Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 4082 2023-06-07 06:47:54 |
2 format correct Meta information modification 4082 2023-06-07 08:42:35 | |
3 format correct -2 word(s) 4080 2023-06-09 09:58:38 |

Video Upload Options

Do you have a full video?


Are you sure to Delete?
If you have any further questions, please contact Encyclopedia Editorial Office.
Seymour, E.; Ekiz Kanik, F.; Diken Gür, S.; Bakhshpour-Yucel, M.; Araz, A.; Lortlar Ünlü, N.; Ünlü, M.S. Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection. Encyclopedia. Available online: (accessed on 17 April 2024).
Seymour E, Ekiz Kanik F, Diken Gür S, Bakhshpour-Yucel M, Araz A, Lortlar Ünlü N, et al. Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection. Encyclopedia. Available at: Accessed April 17, 2024.
Seymour, Elif, Fulya Ekiz Kanik, Sinem Diken Gür, Monireh Bakhshpour-Yucel, Ali Araz, Nese Lortlar Ünlü, M. Selim Ünlü. "Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection" Encyclopedia, (accessed April 17, 2024).
Seymour, E., Ekiz Kanik, F., Diken Gür, S., Bakhshpour-Yucel, M., Araz, A., Lortlar Ünlü, N., & Ünlü, M.S. (2023, June 07). Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection. In Encyclopedia.
Seymour, Elif, et al. "Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection." Encyclopedia. Web. 07 June, 2023.
Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection

Optical biosensors measure the optical signals as the changes in the optical properties and characteristics on the transducer surface in the case of an interaction of the immobilized biorecognition element with the measured substance. Optical biosensors can use different types of biorecognition elements such as antibodies, aptamers, peptides, nucleic acids, peptide nucleic acids, proteins, enzymes, or whole cells on the transducer surface, which is designed to bind with the target substance specifically.

solid-phase optical biosensors virus diagnostics fluorescence-based sensors surface plasmon resonance optical resonators

1. Fluorescence-Based Optical Sensors for Virus Detection

Fluorescence-based optical biosensors employ fluorescent labels to produce the optical signal, which results from the binding of the labeled detection molecule to the capture probe and analyte complex on the transducer [1][2][3]. They are widely used in assay development owing to numerous commercially available fluorescent labels, uncomplicated labeling methods, multi-color fluorophores for multiplexed assays, fast response times with localized fluorescence signal, high temporal resolution, and sufficient detection sensitivity [4]. These advantages of fluorescence optical biosensors are desirable for the detection of viruses and biological molecules [5][6][7][8]. However, certain limitations such as fluorophore blinking, photobleaching, and insufficient detection limits for some target molecules make fluorescence-based optical biosensors less applicable in certain applications, for instance, in the detection of low-abundance nucleic acids [9]. Moreover, nonspecific binding of the fluorescent labels to other components in the sample media remains an issue in fluorescence detection systems [10]. Additionally, irreversible photobleaching of the fluorescent label restrains the observation time, hence affecting the reliability of the test [11].
Fluorescence-based optical biosensor technologies are commonly compared with ELISA due to the similarities in the detection method, application, the use of common fluorescence labels, and ELISA’s widespread use and reliability. ELISA requires a laboratory environment, an intricate process, sophisticated equipment, and trained personnel, making it a less-ideal choice for low-resource settings [12][13]. On the other hand, fluorescence-based optical sensors stand out by offering point-of-care (POC) testing and cost-effectiveness. With the advances in technology, smartphones have become more integrated into the recent designs of fluorescence-based POC optical biosensor platforms. Smartphones can be used to visualize labeled viruses and fluorescent nanoparticles by incorporating them into POC devices. Biosensors using smartphones for monitoring either take advantage of the phone’s built-in sensors, such as the camera, magnetic sensor, and ambient-light sensor, or use external sensor modules connected via wired or wireless connections to the integrated diagnostic system. Smartphone-based virus-detection systems are not as sensitive as gold-standard diagnostic methods. However, these systems are portable and scalable, and therefore, they have good prospects for the development of an accessible POC for viral disease surveillance and management [14].

2. Colorimetric Biosensors for Virus Detection

Colorimetry-based biosensors allow visual detection via a change in color detected with the naked eye or simple, low-cost, and portable optical detectors. These features make them proper candidates to fabricate POC devices that can be used for rapid and cost-effective virus detection [15]. They employ a simple platform with a quick response and fair sensitivity and selectivity [16]. In colorimetry-based solid-phase biosensors, on the sensor surface, which is usually a simple test strip, when the sample solution is introduced, a ligand–target complex is formed on the solid support. This complex results in a shift in color that can be easily observed for quantitative measurements. With the recent advancements in nanotechnology, the sensitivity of colorimetric detection systems has been improved by using various functional nanomaterials such as metal and metal oxide NPs, quantum dots, graphene, and derivatives [17]. In the NP-based approach, colloidal NPs that change color during aggregation or dispersion are conjugated with the biosensing element. Plasmonic-based colorimetric biosensors benefit from the localized surface plasmon resonance (LSPR) extinction coefficient in the visible range of noble metal NPs such as gold NPs (AuNPs). Binding events between the analyte and the AuNP-conjugated bioreceptor cause visible color change to show the presence of the virus [18]. NP-based colorimetric sensors can be used in a wide range of virus sensing applications. Khoris and coworkers designed an immunoassay-based sensing technique that detected hepatitis E virus (HEV) in real-time using Ag-decorated AuNPs. Anti-HEV IgG antibodies were conjugated to AuNPs and in situ silver deposition was achieved on the surface of antibody–AuNP conjugates as a signal-amplification strategy. The virus particles were entrapped by the utilized nanocomposites whereas 3,3′,5,5′-tetramethylbenzidine (TMB) and H2O2 were added to decompose back the Ag shell to Ag+. After the addition of TMB-H2O2, based on the obvious color change, the concentration of HEV was quantified and real-time monitoring of HEV in a real sample was realized [19].
Paper-based lateral flow immunoassays (LFIAs) as POC devices are widely used for early disease diagnostics. Despite their widespread use, they are often limited due to insufficient sensitivity for the required sample sizes and short time frames of testing. Loynachan et al. designed a highly sensitive, serum-stable, paper-based, and nanoparticle catalyst-labeled LFIA for the detection of a viral capsid protein, p24, one of the earliest and most conserved biomarkers of HIV. They used porous platinum core-shell nanocatalysts (PtNCs), and then explored the application of antibody-functionalized PtNCs with high-affinity and -specificity modified nanobodies toward p24. They established the key larger-nanoparticle-size regimes needed for efficient amplification and performance in LFIA [20].

3. Virus Detection with Surface Plasmon Resonance and Localized Surface Plasmon Resonance

Surface plasmon resonance (SPR) is defined as an electromagnetic (EM) phenomenon depending on the collective resonant oscillations of free electrons and incoming protons passing through a metal-dielectric interface. The working principles of SPR-based optical sensors depend on the detection of changes in the refractive index that arise on the dielectric surface near the metal layer [21][22]. The properties of this metal layer strongly influence the SPR response that is generated according to the refractive index change. The metals that have conduction-band electrons, such as gold, silver, aluminum, and copper, show the ability to resonate at an appropriate wavelength with the incident light. Gold is the most preferred metal film due to its chemical stability and sensitivity for sensing applications [23]. A typical SPR-based sensor consists of three main components: (i) the immobilized recognition element, (ii) the prism of light, and (iii) the analyte [24]. The recognition molecule is immobilized onto the gold surface of the sensor chip. After surface functionalization, a sample solution containing the analyte is passed across the chip surface. The incident light passing through the prism excites the electrons of the metal film to form a surface plasmon. As the incident light reaches the medium at various angles, the photons are absorbed by the plasmon wave at a specific angle, the critical angle, which is affected by the refractive index of the medium. When an analyte binds to the immobilized recognition element, due to the mass accumulation on the immobilized layer, the refractive index of the medium near the chip surface changes, which shifts the critical angle for the immobilized molecule [25][26][27]. Thus, any physical change that causes a refractive index change can be monitored without labeling in real time. SPR-based sensing techniques offer good potential for rapid and POC detection of viruses due to their sensitive and label-free detection mechanisms. Antibodies against viral antigens are used as bio-receptors to capture viral proteins and intact viruses on the sensor chip surface. Additionally, artificial recognition sites obtained using molecular imprinting or laboratory-made capture molecules, such as DNA and RNA aptamers, are used to capture several viruses [28]. SPR sensing technology, which is highly accurate in detecting biomolecular interactions, also offers various advantages such as label-free monitoring, rapid and sensitive detection, and the ability to miniaturize for on-site monitoring [29]. However, to succeed in the early diagnosis of viruses using the SPR method, further enhancements in the selectivity and sensitivity are still required [28]. Here, different SPR-based techniques that can detect viruses are discussed.
The receptor–analyte interaction occurring on the surface of plasmonic biosensors is also monitored using localized surface plasmon resonance (LSPR). Unlike SPR, LSPR is formed by a light wave absorbed within conductive nano-plasmonic materials that are smaller than the wavelength of the incident light [18]. Owing to the enhanced signal amplification achieved by nanomaterials that have specific optical, electrical, and magnetic features, a low limit of detection can be obtained. While the incident light interacts with the metallic nanoparticles (NPs) of the surface, a strong localized EM field generated around these nanostructures enables a strong peak in the course of the absorption spectrum collection at the resonance [30]. The height of the LSPR peak and the corresponding wavelength are affected by not only the sensing medium but also the material type, size, and shape of the plasmonic NPs. The utilization of the nanoparticles for the decoration of the chip surface also provides a large surface area to immobilize a high number of bioreceptor molecules, increasing the sensitivity and specificity of the sensing technique. Several metallic nanostructures, such as nanospheres, nanofibers, nanorods, nanoshells, and nanowires, can be used to fabricate sensing surfaces [31]. The dimensions and the shape of these nanostructures directly affect their plasmonic properties (scattering and absorption ratio, resonance wavelength) [32]. Two main drawbacks of SPR are circumvented with LSPR: first, temperature sensitivity is not an issue for LSPR since the method depends on a simple absorbance measurement; second, less time is required for the whole binding assay due to the faster spread of the analyte to the increased surface area of the NPs compared with a metallic film [33][34]. On the other hand, the response generated by non-specific binding during the analyte incubation and the refractive index variation is the major drawback of LSPR, limiting the applicability and effectiveness of the sensor, especially for the detection from complex samples [35]. Over the last decade, there was a significant increase in the number of nanomaterial-based sensing techniques developed for viral diagnosis.

4. Virus Detection with Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS)-based sensing platforms rely on the amplification of the Raman response of an analyte molecule absorbed on the nanostructured noble metal substrate. The generation of a new complex between the analyte and metal surface causes modification of the adsorbate polarizability and EM enhancement by improving the re-emitted Raman scattering coming from the analyte and local incident field on the analyte [36][37]. SERS-based sensing gained attention over the last few decades due to its advantages: (i) high sensitivity, (ii) capability for multiplex sensing, (iii) applicability as a POC device, and (iv) laborless sample preparation [38]. Although Raman spectroscopy is a useful tool for analyte determination by providing fingerprints such as a spectrum for complex samples, its inherently weak signals limit its use for diagnosis. However, in SERS technology, the limitations of the weak signal of Raman-active material are overcome by enhancing the EM field by using metallic nanostructures. The development of high-sensitivity SERS sensors with an advanced EM field is carried out by optimizing the design of plasmonic nanostructures [30]. The main advantages of SERS technology are the specific analyte determination even at very low concentrations without sample pre-treatment and its applicability as a POC device [39]. On the other hand, the main challenge that limits the reproducibility of the SERS signal is the signal-reducing degradation in the substrate over time due to the requirement for close contact between the analyte and the amplification surface [40]. SERS-based sensors can be classified as direct and indirect. While the direct method relies on the detection of the spectrum of an analyte, in the indirect technique that is constructed in sandwich format, SERS signals are obtained from the reporter molecule, not the analyte. To differentiate the spectral data of an analyte in the direct technique, the main component and linear discriminant analysis must be performed by comparing the samples of patients and healthy individuals [41]. In the indirect technique, the sensitivity of the method is significantly increased at ultra-low concentrations by using an immunoassay format to detect the analyte. In order to meet the growing need for accurate and rapid virus detection, multiplex immunoassay-based SERS has become prominent due to the limitations of PCR-based techniques that depend only on genetic material for testing [42].

5. Optical Resonators for Virus Detection

Optical resonator-based sensor systems have recently attracted significant attention as a powerful tool for detecting a range of biological and chemical analytes with high sensitivity and specificity [43]. These sensors measure the spectral changes in the resonant frequency of an optical cavity when the analyte is introduced into the cavity. The main principle of an optical resonator sensor is based on detecting light-intensity changes induced by changes in the refractive index of the medium surrounding the resonator. The resonator consists of a thin film layer or a ring resonator that supports resonant modes, which are excited by a laser beam. The resonant modes of the resonator are highly sensitive to changes in the refractive index of the surrounding medium. When a target molecule or virus binds to the resonator surface, it causes a change in the refractive index which is detected as a shift in the resonator’s resonant frequency [44].
The basic design of an optical resonator sensor consists of a high-quality factor (Q-factor) resonator, such as a microdisk or microring, and a waveguide coupled to the resonator. The resonator acts as a sensitive transducer capable of detecting changes in the refractive index of the surrounding environment caused by the analyte binding to the resonator’s surface. The change in the resonant frequency is then measured by monitoring the light transmitted through the waveguide. Some of the most common types of optical resonators are Fabry–Perot cavities, whispering gallery mode (WGM) cavities, photonic crystal cavities (PC), and plasmonic resonators [45][46].
For biological particle detection, optical resonators such as microspheres and microtoroids have been used to detect individual virus particles of about 100 nm in a label-free format [47][48]. WGM cavities are highly efficient optical resonators with high Q-factors, allowing for the detection of very small changes in the refractive index of the cavity, and therefore making them useful for various sensing applications. He et al. developed a WGM microresonator using frequency splitting in a microlaser and showed the detection of the influenza A virus on this sensor [49]. Their method relies on measuring the changes in the beat frequency as an ultra-narrow emission line from a WGM microlaser is split into two modes due to nanoparticle binding. Before the nanoparticles arrive, there is a single laser mode with constant laser intensity. The lasing mode splits into two modes when the first nanoparticle binds, generating a beat note with a frequency that is equal to the frequency difference between the two modes. Using this approach, they could detect sizes as small as 15 nm for polystyrene nanoparticles and 10 nm for gold nanoparticles, as well as the influenza A virus. However, this system was tested with purified nanoparticle and virus solutions and has yet to show multiplexed virus detection from complex biological systems.
Optical resonators offer several advantages over traditional optical devices, including high sensitivity, selectivity, and miniaturization. Optical resonators can be designed to have a very high Q-factor, which allows for the efficient coupling between the optical signal and the surrounding environment. However, optical resonators also have some limitations, including sensitivity to temperature and fabrication complexity.

6. Interferometry-Based Sensor Platforms

Viruses are difficult to detect using conventional light microscopy, which mostly relies on measuring the light scattered by the imaged objects. This is due to their small size (typically 20–300 nm in diameter) and low contrast. The light–particle interaction for small-sized particles can be represented by an induced dipole. The strength of an induced dipole is directly proportional to the polarizability of the particle, which can be given as
α = 4 π ε 0 R 3 ε p ε m ε p + 2 ε m
where R is the radius of the particle and εp and εm are the permittivity of the particle and medium, respectively. The optical techniques that detect the scattered light intensity generate a signal proportional to |Es|2, which scales with |α|2; thus, R6. Therefore, the scattering signal recorded at the detector drops below the shot-noise limit for small particles. On the contrary, interferometric imaging utilizes a strong reference beam (Er) that interacts with the weak scattered fields (Es) from the particle and modifies the intensity obtained at the detector as
I E r + E s 2 E r 2 + E s 2 + 2 E r | | E s c o s θ r s
where θrs is the phase angle difference between the reference and scattered fields. As the particle size becomes smaller, the scattered field, the second term in Equation (2), becomes very small compared to the other two terms representing the reference field and the interference signal. Once the reference field is subtracted, the signal recorded at the detector is proportional to the multiplication of the reference and scattered fields, and thus proportional to R3 instead of R6. As a result, interferometric imaging makes it possible to detect smaller particles and a higher dynamic range of particle sizes. Due to these advantages, interferometry has been utilized for both ensemble-based measurements and single-nanoparticle detection in previous studies [50]. One example of ensemble-based measurement techniques is biolayer interferometry (BLI), a label-free, real-time characterization technique for biomolecular interactions [51]. In this technique, a fiber optic biosensor is used to illuminate the sensor area with white light, and the resulting shift in the wavelength of the reflected light is recorded. Although this technique was shown to perform antibody detection with a similar sensitivity to ELISA, there are some disadvantages associated with it, such as the inability to detect single nanoparticles and signal jumps as the new solutions are introduced to the well [52]. Interferometry-based nanoparticle imaging techniques have also been developed for single-virus detection [53][54]. However, these techniques use cost-inefficient lasers as the light source and can be time-consuming due to their small measurement area.

7. Virus Diagnostics Applications of SP-IRIS

SP-IRIS can count and size each nanoparticle bound to capture probes on the sensor surface over a large sensor area, orders of magnitude larger than other virus-imaging techniques such as electron microscopy. It allows for a large range of nanoparticle detection, including natural nanoparticles (e.g., viruses) and synthetic nanoparticles (e.g., gold nanospheres, gold nanorods) in a highly-multiplexed microarray format. So far, SP-IRIS has been shown to detect many different biological targets, such as viruses [55], allergen-specific antibodies [56], extracellular vesicles [57], bacteria [58], and microRNA [59]. When the target is a nanoparticle itself, such as viruses, the detection can be performed directly without using any secondary labels. If the biomolecule being searched for is below the size limit of SP-IRIS (~30 nm), the target binding can be monitored using specific detection probes attached to nanoparticle barcodes such as gold nanoparticles.
To demonstrate the applicability of SP-IRIS to POC diagnostics as a rapid detection method, a disposable passive microfluidic cartridge was designed with a multilayer polymer laminate structure and an integrated absorbent paper to establish capillary flow of the sample in the cartridge. This passive-flow integrated SP-IRIS achieved a better sensitivity than ELISA and a commercial rapid antigen test by detecting 104 PFU/mL rVSV-EBOV in less than 20 min [60][61]. A different study by Daaboul et al. demonstrated the usability of SP-IRIS for the detection and characterization of a variety of virus sizes ranging from 40 nm for the Zika virus to 360 nm for the Vaccinia virus and filamentous virus particles such as the Ebola virus [62]. Recently, Yurdakul et al. showed a different modality of SP-IRIS, referred to as single-particle interferometric microscopy, for obtaining shape and size information that will enable in-depth morphological studies of viruses [63]. Collectively, these studies demonstrated the potential of SP-IRIS as a sensitive, fast, and multiplexed virus-detection platform in a label-free and sample-to-answer format.
Besides the microfluidics integration and improvements in the optical setup of SP-IRIS, sensor-chip surface chemistry was also studied in an effort to increase the sensitivity of detection. By using a technique called DNA-directed antibody immobilization (DDI), Seymour et al. showed that capture antibodies can be elevated over the surface (~14 nm) through the use of DNA linkers attached to the antibodies [64]. This new surface-preparation technique provided a 16-fold increase in sensitivity for rVSV-EBOV detection for a 15 min incubation period. This improvement is most likely due to the increased accessibility of the antibodies for virus binding and increased functionality due to fewer surface attachment points in the antibody structure.
Table 1 presents some examples of viral diagnostics platforms operating with the optical mechanisms reviewed in this work and compares their performances in terms of linear range, LOD, and assay time. With the recent advances in camera and detector development and with the use of smartphones, fluorescence- and colorimetry-based optical bioassays have become a common choice in POC technologies since they provide sufficient sensitivity in virus detection. They provide the users with the advantages an ELISA assay offers, such as a low limit of detection, quantitative measurement, and applicability with various samples. However, some may require a tedious process for sample preparation, and the assay conditions, such as the temperature and pH of the sample, may affect the results. In addition, the labeling process is time-consuming for both techniques and may require complex steps in some applications.
Table 1. Examples of solid-phase optical biosensors using different detection mechanisms, their applications, and assay-performance characteristics.
SPR sensors are commonly reported to have a very high sensitivity and provide simple and real-time detection; however, the bulk effect and low selectivity are the main disadvantages of SPR systems. The main advantages of LSPR systems are ease of operation, fast detection, and insensitivity to the temperature changes, enabling their use in many areas. However, LSPR-based platforms cannot distinguish between different binding events, making them less useful for multiplexed analysis.
The SERS system has gained attention due to its sensitivity, capability for multiplex sensing, and specific analyte determination ability, even at very low concentrations. On the other hand, signal-reducing degradation in the substrate over time due to the requirement for close contact between the analyte and the amplification surface is the main challenge limiting the reproducibility of the SERS signal.
SP-IRIS offers significant advantages compared to the other optical biosensing platforms mentioned here. First, SP-IRIS has a comparable sensitivity to SPR, the most commonly used label-free biosensor, while having a higher multiplexing capability, substantially less-expensive substrates, and a shorter analysis time [83]. Moreover, the detection principle of SP-IRIS is immune to the bulk effect, a major problem of SPR-based systems caused by the changes in the refractive index of the solution. SP-IRIS overcomes any background-related effect by imaging only the nanoparticles bound to the surface. Moreover, unlike optical-resonator-based sensors, the SP-IRIS signal is not affected by environmental factors such as temperature changes or the binding position of the particles on the sensor. Thus, SP-IRIS combines a robust and reliable signal-transduction mechanism with high-sensitivity, high-throughput detection in a cost-effective and easy-to-use platform. The challenges related to the surface probe immobilization and the sensor chip shelf-life were overcome by implementing configurable DNA chips, and the assay procedure was greatly simplified by microfluidic integration. These features make SP-IRIS an ideal candidate for rapid and reliable virus diagnostics, especially for POC applications.


  1. Damborský, P.; Švitel, J.; Katrlík, J. Optical biosensors. Essays Biochem. 2016, 60, 91–100.
  2. Mehrotra, P. Biosensors and their applications—A review. J. Oral Biol. Craniofacial Res. 2016, 6, 153–159.
  3. Celiker, T.; Ghorbanizamani, F.; Moulahoum, H.; Guler Celik, E.; Tok, K.; Zihnioglu, F.; Cicek, C.; Sertoz, R.; Arda, B.; Goksel, T.; et al. Fluorescent bioassay for SARS-CoV-2 detection using polypyrene-g-poly(ε-caprolactone) prepared by simultaneous photoinduced step-growth and ring-opening polymerizations. Microchim. Acta 2022, 189, 202.
  4. Sharma, A.; Mishra, R.K.; Goud, K.Y.; Mohamed, M.A.; Kummari, S.; Tiwari, S.; Li, Z.; Narayan, R.; Stanciu, L.A.; Marty, J.L. Optical biosensors for diagnostics of infectious viral disease: A recent update. Diagnostics 2021, 11, 2083.
  5. Kulzer, F.; Orrit, M. Single-Molecule Optics. Annu. Rev. Phys. Chem. 2004, 55, 585–611.
  6. Shirani, M.; Kalantari, H.; Khodayar, M.J.; Kouchak, M.; Rahbar, N. A novel strategy for detection of small molecules based on aptamer/gold nanoparticles/graphitic carbon nitride nanosheets as fluorescent biosensor. Talanta 2020, 219, 121235.
  7. Salama, A.M.; Yasin, G.; Zourob, M.; Lu, J. Fluorescent Biosensors for the Detection of Viruses Using Graphene and Two-Dimensional Carbon Nanomaterials. Biosensors 2022, 12, 460.
  8. Clegg, R.M. Fluorescence resonance energy transfer. Curr. Opin. Biotechnol. 1995, 6, 103–110.
  9. Maddali, H.; Miles, C.E.; Kohn, J.; O’Carroll, D.M. Optical Biosensors for Virus Detection: Prospects for SARS-CoV-2/COVID-19. ChemBioChem 2021, 22, 1176–1189.
  10. Sharma, A.; Khan, R.; Catanante, G.; Sherazi, T.A.; Bhand, S.; Hayat, A.; Marty, J.L. Designed Strategies for Fluorescence-Based Biosensors for the Detection of Mycotoxins. Toxins 2018, 10, 197.
  11. Ekiz-Kanik, F.; Sevenler, D.D.; Ünlü, N.L.; Chiari, M.; Ünlü, M.S. Surface chemistry and morphology in single particle optical imaging. Nanophotonics 2017, 6, 713–730.
  12. Tai, J.; Fan, S.; Ding, S.; Ren, L. Gold Nanoparticles Based Optical Biosensors for Cancer Biomarker Proteins: A Review of the Current Practices. Front. Bioeng. Biotechnol. 2022, 10, 877193.
  13. Orooji, Y.; Sohrabi, H.; Hemmat, N.; Oroojalian, F.; Baradaran, B.; Mokhtarzadeh, A.; Mohaghegh, M.; Karimi-Maleh, H. An Overview on SARS-CoV-2 (COVID-19) and Other Human Coronaviruses and Their Detection Capability via Amplification Assay, Chemical Sensing, Biosensing, Immunosensing, and Clinical Assays. Nano-Micro Lett. 2021, 13, 18.
  14. Xiao, M.; Tian, F.; Liu, X.; Zhou, Q.; Pan, J.; Luo, Z.; Yang, M.; Yi, C. Virus Detection: From State-of-the-Art Laboratories to Smartphone-Based Point-of-Care Testing. Adv. Sci. 2022, 9, 2105904.
  15. Xu, S.; Ouyang, W.; Xie, P.; Lin, Y.; Qiu, B.; Lin, Z.; Chen, G.; Guo, L. Highly Uniform Gold Nanobipyramids for Ultrasensitive Colorimetric Detection of Influenza Virus. Anal. Chem. 2017, 89, 1617–1623.
  16. Choi, Y.; Hwang, J.H.; Lee, S.Y. Recent Trends in Nanomaterials-Based Colorimetric Detection of Pathogenic Bacteria and Viruses. Small Methods 2018, 2, 1700351.
  17. Wu, Y.; Feng, J.; Hu, G.; Zhang, E.; Yu, H.-H. Colorimetric Sensors for Chemical and Biological Sensing Applications. Sensors 2023, 23, 2749.
  18. Mauriz, E. Recent Progress in Plasmonic Biosensing Schemes for Virus Detection. Sensors 2020, 20, 4745.
  19. Khoris, I.M.; Chowdhury, A.D.; Li, T.-C.; Suzuki, T.; Park, E.Y. Advancement of capture immunoassay for real-time monitoring of hepatitis E virus-infected monkey. Anal. Chim. Acta 2020, 1110, 64–71.
  20. Loynachan, C.N.; Thomas, M.R.; Gray, E.R.; Richards, D.A.; Kim, J.; Miller, B.S.; Brookes, J.C.; Agarwal, S.; Chudasama, V.; McKendry, R.A.; et al. Platinum Nanocatalyst Amplification: Redefining the Gold Standard for Lateral Flow Immunoassays with Ultrabroad Dynamic Range. ACS Nano 2018, 12, 279–288.
  21. Fen, Y.W.; Yunus, W.M.M.; Yusof, N.A.; Ishak, N.S.; Omar, N.A.S.; Zainudin, A.A. Preparation, characterization and optical properties of ionophore doped chitosan biopolymer thin film and its potential application for sensing metal ion. Optik 2015, 126, 4688–4692.
  22. Zainudin, A.A.; Fen, Y.W.; Yusof, N.A.; Omar, N.A.S. Structural, optical and sensing properties of ionophore doped graphene based bionanocomposite thin film. Optik 2017, 144, 308–315.
  23. Omar, N.A.S.; Fen, Y.W. Recent development of SPR spectroscopy as potential method for diagnosis of dengue virus E-protein. Sens. Rev. 2018, 38, 106–116.
  24. Murali, S.; Rustandi, R.R.; Zheng, X.; Payne, A.; Shang, L. Applications of Surface Plasmon Resonance and Biolayer Interferometry for Virus-Ligand Binding. Viruses 2022, 14, 717.
  25. Rasooly, A.; Herold, K.E. Biosensors and Biodetection: Methods and Protocols. In Methods in Molecular Biology; Humana Press: Clifton, NJ, USA, 2009; pp. v–ix.
  26. Caygill, R.L.; Blair, G.E.; Millner, P.A. A review on viral biosensors to detect human pathogens. Anal. Chim. Acta 2010, 681, 8–15.
  27. Zheng, X.; Bi, C.; Li, Z.; Podariu, M.; Hage, D.S. Analytical methods for kinetic studies of biological interactions: A review. J. Pharm. Biomed. Anal. 2015, 113, 163–180.
  28. Hassan, M.M.; Sium, F.S.; Islam, F.; Choudhury, S.M. A review on plasmonic and metamaterial based biosensing platforms for virus detection. Sens. Bio-Sens. Res. 2021, 33, 100429.
  29. Pandey, P.S.; Raghuwanshi, S.K.; Shadab, A.; Ansari, M.T.I.; Tiwari, U.K.; Kumar, S. SPR Based Biosensing Chip for COVID-19 Diagnosis—A Review. IEEE Sens. J. 2022, 22, 13800–13810.
  30. Shrivastav, A.M.; Cvelbar, U.; Abdulhalim, I. A comprehensive review on plasmonic-based biosensors used in viral diagnostics. Commun. Biol. 2021, 4, 70.
  31. Taghipour, A.; Heidarzadeh, H. Design and Analysis of Highly Sensitive LSPR-Based Metal-Insulator-Metal Nano-Discs as a Biosensor for Fast Detection of SARS-CoV-2. Photonics 2022, 9, 542.
  32. Puiu, M.; Bala, C. SPR and SPR Imaging: Recent Trends in Developing Nanodevices for Detection and Real-Time Monitoring of Biomolecular Events. Sensors 2016, 16, 870.
  33. Kabashin, A.V.; Evans, P.; Pastkovsky, S.; Hendren, W.; Wurtz, G.A.; Atkinson, R.; Pollard, R.; Podolskiy, V.A.; Zayats, A.V. Plasmonic nanorod metamaterials for biosensing. Nat. Mater. 2009, 8, 867–871.
  34. Couture, M.; Zhao, S.S.; Masson, J.-F. Modern surface plasmon resonance for bioanalytics and biophysics. Phys. Chem. Chem. Phys. 2013, 15, 11190–11216.
  35. Guo, L.; Jackman, J.A.; Yang, H.-H.; Chen, P.; Cho, N.-J.; Kim, D.-H. Strategies for enhancing the sensitivity of plasmonic nanosensors. Nano Today 2015, 10, 213–239.
  36. Kenworthy, C.F.; Stoevelaar, L.P.; Alexander, A.J.; Gerini, G. Using the near field optical trapping effect of a dielectric metasurface to improve SERS enhancement for virus detection. Sci. Rep. 2021, 11, 6873.
  37. Ali, A.; Nettey-Oppong, E.E.; Effah, E.; Yu, C.Y.; Muhammad, R.; Soomro, T.A.; Byun, K.M.; Choi, S.H. Miniaturized Raman Instruments for SERS-Based Point-of-Care Testing on Respiratory Viruses. Biosensors 2022, 12, 590.
  38. Li, M.; Cushing, S.K.; Wu, N. Plasmon-enhanced optical sensors: A review. Analyst 2015, 140, 386–406.
  39. Xia, J.; Li, W.; Sun, M.; Wang, H. Application of SERS in the Detection of Fungi, Bacteria and Viruses. Nanomaterials 2022, 12, 3572.
  40. Mousavi, S.M.; Hashemi, S.A.; Rahmanian, V.; Kalashgrani, M.Y.; Gholami, A.; Omidifar, N.; Chiang, W.-H. Highly Sensitive Flexible SERS-Based Sensing Platform for Detection of COVID-19. Biosensors 2022, 12, 466.
  41. Ambartsumyan, O.; Gribanyov, D.; Kukushkin, V.; Kopylov, A.; Zavyalova, E. SERS-Based Biosensors for Virus Determination with Oligonucleotides as Recognition Elements. Int. J. Mol. Sci. 2020, 21, 3373.
  42. Saviñon-Flores, F.; Méndez, E.; López-Castaños, M.; Carabarin-Lima, A.; López-Castaños, K.A.; González-Fuentes, M.A.; Méndez-Albores, A. A Review on SERS-Based Detection of Human Virus Infections: Influenza and Coronavirus. Biosensors 2021, 11, 66.
  43. Armani, D.K.; Kippenberg, T.J.; Spillane, S.M.; Vahala, K.J. Ultra-high-Q toroid microcavity on a chip. Nature 2003, 421, 925–928.
  44. Iqbal, M.; Gleeson, M.A.; Spaugh, B.; Tybor, F.; Gunn, W.G.; Hochberg, M.; Baehr-Jones, T.; Bailey, R.C.; Gunn, L.C. Label-free biosensor arrays based on silicon ring resonators and high-speed optical scanning instrumentation. IEEE J. Sel. Top. Quantum Electron. 2010, 16, 654–661.
  45. Baaske, M.; Vollmer, F. Optical resonator biosensors: Molecular diagnostic and nanoparticle detection on an integrated platform. ChemPhysChem 2012, 13, 427–436.
  46. Ahmadi, H.; Heidarzadeh, H.; Taghipour, A.; Rostami, A.; Baghban, H.; Dolatyari, M.; Rostami, G. Evaluation of single virus detection through optical biosensor based on microsphere resonator. Optik 2014, 125, 3599–3602.
  47. Vollmer, F.; Arnold, S.; Keng, D. Single virus detection from the reactive shift of a whispering-gallery mode. Proc. Natl. Acad. Sci. USA 2008, 105, 20701–20704.
  48. Zhu, J.; Özdemir, Ş.K.; He, L.; Chen, D.-R.; Yang, L. Single virus and nanoparticle size spectrometry by whispering-gallery-mode microcavities. Opt. Express 2011, 19, 16195.
  49. He, L.; Özdemir, Ş.K.; Zhu, J.; Kim, W.; Yang, L. Detecting single viruses and nanoparticles using whispering gallery microlasers. Nat. Nanotechnol. 2011, 6, 428–432.
  50. Daaboul, G.G.; Lopez, C.A.; Yurt, A.; Goldberg, B.B.; Connor, J.H.; Ünlü, M.S. Label-free optical biosensors for virus detection and characterization. IEEE J. Sel. Top. Quantum Electron. 2012, 18, 1422–1433.
  51. Kamat, V.; Rafique, A. Designing binding kinetic assay on the bio-layer interferometry (BLI) biosensor to characterize antibody-antigen interactions. Anal. Biochem. 2017, 536, 16–31.
  52. Dzimianski, J.V.; Lorig-Roach, N.; O’Rourke, S.M.; Alexander, D.L.; Kimmey, J.M.; DuBois, R.M. Rapid and sensitive detection of SARS-CoV-2 antibodies by biolayer interferometry. Sci. Rep. 2020, 10, 21738.
  53. Yurt, A.; Daaboul, G.G.; Connor, J.H.; Goldberg, B.B.; Ünlü, M.S. Single nanoparticle detectors for biological applications. Nanoscale 2012, 4, 715–726.
  54. Mitra, A.; Ignatovich, F.; Novotny, L. Real-time optical detection of single human and bacterial viruses based on dark-field interferometry. Biosens. Bioelectron. 2012, 31, 499–504.
  55. Daaboul, G.G.; Lopez, C.A.; Chinnala, J.; Goldberg, B.B.; Connor, J.H.; Ünlü, M.S. Digital sensing and sizing of vesicular stomatitis virus pseudotypes in complex media: A model for ebola and marburg detection. ACS Nano 2014, 8, 6047–6055.
  56. Monroe, M.R.; Daaboul, G.G.; Tuysuzoglu, A.; Lopez, C.A.; Little, F.F.; Ünlü, M.S. Single nanoparticle detection for multiplexed protein diagnostics with attomolar sensitivity in serum and unprocessed whole blood. Anal. Chem. 2013, 85, 3698–3706.
  57. Daaboul, G.G.; Gagni, P.; Benussi, L.; Bettotti, P.; Ciani, M.; Cretich, M.; Freedman, D.S.; Ghidoni, R.; Ozkumur, A.Y.; Piotto, C.; et al. Digital Detection of Exosomes by Interferometric Imaging. Sci. Rep. 2016, 6, 37246.
  58. Zaraee, N.; Kanik, F.E.; Bhuiya, A.M.; Gong, E.S.; Geib, M.T.; Lortlar Ünlü, N.; Ozkumur, A.Y.; Dupuis, J.R.; Ünlü, M.S. Highly sensitive and label-free digital detection of whole cell E. coli with Interferometric Reflectance Imaging. Biosens. Bioelectron. 2020, 162, 112258.
  59. Ekiz Kanik, F.; Celebi, I.; Sevenler, D.; Tanriverdi, K.; Lortlar Ünlü, N.; Freedman, J.E.; Ünlü, M.S. Attomolar sensitivity microRNA detection using real-time digital microarrays. Sci. Rep. 2022, 12, 16220.
  60. Scherr, S.M.; Freedman, D.S.; Agans, K.N.; Rosca, A.; Carter, E.; Kuroda, M.; Fawcett, H.E.; Mire, C.H.; Geisbert, T.W.; Ünlü, M.S.; et al. Disposable cartridge platform for rapid detection of viral hemorrhagic fever viruses. Lab Chip 2017, 17, 917–925.
  61. Seymour, E.; Ünlü, N.L.; Carter, E.P.; Connor, J.H.; Ünlü, M.S. Configurable Digital Virus Counter on Robust Universal DNA Chips. ACS Sens. 2021, 6, 229–237.
  62. Daaboul, G.G.; Freedman, D.S.; Scherr, S.M.; Carter, E.; Rosca, A.; Bernstein, D.; Mire, C.H.; Agans, K.N.; Hoenen, T.; Geisbert, T.W.; et al. Enhanced light microscopy visualization of virus particles from Zika virus to filamentous ebolaviruses. PLoS ONE 2017, 12, e0179728.
  63. Yurdakul, C.; Avci, O.; Matlock, A.; Devaux, A.J.; Quintero, M.V.; Ozbay, E.; Davey, R.A.; Connor, J.H.; Karl, W.C.; Tian, L.; et al. High-Throughput, High-Resolution Interferometric Light Microscopy of Biological Nanoparticles. ACS Nano 2020, 14, 2002–2013.
  64. Seymour, E.; Daaboul, G.G.; Zhang, X.; Scherr, S.M.; Lortlar Ünlü, N.; Connor, J.H.; Ünlü, M.S. DNA-Directed Antibody Immobilization for Enhanced Detection of Single Viral Pathogens. Anal. Chem. 2015, 87, 10505–10512.
  65. Fu, Z.; Zeng, W.; Cai, S.; Li, H.; Ding, J.; Wang, C.; Chen, Y.; Han, N.; Yang, R. Porous nanoparticles with superior peroxidase-like activity for colorimetric detection of spike protein of SARS-CoV-2. J. Colloid Interface Sci. 2021, 604, 113–121.
  66. Wang, C.; Yang, X.; Gu, B.; Liu, H.; Zhou, Z.; Shi, L.; Cheng, X.; Wang, S. Sensitive and Simultaneous Detection of SARS-CoV-2-Specific IgM/IgG Using Lateral Flow Immunoassay Based on Dual-Mode Quantum Dot Nanobeads. Anal. Chem. 2020, 92, 15542–15549.
  67. Han, H.; Wang, C.; Yang, X.; Zheng, S.; Cheng, X.; Liu, Z.; Zhao, B.; Xiao, R. Rapid field determination of SARS-CoV-2 by a colorimetric and fluorescent dual-functional lateral flow immunoassay biosensor. Sens. Actuators B Chem. 2022, 351, 130897.
  68. Kong, M.; Li, Z.; Wu, J.; Hu, J.; Sheng, Y.; Wu, D.; Lin, Y.; Li, M.; Wang, X.; Wang, S. A wearable microfluidic device for rapid detection of HIV-1 DNA using recombinase polymerase amplification. Talanta 2019, 205, 120155.
  69. Xu, L.; Wang, R.; Kelso, L.C.; Ying, Y.; Li, Y. A target-responsive and size-dependent hydrogel aptasensor embedded with QD fluorescent reporters for rapid detection of avian influenza virus H5N1. Sens. Actuators B Chem. 2016, 234, 98–108.
  70. Chang, Y.-F.; Wang, W.-H.; Hong, Y.-W.; Yuan, R.-Y.; Chen, K.-H.; Huang, Y.-W.; Lu, P.-L.; Chen, Y.-H.; Chen, Y.-M.A.; Su, L.-C.; et al. Simple Strategy for Rapid and Sensitive Detection of Avian Influenza a H7N9 Virus Based on Intensity-Modulated SPR Biosensor and New Generated Antibody. Anal. Chem. 2018, 90, 1861–1869.
  71. Yoo, H.; Shin, J.; Sim, J.; Cho, H.; Hong, S. Reusable surface plasmon resonance biosensor chip for the detection of H1N1 influenza virus. Biosens. Bioelectron. 2020, 168, 112561.
  72. Kim, J.; Oh, S.Y.; Shukla, S.; Hong, S.B.; Heo, N.S.; Bajpai, V.K.; Chun, H.S.; Jo, C.-H.; Choi, B.G.; Huh, Y.S.; et al. Heteroassembled gold nanoparticles with sandwich-immunoassay LSPR chip format for rapid and sensitive detection of hepatitis B virus surface antigen (HBsAg). Biosens. Bioelectron. 2018, 107, 118–122.
  73. Park, Y.; Ryu, B.; Ki, S.J.; Chen, M.; Liang, X.; Kurabayashi, K. Bioinspired Plasmo-virus for Point-of-Care SARS-CoV-2 Detection. Nano Lett. 2023, 23, 98–106.
  74. Kim, S.; Lee, S.; Lee, H.J. An aptamer-aptamer sandwich assay with nanorod-enhanced surface plasmon resonance for attomolar concentration of norovirus capsid protein. Sens. Actuators B Chem. 2018, 273, 1029–1036.
  75. Liu, H.; Dai, E.; Xiao, R.; Zhou, Z.; Zhang, M.; Bai, Z.; Shao, Y.; Qi, K.; Tu, J.; Wang, C.; et al. Development of a SERS-based lateral flow immunoassay for rapid and ultra-sensitive detection of anti-SARS-CoV-2 IgM/IgG in clinical samples. Sens. Actuators. B. Chem. 2021, 329, 129196.
  76. Zhang, Z.; Li, D.; Wang, X.; Wang, Y.; Lin, J.; Jiang, S.; Wu, Z.; He, Y.; Gao, X.; Zhu, Z.; et al. Rapid detection of viruses: Based on silver nanoparticles modified with bromine ions and acetonitrile. Chem. Eng. J. 2022, 438, 135589.
  77. Wang, X.; Li, S.; Qu, H.; Hao, L.; Shao, T.; Wang, K.; Xia, Z.; Li, Z.; Li, Q. SERS-based immunomagnetic bead for rapid detection of H5N1 influenza virus. Influenza Other Respi. Viruses 2023, 17, 1–7.
  78. Zhu, H.; White, I.M.; Suter, J.D.; Zourob, M.; Fan, X. Opto-fluidic micro-ring resonator for sensitive label-free viral detection. Analyst 2008, 133, 356–360.
  79. Koo, B.; Jin, C.E.; Lee, T.Y.; Lee, J.H.; Park, M.K.; Sung, H.; Park, S.Y.; Lee, H.J.; Kim, S.M.; Kim, J.Y.; et al. An isothermal, label-free, and rapid one-step RNA amplification/detection assay for diagnosis of respiratory viral infections. Biosens. Bioelectron. 2017, 90, 187–194.
  80. Scherr, S.M.; Daaboul, G.G.; Trueb, J.; Sevenler, D.; Fawcett, H.; Goldberg, B.; Connor, J.H.; Ünlü, S.M. Real-Time Capture and Visualization of Individual Viruses in Complex Media. ACS Nano 2016, 10, 2827–2833.
  81. Auer, S.; Koho, T.; Uusi-Kerttula, H.; Vesikari, T.; Blazevic, V.; Hytönen, V.P. Rapid and sensitive detection of norovirus antibodies in human serum with a biolayer interferometry biosensor. Sens. Actuators B Chem. 2015, 221, 507–514.
  82. Ymeti, A.; Greve, J.; Lambeck, P.V.; Wink, T.; Hövell, S.W.F.M.; Beumer, T.A.M.; Wijn, R.R.; Heideman, R.G.; Subramaniam, V.; Kanger, J.S. Fast, Ultrasensitive Virus Detection Using a Young Interferometer Sensor. Nano Lett. 2007, 7, 394–397.
  83. Marn, A.M.; Needham, J.; Chiodi, E.; Ünlü, M.S. Multiplexed, high-sensitivity measurements of antibody affinity using interferometric reflectance imaging sensor. Biosensors 2021, 11, 483.
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to : , , , , , ,
View Times: 369
Revisions: 3 times (View History)
Update Date: 09 Jun 2023