Rabies Virus Infection Induces Type I Interferon Production in an IPS-1 Dependent Manner While Dendritic Cell Activation Relies on IFNAR Signaling
Bibliographic record
Abstract
As with many viruses, rabies virus (RABV) infection induces type I interferon (IFN) production within the infected host cells. However, RABV has evolved mechanisms by which to inhibit IFN production in order to sustain infection. Here we show that RABV infection of dendritic cells (DC) induces potent type I IFN production and DC activation. Although DCs are infected by RABV, the viral replication is highly suppressed in DCs, rendering the infection non-productive. We exploited this finding in bone marrow derived DCs (BMDC) in order to differentiate which pattern recognition receptor(s) (PRR) is responsible for inducing type I IFN following infection with RABV. Our results indicate that BMDC activation and type I IFN production following a RABV infection is independent of TLR signaling. However, IPS-1 is essential for both BMDC activation and IFN production. Interestingly, we see that the BMDC activation is primarily due to signaling through the IFNAR and only marginally induced by the initial infection. To further identify the receptor recognizing RABV infection, we next analyzed BMDC from Mda-5-/- and RIG-I-/- mice. In the absence of either receptor, there is a significant decrease in BMDC activation at 12h post infection. However, only RIG-I-/- cells exhibit a delay in type I IFN production. In order to determine the role that IPS-1 plays in vivo, we infected mice with pathogenic RABV. We see that IPS-1-/- mice are more susceptible to infection than IPS-1+/+ mice and have a significantly increased incident of limb paralysis.
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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 | 0.001 |
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".