Time-Resolved Fluorescence Imaging and Correlative Cryo-Electron Tomography to Study Structural Changes of the HIV-1 Capsid
Bibliographic record
Abstract
The conical HIV-1 capsid protects the internal viral genome and facilitates the infection of target cells. Highly potent antivirals, such as the clinically approved drug Lenacapavir (LEN), block HIV-1 replication by changing the capsid structure and modulating its function. However, structural studies of the HIV-1 capsid, its disassembly, or stabilization by antivirals have been challenging. Here, we developed a correlative light and cryo-electron microscopy (CLEM) workflow to characterize HIV-1 capsid morphology, starting from a small volume of viral particles harvested from cellular supernatants. We report two critical improvements in sample preparation, namely, (1) affinity capture and retention of fluorescent HIV-1 particles on cryo-EM grids to enable mapping virus/capsid location prior to sample vitrification and (2) streamlined alignment protocols to subsequently identify and correlate regions of interest in fluorescence and cryo-EM images. These improvements enable a reproducible CLEM workflow to accurately locate capsids for cryo-electron tomography (cryo-ET) studies. Using this approach, we resolved ultrastructures of HIV-1 capsids treated with LEN and the cellular metabolite inositol hexaphosphate (IP6), revealing distinct modes of capsid lattice stabilization. Finally, using our CLEM workflow, we demonstrate the feasibility of correlating time-resolved fluorescence imaging of capsid disassembly to end point cryo-ET structures. These advances will facilitate in vitro structural studies to define the mechanisms of HIV-1 capsid stabilization and disassembly. The CLEM workflow developed here can also be extended to studying structural changes in other viruses in response to diverse stimuli.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".