iGEM 2021 — Team UPenn

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# Team:UPenn/Notebook

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Awards

Project

[Description](https://2021.igem.org/Team%3AUPenn/Description)
[Implementation Plan](https://2021.igem.org/Team%3AUPenn/Implementation)
[Engineering](https://2021.igem.org/Team%3AUPenn/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AUPenn/Proof_Of_Concept)
[Contributions](https://2021.igem.org/Team%3AUPenn/Contribution)

Outreach

[Collaboration](https://2021.igem.org/Team%3AUPenn/Collaborations)
[Partnership](https://2021.igem.org/Team%3AUPenn/Partnership)
[Education and Communication](https://2021.igem.org/Team%3AUPenn/Communication)

Human Practices

Team

[Meet the Team](https://2021.igem.org/Team%3AUPenn/Team)
[Attributions](https://2021.igem.org/Team%3AUPenn/Attributions)

Judging

[Judging Form](https://igem.org/2021_Judging_Form?id=4036)
[Hardware Prize](https://2021.igem.org/Team%3AUPenn/Hardware)

# Notebook

Document the dates you worked on your project. This should be a detailed account of the work done each day for your project.

### What should this page have?

* Chronological notes of what your team is doing.
* Brief descriptions of daily important events.
* Pictures of your progress.
* Mention who participated in what task.

### Inspiration

You can see what others teams have done to organize their notes:

* [2018 Munich](https://2018.igem.org/Team%3AMunich/Notebook)
* [2019 Georgia State](https://2019.igem.org/Team%3AGeorgia_State/Notebook)
* [2019 Newcastle](https://2019.igem.org/Team%3ANewcastle/Notebook)
* [2020 IISER Pune India](https://2020.igem.org/Team%3AIISER-Pune-India/Notebook)
* [2020 Lund](https://2020.igem.org/Team%3ALund/Notebook)
* [2020 NOVA LxPortugal](https://2020.igem.org/Team%3ANOVA_LxPortugal/Notebook)
* [2020 RDFZ China](https://2020.igem.org/Team%3ARDFZ-China/NoteBook)

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# Team:UPenn/Engineering

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Home

Awards

Project

[Description](https://2021.igem.org/Team%3AUPenn/Description)
[Implementation Plan](https://2021.igem.org/Team%3AUPenn/Implementation)
[Engineering](https://2021.igem.org/Team%3AUPenn/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AUPenn/Proof_Of_Concept)
[Contributions](https://2021.igem.org/Team%3AUPenn/Contribution)

Outreach

[Collaboration](https://2021.igem.org/Team%3AUPenn/Collaborations)
[Partnership](https://2021.igem.org/Team%3AUPenn/Partnership)
[Education and Communication](https://2021.igem.org/Team%3AUPenn/Communication)

Human Practices

Team

[Meet the Team](https://2021.igem.org/Team%3AUPenn/Team)
[Attributions](https://2021.igem.org/Team%3AUPenn/Attributions)

Judging

[Judging Form](https://igem.org/2021_Judging_Form?id=4036)
[Hardware Prize](https://2021.igem.org/Team%3AUPenn/Hardware)

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# ENGINEERING

[ ]
The DBTL Engineering Cycle

![](https://static.igem.org/mediawiki/2021/1/1f/T--UPenn--DBTL1.png)
![](https://static.igem.org/mediawiki/2021/3/38/T--UPenn--DBTL2.png)
![](https://static.igem.org/mediawiki/2021/8/88/T--UPenn--DBTL3.png)

[ ]
Hardware

The device hardware consists of two printed circuit boards (PCBs) sandwiching a standard 96-well clear-bottom plate. The top PCB is a modified OptoPlate-96 (Bugaj and Lim, 2019), and it consists of a 600nm used to take optical density measurements, a blue LED used to stimulate the light-dependent proteins, and in later iterations, a red LED for exciting red light optogenetic systems. The bottom PCB is referred to as the PlateReader and consists of a photodiode used to measure light intensity and a UV LED used to excite our fluorescent protein reporter, mAmetrine (Drobizhev, M., et al., 2011).

This device will be able to stimulate cells expressing optogenetically controllable protein circuits while monitoring the circuits output via fluorescence as well as cell growth through optical density in a 96-well plate format. Therefore the user would be able to run up to 96 different illumination patterns while obtaining live readout of fluorescent protein production and cell growth without disrupting the experiment in a high throughput manner.

In a typical experiment, there will be an optogenetically-responsive sample placed in each well of the 96-well plate. Blue light will control the optogenetic tool, and the combination of the OD LED, excitation LED, and photodiode will allow for real-time measurements of sample OD and fluorescence. The output of their optogenetic pathways may also be measured and observed. Thus, the OptoReader has the ability to stimulate and measure cells simultaneously.

### *OPTOPLATE*

### *EXPERIMENTS*

### *PLATEREADER*

## ***OptoPlate***

The OptoPlate consists of 96 blue and red LEDs arranged in a 96-well plate format that allows for dual stimulation of blue and red light sensitive optogenetic tools (Bugaj and Lim, 2019). The OptoPlate was our impetus to create the Plate Reader and overall the OptoReader. We also fitted the Optoplate with a 600nm LED for measuring optical density.

## ***Plate Reader***

The PlateReader, consists of 96 UV LEDs and 96 photodiodes arranged in a 96-well plate format. The UV LED emits at a wavelength of 395 nm, and therefore allows for excitation of the fluorescent protein we use in our experiments, mAmetrine.

The photodiodes are light sensors that generate a current in response to photons allowing us to read a voltage accross a resistor. The voltage measured is proportional to the intensity of the light hitting the photodiode which allows us to measure protein fluorescence.

Each UV LED on the plate is connected to one of four LED drivers. An LED driver provides the electricity needed to power an LED. A single driver is able to control 24 different LEDs. Therefore the entire plate requires four drivers to supply power to each of the 96 LEDs. An LED driver has the ability to regulate the current and voltage that is supplied to the LED. This ensures that the LED has a consistent voltage applied to it so that its light does not flicker. Additionally, the drivers functions to regulate the amount of current that is applied to the LED. This allows for the LEDs to have their light intensity customized which will prove useful in optogenetic experiments. Each LED driver is connected to a capacitor and a resistor in order to to facilitate a steady current flowing into the driver.

Each photodiode is connected to one of six multiplexers. Each multiplexer can take on 16 photodiodes, thus requiring six multiplexers to power the entire array of photodiodes. A multiplexer takes in many inputs and choose which to send to the Arduino. As a result, the multiplexers can take a reading from many different photodiodes and come out with a single output.
The entire plate is controlled by an Arduino Micro, a microcontroller, connected via USB to the Arduino interface on a computer.

## ***Adaptors***

In order to ensure that the two PCBs can successfully and snugly fit the 96-well plate in between them, two adaptors were designed and 3D printed to secured the PlateReader and the OptoPlate sandwiching a 96-well plate.

The bottom adaptor is secured to the PlateReader by screws and magnets, and it snaps into the bottom of the 96-well plate. This adaptor ensures that the 96-well plate does not shake on top of the PlateReader.

The top adaptor acts as more of a casing. It is secured onto the OptoPlate with screws and surrounds the 96-well plate. A small wall extends from the top adaptor into each well of the 96-well plate in order to ensure no spillage of liquid or light occurs between adjacent wells. A separator that covers half of each well and includes a small pinhole. The small hole allows red light to pass through into the well in a more focused manner. This ensures that there is no extra scattering of red light that would impact any optical density readings.

## ***Filters***

![](https://static.igem.org/mediawiki/2021/e/ee/T--UPenn--Filter_Spectra.png)

In order to ensure that the photodiode does not read the intensities of unwanted wavelengths, two filtering methods were used. The first is a physical filter, a thin film of acrylic that acts as a long-pass filter with a cutoff at 560 nm. Thus, since the stimulation of the fluorescent protein occurs at 395nm, very little of the light from the excitation LED should penetrate the filter to reach the photodiode. Additionally, the photodiode also has its own spectrum of light sensitivity. The photodiode acts as a band-pass filter that reads wavelengths between 480nm-660nm. This ensures that the photodiode is able to read light from the red LED (~600 nm) and the fluorescence (~525 nm). The photodiode also blocks out light from the excitation LED and the stimulation LED used to stimulate optogenetic tools.

[ ]
Software

Our software package includes device control as well as a Graphical User Interface (GUI) programmed in Python and C++ (Arduino)

![](https://static.igem.org/mediawiki/2021/d/d9/T--UPenn--software.png)

Our Graphical User Interface (GUI) allows a user to easily set measurement intervals and optogenetic stimulation intensity and intervals for each well of a 96 well plate.
[](https://static.igem.org/mediawiki/2021/c/cd/T--UPenn--GUIReaderVid.mp4)

### Software Architecture

The user inputs their protocol preferences in the GUI. Via serial communication, the protocols will be sent to the correct Arduino board to control the Blue, Red, and UV LEDs at the specified times.

![](https://static.igem.org/mediawiki/2021/3/3a/T--UPenn--software_diag.jpg)

**The link to the iGEM Judging Release for our software package is found [HERE](https://github.com/igemsoftware2021/UPenn/releases/tag/1.0.0)**

## ***Why the Optoreader?***

The OptoReader was designed, engineered, and tested to overcome current research barrier using optogenetics and increase the depth and types of experiments that can be carried out. Our team engineered an economical device that allows for high-throughput optogenetic experiments through simultaneous fluorescence and optical density readings and optogenetic stimulation in a 96-well plate format. The OptoReader consists of two printed circuit boards (PCB) that sandwich a 96-well plate. The top board is made up of an array of 96 LEDs used for opto-tool stimulation and 96 LEDs used for optical density measurements. The bottom PCB is made of a similar array of 96 LEDs and 96 photodiodes/light sensors that stimulate fluorescence and measure light intensity respectively. With a user-friendly graphical user interface, the OptoReader’s 96-well format allows for a high-throughput experimental design where the user can apply up to 96 different patterns.

### **References**

1. Drobizhev, M., et al., Two-photon absorption properties of fluorescent proteins. Nat Methods, 2011. 8(5): p. 393-9.

2. Bugaj, L.J. and W.A. Lim, High-throughput multicolor optogenetics in microwell plates. Nat Protoc, 2019. 14(7): p. 2205-2228.

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# Team:UPenn/Experiments

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Home

Awards

Project

[Description](https://2021.igem.org/Team%3AUPenn/Description)
[Implementation Plan](https://2021.igem.org/Team%3AUPenn/Implementation)
[Engineering](https://2021.igem.org/Team%3AUPenn/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AUPenn/Proof_Of_Concept)
[Contributions](https://2021.igem.org/Team%3AUPenn/Contribution)

Outreach

[Collaboration](https://2021.igem.org/Team%3AUPenn/Collaborations)
[Partnership](https://2021.igem.org/Team%3AUPenn/Partnership)
[Education and Communication](https://2021.igem.org/Team%3AUPenn/Communication)

Human Practices

Team

[Meet the Team](https://2021.igem.org/Team%3AUPenn/Team)
[Attributions](https://2021.igem.org/Team%3AUPenn/Attributions)

Judging

[Judging Form](https://igem.org/2021_Judging_Form?id=4036)
[Hardware Prize](https://2021.igem.org/Team%3AUPenn/Hardware)

# Proof of Concept

## Fluorescence Calibration

In order to test the device’s ability to detect fluorescence, characterization experiments were conducted with the fluorescent dye, Lucifer Yellow, so that the concentration of dye and thus the expected relative fluorescence would be a known variable. Starting with the stock solution of the dye, serial dilutions of the dye by differing factors were created.

## Calibration Curves

In order to create calibration curves for the fluorescence readout from the device, the stock solution was diluted with 3x dilutions until a dilution factor of 2916x was reached. Each dilution was plated in every well of the plate, and measurements were taken. The UV LED excited the fluorescent of the dye, and the photodiode measured the intensity of the fluorescent. The photodiode can take a single reading in about 10 ms. For this experiment, the photodiode took 100 readings per well at a time. These values were averaged to output a single, averaged reading per well for each dilution of the dye. After conducting the experiment thusly for all the dilutions, each well had a single photodiode reading value for each dilution. The different photodiode readings for a single well at different dilutions were then fit to a four parameter sigmoidal curve resulting in 96 different calibration curves.

To test the efficacy of the calibration curves, different dilutions of known concentration were created in random order and plated in all 96 wells. Photodiode readings were taken in a similar fashion where 100 readings per well were averaged to output a single reading per well. These readings were then compared to the calibration curve for the same well. Just by observing the placement of the readings, it seemed probable that the curve could accurately predict the concentration of the fluorescent dye given the photodiode reading.

For further confirmation, the photodiode readings were used to extrapolate the predicted concentration value. The spread of these predicted concentration values was compared to the spread of the initial photodiode readings to determine whether or not running the data through the calibration curve made the data more accurate and precise.

## Optical Density Calibration

The device’s ability to read the optical density of a cell culture accurately and precisely was tested in a very similar way to how the fluorescence reading ability was tested. E. coli were first grown in LB broth and then concentrated to make a highly concentrated stock of bacteria. After consulting with collaborators, it was determined that they generally work with optical densities (OD) around 4-10. Thus, the bacteria was concentrated to an OD of about 10 in order to reach that high limit of detection. The actual ODs of the bacteria were measured with a Nanodrop machine and correlate to the concentration of the bacteria in a sample. The sample was then diluted to ODs ranging between 0 and 10. Each dilution was plated in every well of the plate and measurements were taken. Once again, 100 readings per well were taken and averaged so that the output from the experiment was one averaged reading per well for a given dilution.

Unlike the fluorescent reading experiments, the intensity of the red LED can be varied in OD measurements. The OD of each diluted cell culture was measured with the intensity of the red LED varying on a scale of 200-800 (the total range of the intensity of the LED runs from 0-4095 in arbitrary units). Based on the experiments, it was found that intensities below 200 did not accurately represent

## Overnight in Bacteria

In order to test the robustness of the device to conduct experiments over long time scales, a series of experiments were conducted over a period of 18 hours. We collected both optical density and fluorescence measurements of arabinose-induced fluorescent bacteria. mAmetrine is a fluorescence protein that was cloned into *E. Coli.* Over 18 hours, we confirmed that bacteria could thrive in the device which was detected through optical density measurements that were corroborated by fluorescence measurements as well.

## Stimulating an Opto-Tool

After validating that each part of the OptoReader worked independently (LEDs and photodiodes), we aimed to test our device in a biological system. Using the pDusk system, we were able to show light-dependent protein production in e. Coli.

pDusk is a system that activates transcription of a fluorescence protein (we cloned mAmetrine) in darkness and represses gene expression in light through a two-component system.

Over 18 hours, we tested two light conditions: darkness and 10% light dosage. Results showed a significant difference in mAmetrine production as indicated by fluorescence values normalized by optical density measurements. Thus, the OptoReader has proven to be able to monitor cell growth, read fluorescent output, and successfully activate/deactivate opto-tools via light-controlled gene expression taking high-throughput data at consistent reading intervals that could not have been achieved through manual reading methodologies that were previously available.

## Feedback Control

Lorem ipsum

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# Team:UPenn/Results

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Home

Awards

Project

[Description](https://2021.igem.org/Team%3AUPenn/Description)
[Implementation Plan](https://2021.igem.org/Team%3AUPenn/Implementation)
[Engineering](https://2021.igem.org/Team%3AUPenn/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AUPenn/Proof_Of_Concept)
[Contributions](https://2021.igem.org/Team%3AUPenn/Contribution)

Outreach

[Collaboration](https://2021.igem.org/Team%3AUPenn/Collaborations)
[Partnership](https://2021.igem.org/Team%3AUPenn/Partnership)
[Education and Communication](https://2021.igem.org/Team%3AUPenn/Communication)

Human Practices

Team

[Meet the Team](https://2021.igem.org/Team%3AUPenn/Team)
[Attributions](https://2021.igem.org/Team%3AUPenn/Attributions)

Judging

[Judging Form](https://igem.org/2021_Judging_Form?id=4036)
[Hardware Prize](https://2021.igem.org/Team%3AUPenn/Hardware)

# RESULTS

# Results

You can describe the results of your project and your future plans here.

### What should this page contain?

* Clearly and objectively describe the results of your work.
* Future plans for the project.
* Considerations for replicating the experiments.

### Describe what your results mean

* Interpretation of the results obtained during your project. Don't just show a plot/figure/graph/other, tell us what you think the data means. This is an important part of your project that the judges will look for.
* Show data, but remember **all measurement and characterization data must also be on the Part's Main Page on the [Registry](http://parts.igem.org/Main_Page).** Otherwise these data will not be in consideration for any medals or part awards!
* Consider including an analysis summary section to discuss what your results mean. Judges like to read what you think your data means, beyond all the data you have acquired during your project.

### Project Achievements

You can also include a list of bullet points (and links) of the successes and failures you have had over your summer. It is a quick reference page for the judges to see what you achieved during your summer.

* A list of linked bullet points of the successful results during your project
* A list of linked bullet points of the unsuccessful results during your project. This is about being scientifically honest. If you worked on an area for a long time with no success, tell us so we know where you put your effort.

### Inspiration

See how other teams presented their results.

* [2019 Newcastle](https://2019.igem.org/Team%3ANewcastle/Results)
* [2019 Munich](https://2019.igem.org/Team%3AMunich/Results)
* [2019 Tec Chihuahua](https://2019.igem.org/Team%3ATec-Chihuahua/Results)
* [2020 Aalto Helsinki](https://2020.igem.org/Team%3AAalto-Helsinki/Results)
* [2020 GreatBay SCIE](https://2020.igem.org/Team%3AGreatBay_SCIE/Results)
* [2020 Queens Canada](https://2020.igem.org/Team%3AQueens_Canada/Results)