Turkish Journal of Biology
Turk J Biol
(2016) 40: 1303-1310
© TÜBİTAK
doi:10.3906/biy-1602-40
http://journals.tubitak.gov.tr/biology/
Research Article
Construction of an oxygen detection-based optic laccase biosensor for polyphenolic
compound detection
1
1
2
2,3
1,4,
2
Kadir BİLİR , Marie-Theres WEIL , Julia LOCHEAD , Fatma Neşe KÖK *, Tobias WERNER
Molecular Biology-Genetics and Biotechnology Program (MOBGAM), İstanbul Technical University, Maslak, İstanbul, Turkey
2
Institute of Analytical Chemistry, Faculty of Biotechnology, University of Applied Sciences, Mannheim, Germany
3
Institute for Pharmacy and Molecular Biotechnology, Heidelberg University, Heidelberg, Germany
4
Department of Molecular Biology and Genetics, İstanbul Technical University, Maslak, İstanbul, Turkey
Received: 11.02.2016
Accepted/Published Online: 25.04.2016
Final Version: 16.12.2016
Abstract: A fiber optic biosensor was constructed from Pleurotus ostreatus laccase for the detection of polyphenolic compounds.
Laccase was immobilized on the surface of the commercially available fiber optic oxygen sensor spots by using 3-aminopropylsilanetriol,
glutaraldehyde, and amino-modified carboxycellulose. A diffusion layer containing tetramethyl orthosilicate (TMOS),
trimethoxymethylsilane (Tri-MOS), and polyvinyl alcohol (PVA) was added to the immobilized laccase layer. The consumption of
oxygen as a result of laccase activity was monitored using a fiber optical measuring setup with catechol as a model substrate. The optimal
enzyme amount was determined as 1.5 mg per 50 µL of enzyme layer mixture, and with one diffusion layer and at pH 6.9, optimum
detection conditions were attained. The biosensors have high reproducibility, stability (at least 85 days if stored in PBS at 4 °C), and
convenient measurement duration (ca. 25 min between two successive measurements). The biosensor was found to have a broad linear
working range for catechol (40–600 µM) and to be applicable to a flow-through system. In summary, an easy-to-produce, reproducible,
and stable laccase sensor with a broad linear working range was produced. The sensor has potential in the food industry as well as in
environmental monitoring for the detection of phenolic compounds.
Key words: Laccase biosensor, phenolic compounds, catechol, oxygen-based optic sensor
1. Introduction
Detection of polyphenolic compounds has been drawing
attention both in the environmental control of toxic
contaminants (side products of industrial and agricultural
processes) and in food quality analysis (Moccelini et
al., 2008; Barrosso et al., 2011; Prehn et al., 2012; Singh
et al., 2012; Neoh et al., 2013). Detection could be done
by various methods involving spectrophotometry, gas
and liquid chromatography, electrochemical methods,
and capillary electrophoresis (Karim and Fakhruddin,
2012; Alshahrani et al., 2014). Both spectrophotometry
and chromatography, however, need time-consuming
pretreatment steps. In addition, spectrophotometry
is prone to interference and chromatography requires
expensive instruments and is not suitable for on-site
detection (Karim and Fakhruddin, 2012; Alshahrani et
al., 2014). These limitations make the design of a portable
device that does not require pretreatment steps inevitable
for rapid on-site monitoring of phenolic compounds and
biosensors are attractive candidates for this purpose.
*Correspondence: [email protected]
In food analysis, laccase (Rahman et al., 2008; DiFusco
et al., 2010), tyrosinase (Kim et al., 2009; Cortina-Puig
et al., 2010), and peroxidase (Mello et al., 2005) enzymes
have been used to detect different phenolic compound
of natural origin such as chlorogenic acid (Moccelini
et al., 2008), catechin (Rahman et al., 2008), caffeic acid
(Cortina-Puig et al., 2010), or food additives like propyl
gallate (Morales et al., 2005). The majority of currently
available sensors for phenolic compound monitoring
are based on electrochemical principles (Barrosso et al.,
2011). One disadvantage of these sensors is their limited
electrochemical selectivity because of the electrooxidation
of species other than the target phenolic compound. In
contrast to electrochemical biosensors, fiber optic sensors
have extremely selective transducers whose signals are not
disturbed by diverse interferences. They also do not have
direct interference from surrounding electric or magnetic
fields because their signal is optic (Mazhorova et al., 2012;
Narsaiah et al., 2012). Fiber optics are self-sufficient and do
not require an external reference signal as electrochemical
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biosensors do (Shaikh and Patil, 2012). Laccases belong to
the blue-copper family of oxidases and have been widely
used in biotechnological applications ranging from textile
and food industries to fuel cell applications (RomanGusetu et al., 2009; Arora and Sharma, 2010; Tastan et al.,
2011; Andreu-Navarro et al., 2012; Betancor et al., 2013).
They could oxidize different substrates with the reduction
of oxygen to water, without hydrogen peroxide generation.
In this study, the aim was to construct a reliable and
easy-to-use laccase biosensor based on a fiber optic system
for on-site detection of phenolic compounds. The principle
of detection was based on the emission of luminescence
from oxygen-sensitive dyes contained in sensor spots.
After excitation, when the luminescent dyes encounter an
oxygen molecule, the excess energy is transferred to that
molecule through a process called dynamic quenching
(Figure 1). The light emission intensity of the sensor spot
is decreased (fewer excited dyes emit photons) as well as
the average excitation lifetime (many dyes reach ground
level rapidly). The relationship between the excitation
lifetime and the oxygen concentration is quantified by the
Stern–Volmer relationship (Carraway et al., 1991). For
precise referencing, the phase modulation technique is
applied (Trettnak et al., 1996). The sensor spot is excited
with sinusoidally modulated light from a light-emitting
diode and therefore the emitted light is also sinusoidally
modulated. The average excitation lifetime is then detected
as the phase angle between these two light emissions. To
construct a biosensor for polyphenol detection, laccase
from Pleurotus ostreatus was immobilized on planar oxygen
sensor spots (SP-PSt3) using 3-aminopropylsilanetriol
(APST) for surface activation, glutaraldehyde (GA) as
a cross-linker, and amino-modified carboxycellulose
(AMC) to form a mechanically stable matrix. Thereafter,
optimum construction and working conditions, e.g.,
reproducibility, measurement duration, response time,
repeatability of response, dynamic working range,
storage stability, and applicability, were investigated.
Flow-through oxygen minisensors (FTC-PSt3) were also
prepared to develop a stable, reproducible laccase sensor
for continuous detection of phenolic compounds. The
construction method is easy and rapid and the resulting
easy-to-use biosensor could allow on-site detection
of phenolic compounds in the food industry and the
environment. The fiber optic system offers flexibility to
the design, which allows for multiple sample detection
or adaptation to flow-through systems and so could be
explored for different applications. Optic measurements,
especially fluorescence measurements, generally require
nonturbid, clear solutions and simple matrices; if not,
the signal intensity is affected. The proposed detection
method, however, involves the use of oxygen-sensitive
dye attached to a fiber optic cable. In this system, the optic
signal is formed on the biosensor surface depending on
oxygen concentration and is transferred directly to the
detector through fiber optics so the fluorescent signal will
not be affected by the turbidity of the solution.
2. Materials and methods
2.1. Materials
The fiber-optic oxygen sensors and transmitters were
purchased from PreSens Precision Sensing GmbH
(Regensburg, Germany). Laccase (EC 1.10.3.2 from
Pleurotus ostreatus, ≥4.0 U/mg) and freshly prepared
catechol (on a weekly basis) were obtained from SigmaAldrich. 3-Aminopropylsilanetriol was purchased from
Degussa AG Aerosil & Silanes, glutaraldehyde from Carl
Roth, and tetramethyl orthosilicate (TMOS), 2-propanol,
and trimethoxymethylsilane (Tri-MOS) from Fluka.
Figure 1. Detection of mechanism of the oxygen detection-based optic system: the emission of luminescence
from oxygen-sensitive dyes contained in sensor spots depends on the amount of oxygen in the environment.
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BİLİR et al. / Turk J Biol
Mowiol was obtained from Kuraray and glycerol from
Carl Roth.
2.2. Methods
2.2.1. Activity determination of laccase
The immobilized laccase activity was determined
spectrophotometrically in 0.1 M sodium acetate buffer
(pH 5) containing catechol (50 mM) or 2,2’-azino-bis(3ethylbenzothiazoline-6-sulfonic acid) (ABTS) (5 mM)
as the substrate at 404 nm (for catechol) or 414 nm
(for ABTS) at room temperature. Laccase-immobilized
sensor spots were fixed into cuvettes with silicone glue.
All measurements were run in parallel with a negative
control containing no enzyme. The value of the extinction
coefficient for the oxidized products of catechol is 740 M–1
cm–1 and for ABTS it is 36,800 M–1 cm–1.
2.2.2. Construction of the laccase-immobilized SP-PSt3
sensor spots
2.2.2.1. Preparation of amino-modified cellulose
Ten grams of carboxycellulose (CC) was washed for
1 h with 200 mL of Millipore filtered deionized water
containing 5 g of sodium chloride. After that, CC was
vacuum filtered and a second wash was carried out with
200 mL of deionized water (Millipore) for another hour.
After the vacuum filtration, a last wash was done for 1 h
using 70% ethanol. The filtered CC was then resuspended
in 200 mL of deionized water. To obtain amino-modified
CC, 4 g of ethylenediamine-dihydrochloride (EDD) was
added into CC solution in small portions under continuous
stirring. Ten minutes later, 350 mg of carbodiimide (EDC)
was added and the pH was set to 4.6 by the addition of
0.1 M hydrochloride acid. The solution was stirred for 4
h and the cellulose was filtered off. The cellulose was then
resuspended in 200 mL of water, stirred for 15 min, and
vacuum filtered. This step was repeated five times. In the
next step, the cellulose was successively washed with NaOH
solution (100 mL, 1 M) and water. Finally, the powder was
washed with 100 mL of ether and dried over silica gel in a
desiccator at room temperature for at least 2 days.
2.2.2.2. Immobilization of laccase
Planar oxygen sensor SP-PSt3 (Figure 2A), a matrix of
polymers with an oxygen-quenchable luminescent dye
and an additional overcoat of medical grade silicone, was
used for the construction of the biosensor. These matrices
were first cut into small round pieces (Ø 3 mm) and
washed with 75% (v/v) 2-propanol (1 mL) and distilled
water twice. The sensor’s nonshiny side was then laid on
the 3-aminopropylsilanetriol (APST, 20%) overnight at
room temperature under light protection for activation.
The next day, the sensors were washed twice in water. In
order to immobilize laccase on the sensor spots, three
different solutions were prepared by dissolving enzyme
(1.0, 1.5, and 3.0 mg) in sodium phosphate buffer (0.1
M, pH 6.9, 22 µL). The cross-linker (glutaraldehyde,
25%, 3 µL) and a matrix stabilizer (amino-modified
carboxycellulose, AMC, 25 µL) were then added and the
well-mixed suspension (50 µL per sensor) was transferred
onto the upper (nonshiny) surface of the sensor. The
enzyme layer dried overnight at room temperature under
light protection.
2.2.2.3. Addition of diffusion layer
The diffusion layer was prepared by using
TMOS:PVA:HCl:Tri-MOS in a volumetric ratio of 2:8:5:1.
After preparation, 40 µL of this mixture was pipetted
onto the laccase layer and left to dry overnight at room
temperature under light protection. To evaluate the effect
of the diffusion layer on sensor performance, the absence
and presence of the diffusion layer (single or double
layers) were tested. To prepare the double diffusion layer
containing sensor spots, the first layer was left to dry for 2
h before pipetting the second layer.
Figure 2. a) Planar oxygen sensor SP-PSt3 and b) fiber-optic chemical sensor that is integrated in a T-shaped flowthrough cell (FTC).
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2.2.2.4. Measurement
After the diffusion layer dried, sensor spots were glued (RS
692-542, silicone glue) into vials that were rinsed prior to
use with acetone to remove all fatty residues and sensors
were left to dry for 24 h at room temperature under light
protection. Phosphate buffer saline (PBS, 20 mL, pH 6.9)
was added to each vial after the glue dried and vials were
connected to an OXY-4 transmitter with fiber optic cables.
The measurements were done under continuous stirring
with the help of a magnetic stirrer with measurement
intervals of 15 s. When the background signal was
stabilized, an increasing concentration of catechol solution
was added into vials step by step and the phase angles for
different catechol concentrations were plotted.
2.2.3. Characterization of the laccase-immobilized SPPSt3 sensor spots
2.2.3.1. Optimization of enzyme and diffusion layer
amount
In order to determine the laccase amount needed for
optimum response, three different enzyme amounts (1.0,
1.5, and 3.0 mg/sensor) were tested. The effect of diffusion
layer presence and its quantity on sensor response was
evaluated by preparing sensors with (one or two layers)
or without a diffusion layer. For all cases, 1.5 mg/sensor
laccase concentration was used.
2.2.3.2. Determination of optimum pH
The performances of the sensors prepared with optimum
enzyme amount and diffusion layer quantity were evaluated
at three different pH conditions that corresponded to
acidic, neutral, and basic pH, namely 5, 6.9, and 9, using
PBS as a buffering system. Since the immobilization of the
enzyme and its storage were carried out at pH 6.9, this
value was also used for activity assays.
2.2.3.3. Determination of dynamic working range
The maximum and minimum phenol detection limit of
the biosensor was investigated in PBS buffer (pH 6.9)
by using optimum sensor conditions. For the highest
detection limit, catechol concentrations between 0.1 and
5.0 mM were used and were added up to 0.6 mM final
concentration step by step (0.1 mM at each step), and then
the buffer was refreshed. This procedure was performed
before each measurement for 1 mM, 2 mM, and 5 mM
catechol. After that, catechol samples with concentrations
between 0.01 and 0.1 mM were used to find the lowest limit
of detection and the linear working range of the biosensor.
2.2.3.4. Determination of reproducibility and hysteresis
behavior
To determine the reproducibility of sensor spots, five spots
were produced simultaneously and the responses of each
sensor were compared using catechol as an analyte. To
determine the hysteresis of the biosensors, first different
1306
concentrations of catechol were added gradually to the
same sensor spot, and then the buffer was refreshed. When
the signal reached equilibrium, measurements were done
in the opposite order, gradually decreasing the catechol
concentration, and the results were compared.
2.2.3.5. Storage stability of the biosensor
The sensor spots were stored in PBS (pH 6.9) at 4 °C, and
at different time points (1, 30, and 85 days), three sensor
spots were randomly taken out and activity measurements
were done using catechol (5 mM).
2.2.3.6. Measurement duration of the biosensor
To determine the measurement duration of the biosensor,
the time necessary for the sensor to complete detection,
i.e. the time between the addition of sample and the
equilibration of the signal, was measured by using samples
of different catechol concentrations, where the final
concentrations ranged between 0.1 and 1.5 mM.
2.2.4. Construction of the laccase-immobilized FTCPSt3 sensor spots
2.2.4.1. Activation and immobilization
For the flow-through system, an oxygen minisensor
(FTC-PSt3) was used. This is a miniaturized fiber-optic
chemical sensor that is integrated in a T-shaped flowthrough cell (FTC) (Figure 2B). One arm of the T-shape
serves as a connection point to the FIBOX oxygen meter
via a polymer optical fiber (Ø 2 mm) as the light guide.
The activation was done as explained in Section 2.2.2.2.
Laccase (10 mg), bovine serum albumin (BSA, 10 mg), and
glycerol (6 mg) were then mixed thoroughly in 100 µL of
dH2O and glutaraldehyde (25 µL, 2.5%) was added to this
solution. For the immobilization, 2.6 µL of this mixture
was pipetted onto the surface of each sensor and left to dry
overnight at room temperature in the dark.
2.2.4.2. Addition of the diffusion layer
The
diffusion
layer
was
prepared
using
ethylcellulose:D4:ethanol solution (90%) with a mass ratio
of 2:1:27. The prepared mixture (1.6 µL) was pipetted once
onto each sensor surface and left to dry overnight at room
temperature in the dark.
2.2.4.3. Measurement
Sensor spots were glued to the head of a plastic tube
attached to the fiber optic cable with the help of silicone
glue and were left to dry for 24 h at room temperature
in the dark. Plastic tubes containing sensor spots were
incubated in PBS (0.1 M, pH 6.9) overnight in order to
humidify the matrix of the sensors. Measurements were
done the following day with the FIBOX 3 transmitter,
introducing catechol solution with a known concentration
via a peristaltic pump after the background signal was
stabilized.
BİLİR et al. / Turk J Biol
60
Phase Angle [°]
55
50
45
40
35
30
25
0
0.2
0.4
0.6
0.8
Catechol concentration (mM)
1
Figure 3. Determination of optimum enzyme amount (● 3 mg,
■ 1.5 mg, and ▲ 1 mg) based on comparison of sensors’ phase
angles for different catechol concentrations (three independent
sensors were used and three measurements were performed with
each).
55
50
Phase Angle [°]
3. Results and discussion
3.1. Optimization of the SP-PSt3 fiber optic biosensor
3.1.1. Effect of enzyme amount
Sensors with different laccase amounts (1.0, 1.5, and 3.0
mg/sensor) and without a diffusion layer were used. The
change in the phase angles based on catechol concentration
was plotted (Figure 3). It could be seen that sensors
constructed with 1 mg of laccase could not respond
effectively to the changes in catechol concentration. When
the laccase amount was increased to 1.5 mg, there was a
dramatic increase in the sensor response. A further increase
in the laccase amount (3 mg), however, led to a decrease in
the phase angle values. This could be due to the excessive
amount of enzyme on the surface (an increased enzyme
layer thickness), which could limit the free movement of
the enzyme needed for enzymatic activity and slow the
mass transport rate of the analyte. This type of behavior
has been reported in the literature for different enzyme
sensors (Mulchandani et al., 1999; Kushwah et al., 2011).
The optimum laccase amount was therefore determined as
1.5 mg per sensor and used in further studies.
3.1.2. Effect of diffusion layer quantity
Sensors (1.5 mg of laccase) with (one or two layer) or
without a diffusion layer were prepared and the results
were plotted according to the changes in phase angle
values (Figure 4). The presence of the diffusion layer
affected the maximum phase angle reached by the system;
biosensors with two diffusion layers reached a lower phase
angle (ca. 48°), while biosensors with one diffusion layer
reached the highest one (ca. 55°). Without a diffusion
layer, the reusability of the sensors was limited because of
external factors that led to the easy loss of enzyme layer
from the sensor surface. This could be the reason for the
45
40
35
30
25
0.0
0.2
0.4
0.6
0.8
Catechol concentration (mM)
1.0
Figure 4. Effect of diffusion layer (DL) on biosensor response:
(●) without DL, (■) with one DL, and (▲) with two DLs.
lower phase angle values obtained in the absence of the
diffusion layer. A biosensor with one diffusion layer was
chosen for further studies.
3.2. Characterization of the biosensor
3.2.1. Effect of pH
The effect of pH was evaluated with the optimized
sensor (1.5 mg of enzyme and 1 diffusion layer) and the
measurements were done in PBS buffer with different
pH values (5, 6.9, and 9) (Figure 5). Optimum pH was
found to be shifted to pH 6.9 upon immobilization when
compared with that of the free form (pH 4.5). This shift in
optimum pH is generally caused by the proton exchange
properties of the immobilization matrix (Cho et al., 2008).
The microenvironment surrounding the immobilized
enzymes affects their apparent optimum values and
anionic polymers, for example, were shown to shift the pH
optimum of the enzyme to more basic values (Tastan et al.,
2011). The biosensor still had considerable activity at pH
5, but its activity was almost completely hindered at pH 9.
It was seen that the loss of activity in alkaline conditions
(e.g., pH 9.0) was not a permanent one and activity could
be restored when the optimum pH value (pH 6.9) was
reached again (data not shown). Laccases generally tolerate
acidic conditions well (4.0–5.5), but their activity drops
abruptly at more basic pH values (>6.0) (Li et al., 2014).
The constructed biosensor therefore has the advantage of
being used in the measurement of samples with pH values
near neutral as opposed to other laccase sensors and it
seemed to keep its activity considerably in mildly acidic
conditions.
3.2.2. Linear working range and limit of detection (LOD)
of the biosensor
The lowest detection phase value (LDPV) was calculated
as 27.76 by the formula LDPV = 3 × (standard deviation
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60
Phase Angle [°]
55
50
45
40
35
30
25
0.0
0.2
0.4
0.6
0.8
Catechol concentration(mM)
1.0
Figure 5. Optimum pH determination of the fiber optic
biosensor. pH (▲) 5.0, (●) 6.9, and (■) 9.0
value of 0 mM) + (phase angle value of 0 mM). A
catechol concentration of 0.04 mM yielded a phase
number of 27.88 (±0.04), so it was noted as the LOD of
the biosensor for catechol. When a wide range of catechol
concentrations (0.1–0.6 mM) was used to determine the
linear working range, a linear regression analysis result
with a good R2 value (0.9876) was obtained (Figure 6).
When the concentration range was narrowed down to
lower concentrations, however, a different linear relation
with a better R2 value (0.9985) was attained. This clearly
showed that the biosensor could be used for the prediction
of catechol concentrations over a broad range of values
(0.1–0.6 mM), but the calibration curve obtained for this
concentration range could fail to determine the lower
concentrations with high accuracy, so one should be careful
in the interpretation of the signal at low concentrations.
For the optical laccase sensor developed by Abdullah
et al. (2007), the LOD was determined as 0.33 mM. A
55
30
29
60
y = 27.307x + 26.749
R² = 0.9985
55
28
45
27
26
40
0
0.05
Phase Angle [°]
Phase angle [°]
50
0.1
35
y = 47.057x + 25.624
R² = 0.9876
30
25
0
0.2
0.4
50
45
40
35
30
0.6
Catechol concentration (mM)
Figure 6. Linear working range of the biosensor (insert shows the
behavior of the sensor at low catechol concentrations).
1308
similar LOD (0.3 mM) was found by Singh et al. (2013)
using tyrosinase for amperometric detection of catechol
with a linear working range of 1.0–6.0 mM. To obtain
better LOD values, incorporation of nanoparticles was
generally proposed by different groups. The usage of gold
nanoparticles, for example, has been found to decrease the
LOD down to 0.03 µM (Brondani et al., 2013). It could
therefore be said that a better LOD value was obtained
when compared with similar electrochemical biosensors
without any nanoparticle incorporation.
3.2.3. Reproducibility of the biosensor
Five sensor spots were produced simultaneously according
to protocol and their responses were tested with different
concentrations of catechol. The slopes of phase angle vs.
catechol concentration graphs were found to be similar
with an acceptable standard deviation (46.8 ± 0.6),
indicating that the reproducibility of the biosensor was
high.
3.2.4. Hysteresis behavior of biosensor response
Different concentrations of catechol were added gradually
up to 0.6 mM (1st measurement). The buffer was then
refreshed and measurements were done in the opposite
order by gradually decreasing the catechol concentration.
During this step, buffer was changed and a specific buffer
+ catechol mixture was added before each measurement
(2nd measurement). Results of sensor response according
to phase angle values were compared (Figure 7). The
biosensor showed almost the same response against the
same catechol concentrations whether the catechol’s
concentration was decreased or increased gradually, so no
detectable hysteresis on biosensor response was observed.
3.2.5. Storage stability of the biosensor
Activity measurements of the immobilized system were
done at different time intervals (1st, 30th, and 85th
days after production) and phase angle vs. catechol
25
0
0.1
0.2
0.3
0.4
0.5
0.6
Catechol concentration (mM)
Figure 7. Comparison of 1st (■) and 2nd (●) measurements’
phase angles to determine hysteresis behavior.
BİLİR et al. / Turk J Biol
48
2
mM
Phase angle [°]
44
6
mM
3 mM
40
0.5
mM
36
32
0.2
mM
6
mM
1
mM
0.5
mM
0
mM
28
2
mM
0.5
mM
0.2
mM
0.2
mM
0
mM
24
20
0
100
200
300
400
500
Time (min)
Figure 8. Determination of sensor applicability to the flowthrough system.
concentration graphs were compared. The slope of these
curves was found to be 44.0, 43.5, and 41.7, respectively,
meaning that no significant change could be detected after
a month and ca. 95% of the biosensor’s initial activity was
retained after 85 days. This result was found to be better
than that of the laccase biosensor constructed by Gomes
and Rebelo (2003), who reported a 62% decrease in
activity after 38 days. Abdullah et al. (2007), on the other
hand, reported a comparable result with almost 90%–98%
activity after 2 months of storage at 4 °C.
3.2.6. Measurement duration
When the measurements were carried out by gradually
increasing the catechol concentration from 0.1 mM to 1.5
mM, a measurement period of around 13 min was needed
for the stabilization of the signal. When the signal recovery
after the washing step, etc. was taken into account,
25–30 min were needed between two successive sample
measurements. It could therefore be concluded that
the biosensor has a short measurement duration (ca. 25
min between two successive measurements) at optimum
conditions, i.e. with one diffusion layer and at pH 6.9.
3.3. Applicability to flow-through system
FTC-PSt3 sensor spots were prepared considering the
optimum parameters of the previous sensor (SP-PSt3) and
measurements were done with randomly chosen catechol
concentrations to determine the response and reliability
of the sensor. Figure 8 shows that the signal could be
reproduced at each attempt, showing that FTC-PSt3
sensors work properly in a flow-through system.
Acknowledgment
The grant from the EU Erasmus Student Exchange Program
for Kadir Bilir is gratefully acknowledged. Julia Lochead
is a student of the HBIGS graduate program and received
a PhD grant from the Albert and Anneliese Konanz
foundation. The authors would also like to acknowledge
that for the preparation of the amino-modified cellulose
and diffusion layer, a method used for glucose oxidase
during the successful acquisition of the project “Enzyme
Immobilization on Commercial Optical Oxygen Sensor
Membranes” [Justice C, Werner T (2007), University
of Applied Sciences Mannheim, data not shown] was
adapted.
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