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Featured researches published by Stanley Tam.


Science | 2008

High-quality binary protein interaction map of the yeast interactome network

Haiyuan Yu; Pascal Braun; Muhammed A. Yildirim; Irma Lemmens; Kavitha Venkatesan; Julie M. Sahalie; Tomoko Hirozane-Kishikawa; Fana Gebreab; Nancy Li; Nicolas Simonis; Tong Hao; Jean François Rual; Amélie Dricot; Alexei Vazquez; Ryan R. Murray; Christophe Simon; Leah Tardivo; Stanley Tam; Nenad Svrzikapa; Changyu Fan; Anne-Sophie De Smet; Adriana Motyl; Michael E. Hudson; Juyong Park; Xiaofeng Xin; Michael E. Cusick; Troy Moore; Charlie Boone; Michael Snyder; Frederick P. Roth

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.


Science | 2011

Independently Evolved Virulence Effectors Converge onto Hubs in a Plant Immune System Network

M. Shahid Mukhtar; Anne-Ruxandra Carvunis; Matija Dreze; Petra Epple; Jens Steinbrenner; Jonathan D. Moore; Murat Tasan; Mary Galli; Tong Hao; Marc T. Nishimura; Samuel J. Pevzner; Susan E. Donovan; Lila Ghamsari; Balaji Santhanam; Viviana Romero; Matthew M. Poulin; Fana Gebreab; Bryan J. Gutierrez; Stanley Tam; Dario Monachello; Mike Boxem; Christopher J. Harbort; Nathan A. McDonald; Lantian Gai; Huaming Chen; Yijian He; Jean Vandenhaute; Frederick P. Roth; David E. Hill; Joseph R. Ecker

An analysis of protein-protein interactions in Arabidopsis identifies the plant interactome. Plants generate effective responses to infection by recognizing both conserved and variable pathogen-encoded molecules. Pathogens deploy virulence effector proteins into host cells, where they interact physically with host proteins to modulate defense. We generated an interaction network of plant-pathogen effectors from two pathogens spanning the eukaryote-eubacteria divergence, three classes of Arabidopsis immune system proteins, and ~8000 other Arabidopsis proteins. We noted convergence of effectors onto highly interconnected host proteins and indirect, rather than direct, connections between effectors and plant immune receptors. We demonstrated plant immune system functions for 15 of 17 tested host proteins that interact with effectors from both pathogens. Thus, pathogens from different kingdoms deploy independently evolved virulence proteins that interact with a limited set of highly connected cellular hubs to facilitate their diverse life-cycle strategies.


Cell | 2015

The BioPlex Network: A Systematic Exploration of the Human Interactome

Edward L. Huttlin; Lily Ting; Raphael J. Bruckner; Fana Gebreab; Melanie P. Gygi; John Szpyt; Stanley Tam; Gabriela Zarraga; Greg Colby; Kurt Baltier; Rui Dong; Virginia Guarani; Laura Pontano Vaites; Alban Ordureau; Ramin Rad; Brian K. Erickson; Martin Wühr; Joel M. Chick; Bo Zhai; Deepak Kolippakkam; Julian Mintseris; Robert A. Obar; Tim Harris; Spyros Artavanis-Tsakonas; Mathew E. Sowa; Pietro De Camilli; Joao A. Paulo; J. Wade Harper; Steven P. Gygi

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.


Molecular Systems Biology | 2009

Edgetic perturbation models of human inherited disorders

Quan Zhong; Nicolas Simonis; Qian -Ru Li; Benoit Charloteaux; Fabien Heuze; Niels Klitgord; Stanley Tam; Haiyuan Yu; Kavitha Venkatesan; Danny Mou; Venus Swearingen; Muhammed A. Yildirim; Han Yan; Amélie Dricot; David Szeto; Chenwei Lin; Tong Hao; Changyu Fan; Denis Dupuy; Robert Brasseur; David E. Hill; Michael E. Cusick; Marc Vidal

Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes’ and ‘edges’, respectively. Better understanding of genotype‐to‐phenotype relationships in human disease will require modeling of how disease‐causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal’) and interaction‐specific or edge‐specific (‘edgetic’) alterations. Global computational analyses of ∼50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies.


Nature Methods | 2011

Next-generation sequencing to generate interactome datasets.

Haiyuan Yu; Leah Tardivo; Stanley Tam; Evan Weiner; Fana Gebreab; Changyu Fan; Nenad Svrzikapa; Tomoko Hirozane-Kishikawa; Edward A. Rietman; Xinping Yang; Julie M. Sahalie; Kourosh Salehi-Ashtiani; Tong Hao; Michael E. Cusick; David E. Hill; Frederick P. Roth; Pascal Braun; Marc Vidal

Next-generation sequencing has not been applied to protein-protein interactome network mapping so far because the association between the members of each interacting pair would not be maintained in en masse sequencing. We describe a massively parallel interactome-mapping pipeline, Stitch-seq, that combines PCR stitching with next-generation sequencing and used it to generate a new human interactome dataset. Stitch-seq is applicable to various interaction assays and should help expand interactome network mapping.


Nature | 2017

Architecture of the human interactome defines protein communities and disease networks

Edward L. Huttlin; Raphael J. Bruckner; Joao A. Paulo; Joe R. Cannon; Lily Ting; Kurt Baltier; Greg Colby; Fana Gebreab; Melanie P. Gygi; Hannah Parzen; John Szpyt; Stanley Tam; Gabriela Zarraga; Laura Pontano-Vaites; Sharan Swarup; Anne E. White; Devin K. Schweppe; Ramin Rad; Brian K. Erickson; Robert A. Obar; K. G. Guruharsha; Kejie Li; Spyros Artavanis-Tsakonas; Steven P. Gygi; J. Wade Harper

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein–protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification–mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.


Nature Communications | 2014

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

Roser Corominas; Xinping Yang; Guan Ning Lin; Shuli Kang; Yun Shen; Lila Ghamsari; Martin P. Broly; Maria J. Rodriguez; Stanley Tam; Shelly A. Trigg; Changyu Fan; Song Yi; Murat Tasan; Irma Lemmens; Xingyan Kuang; Nan Zhao; Dheeraj Malhotra; Jacob J. Michaelson; Vladimir Vacic; Michael A. Calderwood; Frederick P. Roth; Jan Tavernier; Steve Horvath; Kourosh Salehi-Ashtiani; Dmitry Korkin; Jonathan Sebat; David E. Hill; Tong Hao; Marc Vidal; Lilia M. Iakoucheva

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.


The Annals of Thoracic Surgery | 1998

Repeat aortic root replacement

Chiwon Hahn; Stanley Tam; Gus J. Vlahakes; Alan D. Hilgenberg; Cary W. Akins; Mortimer J. Buckley

BACKGROUND Aortic root replacement in patients who have undergone previous aortic root replacement presents a formidable technical challenge, which may lead to increased surgical mortality. METHODS We reviewed our experience from January 1989 through November 1995. Seven consecutive patients (6 men and 1 woman) underwent eight repeat aortic root replacements. Mean follow-up was 19 months. Previous root replacement had been performed with homograft in 1 patient, with a bioprosthetic valve composite graft in 1 patient, and with a mechanical valve composite graft in 6 patients. The techniques used at the previous procedures were the Cabrol technique (2 patients), Bentall technique (3 patients), and the coronary button technique (3 patients). Reoperation was indicated for pseudoaneurysm formation in 4 patients and for endocarditis in the others. RESULTS Aortic homografts were implanted in all patients with endocarditis and mechanical valve composite grafts were used in the others. In all reoperations, the coronary button technique was used. No procedures were done emergently. Concomitant procedures were performed in 2 patients, including mitral valve replacement and aortic arch aneurysm repair. One patient had recurrence of his endocarditis 36 months after operation because of continued intravenous drug use requiring a second successful homograft root replacement. There were no early deaths and one late death at 16 months after operation. CONCLUSIONS Repeat aortic root replacement, even in the setting of endocarditis, can be done with low mortality.


Molecular Systems Biology | 2016

An inter-species protein-protein interaction network across vast evolutionary distance.

Quan Zhong; Samuel J. Pevzner; Tong Hao; Yang Wang; Roberto Mosca; Jörg Menche; Mikko Taipale; Murat Tasan; Changyu Fan; Xinping Yang; Patrick J. Haley; Ryan R. Murray; Flora Mer; Fana Gebreab; Stanley Tam; Andrew MacWilliams; Amélie Dricot; Patrick Reichert; Balaji Santhanam; Lila Ghamsari; Michael A. Calderwood; Thomas Rolland; Benoit Charloteaux; Susan Lindquist; Albert-László Barabási; David E. Hill; Patrick Aloy; Michael E. Cusick; Yu Xia; Frederick P. Roth

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.


Echocardiography-a Journal of Cardiovascular Ultrasound and Allied Techniques | 2003

Successful Repair of Aortic and Mitral Incompetence Induced by Methylsergide Maleate: Confirmation by Intraoperative Transesophageal Echocardiography

D.O. Thomas Joseph; Stanley Tam; Brinda R. Kamat; Judy R. Mangion

Methylsergide maleate, an effective anti‐migraine medication, has a well‐documented association with left‐sided cardiac valve dysfunction. Prior reports have described cardiac valve dysfunction in patients using methylsergide chronically for a minimum of 6 years, with surgical intervention consisting of valve replacement for patients with intractable congestive heart failure. We report a 51‐year‐old woman who developed severe mitral and aortic valvular dysfunction after taking methylsergide maleate for migraine headaches for a period of 19 months, and who subsequently underwent aortic and mitral valve repair with excellent short‐term results. (ECHOCARDIOGRAPHY, Volume 20, April 2003)

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Michael E. Cusick

University of Rome Tor Vergata

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