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Spatial biology, a field pioneered by Dr. Mike Doyle, has been recognized now twice by Nature as its "Method of the Year" – first for spatial transcriptomics in 2020, and now for spatial proteomics in 2024. This achievement has never happened with any other methodology, underscoring the transformative impact of this approach in biomedical research.

Dr. Doyle, the current VP of Research and Economic Development and professor of biology, gives an overview:

The two major applications of spatial biology are spatial transcriptomics, the mapping of the locations of gene expression activity within high-resolution images of cells and tissues, and spatial proteomics, which accomplishes the same goal for the mapping of proteins. Imagine, if you will, a bustling city, vibrant with life. In this city, we have buildings, parks, roads, and myriad human activities occurring within and around these structures. Now, suppose we represent this city as biological tissues, and human activities as biological functions, specific protein locations, or gene expression. In the past, we could study the architecture (structures) and the activities (functions) separately but not both simultaneously. That's where spatial biology comes in—this approach allows us to explore the 'city' and the 'activities' in their totality, within the same context, giving us a panoramic view of life's complex symphony.

Instead of examining a biological sample and its functions separately, we combine both. For example, we map the expression of genes or the locations of proteins onto the structural images of cells and tissues. This allows us to see where and when exactly within a tissue or organ certain biological functions are active. 

Spatial proteomics, the focus of this year’s award, provides unprecedented insights into protein expression and localization within tissues. By combining advanced imaging techniques with mass spectrometry, researchers can visualize and quantify protein activity with high resolution, affording remarkable new observations of complex biological structures.