Alzheimer disease: development of an immunosensor for amyloid beta detection

Alzheimer’s disease: development of an immunosensor for amyloid beta detection Pedro Jorge da Silva Carneiro Supervisor: Prof. Dr. Maria do Carmo Silva Pereira Co-Supervisor: Prof. Dr. Simone Barreira Morais Master’s Program in Biomedical Engineering July, 2013 i Abstract Alzheimer’s disease (AD) is a neurodegenerative pathology that becomes increasingly common with aging, characterized by extracellular accumulation of senile plaques (Aβ), intracellular appearance of neurofibrillary tangles and neuronal loss. AD affects about 35 million people worldwide, and if current trends continue with no medical advancement, one in 85 people will be affected by 2050. Thus, there is an urgent need to develop a cost-effective, easy to use sensor platform to facilitate the diagnostic process, identify patients at an earlier stage and allow monitorization of biochemical effects of the treatments. Since the quantification of amyloid beta (Aβ) has been established as a reliable test to diagnose AD through human clinical trials, an electrochemical immunosensor was designed and developed for detection of this biomarker in biological fluids and is the focus of this work. It is based on a gold electrode modified with mercaptopropionic acid self-assembled monolayer, electrodeposited gold nanoparticles and Aβ antibody. Antibodies act as the biorecognition element of the sensor and selectively capture and bind Aβ42 to the electrode surface. The antibodies were immobilized on gold nanoparticles that offered excellent properties for electroanalytical assays. Cyclic and square-wave voltammetry, as well as electrochemical impedance spectroscopy were used to characterize the construction of the biosensor. The optimum values for the relevant experimental variables were determined. Using the proposed immunosensor, Aβ42 can be specifically detected within a range of 0.451–9028 ng/mL with a 264 pg/mL detection limit. The immunosensor enables real-time, rapid and highly sensitive detection of Aβ with low-cost and opens up the possibilities for diagnostic ex vivo applications and research-based in vivo studies. Keywords: Alzheimer’s disease, amyloid beta, electrochemical immunosensor, selfassembled monolayers, gold nanoparticles. ii Acknowledgements First and foremost, I would like to give my most sincere appreciation to my supervisors, Prof. Maria do Carmo Silva Pereira and Prof. Simone Barreira Morais for their continued support and guidance throughout my research project and in helping me develop scientific thinking and research knowledge. Moreover I would like to give my thanks to Thiago Mielle from REQUIMTE for his essential support and assistance in the laboratory, Sílvia Coelho and Joana Loureiro from LEPAE for their help in the gold nanoparticles synthesis and antibody treatment, respectively. I am also grateful to all REQUIMTE and LEPAE team for their assistance and great work environment. Finally I would like to give thanks to my parents, girlfriend and friends for their continued support and encouragement throughout this year. iii List of Publications Most of the content presented in this thesis was submitted or accepted for publication in: 1. Carneiro, P., Delerue-Matos, C., Morais, S., Pereira, M, Electrochemical Immunosensor for Amyloid Beta-Peptide Detection: Preliminary Study, 3rd Portuguese Bioengineering Meeting - Bioengineering National Congress, Braga February 2013. 2. Carneiro, P., Delerue-Matos, C., Morais, S., Pereira, M, Alzheimer disease: development of an immunosensor for biomarker detection, 6º Encontro de Investigação Jovem da Universidade do Porto, Porto February 2013. iv Contents List of Figures .................................................................................................................. vi List of Abbreviations ........................................................................................................ x 1. Introduction .................................................................................................................. 1 1.1 Main Objectives ...................................................................................................... 2 1.2 Thesis structure ....................................................................................................... 3 2. State of the Art .............................................................................................................. 4 2.1 Alzheimer’s disease – The amyloid cascade hypothesis ........................................ 4 2.2 Biomarkers for Alzheimer’s disease ....................................................................... 6 2.2.1 Biological biomarkers of Aβ-related mechanism............................................. 8 2.3 Electrochemistry ................................................................................................... 11 2.3.1. Mass transfer ................................................................................................. 13 2.3.2 The electrical double layer ............................................................................. 14 2.3.3 Electrode materials ......................................................................................... 15 2.3.4. Electrochemical Techniques ......................................................................... 16 2.3.4.1 Cyclic voltammetry ................................................................................ 16 2.3.4.2 Square-wave voltammetry ...................................................................... 17 2.3.4.3 Electrochemical Impedance Spectroscopy ............................................. 19 2.4 Biosensors ............................................................................................................. 21 2.5 Electrochemical immunosensors .......................................................................... 23 2.5.1 The antibody-antigen interaction ................................................................... 24 2.5.2 Immunoassays ................................................................................................ 25 2.5.3 Antibody immobilization techniques ............................................................. 28 2.5.3.1 Biotin-(strept)avidin interaction ............................................................. 28 2.5.3.2 Antibody-binding proteins ...................................................................... 29 2.5.3.3 Conducting polymers .............................................................................. 30 2.5.3.4 Antibody fragments ................................................................................ 30 2.5.3.5 Self-assembled monolayers .................................................................... 31 2.5.4 Nanomaterials based immunosensors ............................................................ 35 3. Materials and Methods ............................................................................................... 39 3.1 Reagents and equipments ...................................................................................... 39 3.2 Electrochemical analyses ...................................................................................... 40 3.2.1 Pre-treatment of the working electrode .......................................................... 41 v 3.2.2 Self-assembled monolayers ............................................................................ 42 3.2.3 Synthesis and electrodeposition of gold nanoparticles .................................. 42 3.2.4 Antibody immobilization ............................................................................... 43 3.2.5 β-Amiloyd (1-42) detection ............................................................................ 43 4. Results and Discussion ............................................................................................... 45 4.1 Characterization of the electrode surface .............................................................. 45 4.2 Biosensor construction .......................................................................................... 46 4.2.1 Modification of the AuE with self-assembled monolayers ............................ 46 4.2.2 Deposition of gold nanoparticles onto the MPA/AuE ................................... 50 4.2.3 Antibody immobilization onto the AuNPs/MPA/AuE .................................. 54 4.3 Amyloid β (1-42) detection ................................................................................... 58 5. Conclusion and Future directions ............................................................................... 64 6. References .................................................................................................................. 66 vi List of Figures Figure 1 - The amyloid cascade hypothesis [6]. ............................................................... 5 Figure 2 - Biomarkers for each step in the amyloid cascade [3]. ..................................... 7 Figure 3 - Proteolytic cleavages of APP [4]. .................................................................... 8 Figure 4 - Model for Aβ misfolding and aggregation [4]. ................................................ 9 Figure 5 - Proposed model of Aβ-induced synaptotoxic effects and synapse elimination in AD [22]. ...................................................................................................................... 10 Figure 6 - Three methods for mass transfer in electrochemical systems [25]. ............... 13 Figure 7 - Schematic representation of the electrical double layer. IHP-inner Helmholtz plane; OHP-outer Helmholtz plane [29]. ........................................................................ 14 Figure 8 - Typical excitation signal for CV - a triangular potential waveform with switching potentials at V1 and V2 [31]. .......................................................................... 17 Figure 9 - Schematic waveform for square-wave voltammetry [31]. ............................ 18 Figure 10 - a) A schematic diagram of an idealized Randles electrical equivalent circuit [29]; b) Nyquist plot showing the high and low frequency components [34]. ............... 20 Figure 11 - Components of typical biosensor [35]. ........................................................ 21 Figure 12 - A schematic illustrating the “Y”-shaped structure of an antibody [48]. ...... 25 Figure 13 - Schematic representation of (a) competitive and (b) non-competitive immunoassay formats [48]. ............................................................................................ 27 Figure 14 - Schematic diagram of an ideal, single-crystalline SAM of alkanethiolates supported on a gold surface. The anatomy of the SAM is highlighted [84]. ................. 32 Figure 15 - Examples of sulfur compounds that form self-assembled monolayers on metals and semiconductors: (a) alkanethiol; (b) arenethiol; (c) alkanedithiol; (d) dialkyldisulfide; (e) dialkylsulfide. Red: sulfur atom, blue: carbon atom, white: hydrogen atom [82]. ....................................................................................................... 33 Figure 16 - Scheme of a decanethiol molecule adsorbed on gold. Red: sulfur atom; blue: carbon atom; white: hydrogen atom [82]. ...................................................................... 34 Figure 17 - The formation process of self-assembled monolayers. ................................ 35 Figure 18 – Potentiostat PGSTAT-30 (Autolab). ........................................................... 40 Figure 19 – a) Electrochemical cell assembly. Red: Working electrode; Black: Counter electrode; Blue: Reference electrode; b) Working electrode (gold electrode). .............. 41 Figure 20 - Typical cyclic voltammogram obtained with a gold electrode in 0.5 mol/L H2SO4 aqueous solution at a 100 mV/s scan rate. .......................................................... 45 vii Figure 21 - Comparison of the different square-wave voltammograms before (AuE) and after the modification with the different self-assembled monolayers (12 h immersion): cystamine SAM (CYS); cystamine and mercaptoethanol mixed SAM (CYS+ME); mercaptopropionic acid SAM (MPA); mercaptopropionic acid and mercaptoethanol mixed SAM (MPA+ME). Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ......................................... 47 Figure 22 – Square-wave voltammograms obtained for different immersion periods of the gold electrode (AuE) on the 1 mmol/L mercaptopropionic acid solution. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ........................................................................................................ 48 Figure 23 - Square-wave voltammograms obtained for different concentrations of MPA solution for a 2 h immersion period. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ........................... 49 Figure 24 - Nyquist plot of electrochemical impedance spectra for bare gold electrode (AuE) and MPA SAM modified gold electrode. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. .................................................................................... 50 Figure 25 - Absorption spectrum of the gold nanoparticles prepared by the TurkevichFrens method. ................................................................................................................. 51 Figure 26 - Square-wave voltammograms obtained for the bare gold electrode (a), after modification with the 5 mmol/L MPA SAM (b), and electrodeposition of AuNPs synthesized by the Turkevich-Frens method during 600 s (c) and by the potential application during 200 s (d). Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ......................................... 52 Figure 27 – Square-wave voltammograms obtained with the bare gold electrode (AuE) and AuNPs/MPA/AuE biosensor for different AuNPs electrodeposition periods. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ........................................................................................................ 53 Figure 28 - Nyquist plot of electrochemical impedance spectra for bare gold electrode (AuE), MPA/AuE and AuNPs/MPA/AuE. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. ..................................................................................................... 54 Figure 29 – Square-wave voltammograms obtained for AuNPs/MPA/AuE and AuNPs/MPA/AuE modified with different antibody concentrations for a 12 h viii incubation time. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ................................................................... 55 Figure 30 - Nyquist plot of electrochemical impedance spectra for AuNPs/MPA/AuE and AuNPs/MPA/AuE modified with different antibody concentrations. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. ....................................................... 55 Figure 31 - Square-wave voltammograms obtained with the AuNPs/MPA/AuE and the AuNPs/MPA/AuE modified with different antibody (1.0 µg/mL) incubation times. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. .............................................................................. 56 Figure 32 - Nyquist plot of electrochemical impedance spectra for the AuNPs/MPA/AuE modified with different antibody (1.0 µg/mL) incubation times. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. ....................................... 57 Figure 33 - Nyquist plot of electrochemical impedance spectra for the AuE, MPA/AuE, AuNPs/MPA/AuE and Anti-Aβ42/AuNPs/MPA/AuE. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. .................................................................................... 58 Figure 34 - Square-wave voltammograms obtained with the AntiAβ42/AuNPs/MPA/AuE immunosensor after expositions to different Aβ42 concentrations (0 to 9028 ng/mL). Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. ............................ 59 Figure 35 - Nyquist plot of electrochemical impedance spectra observed with the AntiAβ42/AuNPs/MPA/AuE immunosensor after expositions to different Aβ42 concentrations (0 to 9028 ng/mL). Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. ..................................................................................................... 59 Figure 36 - The several steps for the biosensor construction. ........................................ 60 Figure 37 - Nyquist plot of electrochemical impedance spectra for the different stages of the immunosensor construction. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. ................................................................................................................................. 61 Figure 38 - Effect of the Aβ42 concentration (ng/mL) on the peak current (A) of the immunosensor. Error bars correspond to three replicates. ............................................. 62 3 1. Formation of a self-assembled monolayer on the gold surface in order to control the electrode interface. Several self-assembled monolayers (SAMs) were tested and experimental conditions were optimized in order to promote the best immobilization on the gold surface. 2. Electrodeposition of gold nanoparticles on the modified SAM/gold electrode. Gold nanoparticles enhanced the biosensor response and allowed antibody immobilization. Different methods for gold nanoparticles synthesis were tested and compared. 3. Immobilization of the antibody on the gold nanoparticles/SAM/gold electrode. Concentration of the antibody and time of incubation were optimized in order to promote the desired immobilization. The electroanalytical behavior of the developed biosensor was characterized in terms of calibration data. Finally, it was successfully applied to synthetic solutions of Aβ. 1.2 Thesis structure This thesis is divided in 6 chapters. In Chapter 1, the key issues are introduced. The motivations to the work performed, as well as, the main objectives of the work are presented. In Chapter 2 the theoretical aspects concerning the main topics of this work are presented. The following subjects are discussed: the formation of extracellular deposits of Aβ and consequently development of AD, the main electrochemical technique principles, the characteristics of biosensors and immunoassays, properties of nanomaterials and their importance in the development of biosensors. In this section the recent studies related with this theme are also referred. Chapter 3 describes the reagents, equipments and methods used in the performed experiments. In Chapter 4, the results attained are presented and discussed. The topics include the characterization of the gold electrode, the SAMs formation, synthesis and electrodeposition of gold nanoparticles, antibody immobilization and finally detection of Aβ. Chapter 5 is the final chapter of the thesis in which the main conclusions and future perspectives for the work are referred. 4 2. State of the Art 2.1 Alzheimer’s disease – The amyloid cascade hypothesis AD is a neurodegenerative pathology characterized by extracellular deposits of Aβ peptide (senile plaques), intracellular appearance of neurofibrillary tangles and neuronal loss. The amyloid cascade hypothesis defends that the deposition of the Aβ peptide in the brain parenchyma is a crucial step that ultimately leads to AD (Figure 1) [6, 14]. Autosomal dominant mutations that cause early onset familial AD occur in three genes: amyloid precursor protein (APP), presenilin 1 (PS1) and presenilin 2 (PS2) [6, 14]. The first genetic mutations causing AD were discovered in the APP gene [6]. Most of the mutations cluster at or very near the sites within APP that are normally cleaved by proteases called α-, β-, and γsecretases [6]. These mutations promote generation of Aβ by favoring proteolytic processing of APP by βor γ-secretase [4, 6, 14]. Besides the mutations in the PS1 and PS2 genes that alter the APP metabolism through a direct effect on the γ-secretase, four important observations were given to support the amyloid cascade hypothesis. Firstly, the deposition of tau protein in neurofibrillary tangles in the brain occurs without deposition of amyloid [6]. The conclusion is that even the most severe consequences of tau alteration namely, neurofibrillary tangle formation leading to neurodegeneration, are not sufficient to induce the amyloid plaques [6]. This way, the formation of neurofibrillary tangle of tau is likely to be deposited after changes in Aβ metabolism and initial plaque formation, rather than before [6]. Secondly, studies suggest that altered APP processing occurs before tau alterations in the cascade of AD, a notion bolstered by the observation that Aβ toxicity is tau dependent [6]. Thirdly, studies where APP transgenic mice were crossed with apolipoprotein E (apoE) deficient mice, cerebral Aβ deposition was reduced in the offspring, providing strong evidence that the pathogenic role of genetic variability at the human apoE locus is very likely to involve Aβ metabolism [6, 14]. At last, evidence indicates that genetic variability in Aβ catabolism and clearance may contribute to the risk of late-onset AD [6]. These four findings reinforce the theory that cerebral Aβ accumulation is the primary event in AD. These studies have identified multiple steps potentially vulnerable to pharmacologic manipulation that resulted in the development of new drug candidates with disease-modifying potential [4]. This predicts a new type of causal mechanistic 5 treatment beyond symptomatic therapy [3, 4]. This new type of disease-modifying drugs is expected to be most effective if administrated very early in the disease process, before the neurodegenerative process is too severe [3, 4]. However, with the current techniques, the clinical diagnosis of AD can only be made when it is in an advanced stage. Thus, there is a great need for improved diagnostic tools and biomarkers appear as huge promise for the early identification of AD [3-5]. Biomarkers can provide a faster and more convenient responses to some questions and are playing increasingly diverse roles in drug development [3]. Figure 1 - The amyloid cascade hypothesis [6]. 6 2.2 Biomarkers for Alzheimer’s disease “A biomarker (biological marker) is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [3]. In other words, the term biomarker is used to describe any neurochemical agent that is used to evaluate the risk or presence of disease. In this case, biomarkers may facilitate the ability to reliably diagnose AD in very early and perhaps even pre-clinical disease stages [4, 5]. They may also provide objective and reliable measures of drug safety and diseasemodifying treatment efficacy in clinical drug trials in AD. Since the neuropathological changes and symptoms of AD take years to be noticed, the ideal therapy would be to treat the neuropathology as early as possible and biomarkers of pre-clinical AD are likely to play a fundamental role in the development of new therapies [4, 5]. Biomarkers can provide new insights into the neurobiology of AD and generate new and novel therapeutic targets. Disease-related biomarkers can assist in patient selection, sample stratification, course prediction and defining disease severity [3]. Biomarkers may assist in decision making in early clinical development, may inform corporate decisions regarding go or non-go decisions and may decrease cycle time and decrease costs [3]. The key features of an ideal AD biomarker are that it should detect a fundamental feature of the neuropathology, and have a diagnostic sensitivity for AD exceeding 80% together with specificity above 80% for distinguishing AD from other dementias [4]. It should also be reliable, reproducible, non-invasive, simple to perform, and inexpensive [3, 4]. The steps to establish a biomarker consist of confirmation by at least two independent studies conducted by qualified investigators with the results published in peer-reviewed journals, and validation in neuropathologically confirmed cases [4]. Beyond these criteria it would also be important if the biomarker could follow natural disease progression even as the effects of disease-modifying therapies [3-5]. Disease biomarkers may have important roles in three areas: as markers of trait, state, and rate [3, 15]. Trait markers represent risk factors and do not change with the presence of the disease [3, 15]. Trait biomarkers that are representative of an increased risk of AD include the apolipoprotein E 34 (APOE 34) allele [3, 16, 17], APOJ [3, 18, 19], CR1 [3, 19], PICALM [3, 18], SORL1 [3, 20], and TOMM40 [3]. State markers indicate the presence of the disease process and include medial temporal atrophy (MTA) on magnetic resonance imaging (MRI), amyloid imaging, and cerebrospinal fluid (CSF) 7 Aβ and tau protein measures [3]. Rate biomarkers follow disease progression; progressive atrophy detected by MRI and hypometabolism observed on fluorodeoxyglucose (FDG) positron emission tomography (PET) are rate biomarkers that correlate with disease severity [3]. Biomarkers can be collected from a variety of biological compartments (e.g., imaging of brain [3], cerebrospinal fluid Aβ and tau levels [3, 21]) and each compartment provides a different perspective on the pathological processes of AD (Figure 2) [3]. Imaging biomarkers provide insight into the topographic distribution of pathologic changes. Fluid biomarkers may appear in the central nervous system (CNS) compartments by diffusion and are subject to metabolism and excretion; the status of these mechanisms will also affect the relationship of the biomarker to the brain disease [3]. Figure 2 - Biomarkers for each step in the amyloid cascade [3]. The levels of Aβ42 in the CSF in AD are reduced due to deposition of the peptide in Aβ plaques in the brain and the levels of Aβ40 remain unchanged or may be moderately increased. Several studies have examined plasma levels of Aβ in AD but the findings were contradictory [3, 4]. Some groups reported high levels of Aβ40 and Aβ42 in plasma [4]. On the other hand other groups found no change in the Aβ plasma levels [4]. Tau protein levels in CSF increase during the development of AD [3]. Clusterin levels have been found to be increased in brain and CSF of patients with AD, and plasma clusterin was recently reported to be associated with brain atrophy, baseline disease severity, and rapid clinical progression in patients with AD [3]. In this study Aβ is the biomarker that will be explored. 8 2.2.1 Biological biomarkers of Aβ-related mechanism As reported earlier, Aβ is generated by proteolytic cleavage (enzymatic digestion involving βand γ-secretase activities [22]) of the type I transmembrane spanning glycoprotein amyloid precursor protein (APP) (Figure 3) [4, 5, 14, 22]. APP is cleaved at the N-terminus after position 671 by a protease referred to as β-secretase, also known as beta-site APP-cleaving enzyme (BACE) [4, 5, 14, 22]. This cleavage results in the release of a large N-terminal derivative called β-secretase-cleaved soluble APP (βsAPP). At last, the 99 amino acid C-terminal fragment of APP (C99) is cleaved by the γ-secretase complex releasing free Aβ [4, 5, 14, 22]. Figure 3 - Proteolytic cleavages of APP [4]. Once released, the Aβ peptide can be identified in cerebrospinal fluid and plasma, what makes the various species of Aβ really interesting as candidates to biomarkers [4]. The mechanism that enables Aβ monomers to aggregate is not well understood but Aβ can exist as monomers, dimmers, oligomers, protofibrils, fibrils and fibrillar aggregates (Figure 4) [3, 4]. Furthermore, the tendency of Aβ to aggregate seems to be related with the peptide’s primary sequence as Aβ42 variant, which constitutes less than 10% of total Aβ, seems more prone to aggregate than more abundant Aβ40, contributing to the modification of the ratio Aβ40/Aβ42 [4]. 9 Figure 4 - Model for Aβ misfolding and aggregation [4]. Three main synaptotoxic effects of Aβ have been recognized: inhibition of longterm potentiation (LTP), removal of synaptic glutamate receptors and elimination of glutamate synapses (Figure 5) [22]. Glutamate synapses constitute 85-90% of the synapses in the mammalian cortex and their plasticity is thought to be the basis for learning and memory [22]. The postsynaptic membrane of the glutamate synapse is typically equipped with ionotropic AMPA and NMDA receptors [22]. The AMPA receptors are responsible for the normal, fast electrical signaling while the NMDA receptors, which are highly permeable for calcium, are required for the induction of LTP and its counterpart long-term depression (LTD) at these synapses [22]. LTP, a lasting increase in synaptic efficacy, typically involves an expansion of the synapse with more AMPA receptors, whereas the opposite is typical for LTD [22]. The inhibitory action of Aβ on NMDA receptor-dependent LTP has been shown in different experimental settings, including genetic modifications leading to overproduction of Aβ in human CSF and Aβ oligomers from AD brains [22]. 10 Figure 5 - Proposed model of Aβ-induced synaptotoxic effects and synapse elimination in AD [22]. 11 2.3 Electrochemistry Electrochemistry involves chemical phenomena associated with charge separation. Often this charge separation leads to charge transfer, which can occur homogeneously in solution, or heterogeneously on electrode surfaces [23]. Electrodes are linked by conducting paths both in solution (via ionic transport) and externally (via electric wires etc.) so that charge can be transported [23]. If the cell configuration permits, the products of the two electrode reactions can be separated. Electroanalytical techniques analyze the relationship between the measurements of electrical quantities, such as current, potential, or charge, and the chemical parameters [24]. The oxidation/reduction process involves the exchange of electrons from one specie to another. Electrochemical processes take place at the electrodesolution interface [23, 25]. The electrochemical analyses usually require the use of three electrodes - the working electrode, reference electrode and counter electrode – and a contacting solution (electrolyte) containing the analyte [26]. The working electrode can be of various materials and geometries and gives response to the target analyte [26]. The electrode surface is thus a junction between an ionic conductor and an electronic conductor. The reference electrode has constant potential and is independent of the properties of the solution [26]. Different types of electrical signal used for quantification reflect the differences between electroanalytical techniques [11, 23, 25, 27]. Such electroanalytical measurements have been found to have a vast range of applications, where it could be highlighted the biomedical analysis. The objective of controlled-potential electroanalytical experiments is to obtain a current response that is related to the concentration of the target analyte [25]. This objective is accomplished by monitoring the transfer of electron(s) during the redox process of the analyte: where O and R are the oxidized and reduced species, respectively. Electrode reactions are heterogeneous and take place in the interfacial region between electrode and solution, the region where charge distribution differs from that of the bulk phases [11, 23, 25, 27]. O ne- (1) 12 The resulting current-potential plot, also known as voltammogram, is a display of current signal versus the potential signal [28]. The exact shape and magnitude of the voltammetric response is controlled by the processes involved in the electrode reaction. The resulting current from a change in oxidation state of the electroactive species is termed the faradaic current because it obeys Faraday’s law [23, 25]. The faradaic current is a direct measure of the rate of the redox reaction. The total current is a result of the sum of the faradaic currents for the sample and blank solutions, as well as the nonfaradaic charging background current [23, 25]. 19 2.3.4.3 Electrochemical Impedance Spectroscopy Electrochemical Impedance Spectroscopy (EIS) or AC impedance methods have seen tremendous increase in popularity in recent years [34]. Initially applied to the determination of the double layer capacitance, they are now applied to the characterization of electrode processes and complex interfaces [34]. EIS studies the system response to the application of a periodic small amplitude AC signal. These measurements are carried out at different AC frequencies and analysis of the system response contains information about the interface, its structure and reactions taking place there [34]. By varying the excitation frequency of the applied potential over a range of frequencies, one can calculate the complex impedance, sum of the real and imaginary impedance components, of the system as a function of the frequency (i.e. angular frequency, w) [35]. Therefore, EIS combines the analysis of both real and imaginary components of impedance, namely the electrical resistance and reactance [29, 34, 35]. EIS possesses the ability to study any intrinsic material property or specific processes that could influence the conductivity/resistivity or capacitivity of an electrochemical system. Therefore, EIS is a useful tool in the development and analysis of materials for biosensor transduction, such as the study of polymer degradation [35]. However it is a complementary technique and other methods must also be used to elucidate the interfacial processes [34, 35]. The electric equivalent circuit first proposed by Randles, shown in figure 10, is commonly used in EIS for interpretation of impedance spectra [29]. It includes a solution resistance (Rs), a double layer capacitor (Cd) and a charge transfer (Rct) or polarization resistance (Rp). When the charge transfer takes place at the interface, the mass transports of the reactant and product take on roles in determining the rate of electron transfer, which depends on the consumption of the oxidants and the production of the reductant near the electrode surface [29]. The mass transport of the reactants and the products provides another class of impedance, Warburg impedance (ZW), which can be exploited by electroanalytical chemists because it shows up in the form of a peak current in a voltammogram or a current plateau in a polarogram [29]. In addition, to be a useful model in its own right, the Randles model is the starting point for other more complex models [29]. The double layer capacity is parallel with the impedance due to the charge transfer reaction [29]. Figure 10 shows an example of a Nyquist plot for a Randles cell. The solution resistance can be found by 20 reading the real axis value at the high frequency intercept, which is the intercept near the origin of the plot [29]. The value at the right side of the real axis (low frequency region) is the sum of the charge transfer resistance and the solution resistance [29]. The intermediate-frequency component (circle) arising from the Rp and Cd is located in between [29]. In a simple situation, the Warburg element manifests itself in EIS spectra by a line with an angle of 45 degrees in the low frequency region [29]. Figure 10 - a) A schematic diagram of an idealized Randles electrical equivalent circuit [29]; b) Nyquist plot showing the high and low frequency components [34]. For electrochemical sensing, impedance techniques are useful to monitor changes in electrical properties arising from biorecognition events at the surfaces of modified electrodes. For example, changes in the conductivity of the electrode can be measured as a result of protein immobilization and antibody-antigen reactions on the electrode surface [35]. EIS has become a mature and well understood technique. It is now possible to acquire, validate and quantitatively interpret the experimental impedances. However, the most difficult problem in EIS is modeling of the electrode processes. There is almost an infinite variety of different reactions and interfaces that can be studied (corrosion, coating, conducting polymers, batteries and fuel cells, etc.) and the main effort is now applied to understand and analyze these processes [35]. 21 2.4 Biosensors Biosensors are, by definition, sensing devices including a biological component (enzyme, antibody, animal or plant cell, oligonucleotide, lipid, microorganisms, etc.) intimately connected to a physical transducer (electrode, optical fiber, vibrating quartz, etc.) (Figure 11) [35, 36]. This dual configuration permits a quantitative study of the interaction between the analyte and an immobilized biocomponent [36, 37]. Designed for the purpose, biosensors are generally highly selective due to the possibility to tailor the specific interaction of compounds by immobilizing biological recognition elements on the sensor substrate that have a specific binding affinity to the desired molecule [3538]. Typical recognition elements used in biosensors are: enzymes, antibodies, nucleic acids and cells. Ideally, biosensors should be readily implemented and allow for low reagent and energy consumption [35, 36, 39-42]. Nowadays, a lot of biosensors can be found in laboratories around the world but only one is known by its great ratio efficiency/cost and that is the glucose sensor. The major limitation, in several cases, in developing sensing devices is associated with the ability to miniaturize the transduction principle and the lack of cost-effective production method [37, 41]. Biosensors have an important role due to their inherent advantages as robustness, easy miniaturization, excellent detection limits, possibility of using small analyte volumes, and ability to be used in turbid biofluids with optically absorbing and fluorescing compounds [35]. Figure 11 - Components of typical biosensor [35]. 22 In order to construct a successful biosensor a number of conditions must be met [35]: 1. The biocatalyst must be highly specific for the purpose of the analysis, be stable under normal storage conditions and show a low variation between assays. 2. The reaction should be as independent as manageable of such physical parameters as stirring, pH and temperature. This will allow analysis of samples with minimal pre-treatment. If the reaction involves cofactors or coenzymes these should, preferably, also be co-immobilized with the enzyme. 3. The response should be accurate, precise, reproducible and linear over the concentration range of interest. It should also be free from electrical or other transducer induced noise. 4. If the biosensor is to be used for invasive monitoring in clinical situations, the probe must be tiny and biocompatible, having no toxic or antigenic effects. Furthermore, the biosensor should not be prone to inactivation or proteolysis. 5. For rapid measurements of analytes from human samples it is desirable that the biosensor can provide real-time analysis. 6. The complete biosensor should be cheap, small, portable and capable of being used by semi-skilled operators. 23 2.5 Electrochemical immunosensors Immunosensors are affinity ligand-based biosensing devices that couple immunochemical reactions to appropriate transducers [43]. In recent decades, immunosensors have received rapid development and wide applications with various detection formats. The general working principle of the immunosensors is based on the fact that the specific immunochemical recognition of antibodies (antigens) immobilized on a transducer to antigens (antibodies) in the sample media can produce analytical signals dynamically varying with the concentrations of analytes of interest [43-45]. The merits of immunosensors are related to selectivity and affinity of the antibody-antigen reaction [46]. Here, the highly specific binding between the antibody and the antigen involves different types of interaction forces, basically hydrophobic and electrostatic interactions, van der Waals forces and hydrogen bonding. The antigen–antibody reaction is reversible and, owing to the relative weakness of the forces holding the antibody and antigen together, the complex formed would dissociate in dependence upon the reaction environment (e.g. pH and ion strength) [43]. High specificity is achieved by the molecular recognition of target analytes (usually the antigens) by antibodies (biological recognition element) to form a stable complex on the surface of an immunoassay system or an immunosensor [40, 43, 47-49]. On the other hand, sensitivity depends on several factors including the use of high affinity analyte-specific antibodies, their orientation after being immobilized on the immunoassay or immunosensor surface and the appropriate detection system for measuring the analytical signal [48, 49]. This recognition reaction defines the high selectivity and sensitivity of the transducer device [43]. The electronic part is used to amplify and digitalize the physicochemical output signal from the transducer devices such as electrochemical (potentiometric, conductometric, capacitative, impedance, amperometric), optical (fluorescence, luminescence, refractive index), and microgravimetric devices [43]. Electrochemical immunosensors have been applied to several fields of science including medical diagnosis [44, 45, 50], environmental analysis [51, 52] and biological process monitoring [53]. In the biological area, considerable efforts have been devoted to the development of precise, rapid, sensitive, and selective immunosensors by measurement of the markers or pathogenic microorganisms responsible for the diseases, such as proteins, enzymes, viruses, bacteria, and hormones [47, 54-57]. This technology gains practical usefulness from a combination of selective biochemical recognition with 24 the high sensitivity of electrochemical detection [58]. With the development of technology, such biosensors profit from miniaturized electrochemical instrumentation and are thus very advantageous for some sophisticated applications requiring portability, rapid measurement and use with a small volume of samples [58]. Several reviews confirm the attractive advantages of electrochemical biosensors [9, 10, 59-62]. 2.5.1 The antibody-antigen interaction The fundamental basis of all immunosensors is the specificity of the molecular recognition of antigens by antibodies to form a stable complex. Antibodies are a family of glycoproteins known as immunoglobulins (Ig). There are generally five distinct classes of glycoproteins (IgA, IgG, IgM, IgD, and IgE) with IgG being the most abundant class (approximately 70%) and most often used in immunoanalytical techniques [48, 63]. IgG is a “Y”-shaped molecule based upon two distinct types of polypeptide chains (Figure 12). The molecular weight of the smaller (light) chain is approximately 25 kDa, while that of the larger (heavy) chain is approximately 50 kDa. In each IgG molecule, there are two light and two heavy chains held together by disulfide linkages [48, 63]. Antibodies show very high specificity and binding constants toward their corresponding antigens. An antigen has been defined as any agent that gives rise to antibody formation specific for that agent when transferred to a living cell system containing cells of the immunologically competent type [48, 63]. 25 Figure 12 - A schematic illustrating the “Y”-shaped structure of an antibody [48]. 2.5.2 Immunoassays Immunoassay is the predominant analytical technique for quantitative measurements, being used over a wide range of concentrations, in many different biological matrices, and in a range of delivery formats. Immunoassays are the quantitative methods of analysis where antibodies are the primary binding agents for the antigen (which is often the analyte) of interest [9, 43, 46, 48]. All immunoassays depend on measuring the fractional occupancy of the recognition sites. Usually, immunoassays are heterogeneous, which means that either the antibody or the antigen is immobilized on a solid carrier and an immunocomplex is formed upon contact with a solution containing the other immunoagent while homogeneous immunoassays take place in the solution phase. Compared to homogeneous immunoassays, the heterogeneous immunoassays are easily designed and constructed. The unbound proteins are removed by washing and the response obtained from the labels is proportional to the amount of protein bound. However, such a measurement can rely on either the evaluation of occupied sites or, indirectly, on measuring unoccupied sites. This leads to the development of either a “competitive” or a “non-competitive” immunoassay format [46, 48]. In a competitive immunoassay (Figure 13), unlabeled analyte in the test sample is measured by its ability to compete with the labeled antigen for a limited number of 26 antibody-binding sites [46, 48]. In electrochemical immunoassays, an enzyme label or an electroactive label is commonly used. Quantitative analysis can be achieved by determining the amount of labeled analyte that interacted at the binding sites [48]. Therefore, with a fixed number of antibody sites, a smaller signal is expected when the ratio between the quantities of sample to labeled analyte is large [48]. In contrast, a larger signal is obtained when there is a small quantity ratio. Therefore, the signal produced by the bound labeled analyte is usually inversely proportional to the amount of sample analyte [46, 48]. Non-competitive immunoassays (also known as a “sandwich” immunoassay) give the highest level of sensitivity and specificity because of the use of a couple of match antibodies. In this format the sample analyte is captured by an excess of a capture antibody, separating it from the bulk sample [48]. The captured analyte is then exposed to an excess of second signal antibody (secondary antibody (Ab2)), which will only bind to the existing capture antibody-analyte complex [48]. This structure is a classic twosite immunoassay complex in which the analyte is sandwiched between two antibodies (Figure 13). High-affinity antibodies and appropriate labels are usually employed for the amplification of electrochemical signal [46, 48]. Enzyme-labeled antibodies are often used as detection antibodies that result in amplification of the measurement signal [46, 48]. In an ideal non-competitive immunoassay, no signal would be produced in the absence of any analyte because there are no appropriate sites available for binding to the signal antibody [48]. However, in practice, this is not the case due to nonspecific interactions between the signal antibody and other components of the immunoassay [48]. Therefore, it is always desirable to use a blocking reagent to reduce these nonspecific interactions. Nonspecific adsorption also needs to be considered when determining the quantity of signal antibody for use in a system [48]. Although this immunoassay format often offers superior specificity, it can only be used for the quantification of analytes with two antigenic determinants that can be simultaneously recognized [46, 48]. Several studies using both competitive and non-competitive immunoassays have been reported [64-67]. Electrochemical detection of immunointeraction can be performed both with and without labeling. A frequently used format in electrochemical immunosensing is an amperometric immunosensor, where proteins are labeled with enzymes producing an electroactive product from an added substrate [9]. 27 Direct detection without labeling can be performed by cyclic voltammetry, chronoamperometry, impedimetry, and by measuring the current during potential pulses (pulsed amperometric detection). These methods are able to detect a change in capacitance and/or resistance of the electrode induced by binding of protein. These immunosensors have been developed using various substrates [9]. Figure 13 - Schematic representation of (a) competitive and (b) non-competitive immunoassay formats [48]. A critical issue in immunoassays is minimization of nonspecific binding (NSB) of interfering species in samples such as serum or blood, as well as NSB of the labeled Ab2 that arises when this signal producing species is bound to non-antigen sites on the sensor [68]. In labeled assays, non-enzyme Ab2 bound to sites other than the analyte protein still gives a signal, but it is not proportional to the analyte protein concentration. This can increase detection limits and degrade sensitivity [68]. NSB is usually minimized by washing with a cocktail that includes casein or bovine serum albumin and detergents in NSB blocking steps. Another solution consists in tailoring the sensor surface with appropriate chemical groups that can also inhibit protein adsorption, and one of the most effective surfaces features polyethylene glycol (PEG) moieties [69, 70]. Such functionalized surfaces, although useful, may still permit small amounts of NSB that could significantly increase background in the pg to ng/mL analyte concentration ranges [68]. 28 2.5.3 Antibody immobilization techniques Since immunosensors usually measure the signals resulting from the specific immunoreactions between the antigens and the antibodies, it is clear that the immobilization procedures of the antibodies on the surfaces of transducers should play an important role in the construction of immunosensors. The manner in which a capture antibody is immobilized on a solid phase is a critical aspect that requires careful consideration in the design of an immunoassay system, whether it is competitive or non-competitive. A desirable feature of the chosen method is that it results in an immobilized capture antibody that is oriented with minimal steric hindrance to interact favorably with its target antigen. Equally important, it is highly desirable to immobilize the antibody without a significant change in its ability to bind its antigen. Clearly, all these features have a direct bearing on the level of sensitivity and dynamic range achievable by an immunosystem. There are several strategies for immobilizing a capture antibody on a solid phase including covalent attachment, physical adsorption or electrostatic/physical entrapment in a polymer matrix. These commonly used immobilization strategies are described below [48]. 2.5.3.1 Biotin-(strept)avidin interaction Specific affinity interactions for antibody immobilization have been widely used in immunoassay systems in recent years. The (strept)avidin–biotin interaction is one such example. This technique may be used to immobilize various types of biomolecules such as nucleic acids, polysaccharides and proteins, including the capture antibody in immunoassay/immunosensor systems. The technique usually involves biotinylating the capture antibody and coating a solid phase with either avidin or streptavidin [48, 71]. The avidin-biotin and biotin–streptavidin interactions are the strongest known non-covalent interactions, presenting dissociation constants of the order of 10-15 mol/L, between a protein and ligand [72]. The complexes formations are very rapid, and once formed withstand high temperatures, pH variations, and are resistant to dissociation when exposed to chemicals such as detergents and denaturing agents [48, 73]. Equally important, the use of this immobilization technique maintains the biological function of the immobilized antibody. In some cases, neutravidin, which is an almost neutrally charged variation of avidin, is used to minimize any non-specific binding by charged species to maintain high binding affinity for biotin [48, 71]. 35 chain alkanethiols, at least 24 h are necessary for short chain alkanethiols or thiols with certain endgroups different from –CH3 [82]. Figure 17 - The formation process of self-assembled monolayers. The assembly process (Figure 17) starts with a physisorption step, followed by chemisorption of the molecules, and finally the formation of crystalline, ordered domains with molecules in a closed-packed configuration [82, 84, 85]. 2.5.4 Nanomaterials based immunosensors The unique properties of nanoscale materials and the ability to tailor their size and structure offer excellent prospects for designing highly sensitive and selective bioassays of nucleic acids and proteins, and render them applicable in the fields of medical imaging and therapy [8, 98]. Nanostructured materials are interesting tools with specific physical and chemical properties due to quantum-size effects and large surface areas, which provide them unique and different properties compared to bulk materials. Currently, the most intense research involves applying nanomaterials in immobilization [99]. Nanostructured sensor surfaces allow the improvement of biosensors properties and additional increases in their sensitivity by providing high surface areas enabling attachment of a large number of capture antibodies and by facilitating better access of protein analytes to these antibodies, enhancing the performance of bioassays [8, 68, 98, 100-102]. Nanotechnology has generated new innovative materials such as nanoparticles [103, 104], quantum dots [105, 106], nanowires [107, 108] and nanotubes [109, 110], all having unique properties applicable in delivering enhanced loading of biological elements, their increased stability or specificity, and enabling the use of novel transduction schemes. Several studies have reported about the enhancement of electronic properties when metallic nanostructures are used as components for electrodes modification [68, 101, 102]. 36 Nanoparticles of different compositions and dimensions have been widely used in recent years as versatile and sensitive tracers for the electronic, optical, electrochemical and microgravimetric transduction of different biomolecular recognition events. The enormous signal enhancement associated with using nanoparticle amplifying labels and with forming nanoparticle-biomolecule assemblies provides the basis for ultrasensitive detection [68, 98, 101, 102, 111, 112]. Typically, metallic nanoparticles are prepared by chemical reduction of the corresponding transition metal salts in the presence of a stabilizer (often citrate, phosphanes or thiols) which binds to their surface to impart high stability and rich linking chemistry and provide the desired charge and solubility properties [98]. In the case of labile anionic ligands capping layers such as citrate or lipoic acid, the biomolecules are often coupled through noncovalent electrostatic interactions [101]. Nanoparticle labels in immunoassays were first reported by Dequaire et al. [113]. Metals in the nanoparticles served as labels after dissolution of the particles. After the antibodies capture of analyte proteins, Ab2-nanoparticles were added to bind to them, and a NSB blocking wash was done. Then, the nanoparticles were dissolved in acid to produce high concentrations of electroactive metal ions. With gold nanoparticle-Ab2 labels, Au3+ released by acid dissolution was detected by anodic stripping voltammetry to give a 3 pmol/L detection limit for IgG in buffer. Gold nanoparticles (AuNPs) have received great attention due to their attractive electronic, optical, and thermal as well as catalytic properties and potential applications in the fields of physics, chemistry, biology, medicine, and material science [114-119]. Therefore the synthesis and characterization of AuNPs have attracted considerable attention from a fundamental and practical point of view. The preparation of AuNPs generally involves the chemical reduction of gold salt in the aqueous, organic phase or in two phases [114]. However, the high surface energy of AuNPs makes them extremely reactive, and most systems undergo aggregation without protection or passivation of their surfaces [91, 114]. This way, special precautions have to be considered to avoid their aggregation and precipitation [114]. Typically the AuNPs synthesis is performed in the presence of a stabilizer which binds to their surface to impart high stability and high rich linking chemistry and provide the desired charge and solubility properties [91, 114]. The synthesis of AuNPs was reported firstly by Faraday in 1857 [117]. To date a large number of methods has already been developed to synthesize AuNPs. Among them, there are two classic ways which are widely employed. The first method for the 37 preparation of AuNPs in aqueous solution was introduced by Turkevich [120], which was subsequently improved by Frens [121]. In this method, AuNPs are prepared by reducing tetrachloroauric acid (HAuCl4) with sodium citrate in boiling water (Turkevich-Frens method) [122]. The size of the synthesized AuNPs can range from 10100 nm by changing the gold to citrate ratio [117]. The water soluble and negatively charged nanoparticles obtained via this method are usually utilized in the assembly of nano-composites and nano-interfaces based on electrostatic interactions [117, 118]. The second method was developed by Brust et al. in 1994 [123]. AuCl4was reduced by sodium borohydride in the presence of alkane thiols in a two phase system [118]. In addition to spherical nanoparticles, other Au structures can be generated in various shapes such as nanorods [124], nanoshells [125], nanocages [126] and nanocubes [127]. Compared to other nanomaterials, AuNPs are chemically stable, non-toxic and easy to functionalize. The stabilization and functionalization of AuNPs with biomolecular recognition motif have provided flexibility for a variety of applications, including bioassay, bioimaging and biosensor [115, 117, 118, 128]. As a result, DNA [129], enzymes [130], antibodies [131] and some functional polymers [132] can be easily conjugated with AuNPs without affecting their activities [118]. Different types of functionalized AuNPs can be developed as required [118]. From an electroanalytical point of view, AuNPs are particularly interesting because of their high stability, good biological compatibility, excellent conducting capability, and high surface-to-volume ratio [114, 119]. These features provide excellent prospects for interfacing biological recognition events with electronic signal transduction and make AuNPs extremely suitable for developing novel and improved electrochemical sensing and biosensing systems [91, 114, 117, 119]. They can be functionalized to detect specific targets, enabling the achievement of low detection limits, thus offering higher sensitivity and selectivity than conventional strategies. In addition, AuNPs present high conductivity essential for sensors based on electrical detection systems [91, 115, 116, 118, 119, 128]. Kang et al. [133] developed a sensitive immunosensor for Aβ42 using an electrical detection system based on scanning tunneling microscopy (STM). The immunosensor consisted on a sandwich immunoassay using an AuNPs-antibody conjugate. In this investigation, the authors concluded that β-amyloid could be successfully detected with electrical detection technique, achieving a 10 fg/mL detection limit. Georganopoulo et al. [134] used the bio-barcode system to detect 38 protein levels with attomolar sensitivity. The method involves the capture of the analyte with a magnetic particle featuring recognition elements, followed by binding of functionalized AuNPs with a second recognition agent and “barcode” (marker) DNA strands. After magnetic separation of the sandwich complex, the DNA barcodes are released and the DNA strands detected and quantified using the Au-nanoprobe sandwich assay followed by silver enhancement. This method was successfully used for measuring the concentration of amyloid-β-derived diffusible ligands, a potential Alzheimer’s disease marker present at extremely low concentrations (<1 pmol/L) in the cerebrospinal fluid of affected individuals [134]. Another relevant example includes the development of a novel enhancement for immunochromatographic test strips where both the primary and the secondary antibodies are conjugated with AuNPs [135]. This experimental set-up increased the detection limit of the chorionic gonadotropin hormone by an order of magnitude to reach 1 pg/mL. 39 3. Materials and Methods 3.1 Reagents and equipments Alumina solution (γ-Al2O3) 0.3 µm and 0.05 µm were purchased from Gravimeta. All other reagents used were of analytical reagent grade. Sulfuric acid (H2SO4, 98%), hydrogen peroxide (H2O2, 30% Sigma-Aldrich, Steinheim, Germany) and absolute ethanol were purchased from Panreac (Spain). Potassium nitrate (KNO3) was purchased from Pronalab (Mexico). Potassium ferrocyanide (K4[Fe(CN)6].3H2O), potassium ferricyanide (K3Fe(CN)6), potassium hydrogen phosphate (K2HPO4) and potassium dihydrogen phosphate (KH2PO4) were purchased from Riedel-de Haën (Germany). N-(3, Dimethylaminopropyl)-N-ethyl-carbodiimide hydrochloride (EDC), 2-mercaptoethanol, 3-mercaptopropionic acid and glutaraldehyde solution were purchased from Fluka (Switzerland). N-hydroxysuccinimide (NHS), cystamine dihydrochloride, sodium citrate dihydrate, gold(III) chloride solution, ethylenediaminetetraacetic acid (EDTA), 2-imninothiolane hydrochloride, citrate buffer solution and 2,2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) were purchased form Sigma-Aldrich (Steinheim, Germany). Milk powder was obtained from Molico Nestlé. Mouse monoclonal antibody to beta amyloid (1 mg/mL) IgG (ab11132) was purchased from Abcam (U.K). Human antigen β-amyloid peptide (1-42) was purchased from Genscript (USA). Goat anti-mouse IgG secondary antibody was purchased from Pierce antibodies/Thermo Scientific. Ultrapure water (18.2 MΩcm-1 resistivity) was produced by a Milli-Q Simplicity 185 system (Millipore, Molsheim, France). Nitrogen (99.999%) was obtained from LINDE (Portugal). The supporting electrolyte for the electrochemical studies was the phosphate buffer solution (0.1 mol/L, pH=7.4). A solution of 10 mmol/L K3[Fe(CN)6]/K4[Fe(CN)6] was prepared in KNO3 (1 mol/L). pH measurements were performed using a pH meter (GLP 22, Crison) with a combined glass electrode. Weight measurements were performed using an analytical balance (Mettler Toledo) with a 0.00001 g precision. 8 inches microcloth polishing cloth (Buehler) was used to perform the mechanical cleaning of the working electrode. 40 3.2 Electrochemical analyses All voltammetric measurements were performed using Autolab electrochemical system (Eco Chemie, The Netherlands) equipped with PGSTAT-30 and General Purpose Electrochemical system for Windows (GPES) software (Figure 18). The electrochemical cell was assembled using a conventional three-electrode cell which included the developed biosensor (based on a polycrystalline gold electrode, BASi MF2014, surface area 2.0 mm2) as a working electrode, a glassy carbon as counterelectrode and a Ag|AgCl|KClsat reference electrode to which all potentials are referred (Figure 19). All experiments were evaluated by square-wave voltammetry (SWV) and electrochemical impedance spectroscopy (EIS) using Fe(CN)63-/4as electroactive indicator. SWV measurements were performed in a 0.1 mol/L PBS solution (pH=7.4) containing 0.01 mol/L of K3[Fe(CN)6]/K4[Fe(CN)6] by varying the potential from 0.00 to 0.600 V at a 0.405 V/s scan rate. The optimal SWV parameters were a frequency of 100 Hz, amplitude of 40 mV and scan increment of 4 mV. EIS measurements were performed in a 0.01 mol/L K3[Fe(CN)6]/K4[Fe(CN)6] solution using a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. Before the analysis, a 5 min nitrogen purge was performed. Figure 18 – Potentiostat PGSTAT-30 (Autolab). 41 Figure 19 – a) Electrochemical cell assembly. Red: Working electrode; Black: Counter electrode; Blue: Reference electrode; b) Working electrode (gold electrode). 3.2.1 Pre-treatment of the working electrode The pre-treatment of the gold electrode includes three stages: mechanical cleaning, chemical oxidation and electrochemical activation of the surface. The gold electrode was mechanically cleaned by polishing with γ-Al2O3 (0.3 μm and 0.05 μm) and then rinsed with water. Next, the gold electrode was immersed in piranha solution (H2O2:H2SO4, 1:3, v/v). For the electrochemical activation of the surface (to create – COOH and –OH functional groups onto the gold electrode), the electrode was cycled from 0.0 to +1.6 V in 0.5 mol/L H2SO4 solution at 100 mV/s. The electrochemical activation stage was also used to ensure the cleanliness of the gold electrode. The process was repeated until typical gold cyclic voltammograms were obtained. 42 3.2.2 Self-assembled monolayers Several self-assembled monolayers (SAM) to modify the gold electrode surface were tested by immersing the gold electrode in 200 µL of the different SAM solutions for a 12 h period at room temperature: cystamine SAM 0.02 mol/L; cystamine and mercaptoethanol mixed SAM (100 µL cystamine 0.02 mol/L + 100 µL mercaptoethanol 0.02 mol/L); mercaptopropionic acid 1 mmol/L; mercaptopropionic acid and mercaptoethanol mixed SAM (100 µL mercaptopropionic acid 1 mmol/L + 100 µL mercaptoethanol 1 mmol/L). Ethanol was the utilized solvent to prepare the SAM solutions. After washing with ultrapure water, the modified electrodes with cystamine were immersed in a 3% glutaraldehyde solution for 30 minutes. On the other hand, the modified electrodes with mercaptopropionic acid were immersed in a EDC/NHS solution (10 mg EDC + 10 mg NHS diluted in 500 µL PBS pH=7.4) for 30 minutes. After selection of the appropriate SAM, the time of immersion and concentration of the solution for the SAM formation were optimized. 3.2.3 Synthesis and electrodeposition of gold nanoparticles The gold nanoparticles (AuNPs) were synthesized by two different methods. In the first method AuNPs were synthesized in accordance with the Turkevich-Frens method by reduction of HAuCl4 using sodium citrate [122]. Tetrachloroauric acid (HAuCl4) aqueous solution (12.5 mL H2O + 8.86 µL HAuCl4) was warmed to slight boiling with continuously mechanical stirring. 1.25 mL of trisodium citrate 11.42 g/L were added and boiled for 15 min. The AuNPs solution was cooled at room temperature and stored at 4 ºC until further use. Hydrodynamic size and potential zeta values were characterized by dynamic light scattering and laser doppler velocimetry, respectively, using a Zetasizer Nano ZS (Malvern, UK), at 25ºC. AuNPs were also evaluated by UV/vis spectrophotometry (Shimadzu UV-1700 PharmaSpec spectrophotometer) at 527 nm. AuNPs electrodeposition on SAM modified gold electrode was carried out at -0.2 V for 600 s. In the second method, the modified gold electrode was immersed in a 0.1 mol/L KNO3 solution containing 3 mmol/L of HAuCl4. AuNPs were synthesized during the electrochemical deposition by applying a -0.2 V potential for 200 s. Then the electrodeposition period was optimized. 43 3.2.4 Antibody immobilization Antibody against β-amyloid was immobilized on the AuNPs using thiol (-SH) groups. In order to promote immobilization with the proper orientation the antibody was prepared through chemical modification (thiolation) with EDTA and iminothiolane. A mixed solution containing 1 µL of EDTA (0.28 mol/L), 82.6 µL of iminothiolane (0.198 mg/mL) and monoclonal antibody against Aβ42 was prepared after dilution with PBS; the volume of PBS added to the antibody was the necessary to make up a volume of 111 µL. The prepared solution reacted for 45 to 50 minutes at room temperature. After reaction 389 µL of PBS were added to the solution in order to make up a volume of 500 µL and the resulting solution was purified by passing it through a sephadex PD MiniTrap G-25 column (GE Healthcare), following the gravity protocol. In a first instant, the flow-through of the column was discarded. Then the column was eluted with 1.0 mL of PBS and the eluate was collected to an eppendorf. Three concentrations of antibody in PBS were tested (1.0 µg/mL, 2.5 µg/mL and 5.0 µg/mL). The SAM/AuNPs modified gold electrodes were immersed in 300 µL of the different antibody solutions, reacted for 2 h at room temperature and then were incubated at 4 ºC for 12 h. After concentration optimization, the incubation time was also optimized. For that purpose, five incubation times were tested 2.5, 5, 7.5, 10 and 12.5 h. 3.2.5 β-Amiloyd (1-42) detection Firstly in order to evaluate the necessary time to promote the antibody-antigen reaction, an indirect ELISA assay was performed using ABTS as the detection product. The end product is green and the absorbance was measured at 405 nm. For the performance of the ELISA test the antigen was diluted in PBS (pH=7.4) to a final concentration of 90 µg/mL and the antigen was immobilized on the wells of a 96 well plate (Nunc MaxiSorp). The plate was then covered with an adhesive plastic and incubated at 37 ºC for 1 h. After the antigen immobilization it was necessary to block the remaining protein-binding sites in the coated wells by adding 10% non fat dry milk. The plate was covered with an adhesive plastic and incubated at 37 ºC for 1 h. Then diluted primary antibody was added to the coated wells and incubated at room temperature for 5 min. Next, the conjugated secondary antibody diluted in 3% non fat dry milk was added to the coated wells. At last, the substrate solution (ABTS) was 44 added and after sufficient colour development the optical density was measured at 405 nm. After each step the coated wells were washed three times with PBS. After immobilization of the antibody and after washing with ultrapure water, the antibody/AuNPs/SAM modified gold electrodes were immersed in 300 µL of β-amyloid (1-42) solution for 5 min at room temperature. The antigen solutions were prepared in 0.1 mol/L PBS solution (pH=7.4). In this study eight antigen concentrations, 9028, 4514, 2257, 903, 451, 45.1, 4.51 and 0.451 ng/mL were used. The inhibition percentages (IR, %) and the selected antigen concentrations were employed to obtain the analytical data. The inhibition percentage (% IR) was calculated using the following equation (3): %IR=[1-(Ip/Ipº)] ×100 (3) where Ipº and Ip are the peak currents before and after the incubation of the biosensor in the presence of the antigen solution. The standard deviation of the intercepts and the average of slopes of the straight lines from the analytical curves were used to determine the detection (LOD) and quantification limits (LOQ) [136]. All measurements were made, at least, in duplicate. 51 suitable microenvironment on the electrode and lend more freedom of orientation to enhance the direct electron transfer behavior [55]. In this work two methods were used to synthesize the AuNPs. Firstly, the AuNPs were synthesized by the Turkevich-Frens method [122]. As mentioned previously, in this method AuNPs were prepared by reducing tetrachloroauric acid (HAuCl4) with sodium citrate in boiling water. Produced nanoparticles were spectrophotometrically characterized in a range of 200 to 700 nm (Figure 25). From wavelength analysis of the predominant detected peak, the AuNPs size may be estimated in accordance with Link et al. [139]. That way, from observation of Figure 25 it is possible to conclude that the nanoparticles solution exhibits an absorbance peak at 527 nm which correspond to a diameter of 30 ± 10 nm [139]. This data is in accordance with the AuNPs characterization performed by dynamic light scattering. From these measurements it was concluded that the nanoparticles presented a hydrodynamic size of 36.8 ± 0.57 nm. The potential zeta of the AuNPs was -38.1 ± 2.1 mV, confirming the stability of the nanoparticles attained by the citrate-capped effect. Figure 25 - Absorption spectrum of the gold nanoparticles prepared by the Turkevich-Frens method. The immobilization of AuNPs onto the MPA/AuE is usually performed by two methods: electrodeposition or/and by covalent and electrostatic interactions with selfassembled monolayers that present the appropriate functional groups for that purpose. 0 0.2 0.4 0.6 0.8 1 1.2 0 100 200 300 400 500 600 700 800 Absorbance Wavelenght (nm) 52 In this work the nanoparticles were immobilized on the mercaptopropionic acid SAM by electrodeposition, which consists in the application of -0.2 V for 600 s. The second method tested for the AuNPs synthesis is based on the electrodeposition process that occurs at -0.2 V for 200 s when the MPA/AuE is immersed in a KNO3 solution containing HAuCl4 [140]. The AuNPs deposition on the MPA/AuE led to a significantly signal enhancement of the Fe(CN)63-/4redox pair (Figure 26) associated with the increase of the gold electrode area and conductivity. Figure 26 - Square-wave voltammograms obtained for the bare gold electrode (a), after modification with the 5 mmol/L MPA SAM (b), and electrodeposition of AuNPs synthesized by the Turkevich-Frens method during 600 s (c) and by the potential application during 200 s (d). Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. From Figure 26 it can be concluded that the AuNPs synthesized by the both methods caused approximately the same signal enhancement when deposition is applied during 600 and 200 s, respectively for the AuNPs produced by the Turkevich-Frens method and by electrodeposition. Consequently, this second procedure was chosen to obtain the AuNPs/MPA/AuE biosensor since it constitutes a simpler and faster process. The results of the optimization of AuNPs electrodeposition time are presented in Figure 27. It can be concluded that a 100 s period is sufficient to promote a successful synthesis and deposition of AuNPs since the three tested period of time promoted almost the same signal enhancement. a) b) c) d) 53 Figure 27 – Square-wave voltammograms obtained with the bare gold electrode (AuE) and AuNPs/MPA/AuE biosensor for different AuNPs electrodeposition periods. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. EIS was also applied since it is an effective tool for the characterization of the interface properties of the electrode surface during different modification steps. The obtained Nyquist diagrams at the bare AuE, MPA/AuE and AuNPs/MPA/AuE sensor are exhibited in Figure 28. At high frequencies, the diameter of the semicircular portion controls the electron transfer kinetics of the redox process at the electrode interface. It dramatically decreased after modification of the MPA/AuE with AuNPs. In the presence of AuNPs the system exhibited a better performance as electrochemical biosensor. AuNPs are widely used nanomaterials because of their large surface area, strong adsorption ability, and high conductivity [114, 115, 118]. Their conductivity characteristics improve the electron transfer at the electrode surface. They can strongly interact with biomaterials and they have been used as a mediator to immobilize biomolecules and to efficiently retain their activity. Thus they will enable the immobilization of the antibody. At lower frequencies, the linear part is typical of a mass diffusion-limited electron-transfer process. AuE 100 s 150 s 200 s 54 Figure 28 - Nyquist plot of electrochemical impedance spectra for bare gold electrode (AuE), MPA/AuE and AuNPs/MPA/AuE. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. 4.2.3 Antibody immobilization onto the AuNPs/MPA/AuE The antibodies were functionalized through chemical modification (thiolation) to promote the antibody immobilization with the proper orientation. The objective of this treatment was to encourage the antibody immobilization to the AuNPs using thiol groups created in the Fc section of the antibody (Figure 12) in order to make the antigen binding site available. For this purpose the antibody was treated with Traut’s reagent, or 2-iminothiolane, and EDTA. The reagent reacted with the amine groups in the antibodies to result in permanent modifications containing terminal sulfhydryl residues [141]. EDTA was required to stop completely metal-catalyzed oxidation of sulfhydryl groups [141]. Three concentrations (1.0, 2.5 and 5.0 µg/mL) of antibody were tested and a large signal reduction for the Fe(CN)63-/4redox couple was observed (Figure 29). This peak diminution is caused by the partial blockage of the AuNPs/MPA/AuE surface by the antibodies making the electron transfer process between the electrode and the solution slower and more difficult. The spectra attained by EIS (Figure 30) also supported these results confirming that the antibody was successfully immobilized at the AuNPs/MPA/AuE surface. The semicircle diameter at high frequencies was significantly enlarged after immobilization of the antibody and the enlargement of the semicircle diameter seemed proportional to the antibody concentration. AuE MPA/AuE AuNPs/ MPA/AuE 55 Figure 29 – Square-wave voltammograms obtained for AuNPs/MPA/AuE and AuNPs/MPA/AuE modified with different antibody concentrations for a 12 h incubation time. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. Figure 30 - Nyquist plot of electrochemical impedance spectra for AuNPs/MPA/AuE and AuNPs/MPA/AuE modified with different antibody concentrations. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. AuNPs/MPA/AuE Anti-Aβ42 (1.0 µg/mL) Anti-Aβ42 (2.5 µg/mL) Anti-Aβ42(5.0 µg/mL) AuNPs/MPA/AuE Anti-Aβ42 (1.0 µg/mL) Anti-Aβ42 (2.5 µg/mL) Anti-Aβ42(5.0 µg/mL) 56 The concentration that seems to best suit the objective of the work was the amount of 1.0 µg/mL because a high or complete blockage of the surface is undesirable since it would difficult or preclude the antigen quantification. Despite the lower signal reduction achieved with the concentration 1.0 µg/mL, an optimization of the incubation time was performed in order to accomplish a successful immobilization of the antibodies that enabled at the same time the quantification of Aβ42. Five incubation times (2.5, 5, 7.5, 10 and 12.5 h) were tested and the results achieved are exhibited in Figure 31. The 7.5 h incubation time was selected as the most adequate since the signal was reduced to approximately half of the one obtained with AuNPs/MPA/AuE. It ensures the successful antibody immobilization and still enables future antigen quantification. The lower incubation times (2.5 and 5 h) caused a slight signal reduction which did not assure a good antibody immobilization. On the other hand, the highest incubation times (10 and 12.5 h) caused a large signal reduction which would not allow the antigen quantification to be performed. Figure 31 - Square-wave voltammograms obtained with the AuNPs/MPA/AuE and the AuNPs/MPA/AuE modified with different antibody (1.0 µg/mL) incubation times. Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. The impedance spectra attained with the AuNPs/MPA/AuE modified with different antibody (1.0 µg/mL) incubation times are presented in Figure 32. The results are in agreement with those obtained by square-wave voltammetry. The diameter of the AuNPs/MPA/AuE 2.5 h 5 h 7.5 h 10 h 12.5 h 57 semicircles was proportional to the incubation times. In the case of higher incubation times it was observed an increase in the electron transfer resistance which corresponds to the immobilization of higher amounts of antibodies on the biosensor. On the other hand lower incubation times exhibited small diameters which exalts the immobilization of small amounts of antibodies facilitating the electron transfer process between the modified gold electrode and Fe(CN)63-/4-. Figure 33 summarizes the results of impedance spectroscopy concerning the biosensor construction. Figure 32 - Nyquist plot of electrochemical impedance spectra for the AuNPs/MPA/AuE modified with different antibody (1.0 µg/mL) incubation times. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. The next step after antibody immobilization usually is the immobilization of bovine serum albumin (BSA) in order to minimize the nonspecific binding of interfering species present in samples such as serum and blood [68]. However as this sensor was only studied in PBS solutions containing Aβ42 the risk of occurring nonspecific bindings was abolished. Nevertheless, it is important to refer that this is an important step and it is going to be implemented before future tests in samples such as serum, blood or cerebrospinal fluid. 2.5 h 5 h 7.5 h 10 h 12.5 h 58 Figure 33 - Nyquist plot of electrochemical impedance spectra for the AuE, MPA/AuE, AuNPs/MPA/AuE and Anti-Aβ42/AuNPs/MPA/AuE. Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. 4.3 Amyloid β (1-42) detection In order to evaluate the necessary time to promote the antibody-antigen reaction, an indirect ELISA assay performed at 405 nm using ABTS as the detection product was performed. The final product is green making easy to detect the development of the reaction. As a result of this test it was concluded that a 5 min period was enough to promote the link between the antigen and the antibody. Square-wave voltammetry was used to analyze Aβ42 concentrations based on the current intensity Ipº and Ip measured before and after the incubation of the immunosensor in the presence of the antigen solution. The antibody-antigen interaction led to a signal reduction caused by the blockage of the surface making the electron transfer process between the Anti-Aβ42/AuNPs/MPA/AuE surface and Fe(CN)63-/4more difficult. The decrease of the peak current intensities is proportional to the increase of the Aβ42 concentration (0-9028 ng/mL) (Figure 34). These results of SWV and EIS (Figure 35) indicate that the binding of the Aβ42 antigen to the Aβ42 antibody further blocks the electrode transfer barrier and increases the electron transfer resistance in electrochemical impedance measurements. AuE MPA/AuE AuNPs/MPA/AuE Anti-Aβ42/AuNPs/MPA/AuE 59 Figure 34 - Square-wave voltammograms obtained with the Anti-Aβ42/AuNPs/MPA/AuE immunosensor after expositions to different Aβ42 concentrations (0 to 9028 ng/mL). Profiles obtained in a 0.1 mol/L PBS solution pH=7.4 containing 0.01 mol/L Fe(CN)63-/4at a 0.405 V/s scan rate. Figure 35 - Nyquist plot of electrochemical impedance spectra observed with the AntiAβ42/AuNPs/MPA/AuE immunosensor after expositions to different Aβ42 concentrations (0 to 9028 ng/mL). Profiles obtained in a 0.01 mol/L Fe(CN)63-/4solution by applying a frequency range from 10-1 to 105 Hz with an amplitude perturbation of 5 mV. Figure 36 shows the several stages for the biosensor construction. Figure 37 shows the same process but in an impedance spectra reached in a solution of 0.01 mol/L of Fe(CN)63-/4-. The diameter of the semicircle in the Nyquist plot, which exhibits the electron transfer resistance of the layer, can be used to describe the interface properties Aβ42 (0 ng/mL) Aβ42 (0.451 ng/mL) Aβ42 (4.51 ng/mL) Aβ42 (45.1 ng/mL) Aβ42 (451 ng/mL) Aβ42 (4514 ng/mL) Aβ42 (9028 ng/mL) Aβ42 (0 ng/mL) Aβ42 (0.451 ng/mL) Aβ42 (4.51 ng/mL) Aβ42 (45.1 ng/mL) Aβ42 (451 ng/mL) Aβ42 (903 ng/mL) Aβ42 (2257 ng/mL) Aβ42 (4514 ng/mL) Aβ42 (9028 ng/mL) 60 of the electrode for each immobilized step. Firstly, the bare gold electrode exhibited a straight line characteristic of the diffusion limit process. Secondly, the mercaptopropionic acid SAM was immobilized on the gold electrode, blocking its surface and increasing the electron transfer resistance leading to an enlargement of the semicircle diameter. Then AuNPs were electrodeposited onto the MPA/AuE decreasing significantly the electron transfer resistance and consequently the semicircle diameter was reduced to an almost straight line. 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