Rapid detection of SARS-CoV-2: The gradual boom of lateral flow immunoassay

BRET-based biosensors for SARS-CoV-2 oligonucleotide detection

The need for the early detection of emerging pathogenic viruses and their newer variants has driven the urgent demand for developing point-of-care diagnostic tools. Although nucleic acid-based methods such as reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and loop-mediated isothermal amplification (LAMP) have been developed, a more facile and robust platform is still required. To address this need, as a proof-of-principle study, we engineered a prototype-the versatile, sensitive, rapid, and cost-effective bioluminescence resonance energy transfer (BRET)-based biosensor for oligonucleotide detection (BioOD). Specifically, we designed BioODs against the SARS-CoV-2 parental (Wuhan strain) and B.1.617.2 Delta variant through the conjugation of specific, fluorescently modified molecular beacons (sensor module) through a complementary oligonucleotide handle DNA functionalized with the NanoLuc (NLuc) luciferase protein such that the dissolution of the molecular beacon loop upon the binding of the viral oligonucleotide will result in a decrease in BRET efficiency and, thus, a change in the bioluminescence spectra. Following the assembly of the BioODs, we determined their kinetics response, affinity for variant-specific oligonucleotides, and specificity, and found them to be rapid and highly specific. Furthermore, the decrease in BRET efficiency of the BioODs in the presence of viral oligonucleotides can be detected as a change in color in cell phone camera images. We envisage that the BioODs developed here will find application in detecting viral infections with variant specificity in a point-of-care-testing format, thus aiding in large-scale viral infection surveillance.

Lateral flow strip assay of a gene segment in the COVID-19 virus with combined dual readout mode and preliminary multisite hybrid chain reaction amplification

The past and present scenario of COVID-19 has revealed the necessity of simple point-of-care tests. When combined with the great advantages of amplification, lateral flow assay nucleic acid analysis represents a more sensitive molecular diagnostic technique compared to universal protein analysis. Room temperature operation, an enzyme-free nature, and in situ elongation make hybrid chain reaction amplification (HCR) a good candidate for amplified combined lateral flow assays (LFAs). Since dual modes of detection can not only satisfy different application scenarios, but also reduce the false-negative rate, in this paper, visual and fluorescent detection based on labelling with colloidal gold nanoparticles and fluorescence labelling were incorporated into a HCR integrated with a LFA. The detection assay was finished in 30 minutes. The linear relationship between the signal and the concentration of the characteristic segment in the COVID-19 ORF gene was demonstrated. The obtained detection limits of as low as 10 fM (6.02 × 103 copies per mL) and 1 fM (6.02 × 102 copies per mL), respectively, were comparable with those in the literature. The multi-site HCR amplification integrated with LFA of a 1053 bp nucleic acid chain was also preliminarily studied, and tri-site amplification was found to exhibit higher signal intensity than single-site amplification. This study provides a promising strategy for simple, sensitive, and wide-ranging detection of pathogenic bacteria.

Optical lateral flow assays in early diagnosis of SARS-CoV-2 infection

So far, the 2019 novel coronavirus (COVID-19) is spreading widely worldwide. The early diagnosis of infection by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is essential to provide timely treatment and prevent its further spread. Lateral flow assays (LFAs) have the advantages of rapid detection, simple operation, low cost, ease of mass production, and no need for special devices and professional operators, which make them suitable for self-testing at home. This review focuses on the early diagnosis of SARS-CoV-2 infection based on optical LFAs including colorimetric, fluorescent (FL), chemiluminescent (CL), and surface-enhanced Raman scattering (SERS) LFAs for the detection of SARS-CoV-2 antigens and nucleic acids. The types of recognition components, detection modes used for antigen detection, labels employed in different optical LFAs, and strategies to improve the detection sensitivity of LFAs were reviewed. Meanwhile, LFAs coupled with different nucleic acid amplification techniques and CRISPR-Cas systems for the detection of SARS-CoV-2 nucleic acids were summarized. We hope this review provides research mentalities for developing highly sensitive LFAs that can be used in home self-testing for the early diagnosis of SARS-CoV-2 infection.

Magnetic-responsive upconversion luminescence resonance energy transfer (LRET) biosensor for ultrasensitive detection of SARS-CoV-2 spike protein

Upconversion nanoparticles (UCNPs) are ideal donors for luminescence resonance energy transfer (LRET)-based biosensors due to their excellent upconversion luminescence properties. However, the relatively large size of antibodies and proteins limits the application of UCNPs-based LRET biosensors in protein detection because the large steric hindrance of proteins leads to low energy transfer efficiency between UCNPs and receptors. Herein, we developed a magnetic responsive UCNPs-based LRET biosensor to control the coupling distance between antibody-functionalized UCNPs (Ab-UCNPs) as donors and antibody-PEG linker-magnetic gold nanoparticles (Ab-PEG-MGNs) as acceptors for ultrasensitive and highly selective detection of SARS-CoV-2 spike proteins. Our results showed that this platform reversibly shortened the coupling distance between UCNPs and MGNs and enhanced the LRET signal with a 10-fold increase in the limit of detection (LOD) from 20.6 pg/mL without magnetic modulation to 2.1 pg/mL with magnetic modulation within 1 h. The finite-difference time-domain (FDTD) simulation with cyclic distance change confirmed the distance-dependent LRET efficiency under magnetic modulation, which supported the experimental results. Moreover, the applications of this magnetic-responsive UCNP-based LRET biosensor could be extended to other large-size biomolecule detection.

A semi-quantitative visual lateral flow immunoassay for SARS-CoV-2 antibody detection for the follow-up of immune response to vaccination or recovery

The lateral flow immunoassay (LFIA) technique is largely employed for the point-of-care detection of antibodies especially for revealing the immune response in serum. Visual LFIAs usually provide the qualitative yes/no detection of antibodies, while quantification requires some equipment, making the assay more expensive and complicated. To achieve visual semi-quantification, the alignment of several lines (made of the same antigen) along a LFIA strip has been proposed. The numbering of the reacting lines has been used to correlate with the quantity of some biomarkers in serum. Here, we designed the first semiquantitative LFIA for detecting antibodies and applied it to classify the immune response to SARS-CoV-2 raised by vaccination or natural infection. We used a recombinant spike receptor-binding domain (RBD) as the specific capture reagent to draw two test lines. The detection reagent was selected among three possible ligands that are able to bind to anti-spike human antibodies: the same RBD, staphylococcal protein A, and anti-human immunoglobulin G antibodies. The most convenient detector, adsorbed on gold nanoparticles, was chosen based on the highest correlation with an antibody titre of 171 human sera, measured by a reference serological method, and was the RBD (Spearman's rho = 0.84). Incorporated into the semiquantitative LFIA, it confirmed the ability to discriminate high- and low-titre samples and to classify them into two classes (Dunn's test, P < 0.05). The proposed approach enabled the semiquantification of the immune response to SARS-CoV-2 by the unaided eye observation, thus overcoming the requirement of costly and complicated equipment, and represents a general strategy for the development of semiquantitative serological LFIAs.

Recent Studies on Metal-Embedded Silica Nanoparticles for Biological Applications

Recently, silica nanoparticles (NPs) have attracted considerable attention as biocompatible and stable templates for embedding noble metals. Noble-metal-embedded silica NPs utilize the exceptional optical properties of novel metals while overcoming the limitations of individual novel metal NPs. In addition, the structure of metal-embedded silica NPs decorated with small metal NPs around the silica core results in strong signal enhancement in localized surface plasmon resonance and surface-enhanced Raman scattering. This review summarizes recent studies on metal-embedded silica NPs, focusing on their unique designs and applications. The characteristics of the metal-embedded silica NPs depend on the type and structure of the embedded metals. Based on this progress, metal-embedded silica NPs are currently utilized in various spectroscopic applications, serving as nanozymes, detection and imaging probes, drug carriers, photothermal inducers, and bioactivation molecule screening identifiers. Owing to their versatile roles, metal-embedded silica NPs are expected to be applied in various fields, such as biology and medicine, in the future.

Performance evaluation of the cobas SARS-CoV-2 Duo, a novel qualitative and quantitative assay, for the detection of SARS-CoV-2 RNA

IMPORTANCE

Quantitative SARS-CoV-2 tests for viral load are necessary to guide patient treatment, as well as to determine infection control measures and policies. Although the real-time RT-PCR assays can report the Ct value to estimate the viral load, there are several serious concerns regarding the use of Ct values. Importantly, Ct values can vary significantly among between- and within-run methods. The diagnostic performance of the cobas SARS-CoV-2 Duo is appropriate. It is a precise, accurate, and sensitive method for the detection of SARS-CoV-2 RNA and is comparable to two qualitative assays (the cobas SARS-CoV-2 and the Liat cobas SARS-CoV-2 and Inf A/B). In contrast, using the Ct value to estimate viral load is not reliable, and utilization of a quantitative detection test, such as the cobas SARS-CoV-2 Duo, to accurately measure the viral load is needed.

Advancements in the synergy of isothermal amplification and CRISPR-cas technologies for pathogen detection

In the realm of pathogen detection, isothermal amplification technology has emerged as a swift, precise, and sensitive alternative to conventional PCR. This paper explores the fundamental principles of recombinase polymerase amplification (RPA) and recombinase-aid amplification (RAA) and reviews the current status of integrating the CRISPR-Cas system with RPA/RAA techniques. Furthermore, this paper explores the confluence of isothermal amplification and CRISPR-Cas technology, providing a comprehensive review and enhancements of existing combined methodologies such as SHERLOCK and DETECTR. We investigate the practical applications of RPA/RAA in conjunction with CRISPR-Cas for pathogen detection, highlighting how this integrated approach significantly advances both research and clinical implementation in the field. This paper aims to provide readers with a concise understanding of the fusion of RPA/RAA and CRISPR-Cas technology, offering insights into their clinical utility, ongoing enhancements, and the promising prospects of this integrated approach in pathogen detection.

Machine Learning Techniques for Effective Pathogen Detection Based on Resonant Biosensors

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism.

Recent Advances in Quantum Dot-Based Lateral Flow Immunoassays for the Rapid, Point-of-Care Diagnosis of COVID-19

The COVID-19 pandemic has spurred demand for efficient and rapid diagnostic tools that can be deployed at point of care to quickly identify infected individuals. Existing detection methods are time consuming and they lack sensitivity. Point-of-care testing (POCT) has emerged as a promising alternative due to its user-friendliness, rapidity, and high specificity and sensitivity. Such tests can be conveniently conducted at the patient's bedside. Immunodiagnostic methods that offer the rapid identification of positive cases are urgently required. Quantum dots (QDs), known for their multimodal properties, have shown potential in terms of combating or inhibiting the COVID-19 virus. When coupled with specific antibodies, QDs enable the highly sensitive detection of viral antigens in patient samples. Conventional lateral flow immunoassays (LFAs) have been widely used for diagnostic testing due to their simplicity, low cost, and portability. However, they often lack the sensitivity required to accurately detect low viral loads. Quantum dot (QD)-based lateral flow immunoassays have emerged as a promising alternative, offering significant advancements in sensitivity and specificity. Moreover, the lateral flow immunoassay (LFIA) method, which fulfils POCT standards, has gained popularity in diagnosing COVID-19. This review focuses on recent advancements in QD-based LFIA for rapid POCT COVID-19 diagnosis. Strategies to enhance sensitivity using QDs are explored, and the underlying principles of LFIA are elucidated. The benefits of using the QD-based LFIA as a POCT method are highlighted, and its published performance in COVID-19 diagnostics is examined. Overall, the integration of quantum dots with LFIA holds immense promise in terms of revolutionizing COVID-19 detection, treatment, and prevention, offering a convenient and effective approach to combat the pandemic.

Comparison of Three Lateral Flow Immunoassay Formats for the Detection of Antibodies against the SARS-CoV-2 Antigen

Reliable detection of specific antibodies against pathogens by lateral flow immunoassay (LFIA) greatly depends on the composition of the detectable complex and the order of its assembly. We compared three LFIA formats for revealing anti-SARS-CoV-2 antibodies in sera with the following detected complexes in the analytical zone of the strip: antigen-antibodies-labeled immunoglobulin-binding protein (Scheme A); antigen-antibodies-labeled antigen (Scheme B); and immunoglobulin-binding protein-antibodies-labeled antigen (Scheme C). The lowest detection limit was observed for Scheme C, and was equal to 10 ng/mL of specific humanized monoclonal antibodies. When working with pooled positive sera, Scheme C had a detection limit 15 times lower than Scheme B and 255 times lower than Scheme A. Due to the high sensitivity of Scheme C, its application for the panel of human sera (n = 22) demonstrated 100% diagnostic specificity and sensitivity. These consistent results be useful for designing the format of LFIA serodiagnosis for other diseases.

Organokines in COVID-19: A Systematic Review

Coronavirus disease 2019 (COVID-19) is a viral infection caused by SARS-CoV-2 that induces a generalized inflammatory state. Organokines (adipokines, osteokines, myokines, hepatokines, and cardiokines) can produce beneficial or harmful effects in this condition. This study aimed to systematically review the role of organokines on COVID-19. PubMed, Embase, Google Scholar, and Cochrane databases were searched, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and 37 studies were selected, comprising more than 2700 individuals infected with the virus. Among COVID-19 patients, organokines have been associated with endothelial dysfunction and multiple organ failure due to augmented cytokines and increased SARS-CoV-2 viremia. Changes in the pattern of organokines secretion can directly or indirectly contribute to aggravating the infection, promoting immune response alterations, and predicting the disease progression. These molecules have the potential to be used as adjuvant biomarkers to predict the severity of the illness and severe outcomes.