Lateral surface pressure generated by nascent ribosomal RNA suppresses growth of fibrillar centers in the nucleolus
Bibliographic record
Abstract
ABSTRACT Liquid-liquid phase separation (LLPS) has been thought to be the biophysical principle governing the assembly of the multiphase structures of nucleoli, the site of ribosomal biogenesis. Condensates assembled through LLPS increase their sizes to minimize the surface energy as far as their components are available. However, multiple microphases, fibrillar centers (FCs), dispersed in a nucleolus are stable and their sizes do not grow unless the transcription of pre-ribosomal RNA (pre-rRNA) is inhibited. To understand the mechanism of the suppression of the FC growth, we here construct a minimal theoretical model by taking into account the nascent pre-rRNAs tethered to the FC surfaces by RNA polymerase I. Our theory predicts that nascent pre-rRNAs generate the lateral osmotic pressure that counteracts the surface tension of the FCs and this suppresses the growth of the FCs over the stable size. The stable FC size decreases with increasing the transcription rate and decreasing the RNA processing rate. This prediction is supported by our experiments showing that RNA polymerase inhibitors increase the FC size in a dose-dependent manner. This theory may provide insight into the general mechanism of the size control of nuclear bodies. Significance statement The nucleolus, a site of pre-ribosomal RNA (pre-rRNA) production, has a characteristic multiphase structure, which has been thought to be assembled through liquid-liquid phase separation (LLPS). Although condensates assembled through LLPS grow by coarsening or coalescence as far as the components are available, the multiple inner phases, fibrillar centers (FCs), are dispersed in a nucleolus. To investigate the underlying mechanism, we constructed a minimal theoretical model by considering nascent pre-rRNAs tethered to RNA polymerase I at the FC surface. This model is supported by our experiments and explains previous experimental observations. This work shed light on the role of nascent RNAs to control the size of nuclear bodies.
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 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 | 0.000 | 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".