Analytical
Methods
PAPER

Cite this: Anal. Methods, 2018, 10,3066

A low-cost integrated biosensing platform basedon SiN nanophotonics for biomarker detection inurine
D. Martens,ab P. Ramirez-Priego,c M. S. Murib,ab A. A. Elamin,d A. B. GonzalezGuerrero,c M. Stehr,d F. Jonas,d B. Anton,e N. Hlawatsch,e P. Soetaert,f R. Vos,g
A. Stassen,g S. Severi,g W. Van Roy,g R. Bockstaele,f H. Becker, e M. Singh,dL. M. Lechugac and P. Bienstman *ab
We present a low-cost integrated nanophotonic lab-on-a-chip platform suitable for point-of-care (POC)
biomarker analysis. The sensor chip included in the platform contains multiplexed Mach–Zehnderinterferometers with an on-chip optical spectral analyser consisting of an arrayed-waveguide grating.
The sensor chip is fabricated in silicon nitride material, which makes it compatible with consumerelectronics-grade sources and detectors, leading to the possibility of low-cost instrumentation. The
nanophotonic sensor chip exhibits a detection limit of 6  106 RIU (Refractive Index Units), which is in
the same order of magnitude as the reported values for state-of-the-art evanescent wave sensors. The
sensor chip is biofunctionalised with speciﬁc bioreceptors and integrated into a polymer microﬂuidic

Received 26th March 2018
Accepted 4th June 2018cartridge. The POC instrumentation platform contains optical excitation and read-out sub-systems anddedicated on-board software for real-time analysis of patient samples. To demonstrate the versatility ofthe platform, we present results both on the detection of an antigen related to tuberculosis directly in

DOI: 10.1039/c8ay00666k

urine samples using a laboratory prototype and on the detection of a protein biomarker (CRP) related to

rsc.li/methods

inﬂammation using the integrated instrument.

Introduction
Integrated evanescent eld photonic biosensors are promising
candidates for real-time qualitative and quantitative evaluationof biomolecular interactions. In these sensors, a change in theeﬀective refractive index caused by the binding of an analyte toits specic bioreceptor is converted into a measurable quantity,
most commonly a resonant wavelength shi, through an integrated photonic transducer. Various types of sensors have beendeveloped: Young and Mach–Zehnder (MZI) interferometers,
bimodal sensors, ring resonators, photonic crystal based
sensors and various others.1–5 In general, evanescent wave
sensors provide sensitivity, selectivity and versatility, whichmakes them applicable in a broad range of disciplines, rangingaPhotonics Research Group, Ghent University, Imec, Technologiepark-Zwijnaarde 15,
B-9052 Ghent, BelgiumbCenter for Nano- and Biophotonics (NB-Photonics), Ghent University, Ghent, BelgiumcNanobiosensors and Bioanalytical Applications Group, Catalan Institute of
Nanoscience and Nanotechnology (ICN2), CSIC, BIST, CIBER-BBN, Campus UAB,
Bellaterra, 08193 Barcelona, Spaind

LIONEX Diagnostics and Therapeutics GmbH, Braunschweig, GermanyeMicrouidic ChipShop GmbH, Stockholmer Str. 20, D-07747 Jena, GermanyfTrinean NV, Dulle-Grietlaan 17/3, 9050 Gent, Belgiumg

7 Imec, Kapeldreef 75, 3001 Leuven, Belgium

3066 | Anal. Methods, 2018, 10, 3066–3073

from medicine and food quality control to environmental
management. Furthermore, they oﬀer great potential as lab-ona-chip devices, performing point-of-care measurements at anaﬀordable cost.
While practical applications have emerged, in many cases
the readout of these sensors requires either an expensive
tuneable laser or an oﬀ-chip spectrometer, making them
expensive and/or slow. Therefore, the instrumentation cost is
typically high, rendering the system unt for true point-of-careapplications. We aim to overcome this important barrier byusing a broadband light source in combination with an on-chip
spectral lter as the interrogation mechanism.6–8 The lter
divides the transducer spectrum into diﬀerent wavelength
channels with spatially separated output ports. By tting a curveto this dataset, the central wavelength of the original sensor
spectrum is determined with an accuracy that surpasses theresolution of the spectral lter itself by multiple orders ofmagnitude.
The manuscript is structured as follows. First, we present
how such sensor chips can be designed and fabricated using
mass-fabrication-compatible technology. Before moving on toa fully integrated platform with dedicated microuidics andreadout components, we rst characterised the performance ofthe sensor chip in a lab-based prototype with in-house microuidics. We determine the bulk limit-of-detection and thenThis journal is © The Royal Society of Chemistry 2018

PaperAnalytical Methods

move further to perform biosensing experiments to detect
Mycobacterium tuberculosis lipoarabinomannan (LAM) in clinical samples. Aer that, we move from a lab-based prototype toa fully integrated platform that is closer to commercialisation.
We discuss how these silicon nitride based sensor chips can be
integrated into a standard polymer uidics cartridge, anddescribe in more detail the custom readout instrument and theassociated soware. Finally, this integrated platform is used todetect the C-reactive protein biomarker, related to inammatory processes.

Photonic sensor design
The most important property for an integrated photonic sensor
to enable use as a point-of-care diagnostic device is compatibility with a cheap read-out system, requiring no expensive
components such as tuneable lasers or oﬀ-chip spectrometers.
In our design, the approach is to interrogate the sensor throughan oﬀ-chip broadband light source, an on-chip spectral lter
and an oﬀ-chip camera, all of which are aﬀordable in a point-ofcare context. This is especially true for the very near-infrared
wavelength range, which can be used due to the choice ofsensor material. The spectral lter employed is an Arrayed
Waveguide Grating (AWG), which is a state-of-the-art design inthe given wavelength range (850 nm) in terms of footprint aswell as performance.9
As a sensor for this interrogation scheme, a Mach–ZehnderInterferometer (MZI) was selected, with one of the arms isolated
from and the other exposed to the analyte. The main merit ofthis MZI conguration is its large design freedom, whichenables tuning the sensitivity and spectral period independently. The latter is relevant, as the characteristics of integrated
spectral lters are typically restricted by fabrication limitations,10 and their ratio has a large inuence on the nal
performance of the sensor.6 The light interfacing with the chipoccurs through grating couplers. At the input side, the grating
couplers are ood-illuminated by a broadband light source.11
This method allows interrogating multiple sensors at the sametime, and as such opens the door to multiplexing. At the output
side, the transmitted power of a large number of grating
couplers is measured in parallel with a camera. A picture of thecomplete design of the photonic sensing circuit is shown in
Fig. 1.

Interrogation principle based on a broadband source and an
on-chip spectral ﬁlter.

Fig. 2The transduction mechanism is based on the evanescenteld: a change in the environment of the exposed MZI arm,such as a binding event or a bulk refractive index shi, will
result in a change in the eﬀective refractive index of the exposed
MZI arm. This, in turn, results in a phase shi in this arm,
which causes a spectral shi in the whole spectrum of the MZI.
This shi is tracked through continuous monitoring of thelocations of the spectral peaks of the MZI. To determine thepeaks of this spectrum, we illuminate the chip using a broadband light source. The spectrum of the MZI sensor (Fig. 2a) issent through the diﬀerent channels of the spectral lter(Fig. 2b), yielding a discretised version of the sensor spectrum(Fig. 2c). The resolution of this spectrum is typically low, as it islimited by the number of available data points per spectral
period, determined by the channel spacing of the on-chip
spectral lter. To compensate for this drawback, the original
spectrum is reconstructed from the discretised data throughtting (Fig. 2d), and the peak of this reconstructed spectrum istracked. This greatly increases the accuracy of the obtained peakwavelength values. This procedure is more elaborately
described in ref. 6. Compared to other interrogation mechanisms based on tuneable lasers, our approach with an integrated spectral lter allows the use of cheap LEDs, bringing thecost of the source from thousands of dollars to a few dollars or
less.
The whole sensing chip contains 6 sensors, each of themwith their MZI and AWG, as well as 30 output grating couplers
per sensor, one for each of the AWG channels. The entire design
ts in a chip area of less than 6 mm  6 mm (Fig. 3).

Sensor fabrication
Fig. 1 Integrated photonic sensor circuit consisting of a MZI sensor
read-out by an on-chip AWG spectral ﬁlter.

This journal is © The Royal Society of Chemistry 2018

Photonic integrated circuit (PIC) sensors were fabricated basedon the CMOS compatible SiN photonics developed at imec,

Anal. Methods, 2018, 10, 3066–3073 | 3067

Analytical Methods

Paper

into the SiN to maximise light coupling into the waveguide. Auorine-based inductively coupled plasma reactive ion etchingprocess was used to minimise the sidewall roughness andachieve the required sidewall slope. Next, waveguides weredened by a separate 193 nm DUV lithography step anda similar etch, but now the full thickness of the SiN layer wasetched. Following this process, a 2 mm layer of PECVD SiO2 was
deposited and planarised by CMP. Finally sensing regions weredened by lithography using the i-line of Hg at 365 nm followed
by a selective removal of the top oxide cladding using a dry
etching process followed by a wet etching step.
Layout of a sensing circuit consisting of 6 sensors, each of themwith their own MZI and AWG.

Fig. 3using wafer-level processing on standard 725 mm thick 200 mm
Si wafers.10 First a 70 nm thick SiN anti-reective coating was
deposited using plasma-enhanced chemical vapour deposition(PECVD) using SiH4, N2 and NH3 at 400  C (Fig. 4). The purposeof this layer is to decrease the back-reections coming from theoxide–Si interface, which would reduce the light incouplingeﬃciency of the grating couplers. Subsequently, a 2.3 mm thick
PECVD SiO2 layer, which had been specically engineered tocompensate for the stress level of the wafers, was depositedusing SiH4 and N2O. The roughness of the layer was reduced byapplying a short chemical–mechanical polishing (CMP) step.
On top of this oxide layer, a 220 nm thick PECVD SiN layer was
deposited using SiH4, N2 and NH3 at 400  C. This waveguidematerial has been optimised to minimise the light propagation
loss in the visible wavelength range.10 Refractive indices at l ¼
850 nm were nSiO2 ¼ 1.48 and nSiN ¼ 1.88 as measured byellipsometry.
Grating couplers were dened using 193 nm deep ultraviolet(DUV) lithography followed by a shallow etch of 110 nm depth

Fig. 4 Process ﬂow for the SiN photonic chip fabrication. (1) Si
substrate, (2) deposition of the anti-reﬂective coating, (3) depositionand chemical–mechanical polishing (CMP) of the bottom clad, (4)deposition of the SiN waveguide layer, (5) shallow etch of the grating
couplers, (6) deep etch of the waveguides, (7) deposition and CMP of
the top clad, and (8) clad-open etch.

3068 | Anal. Methods, 2018, 10, 3066–3073

Evaluation of the bulk sensitivity
Sensors were initially characterised through bulk sensing ina lab-based setup, with equipment compatible with point-ofcare sensing. The bulk sensing limit-of-detection (LOD)
provides an excellent gure-of-merit as it can be compared
between various sensor types regardless of surface biofunctionalisation. To evaluate this value, the sensor is exposed
to diﬀerent concentrations of a solution (i.e.: HCl) in alternation
with water. An example of a resulting sensorgram, where 5
sensors are measured in parallel, is shown in Fig. 5.
To determine the LOD, the following procedure was used.
The shis of the spectra are tracked, and the sensitivity of eachsensor is calculated as the slope of the obtained spectral shis
as a function of the corresponding changes in the bulk refractive index. The minimum detectable wavelength shi is calculated as 3 times the standard deviation on the signal aertransients have passed. The ratio of minimum detectablewavelength shi to sensitivity yields the LOD. This experiment
was done multiple times, with diﬀerent chips from diﬀerent
wafers. The set of experiments yielded an average LOD of 6 106 RIU, with a standard deviation of 2  106 RIU. This
indicates a high reproducibility (given that we used diﬀerent
chips) as well as results competitive with most integrated
photonic sensors, despite the low-cost read-out.6

Sensorgram of parallel measurement of ﬁve MZI sensors, where
the sensors are exposed to diﬀerent concentrations of HCl in alternation with water.

Fig. 5This journal is © The Royal Society of Chemistry 2018

PaperAnalytical Methods

LAM detection in urine (lab setup)
Before building an integrated readout system with a dedicatedmicrouidic cartridge, we rst tested the functionality of thesensor chip by performing LAM measurements in clinical urine
samples. LAM is a biomarker indicative of tuberculosis (TB)
infection,12 and we correlated the measurements with thedisease status of the participants. All experiments were performed in compliance with the relevant German and Spanish
laws and institutional guidelines, and were approved by the
Aerztekammer Niedersachen and the National Institute ofMedical Research Tanzania. Informed consent was obtained.
To prepare the chips, anti-LAM IgM mAb molecules werecovalently immobilised on the SiN chips using a silane
route.13,14 Prior to any functionalisation, the SiN chips werecleaned in acetone, isopropanol, and ultrapure water. Next, thechips were exposed to oxygen plasma for one minute using
a reactive-ion etching (RIE) system to terminate the surface withhydroxyl groups. Aerwards, the silanisation of the chips was
carried out by liquid-phase deposition of silanes in an organic
solvent.14 The chips were placed in a 600 mM solution of (3amino-propyl)tri-ethoxysilane (APTES, 99%; Sigma-Aldrich,
Steinheim, Germany) in toluene ($99.9%, Sigma-Aldrich) for
15 hours in a nitrogen-lled glove-box. To wash oﬀ unbound
APTES molecules, the chips were rinsed with toluene, followedby tetrahydrofuran (THF, $99.9%, Sigma-Aldrich). Aer drying
the chips under a nitrogen ow, they were cured for 30 minutes
at 120  C, resulting in an especially strong adhesion of the
APTES layer to the surface.14 This way, the surface becomesmodied with amines, allowing for the subsequent reaction
with succinic anhydride (SA) in order to yield a carboxylterminated surface.13,15 Succinic anhydride (SA, $99.9%,
Sigma-Aldrich) was used as a cross-linker molecule to ensure
the binding of the amino group of APTES to the NH2 groups ofthe anti-LAM by providing carboxylic groups at the surface. For
this purpose, the chips were placed overnight in a solution of
800 mM SA in acetonitrile (ACN) (anhydrous, 99.8%, SigmaAldrich), aer which they were rinsed with pure acetonitrileand dried under nitrogen gas. The amine-terminated surface
reacts with one of the two carbonyl groups of the SA molecules,
causing the anhydride ring to open and to form a covalent bondwith this carbonyl group. The other carbonyl group is released toform a free carboxylic acid-terminated surface.16 The anti-LAM
molecules were randomly oriented and covalently coupled tothe carboxyl-terminated SiN chips using the zero-length crosslinker 1-ethyl-3-3-dimethylaminopropyl-carbodiimide (EDC) in
2-[N-morpholino]-ethanesulphonic acid (MES) buﬀer at room
temperature. We found experimentally that a twofold blocking
layer with 0.5 mg mL1 PLL(20)-g[3.5]-PEG(5) (SuSoS) and 10 mg
mL1 BSA-A7906 (Sigma-Aldrich) was required to avoid nonspecic adsorptions when evaluating urine.
Fig. 6 shows the experimental setup used to perform theevaluations of urine samples. In this set-up, an external syringe
pump is employed to pump uids. A dual mode injector valve isused to load the samples to be tested in line with the neutral
PBS buﬀer. During the experiment, rst the buﬀer is owed toThis journal is © The Royal Society of Chemistry 2018

Fig. 6

Experimental setup of the lab-based prototype.

establish the baseline, then the clinical sample, followed by the
buﬀer again to wash away any nonspecic binding. The sensor
chip is squeezed under a home-made PDMS microuidic
channel. The light source is an 850 nm SLED. The signal iscollected using a CMOS camera, which is connected to thecomputer to analyse the detected signal.
A series of urine samples of healthy and non-healthy persons
were selected for experimental tests. Apart from testing the lab
prototype, the use of actual urine samples also allows us toevaluate the eﬀect of nonspecic binding. The samples werepumped into the microow cell at a rate of 10 mL min1 for 20
minutes. Results from four sensors on the chip were analysed.
Fig. 7a and b show the real-time interaction of urine ofhealthy and non-healthy persons with the anti-LAM molecules
immobilised on the SiN sensors. First, 1 PBS (pH ¼ 7) was
administered to the sensors. Aer stabilisation of the signal,
200 mL of a urine sample was injected onto the sensors.
In the case of samples from healthy persons, initially a highspectral shi was encountered due to buﬀer exchange. Thishigh spectral shi was only temporary and started to return toits starting value aer a while since no LAM/anti-LAM binding
was occurring. When 1 PBS was injected aerwards, thespectral shi moved back to a very low value (220 pm) as
compared to the initial shied value. The spectral shi did notcompletely return to its starting value and this can be attributed
to nonspecic binding of residuals present in the urine samples
to the sensor surface.
In the case of samples from non-healthy persons, a highincrease in the spectral shi was encountered due to the buﬀer
eﬀect. However, aerwards, when the 1 PBS was injected,
a high permanent spectral shi compared to its initial value was
encountered. This is due to the fact that LAM was present in theurine and it eﬃciently bound to the anti-LAM immobilised on
the sensor surface. In Fig. 7b, the non-healthy sample caused
a permanent spectral shi of about 6 nm.
A series of urine samples from four healthy persons and four
non-healthy persons was measured. The results are summarised in Table 1. A maximum permanent spectral shi of 0.85 nm
was obtained for healthy persons. The samples from nonhealthy persons caused a minimum permanent spectral shiAnal. Methods, 2018, 10, 3066–3073 | 3069

Analytical Methods

Paper

Microﬂuidic cartridge

Fig. 7 Spectral shift for healthy (a) and non-healthy (b) persons.

Table 1 List of the spectral shift due to a series of samples fromhealthy and non-healthy persons

Sample type

Spectral shi

Healthy # 1
Healthy # 2
Healthy # 3
Healthy # 4
Non-healthy # 1
Non-healthy # 2
Non-healthy # 3
Non-healthy # 4

0.75 nm0.85 nm0.22 nm0.50 nm6.00 nm5.50 nm7.00 nm4.00 nmof 4 nm and a maximum permanent spectral shi of 7 nm,
depending on the concentration of the LAM present in the urine
samples. The permanent spectral shi obtained for samples of
non-healthy persons is very high compared to the permanent
spectral shi obtained due to the healthy samples. Moreover, as
can be noticed from Fig. 7a and b, the shape of the sensorgramsin both cases is also very diﬀerent: while the sample is still
being injected, the spectral shi already starts to decrease forthe healthy person sample, which is not the case for the nonhealthy person sample.
Finally, the sensorgrams also show that an assay time of 10
to 15 minutes is feasible. Also worth noting is that the experiments were done at room temperature and that no sample
preparation was performed.

3070 | Anal. Methods, 2018, 10, 3066–3073

Microuidic cartridge bodies were injection-moulded in COC(cyclo-olen-polymer, trade name Topas). This allows for a costeﬀective large-scale production, so that the cartridges can bemade cheap enough to be disposable.
For the integrated cartridge design, an injection moulding
platform of a microscopy slide format with a footprint of
75.5 mm  25.5 mm was chosen. This format provides an easyto-handle size on which all relevant uidic and detection
functionalities were accommodated, allowing for a high integration density with various functional elements for sucha disposable cartridge.
A photograph of a microuidic cartridge with the integrated
photonic chip is depicted in Fig. 8.
For the inlet of the urine sample and required reagents, theintegrated cartridge includes female Luer interfaces being
compatible with standard syringes, as commonly used.
An integrated lter ensures the retention of coarse components from the urine sample and an integrated air bubble trap
retains undesirable air bubbles. At the end of the uidic path,a reservoir for easy liquid waste handling is placed, followed byan air vent to allow air to escape from the cartridge when thewaste reservoir lls up.
With respect to the integration of the sensor chip, there is anappropriately designed recess on the top, while the rest of the
cartridge is designed to leave parts of the chip exposed for easy
optical access. Indeed, light is coupled into and out of the chip
through grating couplers, and these need to stay exposed.
Fig. 9 shows an intersection through the sensor area of the
microuidic cartridge. Note that the photonic chip is positioned
upside down and that the optical detection is performed fromthe bottom side.

Integrated readout instrument
The fabricated readout instrument is shown in Fig. 10. The POC
platform includes the optical readout, the pumping unit interfacing with the cartridge, and a touch screen with the userinterface. The size of the instrument is determined by the
choice of using vertically oriented syringes to load the samples
and the buﬀers.

Fig. 8 Assembled microﬂuidic cartridge.

This journal is © The Royal Society of Chemistry 2018

PaperAnalytical Methods

Fig. 11 Optical readout module (upside down).

Fig. 9 Cross section (bottom) through the microﬂuidic cartridgealong section A–A (indicated in the top ﬁgure).

The unit is mounted upside down in the bottom part of the
instrument. The light source (SLED) and the detector (CMOS
sensor) are both commercial oﬀ-the-shelf components, coupled
to a custom lens system.
Three syringe pumps are integrated into the readout
instrument (Fig. 12). Each pump has a stepper motor directly
driving a piston up and down. The piston pushes the plunger ofthe syringe downwards, transferring the contents of the syringe(buﬀer, sample, .) to the cartridge. As the distance between thesyringes is small, the piston axis is not in line with the stepper
motor axis, but parallel. A dry bearing system is used to guidethe piston up and down. The piston also includes a pressure
sensor, to detect mechanical contact between the piston head
and the syringe plunger. To increase condence in themeasurements, an extra ow monitoring system was also
installed, consisting of a separate camera system to image theuidic channel to perform bubble detection.
Custom soware was written to reliably identify the positionof the output grating couplers in the images captured by the
CMOS sensor. The intensities of these spots are then used ina tting procedure, which allows us to track the position of thepeak wavelength as a function of time.
Fig. 13 shows a simple proof-of-concept sensing experimenton the instrument using the actual microuidic cartridge,
which measures the physical adsorption of BSA on an unfunctionalised sensor chip.

Fig. 10 Integrated readout instrument.

When designing the concept of this instrument, importancewas given to exibility, the possibility to test alternatives tospecic parts, ease of assembly, ease of shipment and systeminstallation at test sites. Likewise it should be noted that –although the readout architecture is selected to be low-cost – theprototype instrument design is also not yet optimised for cost.
For example, the integration of the full Windows-PC including
a high-resolution touch screen certainly adds to the cost of thesystem, but also oﬀers exibility to update soware in a latestage of the development (testing) cycle.
The optical readout unit (Fig. 11) contains the light source aswell as the light sensor to interrogate the optical biosensor chip.

This journal is © The Royal Society of Chemistry 2018

Fig. 12

Pump unit.

Anal. Methods, 2018, 10, 3066–3073 | 3071

Analytical Methods

Fig. 13 Physical adsorption of BSA using an unfunctionalised
cartridge.

Paper

Fig. 14 Real-time monitoring of diﬀerent CRP concentrations and
BSA as a control with the biosensor instrument.

Biosensing with the integrated readout
instrument
Finally, this setup was used to perform biosensor experiments
using functionalised chips. As a model system to test the
prototype, the immunosensing of the C-reactive protein (CRP)
biomarker was chosen. CRP is a widely used biomarker inpatients that plays an essential role as an early indicator ofinammation and infection, and is also used as an indicator of
prognosis for cardiovascular disease.17,18 CRP concentration inserum under healthy conditions is lower than 10 mg mL1 and it
can increase up to 200 mg mL1 in the case of inammation or
infection. CRP can be detected through interaction with its
specic antibody. As a proof-of-concept, here we focus on theeasier case of CRP detection in buﬀer.
Monoclonal antibody anti-human C-reactive protein C7
produced in mouse and human CRP was purchased from
HyTest (Finland) and BBI Solutions (UK), respectively. All
chemical reagents were purchased from Sigma-Aldrich(Germany).
50 mg mL1 anti-CRP in phosphate buﬀered saline (PBS;
10 mM phosphate, 137 mM NaCl, 2.7 mM KCl, pH 7.4) was
immobilised onto the surface of the chip through physicaladsorption, followed by a 10 mg mL1 bovine serum albumin(BSA) solution to block the free sensor surface. Milli-Q water(Millipore, US) was used as a running buﬀer for the immobilisation and blocking steps. For the CRP protein detection, therunning buﬀer was changed to PBS to ensure optimal conditions for the immunosensing interaction, as well as to maximise
the stability of the bioreceptor layer.
In an immobilisation strategy based on electrostatic interactions, it is not possible to remove the CRP protein bound to
the antibody due to its weak attachment to the sensor surface
and thus an additive immunosensing assay was employed toestablish the analytical calibration curve for the CRP detection.
To study the biointeraction between CRP and its specic antibody, successive dilutions of increasing CRP concentrations(50, 100, 250, 500 and 750 ng mL1) were owed over the sensor
area. A direct relationship between the concentration and thesensor response can be observed (Fig. 14). Furthermore, thespecicity of the immunoassay was analysed by injecting

3072 | Anal. Methods, 2018, 10, 3066–3073

Fig. 15

Calibration curve for the detection of CRP in PBS.

a control of 1000 ng mL1 BSA instead of CRP, resulting ina negligible response of the sensor, as shown also in Fig. 10.
As shown in Fig. 15, a detection curve was obtained byplotting the accumulated response signal as a function of theaccumulated CRP concentration. The limit of detection (LOD)
was determined from the calibration curve as three times thestandard deviation of the signal. The resulting LOD was 19.478
ng mL1 (R2 ¼ 0.9701) which theoretically corresponds to thelowest detectable CRP concentration. These results indicatethat the integrated instrument and the designed photonic
sensor could be used as an eﬀective biosensor for CRP detection
as the concentration of this biomarker when related to infection
or disease is much higher than the one obtained.

Conclusions
We presented an integrated sensor platform that allows lowcost detection of various biomarkers. The sensor chip with an
integrated spectral lter eliminates the need for an expensive
tuneable laser so that a cheaper broad-band light source can beused. A technology to integrate this chip into a microuidic
cartridge was presented, together with the development of
a dedicated readout instrument. We presented proof-of-concept
results for the detection of LAM in actual clinical urine samples

This journal is © The Royal Society of Chemistry 2018

Paperas well as for the detection of CRP. These results show thefeasibility of using this system as a promising platform technology to detect diﬀerent kinds of biomarkers using a cheap
readout instrument.

Conﬂicts of interest
There are no conicts to declare.

Acknowledgements
This work was funded by the European Commission under theFP7 project Pocket (grant 610389). The nanoB2A is a consolidated research group (Grup de Recerca) of the Generalitat deCatalunya and has support from the Departament d'Universitats, Recerca i Societat de la Informació de la Generalitat deCatalunya (2014 SGR 624). The ICN2 is funded by the CERCA
programme/Generalitat de Catalunya. The ICN2 is supported by
the Severo Ochoa programme of the Spanish Ministry of
Economy, Industry and Competitiveness (MINECO, Grant no.
SEV-2013-0295).

References
1 A. F. Gavela, D. G. Garcı́a, J. C. Ramirez and L. M. Lechuga,
Sensors, 2016, 16, 285.
2 L. Liu, M. Jin and Y. Shi, Nanophotonics, 2015, 4, 419–436.
3 F. Vollmer and L. Yang, Nanophotonics, 2012, 1, 267–291.
4 X. Fan, I. M. White, S. I. Shopova, H. Zhu, J. D. Suter and
Y. Sun, Anal. Chim. Acta, 2008, 620, 8–26.
5 A. B. González-Guerrero, J. Maldonado, S. Herranz andL. M. Lechuga, Anal. Methods, 2016, 8(48), 8380–8394.
6 D. Martens and P. Bienstman, Nanophotonics, 2016, 4, 4,
DOI: 10.1515/nanoph-2016-0181.

This journal is © The Royal Society of Chemistry 2018

Analytical Methods

7 T. Claes, W. Bogaerts and P. Bienstman, Opt. Lett., 2011, 36,
3320–3322.
8 M. Kitsara, K. Misiakos, I. Raptis and E. Makarona, Opt.
Express, 2010, 18, 8193–8206.
9 D. Martens, A. Subramanian, S. Pathak, M. Vanslembrouck,
P. Bienstman, W. Bogaerts and R. Baets, Photonics Technol.
Lett., 2015, 27(2), 137–140.
10 A. Z. Subramanian, P. Neutens, A. Dhakal, R. Jansen,
T. Claes, X. Rottenberg, F. Peyskens, S. Selvaraja, P. Helin,
B. Du Bois, K. Leyssens, S. Severi, P. Deshpande, R. Baets
and P. Van Dorpe, IEEE Photonics J., 2013, 5(6), 2202809.
11 D. Martens, G. Dong and P. Bienstman, Appl. Opt., 2017,
56(5), 1286–1290.
12 P. K. Drain, L. Gounder, Fa. Sahid and M.-Y. S. Moosa, Sci.
Rep., 2016, 6, 19992.
13 M. S. Murib, W. S. Yeap, Y. Eurlings, B. van Grinsven,
H.-G. Boyen, B. Conings, L. Michiels, M. Ameloot,R. Carleer, J. Warmer, P. Kaul, K. Haenen, M. J. Schöning,
W. De Ceuninck and P. Wagner, Sens. Actuators, B, 2017,
230, 260–271.
14 E. T. Vandenberg, L. Bertilsson, B. Liedberg, K. Uvdal,
R. Erlandsson, H. Elwing and I. Lundström, J. Colloid
Interface Sci., 1991, 147, 103–118.
15 K. van der Maaden, K. Sliedregt, A. Kros, W. Jiskoot andJ. Bouwstra, Langmuir, 2012, 28, 3403–3411.
16 I. M. Klotz, in Methods in Enzymology, ed. C. H. W. Hirs,
Academic Press, New York, 1967, vol. 11, p. 576.
17 S. K. Vashist, A. G. Venkatesh, E. M. Schneider, C. Beaudoin,
P. B. Luppa and J. H. T. Luong, Biotechnol. Adv., 2016, 34(3),272–290.
18 M. Soler, M. C. Estevez, M. Alvarez, M. A. Otte, B. Sepulveda
and L. M. Lechuga, Sensors, 2014, 14, 2239–2258.

Anal. Methods, 2018, 10, 3066–3073 | 3073