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or even serve as cheap emergency blood substitutes as one recent undergraduate
iGEM team imagined [1].
These applications will require more sophisticated sensing, actuating and regu-
latory logic than chemical production pathways and may depend on the temporal
history of events experienced by the cell. That is, it may be necessary to “remem-
ber” past inputs rather than simply compute and actuate on the present ones. This
biological circuitry would be more akin to a sequential logical system, a prerequi-
site for complex computation, than a combinational one such as simple Boolean
logic. Regulatory networks with such memory are relatively common in those
natural systems that control, for example, development. Memory of past environ-
ments can also confer a fitness advantage in some situations[2], and synthetic
biological two-state memory switches have been built in both prokaryotes[3]and
eukaryotes [4]. It is clear from the complexity of both natural cellular networks
and the oncoming synthetic biological applications that regulatory circuitry of
some sophistication is required to sense and survive in the outside world.
Systems whose output depends not only on the current inputs but the in-
put history are necessary for sophisticated computation and information stor-
age. While it is unlikely we will use bacteria as super-computers for a number of
reasons, it is interesting to note that the chemical networks that underlie their
behavior are formally capable of Turing-machine like computations [5], [6], [7],
[8]. In these systems, the inputs are generally chemical “inducers”, the machine is
a set of chemical reactions, and the state is generally the stationary-state concen-
trations of the internal chemical species. For synthetic biological applications in
the foreseeable future, we will not likely need to design networks with extremely
large computational power. But scaling to larger applications, with more states
and deeper sequential logics is certainly a future need.
In synthetic biological applications to date, the logic of the designed regula-
tory systems is generally simple and implemented by a handful of genetic “parts”
[9]. In most cases, these elements are the standard set of less than five work-horse
promoters such as the tetracycline and lactose inducible promoters and their cog-
nate transcription factors. These promoters have been studied and even modified
slightly for years rendering them useful for gene expression control. There is an
ever increasing bestiary of naturally occurring bacterial promoters and some ef-
forts to engineer synthetic promoters and transcription factors for more complex
logical functions. However, the heterogeneity in behavior of these devices and
undeveloped rules for their composition make designing larger networks with
these components unpredictable. In almost all applications there are unreasonable
number of cycles of design and testing before the system works as desired.
Design of parts families for which it is relatively simple to construct a new
functionally-independent member from knowledge of the current members has
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