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Global landscape of HIV-human protein complexes
Authors:Jäger Stefanie  Cimermancic Peter  Gulbahce Natali  Johnson Jeffrey R  McGovern Kathryn E  Clarke Starlynn C  Shales Michael  Mercenne Gaelle  Pache Lars  Li Kathy  Hernandez Hilda  Jang Gwendolyn M  Roth Shoshannah L  Akiva Eyal  Marlett John  Stephens Melanie  D'Orso Iván  Fernandes Jason  Fahey Marie  Mahon Cathal  O'Donoghue Anthony J  Todorovic Aleksandar  Morris John H  Maltby David A  Alber Tom  Cagney Gerard  Bushman Frederic D  Young John A  Chanda Sumit K  Sundquist Wesley I  Kortemme Tanja  Hernandez Ryan D  Craik Charles S  Burlingame Alma  Sali Andrej  Frankel Alan D  Krogan Nevan J
Affiliation:Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California 94158, USA.
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.
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