5 research outputs found

    Long-Term Imaging of Identified Neural Populations using Microprisms in Freely Moving and Head-Fixed Animals

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    With the advancement of multi-photon microscopy and molecular technologies, fluorescence imaging is rapidly growing to become a powerful approach for studying the structure, function, and plasticity of living brain tissues. In comparison to conventional electrophysiology, fluorescence microscopy can capture the neural activity as well as the morphology of the cells, enabling long-term recordings of the identified neuron populations at single-cell or subcellular resolution. However, high-resolution imaging typically requires a stable, head-fixed setup that restricts the movement of the animal, and the preparation of a flat surface of transparent glass allows visualization of neurons at one or more horizontal planes but is limited in studying the vertical processes running across different depths. Here, we describe a procedure to combine a head plate fixation and a microprism that gives multilayer and multimodal imaging. This surgical preparation not only gives access to the entire column of the mouse visual cortex but allows two-photon imaging in a head-fixed position and one-photon imaging in a freely moving paradigm. Using this approach, one can sample identified cell populations across different cortical layers, register their responses under head-fixed and freely moving states, and track the long-term changes over months. Thus, this method provides a comprehensive assay of the microcircuits, enabling direct comparison of neural activities evoked by well-controlled stimuli and under a natural behavioral paradigm

    Pharmacological Reprogramming of Fibroblasts into Neural Stem Cells by Signaling-Directed Transcriptional Activation

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    Cellular reprogramming using chemically defined conditions, without genetic manipulation, is a promising approach for generating clinically relevant cell types for regenerative medicine and drug discovery. However, small-molecule approaches for inducing lineage-specific stem cells from somatic cells across lineage boundaries have been challenging. Here, we report highly efficient reprogramming of mouse fibroblasts into induced neural stem cell-like cells (ciNSLCs) using a cocktail of nine components (M9). The resulting ciNSLCs closely resemble primary neural stem cells molecularly and functionally. Transcriptome analysis revealed that M9 induces a gradual and specific conversion of fibroblasts toward a neural fate. During reprogramming specific transcription factors such as Elk1 and Gli2 that are downstream of M9-induced signaling pathways bind and activate endogenous master neural genes to specify neural identity. Our study provides an effective chemical approach for generating neural stem cells from mouse fibroblasts and reveals mechanistic insights into underlying reprogramming processes

    Pharmacological Reprogramming of Fibroblasts into Neural Stem Cells by Signaling-Directed Transcriptional Activation

    No full text
    Cellular reprogramming using chemically defined conditions, without genetic manipulation, is a promising approach for generating clinically relevant cell types for regenerative medicine and drug discovery. However, small molecule approaches for inducing lineage-specific stem cells from somatic cells across lineage boundaries have been challenging. Here, we report highly efficient reprogramming of mouse fibroblasts into induced neural stem cell-like cells (ciNSLCs) using a cocktail of nine components (M9). The resulting ciNSLCs closely resemble primary neural stem cells molecularly and functionally. Transcriptome analysis revealed that M9 induces a gradual and specific conversion of fibroblasts towards a neural fate. During reprogramming specific transcription factors such as Elk1 and Gli2 that are downstream of M9-induced signaling pathways bind and activate endogenous master neural genes to specify neural identity. Our study provides an effective chemical approach for generating neural stem cells from mouse fibroblasts, and reveals mechanistic insights into underlying reprogramming processes
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