The Cellular Interactome of the Coronavirus Infectious Bronchitis Virus Nucleocapsid Protein and Functional Implications for Virus Biology
Bibliographic record
Abstract
The coronavirus nucleocapsid (N) protein plays a multifunctional role in the virus life cycle, from regulation of replication and transcription and genome packaging to modulation of host cell processes. These functions are likely to be facilitated by interactions with host cell proteins. The potential interactome of the infectious bronchitis virus (IBV) N protein was mapped using stable isotope labeling with amino acids in cell culture (SILAC) coupled to a green fluorescent protein-nanotrap pulldown methodology and liquid chromatography-tandem mass spectrometry. The addition of the SILAC label allowed discrimination of proteins that were likely to specifically bind to the N protein over background binding. Overall, 142 cellular proteins were selected as potentially binding to the N protein, many as part of larger possible complexes. These included ribosomal proteins, nucleolar proteins, translation initiation factors, helicases, and hnRNPs. The association of selected cellular proteins with IBV N protein was confirmed by immunoblotting, cosedimentation, and confocal microscopy. Further, the localization of selected proteins in IBV-infected cells as well as their activity during virus infection was assessed by small interfering RNA-mediated depletion, demonstrating the functional importance of cellular proteins in the biology of IBV. This interactome not only confirms previous observations made with other coronavirus and IBV N proteins with both overexpressed proteins and infectious virus but also provides novel data that can be exploited to understand the interaction between the virus and the host cell.
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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 | 0.001 | 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".