VIETNAM NATIONAL UNIVERSITY – HO CHI MINH CITY

INTERNATIONAL UNIVERSITY

DEVELOPMENT OF A VERSATILE AND

COMPACT PAPER-BASED MICROFLUIDIC

BIOSENSOR FOR DETECTION OF COPPER

IN FOOD PRODUCTS

A thesis submitted to

The School of Biotechnology, International University

in partial fulfillment of the requirements for the degree of

B.S. in Biotechnology

Student’s name: Nguyễn Lan Thảo - ID:BTIU09046

Supervisor: Dr. Nguyễn Thái Lộc

June 2013

Acknowledgement First of all, it is of great importance to deliver my thankfulness to Dr. Loc

T. Nguyen, who dedicated his generous time and sound knowledge to my

research as a mentor. Truthfully, it was my absolute honor to work with Dr.

Nguyen. Thanks to his insightful instruction, valuable experiences and

motivating encouragement, I became brave and confident enough to take on

plenty of challenges. Had it not been for his constant supports, I would not have

successfully accomplished this study.

Secondly, my sincere gratitude is expressed to Dr. Khoi T. Nguyen for

consulting me with suitable techniques and stimulating ideas to deal with

difficulties that arose during the study of unfamiliar subjects. That was his

inspiration which kept me persistent until the end.

Moreover, I owe my gratefulness to all the laboratory managers and

staffs, particularly MSc. Long H. Nguyen, MSc. Dao Q. T. Tran, MSc. Lieu B. T.

Truong and BSc. Anh L. Dang, who devoted themselves to ensure a well-

equipped and safe laboratory and did not even mind working overtime or at

weekend.

I also would like to take this opportunity to say special thanks to Ms. Han

B. Nguyen, Ms. Yen K. T. Dang and Mr. Trong Q. Luu for standing by me

throughout hardships, as well as cheering me up in various situations. Besides,

the supports from Mr. Thien H. Nguyen are much appreciated. His interesting

lessons enabled me to perform sophisticated image analysis as well as to turn

ideas into vivid figures, all of which contributed to the best presentation I have

ever made.

It would be incomplete not to thank you all – my colleagues in lab 101,

including Ms. Dung M. T. Nguyen, Mr. Dang D. Nguyen, Ms. Hien T. T. Nguyen,

Ms. Khanh K. T. Nguyen, Ms. My H. T. Nguyen, Ms. Oanh K. T. Nguyen, Ms. Vien

L. Ngo and Ms. Tram N. L. Nguyen for supporting and sharing with me no matter

in good times or in bad that made every moment priceless. Together they

created the most memorable semester.

Last but not least, it is my family who I want to convey the deepest

appreciation to. Thank my mom, Mrs. Lan T. Ta and my dad, Mr. Hy D. Nguyen

for giving me such a favorable environment that I could concentrate and do the

best in the study. Thank my brothers for their sweet treats and assistance in

delivering necessary research equipment. No matter what the situations are, my

family is always the greatest back-up that I can count on.

For this moment, my heart is filled with endless love and sympathy from

many other people that I cannot list here due to limited scope. To all of those, I

would love to personally say big thank you and promise to continuously improve

myself.

DEVELOPMENT OF A VERSATILE AND COMPACT

PAPER-BASED MICROFLUIDIC BIOSENSOR FOR

DETECTION OF COPPER IN FOOD PRODUCTS

Thao L. Nguyena, Loc T. Nguyen

a,*

a: School of Biotechnology, International University – Vietnam National University - HCMC

*: Corresponding author’s email address: ntloc@hcmiu.edu.vn

1

Abstract

In this contribution, a versatile, inexpensive and compact paper-based microfluidic

biosensor was developed to detect heavy metals in food products. The underlying

principle was based on sensing of ammonia (NH3) released during urease-

catalyzed hydrolysis of urea. At the presence of heavy metals, the amount of NH3

produced diminished due to inhibition of urease enzyme. Therefore, the

concentration of target heavy metals could be indirectly determined from NH3,

qualitatively, semi-quantitatively or quantitatively. Hydrophobic barriers of

functional areas the sensor were fabricated by paraffin-dipping method. Urease

enzyme was physically immobilized onto the sensor and phenol red was used for

qualitative and semi-quantitative detection of heavy metal via image analysis. The

sensor was also integrated into an electrochemical system using simple screen-

printed electrodes. In the current study, Cu++ was used as a model heavy metal

for testing performance of the sensor. Qualitative results showed that a strong

contrast between safe and unsafe sample, which was critical for the practical

applicability of the sensor. Relationship between color intensity and Cu++

concentration was characterized by a R2 of 0.98 and the linear range covered Cu++

concentrations from 0.01 – 1 ppm. Detection limit was estimated to be 0.018 ppm

which was well below standard limit established by WHO and EC for Cu++.

Quantitative tests were still at beginning stage and were worth further

investigations. The findings from this study demonstrated that the proposed

paper-based biosensor could be a promising platform to develop low-cost test kits

for detection of heavy metals in foods.

Keywords: Paper-based biosensor, wax-dipping, screen-printing electrodes, SPEs,

colorimetric test, amperometric test.

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1. Introduction

Heavy metals are ubiquitous pollutants and their presence in the

environment can be attributed to natural or human activities. Many heavy metals

are carcinogens and may be involved in several dangerous diseases (Hossain et

al., 2011). In general, heavy metals are not easily degraded and tend to

accumulate in soils and sediments (Dominguez-Renedo et al. 2013). Major sources

of soil contamination with heavy metals are wastewater irrigation, solid waste

disposal, sludge applications, vehicular exhaust and industrial activities (Khan et

al. 2008). Plants grown on contaminated soils may build up excessive content of

heavy metals and eventually have negative effects on food quality and safety.

Therefore, it is of critical importance to monitor the contamination of heavy metals

in food products. Currently, analytical methods for heavy metals usually rely on

inductively coupled plasma/atomic, emission spectrometry (ICP/AES), inductively

coupled plasma, mass spectrometry (ICPMS), atomic absorption spectroscopy

(AAS), or wet chemical methods such as titrimetry, gravimetry, colorimetric

assays, etc (Hossain et al., 2011). Despite their high sensitivity, selectivity,

reliability, and accuracy, these methods are time-consuming, require sophisticated

instrumentation, skilled personnel and complicated sample pretreatment

(Turdean, 2011). Inherent drawbacks of these assays restrict their use mainly in

centralized laboratory. Thus, inexpensive, easy-to-use and portable test kits which

can screen contamination of heavy metals for a large number of samples are highly

desirable. Recently, the emergence of paper-based microfluidic devices has

become important resources for low-cost diagnosis. The underlying principle of

these devices is to pattern hydrophilic hydrophobic micron-size capillary channels

on paper using various methods including wax-printing, ink-jet printing,

flexography printing, screen printing, etc. (Li et al. 2012). Paper has advantages

of being inexpensive, lightweight, available everywhere and compatible with

biological samples (Martinez et al. 2010). Paper-based devices can be easily

disposed after use, require very small volume of sample and reagents, capable of

analyzing multianalytes at the same time and easily mass produced (Nie et al.

2010). Several paper-based assays with diverse formats developed for health

care, environmental monitoring, food quality control and forensic science (Li et al.

2012).

Paper-based devices can be applied for either qualitative or quantitative

analysis. When coupled with appropriate detection methods, paper-based devices

can produce quantitative results with reasonable accuracy. Popular detection

methods such as colorimetric, electrochemical, electrochemiluminescence or

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chemiluminescence were extensively reviewed by Li et al. (2012). Paper-based

microfluidic devices can also serve as an excellent platform for biosensor

development. Biosensors with exceptional performance such as high specificity

and sensitivity, rapid response, low cost, compact size and easy-to-use were

considered as important means in clinical, food and environmental monitoring

(Amine et al. 2006). One of the most widely used technique in monitoring

pollutants and toxic compounds is enzyme inhibition-based biosensing in which

concentrations of target compounds can be determined from the extent to which

the enzyme is inhibited, signifying by the product concentration. Popular enzymes

used as bio-recognition elements for detection of heavy metals are horseradish

peroxidase, urease, glucose oxidase, alcohol oxidase, glycerol 3-phosphate

oxidase, invertase and acetylcholinesterase (Amine et al, 2006).

For analysis of heavy metals, several paper-based test kits with significant

contribution in term of sensing methods, sensitivity, selectivity were developed for

mercury (Gu et al., 2011; Hossain et al. 2011; Torabi et al. 2011; Aragay et al.

2012), cadimium (Abe et al. 2011; Hossain et al. 2011; Marzo et al. 2013), copper

(Fang et al. 2010; Hossain et al. 2011), iron (Apilux et al., 2010), lead (Mazumdar

et al., 2010; Hossain et al. 2011), chromium (Hossain et al. 2011; Liu et al., 2012)

and gold (Apilux et al., 2010). Considering the end-use of paper-based devices as

low-cost diagnostic kits in developing countries, they should be able to perform

analyses at different levels of complexity. In certain situation, an inexpensive

qualitative test requiring no advanced analytical skills is sufficient to make sure

that heavy metals in foods, agricultural products or water sources are under a safe

limit. If more accurate results are expected, the same device can be integrated

into colorimetric, electrochemical or other detection systems to produce semi-

quantitative or quantitative results.

Some authors (Fang et al. 2010; Abe et al. 2011; Gu et al., 2011; Torabi

et al. 2011; Aragay et al., 2012; Liu et al. 2012; Marzo et al. 2013) propose

approaches using fluorescence or strip reader to obtain quantitative results

besides qualitative test. However, these methods still require large sample

volume, bulky and sometime complicated fabrication process. Recently, methods

such as wax printing, wax dipping appeared as alternative approaches for

producing inexpensive micron size devices. The fundamental principle of creating

a microfluidic device was to pattern hydrophilic channels bounded by hydrophobic

barriers. One of the simplest method was to use a printer to deposit patterns of

solid wax on the paper which was then heated to enable the wax to penetrate into

the entire thickness of paper, thus generating complete hydrophobic barrier. An

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alternative approach was wax dipping which was first proposed by Songjaroen et

al (2011) which are capable of both qualitative tests by visually observing color

change or quantitative analysis using digital camera. In this method, a mould was

used to produce the hydrophobic areas. The whole assembly of the mould and

paper was quickly dipped and withdrawn from the melting wax. Wax deposited on

the uncovered parts, resulting in desired hydrophobic areas. Paraffin was used in

this study for its easy availability and low prices while having similar characteristics

as wax. The fact is that digital cameras and scanners are not as selective and

sensitive as conventional analytical instrumentation, nevertheless, highly selective

and sensitive detectors are still required for low analyte concentrations (Dungchai

et al. 2009). Electrochemistry-based method is attractive detection soucheme for

paper-based biosensors due to its compact size, low-cost, high sensitivity and

selectivity. Using this method, Apilux et al. (2010) successfully detected gold in

waste stream. Nonetheless, few studies have yet to develop paper-based

biosensors capable of multiple testing schemes for detection of heavy metals in

foods and food products.

In this contribution, our objectives were a) to design and fabricate a paper-

based biosensor using wax-printing technology; b) to apply the produced

biosensors for qualitative and semi-quantitative detection of heavy metals and c)

to integrate the biosensors with electrochemical analyzer.

2. Materials and methods

2.1 Chemicals and solution preparation

Urease (type III, EC 3.5.1.5, 33U/mg) from Canavalia ensiformis (Jack

bean) was purchased from Sigma Aldrich (USA). Carbon ink (C-200) and Ag/AgCl

inks (AGCL-375) were obtained from Hudson (USA).Tris-HCl (min 99.0%) was

from HiMedia Labs (Mumbai, India). Urea, phenol red, CuSO4, KCl, NaOH and HCl

were of analytical grade and used as provided. Filter papers (60x60cm) and white

pellet paraffin wax were sourced from local chemical stores.

Stock solutions of enzyme (1000U/mL), Cu++ (680 ppm) were prepared in

Tris-HCl buffer solution (50mM, pH 7.0). The enzyme stock solution was made on

a weekly basis and kept in refrigerator after use. Urea (0.1M) and KCl (0.1M)

mixture was prepared in distilled water.

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2.2 Fabrication of paper-based microfluidic biosensor

The design and dimensions of the sensor used in this study was illustrated

in Figure 1A. The sensor was developed to accommodate both colorimetric and

electrochemical tests simultaneously. The design was made using CorelDraw x3

(Corel Inc., Mountain View, USA). Initially, reference, working and counter

electrodes were patterned on reaction zone (Figure 1A) using screen printing

method. Carbon ink (C-200) was used for working and counter electrodes whereas

silver/silver chloride ink (AGCL-375) was used for reference electrode. The printed

electrodes sensor was dried at 65oC in oven for about 30 min. The printing patterns

of the electrodes were tested for continuity by a multimeter.

Figure 1. (A)Schematic design of the paper-based biosensor illustrating

sensing zones, loading area and conductive pads to interface electrochemical

system (B)Steel mould used to pattern hydrophilic-hydrophobic channels on

the sensor

In the next stage, the microfluidic channels were created. A mould (Figure

1B) was cut from a 0.3 mm steel plate using computer numerical control (CNC)

machine by a local workshop. The mould can be used many times without

deformation and decrease in resolution of the hydrophilic channels. About 200g

of paraffin was melted in a 500 ml beaker using hot plate (IKA RH Basic 2).

Experiment were conducted at different dipping temperature (55-80oC) and time

(1-5s) to determine the optimal conditions for patterning hydrophylic barrier. Prior

to wax dipping, the filter paper containing printed electrodes were cut into

rectangles (50 mm width x 80 mm length). And sensor was sandwiched between

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the mould and a glass slide. The mould was positioned so that electrochemical

reaction zone was aligned with the printed electrodes. A permanent magnet was

used to hold the mould against the glass slide. The whole assembly was dipped

into the melted paraffin and quickly withdrawn in predetermined time. After the

paraffin was cooled to ambient temperature, the mould was removed and the

sensor was visually examined for any defections. The hydrophilic channels should

remain clear and sharp. The paraffin needed to penetrate evenly into the filter

paper. Those sensors which did not meet the requirements were discarded. The

process was described in Figure 2

Figure 2. Fabricating procedures of paper-based biosensor includes: (1)

Screen-printing working electrode (WE) and counter electrode (CE) using

carbon inks, and (2) reference electrode (RE) and conductive pads with

Ag/AgCl inks .(3-4) The sensor was wax-dipped to create hydrophobic/hydrophilic pattern. (5) Tape was attached to the back side.

2.3 Qualitative and semi-quantitative analysis

The fundamental principle of the qualitative and semi-quantitative analysis

was based on hydrolysis reaction of urea ((NH2)2CO) (1).

32

Urease

222 NH2COOH CO)(NH (1)

The production of ammonia (NH3) led to an increase in pH of the solution,

hence change in color of phenol red. As heavy metals were added to the solution,

their binding to thiol group in the active center of urease diminished catalytic

activity of the enzyme. Since the amount of NH3 produced or pH was affected by

the heavy metals, concentrations of heavy metals can be determined from the

magnitude of color changes. For the proof of concept, the proposed biosensor was

7

tested with Cu++ ions. The testing protocol (Figure 3) basically involved 4 main

steps a) immobilizing enzyme on the reaction zones; b) loading samples on the

sensor; c) incubation and d) taking the readings after adding urea to induce color

change.

Figure 3. Qualitative and semi-quantitative testing procedure (A) Firstly the

mixture of enzyme and indicator was loaded into the sensing zone and (B)

sample was introduced to the loading area. After incubating for 10 min (C)

urea was added and ammonia was produced from the hydrolyzation (D) color develop after 3 min (E) The result was scanned and analyzed.

2.3.1 Enzyme immobilization

In this study, the urease enzyme was physically immobilized on the paper

substrate. Urease enzyme stock solution (200U/ml) was prepared in Tris buffer

(50mM, pH 7.0) and mixed with phenol red solution (0.4% in 50% ethanol) at

ratio 1:1 (V/V). The enzyme-indicator mixture (ED) was used within 3 hours after

preparation and kept on ice. Prior to immobilization of enzyme on the sensor, one

side of the sensor was covered with Scoth tape. Then 1.5 µL of the enzyme-

indicator mixture was placed on each reaction zones and allowed to air-dried for

about 2 min. The free side of reaction zones were now covered with another piece

of Scoth tape (Figure 4A) to control the flow of reagents eventually. Periodically,

enzyme immobilization was verified by adding 25 µL of CuSO4 solution at 0 and 5

mM concentrations to the loading zones of two different sensors. The inhibitory

reaction was incubated for about 10 min. After that, 25 µL of 0.1M urea was

loaded. Since it will take times for color to develop, the reading time was

standardized as 3 minutes afterward. The enzyme immobilization was considered

8

successful if red color was observed for negative sample and no color change was

noticed for positive sample

Figure 4. The attachment of scotch tape to the front and back sides of sensors

to prevent leakage and enhance uniformity of reagent distribution. Tape covers the sensing zones on (A) front side and (B) back side.

2.3.2 Qualitative analysis

The qualitative analysis was based on visual matching color of an unknown

sample to a color scale of which variation of color intensity indicated concentration

ranges of heavy metals present. Experiments were conducted to record

colorimetric response of the sensor to different concentrations of Cu++ (0.001-

1ppm). Using an office scanner (Canon Co. Ltd, Vietnam), the obtained results can

served as the input to construct the color chart for qualitative analysis.

2.3.3 Semi-quantitative analysis

Development of standard curve

Serial dilutions of CuSO4 (0.001-1ppm) solution were prepared from stock

and used to develop standard curve for semi-quantitative analysis. Samples

(25µL) at different concentrations were loaded on the sensors and incubated for

about 10 min. Then, 25 µL of urea (0.1 M) was added and after 3 min, the results

were recorded using the office scanner of which resolution was set at 600 dpi.

(Figure 3B-E).

The analysis of color developed on the loading zones was conducted using

Adobe Photoshop CS2 (Adobe Inc., San Jose, USA) (Figure 3E). The rectangular

9

selection was fixed to 1000 pixel as to cover reacting regions. As Histogram can

automatically filters out the desire single channel color, it was used to measure

the pink color directly from the RGB pictures. Giving that the Green color was the

major contributor to violet color, the Green channel value was measured.

The standard curve was constructed by plotting the color data against

concentrations of heavy metals used. All data points presented were the average

of 9 replications. The detection limits were calculated based on 3 times standard

deviations of the negative control.

Validation

To validate the results, an independent set of samples with known

concentrations were prepared and tested using the developed sensor. Colorimetric

signals were obtained as described in the previous section and the concentration

of heavy metals were estimated from the calibration curves. The recoveries

percentage was calculated as below (Eq.2):

100% )M,Cu oftration log(Concen Calculated

)M,Cu oftration log(Concen Actual = (%)Recovery

(Eq.2)

2.4 Electrochemical test

2.4.1 Experimental set-up

Electrochemical measurement was conducted using Digi-Ivy potentiostat

DY2013 (Austin, TX, USA). A simple custom-made holder was fabricated to

integrate the developed sensor into the electrochemical system (Figure 5).The

sensor could be easily inserted in the holder and three stainless steel screw

interfaced the working, counter and reference electrodes of the sensors to the

corresponding channels of the potentiostat. The contact between the printed pads

of the electrodes on the sensor and the screw was maintained by a paper clip.

10

Figure 5. Experimental set-up for electrochemical measurement.

2.4.2 Urease-based amperometric response of the sensor to different

concentrations of heavy metals.

After the sensor was placed in the holder, a fixed voltage (-1.5 V) was

applied and resulting current was measured for about 40 seconds . The current

intensity was dependent on the amount of NH3 produced in the reaction zone

during urea hydrolysis. Addition of heavy metals resulted in impaired catalytic

ability of urease, hence indirectly affecting the amount of NH3 formed. Therefore,

amperometric response of the sensor could reveal the amount of heavy metals

present in the samples. Percentage of current reduction was used to estimate the

contamination of heavy metals and was given by:

(%)reduction Current %100I

II

1

21

(Eq.3)

With I1, I2 were the measured electrochemical currents before and after

inhibition with Cu++, in µA.

To construct calibration curve, serial dilutions of Cu++ (0, 0.001, 0.01 and

0.1 ppm) were used. Correlation equation describing relationship between current

reduction and concentrations of Cu++ was obtained from regression analysis.

2.5 Data analysis

Each data point represents the average result of six replications. Using

descriptive analysis, the results were showed by mean values plus standard

deviation (SD). Next, the correlation between color intensity and Cu++

concentration was evaluated and the goodness of fit was considered using

coefficient of determination (R2). For comparison purpose, the variation between

measurements was evaluated using ANOVA and the Student t-test.

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3. Result and discussion

3.1 Fabrication of the paper-based microfluidic sensor

Effects of dipping temperature and time

Patterns of paraffin on paper at different dipping temperatures were

presented in Figure 6.

Figure 6. Effect of different dipping temperatures on the resolution of

hydrophobic barrier with (a-f) corresponding to 55-80oC with 5oC increment.

The consistency and resolution of the channels were directly influenced by

melting temperature and dipping time. As evidenced from the photos, the optimal

temperature ranges were from 70-75oC. Under these conditions, hydrophobic-

hydrophilic boundaries were well-defined and the width of the channels was most

consistent. Lower temperatures led to the excessive build-up of paraffin on the

paper surface. When temperature of paraffin was greater than 75oC, melting

paraffin tended to diffuse under the mold and, consequently, damage the

channels, reaction zones and loading area. Quick observations during the

fabrication process revealed that dipping time should be limited within 1 second.

Longer exposure time would result in accumulation of paraffin on the surface,

hence affecting the final finish of the sensor. In a different study (Songjaroen et

al. 2011), white beeswax pellets required significantly higher temperature of

125oC to achieve the optimal patterns. However, dipping time was also

recommended to be no longer than 1 s to prevent the excessive spreading of wax

into the paper. In this study, paraffin was selected to create hydrophobic barriers

of the microfluidic channels. The cost of this material was lower than wax and it

could produce a smooth surface after setting. However, the barriers made by

paraffin were not as stable as expected. As illustrated from Figure 7, after a few

times of exposure to testing reagents, paraffin boundaries weakened and diffusion

of solutions through the hydrophobic barriers was noticed.

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Figure 7. Leakage of reagent due to weakened of hydrophobic barrier after

testing. Comparison of (a) before and (b) after used sensor.

Further studies should investigate on the effects of potential factors such

as melting point, hydrophobic-hydrophilic balance of dipping agent etc. on the

quality of microfluidic channels. The information obtained would be valuable in

selecting appropriate materials for patterning the paper-based sensor.

Effects of fluid flow and evaporation

Performance of the paper-based microfluidic sensors was affected by the

flow and evaporation of the fluids. Due to capillary effects, fluids from loading area

diffused through channels and entered the reaction zones. It was found that,

moving fluid leached and transported the immobilized enzyme and indicators to

the borders of reaction zones. As a result, the variation of color intensity was less

visible for different samples (Figure 8) and this adversely affected the detection of

color change by naked eyes or by optical devices such as cameras or scanners.

Several studies (Martinez et al. 2007; 2008; Abe et al. 2008; Bruzewicz et al.

2008; Carrihlho et al. 2009; Fenton et al. 2009; Li et al. 2012) experienced the

same uneven distribution of color on paper-based microfluidic devices. Fluid

entering reaction zone from a channel spreads radially and carry coloring agents

and lower near the entry port. Visualization of fluid flow clearly confirmed the

patterns of color distribution (Kauffman et al. 2010). Abe et al. (2008) suggested

various solutions including using different geometrical arrangement and increasing

printing cycles of sensing inks. There was some improvement with pH and protein

but not glucose sensing. In this study, several geometrical arrangements,

including 3D patterns, were investigated and none yielded satisfactory results. The

effects of fluid flow on uniformity of color development worsened when the sensing

scheme required multiple loadings of samples and reagents. In the current

research, samples were loaded first and after incubation time, urea solution was

again added to loading area to impart final color change. The flows of sample and

urea solution severely washed off the indicator and it was hardly differentiate color

intensities of different samples.

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Figure 8. Enhanced color stabilization and uniformity due to adhesive tape.

Comparison between sensor with sensing areas (a). uncovered and (b).

covered with tape

Another problem worth mentioning was dependency of color intensity on

evaporation of fluid in the sensing zone. If the sensor was exposed to open air,

the fluids quickly evaporated and color faded within 20 min. The lack of color

stability easily led to misjudgment of the results and left little time for image

capture and processing. To circumvent this problem, adhesive tape was first

covered on both sides of the sensor (Figure 4A). The adhesive tape was very

effective in preventing fluid evaporation, hence enhanced significantly color

stability. The developed color was observed to last for more than 3 to 4 hours.

However, this approach hindered the flow of fluids into reaction zone (possibly due

to build-up of pressure) and makes it difficult to load the samples and reagents.

In another attempt, one side of sensor was fully covered with adhesive tape and

on the other side, only sensing zones were covered, leaving a tiny gap near entry

port as “vent”. With this modification, there was no problem with fluid flow and

color development was very stable. It was also interesting to note that there was

initial radial spread of color to the edge of sensing zone but with increasing time,

coloring agents diffused from the edge to reaction zone and resulted in significantly

uniform color distribution. The findings could be very useful in fabricating paper-

based microfluidic devices with enhanced color stability and uniformity.

3.2 Qualitative test

The colorimetric test kits for heavy metals are applicable for qualitative

assay only if the contrast between safe and unsafe samples is adequately visible.

When exposed to Cu++ at different concentrations ranging from 0 to 10 ppm,

developed sensor revealed significant color change (Figure 9).

Figure 9. Development of color intensity with different concentrations of Cu++ with (a-f) equal 0, 0.001, 0.01, 0.1, 1 and 10 ppm Cu++ respectively.

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Sensing areas shift from a dark violet to yellow color with increasing Cu++

concentration. As evidenced from the data, there is a strong distinction between

samples containing 0 (blank) and 10 ppm of Cu++. Considering standard limits of

Cu++ in drinking water (1 ppm, Food and Drug Administration (FDA)) and

vegetables (5 ppm, CODEX STAN 179-1991), the sensor fabricated in this study

could easily detect the presence of Cu++ in water or food products. Experimental

data were used to develop a color chart which served as standard reference for

qualitative test (Figure 10). Samples classified as positive or negative if the

corresponding colors on the sensor match the right or the left end of the chart,

respectively.

Figure 10. Color chart developed for qualitative test of Cu++ in food sample.

In this research, due to time constraint, the interferences of other heavy

metals were not investigated. The toxicity of heavy metals toward urease

immobilized on chitosan membrane was ranked following the sequence: Hg++>

Ag++> Cu++> Ni++> Cd++> Zn++> Co++> Fe++> Pb++> Mn++ (Krajewska 1991).

However, effects of heavy metals on urease immobilized on paper have not been

reported yet. It would be helpful to determine the levels of heavy metals which

begin to interfere with the final results. In the presence of other heavy metals

above a critical limit, the results can be only interpreted as the overall effects of

the mixtures, rather than Cu++ alone. Nevertheless, the sensor is useful as it can

provide an early warning about the contamination of heavy metals in foods

3.3 Semi-quantitation

The colorimetric response of the sensor to different levels of Cu++ (0-1ppm)

was shown in Figure 11A. At the presence of Cu++, urease enzyme was inhibited,

leading to diminished production of NH3. The amount of Cu++, therefore, had a

direct impact on color intensity inside the sensing areas. The images were

converted into digital values by by splitting the original color into Red, Green, Blue

constitute channels (Figure 11B) using Adobe Photophop CS2. Correlation between

color intensity of individual channels and concentrations of target compound was

analyzed.

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It was found that the coefficients were higher for Red and Green channels

and lower for Blue channels with 0.83, 0.98 and 0.01 respectively (Table 1). The

results suggested a tight relationship between color intensity and measured value

in Green channels.

Table 1. Correlation of color intensity in signal channel

Red Green Blue

Regression coefficient (R2) 0.83 0.98 0.01

Figure 11. Deductive analysis of RGB picture (A)Original sensor in full color

(B) The image was separated into gray scale with using red, blue and green filter for further analysis.

The relationship between Red, Blue values and concentrations of Cu++ was

not significant, indicated by low values of R2, 0.83 and 0.01, respectively (Table

1). In addition, a closed examination of Red and Blue channels showed that they

did not represent color in the sensing areas. Instead, the background or periphery

color due to diffusion of reagents through damaged paraffin borders was captured.

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Color in Green channels was most visually closed to original developed color in the

sensing zones and a strong correlation between Green values and content of Cu++

in the samples was obtained (R2 = 0.98; Figures 12). As a result, values of Green

channel were used to develop the standard curve for semi-quantitative analysis.

Figure 12. Calibration curve for Cu++ concentration from concentration of 0.001-1 ppm

When Cu++ concentration was less than 0.018 ppm, color intensity was

negligibly different from the blank sample (Figure 11A-B.Green). Above 1 ppm,

no color development was observed, indicating a total inhibition of the urease

enzyme on the sensor. As colorimetric response of the sensor to Cu++ content was

linear from 0.01 -1 ppm, a standard curve was constructed for this range of data

with R2 of 0.98 (Figure 12). Detection limit, defined as the analyte concentration

that produce the signal equal to or higher than the average signal produced by the

blank plus 3 standard deviations, was estimated to be 0.018. Detection limit for

Cu++ on paper-based sensor was reported to be 0.02 ppm when reagents were

entrapped in a sol-gel matrix (Hossain et al. 2011). Lateral flow nucleic acid

biosensor based on paper substrate seemed to yield a lower detection limit of

about 10 nM (Fang et al. 2010). However, the detection limit in this study was

still 10 times lower than safe limits of 1 (CODEX STAN 179-1991) and 5 ppm (No.

1881/2006) set by World Health Organization (WHO) and European Commission

(EC), respectively.

Moreover, as compared to previous studies (Hossain et al. 2011; Fang et

al. 2010), the proposed method had the advantages of being simple, compact and

did not require extra expensive instruments beside an office scanner or a digital

camera. This would be important for the application of the sensor in developing

countries where advanced analytical facilities were not easily accessible. In this

R² = 0.9837

120

140

160

180

200

220

-7 -6 -5 -4 -3 -2

Colo

r I

nte

nsit

y

Log(Cu,M)

17

study, factors affecting detection limit of the developed sensor could be attributed

to immobilization of enzyme and hydrophobic barriers. Urease enzyme was

manually deposited on the paper and the immobilization was solely dependent on

physical absorption. Therefore, the distribution of enzyme on sensing zone owing

to spreading of the liquid droplets was not uniform. If reagents were dispensed

using a printer and the mobility of liquid phase was confined by a sol-gel matrix

as described by Hossain et al. (2011), the enzyme would be more uniformly

distributed and there would be enhancement in sensitivity and reproducibility of

the sensor. Moreover, effects from flows of fluid into the channels further had a

negative effect on the development of color in sensing zones. Regarding the

hydrophobic barriers, extended exposure of paraffin to testing reagents made the

borders more permeable to fluids. Consequently, hydrophobic barriers could not

confine the solutions inside sensing zone as expected. This could partly influence

the reproducibility of the test as enzymes and other reagents could have been

washed off the sensing zones. Within the limited time frame of the current study,

it was hardly possible to verify and address all the problems simultaneously.

Future studies should consider the use of a gel matrix for enzyme immobilization

and a different method for patterning hydrophobic barriers.

Table 2. The recovery (%) of Cu++ from validation test

log(Cu,M) Recoveries(%)

Founded Value Actual Value

Set 1

-3.46 -3 86.74

-4.48 -4 89.29

-5.88 -5 84.98

Set 2

-3.31 -3 90.76

-4.79 -4 83.58

-5.60 -5 89.24

Average recovery (%) 87.43

To validate the performance of the sensor, samples with known

concentrations were tested (Table 2). Recoveries varied from 83 – 91 % were

obtained and t-test showed that there was no significant difference (P=0.01, tstat=-

0.34<t4=3.75) between estimated and actual Cu++ concentrations. Based on the

tested performance, the sensor fabricated could be a viable method for screening

of Cu++ in food products.

3.4 Quantitative test

18

Colorimetric method was easy-to-use, inexpensive required no special

skills. However, image analysis was not as sensitive and selective as conventional

analytical instrumentation. Therefore, a quantitative scheme was implemented by

integrating the sensor into an electrochemical system (Digi Ivy 2013). Using

amperometric method, a constant potential was applied and resulting current was

recorded. With respect to the urea hydrolysis reaction (1), production of NH3

affected the ion balance of the solution and, consequently, the intensity of

measured electric current. Theoretically, the concentration of Cu++ was

proportional to degree of enzyme inhibition and indirectly to the amount of NH3

produced. The mechanism of the enzyme-inhibition reaction suggested that

electric current would have certain correlation to concentration of Cu++ in the

solution. Domínguez-Renedo et al. (2009) reported that the presence of heavy

metal induced inhibition of enzyme and subsequently led to decreased

amperometric signal. When samples containing various amounts of Cu++ (0.001 -

1ppm) were tested, interference was observed for Cu++ at 1ppm. The phenomena

was verified using cyclic voltammetry (data not shown) and it could be due to the

oxidation of Cu ion on the working electrode. As a result, solutions with lower Cu++

contents (0.001 – 0.1ppm) were used for electrochemical test. Preliminary

experiments demonstrated no clear relationship between measured current and

concentration of Cu++ using the fabricated sensor. Reproducibility of the

electrochemical test was then verified using the blank sample on different sensors

and the results were presented in Figure 13. It was clear from the graph that the

signals for the same sample were not reproducible on different sensors.

Critical analysis of the given electrochemical testing protocols revealed

potential factors which may affect the measured signals. They could be

hypothesized to include i) variation of resistance values of the current screen-

printed electrodes, ii) effects of electrode surface and iv) interference from

unknown impurities in the conductive inks or thinning agents.

19

Figure 13. Measured electrochemical signals using 4 different sensors in response to blank

A set of 32 sensors was first tested for values of resistance, from the

conductive pad to the tip of the electrode. Reference electrodes showed negligible

resistance value and were not different for the given sensors. However, working

and counter electrodes, made from carbon paste (Conductive Compounds

Company), were found to have significant variations in resistance values.

Resistances of working and counter electrodes had mean values of 315.94 ±

269.95 and 823.90 ± 540.80 ohms, respectively. Large standard deviations of

electrode resistances indicated large variations in quality of fabricated sensors

which could be one of the causes of poor reproducibility. To help eliminate the

differences of sensors, baseline corrections were conducted for individual sensors.

Electrochemical measurements were run for individual sensors using only buffer

solution and baseline was corrected based on blank sample (0 M Cu++) as follow:

Iii n

'

n (Eq.4)

nreference III (Eq.5)

where '

ni is the corrected current value of sample n, ni is the measured current

of sample n, referenceI is baseline current of blank sample and nI is base line current

of sample n.

-250

-200

-150

-100

-50

0

0 10 20 30 40

Cu

rren

t (µ

A)

Time (s)

S1

S2

S3

S4

20

Figure 14 Measured electrochemical signals in response to concentration of Cu++ (0-0.1 ppm) after baseline corrected.

Figure 14 showed the results of a typical amperometric test after baseline

correction. After 40 s, the current recorded were -12.52, -10.96, -9.59 and -7.83

µA for samples at 0, 0.001, 0.01 and 0.1 ppm, respectively. The responses were

contradictory to results obtained by Domínguez-Renedo et al. (2009) regarding

relationship between current signal and concentrations of heavy metals. Moreover,

the trends also varied among different tests. Additional experiments were further

attempted to partly phase out the effects of electrode resistances, electrode

surfaces and contamination of impurities. Amperometric measurements were

conducted for samples at different concentrations on the same sensor.

As evidenced from Figure 15, the recorded signals decreased proportionally

with increasing concentration of metal and the trend was consistent earlier findings

(Domínguez-Renedo et al. 2009). The findings pointed out that the consistency

of the fabricated sensors required significant improvement. In addition, other

electrochemical tests which can minimize the effects of impurity contamination

such as cyclic voltammetry, square wave voltammetry and pulse differential

voltammetry, etc were worth more trials.

-30

-25

-20

-15

-10

-5

0

0 10 20 30 40

Cu

rren

t (µ

A)

Time (s)

Reference

0.001

0.01

0.1

21

Figure 15. Current recorded from successive measurement of samples

containing different concentration of Cu++ (0-0.1ppm) on the same sensor

4. Recommended future studies

Within the time frame of the current research, not all problems could be

effectively addressed. To improve detection limit as well as electrochemical

analysis based of the existing sensor, it was recommended that the following

problems be investigated:

a. Utilization of sol-gel matrix to reduce the nonuniformity, leaching of

enzymes and other reagents. The approach was proposed by some authors

(Tsai et al. 2003; Hossain et al. 2011; Verma et al. 2010) and it seemed

that improved results were obtained.

b. Adoption of other electrochemical testing scheme such as bienzyme system

(Rodriguez et al. 2004), square wave voltametry, cyclic voltametry to

reduce the effects of sensor variations.

c. Trials with other electrode configurations to minimize the resistance

variation (Palchetti et al.2009 ,Crew et al.2011; Ge et al. 2012).

d. Considering the applicability of the device, stability of the sensor during

storage and its lifetime needs more researches.

e. Investigations are of essential as to explore the capacity of proposed

analytical sensor. For instance, the ability to detect more heavy metals are

of interest to disclosure. It was suggested by Krawczyk et al (2000) that

urease potentially inhibited by a wide range of metals

Hg++>Ag+>Cu++>Pb++>Cd++>Zn++>Ni++>Mn++ with sensitivity decreasing

accordingly.

-40

-35

-30

-25

-20

-15

-10

-5

0 10 20 30 40

Cu

rren

t (µ

A)

Time(s)

Reference

0.001

0.01

0.1

22

f. Replacing the key enzyme and establishing new signaling pathway, the use

of paper-based sensor could possibly be widen to other areas to detect also

pesticide, fungal toxins, bacteria or even DNA. (Hossain et al. 2009;

Luckham and Brannan. 2010; Crew. 2011; Ge et al. 2012)

5. Conclusion

In summary, this study had evidenced the applicability of a versatile paper-

based microfluidic biosensor for sensing heavy metals. Information on fabrication

protocols such as control of fluid flow, patterning hydrophobic barriers,

electrochemical analysis could be helpful for future studies on paper-based

biosensors. As compared to safe levels of Cu++ a significantly low detection limit

of 0.018 ppm was established and linear range from 0.01 – 1 ppm were obtained.

The performance of the sensor was further validated with samples at known

concentrations and recovery percentages were found to be from 83 to 91 %. The

current study was still unable to eliminate variations in characteristics of screen-

printed electrodes which could have been the causes of inconsistent trends in

electrochemical measurement. Nevertheless, the obtained results could provide

an important framework for continued research on paper-based biosensor for

detection of heavy metal.

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