mRNA-encoded HIV-1 Env trimer ferritin nanoparticles induce monoclonal antibodies that neutralize heterologous HIV-1 isolates in mice
Bibliographic record
Abstract
The success of nucleoside-modified mRNAs in lipid nanoparticles (mRNA-LNP) as COVID-19 vaccines heralded a new era of vaccine development. For HIV-1, multivalent envelope (Env) trimer protein nanoparticles are superior immunogens compared with trimers alone for priming of broadly neutralizing antibody (bnAb) B cell lineages. The successful expression of complex multivalent nanoparticle immunogens with mRNAs has not been demonstrated. Here, we show that mRNAs can encode antigenic Env trimers on ferritin nanoparticles that initiate bnAb precursor B cell expansion and induce serum autologous tier 2 neutralizing activity in bnAb precursor V H + V L knock-in mice. Next-generation sequencing demonstrates acquisition of critical mutations, and monoclonal antibodies that neutralize heterologous HIV-1 isolates are isolated. Thus, mRNA-LNP can encode complex immunogens and may be of use in design of germline-targeting and sequential boosting immunogens for HIV-1 vaccine development.
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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 | 0.001 |
| 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 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".