Jean François Rual

Towards a proteome-scale map of the human protein-protein interaction network.

Systematic mapping of protein–protein interactions, or ‘interactome’ mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein–protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of ∼8,100 currently available Gateway-cloned open reading frames and detected ∼2,800 interactions. This data set, called CCSB-HI1, has a verification rate of ∼78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by ∼70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.

High-quality binary protein interaction map of the yeast interactome network

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a “second-generation” high-quality, high-throughput Y2H data set covering ∼20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

A Protein–Protein Interaction Network for Human Inherited Ataxias and Disorders of Purkinje Cell Degeneration

Many human inherited neurodegenerative disorders are characterized by loss of balance due to cerebellar Purkinje cell (PC) degeneration. Although the disease-causing mutations have been identified for a number of these disorders, the normal functions of the proteins involved remain, in many cases, unknown. To gain insight into the function of proteins involved in PC degeneration, we developed an interaction network for 54 proteins involved in 23 inherited ataxias and expanded the network by incorporating literature-curated and evolutionarily conserved interactions. We identified 770 mostly novel protein-protein interactions using a stringent yeast two-hybrid screen; of 75 pairs tested, 83% of the interactions were verified in mammalian cells. Many ataxia-causing proteins share interacting partners, a subset of which have been found to modify neurodegeneration in animal models. This interactome thus provides a tool for understanding pathogenic mechanisms common for this class of neurodegenerative disorders and for identifying candidate genes for inherited ataxias.

A Protein Complex Network of Drosophila melanogaster

Determining the composition of protein complexes is an essential step toward understanding the cell as an integrated system. Using coaffinity purification coupled to mass spectrometry analysis, we examined protein associations involving nearly 5,000 individual, FLAG-HA epitope-tagged Drosophila proteins. Stringent analysis of these data, based on a statistical framework designed to define individual protein-protein interactions, led to the generation of a Drosophila protein interaction map (DPiM) encompassing 556 protein complexes. The high quality of the DPiM and its usefulness as a paradigm for metazoan proteomes are apparent from the recovery of many known complexes, significant enrichment for shared functional attributes, and validation in human cells. The DPiM defines potential novel members for several important protein complexes and assigns functional links to 586 protein-coding genes lacking previous experimental annotation. The DPiM represents, to our knowledge, the largest metazoan protein complex map and provides a valuable resource for analysis of protein complex evolution.

Systematic analysis of genes required for synapse structure and function

Chemical synapses are complex structures that mediate rapid intercellular signalling in the nervous system. Proteomic studies suggest that several hundred proteins will be found at synaptic specializations. Here we describe a systematic screen to identify genes required for the function or development of Caenorhabditis elegans neuromuscular junctions. A total of 185 genes were identified in an RNA interference screen for decreased acetylcholine secretion; 132 of these genes had not previously been implicated in synaptic transmission. Functional profiles for these genes were determined by comparing secretion defects observed after RNA interference under a variety of conditions. Hierarchical clustering identified groups of functionally related genes, including those involved in the synaptic vesicle cycle, neuropeptide signalling and responsiveness to phorbol esters. Twenty-four genes encoded proteins that were localized to presynaptic specializations. Loss-of-function mutations in 12 genes caused defects in presynaptic structure.

An experimentally derived confidence score for binary protein-protein interactions

Information on protein-protein interactions is of central importance for many areas of biomedical research. At present no method exists to systematically and experimentally assess the quality of individual interactions reported in interaction mapping experiments. To provide a standardized confidence-scoring method that can be applied to tens of thousands of protein interactions, we have developed an interaction tool kit consisting of four complementary, high-throughput protein interaction assays. We benchmarked these assays against positive and random reference sets consisting of well documented pairs of interacting human proteins and randomly chosen protein pairs, respectively. A logistic regression model was trained using the data from these reference sets to combine the assay outputs and calculate the probability that any newly identified interaction pair is a true biophysical interaction once it has been tested in the tool kit. This general approach will allow a systematic and empirical assignment of confidence scores to all individual protein-protein interactions in interactome networks.

Systematic Interactome Mapping and Genetic Perturbation Analysis of a C. elegans TGF-β Signaling Network

To initiate a system-level analysis of C. elegans DAF-7/TGF-beta signaling, we combined interactome mapping with single and double genetic perturbations. Yeast two-hybrid (Y2H) screens starting with known DAF-7/TGF-beta pathway components defined a network of 71 interactions among 59 proteins. Coaffinity purification (co-AP) assays in mammalian cells confirmed the overall quality of this network. Systematic perturbations of the network using RNAi, both in wild-type and daf-7/TGF-beta pathway mutant animals, identified nine DAF-7/TGF-beta signaling modifiers, seven of which are conserved in humans. We show that one of these has functional homology to human SNO/SKI oncoproteins and that mutations at the corresponding genetic locus daf-5 confer defects in DAF-7/TGF-beta signaling. Our results reveal substantial molecular complexity in DAF-7/TGF-beta signal transduction. Integrating interactome maps with systematic genetic perturbations may be useful for developing a systems biology approach to this and other signaling modules.

RNAi Screening Implicates a SKN-1-Dependent Transcriptional Response in Stress Resistance and Longevity Deriving from Translation Inhibition

Caenorhabditis elegans SKN-1 (ortholog of mammalian Nrf1/2/3) is critical for oxidative stress resistance and promotes longevity under reduced insulin/IGF-1–like signaling (IIS), dietary restriction (DR), and normal conditions. SKN-1 inducibly activates genes involved in detoxification, protein homeostasis, and other functions in response to stress. Here we used genome-scale RNA interference (RNAi) screening to identify mechanisms that prevent inappropriate SKN-1 target gene expression under non-stressed conditions. We identified 41 genes for which knockdown leads to activation of a SKN-1 target gene (gcs-1) through skn-1-dependent or other mechanisms. These genes correspond to multiple cellular processes, including mRNA translation. Inhibition of translation is known to increase longevity and stress resistance and may be important for DR–induced lifespan extension. One model postulates that these effects derive from reduced energy needs, but various observations suggest that specific longevity pathways are involved. Here we show that translation initiation factor RNAi robustly induces SKN-1 target gene transcription and confers skn-1-dependent oxidative stress resistance. The accompanying increases in longevity are mediated largely through the activities of SKN-1 and the transcription factor DAF-16 (FOXO), which is required for longevity that derives from reduced IIS. Our results indicate that the SKN-1 detoxification gene network monitors various metabolic and regulatory processes. Interference with one of these processes, translation initiation, leads to a transcriptional response whereby SKN-1 promotes stress resistance and functions together with DAF-16 to extend lifespan. This stress response may be beneficial for coping with situations that are associated with reduced protein synthesis.

Identification of a Brucella spp. secreted effector specifically interacting with human small GTPase Rab2

Bacteria of the Brucella genus are facultative intracellular class III pathogens. These bacteria are able to control the intracellular trafficking of their vacuole, presumably by the use of yet unknown translocated effectors. To identify such effectors, we used a high‐throughput yeast two‐hybrid screen to identify interactions between putative human phagosomal proteins and predicted Brucella spp. proteins. We identified a specific interaction between the human small GTPase Rab2 and a Brucella spp. protein named RicA. This interaction was confirmed by GST‐pull‐down with the GDP‐bound form of Rab2. A TEM‐β‐lactamase‐RicA fusion was translocated from Brucella abortus to RAW264.7 macrophages during infection. This translocation was not detectable in a strain deleted for the virB operon, coding for the type IV secretion system. However, RicA secretion in a bacteriological culture was still observed in a ΔvirB mutant. In HeLa cells, a ΔricA mutant recruits less GTP‐locked myc‐Rab2 on its Brucella‐containing vacuoles, compared with the wild‐type strain. We observed altered kinetics of intracellular trafficking and faster proliferation of the B. abortusΔricA mutant in HeLa cells, compared with the wild‐type control. Altogether, the data reported here suggest RicA as the first reported effector with a proposed function for B. abortus.

Large-scale RNAi screens identify novel genes that interact with the C. elegans retinoblastoma pathway as well as splicing-related components with synMuv B activity

BackgroundThe retinoblastoma tumor suppressor (Rb) acts in a conserved pathway that is deregulated in most human cancers. Inactivation of the single Rb-related gene in Caenorhabditis elegans, lin-35, has only limited effects on viability and fertility, yet causes changes in cell-fate and cell-cycle regulation when combined with inactivation of specific other genes. For instance, lin-35 Rb is a synthetic multivulva (synMuv) class B gene, which causes a multivulva phenotype when inactivated simultaneously with a class A or C synMuv gene.ResultsWe used the ORFeome RNAi library to identify genes that interact with C. elegans lin-35 Rb and identified 57 genes that showed synthetic or enhanced RNAi phenotypes in lin-35 mutants as compared to rrf-3 and eri-1 RNAi hypersensitive mutants. Based on characterizations of a deletion allele, the synthetic lin-35 interactor zfp-2 was found to suppress RNAi and to cooperate with lin-35 Rb in somatic gonad development. Interestingly, ten splicing-related genes were found to function similar to lin-35 Rb, as synMuv B genes that prevent inappropriate vulval induction. Partial inactivation of specific spliceosome components revealed further similarities with lin-35 Rb functions in cell-cycle control, transgene expression and restricted expression of germline granules.ConclusionWe identified an extensive series of candidate lin-35 Rb interacting genes and validated zfp-2 as a novel lin-35 synthetic lethal gene. In addition, we observed a novel role for a subset of splicing components in lin-35 Rb-controlled processes. Our data support novel hypotheses about possibilities for anti-cancer therapies and multilevel regulation of gene expression.