Dual recombinase fate mapping reveals a transient cholinergic phenotype in multiple populations of developing glutamatergic neurons
Bibliographic record
Abstract
Abstract Cholinergic transmission shapes the maturation of glutamatergic circuits, yet the developmental sources of acetylcholine have not been systematically explored. Here, we have used Cre‐recombinase‐mediated genetic labeling to identify and map both mature and developing CNS neurons that express choline acetyltransferase (ChAT). Correction of a significant problem with a widely used ChatCre transgenic line ensures that this map does not contain expression artifacts. ChatCre marks all known cholinergic systems in the adult brain, but also identifies several brain areas not usually regarded as cholinergic, including specific thalamic and hypothalamic neurons, the subiculum, the lateral parabrachial nucleus, the cuneate/gracilis nuclei, and the pontocerebellar system. This ChatCre fate map suggests transient developmental expression of a cholinergic phenotype in areas important for cognition, motor control, and respiration. We therefore examined expression of ChAT and the vesicular acetylcholine transporter in the embryonic and early postnatal brain to determine the developmental timing of this transient cholinergic phenotype, and found that it mirrored the establishment of relevant glutamatergic projection pathways. We then used an intersectional genetic strategy combining ChatCre with Vglut2Flp to show that these neurons adopt a glutamatergic fate in the adult brain. The transient cholinergic phenotype of these glutamatergic neurons suggests a homosynaptic source of acetylcholine for the maturation of developing glutamatergic synapses. These findings thus define critical windows during which specific glutamatergic circuits may be vulnerable to disruption by nicotine in utero, and suggest new mechanisms for pediatric disorders associated with maternal smoking, such as sudden infant death syndrome.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".