Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
Emilio Gómez-González, Beatriz Fernández‐Muñoz, Alejandro Barriga‐Rivera, Jose Manuel Navas-Garcia, Isabel Fernández-Lizaranzu, Francisco Javier Munoz-Gonzalez, Rubén Parrilla Giráldez, Desirée Requena-Lancharro, Manuel Guerrero-Claro, Pedro Gil-Gamboa, Cristina Rosell‐Valle, Carmen Gómez-González, María José Mayorga-Buiza, María Martín-López, Olga Muñoz, Juan Carlos Gómez Martı́n, María Isabel López, Jesus Aceituno-Castro, Manuel A. Perales‐Esteve, Antonio Puppo-Moreno, Francisco Garcı́a-Cózar, Lucia Olvera-Collantes, Silvia de los Santos-Trigo, Emília Gómez, Rosario Sánchez‐Pernaute, Javier Padillo–Ruiz, Javier Márquez-Rivas
Abstract
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· $$\upmu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> 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.