Pathogenic microbial contamination of the environment poses a significant threat to human health. Accordingly, microbial surveillance is needed to ensure safe drinking water and air quality. Current analytical methods for microbes are generally either culture-based, gene amplification-based, or sequencing-based. However, these approaches require centralized facilities, well-trained personnel, and specialized instruments that result in high costs and long turnaround times. Surface-enhanced Raman spectroscopy (SERS)-based techniques have been proposed to overcome these limitations. In this dissertation, we discuss work conducted to develop novel SERS-based methods to enable both sensitive microbial quantification and analysis of the interactions of pathogens, their hosts, and the surrounding environment. We first developed a labeled SERS-based lateral flow test for virus quantification. Optimization of the lateral flow design and digital signal analysis enabled high sensitivity towards SARS-CoV-2. To elicit a comprehensive understanding of pathogen infection, label-free living-cell SERS sensors were engineered by incubating host cells with nanoparticles. SERS spectral changes in host cellular components and metabolites during infection were used for viral quantification and offered inherent insights into the temporal and spatial molecular-level mechanisms of infection. These biosensors were validated using bacteriophage Phi6 and then developed for infectious H1N1 influenza. To understand microbial survival in the environment, living-cell SERS methods were applied under various conditions. Results showed cell inactivation and antibiotic treatment induced significant cellular and metabolic responses in the living whole-cell sensors, implying their potential applicability to various environmental conditions. Our research achieves rapid and on-site pathogen quantification and infection mechanism identification. / Doctor of Philosophy / Pathogenic microbes, such as the SARS-CoV-2 virus, can spread through air and water and are potentially harmful to human health. Monitoring the concentrations of these microbes in the environment is crucial to track their presence and provide an early warning of their spread. Unfortunately, current microbial detection methods are often expensive and take a long time since they typically require professional facilities and expert elicitation. Our research relies on a technique called surface-enhanced Raman spectroscopy (SERS) to address these challenges. SERS enables identification and quantification of microbes by analyzing specific features (i.e., peak position, peak intensity) in the spectra. We first applied this technique by modifying a commercial SARS-CoV-2 antigen test kit with a label molecule that provides SERS signals. We achieve accurate and sensitive quantification, even in the presence of high levels of environmental interference. To better understand how these harmful microbes interact with our bodies, we developed sensors that can measure SERS signal changes in host cells before and after infection. These sensors were tested using the bacteriophage virus Phi6 that infects bacteria and infectious H1N1 influenza virus. Furthermore, we applied these sensors to study how bacteria respond to different environmental conditions, providing valuable insights into their survival and behavior under various conditions. In summary, our research introduces methods that are more accessible to identify and quantify harmful microbes that can be potentially used by the general public. The methods provide us with molecular level understanding of pathogen interactions with humans and the environment.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/118270 |
| Date | 04 March 2024 |
| Creators | Wang, Wei |
| Contributors | Civil and Environmental Engineering, Vikesland, Peter J., Isaacman-VanWertz, Gabriel, Marr, Linsey C., Zhou, Wei |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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