Electrochemical Aptamer Biosensors for the Detection of ...

Electrochemical Aptamer Biosensors for the Detection of

Amyloid-beta Oligomers

Von der Fakultät für Mathematik, Informatik und Naturwissenschaften der RWTH Aachen

University zur Erlangung des akademischen Grades einer

Doktorin der Naturwissenschaften genehmigte Dissertation

vorgelegt von

Master of Science in Analytical Chemistry

Yuting Zhang

Aus

Anhui, China

Berichter: Universitätsprofessor Dr. rer. nat. Ulrich Simon

Universitätsprofessor Dr. rer. nat. Andreas Offenhäusser

Tag der mündlichen Prüfung: 3rd

July, 2020

Diese Dissertation ist auf den Internetseiten der Universitätsbibliothek verfügbar.

I

Abstract

Alzheimer‘s disease (AD) is the most common chronic neurodegenerative disease

characterized by progressive and irreversible cognitive decline. Early detection of AD becomes

especially urgent due to its latency more than 20 years and the uncertainty of current diagnosis.

Amyloid-β oligomer (AβO) is an important diagnostic marker for Alzheimer's disease (AD) and

potential therapeutic target for treating it. Recently, more and more research show that amyloid-β

oligomer (AβO) is toxic to brain cells by dysfunction of receptors on the cell surface and ion

flow caused by abnormal membrane structures [1, 2]. Therefore, the development of a biosensor

that can sensitively and selectively detect AD biomarkers AβO has become an important

research field. This thesis reports on the development of electrochemical aptamer sensors

(aptasensors) for the specific recognition of AβO based on the binding of these biomarkers to

ssDNA aptamer receptors.

Firstly, a simple and label-free electrochemical biosensor was realized for the specific

recognition of AβO based on the binding of these biomarkers to ssDNA aptamer receptors. From

the analysis results of electrochemical impedance spectroscopy (EIS), the novel aptasensor

shows a wide linear concentration range from 0.1 nM to 500 nM with a low detection limit of

0.03 nM. Furthermore, owing to the high selectivity among Aβ species, this label-free sensor is

used to monitor the process of Aβ protein aggregation, which is validated by atomic force

microscope analysis. Besides, the aptasensor can be used to detect AβO in artificial cerebrospinal

fluid (CSF) with satisfying accuracy. To our knowledge, it is the first label-free aptasensor for an

AβO assay based on EIS that works in artificial CSF and can be used for monitoring Aβ protein

aggregation.

To overcome the un-specific adsorption of EIS aptasensor and further improve the

sensitivity towards AβO detection, an aptasensor based on stem-loop probes was developed for

sensitive and specific detection of Aβ oligomers by an amperometric transducer principle using

alternating current voltammetry (ACV). Furthermore, the current-signal aptasensor makes it

possible to transfer the sensing platform to the next microelectrodes because the too high

impedance due to the small electrode size of microelectrode is not benefiting for the

improvement of sensor sensitivity. The signal transduction mechanism relies on redox ferrocene

II

(Fc) reporting via charge transfer on a molecular recognition event involving a conformational

change of the molecular beacon. The stem-loop structures were optimized by considering the

aptamers‘ stem length, spacer, and different ferrocene terminals. In addition, the assembly and

signal recording including aptamer concentration and ACV frequency are discussed. Using the

optimized stem-loop probe (B-3‘ Fc), the aptasensor showed an increase of the Fc peak current

induced by AβO binding within the broad concentration range spanning six orders of magnitude.

Furthermore, the detection limit of the sensor can be further decreased by optimizing the ACV

frequency, however at the costs of a narrowed detection range.

Multielectrode arrays (MEAs) have been increasingly used for biosensors due to their fast

mass transfer rate, redundant signal recording and high spatial resolution. However, the number

of receptors on the transducer surface is limited, and the high device impedance caused by the

small size of the microelectrode hampers the downscaling of emerging biosensors concepts such

as aptasensors. AD is often associated with mitochondrial dysfunction, which is closely related

to the level of adenosine triphosphate (ATP). Therefore, simultaneous detection of AβO and

ATP on the same MEAs chip has a significance for the early detection of AD and pathological

study of other neurodegenerative diseases. Therefore, a multi-aptamer modified MEA chip was

developed based on microelectrodes with electrodeposited 3D nanostructured gold (3D-GMEs).

Linear sweep voltammetry, square wave voltammetry and chronoamperometry (CA) were used

to electrodeposit gold on the microelectrode surface. The surface morphologies of the 3D-GMEs

obtained by different deposition conditions were observed by scanning electron microscopy, and

the electroactive areas of the 3D-GMEs were obtained by cyclic voltammetry (CV) in 0.05 M

H2SO4. Considering the results of the topographical characterization and obtained

electrochemical active area, CA was used for electrodeposition to achieve the optimal stability

and large active areas. CV and electrochemical impedance spectroscopy were utilized for the

electrochemical characterization of gold electrodeposited electrodes, and alternating current

voltammetry was used to detect signal changes of labeled ferrocene after aptamer conformation

change due to target-aptamer binding. The stem-loop aptamer modified 3D gold microelectrode

was used to detect AβO with a wide linear range from 1 pM to 200 nM. The selectivity, stability,

reusability, and real sample detection of the aptasensor are also investigated. Finally, to realize

the modification of different aptamer receptors at different 3D-GMEs on the same MEAs chip,

electrochemical cleaning and plasma cleaning were also applied for 3D-GMEs regeneration. The

III

regenerated 3D gold microelectrodes can be used for the new modification of aptamer again ATP,

and the developed aptasensor shows a linear range from 0.01 nM to 1000 nM for ATP detection.

Finally, ATP and AβO could be detected simultaneously in the same analyte solution. The easy

fabrication, miniaturization, pico-molar and lower sensitivity, as well as selectivity even over

other Aβ species make the developed electrochemical aptasensors interesting for point-of-care

applications rather than for pharmacological drug studies.

V

Zusammenfassung

Die Alzheimer-Krankheit (AD) ist die am weitesten verbreitete, chronische,

neurodegenerative Erkrankung, die mit einem fortschreitenden und irreversiblen Verlust

kognitiver Fähigkeiten verbunden ist. Deren Frühdiagnose ist von besonderer Dringlichkeit, da

Alzheimer eine Latenzzeit von mehr als 20 Jahren aufweist. Amyloid- Oligomere (AO) sind

wichtige diagnostische Biomarker für AD und ein bedeutendes therapeutischen Ziel die

Krankheit zu heilen. In letzter Zeit deuten immer mehr Studien darauf hin, dass AO toxisch für

Zellen des zentralen Nervensystems ist, hervorgerufen durch Störung der Funktion von

Rezeptoren der Zellmembran sowie Störungen des Ionenaustauschs durch abnormale

Membranstrukturen [1,2]. Daher hat sich die Suche nach Biosensoren, die selektiv und sensitiv

AD Biomarker nachweisen können, zu einem bedeutenden Forschungsfeld entwickelt. In dieser

Arbeit wird über die Entwicklung von elektrochemischen Aptamersensoren für den spezifischen

Nachweis von AO berichtet, basierend auf der Bindung zwischen diesen Biomarkern und

ssDNS Aptamerrezeptoren.

Zu Beginn wurde ein einfacher labelfreier elektrochemischer Biosensor hergestellt. Die

Analyse der Daten der Elektrochemischen Impedanzspektroskopie (EIS) ergab für diesen Sensor

einen breiten linearen Konzentrationsbereich von 0.1 nM bis 500 nM und eine niedrige

Detektionsgrenze von 0.03 nM. Weiterhin wurde der Sensor aufgrund seiner hohen Selektivität

für die Verfolgung von A Aggregationsprozesse genutzt. Die Ergebnisse wurden durch

Rasterkraftuntersuchungen validiert. Darüber hinaus wurde gezeigt, dass der Sensor für den

Nachweis der Biomarker in künstlicher zerebrospinaler Flüssigkeit (aCSF) mit

zufriedenstellender Genauigkeit benutzt werden kann. Nach gegenwärtigem Kenntnisstand ist

dies der erste labelfreie Aptamersensor für den Nachweis von AO basierend auf EIS, der mit

aCSF duchgeführt werden kann und die Untersuchung des Aggregationsverhaltens von

Amyloidmolekülen erlaubt.

Um jedoch die unspezifische Bindung zwischen Sensoroberfläche und Analytmoleküle

zu unterdrücken und die Sensitivität des AO Nachweises zu erhöhen, wurde ein Aptasensor

basierend auf Stamm-Schleifen Rezeptoren entwickelt. Hierfür wurden die Rezeptoren mit

Redoxsonden modifiziert, was einen amperometrischer Nachweis mittels Wechselsstrom-

VI

Voltammetrie (ACV) ermöglichte. Der Wechsel des Transducerprinzips war auch für die

Miniaturisierung des Sensors von entscheidender Bedeutung, da die hohe Impedanz von

Mikroelektroden impedimetrische Nachweise erschwert. Das amperometrische

Transducerprinzip beruht auf dem Ladungstransfer von aptamerassoziierten Redoxgruppen, der

von Konformationsänderungen des Rezeptors abhängt. Die Stamm-Schleifen Struktur wurde

bezüglich der Stammlänge, Spacersequenz und Position der Redoxgruppe am Aptamerrezeptor

optimiert. Zusätzlich wurde der Einfluss der Aptamerkonzentration und der ACV Frequenz auf

das Sensorsignal untersucht. Von allen getesteten Sequenzen erwies sich (B-3‘ Fc) mit der

Redoxsonde am 3‘- und einer Thiolgruppe am 5‘-terminalen Ende als am besten geeignet mit

einem breiten Konzentrationsbereich, der sechs Größenordnungen umspannte. Es wurde

weiterhin beobachtet, dass die Detektionsgrenze zu niedrigeren Limits verschoben werden kann,

jedoch nur auf Kosten eines eingeschränkten Detektionsbereiches.

Mikroelektrodenfelder (MEAs) gewinnen stetig an Bedeutung für die Entwicklung von

Biosensoren aufgrund hohen Massentransports im Elektrolyten zu den Elektroden, redundanter

Messsignale und hoher räumlicher Auflösung. Jedoch ist für diese Systeme die Anzahl an

Rezeptoren an der Oberfläche begrenzt und die hohe Impedanz, hervorgerufen durch die geringe

Elektrodengröße, erschweren das herunterskalieren der Aptamersensoren. AD ist oft mit

Fehlfunktionen der Mitochondrien assoziiert, was sich stark auf die Konzentration an Adenosin

Triphosphat (ATP) in Neuronen auswirkt. Die simultane Detektion von AβO und ATP mithilfe

des selben MEA Chips stellt eine Chance für die Früherkennung und pathologische

Untersuchungen von AD dar. Daher wurde ein Chip entwickelt, der Mikroelektroden enthält

deren Oberfläche durch Goldnanostrukturen vergrößert und mit unterschiedlichen

Aptamerrezeptoren modifiziert wurde. Linearvorschubvoltammetrie,

Rechteckspannungsvoltametrie und Chronoamperometrie (CA) wurden verwendet, um Gold auf

die Mikroelektroden zu deponieren (3D-GMEs). Die Oberflächenmorphologie der

unterschiedlichen Nanogold-Mikroelektroden wurde mithilfe von Rasterelektronenmikroskopie

untersucht und deren elektroaktive Oberfläche durch Oxidations-Reduktionszyklen in

schwefelsauren Lösungen ermittelt. Die Ergebnisse dieser Untersuchungen legten nahe, das

Chronoamperometrie den besten Kompromiss zwischen großer elektroaktiver Oberfläche und

Sensorstabilität lieferte. CV und EIS wurden verwendet, um die 3D-GMEs elektrochemisch zu

charakterisieren. Die Änderungen der Redoxsignal, hervorgerufen durch

VII

Konformationsvariationen der Ferrocen-markierten Aptamermoleküle, wurden mit ACV

detektiert. Die Stamm-Schleifen-Aptamer modifizierten 3D Goldmikroelektroden waren in der

Lage, AβO in einem breiten Konzentrationsbereich von 1 pM bis 200 nM nachzuweisen. Zudem

wurde die Selektivität, Stabilität, Wiederverwendbarkeit und Arbeitsfähigkeit in realen Proben

untersucht. Abschließend, wurden Methoden zur gezielten elektrochemischen bzw.

plasmachemischen Regeneration von ausgewählter Elektroden des Elektrodenfeldes entwickelt,

damit weitere Aptamerrezeptoren an diese Elektroden des Sensorfeldes gebunden werden

können. Beispielhaft wurden die regenerierten 3D Gold Mikroelektroden mit ATP Aptameren

modifiziert und der korrespondierende Analyt in einem Detektionsbereich zwischen 0.01 nM und

1000 nM mit einem Detektionslimit von 0.002 nM nachgewiesen. Abschließend konnten ATP

und AO gleichzeitige in derselben Analytlösung nachgewiesen werden. Die einfache

Herstellung, Miniaturisierbarkeit, Sensitivität im Pico-Molarbereich und darunter, als auch

Selektivität selbst gegenüber anderen A Spezies macht die hier entwickelten AO

Aptamersensoren interessant für Point-of-Care Anwendungen als auf für pharmakologische

Wirkstoffstudien.

IX

Content

Chapter 1 Introduction .................................................................................................................... 1

Chapter 2 Fundamentals and theory ............................................................................................... 5

2.1 Aptamer as receptor ............................................................................................................. 5

2.1.1 Systematic evolution of ligands by exponential enrichment ..................................... 6

2.1.2 Aptamer specificity and advantages........................................................................... 7

2.2 Electrochemical aptasensor .................................................................................................. 9

2.2.1 Working principle of electrochemical biosensors .................................................... 10

2.2.2 DNA probe immobilization ..................................................................................... 10

2.2.3 Classification of aptasensors .................................................................................... 12

2.3 Fundamentals of Electrochemistry ..................................................................................... 13

2.3.1 Electrochemical interface and processes .................................................................. 14

2.3.2 Voltammetry ............................................................................................................ 17

2.3.3 Electrochemical impedance spectroscopy................................................................ 24

2.4 Non-electrochemical characterization techniques .............................................................. 29

2.4.1 Scanning electron microscopy ................................................................................. 29

2.4.2 Atomic force microscopy ......................................................................................... 31

2.4.3 UV-Vis spectroscopy ............................................................................................... 32

Chapter 3 Materials and methods ................................................................................................. 35

3.1 Reagents ............................................................................................................................. 35

3.2 Electrode preparation ......................................................................................................... 36

3.2.1 Gold rod electrode cleaning ..................................................................................... 36

3.2.2 Multielectrode arrays preparation and cleaning ....................................................... 37

3.3 Fabrication of the aptasensor ............................................................................................. 38

X

3.3.1 DNA concentration measurements .......................................................................... 38

3.3.2 Immobilization of aptamer ....................................................................................... 39

3.4 Preparation of amyloid-β peptides ..................................................................................... 40

3.5 Electrochemical measurements .......................................................................................... 40

3.5.1 Cyclic voltammetry .................................................................................................. 41

3.5.2 Electrical impedance spectroscopy .......................................................................... 42

3.5.3 Alternating current voltammetry .............................................................................. 43

3.5.4 Chronocoulometry for receptor density ................................................................... 43

3.6 Electrodeposition of gold nanostructures (3D-GMEs) ...................................................... 43

3.7 Morphological characterization ......................................................................................... 44

3.7.1 AFM for Aβ peptides aggregation process .............................................................. 44

3.7.2 AFM for characterizing aptasensor preparation ....................................................... 44

3.7.3 Scanning electron microscopy of 3D-GMEs ........................................................... 45

3.8 Regeneration of microelectrodes on 3D-GMEAs .............................................................. 45

Chapter 4 Results and discussion .................................................................................................. 47

4.1 Characterization of aptasensor preparation ........................................................................ 47

4.1.1 Electrochemical characterization of the aptasensor fabrication process .................. 47

4.1.2 Aptamer surface density ........................................................................................... 48

4.1.3 Morphological characterization of the aptasensor fabrication process .................... 50

4.1.4 Comparison of different aptamers ............................................................................ 54

4.2 Monitoring amyloid-β proteins aggregation based on label-free aptasensor ..................... 55

4.2.1 Scheme of the impedimetric biosensor .................................................................... 55

4.2.2 Aptasensor performance........................................................................................... 56

4.2.3 Monitoring Aβ proteins aggregation ........................................................................ 61

4.3 Amperometric aptasensor for AβO detection .................................................................... 62

XI

4.3.1 Scheme of the amperometric aptasensor based on stem-loop .................................. 64

4.3.2 Comparison of the aptamer stem-loop structures..................................................... 66

4.3.3 Optimizations of aptamer concentration and frequency .......................................... 71

4.3.4 Performance of aptasensor for AβO ......................................................................... 74

4.4 Electrochemical dual-aptamer biosensor based on 3D-GMEs ........................................... 77

4.4.1 Optimize deposition conditions ............................................................................... 79

4.4.2 Comparison 3D-GMEs with bare microelectrodes .................................................. 88

4.4.3 Performance of aptasensor for AβO ......................................................................... 90

4.4.4. Regeneration of 3D-GMEAs for ATP detection ..................................................... 96

Chapter 5 Conclusions and outlook ............................................................................................ 103

Acknowledgements ..................................................................................................................... 107

Appendix I: Abbreviations .......................................................................................................... 109

Appendix II: List of Figures ....................................................................................................... 111

Appendix III: List of Tables ....................................................................................................... 117

References ................................................................................................................................... 119

Introduction

1

Chapter 1 Introduction

Alzheimer's disease (AD), as the most common form of dementia, is an irreversible age-

related, progressive brain disorder causing memory loss and impaired thinking skills [3, 4].

According to the world Alzheimer report 2018, AD affects more than 50 million people and this

number will reach 152 million by 2050 [5, 6]. Because the onset of AD occurs stealthily many

years before the emergence of the initial symptoms, early diagnosis of AD is difficult [7].

However, the existing treatments now are only available to maintain AD patients‘ mental

abilities instead of reversing the progression of AD. Since 1988, more than 100 related drugs had

tested for curing AD. However, among them, only 4 drugs were authoritatively applied, but

limited to certain patients [6]. Therefore, if early diagnosis of AD can be achieved by the

detection of biomarkers before brain cell injury, it can be very useful for subsequent treatment

and maintenance of cognitive ability. Also, the clinical diagnosis now only provides an overall

sensitivity of 85% mainly based on patients‘ history, cognitive assessment and neuroimaging [8,

9]. Therefore, searching for a reliable, inexpensive, and sensitive biomarker that can be used in

early diagnosis of AD is an urgent scientific challenge and an area of active research.

The pathology of AD is characterized by the aggregation of amyloid-β (Aβ) which is a

small 39−43 amino acid residue derived from amyloid precursor protein in the brain of the

patients [10]. For many years, scientists assumed that the Aβ-induced neurotoxicity in cell

culture and in vivo was associated with insoluble Aβ fibrils (AβF) and plaques (AβP) [11, 12].

However, recent evidences indicate that the small and soluble Aβ oligomers (AβO), also found

in AD patients‘ cerebrospinal fluid (CSF), are correlated with AD onset much more strongly than

the insoluble AβF and small Aβ monomers (AβM). In the new pathology of AD, AβO induce

neuron cells death and brain disorder through a variety of physiological and biological activities,

including the abnormal flow of ions, synaptic dysfunction and impaired kinase activity related to

long-term potentiation [1, 13, 14]. Accordingly, AβO has been regarded as attractive biomarkers

for the exploitation of diagnostic and therapeutic reagents of AD.

A variety of approaches have been employed for detecting soluble AβO, such as surface-

based fluorescence intensity distribution analysis [15], fluorescence microscopy [16], enzyme-

2

linked immunosorbent assay [17], electrochemical techniques [18, 19], localized surface

plasmon resonance [20], and mass spectrometry [21]. Among those methods, an electrochemical

immunosensing methodology due to its high sensitivity/specificity as well as simplicity of

instrumentation fast, selective and ultrasensitive detection capabilities has been adopted for

specific AβO detection [22]. The EIS method as one of the best non-invasive analytical tools

combining antigen-antibody binding is the most commonly used for AβO assay[23, 24].

However, they are usually time-consuming, labor-intensive, and costly, because of the expensive

antibody production [25]. Besides, the antibodies show the specific binding to AβO by only one

site binding from the N terminus of AβO, which means antibodies cannot perform an outstanding

selectivity detection for AβO against other Aβ species. Consequently, there is still a need to

improve the simplicity, selectivity, stability, and sensitivity of these analytical methods to make

them more affordable and the diagnosis more reliable for real sample test in CSF.

Aptamers have emerged as alternative bio-recognition elements to antibodies due to their

high stability, low cost, and versatility easy modification chemistry [26]. So far, aptamers have

been combined with fluorescent [27], colorimetric [28], and electrochemical transducers [29],

with the aim to develop versatile novel biosensors for a huge variety of biomarkers such as

malaria-related PfLDH [30], ATP [31, 32] and VEGF [33] for cancer diagnosis. Aptamers,

screened through the systematic evolution of ligands by exponential enrichment process from

random RNA or DNA libraries, are artificial oligonucleic acids or peptide molecules that require

the formation of three-dimensional structures for target binding, for example, hairpin,

pseudoknot, bulge, or G-quartet [34]. The aptamers react with target molecules through

hydrogen bonding, hydrophobic stacking, van der Waals forces, etc. [35]. Recently, Tsukakoshi

et al. have selected AβO ssDNA aptamers through the combination of a gel-shift assay and a

competitive screening method [36]. The selected aptamers have been successfully used in

biological assays for Aβ detection by fluorescence or electrochemiluminescence signals;

however, the complicated preparation and high costs make them hard to realize on large-scale

and daily usage [37, 38].

Electrochemical aptamer sensors (aptasensors) are widely used and possess great potential

for personalized medicine (diagnostic tests to guide therapy) due to the high sensitivity, fast

response, and simple operation [39, 40]. Since most DNA oligonucleotides are not redox-active

and cannot produce faradic responses, electrochemically active substances need to be introduced

Introduction

3

for the electrochemical analysis. Based on the introduction of the electroactive substances, the

electrochemical aptamer sensors can be divided into two types: the label-free aptasensor and the

labeled aptasensor. The label-free aptasensor detects the concentration of the target based on

changes in the electrochemical parameters of the indicator molecules (redox probes) in the

solution. In contrast to this, the terminal end of DNA used for the labeled aptasensor needs to be

modified with an electroactive molecule as a signal indicator. We first implemented the reported

aptamer into the gold rod electrodes to develop a label-free EIS aptasensor. To the best of our

knowledge, no report on aptasensor specific to AβO directly and conveniently based on EIS

technology has been published so far according to our literature survey. In order to overcome the

un-specific adsorption of EIS aptasensor, also make the sensing platform to be more compatible

with microelectrodes which in contrast to EIS sensors (since they have a very high impedance

due to the small electrode size which impairs sensitivity), an amperometric aptasensor based on

stem-loop aptamer is further advanced by optimizing the detection scheme.

Molecular beacons (MB), as a large class of labeled aptamer sensors, first developed by

Tyagi and Kramer in 1996, are single-stranded oligonucleotide probes that adopt a stem-loop

configuration by intramolecular base pairing with a fluorophore/quencher pair that possesses a

stem-loop structure. MB is mainly used for DNA sequence detection based on changes in

fluorescence intensity [41]. In addition to optical biosensors, MB can also be engineered for

electrochemical detection by replacing their fluorophores with redox groups [42]. The stem-loop

structured DNA probes are superior to linear probes in several aspects for the detection of target

molecules [43].

The greatest advantage regarding stem-loop aptamers is the strong

conformational change induced by the target binding and the reduction of the degree of freedom

of the aptamer, which leads to increased background currents due to unspecific charge transfer.

At present, most electrochemical aptasensors are based on the traditional gold electrode

and the glassy carbon electrode. As the size of the electrode has a considerable impact on the

mass transport of redox-active species to and from the electrode surface and the bulk solution,

the development of microelectrodes is practically meaningful to further push electrochemical

sensing into new space and time domains [44]. Multielectrode arrays are powerful tools in the

electrochemical analysis as they allow access to mass transport rates comparable to

microelectrodes and current levels similar to macroelectrodes [45]. Furthermore, the small

4

dimensions of MEAs offer several additional appealing advantages such as low background

charging, small RC time constants, low ohmic drops, and enables high spatial-resolution, which

has been utilized in investigating environmental sediments, food, and nervous tissues [46-48].

The key issue for the development of aptasensor based on microelectrodes is to increase

the amount of aptamer fixation and maintain target accessibility [49]. In this thesis, a promising

approach is tested to improve the sensitivity of microelectrode aptasensors by enhancing the

number of aptamer receptors by increasing the 3-dimensional (3D) microelectrodes area. Gold is

an excellent electrode material since it has a wide potential window where it is ideally

polarizable and molecules can be easily self-assembled through thiol groups [50-52]. To improve

the sensitivity of the aptasensor, the 3D nanostructured gold was electrodeposited on the

microelectrode (3D-GME) to enlarge the active surface for aptamer immobilization while

maintaining the microelectrode geometric footprint.

This Ph.D. thesis aims to establish electrochemical aptasensors for highly sensitive

detection of AβO. We intend to establish an aptamer-based sensor platform to monitor the AβO

based on multielectrode arrays. Different receptors are assembled on different electrodes of the

same chip to fulfill parallel detection of various targets of AD and early detection of the

neurodegenerative diseases. We expect that the experimental results of the proposed project will

promote future studies of advanced aptamer-based electrochemical sensing devices using novel

aptamer constructs and electrochemical platforms.

Fundamentals and theory

5

Chapter 2 Fundamentals and theory

2.1 Aptamer as receptor

Deoxyribonucleic acid (DNA) is a biological macromolecule with genetic information

that can form genetic instructions to guide biological development and vital functioning [53, 54].

Its constituent unit is deoxynucleotide, including base, pentose, and phosphoric acid. The

nitrogenous bases of nucleic acids can be divided into four categories, namely adenine

(abbreviated as A), thymine (abbreviated as T), cytosine (abbreviated as C), and guanine

(abbreviated as G) [55]. Each pentose molecule is connected to one of the four bases. The

sequences formed by these bases along the long strand of DNA can form a genetic code, which is

the basis for the synthesis of the amino acid sequence of the protein.

In March 1953, Waston and Crick clarified the DNA double helix structure [56], which

opened a new chapter in life sciences and created a new era of science and technology. Most of

the DNA exists in a double-stranded structure (dsDNA) with a double helix structure by non-

covalent bonds. The process of the two chains separated into two separate single-stranded DNA

(ssDNA) is called melting, which occurs at high temperatures, low salt, and high pH value. In

each ssDNA, the pentose and the phosphate molecule are linked by an ester bond to form a long-

chain skeleton. The formed phosphodiester bonds between the third and fifth carbon atoms of

adjacent sugar rings are known as the 3′-end (three prime end), and 5′-end (five prime end)

carbons, shown in Figure 2.1. When the phosphodiester bonds of DNA begins from the third and

ends in fifth carbon atoms of the pentose, the sequence of the DNA is 3′-end to 5′-end, vice versa.

The prime symbol is used to distinguish these carbon atoms from those of the base to which the

deoxyribose forms a glycosidic bond. With the development of biogenetics and information

science, the principle of base pairing has attracted much attention to the development and

preparation of DNA sensors. With the advancement and development of DNA molecular

research, nucleic acid ligands exhibit high affinity and specific binding to selected target

molecules, so the concept of aptasensors also surfaced to acquire information on target molecular

information.

https://en.wikipedia.org/wiki/Phosphodiester_bond

https://en.wikipedia.org/wiki/Atom

https://en.wikipedia.org/wiki/Directionality_(molecular_biology)#3%E2%80%B2-end


https://en.wikipedia.org/wiki/Phosphodiester_bond

https://en.wikipedia.org/wiki/Atom



https://en.wikipedia.org/wiki/Glycosidic_bond

6

Figure 2.1 The chemical structures of DNA molecules [57].

2.1.1 Systematic evolution of ligands by exponential enrichment

These single-stranded oligonucleotides tend to form secondary structures such as hairpins,

pockets, knuckles, and tetramers, and thus can bind to target molecules, such as proteins or other

life molecules to form complexes with strong binding forces [58]. Nucleic acid aptamers are

small segments of the oligonucleotide acid chain obtained by in vitro screening techniques,

namely the systematic evolution of ligands by exponential enrichment (SELEX) [59], bind to the

corresponding ligand-target molecules with high affinity and strong specificity. In SELEX, a

synthetic single-stranded random oligonucleotide library is established, which includes a large

amount of random DNA sequences. After eluting, the unbound oligonucleotide chains are

separated to select an oligonucleotide sequence with a specific binding ability against the target

molecule [60]. A new sub-primary library is generated by transcription of these selected specific

sequences in vitro and then interacted with the target molecules. After several cycles, nucleic

acid aptamers that bind strongly to the target molecule can be selected, as shown in Figure 2.2.


7

Figure 2.2 Flow chart of the SELEX screening technique [58].

2.1.2 Aptamer specificity and advantages

The spatial conformation of single-stranded DNA in solution is uncertain, and specific

interactions are facilitated by the three-dimensional structure of the single strand. When the

target is present, adaptive folding can occur to form a special thermodynamically stable 3D

structure such as stem-loop, pseudoknot, bulge loop, and G-quadruplex, which is tightly bound

to the target molecule by hydrogen bonding, hydrophobic packing, van der Waals force, etc. [61,

62]. Figure 2.3 shows structures of some nucleic acid ligands: Figure 2.3A shows the aptamer

with pseudoknot for HIV-1 reverse transcriptase; Figure 2.3B displays the aptamer with G-

quadruplex for thrombin; Figure 2.3C represents the aptamer with hairpin or stem-loop for

Bacteriophage T4 polymerase; Figure 2.3D shows the aptamer with bulge loop for ATP.

8

Figure 2.3. Some 3D structures of aptamer oligonucleotides for different targets [61].

The binding principle between an aptamer and a target molecule is completely different

from the one between an antibody and an antigen. In general, it is not necessary to know the

internal structure and principle of combination, as long as a specific nucleic acid sequence with a

high binding force can be identified by SELEX technology. Thus, aptamers have become one of

the most promising molecular receptors. Compared with traditional protein antibodies, nucleic

acid aptamers have the following characteristics.

- A wide range of target molecules. The range of possible target molecules is very wide,

including a variety of organic molecules, inorganic molecules, and other life substances, such as

protein, skin segment, even whole cells, bacteria, viruses and so on [63, 64].


9

- High affinity. The aptamer binds to the target molecule forming a stable compound.

The dissociation constant is generally ranging from pM to nM, being even higher than that of

conventional antigen-antibody complexes [65].

- Strong specificity. The nucleic acid aptamers specifically recognize the spatial

structure of the corresponding target molecules. However, it often depends strongly on the

medium that was used during the SELEX process.

- In vitro preparation. Successful screening of aptamer specific to a molecule takes

often a few months; however, once the sequence is known it can be synthesized in large

quantities in the lab by PCR without involving animals [66, 67]. The period of antibody

screening is much longer than that of the nucleic acid aptamer and more expensive.

- Easy modification. Since aptamers are essentially oligomeric nucleotide chains, they

can be easily chemically modified. [68, 69].

- High stability. Aptamers can be storied for a long time and can be used repeatedly,

while traditional antibodies denature easily and are difficult to preserve.

- Controllable binding conditions. As aptamers are screened by SELEX techniques in

vitro, screening conditions can be set according to experimental requirements.

2.2 Electrochemical aptasensor

Electrochemical aptasensor are biosensors that combine electrochemical analysis with biological

DNA technology to quantitatively and selectively detect targets. Compared with traditional

genetic techniques, electrochemical aptasensors have the advantages of fast detection, high

sensitivity and easy operation. Besides, unlike enzymes or antibodies based biosensors,

10

electrochemical aptasensor have very stable DNA recognition layers, which are easy to

immobilize, regenerate, and reuse. These excellent properties make electrochemical aptasensors

widely used in biomarker assay, environmental monitoring, drug screening, forensic

identification and food testing, with invaluable development prospects and application value [70-

73].

2.2.1 Working principle of electrochemical biosensors

Most of the aptamer sensors use solid electrodes as the working electrodes, while single-

stranded DNA immobilized at the electrode surface as a molecular receptor. Figure 2.4 shows the

working schematic diagram of the electrochemical aptasensor. The target is captured at the

electrode surface by the specific recognition between the aptamer and the target. The transducer

converts the concentration input-signal into an electrochemical output-signal such as potential,

current, or impedance, which changes with the target concentration, thereby realizing not only

qualitative but also qualitative analysis of the target.

Figure 2.4 Working schematic diagram of the electrochemical aptasensor.

2.2.2 DNA probe immobilization

It is well known that the effective and stable immobilization of DNA probes on the

electrode surface is a key step in the preparation of electrochemical aptasensors. The


11

immobilization technique of DNA aptamers should not only ensure to immobilize DNA probes

on a specific vector but also to keep their specific binding activity with the target molecules. This

requires also a tuning of the receptor density on the surface which has to be balanced between

high densities to an enable number of binding signals and avoiding strong electrostatic repulsion

impairing optimal folding for target recognition.

Self-assembled monolayers. Highly ordered mono-molecular films can be

spontaneously formed by self-assembly methods on electrode surfaces through chemical bonding

interaction between molecules and molecules [74, 75]. The self-assembly method is widely

employed in the construction of electrochemical aptasensors. It is common to attach the DNA via

an alkane-thiol chain to the gold electrode surface. The thiol group forms a stable bond to the

gold surface. The short alkane chain supports the formation of a dense monolayer via rigid

intermolecular packing. Often, the ssDNA receptors are immobilized together with backfill

molecules such as mercapto-alkanols into mixed monolayers to tune the optimal receptor density

on the surface. In these mixed monolayers, unspecific binding is suppressed and the DNA

strands can stand at an angle on the electrode surface [76]. This keeps the aptamers conformation

flexible with a high degree of freedom, which ensures on the hand the aptamers high binding

efficiency; on the other hand, it can hinder the error caused by non-specific adsorption,

effectively reducing the impact of false-positive signals on the analysis results [77].

Covalent Bonding. DNA molecules can generally be combined with the incompatible

carrier surface by covalent bonds. In covalent bonding approaches, the electrode surface firstly is

modified by reactive groups that can form covalent bonds with the DNA probes, such as

guanamine bonds, ester bonds or ether bonds. Alternatively, the probe DNA can be derivatized

by groups that can couple to bifunctional reagents or a coupling activator that are attached to the

12

carrier surface in a first step without affecting the activity and specific recognition of the probe

molecule [33, 78].

Electrostatic binding. As each nucleotide contains a negatively charged phosphate

group, they can absorb to a positively charged carrier surface by electrostatic interaction. The

advantages of this method are its simplicity, fast adsorption kinetics, and it does not require

chemical cross-linking or chemical modification of the probe. But it can be influenced by some

solution conditions, such as the salt concentration and the pH value. Moreover, because of multi-

site adsorption, the probe DNA lies flat on the substrate surface, resulting in reduced motion

freedom, recognition and hybridization [79]

Avidin-biotin binding. The avidin group is covalently coupled or electrostatically

adsorbed onto the carrier surface, and then the biotin-labeled DNA probes are coated on it. The

immobilization of the DNA probe is achieved by specific binding between biotin and avidin. The

biotin-avidin binding has advantages, such as specificity, rapidity, stability, and mild reaction

conditions.

2.2.3 Classification of aptasensors

As DNA molecules are mostly not electrochemically active and cannot participate in

electrochemical reactions, electrochemically active substances need to be added during

electrochemical analysis. According to the introduction methods of electrochemically active

substances, electrochemical aptasensors can be classified into the following two types: One is the

label-free aptasensor using the small molecular probes in electrolyte as the signaling element; the

other is the labeled aptasensor based on DNA molecules modified with a small redox molecule

as the redox reporter. Please note that the term ―label-free‖ refers to the modification of the


13

receptor only, not of the analyte as it is usually the case during optical DNA. In this work, the

analyte remains always unlabeled.

Aptasensors with label-free receptors

The label-free electrochemical aptasensor refers to an electrochemical sensor that is

developed from nucleic acid probes without attaching any electroactive label to it, and detecting

the target according to the electrochemical signal changes through foreign redox mediators as

voltage, current, capacitance or impedance signal before and after aptamer-target binding [80].

Compared with the labeled electrochemical aptasensor, it has advantages such as simple

operation and fewer preparation steps, but the sensitivity is usually moderate.

Aptasensors with labeled receptors

For labeled aptasensor, the capture DNA molecules are modified by electrochemically

active substances as signal markers. When capture DNA binds with the target molecules, the

electroactive labels are brought to the surface of the electrode or away from the electrode surface.

Therefore, the concentrations of the target can be derived from the changed intensity of the

electrochemical signals [81]. The small molecules currently used for DNA labeling include

active groups such as ferrocene, methylene blue, enzymes or nanoparticles. Due to the

advantages of simple operation, rapid detection, stable nucleic acid recognition layer, and

reproducible reusability, the labeled aptasensor plays an important role in bioanalysis.

2.3 Fundamentals of Electrochemistry

14

2.3.1 Electrochemical interface and processes

Electrochemistry is a discipline that studies the conversion between chemical energies

and electrical energies [82, 83]. Electroanalytical chemistry began in the early 19th century and

has developed rapidly in the past 100 years, which uses the electrochemical properties of the

electroactive substances to determine the composition and content of analyte molecules [84, 85].

This section introduces the basic electrochemical theories involved in this work, such as

electrochemical interfaces and electrode processes, as well as electrical analysis techniques

related to this work, including voltammetry and electrochemical impedance spectroscopy.

As the electrode reactions occur at the electrode/electrolyte interface, the structures and

properties of the electrode/electrolyte interface have a great influence on the electrode reaction.

First, the electric field of the interface caused by the electrochemical double layer between the

electrode and the solution can reach 108 V cm

−1, which can greatly impact the electrode reaction

rate [86, 87]. Secondly, the properties of the electrode material and the composition of the

electrolyte also have a significant effect on the electrode reaction.

At present, the most authoritative double layer model is the Bockris/Devanathan/Müller

(BDM) model; and it is considered that the double layer is composed of several layers. The layer

closest to the surface of the electrode is called the Helmholtz layer, which is formed by a highly

polar solvent such as water. Specifically adsorbed, partially solvated ions are located in the inner

Helmholtz plane (IHP) layer and are considered as being specifically adsorbed. The plane that

fully solvated ions can only reach is called the outer Helmholtz plane (OHP). The interaction of

these ions with the electrode involves only electrostatic forces, also known as non-specifically

adsorbed ions. The non-specifically adsorbed ions are distributed in the diffusion layer due to the


15

action of the electric field and extend to the bulk solution. Figure 2.5 shows the BDM model of

the electric double layer.

The thickness of the electric double layer can be obtained by the Debye-Hückel length.

Typically, the thickness of the electric double layer is approximately equal to 1.5 times the

Debye-Hückel length (k−1

) [88].

𝑘﹣1 = (𝜀r𝜀0𝑘B𝑇/2𝑐0𝑧i2𝑒2)1/2

where c0 is the bulk concentration of the electrolyte, εr is the relative dielectric

permittivity of the solvent, ε0 is the permittivity of the vacuum, kB is the Boltzmann constant, T is

the temperature, z is the ion charge, and e is the elementary charge. When z = 1, the approximate

κ−1

values calculated for electrolyte concentrations of 1 × 10−3

, 1 × 10−5

, and 1 × 10−7

M are 10

nm, 100 nm, and 1 μm, respectively. The thickness of the electric double layer also depends on

the potential. The larger the difference between the electrode potential and the zero charge

potential, the smaller the Debye- Hückel length.

Figure 2.5 the BDM model of the electric double layer [89].

16

In electrochemistry, the electrode reactions occur at the interface. The chemical

conversion and the mass transfer process in the solution layer near the electrode are referred to as

electrode processes. Electrochemical reactions always occur in pairs at the electrode. One is an

oxidation reaction:

𝐑𝐞𝐝 − 𝒏𝒆− 𝐎𝐱 (2.1)

and the other is a reduction reaction:

𝐎𝐱 + 𝒏𝒆− 𝐑𝐞𝐝 (2.2)

where Ox represents an oxidized state, and Red represents a reduced state. Normally, if

electrons at the cathode participate in the reduction reaction, electrons at the anode should flow

out to supply electrons required for the external circuit. Therefore, the amount of reactants or

products involved in the chemical reaction is directly proportional to the number of charge

carriers passing through the electrodes. Assuming that the number of electrons flowing into the

external circuit is 1 mol, NA = 6.02 × 1023

electrons and considering the elementary charge (e) of

each electron is 1.062 × 10−19

C, the total charge flowing into the cathode is NA × e = 96500 C,

which is the Faraday constant, expressed as F, and the unit is C mol−1

.

The Nernst equation shows the relationship between the electrode potential and the

concentration of the corresponding redox substances in the electrolyte. In equilibrium state, for

the redox reaction system:

𝐎𝐱 + 𝒏𝒆﹣ 𝐑𝐞𝐝 (2.3)

the electrode potential E can be calculated by the Equation (2.4) below:

𝑬 = 𝑬𝟎 + 𝑹𝑻

𝒏𝑭∙ 𝒍𝒐𝒈

𝑪𝑶

𝑪𝑹 (2.4)


17

where E0 is the standard potential, R is the universal gas constant, T is temperature, n is

the number of electrons, F is Faraday constant, CO and CR are the bulk concentration of reactive

species. When a current is passed through the electrode, a net reaction occurs, the electrode

potential will deviate from the equilibrium potential. This phenomenon is called electrode

polarization. When the electrode deviates from the equilibrium potential due to the polarization

phenomenon, this deviation value is called overpotential η:

𝜼 = 𝑬𝒆𝒒 − 𝑬 (2.5)

For any electrochemical reaction, to overcome the potential barrier at the

electrode/electrolyte interface, the overpotential needs to be supplied to maintain the electrode

reaction. The relationship between the overpotential and the current I is described by the Butler-

Volmer equation, where j is current density, A is electrode area, j0 is exchange current density,

and α is the charge transfer coefficient.

𝒋 =𝟏

𝒛𝑭𝑨= 𝒋𝟎 ﹣𝒆𝒙𝒑 ﹣

𝜶𝒛𝑭

𝑹𝑻𝜼 + 𝒆𝒙𝒑 ﹣

(𝟏－𝜶)𝒛𝑭

𝑹𝑻𝜼 (2.6)

2.3.2 Voltammetry

Voltammetry is an electrochemical analysis method based on recording of current-

voltage curves. Compared to the potentiometric analysis, voltammetry represents the

measurement of the current at a certain potential; while potential analysis is the measurement of

system potential under zero current condition. Polarography is an early form of voltammetry and

was founded in 1922 by Jaroslav Heyrovsky, who was awarded the Nobel Prize in Chemistry in

1959 for his outstanding contribution to the electrochemical analysis [90, 91]. Since the late

1960s, voltammetry has been greatly developed due to the extensive use of solid electrodes in

life sciences and materials science. This section focuses on the commonly used voltammetry

18

methods, i.e. linear sweep voltammetry, cyclic voltammetry, square wave voltammetry,

differential pulse voltammetry, and alternating current voltammetry.

Linear sweep voltammetry

In this work, linear sweep voltammetry (LSV) was performed to electrodeposit gold on

MEAs for getting the optimal microelectrode surface by applying the decisive parameters of

each method (Section 4.4.1). In LSV, the electrode potential varies at a constant rate from a

lower limit to an upper potential limit while the resulting current is recorded. Because LSV scans

at a fast scan rate, the polarization current increases firstly if a freely diffusing redox molecule is

present in the electrolyte and its redox potential is reached. When the concentration of the

electroactive substance is exhausted and drops, also the current decreases and a current peak

appears. Following, when the polarization voltage continues to increase, the current reaches a

plateau at the ultimate diffusion current [92]. The value from the peak apex to the baseline of the

LSV curve is called the peak current (Ip) and the potential corresponding to the peak apex is

called the peak potential (Ep), Figure 2.6.

Figure 2.6 Linear increase of the potential vs time in LSV [93].


19

In LSV, the response current is affected by the speed of the electrode reaction. For a

reversible electrode reaction, the LSV curve shows a well-defined peak shape as the current is

controlled by the polarization speed and diffusion coefficient of the redox active species [94-96].

The equation of the peak current is:

𝑰𝐏 = 𝟐. 𝟔𝟗 × 𝟏𝟎𝟓 𝒏𝟑/𝟐 𝑫𝟏/𝟐 𝝂𝟏/𝟐 𝑨 𝒄 (2.7)

where Ip is the peak height; n is the number of electrons; A is area (cm2 ); D is the

diffusion coefficient (cm2 sec

−1); v is scan rate (V sec

−1); c is the bulk concentration of the

solution (M). The relationship between the peak potential and the half-wave potential of the

classical polarographic wave is:

𝑬𝐏 = 𝑬𝟏/𝟐 − 𝟏. 𝟏𝑹𝑻

𝒏𝑭= 𝑬𝟏/𝟐－

𝟎.𝟎𝟐𝟖

𝒏 (𝟐𝟓 ) (2.8)

Cyclic voltammetry (CV)

This voltammetry method uses the triangular voltage sweep instead of the sawtooth

waves. At the beginning of the scanning, the applied potential scans in one direction for instance

negatively and the electroactive substances are correspondingly reduced at the electrode. After

the vertex potential is reached, the scan direction reverses and the electroactive substance is

reoxidized (for reversible redox species) at the electrode. As a result, a cycle of reduction-

oxidation processes is completed in a triangular wave form. As shown in Figure 2.7, the upper

half of the CV curve is the cathode reduction wave (Ipc and Epc) and the lower half is the anode

reduction wave (Ipa and Epa). The peak currents can be calculated by the above-mentioned

Equation (2.7). If the electrode reaction is reversible, the upper and lower portions of the curve

20

are substantially symmetrical. According to Equation (2.8), the potential difference between Epc

and Epa should be:

𝚫𝑬𝑷 = 𝑬𝑷𝒂 − 𝑬𝑷𝒄

= 𝟐. 𝟐𝟐 𝑹𝑻

𝒏𝑭=

𝟓𝟔.𝟓

𝒏 𝐦𝐕 (2.9)

And the two peak current should be satisfied:

𝑰𝑷𝒂≈ 𝑰𝑷𝒄

(2.10)

Figure 2.7 (A) The triangular pulse voltage of CV; (B) Voltage as a function of time and current

as a function of voltage for CV [97].

Therefore, CV is a commonly used electrochemical analysis method in a wide range of

applications including the investigation on the properties of electrode reactions, mechanisms,

electrode process kinetics, etc. However, it is generally not used for component analysis, due to

the large charging current and wide peak shape [98-100].

Square wave voltammetry

Square wave voltammetry (SWV) was used to electrodeposit gold on the microelectrode

in this Ph.D. thesis. The potential waveform of SWV can be viewed as a superposition of a

regular square wave onto an underlying staircase with a high scan rate, Figure 2.8A. During

SWV, the charging current (Ic) is expressed by [101]


21

𝑰𝒄 = 𝑲𝒆﹣𝒕

𝑹𝑪 (2.11)

where R is circuit resistance; C is an electric double layer capacitor; t is time. Obviously

Ic is recessed with the exponent of time;

while electrolysis current (Id) is

𝑰𝒅 = 𝑲𝝂𝟏/𝟐 = 𝑲𝒕﹣𝟏

𝟐 (2.12)

which is recessed with the square root of time. Therefore, in SWV, Ic will be

discriminated but Id can be retained by delaying the current measurement to the end of the pulse

[102-104].

The current is sampled twice during each square wave cycle: one at the end of the

forward pulse (Ifor), and another at the end of the reverse pulse (Irev), shown in Figure 2.8B. The

current difference (Inet or ΔI) between the two measurements is plotted vs. the potential staircase.

Square wave voltammetry yields peaks from faradic processes, where the peak height is directly

proportional to the concentration of the species in solution. Since SWV as a pulsed technique can

discriminate the charging current, it has advantages as below:

Speed: In SWV, small voltage pulses are superimposed on the linear voltage ramp, the

pulses with the magnitude of 5−100 mV are applied during the several ms of the cycle pulse. It

allows to make fast measurements and investigate faster reactions.

Sensitivity: SWV eliminates the influence of charging current and increases the

sensitivity of the detection, which is beneficial to the detection of rare or expensive analytes.

Selectivity: Due to the instantaneous change of the square wave voltage, the ions on the

electrode surface react rapidly, resulting in concentration polarization in a short time, making the

22

peak shape of SWV sharper. It can tell differentiate between species with similar potential (as

close as 40 mV peak difference) [105].

However, it also brings some disadvantages. Firstly, it is rare to observe a peak for

irreversible reactions, because of the high scan rate. Secondly, it will produce a high blank noise

because of decreased resistance of the solution by adding high concentrated electrolyte.

Figure 2.8 (A) single potential cycle in square-wave voltammetry; (B) typical square-wave

voltammogram [106]. Ifor is the forward pulse current, and Irev is the reverse pulse current.

Differential pulse voltammetry

Differential pulse voltammetry (DPV) can solve some of the above-mentioned drawbacks

of SWV by extending the time of each pulse to 60 ms, which is much longer than several ms of

SWV [107, 108]. In DPV, the currents are recorded only before each potential changing, as

shown in Figure 2.9. The current difference is then plotted against the applied potential to

eliminate the blank noise. Charging currents are consequently almost fully eliminated. The peak

current of DPV curve is proportional to the concentration of corresponding analytes [109, 110].

The voltage resolution for different peaks is high as well, which allows distinguishing species

with peak potential differences as small as 50 mV [111].


23

Figure 2.9 Excitation signal for the differential pulse voltammetry [112].The red lines are the

current recording before each potential changing.

Alternating current voltammetry

Alternating current voltammetry (ACV) in this work was used to operate the

electrochemical aptasensor with surface confined redox processes, which facilitates low noise

levels and in principle also simultaneous detection of various targets. For ACV, a small

alternating voltage with constant magnitude is superimposed on a conventional DC potential

scan, Figure 2.10A. Only the AC portion of the total current is measured and plotted as a

function of the DC potential. Near the reduction potential of the electroactive material, the

sinusoid has maximum impact on the current, so the ACV response gives a peak-shape wave,

Figure 2.10B. The peak potential is the same as the polarographic half-wave potential. The peak

current can be calculated by Equation (2.13) and is proportional to the concentration of the

electroactive species in the solution. Due to the absence of charging current, the measurement

24

sensitivity can be higher than that of cyclic voltammetry measurements. As ACV requires

electrochemical reactions in both the forward and reverse directions, this method is also

commonly used to measure the kinetic parameters of the electrode reaction and to study the

reaction mechanism [113, 114].

𝑰𝑷 =𝒏𝟐𝑭𝟐𝑨𝝎𝟏/𝟐𝑫𝟏/𝟐𝑪𝚫𝑬

𝟒𝑹𝑻 (2.13)

Figure 2.10 (A) Excitation signal for the alternating current voltammetry; (B) typical ACV curve

[115].

2.3.3 Electrochemical impedance spectroscopy

Electrochemical impedance spectroscopy (EIS) measures the electrical signal of an

electrochemical system, to which a small amplitude AC sinusoidal potential/current wave with

different frequencies (), is applied to analyze the electrochemical properties of the system,

Figure 2.11 [116, 117]. The measured response signal is not a DC current or a potential change

with time, but rather the ratio of the AC potential to the current signal, namely impedance. The

impedance is defined as the ratio of the excitation signal X and the response signal Y, including

the real part, imaginary part, modulus value, and phase angle of the impedance at different


25

frequencies. There are two commonly used EIS plots: one is termed as the Nyquist plot and the

other is the Bode plot, Figure 2.12.

Figure 2.11 Scheme of electrochemical impedance spectroscopy.

In Nyquist plots, the real part of the impedance is plotted as a horizontal axis, while the

negative part of the imaginary part is presented as a vertical axis, Figure 2.12A. Each point in the

curve represents a frequency, which decreases from left side to right side. At each frequency, a

line can be obtained by the connecting signal point to the 0 coordinate. The length of the line is

called the modulus of the impedance and the angle between the lines and X axis is called the

phase angle of the impedance.

26

Figure 2.12 (A) Nyquist plot and (B) Bode plot of the impedance spectrum of an RC circuit. A

diagram of the RC circuit is shown as in inset in the Nyquist plot. The arrows indicate

that the frequency increases toward the origin of the plot. In the Bode plot, Z′ and Z″

versus frequency are plotted [118].

The Bode plot consists of two presentations whose X axises are in both cases the

logarithm of the frequency, while one of the ordinates is the logarithm of the impedance modulus,

and the other is the phase angle of the impedance, Figure 2.12B. Besides the Nyquist and Bode

plots, there are several other ways to present the impedance of the electrochemical system (for

instance showing the admittance instead of impedance), each emphasizing certain aspects of the

studied electrochemical systems.

Kinetic and mass-transfer control EIS

If the charge transfer kinetics is not very fast, the charge transfer process and the

diffusion process will control together the electrode process, and both electrochemical

polarization and concentration polarization will exist simultaneously [119]. In this case, the

equivalent circuit of the electrochemical system can be simply expressed as


27

The impedance caused by the diffusion process is introduced into the circuit by a

Warburg impedance (Zw). The Zw can be thought as the series circuit of a diffusion resistor Rw

and a pseudo diffusion capacitor (Cw).

𝑹𝑾 = 𝛔

𝝎𝟏/𝟐 (2.14)

𝑪𝑾 = 𝟏

𝛔𝝎𝟏/𝟐 (2.15)

Thus, the impedance of Zw is equal to:

𝒁𝑾 = 𝛔𝝎−𝟏/𝟐(𝟏－𝒋) (2.16)

The impedance of the entire circuit is equal to:

𝒁 = 𝑹𝛀 +𝟏

𝒋𝝎𝑪𝐝+𝟏

𝑹𝐜𝐭+𝛔𝝎−𝟏/𝟐(𝟏－𝒋)

(2.17)

The real part of the available impedance:

𝒁𝐑𝐞 = 𝑹𝛀 +𝑹𝐜𝐭+𝛔𝝎−𝟏/𝟐

(𝑪𝐝𝛔𝝎𝟏/𝟐+𝟏)𝟐+𝝎𝟐𝑪𝐝𝟐(𝑹𝐜𝐭+𝛔𝝎−𝟏/𝟐)𝟐

(2.18)

The imaginary part of the available impedance:

𝒁𝐈𝐦 =𝝎𝑪𝐝(𝑹𝐜𝐭+𝛔𝝎−𝟏/𝟐)𝟐+𝛔𝝎−𝟏/𝟐(𝝎𝟏/𝟐𝑪𝐝𝛔+𝟏)

(𝑪𝐝𝛔𝝎𝟏/𝟐+𝟏)𝟐+𝝎𝟐𝑪𝐝𝟐(𝑹𝐜𝐭+𝛔𝝎−𝟏/𝟐)𝟐

(2.19)

When is low enough, the real and imaginary parts are simplified to:

𝒁𝐑𝐞 = 𝑹𝛀 + 𝑹𝐜𝐭 + 𝛔𝝎−𝟏/𝟐 (2.20)

𝒁𝐈𝐦 = 𝛔𝝎−𝟏/𝟐 + 𝟐𝛔𝟐𝑪𝐝 (2.21)

28

After eliminating , the relationship between the real part and the imaginary part is:

𝒁𝐈𝐦 = 𝒁𝐑𝐞 − 𝑹𝛀 − 𝑹𝐜𝐭 + 𝟐𝛔𝟐𝑪𝐝 (2.22)

Accordingly, the diffusion process in the Nyquist plot exhibits a straight line with a tilt

angle of 45 degrees.

When is high enough, the impedance is simplified to:

(𝒁𝐑𝐞－𝑹𝛀－𝑹𝐜𝐭

𝟐)𝟐 + 𝒁𝐈𝐦

𝟐 =(𝑹𝐜𝐭

𝟐)𝟐 (2.23)

Obviously, Equation (2.23) exhibits a semicircle centered at RΩ+Rct/2 with the radius of

Rct/2 in the Nyquist plot.

Figure 2.13 Diagram of Nyquist plot for simple Randles circuit [118].

When the electrode process is jointly controlled by the charge transfer and diffusion

processes, the Nyquist plot is composed of a semicircle in a high frequency region and a 45-

degree straight line in a low frequency region, shown in Figure 2.13. The high frequency region

is controlled by the electrode reaction kinetics (charge transfer process), and the low frequency

region is controlled by the diffusion of the reactants or products of the electrode reaction. From

the EIS curves, the ohmic resistance, the charge transfer resistance, the electric double layer


29

capacitance of the electrode interface, and the parameters related to the diffusion coefficient can

be obtained and analyzed [120, 121]. Therefore, EIS is widely applied to study the electrode

reaction kinetics.

2.4 Non-electrochemical characterization techniques

2.4.1 Scanning electron microscopy

Scanning electron microscopy (SEM) uses a highly focused electron beam which is

scanned linewise over the specimen to generated elastically or inelastically scattered electrons or

x-rays that are used to image the surface of conducting samples. Since the resolution of SEM

beyond the Abbe limit, SEM has been widely used in nanoscience, which has promoted the rapid

development of various related disciplines, including functional materials, biology, medicine,

metallurgy [122-124].

Figure 2.14 (A) useful signals generated by electron-matter interactions in a thin sample; (B)

schematic diagram of the core components of an SEM microscopy [125].

30

The SEM equipment consists of an electron source, condenser lenses, apertures, a

scanning system (deflection coils), an electron collection system (detectors), an imaging screen

(mainly previously), and optionally an X-ray receiving system (component analysis), Figure

2.14B. When a high-energy incident electron hits the surface of the material, multiple signals

such as secondary electrons, Auger electrons, characteristic x-rays, and backscattered electrons

are generated in the excited region (as shown in Figure 2.14A). The signal detector collects these

electrons, correlates their intensity to a certain position and the sample, and converts this

information into an image in sequence. Mostly the secondary electron is used for imaging the

material topography, since they possess the highest surface sensitivity of a sample [126].

Secondary electron is ejected mainly from the valence band due to inelastic scattering processes

with the incident electrons and exited core electrons. Since they originate from valence orbitals,

they possess low kinetic energies and cannot travel far in the material. Therefore only secondary

electrons from the region a few nanometers to several tens of nanometers below the surface of

the sample can leave the material and be sucked up by electromagnetic fields of the secondary

electron detector. Its yield is mainly determined by the morphology and composition of the

sample. The back scattered electrons possess higher chemical contrast since the back scatter

cross-section depends on the atomic number of the element. The information depth is deeper

since they have a much higher kinetic energy.

SEM provides many advantages: (1) a high magnification, continuously adjustable

between 20 and 1000,000 times (system dependent); (2) a large depth of field, a large field of

view, and a three-dimensional image, which can directly observe the fine structure of various

uneven surfaces; (3) simple sample preparation. Disadvantages or requirements: (1) Test under

vacuum increases operating complexity and time; (2) The samples should be conductive surfaces.

For poorly conductive or insulated surfaces, metallization is required.


31

2.4.2 Atomic force microscopy

Atomic force microscope (AFM) is used to study the surface structure and properties of

materials also including insulators by detecting the extremely weak interatomic interaction

between the surface of the sample and a micro force-sensitive element which is usually a

cantilever. Such micro-cantilever is fixed on the one end and has a tiny tip on the other end,

which lightly contacts the surface of the sample either via attractive or repulsive forces. Due to

the extremely weak force between the cantilever tip and the sample, the cantilever will undulate

in a direction perpendicular to the sample surface by controlling the constant force during the

AFM scanning, Figure 2.15. The deflection of the cantilever according to the interaction with the

sample is measured optically via a laser focused on the back of the cantilever and a position

sensitive photodetector. Usually, the AFM is operated either in contact or in tapping mode, using

the static deflection or the oscillation amplitude as feedback information, respectively. The

image of the surface topography is generated by scanning the position of the sample in x and y

direction on a predefined, equidistant 2D grid while moving the sample in z direction such that

the deflection or oscillation amplitude is kept constant. The respective displacement of the

sample in x, y, and z direction is used by the controller unit of the microscope to calculate

images of the 3D surface topography of the sample [127].

Figure 2.15 The Schematic diagram of Atomic Force Microscope [128].

32

AFM characteristics:

1. AFM measures surface topography features (sometimes also called particles) with the

dimensions down to 0.1 nanometers. The system images are more accurately in z direction than

in x and y due to the convolution of sample and tip topography. One further limitation is that the

obtained data are not statistical and local. It is suitable for measuring the surface features such as

individual particles or proteins rather than an overall statistical characterization of samples.

However, imaging the sample on different locations diminishes this shortcoming and enhances

the reliability of the observations.

2. AFM can work in different environments such as vacuum, atmosphere and normal

temperature, and even water and other solutions. Special sample preparation technology is not

required. Since AFM is a method that relies on a mechanical contact between sample and probe,

it can have some invasiveness. Therefore, the forces used to image the sample should be kept as

small as possible and correlate with the sensitivity of the sample. In this work, mainly the less

invasive attractive-tapping mode was used to image the aptamer and peptide modified samples.

2.4.3 UV-Vis spectroscopy

Ultraviolet-visible absorption (UV-Vis) spectroscopy is the absorption spectrum

produced by the transition of electrons when the substance molecules absorb the electromagnetic

waves in the ultraviolet-visible region. Generally speaking, the wavelength range of the UV-Vis

spectrum is mainly from 200 nm to 800 nm [129]. Different molecules have different

characteristic energy levels and level differences due to their different compositions and

structures. Each substance can only absorb the light radiation equivalent to its own internal

energy level difference, leading to the selective absorption of different wavelengths.

The absorption of electromagnetic waves in the ultraviolet-visible region will cause the

valence electrons in the molecule to transfer from a molecular orbital with lower energy to an

empty anti-bond molecular orbital with higher energy. Thus, the absorption bands observed in

the UV-Vis spectrum correspond to the energy difference between electronic energy levels in the

molecule. Normally, the molecular orbitals related to valence electron transitions are: σ, σ*, π, π*,

n, and their energy level possesses the following order: σ<π<n<π*<σ*. In the ground state, the

valence electrons are on a bond or non-bond orbits, while the anti-bond orbits are empty.


33

Therefore, there are four main types of valence electron transitions in the molecule: σ→σ*,

n→σ*, π→π*, n→π*, and the energy required for the transition is ranked as: σ→σ* > n→σ*>

π→π* >n→π*, shown in Figure 2.16.

Figure 2.16 The absorption bands in the UV-Vis spectrum correspond to transitions of the

electronic energy levels.

Beer-Lambert law

The concentration of DNA molecules can be determined by measuring the absorbance at

260 nm with the UV/Vis spectrum according to the Beer-Lambert law. In UV-Vis spectrometer,

the parallel ultraviolet light sequentially passes through to a certain concentration of the sample

solution, and A is respectively measured, and A is used as the ordinate, and the wavelength (nm)

is plotted on the abscissa to obtain the UV-Vis spectrum. The selective absorption of light for

molecules follows the Beer-Lambert law:

A = εcL = −log (I/I0) (2.24)

where A is the absorbance, ε is the molar extinction coefficient, c is the molar

concentration of the solution, L is the thickness of the liquid layer, I is the transmitted light

34

intensity, and I0 is the incident light intensity [130]. When a bundle of parallel monochromatic

light passes vertically through a uniform non-scattering sample solution, its absorbance A is

proportional to the concentration of the sample solution c and the thickness of the liquid layer L.

Materials and methods

35

Chapter 3 Materials and methods

3.1 Reagents

Aβ peptide (Aβ1-40, 4 kDa) was purchased from Peptide Institute Inc. (Japan). Tris

(hydroxymethyl) aminomethane, magnesium chloride, sodium chloride, potassium chloride,

1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), Tris (2-carboxyethyl) phosphine hydrochloride

(TCEP), 6-mercapto-1-hexanol (MCH), potassium ferricyanide (K3[Fe(CN)6]), potassium

ferrocyanide (K4[Fe(CN)6]), sulfuric acid (H2SO4), CaCl2·2H2O, hydrogen tetrachloroaurate

hydrate (HAuCl4·3H2O), LiCl, poly(dimethysiloxane) (PDMS, Sylgard 184) and curing agent

were purchased from Sigma Aldrich. Human serum albumin (HSA) was obtained from Gibco.

Ethanol and isopropanol were purchased from Merck. Artificial cerebrospinal fluid (aCSF) used

in real sample detection was prepared by 150 mM NaCl, 3.0 mM KCl, 1.4 mM CaCl2·2H2O, 1

mM NaH2PO4, and 0.8 mM MgCl2·6H2O.

Analytical grade chemicals and Milli-Q water (18.25 MΩ cm) were used throughout all the

experiments. The Aβ oligomer-specific DNA aptamers were synthesized by FRIZ Biochem

Gesellschaft für Bioanalytik GmbH (Neuried, Germany) according to the published literature,

listed in Table 3.1 [32].

Table 3.1 Oligonucleotide sequences used in this work.

Name Sequence

O1 5‘-OH-(CH2)6-S-S-(CH2)6-GCGTGTGGGGCTTGGGCAGCTGGG-3‘

O2 5‘-OH-(CH2)6-S-S-(CH2)6-CAGGGGTGGGCAAAGGGCGGTGGTG-3‘

O3 5‘-OH--(CH2)6-S-S-(CH2)6-GCCTGTGGTGTTGGGGCGGGTGCG-3‘

ST-4 5‘-Fc-(CH2)6-GCCTGTGGTGTTGGGGCGGGTGCGAGGC-(CH2)6-S-S-(CH2)6-OH-3‘

ST-5 5‘-Fc-(CH2)6-GCCTGTGGTGTTGGGGCGGGTGCGCAGGC-(CH2)6-S-S-(CH2)6-OH-3‘

ST-6 5‘-Fc-(CH2)6-GCCTGTGGTGTTGGGGCGGGTGCGACAGGC-(CH2)6-S-S-(CH2)6-OH-3‘

A-3‘ Fc 5‘-OH-(CH2)6-S-S-(CH2)6-CCAACGCCTGTGGTGTTGGGGCGGGTGCGGTTGG-(CH2)6-Fc-3‘

A-5‘ Fc 5‘-Fc-(CH2)6-CCAACGCCTGTGGTGTTGGGGCGGGTGCGGTTGG-(CH2)6-S-S-(CH2)6-OH-3‘

B-3‘ Fc 5‘-OH-(CH2)6-S-S-(CH2)6-CGCACGCCTGTGGTGTTGGGGCGGGTGCG-(CH2)6-Fc-3‘

B-5‘ Fc 5‘-Fc-(CH2)6-CGCACGCCTGTGGTGTTGGGGCGGGTGCG-(CH2)6-S-S-(CH2)6-OH-3‘

ATP 5‘-Ferrocene-(CH2)6-ACC TGG GGG AGT ATT GCG GAG GAA GGT-(CH2)6-SH-3

36

Note: Pink letters indicate nucleotides that were inserted into the original aptamer sequence to

form a stem-loop either with nucleotides of the original aptamer sequence or with inserted

nucleotides (orange letter) at the opposite end of the DNA.

3.2 Electrode preparation

3.2.1 Gold rod electrode cleaning

The gold electrodes with 2 mm in diameter covered by poly tetra fluoroethylene (PTFE,

shown in Figure 3.1) were cleaned prior to aptamer modification as reported before [131]. Firstly,

the gold electrodes were polished with aqueous slurries of 0.3 and 0.05 mm α-Al2O3 powders on

a microcloth, followed by rinsing with Milli-Q water. Secondly, the electrodes were sonicated in

ethanol, isopropanol and Milli-Q water for 5 min each, then dried in a nitrogen stream to obtain

clean gold electrode surfaces. Finally, they were activated with electrochemical cleaning in 0.5

M NaOH (from −1.5 V to −0.35 V, 500 scans at a scan rate of 2 V s−1

) and 0.5 M H2SO4 (from

−0.35 V to 1.5 V, 100 scans at a scan rate of 1 V s−1

) solution by performing the cyclic

voltammetry (CV). The electrode area can be determined by running a CV cycle in a fresh 0.5 M

H2SO4 solution from 0 V to 1.5 V.

Figure 3.1 Gold rod electrode used in this work.


37

3.2.2 Multielectrode arrays preparation and cleaning

Multielectrode arrays (MEAs) were produced in an ISO 1-3 cleanroom on a borosilicate

wafer with a thickness of 500 µm and a diameter of 100 mm, shown in Figure 3.2. Firstly, the

wafer was spin-coated by a double resist system LOR 3b (Microchem, Newton, MA) and

nLOF2070 (MicroChemicals, Ulm, Germany). The feedlines and the 64 microelectrodes pattern

were defined via standard photolithography and followed by electron-beam deposition of 10 nm

Ti and 200 nm Au, respectively (Pfeiffer PLS 570, Pfeiffer Vacuum, Asslar, Germany). Then, a

lift-off step was performed in solvent by sonication to remove the photoresist layers. In order to

insulate the feedlines, a passivation layer polyimide (PI) was spin-coated onto the wafer. The

electrodes and contact pads can then be directly opened by photolithography with a mask

determining their size. Finally, the wafer was diced into individual 24 × 24 mm2 chips (9

chips/wafer) for further use. For cleaning, new MEAs chips were firstly placed in chip holder

and sonicated in acetone and isopropanol, and Milli-Q water for 5 min, respectively. Then a glass

ring with a height of 5 mm and a diameter of 20 mm was adhered to the center of the cleaning

chip as a reservoir by a mixture of PDMS and curing agent, shown in Figure 3.3. An oxygen

plasma oven (Diener Electronic, Germany) was used for MEAs chip cleaning at an O2 pressure

of 0.5 mbar, 50% power, with a duration of 3 min.

Figure 3.2 Fabrication process of multielectrode arrays: (a−b) spin-coating of photoresists; (c)

photolithography patterning of gold electrodes; (d) electron-beam deposition Ti and Au;

38

(d−e) lift-off process by sonication; (f) spin-coating of polyimide for insulating the

feedlines; (g) active the electrodes and contact pads by photolithography.

Figure 3.3 (A) Borosilicate / gold MEAs with glass ring as electrochemical reservoir cell; (B)

central part of the chip with gold feedlines and 64 microelectrodes.

3.3 Fabrication of the aptasensor

3.3.1 DNA concentration measurements

Before immobilization, the DNA probe was received as lyophilized powders and stored

at −20 C. The stock solution of DNA probes was obtained by dissolving the centrifugal

lyophilized powders in Tris-HCl buffer for 1h, then stored in the fridge at 4 C. The

concentration of DNA molecules was determined by measuring the absorbance at 260 nm with

the UV/Vis spectrometer Lambda 900 (Perkin Elmer, USA), shown in Figure 3.4. According to

the Beer-Lambert law: A=εcL=−log (I/I0), the concentration of DNA molecules was calculated,

where A is the absorbance, ε is the molar extinction coefficient, c is the molar concentration of

the solution, L is the thickness of the liquid layer, I is the transmitted light intensity, and I0 is the

incident light intensity. The ε of DNA probes can be obtained from the following website


39

https://eu.idtdna.com/calc/analyzer. As can be seen from Figure 3.4, the absorbance A of O3

DNA stock solution can directly read from software to 0.32, and ε is εO3 is 220200 L mol−1

cm−1

.

Therefore, the c of this O3 DNA stock solution is 658 µM.

Figure 3.4 UV/Vis spectrometer of the measured DNA stock solution from 220 nm to 400 nm.

3.3.2 Immobilization of aptamer

The DNA modification solution was activated by 10 mM TCEP for 1 h to cleave

disulfide bonds, then diluted with high-salt Tris-HCl buffer (10 mM Tris, 1.5 M NaCl, 1 mM

MgCl2, pH 7.4) to different concentrations. After that, a freshly cleaned gold rod electrode was

immersed in 400 µL solution containing the thiolated aptamer probe at room temperature

overnight. After rinsing with 3 mL Tris-HCl buffer and Milli-Q water, separately, the aptamer-

modified electrode was immersed in 1.0 mM MCH for 60 min to prepare a compact SAM. For

aptasensor based on MEAs, 500 µL thiolated stem-loop ssDNA probe solution and MCH

solution were inserted into the MEAs reservoir, sequentially. Finally, the aptamer modified

electrode was rinsed by 6 mL Tris-HCl buffer and Milli-Q water to remove any excess probe

DNA physically adsorbed on the electrode surface.

https://eu.idtdna.com/calc/analyzer

40

3.4 Preparation of amyloid-β peptides

Aβ oligomers were prepared as described by Tsukakoshi et al [36]. Briefly, the lyophilized

Aβ peptide (Aβ1-40) was treated with HFIP for 20 min on ice, then Milli-Q water was added.

After that, the obtained solution was centrifuged at 14,000 g for 15 min, and the supernatant was

subjected to Ar-gas bubbling (through sterile filter; 30 min) to remove HFIP. Then the solution

was incubated for 24 h with stirring at 800 rpm and centrifuged at 14,000 g for 20 min. Finally,

the obtained supernatant was concentrated by using a molecular weight cutoff filter (10 kD, from

Merck Millipore) to get the concentrated AβO solution. The concentration of prepared AβO was

measured by UV/Vis spectrophotometer at 280 nm.

3.5 Electrochemical measurements

All measurements were performed at room temperature using a three-electrode cell,

including the working electrode, the counter electrode, and the reference electrode. The

introduction of the counter electrode to the working electrode and the reference electrode ensures

that the potential of the working electrode is completely controlled by the applied voltage while

the reference electrode potential remains constant. As shown in Figure 3.5, the polarographic

current flows through the circuit composed by the working electrode and the counter electrode;

the reference electrode and the working electrode form a potential monitoring loop, with no

significant current flow because the operational amplifier has high impedance. In the three-

electrode electrochemical system, the AuR with 2 mm diameter or MEAs were used as working

electrodes, a platinum wire worked as a counter electrode, and a saturated Ag/AgCl electrode

acted as a reference electrode, shown in Figure 3.6. All potentials in this manuscript are denoted

with respect to a standard Ag/AgCl electrode.


41

Figure 3.5 A simple block diagram of a potentiostat and a transimpedance amplifier [132].

Figure 3.6 Three-electrode cells used in AuR (A) and MEAs (B) electrochemical system.

3.5.1 Cyclic voltammetry

Cyclic voltammetry (CV) was performed using an Autolab PGSTAT302 (Eco Chemie,

Netherlands) with NOVA software, shown in Figure 3.7. CV measurements were conducted

42

between 0 V and 0.6 V with a scan rate of 100 mV s−1

in Tris-HCl buffer (10 mM Tris, 150 mM

NaCl, 5 mM KCl, pH 7.4). CV curves for electrode characterization were performed by cycling

between −0.2 V and +0.6 V with a scan rate of 0.1 V s−1 in Tris-HCl buffer containing 0.05 mol

L−1

[Fe(CN)6]3−/4−

, 5 mmol L−1

KCl, and 150 mmol L−1

NaCl for 30 min. CV for electrochemical

cleaning was carried out in 0.5 M NaOH (voltage sweeps from −1.5 V to −0.35 V, 500 scans at a

scan rate of 4 V s−1

) and 0.5 M H2SO4 (voltage sweeps from −0.35 V to 1.5 V, 100 scans at a

scan rate of 1 V s−1

) by cyclic voltammetry to obtain a clean gold electrode surface. The

electrode area was determined by running a CV cycle in a fresh 0.05 M H2SO4 solution from 0 V

to 1. 5 V at a scan rate of 0.1 V s−1

[133].

Figure 3.7 Autolab setup used for electrochemical measurements.

3.5.2 Electrochemical impedance spectroscopy

Electrochemical impedance spectroscopy (EIS) measurements were performed with a

standard three-electrode cell controlled by an Autolab PGSTAT302 (Eco Chemie, Netherlands).


43

EIS measurements were recorded in a frequency range between 1 Hz and 10 kHz at 0.22 V with

a sinusoidal voltage and an amplitude of 10 mV. A Randles equivalent circuit was used to fit the

obtained impedance spectra and to extract the values of the circuit component.

3.5.3 Alternating current voltammetry

ACV measurements were performed using an Autolab PGSTAT302 (Eco Chemie,

Netherlands) with NOVA software in Tris-HCl buffer (10 mM Tris, 150 mM NaCl, 5 mM KCl,

pH 7.4). ACV scans ran between 0 V and 0.5 V with potential steps of 0.005 V, modulation

amplitude 0.025 V, modulation time 0.4 s and interval time 0.8 s.

3.5.4 Chronocoulometry for receptor density

Chronocoulometry (CC) was carried out to determine the surface densities of immobilized

aptamer on electrodes utilizing a CHI1030B electrochemical workstation (Austin, USA), shown

in Figure 3.8. The following parameters were used for the chronocoulometric measurement to

obtain Qdl (charge of electrochemical double layer): initial potential: 0.2 V; final potential: 0.5 V;

number of steps: 2; pulse width: 0.25 s; sample interval: 0.002; sensitivity (C or A/V): 5e–5 A/V.

Figure 3.8 CHI workstation with multi-channel used in electrochemical measurements.

3.6 Electrodeposition of gold nanostructures (3D-GMEs)

44

The electrodeposition of Au was performed on the microelectrodes in an aqueous

solution of 10 mM HAuCl4. A conventional three-electrode cell together with an electrochemical

workstation CHI1030B (Austin, USA) were employed for the electrodeposition. Ag/AgCl and Pt

plate were used as the reference and counter electrodes, respectively. Various electrochemical

technologies were tested to deposition gold on MEA surface, including chronoamperometry (CA,

constant potential including 0.5, 0.55, 0.6, 0.65V, deposition time varied from 240 s to 420s),

linear sweep voltammetry (LSV, potential window 0.6 V to 0.1 V, total time from 1.5 to 10 min)

and square wave voltammetry (SWV, potential window 0.6V to 0.0V, sweep rate 0.001V/s, total

time 10 min).

3.7 Morphological characterization

3.7.1 AFM for Aβ peptides aggregation process

AFM imaging was performed using a Nanoscope Multimode 8 microscope (Bruker)

equipped with a piezoelectric scanner (E-series with a scan range of 13 μm × 13 µm) and

aluminum back coated Si cantilevers from Bruker (OTESPA-R3) with typical values of k ∼ 26

N/m, f0 ∼ 300 kHz, and tip radius of (nom) ∼ 7 nm. Aβ monomers were dissolved in Milli-Q

water to 100 µM and incubated under magnetic stirring in a water bath maintained at 37 . Aβ

peptides were taken out from incubation solution after certain time intervals (0 h, 24 h, 72 h, and

120 h) and deposited on a bare silicon disk surface. After 3 min of deposition, the excess liquid

was taken off and the disk was rinsed with 3 mL of Milli-Q water and gently dried under a

nitrogen flow. All AFM measurements were made in tapping mode, under ambient conditions at

different scan sizes ranging from 5 µm to 200 nm. The images reported in this thesis all had with

the following imaging parameters: scan rate 1 Hz, scan size 1 µm, a resonant frequency range of

AFM cantilever 115 kHz – 300 kHz, and a number of pixels 512 × 512. For the preparation of

AFM samples: After 3 min of deposition, the excess liquid of Aβ proteins was shaken off and the

disk was rinsed with 3 mL of Milli-Q water and gently dried under a nitrogen flow.

3.7.2 AFM for characterizing aptasensor preparation

AFM imaging was performed using the same setup as mentioned in Section 3.7.1 at

different scan sizes ranging from 2 µm to 200 nm. The data shown here had the following


45

imaging parameters: scan rate 1 Hz, scan size of 0.5 µm, a resonant frequency range of AFM

cantilever 115 kHz – 300 kHz, and number of pixels 512 × 512. A bare gold (111) single crystal

disk was used as model electrode surface. The activation and cleaning of the single crystal were

done by thoroughly rinsing it in ethanol, isopropanol, and Milli-Q water. After drying, the crystal

was annealed for 10 min in a hydrogen flame and cooled down to room temperature in an argon

stream. The subsequent aptamer modification and target detection were done as described in

Section 3.3.

3.7.3 Scanning electron microscopy of 3D-GMEs

The morphology of the electrodeposited gold films was examined using scanning

electron microscopy (SEM) by means of a LEO 1550 VP (Zeiss, Germany) with SE2 detector by

applying 20 kV acceleration voltage. Prior to the measurements, the samples were sputtered with

iridium by an Emitec K575x Sputter Coater at 15 mA current for 45 s to prevent charging effects.

3.8 Regeneration of microelectrodes on 3D-GMEAs

Electrochemical cleaning: The 3D-GMEAs regeneration was done by cleaning CV scan

curves in 0.1 M NaOH (−1.5 V to −0.3 V, 10 scans) and 0.05 M H2SO4 (−0.3 V to 1.5 V, 20

scans) at 1 V s−1

.

O2 plasma treatment: O2 plasma cleaning at 0.5 mbar with 50% power for 3 minutes was

also be performed to remove the sulfhydryl groups on the used electrodes. After O2 plasma

cleaning, soaking in ethanol for 20 minutes is necessary to reduce the gold oxide layer.

Results and discussion

47

Chapter 4 Results and discussion

In this chapter, electrochemical aptasensors based on specific binding between the

aptamers and their targets are constructed and the obtained results are discussed in detail. In the

first section, the feasibility of the selected aptamer on the gold rod electrode for specific

detection of AβO is demonstrated by electrochemical characterization together with AFM

morphological characterizations. In the second section, a label-free sensor based on impedance

signal changes is developed for the monitoring aggregation of Aβ proteins. The third section

discusses an amperometric aptasensor for amyloid-beta oligomer detection by optimized stem-

loop structures with adjustable detection range. Finally, we transfer the sensing platform to

MEAs that can be used for dual-target detection of AβO and ATP.

4.1 Characterization of aptasensor preparation

Although the reported AβO ssDNA aptamers selected by Tsukakoshi et al. have been

successfully used in biological assays for AβO detection by fluorescence or

electrochemiluminescence signals, no report on aptasensor specific to AβO directly and

conveniently based on electrode has been published according to our literature survey. Therefore,

in this part, the feasibility to attach the selected aptamer on the electrode and to characterize the

electrochemical and morphological response to AβO binding were studied.

4.1.1 Electrochemical characterization of the aptasensor fabrication process

CV and EIS measurements were performed to characterize to verify the assembly and

binding process of the receptor film on the electrode. Compared with bare gold electrode,

aptamer modified gold rod electrodes (aptamer-AuR) showed larger charge transfer resistance

(Rct) because the negatively charged phosphate backbone of the ssDNA aptamer O3 repels

negatively charged [Fe(CN)6]3−/4−

probe from approaching the gold surface, Figure 4.1A. After

blocking the electrode surface with MCH, Rct further increased due to backfilling of unmodified

electrode areas. Finally, 10 nM of target AβO was added to the as-prepared label-free aptasensor

48

resulting in an obvious Rct increase because of steric blocking and the electrostatic repulsion of

the redox probes from the negatively charged AβO at pH 7.4 [134].

Figure 4.1 CVs (A) and EIS (B) recorded in 5.0 mM [Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150

mM NaCl + 5 mM KCl at bare AuR, aptamer-AuR, MCH-aptamer-AuR, and adding 10

nM AβO. Solid lines are fitting results with the model in the EIS.

In addition, CV measurements were carried out to confirm the EIS results. The cyclic

voltammogram are strongly affected by steric and electrostatic interactions of the redox ions with

the molecules attached to the surface hampering the charge transfer. As shown in Figure 4.1B,

bare AuR gave a well-defined pair of redox peaks with peak potential difference (∆Ep) of 99 mV

and peak current (Ip) of 50.3 µA. After immobilization of aptamer DNA, the Ip decreased to

47.5 µA while the ∆Ep increased to 134 mV, confirming the attachment of charge transfer

inhibiting molecules to the gold electrode. The blocking of unmodified electrode areas with

MCH caused a further decrease of Ip (41.3 µA) and an increase of ∆Ep (218 mV), due to the

increasing repelling properties of the formed self-assembled monolayer. Also, the incubation

with AβO and the resulting formation of aptamer-AβO complexes at the modified electrode

surface leads to a decrease of the peak currents, which coincides with the EIS results.

4.1.2 Aptamer surface density

The surface density of immobilized aptamer was determined by chronocoulometric

measurements as previously reported [135]. Firstly, MCH/aptamer-modified gold electrodes


49

were placed in 3 mL electrolyte and purged thoroughly with nitrogen for 10 min. The following

parameters were used for the chronocoulometric measurement to obtain Qdl (charge of

electrochemical double layer): initial potential: 0.2 V; final potential: 0.5 V; number of steps: 2;

pulse width: 0.25 s; sample interval: 0.002; sensitivity (C or A/V): 5e–5 A/V. Then 15 µL 10

mM RuHex solution was added to the Tris-HCl buffer, purged thoroughly with nitrogen for 10

min, and chronocoulometric measurements were performed again to get Qtotal (charge after

RuHex addition) of the MCH/aptamer-modified gold electrode. The surface density of DNA was

obtained by calculating the charge corresponding to [Ru(NH3)6]3+

electrostatically bound to

surface-confined ssDNA, Figure 4.2. Qss (charge from ssDNA) was obtained as Qtotal − Qdl. The

aptamer modified surface density was calculated by (QssNA/nFA)(z/m), where n is the number of

electrons in the reaction. A is the area of the working electrode, m is the number of nucleotides in

the DNA, z is the charge of the redox molecules and NA is Avogadro‘s number, and F is Faraday

constant. The surface density of aptamer molecules was determined by chronocoulometric

measurements to be 2.8 × 1012

molecules cm−2

for these optimized experimental conditions (0.01

µM ssDNA and 40 min AβO incubation time)

Figure 4.2 Chronocoulometric curves for gold electrodes modified with single-stranded DNA

probes before (black) and after RuHex addition.

50

4.1.3 Morphological characterization of the aptasensor fabrication process

Atomic force microscopy (AFM) is used to investigate the step by step modification of

the sensor electrode and the binding of AβO to the aptamer modified surface. A bare gold (111)

single crystal disk is analyzed by AFM as a reference surface to provide a surface smooth enough

to allow an unambiguous mapping of morphological changes during surface modification. Figure

4.3 shows three rows of images with the top view topography in the first row, a cross-section

corresponding to the respective white lines in the second row, and a 3D image in the bottom row

to visualize the stepwise increase of the surface roughness.

Figure 4.3 Tapping mode AFM images of gold surface before (A) and after aptamer (B), MCH

(C), and AβO (D) surface immobilization. Cross-section analysis (E−H) and 3D AFM

height images (I−L) corresponding to A−D, respectively.


51

The AFM images of the bare Au electrode exhibit atomically flat Au terraces with

monoatomic steps (step height approx. 2Å) on the left side (Figure 4.3A, E, and I) [136]. The

corresponding cross-section shows a flat line with sub-Å corrugations originating mainly from

the noise of the AFM system indicating a clean and adsorbate free surface. After aptamer

immobilization (Figure 4.3B, F, and J), several 3D topographical features can be observed.

Firstly, one can still see monoatomic steps and also holes. The latter can be assigned to defects in

the topmost gold layer generated during aptamer immobilization, which is commonly found for

thiol-based SAMs [137-139]. The diameters of these holes were 10 nm to 20 nm and up to 7

individual aptamer features per hole were counted, in Figure 4.4. Secondly, corrugations are

present on the terrace as well as surrounding the monoatomic holes, which possess feature

heights of around 1 nm and can presumably be assigned to unordered aptamer molecules. Since

the concentration of the aptamer solution was small and no blocking MCH was applied until this

preparation step, it can be assumed that the immobilized ssDNA lie down on the surface, which

is supported by the small feature height (smaller than aptamer length). After blocking the

remaining free Au areas with MCH, the monoatomic defects disappeared. The surface exhibits a

large number of homogeneously distributed hillocks (Figure 4.3C and G) with heights of 1.5 nm

± 0.5 nm (see particle analysis, Table 4.1), suggesting that the aptamer receptors form small

domains of generally upstanding ssDNA surrounded by short chain MCH molecules. Apparently,

a phase separation takes place between polyanionic aptamers and MCH with hydrophobic alkyl

chains. At last, the surface morphology of the Au crystal was studied after its incubation in AβO

medium. The AFM analysis revealed a significant increase in the height of the hillocks

confirming the formation of aptamer/AβO complexes with heights of 3.1 nm ± 0.9 nm. The

surface roughness of the Au crystal continuously increased during the modification sequence

from bare gold, via aptamer and MCH adsorption to the AβO binding from 0.08 nm, 0.33 nm,

0.51 nm to 0.94 nm, respectively. These results are also manifested in the corresponding 3D

AFM height images (Figure 4.3I-L) and the following particle analysis.

52

Figure 4.4 Tapping mode AFM images of the aptamer immobilization on gold surface. The

white arrows indicate Au holes with aptamers decorating the step edges of Au.

Particle analysis of AFM

The size and distributions of molecules bound to the surface during the different

modification steps were investigated by AFM particle sizes analysis, Figure 4.5. For bare crystal

gold surface, no particles could be observed and the grain height was 0 nm, Figure 4.5A. After

aptamer modification, particles were found mainly associated to monoatomic holes in the gold

surface, which had a mean height of 1.0 nm ± 0.4 nm. After MCH blocking, the grain height

increased furtherly to 1.5 nm ± 0.5 nm. Finally, the addition of AβO to the sensor surface caused

an increase of the particle height to 3.1 nm ± 0.9 nm. The particle analysis confirms the observed

increase of the surface roughness associated with the respective surface modifications performed

for the AβO detection assay.


53

Figure 4.5 The particle height distribution of gold surface before (A) and after aptamer (B)

binding, MCH (C) immobilization, and AβO (D) detection. Particles that are used for the

analysis are marked blue. Particles touching the image frames were excluded from the

analysis.

Table 4.1 Particle heights of AFM particle analysis for gold surface before and after aptamer

binding, MCH immobilization, and AβO detection.

Sample Mean (nm) Minimum (nm) Maximum (nm) Sigma (nm)

Bare gold 0.0 0.0 0.0 0.0

Aptamer-gold 1.1 0.3 2.3 0.4

MCH-aptamer-gold 1.5 0.6 3.4 0.5

After AβO binding 3.1 1.4 6.5 0.9

54

4.1.4 Comparison of different aptamers

In the work of Tsukakoshi et al, nine aptamers have been selected using a competitive

screening method, and all aptamers showed chemiluminescent signals from well-immobilized

enzyme-linked oligonucleotide assays, indicating binding of these aptamers to AβO [1]. Among

the nine aptamers, three aptamers with high affinity to AβO (named O1, O2, and O3) were

chosen for the development of electrochemical aptasensors. O3 owns the strongest binding

ability to AβO. The sequences of the label-free thiol-aptamers are as the following:

O1: 5‘-OH-(CH2)6-S-S-(CH2)6-GCGTGTGGGGCTTGGGCAGCTGGG-3‘

O2: 5‘-OH-(CH2)6-S-S-(CH2)6-CAGGGGTGGGCAAAGGGCGGTGGTG-3‘

O3: 5‘-OH--(CH2)6-S-S-(CH2)6-GCCTGTGGTGTTGGGGCGGGTGCG-3‘

To study the electrochemical sensing properties of the three aptamers, 0.01 µM O1, O2,

or O3 were added to the clean gold rod electrodes, then the uncovered areas were blocked by

MCH. The respective aptasensors were used to detect 1 nM AβO in Tris-HCl buffer by EIS. A

comparison of the impedance increase ratio (∆Rct/Rct0) of those three aptasensors gave a similar

signal increase after binding to 1 nM AβO (Figure 4.6). Although these aptamers exhibit

different binding abilities in enzyme-linked oligonucleotide analysis, after modifying them at the

gold electrode surface they showed a similar performance, presumably due to the importance of

steric hindrance during aptamers/targets binding, which becomes a critical factor after tethering

the aptamer receptors to the electrode surface.

Figure 4.6 EIS curves obtained for O1 (A), O2 (B), and O3 (C) immobilized to the gold rod

electrode from a 0.01 µM aptamer solution recorded in 1 nM AβO containing 5.0 mM

[Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl.


55

4.2 Monitoring amyloid-β proteins aggregation based on label-free

aptasensor

In this section, the development of an electrochemical label-free aptasensor is described

for the AβO detection based on electrochemical impedance spectroscopy (EIS). As can be seen

above, EIS is a powerful, non-invasive and semi-quantitative technique to investigate the

electrochemical interfacial properties of bio-electrochemical systems [140]. Because of the high

sensitivity and stability of the aptamer receptor, the EIS aptasensor was used to monitor the

presence and also the aggregation process of amyloid-β proteins in the analyte.

4.2.1 Scheme of the impedimetric biosensor

The working principle of the label-free aptasensor is based on a change of the electrode

impedance caused by the binding of AβO to the surface tethered aptamer receptors, as illustrated

in Figure 4.7. The thiolated DNA probes are bound to the AuR by forming a SAM via the Au–S

bonds. However, since DNA strands can also absorb onto gold surfaces through coordinating

interactions between the electron-rich nitrogen atoms and the electron-deficient gold surface [40],

linear alkyl thiol molecule MCH was used as backfill to orient the immobilized DNA molecules

to support efficient probe-target interactions by displacing non-specifically absorbed DNA

probes and to block the direct charge transfer with solution phase redox molecules

([Fe(CN)6]3−/4−

) at DNA-free electrode surface areas. The concentration of target AβO was

determined based on the change of the charge transfer resistance (Rct) caused by AβO-aptamer

binding via impedance spectroscopy. The results of the EIS measurements were presented as

Nyquist plots and fitted based on Randles equivalent circuit models, which includes Rct, the

electrolyte resistance (R), a constant phase element presenting the double layer capacitance

(CPE), and the Warburg impedance (Zw) [30].

56

Figure 4.7 Mechanism for label-free aptasensor based on the electrochemical impedance method.

4.2.2 Aptasensor performance

EIS was used to detect the Rct signal change caused by AβO binding to the aptamer receptor.

In order to quantify the analyte concentration, the value of impedance increase ratio (∆Rct/Rct0)

was calculated from the change of the impedance after and before the incubation (∆Rct) with

target molecule AβO. The performance of the sensor strongly depends on the receptor layer

immobilized to the transducer surface. The density of aptamer receptors within the SAM is

strongly influenced by the concentration of aptamer during incubation.

Figure 4.8A shows the effect of the aptamer concentration during electrode modification on

the value of ∆Rct/Rct0 in the concentration range from 0.001 µM to 0.05 µM. ∆ Rct/Rct0 increased

significantly with increasing aptamer concentration to 0.01 µM. A further increase in the

incubation concentration leads to a decrease of the sensor signal. The reason for lower signals of

high aptamer densities is a steric hindrance between neighboring aptamer molecules. Large

target molecules or aggregated peptides such as AβO require more space than the corresponding

aptamer receptor occupies on the electrode surface to form the receptor/analyte complex [141].

Thus, the optimal aptamer concentration of 0.01 µM was used in the following experiments.

However, the sensor performance also depends on the binding kinetics of the target

molecule and thus on the incubation time of 1.0 nM AβO, Figure 4.8B. For incubation times

from 10 min to 40 min, the sensor signal ∆Rct/Rct0 increased gradually and leveled off after 40


57

min, which indicates the saturation of the sensor surface. Consequently, 40 min was used as an

optimized incubation time to obtain the best possible sensor sensitivity and assay efficiency.

The pH value of supporting electrolyte solution is another key factor affecting the

electrochemical performance of aptasensor [142, 143]. The influence of the pH value of the Tris-

HCl solution was investigated (Figure 4.8C) in the range from pH 6.0 to 9.0 when the aptasensor

was immersed in the 10 mM Tris-HCl buffer solution containing 10 nM AβO. It was found that

the ∆Rct/Rct0 signal increased with increasing pH value from 6.0 to 7.4 and decreased for higher

values. The reason might be that strongly acidic or alkaline solutions may impair the stability and

activity of the immobilized biomolecules, and thus influence the performance of the aptasensor.

Therefore, a pH value of 7.4 was employed throughout the subsequent experiments.

To test the performance of the electrochemical aptasensor for the label-free determination of

AβO, the calibration curve was determined in Tris-HCl buffer solution by EIS. Therefore, the

impedance spectra of the MCH/aptamer modified-AuR electrode were recorded before and after

the administration of different concentrations of AβO. The EIS data are presented as Nyquist

plots, Figure 4.9A. Along with the increase of the AβO amount, Rct increased gradually, implying

that more aptamer-AβO complex formed at the electrode surface hindering the [Fe(CN)6]3−/4−

to

access to the electrode. ∆Rct/Rct0 increased linearly with increasing concentration of AβO within

a broad concentration range from 0.1 nM to 500 nM [∆Rct/Rct0 (%) = 22.8 + 0.20 CAβO (nM)]

with a correlation coefficient of 0.99, Figure 4.9B. The detection limit of this method was

estimated to be 0.03 nM with 3, where is the relative standard deviation (RSD) parallel

measurements of the blank solution.

Figure 4.8 Effects of concentration of aptamer (A), incubation time of AβO (B) and pH value

(C).

https://www.sciencedirect.com/science/article/pii/S0956566315302232#s0090

58

Figure 4.9 (A) EIS curves obtained at MCH-aptamer-AuR upon different concentrations of Aβ

into 5.0 mM [Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl, solid lines

are fitting results with the model; (B) The calibration curve for AβO from 1 nM to 500

nM.

To investigate the selectivity of the assay method, the aptasensor was incubated with

different Aβ species including AβM, AβO, and AβF, Figure 4.10A. In contrast to AβO, the AβM

did not cause an apparent change of the sensor signal and AβF caused only a minor response

because there are still some residuals of smaller Aβ fragments in the analyte solution from the

AβF formation. Obviously, the existence of AβM and AβF exerted a minor impact on the assay

of AβO attributed to the high specific recognition of the selected aptamer against AβO [36, 37].

These results indicate that the developed sensor with selectivity binds Aβ oligomers and could be

potentially employed in real samples of body fluids.

The precision and accuracy of the method were determined by intra- and inter-day assay

variance. Intra-day variation was calculated from the analysis of six replicates of each sample on

the same day, whereas inter-day variability was determined from the analysis of three tests for

each sample on 3 different days. As shown in Table 4.2, the RSD values of intra and inter-day

assays are within 15%, indicating satisfying intra and inter-day stability, which confirm that the

method is sufficiently stable for detection of AβO.


59

Table 4.2 Intra- and inter-assay precision data.

Actual concentration Measured concentration (nM); RSD (%)

nM Intra-day (n = 6) Inter-day (n = 3)

1.0 0.93; 2.1 1.02; 1.5

10 10.3; 3.4 8.4; 4.7

100 108; 3.2 85.1; 6.7

Furthermore, the storage stability of the sensor was tested for an AβO concentration of 1

nM, Figure 4.10B. After the aptasensor was stored in Tris-HCl buffer solution at 4 for one

week, the signal increase percentage caused by AβO binding retained 94% of the original value;

even after 14 days, the sensor retained 85% of original sensitivity. These results confirm that the

proposed aptasensor has a high stability, which can be attributed to the stability of aptamer

oligonucleotide in ambient temperature compared to antibodies.

One of the advantages of aptamers over antibodies is the improved chemical stability to

make sensor regeneration possible, because the aptamer is chemisorbed on the electrode surface

through a gold-thiol bond. A highly concentrated urea solution was used as a regeneration

reagent to dissociate the aptamer-target linkage without influence the affinity of surface-bound

aptamer [52]. After immersing in 6 M urea solution, the redox response could be regenerated to

91% of its initial value, Figure 4.10C and D. After 3 cycles of surface regeneration, the detection

errors are less than 10%, suggesting our aptasensor is reusable for the detection of AβO.

To demonstrate the versatility of this method, the developed aptasensor was used to

determine the concentration of AβO in artificial CSF. The results were analyzed by standard

addition method, and the mean recovery (n=3) during the experiments for spiked samples were

utilized to calculate the RSD of the assay, as listed in Table 4.3. We observed a recovery of

107%, 105%, and 93%, indicating that our aptasensor represents a suitable platform for the

detection of AβO in real samples such as body fluids of AD patients.

60

Figure 4.10 (A) Selectivity towards 1 nM Aβ monomers (AβM), Aβ fibrils (AβF), AβO; (B)

Long-term stability of the aptasensor at 4 degrees for 7 days and 14 days; Reuse of

aptasensor toward 100 nM AβO regenerated by rinsing with 6 M urea (C and D).

Table 4.3 Results of the detection of AβO in artificial CSF by standard addition method.

Sample No. Added (nM) Found (nM) Recovery RSD (n=3)

1 1 1.07 ± 0.03 107 % 3.2 %

2 10 10.5 ± 0.49 105 % 4.9 %

3 100 92.7 ± 3.7 93 % 3.7 %


61

4.2.3 Monitoring Aβ proteins aggregation

Cleavages of amyloid precursor protein by serial secretase give rise to various forms of Aβ

proteins. The aggregation of these Aβ proteins is a common step in the pathogenesis of

Alzheimer‘s disease. Monitoring the aggregation of Aβ proteins is an important tool to evaluate

the performance of drugs to inhibit the Aβ fibrosis. Therefore, clarifying the aggregation

behavior from monomers into fibrils is not only helpful for understanding the disease

progression but also for the AD drug development.

Based on the high selectivity of the presented aptasensor, we monitored the aggregation

process of amyloid-β proteins. Aβ monomers were dissolved in Milli-Q water and incubated

under magnetic stirring in a water bath maintained at 37 for different times (0 h, 24 h, 72 h,

and 120 h) and subsequently exposed to the label-free aptasensor, Figure 4.11. After 24 h of Aβ

monomers incubation, the aptasensor showed a much higher ∆Rct/Rct0 signal compared to the

starting signal of AβM at 0 h, indicating the formation of AβO. When the Aβ monomers were

incubated for 72 h, the aptasensor gave a smaller impedance change than for 24 h, since a

proportion of AβO continuously aggregated to AβF, which is not bound by the aptamer receptor.

With increasing incubation times (120 h), the aptasensors tended to show even lower responses

due to the progression of AβO aggregation to AβF, finally becoming AβP.

Figure 4.11 Monitoring Aβ proteins aggregation process by developed aptasensor.

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AFM measurements were carried out to verify the aggregation progress of Aβ proteins,

Figure 4.12A−D. After 24 h incubation (Figure 4.12B and E), the Aβ peptides bundled together

and formed nanoparticles, with a height of 1.0 nm to 5.7 nm presumably representing Aβ

monomers and oligomers composed of different numbers of monomers. Note, the height

provides more reliable information about the size of globular objects than the diameter since it is

not superimposed by the tip radius. Incubating the Aβ solution for 72 h (Figure 4.12C and G) led

to the formation of fiber-like Aβ (AβF) aggregates with a height of 3.8 nm to 8.3 nm. An

increase of the incubation time to 120 h (Figure 4.12D and H) resulted in a further aggregation of

Aβ proteins forming crossing fibers and finally AβP, with structures as high as 12 nm. These

AFM results are consistent with the responses observed from the sensor assay, indicating that

ssDNA aptasensors can be used to monitor the progression of Aβ aggregation, which could be

useful for testing the impact of potential AD drugs on aggregation of these amyloid molecules

Figure 4.12 AFM images of bare silicon chip (A) and Aβ peptides incubated for 24 h (B), 72

h(C), and 120 h (D); The corresponding height cross-section along the line (E−H).

4.3 Amperometric aptasensor for AβO detection


63

In Section 4.2, an impedimetric label-free aptasensor utilizing an AβO specific aptamer

was proposed and used to monitor the Aβ peptide aggregation; however, the limit of detection is

still in the range of several tens of picomol due to the impedimetric transducer principle, such as

low sensitivity or un-specific adsorption of interfering species to backfill molecule due to

hydrophobic interaction. Furthermore, a downscaling of the electrode size to sub 100µm is

hardly feasible by impedimetric sensors since the interfacial impedance is very high due to the

small electrode diameter. To facilitate the use of microelectrode transducer and to further

improve the sensitivity of the aptasensor, this part of the work reports on a novel molecular

beacon-based electrochemical aptamer-based (E-AB) sensor for amperometric detection of AβO.

To my knowledge, this is the first work related to the immobilization process and stem-loop

structures optimization of aptamer specific to AβO. Amperometric detection schemes rely on

charge transfer between the electrode and redox probes that are either attached to the receptor

and/or diffuse in the solution phase [144].

In this section, alternating current voltammetry (ACV) was used to operate the sensor

with surface-confined redox processes, which facilitates low noise levels and in principle also

simultaneous detection of various targets. The surface tethered stem-loop probes are dually

labeled with a thiol group at the proximal end for surface coupling and a redox group ferrocene

(Fc) at the distal end for signal reporting. To optimize the aptasensor sensitivity for AβO,

variations of the stem-loop aptamers‘ structures including stem number, ssDNA length, location

of redox probe at 3‘ or 5‘ terminal end, and spacer length are tested. Furthermore, aptamer

immobilization concentration and the ACV detection parameters are studied. The obtained

aptamer film was found to exhibit not only a high sensitivity, selectivity and reproducibility for

64

AβO binding but also an adaptable range of detection and detection limits down to the sub

picomolar range by appropriate selection of ACV signal recording conditions.

4.3.1 Scheme of the amperometric aptasensor based on stem-loop

To construct an amperometric Fc-based aptamer biosensor for AβO, a surface-

immobilized stem-loop ssDNA strands was employed as recognition elements and ferrocene as

redox signal label. The structures of DNA oligonucleotides used in this work are shown in Figure

4.14. The stem-loop receptor, dually labeled with thiol and ferrocene, has been designed such

that it has two five-base sequences at the terminal ends of the aptamer-probe, so that the DNA

strand will be closed and form a double-stranded stem structure by thermostable paring. The

concept of AβO detection based on a stem-loop aptamer is shown in Figure 4.13. After cleaning

the gold electrode surface, the stem-loop probe is assembled at the electrode interface to form the

SAMs through a strong DNA-thiol bonding. Then the remaining uncovered areas of the electrode

are blocked again by MCH decreasing unspecific adsorption, similar to the impedimetric sensor,

see Section 4.2. Directly after the formation of the mixed monolayer, the immobilized stem-loop

probe exists in its ―closed‖ state in the absence of target AβO, at which the ferrocene is localized

close to the electrode surface facilitating an efficient electron transfer and consequently enabling

the measurement of high redox currents. After administration of the target AβO, it binds to the

ssDNA and breaks the stem, which causes a transformation of the DNA into the ―open‖

conformation. This increases the distance between ferrocene and the electrode surface, which

diminishes the charge transfer current. Since the electron transfer depends exponentially on the

distance between donor and acceptor, even small changes in the aptamer conformation can be

efficiently probed by the amperometric detection scheme.


65

Figure 4.13 Mechanism for aptasensor detection based on a stem-loop aptamer.

Figure 4.14 Oligonucleotide sequences used in this work. Red and yellow lines indicate

nucleotides that were inserted into the original aptamer sequence to form a stem-loop; the

blue curves are the original aptamer sequences.

66

4.3.2 Comparison of the aptamer stem-loop structures

In this part of the work, the development of an aptasensor containing a stem-loop was

intended that shows signal off characteristics, means that the redox current drops after target

binding. In order to find the optimal stem-loop configuration with the highest signal response,

the stem length, spacer length, and position of the ferrocene terminus were altered. The relative

suppression (SS) of the ferrocene faraday current (I−I0)/I0 (%) was determined as the sensor

signal.

Effect of the Stem Length

The stem length is a key parameter that determines the response of a ssDNA-Fc strand to

its target. If the stem is too long or short, the hairpin-like conformation doesn‘t open or opens too

easily, affecting the response signal of ferrocene upon target administration. Hence the stem

length of the stem-loop must be properly chosen in order to obtain an optimal balance: strong

enough to form the hairpin structure but also weak enough to be dissociated when target AβO

binds to the aptamer. Each base pair contributes to the stem-loop by a binding energy ΔG of

approximately 5 kJ/mol [145]. The binding energy to the target needs to exceed the energy sum

of all base pairs. To obtain the optimal stem length, three DNA stem-loop probes were designed

that contain different stem lengths between 4 and 6 base pairs (ST-4, ST-5, and ST-6, shown in

Table 3.1 and Figure 4.14) and tested the sensing performance of the corresponding aptasensors.

Their responses to the same concentration of AβO targets (10 pM) are shown in Figure 4.15A−C.

Electrodes modified with ST 4 show unstable and random ACV peak currents. The black lines

represent responses of the aptasensor in Tris-HCl buffer without AβO (blank). The current

response was unstable and increased with the number of scans, indicating transient stem-loop

formation. After adding 10 pM AβO, the current decreased a little but subsequently increased

again (red lines). These results demonstrate that a stem length of 4 base pairs is too short for the

ssDNA sequences to form a sturdy and stable stem-loop structure. For the blank ST-5 probe, the

current response became reproducible for repeated ACV scans. After adding 10 pM AβO, the ST-

5 aptasensor showed (34.8 ± 2.0) % SS, while the aptasensor containing ST-6 exhibited only (20

± 3.6) % SS. The signal difference between ST-5 and ST-6 suggests that the stem formation

strongly competes with the target binding, if six stem base pairs are used. Consequently, the stem

structure is conserved, even if the target is present for many of the surface tethered aptamer


67

receptors and the distance between Fc and electrode surface does not change sufficiently. Among

different aptamers with different stem length, the ST-5 showed the best detection performance

towards AβO. Therefore, we chose the ssDNA sequence containing a stem-loop with 5 base pairs

(ST-5) for the subsequent tests.

In the following, two additional design motifs are introduced for the oligonucleotide

aptamers namely additional based pairs that are forming the stem and the location of the redox

probe, as well as the thiol linker, are inverted. At first, additional stem forming bases were added

either on both sides of the aptamer strand or alternatively, on only one end leading to ssDNA

molecules with 34 (named Probe A) and 29 bases (named Probe B), respectively. Probe B forms

the stem between additional and own bases while Probe A uses exclusively additional bases for

the stem on both terminal ends. The second design motif concerns the location of the thiol linker

and the redox probe. DNA with thiol at the 5‘ end and ferrocene at the 3‘ end are named 3‘ Fc.

Conversely, the DNA with 3‘ end thiol and 5‘ end ferrocene are termed as 5‘ Fc.

68

Figure 4.15 ACV curves recorded towards 10 pM AβO in 10 mM Tris-HCl + 150 mM NaCl + 5

mM KCl at ST-4 (A), ST-5 (B), and ST-6 (C) aptasensor; (D) The SS of the different

oligonucleotide-length aptamer sensors A-3‘Fc, A-5‘Fc, B-3‘Fc, and B-5‘Fc responding

to 10 pM AβO. The effect of location of thiol and ferrocene (B and E) and spacer (B and

F) on AβO response.


69

Effect of the oligonucleotide length.

Comparing the SS of the different aptamer receptors responding to 10 pM AβO, aptamer

A always gave a lower signal decrease than aptamer B, independent whether the redox probe was

located at the 3‘ or 5‘ terminal end, Figure 4.15D. This might be caused by two main reasons:

firstly, aptamer B is shorter than aptamer A, tending to form more compact and stable SAMs.

Singh et al. have found that single-stranded DNA with short chains (less than 10 bases) or long

chains (more than 30 bases) does not produce appropriate films because of the self-protection

mechanism observed during DNA surface film formation [146]. This means that long chains will

intertwine with neighboring strands rather than interacting with the electrode material, inhibiting

the film growth. Second: the long sequence of aptamer A makes the formation of stem-loop

structures less favorable due to entropic reasons [147]. Therefore, short-length aptamer B

oligonucleotides including 29 bases were chosen for the further design optimization of the stem-

loop DNA probe for AβO sensing.

Location of thiol and ferrocene at 3’ or 5’

The position of the thiol binding and Fc redox group also affects the aptamer sensing

performance for the same DNA oligonucleotide sequence and length. A comparison of current

response of ST-5 (5‘ Fc, Figure 4.15B), B-3‘Fc modified electrodes (Figure 4.15E) exhibits a

higher SS of 39 ± 1.2 % in comparison to 34.8 ± 2.0 % for B-5‘Fc, which can be attributed to

two differences in the stem-loop structure. On the one hand, narrow and well-defined peaks are

obtained for 3‘-terminal Fc aptamers, while aptamers with redox probes attached to the 5‘-

terminal end showed broad peak shapes. This is because the 3‘ Fc group reaches the electrode

surface easily and proceed to reversible heterogeneous electron transfer [148, 149]. The total

amount of 3‘ terminal Fc group can be correlated quantitatively to the height of the anodic or the

cathodic peak corrected from the background current.

On the other hand, also the attachment of the two aptamer receptors on the electrode is

different due to the opposite position of the thiol binding moiety. 3‘ thiol groups can access to

gold surface better than those attached to the 5‘-terminal end, facilitating higher surface density

of aptamer receptors [150, 151]. The estimation of the aptamer density by chronocoulometry

confirms this assumption, Figure 4.16. The density of B-3‘Fc aptamers deposited from 1.0 µM

70

solutions is with 2.75 *1012

molecules cm-2

nearly 50 % smaller than those of B-5‘ Fc aptamers

deposited from a solution of the same concentration. This low value for B-3‘Fc aptamers

indicates that the chains are sparsely grafted on the electrode surface as non-interpenetrating

polymer coils [152, 153]. The aptamers form parallel G-quadruplex structures after target

binding, which is relatively bulky and requires much space for AβO recognition. It should be

noted that optimal stem-loop ssDNA probe density is 2.4 − 5.0 times lower than that of linear

ssDNA probes on the same surfaces [49, 154], indicating that the stem-loop requires more space

to unfold upon target immobilization. Hence, 3‘-terminal redox and 5‘-terminal thiol labeling

provides apparently the highest SS and is the most appropriate single-stranded oligonucleotide

receptor for the detection of AβO.

Figure 4.16 The surface aptamer density of B-3‘Fc (A) and B-5‘Fc (B) modified electrode was

quantified using chronocoulometric technique.

Effect of spacer

Another possible aspect that contributes to the large SS (39 ± 1.2 %) of B-3‘ Fc in

comparison to B-5‘ Fc (31.9 ± 1.9 %) modified receptors is that the added bases are located at

the terminal bound to the surface, which could act as a spacer for B-3‘ Fc. In order to study the

effect of a spacer group on the sensor performance, we compared the response of AuR electrodes

modified with B-5‘ Fc and ST-5 modified (Fc also on 5‘ terminal end) towards administration of

10 pM AβO. Figure 4.15B and F show that ST-5 modified AuRs exhibit a bigger signal decrease

of about 34.8 ± 2.0 % than that of B-5‘ Fc of 31.9 ± 1.9 %. Moreover, the ST-5 modified sensors


71

(Figure 4.15B) exhibited a stable peak potential before and after AβO binding compared to B-5‘

Fc modified sensors (Figure 4.15F). It has been reported that aptamers, where the unit

undergoing the conformational change is located close to the electrode surface, may not be able

to fold into the three-dimensional structure necessary for target recognition due to steric

hindrance [155]. Therefore, the incorporation of a spacer can render a molecular probe attached

to a solid support more accessible to its target, which has been proven to be an effective strategy

to increase the sensitivities of ssDNA based sensors [156, 157]. In summary, considering the

effects of stem length, oligonucleotide length, thiol and Fc terminal position, and spacer,

oligonucleotide B-3‘Fc exhibits the highest signal and is chosen as the optimal receptor in the

next experiments.

4.3.3 Optimizations of aptamer concentration and frequency

Since the breaking of the stem affects the dynamics of the DNA associated redox probe

signaling, the sensor performance sensitively depends on the receptor immobilization condition,

which can affect the blank (background) and the target responses, see above. In this assay, the

density of Fc probes has a strong impact on the performance of the sensor since the difference

between background and target response is used as a quantitative measure. The receptor surface

density depends on the receptor and ion concentration of the immobilization solution due to

electrostatic repulsion between negatively charged ssDNA molecules. As can be seen from

Figure 4.17A, from 0.1 μM to 1.0 μM, the aptasensor response increase then decreased after 1.0

μM. This is because very high receptor densities can lead to steric hindrance during target

binding and high background signals, while sensors with very low receptor densities may suffer

from system noises corresponding to the detection limit.

Figure 4.17B shows the dependence of SS on incubation time between aptamer and AβO

from 10 min to 50 min. The response started at 10 min, and then gradually increased for the first

30 min, then reached a plateau after 30 min, suggesting that the association reaction between

aptamer and AβO almost saturated at 30 min. Thus, 30 min was selected as the adequate

incubation time for the aptamer probe to interact with AβO. Interestingly, the binding kinetics is

similar for both impedimetric and amperometric transducer. It can be therefore concluded that

the attachment of a redox probe doesn‘t affect the analyte binding kinetics.

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Figure 4.17 Effects of concentration (A) of aptamer and incubation time of aptamer-target (B)

on AβO response in 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl.

Next, the effect of the applied AC frequency on the signal gain was investigated. For

amperometric sensors that employ a surface-immobilized reversible redox label, the redox signal

depends inherently on the applied frequency in ACV measurements (Figure 4.18) [158, 159]. For

B-3‘ Fc receptors (Figure 4.18E), the redox current from Fc group increased between 1 Hz and

10 Hz and dropped from 10 Hz to 40 Hz in the absence of AβO (blank). A similar trend was

observed for sensors in the target-bound state (10 pM and 0.1 nM AβO). The peak current should

be proportional to the AC frequency when the frequency is sufficiently lower than the electron-

transfer rate. However, as the applied frequency reaches a threshold value where electron

transfer can no longer keep up with the oscillating potential, the peak current diminishes relative

to the background current [160, 161]. Since the % SS is determined using both the pre- and post-

binding currents, it also depends on the applied frequency. The distance between redox group

and electrode is larger for the target bound state of the aptamer in comparison to the stem-loop,

which results in a drop of the current at lower frequencies for the former. The relative difference

between target bound and stem-loop currents is largest for 20 Hz, which can be considered as the

optimal AC frequency providing the best sensitivity of the target detection. However, the high

sensitivity comes on the costs of a smaller detection range, since the currents drop to zero

already at relatively low analyte concentrations of 10 nM AβO or higher. Therefore, we chose 20

Hz for the detection of low amounts of AβO, and 10 Hz to achieve a wide dynamic range of

detection.


73

Figure 4.18 Effects of ACV frequency on AβO detection response from 5 Hz to 40 Hz：A−D:

ACV responses of aptasensor towards different concentrations of AβO; E: aptasenor

responses to blank, 10 pM, and 0.1 nM AβO at different frequency; F: aptasenor

responses towards 10 pM AβO at different frequency.

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4.3.4 Performance of aptasensor for AβO

To demonstrate the versatility of the optimized oligonucleotide probe, we used AuR

electrodes modified with B-3‘ Fc oligonucleotide probe to detect AβO via disrupting the stem-

loop structure. The sensitivity of the electrochemical aptasensor for the target assay was

determined by varying the AβO concentrations. The sensor showed a semi-logarithmic

concentration-dependence in the range from 1.0 pM to 1500 nM, saturating at 1500 nM, when a

frequency of 10 Hz was applied (Figure 4.19A). The calibration equation was SS (%) = 8.5%

lgC + 0.58 with a correlation coefficient of 0.991 (Figure 4.19B). The signal at the detection

limit was 6.5*10-6

nM defined as 3 times the standard deviation and the blank signal. Similarly,

at an applied frequency of 20 Hz, the SS possessed also a semi-logarithmic dependence on the

AβO concentration from 0.1 pM to 10 nM. The calibration curve was determined to be SS (%) =

13.4% lgC + 0.358 with a correlation coefficients of 0.999. The signal at the detection limit for

AβO was calculated to be 0.002 pM.

To evaluate the selectivity of the ssDNA molecular beacon against AβO, control

experiments were performed using 10 pM AβM and AβF as interfering targets. As shown in

Figure 4.20A, a significant SS of about 40% was observed induced by the interaction of the

aptamer probe with AβO, while the signal caused by the other Aβ peptides was significantly

lower. Nevertheless, there was also an approximately 10% SS caused by the presence of AβM

and AβF for our aptasensor, maybe owing to residual AβO generated during the preparation of

AβM and AβF samples. However, this result indicates that AβO binds to its aptamer with higher

affinity than other Aβ forms and the molecular oligonucleotide redox beacon shows a high

selectivity toward AβO.


75

Figure 4.19 (A) ACV curves obtained at B-3‘ Fc modified AuR upon different concentrations of

AβO applied 10 Hz, (B) The calibration curve for AβO from 1 pM to 1500 nM. (C) ACV

curves obtained at B-3‘ Fc modified AuR upon different concentrations of AβO from

applied 20 Hz, (D) The calibration curve for AβO from 0.1 pM to 10 nM.

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Figure 4.20 (A) Selectivity of the developed aptasensor towards 10 pM AβM, AβO and AβF in

10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl; (B) Stability of the aptasensor signal

towards 1 pM AβO stored in a fridge of 4 degree for 7 days and 14 days.

The long-term stability and reproducibility of the sensing interface are important factors

for the development and practical implementation of an aptasensor. The stability of the

electrochemical aptasensor was tested over a period of two weeks (Figure 4.20B). After each

measurement, the aptamer sensor was stored in a Tris-HCl buffer solution at 4 °C. It was

observed that the aptasensor could still retain within 80% of its initial response, indicating that

the developed aptasensors attain a sufficient stability for AβO detection. The relative standard

deviation (R.S.D.) of reproducibility at one modified electrode was calculated to be 1.2% for 3

successive determinations of 10 pM AβO. For 3 different aptasensors, the R.S.D was 3.0%.

AβO levels in cerebrospinal fluid is related to AD pathology, therefore the detection

assay of AβO in real samples could become a powerful tool for clinical diagnosis of AD. To

demonstrate the versatility of this aptasensor, AβO detection was tested in aCSF, as illustrated in

Table 4.4. Our data showed an acceptable conformance of 89% to 107% with data obtained for

the calibration curves, indicating good accuracy and validity of the developed assay for AβO

detection in aCSF samples.


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Table 4.4 Results of the detection of AβO in artificial CSF by standard addition method.

Sample No. Added (nM) Found (nM) Recovery RSD (n=3)

1 0.1 0.12 ± 0.003 119 % 3.1 %

2 1.0 1.08 ± 0.07 108 % 6.8 %

3 1000 1157 ± 37 116 % 3.7 %

4.4 Electrochemical dual-aptamer biosensor based on 3D-GMEs

Multielectrode arrays (MEAs) have been used not only as electrophysiological but also as

biochemical sensors as they facilitate high mass-transfer rates and spatial resolution. However,

they possess a limited versatility for aptamer sensor applications because of its low sensitivity

caused by the small electrode size. The downscaling of the electrode size from mm to µm

diameters leads to a significant reduction of the number of receptors that can be attached to the

sensor surface. Nevertheless, in this part of the work, the strand B-3‘ Fc, selected in the previous

section, was utilized for the detection of AβO on a 64 channel MEA instead of a gold rod

macroelectrode. To overcome the low number of ssDNA receptors tethered to the MEAs, 3D

nanostructures were electrodeposited on these electrodes (3D-GME). This enhances the active

surface for aptamer immobilization while maintaining the microelectrode geometric footprint.

Electrodeposition methods, deposition potential, and time were systematically altered and the

active surface areas as well as the morphologies of 3D-GMEs were investigated by cyclic

voltammetry (CV) scans in sulfuric acid and scanning electron microscopy (SEM). After

cleaning 3D-GMEAs, the MEAs were incubated in a certain concentration of stem-loop aptamer

solution overnight. Subsequently, the MEAs were rinsed by Tris-HCl buffer and Milli-Q water 3

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times to remove those DNA molecules that were non-specifically absorbed on the electrode

surface, separately. As for the other aptasensors, also the microelectrode chip was incubated 0.1

mM MCH solution for 1 h as backfill and subsequently rinsed 6 times by Tris-HCl buffer and

Milli-Q water.

When the target was absent, the aptamer molecules were in closed state, where the Fc is

in vicinity to the electrode surface, facilitating an electron transfer and enabling a high blank

current signal. When the target AβO was present and bind to the aptamer molecules, the stem-

loops were broken and disconnected the Fc-tagged DNA terminus, impairing the electrons

transfer and causing an off-current signal. The electrochemical properties and analytical

performance of electrochemical aptasensors based on 3D-GMEs were studied by CV,

electrochemical impedance spectroscopy (EIS), and ACV.

Based on the merits of MEAs, a multi-channel and multi-target detection was realized on

this sensing platform. Figure 4.21 shows the scheme of a dual-detection of AO and ATP on the

same 3D-GMEAs chip. Electrochemical measurements can be performed simultaneously at the

64 microelectrodes on the same MEAs chip. AD is often associated with mitochondrial

dysfunction, which is closely related to the level of adenosine triphosphate (ATP). Therefore,

simultaneous detection of AβO and ATP on the same MEAs chip has a significance for the early

detection of AD and pathological study of other neurodegenerative diseases. In our case, ATP

was applied as a second model biomarker to identify the feasibility of the novel 3D-GMEAs

sensing platform for dual-target measurements. The 3D-GMEAs were regenerated by

electrochemical cleaning in order to facilitate the attachment of multi-aptamer receptors onto

different electrodes. After regeneration of parts of the used microelectrodes, the aptamer against

ATP was applied to the regenerated microelectrodes. When the ATP binds to its linear, stem-


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loop free aptamer, a signal increase occurred caused by a conformational change which bends

aptamer with its redox group ferrocene closer to the electrode surface.

Figure 4.21 Scheme of dual-detection of AβO and ATP by corresponding aptamers tethered on

different microelectrode of the same MEA chip.

4.4.1 Optimize deposition conditions

In this work, we intend to achieve a large 3D electroactive surface area for

immobilization of sufficient aptamer receptors but keeping the small 2D size, which is beneficial

for a high spatial resolution of MEAs. In addition, for immobilization of multiple aptamers, a

stable 3D surface is required to allow a stripping of bound molecules and a regeneration of the

microelectrode surfaces. Several electrochemical methods including linear sweep voltammetry

(LSV), square wave voltammetry (SWV) and chronoamperometry (CA) were utilized to

electrodeposit gold on MEAs for getting the optimal microelectrode surface by varying the

decisive parameters of each method.

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Figure 4.22 (A) CV curves of microelectrodes with gold electrodeposited by LSV for different

deposition times from 1.0 min to 10 min in 0.05 M H2SO4 sweeping from 0 V to 1.35 V

at 0.1 V s−1

. (B) The integrated areas of the reduction peaks at 0.9 V (Ag/AgCl). (C) CV

curves for electroactive surfaces of different microelectrodes on the same MEAs chip

with deposition time of 5 min.

Firstly, the performances are discussed of MEAs with nanogold electrodeposited by

voltammetry methods including LSV and SWV. Because the scan rate is a key factor for these

electrodeposition methods, scan rate or deposition time were varied to optimize the

electrochemical active surface area. In LSV, the electrode potential was swept at different rates

between 0.001 V s−1

(1 min) and 0.0001 V s−1

(10 min) throughout the scan from a lower (0 V)

to a higher potential (0.6 V). In order to compare the electrochemical performance of gold

electrodes with different deposition conditions, CVs were recorded in sulfuric acid to determine

their active surface areas [133]. In Figure 4.22A, voltammograms are shown of different

microelectrodes with nanogold electrodeposited by LSV at different scan rates in 0.05 M H2SO4.

These CV curves showed typical features for a clean good surface including multiple

overlapping oxidation peaks at around 1.3 V and a single sharp reduction peak at around 0.9 V

[162, 163]. By comparison of the reduction peak areas after electrodeposited for 1.0 min to 10

min, the peak areas increased continually. This increase was caused by the longer deposition


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time, since more gold ions are reduced at the electrode surface. According to the integrated areas

of the reduction peaks, the electrochemical active surfaces were calculated, Figure 4.22B. The

electroactive surface area scales linearly with the deposition time and is largest after 10 min

deposition [164, 165]. However, it is noteworthy that the relative standard deviation (RSD) of

the electrode active area increased when the deposition time exceeded 5 minutes (scan rate was

less than 0.0002 V s−1

). Taking the deposition time of 5 min as an example (Figure 4.22C), the

same deposition condition resulted in greatly different active areas for different microelectrodes.

To elucidate the origin of these variation, an SEM morphology analysis was performed, Figure

4.23.

It can be seen that when the deposition rate was 0.001 V s−1

and the deposition time was

1.0 min, the deposited gold surface was smooth and covered only the surface of the

microelectrode. The black dots in the figures were caused by gold particles peeled off the

electrodes (enlarged figure, Figure 4.23B). Then, when the deposition rate decreased to 0.004 V

s−1

and the deposition time increased to 2.5 min, the nanogold coverage increase everywhere on

the microelectrode, indicated by a higher surface roughness. However, already at this scan rate,

an enhanced electrodeposition at the microelectrode edges became apparent, which lead to a

local increase of the surface rougher. Leaf-like gold structures began to appear around the

periphery of the microelectrode. When the deposition time lasted longer than 5 min, the

deposited gold crystal grew along the crystal plane and as time goes on, additional small leaf

crystal grew around these large leaves [166, 167]. The enhanced electrodeposition is a

consequence of the hemispherical diffusion profile at microelectrodes, which leads to a fast

transport at the electrode edge and a slow parallel diffusion at the center of the microelectrode.

However, these leaf-like structures are very fragile and had poor mechanical properties, Figure

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4.23D. Parts of the electrodeposited nanogold broke off. This stochastic process contributes to

the observed large deviation of the determined electroactive surface area, Figure 4.22B, which

can strongly affect the results of the electrochemical experiments and the 3D-GMEA

reproducibility.


83

Figure 4.23 SEM images of the gold electrodeposited microelectrodes generated at different

deposition time by LSV (A to F) and SWV (G and H); B is magnified view of A.

Also, SWV was used to electrodeposit gold on the microelectrodes. In square wave

voltammetry, the potential waveform can be considered as a superposition of a regular square

84

wave onto an underlying staircase. In order to optimize the deposition conditions, we chose 2.5

min and 10 min as representative deposition times. The influence of deposition time on the gold

morphology was similar for SWV and LSV, Figure 4.23G and H. When the deposition time was

2.5 min, the nanogold covered the microelectrode uniformly and horizontally, Figure 4.23G. As

the deposition time was extended to 10 min, the edges of the electrodes grew to large and loose

leaf-like shoot buds, which easily broke off from the microelectrode base. The bad mechanical

properties impair the reusability of the microelectrode.

Since in voltammetry, voltage sweeps are performed from higher to lower potentials and

vice versa, it is difficult to extract the effect of voltage on the electrodeposited gold surface.

Therefore, chronoamperometry (CA) was used for this purpose in our experiments. CA is an

electrochemical technique that applies a defined potential step and the resulting current from

faradaic processes occurring at the electrode is monitored as a function of time. The deposition

potential and deposition time are the key factors affecting electrodeposition. Firstly, the

deposition potentials from 0.7 V to 0.5 V were used to electrodeposited gold in a 10 mM AuHCl4

solution for 7 min. SEM was used to observe the morphology of the deposited gold at each

potential, in Figure 4.24. At a voltage of 0.65 V, the nucleation was fast and the crystal growth

rate was slow due to the low overpotential [168, 169]. Small gold particle structures decorated

the entire microelectrode surface evenly, so the deposited gold showed a smooth surface

morphology. When the deposition potential decreased to 0.6 V, the particle size became larger

than that at 0.65 V since the overpotential increased. After lowering the deposition potential to

0.55 V, the morphology of deposited gold surface changed significantly to a cauliflower-like

structure. A possible reason is the high overpotential, which leads to an increase of the charge

transfer rate at the electrode and a limitation of the electrodeposition by the mass transport

towards the electrode. Again, the diffusion rate of ions at the edge of the micro-disk electrode is


85

much higher than at the center. The crystal growth is exacerbated on a small number of crystal

nuclei at the edges, causing crystals to grow along the periphery and leaving the center empty

[169-171]. When the deposition potential was further reduced to 0.5 V, the higher overpotential

caused more pronounced edge growth, Figure 4.24D. Subsequently, the influence of

electrodeposition time was studied for 4 min to 8 min at the same deposition potential of 0.6 V,

Figure 4.24E−H. It can be seen that there was no obvious difference for the morphologies of gold

surface deposited for all these times, which is caused by the limitation of the deposition by the

charge transfer and not the mass transport. The crystal-growth rates are small enough to cover

the surface smoothly for this lower overpotential. The microelectrode can obtain a solid and

stable gold morphology for CA at low overpotential, which represents a prerequisite for

subsequent aptamer modification and repeated regeneration of the aptasensor.

86

Figure 4.24 SEM images of the surfaces of gold electrodeposited microelectrodes formed by CA

at different deposition potentials (A to D) and time (E to H).

To further compare various deposition conditions of CA, the electrochemical active areas

of electrodeposited gold surfaces were measured by CV, Figure 4.25. The electroactive areas

were calculated from the coulomb peak areas of the gold reduction at around 0.9 V in 0.05 M


87

H2SO4. As the electrodeposition potential decreased from 0.7 V to 0.6 V, the electrode active

area rapidly increased, Figure 4.25B. At potentials lower than 0.6 V, the electrode active area

increases slowly, but the RSD of the deposition areas became larger, similar to Figure 4.22B.

Taking the electrochemical (Figure 4.25B) and morphological studies (Figure 4.24G) together

then it can be concluded that a gold deposition with the potential of 0.6 V for 7 min results in an

active area as high as (1.5 ± 0.1) *10−3

mm2 and retains a relatively stable spherical structure

(low RSD), which is favorable for the stability of the electrode material. Therefore, considering

the electrode active area and electrode surface stability, 0.6 V is selected as the most suitable

deposition potential. Figure 4.25C and D shows that the electrochemical active surface area of

microelectrode with gold electrodeposited at 0.6 V is less affected by the deposition time and

reaches a maximum at 7 min, so 7 min can be considered as best suited deposition time.

In the work from Kelley‘s group, nucleic acid probes immobilized on the highly branched

electrodes by electrodeposition attained high sensitivity and rapid detection with target

molecules in solution [172]. However, the reproducibility and stability of these microelectrodes

with loose and mechanically fragile structures have not been considered, see Figure 4.23D.

Stability and reproducibility are crucial factors for the multi-aptamer immobilization of MEAs.

In order to achieve the modification of multiple aptamers and the detection of multiple targets,

the stability of the electrodes was considered as an important factor in this work. CA was used

for subsequent experiments, because the electrodeposition potential of CA can be controlled at a

lower overpotential to avoid excessive edge crystallization. Compared to the electroactive

surface of bare microelectrode, the electroactive area of the 3D-GME increased about 12 times

(more details discussed in Section 4.4.2). Therefore, the experimental parameters of CA with a

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potential step from 0 V to 0.6 V for 7 min are used to provide a large and more controllable 3D

electrodeposited gold microelectrode (3D-GME) for the next aptamer modification.

Figure 4.25 (A) The CV curves of gold electrodeposited microelectrodes by CA for different

deposition potentials (A) and times (C) in 0.05 M H2SO4 scanned from 0 V to 1.5 V at

0.1 V s−1

. The integrated areas of the reduction peaks at around 0.9 V for different

deposition potentials (B) and times (D) corresponding to (A) and (C), respectively.

4.4.2 Comparison 3D-GMEs with bare microelectrodes

In order to compare the electrochemical properties of the developed 3D-GME and bare

microelectrode, CV and EIS were used to characterize the electrochemical properties in

[Fe(CN)6]3−/4−

solution, as shown in Figure 4.26A and B. As can be seen from the CV diagrams,

the unmodified microelectrode exhibited a small limiting steady state redox current (> 10 nA)


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characteristic rather for micro-disk electrodes than for micro-spherical electrode [173, 174]. This

indicates that due to the small size of the electrode, the probe [Fe(CN)6]3−/4−

have a very poor

electron transfer performance on the bare microelectrode. From impedance spectrum of Figure

4.26B, it can be seen that the bare microelectrode showed a huge charge transfer resistance (Rct)

approximately 2.6 × 107 ohm, while the Rct of 3D-GME was greatly reduced to 2 × 10

6 ohm,

which indicates that the 3D-GME has much better charge transfer performance due to an

increased 3D surface area and beneficial electrode shape.

Figure 4.26 CV (A) and EIS Nyquist plot (B) of the characterization of bare and gold deposited

microelectrodes, solid lines are fitting results with Randles equivalent circuit models. The

CV curves of bare and gold electrodeposited microelectrodes for determining

90

electroactive surfaces. (D) The ACV response curves of the aptamer modified bare

electrode and the GD-microelectrode for blank Tris-HCl buffer.

The number of aptamer receptors immobilized at the electrode plays a crucial role in the

sensitivity of the aptamer sensor. The CV of 3D-GME recorded in sulfuric acid showed a series

of broad peaks around 1.3 V, Figure 4.26C, corresponding to the oxidation potential of gold, and

a sharp peak around 0.9 V, corresponding to the reduction of gold. The electrode surfaces

derived from the cathode peak of the bare microelectrode (1.2 *10−4

mm2) was much smaller

than that of the 3D-GME (1.5 *10−3

mm2). After electrodeposition, the electrode area increased

about 12 times, which greatly increased the configurable area and attenuates the disadvantage of

microelectrode to possess a small area to attach receptors. The 3D-GMEAs retain on the one

hand their small size and high spatial resolution, but on the other hand possess an enhanced

electroactive area, which provides a favorable condition for further improving the sensitivity of

the aptasensor based on microelectrode. Next, the DNA aptamers with stem-loop structures were

tethered on the bare electrode and the 3D-GME to evaluate the current signal. Figure 4.26D

shows the ACV response curves of the bare electrode and the 3D-GME in Tris-HCl buffer. It can

be seen that the 3D-GME exhibits a huge current response reaching the nA level, 10 times higher

than the current response obtained from the microelectrode without gold deposition.

4.4.3 Performance of aptasensor for AβO

As the signal suppression rate (SS) of the aptasensor comes from the destruction of the

stem-loop DNA molecules attached to the 3D-GME, the concentration of the DNA aptamer

solution needs to be optimized to obtain the optimal performance. An aptasensor with low

receptor density may suffer from system noises, while an aptasensor modified by excessively

dense DNA causes a decrease in the target binding effectiveness due to steric hindrance.


91

Therefore, in order to obtain a suitable aptamer modification concentration, the aptamer

concentration was optimized from 0.1 µM to 2.0 µM for 1 nm AβO detection, Figure 4.27A.

When the concentration increased from 0.1 µM to 1.0 µM, the response signal SS of the

electrode increases rapidly. After 1.0 µM, the response signal of the electrode reached a plateau

then decreased slowly, so 1.0 µM B-5‘ Fc is used in the next experiment for measuring AβO.

This concentration is similar to that found for macroelectrodes indicating that the 3D surface

morphology of the electrodeposited nanogold doesn‘t affect the aptamer immobilization as well

as the aptamer-AβO complex formation.

Incubation time is also an important fact influencing the performance of aptasensor.

Figure 4.27B shows the dependence of SS on incubation time between aptamer and AβO from

10 min to 40 min. It was found that the SS signal increased with increasing incubation time from

10 min to 20 min and maintained after that, suggesting that the binding kinetics between aptamer

and AβO almost reaches saturation at 20 min, which is faster than that of aptasensor based on

macroelectrode due to the fast mass transfer rate on 3D-GME. Thus, 20 min was selected as the

incubation time for the aptamer probe to interact with AβO.

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Figure 4.27 Effects of concentration of aptamer (A) and incubation time of aptamer-AβO (B) for

1 nM AβO detection in 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl.

A series of ACV curves were recorded for quantitative detection of AβO by the

developed stem-loop aptamer modified 3D-GME, Figure 4.28A. It can be seen that upon the

optimal experimental conditions, the peak current of the ACV curve decreased as the

concentration of the target increasing from 1 pM to 200 nM. The SS is plotted against the AβO

concentration shown in Figure 4.28B. A linear relationship was found between the logarithmic

presentation of the AβO concentration and SS with the equation of SS (%) = 16% lgC + 0.54

with a correlation coefficient of 0.993. The detection limit was calculated to 0.3 pM defined as

the mean of the blank signal and 3 times the relative standard deviation. Compared to the AβO

aptasensor based on macroelectrode, this aptasensors based on 3D-GME shows a higher

sensitivity but a higher detection limit due to the amplifier noise for microelectrode. The other

AβO sensors were compared to the developed aptasensor in this thesis, in Table 4.5. The

amperometric aptasensor is sensitive enough for the detection of low concentration of AβO in

CSF and covers the human physiological levels for AβO. More importantly, these

electrochemical aptasensors obviates the utilization of enzyme-linked antibody and expensive

instruments, thus reducing the operational complexity and assay cost.

Furthermore, the aptamer sensor reusability was studied, Figure 4.28C. A high

concentration of urea solution acts as an eluent to gently interrupt the binding between the


93

aptamer and the target. The used 3D-GME aptasensor was first used to detect 0.1 nM AβO.

Subsequently, the sensor was incubated in 6 M urea for 10 min and washed with 3 mL Milli-Q

water. The current signal of the recycled aptasensor can be restored to the original blank signal

and three repeated detection cycles were performed.

Table 4.5 Performance comparison of the proposed electrochemical aptasensor in this thesis

with other AβO sensors.

Method Linear range Detection

limit Ref.

Magnetic bead-droplet immunoassay (12.5 – 200) pg/mL 10.7 pg mL−1

[17]

Surface plasmon resonance sensor 0.04 μM – 1.2 μM 0.1 μM [20]

Fluorescent aptsensor 0 μM – 19.25 μM 3.57 nM [37]

ELISA (0.26–5.21) μg/ml - [175]

Electrochemical biosensor 20 pM – 100 nM 8 pM [176]

Upconversion fluorescent 0.2 nM – 15 nM 36 pM [177]

Peptide-linked immunosorbent assay 0.35 pM −1.5 pM - [178]

Electrochemiluminescence (0.1 – 10) ng/mL 19.95 fg/mL [179]

Label-free aptasensor 0.1 nM – 500 nM 0.03 nM Section 4.2

Amperometric aptasensor 0.1 pM to 10 nM

1.0 pm to 1500 nM

0.002 pM

0.006 pM Section 4.3

Aptasensor based on 3D-GME 1.0 pM to 200 nM 0.3 pM This section

In order to evaluate the selectivity of the constructed aptasensor based on 3D-GME, the

interference of AβO detection by AβM and AβF was detected at the same concentration, Figure

4.28D. It can be seen that AβM and AβF had some small but noticeable influence on the

detection of 0.1 nM AβO. This observation confirms the high selectivity of the aptamer observed

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for macroelectrodes, which indicates that the high surface roughness and the different energy

landscape due to the high number of Au step edges do not impair the selectivity. There is a

certain interference especially for AβF, however, it is very likely that those samples also contain

other Aβ aggregates since their state is very transient. Nevertheless, the specificity of the novel

aptasensor not only facilitates the efficiency of the AβO analysis for the diagnosis of AD, but

may pave the way to in vitro drug screening based on AβO specific sensors.

Figure 4.28 ACV curves obtained from B-3‘ Fc modified AuR upon incubation in different

concentrations of AβO; an ACV frequency of 10 Hz was used. (B) The calibration curve

obtained for a concentration range of AβO from 1 pM to 1500 nM. (C) Regeneration and


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reuse of aptasensor toward 0.1 nM AβO regenerated by rinsing with 6 M urea. (D)

Selectivity of the developed aptasensor towards 1 nM AβM, AβO and AβF in 10 mM

Tris-HCl + 150 mM NaCl + 5 mM KCl.

Figure 4.29 (A) ACV curves obtained at different 3D-GMEs of the same chip before (solid line)

and after (dot line) adding 10 nM AβO; (B) The aptasenor responses towards 10 nM AβO

at different 3D-GMEs: the dot line is the average value of aptasensor signal; the width of

the blue rectangle represents the standard deviation.

One of the advantages of MEAs is that the reliability of detection can be increased

through the analysis of several redundant signals from different electrodes of the same chip.

MEAs can provide redundant information from multiple detection sites different from a signal

device. There are two advantages: on the one hand, the electrochemical signals of multiple

electrodes obtained in a short time can minimize the negative effects due to the test failure of a

single electrode. As can be seen from Figure 4.29, eight 3D-GMEs on the same chip were used

to detect 10 nM AβO. Among them, R2E8 clearly gave an excessive blank current considerably

96

higher than for the other electrodes. This indicates that this electrode shows an irregular response

and should be eliminated from the analysis. On the other hand, multi-channel and multi-electrode

detection can also detect electrochemical signals with higher accuracy by superimposing

experimental results by reducing the standard deviation.

4.4.4. Regeneration of 3D-GMEAs for ATP detection

For MEAs, another significant advantage is that multiple aptamers can be tethered to the

electrodes and multi-target detection can be performed to obtain more information about the

analyte. Furthermore, the spatial distribution of these targets can be potentially recorded. Since

the modification of the aptamer is performed in the solution phase, each aptamer is immobilized

on all active electrodes on the same chips. However, multi-target detection requires that different

electrodes are modified with different aptamer receptors. Therefore, the selective regeneration of

3D-GME for multiple tethering steps of additional aptamer molecules is crucial to establish such

advanced sensing platforms. Figure 4.30 shows the CV diagrams of previously used 3D-GME in

0.05 M H2SO4 after electrochemical cleaning (A) and O2 plasma cleaning (B). It can be seen in

Figure 4.30A that the gold oxidation and reduction peaks of the aptamer modified electrodes (red)

was greatly reduced due to a large amount of adsorbed aptamer and MCH molecules in

comparison to the bare electrode (black). After scanning 20 CV cycles in 0.05 M H2SO4 solution,

the active area of the electrode increased compared with that before cycling, reaching 60% of the

original area. Alternatively, a combination of 10 CV scans in 0.5 M NaOH and 20 scans in 0.05

M H2SO4 fully regenerated the active surface area of the electrode, which facilitates the

attachment of additional types of aptamer receptors.

Another approach to regenerate the MEA electrodes is O2 plasma cleaning, which

however acts globally on all microelectrodes of the chip. Here, a protocol of 0.5 mbar O2


97

pressure, 50% power, and an etching time of 3 minutes was used to remove the molecules with

sulfhydryl groups from the 3D-GMEs. After O2 plasma cleaning, soaking in ethanol is necessary

due to the formation of an oxide layer on metal during plasma cleaning to reduce the oxide layer,

which is conducive to subsequent modifications of thiol containing molecules [180]. After O2

plasma cleaning and ethanol soaking for 20 minutes, the regenerated microelectrode recovered

the original surface mostly, Figure 4.30B. A minor increase in the surface area can be noticed

presumably caused by a slight degeneration of the electrode passivation. However, the 3D

structure was not significantly altered by the O2 plasma treatment. Consequently, both cleaning

methods are suitable for 3D-GME cleaning. The O2 plasma can be used to regenerate the entire

3D-GME arrays after usage to reset it for a second application. The electrochemical reactivation

in NaOH and H2SO4 can selectively regenerate individual microelectrode due to the ability to

apply the potential only to a specific electrode, which is crucial for multiple receptor

modification and multiple target detection.

In order to prove that the constructed 3D-GMEAs sensing platform can be used for the

detection of multi-targets, adenosine triphosphate (ATP) was used as a model analyte in our

experiments. ATP acts as an intracellular biomolecule for energy transfer and storage that can be

produced by oxidative phosphorylation in mitochondria [181]. AβO molecules penetrate into the

proton separating membrane, promote the formation of reactive oxygen species, causing

mitochondrial dysfunction, and resulting in a decrease in ATP synthesis. However, the detection

of ATP can not only provide more accurate evidence for AD diagnosis, but is also an important

biomarker for the detection of other neurodegenerative diseases, such as Huntington‘s disease,

Friedreich‘s ataxia, or multiples sclerosis (deviating ATP levels in CSF) [182, 183].

98

Figure 4.30 Electrochemical cleaning combining 10 CV scans in 0.5 M NaOH and 20 scans in

0.05 M H2SO4 (A) and O2 plasma treatment with 0.5 mbar O2 pressure, 50% power, and

an etching time of 3 minutes (B) for regeneration of the used MEAs(C). ACV curves

obtained at regenerated 3D-GME for the detection of ATP as second analyte at different

concentrations. (D) The calibration curve for ATP for concentrations varying from 0.01

nM to 1000 nM.

Firstly, parts of the microelectrodes in the MEAs modified AβO aptamer were selectively

regenerated by electrochemical cleaning, and then a 0.5 µM aptamer solution against ATP was

used to modify the regenerated 3D-GMEs. Noteworthy, the microelectrodes modified with AβO

aptamers were note regenerated and retained their aptamers on the 3D-GME, while only the

regenerated microelectrodes were modified with the second aptamer against ATP. Consequently


99

two types of aptamer modified microelectrode co-existed on the same 3D-GMEAs chip. The

ACV responses of ATP aptasensor based on regenerated 3D-GMEAs strongly depends on the

concentrations of ATP in a type of signal-on response, Figure 4.30C. The aptasensor showed a

logarithmic concentration-dependence in the range from 0.01 nM to 1000 nM, indicating that the

presence of AβO aptamers does not affect the detection of ATP. The calibration equation was I

(nA) = 4.7 lgC + 13.6 with a correlation coefficient of 0.995 (Figure 4.30D). The limit of

detection was 0.002 nM defined as 3 times the standard deviation and the mean of the blank

signal.

Table 4.6 Performance comparison of the proposed electrochemical aptasensor based on 3D-

GMEAs with other ATP sensors

Method Linear range Detection limit Ref.

Electrochemical current

rectification 0–5 μM 114 nM [32]

Biosensor on microelectrode 0.25 μM – 4 μM 9.9 nM [184]

Biosensor on MB aptamer 0.1 μM – 50 μM 0.05 μM [185]

Fluorescent sensor – 5 μM [186]

Fluorescence resonance energy

transfer assay 2 μM – 16 μM 1.7 μM [187]

HPLC 1 μM – 12 μM – [188]

Aptamer sensor 1 μM – 1000 μM 1 μM [189]

Aptasensor based on 3D-GME 0.01 nM – 1000 nM 0.002 nM This section

The detection limits of other previously reported ATP sensors are compared to the

developed electrochemical aptasensor based on 3D-GMEAs in Table 4.6. The ATP sensors

whether based on microelectrode or aptamer show higher detection limits than electrochemical

100

aptasensor based on 3D-GMEAs. The developed sensor is more sensitive than most of other

reported ATP sensors including fluorescence methods and high-performance liquid

chromatography (HPLC). These results illustrate that our 3D-GMEAs can be used for the dual-

aptamer modification and the dual-target detection, which is also a possible sensing platform for

future multi-aptamer modification and multi-target detection.

Since AβO is highly toxic to the cells of the central nervous system, its early proof of

their presence in CSF is crucial but intricate. To realize an aptamer based AβO assay the

detection amyloid oligomers in aCSF tested. In addition, ATP levels in CSF have been also

certificated to vary during the development of neurodegenerative diseases including AD. The

absolute level of specific biomarker is strongly dependent on the individual. The combination of

different biomarker signals relevant for the same disease can improve the reliability of the test

results and simplify the diagnosis [144]. To demonstrate the feasibility of simultaneous detection

of AβO and ATP in aCSF, both biomarker samples were tested at the same 3D-MEAs chip,

Table 4.7. It can be seen from the results of the standard addition method that our dual-aptamer

biosensor based on nanostructured multielectrode arrays has high accuracy and feasibility for the

detection of both AβO and ATP at the same chip in aCSF solution. The measured averaged

signals deviated less than 20% from the concentration of the added sample. Here, the accuracy

benefits from the redundancy of the data acquisition since the signal of several channels can be

averaged. It is noteworthy furthermore, that the regeneration procedure does not impair the

binding capability of the aptamer receptors, although they were exposed to harsh corrosive

NaOH and H2SO4 solutions. The chemical robustness of aptamers is certainly an advantage of

these receptors over antibodies, which tend to denature.


101

Table 4.7 Results of the detection of AβO and ATP at the same 3D-GMEA chip in aCSF by

standard addition method.

Samples Found (nM); Recovery (%); RSD (n=3)

Added (nM) AβO ATP

0.1 0.103; 103%; 4.9% 0.083; 83%; 3.5%

1.0 0.92; 92%; 5.8% 0.88; 88%; 3.3%

10 9.5; 95%; 9.6% 11.5; 115%; 6.8%

Conclusions and outlook

103

Chapter 5 Conclusions and outlook

In this thesis, electrochemical aptasensors were developed for the sensitive and selectivity

detection of AβO to achieve an early diagnosis of Alzheimer‘s disease. Aptamers are used as

receptores for direct and post-modification on macroelectrode surfaces for the construction of the

label-free impedance aptasensor and the labeled amperometric aptasensor based stem-loop

aptamer. To fulfill parallel detection of various targets of AD, an aptasensor based on 3D-

GMEAs platform is developed to simultaneous detection of AβO and ATP.

Firstly, to demonstrate that the screened aptamers can be modified on the electrodes and still

maintain the specific binding towards AβO at the electrode surface, electrochemical

characterization and morphological characterization were performed to characterize the

fabrication process of the aptasensor and to verify the assembly and binding process. The EIS,

CV, and AFM analysis revealed the successful preparation of electrochemical aptasensor and the

formation of aptamer/AβO complexes at the electrode surface. In addition, aptamers exhibiting

different binding forces in the enzyme-linked oligonucleotide analysis are modified on the gold

rod electrode to construct different electrochemical aptasensors, but the difference of the

electrochemical responses of these aptasensors is not significant.

Secondly, a simple and novel label-free aptasensor was developed for the selective and

sensitive detection of AβO by monitoring changes in the charge transfer resistance of redox

probes using impedance spectroscopy. The proposed aptasensor exhibited a wide linear

concentration detection range from 0.1 nm to 500 nM and a low detection limit of 0.03 nM. The

aptasensor can be used to assay AβO in aCSF with satisfying accuracy. Due to the chemical

stability of the aptamers compared with antibodies, the reported aptasensor provided a high

stability and regeneration ability during AβO detection, suggesting a great potential for point of

care applications. Moreover, a high selectivity towards AβO over other Aβ protein species was

observed. The new aptasensor was able to monitor the aggregation process of Aβ proteins, which

was confirmed by AFM morphology characterization. The ability of the aptasensor to track the

aggregation process of Aβ proteins is beneficial not only to early diagnose and study the

pathogenesis of AD but also for the development of AD medical treatments.

In the third section, to overcome the drawbacks of impedance spectroscopy such as low

104

sensitivity or unspecific adsorption of interfering species to backfill molecule due to hydrophobic

interaction, a simple and sensitive aptasensor based on ssDNA stem-loop probes was proposed

for the selective detection of AβO by amperometric response change using ACV. To obtain

satisfactory performance, we optimized systematically the stem-loop structures including stem

number, oligonucleotide length, location of redox probes, sequence, and spacer. In the end, a

stem-loop with 5 base pairs and a ferrocene label attached to the 3‘ terminal end was found to

possess the highest signal change caused by target binding. The proposed aptasensor exhibited a

wide concentration detection range from 0.1 pM to 1500 nM with a low detection limit at a fM

level, which is sensitive enough for the detection of physiological concentration of AβO. We also

found that the detection range can be adjusted by varying the ACV frequency, which facilitated

either a low detection limit or a broad detection range. A long-time stability test yielded 80%

conservation of the original signal after a two-week storing period. In addition, a considerable

selectivity towards AβO over other Aβ protein species was observed. These excellent sensor

features as well as its other characteristics, such as easy fabrication and operation convenience,

make this aptamer design a promising receptor to be used for AβO detection on microelectrodes.

Finally, a dual-aptamer modified 3D-MEAs was developed for simultaneous detection of

AβO and ATP in artificial cerebrospinal fluid. By comparing various electrodeposition methods,

chronoamperometry applying a potential step from 0 V to 0.6 V and time of 7 min generated the

optimal compromise between large active surface areas and high stability. The large active

surface area facilitated sufficient receptor load and the stability enabled not only a high

reproducibility but also an electrode regeneration for multi-aptamer immobilization. The

morphological and electrochemical characterizations exhibited significant reduction of the

electron transfer resistance and increase the active area of the 3D-GMEs compared with bare

microelectrodes. A linear detection range was achieved during AβO assays from 1 pM to 200 nM

with low LOD of 0.3 pM. In addition, cleaning methods and the regeneration capability of the

3D-GMEAs were evaluated. 3D-GMEAs already used for sensor applications can be quickly and

completely cleaned by O2 plasma, or can be selectively regenerated by removing all surface

tethered molecules by oxidation/reductions cycles on selected electrode of the 3D-GME array.

The electrochemical cleaning facilitated the subsequent modification of reactivated electrode by

aptamer receptors against ATP on the same 3D-GMEAs chip. The obtained ATP aptasensor

exhibited a linear detection range from 10 pM to 1000 nM with a limit of detection of 2 pM.

Conclusions and outlook

105

Furthermore, this dual-aptamer biosensor was used to perform a parallel AβO and ATP assay in

aCSF. The 3D-GMEAs can be utilized as biosensing platform for multi-aptamer receptor and

multiple target detection with larger electroactive surface and high spatial resolution facilitating

redundant signal recording for reliable target analysis.

In the future, several further efforts could be done on the development of electrochemical

aptasensors. New combinations of nanomaterials and aptamers can be used for the abundant

immobilization of aptamer receptors ensuring high receptor load on small lateral dimensions or

nanoparticles with high electrochemical activity are tagged as redox labels on the terminal end of

the aptamer chains for ultrasensitive detection. The constructed 3D-GMEAs can be applied as a

biosensing platform for not only aptamers, but also other recognition molecules and materials for

multi-channel multi-target detection in a short time. Last but not least, the 3D nanostructured

multielectrode arrays chip platform with small size and high spatial resolution could be

converted to flexible substrates and used for redundant signal recording in vivo, including

measuring the concentration of various analytes and analyzing concentration gradients.

Acknowledgements

107

Acknowledgements

There are many people I would like to express my deep thanks for their help, support, and

encouragement during my Ph.D. study.

Prof. Andreas Offenhäusser, my supervisor, first of all, I would like to thank you for

giving me this chance to work and learn in this friendly and advanced research environment.

Thank you again for all your support and advice in research and study.

Dr. Dirk Mayer, my direct supervisor, I sincerely thank you for your patience guidance

during my Ph.D. research. You always give an excellent suggestion when I am confused. I learn

a lot of knowledge from every discussion with you that will benefit my whole academic career.

Thank you again very much for your help and support in experiments, publication, and Ph.D.

thesis.

Prof. Ulrich Simon, my second supervisor, I would be greatly appreciated for your

insightful advices and discussions for reviewing my Ph.D. thesis. I am appreciated for your

contributions.

Prof. Dieter Willbold and Dr. Christian Zafiu, thank you for your help and discussion for

my work and critical comments for my publication.

Michael Prömper and Marko Banzet, thank you for the technical support in fabricating

MEAs.

Bettina Breuer, Dr. Elmar Neuman, and Elke Brauweiller-Reuters, thank you for the help

in my experiments.

Lingyan Feng, Lena Nörbel, Gabriela Figueroa-Miranda, Christopher Beale, Yuanying

Liang, Changtong Wu, Stefanie Hamacher, and Lei Zhou, thank you for kind help and useful

advice for my work in Molecular Bioelectronics group meeting.

I would like to thank all the members in ICS-8 for the nice working environment, and

thanks whoever offered me help in the institute.

Finally, I want to thank my parents, husband and son, thank you for your endless love

and encouragement to give me the strength and motivation to complete my doctoral study.

Appendix I: Abbreviations

109

Appendix I: Abbreviations

Aptamer sensor: Aptasensor

AD: Alzheimer's disease

AβM: Amyloid-β monomers:

AβO: Amyloid-β oligomers:

AβF: Amyloid-β fibrils:

DNA: Deoxyribonucleic acid

A: Adenine

T: Thymine

C: Cytosine

G: Guanine

SELEX: Systematic evolution of ligands by exponential enrichment

SAM: Self-assembled monolayer

LSV: Linear sweep voltammetry

CV: Cyclic voltammetry

SWV: Square wave voltammetry

DPV: Differential pulse voltammetry

ACV: Alternating current voltammetry

EIS: Electrochemical impedance spectroscopy

Rct: Charge transfer resistance

R: Electrolyte resistance

CPE: Double layer capacitance

Zw: Warburg impedance

CC: Chronocoulometry

CA: Chronoamperometry

110

CSF: Cerebrospinal fluid

MB: Molecular beacons

ST: Stem-loop

AuR: Gold rod electrode

MEAs: Multielectrode arrays

3D-GME: 3D gold microelectrode

SEM: Scanning electron microscopy

AFM: Atomic force microscopy

UV-Vis: Ultraviolet-visible absorption spectroscopy

HFIP: 1,1,1,3,3,3-hexafluoro-2-propanol

TCEP: Tris (2-carboxyethyl) phosphine hydrochloride

MCH: 6-mercaptho-1-hexanol

Tris: Tris (hydroxymethyl) aminomethane

PDMS: poly(dimethysiloxane

PI: Polyimide

RSD: Relative standard deviation

SS: The signal suppression rate

ATP: Adenosine triphosphate

Appendix II: List of Figures

111


Figure 2.1 The chemical structures of DNA molecules [57]. ........................................................ 6

Figure 2.2 Flow chart of the SELEX screening technique [58]. .................................................... 7

Figure 2.3. Some 3D structures of aptamer oligonucleotides for different targets [61]. ............... 8

Figure 2.4 Working schematic diagram of the electrochemical aptasensor. ............................... 10

Figure 2.5 the BDM model of the electric double layer [89]. ...................................................... 15

Figure 2.6 Linear increase of the potential vs time in LSV [93]. ................................................ 18

Figure 2.7 (A) The triangular pulse voltage of CV; (B) Voltage as a function of time and current

as a function of voltage for CV [97]. ............................................................................................ 20

Figure 2.8 (A) single potential cycle in square-wave voltammetry; (B) typical square-wave

voltammogram [106]. Ifor is the forward pulse current, and Irev is the reverse pulse current. ....... 22

Figure 2.9 Excitation signal for the differential pulse voltammetry [112].The red lines are the

current recording before each potential changing. ........................................................................ 23

Figure 2.10 (A) Excitation signal for the alternating current voltammetry; (B) typical ACV curve

[115]. ............................................................................................................................................. 24

Figure 2.11 Scheme of electrochemical impedance spectroscopy. .............................................. 25

Figure 2.12 (A) Nyquist plot and (B) Bode plot of the impedance spectrum of an RC circuit. A

diagram of the RC circuit is shown as in inset in the Nyquist plot. The arrows indicate that the

frequency increases toward the origin of the plot. In the Bode plot, Z′ and Z″ versus

frequency are plotted [118]. .......................................................................................................... 26

Figure 2.13 Diagram of Nyquist plot for simple Randles circuit [118]. ...................................... 28

Figure 2.14 (A) useful signals generated by electron-matter interactions in a thin sample; (B)

schematic diagram of the core components of an SEM microscopy [125]. ................................. 29

112

Figure 2.15 The Schematic diagram of Atomic Force Microscope [128]. .................................. 31

Figure 2.16 The absorption bands in the UV-Vis spectrum correspond to transitions of the

electronic energy levels................................................................................................................. 33

Figure 3.1 Gold rod electrode used in this work. ......................................................................... 36

Figure 3.2 Fabrication process of multielectrode arrays: (a−b) spin-coating of photoresists; (c)

photolithography patterning of gold electrodes; (d) electron-beam deposition Ti and Au; (d−e)

lift-off process by sonication; (f) spin-coating of polyimide for insulating the feedlines; (g) active

the electrodes and contact pads by photolithography. .................................................................. 37

Figure 3.3 (A) Borosilicate / gold MEAs with glass ring as electrochemical reservoir cell; (B)

central part of the chip with gold feedlines and 64 microelectrodes. ........................................... 38

Figure 3.4 UV/Vis spectrometer of the measured DNA stock solution from 220 nm to 400 nm.

....................................................................................................................................................... 39

Figure 3.5 A simple block diagram of a potentiostat and a transimpedance amplifier [132]. ..... 41

Figure 3.6 Three-electrode cells used in AuR (A) and MEAs (B) electrochemical system. ....... 41

Figure 3.7 Autolab setup used for electrochemical measurements. ............................................. 42

Figure 3.8 CHI workstation with multi-channel used in electrochemical measurements. .......... 43

Figure 4.1 CVs (A) and EIS (B) recorded in 5.0 mM [Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150

mM NaCl + 5 mM KCl at bare AuR, aptamer-AuR, MCH-aptamer-AuR, and adding 10 nM

AβO. Solid lines are fitting results with the model in the EIS. ..................................................... 48

Figure 4.2 Chronocoulometric curves for gold electrodes modified with single-stranded DNA

probes before (black) and after RuHex addition. .......................................................................... 49

Figure 4.3 Tapping mode AFM images of gold surface before (A) and after aptamer (B), MCH

(C), and AβO (D) surface immobilization. Cross-section analysis (E−H) and 3D AFM height

images (I−L) corresponding to A−D, respectively. ...................................................................... 50


113

Figure 4.4 Tapping mode AFM images of the aptamer immobilization on gold surface. The

white arrows indicate Au holes with aptamers decorating the step edges of Au. ......................... 52

Figure 4.5 The particle height distribution of gold surface before (A) and after aptamer (B)

binding, MCH (C) immobilization, and AβO (D) detection. Particles that are used for the

analysis are marked blue. Particles touching the image frames were excluded from the analysis.

....................................................................................................................................................... 53

Figure 4.6 EIS curves obtained for O1 (A), O2 (B), and O3 (C) immobilized to the gold rod

electrode from a 0.01 µM aptamer solution recorded in 1 nM AβO containing 5.0 mM

[Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl................................................ 54

Figure 4.7 Mechanism for label-free aptasensor based on the electrochemical impedance method.

....................................................................................................................................................... 56

Figure 4.8 Effects of concentration of aptamer (A), incubation time of AβO (B) and pH value

(C). ................................................................................................................................................ 57

Figure 4.9 (A) EIS curves obtained at MCH-aptamer-AuR upon different concentrations of Aβ

into 5.0 mM [Fe(CN)6]3−/4−

+ 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl, solid lines are

fitting results with the model; (B) The calibration curve for AβO from 1 nM to 500 nM. .......... 58

Figure 4.10 (A) Selectivity towards 1 nM Aβ monomers (AβM), Aβ fibrils (AβF), AβO; (B)

Long-term stability of the aptasensor at 4 degrees for 7 days and 14 days; Reuse of aptasensor

toward 100 nM AβO regenerated by rinsing with 6 M urea (C and D). ....................................... 60

Figure 4.11 Monitoring Aβ proteins aggregation process by developed aptasensor. .................. 61

Figure 4.12 AFM images of bare silicon chip (A) and Aβ peptides incubated for 24 h (B), 72

h(C), and 120 h (D); The corresponding height cross-section along the line (E−H). ................... 62

Figure 4.13 Mechanism for aptasensor detection based on a stem-loop aptamer. ....................... 65

114

Figure 4.14 Oligonucleotide sequences used in this work. Red and yellow lines indicate

nucleotides that were inserted into the original aptamer sequence to form a stem-loop; the blue

curves are the original aptamer sequences. ................................................................................... 65

Figure 4.15 ACV curves recorded towards 10 pM AβO in 10 mM Tris-HCl + 150 mM NaCl + 5

mM KCl at ST-4 (A), ST-5 (B), and ST-6 (C) aptasensor; (D) The SS of the different

oligonucleotide-length aptamer sensors A-3‘Fc, A-5‘Fc, B-3‘Fc, and B-5‘Fc responding to 10

pM AβO. The effect of location of thiol and ferrocene (B and E) and spacer (B and F) on AβO

response......................................................................................................................................... 68

Figure 4.16 The surface aptamer density of B-3‘Fc (A) and B-5‘Fc (B) modified electrode was

quantified using chronocoulometric technique. ............................................................................ 70

Figure 4.17 Effects of concentration (A) of aptamer and incubation time of aptamer-target (B)

on AβO response in 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl.......................................... 72

Figure 4.18 Effects of ACV frequency on AβO detection response from 5 Hz to 40 Hz：A−D:

ACV responses of aptasensor towards different concentrations of AβO; E: aptasenor responses to

blank, 10 pM, and 0.1 nM AβO at different frequency; F: aptasenor responses towards 10 pM

AβO at different frequency. .......................................................................................................... 73

Figure 4.19 (A) ACV curves obtained at B-3‘ Fc modified AuR upon different concentrations of

AβO applied 10 Hz, (B) The calibration curve for AβO from 1 pM to 1500 nM. (C) ACV curves

obtained at B-3‘ Fc modified AuR upon different concentrations of AβO from applied 20 Hz, (D)

The calibration curve for AβO from 0.1 pM to 10 nM. ................................................................ 75

Figure 4.20 (A) Selectivity of the developed aptasensor towards 10 pM AβM, AβO and AβF in

10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl; (B) Stability of the aptasensor signal towards 1

pM AβO stored in a fridge of 4 degree for 7 days and 14 days. ................................................... 76


115

Figure 4.21 Scheme of dual-detection of AβO and ATP by corresponding aptamers tethered on

different microelectrode of the same MEA chip. .......................................................................... 79

Figure 4.22 (A) CV curves of microelectrodes with gold electrodeposited by LSV for different

deposition times from 1.0 min to 10 min in 0.05 M H2SO4 sweeping from 0 V to 1.35 V at 0.1 V

s−1

. (B) The integrated areas of the reduction peaks at 0.9 V (Ag/AgCl). (C) CV curves for

electroactive surfaces of different microelectrodes on the same MEAs chip with deposition time

of 5 min. ........................................................................................................................................ 80

Figure 4.23 SEM images of the gold electrodeposited microelectrodes generated at different

deposition time by LSV (A to F) and SWV (G and H); B is magnified view of A. ..................... 83

Figure 4.24 SEM images of the surfaces of gold electrodeposited microelectrodes formed by CA

at different deposition potentials (A to D) and time (E to H). ...................................................... 86

Figure 4.25 (A) The CV curves of gold electrodeposited microelectrodes by CA for different

deposition potentials (A) and times (C) in 0.05 M H2SO4 scanned from 0 V to 1.5 V at 0.1 V s−1

.

The integrated areas of the reduction peaks at around 0.9 V for different deposition potentials (B)

and times (D) corresponding to (A) and (C), respectively. ........................................................... 88

Figure 4.26 CV (A) and EIS Nyquist plot (B) of the characterization of bare and gold deposited

microelectrodes, solid lines are fitting results with Randles equivalent circuit models. The CV

curves of bare and gold electrodeposited microelectrodes for determining electroactive surfaces.

(D) The ACV response curves of the aptamer modified bare electrode and the GD-

microelectrode for blank Tris-HCl buffer. .................................................................................... 89

Figure 4.27 Effects of concentration of aptamer (A) and incubation time of aptamer-AβO (B) for

1 nM AβO detection in 10 mM Tris-HCl + 150 mM NaCl + 5 mM KCl. ................................... 92

116

Figure 4.28 ACV curves obtained from B-3‘ Fc modified AuR upon incubation in different

concentrations of AβO; an ACV frequency of 10 Hz was used. (B) The calibration curve

obtained for a concentration range of AβO from 1 pM to 1500 nM. (C) Regeneration and reuse

of aptasensor toward 0.1 nM AβO regenerated by rinsing with 6 M urea. (D) Selectivity of the

developed aptasensor towards 1 nM AβM, AβO and AβF in 10 mM Tris-HCl + 150 mM NaCl +

5 mM KCl. .................................................................................................................................... 94

Figure 4.29 (A) ACV curves obtained at different 3D-GMEs of the same chip before (solid line)

and after (dot line) adding 10 nM AβO; (B) The aptasenor responses towards 10 nM AβO at

different 3D-GMEs: the dot line is the average value of aptasensor signal; the width of the blue

rectangle represents the standard deviation. ................................................................................. 95

Figure 4.30 Electrochemical cleaning combining 10 CV scans in 0.5 M NaOH and 20 scans in

0.05 M H2SO4 (A) and O2 plasma treatment with 0.5 mbar O2 pressure, 50% power, and an

etching time of 3 minutes (B) for regeneration of the used MEAs(C). ACV curves obtained at

regenerated 3D-GME for the detection of ATP as second analyte at different concentrations. (D)

The calibration curve for ATP for concentrations varying from 0.01 nM to 1000 nM. ............... 98

Appendix III: List of Tables

117

Appendix III: List of Tables

Table 3.1 Oligonucleotide sequences used in this work. .............................................................. 35

Table 4.1 Particle heights of AFM particle analysis for gold surface before and after aptamer

binding, MCH immobilization, and AβO detection. .................................................................... 53

Table 4.2 Intra- and inter-assay precision data. ........................................................................... 59

Table 4.3 Results of the detection of AβO in artificial CSF by standard addition method.......... 60

Table 4.4 Results of the detection of AβO in artificial CSF by standard addition method.......... 77

Table 4.5 Performance comparison of the proposed electrochemical aptasensor in this thesis

with other AβO sensors. ................................................................................................................ 93

Table 4.6 Performance comparison of the proposed electrochemical aptasensor based on 3D-

GMEAs with other ATP sensors................................................................................................... 99

Table 4.7 Results of the detection of AβO and ATP at the same 3D-GMEA chip in aCSF by

standard addition method. ........................................................................................................... 101

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