Scanning mutagenesis studies of HIV-1 Env immunogenicity and structure

Abstract

Human Immunodeficiency Virus type 1 (HIV-1) is the etiological agent of Acquired Immunodeficiency Syndrome (AIDS). AIDS is a global pandemic with 36.7 million people living with HIV-1 all over the world and approximately 2 million new infections occurring every year (UNAIDS Fact Sheet, 2017). Eradication of HIV/AIDS can be realized through the development of effective vaccines that confer sterilizing immunity. However, despite continuous effort and extensive research, no vaccine exists against the HIV-1 virus till date. Aspartate mutagenesis was used as a tool to probe residue burial at selected residues in the N-heptad repeat (NHR) of gp41. Mutagenesis to Asp is known to have the maximum extent of destabilization at buried positions and can be employed to identify buried residues in a protein of unknown structure. In addition, mutagenesis to Tryptophan was also carried out to probe the tolerance of a bulky, hydrophobic group at selected positions in the NHR. A FACS-based mammalian cell surface display assay was used to determine the effect of Asp and Trp mutations on the native pre-fusion structure of the Env. Mutagenesis in the NHR of gp41 led to destabilization of the native pre-fusion Env trimer. The extent of Env destabilization was directly correlated to b12/b6 binding MFI ratios. The b12/b6 binding MFI ratio was used as an estimate of the extent of residue burial in a protein structure. Mammalian surface display studies of Asp mutants suggested that A578 is most buried in the native Env structure. This was supported by pseudoviral infectivity assays and solvent accessibility calculations on pre-fusion Env. For Trp mutants, maximum destabilization was observed for Q567W which is expected since this mutation leads to a change in nature of the amino acid (polar to non-polar substitution) which is not the case for the other mutants. Thus, Asp scanning mutagenesis can be used to extricate structural information about residue accessibility in proteins, especially in the absence of high-resolution structural information. This information can be used to generate structural models of proteins and provide important insights into protein structure and function.