Mechanistic Insights into the Multiple Activities of the Rad5 Family of Enzymes.

The budding yeast protein Rad5 is highly conserved among eukaryotes. Rad5 and its orthologs including helicase like transcription factor (HLTF) and SNF2 histone linker PHD RING helicase (SHPRH) in humans constitute a unique family of enzymes that play critical roles in the cellular response to DNA replication stresses. The function of the Rad5 family of enzymes is fulfilled by their multiple activities, including ubiquitin ligase, replication fork regression activities and others. Herein, we review recent studies that provided mechanistic insights into their multiple activities and their coordination.

The ER membrane complex (EMC) can functionally replace the Oxa1 insertase in mitochondria.

Two multisubunit protein complexes for membrane protein insertion were recently identified in the endoplasmic reticulum (ER): the guided entry of tail anchor proteins (GET) complex and ER membrane complex (EMC). The structures of both of their hydrophobic core subunits, which are required for the insertion reaction, revealed an overall similarity to the YidC/Oxa1/Alb3 family members found in bacteria, mitochondria, and chloroplasts. This suggests that these membrane insertion machineries all share a common ancestry. To test whether these ER proteins can functionally replace Oxa1 in yeast mitochondria, we generated strains that express mitochondria-targeted Get2-Get1 and Emc6-Emc3 fusion proteins in Oxa1 deletion mutants. Interestingly, the Emc6-Emc3 fusion was able to complement an Δoxa1 mutant and restored its respiratory competence. The Emc6-Emc3 fusion promoted the insertion of the mitochondrially encoded protein Cox2, as well as of nuclear encoded inner membrane proteins, although was not able to facilitate the assembly of the Atp9 ring. Our observations indicate that protein insertion into the ER is functionally conserved to the insertion mechanism in bacteria and mitochondria and adheres to similar topological principles.

Yeast Translational Activator Mss51p and Human ZMYND17 - Two Proteins with a Common Origin, but Different Functions.

Despite its similarity to protein biosynthesis in bacteria, translation in the mitochondria of modern eukaryotes has several unique features, such as the necessity for coordination of translation of mitochondrial mRNAs encoding proteins of the electron transport chain complexes with translation of other protein components of these complexes in the cytosol. In the mitochondria of baker's yeast Saccharomyces cerevisiae, this coordination is carried out by a system of translational activators that predominantly interact with the 5'-untranslated regions of mitochondrial mRNAs. No such system has been found in human mitochondria, except a single identified translational activator, TACO1. Here, we studied the role of the ZMYND17 gene, an ortholog of the yeast gene for the translational activator Mss51p, on the mitochondrial translation in human cells. Deletion of the ZMYND17 gene did not affect translation in the mitochondria, but led to the decrease in the cytochrome c oxidase activity and increase in the amount of free F1 subunit of ATP synthase. We also investigated the evolutionary history of Mss51p and ZMYND17 and suggested a possible mechanism for the divergence of functions of these orthologous proteins.

Paths Through the Yeast Regulatory Network in Different Physiological States.

We analyse paths through the regulatory networks that control gene-expression patterns in Yeast, in five different physiological states: cell cycle, DNA damage, stress response, diauxic shift, and sporulation. The network in each state is specified as a directed graph, containing different sets of edges connecting pairs selected from a combined set of 1475 nodes. Each network contains some nodes that have no parents, and others that have no children. We call these, respectively, 'source' and 'sink' nodes. For each network we enumerate paths between source and sink nodes. In a previous paper (Lesk and Konagurthu, 2020), we defined, extracted and compared the neighbourhoods of each transcription factor in different physiological states, and how the system reconfigures itself. Here we compare the usage of nodes and edges by different networks, and how they are assembled into paths. The picture that emerges is that the networks are not disjoint but show substantial sharing of nodes and edges; however, they assemble these materials into different sets of paths. Four of the networks, other than the cell-cycle network, contain paths between only a small fraction (<13%) of possible source-sink pairs. Although the cell-cycle network is not an outlier in terms of total number of nodes and edges, and number of sink nodes, it is very much an outlier in having a greater proportion of source-to-sink paths than the other networks.

Distinct classes of misfolded proteins differentially affect the growth of yeast compromised for proteasome function.

Maintenance of the proteome (proteostasis) is essential for cellular homeostasis and prevents cytotoxic stress responses that arise from protein misfolding. However, little is known about how different types of misfolded proteins impact homeostasis, especially when protein degradation pathways are compromised. We examined the effects of misfolded protein expression on yeast growth by characterizing a suite of substrates possessing the same aggregation-prone domain but engaging different quality control pathways. We discovered that treatment with a proteasome inhibitor was more toxic in yeast expressing misfolded membrane proteins, and this growth defect was mirrored in yeast lacking a proteasome-specific transcription factor, Rpn4p. These results highlight weaknesses in the proteostasis network's ability to handle the stress arising from an accumulation of misfolded membrane proteins.

Co-translational assembly and localized translation of nucleoporins in nuclear pore complex biogenesis.

mRNA translation is coupled to multiprotein complex assembly in the cytoplasm or to protein delivery into intracellular compartments. Here, by combining systematic RNA immunoprecipitation and single-molecule RNA imaging in yeast, we have provided a complete depiction of the co-translational events involved in the biogenesis of a large multiprotein assembly, the nuclear pore complex (NPC). We report that binary interactions between NPC subunits can be established during translation, in the cytoplasm. Strikingly, the nucleoporins Nup1/Nup2, together with a number of nuclear proteins, are instead translated at nuclear pores, through a mechanism involving interactions between their nascent N-termini and nuclear transport receptors. Uncoupling this co-translational recruitment further triggers the formation of cytoplasmic foci of unassembled polypeptides. Altogether, our data reveal that distinct, spatially segregated modes of co-translational interactions foster the ordered assembly of NPC subunits and that localized translation can ensure the proper delivery of proteins to the pore and the nucleus.

Using Yeast to Define the Regulatory Role of Protein Lysine Methylation.

The post-translational modifications (PTM) of proteins are crucial for cells to survive under diverse environmental conditions and to respond to stimuli. PTMs are known to govern a broad array of cellular processes including signal transduction and chromatin regulation. The PTM lysine methylation has been extensively studied within the context of chromatin and the epigenetic regulation of the genome. However, it has also emerged as a critical regulator of non-histone proteins important for signal transduction pathways. While the number of known non-histone protein methylation events is increasing, the molecular functions of many of these modifications are not yet known. Proteomic studies of the model system Saccharomyces cerevisiae suggest lysine methylation may regulate a diversity of pathways including transcription, RNA processing, translation, and signal transduction cascades. However, there has still been relatively little investigation of lysine methylation as a broad cellular regulator beyond chromatin and transcription. Here, we outline our current state of understanding of non-histone protein methylation in yeast and propose ways in which the yeast system can be leveraged to develop a much more complete picture of molecular mechanisms through which lysine methylation regulates cellular functions.

Mitochondrial Carriers for Aspartate, Glutamate and Other Amino Acids: A Review.

Members of the mitochondrial carrier (MC) protein family transport various molecules across the mitochondrial inner membrane to interlink steps of metabolic pathways and biochemical processes that take place in different compartments; i.e., are localized partly inside and outside the mitochondrial matrix. MC substrates consist of metabolites, inorganic anions (such as phosphate and sulfate), nucleotides, cofactors and amino acids. These compounds have been identified by in vitro transport assays based on the uptake of radioactively labeled substrates into liposomes reconstituted with recombinant purified MCs. By using this approach, 18 human, plant and yeast MCs for amino acids have been characterized and shown to transport aspartate, glutamate, ornithine, arginine, lysine, histidine, citrulline and glycine with varying substrate specificities, kinetics, influences of the pH gradient, and capacities for the antiport and uniport mode of transport. Aside from providing amino acids for mitochondrial translation, the transport reactions catalyzed by these MCs are crucial in energy, nitrogen, nucleotide and amino acid metabolism. In this review we dissect the transport properties, phylogeny, regulation and expression levels in different tissues of MCs for amino acids, and summarize the main structural aspects known until now about MCs. The effects of their disease-causing mutations and manipulation of their expression levels in cells are also considered as clues for understanding their physiological functions.

Comprehensive and quantitative analysis of G1 cyclins. A tool for studying the cell cycle.

In eukaryotes, the cell cycle is driven by the actions of several cyclin dependent kinases (CDKs) and an array of regulatory proteins called cyclins, due to the cyclical expression patterns of the latter. In yeast, the accepted pattern of cyclin waves is based on qualitative studies performed by different laboratories using different strain backgrounds, different growing conditions and media, and different kinds of genetic manipulation. Additionally, only the subset of cyclins regulating Cdc28 was included, while the Pho85 cyclins were excluded. We describe a comprehensive, quantitative and accurate blueprint of G1 cyclins in the yeast Saccharomyces cerevisiae that, in addition to validating previous conclusions, yields new findings and establishes an accurate G1 cyclin blueprint. For the purposes of this research, we produced a collection of strains with all G1 cyclins identically tagged using the same and most respectful procedure possible. We report the contribution of each G1 cyclin for a broad array of growing and stress conditions, describe an unknown role for Pcl2 in heat-stress conditions and demonstrate the importance of maintaining the 3'UTR sequence of cyclins untouched during the tagging process.

Essential Protein Detection by Random Walk on Weighted Protein-Protein Interaction Networks.

Essential proteins are critical to the development and survival of cells. Identification of essential proteins is helpful for understanding the minimal set of required genes in a living cell and for designing new drugs. To detect essential proteins, various computational methods have been proposed based on protein-protein interaction (PPI) networks. However, protein interaction data obtained by high-throughput experiments usually contain high false positives, which negatively impacts the accuracy of essential protein detection. Moreover, most existing studies focused on the local information of proteins in PPI networks, while ignoring the influence of indirect protein interactions on essentiality. In this paper, we propose a novel method, called Essentiality Ranking (EssRank in short), to boost the accuracy of essential protein detection. To deal with the inaccuracy of PPI data, confidence scores of interactions are evaluated by integrating various biological information. Weighted edge clustering coefficient (WECC), considering both interaction confidence scores and network topology, is proposed to calculate edge weights in PPI networks. The weight of each node is evaluated by the sum of WECC values of its linking edges. A random walk method, making use of both direct and indirect protein interactions, is then employed to calculate protein essentiality iteratively. Experimental results on the yeast PPI network show that EssRank outperforms most existing methods, including the most commonly-used centrality measures (SC, DC, BC, CC, IC, and EC), topology based methods (DMNC and NC) and the data integrating method IEW.

Comparative genomics of nuclear envelope proteins.

BACKGROUND: The nuclear envelope (NE) that encapsulates the nuclear genome is a double lipid bilayer with several integral and peripherally associated proteins. It is a characteristic feature of the eukaryotes and acts as a hub for a number of important nuclear events including transcription, repair, and regulated gene expression. The proteins associated with the nuclear envelope mediate the NE functions and maintain its structural integrity, which is crucial for survival. In spite of the importance of this structure, knowledge of the protein composition of the nuclear envelope and their function, are limited to very few organisms belonging to Opisthokonta and Archaeplastida supergroups. The NE composition is largely unknown in organisms outside these two supergroups. RESULTS: In this study, we have taken a comparative sequence analysis approach to identify the NE proteome that is present across all five eukaryotic supergroups. We identified 22 proteins involved in various nuclear functions to be part of the core NE proteome. The presence of these proteins across eukaryotes, suggests that they are traceable to the Last Eukaryotic Common Ancestor (LECA). Additionally, we also identified the NE proteins that have evolved in a lineage specific manner and those that have been preserved only in a subset of organisms. CONCLUSIONS: Our study identifies the conserved features of the nuclear envelope across eukaryotes and provides insights into the potential composition and the functionalities that were constituents of the LECA NE.

Investigating the Network Basis of Negative Genetic Interactions in Saccharomyces cerevisiae with Integrated Biological Networks and Triplet Motif Analysis.

Negative genetic interactions in Saccharomyces cerevisiae have been systematically screened to near-completeness, with >500 000 interactions identified. Nevertheless, the biological basis of these interactions remains poorly understood. To investigate this, we analyzed negative genetic interactions within an integrated biological network, being the union of protein-protein, kinase-substrate, and transcription factor-target gene interactions. Network triplets, containing two genes/proteins that show negative genetic interaction and a third protein from the network, were then analyzed. Strikingly, just six out of 15 possible triplet motif types were present, as compared to randomized networks. These were in three clear groups: protein-protein interactions, signaling, and regulatory triplets where the latter two showed no overlap. In the triplets, negative genetic interactions were associated with paralogs and ohnologs; however, these were very rare. Negative genetic interactions among the six triplet motifs did however show strong dosage constraints, with genes being significantly associated with toxicity on overexpression and periodicity in the cell cycle. Negative genetic interactions overlapped with other interaction types in 37% of cases; these were predominantly associated with protein complexes or signaling events. Finally, we highlight regions of "network vulnerability" containing multiple negative genetic interactions; these could be targeted in fungal species for the regulation of cell growth.

A New Method for Identifying Essential Proteins by Measuring Co-Expression and Functional Similarity.

Identification of essential proteins is a fundamental task for understanding cellular life. With the increasing availability of high-throughput data, which enable the identification of essential proteins by computational methods from the network level. Various computational methods have been proposed based on topological properties of protein-protein interaction (PPI) network or combining additional biological information. However, the prediction precision is still unsatisfied especially when predicting a small amount of essential proteins. In this paper, we propose a novel method for predicting essential proteins by integrating Gene expression profiles and Gene Ontology (GO) annotation data, called GEG. To demonstrate the performance of GEG method, we evaluated GEG on two PPI networks of Saccharomyces cerevisiae. Simulation results showed that GEG achieved better result performance than the five other state-of-the-art methods. We also demonstrate that the GEG is robust against perturbation in terms of precision-recall and receiver operating characteristic measures. The results indicate that appropriate integrating topological properties with additional biological information will be a great help for identification of essential proteins. The new proposed method GEG is effective and useful for predicting essential proteins in PPI networks.

Target selection by natural and redesigned PUF proteins.

Pumilio/fem-3 mRNA binding factor (PUF) proteins bind RNA with sequence specificity and modularity, and have become exemplary scaffolds in the reengineering of new RNA specificities. Here, we report the in vivo RNA binding sites of wild-type (WT) and reengineered forms of the PUF protein Saccharomyces cerevisiae Puf2p across the transcriptome. Puf2p defines an ancient protein family present throughout fungi, with divergent and distinctive PUF RNA binding domains, RNA-recognition motifs (RRMs), and prion regions. We identify sites in RNA bound to Puf2p in vivo by using two forms of UV cross-linking followed by immunopurification. The protein specifically binds more than 1,000 mRNAs, which contain multiple iterations of UAAU-binding elements. Regions outside the PUF domain, including the RRM, enhance discrimination among targets. Compensatory mutants reveal that one Puf2p molecule binds one UAAU sequence, and align the protein with the RNA site. Based on this architecture, we redesign Puf2p to bind UAAG and identify the targets of this reengineered PUF in vivo. The mutant protein finds its target site in 1,800 RNAs and yields a novel RNA network with a dramatic redistribution of binding elements. The mutant protein exhibits even greater RNA specificity than wild type. The redesigned protein decreases the abundance of RNAs in its redesigned network. These results suggest that reengineering using the PUF scaffold redirects and can even enhance specificity in vivo.

A Topology Potential-Based Method for Identifying Essential Proteins from PPI Networks.

Essential proteins are indispensable for cellular life. It is of great significance to identify essential proteins that can help us understand the minimal requirements for cellular life and is also very important for drug design. However, identification of essential proteins based on experimental approaches are typically time-consuming and expensive. With the development of high-throughput technology in the post-genomic era, more and more protein-protein interaction data can be obtained, which make it possible to study essential proteins from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. Most of these topology based essential protein discovery methods were to use network centralities. In this paper, we investigate the essential proteins' topological characters from a completely new perspective. To our knowledge it is the first time that topology potential is used to identify essential proteins from a protein-protein interaction (PPI) network. The basic idea is that each protein in the network can be viewed as a material particle which creates a potential field around itself and the interaction of all proteins forms a topological field over the network. By defining and computing the value of each protein's topology potential, we can obtain a more precise ranking which reflects the importance of proteins from the PPI network. The experimental results show that topology potential-based methods TP and TP-NC outperform traditional topology measures: degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), subgraph centrality (SC), eigenvector centrality (EC), information centrality (IC), and network centrality (NC) for predicting essential proteins. In addition, these centrality measures are improved on their performance for identifying essential proteins in biological network when controlled by topology potential.

The GCKIII kinase Sps1 and the 14-3-3 isoforms, Bmh1 and Bmh2, cooperate to ensure proper sporulation in Saccharomyces cerevisiae.

Sporulation in the budding yeast Saccharomyces cerevisiae is a developmental program initiated in response to nutritional deprivation. Sps1, a serine/threonine kinase, is required for sporulation, but relatively little is known about the molecular mechanisms through which it regulates this process. Here we show that SPS1 encodes a bona-fide member of the GCKIII subfamily of STE20 kinases, both through phylogenetic analysis of the kinase domain and examination of its C-terminal regulatory domain. Within the regulatory domain, we find Sps1 contains an invariant ExxxPG region conserved from plant to human GCKIIIs that we call the EPG motif; we show this EPG motif is important for SPS1 function. We also find that Sps1 is phosphorylated near its N-terminus on Threonine 12, and that this phosphorylation is required for the efficient production of spores. In Sps1, Threonine 12 lies within a 14-3-3 consensus binding sequence, and we show that the S. cerevisiae 14-3-3 proteins Bmh1 and Bmh2 bind Sps1 in a Threonine 12-dependent fashion. This interaction is significant, as BMH1 and BMH2 are required during sporulation and genetically interact with SPS1 in sporulating cells. Finally, we observe that Sps1, Bmh1 and Bmh2 are present in both the nucleus and cytoplasm during sporulation. We identify a nuclear localization sequence in Sps1 at amino acids 411-415, and show that this sequence is necessary and sufficient for nuclear localization. Taken together, these data identify regions within Sps1 critical for its function and indicate that SPS1 and 14-3-3s act together to promote proper sporulation in S. cerevisiae.

Genome-wide screens for sensitivity to ionizing radiation identify the fission yeast nonhomologous end joining factor Xrc4.

Nonhomologous end joining (NHEJ) is the main means for repairing DNA double-strand breaks (DSBs) in human cells. Molecular understanding of NHEJ has benefited from analyses in the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe. In human cells, the DNA ligation reaction of the classical NHEJ pathway is carried out by a protein complex composed of DNA ligase IV (LigIV) and XRCC4. In S. cerevisiae, this reaction is catalyzed by a homologous complex composed of Dnl4 and Lif1. Intriguingly, no homolog of XRCC4 has been found in S. pombe, raising the possibility that such a factor may not always be required for classical NHEJ. Here, through screening the ionizing radiation (IR) sensitivity phenotype of a genome-wide fission yeast deletion collection in both the vegetative growth state and the spore state, we identify Xrc4, a highly divergent homolog of human XRCC4. Like other fission yeast NHEJ factors, Xrc4 is critically important for IR resistance of spores, in which no homologous recombination templates are available. Using both extrachromosomal and chromosomal DSB repair assays, we show that Xrc4 is essential for classical NHEJ. Exogenously expressed Xrc4 colocalizes with the LigIV homolog Lig4 at the chromatin region of the nucleus in a mutually dependent manner. Furthermore, like their human counterparts, Xrc4 and Lig4 interact with each other and this interaction requires the inter-BRCT linker and the second BRCT domain of Lig4. Our discovery of Xrc4 suggests that an XRCC4 family protein is universally required for classical NHEJ in eukaryotes.

The evolution of the ribosome biogenesis pathway from a yeast perspective.

Ribosome biogenesis is fundamental for cellular life, but surprisingly little is known about the underlying pathway. In eukaryotes a comprehensive collection of experimentally verified ribosome biogenesis factors (RBFs) exists only for Saccharomyces cerevisiae. Far less is known for other fungi, animals or plants, and insights are even more limited for archaea. Starting from 255 yeast RBFs, we integrated ortholog searches, domain architecture comparisons and, in part, manual curation to investigate the inventories of RBF candidates in 261 eukaryotes, 26 archaea and 57 bacteria. The resulting phylogenetic profiles reveal the evolutionary ancestry of the yeast pathway. The oldest core comprising 20 RBF lineages dates back to the last universal common ancestor, while the youngest 20 factors are confined to the Saccharomycotina. On this basis, we outline similarities and differences of ribosome biogenesis across contemporary species. Archaea, so far a rather uncharted domain, possess 38 well-supported RBF candidates of which some are known to form functional sub-complexes in yeast. This provides initial evidence that ribosome biogenesis in eukaryotes and archaea follows similar principles. Within eukaryotes, RBF repertoires vary considerably. A comparison of yeast and human reveals that lineage-specific adaptation via RBF exclusion and addition characterizes the evolution of this ancient pathway.

The complex evolutionary dynamics of Hsp70s: a genomic and functional perspective.

Hsp70 molecular chaperones are ubiquitous. By preventing aggregation, promoting folding, and regulating degradation, Hsp70s are major factors in the ability of cells to maintain proteostasis. Despite a wealth of functional information, little is understood about the evolutionary dynamics of Hsp70s. We undertook an analysis of Hsp70s in the fungal clade Ascomycota. Using the well-characterized 14 Hsp70s of Saccharomyces cerevisiae, we identified 491 orthologs from 53 genomes. Saccharomyces cerevisiae Hsp70s fall into seven subfamilies: four canonical-type Hsp70 chaperones (SSA, SSB, KAR, and SSC) and three atypical Hsp70s (SSE, SSZ, and LHS) that play regulatory roles, modulating the activity of canonical Hsp70 partners. Each of the 53 surveyed genomes harbored at least one member of each subfamily, and thus establishing these seven Hsp70s as units of function and evolution. Genomes of some species contained only one member of each subfamily that is only seven Hsp70s. Overall, members of each subfamily formed a monophyletic group, suggesting that each diversified from their corresponding ancestral gene present in the common ancestor of all surveyed species. However, the pattern of evolution varied across subfamilies. At one extreme, members of the SSB subfamily evolved under concerted evolution. At the other extreme, SSA and SSC subfamilies exhibited a high degree of copy number dynamics, consistent with a birth-death mode of evolution. KAR, SSE, SSZ, and LHS subfamilies evolved in a simple divergent mode with little copy number dynamics. Together, our data revealed that the evolutionary history of this highly conserved and ubiquitous protein family was surprising complex and dynamic.

Biology and genetics of prions causing neurodegeneration.

Prions are proteins that acquire alternative conformations that become self-propagating. Transformation of proteins into prions is generally accompanied by an increase in ß-sheet structure and a propensity to aggregate into oligomers. Some prions are beneficial and perform cellular functions, whereas others cause neurodegeneration. In mammals, more than a dozen proteins that become prions have been identified, and a similar number has been found in fungi. In both mammals and fungi, variations in the prion conformation encipher the biological properties of distinct prion strains. Increasing evidence argues that prions cause many neurodegenerative diseases (NDs), including Alzheimer's, Parkinson's, Creutzfeldt-Jakob, and Lou Gehrig's diseases, as well as the tauopathies. The majority of NDs are sporadic, and 10% to 20% are inherited. The late onset of heritable NDs, like their sporadic counterparts, may reflect the stochastic nature of prion formation; the pathogenesis of such illnesses seems to require prion accumulation to exceed some critical threshold before neurological dysfunction manifests.