budding yeasts are prime models in genomics and cell biology, but the ecological factors that determine their success in non-human-associated habitats is poorly understood. In North America Saccharomyces yeasts are present on the bark of deciduous trees, where they feed on bark and sap exudates. In the North East, Saccharomyces paradoxus is found on maples, which makes maple sap a natural substrate for this species. We measured growth rates of S. paradoxus natural isolates on maple sap and found variation along a geographical gradient not explained by the inherent variation observed under optimal laboratory conditions. We used a functional genomic screen to reveal the ecologically relevant genes and conditions required for optimal growth in this substrate. We found that the allantoin degradation pathway is required for optimal growth in maple sap, in particular genes necessary for allantoate utilization, which we demonstrate is the major nitrogen source available to yeast in this environment. Growth with allantoin or allantoate as the sole nitrogen source recapitulated the variation in growth rates in maple sap among strains. We also show that two lineages of S. paradoxus display different life-history traits on allantoin and allantoate media, highlighting the ecological relevance of this pathway.

Combining the Dihydrofolate Reductase Protein-Fragment Complementation Assay with Gene Deletions to Establish Genotype-to-Phenotype Maps of Protein Complexes and Interaction Networks

Systematically measuring the impact of gene deletion on protein-protein interactions is a promising approach to reveal the structural bases of protein interaction networks and to allow a better understanding of how genotypes translate into phenotypes. Genetic and protein-interaction tools in yeast now allow us to explore this third dimension of protein-protein interaction networks. Because it is scalable and quantitative, the protein-fragment complementation assay (PCA) using dihydrofolate reductase (DHFR) as the reporter protein provides an exceptionally powerful tool for such a purpose. Here, we describe a fully automated protocol that combines DHFR PCA for protein-protein interaction measurement and synthetic genetic array (SGA) technology for introducing mutant and other alleles into PCA strains using genetic crosses. In this, PCA strains are crossed with strains carrying a gene deletion and SGA markers, and the recombinant haploid progeny are selected by SGA. The resulting haploid strains, each expressing a DHFR-fragment fusion protein in a gene-specific haploid deletion background, are crossed to measure the interaction between the two recombinant proteins by PCA in a diploid homozygous deletion background. This approach can be used to measure a single protein interaction in a large array of genetic backgrounds or a large number of protein interactions in a small number of genetic backgrounds.

Speciation driven by hybridization and chromosomal plasticity in a wild yeast

Hybridization is recognized as a powerful mechanism of speciation and a driving force in generating biodiversity. However, only few multicellular species, limited to a handful of plants and animals, have been shown to fulfil all the criteria of homoploid hybrid speciation. This lack of evidence could lead to the interpretation that speciation by hybridization has a limited role in eukaryotes, particularly in single-celled organisms. Laboratory experiments have revealed that fungi such as budding yeasts can rapidly develop reproductive isolation and novel phenotypes through hybridization, showing that in principle homoploid speciation could occur in nature. Here, we report a case of homoploid hybrid speciation in natural populations of the budding yeast Saccharomyces paradoxus inhabiting the North American forests. We show that the rapid evolution of chromosome architecture and an ecological context that led to secondary contact between nascent species drove the formation of an incipient hybrid species with a potentially unique ecological niche.

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.

Evolutionary rescue by compensatory mutations is constrained by genomic and environmental backgrounds

Since deleterious mutations may be rescued by secondary mutations during evolution, compensatory evolution could identify genetic solutions leading to therapeutic targets. Here, we tested this hypothesis and examined whether these solutions would be universal or would need to be adapted to one's genetic and environmental makeups. We performed experimental evolutionary rescue in a yeast disease model for the Wiskott–Aldrich syndrome in two genetic backgrounds and carbon sources. We found that multiple aspects of the evolutionary rescue outcome depend on the genotype, the environment, or a combination thereof. Specifically, the compensatory mutation rate and type, the molecular rescue mechanism, the genetic target, and the associated fitness cost varied across contexts. The course of compensatory evolution is therefore highly contingent on the initial conditions in which the deleterious mutation occurs. In addition, these results reveal biologically favored therapeutic targets for the Wiskott–Aldrich syndrome, including the target of an unrelated clinically approved drug. Our results experimentally illustrate the importance of epistasis and environmental evolutionary constraints that shape the adaptive landscape and evolutionary rate of molecular networks.

Dissecting the calcium-induced differentiation of human primary keratinocytes stem cells by integrative and structural network analyses

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products ('di-chromatic'), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation.

Systematic identification of signal integration by protein kinase A

Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein-protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA.

Genome-wide protein-protein interaction screening by protein-fragment complementation assay (PCA) in living cells

Proteins are the building blocks, effectors and signal mediators of cellular processes. A protein's function, regulation and localization often depend on its interactions with other proteins. Here, we describe a protocol for the yeast protein-fragment complementation assay (PCA), a powerful method to detect direct and proximal associations between proteins in living cells. The interaction between two proteins, each fused to a dihydrofolate reductase (DHFR) protein fragment, translates into growth of yeast strains in presence of the drug methotrexate (MTX). Differential fitness, resulting from different amounts of reconstituted DHFR enzyme, can be quantified on high-density colony arrays, allowing to differentiate interacting from non-interacting bait-prey pairs. The high-throughput protocol presented here is performed using a robotic platform that parallelizes mating of bait and prey strains carrying complementary DHFR-fragment fusion proteins and the survival assay on MTX. This protocol allows to systematically test for thousands of protein-protein interactions (PPIs) involving bait proteins of interest and offers several advantages over other PPI detection assays, including the study of proteins expressed from their endogenous promoters without the need for modifying protein localization and for the assembly of complex reporter constructs.

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.

Molecular mechanisms of paralogous compensation and the robustness of cellular networks

Robustness is the ability of a system to maintain its function despite environmental or genetic perturbation. Genetic robustness is a key emerging property of living systems and is achieved notably by the presence of partially redundant parts that result from gene duplication. Functional overlap between paralogs allows them to compensate for each other's loss, as commonly revealed by aggravating genetic interactions. However, the molecular mechanisms linking the genotype (loss of function of a gene) to the phenotype (genetic buffering by a paralog) are still poorly understood and the molecular aspects of this compensation are rarely addressed in studies of gene duplicates. Here, we review molecular mechanisms of functional compensation between paralogous genes, many of which from studies that were not meant to study this phenomenon. We propose a standardized terminology and, depending on whether or not the molecular behavior of the intact gene is modified in response to the deletion of its paralog, we classify mechanisms of compensation into passive and active events. We further describe three non-exclusive mechanisms of active paralogous compensation for which there is evidence in the literature: changes in abundance, in localization, and in protein interactions. This review will serve as a framework for the genetic and molecular analysis of paralogous compensation, one of the universal features of genetic systems.

Modulation of the yeast protein interactome in response to DNA damage

Cells deploy diverse mechanisms to physiologically adapt to potentially detrimental perturbations. These mechanisms include changes in the organization of protein-protein interaction networks (PINs). Most PINs characterized to date are portrayed in a single environmental condition and are thus likely to miss important connections among biological processes. In this report, we show that the yeast DHFR-PCA on high-density arrays allows to detects modulations of protein-protein interactions (PPIs) in different conditions by testing more than 1000 PPIs in standard and in a drug-inducing DNA damage conditions. We identify 156 PPIs that show significant modulation in response to DNA damage. We provide evidence that modulated PPIs involve essential genes (NOP7, EXO84 and LAS17) playing critical roles in response to DNA damage. Additionally, we show that a significant proportion of PPI changes are likely explained by changes in protein localization and, to a lesser extent, protein abundance. The protein interaction modules affected by changing PPIs support the role of mRNA stability and translation, protein degradation and ubiquitylation and the regulation of the actin cytoskeleton in response to DNA damage. Overall, we provide a valuable tool and dataset for the study of the rewiring of PINs in response to environmental perturbations.

BIOLOGICAL SIGNIFICANCE

We show that the DHFR-PCA is a high-throughput method that allows the detection of changes in PPIs associated with different environmental conditions using DNA damage response as a testbed. We provide a valuable resource for the study of DNA damage in eukaryotic cells. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Reverse PCA, a systematic approach for identifying genes important for the physical interaction between protein pairs

Protein-protein interactions (PPIs) are of central importance for many areas of biological research. Several complementary high-throughput technologies have been developed to study PPIs. The wealth of information that emerged from these technologies led to the first maps of the protein interactomes of several model organisms. Many changes can occur in protein complexes as a result of genetic and biochemical perturbations. In the absence of a suitable assay, such changes are difficult to identify, and thus have been poorly characterized. In this study, we present a novel genetic approach (termed “reverse PCA”) that allows the identification of genes whose products are required for the physical interaction between two given proteins. Our assay starts with a yeast strain in which the interaction between two proteins of interest can be detected by resistance to the drug, methotrexate, in the context of the protein-fragment complementation assay (PCA). Using synthetic genetic array (SGA) technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify those mutations that disrupt the physical interaction of interest. We were able to successfully validate this novel approach by identifying mutants that dissociate the conserved interaction between Cia2 and Mms19, two proteins involved in Iron-Sulfur protein biogenesis and genome stability. This method will facilitate the study of protein structure-function relationships, and may help in elucidating the mechanisms that regulate PPIs.

Protein–protein interactions (PPI) occur when two or more proteins bind together to form large molecular machines. The importance of PPIs led to the development of multitude technologies to detect them, and to the first maps of the protein interactomes. One important challenge in biology is to understand how protein complexes respond to genetic perturbations; however, in the absence of a suitable assay, such changes have been poorly characterized. Here, we present a novel systematic genetic approach (termed “reverse PCA”), that demonstrates how the yeast protein complementation assay (PCA), coupled with the synthetic genetic array (SGA) technology may be used to study the modulation of protein–protein interactions in-vivo in response to genetic perturbations. Our assay starts with a yeast strain in which the interaction between given proteins can be detected by resistance to the drug, methotrexate. Using the SGA technology, we can systematically identify yeast mutants that reverse this interaction. We were able to successfully validate this approach by identifying mutants that dissociate the conserved interaction between Cia2 and Mms19, two proteins involved in Iron-Sulfur protein biogenesis and genome stability. This method will facilitate the study of protein structure-function relationships, and elucidate the mechanisms that regulate PPIs.