HIV-1 Amino Acid Toggling and Immune Escape
Author Information
Author(s): Wayne Delport, Konrad Scheffler, Cathal Seoighe
Primary Institution: Institute of Infectious Disease and Molecular Medicine, University of Cape Town
Hypothesis
The toggling model may have greater power to detect adaptively evolving sites in HIV-1 than standard models of diversifying selection.
Conclusion
The toggling selection model detects a larger number of positively selected sites in HIV-1, suggesting that escape and reversion at functionally constrained sites are common.
Supporting Evidence
- The toggling model outperformed standard models in detecting positive selection.
- Significantly more positively selected sites were detected in nef and env genes.
- Many sites detected as toggling were also associated with HLA alleles.
Takeaway
HIV can change its proteins to avoid being caught by the immune system, but sometimes these changes make it harder for the virus to survive. This study shows how often this happens.
Methodology
A probabilistic model of protein coding sequence evolution was used to detect sites in HIV-1 that exhibit rapid escape and reversion patterns.
Potential Biases
Potential bias in model comparisons due to using the same data to define the wild type state.
Limitations
The model assumes a single wild type amino acid at each site, which may not always reflect the true evolutionary dynamics.
Participant Demographics
HIV-1 sequences from individuals with known HLA types.
Statistical Information
P-Value
0.001374 for nef; 0.001028 for env
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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