Research Summary

My current project focuses on the development of a biosensor for detection of cell growth. I work with Marinobacter and E. coli cells to calibrate the sensor and identify key frequency markers in electrical impedance spectroscopy data. In order to take the necessary data points. I use both a potentiostat for lower frequencies, and an LCR meter for higher frequencies. I utilize electrical impedance spectroscopy and cyclic voltametry data to calculate and build the internal circuit for the biosensor chip.
During my research project, I have learned how to work with both the potentiostat and the LCR meter. I learned how to automate measurements using LabView and the PSTrace software as well as MATLAB and Python. I also developed analytical skills for Nyquist and Bode and learned how to analyze and read them. I also learned how to design circuits from said plots and develop visual representation of the circuits.

Milestones

A couple of milestones I achieved in my project

Took Lead on Project

During my first month at WISE Labs, I took over the data collection and analysis portion of project from my mentor. I developed protocols, and automated our plotting software to streamline the data collection process.

Cell Detection

One of the challenges we faced when started to experiment with cells, was that there was very little difference between the electrochemical signals of plain media and bacteria. To rectify this issue, I increased the optical density of the bacteria and added DC offsets to the EIS measurements.

Oxygen Sensor Experiment

In order to correctly calibrate the biosensor, we also needed to account for oxygen levels within the media. I set up a fluorescent oxygen probe system to detect changes in oxygen and how the impedance of bacteria is affected.

Data Collection Process

Data collection begins with using a potentiostat, a adapter, an electrode, and media or cells. After running electrical impedance spectrography (EIS) or cyclic voltammetry (CV) signals, I can then use an automated MATLAB script to plot the data into Nyquist or Bode Plots. Such plots are vital to identify key frequencies and develop the internal circuit of the chip.

Process and Results

Potentiostat Set up

Screen Shot 2023-08-24 at 1.25.11 PM.png

Screen Shot 2023-08-24 at 1.26.50 PM.png

Left: adapter with electrode taking measurements in LB media

Right: Potentiostat set up with adapter and media taking EIS measurements

Plotting Method

Results and Analysis

After taking the data, I use a MATLAB script to plot the average and variance of each data set against each other.

DC 0.01 - BB vs Marinobacter Nyquist Plot Shaded copy.png

DC 0.01 - BB vs Marinobacter Bode Plot.png

We currently plot 4 different types of data. To identify the difference between cells and no cells we use electrical impedance data (Nyquist and Body) or CV data. For pH or oxygen measurements we use open potentiometry data

Example of CV data

Here is an example of CV data for E. coli and LB plotted on top of each other. In CV, a potential is applied to the working electrode of the gold or carbon electrode being used. The resulting current is then measured and plotted along the Y axis. The resulting curve gives vital information regarding the capacitance and resistance of circuit measured within the solution.

Example of EIS data

Nyquist:

Here is an example of the EIS data for Marinobacter and BB media. The average and variance of 3 different trials is taken for each substance and plotted against each other. Additionally, when doing EIS measurements, it is possible to apply a DC offset to the electrode, or a potential between the working and the reference electrode. The process can amplify electrochemical signals between cells and no cells and allow further insight into the data.

Bode:

The same data can then be plotted to view the phase and impedance measured in the media. The phase and impedance are also vital to identify differences between cells and no cells and identify key frequencies at which the biosensor should take data points.

Example of Open Potentiometry Data

Here are some examples of open potentiometry data along with the linear regression. In this experiment, we measured how a change in pH of media affected the measured voltage of the substance. In this experiment, we were able to see a clear trend where a higher pH yielded a lower measured voltage.

Screen Shot 2023-08-24 at 11.32.34 AM.png

Screen Shot 2023-08-24 at 11.47.57 AM.png

Screen Shot 2023-08-24 at 11.49.00 AM.png

Next Steps

Currently, we have been working to adjust our protocol to detect a difference between cells and no cells. Now our focus will shift to scale up our measurements to include the eVOLVER and design an automated system to complete the previously mentioned measurements.