title: Network-based prediction and analysis of HIV dependency factors.
abstract: HIV Dependency Factors (HDFs) are a class of human proteins that are essential for HIV replication, but are not lethal to the host cell when silenced. Three previous genome-wide RNAi experiments identified HDF sets with little overlap. We combine data from these three studies with a human protein interaction network to predict new HDFs, using an intuitive algorithm called SinkSource and four other algorithms published in the literature. Our algorithm achieves high precision and recall upon cross validation, as do the other methods. A number of HDFs that we predict are known to interact with HIV proteins. They belong to multiple protein complexes and biological processes that are known to be manipulated by HIV. We also demonstrate that many predicted HDF genes show significantly different programs of expression in early response to SIV infection in two non-human primate species that differ in AIDS progression. Our results suggest that many HDFs are yet to be discovered and that they have potential value as prognostic markers to determine pathological outcome and the likelihood of AIDS development. More generally, if multiple genome-wide gene-level studies have been performed at independent labs to study the same biological system or phenomenon, our methodology is applicable to interpret these studies simultaneously in the context of molecular interaction networks and to ask if they reinforce or contradict each other.
authors.affiliation: Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America. murali@cs.vt.edu
authors.forename: T M
authors.initials: TM
authors.lastname: Murali
authors.forename: Matthew D
authors.initials: MD
authors.lastname: Dyer
authors.forename: David
authors.initials: D
authors.lastname: Badger
authors.forename: Brett M
authors.initials: BM
authors.lastname: Tyler
authors.forename: Michael G
authors.initials: MG
authors.lastname: Katze
mesh_terms: D000465:Algorithms; D000818:Animals; D002522:Chlorocebus aethiops; D016000:Cluster Analysis; D030562:Databases, Protein; D018450:Disease Progression; D006678:HIV / Q000502:physiology; D015658:HIV Infections / Q000378:metabolism*; D054884:Host-Pathogen Interactions / Q000502:physiology*; D054298:Human Immunodeficiency Virus Proteins / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D008254:Macaca nemestrina; D015233:Models, Statistical; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D040901:Proteomics; D034622:RNA Interference; D015203:Reproducibility of Results; D016097:Simian Acquired Immunodeficiency Syndrome / Q000378:metabolism; D015302:Simian Immunodeficiency Virus / Q000502:physiology; D014779:Virus Replication
chemical_list: D054298:Human Immunodeficiency Virus Proteins; D011506:Proteins