Autoinducer 2 (AI-2) is a quorum sensing signal employed by bacteria to coordinate
their response to environmental stresses. The objective of this study was to determine the
relationship between presence of AI-2 molecules, exposure to sub-therapeutic tetracycline,
the expression of genes associated with the conjugal transfer of antibiotic resistance
plasmids, and the conjugal transfer of these plasmids in Escherichia coli. The studies showed
that AI-2 activity increased in Tets E. coli in the presence of tetracycline (2 õg/mL) under
both batch and continuous culture conditions. The presence of AI-2 molecules induced
tetracycline tolerance development in Tets E. coli. The studies showed that the survival rates
of Tets E. coli exposed to AI-2 molecules were significantly higher compared to the cells not
exposed to AI-2 molecules or cells that were exposed to only LB (Lauria-Bertani) broth.
Molecular analyses using real-time PCR indicate that the expression of at least one
conjugation-associated gene (trbC) is increased 9-fold in cells exposed to AI-2 molecules in
the presence of sub-therapeutic tetracycline compared to its negative controls. The
transconjugation frequency of the plasmid RP4 carrying the tet(A) gene increased between
10-100 fold in the presence of AI-2 molecules. In companion studies, AI-2-like activity was
detected in fish, tomatoes, cantaloupes, carrots and milk samples. Interestingly, ground beef
and poultry meat contained substances that appear to inhibit AI-2 activity. Collectively, these results highlight the potential importance of bacterial quorum sensing signals such as AI-2 in
the response of bacterial cells to environmental stimuli and the possible role of quorum
sensing signals in the quality and safety of foods.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4198 |
| Date | 30 October 2006 |
| Creators | Lu, Lingeng |
| Contributors | Pillai, Suresh D. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Dissertation, text |
| Format | 856918 bytes, electronic, application/pdf, born digital |
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