E. coli chemotaxis is an example of
systems biology’s application (see Figure
1). Chemotaxis is defi ned as directed
motion of a cell toward increasing (or
decreasing) concentrations of a particular
chemical substance. E. coli has been
observed to migrate toward areas of
higher aspartate concentrations through
a series of “runs” and “tumbles.” The
“runs” are linear paths taken by the
bacteria, while the “tumbles” are random
rotations that reorient the bacteria. When
bacteria reach higher concentrations
of aspartate, time spent “running” in
proportion to “tumbling” increases—the
logic being that if higher concentrations
of aspartate are encountered, the
bacterium is on the right track and
should continue in that direction. If the
E. coli fails to detect increasing aspartate
concentrations, the bacterium eventually
exhibits “adaptation,” where it returns to
the baseline “tumble and run” activities.
This ensures that it does not continually
head in the wrong direction.
Conventional medical methods have,
for more than a decade, been able to
identify the enzymes and molecules
involved in the chemotactic pathway.
Despite this, little was known about how
the interactions in this pathway translated
to its known chemotactic behavior,
namely the ability of E. coli to “adapt” in a
large range of aspartate concentrations.
Spiro, et al. [31] used systems methods
in 1997 to provide a mechanistic
explanation. They placed the involved
enzymes into a mathematical equation
(context), considered the relationship
between these enzymes (space),
and analyzed the activities for each
enzyme with the use of computational
tools (time). Increased temporal
detections of aspartate led to reduced
autophosphorylation rate of the aspartate
receptor. This effect reduced the
tumbling rate and increased the running
time. When there was no increased
detection of aspartate, methylation of
the aspartate receptor occurred, which
increased the autophosphorylation
rate and caused the E. coli to return to
prestimulus tumble-and-run activities
(adaptation). Importantly, this adaptive
behavior occurred at different aspartate
concentrations, explaining how E.
coli does not perpetually exist in an
excited state, even at higher aspartate
concentrations.
Similar conceptual breakthroughs have
been obtained with the use of systems
methods in other biological phenomena,
such as bacteriophage lysis-lysogeny
[32], biological oscillations [33,34],
circadian rhythms [35,36], and Drosophila
development [37–39]. In these situations,
the incorporation of context, time, and
space into the equation has provided
information not otherwise obtained
through structural information alone.