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

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 t...

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Autores principales:	Emilio Gomez-Gonzalez, Beatriz Fernandez-Muñoz, Alejandro Barriga-Rivera, Jose Manuel Navas-Garcia, Isabel Fernandez-Lizaranzu, Francisco Javier Munoz-Gonzalez, Ruben Parrilla-Giraldez, Desiree Requena-Lancharro, Manuel Guerrero-Claro, Pedro Gil-Gamboa, Cristina Rosell-Valle, Carmen Gomez-Gonzalez, Maria Jose Mayorga-Buiza, Maria Martin-Lopez, Olga Muñoz, Juan Carlos Gomez Martin, Maria Isabel Relimpio Lopez, Jesus Aceituno-Castro, Manuel A. Perales-Esteve, Antonio Puppo-Moreno, Francisco Jose Garcia Cozar, Lucia Olvera-Collantes, Silvia de los Santos-Trigo, Emilia Gomez, Rosario Sanchez Pernaute, Javier Padillo-Ruiz, Javier Marquez-Rivas
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3a251ef5366b445c991b7434204b733f
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spelling	oai:doaj.org-article:3a251ef5366b445c991b7434204b733f2021-12-02T19:06:33ZHyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples10.1038/s41598-021-95756-32045-2322https://doaj.org/article/3a251ef5366b445c991b7434204b733f2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95756-3https://doaj.org/toc/2045-2322Abstract 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· $$\upmu$$ 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.Emilio Gomez-GonzalezBeatriz Fernandez-MuñozAlejandro Barriga-RiveraJose Manuel Navas-GarciaIsabel Fernandez-LizaranzuFrancisco Javier Munoz-GonzalezRuben Parrilla-GiraldezDesiree Requena-LancharroManuel Guerrero-ClaroPedro Gil-GamboaCristina Rosell-ValleCarmen Gomez-GonzalezMaria Jose Mayorga-BuizaMaria Martin-LopezOlga MuñozJuan Carlos Gomez MartinMaria Isabel Relimpio LopezJesus Aceituno-CastroManuel A. Perales-EsteveAntonio Puppo-MorenoFrancisco Jose Garcia CozarLucia Olvera-CollantesSilvia de los Santos-TrigoEmilia GomezRosario Sanchez PernauteJavier Padillo-RuizJavier Marquez-RivasNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Emilio Gomez-Gonzalez Beatriz Fernandez-Muñoz Alejandro Barriga-Rivera Jose Manuel Navas-Garcia Isabel Fernandez-Lizaranzu Francisco Javier Munoz-Gonzalez Ruben Parrilla-Giraldez Desiree Requena-Lancharro Manuel Guerrero-Claro Pedro Gil-Gamboa Cristina Rosell-Valle Carmen Gomez-Gonzalez Maria Jose Mayorga-Buiza Maria Martin-Lopez Olga Muñoz Juan Carlos Gomez Martin Maria Isabel Relimpio Lopez Jesus Aceituno-Castro Manuel A. Perales-Esteve Antonio Puppo-Moreno Francisco Jose Garcia Cozar Lucia Olvera-Collantes Silvia de los Santos-Trigo Emilia Gomez Rosario Sanchez Pernaute Javier Padillo-Ruiz Javier Marquez-Rivas Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
description	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· $$\upmu$$ 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.
format	article
author	Emilio Gomez-Gonzalez Beatriz Fernandez-Muñoz Alejandro Barriga-Rivera Jose Manuel Navas-Garcia Isabel Fernandez-Lizaranzu Francisco Javier Munoz-Gonzalez Ruben Parrilla-Giraldez Desiree Requena-Lancharro Manuel Guerrero-Claro Pedro Gil-Gamboa Cristina Rosell-Valle Carmen Gomez-Gonzalez Maria Jose Mayorga-Buiza Maria Martin-Lopez Olga Muñoz Juan Carlos Gomez Martin Maria Isabel Relimpio Lopez Jesus Aceituno-Castro Manuel A. Perales-Esteve Antonio Puppo-Moreno Francisco Jose Garcia Cozar Lucia Olvera-Collantes Silvia de los Santos-Trigo Emilia Gomez Rosario Sanchez Pernaute Javier Padillo-Ruiz Javier Marquez-Rivas
author_facet	Emilio Gomez-Gonzalez Beatriz Fernandez-Muñoz Alejandro Barriga-Rivera Jose Manuel Navas-Garcia Isabel Fernandez-Lizaranzu Francisco Javier Munoz-Gonzalez Ruben Parrilla-Giraldez Desiree Requena-Lancharro Manuel Guerrero-Claro Pedro Gil-Gamboa Cristina Rosell-Valle Carmen Gomez-Gonzalez Maria Jose Mayorga-Buiza Maria Martin-Lopez Olga Muñoz Juan Carlos Gomez Martin Maria Isabel Relimpio Lopez Jesus Aceituno-Castro Manuel A. Perales-Esteve Antonio Puppo-Moreno Francisco Jose Garcia Cozar Lucia Olvera-Collantes Silvia de los Santos-Trigo Emilia Gomez Rosario Sanchez Pernaute Javier Padillo-Ruiz Javier Marquez-Rivas
author_sort	Emilio Gomez-Gonzalez
title	Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
title_short	Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
title_full	Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
title_fullStr	Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
title_full_unstemmed	Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
title_sort	hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3a251ef5366b445c991b7434204b733f
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Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

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