Abstract
This work discusses label-free biosensing application of a double-layer optical fiber interferometer where the second layer tailors the reflection conditions at the external plain and supports changes in reflected optical spectrum when a bio-layer binds to it. The double-layer nanostructure consists of precisely tailored thin films, i.e., titanium (TiO2) and hafnium oxides (HfO2) deposited on single-mode fiber end-face by magnetron sputtering. It has been shown numerically and experimentally that the approach besides well spectrally defined interference pattern distinguishes refractive index (RI) changes taking place in a volume and on the sensor surface. These are of interest when label-free biosensing applications are considered. The case of myeloperoxidase (MPO) detection—a protein, which concentration rises during inflammation—is reported as an example of application. The response of the sensor to MPO in a concentration range of 1 × 10−11–5 × 10−6 g/mL was tested. An increase in the MPO concentration was followed by a redshift of the interference pattern and a decrease in reflected power. The negative control performed using ferritin proved specificity of the sensor. The results reported in this work indicate capability of the approach for diagnostic label-free biosensing, possibly also at in vivo conditions.
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Introduction
Acute or chronic inflammation is considered a common pathway for the pathogenesis of many diseases in living organisms1,2. The detection of inflammatory markers has been shown to be a useful prognostic tool in various pathological conditions, including cancer, coronary heart disease or aneurysm formation3,4,5,6. Currently, various methods for assessing the presence and severity of inflammatory processes are available, among which the simplest and the most widely used in clinical practice are a subjective assessment of non-specific inflammation signs by palpation of enlarged reactive lymph nodes or body temperature assessment during the physical examination. Although these methods are often used in point-of-care settings, they are operator dependent or lack sensitivity and specificity. Other commonly used methods include qualitative or quantitative assessment of biomarkers concertation in biological fluids, e.g., C-reactive protein (CRP)—an acute phase protein synthesized by the liver7,8. However, method based on CRP analysis lacks specificity and reflects a general, non-specific systemic response. Although other inflammation markers are available, most of them are evaluated ex vivo using time-consuming measurement methods, such as enzyme-linked immunosorbent assay (ELISA).
To provide a focused analysis that could lead to more effective diagnosis and treatment, inflammation monitoring directly at the site of the inflammation is required9,10. One of the markers of which concentration rises locally during inflammation is myeloperoxidase (MPO)11—a protein mainly expressed in immune granulocytic cells, neutrophils and eosinophils. Many works have been reported on locally elevated MPO level during inflammation. For example, an intracranial aneurysms study has shown that local plasma MPO concentrations were 2.7 times higher in the aneurysm lumen than in the femoral arterial blood in this patient population12. Increased concentration as well as biological activity of MPO is now considered as a reliable oxidative stress and inflammatory marker among many commonly occurring conditions6,11,13. The central role of MPO in acute and chronic inflammatory processes, as well as its prognostic value, sparked interest in its evaluation in various clinical scenarios. Most studies on MPO detection methods are based either on the determination of the enzyme activity level or the assessment of its concentration. To date, several attempts have been made to evaluate MPO activity in vivo (meaning: in whole, intact living organisms), e.g., using positron emission tomography (PET)14, magnetic resonance imaging (MRI)14,15,16, as well as fluorescence17 and bioluminescence18 measurements. However, those methods are limited to relatively superficial structures (fluorescence or bioluminescence) or rely on labels insufficiently tested for safety on living organisms and potentially toxic (MRI or PET). Attempts are underway to develop a new generation of biocompatible biosensors for evaluating MPO or other biomarkers that overcome the limitations of current methods and may be suitable for in vivo applications19.
Among solutions for label-free and in vivo detection, optical fiber sensors (OFS), with their assets such as miniaturized design, real-time response and immunity to electromagnetic interactions, are optimal for recognition of different proteins, including MPO. Considering in vivo detection conditions, the sensing part of OFS should be integrated with optical fiber and placed at the fiber tip20. An optical fiber can be easily introduced, e.g., into artery, by a catheter and only the small biosensing element on a tip interacts with the surrounding medium. In such a probe-like approach, the reflected light, after interacting with the external factor surrounding the sensing part, returns to the detector with the same medium, i.e., optical fiber. In-line OFS based on, e.g., surface-enhanced Raman scattering or localized surface plasmon resonance (LSPR), where the sensing interactions take place on the fiber end-face have already been reported and applied as biosensors21,22,23,24,25. Optical fiber-based Fabry–Perot interferometers (FPIs) with the sensing element on the tip have also been applied as biosensors26,27,28. However, manufacturing of majority of these sensors may be perceived as technologically demanding, which limits their mass production and disposability. An interesting solution was proposed in29, where the sensing mechanism is based on a single-layer deposited on the optical fiber tip, greatly simplifying and shortening the sensor manufacturing. Also, a large-scale production of such sensors is possible, especially with deposition techniques that allow for high control of film growth on the surface, such as magnetron sputtering. Wide selection of the thin film materials, as well as their possible robustness in experimental conditions also need to be noted. However, there are some curtail limitations of the single-layer approach. Considering its sensitivity to external refractive index (RI), only the change in reflected power can be monitored, i.e., the interference pattern does not undergo any shift in the wavelength domain with the external RI29. Moreover, when the structure is not in air, but immersed in higher RI solutions, such as water, the overall reflected power drops significantly. When additionally the RIs of the layer is low vs the fiber material, the reflected pattern is impossible to be traced. It must be noted that the power in optical fiber systems can be disturbed not only by the target biological species, but also by many other factors, such as stress, bend, or applied connectors. From this point of view, a single-layer solution may not be considered as highly promising for label-free biosensing applications. Thus, some improvements of that configuration have already been worked out such as the one reported in30, or another called bio-layer interferometry focusing on biomolecular interactions on the sensor surface31. In this solution, the cavity is formed by a layer with RI similar to the targeted biological material, but beforehand, the optical fiber end-face is coated by a below 50 nm in thickness high-RI layer32. The main role of the additional layer is to increase the reflectivity since the RI contrast between the cavity layer and the fiber material is low. When targeted material bind to the surface, the cavity length increases, resulting in the interference pattern shifting towards longer wavelengths.
In this work, we report for the first time the label-free biosensing concept based on a modified FPI where the cavity is formed by two thin films, and the second one tailors the reflection conditions at the external plain and supports changes in reflected optical spectrum when bio-layer binds to it. In the double-layer approach the electromagnetic field distribution is modified to distinguish changes in RI taking place in the vicinity of the sensor (volume sensitivity) and when a biological layer is formed on its surface (surface sensitivity). Also, both of the sensitivities can be enhanced compared to the single-layer approach with a proper tailoring of thin film parameters as RI and thickness33. For the biosensing purposes presented in this work, i.e., detection of specified inflammatory markers, e.g., MPO, two transparent thin films were chosen, namely titanium (TiO2) and hafnium oxides (HfO2). Both the materials are biocompatible, robust, and were deposited using magnetron sputtering on the fiber end-face, allowing for relatively simple and large scale fabrication of such devices. Moreover, the properties of the HfO2 as a functionalized outer layer are studied. It is worth mentioning that except for suitable for this work optical properties, HfO2 was chosen due to its cytocompatibility, which is crucial for future in vivo applications34. HfO2 was already applied as a biosensing layer for the electrochemical detection of human interleukin-135. The material has already been used also for fabrication of some optical sensors, such as those based on lossy mode resonance and long-period fiber grating36,37, but according to our best knowledge it has not yet been functionalized towards application in optical biosensing. Thus, the ability for HfO2 functionalization with different protocols is studied and compared to properties of other oxides, such as indium tin oxide (ITO) and silicon oxide (SiO2), that are widely used for biosensing purposes. After the sensor functionalization and antibody immobilization, capability to detect MPO as a target protein is studied and compared to response to ferritin as a negative control, assessing the potential of the sensor for diagnostic applications.
Methods
Thin film deposition
The sensor is based on a single-mode optical fiber (SMF28) purchased from Thorlabs. Its end-face was cleaved, and a batch of fibers was placed in the in-house designed deposition holder for magnetron sputtering system with 8-inch targets (Oxford Plasmalab 400). Deposition time for each material was adjusted according to numerical analysis described in the section “Numerical analysis”. The aim assumed reaching a possibly deep minimum of reflected power in interference pattern when investigated in water solutions. For deposition of TiO2, the Ti target was sputtered for up to 40 min under a pressure of 6 mTorr. The O2 flow was set to 25 sccm. Deposition of the HfO2 was up to 7 min-long and took place at O2 flow set to 10 sccm. As an inert gas Ar was applied in both the depositions. The fibers stayed in the chamber at low pressure between Ti and Hf sputtering.
To analyze the efficiency of chemical functionalization a set of thin films, i.e., HfO2, ITO and SiO2, was deposited on reference silicon wafers. The deposition parameters of HfO2 were as given above while those for ITO and SiO2 are given in Section S1 in Supplementary Information.
Numerical analysis
The spectral response of the sensor was analyzed numerically using the transfer matrix method algorithm described in detail in38. The algorithm was used as a simple and reliable alternative to more complex and advanced algorithms, such as, e.g., finite difference time domain (FDTD) or finite element method (FEM). Considering the presented data, the proposed algorithm seems well suited for the purpose, as it gives results in good agreement with the experimental data. The method treats a system as a combination of multiple media (layers) individually described by a matrix. The matrix includes information on the refractive index and thickness of each layer. The final structure consists of five media, where the first and the last ones describe infinite initial and final media for electromagnetic wave propagation. The inner three layers constitute the sensor (two thin film layers) and simulate the biological layer. However, initially, the structure was simulated as a standard FPI formed by 3 media, i.e., a plane wave was propagating through the SMF core and reflecting on the interfaces with TiO2 film and with an external medium. Successively, additional media, i.e., HfO2 as the second thin film and a medium corresponding to a biological layer, were introduced to the model. Properties of TiO2 and HfO2 deposited as described in the section “Thin film deposition” on reference Si wafers were obtained using Horiba Jobin Yvon UVISEL spectroscopic ellipsometer. According to39, the RI of a biological layer was fixed to 1.45 RIU. The response of the sensor was simulated in the set of external media with RI (next) in a range of 1.33 to 1.41 RIU. The simulations determined the volume sensitivity, defined as a shift of wavelength corresponding to minima in the interference pattern per next, and the surface sensitivity, defined as the wavelength shift induced by the growth of a biological film on the sensor surface.
Optical measurements of the sensor
After the fabrication described in section “Thin film deposition”, the sensors were installed in a measurement setup consisting of LEUKOS SM30 supercontinuum white light source, Thorlabs 6015-3 circulator, and Yokogawa AQ6370B Optical Spectrum Analyzer. First, the spectra were recorded in the water and glycerin mixtures of a next range from 1.33 to 1.41 RIU. The next was measured using Rudolph J57AB automatic refractometer at 589 nm. Based on these results the volume sensitivity was determined experimentally.
Sensors’ surface functionalization and analysis
Reagents and biological materials
Monoclonal anti-Myeloperoxidase antibody (IgG), Goat Anti-Rabbit IgG H&L labeled with Alexa Flour 488 (IgG-Alexa488), and Native human Myeloperoxidase protein (MPO) were purchased from Abcam. Native Human Ferritin, (3-Aminopropyl)triethoxysilane (APTES), Triethylamine, Bovine Serum Albumin (BSA), and Phosphate Buffered Saline (PBS) were purchased from Sigma Aldrich. 3-(Triethoxysilyl)propylsuccinic anhydride (TESPSA) was purchased from ABCR.
Functionalization methods and verification of their performance
Before surface modification, sensors and reference samples were cleaned in isopropanol, ethanol, and water (for 5 min in each) and dried under a stream of argon. Prior to the silanization, the surfaces were activated by oxygen plasma (Digital UV Ozon System, Novascan). Next, two separate silanization protocols were tested and compared to select the most efficient surface’s modification method. Silanization with APTES was done similarly to the protocol described in40. The samples were placed in the desiccator over two small containers, one containing 30 µL of APTES and the other 10 µL of triethylamine as a catalyst. Then they were left at room temperature under Ar atmosphere for 2 h. Next, the reagents were removed from the desiccator and the samples were left for 48 h under an Ar atmosphere to cure the silane layer. Silanization with TESPSA was done similarly to the protocol described in41 with further modifications. Simply, the samples were placed in the desiccator over an open container with a small amount of TESPSA under a pressure of c.a. 1 mbar and additional heating from an externally positioned IR-lamp (Beurer IL11) for 4 h. Next, the optical fibers and reference samples were cured and annealed to dehydrate the succinic anhydride groups at 120 °C for 1.5 h.
After the silanizations the surface composition of the reference samples were evaluated by X-ray photoelectron spectroscopy (XPS). The procedure was described in detail in Section S2 in Supplementary Information.
Reference samples modification with antibodies and their analysis
A 100 µL of 1:1000 primary IgG solution in PBS was applied to the reference sample surfaces (bare oxides, silanized oxide with amine or carboxylic terminated groups) and incubated for 45 min. The surfaces were modified with primary IgG via physical adsorption or peptide bond formation between corresponding terminal groups on IgG and silanized oxide surface. Next, the samples were washed with PBS buffer containing 0.05% Tween20. Then 500 µL of blocking solution (1% BSA in PBS buffer) was applied to the surfaces and incubated for 30 min to cover unmodified surfaces. Next, they were washed again with PBS buffer containing 0.05% Tween20. In the next step, 100 µL of a secondary antibody IgG-Alexa488 solution in PBS buffer in the ratio 1:1000 was applied to the surface and incubated for 45 min. Finally, the surfaces were washed again with PBS buffer containing 0.05% Tween20 following by washing with deionized water.
The interaction with the secondary antibody was investigated using wide-field fluorescence microscopy (Eclipse Ti2-U, Nikon) with Semrock set filters FITC-5050A. The images were processed in ImageJ (Fiji®). The analysis of the photos consisted of automatically counted points showing fluorescence in specific areas of the sample. These areas were squared with a side length of 100 pixels (approx. 30 µm) and located in the center of antibody-modified area. The mean value of the florescence intensity and its standard deviation were calculated. All values were normalized using values obtained for the same surfaces, but unmodified with silanes.
Biosensing procedure
The end-face optical fiber coated with HfO2 and modified with terminal carboxylic groups via silanization process sensors were incubated in the IgG solution (3.3 × 10−6 g/mL) for 45 min. This step enabled to chemical bonding of IgG to the surface via peptide bond formation. Then, they were washed for 5 min in PBS (with a shake speed of 250 rpm) and placed in a fresh PBS to obtain reference spectrum. Next, the sensor’s surface was blocked with BSA (1% in PBS) introduced for 30 min. The washing procedure was repeated as described above.
After the described modification, the sensor was used for the detection of MPO protein. It was incubated in the following concentrations of MPO: 1 × 10−11, 1 × 10−10, 1 × 10−9 and 5 × 10−6 g/mL. The incubation time in each MPO solution was set to 30 min. Each incubation step was followed by the mentioned above washing procedure to obtain reference spectrum. During the selectivity measurement, the sensor was immersed in a non-specific to the used receptor ferritin solution (5 × 10−6 g/mL) for 30 min. Then, the sensor was washed, measured in PBS, and incubated in a specific MPO protein solution (5 × 10−6 g/mL).
The optical spectra during the biosensing procedure were registered in a range of λ = 1500–1600 nm using the HBM FS22 BraggMETER interrogator, consisting of an embedded tunable light source, optical circulators, and photodiodes. Figure 1 depicts the schematic of the measurement setup and the sensor’s modification. The registered curves were fitted with the Fourier series in the narrowed region, where the reflected power minimum was found. The presented spectra are an average of 10 consecutive (approximated) measurements in a PBS buffer. The MPO concentration dependence was repeated on a dozen or more different sensors.
Results and discussion
Optical properties of the sensor
The most significant parameters determining the response of the double-layer optical fiber interferometer are RI and thicknesses of the thin films forming the sensing structure. As the proposed sensing solution can be adjusted towards a wide range of applications, not only for the MPO binding by antibodies immobilized on the sensor surface considered in this work, a set of assumptions must be stated at the design stage. First, the sensor wavelength range of operation between 1500 and 1600 nm is expected due to the availability of well-developed telecom interrogation systems. Therefore, it is important to reach a spectrally possibly well-defined interference minimum of reflected power, the evolution of which will be monitored during the biosensing procedure. That condition is ensured by a high RI material, which, in the case of this paper, is TiO2. Secondly, surface sensitivity is crucial for label-free biosensing applications where the binding of biological material to the surface is concerned. It has already been shown that choosing thin films forming double-layer structures with low RI contrast makes it possible to reach high surface sensitivity26. Thus, HfO2 has been applied as the second thin film, which has a slightly lower RI and is biocompatible. Thirdly, the biosensing procedure will take place in aqueous solutions, i.e., for the next values slightly above that of water (at λ = 1550 nm next for water reaches 1.315 RIU42). Therefore, the thickness of both thin films must be adjusted to the abovementioned conditions. A detailed discussion about the influence of the thin films’ parameters on the sensing performance of the double-layer structure has already been reported and discussed in33.
The numerical analysis was performed first to identify the proper thicknesses of the TiO2 and HfO2 to be deposited on the fiber end-face. For the simulations, the experimentally obtained RI of both the layers forming the sensing part was used. It can be seen in Fig. 2a that for the thickness of TiO2 reaching 305 nm, a relatively broad interference minimum can be obtained at λ ≈ 1400 nm. When an additional HfO2 layer of 62 nm is deposited, the minimum shifts towards longer wavelengths, and it gets more profound due to increasing both the optical path and Q-factor of the resonator. The phenomenon of modification of reflection conditions by the second layer in the double-layer structure has been discussed in detail in33. For the sensing purposes it is highly beneficial since narrower spectral features significantly improve the sensor’s resolution. The full width at half maximum (FWHM) for the FPI based only on TiO2 reaches 67 nm, while it drops to 26 nm when the double-layer approach with TiO2 and HfO2 layers is concerned. Therefore, the figure of merit (FoM), defined as a ratio of sensitivity to FWHM, is increased by a factor of over 2.5 when the double-layer approach is applied.
(a–c) Simulated and (d) experimental optical spectra of TiO2/HfO2 nanostructure in different next. (a) Comparison between TiO2-only and TiO2/HfO2 nanostructures when next was set to this of water. (b) Impact of additional layer (RI = 1.45 RIU) growth on TiO2/HfO2 nanostructure when next was set to this of water. (c,d) Optical spectra of TiO2/HfO2 nanostructure for next from 1.33 to 1.41 RIU.
Further numerical analysis has shown the impact of the growth of an additional film (3rd layer) on the spectrum when water was assumed as an external medium (Fig. 2b). The extra film with an RI of 1.45 RIU was considered a reference to binding a biological material to the sensor surface. As can be seen, with the increase of the additional film thickness, the minimum shifts towards longer wavelengths and its power decreases as a result of further improvement of the resonator parameters. The calculated surface sensitivity at these conditions reached 0.43 nm/nm.
As another parameter frequently considered in the case of optical fiber-based biosensors, the volume sensitivity of the TiO2/HfO2 nanostructure was analyzed next. Changes in next may significantly disturb the readout of the sensing system. Thus, optical spectra of the double-layer interferometer were simulated (Fig. 2c), as well as measured (Fig. 2d). The minimum shifts towards shorter wavelengths with the next, i.e., the trend is opposite to the one for the thin film growth on the sensor surface. The wavelength shift induced by next is linear in the entire measured range and volume sensitivity reaches 150 nm/RIU with a FoM of 3.8 RIU−1. The sensitivity to the volume next changes can be improved by increasing the RI contrast between the layers as the Fabry–Perot resonator parameters change, and thus the sensor interacts differently with the surrounding medium, as discussed in detail in33. However, when the operation wavelength range is limited, and the interference pattern should best spectrally-defined in aqueous solutions, it is not possible to maintain high surface sensitivity conditions at the same time. Considering further biosensing experiments, the sensor was optimized towards the surface sensitivity at the sacrifice of the volume one. It must be noted that a single-layer FPI, compared to the double-layer approach presented here, does not offer the capability to monitor next by wavelength shift but rather solely by the changes of reflected power, which follows the next33. The monitoring of wavelength is rather expected in the sensing systems due to its immunity to power fluctuations that may take place in the measurement setups. For the double-layer interferometer, the reflected power initially decreases and later tends to increase with next. The lowest reflected power was found for next = 1.37 RIU. The experiment results follow the same trend, but the minimum does not get as deep as for numerical analysis. The difference originates from model simplifications, and specifically, in this case, the extinction coefficients of the thin film materials were assumed to be equal to zero while they may reach non-zero values43.
Other optical fiber sensors able to discriminate between the volume and surface sensitivity are considered, mainly those reported recently and based on the SPR effect obtained for gold-coated titled fiber Bragg grating44 and leaky mode resonance-based sensor, where the end-face of multimode optical fiber is coated by TiO245. Their surface sensitivities reach 0.216 nm/nm and 0.595 nm/nm in the former and latter case, respectively. However, it must be noted that the sensitivities were identified for higher RI of the additional layer, i.e., reaching 1.483 RIU. For higher RI of the additional layer, the sensitivity is expected to be higher and comparable to that reported in45. It needs to be emphasized that neither of the abovementioned sensors was verified experimentally for label-free biosensing purposes. The results of the biosensing experiment with the double-layer interferometer are shown in section “Biosensing”.
Biosensing
First, the binding of MPO as a target protein by the applied IgG was verified. To study these IgG-MPO interactions and adjust the optimal experimental conditions the bio-layer interferometry method was used initially. The results with the description of the measurement system used for this purpose were presented in Section S2 in Supplementary Information. The dissociation constant was determined at KD = 1.09 × 10−11 M, indicating strong and stable interactions between the applied biomaterials. Next, the capability of MPO detection using the developed optical fiber biosensor was studied. Based on the results shown in Section S3 in the Supplementary Information, the end-face of the fiber was functionalized with TESPSA and the IgG was immobilized on the sensor surface via peptide bond formation. Then, the surface was additionally blocked by BSA to avoid any non-specific interactions between the targeted protein and free, un-modified spaces between the IgGs. Finally, the sensor was immersed sequentially in the solutions with elevating MPO concentration. Each step of the procedure results in a spectral shift towards longer wavelengths and a decrease of the reflected power (Fig. 3). Depending on the concentration, the shift and drop range from 0.059 nm and 0.29 dB for the lowest MPO concentration up to 0.415 nm and 1.19 dB for the highest one. It must be noted that the observed effect corresponds well with the numerical analysis shown in Fig. 2b and proves the capability for label-free biosensing application of the developed double-layer interferometry approach. For the applied setup, the obtained experimental limit of detection (LOD) is comparable to the existing standard MPO evaluation methods, e.g., ELISA with a LOD of ca. 1 × 10−11 g/mL46,47. Moreover, it needs to be emphasized that the sensor has been designed to detect MPO during the inflammatory process. In such circumstances, MPO concentration rises locally and may reach even 1 × 10−7 g/mL, which greatly exceeds the obtained LOD48,49.
MPO detection. (a) Schematic representation of the biosensing procedure. (b) Averaged optical spectra of the sensor in PBS recorded after the immobilization of the IgG, BSA, and the incubation in different MPO concentrations (black arrow indicates the following steps of biosensing procedure). (c) Interference pattern minimum properties (wavelength and power) after each experiment step.
Next, to verify the selectivity of this sensing approach, a negative control was performed using ferritin to confirm that the obtained spectral shift and power drop were induced by specific MPO binding. Ferritin belongs to the group of acute inflammatory phase proteins whose blood levels increase unspecifically under various clinical scenarios50 and has been chosen as a protein that can potentially disturb the MPO recognition51. MPO and ferritin are two distinct proteins, however, they do share some common features, i.e., both MPO and ferritin contain iron as an essential component. What is more, MPO and ferritin have roles in the immune response. MPO, predominantly found in neutrophils, contributes to host defense by producing hypochlorous acid. In contrast, ferritin functions as an iron storage protein, and its levels can be influenced by inflammation or infection. Both MPO and ferritin are associated with oxidative stress. MPO generates reactive oxygen species during its typical function, whereas ferritin sequesters and stores iron, thus reducing free iron availability and protecting cells from oxidative stress. Finally, elevated levels of MPO and ferritin serve as diagnostic or prognostic markers in various diseases. For these reasons, ferritin has been selected as an appropriate negative control for MPO. Figure 4 presents the development of the interference minimum after incubation of the sensor in ferritin. As can be seen, ferritin induces a slight shift of the minimum towards shorter wavelengths while, at the same time, the power drop was not registered. Numerical analyses confirmed by the experiments show that every change on the sensor surface leads to changes in both the parameters, i.e., wavelength and power. Thus, monitoring the wavelength and power responses may be considered crucial. Next, incubation in MPO at a concentration of 5 × 10−6 g/mL (positive control), in turn, caused an apparent shift towards longer wavelengths accompanied by the power decrease, indicating a specific binding of the targeted protein. Compared with a slight change induced by ferritin of the same concentration, the results fully confirm the sensor’s selectivity to MPO.
Negative control. (a) Schematic representation of the procedure. (b) Averaged optical spectra of the sensor in PBS recorded after the immobilization of the primary IgG, BSA, and the incubation in non-specific ferritin and specific MPO. (c) Interference pattern minimum wavelength and power after each experimental step.
As mentioned earlier, in vivo biosensing is crucial for analyzing inflammatory processes, especially in hard-to-reach places close to brain tumors, etc. Therefore, the possibility of distinguishing the specific interactions between a receptor immobilized on the sensor surface and the target present within the body fluids, at best without the washing step, is required. To assess the potential sensor’s response at these conditions, the optical spectra was monitored during the incubation step in the non-specific and specific proteins, i.e., ferritin and MPO, respectively. Figure 5 shows the evolution of the minimum parameters at the time of the experiment. The incubation in ferritin, as discussed above, did not result in significant changes in the parameters, i.e., a slight wavelength blueshift is only observed (Δλ = − 0.170 nm), confirming the results shown in Fig. 4b. An entirely different behavior has been observed during the MPO incubation, i.e., continuous and rapid power drop (ΔP = − 1.02 dB) with a significant redshift (Δλ = 1.953 nm), indicating successful receptor-target interactions. The ability to distinguish the specific analyte from the non-specific one at the incubation stage gives great promise for efficient performance during in vivo tests.
Some assumptions need to be made to compare our biosensing concept with other optical-fiber-based sensing solutions capable of in vivo applications. Due to safety reasons, the fiber should not be placed inside the body by itself only. Thus, we need to assume that a speculum or a catheter is required for the sensor assembly. To assure the optimal working conditions of the OFS, in such cases, it is crucial to have the sensing element on the optical fiber end-face. When the sensing element is also placed on the side surface of the optical fiber, attaching it to the speculum/catheter may physically block the part of it, therefore limiting its performance. Moreover, the side surface is typically larger than the end-face, which limits the capability for precise identification of the point of the performed measurements. Considering the label-free optical fiber biosensors where the sensing element is placed only on the end-face, the sensors based on surface-enhanced Raman scattering and localized SPR are mainly considered21,47,48. Table 1 presents an overview of chosen optical fiber sensors. These include technologies such as the plasmonic optical fiber nanoprobe developed by Liang et al., tailored for protein molecule detection with a sensitivity reaching 8.1 μg/mL22, and the fiber-optic LSPR sensor with a gold nanoparticle array by Kim et al., which achieves a remarkable limit of detection at 1.3 pg/mL for prostate-specific antigen23. Additionally, the multiplexed remote SPR detection sensor by Desmet et al. utilizes an optical fiber bundle to detect various antibodies with limits of detection down to a few tenths of nM, showcasing a robust capability for in situ and multiplexed biomolecular analysis25. Even though some of them have reached LOD as low as hundreds of fg/mL of targeted protein such as Free Prostate Specific Antigen24, it must be noted that compared to the solution reported in this work, the fabrication procedure of the other biosensors is complex. Many technological and chemical modification steps required in these cases do not allow for mass production by batch fabrication. Moreover, they contain such elements as nanoparticles that may be released during potential in vivo examination21. The sensor presented in this work, in turn, can be easily batch-fabricated and upscaled. Moreover, a great variety of materials can be applied in the proposed approach, among which many are non-invasive and biocompatible, such as HfO2 used as the external layer.
Conclusions
This work discussed the possible approach toward diagnostic detection of inflammatory markers using optical fiber sensors, which are scalable in fabrication quantities. The proposed solution is based on a modified Fabry–Perot interferometer formed by the deposition of two thin layers, i.e., TiO2 and HfO2 films on standard single-mode optical fiber end-face. The HfO2 film, as well as the selectively formed biological layer on the film surface, modify reflection at the external plane of the interferometer, making label-free biosensing possible. Moreover, the low refractive index contrast between the applied thin film materials and tailored design of the sensor allowed for discriminating the changes in optical properties in a volume and on the sensor surface. This feature is crucial, especially in the specific detection of targeted species in vivo, where the readout may be easily disturbed, and the washing procedure is highly limited. The surface sensitivity of the proposed sensor reaches 0.43 nm/nm and is comparable to the ones obtained for other reported optical-fiber-based solutions, showing the capability of surface and volume sensitivity distinction. Furthermore, the biosensing performance of the sensor has been investigated, considering myeloperoxidase (MPO) as a target—a protein whose concentration and biological activity rise during inflammation. The optimized chemical functionalization allowed for efficient immobilization of monoclonal anti-MPO antibodies as a receptor and detection of MPO concentration as low as 1 × 10−11 g/mL. The obtained detection limit is sufficient for MPO recognition during the inflammation and comparable with standard but ex vivo and time-consuming evaluation methods such as, e.g., ELISA. The negative control tests performed with ferritin –an abundant blood serum protein and possible MPO’s sensing disturbance—confirmed the sensor’s selectivity. Moreover, the sensor’s response was continuously monitored during incubation steps with both proteins. The results revealed the possibility of distinguishing the specific interactions between the receptor and targeted protein without washing steps. This asserts the capability of the sensor to work efficiently during diagnostic examinations. What is more, with the possibility of application of various materials forming the double-layer interferometer, batch fabrication, and label-free sensing with no advanced data processing, the proposed approach seems to be a universal and attractive alternative to biosensing solutions reported to date. Promising results on label-free biosensing obtained with the double-layer interferometer and shown in this work make it possible to apply the device for investigations of more complex analytes, such as whole blood samples, especially at in vivo conditions.
Data availability
The datasets generated during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
Authors acknowledge support received from Dr. Ewa Roźniecka within developing functionalization procedures.
Funding
Funding statements were provided by Narodowe Centrum Nauki (Grant No. 2019/35/B/ST7/04388), Narodowe Centrum Badań i Rozwoju (Grant No. TECHMATSTRATEG-III/0042/2019).
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D.B., M.J., P.M., K.B., M.K., T.R., J.N., and M.Ś. wrote the manuscript; D.B., M.J., K.B., M.K., T.R., J.N., and M.Ś. were involved in conceptualization; D.B., M.K., P.M. processed the measurement data; D.B. and K.B. prepared figures; M.K. performed numerical analysis; P.M. and A.M. performed measurements; N.K. designed technology and fabricated sensors; T.R., J.N. and M.Ś. supervised projects and provided resources.
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Burnat, D., Janik, M., Kwietniewski, N. et al. Double-layer optical fiber interferometer with bio-layer-modified reflector for label-free biosensing of inflammatory proteins. Sci Rep 14, 23127 (2024). https://doi.org/10.1038/s41598-024-70058-6
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DOI: https://doi.org/10.1038/s41598-024-70058-6