Nanobiosensor Based on Sugar Code-AuNPs Aggregation: A Key to Opening New Gates in Rapid Diagnosis of Streptococcal Pharyngitis

Abstract

Streptococcal pharyngitis is mainly caused by Streptococcus pyogenes (GAS), which if left untreated can lead to rheumatic heart disease. The accurate diagnosis of streptococcal pharyngitis is a challenge for clinicians because several symptoms of streptococcal pharyngitis are similar to viral pharyngitis. There are some commercially available biosensors for the rapid diagnosis of streptococcal pharyngitis. Nevertheless, they are not widely used by physicians, mainly because of their high price and dependence on the instrument. Serotype M1 GAS is the most prevalent cause of streptococcal pharyngitis and binds to H-1 antigen, a sugar code found on oral epithelial cells. Here, we present a nanobiosensor based on aggregation of H-1 antigen-conjugated gold nanoparticles for the rapid, qualitative, and quantitative detection of M1 GAS, which is inspired by the sugar code-lectin interaction. It is noteworthy that M1 GAS was detected in a wide concentration range (1 × 103–1×106 CFU/ml) with a linear response and a short detection time of 20 min. Good reproducibility, easy-to-use, and relatively low production cost are among other attractive features of this nanobiosensor. This work provides a strategic roadmap for developing a new generation of biosensors via targeting the sugar code-lectin interaction in future studies.

Fabrication of a Microfluidic Test Device with a 3D Printer and Its Combination with the Loop Mediated Isothermal Amplification Method to Detect Streptococcus pyogenes

“…When the literature was reviewed for S. pyogenes detection with microfluidic device design, it was found that Huang et al developed a microfluidic PCR array system for different respiratory tract infection agents, including S. pyogenes , and reported that it had 100% sensitivity [ 29 ], but this test differed from our study in that it was a very complicated system and could not be used in POC detection. Unlike our study, Mohajeri et al developed a method for the diagnosis of S. pyogenes with nanoparticles and reported that they were able to detect it in 20 min [ 30 ]. It was found that there is no literature data on the detection of S. pyogenes in microfluidic devices designed with 3D printers.…”