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The Use of Microfluidics and Dielectrophoresis for Separation, Concentration, and Identification of Bacteria

Typical bacterial analysis involves culturing and visualizing colonies on an array of agar plates. The growth patterns and colors among the array are used to identify the bacteria. For fast growing bacteria such as Escherichia coli, analysis will take one to two days. However, slow growing bacteria such as mycobacteria can take weeks to identify. In addition, there are some species of bacteria that are viable but nonculturable. This lengthy analysis time is unacceptable for life-threatening infections and emergency situations. It is clear that to decrease the analysis of the bacteria, the culturing and growth steps must be avoided. The goal of this research is to design, build, and test a device that could decrease the analysis time of bacteria.
Device design accommodates for the varied growth and environmental conditions of expected samples for bacterial analysis. Clinical samples containing bacteria come in a wide variety of forms including urine, saliva, sputum, blood, etc. Each medium will have associated debris and other contaminants that must be isolated from bacteria before identification. This process can be challenging as bacteria and debris can range in size from a fraction of a micrometer to tens of micrometers. In addition, a device must be equipped to accurately identify bacteria regardless of growth conditions. Thus, to decrease the analysis time of bacteria, a device must be capable of isolation, concentration, and identification at a micron level.
In this dissertation, a device was designed, built, and tested that incorporates dielectrophoresis for cell sorting and Raman spectroscopy for identification. Using the device, bacteria (1 μm in length) were successfully isolated away from 5 μm polystyrene spheres and Raman spectra of the trapped bacteria were collected. The simultaneous isolation and identification of bacteria from a mixed sample indicates the capability for the cDEP-Raman device to decrease the analysis time of bacteria from clinical samples.

Identiferoai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-8151
Date01 May 2018
CreatorsHanson, Cynthia
PublisherDigitalCommons@USU
Source SetsUtah State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceAll Graduate Theses and Dissertations
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