Marc Vidal

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.

The human disease network

A network of disorders and disease genes linked by known disorder–gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

In apparently scale-free protein–protein interaction networks, or ‘interactome’ networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the ‘hubs’, interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein–protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: ‘party’ hubs, which interact with most of their partners simultaneously, and ‘date’ hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes—or modules —to each other, whereas party hubs function inside modules.

A mitochondrial protein compendium elucidates complex I disease biology.

Mitochondria are complex organelles whose dysfunction underlies a broad spectrum of human diseases. Identifying all of the proteins resident in this organelle and understanding how they integrate into pathways represent major challenges in cell biology. Toward this goal, we performed mass spectrometry, GFP tagging, and machine learning to create a mitochondrial compendium of 1098 genes and their protein expression across 14 mouse tissues. We link poorly characterized proteins in this inventory to known mitochondrial pathways by virtue of shared evolutionary history. Using this approach, we predict 19 proteins to be important for the function of complex I (CI) of the electron transport chain. We validate a subset of these predictions using RNAi, including C8orf38, which we further show harbors an inherited mutation in a lethal, infantile CI deficiency. Our results have important implications for understanding CI function and pathogenesis and, more generally, illustrate how our compendium can serve as a foundation for systematic investigations of mitochondria.

COT drives resistance to RAF inhibition through MAP kinase pathway reactivation

Oncogenic mutations in the serine/threonine kinase B-RAF (also known as BRAF) are found in 50–70% of malignant melanomas. Pre-clinical studies have demonstrated that the B-RAF(V600E) mutation predicts a dependency on the mitogen-activated protein kinase (MAPK) signalling cascade in melanoma—an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance. Identification of resistance mechanisms in a manner that elucidates alternative ‘druggable’ targets may inform effective long-term treatment strategies. Here we expressed ∼600 kinase and kinase-related open reading frames (ORFs) in parallel to interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (the gene encoding COT/Tpl2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAF(V600E) cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signalling. Moreover, COT expression is associated with de novo resistance in B-RAF(V600E) cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibitors. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.

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.

Interactome networks and human disease.

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.

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.

GATEWAY recombinational cloning: application to the cloning of large numbers of open reading frames or ORFeomes.

Publisher Summary Complete genome sequences are available for three model organisms— Escherichia coli , Saccharomyces cerevisiae , and Caenorhabditis elegans —and for several pathogenic microorganisms such as Helicobacter pylori . Complete genome sequences are expected to become available soon for other model organisms and for humans. This information is expected to revolutionize the way biological questions can be addressed. Molecular mechanisms should now be approachable on a more global scale in the context of (nearly) complete sets of genes, rather than by analyzing genes individually. However, most open reading frames (ORFs) predicted from sequencing projects have remained completely uncharacterized at the functional level. The emerging field of functional genomics addresses this limitation by developing methods to characterize the function of large numbers of predicted ORFs simultaneously.

A cDNA encoding a pRB-binding protein with properties of the transcription factor E2F

The retinoblastoma protein (pRB) plays an important role in the control of cell proliferation, apparently by binding to and regulating cellular transcription factors such as E2F. Here we describe the characterization of a cDNA clone that encodes a protein with properties of E2F. This clone, RBP3, was identified by the ability of its gene product to interact with pRB. RBP3 bound to pRB both in vitro and in vivo, and this binding was competed by viral proteins known to disrupt pRB-E2F association. RBP3 bound to E2F recognition sequences in a sequence-specific manner. Furthermore, transient expression of RBP3 caused a 10-fold transactivation of the adenovirus E2 promoter, and this transactivation was dependent on the E2F recognition sequences. These properties suggest that RBP3 encodes E2F, or an E2F-like protein.