Chip-based digital surface plasmon resonance sensing platform for ultrasensitive biomolecular detection

Biomimetic affinity sensor for the ultrasensitive detection of neonicotinoids

Multiple pesticides are often used in combination to protect crops from pests. This makes rapid on-site detection of pesticide contamination challenging. Herein, we describe a method for simultaneous detection of diverse neonicotinoid pesticides using a sensor that combines neonicotinoid-specific odorant-binding protein 2 (OBP2), which was cloned from an insect chemical sensing protein and modified gold nanoparticles with local surface plasmon resonance (LSPR)-based digital nanoplasmonometry (DiNM). When neonicotinoid pesticides bind to OBP2 on gold nanoparticles, the induced LSPR shift peak wavelength is too small to be measured using conventional LSPR immunoassays. DiNM records and compares the scattered image intensity in two adjacent wavelength bands, A and B, centered on the LSPR peak. It considers both the peak shift and the relative intensity change in these two bands, resulting in a significant LSPR signal enhancement. Then the spectral-image contrast was computed as the signal response. Using this approach, we obtained excellent limits of detection (LODs) of 1.4, 1.5, and 4.5 ppb for the neonicotinoids imidacloprid, acetamiprid, and dinotefuran, respectively. Blind tests demonstrated high positive and negative rates for teas, approximately 85 and 100%, respectively. Recombinant OBP2 produced in E. coli offers several advantages over antibodies, including high yield, time savings, and cost effectiveness. Moreover, this method is highly selective and sensitive to neonicotinoids, making it practical for field use.

Direct and Sensitive Detection of Dopamine Using Carbon Quantum Dots Based Refractive Index Surface Plasmon Resonance Sensor

Abnormality of dopamine (DA), a vital neurotransmitter in the brain’s neuronal pathways, causes several neurological diseases. Rapid and sensitive sensors for DA detection are required for early diagnosis of such disorders. Herein, a carbon quantum dot (CQD)-based refractive index surface plasmon resonance (SPR) sensor was designed. The sensor performance was evaluated for various concentrations of DA. Increasing DA levels yielded blue-shifted SPR dips. The experimental findings revealed an excellent sensitivity response of 0.138°/pM in a linear range from 0.001 to 100 pM and a high binding affinity of 6.234 TM⁻¹. The effects of varied concentrations of DA on the optical characteristics of CQD thin film were further proved theoretically. Increased DA levels decreased the thickness and real part of the refractive index of CQD film, according to fitting results. Furthermore, the observed reduction in surface roughness using AFM demonstrated that DA was bound to the sensor layer. This, in turn, explained the blue shift in SPR reflectance curves. This optical sensor offers great potential as a trustworthy solution for direct measurement due to its simple construction, high sensitivity, and other sensing features.

Towards a protein-selective Raman enhancement by a glycopolymer-based composite surface

Surface-enhanced Raman scattering (SERS), which is based on the surface plasmon resonance (LSPR) of noble metal nanostructures, is widely used in the biological field due to its advantages of non-damaging samples and detection up to the molecular level. For biological SERS detection, preparation of substrates with biocompatibility and specific adsorption, leading to selective enhancement of the target biomolecules, are important design strategies. Utilizing the specific interaction between a carbohydrate and protein, a glycopolymer-based composite surface is fabricated to realize specific SERS detection of proteins. Herein, we use N-3,4-dihydroxybenzeneethyl methacrylamide (DMA), 2-deoxy-2-(methacrylamido)glucopyranose (MAG) and methacrylic acid (MAA) as monomers in a sunlight-induced RAFT polymerization to synthesize a dopamine-containing glycopolymer. The glycopolymers are used to prepare a SERS substrate. The composite surface shows specific protein adsorption capacity, and the selective Raman enhancement of specific proteins was successfully achieved between the two different proteins Con A and BSA. This provides a feasible approach to design a SERS surface for protein detection and the study of the interaction between sugar and proteins.

Spectral image contrast-based flow digital nanoplasmon-metry for ultrasensitive antibody detection

Background

Gold nanoparticles (AuNPs) have been widely used in local surface plasmon resonance (LSPR) immunoassays for biomolecule sensing, which is primarily based on two conventional methods: absorption spectra analysis and colorimetry. The low figure of merit (FoM) of the LSPR and high-concentration AuNP requirement restrict their limit of detection (LOD), which is approximately ng to μg mL⁻¹ in antibody detection if there is no other signal or analyte amplification. Improvements in sensitivity have been slow in recent for a long time, and pushing the boundary of the current LOD is a great challenge of current LSPR immunoassays in biosensing.

Results

In this work, we developed spectral image contrast-based flow digital nanoplasmon-metry (Flow DiNM) to push the LOD boundary. Comparing the scattering image brightness of AuNPs in two neighboring wavelength bands near the LSPR peak, the peak shift signal is strongly amplified and quickly detected. Introducing digital analysis, the Flow DiNM provides an ultrahigh signal-to-noise ratio and has a lower sample volume requirement. Compared to the conventional analog LSPR immunoassay, Flow DiNM for anti-BSA detection in pure samples has an LOD as low as 1 pg mL⁻¹ within only a 15-min detection time and 500 μL sample volume. Antibody assays against spike proteins of SARS-CoV-2 in artificial saliva that contained various proteins were also conducted to validate the detection of Flow DiNM in complicated samples. Flow DiNM shows significant discrimination in detection with an LOD of 10 pg mL⁻¹ and a broad dynamic detection range of five orders of magnitude.

Conclusion

Together with the quick readout time and simple operation, this work clearly demonstrated the high sensitivity and selectivity of the developed Flow DiNM in rapid antibody detection. Spectral image contrast and digital analysis further provide a new generation of LSPR immunoassay with AuNPs.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-01188-6.

Plasmonic nanobiosensor based on Au nanorods with improved sensitivity: A comparative study for two different configurations

Biosensors presenting high sensitivity for the detection of biomolecules are very promising for diseases diagnosis. Nowadays, there is a need for the development of biosensors with fast, trustworthy diagnosis and mostly with low cost, mainly for applications in developing countries. Label-free plasmonic biosensors are good candidates to reach out all these characteristics due to the possibility of spectral tunability, fast sensor response, real-time detection, strong enhancement of the local electric field and excellent adaptability to assemble different nanobiotechnology architectures. In this paper, two different configurations for LSPR based biosensor were developed by using solution-phase gold nanorods (S-P-AuNRs) and AuNRs-chip. The LSPR sensitivities were evaluated by monitoring shifts in the longitudinal plasmon band with changes in the refractive index of the medium surrounding the nanoparticles. AuNRs-chip presented higher sensitivity of 297 nm RIU^-1 (refractive index unit) against 196 nm RIU^-1 for S-P-AuNRs. Figure of merit (FOM) for AuNRs-chip and S-P-AuNRs were 3.0 and 2.2 RIU^-1, respectively. This result was assigned to the coupling of the lower energy longitudinal LSPR mode of propagation for AuNRs-chip among nearby nanoparticles in the film. In addition, an improvement of at least 18% in sensitivity was obtained comparing to others AuNRs based assay with similar aspect ratio. FOM is more appropriate to compare different approaches, in this case, the proposed biosensor reached improvements of at least 114%, presenting higher values even when compared to AuNRs of higher aspect ratio. As a proof of concept, AuNRs surface was chemically modified using mercaptoundecanoic acid followed activation with ethylcarbodiimide and N-hidroxysuccinimide to allow the interaction between Bovine Serum Albumin (BSA) antibody and correspondent antigen. Both configurations studied resulted in efficient plasmonic biosensors, presenting high sensitivity for changes in the refractive index and for surface binding with anti-BSA.

Surface plasmon resonance biosensor based on graphene and grating excitation

A surface plasmon resonance biosensor based on a graphene-decorated grating excitation structure is proposed in this paper. The biosensor consists of a three-layer structure, including a graphene layer, a grating layer, and a high refractive index layer. The material of the grating layer is silica. The graphene is physically deposited on the grating ridges. An incident light with transverse magnetic polarization is used to excite surface plasmons in the mid-infrared spectral region, which is highly localized at both ends of the graphene layer. The property of the sensor is improved by the high refractive index dielectric layer, which enhances the absorption of incident light and increases the depth of the spectra. The finite-difference time-domain method is used to simulate the property of the sensor. The structure of the sensor could be optimized by changing the structural parameters and comparing the simulation results. The effective refractive index (RI) on the surface and the wavelength of the reflective resonance absorption peak will be changed when the surface of graphene adsorbs the surrounding analyte. The results show that the relationship between the analyte RI and the resonance wavelength is linear. The measurement range of analyte RI is 1-1.8, and the sensitivity is 2780 nm/RIU.

Advances in human chorionic gonadotropin detection technologies: a review

Human chorionic gonadotropin (HCG) is a glycoprotein secreted by placental trophoblast cells in pregnancy. HCG is a heterodimer composed of two different α- and β-subunits, with the latter being unique to HCG. As well as being the most important diagnostic markers for pregnancy, HCG is also a tumor marker, therefore, quantitative detection of HCG is of great value. Numerous advanced technologies have been developed for HCG concentration detection including electrochemical immunoassay, chemiluminescent immunoassay, fluorescence immunoassay, resonance scattering spectrometry, atomic emission spectrometry, radioimmunoassay, MS and so on. Some have pursued simple and easy operation, while others have emphasized on accuracy and applications in clinical medicine. This review provides a comprehensive summary of various methods of detecting HCG.