In Vivo Spike-Timing-Dependent Plasticity in the Optic Tectum of Xenopus Laevis

Spike-timing-dependent plasticity (STDP) is found in vivo in a variety of systems and species, but the first demonstrations of in vivo STDP were carried out in the optic tectum of Xenopus laevis embryos. Since then, the optic tectum has served as an excellent experimental model for studying STDP in sensory systems, allowing researchers to probe the developmental consequences of this form of synaptic plasticity during early development. In this review, we will describe what is known about the role of STDP in shaping feed-forward and recurrent circuits in the optic tectum with a focus on the functional implications for vision. We will discuss both the similarities and differences between the optic tectum and mammalian sensory systems that are relevant to STDP. Finally, we will highlight the unique properties of the embryonic tectum that make it an important system for researchers who are interested in how STDP contributes to activity-dependent development of sensory computations

Genetically encoded proton sensors reveal activity-dependent pH changes in neurons

The regulation of hydrogen ion concentration (pH) is fundamental to cell viability, metabolism, and enzymatic function. Within the nervous system, the control of pH is also involved in diverse and dynamic processes including development, synaptic transmission, and the control of network excitability. As pH affects neuronal activity, and can also itself be altered by neuronal activity, the existence of tools to accurately measure hydrogen ion fluctuations is important for understanding the role pH plays under physiological and pathological conditions. Outside of their use as a marker of synaptic release, genetically encoded pH sensors have not been utilized to study hydrogen ion fluxes associated with network activity. By combining whole-cell patch clamp with simultaneous two-photon or confocal imaging, we quantified the amplitude and time course of neuronal, intracellular, acidic transients evoked by epileptiform activity in two separate in vitro models of temporal lobe epilepsy. In doing so, we demonstrate the suitability of three genetically encoded pH sensors: deGFP4, E2GFP, and Cl-sensor for investigating activity-dependent pH changes at the level of single neurons

Active cortical networks promote shunting fast synaptic inhibition in vivo

Fast synaptic inhibition determines neuronal response properties in the mammalian brain and is mediated by chloride-permeable ionotropic GABA-A receptors (GABAARs). Despite their fundamental role, it is still not known how GABAARs signal in the intact brain. Here, we use in vivo gramicidin recordings to investigate synaptic GABAAR signaling in mouse cortical pyramidal neurons under conditions that preserve native transmembrane chloride gradients. In anesthetized cortex, synaptic GABAARs exert classic hyperpolarizing effects. In contrast, GABAAR-mediated synaptic signaling in awake cortex is found to be predominantly shunting. This is due to more depolarized GABAAR equilibrium potentials (EGABAAR), which are shown to result from the high levels of synaptic activity that characterize awake cortical networks. Synaptic EGABAAR observed in awake cortex facilitates the desynchronizing effects of inhibitory inputs upon local networks, which increases the flexibility of spiking responses to external inputs. Our findings therefore suggest that GABAAR signaling adapts to optimize cortical functions

Pro-maturational effects of human iPSC-derived cortical astrocytes upon iPSC-derived cortical neurons

Astrocytes influence neuronal maturation and function by providing trophic support, regulating the extracellular environment, andmodulating signaling at synapses. The emergence of induced pluripotent stem cell (iPSC) technology offers a human system with whichto validate and re-evaluate insights from animal studies. Here, we set out to examine interactions between human astrocytes and neuronsderived from a common cortical progenitor pool, thereby recapitulating aspects ofin vivocortical development. We show that the corticaliPSC-derived astrocytesexhibit many of the molecular and functional hallmarks of astrocytes. Furthermore, optogenetic and electrophys-iological co-culture experiments reveal that the iPSC-astrocytes can actively modulate ongoing synaptic transmission and exertpro-maturational effects upon developing networks of iPSC-derived cortical neurons. Finally, transcriptomic analyses implicate syn-apse-associated extracellular signaling in the astrocytes’ pro-maturational effects upon the iPSC-derived neurons. This work helps laythe foundation for future investigations into astrocyte-to-neuron interactions in human health and disease

Optogenetic determination of dynamic and cell-type-specific inhibitory reversal potentials

The reversal potential refers to the membrane potential at which the net current flow through a channel reverses direction. The reversal potential is determined by transmembrane ion gradients and, in turn, determines how the channel's activity will affect the membrane potential. Traditional investigation into the reversal potential of inhibitory ligand-gated ion channels (EInh) has relied upon the activation of endogenous receptors, such as the GABA-A receptor (GABAAR). There are, however, challenges associated with activating endogenous receptors, including agonist delivery, isolating channel responses, and the effects of receptor saturation and desensitization. Here, we demonstrate the utility of using a light-gated anion channel, stGtACR2, to probe EInh in the rodent brain. Using mice of both sexes, we demonstrate that the properties of this optically activated channel make it a suitable proxy for studying GABAAR receptor-mediated inhibition. We validate this agonist-independent optogenetic strategy in vitro and in vivo and further show how it can accurately capture differences in EInh dynamics following manipulations of endogenous ion fluxes. This allows us to explore distinct resting EInh differences across genetically defined neuronal subpopulations. Using this approach to challenge ion homeostasis mechanisms in neurons, we uncover cell-specific EInhdynamics that are supported by the differential expression of endogenous ion handling mechanisms. Our findings therefore establish an effective optical strategy for revealing novel aspects of inhibitory reversal potentials and thereby expand the repertoire of optogenetics

sUPRa is a dual-color reporter for unbiased quantification of the unfolded protein response with cellular resolution

The unfolded protein response (UPR) maintains proteostasis upon endoplasmic reticulum (ER) stress, and is initiated by a range of physiological and pathological processes. While there have been advances in developing fluorescent reporters for monitoring individual signaling pathways of the UPR, this approach may not capture a cell’s overall UPR activity. Here we describe a novel sensor of UPR activity, sUPRa, which is designed to report the global UPR. sUPRa displays excellent response characteristics, outperforms reporters of individual UPR pathways in terms of sensitivity and kinetics, and responds to a range of different ER stress stimuli. Furthermore, sUPRa’s dual promoter and fluorescent protein design ensures that both UPR-active and inactive cells are detected, and controls for reporter copy number. Using sUPRa, we reveal UPR activation in layer 2/3 pyramidal neurons of mouse cerebral cortex following a period of sleep deprivation. sUPRa affords new opportunities for quantifying physiological UPR activity with cellular resolution

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Somnotate: a probabilistic sleep stage classifier for studying vigilance state transitions

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"—a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution