Peroxisome biogenesis and the formation of multivesicular peroxisomes during tombusvirus infection: a role for ESCRT?This review is one of a selection of papers published in the Special Issue on Plant Cell Biology.
Bibliographic record
Abstract
Peroxisomes are highly dynamic organelles with regard to their metabolic functions, shapes, distribution, movements, and biogenesis. They are also important as sites for the development of some viral pathogens. It has long been known that certain members of the tombusvirus family recruit peroxisomes for viral RNA replication and that this process is accompanied by dramatic changes in peroxisome morphology, the most remarkable of which is the extensive inward vesiculation of the peroxisomal boundary membrane leading to the formation of a peroxisomal multivesicular body (pMVB). While it is unclear how the internal vesicles of a pMVB form, they appear to serve in effectively concentrating viral membrane-bound replication complexes and protecting nascent viral RNAs from host-cell defences. Here, we review briefly the biogenesis of peroxisomes and pMVBs and discuss recent studies that have begun to shed light on how components of the tombusvirus replicase exploit the molecular mechanisms involved in peroxisome membrane protein sorting. We also address the question of what controls invagination and vesicle formation at the peroxisomal membrane during pMVB biogenesis. We propose that tombusviruses exploit protein constituents of the class E vacuolar protein-sorting pathway referred to as ESCRT (endosomal sorting complex required for transport) in the formation of pMVBs. This new pMVB–ESCRT hypothesis reconciles current paradigms of pMVB biogenesis with the role of ESCRT in endosomal multivesicular body formation and the ability of enveloped RNA viruses, including HIV, to appropriate the ESCRT machinery to execute their budding programme from cells.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".