Researchers at Wayne State used rapid, reagent-less Raman based diagnostics for point-of-need pathogen detection

Posted by Wendy Wise on

Diseases such as Pandemic Influenza and COVID-19, among others, support the utility of rapid point-of-need field analysis of samples for respiratory pathogens. Researchers at Wayne State University used rapid, reagent-less Raman based diagnostics for point-of-need pathogen detection. Results took less than 2 minutes to display. The application of Raman spectroscopy in this context has the added benefit of not requiring primers, probes, or perishable detection materials. Combined with multiclass machine learning spectral analysis via Gradient Boosting Machine, accurate identification of SARS-CoV-2, human coronaviruses OC43, NL63, 229E, Influenza A (H1N1), respiratory syncytial virus, and Streptococcus pyogenes in spiked clinical nasal swab samples was demonstrated at 99% sensitivity and 93% specificity.

Link to the study in Biosensors and Bioelectronics: X, below. 

Counter-propagating Gaussian beam enhanced Raman spectroscopy for rapid reagentless detection of respiratory pathogens in nasal swab samples

Gregory W. Auner, S. Kiran Koya, Changhe Huang, Charles J. Shanley, Micaela Trexler, Sally Yurgelevic, Jake DeMeulemeester, Krista Bui, Kristen Amex-Sherer, Michelle A. Brusatori

September 13, 2022

Biosensors and Bioelectronics: X

Abstract:

Co-circulation of respiratory viruses compounded by similarities in clinical presentation and mode of transmission underscores the need for broad range pathogen detection. Accurate identification and diagnosis at the point-of-need is critical to limiting disease spread. A novel point-of-need Raman spectroscopy-based platform is described for rapid detection of multiple respiratory pathogens in nasal swab samples with high sensitivity and specificity. The system takes advantage of a counter-propagating Gaussian beam focused within the sample chamber that augments the Raman signal of pathogens. Combined with multiclass machine learning spectral analysis via Gradient Boosting Machine, accurate identification of SARS-CoV-2, human coronaviruses OC43, NL63, 229E, Influenza A (H1N1), respiratory syncytial virus, and Streptococcus pyogenes in spiked clinical nasal swab samples was demonstrated at 99% sensitivity and 93% specificity. The limit of detection was assessed using binary class Support Vector Machine with SARS-CoV-2 in nasal swab samples against negative control at 2.2 × 104 virions/swab. The spectrometer can be operated by minimally trained personnel with software-generated diagnostic yes/no results in 2 min or less, making it well suited for point-of-need applications. Furthermore, adaptive algorithms can detect and differentiate new and emerging variants using a Raman spectral database.

Innovative Research product used: https://www.innov-research.com/products/pooled-human-nasal-fluid


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