Systems metabolomics: from metabolomic snapshots to design principles

Area of Science:

• Biochemistry
• Systems Biology
• Computational Biology

Background:

• Metabolomics is a rapidly expanding technology with diverse applications.
• Understanding metabolism requires integrating various data types and advanced tools.

Purpose of the Study:

• To highlight the system-level understanding of metabolism.
• To explore the potential of multi-omic approaches and integrated tools.
• To advance precision therapies for multifactorial diseases.

Main Methods:

• Integration of metabolic snapshots with metabolic fluxes.
• Utilizing physiological readouts and metabolic models.
• Employing knowledge-informed Artificial Intelligence tools.
• Dissecting metabolic features at cellular and subcellular resolution.

Main Results:

• System-level understanding of metabolism is achievable through integrated approaches.
• Multi-omic strategies offer unprecedented opportunities.
• Development of precision therapies for complex diseases is facilitated.

Conclusions:

• Integrated metabolomics and multi-omic approaches are crucial for understanding metabolic (dis)regulation.
• These advancements provide new avenues for developing precision therapies in diseases like cancer and neurodegenerative disorders.