Environmental Engineering Reference
In-Depth Information
2. State of the Science
2.1. Kinetic Models
Kinetic expressions describe quantitative relationships among enzyme concentrations,
substrate concentrations, product concentrations, and rates of product generation. Reliable
kinetic expressions are highly advantageous to the design of cost-effective bioprocesses,
especially in the production of comparatively low-value, high-volume products such as
biofuels and biomaterials. In these cases, in which small losses of substrates to undesired
metabolic byproducts can render a process economically impractical, kinetic models are
essential to the achievement of high substrate conversion efficiency.
2.1.1. Metabolic flux analysis
. In many biosynthetic pathways of interest, simple
understanding of metabolite transformation kinetics (substrate consumption rates,
intermediate lifetimes, and product production rates) is sufficient for reactor design, causing
understanding of individual enzyme kinetics to be unnecessary. In these cases, an approach
known as metabolic flux analysis, or MFA, is convenient to describe the flow of each
metabolite through nodes, or enzymatic transformations, throughout an entire biochemical
network. The result is a comprehensive flux map that shows and quantifies all major anabolic
(synthetic) and catabolic (degradative) processes of interest, as well as points of sensitivity to
perturbation of metabolite or enzyme concentrations, or flux control coefficients, within an
organism [6, 7]. Once such a mathematical framework has been established experimentally,
fluxes of particular metabolites can be predicted over ranges of conditions and flux maps can
be compared among different organisms and growth conditions to reveal optimal process
conditions. In addition, flux maps and comparisons among different flux maps may indicate
possible targets for genetic modifications within the cultivated organism, reveal the outcome
of genetic manipulations that have already been performed, or yield more basic insight
regarding cellular energy metabolism [8].
In the initial development of a metabolic flux map, all theoretically possible enzyme
reactions in the network are considered; postulation of a map appropriate to a particular
process then involves the designation of some reactions as dormant. Metabolic flux analysis
experiments are typically performed in stirred-tank reactors (STRs), also known as
chemostats, to establish steady-state conditions. Concentrations of substrates, intermediates
(where possible), and products are then monitored over time to reveal their interdependences,
and the flux map is refined based on the results. Highly reproducible data are prerequisite for
the confirmation of a postulated metabolic network, however, and until pathways have been
rigorously established, the uniqueness of the proposed network is typically viewed with
caution [9].
For the analysis of large metabolic networks, the use of isotopically labeled substrates
(e.g.,
13
CH3COO-) is often required to trace the flows of compounds present at low
concentrations. The great amount of data generated by such experiments can lead to sizable
computational challenges, because fluxes through individual pathways must then be
calculated by solving large sets of non-linear equations. Fortunately, new quasi-linear algebra
methods have been developed to calculate fluxes from large data sets and, importantly, to
estimate sensitivities to measurement errors [10]. A number of systematic descriptions of
metabolic pathways for E. coli have been developed using these methods [11-13].
2.1.2. Enzymatic kinetic models
. Detailed kinetic models, involving descriptions of
enzyme characteristics, fall into three broad categories. The most detailed and comprehensive
