Person: Hill, David
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Hill, David
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Publication Model Comparison and Assessment for Single Particle Tracking in Biological Fluids(Informa UK Limited, 2016) Lysy, Martin; Pillai, Natesh; Hill, David; Forest, M. Gregory; Mellnik, John W. R.; Vasquez, Paula A.; McKinley, Scott A.State-of-the-art techniques in passive particle-tracking microscopy provide high-resolution path trajectories of diverse foreign particles in biological fluids. For particles on the order of 1 μm diameter, these paths are generally inconsistent with simple Brownian motion. Yet, despite an abundance of data confirming these findings and their wide-ranging scientific implications, stochastic modeling of the complex particle motion has received comparatively little attention. Even among posited models, there is virtually no literature on likelihood-based inference, model comparisons, and other quantitative assessments. In this article, we develop a rigorous and computationally efficient Bayesian methodology to address this gap. We analyze two of the most prevalent candidate models for 30-sec paths of 1 μm diameter tracer particles in human lung mucus: fractional Brownian motion (fBM) and a Generalized Langevin Equation (GLE) consistent with viscoelastic theory. Our model comparisons distinctly favor GLE over fBM, with the former describing the data remarkably well up to the timescales for which we have reliable information. Supplementary materials for this article are available online.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 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.Publication 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, MarcGenotypic 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.Publication 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, EricEpstein-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.Publication 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, JamesThe 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.