CRC TRR 353

Regulation of cell death decisions
Subproject Prof.'in Dr. Garcia Saez: Death pores: decision-making at the execution step of regulated necrosis

The death of individual cells is a frequent event in a mammalian organism, and aberrations in cell death may have severe consequences to human health. In many, probably most instances, cell death is regulated, i.e. occurs as the result of cell-intrinsic signaling. The best-investigated form of regulated cell death, apoptosis, has been known for about 50 years. Additional, distinct cell death modalities have been discovered more recently, including necroptosis, pyroptosis, ferroptosis and oxeiptosis. A multitude of signaling steps in cell death processes have been described. However, with the multitude of different cell types investigated, with the intersection of cell death pathways with other signal transduction events and the separate but similar activities of cell death signaling components, it has been impossible to date to derive a comprehensive conceptual or mechanistic picture of cell death in the human body. We believe that a critical issue on the way to understanding cell death is to appreciate how a cell makes the decision to die. This decision has a number of levels, and two important aspects are the molecular decision to undergo a specific form of cell death, and the decision to make the choice of cell death modality. These two key points will form the focus of this program.

- Project funding: 1st funding period: 01/2023 - 12/2026
- Spokesperson: Prof. Dr. Brunner
- Participating Faculties: Faculty of Mathematical and Natural Sciences
- KPA: Ageing-associated Diseases
- Relevant SDGs: Good Health and well being (3)
- Applicant University: University Konstanz
- Co-applicant Universities: Albert-Ludwigs-University Freiburg, Technical University Munich (TUM)
- Partner: The Austrian Science Fund (FWF), Medical University Innsbruck, University Stuttgart, University of Cologne, Helmholtz-Centre Munich - German Researchcenter for Health and Environment, MPI for biological intelligence

Further information about this SFB can be found here: SFB TRR 353 homepage

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