Tissue Specific Transcriptome Changes Upon Influenza A Virus Replication in the Duck
Bibliographic record
Abstract
Ducks are the natural host and reservoir of influenza A virus (IAV), and as such are permissive to viral replication while being unharmed by most strains. It is not known which mechanisms of viral control are globally regulated during infection, and which are specific to tissues during infection. Here we compare transcript expression from tissues from Pekin ducks infected with a recombinant H5N1 strain A/Vietnam 1203/04 (VN1203) or an H5N2 strain A/British Columbia 500/05 using RNA-sequencing analysis and aligning reads to the NCBI assembly ZJU1.0 of the domestic duck (Anas platyrhynchos) genome. Highly pathogenic VN1203 replicated in lungs and showed systemic dissemination, while BC500, like most low pathogenic strains, replicated in the intestines. VN1203 infection induced robust differential expression of genes all three days post infection, while BC500 induced the greatest number of differentially expressed genes on day 2 post infection. While there were many genes globally upregulated in response to either VN1203 or BC500, tissue specific gene expression differences were observed. Lungs of ducks infected with VN1203 and intestines of birds infected with BC500, tissues important in influenza replication, showed highest upregulation of pattern recognition receptors and interferon stimulated genes early in the response. These tissues also appear to have specific downregulation of inflammatory components, with downregulation of distinct sets of proinflammatory cytokines in lung, and downregulation of key components of leukocyte recruitment and complement pathways in intestine. Our results suggest that global and tissue specific regulation patterns help the duck control viral replication as well as limit some inflammatory responses in tissues involved in replication to avoid damage.
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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".