mRNA lipid nanoparticles expressing cell-surface cleavage independent HIV Env trimers elicit autologous tier-2 neutralizing antibodies
Bibliographic record
Abstract
The HIV-1 envelope glycoprotein (Env) is the sole neutralizing determinant on the surface of the virus. The Env gp120 and gp41 subunits mediate receptor binding and membrane fusion and are generated from the gp160 precursor by cellular furins. This cleavage event is required for viral entry. One approach to generate HIV-1 neutralizing antibodies following immunization is to express membrane-bound Env anchored on the cell-surface by genetic means using the natural HIV gp41 transmembrane (TM) spanning domain. To simplify the process of Env trimer membrane expression we sought to remove the need for Env precursor cleavage while maintaining native-like conformation following genetic expression. To accomplish these objectives, we selected our previously developed 'native flexibly linked' (NFL) stabilized soluble trimers that are both near-native in conformation and cleavage-independent. We genetically fused the NFL construct to the HIV TM domain by using a short linker or by restoring the native membrane external proximal region, absent in soluble trimers, to express the full HIV Env ectodomain on the plasma membrane. Both forms of cell-surface NFL trimers, without and with the MPER, displayed favorable antigenic profiles by flow cytometry when expressed from plasmid DNA or mRNA. These results were consistent with the presence of well-ordered cell surface native-like trimeric Env, a necessary requirement to generate neutralizing antibodies by vaccination. Inoculation of rabbits with mRNA lipid nanoparticles (LNP) expressing membrane-bound stabilized HIV Env NFL trimers generated tier 2 neutralizing antibody serum titers in immunized animals. Multiple inoculations of mRNA LNPs generated similar neutralizing antibody titers compared to immunizations of matched NFL soluble proteins in adjuvant. Given the recent success of mRNA vaccines to prevent severe COVID, these are important developments for genetic expression of native-like HIV Env trimers in animals and potentially in humans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".