Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling.
Authors | |
Keywords | |
Abstract | Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. |
Year of Publication | 2017
|
Journal | Cell Rep
|
Volume | 21
|
Issue | 10
|
Pages | 2965-2977
|
Date Published | 2017 Dec 05
|
ISSN | 2211-1247
|
DOI | 10.1016/j.celrep.2017.07.048
|
PubMed ID | 29212039
|
PubMed Central ID | PMC5752146
|
Links | |
Grant list | R01 GM107536 / GM / NIGMS NIH HHS / United States
R24 DK092760 / DK / NIDDK NIH HHS / United States
|