Molecular Biology of the CellSystems BiologyPeer-reviewed journal article
A morphology and secretome map of pyroptosis
Michael J. LippincottiD, Jenna TomkinsoniD, Dave BunteniD, Milad MohammadiiD, Johanna Kastl, Johannes Knop, Ralf Schwandner, Jiamin HuangiD, Grant Ongo, Nathaniel RobichaudiD, Milad DagheriD, Andrés Mansilla-Soto, Cynthia Saravia-Estrada, Masafumi TsuboiiD, Carla Basualto-AlarcóniD, Gregory P. WayiD
Abstract
Pyroptosis represents one type of Programmed Cell Death (PCD). It is a form of inflammatory cell death that is canonically defined by caspase-1 cleavage and Gasdermin-mediated membrane pore formation. Caspase-1 initiates the inflammatory response (through IL-1{beta} processing), and the N-terminal cleaved fragment of Gasdermin D polymerizes at the cell periphery forming pores to secrete pro-inflammatory markers. Cell morphology also changes in pyroptosis, with nuclear condensation and membrane rupture. However, recent research challenges canon, revealing a more complex secretome and morphological response in pyroptosis, including overlapping molecular characterization with other forms of cell death, such as apoptosis. Here, we take a multimodal, systems biology approach to characterize pyroptosis. We treated human Peripheral Blood Mononuclear Cells (PBMCs) with 36 different combinations of stimuli to induce pyroptosis or apoptosis. We applied both secretome profiling (nELISA) and high-content fluorescence microscopy (Cell Painting). To differentiate apoptotic, pyroptotic and control cells, we used canonical secretome markers and modified our Cell Painting assay to mark the N-terminus of Gasdermin-D. We trained hundreds of machine learning (ML) models to reveal intricate morphology signatures of pyroptosis that implicate changes across many different organelles and predict levels of many pro-inflammatory markers. Overall, our analysis provides a detailed map of pyroptosis which includes overlapping and distinct connections with apoptosis revealed through a mechanistic link between cell morphology and cell secretome.
- organism: human
- assay: proteomics
- research focus: cell type annotation
- research focus: clustering
- approach: machine learning (classical)
- Citations
- 14
- FWCI
- 3.89
- Field percentile
- top 5%
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