Worldwide, 3.575 million people die each year from water-related diseases. The water and sanitation crisis claims more lives than any warfare and is predicted to be one of the biggest global challenges of this century. The rapid, accurate detection of viral pathogens from environmental samples is an ongoing and pertinent challenge in biological engineering. Currently employed methods are lacking in either efficiency or specificity. Here we explore a novel method for virus detection and concurrently use this method to learn more about the very early stages of the virus infection process. The method combines Fourier transform infrared (FTIR) spectroscopy, a method of visualizing molecules based on changes in vibration of particles, and mammalian cells as the biosensor. This method is used to detect and investigate viruses from the family picornaviridae, chosen due to their public health burden and their widespread presence in environmental samples, especially water sources. This family includes the Polioviruses, echoviruses and Coxsackieviruses, among others, many of which are human pathogens.The research outlined in this dissertation is aimed at developing and implementing a new cell-based biosensor that combines the advantages of FTIR spectroscopy with the ability of buffalo green monkey kidney (BGMK) cells to sense diverse stimuli, including infective enteroviruses. The goal of developing this biosensor is outlined in the first paper. The second paper focuses on the application of advanced statistical methods to analyze the spectra to discriminate different viral infections in BGMK cells. Finally, we designed a non-reactive metal biochamber to use with attenuated total reflectance-FTIR. This allowed near-continuous acquisition of real-time spectral data for the study of biochemical changes in mammalian cells caused by poliovirus (PV1) infection. This system is capable of tracking changes in cell biochemistry in minute intervals for many hours at a time.This work demonstrates the feasibility of FTIR spectroscopy in combination with the broad sensitivity of mammalian cells for potential use in the detection of infective viruses from environmental samples. We envision this method being extended to high throughput, automated systems to screen for viruses or other toxins in drinking water systems and medical applications.

BACKGROUND: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.