We present a spheroid trapping device, compatible with traditional tissue culture plates, to confine microtissues in a small area and allow suspension cultures to be treated like adherent cultures with minimal loss of spheroids due to aspiration. We also illustrate an automated morphology-independent procedure for cell recognition, segmentation, and a calcium spike detection technique for high-throughput analysis in 3D cultured tissue. Our cell recognition technique uses a maximum intensity projection of spatial-temporal data to create a binary mask, which delineates individual cell boundaries and extracts mean fluorescent data for each cell through a series of intensity thresholding and cluster labeling operations. The temporal data are subject to sorting for imaging artifacts, baseline correction, smoothing, and spike detection algorithms. We validated this procedure through analysis of calcium data from 2D and 3D SHSY-5Y cell cultures. Using this approach, we rapidly created regions of interest (ROIs) and extracted fluorescent intensity data from hundreds of cells in the field of view with superior data fidelity over hand-drawn ROIs even in dense (3D tissue) cell populations. We sorted data from cells with imaging artifacts (such as photo bleaching and dye saturation), classified nonfiring and firing cells, estimated the number of spikes in each cell, and documented the results, facilitating large-scale calcium imaging analysis in both 2D and 3D cultures. Since our recognition and segmentation technique is independent of morphology, our protocol provides a versatile platform for the analysis of large confocal calcium imaging data from neuronal cells, glial cells, and other cell types.
Fiber photometry does not reflect spiking activity in the striatum
