Multi-Omics and Genome-Scale Modeling Reveal a Metabolic Shift During C. elegans Aging

Area of Science:

• Systems biology
• Metabolomics
• Aging research

Background:

• Aging involves complex metabolic alterations.
• Understanding metabolic changes during aging is crucial for healthspan research.
• Caenorhabditis elegans is a model organism for aging studies.

Purpose of the Study:

• To investigate age-related metabolic changes in Caenorhabditis elegans using a multi-omics approach.
• To develop and validate an improved Flux Balance Analysis (FBA) method for aging studies.
• To provide a comprehensive resource for studying metabolic dynamics during aging.

Main Methods:

• Multi-omics data collection including transcriptomics and targeted metabolomics at multiple time points.
• Utilizing a whole-genome metabolic model of C. elegans combined with mathematical modeling.
• Development of a novel FBA method integrating biomass production and metabolomics data.

Main Results:

• Standard FBA failed to accurately predict in vivo fluxes and age-related Citric Acid cycle changes.
• The novel FBA method successfully predicted metabolic fluxes and age-associated alterations.
• Detailed case study validated age-associated changes in the Citric Acid cycle.

Conclusions:

• The developed multi-omics and modeling approach provides a robust resource for aging research.
• The novel FBA method enhances the accuracy of metabolic flux predictions in aging studies.
• This study offers insights into the metabolic landscape of normal aging in C. elegans.