Roles for the two-hybrid system in exploration of the yeast protein interactome

Activity-based protein profiling: from enzyme chemistry to proteomic chemistry

Genome sequencing projects have provided researchers with a complete inventory of the predicted proteins produced by eukaryotic and prokaryotic organisms. Assignment of functions to these proteins represents one of the principal challenges for the field of proteomics. Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale. Here, we review the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.

Fishing for anti-leishmania drugs: principles and problems

To date, there are no vaccines against any of the major parasitic diseases including leishmaniasis, and chemotherapy is the main weapon in our arsenal. Current drugs are toxic and expensive, and are losing their effectiveness due to parasite resistance. The availability of the genome sequence of two species of Leishmania, Leishmania major and Leishmania infantum, as well as that of Trypanosoma brucei and Trypanosoma cruzi should provide a cornucopia of potential new drug targets. Their exploitation will require a multi-disciplinary approach that includes protein structure and function and high throughput screening of random and directed chemical libraries, followed by in vivo testing in animals and humans. We outline the opportunities that are made possible by recent technologies, and potential problems that need to be overcome.

Integrating metabolomics and phenomics with systems models of cardiac hypoxia

Hypoxia is the major cause of necrotic cell death in myocardial infarction. Cellular energy supply and demand under hypoxic conditions is regulated by many interacting signaling and transcriptional networks, which complicates studies on individual proteins and pathways. We apply an integrated systems approach to understand the metabolic and functional response to hypoxia in muscle cells of the fruit fly Drosophila melanogaster. In addition to its utility as a hypoxia-tolerant model organism, Drosophila also offers advantages due to its small size, fecundity, and short life cycle. These traits, along with a large library of single-gene mutations, motivated us to develop new, computer-automated technology for gathering in vivo measurements of heart function under hypoxia for a large number of mutant strains. Phenotype data can be integrated with in silico cellular networks, metabolomic data, and microarrays to form qualitative and quantitative network models for prediction and hypothesis generation. Here we present a framework for a systems approach to hypoxia in the cardiac myocyte, starting from nuclear magnetic resonance (NMR) metabolomics, a constraint-based metabolic model, and phenotypic profiles.

New fast BiFC plasmid assay system for in vivo protein-protein interactions

In this age of massive genetic and protein information, a fast and reliable method of studying in vivo protein-protein interactions is necessary. We have developed a novel system that can overcome limitations of existing assay methods. This new method adopts two existing systems for fast analysis of diverse protein-protein interactions. For rapid, large-scale cloning, we adopted the Gateway system and developed novel destination vectors containing YFP N-terminus (YN) or YFP C-terminus (YC) to visualize protein-protein interactions in vivo using bimolecular fluorescence complementation (BiFC). Using this system, we investigated molecular interactions among the three POZ-domain regulatory proteins mAPM-1, LRF, KLHL10 that belong to a subgroup of human POZ-domain proteins, and showed that the POZ-domains of mAPM-1, LRF and KLHL10 could form both homodimers and heterodimers. This new method is a highly efficient, sensitive and specific assay method for protein-protein interaction in vivo.

PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

BACKGROUND

A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem.

RESULTS

In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules.

CONCLUSION

Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives). In our study, S. cerevisiae (yeast) data is used to demonstrate the effectiveness of our method.

Co-immunoprecipitations revisited: an update on experimental concepts and their implementation for sensitive interactome investigations of endogenous proteins

The study of protein-protein interactions involving endogenous proteins frequently relies on the immunoaffinity capture of a protein of interest followed by mass spectrometry-based identification of co-purifying interactors. A notorious problem with this approach is the difficulty of distinguishing physiological interactors from unspecific binders. Additional challenges pose the need to employ a strategy that is compatible with downstream mass spectrometry and minimizes sample losses during handling steps. Finally, the complexity of data sets demands solutions for data filtering. Here we present an update on co-immunoprecipitation procedures for sensitive interactome mapping applications. We define the relevant terminology, review methodological advances that reduce sample losses, and discuss experimental strategies that facilitate recognition of candidate interactors through a combination of informative controls and data filtering. Finally, we provide starting points for initial validation experiments and propose conventions for manuscripts which report on co-immunoprecipitation work.

Affinity chromatography: A useful tool in proteomics studies

Separation or fractionation of a biological sample in order to reduce its complexity is often a prerequisite to qualitative or quantitative proteomic approaches. Affinity chromatography is an efficient protein separation method based on the interaction between target proteins and specific immobilized ligands. The large range of available ligands allows to separate a complex biological extract in different protein classes or to isolate the low abundance species such as post-translationally modified proteins. This method plays an essential role in the isolation of protein complexes and in the identification of protein-protein interaction networks. Affinity chromatography is also required for quantification of protein expression by using isotope-coded affinity tags.

Cell size at S phase initiation: an emergent property of the G1/S network

The eukaryotic cell cycle is the repeated sequence of events that enable the division of a cell into two daughter cells. It is divided into four phases: G₁, S, G₂, and M. Passage through the cell cycle is strictly regulated by a molecular interaction network, which involves the periodic synthesis and destruction of cyclins that bind and activate cyclin-dependent kinases that are present in nonlimiting amounts. Cyclin-dependent kinase inhibitors contribute to cell cycle control. Budding yeast is an established model organism for cell cycle studies, and several mathematical models have been proposed for its cell cycle. An area of major relevance in cell cycle control is the G₁ to S transition. In any given growth condition, it is characterized by the requirement of a specific, critical cell size, P_S, to enter S phase. The molecular basis of this control is still under discussion. The authors report a mathematical model of the G₁ to S network that newly takes into account nucleo/cytoplasmic localization, the role of the cyclin-dependent kinase Sic1 in facilitating nuclear import of its cognate Cdk1-Clb5, Whi5 control, and carbon source regulation of Sic1 and Sic1-containing complexes. The model was implemented by a set of ordinary differential equations that describe the temporal change of the concentration of the involved proteins and protein complexes. The model was tested by simulation in several genetic and nutritional setups and was found to be neatly consistent with experimental data. To estimate P_S, the authors developed a hybrid model including a probabilistic component for firing of DNA replication origins. Sensitivity analysis of P_S provides a novel relevant conclusion: P_S is an emergent property of the G₁ to S network that strongly depends on growth rate.

A major property of living cells is their ability to maintain mass homeostasis throughout cell divisions. It has been proposed that in order to achieve such homeostasis, some critical event(s) in the cell cycle will take place only when the cell has grown beyond a critical cell size. In the budding yeast Saccharomyces cerevisiae, a widely used model for the study of the eukaryotic cell cycle, a large body of evidence indicates that cells have to reach a critical size before they start to replicate their DNA and to form bud, which will give rise to the daughter cell. This critical cell size is modulated by growth rate, hence by nutritional conditions and the multiplicity of genetic material (i.e., ploidy). The authors present a mathematical model of the regulatory molecular network acting at the G₁ to S transition. The major novel features of this model compared with previous models of this process are (1) the accounting for cell growth (i.e., the increase in cell volume); (2) the explicit consideration of the fact that cells have a nucleus and a cytoplasm, and that key cell cycle regulatory molecules must move between these different compartments and can only react or regulate each other if they are in the same compartment; and (3) the requirement of sequential overcoming of two molecular thresholds given by a cyclin-dependent kinase/cyclin and a cyclin-dependent kinase inhibitor. The model was tested by simulating the processes during G₁ to S transition for different growth conditions or for different mutants and by comparing the results with experimental data. A parameter sensitivity analysis (i.e., testing the model predictions when parameters are varied), newly indicates that the critical cell size is an emergent property of the G₁ to S network. The model leads to a unified interpretation of seemingly disparate experimental observations and makes predictions to be experimentally verified.

The type 2 dengue virus envelope protein interacts with small ubiquitin-like modifier-1 (SUMO-1) conjugating enzyme 9 (Ubc9)

Dengue viruses are mosquito-borne flaviviruses and may cause the life-threatening dengue hemorrhagic fever and dengue shock syndrome. Its envelope protein is responsible mainly for the virus attachment and entry to host cells. To identify the human cellular proteins interacting with the envelope protein of dengue virus serotype 2 inside host cells, we have performed a screening with the yeast-two-hybrid-based "Functional Yeast Array". Interestingly, the small ubiquitin-like modifier-1 conjugating enzyme 9 protein, modulating cellular processes such as those regulating signal transduction and cell growth, was one of the candidates interacting with the dengue virus envelope protein. With co-precipitation assay, we have demonstrated that it indeed could interact directly with the Ubc9 protein. Site-directed mutagenesis has demonstrated that Ubc9 might interact with the E protein via amino acid residues K51 and K241. Furthermore, immunofluorescence microscopy has shown that the DV2E-EGFP proteins tended to progress toward the nuclear membrane and co-localized with Flag-Ubc9 proteins around the nuclear membrane in the cytoplasmic side, and DV2E-EGFP also shifted the distribution of Flag-Ubc9 from evenly in the nucleus toward concentrating around the nuclear membrane in the nucleic side. In addition, over-expression of Ubc9 could reduce the plaque formation of the dengue virus in mammalian cells. This is the first report that DV envelope proteins can interact with the protein of sumoylation system and Ubc9 may involve in the host defense system to prevent virus propagation.

All duplicates are not equal: the difference between small-scale and genome duplication

BACKGROUND

Genes in populations are in constant flux, being gained through duplication and occasionally retained or, more frequently, lost from the genome. In this study we compare pairs of identifiable gene duplicates generated by small-scale (predominantly single-gene) duplications with those created by a large-scale gene duplication event (whole-genome duplication) in the yeast Saccharomyces cerevisiae.

RESULTS

We find a number of quantifiable differences between these data sets. Whole-genome duplicates tend to exhibit less profound phenotypic effects when deleted, are functionally less divergent, and are associated with a different set of functions than their small-scale duplicate counterparts. At first sight, either of these latter two features could provide a plausible mechanism by which the difference in dispensability might arise. However, we uncover no evidence suggesting that this is the case. We find that the difference in dispensability observed between the two duplicate types is limited to gene products found within protein complexes, and probably results from differences in the relative strength of the evolutionary pressures present following each type of duplication event.

CONCLUSION

Genes, and the proteins they specify, originating from small-scale and whole-genome duplication events differ in quantifiable ways. We infer that this is not due to their association with different functional categories; rather, it is a direct result of biases in gene retention.

Cataloging the relationships between proteins: a review of interaction databases

By organizing and making widely accessible the increasing amounts of data from high-throughput analyses, protein interaction databases have become an integral resource for the biological community in relating sequence data with higher-order function. To provide a sense of the use and applicability of these databases, we describe each of the major comprehensive interaction databases as well as some of the more specialized ones. Content description, search/browse functionalities, and data presentation are discussed. A succinct explanation of database contents helps the user quickly identify whether the database contains applicable information to their research interest. Broad levels of search/browse functions as well as descriptions/examples allow users to quickly find and access pertinent data. At this point, clear presentation of search results as well as the primary content is necessary. Many databases display information graphically or divided into smaller digestible parts over a number of tabbed/linked pages. In addition, cross-linking between the databases promotes interconnectivity of the data and is an added layer of relational data for the user. Overall, although these protein interaction databases are under continual improvement, their current state shows that much time and effort has gone into organizing and presenting these large sets of data-describing protein interactions.

Ions of the interactome: The role of MS in the study of protein interactions in proteomics and structural biology

The role of MS in the study of protein-protein interactions in solution is described from a proteomics perspective, in terms of high-throughput analyses of protein complexes in vivo, through to chemical and biochemical treatments ahead of MS analysis in the context of complementary experimental approaches in structural biology. The use of MS to characterise protein-protein interactions is described following the single and tandem affinity purification of protein complexes and assemblies of expressed proteins in host cells, the isolation and preservation of protein complexes on surfaces and microarrays, and their prior treatment with chemical and biochemical probes by hydrogen exchange, radical probe, chemical cross-linking, and limited proteolysis. The advantages and disadvantages of each of the approaches are presented. These new and emerging applications, which further demonstrate the power of MS, continue to ensure that the mass spectrometer will remain at the heart of discoveries in proteomics in the foreseeable future.

Biomarker discovery and compound evaluation using two-hybrid proteomic systems

Many proteomic technologies require a heavy investment in expertise and technology, which place these approaches beyond many labs and small companies. However, proteomic approaches are ideal for pilot experiments, identifying relevant biomarkers and protein pathways for development or analysis of therapeutic compounds. The two-hybrid proteomic systems are available and affordable to most researchers, requiring little more than standard microbiological equipment. The screens rapidly generate data, identifying protein interactions that can be used to construct small local protein networks. Using data from large-scale projects, these small local protein networks can be used to identify the larger cellular pathways that are being affected by therapeutic compounds in the screen. The foundation for the two-hybrid proteomic systems are commercially available, as are high quality cDNA libraries. The straightforwardness of the two-hybrid proteomic system allows smaller groups to focus their resources on critical cellular pathways and molecular targets by taking advantage of a trusted molecular assay and an ever growing set of postgenomic era databases.

Yeast Protein Interactome topology provides framework for coordinated-functionality

The architecture of the network of protein–protein physical interactions in Saccharomyces cerevisiae is exposed through the combination of two complementary theoretical network measures, betweenness centrality and ‘Q-modularity’. The yeast interactome is characterized by well-defined topological modules connected via a small number of inter-module protein interactions. Should such topological inter-module connections turn out to constitute a form of functional coordination between the modules, we speculate that this coordination is occurring typically in a pairwise fashion, rather than by way of high-degree hub proteins responsible for coordinating multiple modules. The unique non-hub-centric hierarchical organization of the interactome is not reproduced by gene duplication-and-divergence stochastic growth models that disregard global selective pressures.

The model organism as a system: integrating 'omics' data sets

Various technologies can be used to produce genome-scale, or 'omics', data sets that provide systems-level measurements for virtually all types of cellular components in a model organism. These data yield unprecedented views of the cellular inner workings. However, this abundance of information also presents many hurdles, the main one being the extraction of discernable biological meaning from multiple omics data sets. Nevertheless, researchers are rising to the challenge by using omics data integration to address fundamental biological questions that would increase our understanding of systems as a whole.

Large-scale identification of protein-protein interaction of Escherichia coli K-12

Protein-protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni2+-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.

Converging on a general model of protein evolution

The availability of high-throughput genomic databases that establish protein dispensability, expression and interaction networks enables rigorous tests of competing models of protein evolution. Recent research utilizing these new data sets shows that protein evolution is more complex than was previously thought. Several variables, including protein dispensability, expression, functional density, and genetic modularity, appear to have independent effects on the evolutionary rate of proteins, suggesting that proteomes have evolved via an assembly of selectional regimes. These results indicate that a general model of protein evolution will emerge as more functional genomic data from a diversity of organisms accumulate.

A yeast two-hybrid knockout strain to explore thioredoxin-interacting proteins in vivo

All organisms contain thioredoxin (TRX), a regulatory thiol:disulfide protein that reduces disulfide bonds in target proteins. Unlike animals and yeast, plants contain numerous TRXs for which no function has been assigned in vivo. Recent in vitro proteomic approaches have opened the way to the identification of >100 TRX putative targets, but of which none of the numerous plant TRXs can be specifically associated. In contrast, in vivo methodologies, including classical yeast two-hybrid (Y2H) systems, failed to reveal the expected high number of TRX targets. Here, we developed a yeast strain named CY306 designed to identify TRX targets in vivo by a Y2H approach. CY306 contains a GAL4 reporter system but also carries deletions of endogenous genes encoding cytosolic TRXs (TRX1 and TRX2) that presumably compete with TRXs introduced as bait. We demonstrate here that, in the CY306 strain, yeast TRX1 and TRX2, as well as Arabidopsis TRX introduced as bait, interact with known TRX targets or putative partners such as yeast peroxiredoxins AHP1 and TSA1, whereas the same interactions cannot be detected in classical Y2H strains. Thanks to CY306, we also show that TRXs interact with the phosphoadenosine-5-phosphosulfate (PAPS) reductase MET16 through a conserved cysteine. Moreover, interactions visualized in CY306 are highly specific depending on the TRX and targets tested. CY306 constitutes a relevant genetic system to explore the TRX interactome in vivo and with high specificity, and opens new perspectives in the search for new TRX-interacting proteins by Y2H library screening in organisms with multiple TRXs.

Emerging tools for real-time label-free detection of interactions on functional protein microarrays

The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions--yeast two-hybrid and immunoprecipitation with mass spectrometric detection--have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.

Weak protein-protein interactions as probed by NMR spectroscopy

Weak protein-protein interactions (PPIs) are fundamental to many cellular processes, such as reversible cell-cell contact, rapid enzyme turnover and transient assembly and/or reassembly of large signaling complexes. However, structural and functional characterizations of weak PPIs have been technically challenging and lagged behind those for strong PPIs. Here, we describe nuclear magnetic resonance (NMR) spectroscopy as a highly effective tool for unraveling the atomic details of weak PPIs. We highlight the recent advances of how NMR can be used to rapidly detect and structurally determine extremely weak PPIs (K(d)>10(-4)M). Coupled with functional approaches, NMR has the potential to look into a wide variety of biologically important weak PPIs at the detailed molecular level, thereby facilitating a thorough view of how proteins function in living cells.

Effect of sampling on topology predictions of protein-protein interaction networks

Currently available protein-protein interaction (PPI) network or 'interactome' maps, obtained with the yeast two-hybrid (Y2H) assay or by co-affinity purification followed by mass spectrometry (co-AP/MS), only cover a fraction of the complete PPI networks. These partial networks display scale-free topologies--most proteins participate in only a few interactions whereas a few proteins have many interaction partners. Here we analyze whether the scale-free topologies of the partial networks obtained from Y2H assays can be used to accurately infer the topology of complete interactomes. We generated four theoretical interaction networks of different topologies (random, exponential, power law, truncated normal). Partial sampling of these networks resulted in sub-networks with topological characteristics that were virtually indistinguishable from those of currently available Y2H-derived partial interactome maps. We conclude that given the current limited coverage levels, the observed scale-free topology of existing interactome maps cannot be confidently extrapolated to complete interactomes.

Interactome: gateway into systems biology

Protein-protein interactions are fundamental to all biological processes, and a comprehensive determination of all protein-protein interactions that can take place in an organism provides a framework for understanding biology as an integrated system. The availability of genome-scale sets of cloned open reading frames has facilitated systematic efforts at creating proteome-scale data sets of protein-protein interactions, which are represented as complex networks or 'interactome' maps. Protein-protein interaction mapping projects that follow stringent criteria, coupled with experimental validation in orthogonal systems, provide high-confidence data sets immanently useful for interrogating developmental and disease mechanisms at a system level as well as elucidating individual protein function and interactome network topology. Although far from complete, currently available maps provide insight into how biochemical properties of proteins and protein complexes are integrated into biological systems. Such maps are also a useful resource to predict the function(s) of thousands of genes.

Oracle Database 10g: a platform for BLAST search and Regular Expression pattern matching in life sciences

As database management systems expand their array of analytical functionality, they become powerful research engines for biomedical data analysis and drug discovery. Databases can hold most of the data types commonly required in life sciences and consequently can be used as flexible platforms for the implementation of knowledgebases. Performing data analysis in the database simplifies data management by minimizing the movement of data from disks to memory, allowing pre-filtering and post-processing of datasets, and enabling data to remain in a secure, highly available environment. This article describes the Oracle Database 10g implementation of BLAST and Regular Expression Searches and provides case studies of their usage in bioinformatics. http://www.oracle.com/technology/software/index.html

Shared components of protein complexes--versatile building blocks or biochemical artefacts?

Protein complexes perform many important functions in the cell. Large-scale studies of protein-protein interactions have not only revealed new complexes but have also placed many proteins into multiple complexes. Whilst the advocates of hypothesis-free research touted the discovery of these shared components as new links between diverse cellular processes, critical commentators denounced many of the findings as artefacts, thus questioning the usefulness of large-scale approaches. Here, we survey proteins known to be shared between complexes, as established in the literature, and compare them to shared components found in high-throughput screens. We discuss the various challenges to the identification and functional interpretation of bona fide shared components, namely contaminants, variant and megacomplexes, and transient interactions, and suggest that many of the novel shared components found in high-throughput screens are neither the results of contamination nor central components, but appear to be primarily regulatory links in cellular processes.

Novel mobilizable prokaryotic two-hybrid system vectors for high-throughput protein interaction mapping in Escherichia coli by bacterial conjugation

Since its initial description, the yeast two-hybrid (Y2H) system has been widely used for the detection and analysis of protein–protein interactions. Mating-based strategies have been developed permitting its application for automated proteomic interaction mapping projects using both exhaustive and high-throughput strategies. More recently, a number of prokaryotic two-hybrid (P2H) systems have been developed but, despite the many advantages such Escherichia coli-based systems have over the Y2H system, they have not yet been widely implemented for proteomic interaction mapping. This may be largely due to the fact that high-throughput strategies employing bacterial transformation are not as amenable to automation as Y2H mating-based strategies. Here, we describe the construction of novel conjugative P2H system vectors. These vectors carry a mobilization element of the IncPα group plasmid RP4 and can therefore be mobilized with high efficiency from an E.coli donor strain encoding all of the required transport functions in trans. We demonstrate how these vectors permit the exploitation of bacterial conjugation for technically simplified and automated proteomic interaction mapping strategies in E.coli, analogous to the mating-based strategies developed for the Y2H system.

Studying the interactome with the yeast two-hybrid system and mass spectrometry

Protein interactions are crucial to the life of a cell. The analysis of such interactions is allowing biologists to determine the function of uncharacterized proteins and the genes that encode them. The yeast two-hybrid system has become one of the most popular and powerful tools to study protein-protein interactions. With the advent of proteomics, the two-hybrid system has found a niche in interactome mapping. However, it is clear that only by combining two-hybrid data with that from complementary approaches such as mass spectrometry (MS) can the interactome be analyzed in full. This review introduces the yeast two-hybrid system to those unfamiliar with the technique, and discusses how it can be used in combination with MS to unravel the network of protein interactions that occur in a cell.

Exhaustive identification of interaction domains using a high-throughput method based on two-hybrid screening and PCR-convergence: molecular dissection of a kinetochore subunit Spc34p

The Dam1 complex, also known as DASH complex, is the outer kinetochore protein complex of yeast that plays a crucial role in attachment of kinetochore to microtubule. The Dam1 complex is formed by at least nine proteins including Dam1p, Duo1p, Dad1p, Spc19p and Spc34p. In this study, domains of Spc34p that physically interact with other subunits of the complex were mapped using a high-throughput methodology. The method is a combination of two-hybrid screening of a random truncation library of the Spc34 gene and a unique PCR-based amplification that converge the selected DNA fragments to a few short fragments. Duo1p, Dam1p, Dad1p and Spc19p binding domains of Spc34p were mapped on M1-E59, M1-D47, M1-D47 or T207-E295 and S154-Q294, respectively. Most of the boundaries were located at less conserved regions among fungal Spc34p homologs, which is consistent with the boundaries of the putative secondary structures. The accuracy of the mapped domain boundaries was verified using truncated Spc34p polypeptides. The results and methodology we demonstrated herein not only shed light on the molecular architecture of the protein complex but also pave the road to the high-throughput identification of specific interaction domains of proteins whose possible interaction partners have been identified in genome-scale analyses.

Biochemical characterization of protein complexes from the Helicobacter pylori protein interaction map: strategies for complex formation and evidence for novel interactions within type IV secretion systems

We have investigated a large set of interactions from the Helicobacter pylori protein interaction map previously identified by high-throughput yeast two-hybrid (htY2H)-based methods. This study had two aims: i) to validate htY2H as a source of protein-protein interaction complexes for high-throughput biochemical and structural studies of the H. pylori interactome; and ii) to validate biochemically interactions shown by htY2H to involve components of the H. pylori type IV secretion systems. Thus, 17 interactions involving 31 proteins and protein fragments were studied, and a general strategy was designed to produce protein-interacting partners for biochemical and structural characterization. We show that htY2H is a valid source of protein-protein complexes for high-throughput proteome-scale characterization of the H. pylori interactome, because 76% of the interactions tested were confirmed biochemically. Of the interactions involving type IV secretion proteins, three could be confirmed. One interaction is between two components of the type IV secretion apparatus, ComB10 and ComB4, which are VirB10 and VirB4 homologs, respectively. Another interaction is between a type IV component (HP0525, a VirB11 homolog) and a non-type IV secretion protein (HP01451), indicating that proteins other than the core VirB (1-11)-VirD4 proteins may play a role in type IV secretion. Finally, a third interaction was biochemically confirmed between CagA, a virulence factor secreted by the type IV secretion system encoded by the Cag pathogenicity island, and a non-type IV secretion protein, HP0496.

Recent developments in the analysis of protein complexes

The goal of this review is to analyse how recent technical developments contributed to the biochemical characterisation of protein complexes. Improvement of tags used for protein purification, including in our own laboratory, and the development of new strategies have allowed the use of generic procedures for the purification of a wide variety of protein complexes. Together with increased mass spectrometry sensitivity and automation, this made high throughput studies of protein complexes possible and allowed proteome-wide analyses of protein complexes. However, knowledge of protein complex composition, even at the cellular level, will not be sufficient to understand their function. We suggest that the next level of analysis in this area will be the definition of internal subunit arrangement in complexes as a first step toward more detailed structural analyses.

A Comparative Analysis of an Orthologous Proteomic Environment in the Yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe

The sequential application of protein tagging, affinity purification, and mass spectrometry enables highly accurate charting of proteomic environments by the characterization of stable protein assemblies and the identification of subunits that are shared between two or more protein complexes, termed here "proteomic hyperlinks." We have charted the proteomic environments surrounding the histone methyltransferase, Set1, in both yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe. Although the composition of these nonessential Set1 complexes is remarkably conserved, they differ with respect to their hyperlinks to their proteomic environments. We speculate that conservation of the core components of protein assemblies and variability of hyperlinks represents a general principle in the molecular organization of eukaryotic proteomes.

Digitizing life at the level of the cell: high-performance laser-scanning microscopy and image analysis for in toto imaging of development

The field of biological imaging is progressing at an amazing rate. Advances in both laser-scanning microscopy and green fluorescent protein (GFP) technology are combining to make possible imaging-based approaches for studying developmental mechanisms that were previously impossible. Modern confocal and multi-photon microscopes are pushing the envelope of speed, sensitivity, spectral resolution, and depth resolution to allow in vivo imaging of whole, live embryos at cellular resolution over extended periods of time. In toto imaging, in which nearly every cell in an embryo or tissue can be tracked through space and time during development, may become a standard technique for small transparent embryos such as zebrafish and early stage chick and mouse embryos. GFP and its spectral variants can be used to mark a wide range of in vivo biological information for in toto imaging including gene expression patterns, mutant phenotypes, and protein subcellular localization patterns. Combining in toto imaging and GFP transgenic approaches on a large scale may usher in an explosion of in vivo, developmental data as has happened in the past several years with genomic data. There are significant challenges that must be met to reach these goals. This paper will discuss the current state-of-the-art, the challenges, and the prospects of in toto imaging in the areas of imaging, image analysis, and informatics.