Coffee Ring Effect Enhanced Surface Plasmon Resonance Imaging Biosensor via 2-λ Fitting Detection Method

Abstract

SPR biosensors have been extensively used for investigating protein-protein interactions. However, in conventional surface plasmon resonance (SPR) biosensors, detection is limited by the Brownian-motion-governed diffusion process of sample molecules in the sensor chip, which makes it challenging to detect biomolecule interactions at ultra-low concentrations. Here, we propose a highly sensitive SPR imaging biosensor which exploits the coffee ring effect (CRE) for in situ enrichment of molecules on the sensing surface. In addition, we designed a wavelength modulation system utilizing two LEDs to reduce the system cost and enhance the detection speed. Furthermore, a detection limit of 213 fM is achieved, which amounts to an approximately 365 times improvement compared to traditional SPR biosensors. With further development, we believe that this SPR imaging system with high sensitivity, less sample consumption, and faster detection speed can be readily applied to ultra-low-concentration molecular detection and interaction analysis.

Keywords: biophotonics and plasmonics; biosensing and bioimaging; coffee ring effect; surface plasmon resonance.

Figure 1

The 2−λ fitting method description and error analysis: (a) the 3D plot of the change of $∆I$ with the W and RW; $∆I$ = 0.001473 a.u. is the minimum value when the RW = 632.4 nm and W = 45.5; (b) the SPR spectral curve via the 2−λ algorithm and real spectrum with different RI; (c) the RW via the 2−λ algorithm and the real RW with RI; (d) comparison of linear fitting between the RW via the 2−λ algorithm and the real RW in the applicable RW range.

Figure 2

The WSPRi system: (a) schematic diagram of system optical path (L1–7: lens; P1–2: polarizer; DA: diaphragm aperture); (b) working sequence diagram of LED and camera in the system.

Figure 3

The RW varies with different concentrations of saline; the inset fig. is the change in the RW caused by low-concentration NaCl solution.

Figure 4

Dynamic monitoring of the near-field ion concentration distribution during the evaporation of the droplet: (a) real-time response curves for center and edge positions of brine and pure water during evaporation; (b,c) the change in RW images by false color at different times.

Figure 5

Detection of RW at 7.5 min and after PBS drop.

Figure 6

RW imaging results under different conditions: (a) goat-anti-human IgG with 500 ng/mL liquid to be tested; (b) the liquid to be tested is PBS; (c) anti-mouse IgG (H + L) with 500 ng/mL liquid to be tested.

Figure 7

Calibration plot corresponding to the shift in RW with respect to IgG concentration, the black curve represents the RW signal corresponding to different concentrations of IgG (2.5, 5, 7.5, 10, 20, 50, 100, and 200 ng/mL), and the red curve represents a linear fitting curve within the range of 2.5 ng/mL to 50 ng/mL.