Keeping up with the condensates: The retention, gain, and loss of nuclear membrane-less organelles
Bibliographic record
Abstract
In recent decades, a growing number of biomolecular condensates have been identified in eukaryotic cells. These structures form through phase separation and have been linked to a diverse array of cellular processes. While a checklist of established membrane-bound organelles is present across the eukaryotic domain, less is known about the conservation of membrane-less subcellular structures. Many of these structures can be seen throughout eukaryotes, while others are only thought to be present in metazoans or a limited subset of species. In particular, the nucleus is a hub of biomolecular condensates. Some of these subnuclear domains have been found in a broad range of organisms, which is a characteristic often attributed to essential functionality. However, this does not always appear to be the case. For example, the nucleolus is critical for ribosomal biogenesis and is present throughout the eukaryotic domain, while the Cajal bodies are believed to be similarly conserved, yet these structures are dispensable for organismal survival. Likewise, depletion of the Drosophila melanogaster omega speckles reduces viability, despite the apparent absence of this domain in higher eukaryotes. By reviewing primary research that has analyzed the presence of specific condensates (nucleoli, Cajal bodies, amyloid bodies, nucleolar aggresomes, nuclear speckles, nuclear paraspeckles, nuclear stress bodies, PML bodies, omega speckles, NUN bodies, mei2 dots) in a cross-section of organisms (e.g., human, mouse, D. melanogaster, Caenorhabditis elegans, yeast), we adopt a human-centric view to explore the emergence, retention, and absence of a subset of nuclear biomolecular condensates. This overview is particularly important as numerous biomolecular condensates have been linked to human disease, and their presence in additional species could unlock new and well characterized model systems for health research.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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".