The ability to learn and form memories is critical for animals to make choices that promote their survival. The biological processes underlying learning and memory are mediated by a variety of genes in the nervous system, acting at specific times during memory encoding, consolidation, and retrieval. Many studies have utilised candidate gene approaches or random mutagenesis screens in model animals to explore the key molecular drivers for learning and memory. We propose a complementary approach to identify this network of learning regulators: the proximity-labelling tool TurboID, which promiscuously biotinylates neighbouring proteins, to snapshot the proteomic profile of neurons during learning. To do this, we expressed the TurboID enzyme in the entire nervous system of Caenorhabditis elegans and exposed animals to biotin only during the training step of an appetitive gustatory learning paradigm. Our approach revealed hundreds of proteins specific to 'trained' worms, including components of molecular pathways previously implicated in memory in multiple species such as insulin signalling, G-protein-coupled receptor signalling, and MAP kinase signalling. Most (87-95%) of the proteins identified are neuronal, with relatively high representation for neuron classes involved in locomotion and learning. We validated several novel regulators of learning, including cholinergic receptors (ACC-1, ACC-3, LGC-46) and putative arginine kinase F46H5.3. These previously uncharacterised learning regulators all showed a clear impact on appetitive gustatory learning, with F46H5.3 showing an additional effect on aversive gustatory memory. Overall, we show that proximity labelling can be used in the brain of a small animal as a feasible and effective method to advance our knowledge on the biology of learning.
Identifying regulators of associative learning using a protein-labelling approach in Caenorhabditis elegans.
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作者:Rahmani Aelon, McMillen Anna, Allen Ericka, Ansaar Radwan, Green Renee, Johnson Michaela E, Poljak Anne, Chew Yee Lian
| 期刊: | Elife | 影响因子: | 6.400 |
| 时间: | 2026 | 起止号: | 2026 Jan 28; 14:RP108438 |
| doi: | 10.7554/eLife.108438 | ||
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