Pseudomonas syringae pv. syringae B728a, an aggressive bacterial pathogen of bean, utilizes large surface populations and extracellular signaling to initiate a fundamental change from an epiphytic to a pathogenic lifestyle. Extracytoplasmic function (ECF) sigma (σ) factors serve as important regulatory factors in responding to various environmental signals. Bioinformatic analysis of the B728a genome has revealed 10 ECF sigma factors, five of which have high levels of sequence similarity to the FecI-type of ECF sigma factors and play a known role in the regulation of various iron transport systems. Because iron is essential for the induction of major virulence factors in B728a, I hypothesized that these FecI-type sigma factors may play a critical role in the bacterium’s transition between lifestyles. Deletion mutants of two FecI-type sigma factors, Psyr_1040 and Psyr_1107, in B728a have been created using homologous recombination based on the phage λ Red recombinase method.
This study shows that the B728a FecI-type sigma factors, Psyr_1040 and Psyr_1107 are affected by conditions of iron stress, and influence the expression of putative outer membrane receptors and transmembrane sensors associated with these genes. Moreover, Psyr_1107 contributes to the expression of a cluster of predicted pili assembly genes downstream of it. Mutations in Psyr_1040 and Psyr_1107 affect the population levels of B728a in bean plants, since in planta growth of deletion mutants of B728a lacking Psyr_1040 and Psyr_1107 appears to be slower than wild-type B728a. In this thesis, the possible roles of Psyr_1040 and Psyr_1107 in the adaptation of B728a to a pathogenic lifestyle are addressed using a combination of phenotypic characterization and quantitative real-time PCR (qRT-PCR) analyses.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/149216 |
| Date | 02 October 2013 |
| Creators | Basu Thakur, Poulami |
| Contributors | Gross, Dennis C, Yuan, Joshua S, Pierson, Elizabeth A |
| Source Sets | Texas A and M University |
| Detected Language | English |
| Type | Thesis, text |
| Format | application/pdf |
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