Development of an HIV-1 Microbicide Based on Caulobacter crescentus: Blocking Infection by High-Density Display of Virus Entry Inhibitors
Bibliographic record
Abstract
The HIV/AIDS pandemic remains an enormous global health concern. Despite effective prevention options, 2.6 million new infections occur annually, with women in developing countries accounting for more than half of these infections. New prevention strategies that can be used by women are urgently needed. Topical microbicides specific for HIV-1 represent a promising prevention strategy. Conceptually, using harmless bacteria to display peptides or proteins capable of blocking entry provides an inexpensive approach to microbicide development. To avoid the potential pitfalls of engineering commensal bacteria, our strategy is to genetically display infection inhibitors on a non-native bacterium and rely on topical application of stabilized bacteria before potential virus exposure. Due to the high density cell-surface display capabilities and the inherent low toxicity of the bacterium, the S-layer mediated protein display capabilities of the non-pathogenic bacterium Caulobacter crescentus has been exploited for this approach. We have demonstrated that C. crescentus displaying MIP1α or CD4 interfered with the virus entry pathway and provided significant protection from HIV-1 pseudovirus representing clade B in a standard single cycle infection assay. Here we have expanded our C. crescentus based microbicide approach with additional and diverse classes of natural and synthetic inhibitors of the HIV-1 entry pathway. All display constructs provided variable but significant protection from HIV-1 infection; some with protection as high as 70%. Further, we describe protection from infection with additional viral clades. These findings indicate the significant potential for engineering C. crescentus to be an effective and readily adaptable HIV-1 microbicide platform.
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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 | 0.000 |
| 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".