ArticleLab on a chip2025
Modular, open-sourced multiplexing for democratizing spatial omics.
Article in Lab on a chip, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
9 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.