Detection and quantification of poliovirus infection using FTIR spectroscopy and cell culture
AffiliationAgricultural and Biosystems Engineering, University of Arizona, Tucson, Arizona, USA 85721
Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA 85724
Fourier Transform Infrared (FTIR) spectroscopy
zinc selenide (ZnSe)
partial least squares
buffalo green monkey kidney (BGMK) cells
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CitationLee-Montiel et al. Journal of Biological Engineering 2011, 5:16 http://www.jbioleng.org/content/5/1/16
Rights© 2011 Lee-Montiel et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)
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AbstractBACKGROUND:In a globalized word, prevention of infectious diseases is a major challenge. Rapid detection of viable virus particles in water and other environmental samples is essential to public health risk assessment, homeland security and environmental protection. Current virus detection methods, especially assessing viral infectivity, are complex and time-consuming, making point-of-care detection a challenge. Faster, more sensitive, highly specific methods are needed to quantify potentially hazardous viral pathogens and to determine if suspected materials contain viable viral particles. Fourier transform infrared (FTIR) spectroscopy combined with cellular-based sensing, may offer a precise way to detect specific viruses. This approach utilizes infrared light to monitor changes in molecular components of cells by tracking changes in absorbance patterns produced following virus infection. In this work poliovirus (PV1) was used to evaluate the utility of FTIR spectroscopy with cell culture for rapid detection of infective virus particles.RESULTS:Buffalo green monkey kidney (BGMK) cells infected with different virus titers were studied at 1 - 12 hours post-infection (h.p.i.). A partial least squares (PLS) regression method was used to analyze and model cellular responses to different infection titers and times post-infection. The model performs best at 8 h.p.i., resulting in an estimated root mean square error of cross validation (RMSECV) of 17 plaque forming units (PFU)/ml when using low titers of infection of 10 and 100 PFU/ml. Higher titers, from 103 to 106 PFU/ml, could also be reliably detected.CONCLUSIONS:This approach to poliovirus detection and quantification using FTIR spectroscopy and cell culture could potentially be extended to compare biochemical cell responses to infection with different viruses. This virus detection method could feasibly be adapted to an automated scheme for use in areas such as water safety monitoring and medical diagnostics.
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