A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology

Abstract

Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or can be a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues of by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label all neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and morphological deformations. 4. Implement novel protocol for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cells density of one brain region in less than 1 min and is highly replicable to cortical and subcortical gray matter regions and structures throughout the brain. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57B6/6J and 2 BXD strains. The data represent the variability among cases for the same brain region and across regions within case. Our data are consistent with previous studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications in how genetics, environment, and development across the lifespan impact brain structure.