Year of Publication

2014

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Agriculture, Food and Environment

Department

Animal and Food Sciences

First Advisor

Dr. Clair Hicks

Abstract

The objective of this study was to determine if acoustic emissions (AE) generated by three strains of Escherichia Coli (5024-parent strain, 8279-mutant strain and 8279-random/unrelated strain) could be used to differentiate each strain during their growth cycle. An acoustic sensor with an operating range of 35 kHz-100 kHz was inserted into the growth vessel and attached to a selected channel to capture AE data. The growth vessel was loaded with 60 ml of tryptic soy broth (TSB) (0.25% fructose) media with alginate (1.1%) or without alginate and inoculated with 1% (108 CFU/ml) of an E. coli strain. The growth vessel was placed in a monitoring chamber and incubated at 32°C for 8-9 h. The AE’s generated by each strain were collected throughout the growth cycle. All strains grown in media with and without alginate generated AE’s within 5 min post inoculation. Strains grown in media without alginate generated stronger (P < 0.0001) absolute energy (ABSE) and higher peak frequencies (PFRQ’s), than in media with alginate. The AE’s generated by strains 5024 and 8237 were stronger and easily distinguished from those generated by strain 8279. Strain 8237 generated 12% stronger ABSE from the 3rd to 8th h and 51% stronger PFRQ intensities than strain 5024 during 0-8 h. However, strain 5024 generated 15% stronger ABSE and 31% higher PFRQ’s during the final hour of growth. Strain 5024 generated the highest PFRQ’s from 5-50 kHz, while strain 8237 generated higher frequencies from 100-500 kHz. Fourteen distinguishable differences (P< 0.05) in generated PFRQ’s, between strains 5024 and 8237, were also observed in every 5 kHz increments from 100-500 kHz. Of these differences, strain 8237 generated higher frequencies within eight of the kHz ranges, while strain 5024 generated higher frequencies within six other kHz ranges. These data suggests that all bacteria may generate different AE’s, thus producing a unique “fingerprint” of sound that will allow for its identification.

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