Improved flux profiling in genome-scale modeling of human cell metabolism.

ABSTRACT: Understanding human cell metabolism through genome-scale flux profiling is of interest to diverse research areas of human health and disease. Metabolic modeling using genome-scale metabolic models (GEMs) has the potential to achieve this, but has been limited by a lack of appropriate input data as model constraints. Here, we compare the commonly used consumption and release (CORE) method to a regression-based method (regression during exponential growth phase; REGP). We found that the CORE method is not reliable despite being prevalent in human studies, whereas the exchange fluxes determined by REGP provide constraints that substantially improve GEM simulations for human cell lines. Our results show that the GEM-simulated feasible flux space is constrained to a biologically plausible regio

SUBMITTER: Huijer CAM 

PROVIDER: S-EPMC12853175 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature