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Open-source Photobleacher for Fluorescent Imaging of Large Pigment-Rich Tissues

Murakami, T. C.; Belenko, N.; Dennis, G.; Wang, C.; Siantoputri, M. E.; Maeda, Y.; Pressl, C.; Heintz, N.

2025-02-25 neuroscience
10.1101/2025.02.24.639965 bioRxiv
Show abstract

Fluorescent imaging enables visualization of the specific molecules of interest with high contrast, and the use of multiple fluorophores in a single tissue sample allows visualization of complex relationships between biological molecules, cell types, and anatomy. The utility of fluorescent imaging in human tissue has been limited by endogenous pigments that can block the light path or emit an autofluorescence, thereby interfering with the specific imaging of target molecules. Although photobleachers have been developed to quench endogenous pigments, the lack of customizability limits their utility for a broad range of applications. Here, we present a high luminous-intensity photobleacher that is based on rigorous simulations of illumination patterns using the laws of radiation, along with the framework to maximize bleaching efficiency. This open-source project is designed to help researchers customize and scale according to the tissue types and the research goals. The photobleacher is applicable to both thin tissue slices and large-volume cleared tissue samples to enable serial three-dimensional imaging of postmortem human brain using multiplexed antibody or oligonucleotide probes. SIGNIFICANCE STATEMENTPhotobleaching is an effective technique for quenching endogenous pigments, enabling multiplexed fluorescent imaging of pigment-rich tissues, such as postmortem human samples. While many photobleaching strategies have been proposed, there is no standard guidance on how to design and use a photobleacher. This study introduces a general strategy for designing an effective, scalable, and customizable photobleacher, and proposes a workflow for properly treating tissues with the photobleacher. The technique enables high-contrast molecular visualization in tissues of various sizes, including large volumetric cleared tissues. Our framework will accelerate the quantitative understanding of human molecular anatomy and is applicable to diverse biological fields, including medical diagnostics.

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