Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

Area of Science:

• Stem cell biology
• Metabolic regulation
• Systems biology

Background:

• Metabolism is a critical stem cell hallmark influencing cell fate, pluripotency, and self-renewal.
• Understanding stem cell metabolism is limited by the absence of genome-scale network models.

Purpose of the Study:

• To develop a systems approach integrating metabolomics data and computational modeling to analyze stem cell metabolism.
• To characterize metabolic differences between naive and primed murine pluripotent stem cells.

Main Methods:

• Integration of time-course metabolomics data with a computational model of metabolism.
• Analysis of metabolic states in naive and primed murine pluripotent stem cells.
• Validation of model predictions using metabolomics data from Lin28-deficient cells.

Main Results:

• One-carbon metabolism, including phosphoglycerate dehydrogenase, folate, and nucleotide synthesis, is a key differentiating pathway between naive and primed stem cells.
• Differential sensitivity to anti-folates was observed between the two stem cell states.
• The pluripotency factor Lin28 was identified as a regulator of one-carbon metabolism.
• Metabolic reactions related to S-adenosyl-methionine production differentially impact histone methylation in naive and primed cells.

Conclusions:

• A network-based approach provides a framework for characterizing metabolic changes in stem cells.
• Metabolic insights can elucidate mechanisms underlying pluripotency and cell fate determination.
• Targeting specific metabolic pathways may offer new therapeutic strategies for stem cell-related conditions.