Systems Biology and Metabolic Engineering in Bacteria - Systems Biology of Metabolic and Signaling Networks - page 341

Chapter 13
Systems Biology and Metabolic Engineering
in Bacteria
Johannes Geiselmann
Abstract Complete metabolic maps are currently available for a number of impor-
tant bacteria. Even when these maps are not experimentally confirmed, the topology
of the metabolic network can be reconstructed from the genome sequence. Despite
this extensive information, we still lack a good understanding of metabolic
adaptations, the interactions of metabolism with gene regulation and tools for
predicting the metabolic consequences of modifying the metabolic or genetic
regulatory network of a bacterium. This chapter will briefly review current methods
for analyzing bacterial metabolism from topological models and steady state
techniques, such as flux balance analysis, to dynamical models using ordinary
differential equations. Even though still incomplete, these models can predict the
metabolic behavior of modified organisms. Using these tools, we can create novel
metabolic pathways or optimize the yield of a desired metabolite. Focusing on
Escherichia coli , we present examples of successful metabolic engineering using
such systems-wide, rational approaches, integrating modeling and experiments.
The conjunction of systems biology to metabolic engineering yields new insights
into the fundamental functioning of the cell and opens the path to the biological
production of a large variety of commodity chemicals.
13.1 Metabolism and Systems Biology
Microbes are relatively simple organisms, they grow in very diverse environments
and their genomes are sequenced. For model organisms, such as E. coli or Saccharo-
myces cerevisiae , the metabolic network is very well mapped and many of the genetic
and metabolic regulatory interactions have been characterized. These organisms
are therefore an ideal study object for systems biology with the dual goal of
J. Geiselmann ( * )
Laboratory of Adaptation and Pathogenicity of Microorganisms, University Joseph Fourier,
CNRS UMR5163, Grenoble, France
e-mail: [e-mail]