UCSF UCB Championship Poster

Sense & Secrete-Ability
UCSF & UCB
Eleanor Amidei, Sabrina Chu, Shuaixin He, Jessica Hsueh, Derrick Lee, Jeffrey Shu, Eric Wong, Robert Wong, Ianto Lin Xi, George Yip
Advisors: Kara Helmke, Wendell Lim, Hyun Youk
Mentors: Jonathan Asfaha, Alain Bonny, Michael Broeker, PJ Buske, Kevin Hartman, Ben Heineike, Zairan Lu, Justin McLaurin, Leo Morsut, Anusuya Ramasubramanian
Results
Background
Stimulus
Communication
Variable cell response
Community response
The goal of our project is to engineer a synthetic eukaryotic circuit
that models variable individual responses and collective behavior
of the population.
Building a synthetic collective
Our plan is to construct a circuit in S. cereOverview
visiae that measures both INDIVIDUAL
The
stimulus
will
directly
drive
a
reporter
to
read
and COMMUNITY responses to a stimulus. A out INDIVIDUAL RESPONSE.
Individual
A
Community
STIMULUS
Biobricks Circuit
COMMUNICATION
RESPONSE
SECONDARY SIGNAL
BioBricks Circuit
3
DOXYCYCLINE
1
ALPHA FACTOR
2
communication SIGNAL that can be sensed and
secreted by all cells in the population, eliciting a
COMMUNITY RESPONSE with a different
reporter.
B
Overview
RESPONSE
B The stimulus will also control the output of a
4
Our
STIMULUS
is
controlled
by
the
presence
of
the
1
drug doxycycline and production of transcription
factor rtTA. When these components bind they
drive genes following the pTET promoter.
The below data from our flow cytometry
analysis shows two distinct populations of
expression.
By rearranging the flow cytometry data and separating
the GFP and RFP output, we can see that although we
have two different individual responses, the community
responses are the same.
Individual
Individual Response
In nature, we see examples of cells in a local population that express a
varying range of individual responses to a given stimulus, which may be due
to differences in extracellular environment or intercellular makeup. Despite
this variation, cells often coordinate to elicit a collective response as a
population, usually by developing unique social behaviors through
cell-to-cell communication [1].
Community
Community Response
INDIVIDUAL RESPONSE, GFP output, is plotted on
the y axis while COMMUNITY RESPONSE, RFP
output, is plotted on the x axis.
Low Individual Response Strain
High Individual Response Strain
The differing GFP expression levels but similar RFP expression indicate a converging response different
from when the populations respond individually. Therefore we confirmed our predictions and
achieved our goal of building a cellular circuit that measures individual and collective behavior.
Modeling with Kilobots
Kilobots are small robots that can be programmed to produce complex community behaviors using electronic signals to
communicate with each other [4]. The Kilobots provide a physical macroscopic model of our yeasts’ sense-and-secrete
circuits that can be used to look for new behaviors when tuning communication parameters.
2 The stimulus drives our INDIVIDUAL RESPONSE,
production of GFP.
The stimulus will also drive the production of an
3
endogenous yeast SIGNAL: alpha factor. All cells in
the population can sense and secrete alpha factor.
To
read
out
this
COMMUNITY
RESPONSE,
we
4
used an alpha factor responsive promoter (AFRP)
to drive the fluorescent reporter RFP.
Measuring Collective Behavior
Methodology
We test the ability of our circuit to produce convergent We used two types of promoters endogenous to S. cerevisiae:
behavior despite synthetically engineered variation 5 constitutive promoters and 11 alpha-factor responsive
promoters (AFRPs) [2, 3].
by mixing our circuits with the lowest and highest
2 This synthetically engineered
individual response (2).
See the Parts Registry
variation is achieved by altering constitutive pTEF1
for more information:
promoter mutants to drive rtTA.
BBa_K1346000 4.5
4
3
Final: all converge to
same state and color
See our wiki for examples of more programmed behaviors.
Exploring Communication ParamEters
Negative Feedback
Positive Feedback
4
2.5
3.5
3
2.5
2
1.5
BBa_K1346013
1
Mean GFP (AU)
Mean GFP (AU)
4
x 10
Initial: varied expressionlevels and color
Our goal is to incorporate communication motifs that tune communication parameters to
potentially model other complex systems, such as population divergence.
Promoter Characterization
x 10
This example shows a converging
behavior similar to our project.
Control
ASG7
YDR124W
PRM6
AGA1
CLG1
PRM2
PCL2
ECM18
SAG1
PRM1
2
1.5
1
BAR1
0.5
0.5
0
1.Mix strains with different
autonomous responses
(GFP)
2.Induce the co-culture
pTEF1
m3
m6
m7
pTEF1 Mutants
0
m10
Constitutive Promoters
0 0.5 1
10
100
[alpha](nM)
1000 3000
Inducible Promoters
The promoters were placed in front of GFP and characterized
using flow cytometry to measure fluorescence, then some
were selected to drive our circuit’s individual response.
3.Measure the community
response (RFP)
Individual Response
4
x 10
Mean GFP (AU)
10
We expect that through intercellular signaling and
4 the two populations’
the community circuit (4),
community response will look indistinguishable,
as measured by flow cytometry.
N/A
8
Control
pTEF1
pTEF1(m3)
pTEF1(m6)
pTEF1(m7)
pTEF1(m10)
6
4
2
0
0
0.03 0.06 0.09
0.3
0.60.9
[Doxycycline](µg/µl)
3
6 9
30
60
We measured the variability of
our circuits’ individual response
with differing pTEF1 promoter
mutants driving rtTA (2)
2 .
When induced with different
levels of doxycycline (1)
1 , the
circuits had the most variability
near a doxycycline concentration of 0.3µg/µl.
We can increase Bar1 secretion, a protease that
degrades extracellular alpha factor, in order to
limit signal range.
We can increase alpha factor secretion and alpha
factor receptors in order to amplify the signal
locally.
We have constructed tunable feedback loops utilizing AFRPs and have done preliminary testing, but have yet to acquire
any conclusive data. Prior work and modeling indicates Bar1 secretion and strong positive feedback may lead to more
complex behaviors such as divergence [1].
References
1. Youk, H., & Lim, W. A. (2014). Secreting and Sensing the Same Molecule Allows Cells to Achieve Versatile
Social Behaviors. Science (New York, N.Y.), 343(6171), 1242782. doi:10.1126/science.1242782
2. Nevoigt, E., Kohnke, J., Fischer, C. R., Alper, H., Stahl, U., & Stephanopoulos, G. (2006). Engineering of promoter replacement cassettes for fine-tuning of gene expression in Saccharomyces cerevisiae. Applied and Environmental Microbiology, 72(8), 5266–73. doi:10.1128/AEM.00530-06
3. Roberts, C. J. (2000). Signaling and Circuitry of Multiple MAPK Pathways Revealed by a Matrix of Global Gene
Expression Profiles. Science, 287(5454), 873–880. doi:10.1126/science.287.5454.873
4. Rubenstein, M., Ahler, C., & Nagpal, R. (2012). Kilobot: A low cost scalable robot system for collective behaviors. 2012 IEEE International Conference on Robotics and Automation, 3293–3298. doi:10.1109/ICRA.2012.6224638
Acknowledgments
We would like to thank
Hyun Youk and Wendell
Lim for inspiring and assisting us in our project.
We would also like to thank
George Cachianes.
Check out our website
for more information:

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