Initiation of HIV-1 Gag lattice assembly is required for recognition of the viral genome packaging signal.
Xiao LeiDaniel Gonçalves-CarneiroTrinity M ZangPaul D BieniaszPublished in: eLife (2023)
The encapsidation of HIV-1 gRNA into virions is enabled by the binding of the nucleocapsid (NC) domain of the HIV-1 Gag polyprotein to the structured viral RNA packaging signal (Ψ) at the 5' end of the viral genome. However, the subcellular location and oligomeric status of Gag during the initial Gag-Ψ encounter remain uncertain. Domains other than NC, such as capsid (CA), may therefore indirectly affect RNA recognition. To investigate the contribution of Gag domains to Ψ recognition in a cellular environment, we performed protein-protein crosslinking and protein-RNA crosslinking immunoprecipitation coupled with sequencing (CLIP-seq) experiments. We demonstrate that NC alone does not bind specifically to Ψ in living cells, whereas full-length Gag and a CANC subdomain bind to Ψ with high specificity. Perturbation of the Ψ RNA structure or NC zinc fingers affected CANC:Ψ binding specificity. Notably, CANC variants with substitutions that disrupt CA:CA dimer, trimer, or hexamer interfaces in the immature Gag lattice also affected RNA binding, and mutants that were unable to assemble a nascent Gag lattice were unable to specifically bind to Ψ. Artificially multimerized NC domains did not specifically bind Ψ. CA variants with substitutions in inositol phosphate coordinating residues that prevent CA hexamerization were also deficient in Ψ binding and second-site revertant mutants that restored CA assembly also restored specific binding to Ψ. Overall, these data indicate that the correct assembly of a nascent immature CA lattice is required for the specific interaction between Gag and Ψ in cells.
Keyphrases
- antiretroviral therapy
- hiv positive
- protein protein
- hiv infected
- human immunodeficiency virus
- living cells
- hepatitis c virus
- protein kinase
- sars cov
- hiv testing
- hiv aids
- binding protein
- nucleic acid
- single cell
- men who have sex with men
- machine learning
- gene expression
- cell proliferation
- cell death
- signaling pathway
- big data
- electronic health record
- single molecule
- coronavirus disease
- cell cycle arrest
- deep learning