Functional characterization of oligoadenylate synthetase (OAS) by dual polymerase-endoribonuclease assay
Bibliographic record
Abstract
The innate immune system includes a class of viral double stranded RNA (dsRNA) binding enzymes known as 2’-5’-oligoadenylate synthetases (OAS). The OAS family detects viral dsRNA and initiates downstream processes. The binding of viral dsRNA by OAS enables catalysis of substrate ATP into 2′-5′-linked oligoadenylate chains (2-5A). 2-5A chains longer than 3 nucleotides then activate an RNA degrading enzyme named RNase L, which in turn non-specifically degrades cellular and viral RNA causing host cell death. My research group has been investigating the interaction between the smallest OAS family member, OAS1 (42 kDa), with a double-stranded region of the West Nile virus (WNV) RNA genome. This region of the genome is conserved amongst the Flaviviridae family of viruses, of which WNV is a member. Therefore, the goal of my work is to see whether similar RNA regions in other Flaviviridae members using Zika Virus, Japanese Encephalitis Virus, WNV and Dengue Virus as model systems for studying this interaction. The approach will be to produce viral RNA from the conserved regions and determine the minimal RNA required for binding of OAS1 and catalytic activation of OAS1. I have produced a dual OAS-RNase L activity assay which provides data in shorter time intervals, measures OAS activity and RNase L activity simultaneously, and requires very low concentrations of reactants. The data obtained from this assay will be used to assess activation of OAS enzyme by flavivirus RNA and help paint a more complete picture of OAS mechanism of action.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".