262
Chapter 7
Large industrial bioreactors present greater control problems than laboratory reactors, but the
economic consequences of unscheduled excursions in pH and temperature during a large-scale
bioreaction are significant, and the investment in expensive multilevel pH and
T
control adds up to
a substantial part of the total reactor investment. The control algorithms are sometimes quite
complex since the optimum pH and
T
may change during the process - e.g., from an initial biomass
growth phase to a production phase in which a secondary metabolite is produced.
The influence of temperature on the maximum specific growth rate of a microorganism is similar to
that observed for the activity of an enzyme: An increase with increasing temperature
14
) to a certain
point where protein dénaturation starts, and a rapid decrease beyond this temperature. For
temperatures below the onset of protein dénaturation the maximum specific growth rate increases in
much the same way as for a normal chemical rate constant:
A
m u
(7.27)
where
A
is a constant and
E%
is the activation energy of the growth process. Assuming that the
proteins are temperature-denatured by a reversible chemical reaction with free energy change ^G d
and that denatured proteins are inactive, one may propose (Roels, 1983) an expression for
that
is closely related to the Hougen-Watson expression for catalyst activity in classical reaction
engineering:
A
exp
{-Ez i RT)
1 +
B
exp(-A G d
! RT)
(7.28)
Figure 7.10 is a typical Arrhenius plot (reciprocal absolute temperature on the abscissa and log M
on
the ordinate) for
E. coli.
The linear portion of the curve between approximately 21 and 37.5 °C is
well represented by Eq. (7.27), while the sharp bend and rapid decrease of the specific growth rate
for
T
> 39 °C shows the influence of the denominator term in Eq. (7.28). Table 7.4 lists the
parameters found by fitting the model in Eq. (7.28) to the data in Fig. 7.10. The results of the model
calculations are shown as lines on the figure. Esener
et al.
(1981a) also applied Eq. (7.28) to
describe the influence of the temperature on the maximum specific growth rate of
Klebsiella
pneumoniae,
and the resulting parameters are also included in Table 7.5. It is observed that in the
low temperature range the influence of the temperature is stronger for
K. pneumoniae
than for
E.
coli,
i.e.,
E g
is larger for
K. pneumoniae
than for
E. coll
On the other hand, dénaturation of the
proteins is much more temperature-sensitive in
E. coli
than in
K. pneumoniae.
Figure 7.10 also
illustrates the general observation that the maximum specific growth rate is always lower for
growth on a minimal medium compared with growth on a complex medium. The parameter
A
is
smaller for growth on the glucose-minimal medium than for growth on the glucose-rich medium,
and
A
is therefore not a characteristic parameter for the individual strain but rather a function of,
e.g., the medium composition.
Es
is the same for the two media, and it may therefore be a
characteristic parameter for a given strain.
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