Project description:We characterized transcriptomes of a Sinorhizobium meliloti wild type strain (CL150) expressing either Ca. Liberibacter asiaticus ctrA or Sinorhizobium meliloti ctrA
Project description:We wanted to test the effect on global gene expression of depleting the essential cell cycle regulator CtrA in order to determine the genes both indirectly and directly transcriptionally regulated by CtrA Gene expression changes in S. meliloti 1,2,4 and 6 hours post CtrA depletion Log-phase S. meliloti cultures carrying an IPTG-inducible allele of CtrA were split and transferred to growth media lacking IPTG (depletion) and with 1mM IPTG (control). Samples for RNA extraction were taken 1,2,4, and 6 hours after the start of the depletion experiment to monitor gene expression changes in the population after different periods of CtrA depletion.
Project description:We wanted to test the effect on global gene expression of depleting the essential cell cycle regulator CtrA in order to determine the genes both indirectly and directly transcriptionally regulated by CtrA Gene expression changes in S. meliloti 1,2,4 and 6 hours post CtrA depletion
Project description:In α-proteobacteria, strict regulation of cell cycle progression is necessary for the specific cellular differentiation required for adaptation to diverse environmental niches. The symbiotic lifestyle of Sinorhizobium meliloti requires a drastic cellular differentiation that includes genome amplification. To achieve polyploidy, the S. meliloti cell cycle program must be altered to uncouple DNA replication from cell division. In the α-proteobacterium Caulobacter crescentus, cell cycle regulated transcription plays an important role in control of cell cycle progression but this has not been demonstrated in other α-proteobacteria. Here we describe a robust method for synchronizing cell growth that enabled the first global analysis of S. meliloti cell cycle regulated gene expression. The objective of the microarray-based cell cycle gene expression analysis was to determine which genes were transcriptionally regulated as a funciton of a cell cycle in order to understand the contribution of transcriptional regulation to the timing of cell cycle events. The microarray analysis identified 462 genes with cell cycle regulated transcripts, including several key cell cycle regulators, and genes involved in motility, attachment, and cell division. Only 28% of the 462 S. meliloti cell cycle regulated genes were also transcriptionally cell cycle regulated in C. crescentus. Furthermore, CtrA and DnaA binding motif analysis revealed little overlap between the cell cycle-dependent regulons of CtrA and DnaA in S. meliloti and C. crescentus. The predicted S. meliloti cell cycle regulon of CtrA, but not that of DnaA, was strongly conserved in more closely related α-proteobacteria with similar ecological niches as S. meliloti, suggesting that the CtrA cell cycle regulatory network may control functions of central importance to the specific lifestyles of α-proteobacteria. Gene expression levels were quantified in synchronously growing S. meliloti cultures across 8 time points and compared to gene expression levels in unsynchronized culture via a two-color custom agilent array
Project description:Within this work we identified and characterized SMc03169 (hhrA) as a new Sinorhizobium meliloti gene product with relevance to biological nitrogen fixation symbiosis with leguminous plants. HhrA belongs to the TetR-family of repressors and its deletion from S. meliloti genome affected considerably gene expression as well as several phenotypic traits.
Project description:In α-proteobacteria, strict regulation of cell cycle progression is necessary for the specific cellular differentiation required for adaptation to diverse environmental niches. The symbiotic lifestyle of Sinorhizobium meliloti requires a drastic cellular differentiation that includes genome amplification. To achieve polyploidy, the S. meliloti cell cycle program must be altered to uncouple DNA replication from cell division. In the α-proteobacterium Caulobacter crescentus, cell cycle regulated transcription plays an important role in control of cell cycle progression but this has not been demonstrated in other α-proteobacteria. Here we describe a robust method for synchronizing cell growth that enabled the first global analysis of S. meliloti cell cycle regulated gene expression. The objective of the microarray-based cell cycle gene expression analysis was to determine which genes were transcriptionally regulated as a funciton of a cell cycle in order to understand the contribution of transcriptional regulation to the timing of cell cycle events. The microarray analysis identified 462 genes with cell cycle regulated transcripts, including several key cell cycle regulators, and genes involved in motility, attachment, and cell division. Only 28% of the 462 S. meliloti cell cycle regulated genes were also transcriptionally cell cycle regulated in C. crescentus. Furthermore, CtrA and DnaA binding motif analysis revealed little overlap between the cell cycle-dependent regulons of CtrA and DnaA in S. meliloti and C. crescentus. The predicted S. meliloti cell cycle regulon of CtrA, but not that of DnaA, was strongly conserved in more closely related α-proteobacteria with similar ecological niches as S. meliloti, suggesting that the CtrA cell cycle regulatory network may control functions of central importance to the specific lifestyles of α-proteobacteria. Gene expression levels were quantified in synchronously growing S. meliloti cultures across 8 time points and compared to gene expression levels in unsynchronized culture via a two-color custom agilent array A two-color array format was used with time point from synchronous culture being competed with a sample from unsynchronized culture (control same for all arrays) to determine the cell cycle-phase specific induction or repression of genes relative to batch culture which contains cells in all phases of the cell cycle. For each of the 8 cell cycle time points, four biological replicates were used resulting in 4 arrays per time point and a total of 32 arrays. The arrays also contained duplicates of each probe resulting in two technical replicates per biological replicate per time point.