Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
Citació
- Gomez‑Gonzalez E, Fernandez‑Muñoz B, Barriga‑Rivera, A, Navas‑Garcia JM, Fernandez‑Lizaranzu I, Munoz‑Gonzalez FJ, Parrilla‑Giraldez R, Requena‑Lancharro D, Guerrero‑Claro M, Gil‑Gamboa P, Rosell‑Valle C, Gomez‑Gonzalez C, Mayorga‑Buiza MJ, Martin‑Lopez M, Muñoz O, Gomez Martin JC, Relimpio Lopez MI, Aceituno‑Castro J, Perales‑Esteve MA, Puppo‑Moreno A, Garcia Cozar FJ, Olvera‑Collantes L, de los Santos‑Trigo S, Gomez E, Sanchez Pernaute R, Padillo‑Ruiz J, Marquez‑Rivas J. Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples. Sci Rep. 2021;11:16201. DOI: 10.1038/s41598-021-95756-3
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Descripció
Resum
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·μ 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.