Genome-wide analysis of Homo sapiens, Arabidopsis thaliana, and Saccharomyces cerevisiae reveals novel attributes of tail-anchored membrane proteins
Bibliographic record
Abstract
BACKGROUND: Tail-anchored membrane proteins (TAMPs) differ from other integral membrane proteins, because they contain a single transmembrane domain at the extreme carboxyl-terminus and are therefore obliged to target to membranes post-translationally. Although 3-5% of all transmembrane proteins are predicted to be TAMPs only a small number are well characterized. RESULTS: To identify novel putative TAMPs across different species, we used TAMPfinder software to identify 859, 657 and 119 putative TAMPs in human (Homo sapiens), plant (Arabidopsis thaliana), and yeast (Saccharomyces cerevisiae), respectively. Bioinformatics analyses of these putative TAMP sequences suggest that the list is highly enriched for authentic TAMPs. To experimentally validate the software predictions several human and plant proteins identified by TAMPfinder that were previously uncharacterized were expressed in cells and visualized at subcellular membranes by fluorescence microscopy and further analyzed by carbonate extraction or by bimolecular fluorescence complementation. With the exception of the pro-apoptotic protein harakiri, which is, peripherally bound to the membrane this subset of novel proteins behave like genuine TAMPs. Comprehensive bioinformatics analysis of the generated TAMP datasets revealed previously unappreciated common and species-specific features such as the unusual size distribution of and the propensity of TAMP proteins to be part of larger complexes. Additionally, novel features of the amino acid sequences that anchor TAMPs to membranes were also revealed. CONCLUSIONS: The findings in this study more than double the number of predicted annotated TAMPs and provide new insights into the common and species-specific features of TAMPs. Furthermore, the list of TAMPs and annotations provide a resource for further investigation.
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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 | 0.000 |
| 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".