Dataset Information

Global landscape of HIV-human protein complexes.

ABSTRACT: 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.

SUBMITTER: Jager S

PROVIDER: S-EPMC3310911 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Global landscape of HIV-human protein complexes.

Jäger Stefanie S Cimermancic Peter P Gulbahce Natali N Johnson Jeffrey R JR McGovern Kathryn E KE Clarke Starlynn C SC Shales Michael M Mercenne Gaelle G Pache Lars L Li Kathy K Hernandez Hilda H Jang Gwendolyn M GM Roth Shoshannah L SL Akiva Eyal E Marlett John J Stephens Melanie M D'Orso Iván I Fernandes Jason J Fahey Marie M Mahon Cathal C O'Donoghue Anthony J AJ Todorovic Aleksandar A Morris John H JH Maltby David A DA Alber Tom T Cagney Gerard G Bushman Frederic D FD Young John A JA Chanda Sumit K SK Sundquist Wesley I WI Kortemme Tanja T Hernandez Ryan D RD Craik Charles S CS Burlingame Alma A Sali Andrej A Frankel Alan D AD Krogan Nevan J NJ

Nature 20111221 7381

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 p ...[more]

PMID: 22190034

Similar Datasets

Project description:If perturbing two genes together has a stronger or weaker effect than expected, they are said to genetically interact. Genetic interactions are important because they help map gene function, and functionally related genes have similar genetic interaction patterns. Mapping quantitative (positive and negative) genetic interactions on a global scale has recently become possible. This data clearly shows groups of genes connected by predominantly positive or negative interactions, termed monochromatic groups. These groups often correspond to functional modules, like biological processes or complexes, or connections between modules. However it is not yet known how these patterns globally relate to known functional modules. Here we systematically study the monochromatic nature of known biological processes using the largest quantitative genetic interaction data set available, which includes fitness measurements for ?5.4 million gene pairs in the yeast Saccharomyces cerevisiae. We find that only 10% of biological processes, as defined by Gene Ontology annotations, and less than 1% of inter-process connections are monochromatic. Further, we show that protein complexes are responsible for a surprisingly large fraction of these patterns. This suggests that complexes play a central role in shaping the monochromatic landscape of biological processes. Altogether this work shows that both positive and negative monochromatic patterns are found in known biological processes and in their connections and that protein complexes play an important role in these patterns. The monochromatic processes, complexes and connections we find chart a hierarchical and modular map of sensitive and redundant biological systems in the yeast cell that will be useful for gene function prediction and comparison across phenotypes and organisms. Furthermore the analysis methods we develop are applicable to other species for which genetic interactions will progressively become more available.

Dataset Information

Global landscape of HIV-human protein complexes.

Publications

Global landscape of HIV-human protein complexes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets