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While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").

SummaryHow disease-associated mutations impair protein activities in the context of biological networks remains mostly undetermined. Although a few renowned alleles are well characterized, functional information is missing for over 100,000 disease-associated variants. Here we functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays. The majority of disease-associated alleles exhibit wild-type chaperone binding profiles, suggesting they preserve protein folding or stability. While common variants from healthy individuals rarely affect interactions, two-thirds of disease-associated alleles perturb protein-protein interactions, with half corresponding to “edgetic” alleles affecting only a subset of interactions while leaving most other interactions unperturbed. With transcription factors, many alleles that leave protein-protein interactions intact affect DNA binding. Different mutations in the same gene leading to different interaction profiles often result in distinct disease phenotypes. Thus disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.

SummaryGene regulatory networks (GRNs) comprising interactions between transcription factors (TFs) and regulatory loci control development and physiology. Numerous disease-associated mutations have been identified, the vast majority residing in non-coding regions of the genome. As current GRN mapping methods test one TF at a time and require the use of cells harboring the mutation(s) of interest, they are not suitable to identify TFs that bind to wild-type and mutant loci. Here, we use gene-centered yeast one-hybrid (eY1H) assays to interrogate binding of 1,086 human TFs to 246 enhancers, as well as to 109 non-coding disease mutations. We detect both loss and gain of TF interactions with mutant loci that are concordant with target gene expression changes. This work establishes eY1H assays as a powerful addition to the toolkit of mapping human GRNs and for the high-throughput characterization of genomic variants that are rapidly being identified by genome-wide association studies.

The karyotypic chaos exhibited by human epithelial cancers complicates efforts to identify mutations critical for malignant transformation. Here we integrate complementary genomic approaches to identify human oncogenes. We show that activation of the ERK and phosphatidylinositol 3-kinase (PI3K) signaling pathways cooperate to transform human cells. Using a library of activated kinases, we identify several kinases that replace PI3K signaling and render cells tumorigenic. Whole genome structural analyses reveal that one of these kinases, IKBKE (IKKepsilon), is amplified and overexpressed in breast cancer cell lines and patient-derived tumors. Suppression of IKKepsilon expression in breast cancer cell lines that harbor IKBKE amplifications induces cell death. IKKepsilon activates the nuclear factor-kappaB (NF-kappaB) pathway in both cell lines and breast cancers. These observations suggest a mechanism for NF-kappaB activation in breast cancer, implicate the NF-kappaB pathway as a downstream mediator of PI3K, and provide a framework for integrated genomic approaches in oncogene discovery.

PMCID: PMC4266588.-- et al., Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ∼14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ∼30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a >broader> human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help >connect the dots> of the genomic revolution., This work was supported primarily by NHGRI grant R01/U01HG001715 awarded to M.V., D.E.H., F.P.R., and J.T. and in part by the following grants and agencies: NHGRI P50HG004233 to M.V., F.P.R., and A.-L.B.; NHLBI U01HL098166 subaward to M.V.; NHLBI U01HL108630 subaward to A.-L.B.; NCI U54CA112962 subaward to M.V.; NCI R33CA132073 to M.V.; NIH RC4HG006066 to M.V., D.E.H., and T.H.; NICHD ARRA R01HD065288, R21MH104766, and R01MH105524 to L.M.I.; NIMH R01MH091350 to L.M.I. and T.H.; NSF CCF-1219007 and NSERC RGPIN-2014-03892 to Y.X.; Canada Excellence Research Chair, Krembil Foundation, Ontario Research Fund–Research Excellence Award, Avon Foundation, grant CSI07A09 from Junta de Castilla y Leon (Valladolid, Spain), grant PI12/00624 from Ministerio de Economia y Competitividad (AES 2012, ISCiii, Madrid, Spain), and grant i-Link0398 from Consejo Superior de Investigaciones Científicas (CSIC, Madrid, Spain) to J.D.L.R.; Spanish Ministerio de Ciencia e Innovación (BIO2010-22073) and the European Commission through the FP7 project SyStemAge grant agreement n: 306240 to P.A.; Group-ID Multidisciplinary Research Partnerships of Ghent University, grant FWO-V G.0864.10 from the Fund for Scientific Research-Flanders and ERC Advanced Grant N° 340941 to J.T.; EMBO long-term fellowship to A.K.; Institute Sponsored Research funds from the Dana-Farber Cancer Institute Strategic Initiative to M.V. I.L. is a postdoctoral fellow with the FWO-V. M.V. is a “Chercheur Qualifié Honoraire” from the Fonds de la Recherche Scientifique (FRS-FNRS, Wallonia-Brussels Federation, Belgium). Since performing the work described, C. Fontanillo has become an employee of Celgene Research SL, part of the Celgene Corporation.

SummaryMitochondria 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.

SummaryMany 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.

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms., Journal Article, Research Support, N.I.H. Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S., info:eu-repo/semantics/published

available in PMC 2010 June 28., During the course of a viral infection, viral proteins interact with an array of host proteins and pathways. Here, we present a systematic strategy to elucidate the dynamic interactions between H1N1 influenza and its human host. A combination of yeast two-hybrid analysis and genome-wide expression profiling implicated hundreds of human factors in mediating viral-host interactions. These factors were then examined functionally through depletion analyses in primary lung cells. The resulting data point to potential roles for some unanticipated host and viral proteins in viral infection and the host response, including a network of RNA-binding proteins, components of WNT signaling, and viral polymerase subunits. This multilayered approach provides a comprehensive and unbiased physical and regulatory model of influenza-host interactions and demonstrates a general strategy for uncovering complex host-pathogen relationships., National Institutes of Health (U.S.) (grant U01 AI074575), National Institutes of Health (U.S.) (grant U54 AI057159), National Institutes of Health (U.S.) (NIH New Innovator Award), Ford Foundation (Predoctoral Fellowship), Ellison Medical Foundation, National Institutes of Health (U.S.) (NIH grant R01 HG001715), National Institutes of Health (U.S.) (grant P50 HG004233), National Institutes of Health (U.S.) (PIONEER award), Howard Hughes Medical Institute, Burroughs Wellcome Fund (Career Award at the Scientific Interface), Alfred P. Sloan Foundation