Spatiotemporal proteomic profiling of the pro-inflammatory response to lipopolysaccharide in the THP-1 human leukaemia cell line

Journal article

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

Authors: Mulvey, CM; Breckels, LM; Crook, OM; Sanders, DJ; Ribeiro, ALR

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Nature Communications
• Volume: 12
• Issue: 1
• Pages: 5773-5773
• Article number: 5773
• Publication date: 2021-10-01
• DOI: 10.1038/s41467-021-26000-9
• EISSN: 2041-1723
• ISSN: 2041-1723
• Language: English
• Keywords: Genetics; Bioinformatics; Proteomics; Biology; Protein subcellular localization prediction; THP1 cell line; Gene; Cell culture; Immunology; Immune system; Biochemistry; Proteome; Cell biology; Computational biology; Quantitative proteomics; Lipopolysaccharide