Characterization and discrimination of spike protein in SARS-CoV-2 virus-like particles via surface-enhanced Raman spectroscopy.

Non-infectious virus-like particles (VLPs) are excellent structures for development of many biomedical applications such as drug delivery systems, vaccine production platforms, and detection techniques for infectious diseases including SARS-CoV-2 VLPs. The characterization of biochemical and biophysical properties of purified VLPs is crucial for development of detection methods and therapeutics. The presence of spike (S) protein in their structure is especially important since S protein induces immunological response. In this study, development of a rapid, low-cost, and easy-to-use technique for both characterization and detection of S protein in the two VLPs, which are SARS-CoV-2 VLPs and HIV-based VLPs was achieved using surface-enhanced Raman spectroscopy (SERS). To analyze and classify datasets of SERS spectra obtained from the VLP groups, machine learning classification techniques including support vector machine (SVM), k-nearest neighbors (kNN), and random forest (RF) were utilized. Among them, the SVM classification algorithm demonstrated the best classification performance for SARS-CoV-2 VLPs and HIV-based VLPs groups with 87.5% and 92.5% accuracy, respectively. This study could be valuable for the rapid characterization of VLPs for the development of novel therapeutics or detection of structural proteins of viruses leading to a variety of infectious diseases.

Investigation of Gold Nanoparticle Naproxen-Derived Conjugations in Ovarian Cancer.

Ovarian cancer, which is one of the most diagnosed cancer types among women, maintains its significance as a global health problem. Several drug candidates have been investigated for the potential treatment of ovarian cancer. Nonsteroidal anti-inflammatory drugs (NSAIDs) demonstrated anti-cancer activity through the inhibition of cyclooxygenase 2 (COX-2) and by inhibiting COX-2-dependent prostaglandin (PG) production. Naproxen is one of the most used NSAIDs and Naproxen-derived compounds (NDCs) may show potential treatment effects on cancer as chemotherapeutic drugs. Although there are successful drug development studies, the lack of solubility of these drug candidates in aqueous media results in limited bioavailability and high variability of patient responses during treatment. Low aqueous solubility is one of the main problems in the pharmaceutical industry in terms of drug development. Nanotechnology-based strategies provide solutions to hydrophobic drug limitations by increasing dispersion and improving internalization. In this study, two different NDCs (NDC-1 and NDC-2) bearing a thiosemicarbazide/1,2,4-triazole moiety were synthesized and tested for chemotherapeutic effects on ovarian cancer cells, which have a high COX-2 expression. To overcome the limited dispersion of these hydrophobic drugs, the drug molecules were conjugated to the surface of 13 nm AuNPs. Conjugation of drugs to AuNPs increased the distribution of drugs in aqueous media, and NDC@AuNP conjugates exhibited excellent colloidal stability for up to 8 weeks. The proposed system demonstrated an increased chemotherapeutic effect than the free drug counterparts with at least 5 times lower IC50 values. NDC@AuNP nanosystems induced higher apoptosis rates, which established a simple and novel way to investigate activity of prospective drugs in drug discovery research.

Investigation of mammalian cells expressing SARS-CoV-2 proteins by surface-enhanced Raman scattering and multivariate analysis.

COVID-19 has caused millions of cases and deaths all over the world since late 2019. Rapid detection of the virus is crucial for controlling its spread through a population. COVID-19 is currently detected by nucleic acid-based tests and serological tests. However, these methods have limitations such as the requirement of high-cost reagents, false negative results and being time consuming. Surface-enhanced Raman scattering (SERS), which is a powerful technique that enhances the Raman signals of molecules using plasmonic nanostructures, can overcome these disadvantages. In this study, we developed a virus-infected cell model and analyzed this model by SERS combined with Principal Component Analysis (PCA). HEK293 cells were transfected with plasmids encoding the nucleocapsid (N), membrane (M) and envelope (E) proteins of SARS-CoV-2 via polyethyleneimine (PEI). Non-plasmid transfected HEK293 cells were used as the control group. Cellular uptake was optimized with green fluorescence protein (GFP) plasmids and evaluated by fluorescence microscopy and flow cytometry. The transfection efficiency was found to be around 60%. The expression of M, N, and E proteins was demonstrated by western blotting. The SERS spectra of the total proteins of transfected cells were obtained using a gold nanoparticle-based SERS substrate. Proteins of the transfected cells have peak positions at 646, 680, 713, 768, 780, 953, 1014, 1046, 1213, 1243, 1424, 2102, and 2124 cm-1. To reveal spectral differences between plasmid transfected cells and non-transfected control cells, PCA was applied to the spectra. The results demonstrated that SERS coupled with PCA might be a favorable and reliable way to develop a rapid, low-cost, and promising technique for the detection of COVID-19.