Patch-seq: Past, Present, and Future

Sample collection protocol for single-cell RNA sequencing of functionally identified neuronal populations in vivo

Here, we present a sample collection protocol for single-cell RNA sequencing of functionally identified neuronal populations in vivo with a virally delivered activity-dependent labeling tool (CaMPARI2). We describe steps for photoconversion in mice during the onset of computationally relevant events in a virtual reality environment, followed by removal and dissociation of the photo-labeled tissue, and separation of differentially labeled groups with fluorescence-activated cell sorting (FACS). We then detail procedures for characterizing and examining functionally relevant groups using standard bioinformatic techniques. For complete details on the use and execution of this protocol, please refer to O'Toole et al.1.

Integrating physiological and transcriptomic analyses at the single-neuron level

Neurons generate various spike patterns to execute different functions. Understanding how these physiological neuronal spike patterns are related to their molecular characteristics is a long-standing issue in neuroscience. Herein, we review the results of recent studies that have addressed this issue by integrating physiological and transcriptomic techniques. A sequence of experiments, including in vivo recording and/or labeling, brain tissue slicing, cell collection, and transcriptomic analysis, have identified the gene expression profiles of brain neurons at the single-cell level, with activity patterns recorded in living animals. Although these techniques are still in the early stages, this methodological idea is principally applicable to various brain regions and neuronal activity patterns. Accumulating evidence will contribute to a deeper understanding of neuronal characteristics by integrating insights from molecules to cells, circuits, and behaviors.

A phosphate transporter in VIPergic neurons of the suprachiasmatic nucleus gates locomotor activity during the light/dark transition in mice

The suprachiasmatic nucleus (SCN) encodes time of day through changes in daily firing; however, the molecular mechanisms by which the SCN times behavior are not fully understood. To identify factors that could encode day/night differences in activity, we combine patch-clamp recordings and single-cell sequencing of individual SCN neurons in mice. We identify PiT2, a phosphate transporter, as being upregulated in a population of Vip+Nms+ SCN neurons at night. Although nocturnal and typically showing a peak of activity at lights off, mice lacking PiT2 (PiT2-/-) do not reach the activity level seen in wild-type mice during the light/dark transition. PiT2 loss leads to increased SCN neuronal firing and broad changes in SCN protein phosphorylation. PiT2-/- mice display a deficit in seasonal entrainment when moving from a simulated short summer to longer winter nights. This suggests that PiT2 is responsible for timing activity and is a driver of SCN plasticity allowing seasonal entrainment.

Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma

Prior studies have described the complex interplay that exists between glioma cells and neurons, however, the electrophysiological properties endogenous to tumor cells remain obscure. To address this, we employed Patch-sequencing on human glioma specimens and found that one third of patched cells in IDH mutant (IDH mut ) tumors demonstrate properties of both neurons and glia by firing single, short action potentials. To define these hybrid cells (HCs) and discern if they are tumor in origin, we developed a computational tool, Single Cell Rule Association Mining (SCRAM), to annotate each cell individually. SCRAM revealed that HCs represent tumor and non-tumor cells that feature GABAergic neuron and oligodendrocyte precursor cell signatures. These studies are the first to characterize the combined electrophysiological and molecular properties of human glioma cells and describe a new cell type in human glioma with unique electrophysiological and transcriptomic properties that are likely also present in the non-tumor mammalian brain.

A deep-learning strategy to identify cell types across species from high-density extracellular recordings

High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but don't reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifier's predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.

Molecular and cellular mechanisms of selective vulnerability in neurodegenerative diseases

The selective vulnerability of specific neuronal subtypes is a hallmark of neurodegenerative diseases. In this Review, I summarize our current understanding of the brain regions and cell types that are selectively vulnerable in different neurodegenerative diseases and describe the proposed underlying cell-autonomous and non-cell-autonomous mechanisms. I highlight how recent methodological innovations - including single-cell transcriptomics, CRISPR-based screens and human cell-based models of disease - are enabling new breakthroughs in our understanding of selective vulnerability. An understanding of the molecular mechanisms that determine selective vulnerability and resilience would shed light on the key processes that drive neurodegeneration and point to potential therapeutic strategies to protect vulnerable cell populations.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

Tuning neural circuits and behaviors by microglia in the adult brain

Microglia are the primary immune cells of the CNS, contributing to both inflammatory damage and tissue repair in neurological disorder. In addition, emerging evidence highlights the role of homeostatic microglia in regulating neuronal activity, interacting with synapses, tuning neural circuits, and modulating behaviors. Herein, we review how microglia sense and regulate neuronal activity through synaptic interactions, thereby directly engaging with neural networks and behaviors. We discuss current studies utilizing microglial optogenetic and chemogenetic approaches to modulate adult neural circuits. These manipulations of microglia across different CNS regions lead to diverse behavioral consequences. We propose that spatial heterogeneity of microglia-neuron interaction lays the groundwork for understanding diverse functions of microglia in neural circuits and behaviors.

A perspective on translating genomic discoveries into targets for brain-machine interface and deep brain stimulation devices

Mental illnesses have a huge impact on individuals, families, and society, so there is a growing need for more efficient treatments. In this context, brain-computer interface (BCI) technology has the potential to revolutionize the options for neuropsychiatric therapies. However, the development of BCI-based therapies faces enormous challenges, such as power dissipation constraints, lack of credible feedback mechanisms, uncertainty of which brain areas and frequencies to target, and even which patients to treat. Some of these setbacks are due to the large gap in our understanding of brain function. In recent years, large-scale genomic analyses uncovered an unprecedented amount of information regarding the biology of the altered brain function observed across the psychopathology spectrum. We believe findings from genetic studies can be useful to refine BCI technology to develop novel treatment options for mental illnesses. Here, we assess the latest advancements in both fields, the possibilities that can be generated from their intersection, and the challenges that these research areas will need to address to ensure that translational efforts can lead to effective and reliable interventions. Specifically, starting from highlighting the overlap between mechanisms uncovered by large-scale genetic studies and the current targets of deep brain stimulation treatments, we describe the steps that could help to translate genomic discoveries into BCI targets. Because these two research areas have not been previously presented together, the present article can provide a novel perspective for scientists with different research backgrounds. This article is categorized under: Neurological Diseases > Genetics/Genomics/Epigenetics Neurological Diseases > Biomedical Engineering.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states

The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multimodal single-cell datasets enables the investigation of cell types and states heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for the exploration of excitability states of neurons based on their Action Potential (AP) waveforms. The NSS method describes the AP waveform based on a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach on two datasets of murine cortical neurons, focusing it on GABAergic neurons. The validation process involves a combination of NSS-based clustering analysis, features exploration, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. Results show that the NSS-based analysis captures neuronal excitability states that possess biological relevance independently of cell subtype. In particular, Neuronal Spike Shapes (NSS) captures, among others, a well-characterized fast-spiking excitability state, supported by both electrophysiological and transcriptomic validation. Gene Ontology Enrichment Analysis reveals voltage-gated potassium (K+) channels as specific markers of the identified NSS partitions. This finding strongly corroborates the biological relevance of NSS partitions as excitability states, as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, being directly implicated in the regulation of neuronal excitability.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Patch-seq: Advances and Biological Applications

Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research.

Activation of Kv7 channels normalizes hyperactivity of the VTA-NAcLat circuit and attenuates methamphetamine-induced conditioned place preference and sensitization in mice

The brain circuit projecting from the ventral tegmental area (VTA) to the nucleus accumbens lateral shell (NAcLat) has a key role in methamphetamine (MA) addiction. As different dopamine (DA) neuron subpopulations in the VTA participate in different neuronal circuits, it is a challenge to isolate these DA neuron subtypes. Using retrograde tracing and Patch-seq, we isolated DA neurons in the VTA-NAcLat circuit in MA-treated mice and performed gene expression profiling. Among the differentially expressed genes, KCNQ genes were dramatically downregulated. KCNQ genes encode Kv7 channel proteins, which modulate neuronal excitability. Injection of both the Kv7.2/3 agonist ICA069673 and the Kv7.4 agonist fasudil into the VTA attenuated MA-induced conditioned place preference and locomotor sensitization and decreased neuronal excitability. Increasing Kv7.2/3 activity decreased neural oscillations, synaptic plasticity and DA release in the VTA-NacLat circuit in MA-treated mice. Furthermore, overexpression of only Kv7.3 channels in the VTA-NacLat circuit was sufficient to attenuate MA-induced reward behavior and decrease VTA neuron excitability. Activation of Kv7 channels in the VTA may become a novel treatment strategy for MA abuse.

MANGEM: A web app for multimodal analysis of neuronal gene expression, electrophysiology, and morphology

Single-cell techniques like Patch-seq have enabled the acquisition of multimodal data from individual neuronal cells, offering systematic insights into neuronal functions. However, these data can be heterogeneous and noisy. To address this, machine learning methods have been used to align cells from different modalities onto a low-dimensional latent space, revealing multimodal cell clusters. The use of those methods can be challenging without computational expertise or suitable computing infrastructure for computationally expensive methods. To address this, we developed a cloud-based web application, MANGEM (multimodal analysis of neuronal gene expression, electrophysiology, and morphology). MANGEM provides a step-by-step accessible and user-friendly interface to machine learning alignment methods of neuronal multimodal data. It can run asynchronously for large-scale data alignment, provide users with various downstream analyses of aligned cells, and visualize the analytic results. We demonstrated the usage of MANGEM by aligning multimodal data of neuronal cells in the mouse visual cortex.

Heralding a new era of oxytocinergic research: New tools, new problems?

According to classic neuroendocrinology, hypothalamic oxytocin cells can be categorized into parvo- and magnocellular neurons. However, research in the last decade provided ample evidence that this black-and-white model of oxytocin neurons is most likely oversimplified. Novel genetic, functional and morphological studies indicate that oxytocin neurons might be organized in functional modules and suggest the existence of five or more distinct oxytocinergic subpopulations. However, many of these novel, automated high-throughput techniques might be inherently biased and interpretation of acquired data needs to be approached with caution to enable drawing sound and reliable conclusions. In addition, the recent finding that astrocytes in various brain regions express functional oxytocin receptors represents a paradigm shift and challenges the view that oxytocin primarily acts as a direct peptidergic neurotransmitter. This review highlights the latest technical advances in oxytocinergic research, puts recent studies on the oxytocin system into context and formulates various provocative ideas based on novel findings that challenges various prevailing hypotheses and dogmas about oxytocinergic modulation.

The organization of spinal neurons: Insights from single cell sequencing

To understand how the spinal cord enacts complex sensorimotor functions, researchers have studied, classified, and functionally probed it's many neuronal populations for over a century. Recent developments in single-cell RNA-sequencing can characterize the gene expression signatures of the entire set of spinal neuron types and can simultaneously provide an unbiased view of their relationships to each other. This approach has revealed that the location of neurons predicts transcriptomic variability, as dorsal spinal neurons become highly distinct over development as ventral spinal neurons become less so. Temporal specification is also a major source of gene expression variation, subdividing many of the canonical embryonic lineage domains. Together, birthdate and cell body location are fundamental organizing features of spinal neuron diversity.

Retinal ganglion cell repopulation for vision restoration in optic neuropathy: a roadmap from the RReSTORe Consortium

Retinal ganglion cell (RGC) death in glaucoma and other optic neuropathies results in irreversible vision loss due to the mammalian central nervous system's limited regenerative capacity. RGC repopulation is a promising therapeutic approach to reverse vision loss from optic neuropathies if the newly introduced neurons can reestablish functional retinal and thalamic circuits. In theory, RGCs might be repopulated through the transplantation of stem cell-derived neurons or via the induction of endogenous transdifferentiation. The RGC Repopulation, Stem Cell Transplantation, and Optic Nerve Regeneration (RReSTORe) Consortium was established to address the challenges associated with the therapeutic repair of the visual pathway in optic neuropathy. In 2022, the RReSTORe Consortium initiated ongoing international collaborative discussions to advance the RGC repopulation field and has identified five critical areas of focus: (1) RGC development and differentiation, (2) Transplantation methods and models, (3) RGC survival, maturation, and host interactions, (4) Inner retinal wiring, and (5) Eye-to-brain connectivity. Here, we discuss the most pertinent questions and challenges that exist on the path to clinical translation and suggest experimental directions to propel this work going forward. Using these five subtopic discussion groups (SDGs) as a framework, we suggest multidisciplinary approaches to restore the diseased visual pathway by leveraging groundbreaking insights from developmental neuroscience, stem cell biology, molecular biology, optical imaging, animal models of optic neuropathy, immunology & immunotolerance, neuropathology & neuroprotection, materials science & biomedical engineering, and regenerative neuroscience. While significant hurdles remain, the RReSTORe Consortium's efforts provide a comprehensive roadmap for advancing the RGC repopulation field and hold potential for transformative progress in restoring vision in patients suffering from optic neuropathies.

Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection

Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including identifying spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse patch-seq datasets

Microglia are cells with diverse roles, including the regulation of neuronal excitability. We leveraged Patch-seq to assess the presence and effects of microglia in the local microenvironment of recorded neurons. We first quantified the amounts of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons, observing extensive contamination. Variation in microglial contamination was explained foremost by donor identity, particularly in human samples, and additionally by neuronal cell type identity in mice. Gene set enrichment analysis suggests that microglial contamination is reflective of activated microglia, and that these transcriptional signatures are distinct from those captured via single-nucleus RNA-seq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results generalize beyond Patch-seq to suggest that activated microglia may be widely present across brain slice preparations and contribute to neuron- and donor-related electrophysiological variability in vitro.

Compound models and Pearson residuals for normalization of single-cell RNA-seq data without UMIs

Before downstream analysis can reveal biological signals in single-cell RNA sequencing data, normalization and variance stabilization are required to remove technical noise. Recently, Pearson residuals based on negative binomial models have been suggested as an efficient normalization approach. These methods were developed for UMI-based sequencing protocols, where unique molecular identifiers (UMIs) help to remove PCR amplification noise by keeping track of the original molecules. In contrast, full-length protocols such as Smart-seq2 lack UMIs and retain amplification noise, making negative binomial models inapplicable. Here, we extend Pearson residuals to such read count data by modeling them as a compound process: we assume that the captured RNA molecules follow the negative binomial distribution, but are replicated according to an amplification distribution. Based on this model, we introduce compound Pearson residuals and show that they can be analytically obtained without explicit knowledge of the amplification distribution. Further, we demonstrate that compound Pearson residuals lead to a biologically meaningful gene selection and low-dimensional embeddings of complex Smart-seq2 datasets. Finally, we empirically study amplification distributions across several sequencing protocols, and suggest that they can be described by a broken power law. We show that the resulting compound distribution captures overdispersion and zero-inflation patterns characteristic of read count data. In summary, compound Pearson residuals provide an efficient and effective way to normalize read count data based on simple mechanistic assumptions.

Toward the Next Generation of Neural Iontronic Interfaces

Neural interfaces are evolving at a rapid pace owing to advances in material science and fabrication, reduced cost of scalable complementary metal oxide semiconductor (CMOS) technologies, and highly interdisciplinary teams of researchers and engineers that span a large range from basic to applied and clinical sciences. This study outlines currently established technologies, defined as instruments and biological study systems that are routinely used in neuroscientific research. After identifying the shortcomings of current technologies, such as a lack of biocompatibility, topological optimization, low bandwidth, and lack of transparency, it maps out promising directions along which progress should be made to achieve the next generation of symbiotic and intelligent neural interfaces. Lastly, it proposes novel applications that can be achieved by these developments, ranging from the understanding and reproduction of synaptic learning to live-long multimodal measurements to monitor and treat various neuronal disorders.

Differential expression of GABAA receptor subunits δ and α6 mediates tonic inhibition in parvalbumin and somatostatin interneurons in the mouse hippocampus

Inhibitory γ-aminobutyric acid (GABA)-ergic interneurons mediate inhibition in neuronal circuitry and support normal brain function. Consequently, dysregulation of inhibition is implicated in various brain disorders. Parvalbumin (PV) and somatostatin (SST) interneurons, the two major types of GABAergic inhibitory interneurons in the hippocampus, exhibit distinct morpho-physiological properties and coordinate information processing and memory formation. However, the molecular mechanisms underlying the specialized properties of PV and SST interneurons remain unclear. This study aimed to compare the transcriptomic differences between these two classes of interneurons in the hippocampus using the ribosome tagging approach. The results revealed distinct expressions of genes such as voltage-gated ion channels and GABAA receptor subunits between PV and SST interneurons. Gabrd and Gabra6 were identified as contributors to the contrasting tonic GABAergic inhibition observed in PV and SST interneurons. Moreover, some of the differentially expressed genes were associated with schizophrenia and epilepsy. In conclusion, our results provide molecular insights into the distinct roles of PV and SST interneurons in health and disease.

CAJAL enables analysis and integration of single-cell morphological data using metric geometry

High-resolution imaging has revolutionized the study of single cells in their spatial context. However, summarizing the great diversity of complex cell shapes found in tissues and inferring associations with other single-cell data remains a challenge. Here, we present CAJAL, a general computational framework for the analysis and integration of single-cell morphological data. By building upon metric geometry, CAJAL infers cell morphology latent spaces where distances between points indicate the amount of physical deformation required to change the morphology of one cell into that of another. We show that cell morphology spaces facilitate the integration of single-cell morphological data across technologies and the inference of relations with other data, such as single-cell transcriptomic data. We demonstrate the utility of CAJAL with several morphological datasets of neurons and glia and identify genes associated with neuronal plasticity in C. elegans. Our approach provides an effective strategy for integrating cell morphology data into single-cell omics analyses.

Heterogeneous organization of Locus coeruleus: An intrinsic mechanism for functional complexity

Locus coeruleus (LC) is a small nucleus located deep in the brainstem that contains the majority of central noradrenergic neurons, which provide the primary source of noradrenaline (NA) throughout the entire central nervous system (CNS).The release of neurotransmitter NA is considered to modulate arousal, sensory processing, attention, aversive and adaptive stress responses as well as high-order cognitive function and memory, with the highly ramified axonal arborizations of LC-NA neurons sending wide projections to the targeted brain areas. For over 30 years, LC was thought to be a homogeneous nucleus in structure and function due to the widespread uniform release of NA by LC-NA neurons and simultaneous action in several CNS regions, such as the prefrontal cortex, hippocampus, cerebellum, and spinal cord. However, recent advances in neuroscience tools have revealed that LC is probably not so homogeneous as we previous thought and exhibits heterogeneity in various aspects. Accumulating studies have shown that the functional complexity of LC may be attributed to its heterogeneity in developmental origin, projection patterns, topography distribution, morphology and molecular organization, electrophysiological properties and sex differences. This review will highlight the heterogeneity of LC and its critical role in modulating diverse behavioral outcomes.

Current Best Practices for Analysis of Dendritic Spine Morphology and Number in Neurodevelopmental Disorder Research

Quantitative methods for assessing neural anatomy have rapidly evolved in neuroscience and provide important insights into brain health and function. However, as new techniques develop, it is not always clear when and how each may be used to answer specific scientific questions posed. Dendritic spines, which are often indicative of synapse formation and neural plasticity, have been implicated across many brain regions in neurodevelopmental disorders as a marker for neural changes reflecting neural dysfunction or alterations. In this Perspective we highlight several techniques for staining, imaging, and quantifying dendritic spines as well as provide a framework for avoiding potential issues related to pseudoreplication. This framework illustrates how others may apply the most rigorous approaches. We consider the cost-benefit analysis of the varied techniques, recognizing that the most sophisticated equipment may not always be necessary for answering some research questions. Together, we hope this piece will help researchers determine the best strategy toward using the ever-growing number of techniques available to determine neural changes underlying dendritic spine morphology in health and neurodevelopmental disorders.

Photoselective sequencing: microscopically guided genomic measurements with subcellular resolution

In biological systems, spatial organization and function are interconnected. Here we present photoselective sequencing, a new method for genomic and epigenomic profiling within morphologically distinct regions. Starting with an intact biological specimen, photoselective sequencing uses targeted illumination to selectively unblock a photocaged fragment library, restricting the sequencing-based readout to microscopically identified spatial regions. We validate photoselective sequencing by measuring the chromatin accessibility profiles of fluorescently labeled cell types within the mouse brain and comparing with published data. Furthermore, by combining photoselective sequencing with a computational strategy for decomposing bulk accessibility profiles, we find that the oligodendrocyte-lineage-cell population is relatively enriched for oligodendrocyte-progenitor cells in the cortex versus the corpus callosum. Finally, we leverage photoselective sequencing at the subcellular scale to identify features of chromatin that are correlated with positioning at the nuclear periphery. These results collectively demonstrate that photoselective sequencing is a flexible and generalizable platform for exploring the interplay of spatial structures with genomic and epigenomic properties.

Biosensors integrated 3D organoid/organ-on-a-chip system: A real-time biomechanical, biophysical, and biochemical monitoring and characterization

As a full-fidelity simulation of human cells, tissues, organs, and even systems at the microscopic scale, Organ-on-a-Chip (OOC) has significant ethical advantages and development potential compared to animal experiments. The need for the design of new drug high-throughput screening platforms and the mechanistic study of human tissues/organs under pathological conditions, the evolving advances in 3D cell biology and engineering, etc., have promoted the updating of technologies in this field, such as the iteration of chip materials and 3D printing, which in turn facilitate the connection of complex multi-organs-on-chips for simulation and the further development of technology-composite new drug high-throughput screening platforms. As the most critical part of organ-on-a-chip design and practical application, verifying the success of organ model modeling, i.e., evaluating various biochemical and physical parameters in OOC devices, is crucial. Therefore, this paper provides a logical and comprehensive review and discussion of the advances in organ-on-a-chip detection and evaluation technologies from a broad perspective, covering the directions of tissue engineering scaffolds, microenvironment, single/multi-organ function, and stimulus-based evaluation, and provides a more comprehensive review of the progress in the significant organ-on-a-chip research areas in the physiological state.

Spatial distribution of heterogeneity as a modulator of collective dynamics in pancreatic beta-cell networks and beyond

We study the impact of spatial distribution of heterogeneity on collective dynamics in gap-junction coupled beta-cell networks comprised on cells from two populations that differ in their intrinsic excitability. Initially, these populations are uniformly and randomly distributed throughout the networks. We develop and apply an iterative algorithm for perturbing the arrangement of the network such that cells from the same population are increasingly likely to be adjacent to one another. We find that the global input strength, or network drive, necessary to transition the network from a state of quiescence to a state of synchronised and oscillatory activity decreases as network sortedness increases. Moreover, for weak coupling, we find that regimes of partial synchronisation and wave propagation arise, which depend both on network drive and network sortedness. We then demonstrate the utility of this algorithm for studying the distribution of heterogeneity in general networks, for which we use Watts-Strogatz networks as a case study. This work highlights the importance of heterogeneity in node dynamics in establishing collective rhythms in complex, excitable networks and has implications for a wide range of real-world systems that exhibit such heterogeneity.

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types ¹ . Neural cell types have previously been defined by morphology ^{2, 3} , electrophysiology ^{4, 5} , transcriptomic expression ^6-8 , connectivity ^9-13 , or even a combination of such modalities ^14-16 . More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells ^17-20 . Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex ²¹ . It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type ^{22, 23} known to be Somatostatin positive (Sst+) ^{24, 25} , were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

Pimozide Increases a Delayed Rectifier K+ Conductance in Chicken Embryo Vestibular Hair Cells

Pimozide is a conventional antipsychotic drug largely used in the therapy for schizophrenia and Tourette's syndrome. Pimozide is assumed to inhibit synaptic transmission at the CNS by acting as a dopaminergic D₂ receptor antagonist. Moreover, pimozide has been shown to block voltage-gated Ca²⁺ and K⁺ channels in different cells. Despite its widespread clinical use, pimozide can cause several adverse effects, including extrapyramidal symptoms and cardiac arrhythmias. Dizziness and loss of balance are among the most common side effects of pimozide. By using the patch-clamp whole-cell technique, we investigated the effect of pimozide [3 μM] on K⁺ channels expressed by chicken embryo vestibular type-II hair cells. We found that pimozide slightly blocks a transient outward rectifying A-type K⁺ current but substantially increases a delayed outward rectifying K⁺ current. The net result was a significant hyperpolarization of type-II hair cells at rest and a strong reduction of their response to depolarizing stimuli. Our findings are consistent with an inhibitory effect of pimozide on the afferent synaptic transmission by type-II hair cells. Moreover, they provide an additional key to understanding the beneficial/collateral pharmacological effects of pimozide. The finding that pimozide can act as a K⁺ channel opener provides a new perspective for the use of this drug.

Isolation and transfection of myenteric neurons from mice for patch-clamp applications

The enteric nervous system (ENS) is a complex neuronal network organized in ganglionated plexuses that extend along the entire length of the gastrointestinal tract. Largely independent of the central nervous system, the ENS coordinates motility and peristalsis of the digestive tract, regulates secretion and absorption, and is involved in immunological processes. Electrophysiological methods such as the patch-clamp technique are particularly suitable to study the function of neurons as well as the biophysical parameters of the underlying ion channels under both physiological and pathophysiological conditions. However, application of the patch-clamp method to ENS neurons remained difficult because they are embedded in substantial tissue layers that limit access to and targeted manipulation of these cells. Here, we present a robust step-by-step protocol that involves isolation of ENS neurons from adult mice, culturing of the cells, their transfection with plasmid DNA, and subsequent electrophysiological characterization of individual neurons in current-clamp and voltage-clamp recordings. With this protocol, ENS neurons can be prepared, transfected, and electrophysiologically characterized within 72 h. Using isolated ENS neurons, we demonstrate the feasibility of the approach by functional overexpression of recombinant voltage-gated Na_V1.9 mutant channels associated with hereditary sensory and autonomic neuropathy type 7 (HSAN-7), a disorder characterized by congenital analgesia and severe constipation that can require parenteral nutrition. Although our focus is on the electrophysiological evaluation of isolated ENS neurons, the presented methodology is also useful to analyze molecules other than sodium channels or to apply alternative downstream assays including calcium imaging, proteomic and nucleic acid approaches, or immunochemistry.

Purkinje Cell Patterning-Insights from Single-Cell Sequencing

Despite their homogeneous appearance, Purkinje cells are remarkably diverse with respect to their molecular phenotypes, physiological properties, afferent and efferent connectivity, as well as their vulnerability to insults. Heterogeneity in Purkinje cells arises early in development, with molecularly distinct embryonic cell clusters present soon after Purkinje cell specification. Traditional methods have characterized cerebellar development and cell types, including Purkinje cell subtypes, based on knowledge of selected markers. However, recent single-cell RNA sequencing studies provide vastly increased resolution of the whole cerebellar transcriptome. Here we draw together the results of multiple single-cell transcriptomic studies in developing and adult cerebellum in both mouse and human. We describe how this detailed transcriptomic data has increased our understanding of the intricate development and function of Purkinje cells and provides first clues into features specific to human cerebellar development.

Linking transcriptomes with morphological and functional phenotypes in mammalian retinal ganglion cells

Retinal ganglion cells (RGCs) are the brain's gateway to the visual world. They can be classified into different types on the basis of their electrophysiological, transcriptomic, or morphological characteristics. Here, we characterize the transcriptomic, morphological, and functional features of 472 high-quality RGCs using Patch sequencing (Patch-seq), providing functional and morphological annotation of many transcriptomic-defined cell types of a previously established RGC atlas. We show a convergence of different modalities in defining the RGC identity and reveal the degree of correspondence for well-characterized cell types across multimodal data. Moreover, we complement some RGC types with detailed morphological and functional properties. We also identify differentially expressed genes among ON, OFF, and ON-OFF RGCs such as Vat1l, Slitrk6, and Lmo7, providing candidate marker genes for functional studies. Our research suggests that the molecularly distinct clusters may also differ in their roles of encoding visual information.

The contribution of ion channels to shaping macrophage behaviour

The expanding roles of macrophages in physiological and pathophysiological mechanisms now include normal tissue homeostasis, tissue repair and regeneration, including neuronal tissue; initiation, progression, and resolution of the inflammatory response and a diverse array of anti-microbial activities. Two hallmarks of macrophage activity which appear to be fundamental to their diverse cellular functionalities are cellular plasticity and phenotypic heterogeneity. Macrophage plasticity allows these cells to take on a broad spectrum of differing cellular phenotypes in response to local and possibly previous encountered environmental signals. Cellular plasticity also contributes to tissue- and stimulus-dependent macrophage heterogeneity, which manifests itself as different macrophage phenotypes being found at different tissue locations and/or after different cell stimuli. Together, plasticity and heterogeneity align macrophage phenotypes to their required local cellular functions and prevent inappropriate activation of the cell, which could lead to pathology. To execute the appropriate function, which must be regulated at the qualitative, quantitative, spatial and temporal levels, macrophages constantly monitor intracellular and extracellular parameters to initiate and control the appropriate cell signaling cascades. The sensors and signaling mechanisms which control macrophages are the focus of a considerable amount of research. Ion channels regulate the flow of ions between cellular membranes and are critical to cell signaling mechanisms in a variety of cellular functions. It is therefore surprising that the role of ion channels in the macrophage biology has been relatively overlooked. In this review we provide a summary of ion channel research in macrophages. We begin by giving a narrative-based explanation of the membrane potential and its importance in cell biology. We then report on research implicating different ion channel families in macrophage functions. Finally, we highlight some areas of ion channel research in macrophages which need to be addressed, future possible developments in this field and therapeutic potential.

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

Advancements in the Quest to Map, Monitor, and Manipulate Neural Circuitry

Neural circuits and the cells that comprise them represent the functional units of the brain. Circuits relay and process sensory information, maintain homeostasis, drive behaviors, and facilitate cognitive functions such as learning and memory. Creating a functionally-precise map of the mammalian brain requires anatomically tracing neural circuits, monitoring their activity patterns, and manipulating their activity to infer function. Advancements in cell-type-specific genetic tools allow interrogation of neural circuits with increased precision. This review provides a broad overview of recombination-based and activity-driven genetic targeting approaches, contemporary viral tracing strategies, electrophysiological recording methods, newly developed calcium, and voltage indicators, and neurotransmitter/neuropeptide biosensors currently being used to investigate circuit architecture and function. Finally, it discusses methods for acute or chronic manipulation of neural activity, including genetically-targeted cellular ablation, optogenetics, chemogenetics, and over-expression of ion channels. With this ever-evolving genetic toolbox, scientists are continuing to probe neural circuits with increasing resolution, elucidating the structure and function of the incredibly complex mammalian brain.

A Molecular Landscape of Mouse Hippocampal Neuromodulation

Adaptive neuronal circuit function requires a continual adjustment of synaptic network parameters known as “neuromodulation.” This process is now understood to be based primarily on the binding of myriad secreted “modulatory” ligands such as dopamine, serotonin and the neuropeptides to G protein-coupled receptors (GPCRs) that, in turn, regulate the function of the ion channels that establish synaptic weights and membrane excitability. Many of the basic molecular mechanisms of neuromodulation are now known, but the organization of neuromodulation at a network level is still an enigma. New single-cell RNA sequencing data and transcriptomic neurotaxonomies now offer bright new lights to shine on this critical “dark matter” of neuroscience. Here we leverage these advances to explore the cell-type-specific expression of genes encoding GPCRs, modulatory ligands, ion channels and intervening signal transduction molecules in mouse hippocampus area CA1, with the goal of revealing broad outlines of this well-studied brain structure’s neuromodulatory network architecture.

Identification of TPBG-Expressing Amacrine Cells in DAT-tdTomato Mouse

Purpose

Neurons are the bricks of the neuronal system and experimental access to certain neuron subtypes will be of great help to decipher neuronal circuits. Here, we identified trophoblast glycoprotein (TPBG)-expressing GABAergic amacrine cells (ACs) that were selectively labeled in DAT-tdTomato transgenic mice.

Methods

Retina and brain sections were prepared for immunostaining with antibodies against various biomarkers. Patch-sequencing was performed to obtain the transcriptomes of tdTomato-positive cells in DAT-tdTomato mice. Whole-cell recordings were conducted to identify responses to light stimulation.

Results

Tyrosine hydroxylase immunoreactive cells were colocalized with tdTomato-positive cells in substantia nigra pars compacta, but not in the retina. Transcriptomes collected from tdTomato-positive cells in retinas via Patch-sequencing exhibited the expression of marker genes of ACs (Pax6 and Slc32a1) and marker genes of GABAergic neurons (Gad1, Gad2, and Slc6a1). Immunostaining with antibodies against relevant proteins (GAD67, GAD65, and GABA) also confirmed transcriptomic results. Furthermore, tdTomato-positive cells in retinas selectively expressed Tpbg, a marker gene for distinct clusters molecularly defined, which was proved with TPBG immunoreactivity in fluorescently labeled cells. Finally, tdTomato-positive cells recorded showed ON-OFF responses to light stimulation.

Conclusions

Ectopic expression occurs in the retina but not in the substantia nigra pars compacta in the DAT-tdTomato mouse, and fluorescently labeled cells in the retina are TPBG-expressing GABAergic ACs. This type of transgenic mice has been proved as an ideal tool to achieve efficient labeling of a distinct subset of ACs that selectively express Tpbg.

Transcriptomes of electrophysiologically recorded Dbx1-derived respiratory neurons of the preBötzinger complex in neonatal mice

Breathing depends on interneurons in the preBötzinger complex (preBötC) derived from Dbx1-expressing precursors. Here we investigate whether rhythm- and pattern-generating functions reside in discrete classes of Dbx1 preBötC neurons. In a slice model of breathing with ~ 5 s cycle period, putatively rhythmogenic Type-1 Dbx1 preBötC neurons activate 100-300 ms prior to Type-2 neurons, putatively specialized for output pattern, and 300-500 ms prior to the inspiratory motor output. We sequenced Type-1 and Type-2 transcriptomes and identified differential expression of 123 genes including ionotropic receptors (Gria3, Gabra1) that may explain their preinspiratory activation profiles and Ca2+ signaling (Cracr2a, Sgk1) involved in inspiratory and sigh bursts. Surprisingly, neuropeptide receptors that influence breathing (e.g., µ-opioid and bombesin-like peptide receptors) were only sparsely expressed, which suggests that cognate peptides and opioid drugs exert their profound effects on a small fraction of the preBötC core. These data in the public domain help explain the neural origins of breathing.

Harnessing the Power of Stem Cell Models to Study Shared Genetic Variants in Congenital Heart Diseases and Neurodevelopmental Disorders

Advances in human pluripotent stem cell (hPSC) technology allow one to deconstruct the human body into specific disease-relevant cell types or create functional units representing various organs. hPSC-based models present a unique opportunity for the study of co-occurring disorders where “cause and effect” can be addressed. Poor neurodevelopmental outcomes have been reported in children with congenital heart diseases (CHD). Intuitively, abnormal cardiac function or surgical intervention may stunt the developing brain, leading to neurodevelopmental disorders (NDD). However, recent work has uncovered several genetic variants within genes associated with the development of both the heart and brain that could also explain this co-occurrence. Given the scalability of hPSCs, straightforward genetic modification, and established differentiation strategies, it is now possible to investigate both CHD and NDD as independent events. We will first overview the potential for shared genetics in both heart and brain development. We will then summarize methods to differentiate both cardiac & neural cells and organoids from hPSCs that represent the developmental process of the heart and forebrain. Finally, we will highlight strategies to rapidly screen several genetic variants together to uncover potential phenotypes and how therapeutic advances could be achieved by hPSC-based models.

Towards Tabula Gallus

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

A single-cell guide to retinal development: Cell fate decisions of multipotent retinal progenitors in scRNA-seq

Recent advances in high throughput single-cell RNA sequencing (scRNA-seq) technology have enabled the simultaneous transcriptomic profiling of thousands of individual cells in a single experiment. To investigate the intrinsic process of retinal development, researchers have leveraged this technology to quantify gene expression in retinal cells across development, in multiple species, and from numerous important models of human disease. In this review, we summarize recent applications of scRNA-seq and discuss how these datasets have complemented and advanced our understanding of retinal progenitor cell competence, cell fate specification, and differentiation. Finally, we also highlight the outstanding questions in the field that advances in single-cell data generation and analysis will soon be able to answer.

SCN2A contributes to oligodendroglia excitability and development in the mammalian brain

Spiking immature oligodendrocytes (OLs), referred to as spiking OLs, express voltage-activated Na⁺ channels (Na_v) and K⁺ (K_v) channels, endowing a subpopulation of OLs with the ability to generate Na_v-driven spikes. In this study, we investigate the molecular profile of spiking OLs, using single-cell transcriptomics paired with whole-cell patch-clamp recordings. SCN2A, which encodes the channel Na_v1.2, is specifically expressed in spiking OLs in the brainstem and cerebellum, both in mice and in Olive baboons. Spiking OLs express lineage markers of OL progenitor cells (OPCs) and pre-myelinating OLs, indicating they belong to a transitional stage during differentiation. Deletion of SCN2A reduces the Na_v current-expressing OL population and eliminates spiking OLs, indicating that SCN2A is essential for spiking in OLs. Deletion of SCN2A does not impact global OL proliferation but disrupts maturation of a subpopulation of OLs, suggesting that Na_v1.2 is involved in heterogeneity in OL lineage cells and their development.

In Vivo Whole-Cell Patch-Clamp Methods: Recent Technical Progress and Future Perspectives

Brain functions are fundamental for the survival of organisms, and they are supported by neural circuits consisting of a variety of neurons. To investigate the function of neurons at the single-cell level, researchers often use whole-cell patch-clamp recording techniques. These techniques enable us to record membrane potentials (including action potentials) of individual neurons of not only anesthetized but also actively behaving animals. This whole-cell recording method enables us to reveal how neuronal activities support brain function at the single-cell level. In this review, we introduce previous studies using in vivo patch-clamp recording techniques and recent findings primarily regarding neuronal activities in the hippocampus for behavioral function. We further discuss how we can bridge the gap between electrophysiology and biochemistry.