Date of Award

3-2-2021

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Physics

First Advisor

Steven J. Rehse

Keywords

Bacteria, Discrimination, Enhancement, Laser, LIBS, Plasma

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

Bacterial pathogens can be differentiated via an elemental analysis techniqueknown as laser-induced breakdown spectroscopy (LIBS). This spectrochemical technique provides a near-instantaneous measurement of the elemental composition of a target. The aim of this work was to demonstrate the feasibility of LIBS for the rapid identification and discrimination of bacteria in simulated clinical specimens based on reproducible differences in the concentration of inorganic elements in bacterial cells. This research will describe the current experimental technique, including bacteria collection and mounting protocols, LIBS data acquisition, and spectral data analysis. These include methods for the collection, concentration, and separation of bacteria from unwanted biological matter, deposition of bacterial cells on a suitable ablation medium, the formation of high temperature laser-induced micro plasmas, collection, and analysis of the atomic emission spectra with a high-resolution spectrometer, and the differentiation of LIBS emission spectra from different bacterial species and genera using computerized chemometric algorithms. The construction of a spectral library database containing the LIBS emission spectra from hundreds of spectra obtained from highly diluted specimens of Staphylococcus epidermidis, Escherichia coli, Mycobacterium smegmatis, Pseudomonas aeruginosa, Enterococcus cloacae and sterile water control specimens is ongoing. Manipulation of this library with outlier elimination techniques, reduction of elemental contaminants contributing to extraneous background signals, and the addition of silver microparticles to enhance signal intensities are all being investigated to produce a standardized protocol that minimizes the bacterial limit of detection while maximizing classification accuracy.

Share

COinS