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Innovative Approaches for the Electrochemical
Detection of Acetylcholinesterase Inhibitors
Vladimir Dounin
A thesis submitted in conformity with the requirements for
oxidation peak currents in the presence of AChE and paraoxon
51
Figure 2.17 Calibration plots for the ThT-based AChE inhibitor biosensor and
DP voltammograms illustrating changes occurring to ThT oxidation
peak currents during measurements
52
Figure 2.18 Illustration of ThT oxidation at the GC electrode surface while in the
presence of AChE and inhibitor molecules
53
CHAPTER 3
Figure 3.1 Flowchart representation of procedural steps completed during
measurements for the gold DEP chip research
60
Figure 3.2 Comparison of DP voltammograms for 280 nM ThT taken directly in
solution or after a wash step in PBS buffer
64
Figure 3.3 Comparison of DP voltammograms for a solution of 280 nM ThT
and 12.5 nM AChE taken directly in solution or after a wash step in
PBS buffer
64
Figure 3.4 Comparison of CVs for 20 mM ferri-ferrocyanide on a GC electrode
in PBS buffer and in solution with 12.5 nM AChE
66
Figure 3.5 Comparison of CVs for 20 mM ferri-ferrocyanide on a GC electrode
in solutions with varying AChE concentrations
67
Figure 3.6 Comparison of CVs for 20 mM ferri-ferrocyanide on a GC electrode
in PBS buffer versus a solution of 100 ppm carbachol
69
Figure 3.7 Comparison of CVs for 20 mM ferri-ferrocyanide on a GC electrode
in a solution of 12.5 nM AChE versus a solution of 12.5 nM AChE
with 100 ppm carbachol
70
Figure 3.8 Comparison of CVs for 20 mM ferri-ferrocyanide on a GC electrode
in a solution of 200 nM AChE versus a solution of 200 nM AChE
with 280 nM ThT
71
vii
Commonly Used Abbreviations
ACh: Acetylcholine
AChE: Acetylcholinesterase
ATCh: Acetylthiocholine
BTA-1: Benzothiazole-1
Ch: Choline
CNT: Carbon nanotubes
CV: Cyclic voltammetry
DEP chips: Disposable electrochemical printed chips
DPV: Differential pulse voltammetry
FET: Field effect transistor
GC electrode: Glassy carbon electrode
NMR: Nuclear magnetic resonance
OPH: Organophosphorous hydrolase
PBS: Phosphate buffer solution (saline)
TCh: Thiocholine
ThT: Thioflavin T
1
1. INTRODUCTION
1.1 Towards the Detection of Acetylcholinesterase Inhibitors
The acetylcholine (ACh) neurotransmitter performs very important functions in the
peripheral and central nervous systems. The presence of the ACh neurotransmitter
is primarily regulated by the acetylcholinesterase (AChE) enzyme, whose native
function is to cleave ACh into choline and acetate. AChE inhibitors disrupt ACh
regulation and consequently promote elevated levels of ACh in nervous and muscle
tissues with complex physiological effects1-3. Some of these effects are understood
well enough to warrant medicinal uses of AChE inhibitors such as in Alzheimer’s
disease treatments. Critical elevation of ACh produces a fatal disruption of the
nervous system. This fact has led to the successful introduction of AChE inhibitors to
maximize crop yields in agriculture by killing insects and other pests that destroy
crops. The use of AChE inhibitors in warfare has also occurred such as with the
infamous Sarin gas, which was dispersed by a radical religious cult to target
innocent people in the 1995 “Sarin Subway Incident” in Tokyo4. Furthermore, poor
control of AChE inhibitors used in agriculture has resulted in many accidental
poisonings and the introduction of these chemicals into water and food resources.
The effects of consuming AChE inhibitors at sub-critical concentrations over
prolonged periods of time are currently poorly understood. Existing data, particularly
on organophosphate AChE inhibitors, suggests that there is a range of sensitive
non-AChE targets in living systems5 in addition to AChE and that the
phosphorylation of these additional targets leads to detrimental effects in the fields
of development and behaviour6. Regulatory bodies in Europe and North America
have limited the maximum allowable concentration of many AChE inhibitors in food
and water to be at most in the mid-ppb range and usually at 20 ppb or lower7-9.
Early efforts towards the detection of AChE inhibitors were traditionally
accomplished through the chromatographic separation of samples followed by
analysis through nuclear magnetic resonance and mass spectrometry10. These
approaches provide accurate determination of AChE inhibitor identities and can
quantify their sample concentrations precisely. However, these traditional
2
approaches take hours to complete, need sample preparation steps, and require a
skilled operator to run the appropriate test procedures11. In modern times, alternative
detection methods continue to be developed in the form of biosensors that are
relatively cost-effective, sensitive, and offer rapid analysis of samples for AChE
inhibitors with a minimal amount of required training of personnel. This chapter will
provide an overview of biological sensing for these inhibitors before proceeding on
to the details of the featured research completed in the Kerman Group laboratory in
2009-2010.
1.2 Biological Sensing
The term ‘biosensor’ describes a device designed for the detection of a particular
analyte through a measurable interaction of the analyte with a biological recognition
element. The biological recognition element can consist of structures that are
relevant to living organisms, ranging from entire cells to complicated proteins or
even to something as small as a short oligonucleotide. The interaction of analyte
with the biological recognition element can be detected through a suitable
transducer, which is a device integrated into the biosensor that can respond to the
biological interaction events in the form of a change in some measurable quantity,
usually presenting itself as an electrical signal 12. The signal from the transducer can
then be amplified and processed for interpretation by the end-user in analog or
digital formats13.
Figure 1.1. A general flowchart representation of biosensor operation.
The choice of the biological recognition element and transducer ultimately
determines the capacity of the assembled device for biological sensing in terms of
3
the simplicity of use, assembly and operation costs, portability, and the overall
performance of measurements in selectivity, sensitivity, speed, and stability.
The characteristics of the biological recognition element are most important in
determining the biosensor’s performance in selectivity – the capacity to detect target
analytes without significant signal interference from non-target analytes – and
specificity – the capacity to only detect the target analyte in the presence of non-
target analytes13. The detection occurs either through a selective binding event,
such as an interaction of an antigen with an antibody, or through a selective reaction
such as that observed for enzymes and their substrates12. Sensitivity and sensor
measurement speed are usually inversely related due to the limiting rates of the
interactions taking place at the biological recognition layer. Finally, the biological
recognition element may undergo degradation and structural changes over time,
which affects stability and reusability. Immobilization of the biological component is
possible using a variety of approaches, including gel entrapment, adsorption,
membrane confinement, and chemical functionalization13. Meanwhile, the
technology that is used for the transducer limits the sensitivity and portability of the
biosensor. Technological improvements in transducer development can improve
sensitivity and allow for smaller sensor size for better portability. The transducer also
affects the speed of measurements made with the biosensor since some transducer
technologies take longer to work than others.
1.3 Acetylcholinesterase Inhibitors: The Target Analytes
AChE inhibitors are chemical or biological compounds that can interact with the
AChE enzyme to inhibit its function of breaking down ACh. A variety of chemical
structures show AChE-inhibiting activity. Several different categories of AChE
inhibitors exist, of which the most popular are the carbamates and
organophosphates for their applications in agriculture. The carbamate category
includes a variety of compounds that contain the carbamate ester functional group.
4
In contrast, organophosphate AChE inhibitors are ester derivatives of phosphoric
acid. The chemical structures of these two categories of inhibitors are shown below.
Figure 1.2. General chemical structures for the most popular categories of AChE inhibitors,
namely organophosphates (left) and carbamates (right).
The routes of entry for AChE inhibitors are through ingestion, absorption, and
respiration. The absorption of these compounds into the body results in the targeting
of AChE enzymes that exist in the muscle, blood, and nervous system14. As the
AChE inhibitor encounters an AChE enzyme, it usually interacts with the enzyme’s
catalytic site, which is located at the bottom of a deep and narrow gorge15. This
interaction can be irreversible with the covalent modification of a serine residue in
the catalytic site or can be reversible if the interaction is based on temporary affinity
binding. For example, the carbamate class of AChE inhibitors reacts with the serine
residue through a carbamylation reaction, which transfers the methylcarbamoyl ester
group to the serine. In contrast, the organophosphate class of AChE inhibitors
undergo a phosphorylation reaction with the same serine residue, leaving a
phosphate group attached.
Phosphorylation of the serine residue is not readily reversible without an antidote
such as 2-pralidoxime (2-PAM) and becomes permanent within 10 h of exposure as
“aging” – the process of dealkylation at the attached organophosphate’s R groups –
takes place16. In this process, the alkoxy-O-P bonds of the attached
organophosphate are broken and replaced with weaker hydroxy leaving groups
either through a general acid catalyzed nucleophilic substitution reaction or assisted
by stabilization of leaving groups by amino acids within the catalytic site of the
enzyme17. In contrast to what happens with organophosphates, a carbomylated
5
serine is very unstable and undergoes hydrolysis in a matter of hours to regenerate
the serine residue18.
Figure 1.3. Mechanisms involved in the action of paraoxon (an organophosphate AChE
inhibitor) and carbofuran (a carbamate AChE inhibitor) on AChE’s active site serine residue.
Apart from carbamates and organophosphates, other types of AChE inhibitors
include phenanthrene, piperidine, and indanone. Their mechanisms of action are
affinity-based with ionic and hydrogen bond interactions between functional groups
and amino acid residues in the catalytic site of AChE. In addition to the catalytic site,
the peripheral binding site exists near the entrance to the gorge that leads to the
catalytic site. It is another possible target for AChE inhibitors that function by
blocking the entrance of ACh to the enzyme’s catalytic site. Inhibitors that interact
with the peripheral site include small molecules such as propidium and also peptide
toxins like fasciculin15. Certain compounds have also been specifically designed for
medicinal purposes to interact weakly with both the catalytic site and peripheral
binding site, such as Donepezil for Alzheimer’s disease treatment.
6
The toxicity of AChE inhibitors to an organism varies depending on several factors
including the chemical structure of the inhibitor and the species variant of the AChE
enzyme exposed to the inhibitor. In general, AChE inhibitors that target the catalytic
site have a toxicity that is primarily determined by the conformational freedom of the
leaving group that is removed during the alkylation step and also by the inhibitor’s
hydrophobicity. These properties determine the accessibility of the catalytic site to
the inhibitor, since the catalytic gorge consists largely of hydrophobic amino acid
residues19. Variations in the DNA sequence encoding for the AChE enzyme between
different species can also make particular AChE enzymes more susceptible to
certain AChE inhibitors than others. This has been exploited for the production of
AChE mutants that can be applied for the purpose of AChE inhibitor detection with
some degree of selectivity for particular inhibitor structures.
1.4 The Biological Recognition Element
1.4.1 Acetylcholinesterase
The AChE enzyme has an asymmetric, usually globular ellipsoidal protein structure
that consists of a large central α/β-sheet core with 8 β-sheets that are connected to
one another by α-helices, which designates it structurally as a α/β-fold enzyme20.
This central core is surrounded by another 15 α-helices21. The primary function of
AChE is to break down the neurotransmitter ACh into choline (Ch) and acetate at
cholinergic synapses as indicated in the following equation
Figure 1.4. The AChE-catalyzed cleavage reaction of acetylcholine (ACh) into choline (Ch)
and acetate.
7
The AChE enzyme appears most abundantly in a tetrameric form with average
dimensions of 25 x 18 x 1.6 nm (~720’000 Å3)21. Each enzyme has an active site
volume of ~300 Å3 at the bottom of a ~20 Å deep hydrophobic gorge. The gorge is
lined with mostly aromatic amino acid residues along with a few acidic residues,
which are known to affect the affinity of AChE enzymes from different species to
their substrates and inhibitors20. Near the edge of this hydrophobic gorge lies an
anionic peripheral binding site, whose amino acid residues form an electric field that
attracts the cationic acetylcholine substrate into the gorge and down towards the
active site with the help of dipole-dipole interactions with the aromatic amino acid
residues20.
Figure 1.5. An illustration of the AChE enzyme’s structure for visualization purposes, with
the green area representing the active site and a yellow molecule shown occupying the
peripheral binding site. X-ray diffraction results showing the interaction of Thioflavin T with
electric eel AChE are available on the Protein Data Bank at the DOI: 10.2210/pdb2j3q/pdb
The AChE enzyme is classified as a serine hydrolase, with a catalytic triad present
at its active site that consists of serine, histidine, and glutamate amino acid residues.
The latter acidic residue is usually found to be aspartate in most serine hydrolase
enzymes. The aspartate residue stabilizes the histidine residue’s intermediate
imidazolium cation, which isolates the choline group of the natural substrate20. This
is followed by a hydrolysis reaction that cleaves off acetate. In addition to AChE’s
native function in modulating ACh concentrations in the nervous system, its other
functions include neuritogenesis, synaptogenesis, and amyloid-β complex
formation22.
8
1.4.2 Operation of the Biological Recognition Element
The biological recognition element of a biological sensor can contain sugars,
proteins (including enzymes such as AChE), nucleic acids, receptors, or entire cells.
The mode of action is classified as being either catalytic or affinity-based23. Catalytic
recognition is made possible by the selective affinity of enzymes for their substrates.
When the enzymes are activated or inhibited, the quantity of product made over time
changes and the difference can be measured24. Furthermore, enzymes can be
involved in transforming the target analyte as a substrate into a different measurable
product. An example of catalytic recognition applied for AChE inhibitor detection is
the use of organophosphorous hydrolase (OPH), an enzyme that breaks P-O bonds
of organophosphate compounds to make alcohol and acid products25. These
products can then be detected with a variety of transducers.
P
O
O
O
O
+ H2O +R3
OHR3
R1
R2
P
HO
O
O
O
R1
R2
OPH
Figure 1.6. General reaction scheme of an organophosphate compound with the OPH
enzyme.
Affinity-based recognition involves the irreversible and non-catalytic binding of a
target species to the biological recognition element23. Affinity-based recognition of
AChE inhibitors has traditionally been achieved with immunoassays by using
antibodies that have affinity for certain inhibitor compounds. In the first research
project described in this document, catalytic-based recognition was applied for the
detection of AChE inhibitors using the AChE enzyme.
In order to understand the processes taking place at the catalytic-based biological
recognition element, enzymes are modelled with fundamental enzyme kinetics and
Michaelis-Menten kinetics in mind. The observed initial rate of reaction depends on
the concentration of the substrate (S), enzyme (E), and the Michaelis (KM) and
9
dissociation (kd) constants respectively. The constants reflect the relative rates of
substrate-enzyme association/dissociation and product formation.
As product P is created through the enzyme catalyzed reaction, there is an initial
linear relationship between the change in product concentration d[P] and time.
However, as [S] decreases and [P] increases, the rate of enzyme activity decreases
due to a lack of saturation of the enzyme by substrate and/or competitive inhibition
due to the affinity of the product to the enzyme’s active site. Therefore, depending
on how an enzyme-based biosensor is calibrated in terms of incubation times with
the substrate, different types of responses can be obtained for the same measured
phenomenon. This is complicated when AChE is the chosen enzyme since AChE
inhibitors may also be substrates of AChE. Furthermore, some AChE inhibitors
permanently inhibit the enzyme (organophosphates), some do so temporarily
(carbamates), and yet others simply compete with ACh for the catalytic site.
There are also some subtle details about the structure and function of enzymes that
affect biosensor measurements. Very low concentrations of inhibitors can
sometimes tend to activate instead of inhibit AChE. This is likely due to interactions
of the inhibitors with the peripheral binding site of AChE, causing conformational
changes that improve accessibility of the active site. These interactions also appear
to be time-dependent, with prolonged peripheral site binding leading to decreased
accessibility of substrates to the active site26. The effectiveness of AChE inhibitors
decreases with increasing concentrations of the inhibitors due to the development of
steric blockades around the entrance to the enzyme active site27. These facts
explain the wide variety of possible output responses, linear and non-linear,
10
obtained from different biosensor designs that use various concentrations of enzyme
and substrate along with different incubation times.
Realizing the need for a standardized approach to achieving linear sensor
responses in the design and calibration of AChE-based AChE inhibitor biosensors,
Zhang et al.28 recommended that AChE and its substrate should exist at
concentrations that ensure the rate of product formation is not contingent on
substrate concentration. In this case, kinetically controlled conditions would be
maintained. The substrate should saturate the enzyme (i.e. [S] >> KM) to ensure that
it operates with zero-order kinetics29. In contrast, the incubation of AChE with
inhibitors in the experimental sample should take place under diffusion controlled
conditions, so that the enzymes are not saturated by the inhibitors at any time. If
saturation of AChE occurs during this step, the rate of inhibition is no longer linearly
dependent on inhibitor concentration since there is competition between inhibitor
molecules for access to the enzyme active site.
Figure 1.7. Schematic of diffusion controlled conditions (a), where diffusion of substrate to the enzyme determines the rate of reaction, unlike kinetic controlled conditions (b), where the enzymes are saturated and working as fast as they can. Sometimes, in kinetically controlled conditions, steric hindrance of the substrates near the active site can slow the exit of the enzyme product, thus decreasing the aggregate rate of reaction.
The suggested standardized approach by Zhang et al.28 may not necessarily work
for all different types of enzymes that may appear at the biological recognition
11
element. In general, enzyme interactions with the target analyte that is being
quantified should take place under diffusion controlled conditions to ensure linearity
in sensor response. Saturation of the enzyme by the analyte creates a situation
where not all of the analyte molecules have an opportunity to interact with the
enzyme during the incubation step. However, when the enzyme-catalyzed reaction
is used strictly to amplify the biosensor signal, kinetic controls are necessary to
ensure that the enzymes are consistently creating products for maximum biosensor
signal response. Without kinetic control, inhibited enzymes may not even have any
significant impact on overall product formation during the incubation step with their
substrate. Under kinetic controls, all of the enzymes work throughout the substrate
incubation step and a decrease in product due to enzyme inhibition will be more
visible. In practice, saturation of the enzyme at the biological recognition layer leads
to kinetic control but, if too much substrate is present, reaction rates decrease due to
the presence of steric blockades at the enzyme active sites.
1.5 Literature Review of Acetylcholinesterase Inhibitor Detection
The use of NMR and mass spectrometry is a well-established analytical approach
for the detection and identification of AChE inhibitors. However, detection
techniques which are faster, cheaper, and portable have been developed over the
past thirty years. In the early-to-mid 1980s, immunoassays had come into popularity
and some antibodies had been developed for certain AChE inhibitors, such as
soman and paraoxon, either directly or as a part of haptens when the inhibitor
molecules are too small to be recognized by antibodies on their own10, 30. Using a
competitive inhibition enzyme immunoassay format, Hunter et al.10 showed that it
was possible to detect paraoxon in low-ppb ranges both in solution and in serum.
Detection usually involves the enzyme-linked immunosorbent assay format or an
assay featuring fluorescent- or chemiluminescent-tagged antibodies31. Currently,
research is ongoing to produce recombinant antibodies for a variety of small
molecules such as AChE inhibitors, although the overall number of useful antibodies
remains low to this day. Unfortunately, the impressive detection abilities of
12
immunoassays also usually require multiple preparation steps and a long incubation
times that require multiple hours to complete11. However, it has been recently shown
that immunoassays can actually be used to detect AChE inhibitors in as little as 10
min and in a single step but with somewhat higher detection limits nearing 250 ppb.
This was accomplished by Zhou et al.32 in the form of a gold
immunochromatographic assay using carbofuran monoclonal antibodies labelled
with colloidal gold particles. Although this detection limit is not as low as other more
sophisticated sensing platforms, this immunoassay approach is sufficient to test for
toxic levels of many AChE inhibitors. It would also be useful to test for regulatory
compliance in the United States, where AChE inhibitor concentrations are regulated
to be in the mid-ppb to low-ppm ranges9. Further developments of this type of
immunochromatographic technique may also improve detection limits in the near
future, such as with silver enhancement of the gold nanocolloid, which allows for
double labelling of the same antibody31. Thus, the application of rapid
immunoassays for AChE detection is not an idea that should be readily dismissed.
There remains an overall scarcity of useful antibodies that respond to AChE
inhibitors even to this day. Once this scarcity is addressed, the usefulness of
immunoassay techniques will be better recognized.
The slow detection times of traditional immunoassay techniques existing in the
1980s drew attention to the exploration of other biological recognition and
transduction approaches for the detection of pesticides including AChE inhibitors. At
about the same time as immunoassays were being developed for this purpose,
research groups were beginning to apply the AChE and organophosphate hydrolase
(OPH) enzymes as the biological recognition elements coupled with a variety of
common transducers in optical, electrochemical, and mass-sensitive sensor
designs. OPH is an enzyme that only breaks down organophosphate compounds
into an alcohol and an acid, both of which are more useful for transduction purposes
than the original triester compounds themselves25. In the literature, there are many
peer-reviewed articles that document research on AChE inhibitor detection featuring
AChE and OPH. Furthermore, excellent efforts have been made to develop methods
13
of preserving enzyme activity over time so that the potential biosensors would have
a substantial shelf life on the order of months to years.
Sensors featuring optical transduction mostly rely on the interaction of an indicator
or sensor surface either directly with the analyte or indirectly with other species in
the sensor environment that can report on analyte concentrations. Sensing occurs
when resulting changes in absorbance or fluorescence are detected. Optical
transduction systems are very diverse and include many flavours of absorbance,
bioluminescence, chemiluminescence, evanescence and fluorescence33. In 2005,
White and Harmon demonstrated that portable and rapid optical solid-state detection
of organophosphates was feasible using OPH immobilized on glass microscope
slides with detection limits in the ppt-range and detection times of 10 seconds34. This
technique featured monitoring the absorbance of copper metalloporphyrins that
interact with the OPH enzyme and get displaced by trace concentrations of the
organophosphate substrates. A similar concept using AChE was applied by
Nagatani et al.35 where 5,5 dithiobis-2-nitrobenzoic acid was converted through a
reaction with thiocholine into 5 -mercapto-2-nitrobenzoic acid, where the latter
chemical compound was detected optically as a yellow dye that absorbed light at
410 nm. In the presence of AChE inhibitors, AChE would produce fewer thiocholine
molecules from its cleavage of acetylthiocholine (ATCh) substrate, producing lower
concentrations of the yellow dye. This approach allowed for visual discrimination
between 0.1 and 0.2 ppm DZN-oxon and down to the low-ppb range with a hand-
held photometer. More recently in 2007, Vamvakaki and Chaniotakis36 applied
liposomes to trap AChE and a pH-sensitive fluorescent dye called pyranine while
allowing the transport of ACh and AChE inhibitors through porins in the liposome. In
the presence of AChE inhibitors, AChE activity decreased inside the liposomes and
pyranine fluorescence decreased. Using this approach, detection limits in the mid-
ppq range were established with measurement times in as little as 5 min. Then, in
2009, Dale and Rebek37 achieved millisecond detection times without a biological
recognition element, opting instead to use oxime ring chemistry to detect
organophosphate nerve gas agents at ppm levels and lower. The presence of
organophosphates produces a ring-closing reaction that red shifts oxime
14
fluorescence maxima by 30 nm. This sensor has excellent potential to be used for
real-time personnel monitoring in hazardous conditions where AChE inhibitors may
be present.
The use of semiconductor nanoparticles (quantum dots) for AChE inhibitor detection
has also just recently been realized as biosensor research continued to develop
through 2003. Quantum dots are desirable for use in optical detection systems due
to their resistance to photo-bleaching, their wide excitation wavelength ranges, and
narrow size-dependent emission wavelengths that allow for multiplexing applications
when compared to conventional fluorescent dyes31. An excellent review of quantum
dots and their applications in optical detection systems can be found in the cited
literature12, 38. Using quantum dots functionalized with OPH, Constantine et al.39
found that paraoxon’s binding with OPH resulted in changes in quantum dot
photoluminescence. This type of biosensor yielded detection limits in the low ppb-
range for paraoxon almost instantly upon introduction of the sample to the quantum
dots as the OPH underwent conformational changes. However, more development
is required to improve selectivity of this type of sensor by experimenting with
different quantum dot coatings, possibly changing the structural properties of OPH
or replacing OPH with other biomolecules that interact with AChE inhibitors31.
However, quantum dots are definitely not limited to use with optical transduction,
since they are also applicable in electronic transduction systems due to their
capacity for electron exchange. Quantum dots have also been shown to be useful in
photoelectrochemical transduction designs in AChE inhibitor biosensors. Pardo-
Yissar et al.40 used AChE-derivatized quantum dots that were then covalently linked
to a gold electrode surface to create a photoelectrochemically active biosensor that
responds to thiocholine. Thiocholine interacts with the quantum dots, enabling them
to produce a stable photocurrent upon excitation by wavelengths of light in their
absorption band. In the presence of AChE inhibitors, tested in the ppm-range for this
sensor, less thiocholine was produced and the photocurrent decreased significantly.
Although the detection limit was not reported in this study, it is nevertheless a very
unique application of quantum dots and nanomaterials towards the detection of
AChE inhibitors.
15
Continuing on the topic of nanomaterials, the growth processes of nanoparticles
have also been utilized in biosensor designs for the detection of AChE inhibitors.
When AChE breaks ATCh into thiocholine, the latter product’s presence apparently
serves to slow the growth of gold-silver nanoparticles originating from the deposition
of silver on seed gold nanoparticles in the presence of a reducing agent such as
ascorbic acid. Thiocholine binds to the seed gold nanoparticle surface and blocks
the access of silver atoms to the gold nanoparticle surfaces. In the presence of
AChE inhibitors, less thiocholine is produced by AChE and an increase in the rate of
nanoparticle growth is seen. Virel et al.41 applied this observation to make a
biosensor using a colorimetric assay measuring absorbance at 400 nm for the gold-
silver nanoparticle plasmon band. AChE inhibitors such as paraoxon were tested
and detected in low ppb-levels in a matter of 5-10 min. A similar system in which
osmium complexes are made to play a role in gold nanoparticle growth was realized
by Xiao et al.42. When AChE cleaved ACh into Ch, this allowed for the reduction of
an oxidized osmium complex through the concurrent oxidation of Ch into betaine.
The reduced osmium complex promotes nanoparticle growth. The presence of
AChE inhibitors decreased the production of choline, the necessary reducing agent
to regenerate the required osmium complex, subsequently slowing nanoparticle
growth42.
Interesting work has also been conducted using carbon nanotubes (CNTs) for
application in biosensor design. CNTs represent a nanomaterial with many possible
applications in sensor design due to their large surface area, electrical conductivity,
stability, self-assembly, and capacity for surface modifications. CNTs have mostly
found applications in sensors using electric and electrochemical transduction
schemes, the latter of which will be introduced later in this document after a primer
introduction to electrochemical transduction. As of yet, there are very few notable
cases that are not related to electrochemical transduction where CNTs were applied
for the detection of AChE inhibitors, such as with the sensor developed by Ishii et
al.43 that features afield effect transistor (FET)- based AChE inhibitor biosensor
using AChE immobilized on carbon nanotubes. This biosensor exploits the fact that
CNTs are useful as semiconductor materials. When AChE inhibitors bind to the
16
immobilized enzymes on the CNT surface, the effective potential at the surface of
the CNTs is changed and can be detected through the source-drain current in the
microampere range. With an incubation time of 10 min, the sensor could achieve
detection limits of 200 ppq, which makes it one of the most sensitive devices for
measuring the presence of the AChE inhibitors acephate and fenitrothion.
Mass-sensitive transduction schemes have also been applied for the purpose of
AChE inhibitor detection. These include piezoelectric transducers and surface
plasmon resonance transducers (both the standard and localized varieties).
Piezoelectric transducers feature materials, such as quartz, which respond to
mechanical stresses by producing an electric potential that can be detected,
amplified and analyzed as a quantitative signal. A good example of an AChE
inhibitor biosensor using a piezoelectric transducer is the precipitation biosensor
reported by Kim et al.44 in 2007. A quartz crystal microbalance was used with a gold
modified quartz surface, which allowed for the immobilization of AChE in close
proximity to the surface via a sulphur-tagged linker. The substrate used was 3-
indolyl acetate, which is cleaved into 3-hydroxyindole by AChE. This product
oxidizes into a blue precipitate that settles onto the quartz surface and thus creates
a shift in the resonance frequency detected on the microbalance. Using this sensor
configuration, Kim et al.44 achieved mid-ppt to low-ppb detection limits for carbofuran
and EPN in 10 min. In contrast to piezoelectric transduction, surface plasmon
resonance (SPR) relies on the sensitivity of surface plasmons to changes in the
refractive index of bulk solution (or air) within nanometers of the metal surface45.
Using SPR, Rajan et al.46 developed a flow-based sensor that detected binding
events of an AChE inhibitor with AChE that was immobilized on the silver core of a
plastic-cladded silica optical fiber. In the presence of acetylcholine substrate, the
introduction of chlorphyrifos changed the refraction index in the vicinity of the silver
core and thus led to changes in the SPR wavelength. This effect was believed to be
occurring due to expulsion of acetylcholine from the AChE active site. This approach
led to detection limits in the low-ppb range in less than 10 min. Using a similar flow-
based SPR approach and similar measurement timelines, Mauriz et al.47 obtained
17
ppt-range detection limits for chlorphyrifos by replacing AChE with anti-chlorphyrifos
antibodies.
In closing of this literature review on AChE inhibitor biosensor designs, it is worth
mentioning the application of photothermal transduction for the purpose of detecting
AChE inhibitors due to the distinct characteristics of the transduction method, which
measures temperature changes in samples. Using an argon ion laser, Pogacnik et
al.48 irradiated thiocholine and measured the temperature change of the sample to
give an indication of existing AChE activity versus control experiments. The
presence of AChE inhibitors in a sample would decrease AChE activity. This would
in turn lead to lower amounts of thiocholine in solutions and lower detected changes
in temperature versus controls. With this approach, it was possible to achieve
detection of low-ppb ranges of AChE inhibitors in 6 min with excellent matching to
real sample concentrations detected by GC-MS measurements. Although the
thermal lens spectrometer required for these measurements is quite bulky, there is
definitely room for miniaturization as current portable models come in the size of a
suitcase (15 cm x 10 cm x 3 cm) containing all of the components including laser
diodes and bioanalytical column49. This type of biosensor would be most applicable
to work with samples that do not require substantial preparation steps, such as river
water, since foodstuffs typically require lengthy procedures including pureeing and
centrifugation prior to injection into the bioanalytical column of the biosensor.
It is evident from this brief literature review that many different biosensor designs
exist for the purpose of detecting AChE inhibitors. These rely on a variety of different
transduction schemes but many share the common biological recognition element
that is the AChE enzyme or OPH enzyme. These enzymes allow for limited
specificity in a biosensor given that OPH responds to organophosphates whereas
AChE is inhibited by AChE inhibitors. However, the enzymes are also affected by
their solvents, pH, ionic strength, and proteases existing in solution that degrade the
enzyme protein structure. This is critical when such biosensors are tested using real
samples as it can lead to questions about the reliability of the devices for on-field
use. It is not surprising then that very few (~20%) peer-reviewed academic papers
18
describing biosensors for AChE inhibitors include any real sample analyses in their
research reports50. Furthermore, where the enzymes can be demonstrated to work
as intended in real samples, they cannot distinguish between different
organophosphates or AChE inhibitors in any given unknown sample. The activity of
OPH only indicates the presence of any solvated organophosphate substrates
whereas loss of AChE activity only indicates the presence of some kind of AChE
inhibitor. Thus, in real samples where the identity of AChE inhibitors present in
solution is unknown, the sensor output has very limited value beyond indicating that
some species are present that interact with the enzyme at the biological recognition
element. Composite samples containing more than one type of AChE inhibitor would
require additional modifications to a biosensor in order for the device to provide
meaningful information about the individual components. Some attempts have been
made to achieve this through favourable modification of enzyme conformation.
Using directed evolution and amino acid substitutions, it is possible to isolate AChE
mutants that are more or less sensitive to particular AChE inhibitor species. For
example, Bachmann et al.51 created genetically engineered variants of the
Drosophila melanogaster AChE enzyme, which they subsequently applied in the
development of an artificial neural network (ANN) that could identify the component
concentrations of composite solutions of paraoxon and carbofuran. The ANN
processed collected readings from four different D. melanogaster AChE enzymes to
predict the individual concentrations of paraoxon and carbofuran in each sample
solution. The group succeeded in establishing a detection range between 0-5 ppb
for each compound with ~10% prediction error.
In the research described within this document, electrochemical transduction was
utilized along with AChE as the biological recognition element. This research
direction is not meant to reflect a particular bias for electrochemical techniques or
the biological recognition element, since the variety of options reported in this
literature review have all shown very impressive capabilities for AChE inhibitor
detection. It serves as a contribution to our current understanding of electrode
surface modifications and explores a new way of monitoring AChE inhibitors through
19
the oxidation of molecules that weakly intercalate with AChE. This is described in
further detail in Section 1.8.
1.6 Electrochemical Transduction: Voltammetry
This primer on electrochemical transduction was assembled based on the reference
material presented in an excellent introductory book to electrochemistry techniques
called Analytical Electrochemistry by Joseph Wang 52. Readers who wish to become
more familiarized with electrochemistry as it applies to chemical and biological
sensors are encouraged to consult this resource in the cited literature. In addition,
the electrochemistry scholar seeking a thorough understanding of electrochemical
techniques may refer to Alan J. Bard’s and Larry R. Faulkner’s book Electrochemical
Methods: Fundamentals and Applications53. The use of electrochemical transduction
offers the benefits of low costs, short measurement times, and an excellent potential
for the miniaturization and portability of the final assembled biosensor24.
Electrochemical transduction is not affected by the turbidity of sample solutions,
which is a major problem in the application of optical transduction platforms to such
samples54. Furthermore, the transduction process is relatively simple compared to
other technologies. In addition to the sample being analyzed, the components
required for electrochemical transduction include an electrode system, a voltage
source, and a potentiostat to collect electrical measurements. The electrode system
usually consists of three electrodes: working, reference, and counter. There are
many forms of electrode systems that are available in a variety of shapes and sizes
of which two were used in the research described herein: rod-shaped individual
electrodes and screen-printed electrodes.
Electrochemical transduction involves the monitoring of redox (reduction-oxidation)
reactions at the working electrode surface under various conditions of applied
potential from the voltage source. In general, a redox reaction at the electrode
surface involves the transfer of electrons to and from the members of the redox
species at a particular value of applied potential as described by the Nernst
equation,
where
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
oxidized analyte concentration and C
The current observed at the applied potential depends on the flu
(O) or reduced (R)
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
C(x,t) is the concentration
added to negate flux due to a potential gradient and the sample solution is not
stirred during
After addressing the
diffusional flux, current can eventually be expressed through the Cottrell equation
(given here for a planar
where
applied past and above the value of E
become depleted and a diffusion layer
called
on the x
exists within 59 mV of E
solution over the voltage scanning period
where Eo is the standard redox potential for the redox reaction,
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
oxidized analyte concentration and C
The current observed at the applied potential depends on the flu
(O) or reduced (R)
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
represents the concentration gradient,
C(x,t) is the concentration
added to negate flux due to a potential gradient and the sample solution is not
stirred during the
After addressing the
diffusional flux, current can eventually be expressed through the Cottrell equation
en here for a planar
here A is the area of a planar electrode (in cm
applied past and above the value of E
become depleted and a diffusion layer
called a voltammogram
on the x-axis. The result of the sweep is a
exists within 59 mV of E
olution over the voltage scanning period
is the standard redox potential for the redox reaction,
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
oxidized analyte concentration and C
The current observed at the applied potential depends on the flu
(O) or reduced (R) analyte to the electrode surface,
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
represents the concentration gradient,
C(x,t) is the concentration
added to negate flux due to a potential gradient and the sample solution is not
the measurement
After addressing the mathematical expression for the
diffusional flux, current can eventually be expressed through the Cottrell equation
en here for a planar electrode):
A is the area of a planar electrode (in cm
applied past and above the value of E
become depleted and a diffusion layer
voltammogram can be plotted with current
The result of the sweep is a
exists within 59 mV of Eo, demonstrating the oxidation of reduced species existing in
olution over the voltage scanning period
is the standard redox potential for the redox reaction,
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
oxidized analyte concentration and C
The current observed at the applied potential depends on the flu
analyte to the electrode surface,
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
represents the concentration gradient,
C(x,t) is the concentration of O or R at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
measurement, only diffusion plays a role in determining the flux.
mathematical expression for the
diffusional flux, current can eventually be expressed through the Cottrell equation
electrode):
A is the area of a planar electrode (in cm
applied past and above the value of E
become depleted and a diffusion layer
can be plotted with current
The result of the sweep is a
, demonstrating the oxidation of reduced species existing in
olution over the voltage scanning period
is the standard redox potential for the redox reaction,
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
oxidized analyte concentration and CR is the initial reduced analyte concentration.
The current observed at the applied potential depends on the flu
analyte to the electrode surface,
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
represents the concentration gradient,
at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
, only diffusion plays a role in determining the flux.
mathematical expression for the
diffusional flux, current can eventually be expressed through the Cottrell equation
A is the area of a planar electrode (in cm
applied past and above the value of Eo, the reduced species at the electrode surface
become depleted and a diffusion layer of redox
can be plotted with current
The result of the sweep is a voltammogram with a current
, demonstrating the oxidation of reduced species existing in
olution over the voltage scanning period. At a constant applied potential or with a
is the standard redox potential for the redox reaction,
electrons involved in the redox reaction per molecule, F is
is the universal gas constant, T is the Kelvin scale temperature, C
is the initial reduced analyte concentration.
The current observed at the applied potential depends on the flu
analyte to the electrode surface,
where D represents the diffusion coefficient for the analyte (in cm
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
represents the concentration gradient, is the potential gradient, and
at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
, only diffusion plays a role in determining the flux.
mathematical expression for the
diffusional flux, current can eventually be expressed through the Cottrell equation
A is the area of a planar electrode (in cm2). When a pote
, the reduced species at the electrode surface
redox species is
can be plotted with current (I) on the y
voltammogram with a current
, demonstrating the oxidation of reduced species existing in
. At a constant applied potential or with a
is the standard redox potential for the redox reaction, n is the number of
electrons involved in the redox reaction per molecule, F is the Faraday constant,
is the universal gas constant, T is the Kelvin scale temperature, C
is the initial reduced analyte concentration.
The current observed at the applied potential depends on the flux (J)
where D represents the diffusion coefficient for the analyte (in cm2/s), z is the charge
of the redox active species, V(x,t) is the hydrodynamic velocity in the x
is the potential gradient, and
at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
, only diffusion plays a role in determining the flux.
mathematical expression for the time-dependence of the
diffusional flux, current can eventually be expressed through the Cottrell equation
When a pote
, the reduced species at the electrode surface
species is established.
on the y-axis and potential
voltammogram with a current
, demonstrating the oxidation of reduced species existing in
. At a constant applied potential or with a
n is the number of
the Faraday constant,
is the universal gas constant, T is the Kelvin scale temperature, CO is the initial
is the initial reduced analyte concentration.
(J) of the oxidized
/s), z is the charge
of the redox active species, V(x,t) is the hydrodynamic velocity in the x-direction,
is the potential gradient, and
at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
, only diffusion plays a role in determining the flux.
dependence of the
diffusional flux, current can eventually be expressed through the Cottrell equation
When a potential sweep is
, the reduced species at the electrode surface
established. A graph
axis and potential
voltammogram with a current peak that
, demonstrating the oxidation of reduced species existing in
. At a constant applied potential or with a
20
n is the number of
the Faraday constant, R
is the initial
is the initial reduced analyte concentration.
oxidized
/s), z is the charge
direction,
is the potential gradient, and
at a particular position and time. If excess salt is
added to negate flux due to a potential gradient and the sample solution is not
, only diffusion plays a role in determining the flux.
dependence of the
diffusional flux, current can eventually be expressed through the Cottrell equation
ntial sweep is
, the reduced species at the electrode surface
A graph
axis and potential (V)
peak that
, demonstrating the oxidation of reduced species existing in
. At a constant applied potential or with a
21
linear potential sweep, the area of this peak can be used to quantify the
concentration of the analyte in solution. However, in many applied electrochemical
experiments, including the ones performed in the described research, non-linear
potential sweeps were applied to produce peaks that cannot be theoretically linked
to analyte concentration. However, this is a trade-off for sharper and more distinct
peaks than seen in linear potential sweeps. This is the case for the technique of
differential pulse voltammetry (DP Voltammetry), which involves the application of
pulsed potentials superimposed on a linear potential sweep. Current is recorded just
before and right after the pulse is applied so as to allow background charging
processes at the electrode surface that are unrelated to the presence of analyte in
solution to be completed first, thus decreasing measurement noise. The resulting
voltammogram yields peaks whose height rather than area is directly proportional to
analyte concentration,
where σ is and ∆E is the pulse amplitude. The peak potential, Ep, is related
to the polarographic half-wave potential E0.5 by
Inorganic compounds, such as the model ferri-ferrocyanide redox couple, are found
to yield reproducible oxidation and reduction peaks theoretically separated by 59
mV. With cyclic, linear potential sweeps, the peak currents appear proportional to
the square-root of the scan rate (in V/s). The application of potential sweeps,
whether linear or not, to organic molecules usually yields peaks that are not
reversible. An oxidation sweep on organic molecules usually yields peaks that do
not have a symmetrical matching peak in a subsequent reduction sweep and vice
versa. This property usually extends for most biological molecules including
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