<p>To kill more or less cell, our device needs to control light intensity. To do so, we make this electronic circuit shown below.</br></br>
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<p id="legend"><strong><em>Electronic circuit that enables us to control light intensity</em></strong></br>
<p id="legend"><strong><em>Electronic circuit that enables us to control light intensity</em></strong></br>
This circuit stabilizes the amperage of the LED lamp at 0.5A thanks to a bipolar transistor, three diodes and the R3 and R4 resistors.
This circuit stabilizes the amperage of the LED lamp at 0.5A thanks to a bipolar transistor, three diodes and the R3 and R4 resistors.
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</br>The MOS transistor is controlled by Arduino and is used like a switch. It allows us to control the average light intensity of the LED lamp.
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</br>The MOS transistor is controlled by Arduino and is used like a switch. It allows us to control the average light intensity of the LED lamp.
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<p>The first part of this circuit – all components above the MOS transistor - stabilizes the amperage of the LED lamp and the second – composed by the MOS transistor and Arduino - allows us to control the average light intensity of the LED lamp.</br>
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The nominal power of the LED is 6W when 12V is applied. That means that the amperage going through the LED lamp is 0.5A.</br>
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Since we cannot be sure that our alimentation is completely stable, we need to stabilize it thank to a bipolar transistor, three diodes and two resistors.</br></br>
Our project aims to control the concentration of living bacteria in a culture. 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 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.
Logical scheme of our device
The computer is giving orders to the microcontroller that control the light source (intensity and wavelengths) that illuminate the sample. Then the photodiode is measuring the level of fluorescence of the Red Fluorescent protein that is produced in the sample and the microcontroller is giving back the information to the computer that will change the intensity and the wavelength according to the measurement
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.
However 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.
A member of the team working on the photodiode
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 below.
Oscillograms showing the two different mode of the photodiode.The first oscillogramm shows the pulse train mode and the second the 50% duty cycle mode
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.
Arduino
Arduino is an (easily) programmable microcontroller. It is used here to convert the frequency given by the photodiode in irradiance that gives us the light intensity. In
addition, it will communicate with the computer and control the lamp intensity to act of
the bacterial suspension. To measure the frequency of the peaks emitted by the photodiode, the Arduino
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:
Irradiance=frequency/(frequency scaling)= samples/(frequency scaling × length)
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.
If the algorithm is right, the curve should follow the equation x=y, which means that Arduino and the oscilloscope measure the same frequencies.
Characterization of the algorithm in Arduino
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 cycle mode, and the last one gives us the standard deviation of the 50% duty cycle mode
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 microcontroller program. At the end of this loop the program jump back to the beginning of the loop, but when the photodiode emits peaks at increasing frequencies, the microcontroller is not fast enough and misses one pulse out of two which explains the curves y=x then y=x/2. efficient at all, that makes us believe this is the right explanation. In addition, the plot of the standard deviation as a function of the frequency demonstrates that the system is very precise for low light intensities. The errors are below 0.5% when 100 pulses are recorded. At the lowest illuminations, the device will measure the fluorescence of the bacterial culture every 5 min, which is enough for this kind of sample. In the next paragraph, we are going to see that the device is efficient enough to measure low light intensity like fluorescence.
Fluorescence Measurement
For the proof of concept of 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 we 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.
TALKE'coli: C2M part
on the left: the real device, on the right: functional schematic
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.
Electronic circuit
To kill more or less cell, our device needs to control light intensity. To do so, we make this electronic circuit shown below.
Electronic circuit that enables us to control light intensity
This circuit stabilizes the amperage of the LED lamp at 0.5A thanks to a bipolar transistor, three diodes and the R3 and R4 resistors.
The MOS transistor is controlled by Arduino and is used like a switch. It allows us to control the average light intensity of the LED lamp.
The first part of this circuit – all components above the MOS transistor - stabilizes the amperage of the LED lamp and the second – composed by the MOS transistor and Arduino - allows us to control the average light intensity of the LED lamp.
The nominal power of the LED is 6W when 12V is applied. That means that the amperage going through the LED lamp is 0.5A.
Since we cannot be sure that our alimentation is completely stable, we need to stabilize it thank to a bipolar transistor, three diodes and two resistors.
We know that:
Servomotor
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.
On the left, the first position of the servomotor and on the right, the second position of the servomotor
Known dimensions :
L: distance between the center of the servomotor S and the center of the hole in the box A (6.5cm)
h: height from A to S (2cm)
R: radius of the filter and also the hole in the box (1cm)
X: distance between one part of the arm and the filter rack (0.2cm)
b: distance between the beginning of the filter rack and the filter (0.2cm) – 2b is the distance between each filters
Dimensions to determine::
a: radius of the servomotor
l: length of the arm that moves the filter rack
A rotating servomotor was used to move a sliding filter holder in front of the light and the photodiode. Geometrical considerations explained above allowed us to dimension the lever arm that translates the rotating movement of the motor in the translation of the filter rack.
It is known that:
$L=a+\sqrt{l^2-h^2}+X+b+R$ (first position [1])
$L=\sqrt{l^2-h^2}+X+5.(b+R)-a$ (second position [2])
That means:
To have enough power to push and pull the filter rack the angle α need to be bigger than 45°, that means:
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