Probes for SST

Converging evidence suggests that deficits in somatostatin (SST)-expressing neuron signaling contributes to major depressive disorder. Preclinical studies show that enhancing this signaling, specifically at α5 subunit-containing γ-ami­nobutyric acid subtype A receptors (α5-GABAARs), provides a potential means to overcome low SST neuron function. The cortical microcircuit comprises multiple subtypes of inhibitory γ-aminobutyric acid (GABA) neurons and excitatory pyramidal cells (PYCs). In this study, multilabel fluorescence in situ hybridization was used to characterize α5-GABAAR gene expression in PYCs and three GABAergic neuron subgroups – vasoactive intestinal peptide (VIP)-, SST-, and parvalbumin (PV)-expressing cells – in the human and mouse frontal cortex. Across species, we found the majority of gene expression in PYCs (human: 39.7%; mouse: 54.14%), less abundant expression in PV neurons (human: 20%; mouse: 16.33%), and no expression in VIP neurons (0%). Only human SST cells expressed GABRA5, albeit at low levels (human: 8.3%; mouse: 0%). Together, this localization suggests potential roles for α5-GABAARs within the cortical microcircuit: (1) regulators of PYCs, (2) regulators of PV cell activity across species, and (3) sparse regulators of SST cell inhibition in humans. These results will advance our ability to predict the effects of pharmacological agents targeting α5-GABAARs, which have shown therapeutic potential in preclinical animal models.

Cell-specific molecular investigations of the human brain are essential for understanding the neurobiology of diseases, but are hindered by postmortem conditions and technical challenges. To address these issues we developed a multi-label fluorescence in situ hybridization protocol and a novel optical filter device to identify cell types and control for tissue autofluorescence. We show that these methods can be used with laser-capture microdissection for human brain tissue cell-specific molecular analysis.

The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.

The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals. Cross-region analysis of these 565 cell populations revealed features of brain organization, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions. Systematic neuronal classifications for two complex basal ganglia nuclei and the striatum revealed a rare population of spiny projection neurons. This adult mouse brain cell atlas, accessible through interactive online software (DropViz), serves as a reference for development, disease, and evolution.

A wealth of data has elucidated the mechanisms by which sensory inputs are encoded in the neocortex, but how these processes are regulated by the behavioral relevance of sensory information is less understood. Here, we focus on neocortical layer 1 (L1), a key location for processing of such top-down information. Using Neuron-Derived Neurotrophic Factor(NDNF) as a selective marker of L1 interneurons (INs) and in vivo 2-photon calcium imaging, electrophysiology, viral tracing, optogenetics, and associative memory, we find that L1 NDNF-INs mediate a prolonged form of inhibition in distal pyramidal neuron dendrites that correlates with the strength of the memory trace. Conversely, inhibition from Martinotti cells remains unchanged after conditioning but in turn tightly controls sensory responses in NDNF-INs. These results define a genetically addressable form of dendritic inhibition that is highly experience dependent and indicate that in addition to disinhibition, salient stimuli are encoded at elevated levels of distal dendritic inhibition.

Background Aging is accompanied by altered thinking (cognition) and feeling (mood), functions that depend on information processing by brain cortical cell microcircuits. We hypothesized that age-associated long-term functional and biological changes are mediated by gene transcriptomic changes within neuronal cell-types forming cortical microcircuits, namely excitatory pyramidal cells (PYC) and inhibitory GABAergic neurons expressing vasoactive intestinal peptide (Vip), somatostatin (Sst) and parvalbumin (Pvalb). Methods To test this hypothesis, we assessed locomotor, anxiety-like and cognitive behavioral changes between young (2 months, n=9) and old (22 months, n=12) male C57BL/6 mice, and performed frontal cortex cell-type specific molecular profiling, using laser-capture microscopy and RNA sequencing. Results were analyzed by neuroinformatics and validated by fluorescent in situ hybridization. Results Old-mice displayed increased anxiety and reduced working memory. The four cell-types displayed distinct age-related transcriptomes and biological pathway profiles, affecting metabolic and cell signaling pathways, and selective markers of neuronal vulnerability (Ryr3), resilience (Oxr1), and mitochondrial dynamics (Opa1), suggesting high age-related vulnerability of PYCs, and variable degree of adaptation in GABAergic neurons. Correlations between gene expression and behaviors suggest that changes in cognition and anxiety associated with age are partly mediated by normal age-related cell changes, and that additional age-independent decreases in synaptic and signaling pathways, notably in PYC and SST-neurons further contribute to behavioral changes. Conclusions Our study demonstrates cell-dependent differential vulnerability and coordinated cell-specific cortical microcircuit molecular changes with age. Collectively, the results suggest intrinsic molecular links between aging, cognition and mood-related behaviors with SST-neurons contributing evenly to both behavioral conditions.