Beyond 2D: A scalable and highly sensitive method for a comprehensive 3D analysis of kidney biopsy tissue

超越二维:一种可扩展且高度灵敏的肾活检组织全面三维分析方法

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作者:Hiroyuki Yamada, Shin-Ichi Makino, Issei Okunaga, Takafumi Miyake, Kanae Yamamoto-Nonaka, Juan Alejandro Oliva Trejo, Takahiro Tominaga, Maulana A Empitu, Ika N Kadariswantiningsih, Aurelien Kerever, Akira Komiya, Tomohiko Ichikawa, Eri Arikawa-Hirasawa, Motoko Yanagita, Katsuhiko Asanuma

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.

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