skip to main content

This content will become publicly available on December 1, 2023

Title: Selective control of synaptically-connected circuit elements by all-optical synapses
Abstract Understanding percepts, engrams and actions requires methods for selectively modulating synaptic communication between specific subsets of interconnected cells. Here, we develop an approach to control synaptically connected elements using bioluminescent light: Luciferase-generated light, originating from a presynaptic axon terminal, modulates an opsin in its postsynaptic target. Vesicular-localized luciferase is released into the synaptic cleft in response to presynaptic activity, creating a real-time Optical Synapse. Light production is under experimenter-control by introduction of the small molecule luciferin. Signal transmission across this optical synapse is temporally defined by the presence of both the luciferin and presynaptic activity. We validate synaptic Interluminescence by multi-electrode recording in cultured neurons and in mice in vivo. Interluminescence represents a powerful approach to achieve synapse-specific and activity-dependent circuit control in vivo.
; ; ; ; ; ; ; ; ; ; ; ;
Award ID(s):
Publication Date:
Journal Name:
Communications Biology
Sponsoring Org:
National Science Foundation
More Like this
  1. A considerable amount of energy is expended following presynaptic activity to regenerate electrical polarization and maintain efficient release and recycling of neurotransmitter. Mitochondria are the major suppliers of neuronal energy, generating ATP via oxidative phosphorylation. However, the specific utilization of energy from cytosolic glycolysis rather than mitochondrial respiration at the presynaptic terminal during synaptic activity remains unclear and controversial. We use a synapse specialized for high-frequency transmission in mice, the calyx of Held, to test the sources of energy used to maintain energy during short activity bursts (<1 s) and sustained neurotransmission (30–150 s). We dissect the role of presynaptic glycolysis versusmore »mitochondrial respiration by acutely and selectively blocking these ATP-generating pathways in a synaptic preparation where mitochondria and synaptic vesicles are prolific, under near-physiological conditions. Surprisingly, if either glycolysis or mitochondrial ATP production is intact, transmission during repetitive short bursts of activity is not affected. In slices from young animals before the onset of hearing, where the synapse is not yet fully specialized, both glycolytic and mitochondrial ATP production are required to support sustained, high-frequency neurotransmission. In mature synapses, sustained transmission relies exclusively on mitochondrial ATP production supported by bath lactate, but not glycolysis. At both ages, we observe that action potential propagation begins to fail before defects in synaptic vesicle recycling. Our data describe a specific metabolic profile to support high-frequency information transmission at the mature calyx of Held, shifting during postnatal synaptic maturation from glycolysis to rely on monocarboxylates as a fuel source. NEW & NOTEWORTHY We dissect the role of presynaptic glycolysis versus mitochondrial respiration in supporting high-frequency neurotransmission, by acutely blocking these ATP-generating pathways at a synapse tuned for high-frequency transmission. We find that massive energy expenditure is required to generate failure when only one pathway is inhibited. Action potential propagation is lost before impaired synaptic vesicle recycling. Synaptic transmission is exclusively dependent on oxidative phosphorylation in mature synapses, indicating presynaptic glycolysis may be dispensable for ATP maintenance.« less
  2. Detecting synaptic connections using large-scale extracellular spike recordings presents a statistical challenge. Although previous methods often treat the detection of each putative connection as a separate hypothesis test, here we develop a modeling approach that infers synaptic connections while incorporating circuit properties learned from the whole network. We use an extension of the generalized linear model framework to describe the cross-correlograms between pairs of neurons and separate correlograms into two parts: a slowly varying effect due to background fluctuations and a fast, transient effect due to the synapse. We then use the observations from all putative connections in the recordingmore »to estimate two network properties: the presynaptic neuron type (excitatory or inhibitory) and the relationship between synaptic latency and distance between neurons. Constraining the presynaptic neuron’s type, synaptic latencies, and time constants improves synapse detection. In data from simulated networks, this model outperforms two previously developed synapse detection methods, especially on the weak connections. We also apply our model to in vitro multielectrode array recordings from the mouse somatosensory cortex. Here, our model automatically recovers plausible connections from hundreds of neurons, and the properties of the putative connections are largely consistent with previous research. NEW & NOTEWORTHY Detecting synaptic connections using large-scale extracellular spike recordings is a difficult statistical problem. Here, we develop an extension of a generalized linear model that explicitly separates fast synaptic effects and slow background fluctuations in cross-correlograms between pairs of neurons while incorporating circuit properties learned from the whole network. This model outperforms two previously developed synapse detection methods in the simulated networks and recovers plausible connections from hundreds of neurons in in vitro multielectrode array data.« less
  3. The vertical lobe (VL) in the octopus brain plays an essential role in its sophisticated learning and memory. Early anatomical studies suggested that the VL is organized in a “fan-out fan-in” connectivity matrix comprising only three morphologically identified neuron types; input axons from the superior frontal lobe (SFL) innervating en passant millions of small amacrine interneurons (AMs) which converge sharply onto large VL output neurons (LNs). Recent physiological studies confirmed the feedforward excitatory connectivity: a glutamatergic synapse at the first SFL-to-AM synaptic layer and a cholinergic AM-to-LNs synapse. SFL-to-AMs synapses show a robust hippocampal-like activity-dependent long-term potentiation (LTP) of transmittermore »release. 5-HT, octopamine, dopamine, and nitric oxide modulate short- and long-term VL synaptic plasticity. Here we present a comprehensive histolabeling study to better characterize the neural elements in the VL. We generally confirmed glutamatergic SFLs and cholinergic AMs. Intense labeling for NOS activity in the AMs neurites fitted with the NO-dependent presynaptic LTP mechanism at the SFL-to-AM synapse. New discoveries here reveal more heterogeneity of the VL neurons than previously thought. GABAergic AMs suggest a subpopulation of inhibitory interneurons in the first input layer. Clear GABA labeling in the cell bodies of LNs supported an inhibitory VL output yet the LNs co-expressed FMRFamide-like neuropeptides suggesting an additional neuromodulatory role of the VL output. Furthermore, a group of LNs was glutamatergic. A new cluster of cells organized in a “deep nucleus” showed rich catecholaminergic labeling and may play a role in intrinsic neuromodulation. In situ hybridization and immunolabeling allowed characterization and localization of a rich array of neuropeptides and neuromodulators, likely involved in reward/punishment signals. This analysis of the fast transmission system, together with the newly found cellular elements helps integrate behavioral, physiological, pharmacological, and connectome findings into a more comprehensive understanding of an efficient learning and memory network.« less
  4. Neuronal synapses transmit electrochemical signals between cells through the coordinated action of presynaptic vesicles, ion channels, scaffolding and adapter proteins, and membrane receptors. In situ structural characterization of numerous synaptic proteins simultaneously through multiplexed imaging facilitates a bottom-up approach to synapse classification and phenotypic description. Objective automation of efficient and reliable synapse detection within these datasets is essential for the high-throughput investigation of synaptic features. Convolutional neural networks can solve this generalized problem of synapse detection, however, these architectures require large numbers of training examples to optimize their thousands of parameters. We propose DoGNet, a neural network architecture that closesmore »the gap between classical computer vision blob detectors, such as Difference of Gaussians (DoG) filters, and modern convolutional networks. DoGNet is optimized to analyze highly multiplexed microscopy data. Its small number of training parameters allows DoGNet to be trained with few examples, which facilitates its application to new datasets without overfitting. We evaluate the method on multiplexed fluorescence imaging data from both primary mouse neuronal cultures and mouse cortex tissue slices. We show that DoGNet outperforms convolutional networks with a low-to-moderate number of training examples, and DoGNet is efficiently transferred between datasets collected from separate research groups. DoGNet synapse localizations can then be used to guide the segmentation of individual synaptic protein locations and spatial extents, revealing their spatial organization and relative abundances within individual synapses. The source code is publicly available:« less
  5. The role of the cannabinoid receptor 2 (CNR2) is still poorly described in sensory epithelia. We found strong cnr2 expression in hair cells (HCs) of the inner ear and the lateral line (LL), a superficial sensory structure in fish. Next, we demonstrated that sensory synapses in HCs were severely perturbed in larvae lacking cnr2. Appearance and distribution of presynaptic ribbons and calcium channels (Ca v 1.3) were profoundly altered in mutant animals. Clustering of membrane-associated guanylate kinase (MAGUK) in post-synaptic densities (PSDs) was also heavily affected, suggesting a role for cnr2 for maintaining the sensory synapse. Furthermore, vesicular trafficking inmore »HCs was strongly perturbed suggesting a retrograde action of the endocannabinoid system (ECs) via cnr2 that was modulating HC mechanotransduction. We found similar perturbations in retinal ribbon synapses. Finally, we showed that larval swimming behaviors after sound and light stimulations were significantly different in mutant animals. Thus, we propose that cnr2 is critical for the processing of sensory information in the developing larva.« less