Escherichia coli
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA407221 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6038179_1.fastq.gz | Fastqsanger.gz | |||
| SRR6038179_2.fastq.gz | Fastqsanger.gz |
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Project description:Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows exclusively in the xylem of several plants, causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time-course experiment (2, 8 and 12 hours) revealed many differentially expressed genes under nitrogen starvation, such as genes related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes induced by nitrogen starvation in a σ54-dependent manner. A more complete picture of the σ54 regulon was achieved by combining the transcriptome data with an in silico search for potential σ54-dependent promoters, using a position weight matrix approach. One of these σ54-predicted binding sites, located upstream of the glnA gene (encoding a glutamine synthetase), was validated by primer extension assays, confirming that this gene has a σ54-dependent promoter and contains a predicted NtrC binding site. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the σ54 regulon.
2010-12-21 | GSE21647 | GEO
Project description:Promoters play a central role in controlling gene regulation; however, a small set of promoters is used for most genetic construct design in the yeast Saccharomyces cerevisiae. The ability to generate and utilize models that accurately predict protein expression from promoter sequence may enable rapid generation of novel useful promoters, facilitating synthetic biology efforts in this model organism. We measured the activity of over 675,000 unique sequences in a constitutive promoter library, and over 327,000 sequences in a library of inducible promoters. Training an ensemble of convolutional neural networks jointly on the two datasets enabled very high (R2 > 0.79) predictive accuracies on multiple prediction tasks. We developed model-guided design strategies which yielded large, sequence-diverse sets of novel promoters exhibiting activities similar to current best-in-class sequences. In addition to providing large sets of new promoters, our results show the value of model-guided design as an approach for generating DNA parts.
2019-12-01 | GSE135464 | GEO
Project description:Cellular transcription enables cells to adapt to various stimuli and maintain homeostasis. Transcription factors bind to transcription response elements (TREs) in gene promoters, initiating transcription. Synthetic promoters, derived from natural TREs, can be engineered to control exogenous gene expression using endogenous transcription machinery. This technology has found extensive use in biological research for applications including reporter gene assays, biomarker development, and programming synthetic circuits in living cells. However, a reliable and precise method for selecting minimally-sized synthetic promoters with desired background, amplitude, and stimulation response profiles has been elusive. In this study, we introduce a massively parallel reporter assay library containing 6184 synthetic promoters, each less than 250 bp in length. This comprehensive library allows for rapid identification of promoters with optimal transcriptional output parameters across multiple cell lines and stimuli. We showcase this library’s utility to identify promoters activated in unique cell types, and in response to metabolites, mitogens, cellular toxins, and agonism of both aminergic and non-aminergic GPCRs. We further show these promoters can be used in luciferase reporter assays, eliciting 50-100 fold dynamic ranges in response to stimuli. Our platform is effective, easily implemented, and provides a solution for selecting short-length promoters with precise performance for a multitude of applications.
2024-10-08 | GSE271608 | GEO
Project description:A library of native and synthetic yeast core promoters driving YFP expression
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Project description:The pathogenic bacterium Chlamydia reproduces via two specialized forms inside a eukaryotic host cell. The dividing form called the reticulate body (RB) must convert at late times into the infectious elementary body (EB) for spread to a new host cell. Late genes are a temporal class of chlamydial genes believed to be responsible for RB-to-EB conversion, but late gene regulation is incompletely understood. In this study, we used chromatin immunoprecipitation (ChIP) to investigate two alternative sigma factors, σ28 and σ54, that alter the promoter specificity of C. trachomatis RNA-polymerase. σ28 ChIP-seq identified hctB and tsp as the only promoters bound by σ28, and binding only occurred late, around the time of RB-to-EB conversion. A σ28 overexpression strain confirmed that these genes are transcribed in a σ28-dependent manner. σ54 ChIP-seq showed that σ54 only bound ctl0021 and ctl0052, and only at late times. This σ54 regulon appears to be conserved as in silico analysis identified σ54 promoter sequences upstream of ctl0021 and ctl0052 homologs in all Chlamydia spp. The genes encoding σ28 and σ54 were only transcribed at late times, but ChIP analysis with the late regulator Euo showed that Euo only controls σ28 expression, and late transcription of σ54 is regulated in an Euo-dependent manner. Thus, multiple mechanisms regulate late genes, including Euo and different forms of RNA polymerase. The dedicated use of two alternative RNA polymerases to control just four late genes suggests that these genes and the independent control of their temporal expression are important for RB-to-EB conversion.
2025-04-30 | GSE294424 | GEO
Project description:The pathogenic bacterium Chlamydia reproduces via two specialized forms inside a eukaryotic host cell. The dividing form called the reticulate body (RB) must convert at late times into the infectious elementary body (EB) for spread to a new host cell. Late genes are a temporal class of chlamydial genes believed to be responsible for RB-to-EB conversion, but late gene regulation is incompletely understood. In this study, we used chromatin immunoprecipitation (ChIP) to investigate two alternative sigma factors, σ28 and σ54, that alter the promoter specificity of C. trachomatis RNA-polymerase. σ28 ChIP-seq identified hctB and tsp as the only promoters bound by σ28, and binding only occurred late, around the time of RB-to-EB conversion. A σ28 overexpression strain confirmed that these genes are transcribed in a σ28-dependent manner. σ54 ChIP-seq showed that σ54 only bound ctl0021 and ctl0052, and only at late times. This σ54 regulon appears to be conserved as in silico analysis identified σ54 promoter sequences upstream of ctl0021 and ctl0052 homologs in all Chlamydia spp. The genes encoding σ28 and σ54 were only transcribed at late times, but ChIP analysis with the late regulator Euo showed that Euo only controls σ28 expression, and late transcription of σ54 is regulated in an Euo-dependent manner. Thus, multiple mechanisms regulate late genes, including Euo and different forms of RNA polymerase. The dedicated use of two alternative RNA polymerases to control just four late genes suggests that these genes and the independent control of their temporal expression are important for RB-to-EB conversion.
2025-04-30 | GSE294423 | GEO
Project description:Genetically identical cells exhibit large variability (noise) in gene expression, with important consequences for cellular function. Although the amount of noise decreases with and is thus partly determined by the mean expression level, the extent to which different promoter sequences can deviate away from this trend is not known. Here, we study how different noise levels are encoded by the promoter sequence using massively parallel noise measurements of thousands of synthetically designed promoters. We find that the noise levels of promoters with similar mean expression levels can vary over more than one order of magnitude, with nucleosome-disfavoring sequences resulting in lower noise and more transcription factor binding sites resulting in higher noise. We devised a computational model that can accurately predict the mean-independent component of the noise from DNA sequence alone. Our model suggests that the effect of promoters on noise is partly mediated by the combination of non-specific DNA binding and one-dimensional sliding along the DNA that occurs when transcription factors search for their target sites. Overall, our results demonstrate that small changes in the DNA sequence of promoters can allow tuning of noise levels in a manner that is largely predictable and partly decoupled from effects on the mean expression levels. These insights may assist in designing promoters with desired noise levels. Expression measurements of a collection of synthetic promoters collection that was published in Sharon et al. Nature Biotechnology 2012(doi: 10.1038/nbt.2205). Two replicates of the promoter library integrated into a plasmid in yeast were measured in SC-Glu-URA medium. The promoter library was measured as described in Sharon et. al.(Sharon et al. 2012), except for the differences below. Briefly, a large collection of synthetic promoter reporter gene strains was generated by a pooled ligation of 6500 fully designed DNA oligos (obtained by synthesis on a microarray(LeProust et al. 2010) by Agilent Technologies, Santa Clara, California). The oligos were ligated upstream to a yellow fluorescent protein (YFP) gene with a short (100 bp) core promoter sequence taken from HIS3 gene promoter and into a low copy plasmid which also contains a TEF2 promoter deriving red fluorescent protein (mCherry). The resulting plasmids were then transformation into yeast (S. cerevisiae). Next, the pool of cells was grown in amino acid starvation condition (SCD without amino acid except Histidine), and sorted according to their YFP expression level into 32 expression bins (mCherry was used for gating one plasmid copy cells and for normalization). The DNA of the promoters in each bin were then amplified and sent to multiplexed parallel sequencing. Each sequencing result was mapped to a specific promoter and expression bin, resulting in a distribution of cells that contain each promoter across all expression bins. The following differences were applied relative to the description in Sharon et. al.(Sharon et al. 2012). The medium used both for growing the cells and for their sorting was SC-Glu-URA (synthetic complete media with 2% glucose and without uracil) medium without amino acids, except for Histidine. In order to achieve expression distributions with high resolution that would allow good assessment of expression noise, the library cells were sorted into 32 bins according to their ratio of YFP and mCherry expression level, thereby normalizing for extrinsic noise effects. Each of the two extreme expression bins contained 2% of the library cells and each of the remaining 30 bins contained 3.2%. We collected a total of 10,000,000 cells. As previously described, the mapping of cells to bins involves parallel sequencing of the amplified promoter regions. For this purpose, Illumina Hi-Seq 2000 was used to obtain >30,000,000 mapped reads. The two replicates were separately generated from the ssDNA oligo library and separately measured as described above.
2014-07-12 | E-GEOD-55346 | biostudies-arrayexpress