Eisosome Ultrastructure and Evolution in Fungi, Microalgae, and Lichens
Bibliographic record
Abstract
Eisosomes are among the few remaining eukaryotic cellular differentations that lack a defined function(s). These trough-shaped invaginations of the plasma membrane have largely been studied in Saccharomyces cerevisiae, in which their associated proteins, including two BAR domain proteins, have been identified, and homologues have been found throughout the fungal radiation. Using quick-freeze deep-etch electron microscopy to generate high-resolution replicas of membrane fracture faces without the use of chemical fixation, we report that eisosomes are also present in a subset of red and green microalgae as well as in the cysts of the ciliate Euplotes. Eisosome assembly is closely correlated with both the presence and the nature of cell walls. Microalgal eisosomes vary extensively in topology and internal organization. Unlike fungi, their convex fracture faces can carry lineage-specific arrays of intramembranous particles, and their concave fracture faces usually display fine striations, also seen in fungi, that are pitched at lineage-specific angles and, in some cases, adopt a broad-banded patterning. The conserved genes that encode fungal eisosome-associated proteins are not found in sequenced algal genomes, but we identified genes encoding two algal lineage-specific families of predicted BAR domain proteins, called Green-BAR and Red-BAR, that are candidate eisosome organizers. We propose a model for eisosome formation wherein (i) positively charged recognition patches first establish contact with target membrane regions and (ii) a (partial) unwinding of the coiled-coil conformation of the BAR domains then allows interactions between the hydrophobic faces of their amphipathic helices and the lipid phase of the inner membrane leaflet, generating the striated patterns.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".