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 indicated that WAT responds to environmental cues by adapting the abundance of these "communication routes", however, 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: I) Methanol-based tissue clearing protocols restrict the usable antibody portfolio to methanol resistant antibodies and II) 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 (Tissue Network Quantifier) a Fiji tool for automated 3D quantification of neuron- or vascular network density, freely available at https://github.com/SchweigerLab/TiNeQuant. Given TiNeQuants versatility beyond WAT, it simplifies future efforts studying neuronal or vascular alterations in numerous pathologies.
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