HIV-1 Immune Escape Maps Competing Interests: The authors have declared that no competing interests exist. * E-mail: zbrumme@partners.org ¤ Current address: Fred Hutchinson Cancer Research Center and University of Washington, Seattle, Washington, United States of America . These authors contributed equally to this work. Introduction Cytotoxic T-Lymphocytes (CTL) eliminate virus-infected cells by recognizing virus-derived peptides (‘‘epitopes’’) presented by Human Leukocyte Antigen (HLA) class I molecules on the infected cell surface. The HLA-restricted CTL response is believed to play a major role in the immune control of HIV-1 infection [1,2,3,4,5,6], and it is generally believed that an effective AIDS vaccine will have to elicit cellular as well as humoral (antibody) responses [7,8,9,10,11]. The genes encoding HLA class I are among the most polymorphic in the human genome [12]: each individual expresses up to six different class I alleles (two at each of the A, B and C loci) out of a pool of over two thousand allelic variants defined to date. Each unique HLA molecule is capable of presenting a broad but finite array of epitopes, defined by HLA allele-specific binding motifs. This extensive genetic diversity serves as a mechanism whereby the human immune system, on both the individual as well as on a population basis, is equipped to recognize a vast array of epitopes from a broad range of pathogens. In addition, this extensive diversity means that, at both the individual as well as the population level, the human immune response exerts a complex array of evolutionary selective pressures driving viral evolution [13,14] in equally intricate, sometimes even conflicting [15,16] ways. One of the major mechanisms whereby HIV evades the cellular immune response is through the selection of HLA-restricted CTL escape mutations that allow the virus to evade immune recognition [17,18,19,20]. Escape mutations may interfere with intracellular epitope processing [21,22], disrupt peptide-HLA binding [23,24], or disrupt recognition of the peptide/HLA complex by the T-cell receptor [25,26]. Despite the extensive genetic diversity of both HIV-1 and HLA, recent studies indicate that viral evolution in response to immune selective pressures follows generally predictable patterns and kinetics [13,14,15,27,28,29,30]. For example, in B*57-expressing individu- als, the B*57-associated T242N escape mutation in Gag is selected mere weeks after infection [31,32,33], whereas the B*27-associated R264K (Gag) may take years to develop despite strong continuous immune pressure in individuals expressing B*27 [24,34]. Further- more, both T242N and R264K are typically accompanied by a well-defined set of compensatory mutations [24,35,36]. The development of improved statistical methods [37] combined with the availability of large cohorts for which HIV sequences and HLA data are available has facilitated the systematic identification of HLA-associated CTL escape mutations, both within [15,28,29,38] and across [27] HIV subtypes. Due to the extensive diversity of both HLA and HIV, the identification of mutational escape patterns requires large, well-powered datasets; thus, additional data are needed in order to refine existing escape maps. Indeed, just as the systematic identification of antiretroviral resistance mutations [39] has been of paramount importance to the design and monitoring of HIV therapies [40], the comprehensive elucidation of immune escape pathways will be of relevance to HIV vaccine research. Here, we identify HLA-associated polymorphisms within the three HIV-1 proteins most commonly considered in cellular-based vaccine design strategies (Gag, Pol and Nef) in a combined analysis of three established cohorts totaling .1500 HIV-infected, antiretroviral-na¨ıve individuals. We organize results into protein- wide escape maps illustrating the sites and pathways of immune- driven viral evolution, and hope that these maps will serve as useful reference material for researchers interested in CTL epitope discovery, host-pathogen co-evolution, and HIV vaccine design. Materials and Methods Analysis of three established cohorts and formation of the International HIV Adaptation Collaborative (IHAC) We merged HLA class I and HIV-1 Gag, Pol and Nef sequence data from three existing cohorts of chronically-HIV-infected, antiretroviral na¨ıve individuals previously featured in population- level investigations of HIV immune escape: the British Columbia HOMER cohort (British Columbia, Canada, N = 765) [15,38], the Western Australian HIV Cohort Study (WAHCS; Western Australia, Australia N = 230) [14,37], and US AIDS Clinical Trials Group (ACTG) protocols 5142 participants [41] who also provided human DNA under ACTG protocol 5128 [42] (N = 555). We have assigned the name ‘‘International HIV Adaptation Collaborative’’ (IHAC) to describe this multicenter, international cohort. Ethics Statement Ethical Approval was obtained through the following Institu- tional Review Boards: Providence Health Care/University of British Columbia; Royal Perth Hospital Ethics Committee; and the NIH’s National Institute of Allergy and Infectious Diseases (NIAID) Clinical Science Review Committee (CSRC). Genotyping methods and inter-laboratory methods comparison for quality control HIV and HLA data collection for HOMER cohort participants was performed at the BC Centre for Excellence in HIV/AIDS, Vancouver, Canada. Here, HIV RNA was extracted from plasma using standard methods and regions of interest amplified by nested RT-PCR using HIV-specific primers. PCR amplicons were bulk sequenced on an Applied Biosystems 3100, 3700 and/or 3730 automated DNA sequencer. Data were analyzed using ‘Se- quencher’ (Genecodes) or custom software RE_Call. Nucleotide mixtures were called if the height of the secondary peak exceeded 25% of the height of the dominant peak. HLA class I typing was performed using an in-house sequence-based typing protocol and interpretation algorithm [15]. HIV and HLA data collection for the WAHCS and ACTG 5142/5128 cohort participants was performed at the Centre for Clinical Immunology and Biological Statistics (CCIBS) laboratory in Perth, Australia. Plasma HIV RNA was extracted using standard methods and nearly complete viral genomes amplified using nested RT-PCR. PCR amplicons were bulk-sequenced using Applied Biosystems 3730 automated sequencing. Data were analyzed using semi-automated ASSIGN software with a nucle- otide mixture threshold of 15% after consideration of the signal/ noise ratio, yielding near-full genome sequences. High-resolution HLA class I typing was performed using sequence-based methods and allele interpretation was performed using ASSIGN [41]. To rule out potential biases due to differences in sequence analysis strategies between study sites, an inter-laboratory DNA sequencing comparison between the Vancouver and Perth laboratories was performed prior to merging data. A total of PLoS ONE | www.plosone.org 2 August 2009 | Volume 4 | Issue 8 | e6687