BIOT 183 |
| Nonstationary metabolic flux analysis (NMFA) is at present very computationally intensive, especially for large reaction networks. We applied elementary metabolite unit (EMU) theory to NMFA, dramatically reducing computational difficulty. We also introduced block decoupling, a new method that systematically divides EMU systems of equations into smaller subproblems. These improvements led to a 1500-fold reduction in computational times, enabling an entirely new and more complicated set of problems to be analyzed with NMFA. We simulated nonstationary GC/MS measurements for a large reaction network representing E. coli metabolism that were then used to estimate parameters and their confidence intervals. We found that nonstationary measurements made concentration estimation possible for several metabolites even in the absence of metabolomic data. We applied EMU-based NMFA to experimental nonstationary brown adipocyte measurements and successfully estimated fluxes and some metabolite concentrations. By using NFMA instead of traditional MFA, the experiment required 6 hours instead of 50. |
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Emerging Technologies: Systems Biology
8:00 AM-11:00 AM, Wednesday, August 22, 2007 BCEC -- 108, Oral
Division of Biochemical Technology |