Antibiotic resistance is a worsening threat to human health. Increasing our understanding of the mechanisms causing this resistance will be of great benefit in designing methods to evade resistance and in developing new classes of antibiotics. In this thesis, I have used the TetR Family Transcriptional Regulators (TFRs), which constitute one of the largest antibiotic resistance regulator families, as a model system to study the structure, function and evolution of antibiotic resistance determinants. I performed a thorough examination of the variation and conservation seen in TFR sequences and structures using computational approaches. Through structure comparison, I have identified the most conserved features shared by the TFR family that are crucial for their stability and function. Based on my findings on conserved TFR structural features, a quantitative assay of binding affinity determination was developed. Through sequence comparison and a residue contact map method, I discovered the existence of a conserved residue network that correlates well with the known allostery pathway of TetR. This predicted allosteric communication network was experimentally tested in TtgR. I have also developed methods to identify TFR operator sequences through genomic comparisons and validated my prediction through experiments. In addition, I have developed an in vivo system that can be used to identify and characterize proteins that mediate resistance to almost any antibiotic. This system is simple, fast, and scalable for high-throughput applications, and could be used to discover a wide range of novel antibiotic resistance mechanisms. The principles that I applied to the TFR family could also be applied to other protein families.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/24388 |
| Date | 21 April 2010 |
| Creators | Yu, Zhou |
| Contributors | Davidson, Alan R. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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