Meah, A. | bioRxiv Science

bioRxiv2025

MIST-Explorer: The Comprehensive Toolkit for Spatial Omic Analysis and Visualization of Single-Cell MIST Array Data

Recent advances in spatial proteomics have enabled high-dimensional protein analysis within tissue samples, yet few methods accurately detect low-abundance functional proteins. Spatial MIST (Multiplex In Situ Tagging) is one such technique, capable of profiling over 100 protein markers spatially at single-cell resolution on tissue sections and cultured cells. However, despite the availability of various open-source tools for image registration and visualization, no dedicated software exists to align the images and analyze spatial MIST data effectively. To address this gap, we present MIST-Explorer, a comprehensive, user-friendly toolkit for the visualization and analysis of single-cell spatial MIST array data. Developed in Python with a PyQt6-based graphical interface, MIST-Explorer streamlines the spatial omics workflow--from image preprocessing and registration to cell segmentation and protein quantification. The software supports two workflows: one for preprocessed datasets and another for raw image inputs, ensuring broad compatibility across experimental designs. Key features include tile-based image registration using Astroalign and PyStackReg, deep learning-based segmentation with StarDist, multi-channel visualization with layer controls, and an interactive analysis module offering ROI selection along with histograms, heatmaps, and UMAP plots. MIST-Explorer generates spatially resolved expression tables readily compatible with downstream single-cell analysis pipelines. By integrating all major steps into a single platform, MIST-Explorer empowers researchers to derive biological insights from complex spatial omics datasets without requiring extensive computational expertise. Availability and implementationFreely available at https://github.com/MIST-Explorer/MIST-Explorer.

bioinformatics↗

bioRxiv2022

Imaging unlabeled axons in the mouse retina by second harmonic generation

We describe a novel microscopy for studying the network of axons in the unlabeled fresh wholemount retina. The intrinsic radiation of second harmonic generation (SHG) was utilized to visualize single axons of all major retinal neurons, i.e., photoreceptors, horizontal cells, bipolar cells, amacrine cells, and the retinal ganglion cells. The cell types of SHG+ axons were determined using transgenic GFP/YFP mice. New findings were obtained with retinal SHG imaging: Muller cells do not maintain uniformly polarized microtubules in the processes; SHG+ axons of bipolar cells terminate in the inner plexiform layer (IPL) in a subtype-specific manner; a subset of amacrine cells, presumably the axon-bearing types, emits SHG; and the axon-like neurites of amacrine cells provide a cytoskeletal scaffolding for the IPL stratification. To demonstrate the utility, retinal SHG imaging was applied for testing whether the inner retina is preserved in glaucoma, using DBA/2 mice as a model of glaucoma and DBA/2-Gpnmb+ as the non-glaucomatous control. It was found that the morphology of the inner retina was largely intact in glaucoma and the pre-synaptic compartments to the retinal ganglion cells were uncompromised. It proves retinal SHG imaging as a promising technology for studying the physiological and diseased retina in 3D.

neuroscience↗