Self-amplifying RNAs generated with the modified nucleotides 5-methylcytidine and 5-methyluridine mediate strong expression and immunogenicity <i>in vivo</i>
Bibliographic record
Abstract
Abstract When utilized in therapeutic applications, synthetic self-amplifying RNA (saRNA) can lead to higher and more sustained expression than standard messenger RNA (mRNA). This feature is particularly important for gene replacement therapy applications where prolonged expression could reduce the dose and frequency of treatments. The inclusion of modified nucleotides in synthetic non-amplifying mRNA has been shown to increase RNA stability, reduce immune activation and enhance gene expression. Preclinical and clinical studies with saRNA have so far exclusively relied on RNA containing the canonical nucleotides adenosine, cytidine, guanosine and uridine. For the first time, we show that noncanonical nucleotides, such as 5-methylcytidine (m5C) and 5-methyluridine (m5U), are sufficiently compatible with a replicon derived from Venezuelan equine encephalitis alphavirus mediating protein translation in vitro, while those containing N1-methylpseudouridine in place of uridine show no detectable expression. When administered in vivo, saRNA generated with m5C or m5U mediates sustained gene expression of the luciferase reporter gene, with those incorporating m5U appearing to lead to more prolonged expression. Finally, distinct antigen-specific humoral and cellular immune responses were induced by modified saRNA encoding the model antigen ovalbumin. The use of modified nucleotides with saRNA-based platforms could enhance their potential to be used effectively in a variety of applications.
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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 | 0.001 |
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".