(419b) OM-FBA: Integrate Multi-Omics Data to Flux Balance Analysis to Better Understand Cell Metabolism

omFBA: Integrate Multi-omics Data to Flux Balance Analysis to Better
Understand Cell Metabolism

Weihua Guo, Xueyang Feng*

Department of Biological Systems Engineering, Virginia Polytechnic
Institute and State University, Blacksburg, VA 24060

Constraint-based metabolic modeling such as flux
balance analysis (FBA) has been widely used to simulate cell metabolism. Thanks
to its simplicity and flexibility, numerous algorithms have been developed
based on FBA and successfully predicted the phenotypes of various biological
systems. However, their phenotype predictions may not always be accurate in FBA
because of using the objective function that is assumed for cell metabolism. To
overcome this challenge, we have developed a novel algorithm, namely omFBA, to integrate multi-omics data (e.g. transcriptomics, proteomics and metabolomics) into FBA to
obtain omics-guided objective functions with high accuracy. In general, we
first collected multi-omics data and phenotype data from published database
(e.g. GEO database) for different microorganisms such as Saccharomyces cerevisiae. We then developed a ?Phenotype Match?
algorithm to derive an objective function for FBA that can lead to the most
accurate estimation of the known phenotype (e.g. biomass yield). The derived
objective function was next correlated with multi-omics data via regression
analysis to generate the omics-guided objective functions, which will be
further used to accurately simulate cell metabolism. We have applied omFBA in both E. coli
and S. cerevisiae and found that the
ethanol yield and biomass yield can be accurately predicted in most of the
cases tested (~70%) by using transcriptomics data. In
addition, omFBA could be incorporated with other
existing algorithms easily by using the omics-guided objective functions.
Compared to current approaches that attempt to integrate omics data to FBA
(e.g. ROOM), omFBA can be more advantages in
extendibility and comparability.