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| | <h1>TalkE'coli - Our device</h1> | | <h1>TalkE'coli - Our device</h1> |
| - | | + | <h2 id="Overview">Overview of the device</h2> |
| - | <p>Our project aims to <strong>control the concentration of living bacteria in a culture</strong>. To do so, we designed a genetic network allowing light controlled cell growth. In addition, we built a device in order to send and receive light signals from the bacterial culture. We have thus to create a means of communication from cell to machine and from machine to cell. For cell to machine communication, we chose to measure the red fluorescence of KillerRed. A first function of our device is to excite and measure fluorescence intensity thanks to a light source, excitation/emission optics and a photodiode. In this way, our bacteria will be able to talk to our device. For machine to cell communication, we will use red light to activate a light-inducible promoter that triggers KillerRed production and white light to generate ROS thanks to KillerRed phototoxic activity. In our system, the rate of KillerRed production and the number of living cells will be controlled by the intensity of the red and white light beams. A second function of our device is therefore to generate controlled light intensities at different wavelengths. In this way, our device will be able to talk to our bacteria. Firstly we will explain the choice of the different components, then the several experiences we did to find the most accurate parameters for each part of the device : < a href=#Photodiode> the photodiode</ a> , < a href=#Arduino> Arduino< /a> , < a href= #Fluo> fluorescence measurement</ a> , < a href= #Electronic> the electronic circuit< /a> , < a href=#Servo> the servomotor</ a> . All these elements were integrated in < a href=#Box> the box</ a> that we designed and built.</p> | + | <p>Our project aims to <strong>control the concentration of living bacteria in a culture</strong>. To do so, we designed <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Biology">a genetic network allowing light controlled cell growth </a>. In addition, we built a device in order to send and receive light signals from the bacterial culture. We have thus to create <strong>a means of communication from cell to machine and from machine to cell </strong>. For cell to machine communication, we chose to measure <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Biology">the red fluorescence of KillerRed </a>. The first function of our device is to excite and measure fluorescence intensity thanks to a light source, excitation/emission optics and a photodiode. In this way, our bacteria will be able to talk to our device. For machine to cell communication, we will use red light to activate <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Biology/KR"> light-inducible promoter </a> that triggers KillerRed production and white light to generate ROS thanks to KillerRed phototoxic activity. In our system, the rate of KillerRed production and the number of living cells will be controlled by the intensity of the red and white light beams. Therefore, a second function of our device is to generate controlled light intensities at different wavelengths. In this way, our device will be able to talk to our bacteria.< /br></ br>< /p> |
| | + | <p align="center"><img src="https://static.igem.org/mediawiki/2013/7/79/Logical_scheme.png" alt="Logical_sheme" width="500px" /></p> |
| | + | <p id="legend"><strong><em>Logical scheme of our device</em></strong></br> |
| | + | The computer gets information from the microcontroller about the fluorescence level of the bacterial suspension and calculates the intensity of the light to express KillerRed and control the cell density. The microcontroller itself controls the intensity and the spectrum of the light source that illuminates the sample. The photodiode measures the fluorescence level of KillerRed.</br></br></p> |
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| - | <h2 id="Component">The components</h2>
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| - | <p>To record light intensity, we were inspired by the E. glometer of the Cambridge team of iGEM 2010.<br>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/a/a7/Eglometer.png" alt="The Eglometer" width="500px" /></p>
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| - | <p id="legend"><strong><em>The E. glometer of Cambrige team (iGEM 2010)</em></strong></br>
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| - | Device built by Cambrige team in 2010 to measure the light intensity of their LuxBrick</br>
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| - | <em><strong>Source:</strong></em><a href="https://2010.igem.org/Team:Cambridge/Tools/Eglometer">https://2010.igem.org/Team:Cambridge/Tools/Eglometer</a>
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| - | We use a similar photodiode (TSL230RD) – the same as the TSL230RP-LF but as a surface mounted device (SMD) – and an Arduino Uno. Arduino is a single-board microcontroller created to make electronics more accessible. The main asset of the photodiode is that the output can be either a pulse train or a square wave (50% duty cycle) with its frequency directly proportional to light intensity. Since we are using a microcontroller, it is easy to calculate the frequency with the digital input of the microchip thanks to high or low level detection and we will have a better resolution because low frequencies are easier to measure than low voltages at low light levels. For the optical part we use a LED lamp and a cube filter from a fluorescence microscope with excitation and emission filters and an adjustable lens. The LED lamp was chosen so that e didn't have to buy high-power LEDS and build a card with heat sinks. This lamp illuminates with 520 lumens in a 40° cone under 12V and 6W. The low voltage was chosen as a safety measure and the small angle to avoid losing too much light. The excitation filter is a green interferential filter to excite the red fluorescent protein and the red emission filter is only a colored filter to collect all the red light in order to have a more precise measure. In the cube there is also a dichroic mirror that reflects all the green light and transmits all the red light. This mirror enables us to separate the photodiode from the light source completely.
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| - | <h2 id="Photodiode">The photodiode</h2>
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| - | <p>Before measuring with the photodiode, we need to know if the photodiode works as indicated in the datasheet. The photodiode was plugged in on a 5V stabilized power supply.</br></p>
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| - | <p align="center", style="margin:20px"><img src="https://static.igem.org/mediawiki/2013/5/5f/IGEMerworkphotodiode.png" alt="memberworkingonphotodiode" width="500px"></p>
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| - | <p id="legend"><strong><em>A member of the team working on the photodiode</em></strong></br></p>
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| - | <p>For the same amount of light, we measure the frequency at the output of the photodiode for a pulse train or a square wave (50% duty cycle). According to the datasheet, when using a pulse train the linear relation between the frequency and the irrandiance is given by 1kHz=1µW/cm². When using a square wave (50% duty cycle) it is 1kHz=2µW/cm². This is what we can see on the figure #.
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| - | </br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/5/51/Oscilloscope.png" alt="Oscillogram" width="650px" /></p>
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| - | <p id="legend"><strong><em>Oscillograms showing the two different mode of the photodiode.</em></strong></br>The first oscillogramm shows the pulse train mode and the second the 50% duty cycle mode</br></p>
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| - | <p></br>Since this frequency will be calculated by the Arduino controller, it may cause some trouble to the program to use a pulse train because the duration of the pulse is always 500ns and can be missed by the controller. The square wave (50% duty cycle) seems to be a better solution because of the 50% duty cycle. It means that the pulse duration depend on the frequency. Its duration is equal to 1/2f and since the light intensity we want to measure will be low this type of signal can be easily detected by Arduino.</p>
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| - | <h2 id="Arduino">Arduino</h2>
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| - | <p>Arduino is used to translate the frequency given by the photodiode in irrandiance that gives us the light intensity. The algorithm is quite simple. It counts the number of high levels (samples) and the duration of the measurement (length) and with these two elements it makes this calculation:</br></br>
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| - | <strong>Irradiance=frequency/(frequency scaling)= samples/(frequency scaling × length)</strong></br></br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/2/22/Algo_photodiode.PNG" alt="algo_photodiode" width="500px" /></p>
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| - | To know if this program works, a function generator was plug in one of the digital input of Arduino instead of the photodiode. By changing the frequency of the square signal sent by the generator and measuring several times the frequency with Arduino and compare the measures to the frequency given by an oscilloscope, we can calculate the accuracy of the program.</br>
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| - | If the algorithm is right, the curve should follow the equation x=y, which means that Arduino and the oscilloscope measure the same frequencies.</br></br></p>
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| - | <p align="center", style="margin:30px"><img src="https://static.igem.org/mediawiki/2013/3/31/Arduino_mode1.png" alt="Arduino Mode1" width="550px">
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| - | <img src="https://static.igem.org/mediawiki/2013/8/86/Arduino_mode2.png" alt="Arduino Mode2" width="550px">
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| - | <img src="https://static.igem.org/mediawiki/2013/4/40/Arduino_std.png" alt="Arduino Mode2 standard deviation" width="550px">
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| - | </br></p>
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| - | <p id="legend"><strong><em>Characterization of the algorithm in Arduino</em></strong><br>
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| - | The first graph shows us the reponse of Arduino in pulse train mode, the second one shows us the response of Arduino in 50% duty circle mode, and the last one gives us the standard deviation of the 50% duty circle mode</p>
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| - | <p></br>According our the experience, the pulse train mode is not a good option since the curve doesn’t follow at all the x=y curve. Only three points are shown here because the others are worst. On the other hand, the 50% duty cycle mode seems to work better, at least at the low frequency. For frequencies under 35kHz the curve fits the equation y=x. However above this critical frequency, the response of the microcontroller seems to break down and follows the equation y=x/2. For frequencies over 100kHz, the system does not give reliable results. This is explained by the time of the while loop. In the end of this loop the program needs to get back to the beginning of the loop, it is fast but since the frequency is higher it may be not fast enough that’s why the program misses one pulse out of two and shed light on the curves y=1/2x. The curve of the standard deviation divided by the average shows us that around the critical frequency the program is not efficient at all, that makes us believe this is the right explanation. But this graph displays something else, the program for low frequencies and afterwards for low light intensities is very precise. The errors are under 0.5%. And the number of pulse measured is 100. That means that the device can make a measure every 5 min and this is absolutely enough for measuring a biological system.
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| - | Now we need to know if the device is efficient enough to measure low light intensity like fluorescence.
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| - | <h2 id="Fluo">Fluorescence Measurement</h2>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/c/ca/Optique.png" alt="Fluorometer_igem2013_Grenoble-EMSE-LSU" width="600px" /></p>
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| - | <p id="legend"><strong><em>TALKE'coli: C2M part</em></strong><br>
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| - | on the left: the real device, on the right: functional schematic<br>
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| - | The light from the LED lamp goes through the green excitation filter and illuminate the sample thanks to a dichroic mirror. Then the red fluorescent protein is now excited and re-emits red light that goes through a lens that concentrate it on the photodiode.
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| - | <h2 id="Electronic">Electronic circuit</h2>
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| - | <p></p>
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| - | <h2 id="Servo">Servomotor</h2>
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| - | <p>Since we are only using 3 different wavelengths, green for the fluorescence, red for inducing KillerRed and white light to kill the cell, we just need 3 slots. To be easier to calculate, we assign the first slot to the first position and the third slot to the last position.</p>
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| - | <img src="https://static.igem.org/mediawiki/2013/d/da/Servo_pos1.png" alt="Position1_servo" width="450px" />
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| - | <img src="https://static.igem.org/mediawiki/2013/a/a8/Servo_pos2.png" alt="Position2_servo" width="450px" /></p>
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| - | <p id="legend"><strong><em>On the left, the first position of the servomotor and on the right, the second position of the servomotor </em></strong></br>
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| - | The data:</br>
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| - | <strong>L</strong>: distance between the center of the servomotor S and the center of the hole in the box A (6.5cm)</br>
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| - | <strong>h</strong>: height from A to S (2cm)</br>
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| - | <strong>R</strong>: radius of the filter and also the hole in the box (1cm)</br>
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| - | <strong>X</strong>: distance between one part of the arm and the filter rack (0.2cm)</br>
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| - | <strong>b</strong>: distance between the beginning of the filter rack and the filter (0.2cm) – 2b is the distance between each filters</br>
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| - | What we want to know:</br>
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| - | <strong>a</strong>: radius of the servomotor</br>
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| - | <strong>l</strong>: length of the arm that moves the filter rack</br></br>
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| - | </p>
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| - | <p></br>It is known that: </br></br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/c/cd/Equations1-2.PNG" alt="position_eq_servo" /></p>
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| - | <p></br>That means: </br></br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/1/11/Equations_a.PNG" alt="a_radius_servo" /></p>
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| - | <p></br>To have enough power to push and pull the filter rack the angle <strong>α</strong> need to be bigger than 45°, that means:</br></br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/7/7f/Equations_condition.PNG" alt="condition_servo" /></p>
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| - | <p></br>But knowing <strong>a</strong> we can calculate <strong>l</strong> with [1]:</br></br></p>
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| - | <p align="center"><img src="https://static.igem.org/mediawiki/2013/7/74/Equations_l.PNG" alt="l_length_arm_servo" /></p>
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| | <h2 id="Box">The Box</h2> | | <h2 id="Box">The Box</h2> |
| - | <object width="480" height="360"><param name="movie" value="//www.youtube.com/v/ qruRM62kY- k? hl= fr_FR& version= 3"></param><param name="allowFullScreen" value="true"></param><param name="allowscriptaccess" value="always"></param><embed src="//www.youtube.com/v/ qruRM62kY- k? hl= fr_FR& version= 3" type="application/x-shockwave-flash" width="480" height="360" allowscriptaccess="always" allowfullscreen="true"></embed></object> | + | <p align="center"><object width="480" height="360"><param name="movie" value="//www.youtube.com/v/ OY0- y8JZme0? version= 3& hl= fr_FR"></param><param name="allowFullScreen" value="true"></param><param name="allowscriptaccess" value="always"></param><embed src="//www.youtube.com/v/ OY0- y8JZme0? version= 3& hl= fr_FR" type="application/x-shockwave-flash" width="480" height="360" allowscriptaccess="always" allowfullscreen="true"></embed></object ></br></br></p> |
| | + | <p>Our device is built in such a way that the user <strong>only</strong> needs to <strong>define the concentration of living cells</strong> he wants and put <strong>the Erlenmeyer with our engineered bacteria</strong>. From that moment on, the device works in <strong>standalone manner</strong>. It first measures <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Fluo">the initial red fluorescence</a> (<strong>the baseline</strong>). Then it induces the <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Biology#KR">KillerRed</a> protein using <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Biology/KR">the red-inducible promoter</a>. Every <strong>5 minutes</strong>, TalkE'Coli measures <strong>the red fluorescence level</strong> of the culture. Then the light is switched on and the fluorescence is further recorded. This info is used to <strong>build <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Modelling/Building">a model</a> of cell growth and KillerRed response to illumination</strong>. The computer then calculates the <strong>time profile</strong> of the white light intensity used to <strong>stabilize</strong> the living cell concentration. <strong>The main asset</strong> of the device is that it recalculates the model <strong>during the run and thus adjusts the light intensity more precisely</strong>. Finally, when the living cell population is <strong>stabilized at 10% of its target value</strong>, the computer sends a signal to the user to tell him the success of the procedure. |
| | + | </br></br></p> |
| | + | <p>First, we will explain the choice of the different components, then the several experiments we did to find the most accurate parameters for each part of the device : <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Photodiode">the photodiode and Arduino</a>, <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Fluo">fluorescence measurement</a>, <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Electronic">the electronic circuit</a>, <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Servo">the servomotor</a>. All these elements were then integrated in <a href="https://2013.igem.org/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo#Box">the box</a> that we designed and built.</p> |
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| - | <li id="next"><a href="/Team:Grenoble-EMSE-LSU/Project/Modelling/Predict">Next Page</a></li> | + | <li id="next"><a href="/Team:Grenoble-EMSE-LSU/Project/Instrumentation/Fluo">Next Page</a></li> |
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