Proof of Concept
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Manufacturing an aptasensor device to detect the presence of biomarkers in sweat
The goal of our project was to manufacture a working device that could reliably detect the presence of sepsis-related biomarkers in sweat. We developed a sleeve-like microfluidic aptasensor that incorporated: graphene, screen-printed electrodes and microfluidics to monitor the changing levels of relevant biomarkers in patients (Figures 1 and 2). After finding five biomarkers upregulated in sepsis, we decided to use aptamers to recognize the target biomarkers and we stored them in Escherichia coli. Then, we synthesized them in vitro using asymmetric PCR. The synthesized aptamers were attached to reduced graphene oxide (rGO) via pi-pi stacking between aptamer and the rGO. rGO was well-suited for our project, as this material was conductive enough to detect small electrical changes once biomarkers were bound to aptamers attached to rGO. The solution of rGO and aptamer was deposited on the top of the working electrode of screen-printed electrode, which was connected to the potentiostat circuit to detect electrical changes
To detect binding between biomarkers in sweat and aptamers attached to rGO on electrodes, we prepared different concentrations of biomarkers and measured the impedance change of rGO once the solution of sweat with biomarkers passed through the electrode. This change was monitored using a low-cost potentiostat manufactured by our team. To control the flow of sweat over the electrodes, we manufactured an accessible and flexible microfluidic device.
Figure 1: Envisioned prototype of our aptasensor.
Figure 2: The complete assembly of our aptasensor. The components included microfluidics, screen-printed electrodes, aptamers, rGO, potentiostat.
A working proof-of-concept device that reliably detects the presence of soluble biomarkers
To show that our aptasensor would detect the presence of a biomarker in sweat, we prepared concentrations of each biomarker from 1000 nM and 1.9 nM in sweat-mimicking solution with pH of 6. We modified the working electrodes with either the solution of rGO and 10 nM of aptamer or just with rGO, which was a control. Additionally, we had the second control, where we transferred only sweat at either pH 6 or pH 4.7 without biomarker on the top of the electrode modified with either aptamer and rGO or just rGO. We used cyclic voltammeter to detect electrical changes once the biomarker binds to the aptamers. Cyclic voltammetry includes changing the electrode potential while monitoring the current that passes through the system, and we expected to observe a shift in current peak when a biomarker attaches to the aptamer. We connected our potentiostat to JUAMI software, and we set the scan rate as 100 mV/s with voltage oscillating between -2 to 2 V. We ran 10 cycles, which was 200 seconds, for each experiment.
Figure 3: Using cyclic voltammetry to detect binding between lactoferrin aptamer and biomarker.
Data shows the potentiostat output, where change in current was monitored at desired voltage difference.
We observed the shift of the peak current between the control (rGO) and experimental condition (rGO and aptamer) at all concentrations of biomarker, and, as an example, we showed the results of cyclic voltammetry for lactoferrin concentrations of 1.9 nM and 7.8 nM. We observed that the peak current for the control was about 6 mA at biomarker concentrations of 1.9 nM and 7.8 nM (Fig. 3A and 3C). We observed a shift in peak current between the control (rGO) and experimental condition (rGO and aptamer). The peak current on electrodes covered with rGO and lactoferrin aptamer was -2 mA and -1 mA for 7.8nM and 1.9nM respectively (Fig. 3B and 3D). The same trend was observed when the biomarker concentration of 1.9 nM was used.
Next, we found the maximum current and inferred the potential at which this current was observed. Using Ohm’s Law, we calculated the resistance across the rGO sheet (Table 1). Then, we plotted the concentration of biomarkers against the resistance of the rGO sheet (Figure 4).
|Concentration (nM)||rGO||rGO and aptamer|
*-measured as average between pH 4.7 and pH 6 sweat
Table 1: Resistance values of rGO sheet at varying concentrations of lactoferrin biomarker.
Our data shows significantly increased resistance when the aptamer is attached to the rGO compared to the control without aptamer (Figure 4). The control was a flat line, as the resistance values were around the same value for all of the biomarker concentrations.
Figure 4: The resistance of rGO sheet given the concentrations of lactoferrin biomarker.
When lactoferrin aptamer was attached to rGO, we observed the increase in resistance with increasing biomarker concentration until about 400 nM (Figure 4). The data increases monotonically in a range from 50 nM until around 400 nM. Figure 4 also shows that the lowest concentrations of biomarker (1.9 nM - 50 nM) give resistance values that fall under the curve for the negative control, indicating that the signal is not significant compared to background for the low biomarker range. Afterwards the resistance decreases again which could be explained by aptamers being saturated with biomarkers.
This data showed that there was not any non-specific binding and that binding occurred only in the presence of an aptamer attached to the electrode. The shift of the resistance in rGO and aptamer from the resistance in just rGO and its general increase indicates that the binding of biomarkers and aptamers can be measured using our potentiostat. These findings lead us to believe that our potentiostat can successfully measure biomarker concentrations until saturation of aptamers is reached.
While we may not be able to determine an exact relationship between biomarker concentration and resistance, we are excited that we can distinguish between different biomarker concentrations between 50 nM and 400nM threshold. The binding affinity of lactoferrin reported in literature is 1 ± 0.12 nM3 and concentrations between 1-25 nM indicate sepsis. Although our detection sensitivity might not be great in that range, it could be improved by optimizing the attachment of aptamer to rGO, for example by using spacers and a covalently linking method, such as azide linking to PEI-modified rGO.
The binding affinity of lactoferrin reported in literature is 1 ± 0.12 nM. We wanted to improve the sensitivity of our aptasensor and this could be done by optimizing the attachment to rGO. For instance, by using spacers and a covalently linking method, such as azide linking to PEI-modified rGO. To keep our device as accessible as possible, we decided to not use azide linking. Even so, we are able to detect up to 400 nM and can have a significant impact if it’s taken together with the other biomarkers we targeted. This shows proof of concept of our aptasensor, because each module successfully integrated within the final device and we determined the detection limit of our device.
Additionally, to show that non-specific binding did not occur, we ran another control condition, where we added sweat without biomarkers to the electrode with and without the aptamer. If different current peaks were detected on the electrode modified with aptamer, as compared to electrodes without aptamer, then our aptasensor was not actually detecting the binding of biomarkers in the previous experiment. The change in peak current detected earlier could have just been due to the aptamer modification interacting with the buffer in which the biomarker was dissolved in. We prepared sweat solutions at two different pH values, given that we found two recipes in literature for synthetic sweat and wanted to try out both, and added them to the electrode to run cyclic voltammetry (Figure 5). 1,2
Figure 5: Cyclic voltammetry showed the same current peak in both electrode modified with aptamer and rGO and electrode modified with rGO when they were treated with sweat.
Figure 5 showed that the current peak did not shift when sweat was added to the electrode with rGO, and electrode with rGO and aptamer. In other words, the presence or absence of aptamer did not result in a change in the current peak for sweat samples applied to electrodes with rGO, 2ThThese results showed that the change in peak current detected in aptamer-biomarker binding was not due to the aptamer modification interacting with the buffer in which the biomarker was dissolved in, but rather that the current shift only occurred when biomarker was present in sweat. Resistance values for each condition were found using the peak current and corresponding voltage (Table 2 and Figure 6).
|pH 6||pH 4.7|
|rGO||rGO +Aptamer||rGO||rGO+ aptamer|
Table 2: Resistance values of rGO sheet using sweat.
Figure 4: The resistance of rGO sheet given the concentrations of lactoferrin biomarker.
Table 2 showed that the resistance of rGO was the same in both presence and absence of the aptamer when sweat with pH of 6 was added on the top of the electrode. We observed a slight difference in resistance values in presence and absence of aptamers when sweat with pH of 4.7 was used. This difference in resistance values at more acidic pH of sweat could be due to basic pH of the buffer in which aptamer was dissolved and attached to rGO. The buffer in which aptamers were attached to rGO has a pH of 7.4 which might interfere with the sweat at pH of 4.7, as this sweat is acidic. As we used sweat with pH of 6 to dilute biomarkers and run experiments, and given that pH of natural sweat is 6.3, we concluded that sweat of pH 6 was more convenient for running binding experiments between aptamers and biomarkers. 3 The data we obtained using our potentiostat showed that binding between aptamer and biomarker can reliably be detected at biomarker concentrations in the range from 50 nM to 400 nM. We can see the signal due to biomarker binding when the resistance starts to increasing.
Given that the lactoferrin cutoff is far below our threshold value of 400 nM, our device would be able to alert physicians to the patient’s risk of sepsis, as there is still much space left until saturation. This shows proof of concept that we are able to detect when a patient’s biomarker levels are elevated above low values.
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