Plasticity of Polyubiquitin Recognition as Lysosomal Targeting Signals by the Endosomal Sorting Machinery
Bibliographic record
Abstract
Lysosomal targeting is fundamental for the regulated disposal of ubiquitinated membrane proteins from the cell surface. To elucidate ubiquitin (Ub) configurations that are necessary and sufficient as multivesicular body (MVB)/lysosomal-sorting motifs, the intraendosomal destination and transport kinetics of model transmembrane cargo molecules bearing monoubiquitinated, multi-monoubiquitinated, or polyubiquitinated cytoplasmic tails were determined. Monomeric CD4 chimeras with K63-linked poly-Ub chains and tetrameric CD4-mono-Ub chimeras were rapidly targeted to the lysosome. In contrast, lysosomal delivery of CD4 chimeras exposing K48-linked Ub chains was delayed, whereas delivery of monoubiquitinated CD4 chimeras was undetectable. Similar difference was observed in the lysosomal targeting of mono- versus polyubiquitinated invariant chain and CD4 ubiquitinated by the MARCH (membrane-associated RING-CH) IV Ub ligase. Consistent with this, Hrs (hepatocyte growth factor regulated tyrosine kinase phosphorylated substrate), an endosomal sorting adaptor, binds preferentially to K63-Ub chain and negligibly to mono-Ub. These results highlight the plasticity of Ub as a sorting signal and its recognition by the endosomal sorting machinery, and together with previous data, suggest a regulatory role for assembly and disassembly of Ub chains of specific topology in lysosomal cargo sorting.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".