Bioorthogonal click labeling of an amber-free HIV-1 provirus for in-virus single molecule imaging.

Structural dynamics of human immunodeficiency virus 1 (HIV-1) envelope (Env) glycoprotein mediate cell entry and facilitate immune evasion. Single-molecule FRET using peptides for Env labeling revealed structural dynamics of Env, but peptide use risks potential effects on structural integrity/dynamics. While incorporating noncanonical amino acids (ncAAs) into Env by amber stop-codon suppression, followed by click chemistry, offers a minimally invasive approach, this has proved to be technically challenging for HIV-1. Here, we develope an intact amber-free HIV-1 system that overcomes hurdles of preexisting viral amber codons. We achieved dual-ncAA incorporation into Env on amber-free virions, enabling single-molecule Förster resonance energy transfer (smFRET) studies of click-labeled Env that validated the previous peptide-based labeling approaches by confirming the intrinsic propensity of Env to dynamically sample multiple conformational states. Amber-free click-labeled Env also enabled real-time tracking of single virion internalization and trafficking in cells. Our system thus permits in-virus bioorthogonal labeling of proteins, compatible with studies of virus entry, trafficking, and egress from cells.

HIV-1 Capsid Uncoating Is a Multistep Process That Proceeds through Defect Formation Followed by Disassembly of the Capsid Lattice.

The HIV-1 core consists of a cone-shaped capsid shell made of capsid protein (CA) hexamers and pentamers encapsulating the viral genome. HIV-1 capsid disassembly, referred to as uncoating, is important for productive infection; however, the location, timing, and regulation of uncoating remain controversial. Here, we employ amber codon suppression to directly label CA. In addition, a fluid phase fluorescent probe is incorporated into the viral core to detect small defects in the capsid lattice. This double-labeling strategy enables the visualization of uncoating of single cores in vitro and in living cells, which we found to always proceed through at least two distinct steps─the formation of a defect in the capsid lattice that initiates gradual loss of CA below a detectable level. Importantly, intact cores containing the fluid phase and CA fluorescent markers enter and uncoat in the nucleus, as evidenced by a sequential loss of both markers, prior to establishing productive infection. This two-step uncoating process is observed in different cells, including a macrophage line. Notably, the lag between the release of fluid phase marker and terminal loss of CA appears to be independent of the cell type or reverse transcription and is much longer (>5-fold) for nuclear capsids compared to cell-free cores or cores in the cytosol, suggesting that the capsid lattice is stabilized by capsid-binding nuclear factors. Our results imply that intact HIV-1 cores enter the cell nucleus and that uncoating is initiated through a localized defect in the capsid lattice prior to a global loss of CA.

Label-free imaging of nuclear membrane for analysis of nuclear import of viral complexes.

HIV-1 enters the nucleus of non-dividing cells through the nuclear pore complex where it integrates into the host genome. The mechanism of HIV-1 nuclear import remains poorly understood. A powerful means to investigate the docking of HIV-1 at the nuclear pore and nuclear import of viral complexes is through single virus tracking in live cells. This approach necessitates fluorescence labeling of HIV-1 particles and the nuclear envelope, which may be challenging, especially in the context of primary cells. Here, we leveraged a deep neural network model for label-free visualization of the nuclear envelope using transmitted light microscopy. A training image set of cells with fluorescently labeled nuclear Lamin B1 (ground truth), along with the corresponding transmitted light images, was acquired and used to train our model to predict the morphology of the nuclear envelope in fixed cells. This protocol yielded accurate predictions of the nuclear membrane and was used in conjunction with virus infection to examine the nuclear entry of fluorescently labeled HIV-1 complexes. Analyses of HIV-1 nuclear import as a function of virus input yielded identical numbers of fluorescent viral complexes per nucleus using the ground truth and predicted nuclear membrane images. We also demonstrate the utility of predicting the nuclear envelope based on transmitted light images for multicolor fluorescence microscopy of infected cells. Importantly, we show that our model can be adapted to predict the nuclear membrane of live cells imaged at 37 °C, making this approach compatible with single virus tracking. Collectively, these findings demonstrate the utility of deep learning approaches for label-free imaging of cellular structures during early stages of virus infection.