Protein localisation and translocation between intracellular compartments underlie almost all physiological processes. The hyperLOPIT proteomics platform combines mass spectrometry with state-of-the-art machine learning to map the subcellular location of thousands of proteins simultaneously. We combine global proteome analysis with hyperLOPIT in a fully Bayesian framework to elucidate spatiotemporal proteomic changes during a lipopolysaccharide (LPS)-induced inflammatory response. We report a highly dynamic proteome in terms of both protein abundance and subcellular localisation, with alterations in the interferon response, endo-lysosomal system, plasma membrane reorganisation and cell migration. Proteins not previously associated with an LPS response were found to relocalise upon stimulation, the functional consequences of which are still unclear. By quantifying proteome-wide uncertainty through Bayesian modelling, a necessary role for protein relocalisation and the importance of taking a holistic overview of the LPS-driven immune response has been revealed. The data are showcased as an interactive application freely available for the scientific community.
T-Lymphocytes
,Cell Membrane
,Cell Nucleus
,Lysosomes
,Transport Vesicles
,Humans
,Leukemia
,Inflammation
,rho GTP-Binding Proteins
,Lipopolysaccharides
,Neoplasm Proteins
,Proteome
,Anti-Inflammatory Agents
,Anti-Infective Agents
,Bayes Theorem
,Lymphocyte Activation
,Proteomics
,Signal Transduction
,Cell Shape
,Immunity
,Antigen Presentation
,Up-Regulation
,Protein Transport
,Algorithms
,Time Factors
,Cell Cycle Checkpoints
,Autophagosomes
,THP-1 Cells