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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 20 — Sep. 26, 2011
  • pp: 18965–18978
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Multiplex spectral surface plasmon resonance imaging (SPRI) sensor based on the polarization control scheme

Chi Lok Wong, George Chung Kit Chen, Beng Koon Ng, Shuchi Agarwal, Zhiping Lin, Peng Chen, and Ho Pui Ho  »View Author Affiliations


Optics Express, Vol. 19, Issue 20, pp. 18965-18978 (2011)
http://dx.doi.org/10.1364/OE.19.018965


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Abstract

A two-dimensional (2D) spectral SPR sensor based on a polarization control scheme is reported in this paper. The polarization control configuration converts the phase difference between p- and s- polarization occurring at surface plasmon resonance (SPR) into corresponding color responses in spectral SPR images. A sensor resolution of 2.7 x 10−6 RIU has been demonstrated, which corresponds to more than one order of magnitude resolution improvement (26 times) comparing to existing 2D spectral SPR sensors. Multiplex array detection has also been demonstrated with the spectral SPR imaging sensor. In a 8 x 4 sensor array, 32 samples with different refractive index values were monitored simultaneously. Detection on bovine serum albumin (BSA) antigen-antibody binding further demonstrated the multiplex detection capability of the 2D spectral SPR sensor for bio-molecular interactions. The detection limit is found to be 21ng/ml, which is 36 times better than the detection limit previously reported by phase imaging SPR sensors. In light of the advantages of high sensitivity, 2D multiplex detection and real-time response, the spectral SPR imaging sensor can find promising applications in rapid, high throughput, non-labeling and multiplex detection of protein array for proteomics studies, biomarker screening, disease prognosis, and drug discovery.

© 2011 OSA

1. Introduction

Protein array provides the capability of multiplexed detection, which allows large amount of sample spots to be processed in single measurement. It has been widely used in proteomics [1

1. M. Srivastava, O. Eidelman, C. Jozwik, C. Paweletz, W. Huang, P. L. Zeitlin, and H. B. Pollard, “Serum proteomic signature for cystic fibrosis using an antibody microarray platform,” Mol. Genet. Metab. 87(4), 303–310 (2006). [CrossRef] [PubMed]

], disease prognosis [2

2. G. Mor, I. Visintin, Y. Lai, H. Zhao, P. Schwartz, T. Rutherford, L. Yue, P. Bray-Ward, and D. C. Ward, “Serum protein markers for early detection of ovarian cancer,” Proc. Natl. Acad. Sci. U.S.A. 102(21), 7677–7682 (2005). [CrossRef] [PubMed]

], drug discovery [3

3. M. A. Reynolds, H. J. Kirchick, J. R. Dahlen, J. M. Anderberg, P. H. McPherson, K. K. Nakamura, D. T. Laskowitz, G. E. Valkirs, and K. F. Buechler, “Early biomarkers of stroke,” Clin. Chem. 49(10), 1733–1739 (2003). [CrossRef] [PubMed]

] and biomarker screening [4

4. P. Angenendt, “Progress in protein and antibody microarray technology,” Drug Discov. Today 10(7), 503–511 (2005). [CrossRef] [PubMed]

]. The bound antigens on the antibody array are commonly detected by the direct labeling method [5

5. B. B. Haab, “Methods and applications of antibody microarrays in cancer research,” Proteomics 3(11), 2116–2122 (2003). [CrossRef] [PubMed]

], and dual antibody sandwich assay [5

5. B. B. Haab, “Methods and applications of antibody microarrays in cancer research,” Proteomics 3(11), 2116–2122 (2003). [CrossRef] [PubMed]

,6

6. R. P. Huang, R. Huang, Y. Fan, and Y. Lin, “Simultaneous detection of multiple cytokines from conditioned media and patient’s sera by an antibody-based protein array system,” Anal. Biochem. 294(1), 55–62 (2001). [CrossRef] [PubMed]

]. Either labeling tags (such as, fluorescence [7

7. G. MacBeath and S. L. Schreiber, “Printing proteins as microarrays for high-throughput function determination,” Science 289(5485), 1760–1763 (2000). [PubMed]

], chemiluminescence [8

8. T. O. Joos, M. Schrenk, P. Höpfl, K. Kröger, U. Chowdhury, D. Stoll, D. Schörner, M. Dürr, K. Herick, S. Rupp, K. Sohn, and H. Hämmerle, “A microarray enzyme-linked immunosorbent assay for autoimmune diagnostics,” Electrophoresis 21(13), 2641–2650 (2000). [CrossRef] [PubMed]

] and radioactive isotopes [9

9. H. Ge, “UPA, a universal protein array system for quantitative detection of protein-protein, protein-DNA, protein-RNA and protein-ligand interactions,” Nucleic Acids Res. 28(2), 3e (2000). [CrossRef] [PubMed]

]) or secondary antibodies are required in the bio-assays that can interfere with the original antibody-antigen interactions. In addition, Enzyme-linked immunosorbent assay (ELISA) also requires different second antibody-antigen interaction for each sample in the array.

Surface plasmon resonance imaging (SPRI) is a non-labeling sensing technique for the direct detection of antibody-antigen interaction in an array format [10

10. C. L. Wong, H. P. Ho, T. T. Yu, Y. K. Suen, W. W. Y. Chow, S. Y. Wu, W. C. Law, W. Yuan, W. J. Li, S. K. Kong, and C. Lin, “Two-dimensional biosensor arrays based on surface plasmon resonance phase imaging,” Appl. Opt. 46(12), 2325–2332 (2007). [CrossRef] [PubMed]

,11

11. C. L. Wong, H. P. Ho, Y. K. Suen, S. K. Kong, Q. L. Chen, W. Yuan, and S. Y. Wu, “Real-time protein biosensor arrays based on surface plasmon resonance differential phase imaging,” Biosens. Bioelectron. 24(4), 606–612 (2008). [CrossRef] [PubMed]

]. It can directly detect the bound protein on the antibody array through the refractive index change occurring on the gold sensor surface [12

12. J. Homola, S. S. Yee, and G. Gauglitz, “Surface plasmon resonance sensors: review,” Sens. Actuators B Chem. 54(1-2), 3–15 (1999). [CrossRef]

]. SPR imaging also provides quantitative and kinetic binding information [13

13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

]. Common SPR imaging detection technique is based on the intensity interrogation [13

13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

,14

14. J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods 37(1), 26–36 (2005). [CrossRef] [PubMed]

]. It measures the reflectivity change caused by the refractive index changes on the sensing surface. The major limitation of intensity SPR imaging is the limited sensor resolution [14

14. J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods 37(1), 26–36 (2005). [CrossRef] [PubMed]

] and it can only provide a resolution in 10−5 refractive index unit (RIU).

In recent years, two dimensional (2D) spectral SPR sensors based on the wavelength interrogation have been intensively studied by Jong et al. [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

] and also Wong and Ho et al. [22

22. H. P. Ho, C. L. Wong, K. S. Chan, S. Y. Wu, and C. Lin, “Application of two-dimensional spectral surface plasmon resonance to imaging of pressure distribution in elastohydrodynamic lubricant films,” Appl. Opt. 45(23), 5819–5826 (2006). [CrossRef] [PubMed]

24

24. C. L. Wong, H. P. Ho, K. S. Chan, and S. Y. Wu, “Application of surface plasmon resonance sensing to studying elastohydrodynamic lubricant films,” Appl. Opt. 44(23), 4830–4837 (2005). [CrossRef] [PubMed]

]. Jong et al. has further applied the imaging techniques for the detection of C-reactive protein [18

18. J. S. Yuk, D. G. Hong, H. I. Jung, and K. S. Ha, “Application of spectral SPR imaging for the surface analysis of C-reactive protein binding,” Sens. Actuators B Chem. 119(2), 673–675 (2006). [CrossRef]

] and blood protein [19

19. J. S. Yuk, M. J. Lee, U. R. Kim, and K. S. Ha, “Analysis of blood proteins on protein arrays with a spectral surface plasmon resonance biosensor,” Curr. Appl. Phys. 7(1), 102–107 (2007). [CrossRef]

]. However, their spectral imaging sensors [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

,16

16. J. S. Yuk, H. S. Kim, J. W. Jung, S. H. Jung, S. J. Lee, W. J. Kim, J. A. Han, Y. M. Kim, and K. S. Ha, “Analysis of protein interactions on protein arrays by a novel spectral surface plasmon resonance imaging,” Biosens. Bioelectron. 21(8), 1521–1528 (2006). [CrossRef] [PubMed]

] mainly rely on the SPR absorption dip determination in the spectrum and scanning throughout the entire sample plane for the reconstruction of the spectral SPR image is required (scanning time of a 2mm diameter spot is approximately 180s). Real-time monitoring of bio-molecular interaction is therefore restricted. In addition, it can only provide a resolution in 7 x 10−5 RIU, which is similar to that of conventional intensity SPR imaging sensors [14

14. J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods 37(1), 26–36 (2005). [CrossRef] [PubMed]

].

In this paper, we present a spectral SPR imaging sensor based on a polarization control scheme. A SPR prism coupler is placed in between two polarizers. The angle between the transmission axes of the two polarizers is 90 degrees and therefore the incident beam cannot be transmitted through the cross polarizers. At (or close to) the excitation wavelength of the surface plasmon wave, a phase difference Δφ is introduced between the p- and s- polarization component of the light. The orientation angle of the ellipse α is shifted correspondingly and the rotation of the ellipse allows the light interacting with the surface plasmon to be transmitted through the cross polarizers. Since the surface plasmon excitation condition is only matched with particular region of wavelength, particular spectral profile is produced and corresponding color change is produced in the spectral SPR image. A sensor resolution of 2.7 x 10−6 RIU is demonstrated with the spectral SPR imaging sensor and this provides more than one order of magnitude resolution improvement comparing to the existing 2D spectral SPR imaging sensors [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

] and the most widely used intensity SPR imaging sensors [14

14. J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods 37(1), 26–36 (2005). [CrossRef] [PubMed]

]. In addition, entire sensing surface can be imaged in one single spectral SPR image and no time-consuming scanning [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

] is required. The high throughput array detection ability of the imaging sensor has also been demonstrated in this paper and a 4 x 8 (32 elements) array of refractive index samples are simultaneously monitored with the 2D sensing feature of the imaging sensor. The spectral SPR imaging sensor combines the advantages of real-time response, high sensitivity and 2D multiplex sensing. Thus the sensor can find promising application in multiplex protein array detection for rapid, high throughput and non-labeling detection in proteomics studies, biomarker screening, disease prognosis and drug discovery [1

1. M. Srivastava, O. Eidelman, C. Jozwik, C. Paweletz, W. Huang, P. L. Zeitlin, and H. B. Pollard, “Serum proteomic signature for cystic fibrosis using an antibody microarray platform,” Mol. Genet. Metab. 87(4), 303–310 (2006). [CrossRef] [PubMed]

4

4. P. Angenendt, “Progress in protein and antibody microarray technology,” Drug Discov. Today 10(7), 503–511 (2005). [CrossRef] [PubMed]

].

2. Theory and experimental set-up

2.1 Surface plasmon resonance

The surface plasmon resonance phenomenon was first demonstrated by Otto [25

25. A. Otto, “Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection,” Z. Phys. 216(4), 398–410 (1968). [CrossRef]

] and Kretschmann [26

26. E. Kretschmann, “The determination of the optical constants of metals by the excitation of surface plasmons,” Z. Phys. 241, 313 (1974).

]. The wave vector ksp of the surface plasmon is given by the equation [27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

],
ksp=(ωsp/c)((εmεs)/(εm+εs))1/2
(1)
where εm- the dielectric constant of the metal film, εs- the dielectric constant of the dielectric medium and ωsp - surface plasmon frequency.

In Kretschmann configuration [26

26. E. Kretschmann, “The determination of the optical constants of metals by the excitation of surface plasmons,” Z. Phys. 241, 313 (1974).

], the wave vector of the incident beam is described by the equation [27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

],
kin=(2π/cλ)sinθεp1/2
(2)
where εp is the dielectric constant of the prism material.

At surface plasmon resonance, the energy of the incident photons is transformed into surface plasmons and the resonance condition is described by the equations [27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

],
kin=ksp
(3)
(2π/λ)εp1/2sinθSPR=ωsp((εmεs)/(εm+εs))1/2
(4)
where θSPR is the SPR resonance angle.

Since refractive index ns equals the square root of εs (i.e. ns=εs1/2), the refractive index change in the dielectric medium alters the characteristic of surface plasmon wave and SPR resonance condition.

2.2 Phase difference between p- and s- polarization

S. G. Nelson et al. [28

28. S. G. Nelson, K. S. Johnston, and S. S. Yee, “High sensitivity surface plasmon resonance sensor based on phase detection,” Sens. Actuators B Chem. 35(1-3), 187–191 (1996). [CrossRef]

] reported that a rapid phase change ϕpis produced to the p- polarization component during the surface plasmon excitation. However, the s- polarization component contains no resonant feature, because the oscillation direction is perpendicular to the excitation plane of the surface plasmon wave [12

12. J. Homola, S. S. Yee, and G. Gauglitz, “Surface plasmon resonance sensors: review,” Sens. Actuators B Chem. 54(1-2), 3–15 (1999). [CrossRef]

,13

13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

].

As described by the Fresnel model [27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

,29

29. P. Yeh, Optical waves in layered media, (Wiley, 1988).

,30

30. S. Y. Wu, H. P. Ho, W. C. Law, C. Lin, and S. K. Kong, “Highly sensitive differential phase-sensitive surface plasmon resonance biosensor based on the Mach-Zehnder configuration,” Opt. Lett. 29(20), 2378–2380 (2004). [CrossRef] [PubMed]

], the reflection coefficients rpand rs of p- and s-polarization respectively can be expressed as,
rp=|rp|eiφp
(5)
rs=|rs|eiφs
(6)
Considering a three layer system [prism(1)/metal(2)/dielectric medium(3)], which is used in our experiment set-up, the complex reflection coefficient rp(s) is given by the equation [27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

,29

29. P. Yeh, Optical waves in layered media, (Wiley, 1988).

,30

30. S. Y. Wu, H. P. Ho, W. C. Law, C. Lin, and S. K. Kong, “Highly sensitive differential phase-sensitive surface plasmon resonance biosensor based on the Mach-Zehnder configuration,” Opt. Lett. 29(20), 2378–2380 (2004). [CrossRef] [PubMed]

],
rp(s)=r12+r23exp(2ikz2d)1+r12r23exp(2ikz2d)
(7)
where d is the thickness of the metal film, kz2 is the wave vector at the metal surface, r ij is the Fresnel coefficient between the i th and j th layer. Fresnel coefficient is given by,
rij=ZiZjZi+Zj
(8)
where Zi=εi/kzi for p-polarization
(9)
kzi=ko(εiε1sin2θin)1/2
(10)
Z is the impedance, kzi is the component of the wave vector in the i th layer normal to the metal thin film, kois the wave vector of the optical wave in the free space.

Refractive index variations in the dielectric medium alter the value ofεs, (Δns=Δεs1/2). In p- polarization, the refractive index change alters the Fresnel coefficient rp 23 and therefore the complex reflection coefficient rp is modified. According to Eq. (5), a corresponding phase response ϕp is produced. However, no phase shift is produced to the s- polarization, because the oscillation direction is perpendicular to the excitation plane of the surface plasmon wave [12

12. J. Homola, S. S. Yee, and G. Gauglitz, “Surface plasmon resonance sensors: review,” Sens. Actuators B Chem. 54(1-2), 3–15 (1999). [CrossRef]

,13

13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

,27

27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

]. A phase difference Δϕ is therefore produced between the p- and s- polarizations [30

30. S. Y. Wu, H. P. Ho, W. C. Law, C. Lin, and S. K. Kong, “Highly sensitive differential phase-sensitive surface plasmon resonance biosensor based on the Mach-Zehnder configuration,” Opt. Lett. 29(20), 2378–2380 (2004). [CrossRef] [PubMed]

],

Δφ=(φpφs)
(11)

2.3 Elliptical Polarization

Considering an elliptically polarized lightE and the two orthogonal optical disturbances (p- and s- components) can be represented as [31

31. H. Eugene, Optics, 4th ed. (Addison-Wesley Publishing Company, 2001).

],
Es=Esocos(kzωt)
(12)
Ep=Epocos(kzωt+ϕ)
(13)
where ε is the relative phase difference between the two orthogonal optical disturbances (p- and s- wave).

The elliptically polarized lightEcan be further described by the following equation of ellipse [31

31. H. Eugene, Optics, 4th ed. (Addison-Wesley Publishing Company, 2001).

]
(EpEpo)2+(EsEso)22(EpEpo)(EsEso)cosϕ=sin2ϕ
(14)
The elliptically polarized lightE also makes an orientation angle α with the (Es,Ep) coordinate system [31

31. H. Eugene, Optics, 4th ed. (Addison-Wesley Publishing Company, 2001).

] such that
tan2α=(2EsoEpoE2soE2po)cosϕ
(15)
Recalling Eq. (11), a phase difference between the p- and s- polarizations is produced at surface plasmon excitation,
Δϕ=(ϕpϕs)
Therefore, the wave vector of E can be modified as
Es=Esocos(kzωt)
(16)
Ep=Epocos(kzωt+ϕ+Δφ)
(17)
Based on Eq. (16) and Eq. (17), the equation of the elliptically polarized lightEand the angle with the (Es,Ep) coordinate system are also modified.
(EpEpo)2+(EsEso)22(EpEpo)(EsEso)cos(ϕ+Δφ)=sin2(ϕ+Δφ)
(18)
tan2α=(2EsoEpoE2soE2po)cos(ϕ+Δφ)
(19)
As shown in Fig. 1(a)
Fig. 1 (a) Experimental scheme of the Spectral SPR imaging sensor based on the polarization control scheme (b) The orientation angle shift αof the ellipse of the light, which is produced by the phase difference Δφ between the p- and s- polarization occurring at surface plasmon excitation.
, the SPR prism coupler is placed in between two polarizers. The angle between the transmission axes of these two polarizers is 90 degree. Thus the broad band incident beam can’t be transmitted through the cross polarizers. At (or close to) the excitation wavelength of the surface plasmon wave, a phase difference Δφ is introduced between the p- and s- polarization component of the light. As described by Eq. (19), the orientation angle of the ellipse α is shifted correspondingly (as shown in Fig. 1(b)) and the rotation of the ellipse allows the light interacting with the surface plasmon to be transmitted through the cross polarizers. At wavelength out of the excitation spectral range, the interaction with the surface plasmon wave is weak and the ellipse is almost parallel to the original orientation angle of the incident beam, therefore no significant transmitting light is observed in the wavelength region longer or shorter than the excitation wavelength. The modeling work reported by Homola et al. [32

32. J. Homola and S. S. Yee, “Novel polarization control scheme for spectral surface plasmon resonance sensors,” Sens. Actuators B Chem. 51(1–3), 331–339 (1998). [CrossRef]

] shows that different spectral responses are produced for different phase differences . Δϕ. between the p- and s- polarization.

In this paper, the spectral SPR imaging relies on the color change caused by the spectral response variation, which corresponds to the differential phase change Δϕ between p- and s- polarization. Figure 1(a) shows the experimental set-up of the sensor system. Halogen illuminator is used as a broad band light source. The beam is collimated and expanded with a 10x objective lens and a bi-concave lens. After passing through the first polarizer (input polarizer), the polarized beam enters a gold sensing layer coated on glass prism. A PDMS based micro-fluidic flow cell is attached on the sensor surface for feeding in samples with different refractive index values. Then, the beam passes through a quarter wave plate and the second polarizer (output polarizer). The angle of rotation of the input and output polarizer is chosen to be perpendicular to each other. Finally, the resultant SPR images are captured by a color CCD camera and they are analyzed using our internally developed software.

3. Results and discussions

To estimate the performance of the spectral SPR imaging sensor, measurements on different concentrations of salt solution samples ranged from 0%, 1%, 2%, 3%, 4% and 7%, which corresponding to refractive index values from 1.3333 – 1.3454 RIU [33

33. D. R. Lide, Handbook of Chemistry and Physics, 82nd ed. (CRC Press, 2001).

] have been performed.

Figure 2
Fig. 2 Spectral SPR images for different concentrations of salt solutions. (a) water (0%) (b) 1% salt solution (c) 2% salt solution (d) 3% salt solution (e) 4% salt solution (f) 7% salt solution.
shows the Spectral SPR images for different concentrations of salt solutions. As shown in Fig. 2(a), the Spectral SPR image of water sample (0%) is major in deep red color. When the concentration of salt solution increases from 0% to 7%, the SPR image changes from deep red to green in color (Fig. 2(f)). The color changes in SPR images refer to the spectral characteristics changes caused by the different differential phase shifts (between p- and s- polarization), which is produced by the variation of surface plasmon resonance conditions for different refractive index dielectric samples.

In addition, a portable spectrometer (Ocean Optics USB2000) was used to show the spectral characteristic profiles for different concentrations salt solutions. The spectrums of different salt solution samples are shown in Fig. 3
Fig. 3 Spectrums measured for different concentrations of salt solutions ranged from 0% - 7%. (Normalized will s- polarization spectrum).
. For water (0%) sensing, the spectrum shows that the signal in the red color spectral band (after 600nm) is much higher than that in the green spectral band, therefore the resultant SPR image color is dominant red in color (as shown in Fig. 2(a)). The results also show that the signal from the red spectral band decrease for increasing concentration of salt solutions, while the signals from the green spectral band remains unchanged. These results correlate well with the experimental finding obtained in Fig. 2 that the SPR images change from red to green in color for increasing concentration of salt solutions.

In the analysis of the spectral SPR images, we treat all colors as linear combinations of three primary colors, namely red (R), green (G) and blue (B). An established RGB imaging model has already been defined by the CIE (Commission International de I’Eclarage) to contain three standard primary components (R, G and B refer to monochromatic spectral energies at wavelengths 700nm, 546.1nm and 435.8nm respectively) so that the color of a pixel can be represented by a linear combination of these primary components [34

34. F. van der Heijden, Image Based Measurement System (John Wiley & Sons, 1994).

]. Besides, several other color models have also emerged to provide equivalent representation for different engineering applications. The XYZ, CMYK, YIQ and HSV models are most commonly used color coding systems [34

34. F. van der Heijden, Image Based Measurement System (John Wiley & Sons, 1994).

,35

35. T. Bose, Digital Signal and Image Processing (Wiley, 2004).

]. Nonetheless, only the Hue (H) component in HSV coding directly refers to the dominant wavelength of a color [34

34. F. van der Heijden, Image Based Measurement System (John Wiley & Sons, 1994).

,35

35. T. Bose, Digital Signal and Image Processing (Wiley, 2004).

]. In the present case, since the spectral SPR images are produced by the wavelength dependence spectral characteristic variations, the use of Hue value for analyzing the imaging is a more appropriate approach.

To quantify the color changes in the spectral SPR images, the Hue (H) profiles of the spectral SPR images shown in Fig. 2(a)2(f) are extracted and plotted against the refractive index changes. It gives the response curve of the spectral SPR imaging sensor. Figure 4
Fig. 4 The response curve of the spectral SPR imaging sensor in the refractive index range between 1.3333 - 1.3454 RIU. It shows the sensor responds for different concentration salt solutions ranged from 0%-7%. It shows that the sensor response increases with increasing refractive index values (RIU) and a linear response (from 23.1 to 61.2 Hue unit) is shown in the refractive index range between 1.3333 – 1.3365 RIU. The error bar is obtained from the standard deviation (S.D.) between 5 averaged measurement data.
shows the sensor response for different concentration salt solutions ranged from 0%-7% and it can be seen that the sensor response (Hue values) increases with increasing refractive index values (RIU).

The error bar in Fig. 4 is obtained from the standard deviation (S.D.) between five averaged measurement data. The S.D. values for different concentration samples are listed in Table 1

Table 1. The Measurement Standard Deviation of Different Concentration Salt Solution

table-icon
View This Table
. The overall measurement S.D. of the system is calculated from the average S.D. values among 0%-7% measurement S.D. and this value is used as the Measurement S.D. in the calculation of the sensor resolution.As reported in [13

13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

,37

37. C. L. Wong, H. P. Ho, K. S. Chan, S. Y. Wu, and C. Lin, “Application of spectral surface plasmon resonance to gas pressure sensing,” Opt. Eng. 44(12), 124403 (2005). [CrossRef]

], sensor resolution can be calculated by the relationship shown in Eq. (20) and the sensor resolution of the spectral SPR imaging sensor is found to be 2.7 x 10−6 RIU. It provides one order of magnitude resolution improvement (26 times) over the existing 2D spectral SPR sensors [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

].
resolution=RIUrangeresponse(ΔHue)×measurementS.D.
(20)
In addition, time-consuming scanning is required in the existing 2D spectral SPR sensors [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

]. However, color CCD camera is used in our sensor configuration for the real-time capturing of spectral SPR images. The real-time 2D sensing feature not only enables the detection of fast bio-molecular interactions, but also allows high-throughput detection of a range of reaction sites in an array format.

The 2D sensing feature of the spectral SPR imaging sensor has been demonstrated in the results shown in Fig. 5
Fig. 5 (a) Spectral SPR image taken for three different concentrations (0%, 2% and 7%) of salt solution spots. Different color responses have been demonstrated for different concentration solutions. Deep red, deep green and green color responses are shown for 0%, 2% and 7% salt solution spots respectively. (b) Hue mapping of the spectral SPR image. The responses of 0%, 2% and 7% salt solution spots are 25.7, 69.1 and 83.4 (hue unit) (average value from all sensing sites).
. A 8 x 4 array of salt solution spots were spotted in the gold sensing surface and a color CCD camera was used to capture the responses from all the 32 elements in one single spectral SPR image. Figure 5(a) shows the spectral SPR image taken for three different concentrations (0%, 2% and 7%) of salt solution spots. Different color responses have been demonstrated for different concentration solutions. Deep red, deep green and green color responses are shown for 0%, 2% and 7% salt solution spots respectively. The spectral response in the SPR image was further quantified through Hue (H) profile extraction and it is shown in Fig. 5(b). The responses of 0%, 2% and 7% salt solution spots are 25.7, 69.1 and 83.4 (hue unit) (average value from all sensing sites).

Multiplex detection of antigen-antibody binding interactions has been carried with the 2D spectral SPR sensor. Bovine serum albumin (BSA) antigen and corresponding antibody (anti-BSA) were used as the testing sample in the experiment. As shown in Fig. 6(a)
Fig. 6 (a) Bovine serum albumin (BSA) antigen (1mg/ml) was immobilized in four different locations of the protein array (red spots). The non-specific protein sample (glucose oxidase, 1mg/ml) served as the negative control of the experiment (white spots). (b) Spectral SPR image of the protein array, when the protein was kept in buffer solution. (c) Spectral SPR image of the protein array, which is taken 41 minutes after the injection of BSA antibody (0.01mg/ml). The specific binding between BSA antigen-antibody changed the spectral responses in the BSA antigen sites from red to green color, while no significant color variation were observed in the non-specific sensor sites (glucose oxidase).
, four sensor sites of the protein array were immobilized with BSA antigen (1mg/ml). In addition, a non-specific protein sample (glucose oxidase, 1mg/ml) was immobilized in another four sensor sites and they served as the negative control of the experiment (Fig. 6(a)).

Initially, the protein array was kept at phosphate buffered saline (PBS) buffer solution. Then, anti-BSA (antibody, 0.01mg/ml) was injected to the protein array surface. The subsequent antigen-antibody binding interactions at all sensor sites were imaged by the 2D spectral SPR sensor in parallel. Figure 6(b) shows the spectral SPR image of the protein array, when it was kept at the buffer solution. As shown in the image, red color responses were observed in both specific and non-specific sensor sites. Figure 6(c) further shows the SPR image captured at 41 minutes after the injection of BSA antibody. As shown in the result, the spectral responses of all the specific sites (BSA antigen) were changed from red to green color, which were corresponding to the binding interactions between the BSA antigen and BSA antibody. However, no significant change of spectral response was observed at the non-specific sites (glucose oxidase).

In order to quantify the spectral response changes in the SPR image, Hue extraction has been performed in every sensor site. The average Hue value of the BSA antigen sites is 13.96 ± 0.11 (Hue unit) when the protein array was kept at buffer solution and the Hue value increases to 66.24 ± 0.21 (Hue unit) after the injection of BSA antibody. The injection of 0.01 mg/ml BSA antibody therefore results in a sensor response of 52.28 (Hue unit). In addition, the standard deviation between 10 measurements is 0.11 (Hue unit), when the BSA antigen sites were placed in buffer solution. It gives the measurement stability of the system. Finally, the detection limit of the 2D spectral SPR sensor is calculated with Eq. (21). It is found to be 21ng/ml.
Detection limit =Concentration of bio-moleculeSensor response×Measurement stability
(21)
Comparing to similar works reported by Lee et al. (10−4 mg/ml) [38

38. K. H. Lee, Y. D. Su, S. J. Chen, F. G. Tseng, and G. B. Lee, “Microfluidic systems integrated with two-dimensional surface plasmon resonance phase imaging systems for microarray immunoassay,” Biosens. Bioelectron. 23(4), 466–472 (2007). [CrossRef] [PubMed]

] and Wong et al. (7.7 × 10−4 mg/ml) [11

11. C. L. Wong, H. P. Ho, Y. K. Suen, S. K. Kong, Q. L. Chen, W. Yuan, and S. Y. Wu, “Real-time protein biosensor arrays based on surface plasmon resonance differential phase imaging,” Biosens. Bioelectron. 24(4), 606–612 (2008). [CrossRef] [PubMed]

] with phase imaging SPR sensors, the 2D spectral SPR sensor has demonstrated 36 times improvement in detection limit. The experimental results also demonstrate the capability of the 2D spectral SPR sensor for multiplex bio-molecular binding interactions imaging.

4. Conclusion

A two-dimensional (2D) spectral SPR sensor based on a polarization control scheme has been demonstrated. The polarization control configuration converts the phase shift between p- and s- polarization occurring at surface plasmon resonance (SPR) into corresponding color responses in spectral SPR images. A sensor resolution of 2.7 x 10−6 RIU has been demonstrated, which corresponds to one order of magnitude resolution improvement (26 times) comparing to the existing 2D spectral SPR imaging sensors [15

15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

21

21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

]. The multiplex array detection ability of the imaging sensor has further been demonstrated. In a 4 x 8 sensor array, 32 samples with different refractive index values were simultaneously monitored with the 2D spectral SPR sensor. Detection on bovine serum albumin (BSA) antigen-antibody binding further demonstrated the multiplex detection capability of the 2D spectral SPR sensor for bio-molecular interactions. The detection limit is found to be 21ng/ml, which is 36 times better than the detection limit previously reported by phase imaging SPR sensors [11

11. C. L. Wong, H. P. Ho, Y. K. Suen, S. K. Kong, Q. L. Chen, W. Yuan, and S. Y. Wu, “Real-time protein biosensor arrays based on surface plasmon resonance differential phase imaging,” Biosens. Bioelectron. 24(4), 606–612 (2008). [CrossRef] [PubMed]

,38

38. K. H. Lee, Y. D. Su, S. J. Chen, F. G. Tseng, and G. B. Lee, “Microfluidic systems integrated with two-dimensional surface plasmon resonance phase imaging systems for microarray immunoassay,” Biosens. Bioelectron. 23(4), 466–472 (2007). [CrossRef] [PubMed]

]. The polarization control scheme also provides a simplified way for probing the phase difference between p- and s- polarization, which offers real time sensor response and the information on the entire 2D sensor surface is provided (i.e. pixel to pixel conversion), because no information in the time domain and spatial domain is scarified in the process of phase modulation and phase extraction [10

10. C. L. Wong, H. P. Ho, T. T. Yu, Y. K. Suen, W. W. Y. Chow, S. Y. Wu, W. C. Law, W. Yuan, W. J. Li, S. K. Kong, and C. Lin, “Two-dimensional biosensor arrays based on surface plasmon resonance phase imaging,” Appl. Opt. 46(12), 2325–2332 (2007). [CrossRef] [PubMed]

,39

39. P. I. Nikitin, A. N. Grigorenko, A. A. Beloglazov, M. V. Valeiko, A. I. Savchuk, O. A. Savchuk, G. Steiner, C. Kuhne, A. Huebner, and R. Salzer, “Surface plasmon resonance interferometry for micro-array biosensing,” Sens. Actuators A Phys. 85(1–3), 189–193 (2000). [CrossRef]

41

41. X. Yu, D. Wang, X. Wei, X. Ding, W. Liao, and Z. Xinsheng, “A surface plasmon resonance imaging interferometry for protein micro-array detection,” Sens. Actuators B Chem. 108(1–2), 765–771 (2005). [CrossRef]

]. In light of the advantages of real-time response, high sensitivity and multiplex sensing feature of the spectral SPR imaging sensor, it can find promising applications in rapid, high throughput and non-labeling detection in protein array detection for proteomics studies, biomarker screening, disease prognosis, and drug discovery.

Appendix: RGB to HSV algorithm [36

36. A. R. Smith, “Color gamut transform pairs,” Comput. Graph. 12(3), 12–19 (1978). [CrossRef]

]

The equivalent H, S and V are on the range [0, 1] and r, g and b values (corresponding to the R, G and B values respectively) are on the range [0, 1],
  • 1) Let V = max (r, g, b); (i.e. choosing the maximum component - either r, g or b)
  • 2) Let X = min (r, g, b); (i.e. choosing the minimum component)
  • 3) Let S = (V - X) / V,
  • 4) Let k = (V – r) / (V - X);

    m = (V – g) / (V - X);

    n = (V – b) / (V - X);

  • 5) Conditions

    If r = V and g = X, h = (5 + n);

    If r = V and g ≠ X, h = (1 – m);

    If g = V and b = X, h = (1 + k);

    If g = V and b ≠ X, h = (3 – n);

    If g ≠ V and r = X, h = (3 + m);

    If g ≠ V and r ≠ X, h = (5 – k);

  • 6) hue = h / 6
In the experiment, we express the hue value on the range [0, 255] with the expression - Hue(H)=hue1(255)

Acknowledgment

This project is supported by Singapore Bio-Imaging Consortium under grant RP C-015 /2007. The author (Chi Lok Wong) would like to give thanks to the grace of Jesus Christ throughout every experiment. The prayer from his mother, Vanessa Ho, is also acknowledged.

References and links

1.

M. Srivastava, O. Eidelman, C. Jozwik, C. Paweletz, W. Huang, P. L. Zeitlin, and H. B. Pollard, “Serum proteomic signature for cystic fibrosis using an antibody microarray platform,” Mol. Genet. Metab. 87(4), 303–310 (2006). [CrossRef] [PubMed]

2.

G. Mor, I. Visintin, Y. Lai, H. Zhao, P. Schwartz, T. Rutherford, L. Yue, P. Bray-Ward, and D. C. Ward, “Serum protein markers for early detection of ovarian cancer,” Proc. Natl. Acad. Sci. U.S.A. 102(21), 7677–7682 (2005). [CrossRef] [PubMed]

3.

M. A. Reynolds, H. J. Kirchick, J. R. Dahlen, J. M. Anderberg, P. H. McPherson, K. K. Nakamura, D. T. Laskowitz, G. E. Valkirs, and K. F. Buechler, “Early biomarkers of stroke,” Clin. Chem. 49(10), 1733–1739 (2003). [CrossRef] [PubMed]

4.

P. Angenendt, “Progress in protein and antibody microarray technology,” Drug Discov. Today 10(7), 503–511 (2005). [CrossRef] [PubMed]

5.

B. B. Haab, “Methods and applications of antibody microarrays in cancer research,” Proteomics 3(11), 2116–2122 (2003). [CrossRef] [PubMed]

6.

R. P. Huang, R. Huang, Y. Fan, and Y. Lin, “Simultaneous detection of multiple cytokines from conditioned media and patient’s sera by an antibody-based protein array system,” Anal. Biochem. 294(1), 55–62 (2001). [CrossRef] [PubMed]

7.

G. MacBeath and S. L. Schreiber, “Printing proteins as microarrays for high-throughput function determination,” Science 289(5485), 1760–1763 (2000). [PubMed]

8.

T. O. Joos, M. Schrenk, P. Höpfl, K. Kröger, U. Chowdhury, D. Stoll, D. Schörner, M. Dürr, K. Herick, S. Rupp, K. Sohn, and H. Hämmerle, “A microarray enzyme-linked immunosorbent assay for autoimmune diagnostics,” Electrophoresis 21(13), 2641–2650 (2000). [CrossRef] [PubMed]

9.

H. Ge, “UPA, a universal protein array system for quantitative detection of protein-protein, protein-DNA, protein-RNA and protein-ligand interactions,” Nucleic Acids Res. 28(2), 3e (2000). [CrossRef] [PubMed]

10.

C. L. Wong, H. P. Ho, T. T. Yu, Y. K. Suen, W. W. Y. Chow, S. Y. Wu, W. C. Law, W. Yuan, W. J. Li, S. K. Kong, and C. Lin, “Two-dimensional biosensor arrays based on surface plasmon resonance phase imaging,” Appl. Opt. 46(12), 2325–2332 (2007). [CrossRef] [PubMed]

11.

C. L. Wong, H. P. Ho, Y. K. Suen, S. K. Kong, Q. L. Chen, W. Yuan, and S. Y. Wu, “Real-time protein biosensor arrays based on surface plasmon resonance differential phase imaging,” Biosens. Bioelectron. 24(4), 606–612 (2008). [CrossRef] [PubMed]

12.

J. Homola, S. S. Yee, and G. Gauglitz, “Surface plasmon resonance sensors: review,” Sens. Actuators B Chem. 54(1-2), 3–15 (1999). [CrossRef]

13.

J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).

14.

J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods 37(1), 26–36 (2005). [CrossRef] [PubMed]

15.

J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem. 94(2), 161–164 (2003). [CrossRef]

16.

J. S. Yuk, H. S. Kim, J. W. Jung, S. H. Jung, S. J. Lee, W. J. Kim, J. A. Han, Y. M. Kim, and K. S. Ha, “Analysis of protein interactions on protein arrays by a novel spectral surface plasmon resonance imaging,” Biosens. Bioelectron. 21(8), 1521–1528 (2006). [CrossRef] [PubMed]

17.

J. S. Yuk, J. W. Jung, Y. M. Kim, and K. S. Ha, “Analysis of protein arrays with a dual-function SPR biosensor composed of surface plasmon microscopy and SPR spectroscopy based on white light,” Sens. Actuators B Chem. 129(1), 113–119 (2008). [CrossRef]

18.

J. S. Yuk, D. G. Hong, H. I. Jung, and K. S. Ha, “Application of spectral SPR imaging for the surface analysis of C-reactive protein binding,” Sens. Actuators B Chem. 119(2), 673–675 (2006). [CrossRef]

19.

J. S. Yuk, M. J. Lee, U. R. Kim, and K. S. Ha, “Analysis of blood proteins on protein arrays with a spectral surface plasmon resonance biosensor,” Curr. Appl. Phys. 7(1), 102–107 (2007). [CrossRef]

20.

J. S. Yuk, J. W. Jung, S. H. Jung, J. A. Han, Y. M. Kim, and K. S. Ha, “Sensitivity of ex situ and in situ spectral surface plasmon resonance sensors in the analysis of protein arrays,” Biosens. Bioelectron. 20(11), 2189–2196 (2005). [CrossRef] [PubMed]

21.

J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem. 131(1), 241–246 (2008). [CrossRef]

22.

H. P. Ho, C. L. Wong, K. S. Chan, S. Y. Wu, and C. Lin, “Application of two-dimensional spectral surface plasmon resonance to imaging of pressure distribution in elastohydrodynamic lubricant films,” Appl. Opt. 45(23), 5819–5826 (2006). [CrossRef] [PubMed]

23.

C. L. Wong, H. P. Ho, K. S. Chan, P. L. Wong, S. Y. Wu, F. Guo, and C. Lin, “Application of 2-D spectral surface plasmon resonance imaging to studying elastohydrodynamic lubricant (EHL) films,” Tribol. Int. 41(5), 356–366 (2008). [CrossRef]

24.

C. L. Wong, H. P. Ho, K. S. Chan, and S. Y. Wu, “Application of surface plasmon resonance sensing to studying elastohydrodynamic lubricant films,” Appl. Opt. 44(23), 4830–4837 (2005). [CrossRef] [PubMed]

25.

A. Otto, “Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection,” Z. Phys. 216(4), 398–410 (1968). [CrossRef]

26.

E. Kretschmann, “The determination of the optical constants of metals by the excitation of surface plasmons,” Z. Phys. 241, 313 (1974).

27.

C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.

28.

S. G. Nelson, K. S. Johnston, and S. S. Yee, “High sensitivity surface plasmon resonance sensor based on phase detection,” Sens. Actuators B Chem. 35(1-3), 187–191 (1996). [CrossRef]

29.

P. Yeh, Optical waves in layered media, (Wiley, 1988).

30.

S. Y. Wu, H. P. Ho, W. C. Law, C. Lin, and S. K. Kong, “Highly sensitive differential phase-sensitive surface plasmon resonance biosensor based on the Mach-Zehnder configuration,” Opt. Lett. 29(20), 2378–2380 (2004). [CrossRef] [PubMed]

31.

H. Eugene, Optics, 4th ed. (Addison-Wesley Publishing Company, 2001).

32.

J. Homola and S. S. Yee, “Novel polarization control scheme for spectral surface plasmon resonance sensors,” Sens. Actuators B Chem. 51(1–3), 331–339 (1998). [CrossRef]

33.

D. R. Lide, Handbook of Chemistry and Physics, 82nd ed. (CRC Press, 2001).

34.

F. van der Heijden, Image Based Measurement System (John Wiley & Sons, 1994).

35.

T. Bose, Digital Signal and Image Processing (Wiley, 2004).

36.

A. R. Smith, “Color gamut transform pairs,” Comput. Graph. 12(3), 12–19 (1978). [CrossRef]

37.

C. L. Wong, H. P. Ho, K. S. Chan, S. Y. Wu, and C. Lin, “Application of spectral surface plasmon resonance to gas pressure sensing,” Opt. Eng. 44(12), 124403 (2005). [CrossRef]

38.

K. H. Lee, Y. D. Su, S. J. Chen, F. G. Tseng, and G. B. Lee, “Microfluidic systems integrated with two-dimensional surface plasmon resonance phase imaging systems for microarray immunoassay,” Biosens. Bioelectron. 23(4), 466–472 (2007). [CrossRef] [PubMed]

39.

P. I. Nikitin, A. N. Grigorenko, A. A. Beloglazov, M. V. Valeiko, A. I. Savchuk, O. A. Savchuk, G. Steiner, C. Kuhne, A. Huebner, and R. Salzer, “Surface plasmon resonance interferometry for micro-array biosensing,” Sens. Actuators A Phys. 85(1–3), 189–193 (2000). [CrossRef]

40.

H. P. Ho and W. W. Lam, “Application of differential phase measurement technique to surface plasmon resonance sensors,” Sens. Actuators B Chem. 96(3), 554–559 (2003). [CrossRef]

41.

X. Yu, D. Wang, X. Wei, X. Ding, W. Liao, and Z. Xinsheng, “A surface plasmon resonance imaging interferometry for protein micro-array detection,” Sens. Actuators B Chem. 108(1–2), 765–771 (2005). [CrossRef]

OCIS Codes
(120.5050) Instrumentation, measurement, and metrology : Phase measurement
(240.6680) Optics at surfaces : Surface plasmons
(260.5430) Physical optics : Polarization
(300.6490) Spectroscopy : Spectroscopy, surface
(280.4788) Remote sensing and sensors : Optical sensing and sensors

ToC Category:
Sensors

History
Original Manuscript: March 24, 2011
Revised Manuscript: April 25, 2011
Manuscript Accepted: April 25, 2011
Published: September 15, 2011

Virtual Issues
Vol. 6, Iss. 10 Virtual Journal for Biomedical Optics

Citation
Chi Lok Wong, George Chung Kit Chen, Beng Koon Ng, Shuchi Agarwal, Zhiping Lin, Peng Chen, and Ho Pui Ho, "Multiplex spectral surface plasmon resonance imaging (SPRI) sensor based on the polarization control scheme," Opt. Express 19, 18965-18978 (2011)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-19-20-18965


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References

  1. M. Srivastava, O. Eidelman, C. Jozwik, C. Paweletz, W. Huang, P. L. Zeitlin, and H. B. Pollard, “Serum proteomic signature for cystic fibrosis using an antibody microarray platform,” Mol. Genet. Metab.87(4), 303–310 (2006). [CrossRef] [PubMed]
  2. G. Mor, I. Visintin, Y. Lai, H. Zhao, P. Schwartz, T. Rutherford, L. Yue, P. Bray-Ward, and D. C. Ward, “Serum protein markers for early detection of ovarian cancer,” Proc. Natl. Acad. Sci. U.S.A.102(21), 7677–7682 (2005). [CrossRef] [PubMed]
  3. M. A. Reynolds, H. J. Kirchick, J. R. Dahlen, J. M. Anderberg, P. H. McPherson, K. K. Nakamura, D. T. Laskowitz, G. E. Valkirs, and K. F. Buechler, “Early biomarkers of stroke,” Clin. Chem.49(10), 1733–1739 (2003). [CrossRef] [PubMed]
  4. P. Angenendt, “Progress in protein and antibody microarray technology,” Drug Discov. Today10(7), 503–511 (2005). [CrossRef] [PubMed]
  5. B. B. Haab, “Methods and applications of antibody microarrays in cancer research,” Proteomics3(11), 2116–2122 (2003). [CrossRef] [PubMed]
  6. R. P. Huang, R. Huang, Y. Fan, and Y. Lin, “Simultaneous detection of multiple cytokines from conditioned media and patient’s sera by an antibody-based protein array system,” Anal. Biochem.294(1), 55–62 (2001). [CrossRef] [PubMed]
  7. G. MacBeath and S. L. Schreiber, “Printing proteins as microarrays for high-throughput function determination,” Science289(5485), 1760–1763 (2000). [PubMed]
  8. T. O. Joos, M. Schrenk, P. Höpfl, K. Kröger, U. Chowdhury, D. Stoll, D. Schörner, M. Dürr, K. Herick, S. Rupp, K. Sohn, and H. Hämmerle, “A microarray enzyme-linked immunosorbent assay for autoimmune diagnostics,” Electrophoresis21(13), 2641–2650 (2000). [CrossRef] [PubMed]
  9. H. Ge, “UPA, a universal protein array system for quantitative detection of protein-protein, protein-DNA, protein-RNA and protein-ligand interactions,” Nucleic Acids Res.28(2), 3e (2000). [CrossRef] [PubMed]
  10. C. L. Wong, H. P. Ho, T. T. Yu, Y. K. Suen, W. W. Y. Chow, S. Y. Wu, W. C. Law, W. Yuan, W. J. Li, S. K. Kong, and C. Lin, “Two-dimensional biosensor arrays based on surface plasmon resonance phase imaging,” Appl. Opt.46(12), 2325–2332 (2007). [CrossRef] [PubMed]
  11. C. L. Wong, H. P. Ho, Y. K. Suen, S. K. Kong, Q. L. Chen, W. Yuan, and S. Y. Wu, “Real-time protein biosensor arrays based on surface plasmon resonance differential phase imaging,” Biosens. Bioelectron.24(4), 606–612 (2008). [CrossRef] [PubMed]
  12. J. Homola, S. S. Yee, and G. Gauglitz, “Surface plasmon resonance sensors: review,” Sens. Actuators B Chem.54(1-2), 3–15 (1999). [CrossRef]
  13. J. Homola, Surface Plasmon Resonance Based Sensors (Springer-Verlag, 2006).
  14. J. Homola, H. Vaisocherová, J. Dostálek, and M. Piliarik, “Multi-analyte surface plasmon resonance biosensing,” Methods37(1), 26–36 (2005). [CrossRef] [PubMed]
  15. J. S. Yuk, S. J. Yi, H. G. Lee, H. J. Lee, Y. M. Kim, and K. S. Ha, “Characterization of surface plasmon resonance wavelength by changes of protein concentration on protein chips,” Sens. Actuators B Chem.94(2), 161–164 (2003). [CrossRef]
  16. J. S. Yuk, H. S. Kim, J. W. Jung, S. H. Jung, S. J. Lee, W. J. Kim, J. A. Han, Y. M. Kim, and K. S. Ha, “Analysis of protein interactions on protein arrays by a novel spectral surface plasmon resonance imaging,” Biosens. Bioelectron.21(8), 1521–1528 (2006). [CrossRef] [PubMed]
  17. J. S. Yuk, J. W. Jung, Y. M. Kim, and K. S. Ha, “Analysis of protein arrays with a dual-function SPR biosensor composed of surface plasmon microscopy and SPR spectroscopy based on white light,” Sens. Actuators B Chem.129(1), 113–119 (2008). [CrossRef]
  18. J. S. Yuk, D. G. Hong, H. I. Jung, and K. S. Ha, “Application of spectral SPR imaging for the surface analysis of C-reactive protein binding,” Sens. Actuators B Chem.119(2), 673–675 (2006). [CrossRef]
  19. J. S. Yuk, M. J. Lee, U. R. Kim, and K. S. Ha, “Analysis of blood proteins on protein arrays with a spectral surface plasmon resonance biosensor,” Curr. Appl. Phys.7(1), 102–107 (2007). [CrossRef]
  20. J. S. Yuk, J. W. Jung, S. H. Jung, J. A. Han, Y. M. Kim, and K. S. Ha, “Sensitivity of ex situ and in situ spectral surface plasmon resonance sensors in the analysis of protein arrays,” Biosens. Bioelectron.20(11), 2189–2196 (2005). [CrossRef] [PubMed]
  21. J. S. Yuk, J. W. Jung, J. Hyun, Y. M. Kim, and K. S. Ha, “Development of a scanning surface plasmon microscope based on white light for analysis of a wide range of protein arrays,” Sens. Actuators B Chem.131(1), 241–246 (2008). [CrossRef]
  22. H. P. Ho, C. L. Wong, K. S. Chan, S. Y. Wu, and C. Lin, “Application of two-dimensional spectral surface plasmon resonance to imaging of pressure distribution in elastohydrodynamic lubricant films,” Appl. Opt.45(23), 5819–5826 (2006). [CrossRef] [PubMed]
  23. C. L. Wong, H. P. Ho, K. S. Chan, P. L. Wong, S. Y. Wu, F. Guo, and C. Lin, “Application of 2-D spectral surface plasmon resonance imaging to studying elastohydrodynamic lubricant (EHL) films,” Tribol. Int.41(5), 356–366 (2008). [CrossRef]
  24. C. L. Wong, H. P. Ho, K. S. Chan, and S. Y. Wu, “Application of surface plasmon resonance sensing to studying elastohydrodynamic lubricant films,” Appl. Opt.44(23), 4830–4837 (2005). [CrossRef] [PubMed]
  25. A. Otto, “Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection,” Z. Phys.216(4), 398–410 (1968). [CrossRef]
  26. E. Kretschmann, “The determination of the optical constants of metals by the excitation of surface plasmons,” Z. Phys.241, 313 (1974).
  27. C. L. Wong, Imaging surface plasmon resonance (SPR) photonic sensors, Thesis (Ph.D.), The City University of Hong Kong, 2007.
  28. S. G. Nelson, K. S. Johnston, and S. S. Yee, “High sensitivity surface plasmon resonance sensor based on phase detection,” Sens. Actuators B Chem.35(1-3), 187–191 (1996). [CrossRef]
  29. P. Yeh, Optical waves in layered media, (Wiley, 1988).
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