ACCELERATING DISCOVERY TOGETHER: A COMMUNITY APPROACH TO ANTIBODY VALIDATION AND MULTIPLEXED IMAGING
Multiplexed imaging is a powerful approach for studying the spatial organization and cellular composition of intact tissues at single-cell resolution. The last decade has seen a rapid expansion in the development and commercialization of spatial biology techniques. These methods include technologie...
Saved in:
| Format: | Article |
|---|---|
| Language: | English |
| Published: |
PAGEPress Publications
2025-08-01
|
| Series: | European Journal of Histochemistry |
| Subjects: | |
| Online Access: | https://www.ejh.it/ejh/article/view/4285 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Multiplexed imaging is a powerful approach for studying the spatial organization and cellular composition of intact tissues at single-cell resolution. The last decade has seen a rapid expansion in the development and commercialization of spatial biology techniques. These methods include technologies that probe RNA molecules using imaging-based approaches or spatial barcoding techniques. In addition, proteins may be targeted with antibodies applied to thin sections as well as thick tissue volumes using a variety of approaches. These methods vary in the optical resolution, tissue volume, and number and type of targets (RNA, protein, or both) that can be imaged in a specimen. These technologies have been foundational for the construction of single cell atlases and the study of naturally occurring cancers. Despite their promise, widespread adoption of these methods remains limited by high costs, specialized equipment, and the need for significant technical expertise in tissue processing, reagent validation, image acquisition, and data analysis. To address these barriers, community-driven initiatives led by the Human BioMolecular Atlas Program (HuBMAP) and IBEX Imaging Community are working to streamline and democratize multiplexed imaging. By sharing validated antibody panels, protocols, and best practices, these efforts are reducing the time, resources, and expertise required to generate high-quality spatial data— accelerating discovery through collaboration.
|
|---|---|
| ISSN: | 1121-760X 2038-8306 |