Mechanistic pathway modeling for industrial biotechnology: challenging but worthwhile

Mechanistic (also called kinetic) models quantitatively describe dynamic and steady states of biochemical pathways. They are based on network structure (stoichiometry), regulatory information (enzyme inhibitors and activators) and the corresponding reaction kinetics. Although this approach to understand and predict the behavior of biochemical networks has now been in use for almost half a century, its experimental foundation has dramatically changed in the data-rich age of systems biology. Large mechanistic models, ranging up to the genome scale, are now being built and lots of data are available to validate and test them. From the broad scope of possible modeling applications, this survey focuses on the recent developments and central problems of metabolic network modeling in the field of bioprocess development for industrial biotechnology.

Research highlights
► Models of pathway regulation are highly valuable for bioprocess development.
► Both horizontal networks (metabolites, genes) and their vertical coupling must be considered.
► Model detail must be properly adjusted to the goals of investigation.
► Mechanistic models are data hungry but not all parameters are important.
► Modeling efforts are a major driving force for quantitative bioanalytics.