The preeminent roadblock to the design of an effective preventative HIV-1 vaccine remains our insufficient understanding of immune defense mechanisms that protect against HIV-1. Elite controllers, a small group of patients who spontaneously control HIV-1 replication to undetectable levels, arguably represent the best in vivo human model for studying effective host restriction mechanisms against HIV-1, and these patients have moved into the center of current efforts to identify correlates of immune protection that can be used as a blueprint for HIV-1 vaccine design. In prior studies, investigations on antimicrobial immune defense mechanisms in these patients have focused on individual aspects of host defense mechanisms, such as T- or B- cell mediated immune responses; however, it is now clear that effective restriction of HIV-1 replication in elite controllers is likely to involve numerous additional innate and cell-intrinsic immune defense mechanisms, and that a complex, fine-tuned interplay between multiple different components and compartments of the immune system is responsible for the ability of these persons to spontaneously control HIV-1 infection. Yet, such integrated programs can hardly be detected using traditional reductionist approaches that are biased towards specific previously-defined molecules or investigate one specific aspect of immune defense in an isolated fashion. Systems biology has emerged as a novel integrative methodology that aims at combining global, unbiased data to detect synergistic molecular networks that are associated with and predictive of specific clinical disease outcomes. In this application, an interdisciplinary group of investigators with complementary backgrounds in functional immunology, virology, genomics, transcriptomics, biocomputational modeling and clinical HIV-1 patient care propose to rigorously apply this novel methodology by integrating global, unbiased genetic and transcriptional profiling techniques with functional immunology and virology studies to identify previously unrecognized mechanisms of immune defense against HIV-1 in elite controllers. In specific aim 1, we will generate a unique, first-of-its-kind datasetthat includes comprehensive information on the genetic, gene expression and functional immunologic and virologic characteristics of such patients. Using a combination of different biocomputational algorithms, this data will subsequently be used to detect integrated, multi-system programs of immune protection that are operational in these patients (specific aim 2). These signatures of immune protection will then be tested for their ability to prospectively predict clinical HIV-1 disease outcomes in a cohort of untreated HIV-1 patients identified during primary HIV-1 infection (specific aim 3). This novel methodological approach has the clear potential for revealing previously-unrecognized programs of HIV-1 immune defense in elite controllers, and may substantially increase our conceptual understanding of effective HIV-1 immune protection. Eventually, the identification of a set of different parameters associated with viral control in elite controllers may represent the referential frame for what may be needed in an effective HIV-1 vaccine.