Engineered Post-Translational Logic (PTL)
Samantha C. Sutton , Sara E. Neves , Lauren W. Leung , and Drew Endy

Division of Biological Engineering and
Abstract

Department of Biology, Massachusetts Institute of Technology
Modeling as a Design Tool
Current synthetic biological circuits make use of protein-DNA and RNA-RNA
interactions to control gene expression in bacteria. Systems that rely on the regulation of
gene expression are relatively slow and unsuitable for many applications. Here, we
describe our work to engineer synthetic biological systems in yeast using posttranslational modifications of proteins to define system state and control cell function;
such systems should have faster performance time and enable a wider range of
applications. We have specifically chosen to focus on building phosphorylation-driven
protein circuits. We modeled a specific instance of a post-translational circuit using
methods such as Lyapunov exponents, and showed that the circuit should behave as
desired within a large parameter space. We developed a set of peptide tags that can be
used to drive the phosphorylation of a chosen substrate by a desired mitogen-activated
protein kinase (MAPK). Each phosphorylation event alters a substrate output activity,
such as translocation, degradation, or other binding event. These tags were developed
using the Phospholocator – a construct whose phosphorylation-mediated translocation is
controlled by MAPK activity. Specifically, MAPK phosphorylation of the Phospholocator
nuclear localization sequence (NLS) controls recognition of the NLS by cellular import
machinery. The Phospholocator serves three purposes: to determine the docking sites of
MAPKs of interest, to measure the in vivo activity of such MAP Kinases, and to serve as
a first set of post-translational logic parts. Currently, we have built a version of the
Phospholocator that is targeted by Cdc28; our next step is to build Fus3-, p38-, and Hog1activated instances.

Building and Testing a PTL Device
Example PTL Device: Flip-Flop
In1
Necessary Components of a PO4-MAPK Part
MAPK binds here
Out1
Kinase
MAPK adds phosphate group here
P
Docking site
In2
State 1
P
P
0
0
1
1
P
Kinase
In2
Kinase
Out1
NLS
Substrate
Protein
State 2
Out2
hold
hold
0
1
1
0
not allowed
0
1
0
1
PO4 site
Out2
Kinase
In1
NLS
P
Kinase
P
P
Kinase
When unphosphorylated: Import machinery binds the NLS and brings the device
into the nucleus.
When phosphorylated: Import machinery cannot bind the NLS, and thus the device
remains in the cytosol.
The Phospholocator
Differences between PDL and PTL Flip-Flops
PDL Flip-Flop
PTL Flip-Flop
Cdc 28 Docking site
Swi5 NLS
PO4 site
Swi5 NLS
YFP
+
-gal
Kinase
Why Post-Translational Logic?
Kinase
Our Goal: Engineering Biology
Physics
• Unlimited species concentrations
• Use hill coefficient to describe
cooperativity
• Can make Pseudo-steady state
assumption about protein-DNA
binding
Electrical Engineering
P
k1
• Protein-DNA (Transcriptional) logic (PDL)
– Engineered around gene expression
– Easier to engineer
– Slow response time (hours)
– Uses one subset of cellular functions
+
P
k1
P
k3
+
k2
# of fixed points
An Example of a PTL Device
Activity
of
P
Kinase
Kinase
Activity of
Choice of Modification and Enzyme
+
3
k1, k3 fixed
Activation
Nuclear localization
Degradation
Binding
Powerful tool. Directly
control kinase activity
PTL Flip-Flop is Robust to Concentration Fluctuations
5
Inactive
Cons
May involve
engineering
3o
structure
Good visualization, local Must be compatible with
expertise, previous
translocation machinery,
examples of modular
screen sensitivity
engineering
Good assays, well
studied system, good
screen
No examples of modular
engineering,
confounding fluctuations
in expression
Well-studied, local
expertise
Less interesting function
• Enzyme of choice: MAP Kinase
• Signaling pathways
• Well-studied
•Yeast has two well-known MAPKs: Fus3, and Hog1
• Examples of modular MAPK docking sites
Phospholocator-PO4
• We used Matlab to vary k1, k2, k3, k4 over biologically relevant values, and
then used fsolve to locate the fixed points. Shown above is the number of
fixed points obtained for different values of k2 and k4 (k1 = k3 = 10-4 (nM s)-1).
•Three fixed points can indicate a functional flip-flop, while one cannot.
• We computed the Jacobian of the system evaluated at each fixed point, and
determined the corresponding eigenvalues.
•Two fixed points are asymptotically stable because they have all negative
eigenvalues.
•The remaining fixed point is an unstable fixed point because it has one
positive and three negative eigenvalues, indicating it has 3D stable and
1D unstable manifolds.
15000
10000
Verification of Phosphorylation
1
k2
Active
[ ]o
divergent
(high
Lyapunov
exponent)
5000
Nocodazole arrest (G2/M):
cytosolic
• Cdc28-Cln2 is active during late S and G2/M phase in yeast. In cells arrested
with nocodazole, Cdc28 should be active, and phosphorylate the
Phospholocator. The Phospholocator should then be cytosolic.
• Cdc28-Cln2 is inactive during G1 phase in yeast. In cells arrested with
pheromone, Cdc28 should be inactive, and unable to phosphorylate the
Phospholocator. The Phospholocator should then be nuclear.
Nocodazole
Pheromone
• Modification of choice: phosphorylation
•Best studied phospho-mediated functions
Pros
P
k4
k4
Function
Pheromone arrest (G1/S):
nuclear
k4
PTL Flip-Flop is Robust to Parameter Fluctuations
• Post-translational logic (PTL)
– Engineered around protein modifications
– Difficult to engineer
– Fast response time (seconds)
– Explores new set of applications
PTL Inverter
.
P
• A and B are active until doubly phosphorylated by the other.
• Non-processive phosphorylation gives rise to the requisite ultrasensitive
behavior of pink and green proteins
• Conservation of species means that we are dealing with a 4-D system.
Types of Intracellular Circuits
Activity Out
P
k3
+
k2
+
Synthetic Biology
Activity In
Cell-Cycle Dependent Localization in Yeast
Flip-Flop Model
+
Biology
• Capped species concentrations
• Must generate cooperativity in new
ways
• Cannot make pseudo-steady state
assumption anywhere.
Uses of the Phospholocator
• To build sets of post-translational logic (PTL) parts.
• To determine the docking site and p-motifs of MAP Kinases of interest.
• To detect the activity of MAP Kinases.
Phospholocator
+
–
–
+
–
–
•We ran a SDS-PAGE gel of crude
yeast lysate from cells arrested with
nocodazole or pheromone.
•The Phospholocator was detected
using anti-GFP antibody (gift from
Bob Sauer).
•Phosphorylated construct runs
slower than non-phosphorylated
construct.
Conclusions
•We have shown that a PTL flip-flop will theoretically behave as expected over
a wide range of parameter values.
•We have specified a system of PTL based on MAPKs and translocation
•We have designed a testing scaffold for identifying and characterizing docking
and phosphorylation motifs, and are working on a first set of motifs.
•We have built a working instance of a PTL device: the Phospholocator
Future Directions
• Build a Fus3 activated instance of the Phospholocator
• Build a simple inverter
• Develop a transcription-based localization assay for directed evolution of motifs
Active
0
Inactive
-5000
-5000
0
Ao 5000
[ ]o
10000
15000
convergent
(low
Lyapunov
-20 exponent)
• Our three stable points define a 2D plane in 4D space. We transformed
coordinates so the plane was perpendicular to two axes, and thus we could
work in two dimensional space.
• Varying initial concentrations of the two kinases, we measured the ratio of the
change in initial concentration to the change in equilibrium concentration. This is
known as the method of Lyapunov exponents. Larger ratios indicate a
separatrix, which is the boundary of a domain of attraction.
• We can use this map to determine:
1.The range of concentrations over which our flip-flop will hold state.
2.The amount of stimulus needed to switch states, or “flip.”
Acknowledgements
@Cambridge: Pam Silver, Mike Yaffe, Doug Lauffenburger, Gerry Sussman, the Endy lab,
the Bob Sauer lab, the Chris Kaiser Lab, the Steve Bell Lab .
.
@Berkeley: Alejandro Colman-Lerner, Jeremy Thorner, Kirsten Benjamin, Richard Yu, Roger
Brent, Gustavo Pesce
Funding: Howard Hughes Medical Institute, National Institute of Health, Merck & Co., Inc.
“Our Goal” Images from:http://chemcases.com/cisplat/ cisplat01.htm ; http://www.nature.com/nsu/030421/ 030421-14.html
http://www.northern.wvnet.edu/~tdanford/ icons/CELL.JPG; Ricarose Roque
Transcriptional Modeling example from Gardner et al, Nature. 2000 Jan 20;403(6767):339-42.