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While proteomics approaches have facilitated the analysis of proteins present in cells and tissues, spatial proteomics have enabled the delineation of proteins’ spatial localization within cells, which has enhanced our understanding of their form and function. Different methods have emerged in the past years to visualize protein positioning, which might vary as a function of cell type, cell cycle progression or disease state. Spatial proteomics has thereby provided unprecedented insight into biological processes not only from a fundamental cell biology perspective, but also from a clinical perspective, to study how protein localization changes in pathogenic cells, which could prove useful for finding biomarkers and developing new therapies. This collection highlights some of the advances of the past year in this rapidly evolving field.
“Protein relocalisation plays a major role in the innate immune response but remains incompletely characterised. Here, the authors combine temporal proteomics with LOPIT, a spatial proteomic workflow, in a fully Bayesian framework to elucidate spatiotemporal proteomic changes during the LPS-induced immune response in THP-1 cells.
The classification of breast lesions as indolent or aggressive to tailor treatment is crucial. Here, the authors use single-cell transcriptomics and multiparametric imaging of a breast cancer mouse model, report distinct tumor-immune features for the two types of lesions, and suggest the role of IL-17 signaling in disease progression.
This Primer discusses methods for characterizing the subcellular location and organization of cellular proteins. The authors outline methods for generating spatially resolved proteomics data and describe tools and considerations for data analysis, before discussing the applications of these methods for investigating protein trafficking, identifying multi-localized proteins and localizing proteins at sub-organelle resolution.
Curtis and colleagues use multiplex spatial proteomics on longitudinal HER2-positive breast tumor biopsies through neoadjuvant therapy and develop a classifier that predicts pathological complete response, using on-treatment CD45 as a single biomarker.
Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics.
APEX-based proximity labeling allows capturing protein interaction dynamics but its high labeling background limits its utility for cytosolic proteins. Here, the authors develop more selective proximity labeling probes, enabling the APEX-based characterization of time-resolved cytosolic protein interactomes.
Proximity labeling is used to map and discover proteins in specific subcellular compartments. Here the authors combine APEX-mediated proximity labeling with organic-aqueous phase separation to identify nuclear, nucleolar, and outer mitochondrial membrane RNA binding proteins.
Mapping neuronal proteomes with genetic, subcellular, and temporal specificity is a challenging task. This study uncovers proteome dynamics in two classes of striatal spiny projection neurons in the mouse brain using a genetically targeted APEX2-based proximity labeling approach.