Computational NeuroscienceIsolating specific cell and tissue compartments from 3D images for quantitative regional distribution analysis using novel computer algorithms

- Methods for quantifying the distributions of proteins within cell membranes and of drugs within tissue are limited.
- A method and computer program for isolating specific cell and tissue compartments for quantitative analysis is described.
- We quantified the diffusion dynamics of blood borne compounds in the parenchyma in vivo.
- We map the distribution of cell membrane-associated proteins on neuron dendrites.
- Our method represents an economical and easy to use way for quantitative distribution analysis of 3D image stacks.

BackgroundIsolating specific cellular and tissue compartments from 3D image stacks for quantitative distribution analysis is crucial for understanding cellular and tissue physiology under normal and pathological conditions. Current approaches are limited because they are designed to map the distributions of synapses onto the dendrites of stained neurons and/or require specific proprietary software packages for their implementation.New methodTo overcome these obstacles, we developed algorithms to Grow and Shrink Volumes of Interest (GSVI) to isolate specific cellular and tissue compartments from 3D image stacks for quantitative analysis and incorporated these algorithms into a user-friendly computer program that is open source and downloadable at no cost.ResultsThe GSVI algorithm was used to isolate perivascular regions in the cortex of live animals and cell membrane regions of stained spinal motoneurons in histological sections. We tracked the real-time, intravital biodistribution of injected fluorophores with sub-cellular resolution from the vascular lumen to the perivascular and parenchymal space following a vascular microlesion, and mapped the precise distributions of membrane-associated KCC2 and gephyrin immunolabeling in dendritic and somatic regions of spinal motoneurons.Comparison with existing methodsCompared to existing approaches, the GSVI approach is specifically designed for isolating perivascular regions and membrane-associated regions for quantitative analysis, is user-friendly, and free.ConclusionsThe GSVI algorithm is useful to quantify regional differences of stained biomarkers (e.g., cell membrane-associated channels) in relation to cell functions, and the effects of therapeutic strategies on the redistributions of biomolecules, drugs, and cells in diseased or injured tissues.