Expanding the adenovirus toolbox: reporter viruses for studying the dynamics of human adenovirus replication
Bibliographic record
Abstract
To streamline standard virological assays, we developed a suite of nine fluorescent or bioluminescent replication competent human species C5 adenovirus reporter viruses that mimic their parental wild-type counterpart. These reporter viruses provide a rapid and quantitative readout of various aspects of viral infection and replication based on EGFP, mCherry, or NanoLuc measurement. Moreover, they permit real-time non-invasive measures of viral load, replication dynamics, and infection kinetics over the entire course of infection, allowing measurements that were not previously possible. This suite of replication competent reporter viruses increases the ease, speed, and adaptability of standard assays and has the potential to accelerate multiple areas of human adenovirus research.IMPORTANCEIn this work, we developed a versatile toolbox of nine HAdV-C5 reporter viruses and validated their functions in cell culture. These reporter viruses provide a rapid and quantitative readout of various aspects of viral infection and replication based on EGFP, mCherry, or NanoLuc measurement. The utility of these reporter viruses could also be extended for use in 3D cell culture, organoids, live cell imaging, or animal models, and provides a conceptual framework for the development of new reporter viruses representing other clinically relevant HAdV species.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".