The recent development of metabolic flux analysis has enabled better understanding of the physiological state of microbes by tracing the molecules involved in cellular metabolism. Typically, however, metabolic flux analysis requires that molecular reactions be lumped together because it is too difficult to map all of the atoms involved in cellular processes. DOE researchers at Penn State University have tackled this problem head on by using techniques from pattern recognition and graph theory combined with conventional metabolic flux analysis and high-performance computing. They can now automatically trace the path of all atoms (C, O, N, P, S, metals and their ions) as these atoms move through metabolic reactions in E. coli. Thanks to the database they developed as part of this project, this process can be applied to other organisms so that researchers can quickly design and analyze isotopic labeling experiments. This new approach will allow researchers to better understand the physiological state of a microbe and then to design or enhance metabolic processes, such as for bioenergy production or carbon sequestration.
Reference: Ravikirthi, P., P. Suthers, and C. Maranas. 2011."Construction of an E. Coli Genome-Scale Atom Mapping Model for MFA Calculations," Biotechnology and Bioengineering, available online February 2011 (DOI: 10.1002/bit.23070). PubMed.
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