HIV-1 Immune Escape Maps Figure 2. Protease Immune Escape Map. doi:10.1371/journal.pone.0006687.g002 Discussion HLA-associated polymorphisms were identified in HIV-1 Gag, Pol and Nef in a combined cohort of .1500 chronically-infected, treatment-na¨ıve individuals from established cohorts in Canada, the USA and Western Australia. These cohorts have previously been independently investigated for HLA-associated polymorphisms; how- ever by merging the data and re-analyzing as a whole, we achieved the highest-powered dataset to date to identify HLA associations in HIV subtype B. Indeed, where previous studies had employed a significance threshold of q#0.2 when reporting associations, here we have lowered the threshold to q#0.05, thus focusing on sites with the strongest statistical support for HLA-driven adaptation. The current immune escape maps incorporate some improve- ments over previous iterations. Firstly, the maps cover all proteins in Pol (including RNAseH and Integrase), instead of just protease/ RT as in previous studies [15]. Secondly, all associations, regardless of proximity to known epitopes, are displayed on a single map so that escape patterns in a protein can be visualized globally. Note that, in the case where an HLA-associated polymorphism does not fall within a known optimally-described epitope, we have not attempted to predict the likeliest epitope as has been done previously. This was done in order to avoid forcing an epitope prediction in the case where the HLA association may be attributable to another mechanism (for example a processing escape mutation occurring distant from a published epitope), and also to avoid favoring a particular epitope prediction algorithm among the many that are available (e.g.: MotifScan http://www. hiv.lanl.gov/content/ immunology/motif_scan; Epipred http://atom.research.micro- soft.com/bio/epipred.aspx [55]; SYFPEITHI http://www.syf- peithi.de/Scripts/MHCServer.dll/EpitopePrediction.htm, [56], NetCTL 1.2 http://www.cbs.dtu.dk/services/NetCTL/ [57], and various others [58,59]). That being said, visual inspection of the maps reveals strong evidence for the existence of a number of novel CTL epitopes, particularly in Pol where epitope mapping initiatives may not have been as exhaustive compared to Gag and Nef. Thirdly, the incorporation of a multivariate correction for HLA linkage disequilibrium allows the identification of the HLA allele directly responsible for the association, rather than the manual assignment of the responsible allele using p-values post- hoc as employed in previous studies [15]. Finally, the incorpora- tion of a multivariate correction for codon covariation represents an important step forward [27]. It allows us to discriminate HIV polymorphisms directly attributable to selection pressure by the HLA allele in question, from those who may be better explained indirectly (meaning that their occurrence may be better explained by the presence of an HLA-associated covarying residue, rather than possession of the allele itself). In addition, it allows us to comprehensively identify positively and negatively covarying amino acids across proteins (Table S2), thus providing candidate lists for secondary and/or compensatory mutations associated with known escape sites. Indeed, Carlson et al. [27] demonstrated that the codon covariation analysis accurately re-capitulates known pathways of B*57 and B*27-associated escape in Gag [35,36,60], supporting the use of this tool for the identification of secondary escape patterns for additional HLA-associated escape mutations. Just as the standardized identification of drug resistance mutations [39] has been essential to both basic research as well as the clinical monitoring of HIV-infected individuals, we hope that the identifica- tion of immune escape pathways will be equally relevant to HIV immunology/virology research and AIDS vaccine design. Our results confirm the strong influence of immune escape on HIV diversity [13,14], but more importantly underscore the reproducibility and predictability of immune escape in response to specific HLA pressures [15,27,28,29,38]. We hope these maps and tables will be useful to those interested in CTL epitope discovery, the effects of escape and compensatory mutations on viral replication and pathogenesis, the design of novel vaccines, as well as the broader question of host- pathogen co-evolution. Finally, we have assigned the name ‘‘International HIV Adaptation Collaborative’’ (IHAC) to describe the current multicenter cohort with the hope that this initiative may be expanded to include additional cohorts worldwide in the future. In particular, the merging of data and cohorts across different HIV-1 subtypes [27] will allow us to further explore similarities and differences in HLA-driven polymorphism patterns across subtypes. Supporting Information Table S1 HLA-associated polymorphisms in HIV-1 Gag, Protease, Reverse Transcriptase, Integrase and Nef (all q,0.2). Consistent with the immune escape maps, amino acid numbering begins with 1 for each individual protein (where individual proteins are defined as Gag, Protease, Reverse Transcriptase, Integrase and Nef). Also consistent with the escape maps, the direction of the association (adapted vs. nonadapted) for the specific HLA in question is differentiated by red and blue lettering, respectively. Direct (covariation-corrected) and indirect (non- PLoS ONE | www.plosone.org 6 August 2009 | Volume 4 | Issue 8 | e6687