Dual RNA-Seq characterization of host and pathogen gene expression in liver cells infected with Crimean-Congo Hemorrhagic Fever Virus
Bibliographic record
Abstract
Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne virus that can cause a hemorrhagic fever in humans, with a case fatality rate of up to 40%. Cases of CCHFV have been reported in Africa, Asia, and southern Europe; and recently, due to the expanding range of its vector, autochthonous cases have been reported in Spain. Although it was discovered over 70 years ago, our understanding of the pathogenesis of this virus remains limited. We used RNA-Seq in two human liver cell lines (HepG2 and Huh7) infected with CCHFV (strain IbAr10200), to examine kinetic changes in host expression and viral replication simultaneously at 1 and 3 days post infection. Through this, numerous host pathways were identified that were modulated by the virus including: antiviral response and endothelial cell leakage. Notably, the genes encoding DDX60, a cytosolic component of the RIG-I signalling pathway and OAS2 were both shown to be dysregulated. Interestingly, PTPRR was induced in Huh7 cells but not HepG2 cells. This has been associated with the TLR9 signalling cascade, and polymorphisms in TLR9 have been associated with poor outcomes in patients. Additionally, we performed whole-genome sequencing on CCHFV to assess viral diversity over time, and its relationship to the host response. As a result, we have demonstrated that through next-generation mRNA deep-sequencing it is possible to not only examine mRNA gene expression, but also to examine viral quasispecies and typing of the infecting strain. This demonstrates a proof-of-principle that CCHFV specimens can be analyzed to identify both the virus and host biomarkers that may have implications for prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".