Colorimetric Detection of SARS-CoV-2 Using Plasmonic Biosensors and Smartphones.

Low-cost, instrument-free colorimetric tests were developed to detect SARS-CoV-2 using plasmonic biosensors with Au nanoparticles functionalized with polyclonal antibodies (f-AuNPs). Intense color changes were noted with the naked eye owing to plasmon coupling when f-AuNPs form clusters on the virus, with high sensitivity and a detection limit of 0.28 PFU mL-1 (PFU stands for plaque-forming units) in human saliva. Plasmon coupling was corroborated with computer simulations using the finite-difference time-domain (FDTD) method. The strategies based on preparing plasmonic biosensors with f-AuNPs are robust to permit SARS-CoV-2 detection via dynamic light scattering and UV-vis spectroscopy without interference from other viruses, such as influenza and dengue viruses. The diagnosis was made with a smartphone app after processing the images collected from the smartphone camera, measuring the concentration of SARS-CoV-2. Both image processing and machine learning algorithms were found to provide COVID-19 diagnosis with 100% accuracy for saliva samples. In subsidiary experiments, we observed that the biosensor could be used to detect the virus in river waters without pretreatment. With fast responses and requiring small sample amounts (only 20 µL), these colorimetric tests can be deployed in any location within the point-of-care diagnosis paradigm for epidemiological control.

Electrochemical immunosensors using electrodeposited gold nanostructures for detecting the S proteins from SARS-CoV and SARS-CoV-2.

This paper reports the development of a low-cost (< US$ 0.03 per device) immunosensor based on gold-modified screen-printed carbon electrodes (SPCEs). As a proof of concept, the immunosensor was tested for a fast and sensitive determination of S proteins from both SARS-CoV and SARS-CoV-2, by a single disposable device. Gold nanoparticles were electrochemically deposited via direct reduction of gold ions on the electrode using amperometry. Capture antibodies from spike (S) protein were covalently immobilized on carboxylic groups of self-assembled monolayers (SAM) of mercaptoacetic acid (MAA) attached to the gold nanoparticles. Label-free detection of S proteins from both SARS-CoV and SARS-CoV-2 was performed with electrochemical impedance spectroscopy (EIS). The immunosensor fabricated with 9 s gold deposition had a high performance in terms of selectivity, sensitivity, and low limit of detection (LOD) (3.16 pmol L-1), thus permitting the direct determination of the target proteins in spiked saliva samples. The complete analysis can be carried out within 35 min using a simple one-step assay protocol with small sample volumes (10 µL). With such features, the immunoplatform presented here can be deployed for mass testing in point-of-care settings.

1H qNMR-Based Metabolomics Discrimination of Covid-19 Severity.

The coronavirus disease 2019 (Covid-19), which caused respiratory problems in many patients worldwide, led to more than 5 million deaths by the end of 2021. Experienced symptoms vary from mild to severe illness. Understanding the infection severity to reach a better prognosis could be useful to the clinics, and one study area to fulfill one piece of this biological puzzle is metabolomics. The metabolite profile and/or levels being monitored can help predict phenotype properties. Therefore, this study evaluated plasma metabolomes of 110 individual samples, 57 from control patients and 53 from recent positive cases of Covid-19 (IgM 98% reagent), representing mild to severe symptoms, before any clinical intervention. Polar metabolites from plasma samples were analyzed by quantitative 1H NMR. Glycerol, 3-aminoisobutyrate, formate, and glucuronate levels showed alterations in Covid-19 patients compared to those in the control group (Tukey's HSD p-value cutoff = 0.05), affecting the lactate, phenylalanine, tyrosine, and tryptophan biosynthesis and d-glutamine, d-glutamate, and glycerolipid metabolisms. These metabolic alterations show that SARS-CoV-2 infection led to disturbance in the energetic system, supporting the viral replication and corroborating with the severe clinical conditions of patients. Six polar metabolites (glycerol, acetate, 3-aminoisobutyrate, formate, glucuronate, and lactate) were revealed by PLS-DA and predicted by ROC curves and ANOVA to be potential prognostic metabolite panels for Covid-19 and considered clinically relevant for predicting infection severity due to their straight roles in the lipid and energy metabolism. Thus, metabolomics from samples of Covid-19 patients is a powerful tool for a better understanding of the disease mechanism of action and metabolic consequences of the infection in the human body and may corroborate allowing clinicians to intervene quickly according to the needs of Covid-19 patients.