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为脂肪组织中神经元和血管密度的全组织标记及定量分析开辟道路。

Clearing the path for whole-mount labeling and quantification of neuron and vessel density in adipose tissue.

作者信息

Rauchenwald Thomas, Benedikt-Kühnast Pia, Eder Sandra, Grabner Gernot F, Forstreiter Sebastian, Lang Michaela, Sango Roko, Eisenberg Tobias, Rattei Thomas, Haschemi Arvand, Wolinski Heimo, Schweiger Martina

机构信息

Institute of Molecular Biosciences, University of Graz, 8010 Graz, Austria.

Institute for Diabetes and Cancer, Helmholtz Center Munich, 85764 Neuherberg, Germany.

出版信息

J Cell Sci. 2025 Feb 1;138(3). doi: 10.1242/jcs.263438. Epub 2025 Feb 7.

Abstract

White adipose tissue (WAT) comprises a plethora of cell types beyond adipocytes forming a regulatory network that ensures systemic energy homeostasis. Intertissue communication is facilitated by metabolites and signaling molecules that are spread by vasculature and nerves. Previous works have indicated that WAT responds to environmental cues by adapting the abundance of these 'communication routes'; however, the high intra-tissue heterogeneity questions the informative value of bulk or single-cell analyses and underscores the necessity of whole-mount imaging. The applicability of whole-mount WAT-imaging is currently limited by two factors - (1) methanol-based tissue clearing protocols restrict the usable antibody portfolio to methanol-resistant antibodies and (2) the vast amounts of data resulting from 3D imaging of whole-tissue samples require high computational expertise and advanced equipment. Here, we present a protocol for whole-mount WAT clearing, overcoming the constraints of antibody-methanol sensitivity. Additionally, we introduce TiNeQuant (for 'tissue network quantifier') a Fiji tool for automated 3D quantification of neuron or vascular network density, which we have made freely available. Given TiNeQuants versatility beyond WAT, it simplifies future efforts studying neuronal or vascular alterations in numerous pathologies.

摘要

白色脂肪组织(WAT)包含大量脂肪细胞以外的细胞类型,这些细胞形成一个调节网络,以确保全身能量稳态。代谢物和信号分子通过血管和神经传播,促进了组织间的通讯。以往的研究表明,WAT通过调整这些“通讯途径”的丰度来响应环境信号;然而,组织内高度的异质性使得整体或单细胞分析的信息价值受到质疑,并凸显了整体成像的必要性。目前,整体WAT成像的适用性受到两个因素的限制——(1)基于甲醇的组织透明化方案将可用抗体组合限制为耐甲醇抗体,(2)全组织样本的三维成像产生的大量数据需要高计算专业知识和先进设备。在此,我们提出了一种整体WAT透明化方案,克服了抗体-甲醇敏感性的限制。此外,我们引入了TiNeQuant(“组织网络量化器”),这是一种用于自动三维量化神经元或血管网络密度的Fiji工具,我们已将其免费提供。鉴于TiNeQuant在WAT之外的通用性,它简化了未来在多种病理学中研究神经元或血管改变的工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f86b/11832183/bff48c000026/joces-138-263438-g1.jpg

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