Debra, a protein mediating lysosomal degradation, is required for long-term memory in Drosophila

Upregulated energy metabolism in the Drosophila mushroom body is the trigger for long-term memory

Efficient energy use has constrained the evolution of nervous systems. However, it is unresolved whether energy metabolism may resultantly regulate major brain functions. Our observation that Drosophila flies double their sucrose intake at an early stage of long-term memory formation initiated the investigation of how energy metabolism intervenes in this process. Cellular-resolution imaging of energy metabolism reveals a concurrent elevation of energy consumption in neurons of the mushroom body, the fly's major memory centre. Strikingly, upregulation of mushroom body energy flux is both necessary and sufficient to drive long-term memory formation. This effect is triggered by a specific pair of dopaminergic neurons afferent to the mushroom bodies, via the D5-like DAMB dopamine receptor. Hence, dopamine signalling mediates an energy switch in the mushroom body that controls long-term memory encoding. Our data thus point to an instructional role for energy flux in the execution of demanding higher brain functions.

Energy consumption in the brain is thought to respond to changes in neuronal activity, without informational role. Here the authors show that increased energy flux in the mushroom body, driven by a pair of input dopaminergic neurons, is a command for the formation of long-term memory in Drosophila.

Proteolysis, synaptic plasticity and memory

Protein degradation has many critical functions in the nervous system such as refinement of synaptic connections during development and synaptic plasticity and memory in the adult organisms. A major cellular machinery of proteolysis is the ubiquitin-proteasome pathway (UPP). The UPP precisely regulates proteolysis by covalently attaching ubiquitin, a small protein, to substrates through sequential enzymatic reactions and the proteins marked with the ubiquitin tag are degraded by complex containing many subunits called the proteasome. Research over the years has shown a role for the UPP in regulating presynaptic and postsynaptic proteins critical for neurotransmission and synaptic plasticity. Studies have also revealed a role for the UPP in various forms of memory. Mechanistic investigations suggest that the function of the UPP in neurons is not homogenous and is subject to local regulation in different neuronal sub-compartments. In both invertebrate and vertebrate model systems, local roles have been found for enzymes that attach ubiquitin to substrate proteins as well as for enzymes that remove ubiquitin from substrates. The proteasome also has disparate functions in different parts of the neuron. In addition to the UPP, proteolysis by the lysosome and autophagy play a role in synaptic plasticity and memory. This review details the functions of proteolysis in synaptic plasticity and summarizes the findings on the connection between proteolysis and memory mainly focusing on the UPP including its local roles.

A role of protein degradation in memory consolidation after initial learning and extinction learning in the honeybee (Apis mellifera)

Protein degradation is known to affect memory formation after extinction learning. We demonstrate here that an inhibitor of protein degradation, MG132, interferes with memory formation after extinction learning in a classical appetitive conditioning paradigm. In addition, we find an enhancement of memory formation when the same inhibitor is applied after initial learning. This result supports the idea that MG132 targets an ongoing consolidation process. Furthermore, we demonstrate that the sensitivity of memory formation after initial learning and extinction learning to MG132 depends in the same way on the number of CS-US trials and the intertrial interval applied during initial learning. This supports the idea that the learning parameters during acquisition are critical for memory formation after extinction and that protein degradation in both learning processes might be functionally linked.