Prevalence and environmental abundance of the elusive membrane trafficking complex TSET in five cosmopolitan eukaryotic groups
Bibliographic record
Abstract
Abstract Eukaryotic cell biology is largely understood from paradigms established on few model organisms, largely from the animal and fungi (opisthokonts) and to a lesser extent plants. These organisms, however, constitute only a small proportion of eukaryotic diversity, and the principles of their cell biology may not be universal to other, understudied but globally impactful, organisms. Intriguingly, there are cellular components that are present in diverse eukaryotes, but are not in the animals and fungi on which the best developed models of cell biology are derived. Consequently, these components are not included in the generally adopted frameworks of cellular function that are meant to explain eukaryotic biology. The membrane complex TSET is the best studied such example, well established to play a role in cell division and endocytosis in plants. It is found across eukaryotes, but is highly reduced in opisthokonts. Its general prevalence, abundance, and relevance in eukaryotic cellular activity is unclear. Here we show that TSET is encoded in genomes of five cosmopolitan and critical groups of primarily photosynthetic eukaryotes (green algae, red algae, stramenopiles, haptophytes and cryptophytes), with particular prevalence in the green algae and some stramenopile groups. A meta-analysis of published gene expression data from the model diatom Phaeodactylum tricornutum shows that this complex is coregulated with components of the endomembrane trafficking machinery. Moreover, meta-transcriptomic data from Tara Oceans reveals that TSET genes are both present and expressed by diatoms in the wild. These data suggest that TSET may be playing an important and underrecognized role in cellular activities within marine ecosystems. More broadly, the results support the idea that use of systems-level data for non-model organisms can illuminate our understanding of core principles of eukaryotic cell function, and may reveal important and under-appreciated players that deserve to be integrated into the pervasive models of cellular capacity.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".