The Porcine and Chicken Innate DNA Sensing cGAS-STING-IRF Signaling Axes Exhibit Differential Species Specificity
Bibliographic record
Abstract
The innate immune DNA sensing cyclic GMP-AMP synthase (cGAS)-stimulator of IFN genes (STING) signaling pathway plays a key role in host antiviral function. Although the cGAS-STING pathway has been extensively studied, the cGAS-STING signaling in livestock and poultry is not well understood, and whether the species specificity exists is still unknown. In this study, we found that porcine and chicken STING, but not cGAS, exhibit species differences in regulation of IFN; that is, porcine (p)STING mediates good induction of IFN in mammalian cells and low IFN induction in chicken DF-1 cells; on the contrary, chicken (ch)STING mediates IFN induction only in chicken cells but not in mammalian cells. Furthermore, it was found that the motifs pLxIS of pSTING and pLxVS of chSTING are responsible for the species disparity, with the IFN activity of pSTING and chSTING exchanged by swapping the two pLxI/VS motifs. The pLxI/VS motifs mediated the interactions of various STING with downstream IFN regulatory factors (IRFs), reflecting the species-specific pIRF3 and chIRF7. Next, the STING, IRFs, and STING-IRFs were reconstituted in porcine and chicken macrophages that were genetically knocked out for STING and/or IRFs by the CRISPR-Cas9 approach. The results showed that pSTING plus pIRF3 or chIRF7 are able to induce IFN; however, chSTING plus chIRF7 but not pIRF3 are able to induce IFN, suggesting that pIRF3 is specific and stringent, which underlies the inability of chSTING to induce IFN in mammalian cells. In summary, our findings reveal the differential species specificity in the cGAS-STING pathway and the underlying mechanisms, thus providing valuable insights on the cGAS-STING-IRF signaling axis for comparative immunology.
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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 | 0.001 |
| 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 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".