Kaisong Yuan1,2, Carmen Cuntín-Abal1, Beatriz Jurado-Sánchez1,3, Alberto Escarpa1,3. 1. Department of Analytical Chemistry, Physical Chemistry and Chemical Engineering, University of Alcala, Alcala de Henares, E-28871 Madrid, Spain. 2. Shantou University Medical College, No. 22, Xinling Road, Shantou 515041, China. 3. Chemical Research Institute "Andrés M. del Río", University of Alcala, Alcala de Henares, E-28871 Madrid, Spain.
Abstract
Herein, we describe a Janus micromotor smartphone platform for the motion-based detection of glutathione. The system compromises a universal three-dimensional (3D)-printed platform to hold a commercial smartphone, which is equipped with an external magnification optical lens (20-400×) directly attached to the camera, an adjustable sample holder to accommodate a glass slide, and a light-emitting diode (LED) source. The presence of glutathione in peroxide-rich sample media results in the decrease in the speed of 20 μm graphene-wrapped/PtNPs Janus micromotors due to poisoning of the catalytic layer by a thiol bond formation. The speed can be correlated with the concentration of glutathione, achieving a limit of detection of 0.90 μM, with percent recoveries and excellent selectivity under the presence of interfering amino acids and proteins. Naked-eye visualization of the speed decrease allows for the design of a test strip for fast glutathione detection (30 s), avoiding previous amplification strategies or sample preparation steps. The concept can be extended to other micromotor approaches relying on fluorescence or colorimetric detection for future multiplexed schemes.
Herein, we describe a Janus micromotor smartphone platform for the motion-based detection of glutathione. The system compromises a universal three-dimensional (3D)-printed platform to hold a commercial smartphone, which is equipped with an external magnification optical lens (20-400×) directly attached to the camera, an adjustable sample holder to accommodate a glass slide, and a light-emitting diode (LED) source. The presence of glutathione in peroxide-rich sample media results in the decrease in the speed of 20 μm graphene-wrapped/PtNPs Janus micromotors due to poisoning of the catalytic layer by a thiol bond formation. The speed can be correlated with the concentration of glutathione, achieving a limit of detection of 0.90 μM, with percent recoveries and excellent selectivity under the presence of interfering amino acids and proteins. Naked-eye visualization of the speed decrease allows for the design of a test strip for fast glutathione detection (30 s), avoiding previous amplification strategies or sample preparation steps. The concept can be extended to other micromotor approaches relying on fluorescence or colorimetric detection for future multiplexed schemes.
Fast biomarker detection
is essential for personalized healthcare
and rapid disease treatment. Advances in nanofabrication allow for
the miniaturization of biosensors for such purposes, which along with
smartphone technology led to novel point-of-care (POCs) applications.
Such miniaturized devices are easy to use, holding considerable promise
to reduce costs, increase sampling throughput, and allow their use
in resource-limited settings.[1−3] In such devices, smartphones are
used as detection/readout parts; thus, the integration of sample preparation
compartments or reaction chambers is necessary. For example, lateral-based
flow strips can be easily coupled with mobile phones for fluorescence
detection of peptides indicative of heart failure[4] or colorimetric detection of uric acid in whole blood.[2] A paper-based plasma separation module has been
used in connection with a tailor-made reservoir for colorimetric detection
of total and direct bilirubin in the blood.[5] More sophisticated designs rely on the integration of microchips
for polymerase chain reaction for DNA amplification[6−8] or to promote
microbead aggregation via protein-specific linkage for prostate-specific
antigen detection.[9]Self-propelled
micromotors are microscale devices capable of autonomous
movement in solution.[10−15] In the analytical field, catalytic micromotors propelled by peroxide
decomposition in inner catalytic layers are the most used to date.
Indeed, their autonomous motion along with versatile functionalization
approaches leads to novel developments in the analytical field to
perform a myriad of assays directly using ultralow (nL−μL)
sample volumes.[16−20] The high towing force, small micromotor size, and the possibility
to introduce magnetic parts in its structure allow for efficient navigation
and control in microfluidic chips for future smartphone-based POCs.[21,22] A more promising approach to achieve this goal is the integration
of motion-based sensing approaches based on micromotors. Wang’s
group pioneer the concept after observing the enhanced movement experienced
by Au–Pt nanowires in the presence of Ag+ ions.[23] Changes in the speed were related to Ag+ concentration to develop the sensing strategy, which was
later extended for DNA sensing.[24] The limitations
of the movement of nanowires in salt-rich environments led to the
exploration of bubble-propelled catalytic micromotors. For example,
polymer–Au micromotors with an inner catalase layer experienced
diminished motion in the presence of certain ions (Hg)[25] or nerve agents vapor plumes[26] due to poison of the enzyme. Micromotors with inner Pt
catalytic layers can also be poisoned by thiol-containing metabolites,
resulting in a similar speed decrease.[27] Antibody-modified gold-nanoparticle-polyaniline/Pt micromotors have
been used in connection with secondary antibody-modified microspheres
for anticarcinoembryonic antigen detection. The presence of high concentrations
of the target analyte results in the aggregation of more microspheres,
resulting in a speed decrease in a concentration-dependent manner.[28] Turn-off motion approaches based on poly(3,4-ethylenedioxythiophene)/Au
micromotors[29] or Au/Ag/Ni/Au shells[30] have been described for DNA sensing. The principle
relies on DNA competition toward catalase-labeled secondary probes
(responsible for the propulsion) that are released, resulting in a
speed decrease. Yet, the above-mentioned approaches required the use
of high-performance optical microscopes, which prevents its use in
routine laboratories or in portable detection schemes.The recent
introduction of 3D printing and fast progress in smartphones
allow for the integration of motion-based micromotors assays for POC
diagnosis. Shafiee et al. developed a motion-based cellphone detection
system for HIV-1. The systems compromise a microchip and DNA-modified
micromotors consisting of platinum- and gold-modified polystyrene
beads (6 μm). The detection principle consisted of (1) sample
application in the reservoir of the microchip for loop-mediated isothermal
amplification of the nucleic acid of HIV-1; (2) mixing of resulting
amplicons with the DNA-modified micromotors; and (3) detection of
the motion of the resulting assemblies in peroxide solutions. The
presence of HIV-1 generates large amplicons that reduce the motion/speed
of motors (turn-off). Such a decrease is used as the analytical signal
for HIV detection at a concentration as low as 1000 virus particles
mL–1 with high specificity within an hour.[31] The same design but in a turn-on configuration
was also applied for Zika virus detection. In this case, 3 μm
beads modified with anti-Zika virus monoclonal antibody (anti-ZIKV
mAb) are used to capture the Zika virus, followed by attachment of
anti-ZIKV mAb platinum nanoparticles. The presence of virus in testing
samples results in the accumulation of an increased concentration
of Pt beads, causing the motion in peroxide solutions for the detection
of a concentration as low as 1 particle μL–1.[32] Despite their simplicity, such systems
still require the use of microchips for sample pretreatment and sophisticated
detection algorithms for motion detection as visual detection is not
possible.Inspired by previous micromotors works, herein we
describe a smartphone-based
detection platform for motion-based detection of relevant analytes.
The system relies on the direct coupling of a high-performance commercial
optical scope with the smartphone camera, allowing for the real-time
observation of 20 μm graphene (GO)-wrapped/PtNPs Janus micromotor
motion (see Figure A). A specifically designed 3D attachment allows for the integration
of a light-emitting diode (LED) source for illumination, a glass slide
holder to place a few microliters of the sample, and an easy system
for fast focus. The main aim is to simplify even more the configuration,
leading to a universal platform that can be coupled with any mobile
phone. The concept is demonstrated here to detect glutathione (GSH),
an important peptide biomarker that plays a critical role in cellular
functions. In addition, abnormally high levels of GSH (higher than
15 mM) can be related to many diseases, such as diabetes, or viral
infections, whereas extremely low levels have been associated with
Alzheimer’s disease.[33−36] Such compounds contain also a thiol group, which
can attach to the PtNPs responsible for micromotor motion, using the
decrease in the speed as an analytical signal. Direct visualization
of the speed decrease allows for the design of a test strip for GSH
detection, avoiding previous amplification strategies or sample preparation
steps. The smartphone device proposed here is affordable, is user-friendly,
and does not require special equipment, allowing for fast control,
i.e., in epidemics and remote areas.[37] The
versatility of the strategy allows for easy integration of other micromotor-based
sensing strategies relying on fluorescent or colorimetric detection
of a myriad of biomarkers, allowing for the design of multiplexed
schemes.
Figure 1
Smartphone-based platform design and proof-of-concept application
for glutathione (GSH) detection. (A) Integration of the smartphone
into a 3D-printed platform and description of the different parts
of the device. The schematic of the assembly is described in Video S1. (B) The corresponding picture of the
device. (C) Schematic of GSH detection with GO-wrapped/PtNP Janus
micromotors based on the decrease in the initial speed due to inactivation
of the catalytically active PtNPs by specific interactions with the
thiol group present in the GSH molecule. The time-lapse microscopy
images (taken from Video S2) illustrate
the Janus micromotor motion in the absence (left) and presence of
160 μM of GSH (right) using the smartphone-based platform.
Smartphone-based platform design and proof-of-concept application
for glutathione (GSH) detection. (A) Integration of the smartphone
into a 3D-printed platform and description of the different parts
of the device. The schematic of the assembly is described in Video S1. (B) The corresponding picture of the
device. (C) Schematic of GSH detection with GO-wrapped/PtNP Janus
micromotors based on the decrease in the initial speed due to inactivation
of the catalytically active PtNPs by specific interactions with the
thiol group present in the GSH molecule. The time-lapse microscopy
images (taken from Video S2) illustrate
the Janus micromotor motion in the absence (left) and presence of
160 μM of GSH (right) using the smartphone-based platform.
Experimental Section
Smartphone Device
The 3D platform for the cellphone
setup was designed using SolidWorks 2015 software. The platform contains
a LED source and a sample holder to place a glass slide. The 20×
to 400× Universal Tip scope was purchased from Amazon and directly
attached to an iPhone (Apple), which was used in all experiments.
Micromotor motion was directly observed in the camera application
of the phone, which was also used to record the Videos at 30 FPS.
Micromotor motion was tracked with the Particle Tracker module of
ImageJ free software (https://imagej.net/Particle_Tracker). Additionally, the commercial
Nikon NIS Elements AR 3.2 software and tracking module was used to
check the accuracy of the free software.An inverted optical
microscope (Nikon Eclipse Instrument Inc., TiS/L100) and a Zyla cMOS
digital camera were used to validate the smartphone platform. Movies
were captured and the speed of the micromotors tracked for comparison.
Micromotor Synthesis
All reagents were obtained from
Sigma-Aldrich (Spain) and used without further purification. Polystyrene
microparticles (cat. 87896) were dropped on a clean-glass slide to
generate a monolayer, which was covered with a ∼50 nm gold
by sputter coating. The modified beads were released in ultrapure
water by sonication (0.9 mL) and mixed with 0.1 mL of sulfhydryl-modified
graphene oxide (HS-GO) (cat. 763705) for 2 h to promote attachment
to gold by a thiol bond.[38] Next, the solution
was filtered to remove the excess reagents and dispersed in ultrapure
water (1 mL). The PtNPs were grown in situ in the microparticles by
mixing the solution with 200 μL of chloroplatinic acid hydrate
(1 mg mL–1, cat. 398322) and 20 μL of hydrazine
solution (35 wt % in H2O, cat. 309400) for 2 h. After that,
the reaction solution was filtered with a cyclopore track-etched membrane
(5 μm) to remove free PtNPs. The volume of the solution was
adjusted to 1 mL with ultrapure water and remained stable for 2 months
without any change in its properties.
GSH Detection
For detection, 1 μL of micromotor
solution was mixed with 1 μL of sodium dodecyl sulfate (cat.
71725, final concentration 3%), 1 μL of variable concentrations
of GSH (cat. PHR1359, from 0 to 160 μM) and 1 μL of H2O2 (cat. 216763, final concentration, 5%). Videos
were recorded after 30 s peroxide addition and the speed tracked as
previously specified. The analytical performance was evaluated through
the limit of detection (LOD), the limit of quantification (LOQ), selectivity,
and recovery. Calibration plots were obtained (n =
5) and the LOD or LOQ were calculated as 3 or 10 times the standard
deviation of the ordinate divided by the slope of the calibration
linear fit. Selectivity was evaluated against 160 μM of potentially
interfering species including cysteine (cat. W326305), serine (cat.
S4500), leucine (cat. L8000), arginine (cat. A5006), and bovine serum
albumin (cat. 05470). Recoveries were calculated by a 100-fold dilution
of human serum (cat. H4522). Prior to adding the desired amount of
GSH, its concentration in serum was determined with the micromotors
using a microscope and a phone. Next, the samples were fortified with
3, 25, and 160 μM of GSH.
Results and Discussion
Figure A illustrates
the setup of the micromotor-based detection platform. It consists
of a 3D-printed platform that can be easily tailored for many smartphone
models and a commercial magnification lens attached to the camera
of the phone (overall cost 19€, with an estimated 2-year lifetime).
An animation of the assembly is shown in Video S1. As can be seen, a sample holder for the inclusion of a
glass slide is incorporated, which along with easy-to-use adjustable
screws allows the movement for sample focus, like a high-performance
optical microscope. In that way, a real-time micromotor motion observation
can be achieved, even by nonspecialized personnel. The platform was
tested to develop a protocol for GSH detection in clinical samples.
To this end, we use Janus micromotors whose size is ideal for observation
with the designed system. Micromotors were synthesized using a strategy
previously developed by our research group.[38] Briefly, gold-sputtered PS microspheres were coated with GO modified
with −SH to promote attachment via a thiol bond with an Au
layer. The amount of GO for incubation with the PS-Au particles was
judiciously controlled to leave uncoated a small, asymmetric Au patch.
In this way, preferential growth of the catalytic Pt nanoparticles
is promoted, imparting the micromotors with the asymmetric Janus character
for efficient propulsion in peroxide solutions. To check this, we
incubate the PS-Au particles with variable amounts of GO-SH, followed
by PtNP attachment and subsequent EDX characterization. Additionally,
motion propulsion experiments were tested. Under nonoptimized conditions,
no motion performance is observed because GO covers the whole Au layer,
preventing preferential PtNP growth and thus movement.[38]Figure A shows the SEM and EDX images of the Janus morphology and
the elemental distribution of our micromotors. Also, as can be seen
in Figure B, the micromotor
size is uniform, with distinct Janus parts and a good density of micromotors
in the same batch. While Janus micromotors were used here to demonstrate
real-time detection, tubular designs or other configurations can be
easily observed with our device for future motion-based micromotor
sensing approaches.
Figure 2
GO/PtNP Janus micromotor characterization. (A) Scanning
electron
microscopy (SEM) and energy-dispersive X-ray mapping (EDX) mapping
showing the Janus morphology and elements distribution. (B) SEM images
showing the distribution and uniform micromotor size of a drop taken
from a micromotor batch. Scale bars, 10 μm.
GO/PtNP Janus micromotor characterization. (A) Scanning
electron
microscopy (SEM) and energy-dispersive X-ray mapping (EDX) mapping
showing the Janus morphology and elements distribution. (B) SEM images
showing the distribution and uniform micromotor size of a drop taken
from a micromotor batch. Scale bars, 10 μm.The schematic of the turn-off GSH sensing is depicted in Figure C. Initially, micromotors
propelled at a speed of over 162 ± 5 μm s–1 in 5% peroxide solutions. Yet, under the presence of GSH, the thiol
group present in the molecule can poison the PtNPs catalyst by the
specific union through a thiol bond. This blocks the catalytic active
area, preventing the decomposition of peroxide by the catalyst and
resulting in a decrease in the speed, which can be related to the
GSH concentration. Even more, 160 μM GSH concentrations result
in the almost complete stopping of the micromotor movement because
all active catalytic area is blocked by such an analyte.[27] This is further illustrated in the time-lapse
microscopy images of the inset in Figure B and the related Video S2. The images and videos were taken using a microscope (for
further details, see the Experimental Section), which clearly illustrates the micromotor movement by the naked
eye and the clear differences in the movement.The strategy
was next validated, and the results were compared
to those obtained with a high-performance optical microscope. Figure and related Video S3 illustrate the micromotor movement in
solutions containing increasing concentrations of GSH (from 10 to
160 μM). As can be seen, as the GSH concentration increases,
there is a decrease in the micromotor speed because less catalytic
area is available for peroxide decomposition. This is also revealed
by the bubble tail, with bigger and less abundant oxygen bubbles as
GSH concentration increases. The data were processed to obtain calibration
plots using the micromotor speed as an analytical signal. Figure B shows the calibration
plots obtained using both the smartphone and the conventional optical
microscope. The relevant analytic characteristics are summarized in Table .
Figure 3
Detection strategy and
calibration using a high-performance optical
microscope and a smartphone. (A) Time-lapse images (taken from Video S3) and tracking lines of micromotor navigation
in solutions containing increasing concentrations (0, 10, 100, and
160 μM) of GSH. The top part shows the images obtained with
a smartphone and the bottom part shows the one obtained with a high-resolution
optical microscope. (B) The corresponding calibration plots. Scale
bars, 20 μm.
Table 1
Analytical
Characteristics of GSH
Detection Using the Smartphone and the Optical Microscope
approach
linear range (μM)
R2
intercept (μm s–1)
slope (μm s–1 μM–1)
LOD (μM)
LOQ (μM)
microscope
2.8–160
0.997
123.9 ± 1.0
–47.4 ± 0.7
0.86
2.8
phone
2.8–160
0.998
126.1 ± 0.8
–48.0 ± 1.0
0.89
2.9
Detection strategy and
calibration using a high-performance optical
microscope and a smartphone. (A) Time-lapse images (taken from Video S3) and tracking lines of micromotor navigation
in solutions containing increasing concentrations (0, 10, 100, and
160 μM) of GSH. The top part shows the images obtained with
a smartphone and the bottom part shows the one obtained with a high-resolution
optical microscope. (B) The corresponding calibration plots. Scale
bars, 20 μm.As can be seen in Table , similar results were obtained using both
a smartphone and
an optical microscope. The LODs were 0.89 and 0.86 μM for the
smartphone and a microscope, respectively. The linear range span to
160 μM in both cases. Such LOD is similar to that obtained with
a chemiluminescent method using MnO2-nanosheet-modified
upconversion nanoparticles (0.9 μM)[39] or even lower than that obtained with fluorescent approaches using
polydopamine-doped nanoparticles in the presence of MnO2 (1.5 μM)[40] or AuNC@BSA–MnO2 nanoparticles (20 μM).[41] The LOD obtained with our method is slightly higher than that obtained
with a colorimetric approach using a Ru(bpy)32+-modified metal–organic framework in connection with the substrate
3,3′,5,5′-tetramethylbenzidinedihydrochloride (TMB)
(0.7 μM)[42] or fluorescent approaches
based on carbon dots (0.45 μM)[43] or
boron nitride quantum dots (0.2 μM).[44] Still, as the normal levels of GSH range from 500 to 15 000
μM, our strategy allows for the determination of such an analyte
at physiological conditions.[45]Next,
we evaluated the selectivity of the sensing strategy in the
presence of other amino acids with a structure similar to that of
GSH, which can cause potential interferences. Cysteine was tested
because it contains a thiol group and an amino group in its structure.
Serine, leucine, and arginine, which contain amino and COOH–
groups, were also evaluated. In addition, bovine serum albumin, a
protein commonly present in biological fluids and a well-known agent
that can cause the poisoning of Pt catalyst, was also tested.[46] As can be seen in the time-lapse images of Figure and the corresponding Video S4, the speed of the micromotor does not
change under the presence of 160 μM concentration of each interfering
compound, as compared with the drastic decrease noted in the case
of GSH. In the case of CYS, a thiol-containing compound, no decrease
in the speed is observed up to a 100 μM concentration. At 160
μM, a slight decrease in the speed from 160 ± 25 to 114
± 16 μm s–1 (n = 5 micromotors)
is produced. For higher CYS concentrations (250–1000 μM),
the speed decreases from 85 ± 5 μm s–1 to almost 0. Yet, much higher concentrations of cysteine (more than
250 μM) are needed to greatly affect the micromotor speed for
quantitative purposes, whereas for GSH, only a 160 μM concentration
is needed to completely stop the micromotors (for additional data,
see Figure S1). This can be attributed
to the relatively smaller molecular size of CYS (MW, 122 g mol–1) compared with GSH (MW, 307 g mol–1), thus higher concentrations of CYS are needed to completely block
the Pt catalyst. In a previous work using tubular micromotors driven
by Pt catalyst, a similar effect was reported for a 100 μM concentration
of both compounds, where the initial micromotor speed decrease almost
2.6 times in the presence of GSH but 1.4 times in the presence of
CYS.[27] For BSA, a slight speed decrease
to 149 ± 19 μm s–1 is noted, probably
due to an increase in the viscosity of the samples. A marked decrease
is produced by increasing the concentration up to 500 μM. Such
results testified to the high selectivity of our sensing protocol.
Selectivity was both evaluated with the smartphone and the optical
microscope, obtaining similar results in both cases.
Figure 4
Selectivity of the detection
strategy and detection performance.
(A) Time-lapse images (taken from Video S4) and the corresponding tracking lines of micromotor navigation in
solutions containing 160 μM of GSH, cysteine (Cys), serine (SER),
leucine (LEU), arginine (ARG), and bovine serum albumin (BSA). The
top part shows the images obtained with a smartphone and the bottom
part the one obtained with a high-resolution optical microscope. (B)
The corresponding speed in the presence of the different interferences.
Scale bars, 20 μm.
Selectivity of the detection
strategy and detection performance.
(A) Time-lapse images (taken from Video S4) and the corresponding tracking lines of micromotor navigation in
solutions containing 160 μM of GSH, cysteine (Cys), serine (SER),
leucine (LEU), arginine (ARG), and bovine serum albumin (BSA). The
top part shows the images obtained with a smartphone and the bottom
part the one obtained with a high-resolution optical microscope. (B)
The corresponding speed in the presence of the different interferences.
Scale bars, 20 μm.For future practical
applicability by nonspecialized personnel,
we developed a protocol for GSH sensing in clinical samples, as shown
in Figure . As can
be seen, the device can be prevalidated to construct the calibration
plot in the presence of increasing concentrations of GSH. Pictures
of the micromotor motion and displacement were taken, with a line
at the left indicating the distance traveled by the micromotor. Differences
in the bubble tail can be also checked. The strip correlates the distance
traveled with a color and GSH concentration, so an operator just needs
to observe the motion in the phone to make an estimate of GSH concentration
for fast response. The detection can be performed in less than 30
s and just requires dropping the sample (human serum or plasma) on
a glass slide along with the micromotor and fuel solution. The device
can be used multiple times and the strategy can be extended to any
smartphone as the magnifying lenses can be attached to any camera.
The average micromotor cost per analysis is estimated to be 0.05€,
considering the cost of peroxide, surfactant, and micromotors (in
each synthesis, a total volume of 1 mL of micromotor suspension is
obtained, but only 1 μL is required per analysis).
Figure 5
Protocol for
GSH detection using the smartphone-based platform.
Test strip readout based on the displacement of the micromotors in
the real samples and correlation with GSH concentration and colorimetric
evaluation under the presence of TMB as a substrate.
Protocol for
GSH detection using the smartphone-based platform.
Test strip readout based on the displacement of the micromotors in
the real samples and correlation with GSH concentration and colorimetric
evaluation under the presence of TMB as a substrate.While effective and advantageous in terms of negligible sample
processing, the developed smartphone micromotor-based platforms still
have some limitations which prevent their true use as POC devices.
First, low expeditiousness in sample processing (which requires dropping
on the slide and individual measurement of the sample) needs to be
addressed by the incorporation of automatic sampling in the future.
Second, while direct observation of the sensor is possible, some training
is required for micromotor focusing, monitoring, and speed tracking.
This can be easily addressed by the development of specific software
to be installed in a smartphone as an application, yet it can increase
the cost. All this requires future works to transform the developed
platform into a real POC device.As a double check confirmation
and complement to the motion-based
test strip, a fast colorimetric test with the micromotors can be performed.
To this end, TMB was used as a substrate. Under the presence of H2O2 and nanomaterials with peroxidase-like activity
(graphene, platinum nanoparticles), OH– radicals
are oxidized, generating a blue color in the solution.[47,48] Surprisingly, under the presence of the interferences, no blue color
was developed, probably because all of the peroxide was decomposed
into oxygen and water without the generation of intermediate OH– radicals by the high catalytic activity of PtNPs.[49] Yet, under the presence of GSH, the deep blue
color is generated. Although some authors have reported that GSH can
reduce back TMB, resulting in a decrease in color,[50,51] we observed the opposite. Color appearance in the solution is observed
at concentrations up to 10 μM of GSH. We hypothesize that all
GSH attaches to the PtNPs in the micromotors, thus blocking the active
part responsible for the reduction of GSH. This, in turn, reduces
the catalytic activity, thus some H2O2 in the
solution can react with the graphene oxide present in the micromotor,
generating OH– ions that oxidize the TMB and generate
the blue color. We tested also the colorimetric TMB assay in the presence
of the 1000 μM concentration of CYS. No blue color is generated,
probably because CYS at a high concentration can inhibit TMB oxidation
to generate a blue product, as described in the previous report.[52]To illustrate the applicability of the
smartphone-based platform,
we fortified human serum samples with different levels of GSH to simulate
a protocol for further application in disease monitoring. It is well-known
that GSH levels in normal serum samples are within the range from
500 to 15 000 μM.[53] Thus,
to fit the linear range reported for our method, we diluted the samples
nearly 100-fold with the PBS buffer, thus GSH is within the range
from 5 to 150 μM after dilution. Before performing recovery
experiments, we applied our strategy (both using the microscope and
the phone device) for the detection of GSH in the serum samples (100-fold
dilution) prior to fortification. As can be seen in Figure , the measured concentration
of GSH in serum is about 6 μM (600 mM), which is within the
normal reported range. Such a figure also shows an example of a schematic
of disease monitoring using our device, with an associated concentration
range of “gluthationemeter” (considering the 100-fold
dilution of the serum sample). Low levels of GSH (bellow 5 μM,
in orange in Figure A) are indicative of the oxidative stress associated with Alzheimer’s
and Parkinson’s diseases, as well as health failure or diabetes.[54,55] Values from 5 to 150 μM (in green in Figure A) indicate normal GSH levels. High GSH levels
(in red in Figure A) have been associated with cancer and can induce tumor resistance
to chemotherapy.[56,57] The micromotor-based smartphone
device reported here can be used to monitor the level of GSH in cancer
patients along with other biomarkers, with high levels associated
with the tumor state and efficiency of the treatment.
Figure 6
Health and disease state
prognosis using the micromotor-based POC
device for GSH detection. (A) Schematic illustration of the concept
consisting of blood serum dilution, measurement, and corresponding
GSH levels related to health and potential nonhealthy conditions.
(B) GSH determination in diluted human serum and recoveries obtained
with a microscope and a smartphone (n = 3).
Health and disease state
prognosis using the micromotor-based POC
device for GSH detection. (A) Schematic illustration of the concept
consisting of blood serum dilution, measurement, and corresponding
GSH levels related to health and potential nonhealthy conditions.
(B) GSH determination in diluted human serum and recoveries obtained
with a microscope and a smartphone (n = 3).Additional recovery experiments also testified
to the feasibility
of the smartphone platform for disease monitoring. We assayed concentration
at all of the range studies (low–normal–high), obtaining
excellent recoveries in all cases, ranging from 91.2 to 98.7%. Such
values indicate quantitative analyte measurement, assuring the validity
of the analytical method for its application in real samples.
Conclusions
We have reported here a smartphone portable device based on micromotors
for the naked-eye detection of clinical relevance biomarkers for future
decentralized analysis and use in remote settings. The coupling of
a high-magnification lens allows to directly observe and record videos
of the motion of 20 μm graphene-wrapped/PtNP Janus micromotors
using a phone camera in an easy manner. Yet, while Janus micromotors
are used here to illustrate the concept, the strategy can be easily
extended to other designs such as wires, tubular, etc. The concept
was successfully illustrated for the motion-based detection of glutathione,
an analyte of high clinical relevance, with excellent selectivity
and practical levels. A test strip that correlates the distance traveled
with GSH concentration allows for direct observation of the micromotor
motion in the phone to make an estimate of GSH concentration for fast
response. The detection can be performed in less than 30 s and just
requires dropping the sample (human serum or plasma) on a glass slide
along with the micromotor and fuel solution, with an average cost
of 0.05€ per analysis. The validation against a high-performance
optical microscope further testifies the utility of our universal
device. As such, the smartphone device meets the World Health Organization’s
criteria (affordable, sensitive, specific, user-friendly, rapid, equipment-free).
Future efforts should be aimed at extending the strategy to other
micromotor-based sensing approaches relying on fluorescence or colorimetric
detection for the design of multiplexed schemes. Current challenges
such as low expeditiousness and the development of specific software
to simplify speed measurement still need to be addressed.
Authors: Shih-Chuan Liao; Jing Peng; Michael G Mauk; Sita Awasthi; Jinzhao Song; Harvey Friedman; Haim H Bau; Changchun Liu Journal: Sens Actuators B Chem Date: 2016-06-28 Impact factor: 7.460