Discrimination of the H1N1 and H5N2 Variants of Influenza A Virus Using an Isomeric Sialic Acid-Conjugated Graphene Field-Effect Transistor

There has been a continuous effort to fabricate a fast, sensitive, and inexpensive system for influenza virus detection to meet the demand for effective screening in point-of-care testing. Herein, we report a sialic acid (SA)-conjugated graphene field-effect transistor (SA-GFET) sensor designed using α2,3-linked sialic acid (3'-SA) and α2,6-linked sialic acid (6'-SA) for the detection and discrimination of the hemagglutinin (HA) protein of the H5N2 and H1N1 viruses. 3'-SA and 6'-SA specific for H5 and H1 influenza were used in the SA-GFET to capture the HA protein of the influenza virus. The net charge of the captured viral sample led to a change in the electrical current of the SA-GFET platform, which could be correlated to the concentration of the viral sample. This SA-GFET platform exhibited a highly sensitive response in the range of 10¹-10⁶ pfu mL^-1, with a limit of detection (LOD) of 10¹ pfu mL^-1 in buffer solution and a response time of approximately 10 s. The selectivity of the SA-GFET platform for the H1N1 and H5N2 influenza viruses was verified by testing analogous respiratory viruses, i.e., influenza B and the spike protein of SARS-CoV-2 and MERS-CoV, on the SA-GFET. Overall, the results demonstrate that the developed dual-channel SA-GFET platform can potentially serve as a highly efficient and sensitive sensing platform for the rapid detection of infectious diseases.

Dual-mode detection of avian influenza virions (H9N2) by ICP-MS and fluorescence after quantum dot labeling with immuno-rolling circle amplification

Avian influenza virus (AIVs), hosted in poultry, are the pathogens of many poultry diseases and human infections, which bring huge losses to the poultry breeding industry and huge panic to society. Therefore, it is of great significance to establish accurate and sensitive detection methods for AIVs. In this work, a dual-mode detection method based on immuno-rolling circle amplification (immuno-RCA) and quantum dots (QDs) labeling for inductively coupled plasma mass spectrometry (ICP-MS) and fluorescence detection of H9N2 AIV was developed. The dual-mode detection of the QDs by ICP-MS and fluorescence is used to achieve mutual verification within the analysis results, thus improving the accuracy of the method. With the immuno-RCA, the sensitivity of the method was increased by two orders of magnitude. The limit of detection of the proposed method is 17 ng L^-1 and 61 ng L^-1, and the linear range of the proposed method is 0.05-5 ng mL^-1 and 0.1-5 ng mL^-1 with ICP-MS and fluorescence detection, respectively. The relative standard deviation (n = 7) is 4.9% with ICP-MS detection and 3.1% with fluorescence detection. Furthermore, the proposed method was applied to the analysis of chicken serum samples, no significant different was found for two modes detection and the recoveries of the spiking experiments are acceptable, indicating that the method has good practical potential for real sample analysis.

Detection Methods of Human and Animal Influenza Virus-Current Trends

The basic affairs connected to the influenza virus were reviewed in the article, highlighting the newest trends in its diagnostic methods. Awareness of the threat of influenza arises from its ability to spread and cause a pandemic. The undiagnosed and untreated viral infection can have a fatal effect on humans. Thus, the early detection seems pivotal for an accurate treatment, when vaccines and other contemporary prevention methods are not faultless. Public health is being attacked with influenza containing new genes from a genetic assortment between animals and humankind. Unfortunately, the population does not have immunity for mutant genes and is attacked in every viral outbreak season. For these reasons, fast and accurate devices are in high demand. As currently used methods like Rapid Influenza Diagnostic Tests lack specificity, time and cost-savings, new methods are being developed. In the article, various novel detection methods, such as electrical and optical were compared. Different viral elements used as detection targets and analysis parameters, such as sensitivity and specificity, were presented and discussed.