iGEM 2024 — Team dnhs-sandiego-ca

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#### Contents

* [1. Lab Notebook](#notebook)
* [2. Significant Folds](#significant)
* [3. Titrations Data](#titration)

## Lab Notebook

## Significant Folds

## Titrations Data

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{% extends "layout.html" %} {% block title %}Engineering Design{% endblock %} {%
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#### Contents

* [1. Initial Screen](#screen)
* [2. Titrations](#titrations)

## Initial Screen

The primary goal of our project was to create a foundational advancement
in synthetic biology by conducting a large-scale screening of several
promoters and molecules to identify which pair can be used for biosensor
development. Therefore, the first step of the research was to screen each
of the promoters against each of the molecules. There are a total of 21
promoter plates, each with 95 promoters and 1 control well. We also
selected 10 molecules for the screening: PBA represents 3-Phenoxybenzoic
Acid, LOV represent Lovastatin, PRO represents Propoxur, DEP represents
Diethyl Phthalate, TAR represents Tartaric Acid, CAR represents Carbaryl,
BHL represents Butanoyl-Homoserine Lactone, PGA represents Phenylglyoxylic
Acid, PFS represents Perfluorooctane Sulfonate, and CND represents
Cis-Naphthalene Dihydrodiol.

In our first set of experiments, we measured the fluorescent signal
produced by the molecule and the promoter. Disregarding any wells with an
OD600 value less than 0.1 due to a lack of E. coli growth, we selected
promoters with a sfGFP/OD600 < 1.5. However, due to a lack of sufficient
significant molecule-promoter pairs, the cutoff was lowered to 1.35.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign1.png)

Figure 1. sfGFP (fluorescence) and OD600 (cell density) readings of PBA
with several different promoters

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign2.png)

Figure 2. Top hits for the promoter and molecule combinations that produce
high levels of fluorescence. Reference Notebook page for full spreadsheet
of data.

## Titrations

Once the top 8-12 promoters were identified for each molecule, titrations
were performed to observe the change in fluorescence as the concentration
of the molecule changed. An effective biosensor is meant to measure the
amount of a molecule present. Therefore, the promoter should produce a
stronger fluorescent signal in the presence of greater concentrations of
the molecule with a large dynamic range. Concentrations from 0 M to 10 mM
were tested, as shown below:

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign3.png)

Figure 3. Fluorescence level of 12 strains of PBA with increasing
concentration of the molecule after the titration

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign4.png)

Figure 4. Fluorescence level of 12 strains of TAR with increasing
concentration of the molecule after the titration

After the titrations, there was a lack of promoters that produced
increasing fluorescence proportional to the increasing concentrations of
the molecules, despite producing high fluorescence during the initial
screening process. Additionally, the initial screen fluorescence
sfGFP/OD600 values were much higher than the fluorescence at the same
molecule concentration in the titrations.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign5.png)

Figure 5. Comparison of fluorescence level between the initial screen and
the 1mM well during the titration for 12 strains of PBA

In order to troubleshoot this issue, we noticed that several of the
started up E. coli strains did not produce an OD600 value > 0.1,
indicating there was not enough cell density to produce an accurate
fluorescent reading. The strains were regrown and measured to ensure a
high density before repeating the titration experiments.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign6.png)

Figure 6. Fluorescence level of 12 strains of PRO incorporating the data
of the redone PRO strain titrations

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign7.png)

Figure 7. Fluorescence level of 12 strains of TAR incorporating the data
of the redone TAR strain titrations

While this gave us a few more promising results, there was still a largely
linear trend rather than an exponential one with varying concentrations of
the molecule. Through further investigation, we found that the LB broth we
were using for the E. coli strains was contaminated, which could have
affected the results. After the media was remade under sterilized
conditions and autoclaved after dilution to remove any contamination, the
titration was rerun. The titration values were compared to the initial
screening values again.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign8.png)

Figure 8. Comparison of titration fluorescence levels in new and old media
for certain strains grown in both conditions with CND

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign9.png)

Figure 9. Comparison of titration fluorescence levels in new and old media
for certain strains grown in both conditions with DEP

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign10.png)

Figure 10. Comparison of titration fluorescence levels in new and old
media for a strain grown in both conditions with PBA

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign11.png)

Figure 11. Comparison of titration fluorescence levels in initial
screening, 1mM titration with new media, and 1mM titration with old media
for several different strains

As shown above, the titration values were slightly higher with the new,
uncontaminated media, but they still did not reach the level of the
original screen, which is a problem. We decided to test another variable
to address this issue: the freshness of the strains. Some of the strains
were several days old when they were tested in the titrations, whereas the
strains were fresh from the day before when the screening was conducted.
We regrew the strains and conducted the titration again after they had
been in the incubator for only one day.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign12.jpg)

Figure 12. Comparison of titration fluorescence levels with fresh and old
strains for several different strains tested with CAR

The titrations were only repeated with the top 4 strains of each molecule
as a sample size of the total number of strains. This conserved time and
resources so that more variables could be tested in order to understand
the root of the problem. This set of experiments once again improved the
increasing trends of the data with increasing concentrations of the
molecules and increased the level of fluorescence closer to that of the
initial screening, but it was still slightly lower than expected.

Since the titration has been repeated so many times, our team decided to
repeat the initial screen with some plates in order to ensure the screen
was replicable. Specifically, we used AZ02, AZ03, and AZ11. The new screen
(in orange) matched the old screen values (in blue), indicating that the
results are reliable since it can be repeated.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign13-jpg.png)

Figure 13. Comparison of fluorescence levels between the initial screen
and the new screen for Promoter Plate 2 tested with PRO

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign14.png)

Figure 14. Comparison of fluorescence levels between the initial screen
and the new screen for Promoter Plate 3 tested with TAR

We also broke down the data by compiling the fluorescence levels of a
single promoter with each of the 10 molecules. Since it is highly unlikely
that two or more of these molecules induce the same promoter, we expected
a high level of fluorescence with one molecule and low levels with other
molecules. Some of the promoters followed this trend, while others showed
a high level of fluorescence for the majority of molecules. The latter
were disregarded since their fluorescence wasn’t in response to a
particular molecule as the inducer.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign15.png)

Figure 15. Comparison of fluorescence level of cyoA (a promoter found to
produce significant fluorescence with PBA, in red) when tested against
each of the ten molecules

Our team also noticed that some of the fluorescent plates had been
inaccurately matched to their promoters. This could explain the lack of
increasing fluorescence with increasing molecule concentration, the lower
levels of fluorescence compared to the initial screening, and the lack of
activation by a specific molecule. We corrected those promoters and
performed the titration using the corrected strains.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign16.png)

Figure 16. Mismatched strains from the initial screening and their
correctly identified counterparts

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign17.png)

Figure 17. Comparison of fluorescence level of yjaB (a corrected promoter
found to produce significant fluorescence with BHL, in red) when tested
against each of the ten molecules

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign18.png)

Figure 18. Comparison of fluorescence level of mazG (a corrected promoter
found to produce significant fluorescence with PGA, in red) when tested
against each of the ten molecules

The revised promoters improved the analysis of a promoter’s fluorescence
level against all ten of the molecules. The revised promoters were largely
only induced by one molecule. Based on our final data, we selected the
molecule-promoter combinations that produced the best trend in
fluorescence. These pairs have the potential to be further developed into
biosensors for the molecules and greatly contribute to academic research.
In particular, the following molecules and strains were identified to have
an increasing trend with increasing concentration of the molecule: BHL
with the ydel promoter produced a 1.7x fold increase, CND with the ybcK
promoter produced a 2.2x fold increase, CND with the aegA promoter
produced a 2.8x fold increase, and DEP with the yfiF promoter produced a
2.0x fold increase. We then further analyzed these strains through
computational modeling and research.

![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign19.png)
![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign20.png)
![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign21.png)
![](https://static.igem.wiki/teams/5240/engineering-design/engineeringdesign22.png)

Figures 19-22. Titration graphs for selected strains that have the best
potential for future biosensor development based on data analysis

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{% extends "layout.html" %} {% block title %}Experiments{% endblock %} {% block
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#### Contents

* [1. Protocols Used](#protocols)

## Protocols Used

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{% extends "layout.html" %}
{% block title %}Results{% endblock %}
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#### Contents

* [1. Introduction](#introduction)
* [2. Initial Screening](#initial)
* [3. Titrations](#titrations)
* [4. Redone Strains](#redone)
* [5. Fresh and Old Strains](#fresh)
* [6. Media Comparison](#media)
* [7. Corrected Strains](#Corrected)
* [8. Final Strains](#Final)

## Introduction

In order to establish a basis for biosensor development, a series of experiments were conducted using the library of promoters and the ten molecules we selected. First, each promoter and molecule combination were tested for fluorescence using strains started up in 96 well plates. We then processed the data to identify the promoters that produced the most fluorescence for each of the molecules. After the screen, we tested the levels of fluorescence the promoter produced with different concentrations of the molecule using titrations, trouble-shooting to determine the most promising combinations. A labeling system was used for each of the molecules: PBA represents 3-Phenoxybenzoic Acid, LOV represent Lovastatin, PRO represents Propoxur, DEP represents Diethyl Phthalate, TAR represents Tartaric Acid, CAR represents Carbaryl, BHL represents Butanoyl-Homoserine Lactone, PGA represents Phenylglyoxylic Acid, PFS represents Perfluorooctane Sulfonate, and CND represents Cis-Naphthalene Dihydrodiol.

## Initial Screening

An initial screening round was done where each promoter was tested with each molecule at 1mM concentration to identify which ones produced the highest fold increase in fluorescence.

![](https://static.igem.wiki/teams/5240/results/result-1.jpg)

Table 1. Promoters and fold that produced the highest fold in fluorescence (sfGFP/OD600 value greater that 1.35) for each of the ten molecules

From the screening of 2000 promoters, around 8 to 12 were selected for each of the molecules that produced the highest levels of fluorescence following normalization by the density of cells in the well and by the background fluorescence of each promoter.

## Titrations

Once we identified the top fold increases for each molecule, those promoter strains were titrated across 8 concentrations of their corresponding molecules to examine how the fluorescence varies with concentration. The titration graphs are shown below, with the error bars representing ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results2.png)
![](https://static.igem.wiki/teams/5240/results/results3.png)
![](https://static.igem.wiki/teams/5240/results/results4.png)
![](https://static.igem.wiki/teams/5240/results/results5.png)
![](https://static.igem.wiki/teams/5240/results/results6.png)
![](https://static.igem.wiki/teams/5240/results/results7.png)
![](https://static.igem.wiki/teams/5240/results/results8.png)
![](https://static.igem.wiki/teams/5240/results/results10.png)
![](https://static.igem.wiki/teams/5240/results/results11.png)
![](https://static.igem.wiki/teams/5240/results/results12.png)

Figures 1-10. Titration graphs for all the molecules with trends for each strains

We predicted that the fluorescence would increase with increasing concentrations of the respective molecules since the molecules serve as an inducer for GFP transcription. However, many of the strains actually showed a linear or decreasing trend and had overlapping error bars of standard deviation, indicating the results aren’t statistically significant. The level of fluorescence in the titration at 1 mM was also much lower than that of the original screening, so we took several steps to troubleshoot for these issues.

## Redone Strains

Certain titrations were redone using the same procedure if they had an OD600 value less than 0.1, as this value is outside the threshold of the plate reader, in order to correct the molecule concentrations or obtain better cell growth for the plates. The titration graphs are shown below, with the error bars representing ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results13.png)
![](https://static.igem.wiki/teams/5240/results/results14.png)
![](https://static.igem.wiki/teams/5240/results/results15.png)

Figures 11-13. Titration graphs for each molecule containing updated data from the redone strains.

These results indicated a slightly better increasing trend that aligned with our predictions and also made the results more reliable, as fluorescence from a higher cell density can be measured better and trusted more. However, there still weren’t any strains that showed a strong increase or could potentially be used to make an effective biosensor.

## Fresh and Old Strains

One possible source of deviation between the screen and titration was the freshness of the strain, as the time in the incubator and left on the bench differed between the two procedures, so the titration for the top 4 strains for 3 randomly selected molecules were redone using strains that were incubated for only one day (fresh), just as the initial screening had been. The titration graphs are shown below, with the error bars representing ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results16.jpg)
![](https://static.igem.wiki/teams/5240/results/results17.jpg)
![](https://static.igem.wiki/teams/5240/results/results18.jpg)

Figures 14-16. Comparison of fluorescence levels in fresh and old strains for certain strains grown in both conditions with the molecules

The fresh stains notably increased the level of fluorescence produced by each of the molecule-promoter pairs, as shown in the figures above. It also largely eliminated the sudden peaks at random concentrations that were present with the old strains. This may be due to better efficiency of biological processes when the strains are recently grown. However, the deviation between the initial screen and titration still wasn’t completely resolved.

## Media Comparison (old media compared to new media)

After discovering that the M9 minimal salt media was contaminated, the titrations for the top 4 strains of each molecule (except PFS and LOV due to lack of molecule left) were redone. The titration graphs are shown below, with the error bars representing ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results19.png)
![](https://static.igem.wiki/teams/5240/results/results20.png)
![](https://static.igem.wiki/teams/5240/results/results21.png)
![](https://static.igem.wiki/teams/5240/results/results22.png)
![](https://static.igem.wiki/teams/5240/results/results23.png)
![](https://static.igem.wiki/teams/5240/results/results24.png)
![](https://static.igem.wiki/teams/5240/results/results25.png)
![](https://static.igem.wiki/teams/5240/results/results26.png)

Figures 17-24. Comparison of titration fluorescence levels in new and old media for certain strains grown in both conditions with the molecules

Using the new media, there was a lack of contamination to affect the results of the research or interfere with the production of a fluorescent signal. Largely, the new media further increased the level of fluorescence for each of the strains; however there were some exceptions to this. These exceptions may be due to interference of other environmental factors or experimental error. The new media also changed the trend of the data from linear to slightly increasing with increasing concentration of the molecule, which is what was originally expected. The increasing amount of fluorescence provides promising results for the development of a biosensor since the concentration of a molecule present can be estimated from the amount of fluorescence produced.

## Corrected Strains

Our team also realized that some of the promoters that were matched to wells with a high fluorescent signal in the initial screen were mismatched. As a result, we retested these molecule-promoter pairs with the correct promoter and observed the results of the titration. The titration graphs are shown below, with the error bars representing ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results27.png)
![](https://static.igem.wiki/teams/5240/results/results28.png)

Figures 25-26. Titration graphs for each strain with corrected matching

While the newly titrated strains had a largely decreasing or linear trend rather than the expected increasing trend, it did produce higher levels of fluorescence with respect to a single molecule. This means that only one of the molecules induced the fluorescent response in a 1 mM solution, which is expected based on our background research.

## Final Strains

After several iterations through designing, conducting, and reevaluating our experiment, we finally selected some strains with promising titration results, as shown below. We primarily selected these strains due to a high fold increase across different concentrations, significantly different results, and an increasing trend with increasing concentrations of the respective molecule. The error bars represent ±1 SD.

![](https://static.igem.wiki/teams/5240/results/results29.png)
![](https://static.igem.wiki/teams/5240/results/results30.png)
![](https://static.igem.wiki/teams/5240/results/results31.png)
![](https://static.igem.wiki/teams/5240/results/results32.png)

Figures 27-30. Titration graphs for selected strains that have the best potential for future biosensor development based on data analysis

BHL with the ydel promoter produced a 1.7 times fold increase. CND with the ybcK promoter produced a 2.2 times fold increase. CND with the aegA promoter produced a 2.8 times fold increase. Finally, DEP with the yfiF promoter produced a 2.0 times fold increase. While the level of fluorescence has some drops and inconsistencies at certain concentrations, the overall significant, increasing trend indicates that these strains can be further researched to be eventually developed into effective biosensors to measure the concentrations of their corresponding molecules.

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