w w w. n a t u r e . c o m / n a t u r e | 1
SuPPLementarY InFormatIondoi:10.1038/nature09679
Supplemental Figure 1Regot et al.
Figure S1. Illustrative example of the method for designing distributed biological computation. a. General pattern of connections between cells for multicellular circuits.b. Truth table defining the behavior of a multiplexer circuit. c. Full Boolean function that express the relationship between the logic inputs x1, x2, x3 and the logic output O according to the truth table. d. Simplified version of the Boolean function f describing the same truth table. The analytical expression of the Boolean function determines that the circuit can be implemented using two different sets of engineered cells ρ1 and ρ2. e. Implementation of the circuit with direct mapping between the terms of the Boolean function and the engineered cells. Here ρ1={C11, C12} and ρ2={C21, C22}. The tables determine the logic implemented in each cell. Here rhombus represents the external inputs x1, x2, and x3, red and blue circles represent the internal wiring implemented by the production of a diffusible molecule, and squares are the final output. f. A mixed implementation, where the set ρ1 is a direct mapping of the terms from the Boolean function whereas in ρ2 all the terms have been condensed in a single cell. g. Circuit implementation where both sets ρ1 and ρ2 are implemented by a single cell in each case. Figure S2. Number of possible Boolean functions versus the number of different cells required for their implementation. Each graph represents the number of (nonnull) functions that can be implemented with a defined number of engineered cells that receive 2-inputs (a) and 3-inputs (b). Figure S3. Mathematical analysis of possible 3-input 1-output Boolean functions versus the number of different wires required for their implementation upon different approaches. a. Multicellular approach, b. standard approach based on NAND logic, c. standard approach based on NOR logic
Figure S4. Complete description of a engineered yeast cell library. a. Graphical respresentation and basic genetic information of the two main types of cells used. Schematic representation of cells that express a wiring molecule (Left) and sensor cells (Right). Schematic legend of logic functions. b. Schematic representation of each cell of the library indicating the logic function performed by each cell and their corresponding genotype (all cells are W303 derivatives). Note that some cells can implement two different functions depending on the experimental conditions and the input used (in brackets). Figure S5. Transfer function analyses of the engineered cells of the library. Indicated cells were grown in YPD to mid exponential phase. Cells that respond to a single input were mixed with the appropriate reporter cell (carrying S. cerevisiae or C.albicans STE2) and treated with variable amounts of input (cells treated with synthetic alpha factor were included as a reference). Output producing cells were mixed with appropriate synthetic alpha factor (from S. cerevisiae or C.albicans) and the indicated input, both at different concentrations. Samples were incubated for 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells and represent the mean of three independent experiments. Data are presented as a regular graph for 1 input analyses and as a contour plot for 2 input analyses.
SUPPLEMENTARY INFORMATION
2 | w w w. n a t u r e . c o m / n a t u r e
RESEARCH
Supplemental Figure2Regot et al.
a
bFigure S1. Illustrative example of the method for designing distributed biological computation. a. General pattern of connections between cells for multicellular circuits.b. Truth table defining the behavior of a multiplexer circuit. c. Full Boolean function that express the relationship between the logic inputs x1, x2, x3 and the logic output O according to the truth table. d. Simplified version of the Boolean function f describing the same truth table. The analytical expression of the Boolean function determines that the circuit can be implemented using two different sets of engineered cells ρ1 and ρ2. e. Implementation of the circuit with direct mapping between the terms of the Boolean function and the engineered cells. Here ρ1={C11, C12} and ρ2={C21, C22}. The tables determine the logic implemented in each cell. Here rhombus represents the external inputs x1, x2, and x3, red and blue circles represent the internal wiring implemented by the production of a diffusible molecule, and squares are the final output. f. A mixed implementation, where the set ρ1 is a direct mapping of the terms from the Boolean function whereas in ρ2 all the terms have been condensed in a single cell. g. Circuit implementation where both sets ρ1 and ρ2 are implemented by a single cell in each case. Figure S2. Number of possible Boolean functions versus the number of different cells required for their implementation. Each graph represents the number of (nonnull) functions that can be implemented with a defined number of engineered cells that receive 2-inputs (a) and 3-inputs (b). Figure S3. Mathematical analysis of possible 3-input 1-output Boolean functions versus the number of different wires required for their implementation upon different approaches. a. Multicellular approach, b. standard approach based on NAND logic, c. standard approach based on NOR logic
Figure S4. Complete description of a engineered yeast cell library. a. Graphical respresentation and basic genetic information of the two main types of cells used. Schematic representation of cells that express a wiring molecule (Left) and sensor cells (Right). Schematic legend of logic functions. b. Schematic representation of each cell of the library indicating the logic function performed by each cell and their corresponding genotype (all cells are W303 derivatives). Note that some cells can implement two different functions depending on the experimental conditions and the input used (in brackets). Figure S5. Transfer function analyses of the engineered cells of the library. Indicated cells were grown in YPD to mid exponential phase. Cells that respond to a single input were mixed with the appropriate reporter cell (carrying S. cerevisiae or C.albicans STE2) and treated with variable amounts of input (cells treated with synthetic alpha factor were included as a reference). Output producing cells were mixed with appropriate synthetic alpha factor (from S. cerevisiae or C.albicans) and the indicated input, both at different concentrations. Samples were incubated for 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells and represent the mean of three independent experiments. Data are presented as a regular graph for 1 input analyses and as a contour plot for 2 input analyses.
w w w. n a t u r e . c o m / n a t u r e | 3
SUPPLEMENTARY INFORMATION RESEARCHSupplemental Figure 3
Regot et al.
a
b
c
Figure S1. Illustrative example of the method for designing distributed biological computation. a. General pattern of connections between cells for multicellular circuits.b. Truth table defining the behavior of a multiplexer circuit. c. Full Boolean function that express the relationship between the logic inputs x1, x2, x3 and the logic output O according to the truth table. d. Simplified version of the Boolean function f describing the same truth table. The analytical expression of the Boolean function determines that the circuit can be implemented using two different sets of engineered cells ρ1 and ρ2. e. Implementation of the circuit with direct mapping between the terms of the Boolean function and the engineered cells. Here ρ1={C11, C12} and ρ2={C21, C22}. The tables determine the logic implemented in each cell. Here rhombus represents the external inputs x1, x2, and x3, red and blue circles represent the internal wiring implemented by the production of a diffusible molecule, and squares are the final output. f. A mixed implementation, where the set ρ1 is a direct mapping of the terms from the Boolean function whereas in ρ2 all the terms have been condensed in a single cell. g. Circuit implementation where both sets ρ1 and ρ2 are implemented by a single cell in each case. Figure S2. Number of possible Boolean functions versus the number of different cells required for their implementation. Each graph represents the number of (nonnull) functions that can be implemented with a defined number of engineered cells that receive 2-inputs (a) and 3-inputs (b). Figure S3. Mathematical analysis of possible 3-input 1-output Boolean functions versus the number of different wires required for their implementation upon different approaches. a. Multicellular approach, b. standard approach based on NAND logic, c. standard approach based on NOR logic
Figure S4. Complete description of a engineered yeast cell library. a. Graphical respresentation and basic genetic information of the two main types of cells used. Schematic representation of cells that express a wiring molecule (Left) and sensor cells (Right). Schematic legend of logic functions. b. Schematic representation of each cell of the library indicating the logic function performed by each cell and their corresponding genotype (all cells are W303 derivatives). Note that some cells can implement two different functions depending on the experimental conditions and the input used (in brackets). Figure S5. Transfer function analyses of the engineered cells of the library. Indicated cells were grown in YPD to mid exponential phase. Cells that respond to a single input were mixed with the appropriate reporter cell (carrying S. cerevisiae or C.albicans STE2) and treated with variable amounts of input (cells treated with synthetic alpha factor were included as a reference). Output producing cells were mixed with appropriate synthetic alpha factor (from S. cerevisiae or C.albicans) and the indicated input, both at different concentrations. Samples were incubated for 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells and represent the mean of three independent experiments. Data are presented as a regular graph for 1 input analyses and as a contour plot for 2 input analyses.
SUPPLEMENTARY INFORMATION
4 | w w w. n a t u r e . c o m / n a t u r e
RESEARCH
FUS1::GFP
TetOff::FUS3as
DOX
CELL#11
CELL#7
FUS1::GFP
TetOn::FUS3as
DOX
CaSTE2
CELL#6
FUS1::GFP
FUS1::Out
kss1∆∆∆∆
mf(αααα)1,2∆∆∆∆
α
ste3∆∆∆∆
Activating Input
Inhibitory Inputbar1∆∆∆∆
Activating Input
Inhibitory Input
α
fus3∆∆∆∆
STL1::MF(αααα)1
NaCl
fps11
CELL#1
TetOff::MF(αααα)1
DOX
CELL#3
CELL#4
FUS1::GFP
FUS3as
6a
GAL:: MF(αααα)1
CELL#5
GAL
HXT1::MF(αααα)1
CELL#8
GLU
CELL#9
FUS1::GFP
TetOn::FUS3as
DOX
CELL#12
FUS1::GFP
GALS::FUS3as
17β-E2
ADGEV gal4
TetOff::CaMF(αααα)1
DOX
CELL#13
TetOn::CaMF(αααα)1
DOX
CELL#14
CELL#16
FUS1::mCh
TetOn::FUS3as
DOX
MATα ste3::HIS3
mfα1::LEU mfα2::KanpRS424 STL1::MFα1
YEplac195-fps11
MATa bar1::HIS3 fus3::LEU2 kss1::TRP1
Nat::PGALS-fus3as::Hph
FUS1::GFP::Kan URA3::ADGEV
MATα ste3::HIS3
mfα1::LEU2 mfα2::Kan
pCM183-MFα1
MATa bar1::HIS3
fus3::LEU2 kss1::TRP1 FUS3as::URA
FUS1::GFP::Kan
MATα ste3::HIS3
mfα1::LEU2 mfα2::KanpBEVY-GU-MFα1
MATa bar1::HIS3FUS1::GFP::Kan
MATa bar1::Nat fus3::LEU2 kss1::Hph
ste2::URA3 FUS1::GFP::Kan pAJ1-
CaSTE2 pRS413TetO7-
fus3as
CELL#2
FUS1::GFP
GALS::FUS3as
17β-E2
ADGEV
MATα ste3::HIS3 mfα1::LEU2 mfα2::Kan
YEpHXT1-MFα1
MATa bar1::Natfus3::LEU2 kss1::TRP1
FUS1::GFP::Kan
YIpTetO7-fus3as
MATα ste3::HIS3
mfα1::LEU2 mfα2::KanYCpTetO2-MFα1
MATa bar1::HIS3
fus3::LEU2 kss1::TRP1 FUS1::GFP::Kan
YIpTetOff7-fus3as
MATa bar1::HIS3 fus3::LEU2 kss1::TRP1
Nat::PGALS-fus3as::Hph FUS1::GFP::Kan
gal4::Phl URA3::ADGEV
MATα ste3::HIS3
mfα1::LEU2 mfα2::KanYEpTetOff7-CaMFα1
MATα ste3::HIS3
mfα1::LEU2 mfα2::KanYCpTetO7-CaMFα1
MATa bar1::HIS3
kss1::LEU2 ste2::URA3
FUS1::GFP::Kan sst2::Hph Yip-CaSTE2
Nat::PGALS-FUS3
MATa bar1::Nat
fus3::LEU2 kss1::HphFUS1::URA3::Kan
pRS304 FUS1-mCherry YIpTetO7-fus3as
TetOn::MF(αααα)1
DOX
CELL#10
CELL#15
FUS1::GFP
GALS::FUS3
GAL
CaSTE2
sst2
a
b
IDENTITY
NOT
AND
N-IMPLIES
Supplemental Figure 4Regot et al.
Figure S1. Illustrative example of the method for designing distributed biological computation. a. General pattern of connections between cells for multicellular circuits.b. Truth table defining the behavior of a multiplexer circuit. c. Full Boolean function that express the relationship between the logic inputs x1, x2, x3 and the logic output O according to the truth table. d. Simplified version of the Boolean function f describing the same truth table. The analytical expression of the Boolean function determines that the circuit can be implemented using two different sets of engineered cells ρ1 and ρ2. e. Implementation of the circuit with direct mapping between the terms of the Boolean function and the engineered cells. Here ρ1={C11, C12} and ρ2={C21, C22}. The tables determine the logic implemented in each cell. Here rhombus represents the external inputs x1, x2, and x3, red and blue circles represent the internal wiring implemented by the production of a diffusible molecule, and squares are the final output. f. A mixed implementation, where the set ρ1 is a direct mapping of the terms from the Boolean function whereas in ρ2 all the terms have been condensed in a single cell. g. Circuit implementation where both sets ρ1 and ρ2 are implemented by a single cell in each case. Figure S2. Number of possible Boolean functions versus the number of different cells required for their implementation. Each graph represents the number of (nonnull) functions that can be implemented with a defined number of engineered cells that receive 2-inputs (a) and 3-inputs (b). Figure S3. Mathematical analysis of possible 3-input 1-output Boolean functions versus the number of different wires required for their implementation upon different approaches. a. Multicellular approach, b. standard approach based on NAND logic, c. standard approach based on NOR logic
Figure S4. Complete description of a engineered yeast cell library. a. Graphical respresentation and basic genetic information of the two main types of cells used. Schematic representation of cells that express a wiring molecule (Left) and sensor cells (Right). Schematic legend of logic functions. b. Schematic representation of each cell of the library indicating the logic function performed by each cell and their corresponding genotype (all cells are W303 derivatives). Note that some cells can implement two different functions depending on the experimental conditions and the input used (in brackets). Figure S5. Transfer function analyses of the engineered cells of the library. Indicated cells were grown in YPD to mid exponential phase. Cells that respond to a single input were mixed with the appropriate reporter cell (carrying S. cerevisiae or C.albicans STE2) and treated with variable amounts of input (cells treated with synthetic alpha factor were included as a reference). Output producing cells were mixed with appropriate synthetic alpha factor (from S. cerevisiae or C.albicans) and the indicated input, both at different concentrations. Samples were incubated for 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells and represent the mean of three independent experiments. Data are presented as a regular graph for 1 input analyses and as a contour plot for 2 input analyses.
w w w. n a t u r e . c o m / n a t u r e | 5
SUPPLEMENTARY INFORMATION RESEARCH
% O
F G
FP C
ELLS
[6a] µM
log
[α-f
acto
r] p
M
0
1
2
3
0 2 4 6 8 10
100806040200
% O
F G
FP C
ELLS
[17β-E2] µM
log
[α-f
acto
r] p
M
0
1
2
3
0 5 10 15 20
100806040200
% O
F G
FP C
ELLS
[DOX] ng/ml
log
[α-f
acto
r] p
M
0
1
2
3
0 20 60 80 100
4030201050
40
% O
F G
FP C
ELLS
[DOX] µg/ml
log
[α-f
acto
r] p
M
0
1
2
3
0 2 6 8 10
6040201050
4
% O
F G
FP C
ELLS
% GLU
log
[α-f
acto
r] p
M
0
1
2
3
0 0.5 2 2.5 3
6040201050
1.51
% O
F G
FP C
ELLS
% GLU
log
[α-f
acto
r] p
M
0
1
2
3
0 2 8 10
6040201050
64
% o
fGFP
cel
ls
% GAL
02040
100
0 1 2 3 4 5
6080
6
% o
fGFP
cel
ls
[NaCl]M
02040
100
0 0.2 0.4 0.6
6080
% o
fGFP
cel
ls
[DOX] µg/ml
02040
100
0 2 4 6 8
6080
10
02040
100
0 2 4 6 8
6080
10
% o
fGFP
cel
ls
[DOX] µg/ml
[DOX] µg/ml
02040
100
0 2 4 6 8
6080
10
% o
fGFP
cel
ls
[DOX] µg/ml
02040
100
0 2 4 6 8
6080
10
% o
fGFP
cel
ls
% GLU
02040
100
0 1 2 3 4
6080
% o
fGFP
cel
ls
FUS1::GFP
TetOff::FUS3as
DOX
CELL#11
CELL#7
FUS1::GFP
TetOn::FUS3as
DOX
CaSTE2
STL1::MF(αααα)1
NaCl
fps11
CELL#1
TetOff::MF(αααα)1
DOX
CELL#3
CELL#4
FUS1::GFP
FUS3as
6a
GAL:: MF(αααα)1
CELL#5
GAL
HXT1::MF(αααα)1
CELL#8
GLU
CELL#9
FUS1::GFP
TetOn::FUS3as
DOX
TetOff::
CaMF(αααα)1
DOX
CELL#13
TetOn::
CaMF(αααα)1
DOX
CELL#14
CELL#2
FUS1::GFP
GALS::FUS3as
17β-E2
ADGEV
TetOn::MF(αααα)1
DOX
CELL#10
CELL#15
FUS1::GFP
GALS::FUS3
GLU
CaSTE2
sst2
Supplemental Figure 5Regot et al.
Figure S1. Illustrative example of the method for designing distributed biological computation. a. General pattern of connections between cells for multicellular circuits.b. Truth table defining the behavior of a multiplexer circuit. c. Full Boolean function that express the relationship between the logic inputs x1, x2, x3 and the logic output O according to the truth table. d. Simplified version of the Boolean function f describing the same truth table. The analytical expression of the Boolean function determines that the circuit can be implemented using two different sets of engineered cells ρ1 and ρ2. e. Implementation of the circuit with direct mapping between the terms of the Boolean function and the engineered cells. Here ρ1={C11, C12} and ρ2={C21, C22}. The tables determine the logic implemented in each cell. Here rhombus represents the external inputs x1, x2, and x3, red and blue circles represent the internal wiring implemented by the production of a diffusible molecule, and squares are the final output. f. A mixed implementation, where the set ρ1 is a direct mapping of the terms from the Boolean function whereas in ρ2 all the terms have been condensed in a single cell. g. Circuit implementation where both sets ρ1 and ρ2 are implemented by a single cell in each case. Figure S2. Number of possible Boolean functions versus the number of different cells required for their implementation. Each graph represents the number of (nonnull) functions that can be implemented with a defined number of engineered cells that receive 2-inputs (a) and 3-inputs (b). Figure S3. Mathematical analysis of possible 3-input 1-output Boolean functions versus the number of different wires required for their implementation upon different approaches. a. Multicellular approach, b. standard approach based on NAND logic, c. standard approach based on NOR logic
Figure S4. Complete description of a engineered yeast cell library. a. Graphical respresentation and basic genetic information of the two main types of cells used. Schematic representation of cells that express a wiring molecule (Left) and sensor cells (Right). Schematic legend of logic functions. b. Schematic representation of each cell of the library indicating the logic function performed by each cell and their corresponding genotype (all cells are W303 derivatives). Note that some cells can implement two different functions depending on the experimental conditions and the input used (in brackets). Figure S5. Transfer function analyses of the engineered cells of the library. Indicated cells were grown in YPD to mid exponential phase. Cells that respond to a single input were mixed with the appropriate reporter cell (carrying S. cerevisiae or C.albicans STE2) and treated with variable amounts of input (cells treated with synthetic alpha factor were included as a reference). Output producing cells were mixed with appropriate synthetic alpha factor (from S. cerevisiae or C.albicans) and the indicated input, both at different concentrations. Samples were incubated for 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells and represent the mean of three independent experiments. Data are presented as a regular graph for 1 input analyses and as a contour plot for 2 input analyses.
SUPPLEMENTARY INFORMATION
6 | w w w. n a t u r e . c o m / n a t u r e
RESEARCH
CELL#6
FUS1::GFP
CELL#2
FUS1::GFP
GALS::FUS3as
17β-E2
ADGEV
a
b
c
0
1
0
1
1
1
0
1
NaCl
Output
0
0
1
1
GLU
% of GFP positive cells
0 20 40 60 80 100
1
2
3
4
0 20 40 60 80 100
% of GFP positive cells
0
1
0
1
0
1
0
0
17β-E 2
Output
0
0
1
1
DOX
Output
0
1
0
1
0
1
0
0
α
0
0
1
1
6a
0 20 40 60 80 100
% of GFP positive cells
0 20 40 60 80 100
0 20 40 60 80 100
N-IMPLIES
N-IMPLIES
IMPLIES
TetOff::MF(αααα)1
DOX
CELL#3
STL1::MF(αααα)1
NaCl
fps11
CELL#1
GAL:: MF(αααα)1
CELL#5
GAL
CELL#4
FUS1::GFP
FUS3as
6a
Supplemental Figure 6Regot et al.
Figure S6. N-Implies and Implies circuits. a. One cell based N-IMPLIES. Schematic representation of Cell#4 that implements N-IMPLIES function and the corresponding truth table. Cell were treated as in Figure 3a. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with synthetic alpha factor). b. N-Implies implemented in two cells with different logic. Cells responded to doxycycline and estradiol (inputs) c. Cell based IMPLIES function. Cells as in Figure 3c were used to implement an Implies logic circuit. Inputs were 2 %Glucose and 0.4M NaCl.
Figure S7. Logic gates implemented in vivo using glucose and doxycycline as inputs. a. AND gate. Schematic representation of cells used to implement AND gate with glucose and doxycycline as inputs. Panel ordered as in Figure 7a. Indicated strains were grown in YPGal to mid log exponential phase and mixed proportionally. 2% glucose and 10μg/ml doxycycline were added as inputs. Cells were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data are expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. NOR gate. Panel ordered as in a. c. OR gate. d. NAND gate. e. NAND gate. f. XNOR gate. g.XOR gate.
Figure S8. In vivo characterization of the properties of an AND gate. a. Output duration upon input addition. Indicated cells were grown in YPGal to mid exponential phase and mixed. 2% Glucose and 10μg/ml doxycycline were used as inputs. Cells were incubated for indicated times and samples were analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. Stability of the cirtuit over time. Indicated cells were grown in YPGal to mid log exponential phase and mixed. Culture was maintained at OD 0.4-0.8 during all the experiment. At the indicated times, samples were taken and inputs (2% Glucose and 10μg/ml doxycycline) were added. Collected samples were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of alpha factor). Results represent the mean ± SD of three independent experiments. c, Dynamic response of a circuit using a mircrofluidics platform. Cells as in (a) were grown in YPGal to mid log exponential phase and mixed. Cell mixture was loaded in to a microscopy based microfluidic platform (see methods for details) and indicated input combinations (in brackets) were applied at 1psi (blue arrows). GFP images were taken every 10 minutes. For circuit reset GFP protein was photobleached for 5 minutes and flow was increased up to 5 psi to replace the medium. Images were treated with Matlab for quantification. Data is expressed as average GFP intensity and represent the mean ± SD of three independent experiments. Figure S9. Circuit reprogramming. a. AND gate reprogramming. Schematic representation of cells used in the AND circuit showing most relevant modifications. Truth table corresponding to AND logic gate with a third input to reprogram the circuit. Here, x represents any possible value, i.e. 0 or 1. Indicated cells were treated as in Figure 3a and inhibitor (6a) was added to reprogram the indicated samples. Data are expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of synthetic alpha factor). Results are presented as the mean ± SD of three independent experiments. b. OR gate reprogramming. Panel ordered as in (a) following OR logic. 2% Glucose was added to reprogram the indicated samples.
w w w. n a t u r e . c o m / n a t u r e | 7
SUPPLEMENTARY INFORMATION RESEARCH
CELL#2
FUS1::GFP
GALS::FUS3as
GLU
ADGEV
CELL#9
FUS1::GFP
TetOn::FUS3as
DOX
HXT1::MF(αααα)1
CELL#8
GLU
CELL#2
FUS1::GFP
GALS::FUS3as
GLU
ADGEV
CELL#9
FUS1::GFP
TetOn::FUS3as
DOX
CELL#6
FUS1::GFP
a0 00 11 01 1
0001
GLU
DOX
Output
HXT1::MF(αααα)1
CELL#8
GLU
0 20 40 60 80 100
% of GFP positive cells
AND
b
TetOff::MF(αααα)1
DOX
CELL#3
0 00 11 01 1
1000
GLU
DOX
Output
% of GFP positive cells20 40 60 80 100
NOR
c
HXT1::MF(αααα)1
CELL#8
GLU
TetOn::MF(αααα)1
DOX
CELL#100 00 11 01 1
0111
GLU
DOX
Output
20 40 60 80 100
% of GFP positive cells
OR
dTetOff::MF(αααα)1
DOX
CELL#3
GAL:: MF(αααα)1
CELL#5
GLU
CELL#6
FUS1::GFP
0 00 11 01 1
1110
GLU
DOX
Output
20 40 60 80 100
% of GFP positive cells
NAND
0 00 11 01 1
1001
GLU
DOX
Output
20 40 60 80 100
% of GFP positive cells
XNOR
e
TetOn::MF(αααα)1
DOX
CELL#10
HXT1::MF(αααα)1
CELL#8
GLU
FUS1::GFP
TetOff::FUS3as
DOX
CELL#11
0 00 11 01 1
0110
GLU
DOX
Output
20 40 60 80 100
% of GFP positive cells
XOR
f
CELL#2
FUS1::GFP
GALS::FUS3as
GLU
ADGEV
TetOff::MF(αααα)1
DOX
CELL#3
Supplemental Figure 7Regot et al.
Figure S6. N-Implies and Implies circuits. a. One cell based N-IMPLIES. Schematic representation of Cell#4 that implements N-IMPLIES function and the corresponding truth table. Cell were treated as in Figure 3a. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with synthetic alpha factor). b. N-Implies implemented in two cells with different logic. Cells responded to doxycycline and estradiol (inputs) c. Cell based IMPLIES function. Cells as in Figure 3c were used to implement an Implies logic circuit. Inputs were 2 %Glucose and 0.4M NaCl.
Figure S7. Logic gates implemented in vivo using glucose and doxycycline as inputs. a. AND gate. Schematic representation of cells used to implement AND gate with glucose and doxycycline as inputs. Panel ordered as in Figure 7a. Indicated strains were grown in YPGal to mid log exponential phase and mixed proportionally. 2% glucose and 10μg/ml doxycycline were added as inputs. Cells were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data are expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. NOR gate. Panel ordered as in a. c. OR gate. d. NAND gate. e. NAND gate. f. XNOR gate. g.XOR gate.
Figure S8. In vivo characterization of the properties of an AND gate. a. Output duration upon input addition. Indicated cells were grown in YPGal to mid exponential phase and mixed. 2% Glucose and 10μg/ml doxycycline were used as inputs. Cells were incubated for indicated times and samples were analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. Stability of the cirtuit over time. Indicated cells were grown in YPGal to mid log exponential phase and mixed. Culture was maintained at OD 0.4-0.8 during all the experiment. At the indicated times, samples were taken and inputs (2% Glucose and 10μg/ml doxycycline) were added. Collected samples were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of alpha factor). Results represent the mean ± SD of three independent experiments. c, Dynamic response of a circuit using a mircrofluidics platform. Cells as in (a) were grown in YPGal to mid log exponential phase and mixed. Cell mixture was loaded in to a microscopy based microfluidic platform (see methods for details) and indicated input combinations (in brackets) were applied at 1psi (blue arrows). GFP images were taken every 10 minutes. For circuit reset GFP protein was photobleached for 5 minutes and flow was increased up to 5 psi to replace the medium. Images were treated with Matlab for quantification. Data is expressed as average GFP intensity and represent the mean ± SD of three independent experiments. Figure S9. Circuit reprogramming. a. AND gate reprogramming. Schematic representation of cells used in the AND circuit showing most relevant modifications. Truth table corresponding to AND logic gate with a third input to reprogram the circuit. Here, x represents any possible value, i.e. 0 or 1. Indicated cells were treated as in Figure 3a and inhibitor (6a) was added to reprogram the indicated samples. Data are expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of synthetic alpha factor). Results are presented as the mean ± SD of three independent experiments. b. OR gate reprogramming. Panel ordered as in (a) following OR logic. 2% Glucose was added to reprogram the indicated samples.
SUPPLEMENTARY INFORMATION
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Supplemental Figure 8Regot et al.
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24
Figure S6. N-Implies and Implies circuits. a. One cell based N-IMPLIES. Schematic representation of Cell#4 that implements N-IMPLIES function and the corresponding truth table. Cell were treated as in Figure 3a. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with synthetic alpha factor). b. N-Implies implemented in two cells with different logic. Cells responded to doxycycline and estradiol (inputs) c. Cell based IMPLIES function. Cells as in Figure 3c were used to implement an Implies logic circuit. Inputs were 2 %Glucose and 0.4M NaCl.
Figure S7. Logic gates implemented in vivo using glucose and doxycycline as inputs. a. AND gate. Schematic representation of cells used to implement AND gate with glucose and doxycycline as inputs. Panel ordered as in Figure 7a. Indicated strains were grown in YPGal to mid log exponential phase and mixed proportionally. 2% glucose and 10μg/ml doxycycline were added as inputs. Cells were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data are expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. NOR gate. Panel ordered as in a. c. OR gate. d. NAND gate. e. NAND gate. f. XNOR gate. g.XOR gate.
Figure S8. In vivo characterization of the properties of an AND gate. a. Output duration upon input addition. Indicated cells were grown in YPGal to mid exponential phase and mixed. 2% Glucose and 10μg/ml doxycycline were used as inputs. Cells were incubated for indicated times and samples were analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. Stability of the cirtuit over time. Indicated cells were grown in YPGal to mid log exponential phase and mixed. Culture was maintained at OD 0.4-0.8 during all the experiment. At the indicated times, samples were taken and inputs (2% Glucose and 10μg/ml doxycycline) were added. Collected samples were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of alpha factor). Results represent the mean ± SD of three independent experiments. c, Dynamic response of a circuit using a mircrofluidics platform. Cells as in (a) were grown in YPGal to mid log exponential phase and mixed. Cell mixture was loaded in to a microscopy based microfluidic platform (see methods for details) and indicated input combinations (in brackets) were applied at 1psi (blue arrows). GFP images were taken every 10 minutes. For circuit reset GFP protein was photobleached for 5 minutes and flow was increased up to 5 psi to replace the medium. Images were treated with Matlab for quantification. Data is expressed as average GFP intensity and represent the mean ± SD of three independent experiments. Figure S9. Circuit reprogramming. a. AND gate reprogramming. Schematic representation of cells used in the AND circuit showing most relevant modifications. Truth table corresponding to AND logic gate with a third input to reprogram the circuit. Here, x represents any possible value, i.e. 0 or 1. Indicated cells were treated as in Figure 3a and inhibitor (6a) was added to reprogram the indicated samples. Data are expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of synthetic alpha factor). Results are presented as the mean ± SD of three independent experiments. b. OR gate reprogramming. Panel ordered as in (a) following OR logic. 2% Glucose was added to reprogram the indicated samples.
w w w. n a t u r e . c o m / n a t u r e | 9
SUPPLEMENTARY INFORMATION RESEARCH
Figure S6. N-Implies and Implies circuits. a. One cell based N-IMPLIES. Schematic representation of Cell#4 that implements N-IMPLIES function and the corresponding truth table. Cell were treated as in Figure 3a. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with synthetic alpha factor). b. N-Implies implemented in two cells with different logic. Cells responded to doxycycline and estradiol (inputs) c. Cell based IMPLIES function. Cells as in Figure 3c were used to implement an Implies logic circuit. Inputs were 2 %Glucose and 0.4M NaCl.
Figure S7. Logic gates implemented in vivo using glucose and doxycycline as inputs. a. AND gate. Schematic representation of cells used to implement AND gate with glucose and doxycycline as inputs. Panel ordered as in Figure 7a. Indicated strains were grown in YPGal to mid log exponential phase and mixed proportionally. 2% glucose and 10μg/ml doxycycline were added as inputs. Cells were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data are expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. NOR gate. Panel ordered as in a. c. OR gate. d. NAND gate. e. NAND gate. f. XNOR gate. g.XOR gate.
Figure S8. In vivo characterization of the properties of an AND gate. a. Output duration upon input addition. Indicated cells were grown in YPGal to mid exponential phase and mixed. 2% Glucose and 10μg/ml doxycycline were used as inputs. Cells were incubated for indicated times and samples were analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. Stability of the cirtuit over time. Indicated cells were grown in YPGal to mid log exponential phase and mixed. Culture was maintained at OD 0.4-0.8 during all the experiment. At the indicated times, samples were taken and inputs (2% Glucose and 10μg/ml doxycycline) were added. Collected samples were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of alpha factor). Results represent the mean ± SD of three independent experiments. c, Dynamic response of a circuit using a mircrofluidics platform. Cells as in (a) were grown in YPGal to mid log exponential phase and mixed. Cell mixture was loaded in to a microscopy based microfluidic platform (see methods for details) and indicated input combinations (in brackets) were applied at 1psi (blue arrows). GFP images were taken every 10 minutes. For circuit reset GFP protein was photobleached for 5 minutes and flow was increased up to 5 psi to replace the medium. Images were treated with Matlab for quantification. Data is expressed as average GFP intensity and represent the mean ± SD of three independent experiments. Figure S9. Circuit reprogramming. a. AND gate reprogramming. Schematic representation of cells used in the AND circuit showing most relevant modifications. Truth table corresponding to AND logic gate with a third input to reprogram the circuit. Here, x represents any possible value, i.e. 0 or 1. Indicated cells were treated as in Figure 3a and inhibitor (6a) was added to reprogram the indicated samples. Data are expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of synthetic alpha factor). Results are presented as the mean ± SD of three independent experiments. b. OR gate reprogramming. Panel ordered as in (a) following OR logic. 2% Glucose was added to reprogram the indicated samples.
SUPPLEMENTARY INFORMATION
1 0 | w w w. n a t u r e . c o m / n a t u r e
RESEARCH
CELL#6
FUS1::GFP
CELL#2
FUS1::GFP
GALS::FUS3as
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Supplemental Figure 9Regot et al.
Figure S6. N-Implies and Implies circuits. a. One cell based N-IMPLIES. Schematic representation of Cell#4 that implements N-IMPLIES function and the corresponding truth table. Cell were treated as in Figure 3a. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with synthetic alpha factor). b. N-Implies implemented in two cells with different logic. Cells responded to doxycycline and estradiol (inputs) c. Cell based IMPLIES function. Cells as in Figure 3c were used to implement an Implies logic circuit. Inputs were 2 %Glucose and 0.4M NaCl.
Figure S7. Logic gates implemented in vivo using glucose and doxycycline as inputs. a. AND gate. Schematic representation of cells used to implement AND gate with glucose and doxycycline as inputs. Panel ordered as in Figure 7a. Indicated strains were grown in YPGal to mid log exponential phase and mixed proportionally. 2% glucose and 10μg/ml doxycycline were added as inputs. Cells were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data are expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. NOR gate. Panel ordered as in a. c. OR gate. d. NAND gate. e. NAND gate. f. XNOR gate. g.XOR gate.
Figure S8. In vivo characterization of the properties of an AND gate. a. Output duration upon input addition. Indicated cells were grown in YPGal to mid exponential phase and mixed. 2% Glucose and 10μg/ml doxycycline were used as inputs. Cells were incubated for indicated times and samples were analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% a sample treated with alpha factor). Results represent the mean ± SD of three independent experiments. b. Stability of the cirtuit over time. Indicated cells were grown in YPGal to mid log exponential phase and mixed. Culture was maintained at OD 0.4-0.8 during all the experiment. At the indicated times, samples were taken and inputs (2% Glucose and 10μg/ml doxycycline) were added. Collected samples were incubated 4h at 30ºC and analyzed by flow cytometry as described in methods. Data is expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of alpha factor). Results represent the mean ± SD of three independent experiments. c, Dynamic response of a circuit using a mircrofluidics platform. Cells as in (a) were grown in YPGal to mid log exponential phase and mixed. Cell mixture was loaded in to a microscopy based microfluidic platform (see methods for details) and indicated input combinations (in brackets) were applied at 1psi (blue arrows). GFP images were taken every 10 minutes. For circuit reset GFP protein was photobleached for 5 minutes and flow was increased up to 5 psi to replace the medium. Images were treated with Matlab for quantification. Data is expressed as average GFP intensity and represent the mean ± SD of three independent experiments. Figure S9. Circuit reprogramming. a. AND gate reprogramming. Schematic representation of cells used in the AND circuit showing most relevant modifications. Truth table corresponding to AND logic gate with a third input to reprogram the circuit. Here, x represents any possible value, i.e. 0 or 1. Indicated cells were treated as in Figure 3a and inhibitor (6a) was added to reprogram the indicated samples. Data are expressed as the percentage of GFP positive cells (considering 100% an equally treated sample with 2μg/ml of synthetic alpha factor). Results are presented as the mean ± SD of three independent experiments. b. OR gate reprogramming. Panel ordered as in (a) following OR logic. 2% Glucose was added to reprogram the indicated samples.
w w w. n a t u r e . c o m / n a t u r e | 1 1
SUPPLEMENTARY INFORMATION RESEARCH
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Supplemental Figure 10Regot et al.
Figure S10. Design and in vivo implementation of a multiplexer (MUX2to1) a, Example of an schematic diagram that would yield a putative transcription based single cell MUX2to1. b, In vivo implementation of a 3 cell based MUX2to1. Schematic representation of the cells used in the MUX2to1circuit showing most relevant modifications (see strains and plasmids for complete genotype). Truth table corresponding to a MUX2to1 circuit. Indicated cells were treated as before using doxycycline (selector) and the inputs 17β-estradiol and synthetic Candida albicans alpha factor. Data is expressed as the percentage of GFP positive cells, considering 100% a reference culture treated with alpha factor (S. cerevisiae or C. albicans) for cell#2 cell and cell#7 respectively. Results are presented as the mean ± SD of three independent experiments. Figure S11. A summary of the synthetic constructs obtained in our study, represented as combinatorial units. Left panel displays all the input molecules and engineered cells used here and at right we display eight functional examples of logic gates implemented by single or multicellular components. As we can see from the color-coded presentation, the small cell library is used in multiple ways in order to generate desired (non-trivial) Boolean functions. Adding just an additional type of wire or another output molecule, the number of constructs would exponentially increase.
SUPPLEMENTARY INFORMATION
1 2 | w w w. n a t u r e . c o m / n a t u r e
RESEARCH Supplemental Figure 11Regot et al.
Figure S10. Design and in vivo implementation of a multiplexer (MUX2to1) a, Example of an schematic diagram that would yield a putative transcription based single cell MUX2to1. b, In vivo implementation of a 3 cell based MUX2to1. Schematic representation of the cells used in the MUX2to1circuit showing most relevant modifications (see strains and plasmids for complete genotype). Truth table corresponding to a MUX2to1 circuit. Indicated cells were treated as before using doxycycline (selector) and the inputs 17β-estradiol and synthetic Candida albicans alpha factor. Data is expressed as the percentage of GFP positive cells, considering 100% a reference culture treated with alpha factor (S. cerevisiae or C. albicans) for cell#2 cell and cell#7 respectively. Results are presented as the mean ± SD of three independent experiments. Figure S11. A summary of the synthetic constructs obtained in our study, represented as combinatorial units. Left panel displays all the input molecules and engineered cells used here and at right we display eight functional examples of logic gates implemented by single or multicellular components. As we can see from the color-coded presentation, the small cell library is used in multiple ways in order to generate desired (non-trivial) Boolean functions. Adding just an additional type of wire or another output molecule, the number of constructs would exponentially increase.