Fat traffic control: S-acylation in axonal transport
Bibliographic record
Abstract
Neuronal axons serve as a conduit for the coordinated transport of essential molecular cargo between structurally and functionally distinct subcellular compartments via axonal molecular machinery. Long-distance, efficient axonal transport of membrane-bound organelles enables signal transduction and neuronal homeostasis. Efficient axonal transport is conducted by dynein and kinesin ATPase motors that use a local ATP supply from metabolic enzymes tethered to transport vesicles. Molecular motor adaptor proteins promote the processive motility and cargo selectivity of fast axonal transport. Axonal transport impairments are directly causative or associated with many neurodegenerative diseases and neuropathologies. Cargo specificity, cargo-adaptor proteins, and posttranslational modifications of cargo, adaptor proteins, microtubules, or the motor protein subunits all contribute to the precise regulation of vesicular transit. One posttranslational lipid modification that is particularly important in neurons in regulating protein trafficking, protein-protein interactions, and protein association with lipid membranes is S-acylation. Interestingly, many fast axonal transport cargos, cytoskeletal-associated proteins, motor protein subunits, and adaptors are S-acylated to modulate axonal transport. Here, we review the established regulatory role of S-acylation in fast axonal transport and provide evidence for a broader role of S-acylation in regulating the motor-cargo complex machinery, adaptor proteins, and metabolic enzymes from low-throughput studies and S-acyl-proteomic data sets. We propose that S-acylation regulates fast axonal transport and vesicular motility through localization of the proteins required for the motile cargo-complex machinery and relate how perturbed S-acylation contributes to transport impairments in neurological disorders. SIGNIFICANCE STATEMENT: This review investigates the regulatory role of S-acylation in fast axonal transport and its connection to neurological diseases, with a focus on the emerging connections between S-acylation and the molecular motors, adaptor proteins, and metabolic enzymes that make up the trafficking machinery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".