Hardware

Micro-Q

Overview

Traditionally, the diagnosis of coronary artery disease (CAD) is time-consuming. In the period between tests and results, patients experience anxiety and stress which can lead to patient unhappiness and health decline (Alizadehsani et al., 2012). To address this issue, Lambert iGEM created Micro-Q (see Fig. 1): a frugal PCR tube fluorometer with minimal set-up, capable of quantifying fluorescent biosensor samples within seconds. With a cost of under $20, this device conveniently quantifies various fluorescent signals and sends the results to a mobile app by utilizing a 405nm laser as an excitation light source, a photoresistor sensor to measure fluorescence intensity from PCR tube samples (20-200 µL), and an ESP32 Wi-Fi Microcontroller to process sensor input and transmit data. Micro-Q is entirely open-source, so users can customize the design to fit other reaction containers and measure other fluorescent signals by replacing the light source and filtering for different wavelengths. As a result, this fluorometer enables users worldwide to cost-effectively and rapidly measure their risk of CAD and quantify fluorescence signals.

Figure 1. Micro-Q and its mobile app side-by-side.

Parts List

Design

Micro-Q utilizes two modular components to quantify different types of fluorescent signals: the laser and the emission filter (see Fig. 2). Users can swap the emission filter to block excess light from the laser to direct the sample’s fluorescence to the photoresistor; moreover, they can swap different wavelength lasers to excite the sample and allow for the quantification of their various fluorescence outputs. This photoresistor measures the light intensity, sends it to the ESP32, and updates a database. Micro-Q results can then be visualized with our mobile phone app that depicts the relative fluorescence units (RFU) and the converted microRNA (miRNA) concentration; using this method, miRNA ranges can detect the progression of CAD.

Figure 2. Schematic of Micro-Q.

Schematic

Users can assemble Micro-Q by 3D printing the STL files for the 2 caps and main body found on this GitLab Repository (see Fig. 3). Attach the 2 buttons into the side of the body and slide the photoresistor in the back, twisting the prongs so that these components wrap around into the 2 side channels of the device. Since this may require trial and error, users can use a small screwdriver or object to guide the prongs. Next, solder the connections following the schematic shown in Figure 4. After, screw the laser module into place by fitting the cap through the hole and mounting the module from the other side of the wall. Fit the larger lid into place to cover all of the wiring. Slide the plastic filter into place behind the holder for the PCR tube.

Figure 3. STL renders of Micro-Q from several angles.

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Figure 4. Schematic of Micro-Q wiring.

Usage

To use Micro-Q, first insert a blank PCR tube in the designated holder, close the fluorometer, plug the laser into the power supply, and press Button 1 to read the blank. Then, open the lid and remove the sample. Pipette your sample into a PCR tube and insert it into the designated holder. Close the lid, and press Button 2 to get a reading (see Fig. 5 and 6).

Figure 5. PCR tube holder and buttons of Micro-Q.

Software Pipeline

The photoresistor reads the RFU after a user inserts a PCR tube and takes a measurement. The microcontroller passes this value through a pre-trained linear regression model, producing similar values to a commercial spectrophotometer and sending it to the Google Firestore Database (via wifi) to store in a document. This value is displayed on the mobile app by authenticating with the specific Micro-Q reader; the mobile app shows the raw fluorescence intensity and the converted miRNA concentration through a pre-trained model as shown in Figure 7 (see Modeling). Figure 8 below depicts this entire software pipeline in a flowchart. The files for the mobile app and Micro-Q hardware/CAD can be found on the Software Tools README.

Figure 7. Screenshot from Micro-Q app displaying read value, connection status, and blank status.

Figure 8. Software pipeline of Micro-Q, depicting how the signal translates to miRNA concentration.

Quantification Algorithm

Micro-Q uses a photoresistor to measure the fluorescence of a sample inserted into the device. The photoresistor outputs a current that reflects the light intensity that it observes; since an emission filter is placed directly in front of the photoresistor, the only light that will hit this sensor is fluorescence from the sample. When users press Button 1, the ESP32 microcontroller records a brightness value of a blank, which is used to calculate fluorescence when other samples are measured. Upon pressing Button 2, the ESP32 records a value from the photoresistor and uses the following formula to calculate a brightness value. F_t is the brightness of a fluorescent sample, and F₀ is the brightness of a blank (PSI, n.d.):

\( F_{t}-F_{0}\)

We tested Micro-Q with different concentrations of fluorescein and noticed a logarithmic curve in the Fluorescence vs. Concentration graph shown below (see Fig. 9). Upon further research, we discovered that the photoresistor output is logarithmic, meaning that the output from the photoresistor must be processed so that fluorescence is linearly correlated to concentration. To linearize our data, we applied a power series regression using the curve shown in Figure 10, since we found this is the best function to apply as it achieved the highest R² value when linearized (see Fig. 11). The results are shown below.

\( RFU = 0.00144(F_{t}-F_{0})^{1.75} \)

Figure 9. Nonlinear relationship between concentration and RFU measured by Micro-Q.

Figure 10. Power series regression to linearize Micro-Q values to plate reader values.

Figure 11. Linear relationship between concentration and RFU measured by Micro-Q after processing the data with a power series function.

The ESP32 uses an API to transmit this brightness value to a Firestore Database, also recording a key unique to the specific Micro-Q device. The corresponding mobile app obtains the value from the Database using this unique key and displays it to the user.

Results

Micro-Q was tested using fluorescein from concentrations 0 - 500 µM. To determine its efficacy compared to a commercial fluorometer, we measured triplicates of several concentrations with sample sizes of 100 µL in a plate reader and in Micro-Q. Since relative fluorescence units (RFU) are relative, we scaled the output of Micro-Q to match the scale of the output from the plate reader so that they can be compared (see Fig. 12).

Figure 12. Measurements from plate reader and Micro-Q at different concentrations of fluorescein.

In order to have an accurate comparison of the data from the plate reader and Micro-Q, we added points at the origin to our data set and calculated a slope from a linear regression for each measurement device, assuming a y-intercept of 0. The slopes of the data are ~0.9473 and ~0.9194 from Micro-Q, respectively, achieving a percent error of -2.952%

Micro-Q was also compared against a plate reader in the quantification of BBa_J428112 in DH5-alpha and BL21. The fluorescence/OD600 values are consistent between Micro-Q and plate reader at 6766.657 and 7405.837 for DH5-alpha, and 16916.56 and 21328.17 for BL21. When comparing fluorescence in each cell strain individually, the error bars for Micro-Q and plate reader overlap (see Fig. 13). Therefore, the outputs of Micro-Q and plate reader are not significantly different, validating the fluorescence measurement of our hardware device.

Figure 13. Characterization of BBa_J428112 in DH5-alpha and BL21 quantified in both Micro-Q and plate reader. The error bars between Micro-Q and plate reader do overlap, suggesting there is not a statistically significant difference.

Electrochemical Reporter Mechanisms

Overview

Before choosing a fluorescent reporter for CADlock, Lambert iGEM did extensive research into electrochemical reporter mechanisms. We explored several methods such as galvanic cells and changes in impedance. We did not pursue these methods for this year's project after conducting our initial experiments due to insignificant results. Electrochemical reporting mechanisms provide numerous benefits when it comes to accurate quantification and point of care testing (POCT) (Grieshaber et al., 2008). Instead of attempting to quantify and analyze colorimetric variable yields from many biosensors, using electrochemical biosensors enables straightforward quantification as it measures the change in electrical outputs in a reaction solution. Many electrochemical biosensors are paired with microfluidic chips to provide an intuitive, frugal, and POCT quantification method. Although we did not implement electrochemical reporter mechanisms in our project this year due to time constraints, we explored both oxidation-reduction (redox) reactions and impedance methods for future electrochemical reporter-based iterations of our biosensors.

Redox

Redox reactions are chemical reactions in which a current is produced due to movement of electrons between two solutions (see Fig. 14). Initially, the two solutions must have a significant difference in electrochemical potential to allow electrons to spontaneously move to the solution with a lower potential. The solution with the higher potential acts as the electron donor, losing its electrons to an electron acceptor; the electron donor is oxidized, while the electron acceptor is reduced (Bojang & Wu, 2020). Then, an electrical measurement device, such as an ammeter or multimeter, can measure the movement of electrons as a current (amps).

Figure 14. Diagram depicting a redox reaction.

In order to utilize the redox reaction with our biosensors, we planned to use a pathway of RCA to act as the electron donor in our redox reaction (see RCA). The RCA pathway would produce electrons during the amplification process of microRNA (miRNA) that would flow to an area of higher charge, creating a measurable current. Thus, the galvanic cell could be setup with a 2-chamber system: the electrochemical biosensor, miRNA sample, and the anode in one chamber and the cathode in the other (see Fig. 15). The electrodes would be connected with an ammeter in between to measure the current and a saltwater bridge to complete the circuit. The readings of the current could be used to quantify the miRNA sample in the solution.

Figure 15. Galvanic cell setup for redox reaction measurement.

However, after researching its feasibility, we realized that RCA would not be able to produce enough electrons to create a significant charge that could be detected by low-cost ammeters. Additionally, the two-chamber system is too complex to be effectively recreated on a millifluidic scale for POCT application due to the difficulty in fitting tiny electrodes in such a small scale and maintaining an equal amount of liquid touching each electrode. Moreover, the electrodes are prone to wear which can change the surface area of electrodes and lead to inaccurate results. This is a major drawback for users as the electrodes and solutions must be replaced after each use. For these reasons, this method was discontinued.

Impedance

The second electrochemical method we tested was using impedance-based sensing, which functions by comparing the impedance of the solution, or the solution’s ability to conduct electricity, before and after an enzymatic reaction (Mercer et al., 2019). This method assumes that a reaction’s product is more or less resistant to the flow of electrons than the substrate. We experimented with two different pathways for this method: breaking down sugars to change and producing DNA to block the conductivity of methylene blue.

Sugar Breakdown

Sugars can directly affect an electrical current by impeding the flow of electrons (Hönes et al., 2008). Sucrose is a disaccharide that can be broken down into the monosaccharides glucose and fructose using various enzymes. Although all sugars have the impedance property, smaller sugar molecules have a higher impedance than larger ones. We hypothesized that there may be higher impedance of the solution by breaking down sucrose into its smaller components. For this reporter mechanism, we explored the use of invertase, an enzyme that breaks down sucrose into glucose and fructose (see Fig. 16). We designed a biosensor with invertase as the downstream reporter produced in the presence of a target biomarker. Invertase breaks down free sucrose into glucose and fructose, increasing the impedance of the solution and decreasing the current passing through the solution. The resulting solution can be measured with a glucose meter or a multimeter.

Figure 16. Invertase breaks down sucrose into glucose and fructose.

To test this, we set up an experiment to simulate a sucrose and electrolyte solution before and after adding invertase and tested the conductivity of a 50mL solution containing 3.4 grams (0.01 moles) of sucrose compared to a 50mL solution containing 1.8 grams (0.01 moles) of glucose and 1.8 grams (0.01 moles) of fructose. The first solution containing sucrose and salt had a consistently higher current than the second solution containing glucose, fructose, and salt (see Table 1). Thus, we can conclude that the breakdown of sucrose into its counterparts increases its ability to impede the flow of electricity. This reporter mechanism has fewer steps, making it ideal for electrochemical applications.

DNA Production

We also conducted experiments to determine if DNA binding to methylene blue increases the net impedance (Lee et al., 2013). We theorized that in a solution containing methylene blue as the electrolyte, added DNA molecules will bind to the methylene blue molecules and impede its ability to conduct electricity. As a result, we expected to detect less current with the solution containing both DNA and methylene blue compared to when only methylene blue is present.

However, the results showed that the solution containing both DNA and methylene blue had a higher current than the solution containing just methylene blue (see Table 2). This is likely because we did not take into account the conductivity of both the DNA and the buffer solution it was contained in.

Future Implementations

After assessing these electrochemical reporter mechanisms, we plan on using the Invertase reporter mechanism to advance our measurement tools next year. Invertase offers the most straightforward and consistent electrochemical application as it does not require multiple chambers and yields reproducible results (Hammond et al., 2016). An electrochemical biosensor would allow for an easier measurement setup that can directly quantify samples without the inconvenience of filters, lasers, and photoresistors.

References