Tissue libraries enable rapid determination of conditions that preserve antibody labeling in cleared mouse and human tissue

Abstract

Difficulty achieving complete, specific, and homogenous staining is a major bottleneck preventing the widespread use of tissue clearing techniques to image large volumes of human tissue. In this manuscript, we describe a procedure to rapidly design immunostaining protocols for antibody labeling of cleared brain tissue. We prepared libraries of .5-1.0 mm thick tissue sections that are fixed, pre-treated, and cleared via similar, but different procedures to optimize staining conditions for a panel of antibodies. Results from a library of mouse tissue correlate well with results from a similarly prepared library of human brain tissue, suggesting mouse tissue is an adequate substitute for protocol optimization. These data show that procedural differences do not influence every antibody-antigen pair in the same way, and minor changes can have deleterious effects, therefore, optimization should be conducted for each target. The approach outlined here will help guide researchers to successfully label a variety of targets, thus removing a major hurdle to accessing the rich 3D information available in large, cleared human tissue volumes.

Brain Vasculature Accumulates Tau and Is Spatially Related to Tau Tangle Pathology in Alzheimer’s Disease

“…Three-dimensional histology reveals the accumulation of tau protein along blood vessels Tissue was collected from the inferior temporal gyrus, a region associated with functional impairment and tau accumulation in AD 16 . Each block was sliced into 0.5-1 mm thick sections, then cleared and immunolabeled following an optimized protocol described previously 11 . AD and control human brain tissue samples immunolabeled for phosphotau (AT8, recognizes tau phosphorylated at both S202 and T205), blood vessels (Glut1), neurons (HuD), and cell nuclei (DAPI, Fig.…”

“…However, one challenge of investigating protein distribution in the brain is imaging structures at high resolution in large tissue volumes. Advances in tissue clearing and multiplexed antibody staining have addressed this gap and enabled us to quantify the distribution of tau pathology and determine its spatial relationship to vasculature in the AD brain with single-cell resolution 11, 12 . This allowed us to quantify, in three dimensions, the proximity of phosphorylated tau and NFTs to individually segmented blood vessels.…”

Spatial characterization of tangle-bearing neurons and ghost tangles in the human inferior temporal gyrus with three-dimensional imaging

“…To enable the simultaneous visualization of tau tangles, neurons and other cells in large volumes of human brain tissue, we prepared a library of tissue with variant tissue clearing protocols and found conditions that allow concurrent labelling in human brain tissue as previously described. 7 We stain the tissue with AT8 antibody that binds to phospho-tau Ser202 and Thr205 of tau protein which is accessible at various stages of tangle maturity, including pre-tangles and mature tangles. 2 , 14 - 16 HuD E-1 antibody binds to the ELAV like RNA-binding protein 1, which localizes to the nucleoplasm, nucleoli and cytosol of neurons.…”

“…However, few experiments have realized the promise of studying cellular distributions in cleared human brain tissue. 4 - 6 There are many difficulties that come with scaling up techniques to larger volumes of tissue including inconsistent immunohistochemistry 7 and historically limited options for analysing large three-dimensional datasets. 8 , 9 We focused at first on one of the ‘bookends’ of this process, ghost tangles, since their histological characteristic—the presence of a tangle without an accompanying neuron—is well defined, since they are uncommon in the neocortex and since very little is known even about their spatial characteristics.…”

Successful 3D imaging of cleared biological samples with light sheet fluorescence microscopy

“…A high antigen density can result in antibodies being absorbed by peripheral epitopes faster than they can diffuse through the tissue, resulting in a fluorescent “halo” at the periphery of a mostly unlabeled sample ( Richardson et al, 2021 ; Weiss et al, 2021 ). Interestingly, Zwang et al (2023) recently published an approach inspired by quantitative structure–activity relationship modeling for drug discovery to facilitate the optimization of immunolabeling protocols for thick tissues. Their strategy is based on a library of mouse brain tissues prepared by varying only one or two parameters from a baseline immunolabeling protocol that was used to determine the optimal staining conditions for a panel of antibodies.…”