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Dive into the research topics where Gerard Cagney is active.

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Featured researches published by Gerard Cagney.


Nature | 2000

A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae

Peter Uetz; Loic Giot; Gerard Cagney; Traci A. Mansfield; Richard S. Judson; James Knight; Daniel Lockshon; Vaibhav Narayan; Maithreyan Srinivasan; Pascale Pochart; Alia Qureshi-Emili; Ying Li; Brian Godwin; Diana Conover; Theodore Kalbfleisch; Govindan Vijayadamodar; Meijia Yang; Mark Johnston; Stanley Fields; Jonathan M. Rothberg

Two large-scale yeast two-hybrid screens were undertaken to identify protein–protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.


Nature | 2006

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Nevan J. Krogan; Gerard Cagney; Haiyuan Yu; Gouqing Zhong; Xinghua Guo; Alexandr Ignatchenko; Joyce Li; Shuye Pu; Nira Datta; Aaron Tikuisis; Thanuja Punna; José M. Peregrín-Alvarez; Michael Shales; Xin Zhang; Michael Davey; Mark D. Robinson; Alberto Paccanaro; James E. Bray; Anthony Sheung; Bryan Beattie; Dawn Richards; Veronica Canadien; Atanas Lalev; Frank Mena; Peter Y. Wong; Andrei Starostine; Myra M. Canete; James Vlasblom; Samuel Wu; Chris Orsi

Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.


Cell | 2005

Navigating the Chaperone Network: An Integrative Map of Physical and Genetic Interactions Mediated by the Hsp90 Chaperone

Rongmin Zhao; Mike Davey; Ya-Chieh Hsu; Pia Kaplanek; Amy Hin Yan Tong; Ainslie B. Parsons; Nevan J. Krogan; Gerard Cagney; Duy Mai; Jack Greenblatt; Charles Boone; Andrew Emili; Walid A. Houry

Physical, genetic, and chemical-genetic interactions centered on the conserved chaperone Hsp90 were mapped at high resolution in yeast using systematic proteomic and genomic methods. Physical interactions were identified using genome-wide two hybrid screens combined with large-scale affinity purification of Hsp90-containing protein complexes. Genetic interactions were uncovered using synthetic genetic array technology and by a microarray-based chemical-genetic screen of a set of about 4700 viable yeast gene deletion mutants for hypersensitivity to the Hsp90 inhibitor geldanamycin. An extended network, consisting of 198 putative physical interactions and 451 putative genetic and chemical-genetic interactions, was found to connect Hsp90 to cofactors and substrates involved in a wide range of cellular functions. Two novel Hsp90 cofactors, Tah1 (YCR060W) and Pih1 (YHR034C), were also identified. These cofactors interact physically and functionally with the conserved AAA(+)-type DNA helicases Rvb1/Rvb2, which are key components of several chromatin remodeling factors, thereby linking Hsp90 to epigenetic gene regulation.


Molecular and Cellular Biology | 2003

Methylation of Histone H3 by Set2 in Saccharomyces cerevisiae Is Linked to Transcriptional Elongation by RNA Polymerase II

Nevan J. Krogan; Minkyu Kim; Amy Hin Yan Tong; Ashkan Golshani; Gerard Cagney; Veronica Canadien; Dawn Richards; Bryan Beattie; Andrew Emili; Charles Boone; Ali Shilatifard; Stephen Buratowski; Jack Greenblatt

ABSTRACT Set2 methylates Lys36 of histone H3. We show here that yeast Set2 copurifies with RNA polymerase II (RNAPII). Chromatin immunoprecipitation analyses demonstrated that Set2 and histone H3 Lys36 methylation are associated with the coding regions of several genes that were tested and correlate with active transcription. Both depend, as well, on the Paf1 elongation factor complex. The C terminus of Set2, which contains a WW domain, is also required for effective Lys36 methylation. Deletion of CTK1, encoding an RNAPII CTD kinase, prevents Lys36 methylation and Set2 recruitment, suggesting that methylation may be triggered by contact of the WW domain or C terminus of Set2 with Ser2-phosphorylated CTD. A set2 deletion results in slight sensitivity to 6-azauracil and much less β-galactosidase produced by a reporter plasmid, resulting from a defect in transcription. In synthetic genetic array (SGA) analysis, synthetic growth defects were obtained when a set2 deletion was combined with deletions of all five components of the Paf1 complex, the chromodomain elongation factor Chd1, the putative elongation factor Soh1, the Bre1 or Lge1 components of the histone H2B ubiquitination complex, or the histone H2A variant Htz1. SET2 also interacts genetically with components of the Set1 and Set3 complexes, suggesting that Set1, Set2, and Set3 similarly affect transcription by RNAPII.


Molecular and Cellular Biology | 2002

RNA polymerase II elongation factors of Saccharomyces cerevisiae: a targeted proteomics approach.

Nevan J. Krogan; Minkyu Kim; Seong Hoon Ahn; Guoqing Zhong; Michael S. Kobor; Gerard Cagney; Andrew Emili; Ali Shilatifard; Stephen Buratowski; Jack Greenblatt

ABSTRACT To physically characterize the web of interactions connecting the Saccharomyces cerevisiae proteins suspected to be RNA polymerase II (RNAPII) elongation factors, subunits of Spt4/Spt5 and Spt16/Pob3 (corresponding to human DSIF and FACT), Spt6, TFIIF (Tfg1, -2, and -3), TFIIS, Rtf1, and Elongator (Elp1, -2, -3, -4, -5, and -6) were affinity purified under conditions designed to minimize loss of associated polypeptides and then identified by mass spectrometry. Spt16/Pob3 was discovered to associate with three distinct complexes: histones; Chd1/casein kinase II (CKII); and Rtf1, Paf1, Ctr9, Cdc73, and a previously uncharacterized protein, Leo1. Rtf1 and Chd1 have previously been implicated in the control of elongation, and the sensitivity to 6-azauracil of strains lacking Paf1, Cdc73, or Leo1 suggested that these proteins are involved in elongation by RNAPII as well. Confirmation came from chromatin immunoprecipitation (ChIP) assays demonstrating that all components of this complex, including Leo1, cross-linked to the promoter, coding region, and 3′ end of the ADH1 gene. In contrast, the three subunits of TFIIF cross-linked only to the promoter-containing fragment of ADH1. Spt6 interacted with the uncharacterized, essential protein Iws1 (interacts with Spt6), and Spt5 interacted either with Spt4 or with a truncated form of Spt6. ChIP on Spt6 and the novel protein Iws1 resulted in the cross-linking of both proteins to all three regions of the ADH1 gene, suggesting that Iws1 is likely an Spt6-interacting elongation factor. Spt5, Spt6, and Iws1 are phosphorylated on consensus CKII sites in vivo, conceivably by the Chd1/CKII associated with Spt16/Pob3. All the elongation factors but Elongator copurified with RNAPII.


Nature | 2012

Global landscape of HIV-human protein complexes

Stefanie Jäger; Peter Cimermancic; Natali Gulbahce; Jeffrey R. Johnson; Kathryn E. McGovern; Starlynn C. Clarke; Michael Shales; Gaelle Mercenne; Lars Pache; Kathy H. Li; Hilda Hernandez; Gwendolyn M. Jang; Shoshannah L. Roth; Eyal Akiva; John Marlett; Melanie Stephens; Iván D’Orso; Jason Fernandes; Marie Fahey; Cathal Sean Mahon; Anthony J. O’Donoghue; Aleksandar Todorovic; John H. Morris; David A. Maltby; Tom Alber; Gerard Cagney; Frederic D. Bushman; John A. T. Young; Sumit K. Chanda; Wesley I. Sundquist

Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host’s cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV–human protein–protein interactions involving 435 individual human proteins, with ∼40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.


PLOS Pathogens | 2009

Host Cell Factors in HIV Replication: Meta-Analysis of Genome-Wide Studies

Frederic D. Bushman; Nirav Malani; Jason Fernandes; Iván D'Orso; Gerard Cagney; Tracy L. Diamond; Honglin Zhou; Daria J. Hazuda; Amy S. Espeseth; Renate König; Sourav Bandyopadhyay; Trey Ideker; Stephen P. Goff; Nevan J. Krogan; Alan D. Frankel; John A. T. Young; Sumit K. Chanda

We have analyzed host cell genes linked to HIV replication that were identified in nine genome-wide studies, including three independent siRNA screens. Overlaps among the siRNA screens were very modest (<7% for any pairwise combination), and similarly, only modest overlaps were seen in pairwise comparisons with other types of genome-wide studies. Combining all genes from the genome-wide studies together with genes reported in the literature to affect HIV yields 2,410 protein-coding genes, or fully 9.5% of all human genes (though of course some of these are false positive calls). Here we report an “encyclopedia” of all overlaps between studies (available at http://www.hostpathogen.org), which yielded a more extensively corroborated set of host factors assisting HIV replication. We used these genes to calculate refined networks that specify cellular subsystems recruited by HIV to assist in replication, and present additional analysis specifying host cell genes that are attractive as potential therapeutic targets.


Molecular Cell | 2004

High-definition macromolecular composition of yeast RNA-processing complexes.

Nevan J. Krogan; Wen-Tao Peng; Gerard Cagney; Mark D. Robinson; Robin Haw; Gouqing Zhong; Xinghua Guo; Xin Zhang; Veronica Canadien; Dawn Richards; Bryan Beattie; Atanas Lalev; Wen Zhang; Armaity P. Davierwala; Sanie Mnaimneh; Andrei Starostine; Aaron Tikuisis; Jörg Grigull; Nira Datta; James E. Bray; Timothy R. Hughes; Andrew Emili; Jack Greenblatt

A remarkably large collection of evolutionarily conserved proteins has been implicated in processing of noncoding RNAs and biogenesis of ribonucleoproteins. To better define the physical and functional relationships among these proteins and their cognate RNAs, we performed 165 highly stringent affinity purifications of known or predicted RNA-related proteins from Saccharomyces cerevisiae. We systematically identified and estimated the relative abundance of stably associated polypeptides and RNA species using a combination of gel densitometry, protein mass spectrometry, and oligonucleotide microarray hybridization. Ninety-two discrete proteins or protein complexes were identified comprising 489 different polypeptides, many associated with one or more specific RNA molecules. Some of the pre-rRNA-processing complexes that were obtained are discrete sub-complexes of those previously described. Among these, we identified the IPI complex required for proper processing of the ITS2 region of the ribosomal RNA primary transcript. This study provides a high-resolution overview of the modular topology of noncoding RNA-processing machinery.


Traffic | 2010

HIV Nef is secreted in exosomes and triggers apoptosis in bystander CD4+ T cells.

Metka Lenassi; Gerard Cagney; Maofu Liao; Tomaž Vaupotič; Koen Bartholomeeusen; Yifan Cheng; Nevan J. Krogan; Ana Plemenitaš; B. Matija Peterlin

The HIV accessory protein negative factor (Nef) is one of the earliest and most abundantly expressed viral proteins. It is also found in the serum of infected individuals (Caby MP, Lankar D, Vincendeau‐Scherrer C, Raposo G, Bonnerot C. Exosomal‐like vesicles are present in human blood plasma. Int Immunol 2005;17:879–887). Extracellular Nef protein has deleterious effects on CD4+ T cells (James CO, Huang MB, Khan M, Garcia‐Barrio M, Powell MD, Bond VC. Extracellular Nef protein targets CD4+ T cells for apoptosis by interacting with CXCR4 surface receptors. J Virol 2004;78:3099–3109), the primary targets of HIV, and can suppress immunoglobulin class switching in bystander B cells (Qiao X, He B, Chiu A, Knowles DM, Chadburn A, Cerutti A. Human immunodeficiency virus 1 Nef suppresses CD40‐dependent immunoglobulin class switching in bystander B cells. Nat Immunol 2006;7:302–310). Nevertheless, the mode of exit of Nef from infected cells remains a conundrum. We found that Nef stimulates its own export via the release of exosomes from all cells examined. Depending on its intracellular location, these Nef exosomes form at the plasma membrane, late endosomes or both compartments in Jurkat, SupT1 and primary T cells, respectively. Nef release through exosomes is conserved also during HIV‐1 infection of peripheral blood lymphocytes (PBLs). Released Nef exosomes cause activation‐induced cell death of resting PBLs in vitro. Thus, HIV‐infected cells export Nef in bioactive vesicles, which facilitate the depletion of CD4+ T cells that is a hallmark of acquired immunodeficiency syndrome (AIDS).


Cell | 2009

Functional Organization of the S. cerevisiae Phosphorylation Network

Dorothea Fiedler; Hannes Braberg; Monika Mehta; Gal Chechik; Gerard Cagney; Paromita Mukherjee; Andrea C. Silva; Michael Shales; Sean R. Collins; Sake van Wageningen; Patrick Kemmeren; Frank C. P. Holstege; Jonathan S. Weissman; Michael-Christopher Keogh; Daphne Koller; Kevan M. Shokat; Nevan J. Krogan

Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an epistatic miniarray profile (E-MAP) comprised of 100,000 pairwise, quantitative genetic interactions, including virtually all protein and small-molecule kinases and phosphatases as well as key cellular regulators. Quantitative genetic interaction mapping reveals factors working in compensatory pathways (negative genetic interactions) or those operating in linear pathways (positive genetic interactions). We found an enrichment of positive genetic interactions between kinases, phosphatases, and their substrates. In addition, we assembled a higher-order map from sets of three genes that display strong interactions with one another: triplets enriched for functional connectivity. The resulting network view provides insights into signaling pathway regulation and reveals a link between the cell-cycle kinase, Cak1, the Fus3 MAP kinase, and a pathway that regulates chromatin integrity during transcription by RNA polymerase II.

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Kieran Wynne

University College Dublin

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David Cotter

Royal College of Surgeons in Ireland

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Jane A. English

Royal College of Surgeons in Ireland

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Melanie Föcking

Royal College of Surgeons in Ireland

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Patrick Dicker

Royal College of Surgeons in Ireland

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Peter Uetz

Virginia Commonwealth University

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