Multiplex, quantitative cellular analysis in large tissue volumes with clearing-enhanced 3D microscopy (C _e 3D)

Abstract

Organ homeostasis, cellular differentiation, signal relay, and in situ function all depend on the spatial organization of cells in complex tissues. For this reason, comprehensive, high-resolution mapping of cell positioning, phenotypic identity, and functional state in the context of macroscale tissue structure is critical to a deeper understanding of diverse biological processes. Here we report an easy to use method, clearing-enhanced 3D (C e 3D), which generates excellent tissue transparency for most organs, preserves cellular morphology and protein fluorescence, and is robustly compatible with antibody-based immunolabeling. This enhanced signal quality and capacity for extensive probe multiplexing permits quantitative analysis of distinct, highly intermixed cell populations in intact C e 3D-treated tissues via 3D histo-cytometry. We use this technology to demonstrate large-volume, high-resolution microscopy of diverse cell types in lymphoid and nonlymphoid organs, as well as to perform quantitative analysis of the composition and tissue distribution of multiple cell populations in lymphoid tissues. Combined with histo-cytometry, C e 3D provides a comprehensive strategy for volumetric quantitative imaging and analysis that bridges the gap between conventional section imaging and disassociation-based techniques.tissue clearing | quantitative microscopy | histo-cytometry | immune system M ajor physiological processes rely on the precise positioning of diverse cell types in specific anatomical locations. Such organization allows exposure of cells to appropriate tissue microenvironments that shape their differentiation, promote appropriate cell-cell communication events, and collectively define the global properties of the whole organ. Understanding these structure-function relationships requires a detailed mapping of both the large-scale organization and fine-grained molecular and cellular composition of complex tissues.The majority of information on such processes comes from microscopic imaging of relatively thin (5-20 μm) "2D" tissue crosssections, examining several markers of interest to visualize a limited number of cell populations with respect to a tissue's representative structural elements. Although providing an excellent framework for understanding general features and the respective positioning of well-represented cell types, such data lack information on 3D organization, being particularly limiting for irregular structures such as the vasculature, airways, nervous tissue, inflamed sites, tumors, or reactive lymph nodes. Furthermore, detection and analysis of rare cellular events requires imaging of a large number of disconnected sections, which introduces possible image selection bias and suffers from the potential omission of key physiological landmarks located just outside of the sampled area. Finally, many cell types require simultaneous visualization of multiple phenotypic markers for correct subset identification, making interpretation of cell composition within tissues problematic without the use...

Resident Macrophages Cloak Tissue Microlesions to Prevent Neutrophil-Driven Inflammatory Damage

“…On next day, excess fluids were removed and tissues were transferred into freshly prepared Ce3D-clearing medium. Ce3D-clearing medium was prepared as previously described (Li et al, 2017). In brief, 4 g Histodenz (Sigma-Aldrich; Cat#D2158) were dissolved in 2.75 ml 40 % N-Methylacetamide (Sigma-Aldrich; Cat#M26305) and 5 μl Triton X-100 (Sigma-Aldrich; Cat#T8787) on a rotator for 2 hours at 37° C. Diaphragms were transferred into the clearing medium and incubated for 2 days on a tube rotator at room temperature.…”

Comparative analysis reveals Ce3D as optimal clearing method for in toto imaging of the mouse intestine

“…In recent years, tissue clearing has re‐emerged as a powerful tool for bypassing tissue sectioning. This has led to the development of a plethora of tissue clearing protocols that reduce optical scattering by extracting the lipid fraction and/or by refractive index matching thereby yielding full‐thickness tissue transparency . These protocols allow detailed 3D visualization of intact organs by confocal, light‐sheet, or two‐photon microscopy, but the appropriateness of each method is organ‐specific and depends on the aspired goal in terms of clearing capability, preservation of fluorescent reporter protein signal, compatibility with immunolabeling and nuclear staining, morphological tissue integrity, complexity, and cost …”

“…Although advances were made to overcome these disadvantages, dehydration methods still suffer from sample shrinkage and ultrastructural damage remains unaddressed. To overcome these limitations, a novel category of clearing approaches based on aqueous solutions has been developed: SeeDB/SeeDB2, ClearT/ClearT2, CUBIC and derived protocols including UbasM, Scale/ScaleS, and Ce3D . Whereas the earlier protocols (SeeDB, ClearT2, and Scale) were still hampered by modest clearing capability and GFP preservation, CUBIC and its modifications yielded better clearance .…”

“…Whereas the earlier protocols (SeeDB, ClearT2, and Scale) were still hampered by modest clearing capability and GFP preservation, CUBIC and its modifications yielded better clearance . The more recently developed protocols (SeeDB2, ScaleS, Ce3D, and UbasM) have been reported to show superior outcomes in terms of clearing capability, GFP retention, and morphological preservation . CLARITY and derived protocols compose a third category of clearing approaches, which involves the embedding of intact tissue into a hydrogel .…”

Multiplexed fluorescence microscopy reveals heterogeneity among stromal cells in mouse bone marrow sections

“…Obviously, it is important to preserve the surrounding cells of stromal cells in order to avoid destroying fine processes, which are characteristic for those cells, and in which the hematopoietic cells are entangled. In histo-cytometry volumetric pixels (voxels) are used to gate for marker frequencies in confocal images (41,61). Using hematopoietic cells as an example, we were able to validate our cell quantification algorithm (Fig.…”