Abstract
Success in synthetic biology depends on the efficient
construction of robust genetic circuitry. However, even
the direct engineering of the simplest genetic elements
(switches, logic gates) is a challenge and involves
intense lab work. As the complexity of biological
circuits grows, it becomes more complicated and less
fruitful to rely on the rational design paradigm,
because it demands many time-consuming trial-and-error
cycles. One of the reasons is the context-dependent
behavior of small assembly parts (like BioBricks),
which in a complex environment often interact in an
unpredictable way. Therefore, the idea of evolutionary
engineering (artificial directed in vivo evolution)
based on screening and selection of randomized
combinatorial genetic circuit libraries became popular.
In this article we build on the so-called dual
selection technique. We propose a plasmid-based
framework using toxin-antitoxin pairs together with the
relaxase conjugative protein, enabling an efficient
autonomous in vivo evolutionary selection of simple
Boolean circuits in bacteria (E. coli was chosen for
demonstration). Unlike previously reported protocols,
both ON and OFF selection steps can run simultaneously
in various cells in the same environment without human
intervention; and good circuits not only survive the
selection process but are also horizontally transferred
by conjugation to the neighbor cells to accelerate the
convergence rate of the selection process. Our directed
evolution strategy combines a new dual selection method
with fluorescence-based screening to increase the
robustness of the technique against mutations. As there
are more orthogonal toxin-antitoxin pairs in E. coli,
the approach is likely to be scalable to more complex
functions. In silico experiments based on empirical
data confirm the high search and selection capability
of the protocol.
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