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Analyzing Ex Vivo Metabolic Flux in Splenic and Cardiac Macrophages and Bone Marrow Monocytes
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Modeling the energy metabolism in immune cells
Stefan Schuster1, Jan Ewald1, Christoph Kaleta2
1Department of Bioinformatics, Matthias Schleiden Institute, Friedrich Schiller University Jena, Ernst-Abbe-Pl. 2, 07743 Jena, Germany.
Current Opinion in Biotechnology
|March 26, 2021
Summary
This review explores computational models of human immune cell metabolism, focusing on energy pathways and the Warburg effect in macrophages. It highlights how these models aid understanding of immune cell function and responses to pathogens.
Area of Science:
- Computational Biology
- Immunology
- Metabolic Modeling
Background:
- Immune cell activation involves significant metabolic shifts, notably the Warburg effect where glycolysis is upregulated.
- Understanding these metabolic changes is crucial for comprehending immune responses and diseases.
Purpose of the Study:
- To review and discuss various computational modeling approaches for human immune cell metabolism.
- To focus on energy metabolism and explain the Warburg effect using optimization models.
- To highlight the impact of pathogen interactions on immunometabolism.
Main Methods:
- Constraint-based modeling (metabolic reconstruction, elementary modes, flux balance analysis).
- Evolutionary game theory and kinetic modeling.
- Development of a minimal optimization model for the Warburg effect.
Main Results:
- Summarizes diverse modeling techniques applicable to immune cell metabolism.
- Presents a model explaining the Warburg effect in activated immune cells like macrophages.
- Discusses models for M1/M2 macrophage differentiation, neutrophil ROS production, and tryptophan metabolism.
Conclusions:
- Computational modeling offers powerful tools to dissect complex immune cell metabolic processes.
- Further research is needed to address current obstacles and explore future prospects in immunometabolism modeling.
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