Synthetic Biology Parts, Devices and Applications

200 10 Programming Gene Expression by Engineering Transcript Stability Control and Processing in Bacteria

Drawing on the design principles gleaned from naturally occurring metabolic

control circuits [94, 95], one approach to optimizing p-AS production would be

to implement dynamic controllers that operate as a function of flux through

p-AF, a cell-permeable intermediate. Circuits comprised of static rREDs and

dynamic p-AF-responsive aREDs could be constructed to program flux through

the pathway. In principle, there are many possible control topologies and corre-

sponding RNA-based feedback architectures that could be implemented to

enable high levels of p-AS production. An important aspect of this work will

therefore be to identify and experimentally validate the feedback architectures

that can be implemented across the tunable biochemical parameter ranges.

Finally, results showing the importance of robust folding to the design of

functional rREDs and aREDs are consistent with the idea that kinetically driven

co-transcriptional folding pathways significantly impact cellular RNAs [96].

Systems-level

design goal

Genetic

device

design

goals

Functional

design

Physical

implementation

Model

refinement

Assembly

and

verification

Dynamic

TSC devices

Static

TSC devices

Predictive

mechanistic

models

Mechanistic

models

0

1

Biochemical

understanding

Engineer

components

Biophysical models

for designing

transcripts

Biochecmical models

for predicting

device outputs

Sets of devices

generating

targeted outputs

Ta rgeted

device

outputs

Biochemical

models for identifying

component specifications

RNA

folding

models

(2.1)

(4.1)

(2.4)

(1.x; 3.5; 4.1)

asRNA/sRNA (2.3)

aREDs (2.4)

Riboregulators (3.4)

Riboswitches (3.4)

asRNA/sRNA (2.3)

UTR 1°/2° (2.2; 4.2)

rREDs (2.4)

Seq/Codon (3.3)

In vitro

selection

Systems-level

functions

RNA RNA

Figure 10.4 Model-driven design workflow for engineering gene expression with TSC. A basic

systems-level model is used to identify goals for genetic device outputs. These goals inform

the creation of a mechanistic model based on biochemical understanding, which is used to

identify component specifications needed for device function. Components are then

engineered and/or evolved with in vitro selection to meet the design specifications. Transcript

design methods employing biophysical models of RNA folding are employed to enable the

assembly of individual RNA components into functional devices. The mechanistic model is

then refined to account for engineered component characteristics used to predict device

outputs. Systems-level functions are obtained through the assembly of multiple static and

dynamic RNA devices.