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with mismatched gates are likely to malfunction. In generating biology's com-
plex genetic regulatory networks, natural forces of selection have resulted in
finely tuned interconnections between the different regulatory components. Na-
ture has optimized and matched the kinetic characteristics of these elements so
that they cooperatively achieve the desired regulatory behavior. In building
de novo
biocircuits, we frequently combine regulatory elements that do not
interact in their wild-type settings. Therefore, naive coupling of these elements
will likely produce systems that do not have the desired behavior.
In
genetic process engineering
, the biocircuit designer first determines the
behavioral characteristics of the regulatory components and then modifies the
elements until the desired behavior is attained. Below, we show experimental
results of using this process to convert a nonfunctional circuit with mismatched
gates into a circuit that achieves the correct response. The experiments focus on
examining and modifying the steady-state behavior of the genetic circuits and
represent the first example of designing robust genetic regulatory components
for use in building reliable biocircuits of significant complexity. Future work
will also consider the dynamic behavior of the circuits. The research reported in
this section represents the beginning of a process to assemble a library of com-
ponents with known and useful device physics, akin to the TTL Data Book for
electrical circuit design. The knowledge of device physics plays a fundamental
role in achieving predictable and reliable biocircuit design.
Figure 7.1 shows the wiring diagram of genetic circuits we constructed to
measure the device physics of two seperate inverters, one based on the
lacI
repressor/p(lac) promoter, and the other based on the
cI
repressor/
λ
P(R)
pro-
moter. Because the
R
2
repressor input to the
P
2
IMPLIES ([NOT x] OR y)
Figure 7.1
Genetic circuit diagram to measure the device physics of an
R
3
/P
3
in-
verter: digital logic circuit and the genetic regulatory network implementation (
P
x
:
promoters,
R
x
: repressors, CFP/YFP: reporters).
