Nucleic acid strand length governs mitochondrial reprogramming and mtROS-associated antiviral responses following TLR3 engagement
Bibliographic record
Abstract
Abstract Mitochondria are important rheostats that regulate innate sensing processes by producing energy, biosynthetic precursors, and bioactive molecules that affect cellular signaling. When viral nucleic acids engage endosomal and cytosolic pattern recognition receptors (PRR), antiviral immune responses are supported by mitochondrial remodeling but the role of mitochondria in fine tuning ligand-specific responses remains incompletely understood. For example, endosomal TLR3 can detect various lengths of dsRNA (0.4-8 kb) ranging from viral segmented genomes or endogenous nucleic acids have been shown to induce distinct cytokine profiles. However, it is unclear if these differences are associated with differential mitochondrial remodeling. Here, we report that TLR3 engagement with both high (HMW; 1.5-8 kb) or low molecular weight (LMW; 0.2-1 kb) Polyinosinic:polycytidylic acid (Poly(I:C)) is associated with reduced but sustained oxidative phosphorylation (OXPHOS) activity and increased mitochondrial reactive oxygen species (mtROS) production/accumulation to support antiviral responses in bone marrow-derived macrophages (BMDM). They differed in the amount of mtROS production, their spare respiratory capacity (SRC) and their mitochondrial membrane potential (MMP). Interestingly, while uncoupling protein 2 (UCP2) was found required for antiviral cytokine production, it did not contribute to ligand specific responses. Dynamic modulation of complex I of the electron transport chain (ETC), however resulted in the differential accumulation of mtROS (HMW>LMW). Further, selectively targeting the mtROS derived from Complex I leads to augmented type I IFN production. Overall, these findings highlight that targeting specific sources of mtROS without affecting electron flow may be a potential avenue for specific augmentation of antiviral responses during viral infections.
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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".