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Phadke, R. A.

Publications and source records attributed to Phadke, R. A..

3 recordsLinked to original sources

Overexpression of the schizophrenia risk gene C4 in PV cells drives sex-dependent behavioral deficits and circuit dysfunction.

Fast-spiking parvalbumin (PV)-positive cells are key players in orchestrating pyramidal neuron activity, and their dysfunction is consistently observed in myriad brain diseases. To understand how immune complement dysregulation - a prevalent locus of brain disease etiology - in PV cells may drive disease pathogenesis, we have developed a transgenic mouse line that permits cell-type specific overexpression of the schizophrenia-associated complement component 4 (C4) gene. We found that overexpression of mouse C4 (mC4) in PV cells causes sex-specific behavioral alterations and concomitant deficits in synaptic connectivity and excitability of PV cells of the prefrontal cortex. Using a computational network, we demonstrated that these microcircuit deficits led to hyperactivity and disrupted neural communication. Finally, pan-neuronal overexpression of mC4 failed to evoke the same deficits in behavior as PV-specific mC4 overexpression, suggesting that C4 perturbations in fast-spiking neurons are more harmful to brain function than pan-neuronal alterations. Together, these results provide a causative link between C4 and the vulnerability of PV cells in brain disease.

neuroscience↗

C4 induces pathological synaptic loss by impairing AMPAR trafficking.

During development, activation of the complement pathway, an extracellular proteolytic cascade, results in microglia-dependent synaptic elimination via complement receptor 3 (CR3). Here, we report that decreased connectivity caused by overexpression of C4 (C4-OE), a schizophrenia-associated gene, is CR3 independent. Instead, C4-OE triggers GluR1 degradation through an intracellular mechanism involving endosomal trafficking protein SNX27, resulting in pathological synaptic loss. Moreover, the connectivity deficits associated with C4-OE were rescued by increasing levels of SNX27, linking excessive complement activity to an intracellular endolysosomal recycling pathway affecting synapses.

neuroscience↗

REVEALS: An Open Source Multi Camera GUI For Rodent Behavior Acquisition

Understanding the rich behavioral data generated by mice is essential for deciphering the function of the healthy and diseased brain. However, the current landscape lacks effective, affordable, and accessible methods for acquiring such data, especially when employing multiple cameras simultaneously. We have developed REVEALS (Rodent BEhaVior Multi-camErA Laboratory AcquiSition), a graphical user interface (GUI) written in python for acquiring rodent behavioral data via commonly used USB3 cameras. REVEALS allows for user-friendly control of recording from one or multiple cameras simultaneously while streamlining the data acquisition process, enabling researchers to collect and analyze large datasets efficiently. We release this software package as a stand-alone, open-source framework for researchers to use and modify according to their needs. We describe the details of the GUI implementation, including the camera control software and the video recording functionality. We validate results demonstrating the GUIs stability, reliability, and accuracy for capturing and analyzing rodent behavior using DeepLabCut pose estimation in both an object and social interaction assay. REVEALS can also be incorporated into other custom pipelines to analyze complex behavior, such as MoSeq. In summary, REVEALS provides an interface for collecting behavioral data from one or multiple perspectives that, combined with deep learning algorithms, will allow the scientific community to discover and characterize complex behavioral phenotypes to understand brain function better.

neuroscience↗