We present a simple surface plasmon resonance imaging (SPRi) sensing system based on some common optoelectronic devices in this paper. Using an optical fiber based SPR sensor as sensing element in our system, the SPRi system is dramatically compact. A small universal LED is used as the light source. The light intensity is record as images that can be captured by a simple web camera. A Microsoft Visual C++6.0 based Windows software program is written to process the image data which contain SPRi information. Experimental results show that the relationship between the relative intensity and RI is a linear relation in a RI range from 1.3396 to 1.3645. Using this SPRi device, we measure the specific binding between the Con A and RNase B, which demonstrates its capability for biomedical selective affinity monitoring. The proposed SPRi sensing system also has the capacity for biochemical multiple channel measurement with further investigation.
© 2014 Optical Society of America
Surface Plasmon resonance (SPR) instruments have important application in chemical and biological detection because of their unique advantages such as high sensitivity, real time monitoring and label-free analysis [1–3]. In the past decades, many types of SPR sensors have been proposed. According to their coupling mechanism, they can be generally categorized as prism coupled SPR and optical fiber SPR . According to their modulation approach, SPR devices can be classified into four categories: angle modulation , wavelength modulation , intensity modulation  and phase modulation . Using spatially resolved and high-throughput measurement techniques , SPR imaging (SPRi) sensors have also been widely investigated as new lab-free detection techniques [10, 11]. Some SPRi sensors adopt prism and grating coupling methods [12, 13], which have been for detecting biomolecular interactions [14, 15]. Usually a SPRi system uses a plane-polarized light with ðxed angle as incident light, and a charge-coupled device (CCD) camera for the detection of the reñected light. However, both traditional SPR and SPRi instruments are often too bulky and costly for laboratory and commercial applications because of their sophisticated optics, electrical and flow-cell units, which greatly limit their potential for commercialization and practical applications of this high-sensitive analysis instrument. There are also some solutions to construct economic and high-sensitive SPR sensors by using standard electronic devices [16–18], which shows the possibility to construct the SPR system by electronic devices. All these works are optical prism based SPR system, even special-purpose accessories are replaced by common instrument which can be easily found around the market. But, using the bulk prism-based SPR configuration still limits their miniaturization, dexterity and simplicity. Due to the lower performance of the general electronic components compared to special optical devices of SPR sensing system, the measurement precision and stability level of the commercial SPR sensing system are still better. However, because the SPR system constructed with common electronic devices is easy to achieve, low cost and has less demanding requirement to the working environment, it can be used as a low barrier tool which will be helpful for the application of SPR technologies.
In this paper, we present a compact SPRi sensing system by using common economic electric components, which is very convenient for construction, prototyping, testing and optimization. Different from all other SPRi sensing systems with a prism configuration, we use fiber-optic SPR sensor which has been demonstrated as a sensing device in our system . Fiber optic SPR sensor has advantages such as smart size, high resolution, flexibility, and miniaturization. To our best knowledge, there is almost no optical fiber based SPRi system reported in the previous works. Compared with prism based SPR configuration [20, 21], fiber-optic SPR sensor greatly simplifies optical alignment and light coupling. Also, it needs no separate optical components such as prism, slides, collimators, optical bench, and mechanical parts which are large, expensive and unfavorable for system miniaturization, integration and portability. To alleviate the light fluctuation from the light source, we use a self-compensated structure which integrates the optical fiber based SPRi sensing channel and a reference channel together. The lab-scale experiment shows that the system has good performance in detecting the refractive index (RI) of solutions and the specific recognition of Con A and RNase B, despite that the cost and accuracies of the general electric components we used in this device are far below that of laboratory SPR equipment or commercial devices. Using the small end face of fiber as the monitoring region, this SPRi system can be easily extend for simultaneous multiple-channel imaging analysis which has great potentials to be further developed as a low cost, compact and economic multichannel SPRi system.
2. Principle design and system configuration
Figure 1 shows the principle operation of the proposed fiber-optic SPRi system. As shown in Fig. 1(a), to eliminate the external light interference, the system is set up inside an instrument container. Figure 1(b) illustrates that a regular LED (Ym-1w) with condensing lens is used as the light source, whose central wavelength is 625nm and 3dB bandwidth is 26nm. This LED is a general economic optoelectronics component, which has been widely used as indicator light and also been developed as a lighting source  with advantages of low cost, high efficiency, energy saving, long life, good stability and low operating voltage. A web camera (Sorung, 640 × 480 pixel with USB2.0) is used as the image detection component. The light wavelength range of the LED is within the visible light range and can be detected by the web camera. Using a USB port of a laptop as a DC supply power to the LED, this SPRi system needs no extra power cords and transformers.
To simplify the optical alignment and improve the optical robustness, instead of using prism based SPR setup, we use a fiber optic SPR sensor as the sensing element in this device. It has unique advantages to make SPRi device compact without separate optical components, which also is convenient for optical adjustment, light coupling and propagation. Most importantly for system instrumentation, this fiber-optic SPR sensor can enormously reduce the system cost by eliminating bulky optical components such as the optical lens group and prism. Additionally, unlike prism based SPR system, it does not need a series of stepping motors and rotating parts with complicated structure and control unit.
The schematic diagram of the sensing system is shown in the Fig. 2. The light from the LED enters and transmits in the fiber sensor with multiple modes. Because the fiber cladding of the sensing region has been removed and coated with gold layer, when the sensing region immersed in samples, some light transmitting with appropriate range of angles in the sensing region will satisfy the exciting conditions of SPR. Because the SPR absorption depends on the samples that are attached to the surface of the sensor probe, we can monitor and analyze the sample by detecting the transmitted light intensity.
We use a kind of plastic cladding silica optical fiber (HPOF) (HP 400/430-37/730E YOFC) to fabricate the SPR probe in this work. The diameters of the fiber core and cladding are 400µm and 430µm, respectively, and its numerical aperture is 0.37. The fiber SPR sensor is a short piece of HPOF with length of 7cm, the 5mm sensing part in the middle of the fiber is cladding removed and coated by 50nm of gold. To reduce the connection loss, both end faces of the fiber are polished by emery papers. We will monitor the intensity changes from these detected SPR sensing image to measure the attached RI changes or the variation of the biological environment.
To illustrate the light from LED source can be used for SPR sensing, we measure the SPR absorption spectra of the optic fiber SPR sensor we used in the SPRi system. A spectrum of the sensor in air is recorded as a reference spectrum to normalize the SPR spectra during test. The absorption spectra are recorded by the experiment setup as an inset of Fig. 3 shown. Using a HL-2000-FHSA white light source and a HR4000 spectrometer with the detection range of 450-800 nm (both of them are produced by Ocean Optics, Inc), we detect the absorption spectra response of the fiber optic SPR sensor in the salt solution with different RIs that are shown in Fig. 3. We find the wavelengths of the resonance absorption notches are larger than 640nm, a central wavelength of this whitelight source (625nm) is at the falling edges of the notches. It means that the broadband light will be partly absorbed in different level when it passes through the sensing region, which is attached with different samples and the intensity of light reaching the web camera changes correspondingly.
Compared to the above whitelight source, which has high power up to 5W and usually we use a low power or need light attenuator to reduce its intensity, a normal LED component is sufficient for SPR tests, as shown in Fig. 1, we use LED as light source into fiber without any coupler but just by fixing the fiber end face in front of the LED. The transmitted light through the probe was detected by the web camera. To acquire a clear image, the distance between fiber end face and camera is properly adjusted. As shown in Fig. 3(b), using a light source spectra that measured by SPR sensor in the air as 1 or 100%, we normalize the detected SPR absorption spectra in different RI solutions to get rid of light source fluctuation effect and to amplify SPR absorption signal.
It is well know that web camera is a popular and economic imaging and video device that can capture images using the visible light emitted from the LED we used here. In our system, a manual-focus web camera (640 × 480pixels) connected with a laptop computer acts as a light intensity detection device. However, the intensity detection of web camera is limited to 256 levels. Hence, the aforementioned LED with adjustable light intensity is necessary to improve the intensity detection resolution of the web camera. The images acquired by the web camera were observed by the laptop, which can display, record, process and analyze the image conveniently. To extract the brightness information from image data, an image processing program is developed based on Microsoft Visual C++6.0 in the windows environment. Through image processing, the colored image captured by the web camera is converted into a grayscale image. Every image point has a grayscale value between 0% (white) to 100% (black) to show its brightness. Therefore, the light intensity of the photograph can be calculated by adding the grayscale value of each image point together. Figure 4 shows the analysis of the detected images. Figure 4(a) is a color image captured by the web camera, Fig. 4(b) is the gray image of Fig. 4(a) that is transformed by the software program, and Fig. 4(c) is a three-dimensional intensity distribution of the Fig. 4(b).
3. Experimental Results and discussion
Because the web camera has detection limit (256 level) and instability of the light source, the effect of saturation and power fluctuation are two important factors influence the reliability. In Fig. 5, the light intensity change of the system without sample in 10 minutes was recorded. It shows the fluctuation of the LED is about ± 2.2%. Figure 6 present some photographs of light spots when the fiber SPR sensor in different RI solutions. It can be seen in the central region of the light spots shown in Figs. 6(a)–6(c), saturation occurs when pixels in bright areas are overexposed and turn to completely white. To show the intensity distribution of the light spots, a three-dimensional intensity distribution is plotted by using a MatLab software. In Fig. 6(d), different colors are used to shown the light intensity and brown mesh is drawn to represent the detection limit (256 level) of the web camera. A related two-dimensional intensity distribution of the light spots in Fig. 6(e), it can be found that the area of the saturation region shown in brown gradually increases, i.e., the numbers of the overexposed pixels gradually increase.
We measure the sodium chloride solutions with RIs of 1.3335, 1.3396, 1.3461, 1.3506, 1.3579, and 1.3645. The samples are prepared with sodium chloride in deionized water and their RIs of are calibrated by an Abbe refractometer (WAY-2S), the testing results are shown in Fig. 7. Figure 7(a) illustrate that the intensity of the light spot, and as a comparison, Fig. 7(b) shows the number of the overexposed pixels as functions of RI fitted by polynomial equations. However, since the saturation and power fluctuation, the linearity and stability of the measure curve is not well.
To compensate for the intensity fluctuation of the LED, we improve the above SPRi device by adding a reference optical fiber channel to monitor the light intensity of LED. The dual-channel self-compensated configuration is shown in Fig. 8. Figure 8(a) illustrates the optical configuration of two SPR channels, similar to the sensing channel, both end faces of the referenced optical fiber are also polished and fixed with the LED. The experimental setup is shown in Fig. 8(b). The lens of the web camera is placed near to both fiber end faces of this SPR sensor. Using a manual-focused web camera, we can finely adjust the distance between the lens and the CCD to obtain clear images. To avoid saturation, we solder the LED and a slide rheostat onto a small circuit board to adjust light intensity of LED. Through appropriately lowering the light power, it makes sure the light collected by web camera in its dynamic range.
During the measurement, using a peristaltic pump, sodium chloride solutions with RIs of 1.3335, 1.3396, 1.3461, 1.3506, 1.3577, and 1.3645 are delivered into flow cell in turn. Web camera takes photographs for each test. The specific light intensity values of the light spots are calculated by the image processing program. The photographs taken by web camera are shown as an inset to Fig. 9(a). The two light spots are located in the photograph without any interference from each other. In this work, a reference channel is used to monitor the fluctuation range of the LED and eliminate this unstable factor by dividing the intensities of the measuring channel and reference channel, its light intensity does not affect the test.
Through improving the image processing program by adding image division function, we calculate and compare the light intensities of the two light spots separately. Because the light intensities of the reference and measuring channels are measured at the same time, the relative intensity can be used to effectively eliminate the power fluctuations of the LED. The relative intensity is expressed as: IR = Im/Ir, where the Im and Ir are the intensity values of the sensing and reference channels, respectively. Using this self-compensating configuration, we measure the SPR image with different RI solutions. Moreover, to test the anti-fluctuation capability of the system, we slightly decrease the light intensity after measuring each sodium chloride solutions. Figure 9(a) shows the processed results from detected photographs, from which we find the intensities of the reference channel fluctuate in different levels when measuring the samples with different RIs from 1.3335 to 1.3645. Although the performance of the light source is unstable during the measurement, the experiment results still demonstrate good RI response of this system after calculating the value of the relative intensity and curve fitting. It shows that the fluctuation of light source has significantly affected the measuring channel; the reference channel is necessary and efficient for compensating the light intensity fluctuations. Figure 9(b) illustrates that the relative intensity as a function of RI can be linear fitted in the RI range of 1.3396-1.3645, which can be used for many biochemical samples measurement. In the RI range of 1.3396-1.3645, the system provide a sensitivity of 400%/RIU and a resolution of 7.5 × 10−4 RIU considering the 0.3% noise level. Comparing Fig. 9(b) with Fig. 7(a), this dual-channel self-referenced SPR imaging sensing device has a significant improvement in linearity and reliability.
To evaluate the biosensing performance of our SPRi system, we use it to examine the specific binding of lectin protein and carbohydrate in solution on sensing surface. RNase B, a highly glycosylated protein, is covalently immobilized on the sensing region surface and presents mannose moieties. Briefly, the gold-coated region of the optical fiber is soaked in an ethanolic solution of 11-mercaptoundecanic acid at room temperature for 24 hours and then treated with an aqueous solution containing N-hydroxysuccinimide(NHS, 0.5M)/1-Ethyl-3-[3-dimethylaminopropyl] carbodiimide hydrochloride (EDC, 0.55 M) at 4°C for 30 minutes. The treated optical fiber is dried in a stream of nitrogen and dipped in RNase B (1.0 mg/ml in PBS buffer, pH 7.4) followed by bovine serum albumin (BSA, 0.2 mg/mL in PBS buffer, pH 7.4) at room temperature for 30 minutes each. After BSA blocking, the optic fiber is assembled with a flow cell and aligned for data collection. A sequence of aqueous solutions (HEPES buffer, Con A solution, HEPES buffer, urea solution, and HEPES buffer) is pumped into the flow cell at a flow rate of 1.0 ml/min using peristaltic pump (Longer, BT100-2J). The Con A solution is dissolved in HEPES buffer containing 1mM Ca2+ and 1mM Mg2+ (pH 8.4). In practice, photographs are captured by the web camera within an interval of 10 seconds and processed using a VC + + -based program developed in our lab. The values of the relative intensity are calculated and plotted as a function of time. Figure 10 shows that, the relative intensity increases significantly due to the injection of Con A, which is consistent with the fact that Con A binds specifically to RNase B on the sensing region surface. Once HEPES buffer flows over the sensing region, the relative intensity decrease slightly, suggesting the removal of physically adsorbed Con A molecules. Urea solution (8.0 M) is applied to strip the surface bound Con A and effectively regenerate the sensing region. Using this SPRi system for three rounds of Con A detection with different concentration (0.05 mg/mL, 0.10 mg/mL, and 0.20 mg/mL), the sensing responses become stronger as Con A concentration increases. In the future, a variety of binding ligands can be introduced onto the gold-coated sensing region [23–25], combined with low-fouling background, the demonstrated SPRi system can be used to detect a variety of biomolecules and cells in a specific and quantitative means, which is potentially attractive for biochemical and biomedical applications. During the chemical modification, we just immerse the SPRi probe in small bottles with different reagents, the sample testing processing is easy and fast.
Additionally, the distance between the lens and CCD is adjustable for the web camera and the area of the fiber end face is very tiny, we can use the end faces of a bundle of optical fibers in front of the web camera for image detection, which can be used as many separate SPR sensing channels. Therefore, this fiber optical SPRi sensing device can be further extended for simultaneous multiple channel monitoring as shown in Fig. 11. This is one of the most important advantages of the demonstrated SPRi system. To compensate the temperature effect and other possible uncontrolled influences during the test, we use an additional reference channel to monitor the sensor responses based on the same conditions for both reference and measuring channels with functional coatings. Many Fiber optic SPR probes with different functional coating can be integrated together as needed, which will be very useful for rapid screening of analytes in biomedical measurements. Also, further investigation is under going to combine this SPRi sensor with smart mobile device to realize a portable reliable multichannel fiber optic SPRi sensor system.
Although commercial SPRi systems with high sensitivity and stability are very important for many biomedical analyses, usually these systems are bulk and complex, also requires strict laboratory conditions. The proposed fiber optic SPRi design is conceived as an ancillary tool for preliminary monitoring in various environments, which provide a convenient and easy technique to detect SPR effect in realistic working conditions. These working conditions imply a compromise between ubiquity and performance. Moreover, commercial SPRi devices often require special and sophisticated equipments which have complex structures, high prices and high maintenance costs. To overcome these drawbacks, the SPRi system that we presented here is an innovational integration of fiber optic sensor and universal electronic components, which avoids strict beam alignment and high costs. Although part of the sensitivity might be lost in this transformation, more works can be done to enhance its sensitivity by using advanced optoelectric components or optimized signal processing methods.
Finally, because this SPRi sensing concept does not rely on the dedicated instruments, meanwhile, it has a reference channel to realize its self compensation function, which can ensure its stability for short or long term application. Limited by the scope of this paper, more investigation will be conducted to optimize the whole system that we will publish separately in the future. The demonstrated SPRi system provide a possible way to replace the bulk, expensive SPR imaging instruments by using general optoelectric components in conventional condition. This SPRi system will find application in environmental monitoring, food quality control, and medical diagnostics.
In summary, we proposed and demonstrated a compact SPRi sensing detection system based on common optoelectronic components. Because the low cost of the components that used in this system, this SPRi technique can be implemented in any environments. The components of this SPRi system such as LED, web camera and laptop can be available in many environments like labs, offices or homes. VC + + windows programs are developed to process the detected images. To eliminate the intensity fluctuation of the LED, a reference optical fiber channel is used to compensate for the light source intensity fluctuation by using a relative intensity ratio between intensities of the reference and sensing channels. The lab-scale tests show the system responses linearly to the RI in a RI range from 1.3396 to 1.3645. We also used this system to detect the specific binding between Con A and RNase B to test its capability for biomedical analysis. The results show that this system can detect the selective affinity through recording the combination processing of biomolecules. This fiber optic SPRi sensing system has its unique advantages of easy implementation, low cost, high flexibility, potential for multichannel detection and mobile devices monitored SPRi sensor. Further investigation will be focus on the system optimization include the enhancement of its sensitivity, sensor packaging, system compactness, software improvement, to make it as a practical SPR imaging system for biological and chemical analyzing and monitoring.
The authors would like to acknowledge the financial supports from the National Nature Science Foundation of China (Grant Nos. 61137005, 21104008, and 60977055), and the Ministry of Education of China (Grant No. SRFDP-20120041110040).
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