Identification of Proteins from<i>Prunus persica</i>That Interact with Peach Latent Mosaic Viroid
Bibliographic record
Abstract
Peach latent mosaic viroid (PLMVd) is a small, single-stranded, circular RNA pathogen that infects Prunus persica trees. As with all other known viroids, the PLMVd genome does not encode any proteins. Consequently, it must interact with host cellular factors in order to ensure its life cycle. With the objective of identifying cellular proteins that interact with PLMVd, Northwestern hybridizations were performed using partially purified peach leaf extracts. Mass spectrometric analysis of the detected RNA-protein complexes led to the identification of six putative RNA-binding proteins. One of these was found to be elongation factor 1-alpha (eEF1A), and because of its known involvement in the replication and translation of various RNA viruses, further characterizations were performed. Initially, the existence of this interaction received support from an experiment that immunoprecipitated the eEF1A from a crude extract of infected peach leaves, coupled with reverse transcription-PCR detection of the PLMVd. Subsequently, eEF1A interaction with PLMVd strands of both polarities was confirmed in vitro by electrophoresis mobility shift assays, fluorescence spectroscopy, and the prediction of an altered PLMVd RNase mapping profile in the presence of the protein. The potential contribution of eEF1A to the molecular biology of PLMVd, including for viroid replication, is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".