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Calderwood, Michael

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Calderwood

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Michael

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Calderwood, Michael

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2012 - 202010

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Author's Publications: search.filters.isAuthorOfPublication.d46b98e1-325c-45f2-a0da-9d904abaa848

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    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.
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    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, Marc
    Abstract 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.
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    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 P
    Abstract 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.
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    The EBNA3 Family of Epstein-Barr Virus Nuclear Proteins Associates with the USP46/USP12 Deubiquitination Complexes to Regulate Lymphoblastoid Cell Line Growth
    (Public Library of Science, 2015) Ohashi, Makoto; Holthaus, Amy M.; Calderwood, Michael; Lai, Chiou-Yan; Krastins, Bryan; Sarracino, David; Johannsen, Eric
    The Epstein-Barr virus (EBV) nuclear proteins EBNA3A, EBNA3B, and EBNA3C interact with the cell DNA binding protein RBPJ and regulate cell and viral genes. Repression of the CDKN2A tumor suppressor gene products p16INK4A and p14ARF by EBNA3A and EBNA3C is critical for EBV mediated transformation of resting B lymphocytes into immortalized lymphoblastoid cell lines (LCLs). To define the composition of endogenous EBNA3 protein complexes, we generated lymphoblastoid cell lines (LCLs) expressing flag-HA tagged EBNA3A, EBNA3B, or EBNA3C and used tandem affinity purification to isolate each EBNA3 complex. Our results demonstrated that each EBNA3 protein forms a distinct complex with RBPJ. Mass-spectrometry revealed that the EBNA3A and EBNA3B complexes also contained the deubquitylation complex consisting of WDR48, WDR20, and USP46 (or its paralog USP12) and that EBNA3C complexes contained WDR48. Immunoprecipitation confirmed that EBNA3A, EBNA3B, and EBNA3C association with the USP46 complex. Using chromatin immunoprecipitation, we demonstrate that WDR48 and USP46 are recruited to the p14ARF promoter in an EBNA3C dependent manner. Mapping studies were consistent with WDR48 being the primary mediator of EBNA3 association with the DUB complex. By ChIP assay, WDR48 was recruited to the p14ARF promoter in an EBNA3C dependent manner. Importantly, WDR48 associated with EBNA3A and EBNA3C domains that are critical for LCL growth, suggesting a role for USP46/USP12 in EBV induced growth transformation.
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    Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins
    (Nature Publishing Group, 2012) Rozenblatt-Rosen, Orit; Deo, Rahul C.; Dricot, Amélie; Askenazi, Manor; Tavares, Maria; Abderazzaq, Fieda; Byrdsong, Danielle; Correll, Mick; Fan, Changyu; Feltkamp, Mariet C.; Franchi, Rachel; Garg, Brijesh K.; Gulbahce, Natali; Hao, Tong; Korkhin, Anna; Litovchick, Larisa; Mar, Jessica C.; Pak, Theodore R.; Rabello, Sabrina; Rubio, Renee; Shen, Yun; Tasan, Murat; Wanamaker, Shelly; Roecklein-Canfield, Jennifer; Johannsen, Eric; Barabási, Albert-László; Padi, Megha; Adelmant, Guillaume; Calderwood, Michael; Rolland, Thomas; Grace, Miranda; Pevzner, Samuel; Carvunis, Anne-Ruxandra; Chen, Alyce; Cheng, Jingwei; Duarte, Melissa; Ficarro, Scott; Holthaus, Amy Marie; James, Robert; Singh, Saurav; Spangle, Jennifer; Webber, James T.; Beroukhim, Rameen; Kieff, Elliott; Cusick, Michael; Hill, David; Munger, Karl; Marto, Jarrod; Quackenbush, John; Roth, Fritz; DeCaprio, James; Vidal, Marc
    Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.
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    An RS Motif within the Epstein-Barr Virus BLRF2 Tegument Protein Is Phosphorylated by SRPK2 and Is Important for Viral Replication
    (Public Library of Science, 2013) Duarte, Melissa; Wang, Lili; Calderwood, Michael; Adelmant, Guillaume; Ohashi, Makoto; Roecklein-Canfield, Jennifer; Marto, Jarrod; Hill, David; Deng, Hongyu; Johannsen, Eric
    Epstein-Barr virus (EBV) is a gammaherpesvirus that causes infectious mononucleosis, B cell lymphomas, and nasopharyngeal carcinoma. Many of the genes required for EBV virion morphogenesis are found in all herpesviruses, but some are specific to gammaherpesviruses. One of these gamma-specific genes, BLRF2, encodes a tegument protein that has been shown to be essential for replication in other gammaherpesviruses. In this study, we identify BLRF2 interacting proteins using binary and co-complex protein assays. Serine/Arginine-rich Protein Kinase 2 (SRPK2) was identified by both assays and was further shown to phosphorylate an RS motif in the BLRF2 C-terminus. Mutation of this RS motif (S148A+S150A) abrogated the ability of BLRF2 to support replication of a murine gammaherpesvirus 68 genome lacking the BLRF2 homolog (ORF52). We conclude that the BLRF2 RS motif is phosphorylated by SRPK2 and is important for viral replication.
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    Proto-genes and De Novo Gene Birth
    (Nature Publishing Group, 2012) Carvunis, Anne-Ruxandra; Rolland, Thomas; Wapinski, Ilan; Calderwood, Michael; Yildirim, Muhammed; Simonis, Nicolas; Charloteaux, Benoit; Hidalgo, César A.; Barbette, Justin; Santhanam, Balaji; Brar, Gloria A.; Weissman, Jonathan S.; Regev, Aviv; Thierry-Mieg, Nicolas; Cusick, Michael; Vidal, Marc
    Novel protein-coding genes can arise either through re-organization of pre-existing genes or de novo. Processes involving re-organization of pre-existing genes, notably following gene duplication, have been extensively described. In contrast, de novo gene birth remains poorly understood, mainly because translation of sequences devoid of genes, or “non-genic” sequences, is expected to produce insignificant polypeptides rather than proteins with specific biological functions. Here, we formalize an evolutionary model according to which functional genes evolve de novo through transitory proto-genes generated by widespread translational activity in non-genic sequences. Testing this model at genome-scale in Saccharomyces cerevisiae, we detect translation of hundreds of short species-specific open reading frames (ORFs) located in non-genic sequences. These translation events appear to provide adaptive potential, as suggested by their differential regulation upon stress and by signatures of retention by natural selection. In line with our model, we establish that S. cerevisiae ORFs can be placed within an evolutionary continuum ranging from non-genic sequences to genes. We identify ~1,900 candidate proto-genes among S. cerevisiae ORFs and find that de novo gene birth from such a reservoir may be more prevalent than sporadic gene duplication. Our work illustrates that evolution exploits seemingly dispensable sequences to generate adaptive functional innovation.
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    Identification of FAM111A as an SV40 Host Range Restriction and Adenovirus Helper Factor
    (Public Library of Science, 2012) Fine, Debrah A.; Rozenblatt-Rosen, Orit; Padi, Megha; Korkhin, Anna; James, Robert L.; Adelmant, Guillaume; Yoon, Rosa; Guo, Luxuan; Berrios, Christian Jose; Zhang, Ying; Calderwood, Michael; Velmurgan, Soundarapandian; Cheng, Jingwei; Marto, Jarrod; Hill, David; Cusick, Michael; Vidal, Marc; Florens, Laurence; Washburn, Michael P.; Litovchick, Larisa; DeCaprio, James
    The small genome of polyomaviruses encodes a limited number of proteins that are highly dependent on interactions with host cell proteins for efficient viral replication. The SV40 large T antigen (LT) contains several discrete functional domains including the LXCXE or RB-binding motif, the DNA binding and helicase domains that contribute to the viral life cycle. In addition, the LT C-terminal region contains the host range and adenovirus helper functions required for lytic infection in certain restrictive cell types. To understand how LT affects the host cell to facilitate viral replication, we expressed full-length or functional domains of LT in cells, identified interacting host proteins and carried out expression profiling. LT perturbed the expression of p53 target genes and subsets of cell-cycle dependent genes regulated by the DREAM and the B-Myb-MuvB complexes. Affinity purification of LT followed by mass spectrometry revealed a specific interaction between the LT C-terminal region and FAM111A, a previously uncharacterized protein. Depletion of FAM111A recapitulated the effects of heterologous expression of the LT C-terminal region, including increased viral gene expression and lytic infection of SV40 host range mutants and adenovirus replication in restrictive cells. FAM111A functions as a host range restriction factor that is specifically targeted by SV40 LT.
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    Viral Perturbations of Host Networks Reflect Disease Etiology
    (Public Library of Science, 2012) Gulbahce, Natali; Yan, Han; Dricot, Amélie; Padi, Megha; Byrdsong, Danielle; Franchi, Rachel; Lee, Deok-Sun; Rozenblatt-Rosen, Orit; Mar, Jessica C.; Calderwood, Michael; Baldwin, Amy; Zhao, Bo; Santhanam, Balaji; Braun, Pascal; Simonis, Nicolas; Huh, Kyung-Won; Hellner, Karin; Grace, Miranda; Chen, Alyce; Rubio, Renee; Marto, Jarrod; Christakis, Nicholas A.; Kieff, Elliott; Roth, Fritz; Roecklein-Canfield, Jennifer; DeCaprio, James; Cusick, Michael; Quackenbush, John; Hill, David; Münger, Karl; Vidal, Marc; Barabási, Albert-László
    Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.
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    A Reference Map of the Human Binary Protein Interactome
    (Nature Research, 2020-04-08) Luck, Katja; Kim, Dae-Kyum; Lambourne, Luke; Spirohn, Kerstin; Begg, Bridget E; Bian, Wenting; Brignall, Ruth; Cafarelli, Tiziana; Campos-Laborie, Francisco J.; Charloteaux, Benoit; Choi, Dongsic; Coté, Atina; Daley, Meaghan; Deimling, Steven; Desbuleux, Alice; Dricot, Amélie; Gebbia, Marinella; Hardy, Madeleine; Kishore, Nishka; Knapp, Jennifer; Kovács, István A.; Lemmens, Irma; Mee, Miles W.; Mellor, Joseph C.; Pollis, Carl; Pons, Carles; Richardson, Aaron; Schlabach, Sadie; Teeking, Bridget; Yadav, Anupama; Babor, Mariana; Balcha, Dawit; Basha, Omer; Bowman-Colin, Christian; Chin, Suet-Feung; Choi, Soon Gang; Colabella, Claudia; Coppin, Georges; D'Amata, Cassandra; De Ridder, David; De Rouck, Steffi; Duran-Frigola, Miquel; Ennajdaoui, Hanane; Goebels, Florian; Goehring, Liana; Gopal, Anjali; Haddad, Ghazal; Hatchi, Elodie; Helmy, Mohamed; Jacob, Yves; Kassa, Yoseph; Landini, Serena; Li, Roujia; van Lieshout, Natascha; MacWilliams, Andrew; Markey, Dylan; Paulson, Joseph; Rangarajan, Sudharshan; Rasla, John; Rayhan, Ashyad; Rolland, Thomas; San Miguel Delgadillo, Adriana; Shen, Yun; Sheykhkarimli, Dayag; Sheynkman, Gloria; Simonovsky, Eyal; Taşan, Murat; Tejeda, Alexander; Tropepe, Vincent; Twizere, Jean-Claude; Wang, Yang; Weatheritt, Robert; Weile, Jochen; Xia, Yu; Yang, Xinping; Yeger-Lotem, Esti; Zhong, Quan; Aloy, Patrick; Bader, Gary D.; De Las Rivas, Javier; Gaudet, Suzanne; Hao, Tong; Rak, Janusz; Tavernier, Jan; Hill, David; Vidal, Marc; Roth, Frederick P.; Calderwood, Michael
    Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships. Here, we present a human “all-by-all” reference interactome map of human binary protein interactions, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI has approximately four times more such interactions than high-quality curated interactions from small-scale studies. Integrating HuRI with genome, transcriptome, and proteome data enables the study of cellular function within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying specific subcellular roles of PPIs. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI represents a systematic proteome-wide reference linking genomic variation to phenotypic outcomes.