Sticks and Stones, a conserved cell surface ligand for the Type IIa RPTP Lar, regulates neural circuit wiring in Drosophila

Control of tyrosine phosphorylation is an essential element of many cellular processes, including proliferation, differentiation neurite outgrowth, and synaptogenesis. Receptor-like protein-tyrosine phosphatases (RPTPs) have cytoplasmic phosphatase domains and cell adhesion molecule (CAM)-like extracellular domains that interact with cell-surface ligands and/or co-receptors. We identified a new ligand for the Drosophila Lar RPTP, the immunoglobulin superfamily CAM Sticks and Stones (Sns). Lar is orthologous to the three Type IIa mammalian RPTPs, PTPRF (LAR), PTPRD (PTPδ), and PTPRS (PTPσ). Lar and Sns bind to each other in embryos and in vitro. The human Sns ortholog, Nephrin, binds to PTPRD and PTPRF. Genetic interaction studies show that Sns is essential to Lar’s functions in several developmental contexts in the larval and adult nervous systems. In the larval neuromuscular system, Lar and sns transheterozygotes (Lar/sns transhets) have synaptic defects like those seen in Lar mutants and Sns knockdown animals. Lar and Sns reporters are both expressed in motor neurons and not in muscles, so Lar and Sns likely act in cis (in the same neurons). Lar mutants and Lar/sns transhets have identical axon guidance defects in the larval mushroom body in which Kenyon cell axons fail to stop at the midline and do not branch. Pupal Kenyon cell axon guidance is similarly affected, resulting in adult mushroom body defects. Lar is expressed in larval and pupal Kenyon cells, but Sns is not, so Lar-Sns interactions in this system must be in trans (between neurons). Lastly, R7 photoreceptor axons in Lar mutants and Lar/sns transhets fail to innervate the correct M6 layer of the medulla in the optic lobe. Lar acts cell-autonomously in R7s, while Sns is only in lamina and medulla neurons that arborize near the R7 target layer. Therefore, the Lar-Sns interactions that control R7 targeting also occur in trans.

Mechanisms underlying homeostatic plasticity in theDrosophilamushroom body in vivo

Neural network function requires an appropriate balance of excitation and inhibition to be maintained by homeostatic plasticity. However, little is known about homeostatic mechanisms in the intact central brain in vivo. Here, we study homeostatic plasticity in theDrosophilamushroom body, where Kenyon cells receive feedforward excitation from olfactory projection neurons and feedback inhibition from the anterior paired lateral neuron (APL). We show that prolonged (4-d) artificial activation of the inhibitory APL causes increased Kenyon cell odor responses after the artificial inhibition is removed, suggesting that the mushroom body compensates for excess inhibition. In contrast, there is little compensation for lack of inhibition (blockade of APL). The compensation occurs through a combination of increased excitation of Kenyon cells and decreased activation of APL, with differing relative contributions for different Kenyon cell subtypes. Our findings establish the fly mushroom body as a model for homeostatic plasticity in vivo.

Integration of Odor-Induced Activity of Kenyon Cells in an Electrotonically Compact Drosophila Mushroom Body Output Neuron (MBON)

The formation of an ecologically useful lasting memory requires that the brain has an accurate internal representation of the surrounding environment. In addition, it must have the ability to integrate a variety of different sensory stimuli and associate them with rewarding and aversive behavioral outcomes. Over the previous years, a number of studies have dissected the anatomy and elucidated some of the working principles of the Drosophila mushroom body (MB), the fly’s center for learning and memory. As a consequence, we now have a functional understanding of where and how in the MB sensory stimuli converge and are associated. However, the molecular and cellular dynamics at the critical synaptic intersection for this process, the Kenyon cell-mushroom body output neuron (KC-MBON) synapse, are largely unknown. Here, we introduce a first approach to understand this integration process and the physiological changes occurring at the KC-MBON synapse during Kenyon cell (KC) activation. We use the published connectome of the Drosophila MB to construct a functional computational model of the MBON-α3-A dendritic structure. We simulate synaptic input by individual KC-MBON synapses by current injections into precisely (μm) identified local dendritic sections, and the input from a model population of KCs representing an odor by a spatially distributed cluster of current injections. By recording the effect of the simulated current injections on the membrane potential of the neuron, we show that the MBON-α3-A is electrotonically compact. This suggests that odor-induced MBON activity is likely governed by input strength while the positions of KC input synapses are largely irrelevant.

Inhibitory muscarinic acetylcholine receptors enhance aversive olfactory learning in adult Drosophila

Olfactory associative learning in Drosophila is mediated by synaptic plasticity between the Kenyon cells of the mushroom body and their output neurons. Both Kenyon cells and their inputs from projection neurons are cholinergic, yet little is known about the physiological function of muscarinic acetylcholine receptors in learning in adult flies. Here, we show that aversive olfactory learning in adult flies requires type A muscarinic acetylcholine receptors (mAChR-A), particularly in the gamma subtype of Kenyon cells. mAChR-A inhibits odor responses and is localized in Kenyon cell dendrites. Moreover, mAChR-A knockdown impairs the learning-associated depression of odor responses in a mushroom body output neuron. Our results suggest that mAChR-A function in Kenyon cell dendrites is required for synaptic plasticity between Kenyon cells and their output neurons.

Flexible neural connectivity under constraints on total connection strength

Neural computation is determined by neuron dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of the degree distributions of connectivity based on constraints on a neuron’s total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and the adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.Author summaryHigh-throughput electron microscopic anatomical experiments have begun to yield detailed maps of neural circuit connectivity. Uncovering the principles that govern these circuit structures is a major challenge for systems neuroscience. Healthy neural circuits must be able to perform computational tasks while satisfying physiological constraints. Those constraints can restrict a neuron’s possible connectivity, and thus potentially restrict its computation. Here we examine simple models of constraints on total synaptic weights, and calculate the number of circuit configurations they allow: their computational flexibility. We propose probabilistic models of connectivity that weight the number of synaptic partners according to computational flexibility under a constraint and test them using recent wiring diagrams from a learning center, the mushroom body, in the fly brain. We compare constraints that fix or bound a neuron’s total connection strength to a simple random wiring null model. Of these models, the fixed total connection strength matched the overall connectivity best in mushroom bodies from both larval and adult flies. We also provide evidence suggesting that neural circuits are more flexible in early stages of development and lose this flexibility as they grow towards specialized function.

Inhibitory muscarinic acetylcholine receptors enhance aversive olfactory conditioning in adult Drosophila

Olfactory associative learning inDrosophilais mediated by synaptic plasticity between the Kenyon cells of the mushroom body and their output neurons. Both Kenyon cells and their inputs are cholinergic, yet little is known about the physiological function of muscarinic acetylcholine receptors in learning in adult flies. Here we show that aversive olfactory learning in adult flies requires type A muscarinic acetylcholine receptors (mAChR-A) specifically in the gamma subtype of Kenyon cells. Surprisingly, mAChR-A inhibits odor responses in both Kenyon cell dendrites and axons. Moreover, mAChR-A knockdown impairs the learning-associated depression of odor responses in a mushroom body output neuron. Our results suggest that mAChR-A is required at Kenyon cell presynaptic terminals to depress the synapses between Kenyon cells and their output neurons, and may suggest a role for the recently discovered axo-axonal synapses between Kenyon cells.