A multiplex ELISA-based protein array for screening diagnostic antigens and diagnosis of Flaviviridae infection

A miniprotein receptor electrochemical biosensor chip based on quantum dots

Recently protein binders have emerged as a promising substitute for antibodies due to their high specificity and low cost. Herein, we demonstrate an electrochemical biosensor chip through the electronic labelling strategy using lead sulfide (PbS) colloidal quantum dots (CQDs) and the unnatural SARS-CoV-2 spike miniprotein receptor LCB. The unnatural receptor can be utilized as a molecular probe for the construction of CQD-based electrochemical biosensor chips, through which the specific binding of LCB and the spike protein is transduced to sensor electrical signals. The biosensor exhibits a good linear response in the concentration range of 10 pg mL-1 to 1 μg mL-1 (13.94 fM to 1.394 nM) with the limit of detection (LOD) being 3.31 pg mL-1 (4.607 fM for the three-electrode system) and 9.58 fg mL-1 (0.013 fM for the HEMT device). Due to the high sensitivity of the electrochemical biosensor, it was also used to study the binding kinetics between the unnatural receptor LCB and spike protein, which has achieved comparable results as those obtained with commercial equipment. To the best of our knowledge, this is the first example of using a computationally designed miniprotein receptor based on electrochemical methods, and it is the first kinetic assay performed with an electrochemical assay alone. The miniprotein receptor electrochemical biosensor based on QDs is desirable for fabricating high-throughput, large-area, wafer-scale biochips.

Recombinant TBEV Protein E of the Siberian Subtype Is a Candidate Antigen in the ELISA Test System for Differential Diagnosis

The tick-borne encephalitis virus (TBEV) is one of the most common members of the Orthoflavivirus genus, which comprises the causative agents of severe diseases in humans and animals. Due to the expanding areas of orthoflavivirus infection, its differential diagnosis is highly demanded. Commercial test kits based on inactivated TBEV may not provide reliable differentiation between flaviviruses because of serological crossover in this genus. Application of recombinant domains (sE and dIII) of the TBEV Sukhar-strain protein E as antigens in an ELISA test system allowed us to identify a wide range of antibodies specific to different TBEV strains. We tested 53 sera from human patients with confirmed TBE diagnosis (the efficacy of our test system based on sE protein was 98%) and 56 sera from patients with other orthoflavivirus infections in which no positive ones were detected using our ELISA test system, thus being indicative of its 100% specificity. We also tested mouse and rabbit sera containing antibodies specific to 17 TBEV strains belonging to different subtypes; this assay exhibited high efficacy and differentiation ability in detecting antibodies against TBEV from other orthoflaviviruses such as Omsk hemorrhagic fever, Powassan, yellow fever, dengue, West Nile, Zika, and Japanese encephalitis viruses.

MultiSero: An Open-Source Multiplex-ELISA Platform for Measuring Antibody Responses to Infection

A multiplexed enzyme-linked immunosorbent assay (ELISA) that simultaneously measures antibody binding to multiple antigens can extend the impact of serosurveillance studies, particularly if the assay approaches the simplicity, robustness, and accuracy of a conventional single-antigen ELISA. Here, we report on the development of multiSero, an open-source multiplex ELISA platform for measuring antibody responses to viral infection. Our assay consists of three parts: (1) an ELISA against an array of proteins in a 96-well format; (2) automated imaging of each well of the ELISA array using an open-source plate reader; and (3) automated measurement of optical densities for each protein within the array using an open-source analysis pipeline. We validated the platform by comparing antibody binding to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antigens in 217 human sera samples, showing high sensitivity (0.978), specificity (0.977), positive predictive value (0.978), and negative predictive value (0.977) for classifying seropositivity, a high correlation of multiSero determined antibody titers with commercially available SARS-CoV-2 antibody tests, and antigen-specific changes in antibody titer dynamics upon vaccination. The open-source format and accessibility of our multiSero platform can contribute to the adoption of multiplexed ELISA arrays for serosurveillance studies, for SARS-CoV-2 and other pathogens of significance.

Novel Approaches to an Integrated Route for Trisomy 21 Evaluation

Trisomy 21 (T21) is one of the most commonly occurring genetic disorders, caused by the partial or complete triplication of chromosome 21. Despite the significant progress in the diagnostic tools applied for prenatal screening, commonly used methods are still imprecise and involve invasive diagnostic procedures that are related to a maternal risk of miscarriage. In this case, novel prenatal biomarkers are still being evaluated using highly specialized techniques, which could increase the diagnostic usefulness of biochemical prenatal screening for T21. From the other hand, the T21′s pathogenesis, caused by the improper division of genetic material, disrupting many metabolic pathways, could be further evaluated with the use of omics methods, which could result in bringing relevant insights for the evaluation of potential medical targets. Accordingly, a literature search was undertaken to collect novel information about prenatal screening for Down syndrome with the use of advanced technology, with a particular emphasis on the evaluation of novel screening biomarkers and the discovery of potential medical targets. These meta-analyses are focused on novel approaches designed with the use of omics techniques, representing the most rapidly developing and promising field in research today. Considering the limitations and progress of these methods, the use of omics techniques in evaluating T21 pathogenesis could bring beneficial results in prenatal screening, simultaneously uncovering novel potential medical targets.

Electrochemical Microbiosensor for Detecting COVID-19 in a Patient Sample Based on Gold Microcuboids Pattern

As continues increasing the COVID-19 infections, there is an urgent need for developing fast, simple, selective, and accurate COVID-19 biosensors. A highly uniform gold (Au) microcuboid pattern was used as a microelectrode that allowed monitoring a small analyte. The electrochemical biosensor was used to monitor the COVID-19 S protein within a concentration range from 100 to 5 pmol L⁻¹; it showed a lower detection limit of 276 fmol L⁻¹. Finally, the developed COVID-19 sensor was used to detect a positive sample from a human patient obtained through a nasal swab; the results were confirmed using the PCR technique. The results showed that the SWV technique showed high sensitivity towards detecting COVID-19 and good efficiency for detecting COVID-19 in a positive human sample.

multiSero: open multiplex-ELISA platform for analyzing antibody responses to SARS-CoV-2 infection

Serology has provided valuable diagnostic and epidemiological data on antibody responses to SARS-CoV-2 in diverse patient cohorts. Deployment of high content, multiplex serology platforms across the world, including in low and medium income countries, can accelerate longitudinal epidemiological surveys. Here we report multiSero, an open platform to enable multiplex serology with up to 48 antigens in a 96-well format. The platform consists of three components: ELISA-array of printed proteins, a commercial or home-built plate reader, and modular python software for automated analysis (pysero). We validate the platform by comparing antibody titers against the SARS-CoV-2 Spike, receptor binding domain (RBD), and nucleocapsid (N) in 114 sera from COVID-19 positive individuals and 87 pre-pandemic COVID-19 negative sera. We report data with both a commercial plate reader and an inexpensive, open plate reader (nautilus). Receiver operating characteristic (ROC) analysis of classification with single antigens shows that Spike and RBD classify positive and negative sera with the highest sensitivity at a given specificity. The platform distinguished positive sera from negative sera when the reactivity of the sera was equivalent to the binding of 1 ng mL⁻¹ RBD-specific monoclonal antibody. We developed normalization and classification methods to pool antibody responses from multiple antigens and multiple experiments. Our results demonstrate a performant and accessible pipeline for multiplexed ELISA ready for multiple applications, including serosurveillance, identification of viral proteins that elicit antibody responses, differential diagnosis of circulating pathogens, and immune responses to vaccines.

Comparing machine learning with case-control models to identify confirmed dengue cases

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x103/μL)], fever (≥38°C), low platelet counts [< 100 (x103/μL)], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96-6.76], 3.17 [95%CI: 2.74-3.66], 3.10 [95%CI: 2.44-3.94], and 1.77 [95%CI: 1.50-2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

Efficient Plant Production of Recombinant NS1 Protein for Diagnosis of Dengue

Dengue fever is endemic in more than 120 countries, which account for 3.9 billion people at risk of infection worldwide. The absence of a vaccine with effective protection against the four serotypes of this virus makes differential molecular diagnosis the key step for the correct treatment of the disease. Rapid and efficient diagnosis prevents progression to a more severe stage of this disease. Currently, the limiting factor in the manufacture of dengue (DENV) diagnostic kits is the lack of large-scale production of the non-structural 1 (NS1) protein (antigen) to be used in the capture of antibodies from the blood serum of infected patients. In this work, we use plant biotechnology and genetic engineering as tools for the study of protein production for research and commercial purposes. Gene transfer, integration and expression in plants is a valid strategy for obtaining large-scale and low-cost heterologous protein production. The authors produced NS1 protein of the dengue virus serotype 2 (NS1DENV2) in the Arabidopsis thaliana plant. Transgenic plants obtained by genetic transformation expressed the recombinant protein that was purified and characterized for diagnostic use. The yield was 203 μg of the recombinant protein per gram of fresh leaf. By in situ immunolocalization, transgenic protein was observed within the plant tissue, located in aggregates bodies. These antigens showed high sensitivity and specificity to both IgM (84.29% and 91.43%, respectively) and IgG (83.08% and 87.69%, respectively). The study goes a step further to validate the use of plants as a strategy for obtaining large-scale and efficient protein production to be used in dengue virus diagnostic tests.

Human virus detection with graphene-based materials

Our recent experience of the COVID-19 pandemic has highlighted the importance of easy-to-use, quick, cheap, sensitive and selective detection of virus pathogens for the efficient monitoring and treatment of virus diseases. Early detection of viruses provides essential information about possible efficient and targeted treatments, prolongs the therapeutic window and hence reduces morbidity. Graphene is a lightweight, chemically stable and conductive material that can be successfully utilized for the detection of various virus strains. The sensitivity and selectivity of graphene can be enhanced by its functionalization or combination with other materials. Introducing suitable functional groups and/or counterparts in the hybrid structure enables tuning of the optical and electrical properties, which is particularly attractive for rapid and easy-to-use virus detection. In this review, we cover all the different types of graphene-based sensors available for virus detection, including, e.g., photoluminescence and colorimetric sensors, and surface plasmon resonance biosensors. Various strategies of electrochemical detection of viruses based on, e.g., DNA hybridization or antigen-antibody interactions, are also discussed. We summarize the current state-of-the-art applications of graphene-based systems for sensing a variety of viruses, e.g., SARS-CoV-2, influenza, dengue fever, hepatitis C virus, HIV, rotavirus and Zika virus. General principles, mechanisms of action, advantages and drawbacks are presented to provide useful information for the further development and construction of advanced virus biosensors. We highlight that the unique and tunable physicochemical properties of graphene-based nanomaterials make them ideal candidates for engineering and miniaturization of biosensors.

Label-Free Electrochemical Biosensors for the Determination of Flaviviruses: Dengue, Zika, and Japanese Encephalitis

A highly effective way to improve prognosis of viral infectious diseases and to determine the outcome of infection is early, fast, simple, and efficient diagnosis of viral pathogens in biological fluids. Among a wide range of viral pathogens, Flaviviruses attract a special attention. Flavivirus genus includes more than 70 viruses, the most familiar being dengue virus (DENV), Zika virus (ZIKV), and Japanese encephalitis virus (JEV). Haemorrhagic and encephalitis diseases are the most common severe consequences of flaviviral infection. Currently, increasing attention is being paid to the development of electrochemical immunological methods for the determination of Flaviviruses. This review critically compares and evaluates recent research progress in electrochemical biosensing of DENV, ZIKV, and JEV without labelling. Specific attention is paid to comparison of detection strategies, electrode materials, and analytical characteristics. The potential of so far developed biosensors is discussed together with an outlook for further development in this field.

Adaption of a conventional ELISA to a 96-well ELISA-Array for measuring the antibody responses to influenza virus proteins and vaccines

We describe an adaptation of conventional ELISA methods to an ELISA-Array format using non-contact Piezo printing of up to 30 spots of purified recombinant viral fusion proteins and vaccine on 96 well high-protein binding plates. Antigens were printed in 1 nanoliter volumes of protein stabilizing buffer using as little as 0.25 nanograms of protein, 2000-fold less than conventional ELISA. The performance of the ELISA-Array was demonstrated by serially diluting n = 9 human post-flu vaccination plasma samples starting at a 1/1000 dilution and measuring binding to the array of Influenza antigens. Plasma polyclonal antibody levels were detected using a cocktail of biotinylated anti-human kappa and lambda light chain antibodies, followed by a Streptavidin-horseradish peroxidase conjugate and the dose-dependent signal was developed with a precipitable TMB substrate. Intra- and inter-assay precision of absorbance units among the eight donor samples showed mean CVs of 4.8% and 10.8%, respectively. The plasma could be differentiated by donor and antigen with titer sensitivities ranging from 1 × 10³ to 4 × 10⁶, IC₅₀ values from 1 × 10⁴ to 9 × 10⁶, and monoclonal antibody sensitivities in the ng/mL range. Equivalent sensitivities of ELISA versus ELISA-Array, compared using plasma and an H1N1 HA trimer, were achieved on the ELISA-Array printed at 0.25 ng per 200um spot and 1000 ng per ELISA 96-well. Vacuum-sealed array plates were shown to be stable when stored for at least 2 days at ambient temperature and up to 1 month at 4-8 °C. By the use of any set of printed antigens and analyte matrices the methods of this multiplexed ELISA-Array format can be broadly applied in translational research.

Universal simultaneous multiplex ELISA of small molecules in milk based on dual luciferases

The enzyme-linked immunosorbent assay (ELISA) has become the most important and widely used rapid detection technology for food safety because of its simple operation, fast speed and high sensitivity. Multiplex synchronous detection is the goal of ELISA that is always pursuing for. However, the reported multiplex ELISAs have not truly realized synchronous detection because of the complex signal generation and collection procedures. Here, we developed a dual-luciferases competitive direct bioluminescent immunoassay (DBL-cdELISA) with only one substrate addition step followed immediately by simultaneous signal acquisition. It is the first report of simultaneous multiplex analysis of small molecules based on microtiter plates and enzymes without any additional steps. The IC₅₀ values for norfloxacin (NOR) and sulfamethazine (SMZ) were 0.051 ng mL^-1 and 0.211 ng mL^-1, respectively. The results demonstrated that the application of different luciferases and substrates simplified the signal generation and collection procedures and enabled simultaneous detection of small molecules with a simple procedure, high throughput and fast speed, that will be of great significance for the development of multiple assays.

Progress and Challenges towards Point-of-Care Diagnostic Development for Dengue

Dengue detection strategies involve viral RNA, antigen, and/or antibody detection. Each strategy has its advantages and disadvantages. Optimal, user-friendly, rapid diagnostic tests based on immunochromatographic assays are pragmatic point-of-care tests (POCTs) in regions where dengue is endemic where there are limited laboratory capabilities and optimal storage conditions. Increasingly, there is a greater public health significance for a multiplexing assay that differentiates dengue from Zika or pathogens with similar clinical presentations. Although there have been many assay/platform developments toward POCTs, independent validation and implementation remain very limited. This review highlights the current key progress and challenges toward the development of a dengue POCT.