Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.

Highlights d IL-33 is expressed by subsets of hippocampal neurons and is modulated by experience d Microglia drive dendritic spine plasticity and memory precision via neuronal IL-33 d IL-33 gain of function mitigates some age-related decreases in spine plasticity d Neuronal IL-33 induces microglial remodeling of the extracellular matrix

SummaryAstrocyte dysfunction and neuroinflammation are detrimental features in multiple pathologies of the CNS. Therefore, the development of methods that produce functional human astrocytes represents an advance in the study of neurological diseases. Here we report an efficient method for inflammation-responsive astrocyte generation from induced pluripotent stem cells (iPSCs) and embryonic stem cells. This protocol uses an intermediate glial progenitor stage and generates functional astrocytes that show levels of glutamate uptake and calcium activation comparable with those observed in human primary astrocytes. Stimulation of stem cell-derived astrocytes with interleukin-1β or tumor necrosis factor α elicits a strong and rapid pro-inflammatory response. RNA-sequencing transcriptome profiling confirmed that similar gene expression changes occurred in iPSC-derived and primary astrocytes upon stimulation with interleukin-1β. This protocol represents an important tool for modeling in-a-dish neurological diseases with an inflammatory component, allowing for the investigation of the role of diseased astrocytes in neuronal degeneration.

Human neural progenitors derived from pluripotent stem cells develop into electrophysiologically active neurons at heterogeneous rates, which can confound disease-relevant discoveries in neurology and psychiatry. By combining patch clamping, morphological and transcriptome analysis on single human neurons in vitro, we defined a continuum of poor to highly functional electrophysiological states of differentiated neurons. The strong correlations between action potentials, synaptic activity, dendritic complexity and gene expression highlight the importance of methods for isolating functionally comparable neurons for in vitro investigations of brain disorders. While whole-cell electrophysiology is the gold standard for functional evaluation, it often lacks the scalability required for disease modeling studies. Here, we demonstrate a multimodal machine-learning strategy to identify new molecular features that predict the physiological states of single neurons, independently of the time spent in vitro. As further proof of concept, we selected one of the potential neurophysiological biomarkers identified in this study – GDAP1L1 – to isolate highly functional live human neurons in vitro.