The distribution of CTL epitopes in HIV-1 appears to be random, and similar to that of other proteomes

Abstract

BackgroundHIV-1 viruses are highly capable of mutating their proteins to escape the presentation of CTL epitopes in their current host. Upon transmission to another host, some escape mutations revert, but other remain stable in the virus sequence for at least several years. Depending on the rate of accumulation and reversion of escape mutations, HIV-1 could reach a high level of adaptation to the human population. Yusim et. al. hypothesized that the apparent clustering of CTL epitopes in the conserved regions of HIV-1 proteins could be an evolutionary signature left by large-scale adaptation of HIV-1 to its human/simian host.ResultsIn this paper we quantified the distribution of CTL epitopes in HIV-1 and found that that in 99% of the HIV-1 protein sequences, the epitope distribution was indistinguishable from random. Similar percentages were found for HCV, Influenza and for three eukaryote proteomes (Human, Drosophila, Yeast).ConclusionWe conclude that CTL epitopes in HIV-1 are randomly distributed, and that this distribution is similar to the distribution of CTL epitopes in proteins from other proteomes. Therefore, the visually apparent clustering of CTL epitopes in epitope maps should not be interpreted as a signature of a past large-scale adaptation of HIV-1 to the human cellular immune response.

Role of individual's T‐cell immunome in controlling HIV‐1 progression

“…This finding is in agreement with the general observation that in vitro Non‐progressor individuals present a broader CTL response with the recognition of a large set of CTL epitopes than Progressors . Therefore, the individual's T‐cell immunome of the HIV‐1 strain infecting the subject, that is the set of epitopes that a subject can recognize due to the combination of the self HLA molecules, represents a key factor in controlling HIV progression.…”

Whole-Genome Immunoinformatic Analysis of F. tularensis: Predicted CTL Epitopes Clustered in Hotspots Are Prone to Elicit a T-Cell Response

“…Analysis of the CTL clustering in the HIV-1 Nef protein revealed that the sensitivity of hydrophobic regions to proteasomal processing is the major contributor to the epitope clustering in such regions [51]. A subsequent, comprehensive analysis of the HIV proteome corroborated previous findings on the correlation between epitope-rich regions and hydrophobicity, however the authors claimed that the predicted CTL epitopes in HIV-1 are randomly distributed [55]. Our comprehensive, genome-scale analysis demonstrates a clear enrichment (up to 70%) of membranal proteins containing highly dense regions of overlapping CTL epitopes.…”

Predicted MHC peptide binding promiscuity explains MHC class I ‘hotspots’ of antigen presentation defined by mass spectrometry eluted ligand data

“…An additional factor that has been hypothesized to be associated with MHC class I peptide immunogenicity is immunological hotspots; regions in a protein that are particularly enriched in MHC ligands . These hotspot regions of high MHC ligand concentration have been defined in a multiplicity of ways in various studies within a range of biological areas . Most studies simply define hotspots as clusters of, ideally promiscuous, MHC class I binding peptides; however, for the more detailed studies, an immunological hotspot is defined as a region with a certain density of epitopes within a given protein sequence and with a defined minimum of overlapping peptides in the given region …”

“…Hotspots were initially studied in the context of infectious diseases and intracellular pathogens, most prominently in relation to human immunodeficiency virus 1 (HIV‐1). In fact, the first reports on HIV‐1 epitope clustering in proteins were published only shortly after the discovery of the epitopes themselves . In these studies, hotspots were generated based on predicting high‐affinity MHC class I binders using available prediction algorithms.…”