Comparative proteomic analyses of two reovirus T3D subtypes and comparison to T1L identifies multiple novel proteins in key cellular pathogenic pathways
Bibliographic record
Abstract
Viruses induce changes in the host to facilitate replication and evade the immune response. These changes are reflected by the host's proteome, including differences in protein abundance. Focusing on up and down regulated proteins after a virus infects the cell will lead to a characterization of the host response to infection, and may give insight into how viruses modulate proteins to evade host defense responses. We previously used SILAC to examine host proteomic changes in protein abundance in HEK293 cells infected with reovirus type 1, strain Lang (T1L). For the present study, we extended this analysis by determining cell protein alterations induced by two different reovirus subtypes, a less pathogenic type 3 Dearing (T3D(F)) isolate, and a more pathogenic isolate named T3D(C) that is presently in clinical trials as an anti-cancer oncolytic agent. This comparison of host proteome regulation showed that T3D(C) had a more marked effect on DNA replication proteins, recombination and repair, as well as immunological, apoptotic, and survival cell functions. We also identified several proteins not previously identified in any virus infection; branched chain amino-acid transaminase 2 (BCAT), paternally expressed 10 (PEG10), target of myb1 (TOM1), histone cluster 2 H4b (HIST2H4B) and tubulin beta 4B (TUBB4B).
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".