{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/29330"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/29330","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Surface Enhanced Raman Spectroscopy as a Tool for Waterborne Pathogen Testing","abstract":"The development of a waterborne pathogen detection method that is rapid, multiplex, sensitive, and specific, would be of great assistance for water treatment facilities and would help protect water consumers from harmful pathogens. Here we have utilized surface enhanced Raman spectroscopy (SERS) in a sensitive multiplex pathogen detection method. Two strategies are proposed herein, one that utilizes SERS antibody labels and one that measures the intrinsic SERS signal of organisms. For the SERS label strategy, gold nanoparticles are conjugated with antibodies specific to Cryptosporidium parvum and Giardia lamblia and with organic dye molecules. The dye molecules, rhodamine B isothiocyanate (RBITC) and malachite green isothiocyanate (MGITC) were surface enhanced by the gold nanoparticles resulting in unique fingerprint SERS spectra. The SERS label method was successful in detecting G. lamblia and C. parvum simultaneously. The method was subsequently coupled with a filtration step to both concentrate and capture cysts on a flat surface for detection. Raman mapping across the filter membrane detected ~95% of the spiked cysts in the optimized system. In the second type of strategy, intrinsic virus SERS signals were detected with silver nanoparticles for enhancement. Principal component analysis performed on the spectra data set resulted in the successful differentiation of MS2 and PhiX174 species and also for the differentiation of viable virus samples and inactivated virus samples.","abstract_html":"The development of a waterborne pathogen detection method that is rapid, multiplex, sensitive, and specific, would be of great assistance for water treatment facilities and would help protect water consumers from harmful pathogens. Here we have utilized surface enhanced Raman spectroscopy (SERS) in a sensitive multiplex pathogen detection method. Two strategies are proposed herein, one that utilizes SERS antibody labels and one that measures the intrinsic SERS signal of organisms. For the SERS label strategy, gold nanoparticles are conjugated with antibodies specific to Cryptosporidium parvum and Giardia lamblia and with organic dye molecules. The dye molecules, rhodamine B isothiocyanate (RBITC) and malachite green isothiocyanate (MGITC) were surface enhanced by the gold nanoparticles resulting in unique fingerprint SERS spectra. The SERS label method was successful in detecting G. lamblia and C. parvum simultaneously. The method was subsequently coupled with a filtration step to both concentrate and capture cysts on a flat surface for detection. Raman mapping across the filter membrane detected ~95% of the spiked cysts in the optimized system. In the second type of strategy, intrinsic virus SERS signals were detected with silver nanoparticles for enhancement. Principal component analysis performed on the spectra data set resulted in the successful differentiation of MS2 and PhiX174 species and also for the differentiation of viable virus samples and inactivated virus samples.","abstract_has_math":false,"creators":["Wigginton, Krista Rule"],"institution":"Virginia Tech","degree_name":"Ph. 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Here we have utilized surface enhanced Raman spectroscopy (SERS) in a sensitive multiplex pathogen detection method. Two strategies are proposed herein, one that utilizes SERS antibody labels and one that measures the intrinsic SERS signal of organisms. For the SERS label strategy, gold nanoparticles are conjugated with antibodies specific to Cryptosporidium parvum and Giardia lamblia and with organic dye molecules. The dye molecules, rhodamine B isothiocyanate (RBITC) and malachite green isothiocyanate (MGITC) were surface enhanced by the gold nanoparticles resulting in unique fingerprint SERS spectra. The SERS label method was successful in detecting G. lamblia and C. parvum simultaneously. The method was subsequently coupled with a filtration step to both concentrate and capture cysts on a flat surface for detection. Raman mapping across the filter membrane detected ~95% of the spiked cysts in the optimized system. In the second type of strategy, intrinsic virus SERS signals were detected with silver nanoparticles for enhancement. Principal component analysis performed on the spectra data set resulted in the successful differentiation of MS2 and PhiX174 species and also for the differentiation of viable virus samples and inactivated virus samples."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. 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