Identification of cellular objective for elucidating the physiological state of plasmid-bearing Escherichia coli using genome-scale in silico analysis

Identification of cellular objective for elucidating the physiological state of plasmid-bearing Escherichia coli using genome-scale in silico analysis

Biotechnology Progress

10.1002/btpr.51

http://dx.doi.org/10.1002/btpr.51

Dave Siak-Wei Ow, Dong-Yup Lee, Miranda Gek-Sim Yap, Steve Kah-Weng Oh

24 December 2008

Ow, D. S.-W., Lee, D.-Y., Yap, M. G.-S. and Oh, S. K.-W. (2009), Identification of cellular objective for elucidating the physiological state of plasmid-bearing Escherichia coli using genome-scale in silico analysis. Biotechnol Progress, 25: 61–67. doi: 10.1002/btpr.51

The presence of multiple copies of plasmids in Escherichia coli could induce a complex cascade of physiological changes known as the metabolic burden response. In this work, the physiological effect of such plasmid metabolic burden on E. coli metabolism was investigated by constraint-based genome-scale flux modeling. We systematically applied three cellular objectives: (a) maximizing growth rate, (b) maximizing plasmid production, and (c) maximizing maintenance energy expenditure to quantify in silico flux distributions. These simulated results were compared with experimental flux information to identify which of these cellular objectives best describes the physiological and metabolic states of plasmid-bearing (P+) E. coli. Unlike the wild-type E. coli cells that have directed the metabolism toward an optimum growth rate under the nutrient-limited condition, the maximum growth rate objective could not correctly predict the metabolic state of recombinant P+ cells. Instead, flux simulations by maximizing maintenance energy expenditure showed good consistency with experimental observation, indicating that the P+ cells are energetically less efficient and could require higher maintenance energy. This study demonstrates that the cellular objective of maximizing maintenance energy expenditure provides a better description of the underlying physiological state in recombinant microorganisms relevant to biotechnological applications. © 2008 American Institute of Chemical Engineers Biotechnol. Prog., 2009

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Bioprocessing Technology Institute