Utilization of HIV-1 envelope V3 to identify X4- and R5-specific Tat and LTR sequence signatures. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Antell, Gregory; Dampier, Will; Aiamkitsumrit, Benjamas; Nonnemacher, Michael; Jacobson, Jeffrey; Pirrone, Vanessa; Zhong, Wen; Kercher, Katherine; Passic, Shendra; Williams, Jean; Schwartz, Gregory; Hershberg, Uri; Krebs, Fred; Wigdahl, Brian
• Is Part Of: Retrovirology. Volume 13:Issue 1(2016)
• Page Start: 1
• Page End: 14
• Publication Date: 2016-12
• Subjects: HIV-1 -- Co-receptor -- Tropism -- LTR -- Tat -- V3 -- gp120 -- Diversity -- Divergence -- Transcription factor; Retroviruses -- Periodicals; 579.2569
• DOI: 10.1186/s12977-016-0266-9
• Languages: English
• ISSNs: 1742-4690

Abstract

Abstract Background HIV-1 entry is a receptor-mediated process directed by the interaction of the viral envelope with the host cell CD4 molecule and one of two co-receptors, CCR5 or CXCR4. The amino acid sequence of the third variable (V3) loop of the HIV-1 envelope is highly predictive of co-receptor utilization preference during entry, and machine learning predictive algorithms have been developed to characterize sequences as CCR5-utilizing (R5) or CXCR4-utilizing (X4). It was hypothesized that while the V3 loop is predominantly responsible for determining co-receptor binding, additional components of the HIV-1 genome may contribute to overall viral tropism and display sequence signatures associated with co-receptor utilization. Results The accessory protein Tat and the HlV-1 long terminal repeat (LTR) were analyzed with respect to genetic diversity and compared by Jensen–Shannon divergence which resulted in a correlation with both mean genetic diversity as well as the absolute difference in genetic diversity between R5- and X4-genome specific trends. As expected, the V3 domain of the gp120 protein was enriched with statistically divergent positions. Statistically divergent positions were also identified in Tat amino acid sequences within the transactivation and TAR-binding domains, and in nucleotide positions throughout the LTR. We further analyzed LTR sequences for putative transcription factor binding sites using the JASPAR transcription factor binding profile database and found several putative differences in transcription factor binding sites between R5 and X4 HIV-1 genomes, specifically identifying the C/EBP sites I and II, and Sp site III to differ with respect to sequence configuration for R5 and X4 LTRs. Conclusion These observations support the hypothesis that co-receptor utilization coincides with specific genetic signatures in HIV-1 Tat and the LTR, likely due to differing transcriptional regulatory mechanisms and selective pressures applied within specific cellular targets during the course of productive HIV-1 infection.