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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



SUPPLEMENTARY INFORMATION RESEARCHSupplemental Figure 3

Regot et al.

a

b

c





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





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

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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

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3

0 2 6 8 10

6040201050

4

% O

F G

FP C

ELLS

% GLU

log

[α-f

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M

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0 0.5 2 2.5 3

6040201050

1.51

% O

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ELLS

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log

[α-f

acto

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M

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6040201050

64

% o

fGFP

cel

ls

% GAL

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6080

6

% o

fGFP

cel

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02040

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0 0.2 0.4 0.6

6080

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fGFP

cel

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02040

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0 2 4 6 8

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% o

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FUS1::GFP

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CELL#11

CELL#7

FUS1::GFP

TetOn::FUS3as

DOX

CaSTE2

STL1::MF(αααα)1

NaCl

fps11

CELL#1


DOX

CELL#3

CELL#4

FUS1::GFP

FUS3as

6a

GAL:: MF(αααα)1

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GAL

HXT1::MF(αααα)1

CELL#8

GLU

CELL#9

FUS1::GFP

TetOn::FUS3as

DOX

TetOff::

CaMF(αααα)1

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CELL#13

TetOn::

CaMF(αααα)1

DOX

CELL#14

CELL#2

FUS1::GFP

GALS::FUS3as

17β-E2

ADGEV


DOX

CELL#10

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FUS1::GFP

GALS::FUS3

GLU

CaSTE2

sst2






RESEARCH

CELL#6

FUS1::GFP

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FUS1::GFP

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fps11

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GAL:: MF(αααα)1

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FUS1::GFP

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6a


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.



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

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00001111

MUX2to1

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% of GFP positive cellsCELL#7

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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.


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.

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