Whole Cells - Molecular Theory of the Living Cell - page 390

Consequently, the time-dependent patterns of the changes in RNA levels (i.e., RNA
trajectories or RNA waves) qualify as species (or tokens) of intracellular dissipative
structures (IDSs) (Ji 1985a, b, 2002b) as already indicated.
S. cerevisiae has the capacity to metabolize both glucose and galactose but
prefers the former as the carbon and energy source over the latter. In the presence
of glucose, the organism turns on those genes coding for the enzymes needed to
convert glucose to ethanol, the phenomenon known as glucose induction , and turns
off those genes needed for galactose metabolism, which is known as glucose
repression (DeRisi et al. 1997; Johnston 1999; Ashe et al. 2000; Jona et al. 2000;
Kuhn et al. 2001). The detailed molecular mechanisms underlying these phenomena
are incompletely understood at present (Gasch and Werner-Washburne 2002;
Winderickx et al. 2002). When glucose is depleted, S. cerevisiae increases its rate
of metabolism of ethanol to produce ATP via the Krebs cycle and mitochondrial
respiration (Ronne 1995; Gasch 2002; Winderickx et al. 2002). This metabolic
control is exerted by reversing the glucose repression of the genes encoding the
enzymes required for respiration (or oxidative phosphorylation). This process is
referred to as glucose de-repression (Gasch 2002).
The fact that the trajectory of the average glycolytic RNA molecules decreases
(presumably because these transcripts are no longer needed in the absence of glucose
as the substrate) while that of the average respiratory RNA molecules increases
(presumably because these transcripts are needed to produce the corresponding
enzymes to metabolize ethanol left over from previous glucose fermentation and
the new substrate, galactose) during the first 3 h in Fig. 12.2 provides a strong
experimental support for the notion that the intracellular dissipative structures (e.g.,
the RNA gradients in the time dimension under discussion) are correlated with cell
functions, thus providing one of the first experimental evidences for Step 10 in
Fig. 12.4 (or Step 20 in Fig. 2.11 ) . Thus, IDSs reflect metabolic functions (see the
opposite changes in the glycolytic and respiratory RNA trajectories in Fig. 12.2a ),
leading to the hypothesis that IDSs can be employed as reliable molecular signs (or
signatures) for the metabolic and functional states of the living cells. This makes
RNA trajectories or waves measured with microarrays convenient biomarkers
for monitoring the functional state of metabolic pathways in whole cells whose
de-regulation can lead to various diseases, including cancer (Watters and Roberts
2006). These observations have motivated me to formulate the IDS-Cell Function
Identity Hypothesis as follows:
There is a one-to-one correlation between IDSs and cell functions because IDSs are the
immediate driving forces for all cell functions. (12.1)
The question as to what regulates the intracellular levels of RNA is not simple to
answer because of the complex interactions taking place among the myriad
components of the cell (see Fig. 12.27 for a further discussion). It may well turn
out that what ultimately regulates the intracellular concentrations of any
metabolites, including RNA molecules, is the living cell itself in interaction with
its environment (see Step 9 in Fig. 12.4 or Step 19 in Fig. 2.11 ) and not any
component processes of the cell metabolism such as transcription or translation