Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

This protocol describes methods for conducting magnetic resonance imaging, clearing, and immunolabeling of intact mouse brains using iDISCO+, followed by a detailed description of imaging using light-sheet microscopy, and downstream analyses using NuMorph.

Tissue clearing followed by light-sheet microscopy (LSFM) enables cellular-resolution imaging of intact brain structure, allowing quantitative analysis of structural changes caused by genetic or environmental perturbations. Whole-brain imaging results in more accurate quantification of cells and the study of region-specific differences that may be missed with commonly used microscopy of physically sectioned tissue. Using light-sheet microscopy to image cleared brains greatly increases acquisition speed as compared to confocal microscopy. Although these images produce very large amounts of brain structural data, most computational tools that perform feature quantification in images of cleared tissue are limited to counting sparse cell populations, rather than all nuclei.

Here, we demonstrate NuMorph (Nuclear-Based Morphometry), a group of analysis tools, to quantify all nuclei and nuclear markers within annotated regions of a postnatal day 4 (P4) mouse brain after clearing and imaging on a light-sheet microscope. We describe magnetic resonance imaging (MRI) to measure brain volume prior to shrinkage caused by tissue clearing dehydration steps, tissue clearing using the iDISCO+ method, including immunolabeling, followed by light-sheet microscopy using a commercially available platform to image mouse brains at cellular resolution. We then demonstrate this image analysis pipeline using NuMorph, which is used to correct intensity differences, stitch image tiles, align multiple channels, count nuclei, and annotate brain regions through registration to publicly available atlases.

We designed this approach using publicly available protocols and software, allowing any researcher with the necessary microscope and computational resources to perform these techniques. These tissue clearing, imaging, and computational tools allow measurement and quantification of the three-dimensional (3D) organization of cell-types in the cortex and should be widely applicable to any wild-type/knockout mouse study design.

Whole-brain imaging at single-cell resolution is an important challenge in neuroscience. Cellular-resolution brain images allow for detailed analysis and system-level mapping of brain circuitry and how that circuitry is disrupted by genetic or environmental risk factors for neuropsychiatric disorders, cellular behavior in developing embryos, as well as neural circuits in the adult brain^1,2,3. There are multiple histological methods that allow for high-resolution images of the reconstructed 3D brain; however, these techniques require expensive, specialized equipment, may not b....

All mice were used in accordance with and approved by the Institutional Animal Care and Use Committee (IACUC) at the University of North Carolina at Chapel Hill.

1. Mouse dissection and perfusion

NOTE: The following dissections were performed on P4 and P14 mice using a syringe. The volume of perfusion fluid will vary depending on the age of the animal.

1. Perfusion
   CAUTION: Paraformaldehyde (PFA) is a hazardous chemical. Perform all .......

As the iDISCO+ protocol introduces significant tissue shrinkage, which is easily noticeable by eye (Figure 2B), we added an MRI step to this pipeline prior to tissue clearing to quantify the shrinkage induced by tissue clearing. The workflow starts with removal of the non-brain tissue from the MR image (Figure 2C). Next, a rigid transformation (3 translation and 3 rotation angles) is applied to align the MR image to the light-sheet image (Fi.......

Tissue clearing methods are useful techniques for measuring 3D cellular organization of the brain. There are a host of tissue clearing methods described in the literature, each with its advantages and limitations^6,7,8,9. The options for computational tools to analyze the cell types in the tissue-cleared images are relatively limited. Other available tools have been implemented to sparse cell po.......

This work was supported by the NIH (R01MH121433, R01MH118349, and R01MH120125 to JLS and R01NS110791 to GW) and the Foundation of Hope. We thank Pablo Ariel of the Microscopy Services Laboratory for assisting in sample imaging. The Microscopy Services Laboratory in the Department of Pathology and Laboratory Medicine is supported in part by Cancer Center Core Support Grant P30 CA016086 to the University of North Carolina (UNC) Lineberger Comprehensive Cancer Center. The Neuroscience Microscopy Core is supported by grant P30 NS045892. Research reported in this publication was supported in part by the North Carolina Biotech Center Institutional Support Grant 2016-ID....