The Hsp70–Hsp110 chaperone complex antagonizes Cin8 plus-end motility and prevents premature spindle elongation in S phase.

Systematic affinity purification combined with mass spectrometry analysis of N- and C-tagged cytoplasmic Hsp70/Hsp110 chaperones was used to identify new roles of Hsp70/Hsp110 in the cell. This allowed the mapping of a chaperone–protein network consisting of 1,227 unique interactions between the 9 chaperones and 473 proteins and highlighted roles for Hsp70/Hsp110 in 14 broad biological processes. Using this information, we uncovered an essential role for Hsp110 in spindle assembly and, more specifically, in modulating the activity of the widely conserved kinesin-5 motor Cin8. The role of Hsp110 Sse1 as a nucleotide exchange factor for the Hsp70 chaperones Ssa1/Ssa2 was found to be required for maintaining the proper distribution of kinesin-5 motors within the spindle, which was subsequently required for bipolar spindle assembly in S phase. These data suggest a model whereby the Hsp70–Hsp110 chaperone complex antagonizes Cin8 plus-end motility and prevents premature spindle elongation in S phase.

Summary

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and the associated proteins (Cas) comprise a system of adaptive immunity against viruses and plasmids in prokaryotes. Cas1 is a CRISPR-associated protein that is common to all CRISPR-containing prokaryotes but its function remains obscure. Here we show that the purified Cas1 protein of Escherichia coli (YgbT) exhibits nuclease activity against single-stranded and branched DNAs including Holliday junctions, replication forks, and 5′-flaps. The crystal structure of YgbT and site-directed mutagenesis have revealed the potential active site. Genome-wide screens show that YgbT physically and genetically interacts with key components of DNA repair systems, including recB, recC and ruvB. Consistent with these findings, the ygbT deletion strain showed increased sensitivity to DNA damage and impaired chromosomal segregation. Similar phenotypes were observed in strains with deletion of CRISPR clusters, suggesting that the function of YgbT in repair involves interaction with the CRISPRs. These results show that YgbT belongs to a novel, structurally distinct family of nucleases acting on branched DNAs and suggest that, in addition to antiviral immunity, at least some components of the CRISPR-Cas system have a function in DNA repair.

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among >235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.

Author Summary

Proper assembly of the cell envelope is essential for bacterial growth, environmental adaptation, and drug resistance. Yet, while the biological roles of the many genes and pathways involved in biosynthesis of the cell envelope have been studied extensively in isolation, how the myriad components intersect functionally to maintain envelope integrity under different growth conditions has not been explored systematically. Genome-scale genetic interaction screens have increasingly been performed to great impact in yeast; no analogous comprehensive studies have yet been reported for bacteria despite their prominence in human health and disease. We addressed this by using a synthetic genetic array technology to generate quantitative maps of genetic interactions encompassing virtually all the components of the cell envelope biosynthetic machinery of the classic model bacterium E. coli in two common laboratory growth conditions (rich and minimal medium). From the resulting networks of high-confidence genetic interactions, we identify condition-specific functional dependencies underlying envelope assembly and global remodeling of genetic backup mechanisms that ensure envelope integrity under environmental challenge.

RNA polymerase II (RNAP II) C-terminal domain (CTD) phosphorylation is important for various transcription-related processes. Here, we identify by affinity purification and mass spectrometry three previously uncharacterized human CTD-interaction domain (CID)-containing proteins, RPRD1A, RPRD1B and RPRD2, which co-purify with RNAP II and three other RNAP II-associated proteins, RPAP2, GRINL1A and RECQL5, but not with the Mediator complex. RPRD1A and RPRD1B can accompany RNAP II from promoter regions to 3′-untranslated regions during transcription in vivo, predominantly interact with phosphorylated RNAP II, and can reduce CTD S5- and S7-phosphorylated RNAP II at target gene promoters. Thus, the RPRD proteins are likely to have multiple important roles in transcription.

Elongation factor RbbA is required for ATP-dependent deacyl-tRNA release presumably after each peptide bond formation; however, there is no information about the cellular role. Proteomic analysis in Escherichia coli revealed that RbbA reciprocally co-purified with a conserved inner membrane protein of unknown function, YhjD. Both proteins are also physically associated with the 30S ribosome and with members of the lipopolysaccharide transport machinery. Genome-wide genetic screens of rbbA and yhjD deletion mutants revealed aggravating genetic interactions with mutants deficient in the electron transport chain. Cells lacking both rbbA and yhjD exhibited reduced cell division, respiration and global protein synthesis as well as increased sensitivity to antibiotics targeting the ETC and the accuracy of protein synthesis. Our results suggest that RbbA appears to function together with YhjD as part of a regulatory network that impacts bacterial oxidative phosphorylation and translation efficiency.

Motivation: A post-translational modification (PTM) is a chemical modification of a protein that occurs naturally. Many of these modifications, such as phosphorylation, are known to play pivotal roles in the regulation of protein function. Henceforth, PTM perturbations have been linked to diverse diseases like Parkinson's, Alzheimer's, diabetes and cancer. To discover PTMs on a genome-wide scale, there is a recent surge of interest in analyzing tandem mass spectrometry data, and several unrestrictive (so-called ‘blind’) PTM search methods have been reported. However, these approaches are subject to noise in mass measurements and in the predicted modification site (amino acid position) within peptides, which can result in false PTM assignments.

Results: To address these issues, we devised a machine learning algorithm, PTMClust, that can be applied to the output of blind PTM search methods to improve prediction quality, by suppressing noise in the data and clustering peptides with the same underlying modification to form PTM groups. We show that our technique outperforms two standard clustering algorithms on a simulated dataset. Additionally, we show that our algorithm significantly improves sensitivity and specificity when applied to the output of three different blind PTM search engines, SIMS, InsPecT and MODmap. Additionally, PTMClust markedly outperforms another PTM refinement algorithm, PTMFinder. We demonstrate that our technique is able to reduce false PTM assignments, improve overall detection coverage and facilitate novel PTM discovery, including terminus modifications. We applied our technique to a large-scale yeast MS/MS proteome profiling dataset and found numerous known and novel PTMs. Accurately identifying modifications in protein sequences is a critical first step for PTM profiling, and thus our approach may benefit routine proteomic analysis.

Availability: Our algorithm is implemented in Matlab and is freely available for academic use. The software is available online from http://genes.toronto.edu.

Supplementary Information: Supplementary data are available at Bioinformatics online.

Contact: frey@psi.utoronto.ca

Chromatin modification (CM) plays a key role in regulating transcription, DNA replication, repair and recombination. However, our knowledge of these processes in humans remains very limited. Here we use computational approaches to study proteins and functional domains involved in CM in humans. We analyze the abundance and the pair-wise domain-domain co-occurrences of 25 well-documented CM domains in 5 model organisms: yeast, worm, fly, mouse and human. Results show that domains involved in histone methylation, DNA methylation, and histone variants are remarkably expanded in metazoan, reflecting the increased demand for cell type-specific gene regulation. We find that CM domains tend to co-occur with a limited number of partner domains and are hence not promiscuous. This property is exploited to identify 47 potentially novel CM domains, including 24 DNA-binding domains, whose role in CM has received little attention so far. Lastly, we use a consensus Machine Learning approach to predict 379 novel CM genes (coding for 329 proteins) in humans based on domain compositions. Several of these predictions are supported by very recent experimental studies and others are slated for experimental verification. Identification of novel CM genes and domains in humans will aid our understanding of fundamental epigenetic processes that are important for stem cell differentiation and cancer biology. Information on all the candidate CM domains and genes reported here is publicly available.

Background

Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal.

Principal Findings

To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed “Enrichment Map”, a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results.

Conclusions

Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).

Chromatin modification (CM) is a set of epigenetic processes that govern many aspects of DNA replication, transcription and repair. CM is carried out by groups of physically interacting proteins, and their disruption has been linked to a number of complex human diseases. CM remains largely unexplored, however, especially in higher eukaryotes such as human. Here we present the DAnCER resource, which integrates information on genes with CM function from five model organisms, including human. Currently integrated are gene functional annotations, Pfam domain architecture, protein interaction networks and associated human diseases. Additional supporting evidence includes orthology relationships across organisms, membership in protein complexes, and information on protein 3D structure. These data are available for 962 experimentally confirmed and manually curated CM genes and for over 5000 genes with predicted CM function on the basis of orthology and domain composition. DAnCER allows visual explorations of the integrated data and flexible query capabilities using a variety of data filters. In particular, disease information and functional annotations are mapped onto the protein interaction networks, enabling the user to formulate new hypotheses on the function and disease associations of a given gene based on those of its interaction partners. DAnCER is freely available at http://wodaklab.org/dancer/.

Protein and mRNA copy numbers vary from cell to cell in isogenic bacterial populations. However, these molecules often exist in low copy numbers, and are difficult to detect in single cells. Here we carried out quantitative system-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli. We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size. At high expression levels, the distributions are dominated by extrinsic noise. Strikingly, we found that a single cell's protein and mRNA copy numbers for any given gene are uncorrelated.

Summary

Histone variant H2A.Z has a conserved role in genome stability, although it remains unclear how this is mediated. Here we demonstrate in fission yeast that the Swr1 ATPase inserts H2A.Z (Pht1) into chromatin and Kat5 acetyltransferase (Mst1) acetylates it. Deletion or unacetylatable mutation of Pht1 leads to genome instability, primarily caused by chromosome entanglement/breakage at anaphase. This leads to the loss of telomere-proximal markers, though telomere protection and repeat length are unaffected by the absence of Pht1. Strikingly the chromosome entanglement in pht1Δ anaphase cells can be rescued by forcing chromosome condensation prior to anaphase onset. We show that the condensin complex, required for the maintenance of anaphase chromosome condensation, prematurely dissociates from chromatin in the absence of Pht1. This and other findings suggest an important role for H2A.Z in the architecture of anaphase chromosomes.

Global protein expression profiling can potentially uncover perturbations associated with common forms of heart disease. We have used shotgun tandem mass spectrometry to monitor the state of biological systems in cardiac tissue correlating with disease onset, cardiac insufficiency and progression to heart failure in a time-course mouse model of dilated cardiomyopathy (DCM). However, interpreting the functional significance of the hundreds of differentially expressed proteins has been challenging. Here, we utilize improved enrichment statistical methods and an extensive collection of functionally related gene sets, gaining a more comprehensive understanding of the progressive alterations associated with functional decline in DCM. We visualize the enrichment results as an Enrichment Map, where significant gene sets are grouped based on annotation similarity. This approach vastly simplifies the interpretation of the large number of enriched gene-sets found. For pathways of specific interest, such as Apoptosis and the MAPK cascade, we performed a more detailed analysis of the underlying signaling network, including experimental validation of expression patterns.

The yjeE, yeaZ, and ygjD genes are highly conserved in the genomes of eubacteria, and ygjD orthologs are also found throughout the Archaea and eukaryotes. In this study, we have constructed conditional expression strains for each of these genes in the model organism Escherichia coli K12. We show that each gene is essential for the viability of E. coli under laboratory growth conditions. Growth of the conditional strains under nonpermissive conditions results in dramatic changes in cell ultrastructure. Deliberate repression of the expression of yeaZ results in cells with highly condensed nucleoids, while repression of yjeE and ygjD expression results in at least a proportion of very enlarged cells with an unusual peripheral distribution of DNA. Each of the three conditional expression strains can be complemented by multicopy clones harboring the rstA gene, which encodes a two-component-system response regulator, strongly suggesting that these proteins are involved in the same essential cellular pathway. The results of bacterial two-hybrid experiments show that YeaZ can interact with both YjeE and YgjD but that YgjD is the preferred interaction partner. The results of in vitro experiments indicate that YeaZ mediates the proteolysis of YgjD, suggesting that YeaZ and YjeE act as regulators to control the activity of this protein. Our results are consistent with these proteins forming a link between DNA metabolism and cell division.

Background

One of key issues in the post-genomic era is to assign functions to uncharacterized proteins. Since proteins seldom act alone; rather, they must interact with other biomolecular units to execute their functions. Thus, the functions of unknown proteins may be discovered through studying their interactions with proteins having known functions. Although many approaches have been developed for this purpose, one of main limitations in most of these methods is that the dependence among functional terms has not been taken into account.

Results

We developed a new network-based protein function prediction method which combines the likelihood scores of local classifiers with a relaxation labelling technique. The framework can incorporate the inter-relationship among functional labels into the function prediction procedure and allow us to efficiently discover relevant non-local dependence. We evaluated the performance of the new method with one other representative network-based function prediction method using E. coli protein functional association networks.

Conclusion

Our results showed that the new method has better prediction performance than the previous method. The better predictive power of our method gives new insights about the importance of the dependence between functional terms in protein functional prediction.

The bacterial cell-envelope consists of a complex arrangement of lipids, proteins and carbohydrates that serves as the interface between a microorganism and its environment or, with pathogens, a human host. Escherichia coli has long been investigated as a leading model system to elucidate the fundamental mechanisms underlying microbial cell-envelope biology. This includes extensive descriptions of the molecular identities, biochemical activities and evolutionary trajectories of integral transmembrane proteins, many of which play critical roles in infectious disease and antibiotic resistance. Strikingly, however, only half of the c. 1200 putative cell-envelope-related proteins of E. coli currently have experimentally attributed functions, indicating an opportunity for discovery. In this review, we summarize the state of the art of computational and proteomic approaches for determining the components of the E. coli cell-envelope proteome, as well as exploring the physical and functional interactions that underlie its biogenesis and functionality. We also provide a comprehensive comparative benchmarking analysis on the performance of different bioinformatic and proteomic methods commonly used to determine the subcellular localization of bacterial proteins.

Molecular chaperones are known to be involved in many cellular functions, however, a detailed and comprehensive overview of the interactions between chaperones and their cofactors and substrates is still absent. Systematic analysis of physical TAP-tag based protein–protein interactions of all known 63 chaperones in Saccharomyces cerevisiae has been carried out. These chaperones include seven small heat-shock proteins, three members of the AAA+ family, eight members of the CCT/TRiC complex, six members of the prefoldin/GimC complex, 22 Hsp40s, 1 Hsp60, 14 Hsp70s, and 2 Hsp90s. Our analysis provides a clear distinction between chaperones that are functionally promiscuous and chaperones that are functionally specific. We found that a given protein can interact with up to 25 different chaperones during its lifetime in the cell. The number of interacting chaperones was found to increase with the average number of hydrophobic stretches of length between one and five in a given protein. Importantly, cellular hot spots of chaperone interactions are elucidated. Our data suggest the presence of endogenous multicomponent chaperone modules in the cell.

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a “systems-wide” functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Author Summary

One goal of modern biology is to chart groups of proteins that act together to perform biological processes via direct and indirect interactions. Such groupings are sometimes called functional modules. The types of protein interactions within modules include physical interactions that generate protein complexes and biochemical associations that make up metabolic pathways. We have combined proteomic and bioinformatic tools, and used them to decipher a large number of protein interactions, complexes, and functional modules with high confidence. In addition, exploring the topology of the resulting interaction networks, we successfully predicted specific biological roles for a number of proteins with previously unknown functions, and identified some potential drug targets. Although our work is focused on E. coli, our phylogenetic projections suggest that a considerable fraction of our observations and predictions can be extrapolated to many other bacterial taxa. As all the data derived from this study are publicly available, others may build on our work for further hypothesis-driven studies of gene function discovery.

A novel resource integrating proteomic and genome context-based tools provides a "systems-wide" functional blueprint ofE. coli, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Protein ubiquitination is essential for many events linked to intracellular protein trafficking. We sought to elucidate the possible involvement of the S. cerevisiae deubiquitinating enzyme Ubp2 in transporter and receptor trafficking after we (this study) and others established that affinity purified Ubp2 interacts stably with the E3 ubiquitin ligase Rsp5 and the (ubiquitin associated) UBA domain containing protein Rup1. UBP2 interacts genetically with RSP5, while Rup1 facilitates the tethering of Ubp2 to Rsp5 via a PPPSY motif. Using the uracil permease Fur4 as a model reporter system, we establish a role for Ubp2 in membrane protein turnover. Similar to hypomorphic rsp5 alleles, cells deleted for UBP2 exhibited a temporal stabilization of Fur4 at the plasma membrane, indicative of perturbed protein trafficking. This defect was ubiquitin dependent, as a Fur4 N-terminal ubiquitin fusion construct bypassed the block and restored sorting in the mutant. Moreover, the defect was absent in conditions where recycling was absent, implicating Ubp2 in sorting at the multivesicular body. Taken together, our data suggest a previously overlooked role for Ubp2 as a positive regulator of Rsp5-mediated membrane protein trafficking subsequent to endocytosis.

Acetylation of Saccharomyces cerevisiae histone H3 on K56 by the histone acetyltransferase (HAT) Rtt109 is important for repairing replication-associated lesions. Rtt109 purifies from yeast in complex with the histone chaperone Vps75, which stabilizes the HAT in vivo. A whole-genome screen to identify genes whose deletions have synthetic genetic interactions with rtt109Δ suggests Rtt109 has functions in addition to DNA repair. We show that in addition to its known H3-K56 acetylation activity, Rtt109 is also an H3-K9 HAT, and we show that Rtt109 and Gcn5 are the only H3-K9 HATs in vivo. Rtt109's H3-K9 acetylation activity in vitro is enhanced strongly by Vps75. Another histone chaperone, Asf1, and Vps75 are both required for acetylation of lysine 9 on H3 (H3-K9ac) in vivo by Rtt109, whereas H3-K56ac in vivo requires only Asf1. Asf1 also physically interacts with the nuclear Hat1/Hat2/Hif1 complex that acetylates H4-K5 and H4-K12. We suggest Asf1 is capable of assembling into chromatin H3-H4 dimers diacetylated on both H4-K5/12 and H3-K9/56.

Genomic and proteomic approaches to cardiovascular medicine promise to revolutionize our understanding of disease initiation and progression. This improved appreciation of pathophysiology may be translated into avenues of clinical utility. Gene-based presymptomatic prediction of illness, finer diagnostic subclassifications and improved risk assessment tools will permit earlier and more targeted intervention. Pharmacogenetics will guide our therapeutic decisions and monitor response to therapy. Personalized medicine will require the integration of clinical information, stable and dynamic genomics, and molecular phenotyping. Bioinformatics will be crucial in translating these data into useful applications, leading to improved diagnosis, prediction, prognostication and treatment. The present paper reviews the potential contributions of genomic and proteomic approaches in developing a more personalized approach to cardiovascular medicine.

Abstract

High throughput methods are increasingly being used to examine the functions and interactions of gene products on a genome-scale. These include systematic large-scale proteomic studies of protein complexes and protein–protein interaction networks, functional genomic studies examining patterns of gene expression and comparative genomics studies examining patterns of conservation. Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways. Here we present Bacteriome.org, a resource that combines locally generated interaction and evolutionary datasets with a previously generated knowledgebase, to provide an integrated view of the Escherichia coli interactome. Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest. Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a ‘core’ high quality experimental dataset of 4863 interactions between 1100 proteins and an ‘extended’ experimental dataset of 9860 interactions between 2131 proteins. Bacteriome.org is available online at http://www.bacteriome.org.

Background

Histone modifications have been implicated in the regulation of transcription and, more recently, in DNA replication and repair. In yeast, a major conserved histone acetyltransferase, Hat1p, preferentially acetylates lysine residues 5 and 12 on histone H4.

Results

Here, we report that a nuclear sub-complex consisting of Hat1p and its partner Hat2p interacts physically and functionally with the origin recognition complex (ORC). While mutational inactivation of the histone acetyltransferase (HAT) gene HAT1 alone does not compromise origin firing or initiation of DNA replication, a deletion in HAT1 (or HAT2) exacerbates the growth defects of conditional orc-ts mutants. Thus, the ORC-associated Hat1p-dependent histone acetyltransferase activity suggests a novel linkage between histone modification and DNA replication. Additional genetic and biochemical evidence points to the existence of partly overlapping histone H3 acetyltransferase activities in addition to Hat1p/Hat2p for proper DNA replication efficiency. Furthermore, we demonstrated a dynamic association of Hat1p with chromatin during S-phase that suggests a role of this enzyme at the replication fork.

Conclusion

We have found an intriguing new association of the Hat1p-dependent histone acetyltransferase in addition to its previously known role in nuclear chromatin assembly (Hat1p/Hat2p-Hif1p). The participation of a distinct Hat1p/Hat2p sub-complex suggests a linkage of histone H4 modification with ORC-dependent DNA replication.

Although microarray analysis has provided information regarding the dynamics of gene expression during development of the mouse lung, no extensive correlations have been made to the levels of corresponding protein products. Here, we present a global survey of protein expression during mouse lung organogenesis from embryonic day E13.5 until adulthood using gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry (MudPIT). Mathematical modeling of the proteomic profiles with parallel DNA microarray data identified large groups of gene products with statistically significant correlation or divergence in coregulation of protein and transcript levels during lung development. We also present an integrative analysis of mRNA and protein expression in Nmyc loss- and gain-of-function mutants. This revealed a set of 90 positively and negatively regulated putative target genes. These targets are evidence that Nmyc is a regulator of genes involved in mRNA processing and a repressor of the imprinted gene Igf2r in the developing lung.

Pre-mRNA processing, including 5' end capping, splicing, and 3' end cleavage/polyadenylation, are events coordinated by transcription that can influence the subsequent export and translation of mRNAs. Coordination of RNA processing is crucial in retroviruses such as HIV-1, where inefficient splicing and the export of intron-containing RNAs are required for expression of the full complement of viral proteins. RNA processing can be affected by both viral and cellular proteins, and in this study we demonstrate that a member of the hnRNP E family of proteins can modulate HIV-1 RNA metabolism and expression. We show that hnRNP E1/E2 are able to interact with the ESS3a element of the bipartite ESS in tat/rev exon 3 of HIV-1 and that modulation of hnRNP E1 expression alters HIV-1 structural protein synthesis. Overexpression of hnRNP E1 leads to a reduction in Rev, achieved in part through a decrease in rev mRNA levels. However, the reduction in Rev levels cannot fully account for the effect of hnRNP E1, suggesting that hmRNP E1 might also act to suppress viral RNA translation. Deletion mutagenesis determined that the C-terminal end of hnRNP E1 was required for the reduction in Rev expression and that replacing this portion of hnRNP E1 with that of hnRNP E2, despite the high degree of conservation, could not rescue the loss of function.

Background

Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions.

Results

Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30) and YMR135C (gid8) yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c). The observed interaction was confirmed by tandem affinity purification (TAP tag), verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any) on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not included in genome-wide yeast TAP tagging projects.

Conclusion

PIPE analysis can predict yeast protein-protein interactions. Also, PIPE analysis can be used to study the internal architecture of yeast protein complexes. The data also suggests that a finite set of short polypeptide signals seem to be responsible for the majority of the yeast protein-protein interactions.