The matrix (MA) domains of HIV-1 precursor Gag (PrGag) proteins direct PrGag proteins to plasma membrane (PM) assembly sites where envelope (Env) protein trimers are incorporated into virus particles. MA targeting to PM sites is facilitated by its binding to phosphatidylinositol-(4,5)-bisphosphate [PI(4,5)P2], and MA binding to cellular RNAs appears to serve a chaperone function that prevents MA from associating with intracellular membranes prior to arrival at the PI(4,5)P2-rich PM. Investigations have shown genetic evidence of an interaction between MA and the cytoplasmic tails (CTs) of Env trimers that contributes to Env incorporation into virions, but demonstrations of direct MA-CT interactions have proven more difficult. In direct binding assays, we show here that MA binds to Env CTs. Using MA mutants, matrix-capsid (MACA) proteins, and MA proteins incubated in the presence of inositol polyphosphate, we show a correlation between MA trimerization and CT binding. RNA ligands with high affinities for MA reduced MA-CT binding levels, suggesting that MA-RNA binding interferes with trimerization and/or directly or indirectly blocks MA-CT binding. Rough-mapping studies indicate that C-terminal CT helices are involved in MA binding and are in agreement with cell culture studies with replication-competent viruses. Our results support a model in which full-length HIV-1 Env trimers are captured in assembling PrGag lattices by virtue of their binding to MA trimers. IMPORTANCE The mechanism by which HIV-1 envelope (Env) protein trimers assemble into virus particles is poorly understood but involves an interaction between Env cytoplasmic tails (CTs) and the matrix (MA) domain of the structural precursor Gag (PrGag) proteins. We show here that direct binding of MA to Env CTs correlates with MA trimerization, suggesting models where MA lattices regulate CT interactions and/or MA-CT trimer-trimer associations increase the avidity of MA-CT binding. We also show that MA binding to RNA ligands impairs MA-CT binding, potentially by interfering with MA trimerization and/or directly or allosterically blocking MA-CT binding sites. Rough mapping implicated CT C-terminal helices in MA binding, in agreement with cell culture studies on MA-CT interactions. Our results indicate that targeting HIV-1 MA-CT interactions may be a promising avenue for antiviral therapy.

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The matrix (MA) domain of the HIV-1 precursor Gag protein (PrGag) has been shown interact with the HIV-1 envelope (Env) protein, and to direct PrGag proteins to plasma membrane (PM) assembly sites by virtue of its affinity to phosphatidylinositol-4,5-bisphosphate (PI[4,5]P2). Unexpectedly, HIV-1 viruses with large MA deletions (ΔMA) have been shown to be conditionally infectious as long as they are matched with Env truncation mutant proteins or alternative viral glycoproteins. To characterize the interactions of wild type (WT) and ΔMA Gag proteins with PI(4,5)P2 and other acidic phospholipids, we have employed a set of lipid biosensors as probes. Our investigations showed marked differences in WT and ΔMA Gag colocalization with biosensors, effects on biosensor release, and association of biosensors with virus-like particles. These results demonstrate an alternative approach to the analysis of viral protein-lipid associations, and provide new data as to the lipid compositions of HIV-1 assembly sites.

Individual RNA remains a challenging signal to synthetically transduce into different types of cellular information. Here, we describe Ribozyme-ENabled Detection of RNA (RENDR), a plug-and-play strategy that uses cellular transcripts to template the assembly of split ribozymes, triggering splicing reactions that generate orthogonal protein outputs. To identify split ribozymes that require templating for splicing, we use laboratory evolution to evaluate the activities of different split variants of the Tetrahymena thermophila ribozyme. The best design delivers a 93-fold dynamic range of splicing with RENDR controlling fluorescent protein production in response to an RNA input. We further resolve a thermodynamic model to guide RENDR design, show how input signals can be transduced into diverse outputs, demonstrate portability across different bacteria, and use RENDR to detect antibiotic-resistant bacteria. This work shows how transcriptional signals can be monitored in situ and converted into different types of biochemical information using RNA synthetic biology.