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PARTISAN REVIEW
More recent efforts have demonstrated technologies that may make
computation possible within a living cell. These technologies, which
include a genetic flip-flop, may form the basic elements of a biological
integrated circuit. Such circuits, however, are not likely to be used to
solve difficult computational problems. More likely, they will be used as
synthetic controllers for living cells. Such biological integrated circuits
may, one day, provide a means to control complex biochemical systems
in much the same way that digital and analog circuits provide a means
to control electronic and mechanical systems.
The genetic flip-flop takes advantage of the properties of the basic
cellular processes involved in gene expression. Gene expression refers to
the process by which cells synthesize proteins from the sequence of A's,
G's, C's, and T's encoded into DNA. Proteins carry out the multitude of
biochemical processes necessary to sustain living cells and tissues. When
one specialized set of proteins (regulator proteins) are bound to DNA,
they can activate or inhibit the synthesis of a gene.
The mechanism of the genetic flip-flop is inspired by the mechanism
of an electronic RS latch. In an RS latch, two transistors are configured
so that each inhibits current flow in the other. Thus, two opposing, but
stable, states are created. In the genetic flip-flop, two DNA elements and
their regulator genes are arranged in the bacterium
Escherichia coli
so
that each regulator gene inhibits synthesis of the other. Thus, either gene
can be produced at a given time, but both genes cannot be synthesized
simultaneously. The system can be switched between the production of
either gene by transiently introducing one or another of two chemicals.
These chemicals are analagous to the set and reset signals of an RS latch.
Importantly, we made use of a mathematical model in designing the tog–
gle to deduce the parameter regimes required for bistability and robust
switching.
Our approach to the construction of a genetic toggle switch repre–
sents a significant departure from traditional genetic engineering in that
we relied primarily on the manipulation of network architecture, rather
than the engineering of proteins and other regulatory elements, to
obtain desired behaviors . Moreover, we integrated the development of a
theoretical model with the construction of an experimental device. We
used the theory to guide the construction of the experimental system,
and, conversely, we used the experimental system to improve and gen–
eralize the model.
In spite of its simplistic description of the events underlying gene
expression, the toggle model is extremely effective in predicting the prin–
cipal qualitative features of the experimental gene network. The rea-
