ABSTRACT
Expansion microscopy and light sheet imaging enable fine-scale resolution of intracellular features that comprise neural circuits. Most current techniques visualize sparsely distributed features across whole brains or densely distributed features within individual brain regions. Here, we visualize dense distributions of immunolabeled proteins across early visual cortical areas in adult macaque monkeys. This process may be combined with multiphoton or magnetic resonance imaging to produce multimodal atlases in large, gyrencephalic brains.
ABSTRACT
Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit.
Subject(s)
Neocortex , Animals , Humans , Mice , Axons/metabolism , Interneurons/metabolism , Neocortex/cytology , Neocortex/metabolism , Pyramidal Cells/metabolism , TranscriptomeABSTRACT
Human cortex transcriptomic studies have revealed a hierarchical organization of γ-aminobutyric acid-producing (GABAergic) neurons from subclasses to a high diversity of more granular types. Rapid GABAergic neuron viral genetic labeling plus Patch-seq (patch-clamp electrophysiology plus single-cell RNA sequencing) sampling in human brain slices was used to reliably target and analyze GABAergic neuron subclasses and individual transcriptomic types. This characterization elucidated transitions between PVALB and SST subclasses, revealed morphological heterogeneity within an abundant transcriptomic type, identified multiple spatially distinct types of the primate-specialized double bouquet cells (DBCs), and shed light on cellular differences between homologous mouse and human neocortical GABAergic neuron types. These results highlight the importance of multimodal phenotypic characterization for refinement of emerging transcriptomic cell type taxonomies and for understanding conserved and specialized cellular properties of human brain cell types.
Subject(s)
GABAergic Neurons , Interneurons , Neocortex , Animals , Humans , Mice , Electrophysiological Phenomena , GABAergic Neurons/metabolism , gamma-Aminobutyric Acid/metabolism , Interneurons/metabolism , Neocortex/cytology , Neocortex/metabolism , Patch-Clamp TechniquesABSTRACT
Identification of structural connections between neurons is a prerequisite to understanding brain function. Here we developed a pipeline to systematically map brain-wide monosynaptic input connections to genetically defined neuronal populations using an optimized rabies tracing system. We used mouse visual cortex as the exemplar system and revealed quantitative target-specific, layer-specific and cell-class-specific differences in its presynaptic connectomes. The retrograde connectivity indicates the presence of ventral and dorsal visual streams and further reveals topographically organized and continuously varying subnetworks mediated by different higher visual areas. The visual cortex hierarchy can be derived from intracortical feedforward and feedback pathways mediated by upper-layer and lower-layer input neurons. We also identify a new role for layer 6 neurons in mediating reciprocal interhemispheric connections. This study expands our knowledge of the visual system connectomes and demonstrates that the pipeline can be scaled up to dissect connectivity of different cell populations across the mouse brain.
Subject(s)
Connectome , Visual Cortex , Mice , Animals , Neurons/physiology , Brain/physiology , Visual Cortex/physiology , Visual PathwaysABSTRACT
Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and our astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.
ABSTRACT
We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.
Subject(s)
Neocortex/physiology , Neural Pathways , Neurons/physiology , Synapses/physiology , Synaptic Transmission , Adult , Animals , Datasets as Topic , Excitatory Postsynaptic Potentials , Female , Humans , Inhibitory Postsynaptic Potentials , Male , Mice , Mice, Transgenic , Models, Neurological , Neocortex/cytology , Temporal Lobe/cytology , Temporal Lobe/physiology , Visual Cortex/cytology , Visual Cortex/physiologyABSTRACT
To develop and optimize new scaffold materials for tissue engineering applications, it is important to understand how changes to the scaffold affect the cells that will interact with that scaffold. In this study, we used a hyaluronic acid- (HA-) based hydrogel as a synthetic extracellular matrix, containing modified HA (CMHA-S), modified gelatin (Gtn-S), and a crosslinker (PEGda). By varying the concentrations of these components, we were able to change the gelation time, enzymatic degradation, and compressive modulus of the hydrogel. These changes also affected fibroblast spreading within the hydrogels and differentially affected the proliferation and metabolic activity of fibroblasts and mesenchymal stem cells (MSCs). In particular, PEGda concentration had the greatest influence on gelation time, compressive modulus, and cell spreading. MSCs appeared to require a longer period of adjustment to the new microenvironment of the hydrogels than fibroblasts. Fibroblasts were able to proliferate in all formulations over the course of two weeks, but MSCs did not. Metabolic activity changed for each cell type during the two weeks depending on the formulation. These results highlight the importance of determining the effect of matrix composition changes on a particular cell type of interest in order to optimize the formulation for a given application.