Bioreaction Engineering: From Bioprocess Design to Systems Biology
5
fairly elementary to check whether the essentia] mass balances close. It may be inferred from the
opening remark of the paragraph that this is rarely the case. Lack of instrumentation, the inherent
difficulties of making consistent measurements in biological systems (a fact not readily recognized
by researchers of less complex systems), or - less easily forgivable - a lack of insight into the
biochemistry of the process, that leads to omission of a significant metabolic product, may all
contribute to make the raw experimental data unsuitable for analysis. In Chapter 3 we describe
methods to check the consistency of experimental data on the overall conversion of substrates to
metabolic products.
There is no way in which the myriad reactions occurring inside a microorganism can be described
in a consistent set of equations. There is not nearly enough data to do so - many reaction steps are
unknown even qualitatively - and the result would anyhow be useless for practical purposes. Thus
we shall leave out many reaction steps for either one of two reasons: The rate may be so low that it
’does not influence the process during the time of observation, or the rate may be so high compared
to the frequency of our observations o f the system that the step can be regarded as being in
equilibrium. The rate of mutation of a microorganism is hopefully much smaller than the specific
growth rate of the biomass. Thus mutation can usually be neglected when calculating the result of a
batch experiment (an assumption of a
frozen state).
Similarly many steps of a metabolic pathway
can safely be assumed to be in a
pseudosteady state
because other steps are orders of magnitude
slower and represent the
bottlenecks
of the metabolism. To pinpoint fast and slow steps, the concept
of a
time constant
or
characteristic time
for a certain step is useful. We are usually not interested in
processes with time constants on the order of milliseconds (although these may be the key objects
of spectroscopic studies in fundamental biochemistry), nor are we interested in time constants of
several months. In between these very wide limits there is, however, plenty of scope for the
modeling of bioreactions.
In Chapter 5 we describe methods for analyzing the cell factory in detail - in particular we focus on
the pathways that operate at different growth conditions. This involves both application of simple
models where all the reactions are lumped into a few overall pathways and very detailed models
that consider a large number of reactions in the metabolic network. Concepts for quantification of
the fluxes through the different branches of the metabolic network are presented. These concepts
turn out to be very useful to gain further insight into how the cell operates and hereby one may
design strategies for improving the cell factory. This is often referred to as metabolic flux analysis,
and we present several different methods that can be applied for flux analysis.
Concepts from metabolic flux analysis are clearly useful to gain insight into cell function, but it
does not supply any information about how the fluxes are controlled. Here it is necessaiy to include
information about the enzyme kinetics in the analysis. In Chapter 6 we give a short review of
enzyme kinetics, and then move on to metabolic control analysis (MCA), a concept that enables
quantification of flux control within a given pathway. MCA is extensively described in other
textbooks and in research publications, but the short introduction is illustrative for teaching the
concepts of flux control in biochemical pathways and may be helpful as an introduction to the
subject.
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