Tau protein sensing

As an alternative approach to dynamic magnetic particles’ sensing for the diagnosis of Alzheimer disease, an EIS-based detection of tau protein was investigated, since its abundance and conformation are associated to a family of disorders, such as encephalopathies, Pick’s disease, progressive supranuclear palsy, cortical-basal ganglionic degeneration and AD. Such disorders are named tauopathies and pathological aggregates can usually be found in glia⁸¹ and neurons, since this protein is most expressed in such cells, where it plays a key role in joining the tubulin monomers, which are the brick of the neuronal microtubule network, a fundamental structure to maintain the correct shape that is crucial for the correct signal transmission through the axons. Furthermore, tau proteins also act as a bridge between the microtubules and cytoskeleton or other proteins⁸². An incorrect tau expression can lead to the neuronal cytoskeleton breaking and the formation of pathological structures as neurofibrillary tangles (found after dead in dementia sufferer people), where hyper-phosphorylated 𝜏 dissociated from the neurons are the principal constituents⁸². Other post-translational modification of tau protein very relevant for the insurgence of neurodegenerative diseases are ubiquitination⁸³, glycosylation, glycation, polyamination, nitration and truncation⁸⁴, but also prolyl-isomerization, sumoylation, oxidation and aggregation⁸⁵. More recently, also tau protein acetylation has started to be considered as a factor in the development neurodegenerative diseases⁸⁶.

To adapt the EIS platform for detection of tau protein, the sensing surface of the device has been functionalized with antibodies able to bind the 𝜏 peptide, specifically to recognize the sequence of amino acids 26 − 230. The fabricated devices have been characterized using an Autolab potentiostat in the frequency range [0.1 𝐻𝑧; 100 𝑘𝐻𝑧] and in presence of the redox pair 𝐾 [𝐹𝑒(𝐶𝑁) ]/𝐾 [𝐹𝑒(𝐶𝑁) ] in ratio 1: 1 dispersed in PBS with concentration 10 𝑚𝑀. In the equivalent circuit according to Randles and Ershler model⁷⁷, 𝑅 can be evaluated as the most direct indicator of analyte attachment on the sensing surface.

71 To have a baseline for the signal to be detected, various devices were characterized after antibody immobilization and results are reported in Figure 4.4a. Notably, the graphs have the expected shape and are very close one to the other. We also performed a statistical analysis on the data obtained, with the assumption that they follow a uniform distribution since the number of devices fabricated was not enough to be sure they can be described by a Gaussian. For this reason, we considered the arithmetic average obtained at a specific frequency for both 𝑍 (𝑓) and 𝑍 (𝑓) as the effective measurement value with associated the uniform distribution uncertainty 𝛿 = (𝑖 = 𝑍 , 𝑍 ). Results are shown in Figure 4.4b.

Figure 4.4: (a) Results of Electrochemical Impedance Spectroscopy measurements on devices ready

for tau protein sensing without the analyte inside the redox solution. (b) Statistical analysis performed on the results obtained by device characterization without the analyte with the associated

error bar.

We calculated the electron transfer resistance for each set of measurement by a two-step procedure. First, at high frequencies, we assumed −𝑍 = 𝑎𝑍 + 𝑏𝑍 + 𝑐 and calculated the array (𝑎; 𝑏; 𝑐) by means of a parabolic fit. Then, we calculated the zeros of such function through a Mathematica script: the lower value represents the redox solution ohmic resistance, while the higher one is the electron transfer resistance. At antibody functionalization stage, this analysis leads to estimate an average value of 25 𝑘Ω for 𝑅 , with an associated error of 1 𝑘Ω (with the assumption of uniform errors distribution).

(a) (b)

72 To calibrate the sensor response, solutions were introduced with known concentrations of the tau peptide, in order to build a calibration curve and evaluating the performance of the EIS based platform. The obtained Nyquist plots are reported in Figure 4.5a, evidencing changes in the Ret values, which increase monotonically with the concentration as expected. Figure 4.5b reports the relationship between the electron transfer resistance calculated and the corresponding concentration of analyte in solution introduced inside the chamber. The fitting procedure performed demonstrated good linearity in the sensor response with a sensitivity of about 9 𝑘Ω ⋅ 𝑚𝐿 ⋅ 𝑛𝑔 . Since for any measurement performed with bare devices functionalized with antibodies for tau peptide, it resulted 𝑅 < 27 𝑘Ω, we can calculate the concentration corresponding to this value from the linear fit parameter to estimate the limit of detection of the platform in this specific application, obtaining the value 3.5 𝑛𝑔/𝑚𝐿.

Figure 4.5: (a) Nyquist plot associated with different concentration of the Tau peptide poured in

solution in the microchambers around the sensing area of the devices. (b) Electron transfer resistance Vs concentration plot obtained during calibration phase of the devices’ series.

We also exploited two different approaches for analyzing the data obtained. The first one is based on the shift of resonance frequency of the device due to the presence of the analyte in solution; in fact, it results Ω = , so this parameter depends upon two quantities that are related to what is present near the surface of the interdigitated gold electrodes instead than only 𝑅 , which is considered in the standard approach exposed above. Figure 4.6a reports the spectrum obtained considering the measurement performed on bare devices. It is possible to notice the central peak at Ω , while the other maximum at low frequencies is related to the (a) (b)

73 redox probe diffusion. This kind of measurements were analyzed by performing a parabolic fitting of the peak [400 𝐻𝑧; 10 𝑘𝐻𝑧], which shows good agreement with the hypothesized functional form, obtaining for bare devices the value (91 ± 14)𝐻𝑧.

Another approach exploited is to use as indicator the magnitude of the maximum value obtained for the imaginary part of the impedance, without calculating explicitly the resonance frequency.

Since in the system there are no inductances according to the equivalent circuit employed, 𝑍 has only the contribution due to the double layer capacitance, which can be considered as the series of intrinsic parameter of the system and the surface modifier. The result of the analysis on functionalized electrodes shows a value of (8.7 ± 0.4) 𝑘Ω for |𝑍 |.

Then, these two approaches were repeated after introducing solutions containing different concentration of tau peptide in the devices’ chambers to verify the incidence of different number of this analyte on the signal to be detected. The results for both configurations are reported in Figure 4.6b-c, where the signals show different behavior in the range of concentration investigated. It’s possible to notice that the resonance frequency decreases for higher concentrations while, on the contrary, the magnitude of impedance imaginary part increases.

The estimated sensitivities are respectively 3 𝐻𝑧 ⋅ 𝑚𝐿 ⋅ 𝑛𝑔 and 4.3 𝑘Ω ⋅ 𝑚𝐿 ⋅ 𝑛𝑔 , while the limits of detection are 4 𝑛𝑔/𝑚𝐿 (Ω = 74 𝐻𝑧) and 3.9 𝑛𝑔/𝑚𝐿 (|𝑍 | = 9510 Ω) respectively.

These two alternative approaches employed with respect to standard technique have the advantage of direct evaluation without complex data post processing, but only considering the maximum value measured for the magnitude of impedance imaginary part or its corresponding frequency obtained during the frequency sweep, which can be useful for the platform automation and simplification. Furthermore, the value of 𝑚𝑎𝑥|𝑍 | has shown few fluctuations with respect to the calculated 𝑅 for our series od devices since we obtained, for example, a relative change of 8.3% for the former and 11.2% for the latter.

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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.