A consensus of core protein complex compositions for Saccharomyces cerevisiae

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

A positive statistical benchmark to assess network agreement

Current computational methods for validating experimental network datasets compare overlap, i.e., shared links, with a reference network using a negative benchmark. However, this fails to quantify the level of agreement between the two networks. To address this, we propose a positive statistical benchmark to determine the maximum possible overlap between networks. Our approach can efficiently generate this benchmark in a maximum entropy framework and provides a way to assess whether the observed overlap is significantly different from the best-case scenario. We introduce a normalized overlap score, Normlap, to enhance comparisons between experimental networks. As an application, we compare molecular and functional networks, resulting in an agreement network of human as well as yeast network datasets. The Normlap score can improve the comparison between experimental networks by providing a computational alternative to network thresholding and validation.

Multiple intermolecular interactions facilitate rapid evolution of essential genes

Essential genes are commonly assumed to function in basic cellular processes and to change slowly. However, it remains unclear whether all essential genes are similarly conserved or if their evolutionary rates can be accelerated by specific factors. To address these questions, we replaced 86 essential genes of Saccharomyces cerevisiae with orthologues from four other species that diverged from S. cerevisiae about 50, 100, 270 and 420 Myr ago. We identify a group of fast-evolving genes that often encode subunits of large protein complexes, including anaphase-promoting complex/cyclosome (APC/C). Incompatibility of fast-evolving genes is rescued by simultaneously replacing interacting components, suggesting it is caused by protein co-evolution. Detailed investigation of APC/C further revealed that co-evolution involves not only primary interacting proteins but also secondary ones, suggesting the evolutionary impact of epistasis. Multiple intermolecular interactions in protein complexes may provide a microenvironment facilitating rapid evolution of their subunits.

Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast

Although many prokaryotes have glycolysis alternatives, it's considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP₇) levels. 5-InsP₇ levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism.

Proteotoxicity caused by perturbed protein complexes underlies hybrid incompatibility in yeast

Dobzhansky–Muller incompatibilities represent a major driver of reproductive isolation between species. They are caused when interacting components encoded by alleles from different species cannot function properly when mixed. At incipient stages of speciation, complex incompatibilities involving multiple genetic loci with weak effects are frequently observed, but the underlying mechanisms remain elusive. Here we show perturbed proteostasis leading to compromised mitosis and meiosis in Saccharomyces cerevisiae hybrid lines carrying one or two chromosomes from Saccharomyces bayanus var. uvarum. Levels of proteotoxicity are correlated with the number of protein complexes on replaced chromosomes. Proteomic approaches reveal that multi-protein complexes with subunits encoded by replaced chromosomes tend to be unstable. Furthermore, hybrid defects can be alleviated or aggravated, respectively, by up- or down-regulating the ubiquitin-proteasomal degradation machinery, suggesting that destabilized complex subunits overburden the proteostasis machinery and compromise hybrid fitness. Our findings reveal the general role of impaired protein complex assembly in complex incompatibilities.

Hybrid incompatibility can be an important element of reproductive isolation and speciation. Using chromosome replacement lines of yeast, the authors show that perturbed proteostasis caused by destabilized hybrid protein complexes may represent a general mechanism of hybrid incompatibility.

Rapid intraspecies evolution of fitness effects of yeast genes

Organisms within species have numerous genetic and phenotypic variations. Growing evidences show intraspecies variation of mutant phenotypes may be more complicated than expected. Current studies on intraspecies variations of mutant phenotypes are limited to just a few strains. This study investigated the intraspecies variation of fitness effects of 5,630 gene mutants in ten Saccharomyces cerevisiae strains using CRISPR–Cas9 screening. We found that the variability of fitness effects induced by gene disruptions is very large across different strains. Over 75% of genes affected cell fitness in a strain-specific manner to varying degrees. The strain specificity of the fitness effect of a gene is related to its evolutionary and functional properties. Subsequent analysis revealed that younger genes, especially those newly acquired in S. cerevisiae species, are more likely to be strongly strain-specific. Intriguingly, there seems to exist a ceiling of fitness effect size for strong strain-specific genes, and among them, the newly acquired genes are still evolving and have yet to reach this ceiling. Additionally, for a large proportion of protein complexes, the strain specificity profile is inconsistent among genes encoding the same complex. Taken together, these results offer a genome-wide map of intraspecies variation for fitness effect as a mutant phenotype and provide an updated insight on intraspecies phenotypic evolution.

A genome-scale yeast library with inducible expression of individual genes

The ability to switch a gene from off to on and monitor dynamic changes provides a powerful approach for probing gene function and elucidating causal regulatory relationships. Here, we developed and characterized YETI (Yeast Estradiol strains with Titratable Induction), a collection in which > 5,600 yeast genes are engineered for transcriptional inducibility with single-gene precision at their native loci and without plasmids. Each strain contains SGA screening markers and a unique barcode, enabling high-throughput genetics. We characterized YETI using growth phenotyping and BAR-seq screens, and we used a YETI allele to identify the regulon of Rof1, showing that it acts to repress transcription. We observed that strains with inducible essential genes that have low native expression can often grow without inducer. Analysis of data from eukaryotic and prokaryotic systems shows that native expression is a variable that can bias promoter-perturbing screens, including CRISPRi. We engineered a second expression system, Z3 EB42, that gives lower expression than Z3 EV, a feature enabling conditional activation and repression of lowly expressed essential genes that grow without inducer in the YETI library.

The box C/D snoRNP assembly factor Bcd1 interacts with the histone chaperone Rtt106 and controls its transcription dependent activity

Biogenesis of eukaryotic box C/D small nucleolar ribonucleoproteins initiates co-transcriptionally and requires the action of the assembly machinery including the Hsp90/R2TP complex, the Rsa1p:Hit1p heterodimer and the Bcd1 protein. We present genetic interactions between the Rsa1p-encoding gene and genes involved in chromatin organization including RTT106 that codes for the H3-H4 histone chaperone Rtt106p controlling H3K56ac deposition. We show that Bcd1p binds Rtt106p and controls its transcription-dependent recruitment by reducing its association with RNA polymerase II, modulating H3K56ac levels at gene body. We reveal the 3D structures of the free and Rtt106p-bound forms of Bcd1p using nuclear magnetic resonance and X-ray crystallography. The interaction is also studied by a combination of biophysical and proteomic techniques. Bcd1p interacts with a region that is distinct from the interaction interface between the histone chaperone and histone H3. Our results are evidence for a protein interaction interface for Rtt106p that controls its transcription-associated activity.

Biogenesis of small nucleolar RNAs ribonucleoproteins (snoRNPs) requires dedicated assembly machinery. Here, the authors show that a subset of snoRNP assembly factors interacts, genetically or directly, with factors modulating chromatin architecture, suggesting a link between ribosome formation and chromatin functions.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.

Identification of a novel gene controlling homothallism in the yeast Kazachstania naganishii isolated in Japan

A novel gene controlling homothallic life cycle was identified in the yeast Kazachstania naganishii isolated in Japan. This gene was isolated by means of complementing a mutation, mti1, which had led to heterothallism from original homothallism in the yeast. The configuration of original mutation in MTI1 gene revealed that a truncated product is formed due to occurrence of a stop codon by a nucleotide insertion. When the gene was disrupted with a marker, the disruptant spore clone was haploid and stably heterothallic. Disfunction of the gene caused inability to self-diploidize due to defect of mating-type interconversion. The gene MTI1 (for Mating Type Interconversion) is a weak homolog of the Saccharomyces cerevisiae VID22/ENV11, which has been reported to function in vacuolar protein processing. K. naganishii has a gene representing significant homology with the HO gene of S. cerevisiae on chromosome V, which has not been clarified to be involved in regulation of life cycle in K. naganishii. The MTI1 gene defined in this study is located on K. naganishii chromosome IV and does not represent significant homology to the above ScHO-like gene and any other genes concerning life cycles of yeasts. From the viewpoint of gene evolution, it is extremely interesting that the MTI1 gene is a new type of gene controlling homothallism in addition to an HO-type gene, leading to discovery of an unknown mechanism regulating life cycles in yeasts.

Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes

Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

Extraction and Integration of Genetic Networks from Short-Profile Omic Data Sets

Mass spectrometry technologies are widely used in the fields of ionomics and metabolomics to simultaneously profile the intracellular concentrations of, e.g., amino acids or elements in genome-wide mutant libraries. These molecular or sub-molecular features are generally non-Gaussian and their covariance reveals patterns of correlations that reflect the system nature of the cell biochemistry and biology. Here, we introduce two similarity measures, the Mahalanobis cosine and the hybrid Mahalanobis cosine, that enforce information from the empirical covariance matrix of omics data from high-throughput screening and that can be used to quantify similarities between the profiled features of different mutants. We evaluate the performance of these similarity measures in the task of inferring and integrating genetic networks from short-profile ionomics/metabolomics data through an analysis of experimental data sets related to the ionome and the metabolome of the model organism S. cerevisiae. The study of the resulting ionome–metabolome Saccharomyces cerevisiae multilayer genetic network, which encodes multiple omic-specific levels of correlations between genes, shows that the proposed measures can provide an alternative description of relations between biological processes when compared to the commonly used Pearson’s correlation coefficient and have the potential to guide the construction of novel hypotheses on the function of uncharacterised genes.

Decoupling gene functions from knockout effects by evolutionary analyses

Genic functions have long been confounded by pleiotropic mutational effects. To understand such genetic effects, we examine HAP4, a well-studied transcription factor in Saccharomyces cerevisiae that functions by forming a tetramer with HAP2, HAP3 and HAP5. Deletion of HAP4 results in highly pleiotropic gene expression responses, some of which are clustered in related cellular processes (clustered effects) while most are distributed randomly across diverse cellular processes (distributed effects). Strikingly, the distributed effects that account for much of HAP4 pleiotropy tend to be non-heritable in a population, suggesting they have few evolutionary consequences. Indeed, these effects are poorly conserved in closely related yeasts. We further show substantial overlaps of clustered effects, but not distributed effects, among the four genes encoding the HAP2/3/4/5 tetramer. This pattern holds for other biochemically characterized yeast protein complexes or metabolic pathways. Examination of a set of cell morphological traits of the deletion lines yields consistent results. Hence, only some deletion effects of a gene support related biochemical understandings with the rest being often pleiotropic and evolutionarily decoupled from the gene's normal functions. This study suggests a new framework for reverse genetic analysis.

Dimensionality reduction by UMAP to visualize physical and genetic interactions

Dimensionality reduction is often used to visualize complex expression profiling data. Here, we use the Uniform Manifold Approximation and Projection (UMAP) method on published transcript profiles of 1484 single gene deletions of Saccharomyces cerevisiae. Proximity in low-dimensional UMAP space identifies groups of genes that correspond to protein complexes and pathways, and finds novel protein interactions, even within well-characterized complexes. This approach is more sensitive than previous methods and should be broadly useful as additional transcriptome datasets become available for other organisms.

Cotranslational Folding of Proteins on the Ribosome

Many proteins in the cell fold cotranslationally within the restricted space of the polypeptide exit tunnel or at the surface of the ribosome. A growing body of evidence suggests that the ribosome can alter the folding trajectory in many different ways. In this review, we summarize the recent examples of how translation affects folding of single-domain, multiple-domain and oligomeric proteins. The vectorial nature of translation, the spatial constraints of the exit tunnel, and the electrostatic properties of the ribosome-nascent peptide complex define the onset of early folding events. The ribosome can facilitate protein compaction, induce the formation of intermediates that are not observed in solution, or delay the onset of folding. Examples of single-domain proteins suggest that early compaction events can define the folding pathway for some types of domain structures. Folding of multi-domain proteins proceeds in a domain-wise fashion, with each domain having its role in stabilizing or destabilizing neighboring domains. Finally, the assembly of protein complexes can also begin cotranslationally. In all these cases, the ribosome helps the nascent protein to attain a native fold and avoid the kinetic traps of misfolding.

The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs

Gene duplication is a driver of the evolution of new functions. The duplication of genes encoding homomeric proteins leads to the formation of homomers and heteromers of paralogs, creating new complexes after a single duplication event. The loss of these heteromers may be required for the two paralogs to evolve independent functions. Using yeast as a model, we find that heteromerization is frequent among duplicated homomers and correlates with functional similarity between paralogs. Using in silico evolution, we show that for homomers and heteromers sharing binding interfaces, mutations in one paralog can have structural pleiotropic effects on both interactions, resulting in highly correlated responses of the complexes to selection. Therefore, heteromerization could be preserved indirectly due to selection for the maintenance of homomers, thus slowing down functional divergence between paralogs. We suggest that paralogs can overcome the obstacle of structural pleiotropy by regulatory evolution at the transcriptional and post-translational levels.

The expression tractability of biological traits shaped by natural selection

Understanding how gene expression is translated to phenotype is central to modern molecular biology, and the success is contingent on the intrinsic tractability of the specific traits under examination. However, an a priori estimate of trait tractability from the perspective of gene expression is unavailable. Motivated by the concept of entropy in a thermodynamic system, we here propose such an estimate (S_T) by gauging the number (N) of expression states that underlie the same trait abnormality, with large S_T corresponding to large N. By analyzing over 200 yeast morphological traits, we show that S_T predicts the tractability of an expression-trait relationship. We further show that S_T is ultimately determined by natural selection, which builds co-regulated gene modules to minimize possible expression states.

Mechanisms of Cotranslational Maturation of Newly Synthesized Proteins

The timely production of functional proteins is of critical importance for the biological activity of cells. To reach the functional state, newly synthesized polypeptides have to become enzymatically processed, folded, and assembled into oligomeric complexes and, for noncytosolic proteins, translocated across membranes. Key activities of these processes occur cotranslationally, assisted by a network of machineries that transiently engage nascent polypeptides at distinct phases of translation. The sequence of events is tuned by intrinsic features of the nascent polypeptides and timely association of factors with the translating ribosome. Considering the dynamics of translation, the heterogeneity of cellular proteins, and the diversity of interaction partners, it is a major cellular achievement that these processes are temporally and spatially so precisely coordinated, minimizing the generation of damaged proteins. This review summarizes the current progress we have made toward a comprehensive understanding of the cotranslational interactions of nascent chains, which pave the way to their functional state.

Med15: Glutamine-Rich Mediator Subunit with Potential for Plasticity

The Mediator complex is required for basal activity of the RNA polymerase (Pol) II transcriptional apparatus and for responsiveness to some activator proteins. Med15, situated in the Mediator tail, plays a role in transmitting regulatory information from distant DNA-bound transcription factors to the transcriptional apparatus poised at promoters. Yeast Med15 and its orthologs share an unusual, glutamine-rich amino acid composition. Here, we discuss this sequence feature and the tendency of polyglutamine tracts to vary in length among strains of Saccharomyces cerevisiae, and we propose that different polyglutamine tract lengths may be adaptive within certain domestication habitats.

A role for the unfolded protein response stress sensor ERN1 in regulating the response to MEK inhibitors in KRAS mutant colon cancers

Background

Mutations in KRAS are frequent in human cancer, yet effective targeted therapeutics for these cancers are still lacking. Attempts to drug the MEK kinases downstream of KRAS have had limited success in clinical trials. Understanding the specific genomic vulnerabilities of KRAS-driven cancers may uncover novel patient-tailored treatment options.

Methods

We first searched for synthetic lethal (SL) genetic interactions with mutant RAS in yeast with the ultimate aim to identify novel cancer-specific targets for therapy. Our method used selective ploidy ablation, which enables replication of cancer-specific gene expression changes in the yeast gene disruption library. Second, we used a genome-wide CRISPR/Cas9-based genetic screen in KRAS mutant human colon cancer cells to understand the mechanistic connection between the synthetic lethal interaction discovered in yeast and downstream RAS signaling in human cells.

Results

We identify loss of the endoplasmic reticulum (ER) stress sensor IRE1 as synthetic lethal with activated RAS mutants in yeast. In KRAS mutant colorectal cancer cell lines, genetic ablation of the human ortholog of IRE1, ERN1, does not affect growth but sensitizes to MEK inhibition. However, an ERN1 kinase inhibitor failed to show synergy with MEK inhibition, suggesting that a non-kinase function of ERN1 confers MEK inhibitor resistance. To investigate how ERN1 modulates MEK inhibitor responses, we performed genetic screens in ERN1 knockout KRAS mutant colon cancer cells to identify genes whose inactivation confers resistance to MEK inhibition. This genetic screen identified multiple negative regulators of JUN N-terminal kinase (JNK) /JUN signaling. Consistently, compounds targeting JNK/MAPK8 or TAK1/MAP3K7, which relay signals from ERN1 to JUN, display synergy with MEK inhibition.

Conclusions

We identify the ERN1-JNK-JUN pathway as a novel regulator of MEK inhibitor response in KRAS mutant colon cancer. The notion that multiple signaling pathways can activate JUN may explain why KRAS mutant tumor cells are traditionally seen as highly refractory to MEK inhibitor therapy. Our findings emphasize the need for the development of new therapeutics targeting JUN activating kinases, TAK1 and JNK, to sensitize KRAS mutant cancer cells to MEK inhibitors.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0600-z) contains supplementary material, which is available to authorized users.

Nonsense-mediated mRNA decay involves two distinct Upf1-bound complexes

Nonsense-mediated mRNA decay (NMD) is a translation-dependent RNA degradation pathway involved in many cellular pathways and crucial for telomere maintenance and embryo development. Core NMD factors Upf1, Upf2 and Upf3 are conserved from yeast to mammals, but a universal NMD model is lacking. We used affinity purification coupled with mass spectrometry and an improved data analysis protocol to characterize the composition and dynamics of yeast NMD complexes in yeast (112 experiments). Unexpectedly, we identified two distinct complexes associated with Upf1: Upf1-23 (Upf1, Upf2, Upf3) and Upf1-decapping Upf1-decapping contained the mRNA decapping enzyme, together with Nmd4 and Ebs1, two proteins that globally affected NMD and were critical for RNA degradation mediated by the Upf1 C-terminal helicase region. The fact that Nmd4 association with RNA was partially dependent on Upf1-23 components and the similarity between Nmd4/Ebs1 and mammalian Smg5-7 proteins suggest that NMD operates through conserved, successive Upf1-23 and Upf1-decapping complexes. This model can be extended to accommodate steps that are missing in yeast, to serve for further mechanistic studies of NMD in eukaryotes.

Cotranslational assembly of protein complexes in eukaryotes revealed by ribosome profiling

The folding of newly synthesized proteins to the native state is a major challenge within the crowded cellular environment, as non-productive interactions can lead to misfolding, aggregation and degradation1. Cells cope with this challenge by coupling synthesis with polypeptide folding and by using molecular chaperones to safeguard folding cotranslationally2. However, although most of the cellular proteome forms oligomeric assemblies3, little is known about the final step of folding: the assembly of polypeptides into complexes. In prokaryotes, a proof-of-concept study showed that the assembly of heterodimeric luciferase is an organized cotranslational process that is facilitated by spatially confined translation of the subunits encoded on a polycistronic mRNA4. In eukaryotes, however, fundamental differences—such as the rarity of polycistronic mRNAs and different chaperone constellations—raise the question of whether assembly is also coordinated with translation. Here we provide a systematic and mechanistic analysis of the assembly of protein complexes in eukaryotes using ribosome profiling. We determined the in vivo interactions of the nascent subunits from twelve hetero-oligomeric protein complexes of Saccharomyces cerevisiae at near-residue resolution. We find nine complexes assemble cotranslationally; the three complexes that do not show cotranslational interactions are regulated by dedicated assembly chaperones5–7. Cotranslational assembly often occurs uni-directionally, with one fully synthesized subunit engaging its nascent partner subunit, thereby counteracting its propensity for aggregation. The onset of cotranslational subunit association coincides directly with the full exposure of the nascent interaction domain at the ribosomal tunnel exit. The ribosome-associated Hsp70 chaperone Ssb8 is coordinated with assembly. Ssb transiently engages partially synthesized interaction domains and then dissociates before the onset of partner subunit association, presumably to prevent premature assembly interactions. Our study shows that cotranslational subunit association is a prevalent mechanism for the assembly of hetero-oligomers in yeast and indicates that translation, folding and assembly of protein complexes are integrated processes in eukaryotes.

Characterization of the Interaction between Arginine Methyltransferase Hmt1 and Its Substrate Npl3: Use of Multiple Cross-Linkers, Mass Spectrometric Approaches, and Software Platforms

This study investigated the enzyme-substrate interaction between Saccharomyces cerevisiae arginine methyltransferase Hmt1p and nucleolar protein Npl3p, using chemical cross linking/mass spectrometry (XL/MS). We show that XL/MS can capture transient interprotein interactions that occur during the process of methylation, involving a disordered region in Npl3p with tandem SRGG repeats, and we confirm that Hmt1p and Npl3p exist as homomultimers. Additionally, the study investigated the interdependencies between variables of an XL/MS experiment that lead to the identification of identical or different cross-linked peptides. We report that there are substantial benefits, in terms of biologically relevant cross-links identified, that result from the use of two mass-spectrometry-cleavable cross-linkers [disuccinimido sulfoxide (DSSO) and disuccinimido dibutyric urea (DSBU)], two fragmentation approaches [collision-induced dissociation and electron-transfer dissociation (CID+ETD)] and stepped high-energy collision dissociation (HCD)], and two programs (MeroX and XlinkX). We also show that there are specific combinations of XL/MS methods that are more successful than others for the two proteins investigated here; these are explored in detail in the text. Data are available via ProteomeXchange with identifier PXD008348.

Drug toxicity profiling of a Saccharomyces cerevisiae deubiquitinase deletion panel shows that acetaminophen mimics tyrosine

Post-translational protein modification by addition or removal of the small polypeptide ubiquitin is involved in a range of critical cellular processes, like proteasomal protein degradation, DNA repair, gene expression, internalization of membrane proteins, and drug sensitivity. We recently identified genes important for acetaminophen (APAP) toxicity in a comprehensive screen and our findings suggested that a small set of yeast strains carrying deletions of ubiquitin-related genes can be informative for drug toxicity profiling. In yeast, approximately 20 different deubiquitinating enzymes (DUBs) have been identified, of which only one is essential for viability. We investigated whether the toxicity profile of DUB deletion yeast strains would be informative about the toxicological mode of action of APAP. A set of DUB deletion strains was tested for sensitivity and resistance to a diverse series of compounds, including APAP, quinine, ibuprofen, rapamycin, cycloheximide, cadmium, peroxide and amino acids and a cluster analysis was performed. Most DUB deletion strains showed an altered growth pattern when exposed to these compounds by being either more sensitive or more resistant than WT. Toxicity profiling of the DUB strains revealed a remarkable overlap between the amino acid tyrosine and acetaminophen (APAP), but not its stereoisomer AMAP. Furthermore, co-exposure of cells to both APAP and tyrosine showed an enhancement of the cellular growth inhibition, suggesting that APAP and tyrosine have a similar mode of action.

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.

Trz1, the long form RNase Z from yeast, forms a stable heterohexamer with endonuclease Nuc1 and mutarotase

Proteomic studies have established that Trz1, Nuc1 and mutarotase form a complex in yeast. Trz1 is a β-lactamase-type RNase composed of two β-lactamase-type domains connected by a long linker that is responsible for the endonucleolytic cleavage at the 3'-end of tRNAs during the maturation process (RNase Z activity); Nuc1 is a dimeric mitochondrial nuclease involved in apoptosis, while mutarotase (encoded by YMR099C) catalyzes the conversion between the α- and β-configuration of glucose-6-phosphate. Using gel filtration, small angle X-ray scattering and electron microscopy, we demonstrated that Trz1, Nuc1 and mutarotase form a very stable heterohexamer, composed of two copies of each of the three subunits. A Nuc1 homodimer is at the center of the complex, creating a two-fold symmetry and interacting with both Trz1 and mutarotase. Enzymatic characterization of the ternary complex revealed that the activities of Trz1 and mutarotase are not affected by complex formation, but that the Nuc1 activity is completely inhibited by mutarotase and partially by Trz1. This suggests that mutarotase and Trz1 might be regulators of the Nuc1 apoptotic nuclease activity.

A Functional Link Between Bir1 and the Saccharomyces cerevisiae Ctf19 Kinetochore Complex Revealed Through Quantitative Fitness Analysis

The chromosomal passenger complex (CPC) is a key regulator of eukaryotic cell division, consisting of the protein kinase Aurora B/Ipl1 in association with its activator (INCENP/Sli15) and two additional proteins (Survivin/Bir1 and Borealin/Nbl1). Here, we report a genome-wide genetic interaction screen in Saccharomyces cerevisiae using the bir1-17 mutant, identifying through quantitative fitness analysis deletion mutations that act as enhancers and suppressors. Gene knockouts affecting the Ctf19 kinetochore complex were identified as the strongest enhancers of bir1-17, while mutations affecting the large ribosomal subunit or the mRNA nonsense-mediated decay pathway caused strong phenotypic suppression. Thus, cells lacking a functional Ctf19 complex become highly dependent on Bir1 function and vice versa. The negative genetic interaction profiles of bir1-17 and the cohesin mutant mcd1-1 showed considerable overlap, underlining the strong functional connection between sister chromatid cohesion and chromosome biorientation. Loss of some Ctf19 components, such as Iml3 or Chl4, impacted differentially on bir1-17 compared with mutations affecting other CPC components: despite the synthetic lethality shown by either iml3∆ or chl4∆ in combination with bir1-17, neither gene knockout showed any genetic interaction with either ipl1-321 or sli15-3 Our data therefore imply a specific functional connection between the Ctf19 complex and Bir1 that is not shared with Ipl1.

Capturing protein communities by structural proteomics in a thermophilic eukaryote

The arrangement of proteins into complexes is a key organizational principle for many cellular functions. Although the topology of many complexes has been systematically analyzed in isolation, their molecular sociology in situ remains elusive. Here, we show that crude cellular extracts of a eukaryotic thermophile, Chaetomium thermophilum, retain basic principles of cellular organization. Using a structural proteomics approach, we simultaneously characterized the abundance, interactions, and structure of a third of the C. thermophilum proteome within these extracts. We identified 27 distinct protein communities that include 108 interconnected complexes, which dynamically associate with each other and functionally benefit from being in close proximity in the cell. Furthermore, we investigated the structure of fatty acid synthase within these extracts by cryoEM and this revealed multiple, flexible states of the enzyme in adaptation to its association with other complexes, thus exemplifying the need for in situ studies. As the components of the captured protein communities are known—at both the protein and complex levels—this study constitutes another step forward toward a molecular understanding of subcellular organization.

No Evidence That Protein Noise-Induced Epigenetic Epistasis Constrains Gene Expression Evolution

Changes in gene expression can affect phenotypes and therefore both its level and stochastic variability are frequently under selection. It has recently been proposed that epistatic interactions influence gene expression evolution: gene pairs where simultaneous knockout is more deleterious than expected should evolve reduced expression noise to avoid concurrent low expression of both proteins. In apparent support, yeast genes with many epistatic partners have low expression variation both among isogenic individuals and between species. However, the specific predictions and basic assumptions of this verbal model remain untested. Using bioinformatics analysis, we first demonstrate that the model's predictions are unsupported by available large-scale data. Based on quantitative biochemical modeling, we then show that epistasis between expression reductions (epigenetic epistasis) is not expected to aggravate the fitness cost of stochastic expression, which is in sharp contrast to the verbal argument. This nonintuitive result can be readily explained by the typical diminishing return of fitness on gene activity and by the fact that expression noise not only decreases but also increases the abundance of proteins. Overall, we conclude that stochastic variation in epistatic partners is unlikely to drive noise minimization or constrain gene expression divergence on a genomic scale.

Growth condition dependency is the major cause of non-responsiveness upon genetic perturbation

Investigating the role and interplay between individual proteins in biological processes is often performed by assessing the functional consequences of gene inactivation or removal. Depending on the sensitivity of the assay used for determining phenotype, between 66% (growth) and 53% (gene expression) of Saccharomyces cerevisiae gene deletion strains show no defect when analyzed under a single condition. Although it is well known that this non-responsive behavior is caused by different types of redundancy mechanisms or by growth condition/cell type dependency, it is not known what the relative contribution of these different causes is. Understanding the underlying causes of and their relative contribution to non-responsive behavior upon genetic perturbation is extremely important for designing efficient strategies aimed at elucidating gene function and unraveling complex cellular systems. Here, we provide a systematic classification of the underlying causes of and their relative contribution to non-responsive behavior upon gene deletion. The overall contribution of redundancy to non-responsive behavior is estimated at 29%, of which approximately 17% is due to homology-based redundancy and 12% is due to pathway-based redundancy. The major determinant of non-responsiveness is condition dependency (71%). For approximately 14% of protein complexes, just-in-time assembly can be put forward as a potential mechanistic explanation for how proteins can be regulated in a condition dependent manner. Taken together, the results underscore the large contribution of growth condition requirement to non-responsive behavior, which needs to be taken into account for strategies aimed at determining gene function. The classification provided here, can also be further harnessed in systematic analyses of complex cellular systems.

A global genetic interaction network maps a wiring diagram of cellular function

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

A quantitative genome-wide RNAi screen in C. elegans for antifungal innate immunity genes

BACKGROUND

Caenorhabditis elegans has emerged over the last decade as a useful model for the study of innate immunity. Its infection with the pathogenic fungus Drechmeria coniospora leads to the rapid up-regulation in the epidermis of genes encoding antimicrobial peptides. The molecular basis of antimicrobial peptide gene regulation has been previously characterized through forward genetic screens. Reverse genetics, based on RNAi, provide a complementary approach to dissect the worm's immune defenses.

RESULTS

We report here the full results of a quantitative whole-genome RNAi screen in C. elegans for genes involved in regulating antimicrobial peptide gene expression. The results will be a valuable resource for those contemplating similar RNAi-based screens and also reveal the limitations of such an approach. We present several strategies, including a comprehensive class clustering method, to overcome these limitations and which allowed us to characterize the different steps of the interaction between C. elegans and the fungus D. coniospora, leading to a complete description of the MAPK pathway central to innate immunity in C. elegans. The results further revealed a cross-tissue signaling, triggered by mitochondrial dysfunction in the intestine, that suppresses antimicrobial peptide gene expression in the nematode epidermis.

CONCLUSIONS

Overall, our results provide an unprecedented system's level insight into the regulation of C. elegans innate immunity. They represent a significant contribution to our understanding of host defenses and will lead to a better comprehension of the function and evolution of animal innate immunity.

A genetic network that suppresses genome rearrangements in Saccharomyces cerevisiae and contains defects in cancers

Gross chromosomal rearrangements (GCRs) play an important role in human diseases, including cancer. The identity of all Genome Instability Suppressing (GIS) genes is not currently known. Here multiple Saccharomyces cerevisiae GCR assays and query mutations were crossed into arrays of mutants to identify progeny with increased GCR rates. One hundred eighty two GIS genes were identified that suppressed GCR formation. Another 438 cooperatively acting GIS genes were identified that were not GIS genes, but suppressed the increased genome instability caused by individual query mutations. Analysis of TCGA data using the human genes predicted to act in GIS pathways revealed that a minimum of 93% of ovarian and 66% of colorectal cancer cases had defects affecting one or more predicted GIS gene. These defects included loss-of-function mutations, copy-number changes associated with reduced expression, and silencing. In contrast, acute myeloid leukaemia cases did not appear to have defects affecting the predicted GIS genes.

Here, Richard Kolodner and colleagues use assays in Saccharomyces cerevisiae to identify 182 genetic modifiers of gross chromosomal rearrangements (GCRs). They also compared these Genome Instability Suppressing (GIS) genes and pathways in human cancer genome, and found many ovarian and colorectal cancer cases have alterations to GIS pathways.

Multiplexed, Proteome-Wide Protein Expression Profiling: Yeast Deubiquitylating Enzyme Knockout Strains

Characterizing a protein's function often requires a description of the cellular state in its absence. Multiplexing in mass spectrometry-based proteomics has now achieved the ability to globally measure protein expression levels in yeast from 10 cell states simultaneously. We applied this approach to quantify expression differences in wild type and nine deubiquitylating enzyme (DUB) knockout strains with the goal of creating "information networks" that might provide deeper, mechanistic insights into a protein's biological role. In total, more than 3700 proteins were quantified with high reproducibility across three biological replicates (30 samples in all). DUB mutants demonstrated different proteomics profiles, consistent with distinct roles for each family member. These included differences in total ubiquitin levels and specific chain linkages. Moreover, specific expression changes suggested novel functions for several DUB family members. For instance, the ubp3Δ mutant showed large expression changes for members of the cytochrome C oxidase complex, consistent with a role for Ubp3 in mitochondrial regulation. Several DUBs also showed broad expression changes for phosphate transporters as well as other components of the inorganic phosphate signaling pathway, suggesting a role for these DUBs in regulating phosphate metabolism. These data highlight the potential of multiplexed proteome-wide analyses for biological investigation and provide a framework for further study of the DUB family. Our methods are readily applicable to the entire collection of yeast deletion mutants and may help facilitate systematic analysis of yeast and other organisms.

Acetylome profiling reveals overlap in the regulation of diverse processes by sirtuins, gcn5, and esa1

Although histone acetylation and deacetylation machineries (HATs and HDACs) regulate important aspects of cell function by targeting histone tails, recent work highlights that non-histone protein acetylation is also pervasive in eukaryotes. Here, we use quantitative mass-spectrometry to define acetylations targeted by the sirtuin family, previously implicated in the regulation of non-histone protein acetylation. To identify HATs that promote acetylation of these sites, we also performed this analysis in gcn5 (SAGA) and esa1 (NuA4) mutants. We observed strong sequence specificity for the sirtuins and for each of these HATs. Although the Gcn5 and Esa1 consensus sequences are entirely distinct, the sirtuin consensus overlaps almost entirely with that of Gcn5, suggesting a strong coordination between these two regulatory enzymes. Furthermore, by examining global acetylation in an ada2 mutant, which dissociates Gcn5 from the SAGA complex, we found that a subset of Gcn5 targets did not depend on an intact SAGA complex for targeting. Our work provides a framework for understanding how HAT and HDAC enzymes collaborate to regulate critical cellular processes related to growth and division.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine.

Cell cycle population effects in perturbation studies

Growth condition perturbation or gene function disruption are commonly used strategies to study cellular systems. Although it is widely appreciated that such experiments may involve indirect effects, these frequently remain uncharacterized. Here, analysis of functionally unrelated Saccharyomyces cerevisiae deletion strains reveals a common gene expression signature. One property shared by these strains is slower growth, with increased presence of the signature in more slowly growing strains. The slow growth signature is highly similar to the environmental stress response (ESR), an expression response common to diverse environmental perturbations. Both environmental and genetic perturbations result in growth rate changes. These are accompanied by a change in the distribution of cells over different cell cycle phases. Rather than representing a direct expression response in single cells, both the slow growth signature and ESR mainly reflect a redistribution of cells over different cell cycle phases, primarily characterized by an increase in the G1 population. The findings have implications for any study of perturbation that is accompanied by growth rate changes. Strategies to counter these effects are presented and discussed.

Mapping the cellular response to small molecules using chemogenomic fitness signatures

Genome-wide characterization of the in vivo cellular response to perturbation is fundamental to understanding how cells survive stress. Identifying the proteins and pathways perturbed by small molecules affects biology and medicine by revealing the mechanisms of drug action. We used a yeast chemogenomics platform that quantifies the requirement for each gene for resistance to a compound in vivo to profile 3250 small molecules in a systematic and unbiased manner. We identified 317 compounds that specifically perturb the function of 121 genes and characterized the mechanism of specific compounds. Global analysis revealed that the cellular response to small molecules is limited and described by a network of 45 major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

Mapping of protein-protein interactions of E. coli RNA polymerase with microfluidic mechanical trapping

The biophysical details of how transcription factors and other proteins interact with RNA polymerase are of great interest as they represent the nexus of how structure and function interact to regulate gene expression in the cell. We used an in vitro microfluidic approach to map interactions between a set of ninety proteins, over a third of which are transcription factors, and each of the four subunits of E. coli RNA polymerase, and we compared our results to those of previous large-scale studies. We detected interactions between RNA polymerase and transcription factors that earlier high-throughput screens missed; our results suggest that such interactions can occur without DNA mediation more commonly than previously appreciated.

Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets

Genetic interactions reveal insights into cellular function and can be used to identify drug targets. Here we construct a new model to predict negative genetic interactions in protein complexes by exploiting the evolutionary history of genes in parallel converging pathways in metabolism. We evaluate our model with protein complexes of Saccharomyces cerevisiae and show that the predicted protein pairs more frequently have a negative genetic interaction than random proteins from the same complex. Furthermore, we apply our model to human protein complexes to predict novel cancer drug targets, and identify 20 candidate targets with empirical support and 10 novel targets amenable to further experimental validation. Our study illustrates that negative genetic interactions can be predicted by systematically exploring genome evolution, and that this is useful to identify novel anti-cancer drug targets.

Genetic interactions can reveal insights into cellular functions. Here, Lu et al. show that negative genetic interactions in protein complexes can be predicted by systematically exploring the evolutionary history of genes, which may be useful for the identification of novel targets for anti-cancer drugs.

tRNA 3' processing in yeast involves tRNase Z, Rex1, and Rrp6

Mature tRNA 3' ends in the yeast Saccharomyces cerevisiae are generated by two pathways: endonucleolytic and exonucleolytic. Although two exonucleases, Rex1 and Rrp6, have been shown to be responsible for the exonucleolytic trimming, the identity of the endonuclease has been inferred from other systems but not confirmed in vivo. Here, we show that the yeast tRNA 3' endonuclease tRNase Z, Trz1, is catalyzing endonucleolytic tRNA 3' processing. The majority of analyzed tRNAs utilize both pathways, with a preference for the endonucleolytic one. However, 3'-end processing of precursors with long 3' trailers depends to a greater extent on Trz1. In addition to its function in the nucleus, Trz1 processes the 3' ends of mitochondrial tRNAs, contributing to the general RNA metabolism in this organelle.

Evolutionary rate heterogeneity of core and attachment proteins in yeast protein complexes

In general, proteins do not work alone; they form macromolecular complexes to play fundamental roles in diverse cellular functions. On the basis of their iterative clustering procedure and frequency of occurrence in the macromolecular complexes, the protein subunits have been categorized as core and attachment. Core protein subunits are the main functional elements, whereas attachment proteins act as modifiers or activators in protein complexes. In this article, using the current data set of yeast protein complexes, we found that core proteins are evolving at a faster rate than attachment proteins in spite of their functional importance. Interestingly, our investigation revealed that attachment proteins are present in a higher number of macromolecular complexes than core proteins. We also observed that the protein complex number (defined as the number of protein complexes in which a protein subunit belongs) has a stronger influence on gene/protein essentiality than multifunctionality. Finally, our results suggest that the observed differences in the rates of protein evolution between core and attachment proteins are due to differences in protein complex number and expression level. Moreover, we conclude that proteins which are present in higher numbers of macromolecular complexes enhance their overall expression level by increasing their transcription rate as well as translation rate, and thus the protein complex number imposes a strong selection pressure on the evolution of yeast proteome.

From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II

RNA polymerase II (RNAPII) lies at the core of dynamic control of gene expression. Using 53 RNAPII point mutants, we generated a point mutant epistatic miniarray profile (pE-MAP) comprising ∼60,000 quantitative genetic interactions in Saccharomyces cerevisiae. This analysis enabled functional assignment of RNAPII subdomains and uncovered connections between individual regions and other protein complexes. Using splicing microarrays and mutants that alter elongation rates in vitro, we found an inverse relationship between RNAPII speed and in vivo splicing efficiency. Furthermore, the pE-MAP classified fast and slow mutants that favor upstream and downstream start site selection, respectively. The striking coordination of polymerization rate with transcription initiation and splicing suggests that transcription rate is tuned to regulate multiple gene expression steps. The pE-MAP approach provides a powerful strategy to understand other multifunctional machines at amino acid resolution.

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

Cells contain many important protein complexes involved in performing and regulating structural, metabolic, and signaling functions. One major challenge in cell biology is to elucidate the organization and mechanisms of robustness of these complexes in vivo. We developed a systematic approach to study structural dependencies within complexes in living cells by deleting subunits and measuring pairwise interactions among other components. We used our methodology to perturb two conserved eukaryotic complexes: the retromer and the nuclear pore complex. Our results identify subunits that are critical for the assembly of these complexes, reveal their structural architecture, and uncover mechanisms by which protein interactions are modulated. Our results also show that paralogous proteins play a key role in the robustness of protein complexes and shape their assembly landscape. Our approach paves the way for studying the response of protein interactomes to mutations and enhances our understanding of genotype-phenotype maps.

Network rewiring is an important mechanism of gene essentiality change

Gene essentiality changes are crucial for organismal evolution. However, it is unclear how essentiality of orthologs varies across species. We investigated the underlying mechanism of gene essentiality changes between yeast and mouse based on the framework of network evolution and comparative genomic analysis. We found that yeast nonessential genes become essential in mouse when their network connections rapidly increase through engagement in protein complexes. The increased interactions allowed the previously nonessential genes to become members of vital pathways. By accounting for changes in gene essentiality, we firmly reestablished the centrality-lethality rule, which proposed the relationship of essential genes and network hubs. Furthermore, we discovered that the number of connections associated with essential and non-essential genes depends on whether they were essential in ancestral species. Our study describes for the first time how network evolution occurs to change gene essentiality.

Cluster-based assessment of protein-protein interaction confidence

Background

Protein-protein interaction networks are key to a systems-level understanding of cellular biology. However, interaction data can contain a considerable fraction of false positives. Several methods have been proposed to assess the confidence of individual interactions. Most of them require the integration of additional data like protein expression and interaction homology information. While being certainly useful, such additional data are not always available and may introduce additional bias and ambiguity.

Results

We propose a novel, network topology based interaction confidence assessment method called CAPPIC (cluster-based assessment of protein-protein interaction confidence). It exploits the network’s inherent modular architecture for assessing the confidence of individual interactions. Our method determines algorithmic parameters intrinsically and does not require any parameter input or reference sets for confidence scoring.

Conclusions

On the basis of five yeast and two human physical interactome maps inferred using different techniques, we show that CAPPIC reliably assesses interaction confidence and its performance compares well to other approaches that are also based on network topology. The confidence score correlates with the agreement in localization and biological process annotations of interacting proteins. Moreover, it corroborates experimental evidence of physical interactions. Our method is not limited to physical interactome maps as we exemplify with a large yeast genetic interaction network. An implementation of CAPPIC is available at http://intscore.molgen.mpg.de.

A multidimensional matrix for systems biology research and its application to interaction networks

A multidimensional matrix containing 76 parameters from 21 transcriptomics, proteomics, interactomics, phenotypic and sequence-based data sets, in which each data set covered most of the Saccharomyces cerevisiae proteome, was compiled for systems biology research. The maximal information coefficient (MIC) was used to measure correlations between every pair of parameters. Out of 2850 possible comparisons, 340 pairs of variables (12%) showed statistically significant MIC scores. There were 321 relationships that were expected; these included relationships within physicochemical parameters of proteins, between abundance levels of genes/proteins and expression noise, and between different types of intracellular networks. We found 19 potentially novel relationships between different types of "-omics" data. The strongest of these involved genetic interaction networks, which were correlated with pleiotropy and cell-to-cell variability in protein expression. Protein disorder also showed a number of significant relationships with protein abundance, signaling and regulatory networks. Significant cross-talk was seen between the signaling and kinase interaction networks. Investigation of this revealed densely connected kinase clusters and significant signaling between them, along with signaling centers that act as integrators or broadcasters of intracellular information. These centers may allow for redundancy and a means of dampening noise in networks under a variety of genetic or environmental perturbations.

Dissecting DNA damage response pathways by analysing protein localization and abundance changes during DNA replication stress

Relocalization of proteins is a hallmark of the DNA damage response. We use high-throughput microscopic screening of the yeast GFP fusion collection to develop a systems-level view of protein reorganization following drug-induced DNA replication stress. Changes in protein localization and abundance reveal drug-specific patterns of functional enrichments. Classification of proteins by subcellular destination enables the identification of pathways that respond to replication stress. We analysed pairwise combinations of GFP fusions and gene deletion mutants to define and order two previously unknown DNA damage responses. In the first, Cmr1 forms subnuclear foci that are regulated by the histone deacetylase Hos2 and are distinct from the typical Rad52 repair foci. In a second example, we find that the checkpoint kinases Mec1/Tel1 and the translation regulator Asc1 regulate P-body formation. This method identifies response pathways that were not detected in genetic and protein interaction screens, and can be readily applied to any form of chemical or genetic stress to reveal cellular response pathways.