High-throughput 3D whole-brain quantitative histopathology in rodents

Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer’s disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques.


Supplementary Information
Mouse brain hierarchy. Most elementary structures correspond to the mouse brain atlas labels. Some of these structures are very small brain regions which are not necessarily relevant in studies focusing on pathological markers. We have created a brain ontology adapted from NeuroNames ontology (http://braininfo.rprc.washington.edu) so as to merge small structures into more relevant ones. This hierarchy is made available and can be downloaded along with 3D-HAPi.
Literature survey on amyloid load quantification between 1999 and 2012. (a) Evolution over the last decade of the number of publications referenced on NCBI (http://www.ncbi.nlm.nih.gov/pubmed) that quantify Aβ deposition in mouse models of AD. (b-d) Among those publications, 51 were chosen for further analysis. Articles were selected based on journal impact factor (2012 impact factor had to be at least equal to 2) and if the quantification method was adequately described. In our publication sample, most of the scientists analyzed a total of 3 to 6 sections (b) and manually delineated 1 or 2 ROIs (c) for analysis. Once ROIs are specified, a variety of amyloid plaque segmentation methods were used (d). Some required heavy human interventions like manual segmentation/visual counting or stereology. Scientists mostly used image analysis software. Images were usually segmented using a threshold operation. Some publications did not specify the algorithm used by the software.  The F1 score measures the performance of the automatic segmentation compared to ground-truth annotations. An F1 score greater than 0.7 was considered satisfactory.

SUPPLEMENTARY TABLE 3
Amyloid lowering effect of 13C3a immunotherapy in APP/PS1 mice (dataset 2). APP/PS1dE9 mouse brains tissue processing, block-face photography and histology (dataset 1). Fresh brains were snap frozen and embedded in a mixture of M1 embedding matrix (Thermo Fisher Scientific) and Fast Green (Sigma-Aldrich) before being entirely cut on a CM3050S cryostat (Leica). Four batches of serial coronal brain sections (20 μm), ranging from the brain frontal pole to the end of the caudal part of the cortex, were collected, mounted on superfrost slides and quickly dried. The first series was dedicated to Nissl staining. The fourth series was dedicated to amyloid peptide aggregate staining. The remaining series were stored at -80°C until processing. Images from the surface of the block were recorded every fourth section (before each section of the first series was cut) with a digital camera (Powershot G5 Pro, Canon) at a lateral resolution of 27 µm.

ROI
These photographs were taken at the end of the cryostat wheel crank course, hence with the brain in the same position section after section. An optic fiber-ring light was fixed onto the lens of the camera. This ensured a proper and homogeneous illumination of the sample from section to section. A laptop connected to the camera was used to remotely take photographs and store images directly onto the hard disk.
To highlight Aβ peptide aggregates, after post-fixation in 4% paraformaldehyde in PBS, we performed an IHC staining with BAM10 primary monoclonal antibody (Sigma-Aldrich, 1:500 dilution), a biotinylated goat anti-mouse secondary antibody (Vector Laboratories) and staining was revealed with DAB detection kit (Ventana Medical Systems, Roche). IHC experiments were performed with the automate Discovery XT (Ventana Medical Systems, Roche). All the sections were processed identically. Sections were counter-stained with Bluing Reagent (Ventana Medical Systems, Roche).