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Immunometabolic Circuits in Infection for Advancing Host Directed Therapies
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Systems-based approaches to study immunometabolism.

Vinee Purohit1,2, Allon Wagner3,4, Nir Yosef3,4

  • 1Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.

Cellular & Molecular Immunology
|February 5, 2022
PubMed
Summary
This summary is machine-generated.

Investigating immune cell metabolism using systems biology approaches is complex. This review explores mathematical modeling for systems immunometabolism, aiding future research in this growing field.

Keywords:
GSMMImmunometabolismMetabolic modelingMetabolic techniquesSystems biology

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Area of Science:

  • Computational biology
  • Immunology
  • Systems biology

Background:

  • Single-cell RNA-sequencing (scRNA-seq) reveals cellular complexity.
  • Investigating immune cell metabolism (immunometabolism) is challenging due to cell diversity, sparsity, dynamic metabolism, and tissue specificity.
  • Systems biology offers a framework for understanding complex biological systems.

Purpose of the Study:

  • To define the systemic nature of immunometabolism.
  • To summarize cell- and system-based approaches in immunometabolism research.
  • To introduce mathematical modeling for interrogating metabolic changes in immune cells at a systems level.

Main Methods:

  • Review of existing literature on systems immunometabolism.
  • Discussion of cell- and system-based investigation strategies.
  • Introduction to mathematical modeling techniques for metabolic analysis.

Main Results:

  • Immunometabolism is a complex, systemic process.
  • Various approaches, including mathematical modeling, can be applied to study immune cell metabolism.
  • Current metabolic modeling techniques have both applications and limitations.

Conclusions:

  • Systems-oriented studies of metabolism are becoming central to immunology.
  • Understanding current systems immunometabolism approaches is crucial for researchers.
  • This knowledge will facilitate resource utilization and advance the field of immunometabolism.