Immunostimulatory Potential of Silencing RNAs Can Be Mediated by a Non-Uridine-Rich Toll-Like Receptor 7 Motif
Bibliographic record
Abstract
Microbial infections trigger a multiplicity of responses in the host via innate immune sensors, including the Toll-like receptors (TLRs). TLR7 and TLR8, located in endosomes, detect pathogen-derived RNA, which can be mimicked by synthetic single-stranded oligoribonucleotides (ORNs). Detailed analysis of the immunostimulatory properties of numerous silencing RNAs (siRNAs) revealed that almost all tested siRNAs with a phosphodiester backbone actively stimulated cytokine production in human peripheral blood immune cells, but not all of them did contain previously described guanosine/uridine TLR7 or adenosine/uridine TLR8 motifs. By analysis of sequence variants of these siRNAs (as single- or double-strands), we were able to identify a new immunostimulatory, non-uridine-rich TLR7 motif that is present in many published siRNAs. Interestingly, the activity of this motif is dependent on the backbone chemistry. Phosphorothioate ORNs containing the motif did not stimulate immune activation, whereas phosphodiester ORNs of the same sequence induced a strong TLR7-biased immune response with high amounts of interferon-alpha. Using TLR7- and Myd88-deficient mice, we demonstrated that stimulation by ORNs containing this motif was TLR7 dependent. Our findings are of therapeutic relevance as this motif is present in many siRNA sequences and will to contribute to the immunostimulatory properties of unmodified siRNAs.
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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) | 0.001 | 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".