Method of the Year 2024: spatial proteomics

Approaches for profiling the spatial proteome in tissues are the basis of atlas-scale projects that are delivering on their promise for understanding biological complexity in health and disease.

Hundreds of researchers collaborate on maps of the human body and the subcellular realm. As they scout out their next mapping expeditions, they take stock of atlas-making.

Spatial proteomics is advancing rapidly, transforming physiological and biomedical research by enabling the study of how multicellular structures and intercellular communication shape tissue function in health and disease. Through the analysis of large human tissue collections, spatial proteomics will reveal the complexities of human tissues and uncover multicellular modules that can serve as drug targets and diagnostics, paving the way for precision medicine and revolutionizing histopathology.

Multiplexed tissue imaging has transformed tissue biology by revealing cellular diversity and interactions, but the analysis of its massive datasets remains a bottleneck. Here, we provide an overview of computational advancements, discuss current challenges and envision an AI-driven future in which integrated tools streamline analysis and visualization, unlocking the full potential of multiplexed imaging for breakthroughs in spatial biology.

Spatial proteomics has transformed cancer research by providing unparalleled insights into the microenvironmental landscape of tumors. Here we discuss how these technologies have significantly advanced our understanding of cell–cell interactions, tissue organization and spatially coordinated mechanisms underlying antitumor immune responses, and will pave the way for emerging breakthroughs in cancer research.

Spatial mass spectrometry (MS)-proteomics is a rapidly evolving technology, particularly in the form of Deep Visual Proteomics (DVP), which allows the study of single cells directly in their native environment. We believe that this approach will reshape our understanding of tissue biology and redefine fundamental concepts in cell biology, tissue physiology and ultimately human health and disease.

Spatial proteomics holds the potential to transform the study of proteins in situ in complex tissues, but it needs to be integrated with other layers of omics data to gain a holistic view of cellular function, heterogeneity and interactions, and the underlying mechanisms of these processes. I highlight current challenges and emerging opportunities for multi-omic spatial protein profiling to advance basic research and translational applications.

CRISPR screens are untangling molecular mechanisms that drive biological processes with greater precision and detail.

Experimental and computational studies are paving way for a deeper understanding of the dynamic nature of protein–protein interactions.

Advances in multiplexed super-resolution microscopy will usher in the next era of spatial proteomics.

New experimental and computational methods illuminate the history of cell differentiation and its molecular underpinnings.

Detailed biomechanical models of animal bodies can help to tackle questions about how the brain controls movement and bodily interactions with the environment.

Immune–organoid systems will be the next generation of in vitro models.

Advances aim to capture comprehensive, dynamic genome structures in living cells.

Algorithms help to capture macromolecular motion and structural heterogeneity in native cellular environments.