Raman spectroscopy‐based detection of RNA viruses in saliva: A preliminary report. Issue 10 (10th August 2020)

• Record Type: Journal Article
• Authors: Desai, Sanket; Mishra, Saket V.; Joshi, Asim; Sarkar, Debashmita; Hole, Arti; Mishra, Rohit; Dutt, Shilpee; Chilakapati, Murali K.; Gupta, Sudeep; Dutt, Amit
• Is Part Of: Journal of biophotonics. Volume 13:Issue 10(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-10
• Subjects: GUI‐based automated computational analysis -- linear discriminant analysis -- principal component analysis -- Raman spectroscopy -- RNA virus; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.202000189
• Languages: English
• ISSNs: 1864-063X

Abstract

Abstract: Several non‐invasive Raman spectroscopy‐based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI‐based analytical tool "RNA Virus Detector (RVD)." This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID‐19 pandemic. (http://www.actrec.gov.in/pi-webpages/AmitDutt/RVD/RVD.html ). Abstract : Non‐invasive low‐cost diagnostic tests capable of detecting pathogens at the point of care could play a significant role in early diagnosis. We present a proof of concept using Raman spectroscopy to detect a distinct RNA viral signature in human saliva, with potential for application to the COVID‐19 pandemic.