Detection of Environmental Contaminants in Water Utilizing Raman Scanning for E. coli Phenotype Changes
Flick, Hunter James
MetadataShow full item record
Raman spectroscopy and its counterpart surface-enhanced Raman scattering (SERS) have proven to be effective methods for detecting miniscule changes in the phenotypes of E. coli and other single-celled organisms to aid in the detection of new strains for industrial use and discovery of new antibiotics. The purpose of this study is to develop a method to quickly and accurately detect contaminants in water samples through phenotype changes in E. coli measured through SERS. Contaminated Luria-Bertani (LB) media was inoculated with LB with an OD600 of 1, grown for two hours, and then dried on a flat piece of aluminum foil. These samples were then Raman scanned and processed to determine contaminant-induced changes to the phenotypes of the E. coli. Three types of tests were run to show the effectiveness of this method: single-component, multicomponent, and impure water sources. In single-component tests, it was found that differences due to NaCl contamination could be detected to 5.0E-9 weight percent (wt %), ethanol (EtOH) to 5.0E-7 volumetric percent (% v/v), citric acid (CA) to 2.8E-4 wt %, acetic acid (AA) to 2.6E-4 wt %, kanamycin to 2.5E-11 wt %, ampicillin to 2.5E-10 wt %, CoCl2 to trace amounts, and silver nanoparticles (AgNP) to 5.2E-7 wt %. Many of these are below the detection limits of analytical instrumentation, but their effects on E. coli phenotypes were detectable by Raman spectroscopy. Multicomponent tests showed that in a mixture, the most toxic or most concentrated contaminants have the most effect on cell phenotype. However, it was shown that similar concentrations of similar contaminants may be difficult to discern with current methods. This behavior was also seen in the impure water samples, showing that tap water behaves the closest to a DI control, followed by running water, and finally stagnant bodies. This new method of monitoring E. coli phenotypes with Raman spectroscopy as a biosensor shows promise for the fast, portable, and accurate determination of environmental contaminants with a broad-spectrum and very low detection limits.
General Audience Abstract
Recently, Raman spectroscopy and an enhanced version called surface-enhanced Raman scattering (SERS) have shown promise in showing the effects of a cell’s environment on how it expresses genes and what chemical compounds it produces to survive. It does this through reading the chemical signature it gives off due to these changes, and these readings have been used for showing the effects of antibiotics, finding varieties that are resistant to toxic byproducts of their activities, and as biosensors. The study outlined in this thesis aims to develop a test utilizing SERS to see the reactions of a non-pathogenic strain of E. coli to contaminants in their media and determine their identity. This test was run for three types of contaminated samples: one contaminant, three contaminants, and tests using impure water from a sink tap, a pond, and a stream. For the single contaminants, eight types were tested; NaCl, ethanol, citric acid, acetic acid (AA), kanamycin, ampicillin, CoCl2, and silver nanoparticles. Detection limits for all contaminants were found, with the lowest detectable concentrations all falling below or matching detection limits of common methods. The lowest detectable concentrations came from kanamycin and CoCl2, at 2.5E-11 weight percent and in amounts which are considered beneficial to the environment, respectively. The three-contaminant test shows that it is possible to pinpoint which contaminants are having the highest effect, though if contaminants are similar in nature and in similar concentrations, it may be difficult to pinpoint which is causing the effect. In the final test, similarity of water sources to pure water were found, with tap water being closest, followed by stream water and the most different being pond water. It was also found that pond water and stream water were closest in behavior, showing the power of this method in differentiating sources from each other.
- Masters Theses