CaMK (CMK-1) and O-GlcNAc transferase (OGT-1) modulate mechanosensory responding and habituation in an interstimulus interval-dependent manner in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
Abstract The ability to learn is an evolutionarily conserved adaptation that remains incompletely understood. Genetically tractable model organisms facilitate mechanistic explanations of learning that span genetic, neural circuit, and behavioural levels. Many aspects of neural physiology, including processes that underlie learning ( e.g. neurotransmitter release and long-lasting changes in synaptic strength), are regulated by brief and local changes in [ μ m] levels of free intracellular Ca 2+ . On this scale, changes in [Ca 2+ ] activate many Ca 2+ -sensors, including the Ca 2+ /calmodulin-dependent kinases (CaMKs). Here we reveal that the Caenorhabditis elegans ortholog of CaMK1/4, CMK-1, functions in primary sensory neurons to regulate responses to mechanical stimuli and behavioral plasticity, specifically habituation, a conserved form of non-associative learning. The habituation phenotypes of cmk-1 mutants were dependent on interstimulus interval (ISI), such that CMK-1 slows habituation at short ISIs, but promotes it at long ISIs. We predicted potential CaMK phosphorylation targets from catalytic site analysis of the human and C. elegans CaMKs and mutant analysis of these candidates implicated O-linked N-acetylglucosamine (O-GlcNAc) transferase, OGT-1, in mechanosensitivity and learning. Cell specific rescue and knockdown experiments showed that both CMK-1 and OGT-1 function cell autonomously in mechanosensory neurons to modulate learning. Interestingly, despite their similar mutant phenotypes, detailed behavioral analysis of double mutants demonstrated that CMK-1 and OGT-1 act in parallel genetic pathways. Our research identifies CMK-1 and OGT-1 as co-expressed yet independent regulators of mechanosensitivity and learning.
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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 | 0.001 |
| 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".