Biology Reference
In-Depth Information
In the presence of glucose, budding yeast turns on those genes coding for the
enzymes needed to convert glucose to ethanol (a phenomenon known as
glucose
induction
) and turns off those genes needed for galactose metabolism (known as
glucose repression
) (Kuhn et al. 2001; Johnston 1999; Ashe et al. 2000; Jona et al.
2000). The detailed molecular mechanisms underlying these phenomena are incom-
pletely understood at present and under intensive studies (Gasch 2002; Winderickx
et al. 2002). When glucose is depleted,
Saccharomyces cerevisiae
increases its rate
of metabolism of ethanol to produce ATP via the Krebs cycle and mitochondrial
respiration (Gasch 2002; Ronne 1995). This metabolic control is exerted by revers-
ing (or dis-inhibiting) the glucose repression of the genes encoding the enzymes
required for respiration (i.e., oxidative phosphorylation), and this process is known
as
glucose de-repression
(Gasch 2002). The glucose-galactose shift caused massive
metabolic changes in budding yeast characterized by rapid decreases in most RNA
levels within the first 5 min, continuing to decrease up to about 2 h after which they
generally increased (Fig.
9.1
), presumably due to the induction of enzymes capable of
yeast transcripts under this nutritional shift are complex in detail (see Fig.
9.1a-c
)
but reveal a set of regular patterns, including the fact that the average glycolytic
transcripts decreased between 5 and 360 min, whereas the average respiratory
transcripts increased in the same time period (Fig.
12.2a
). These opposite changes
reflect the anticipated metabolic transitions from glycolysis (i.e., fermentation)
to respiration induced by the glucose removal (leading to
glucose de-repression
mentioned above). This observation provides a concrete evidence to support the
hypothesis that the dynamic patterns of the changes in RNA levels (i.e.,
RNA
dissipatons,
RNA trajectories, or RNA waves) in living cells can serve as indicators
or molecular markers for cell functions (see the IDS-Cell Function IdentityHypothesis
9.2 The p53 Network as a Multidimensional “Hypernetwork”
Just as atoms consist of two types of particles,
hadrons
(i.e., heavy particles including
protons and neutrons) and
leptons
(i.e., light particles including electrons), so the cell
can be viewed as consisting of two types of physical objects -
equilibrium structures
or
equilibrons
(e.g., ground-state molecules such as ATP, proteins, RNA, and DNA,
and their complexes) and
dissipative structures
or
dissipatons
(e.g., ion gradients
across the cytosol or cell membranes, mechanical stress gradients in supercoiled DNA
and the cytoskeleton, and cyclically turning-over molecular machines). It appears
reasonable to conclude that the interactions among select sets of
equilibrons
and
dissipatons
that are organized in space and time can account for all cellular functions
(i.e., phenotypes), just as the interactions among hadrons and leptons are known to
account for all atomic structures and their properties in physics (except perhaps the
phenomenon of entanglement (Albert and Galchen 2009)). We may refer to these
phenotypes (e.g., chemotaxis, morphogenesis, cell cycling) as “phenons” to go with
