Meta-analysis suggests evidence of novel stress-related pathway components in Orsay virus - Caenorhabditis elegans viral model
Bibliographic record
Abstract
The genetic model organism, Caenorhabditis elegans (C. elegans), shares many genes with humans and is the best-annotated of the eukaryotic genome. Therefore, the identification of new genes and pathways is unlikely. Nevertheless, host-pathogen interaction studies from viruses, recently discovered in the environment, has created new opportunity to discover these pathways. For example, the exogenous RNAi response in C. elegans by the Orsay virus as seen in plants and other eukaryotes is not systemic and transgenerational, suggesting different RNAi pathways between these organisms. Using a bioinformatics meta-analysis approach, we show that the top 17 genes differentially-expressed during C. elegans infection by Orsay virus are functionally uncharacterized genes. Furthermore, functional annotation using similarity search and comparative modeling, was able to predict folds correctly, but could not assign easily function to the majority. However, we could identify gene expression studies that showed a similar pattern of gene expression related to toxicity, stress and immune response. Those results were strengthened using protein-protein interaction network analysis. This study shows that novel molecular pathway components, of viral innate immune response, can be identified and provides models that can be further used as a framework for experimental studies. Whether these features are reminiscent of an ancient mechanism evolutionarily conserved, or part of a novel pathway, remain to be established. These results reaffirm the tremendous value of this approach to broaden our understanding of viral immunity in C. elegans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".