Use of surface plasmon resonance imaging to study viral RNA:protein interactions

SPR Based Biosensing Chip for COVID-19 Diagnosis-A Review

Surface Plasmon Resonance (SPR) techniques are highly accurate in detecting biomolecular like blood group measurement, food adulteration, milk adulteration and recently developing as a rapid detection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. In order to validate the clinical diagnosis, Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) of nasopharyngeal swabs has been utilized, which is time consuming and expensive. For fast and accurate detection of the SARS-CoV-2 virus, SPR based biosensing chips are described in this review article. SPR sensors have the potential to be employed for fast, accurate, and portable SARS-CoV-2 virus diagnosis. To combat the SARS-CoV-2 pandemic, there is considerable interest in creating innovative biosensors that are quick, reliable, and sensitive for COVID-19 diagnosis.

Advancements in Testing Strategies for COVID-19

The SARS-CoV-2 coronavirus, also known as the disease-causing agent for COVID-19, is a virulent pathogen that may infect people and certain animals. The global spread of COVID-19 and its emerging variation necessitates the development of rapid, reliable, simple, and low-cost diagnostic tools. Many methodologies and devices have been developed for the highly sensitive, selective, cost-effective, and rapid diagnosis of COVID-19. This review organizes the diagnosis platforms into four groups: imaging, molecular-based detection, serological testing, and biosensors. Each platform's principle, advancement, utilization, and challenges for monitoring SARS-CoV-2 are discussed in detail. In addition, an overview of the impact of variants on detection, commercially available kits, and readout signal analysis has been presented. This review will expand our understanding of developing advanced diagnostic approaches to evolve into susceptible, precise, and reproducible technologies to combat any future outbreak.

Emerging Biosensors to Detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Review

Coronavirus disease (COVID-19) is a global health crisis caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard test for diagnosing COVID-19. Although it is highly accurate, this lab test requires highly-trained personnel and the turn-around time is long. Rapid and inexpensive immuno-diagnostic tests (antigen or antibody test) are available, but these point of care (POC) tests are not as accurate as the RT-PCR test. Biosensors are promising alternatives to these rapid POC tests. Here we review three types of recently developed biosensors for SARS-CoV-2 detection: surface plasmon resonance (SPR)-based, electrochemical and field-effect transistor (FET)-based biosensors. We explain the sensing principles and discuss the advantages and limitations of these sensors. The accuracies of these sensors need to be improved before they could be translated into POC devices for commercial use. We suggest potential biorecognition elements with highly selective target-analyte binding that could be explored to increase the true negative detection rate. To increase the true positive detection rate, we suggest two-dimensional materials and nanomaterials that could be used to modify the sensor surface to increase the sensitivity of the sensor.

A comprehensive review on plasmonic-based biosensors used in viral diagnostics

The proliferation and transmission of viruses has become a threat to worldwide biosecurity, as exemplified by the current COVID-19 pandemic. Early diagnosis of viral infection and disease control have always been critical. Virus detection can be achieved based on various plasmonic phenomena, including propagating surface plasmon resonance (SPR), localized SPR, surface-enhanced Raman scattering, surface-enhanced fluorescence and surface-enhanced infrared absorption spectroscopy. The present review covers all available information on plasmonic-based virus detection, and collected data on these sensors based on several parameters. These data will assist the audience in advancing research and development of a new generation of versatile virus biosensors.

Designed biointerface using near-infrared quantum dots for ultrasensitive surface plasmon resonance imaging biosensors

The surface plasmon resonance imaging chip biointerface is fully designed using near-infrared (NIR) quantum dots (QDs) for the enhancement of surface plasmon resonance imaging (SPRi) signals in order to extend their application for medical diagnostics. The measured SPRi detection signal following the QD binding to the surface was amplified 25-fold for a 1 nM concentration of single-stranded DNA (ssDNA) and 50-fold for a 1 μg/mL concentration of prostate-specific antigen (PSA), a cancer biomarker, thus substantiating their wide potential to study interactions of a diverse set of small biomolecules. This significant enhancement is attributed to the QD's mass-loading effect and spontaneous emission coupling with propagating surface plasmons, which allowed the SPRi limit of detection to be reduced to 100 fM and 100 pg/mL for ssDNA and PSA, respectively. Furthermore, this study illustrates the potential of SPRi to be easily integrated with fluorescent imaging for advanced correlative surface-interaction analysis.

Grading the commercial optical biosensor literature-Class of 2008: 'The Mighty Binders'

Optical biosensor technology continues to be the method of choice for label-free, real-time interaction analysis. But when it comes to improving the quality of the biosensor literature, education should be fundamental. Of the 1413 articles published in 2008, less than 30% would pass the requirements for high-school chemistry. To teach by example, we spotlight 10 papers that illustrate how to implement the technology properly. Then we grade every paper published in 2008 on a scale from A to F and outline what features make a biosensor article fabulous, middling or abysmal. To help improve the quality of published data, we focus on a few experimental, analysis and presentation mistakes that are alarmingly common. With the literature as a guide, we want to ensure that no user is left behind.