Funds for Student Research

  • PI:
  • Niclas Decker
  • Project title:
  • Lipids of Longevity: Axolotls Answer to Ageing
  • Funding period:
  • January 2024 – September 2024
  • Funding organization:
  • TU Dresden

Project description:

Ageing is an omnipresent process that directly influences every human life and plays a significant role in our society. Biomedically, understanding the underlying mechanisms of ageing is crucial, as it will pave the way to a healthier and potentially extended lifespan for humans. So far, the majority of research in ageing was focused on elucidating the role of DNA and protein homeostasis. However, lipids, which are closely linked to all metabolic processes, remains relatively understudied in age-related research.

To gain deeper understanding in lipid quality control and lipostasis during ageing, we will compare age-dependent remodeling of the lipidome in two model organisms: (1) in mice, representing short-lived and fast-ageing animals, and (2) axolotls (Ambystoma mexicanum), a Mexican salamander know for its slow ageing and long life span. This project aims to uncover unique lipid signatures associated with the axolotl’s remarkable longevity and resistance to ageing-related changes and further explore the immense toolbox of evolution. The project will be performed in close collaboration with a Regenerative Biology lab led by Dr. Max H Yun, seeking to understand the principles of regeneration and ageing using salamanders.

Involved LMAI members:

Current projects:

Understanding dynamics of lipid metabolism and oxidation in ferroptotic cell death programme

Ferroptosis as a common underlying pathomechanism in tissue ischemia/reperfusion injury

Pan-European Network in Lipidomics and EpiLipidomcis

Dysregulated systemic release of metabolic and bioactive lipids along hepatocyte-VLDL axis

Extension of the Lipidomics technology platform to include targeted high-throughput phenotyping of lipid metabolism and its remodelling

Apply machine learning and deep learning methods to (epi)lipidomics data analysis

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