Person: Vidal, Marc
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Vidal
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Vidal, Marc
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Publication A framework for exhaustively mapping functional missense variants(John Wiley and Sons Inc., 2017) Weile, Jochen; Sun, Song; Cote, Atina G; Knapp, Jennifer; Verby, Marta; Mellor, Joseph C; Wu, Yingzhou; Pons, Carles; Wong, Cassandra; van Lieshout, Natascha; Yang, Fan; Tasan, Murat; Tan, Guihong; Yang, Shan; Fowler, Douglas M; Nussbaum, Robert; Bloom, Jesse D; Vidal, Marc; Hill, David E; Aloy, Patrick; Roth, Frederick PAbstract Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin‐like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.Publication Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing(Public Library of Science, 2017) Ghadie, Mohamed Ali; Lambourne, Luke; Vidal, Marc; Xia, YuAlternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.Publication Mapping differential interactomes by affinity purification coupled with data independent mass spectrometry acquisition(2013) Lambert, Jean-Philippe; Ivosev, Gordana; Couzens, Amber L.; Larsen, Brett; Taipale, Mikko; Lin, Zhen-Yuan; Zhong, Quan; Lindquist, Susan; Vidal, Marc; Aebersold, Ruedi; Pawson, Tony; Bonner, Ron; Tate, Stephen; Gingras, Anne-ClaudeCharacterizing changes in protein-protein interactions associated with sequence variants (e.g. disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies where cost and time are major considerations. To this end, we have coupled AP to data-independent mass spectrometric acquisition (SWATH), and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. Here, we use AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes, and propose a scalable pipeline for systems biology studies.Publication Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism(Nature Pub. Group, 2014) Corominas, Roser; Yang, Xinping; Lin, Guan Ning; Kang, Shuli; Shen, Yun; Ghamsari, Lila; Broly, Martin; Rodriguez, Maria; Tam, Stanley; Trigg, Shelly A.; Fan, Changyu; Yi, Song; Tasan, Murat; Lemmens, Irma; Kuang, Xingyan; Zhao, Nan; Malhotra, Dheeraj; Michaelson, Jacob J.; Vacic, Vladimir; Calderwood, Michael; Roth, Frederick P.; Tavernier, Jan; Horvath, Steve; Salehi-Ashtiani, Kourosh; Korkin, Dmitry; Sebat, Jonathan; Hill, David; Hao, Tong; Vidal, Marc; Iakoucheva, Lilia M.Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.Publication Mycobacterium tuberculosis Type VII Secreted Effector EsxH Targets Host ESCRT to Impair Trafficking(Public Library of Science, 2013) Mehra, Alka; Zahra, Aleena; Thompson, Victor; Sirisaengtaksin, Natalie; Wells, Ashley; Porto, Maura; Köster, Stefan; Penberthy, Kristen; Kubota, Yoshihisha; Dricot, Amelie; Rogan, Daniel; Vidal, Marc; Hill, David; Bean, Andrew J.; Philips, Jennifer A.Mycobacterium tuberculosis (Mtb) disrupts anti-microbial pathways of macrophages, cells that normally kill bacteria. Over 40 years ago, D'Arcy Hart showed that Mtb avoids delivery to lysosomes, but the molecular mechanisms that allow Mtb to elude lysosomal degradation are poorly understood. Specialized secretion systems are often used by bacterial pathogens to translocate effectors that target the host, and Mtb encodes type VII secretion systems (TSSSs) that enable mycobacteria to secrete proteins across their complex cell envelope; however, their cellular targets are unknown. Here, we describe a systematic strategy to identify bacterial virulence factors by looking for interactions between the Mtb secretome and host proteins using a high throughput, high stringency, yeast two-hybrid (Y2H) platform. Using this approach we identified an interaction between EsxH, which is secreted by the Esx-3 TSSS, and human hepatocyte growth factor-regulated tyrosine kinase substrate (Hgs/Hrs), a component of the endosomal sorting complex required for transport (ESCRT). ESCRT has a well-described role in directing proteins destined for lysosomal degradation into intraluminal vesicles (ILVs) of multivesicular bodies (MVBs), ensuring degradation of the sorted cargo upon MVB-lysosome fusion. Here, we show that ESCRT is required to deliver Mtb to the lysosome and to restrict intracellular bacterial growth. Further, EsxH, in complex with EsxG, disrupts ESCRT function and impairs phagosome maturation. Thus, we demonstrate a role for a TSSS and the host ESCRT machinery in one of the central features of tuberculosis pathogenesis.Publication Identifying pathogenicity of human variants via paralog-based yeast complementation(Public Library of Science, 2017) Yang, Fan; Sun, Song; Tan, Guihong; Costanzo, Michael; Hill, David; Vidal, Marc; Andrews, Brenda J.; Boone, Charles; Roth, Frederick P.To better understand the health implications of personal genomes, we now face a largely unmet challenge to identify functional variants within disease-associated genes. Functional variants can be identified by trans-species complementation, e.g., by failure to rescue a yeast strain bearing a mutation in an orthologous human gene. Although orthologous complementation assays are powerful predictors of pathogenic variation, they are available for only a few percent of human disease genes. Here we systematically examine the question of whether complementation assays based on paralogy relationships can expand the number of human disease genes with functional variant detection assays. We tested over 1,000 paralogous human-yeast gene pairs for complementation, yielding 34 complementation relationships, of which 33 (97%) were novel. We found that paralog-based assays identified disease variants with success on par with that of orthology-based assays. Combining all homology-based assay results, we found that complementation can often identify pathogenic variants outside the homologous sequence region, presumably because of global effects on protein folding or stability. Within our search space, paralogy-based complementation more than doubled the number of human disease genes with a yeast-based complementation assay for disease variation.Publication An inter‐species protein–protein interaction network across vast evolutionary distance(John Wiley and Sons Inc., 2016) Zhong, Quan; Pevzner, Samuel J; Hao, Tong; Wang, Yang; Mosca, Roberto; Menche, Jörg; Taipale, Mikko; Taşan, Murat; Fan, Changyu; Yang, Xinping; Haley, Patrick; Murray, Ryan R; Mer, Flora; Gebreab, Fana; Tam, Stanley; MacWilliams, Andrew; Dricot, Amélie; Reichert, Patrick; Santhanam, Balaji; Ghamsari, Lila; Calderwood, Michael; Rolland, Thomas; Charloteaux, Benoit; Lindquist, Susan; Barabási, Albert‐László; Hill, David; Aloy, Patrick; Cusick, Michael E; Xia, Yu; Roth, Frederick P; Vidal, MarcAbstract In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical‐versus‐functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an “inter‐interactome” approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter‐interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra‐species networks. Although substantially reduced relative to intra‐species networks, the levels of functional overlap in the yeast–human inter‐interactome network uncover significant remnants of co‐functionality widely preserved in the two proteomes beyond human–yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co‐functionality. Such non‐functional interactions, however, represent a reservoir from which nascent functional interactions may arise.Publication Pooled‐matrix protein interaction screens using Barcode Fusion Genetics(John Wiley and Sons Inc., 2016) Yachie, Nozomu; Petsalaki, Evangelia; Mellor, Joseph C; Weile, Jochen; Jacob, Yves; Verby, Marta; Ozturk, Sedide B; Li, Siyang; Cote, Atina G; Mosca, Roberto; Knapp, Jennifer J; Ko, Minjeong; Yu, Analyn; Gebbia, Marinella; Sahni, Nidhi; Yi, Song; Tyagi, Tanya; Sheykhkarimli, Dayag; Roth, Jonathan F; Wong, Cassandra; Musa, Louai; Snider, Jamie; Liu, Yi‐Chun; Yu, Haiyuan; Braun, Pascal; Stagljar, Igor; Hao, Tong; Calderwood, Michael; Pelletier, Laurence; Aloy, Patrick; Hill, David; Vidal, Marc; Roth, Frederick PAbstract High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.Publication Network-based in silico drug efficacy screening(Nature Publishing Group, 2016) Guney, Emre; Menche, Jörg; Vidal, Marc; Barabasi, Albert-LaszloThe increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches for target identification and efficacy prediction. Here, we take advantage of our increasing understanding of the network-based origins of diseases to introduce a drug-disease proximity measure that quantifies the interplay between drugs targets and diseases. By correcting for the known biases of the interactome, proximity helps us uncover the therapeutic effect of drugs, as well as to distinguish palliative from effective treatments. Our analysis of 238 drugs used in 78 diseases indicates that the therapeutic effect of drugs is localized in a small network neighborhood of the disease genes and highlights efficacy issues for drugs used in Parkinson and several inflammatory disorders. Finally, network-based proximity allows us to predict novel drug-disease associations that offer unprecedented opportunities for drug repurposing and the detection of adverse effects.Publication MECP2 Is a Frequently Amplified Oncogene with a Novel Epigenetic Mechanism That Mimics the Role of Activated RAS in Malignancy(American Association for Cancer Research (AACR), 2015) Neupane, Manish; Clark, Allison; Landini, S.; Birkbak, N; Eklund, A. C.; Lim, E.; Culhane, Aedin; Barry, William T.; Schumacher, Sandra; Beroukhim, Rameen; Szallasi, Zoltan; Vidal, Marc; Hill, David; Silver, Daniel P.An unbiased genome-scale screen for unmutated genes that drive cancer growth when overexpressed identified MECP2 as a novel oncogene. MECP2 resides in a region of the Xchromosome that is significantly amplified across 18% of cancers, and many cancer cell lines have amplified, overexpressed MECP2 and are dependent on MECP2 expression for growth. MECP2 copy number gain and RAS family member alterations are mutually exclusive in several cancer types. The MECP2 splicing isoforms activate the major growth factor pathways targeted by activated RAS, the MAPK and PI3K pathways. MECP2 rescued the growth of a KRASG12Caddicted cell line after KRAS down-regulation, and activated KRAS rescues the growth of an MECP2-addicted cell line after MECP2 downregulation. MECP2 binding to the epigenetic modification 5-hydroxymethylcytosine is required for efficient transformation. These observations suggest that MECP2 is a commonly amplified oncogene with an unusual epigenetic mode of action.