Beyond 2D: A scalable and highly sensitive method for a comprehensive 3D analysis of kidney biopsy tissue.
PNAS Nexus
; 3(1): pgad433, 2024 Jan.
Article
in En
| MEDLINE
| ID: mdl-38193136
ABSTRACT
The spatial organization of various cell populations is critical for the major physiological and pathological processes in the kidneys. Most evaluation of these processes typically comes from a conventional 2D tissue cross-section, visualizing a limited amount of cell organization. Therefore, the 2D analysis of kidney biopsy introduces selection bias. The 2D analysis potentially omits key pathological findings outside a 1- to 10-µm thin-sectioned area and lacks information on tissue organization, especially in a particular irregular structure such as crescentic glomeruli. In this study, we introduce an easy-to-use and scalable method for obtaining high-quality images of molecules of interest in a large tissue volume, enabling a comprehensive evaluation of the 3D organization and cellular composition of kidney tissue, especially the glomerular structure. We show that CUBIC and ScaleS clearing protocols could allow a 3D analysis of the kidney tissues in human and animal models of kidney disease. We also demonstrate that the paraffin-embedded human biopsy specimens previously examined via 2D evaluation could be applicable to 3D analysis, showing a potential utilization of this method in kidney biopsy tissue collected in the past. In summary, the 3D analysis of kidney biopsy provides a more comprehensive analysis and a minimized selection bias than 2D tissue analysis. Additionally, this method enables a quantitative evaluation of particular kidney structures and their surrounding tissues, with the potential utilization from basic science investigation to applied diagnostics in nephrology.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Language:
En
Journal:
PNAS Nexus
Year:
2024
Document type:
Article
Affiliation country:
Japan
Country of publication:
United kingdom