Listeria monocytogenes sensing

Figure 4.6: (a) Spectrum obtained for the bare device. (b) Calibration curves in the range [0;10]

ng/mL for the resonance frequency and magnitude of imaginary part of impedance.

4.4 Listeria monocytogenes sensing

The EIS platform used for detection of protein tau was also employed for another application, namely the implementation of a point of care diagnostic tool able to detect the pathogen Listeria monocytogenes⁷⁵. Foodborne diseases represent a widespread problem worldwide, affecting both developed and developing countries, despite the great improvement in food safety and quality control⁸⁷. In this respect, Listeria monocytogenes represents a potential risk to human health, because of its survival mechanisms and ability of adaptation, which allows its persistence and growth in different environmental conditions (cold temperatures, low pH and high salt concentration), leading to its presence in living form also if the food is treated with the standard safety methods⁸⁸. The high incidence of foodborne diseases caused by pathogen contamination led to the development of fast, portable and automated platforms able to detect these kinds of bacteria and their toxins during transport, storage and transformation of the food.

Electrochemical Impedance Spectroscopy based biosensors have been widely used for this purpose, since they present great advantages in terms of ease of miniaturization, lack of reagents, sensitivity, and low cost. In this case, the signal change is due to the release of ionic metabolites from living cells, which leads to bacterial identification and quantification.

Furthermore, the improvements in microfabrication and the actual trend in electronic miniaturization allow the implementation of the same functionalities of the traditional

(a) (b)

75 electrochemical setup in compact and portable Lab On Chip devices, offering possible applications in this field because of the continuous improvement in sensitivity.

These platforms may allow both the isolation and detection of bacterial cells, thanks to the integration of biosensors with additional modules and microfluidic components, being able to perform all the analytical and pre-analytical procedures on the same portable device.

For the detection of Listeria Monocytogenes, the sensing surface has been functionalized with antibodies able to recognize this bacterium. All devices have been characterized in this condition by an IVIUM pocketSTAT, a portable potentiostat with integrated impedance analyzer and excitation system. Preliminarily to the measurements, the redox pair 𝐾 [𝐹𝑒(𝐶𝑁) ]/𝐾 [𝐹𝑒(𝐶𝑁) ] was introduced into the chamber in ratio 1: 1 dispersed in PBS with concentration 10 𝑚𝑀. The characterization in the frequency range [0.1 𝐻𝑧; 1 𝑀𝐻𝑧]

resulted in a value of about 27 𝑘Ω for the electron transfer resistance and the typical shape shown in Figure 4.2 for the Nyquist plot.

For preparing the samples to be measured, the pathogens were isolated in food samples, grown in Half Frazer broth followed by a Listeria Enrichment broth (24 LEB) with selective polymyxin and quinolone supplements (Oxoid, Thermofisher, Milan, Italy). Real time PCR was employed for their identification. After this procedure, an aliquot of exponentially grown bacteria was serially diluted in isotonic solution and then plated into an agar plate with solidified Agar Listeria Ottaviani and Agosti (ALOA). We counted the bacteria on plates containing colonies well-isolated one to the other to identify the number of 𝐶𝐹𝑈/𝑚𝐿. In order to preserve some samples for further analysis, they were prepared in two replicates, to store frozen each dilution. The protocol for the measurements followed was to denaturate them by 10 minutes of heating before performing the EIS analysis.

Listeria monocytogenes suspensions in growth medium and in half-skimmed milk were prepared. Spiked milk samples were made by adding to half-skimmed milk a known concentration of pathogen suspension, in a ratio of 4:1. Since each device has four different sensing areas, two of them were used as control chambers, by pouring only half-skimmed milk or growth medium to have a baseline for the signal that were measured by the sensing chamber having the same “background” but also the suspension of L. monocytogenes to be measured. In order to calibrate the device for specific detection of the bacteria, different concentrations of L.

monocytogenes in culture medium and in the milk suspension were incubated above the sensing

76 region by filling the microfluidic chamber with a volume of 20 𝜇𝐿. Regarding the culture medium, we used serially diluted samples (i.e., 2.2 ⋅ 10 , 2.2 ⋅ 10 , 2.2 ⋅ 10 ) for the measurements, obtaining the Nyquist plots reported in Figure 4.7. As expected, the electron transfer resistance increases with growing concentrations of the bacteria, since the values found for 𝑅 were [51 𝑘Ω, 270 𝑘Ω, 350 𝑘Ω] for the three different probed values [2.2 ⋅ 10 𝐶𝐹𝑈/

𝑚𝐿, 2.2 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿, 2.2 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿].

To check the specificity of the device, we employed as negative control a solution of Salmonella enterica at 3 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿 spotted into the chamber obtaining a plot (green curve in the inset of Figure 4.7) with change in 𝑅 of 7 𝑘Ω with respect to bare antibodies, confirming good performances in the pathogen recognition and giving us the minimum value measurable, from which it is possible to estimate the platform limit of detection for L. monocytogenes in growth medium. Another set of experiments performed for [5.5 𝐶𝐹𝑈/𝑚𝐿, 5.5 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿, 5.5 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿] of L. monocytogenes in culture medium shows about [30 𝑘Ω, 130 𝑘Ω, 330 𝑘Ω], with a slight overlap between the lowest concentration with the antibodies considering the error bars. For this reason, it is reasonable to consider the limit of detection belonging to the range [5.5 𝐶𝐹𝑈/𝑚𝐿, 22 𝐶𝐹𝑈/𝑚𝐿] for this bacterium dispersed into the medium.

Figure 4.7: Nyquist plots for different L. monocytogenes concentration in growth medium, only

antibodies and negative control with Salmonella enterica.

77 The same procedure has been performed for the pathogen in milk, as reported in Figure 4.8. In this case, the concentration probed were [5.5 𝐶𝐹𝑈/𝑚𝐿, 5.5 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿, 5.5 ⋅ 10 𝐶𝐹𝑈/

𝑚𝐿] for the bacteria and 7.5 ⋅ 10 𝐶𝐹𝑈/𝑚𝐿 for the negative control with S. enterica, furthermore we also got the signal resulting from the unspecific absorption of 20 𝜇𝐿 of milk only. In this case, the corresponding values of 𝑅 for the Listeria were [45 𝑘Ω, 196 𝑘Ω, 386 𝑘Ω] (turquoise, blue and purple curves in Figure 4.8). The signal originating from milk is associated to an electron transfer resistance of about 37 𝑘Ω (red curve), while the negative control shows a value very close to the antibodies baseline, namely a diameter of 31 𝑘Ω.

Figure 4.8: Nyquist plots for different L. monocytogenes concentration in milk, only antibodies, pure

milk and negative control with Salmonella enterica.

The calibration curves obtained for the two scenarios under study are reported in Figure 4.9.

Their linear fitting shows a good agreement with the experimental results obtained, so this kind of EIS-based platform is a good candidate to be employed as a point of care device for checking Listeria monocytogenes contamination at different phases of the supply chain during quality control procedures, if further validation assay about robustness, reproducibility, variability and multi-site installation will be performed and passed successfully.

78

Figure 4.9: Calibration curves obtained for L. monocytogenes in milk (red) and culture medium (black).