Modular, open-sourced multiplexing for democratizing spatial omics.

模块化、开源的多路复用技术,实现空间组学的普及化

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作者:Zhang Nicholas, Fang Zhou, Kadakia Priyam, Guo Jamie, Vijay Dakshin, Thapa Manoj, Dembowitz Samuel, Grakoui Arash, Coskun Ahmet F
Spatial omics technologies have revolutionized the field of biology by enabling the visualization of biomolecules within their native tissue context. However, the high costs associated with proprietary instrumentation, specialized reagents, and complex workflows have limited the broad application of these techniques. In this study, we introduce Python-based robotic imaging and staining for modular spatial omics (PRISMS), an open-sourced, automated multiplexing pipeline compatible with several biospecimen targets and streamlined microscopy software tools. PRISMS utilizes a liquid handling robot with thermal control to enable the rapid and automated staining of RNA and protein samples. The modular sample holders and Python control facilitate high-throughput, single-molecule fluorescence imaging on widefield and confocal microscopes. We successfully demonstrated the versatility of PRISMS by imaging tissue slides and adherent cells. We demonstrate that PRISMS can be utilized to perform super-resolved imaging, such as super-resolution radial fluctuations (SRRF). PRISMS is a powerful tool that can be used to democratize spatial omics by providing researchers with an accessible, reproducible, and cost-effective solution for multiplex imaging. Specifically, PRISMS is an open-source, automated multiplexing pipeline for spatial omics, compatible with several sample types and Nikon NIS Elements Basic Research software, as well as Python-based biodevices. It performs high-throughput, single-molecule fluorescence imaging both on widefield and confocal microscopes, and can be used to perform super-resolved imaging, such as SRRF. Overall, PRISMS is a powerful tool that can be used to democratize spatial omics by providing researchers with an accessible, reproducible, and cost-effective solution for multiplex imaging. This open-source platform will enable researchers to push the boundaries of spatial biology and make groundbreaking discoveries.

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