SOLID: minimizing tissue distortion for brain-wide profiling of diverse architectures

Jingtan Zhu, Xiaomei Liu, Zhang Liu, Yating Deng, Jianyi Xu, Kunxing Liu, Ruiying Zhang, Xizhi Meng, Peng Fei, Tingting Yu () and Dan Zhu ()
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Jingtan Zhu: Huazhong University of Science and Technology
Xiaomei Liu: Huazhong University of Science and Technology
Zhang Liu: Huazhong University of Science and Technology
Yating Deng: Huazhong University of Science and Technology
Jianyi Xu: Huazhong University of Science and Technology
Kunxing Liu: Huazhong University of Science and Technology
Ruiying Zhang: Huazhong University of Science and Technology
Xizhi Meng: Huazhong University of Science and Technology
Peng Fei: Huazhong University of Science and Technology
Tingting Yu: Huazhong University of Science and Technology
Dan Zhu: Huazhong University of Science and Technology

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract Brain-wide profiling of diverse biological components is fundamental for understanding complex brain pathology. Despite the availability in whole-brain imaging, it is still challenging to conduct multiplexed, brain-wide analysis with current tissue clearing techniques. Here, we propose SOLID, a hydrophobic tissue clearing method that can minimize tissue distortion while offering impressive clearing performance. SOLID achieves high-quality imaging of multi-color labeled mouse brain, and the acquired datasets can be effectively registered to the Allen Brain Atlas via commonly-used algorithms. SOLID enables generation of neural and vascular maps within one mouse brain, as well as tracing of specific neural projections labeled with viruses. SOLID also allows cross-channel investigations of β-amyloid plaques and neurovascular lesions in the reconstructed all-in-one panorama, providing quantitative insights into structural interactions at different stages of Alzheimer’s disease. Altogether, SOLID provides a robust pipeline for whole-brain mapping, which may widen the utility of tissue clearing techniques in diverse neuroscience research.

Date: 2024
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DOI: 10.1038/s41467-024-52560-7

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