Huntingtin S421 phosphorylation increases kinesin and dynein engagement on early endosomes and lysosomes
Bibliographic record
Abstract
Abstract Huntingtin (HTT) is a scaffolding protein that recruits motor proteins to vesicular cargoes, enabling it to regulate kinesin-1, dynein, and myosin-VI-dependent transport. To maintain the native stoichiometry of huntingtin with its interacting partners, we used CRISPR/Cas9 to induce a phosphomimetic mutation of the endogenous HTT at S421 (HTT-S421D). Using single particle tracking, optical tweezers, and immunofluorescence, we examined the effects of this mutation on the motility of early endosomes and lysosomes. In HTT-S421D cells, lysosomes exhibit longer displacements and higher processive fractions compared to wild-type (HTT-WT) cells. Kinesins and dyneins exert greater forces on early endosomes and lysosomes in cells expressing HTT-S421D. Additionally, endosomes bind to microtubules faster and are more resistant to detachment under load. The recruitment of kinesins and dyneins to microtubules is enhanced in HTT-S421D cells. In contrast, overexpression of HTT had variable effects on the processivity, displacement, and directional bias of both early endosomes and lysosomes. These data indicate that phosphorylation of the endogenous huntingtin causes early endosomes and lysosomes to move longer distances and more processively by recruiting and activating both kinesin-1 and dynein. Statement of Significance The ubiquitous scaffolding protein huntingtin regulates the recruitment and activity of microtubule motors. Huntingtin phosphorylation at S421 enhances the microtubule binding and force generation of kinesin and dynein on early endosomes and lysosomes. Using optical tweezers to measure the forces exerted on endosomes in CRISPR-engineered cells, we find that a phosphomimetic huntingtin mutation (S421D) enhances both kinesin- and dynein-driven forces on early endosomes and lysosomes. The ability to modulate motor activity on a range of organelles makes huntingtin unique and suggests a significant role for huntingtin in regulating intracellular transport.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".