Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

Sci Rep. 2021 Aug 10;11(1):16201. doi: 10.1038/s41598-021-95756-3.

Abstract

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·[Formula: see text]L-1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • HEK293 Cells
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Image Processing, Computer-Assisted / standards
  • Lentivirus / isolation & purification
  • Lentivirus / pathogenicity
  • Lentivirus Infections / diagnosis*
  • Lentivirus Infections / virology
  • Molecular Diagnostic Techniques / methods*
  • Molecular Diagnostic Techniques / standards
  • Point-of-Care Systems
  • Saliva / virology
  • Sensitivity and Specificity
  • Spectroscopy, Near-Infrared / methods*
  • Spectroscopy, Near-Infrared / standards

Grants and funding