CRISPRi knockdowns
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB40851 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR4690500.fastq.gz | Fastqsanger.gz | |||
| ERR4690510.fastq.gz | Fastqsanger.gz | |||
| ERR4690520.fastq.gz | Fastqsanger.gz | |||
| ERR4690501.fastq.gz | Fastqsanger.gz | |||
| ERR4690511.fastq.gz | Fastqsanger.gz |
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Project description:Enzymes maintain metabolism and their concentration affects cellular fitness. High enzyme-levels are costly, but low enzyme-levels can limit metabolic flux. Here, we used CRISPR interference (CRISPRi) to study the consequences of decreasing metabolic enzymes in E. coli below wild-type levels. A time-resolved competition assay with a metabolism-wide CRISPRi library showed that fitness defects appeared late after induction of knockdowns. This suggested that metabolism is robust against decreases of enzymes. The metabolome and proteome of 30 CRISPRi strains revealed the mechanisms that enabled this robustness. First, substrates and allosteric effectors buffered knockdowns by increasing the activity of target-enzymes. Later, metabolite-transcription interactions compensated knockdowns by upregulating the target-pathway or bypass-pathways. For example, we found a new regulation strategy in which 6-phosphogluconate is responsible for bypassing bottlenecks in the pentose-p pathway via the Entner-Doudoroff-pathway. Thus, regulatory metabolites buffer decreases of enzyme-levels, which can occur in nature due to expression noise, mutations or environmental conditions.
2020-10-20 | PXD022070 | Pride
Project description:In this study, we developed a workflow to systematically and selectively induce increases in metabolites by knocking down enzymes with CRISPR interference (CRISPRi). Therefore, we created a sorted CRISPRi library targeting all 1,515 metabolic genes in the most recent genome-scale metabolic model of E. coli (iML151515). In a first step, we screened the metabolome of the CRISPRi library with a fast flow-injection mass spectrometry, which revealed strong and specific accumulation of 36% of the predicted metabolites in the iML1515 model. The accumulating metabolites were unique to certain knockdowns, especially those metabolites associated with the CRISPRi targeted-pathway.
2024-08-07 | MSV000095534 | MassIVE
Project description:In this study, we developed a workflow to systematically and selectively induce increases in metabolites by knocking down enzymes with CRISPR interference (CRISPRi). Therefore, we created a sorted CRISPRi library targeting all 1,515 metabolic genes in the most recent genome-scale metabolic model of E. coli (iML1515). In a first step, we screened the metabolome of the CRISPRi library with a fast flow-injection mass spectrometry, which revealed strong and specific accumulation of 36% of the predicted metabolites in the iML1515 model. The accumulating metabolites were unique to certain knockdowns, especially those metabolites associated with the CRISPRi targeted-pathway. Therefore, we followed-up on accumulating metabolites that were directly associated to the CRISPRi target-gene (i.e. all reactants of the respective enzyme) and measured their fragmentation spectra and chromatographic retention times with LC-MS2. This resulted in experimental fragmentation spectra and chromatographic retention times of 111 metabolites.
2024-08-07 | MSV000095536 | MassIVE
Project description:In this study, we developed a workflow to systematically and selectively induce increases in metabolites by knocking down enzymes with CRISPR interference (CRISPRi). Therefore, we created a sorted CRISPRi library targeting all 1,515 metabolic genes in the most recent genome-scale metabolic model of E. coli (iML15159). In a first step, we screened the metabolome of the CRISPRi library with a fast flow-injection mass spectrometry, which revealed strong and specific accumulation of 36% of the predicted metabolites in the iML1515 model. The accumulating metabolites were unique to certain knockdowns, especially those metabolites associated with the CRISPRi targeted-pathway. Therefore, we followed-up on accumulating metabolites that were directly associated to the CRISPRi target-gene (i.e. all reactants of the respective enzyme) and measured their fragmentation spectra and chromatographic retention times with LC-MS2. This resulted in experimental fragmentation spectra and chromatographic retention times of 111 metabolites. Three of these fragmentation spectra were verified by 13C labelling experiments.
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Project description:CRISPR interference (CRISPRi) is a powerful new tool used in different organisms that provides a fast, specific, and reliable way to knockdown gene expression. Caulobacter crescentus is a well-studied model bacterium, and although a variety of genetic tools have been developed, it currently takes several weeks to delete or deplete individual genes, which significantly limits genetic studies. Here, we optimized a CRISPRi approach to specifically downregulate the expression of genes in C. crescentus. Although the Streptococcus pyogenes CRISPRi system commonly used in other organisms does not work efficiently in Caulobacter, we demonstrate that a catalytically-dead version of Cas9 (dCas9) derived from the type II CRISPR3 module of Streptococcus thermophilus or from Streptococcus pasteurianus can each be effectively used in Caulobacter. We show that these CRISPRi systems can be used to rapidly and inducibly deplete ctrA or gcrA, two essential well-studied genes in Caulobacter, in either asynchronous or synchronized populations of cells. Additionally, we demonstrate the ability to multiplex CRISPRi-based gene knockdowns, opening new possibilities for systematic genetic interaction studies in Caulobacter.
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Project description:In this study, we developed a workflow to systematically and selectively induce increases in metabolites by knocking down enzymes with CRISPR interference (CRISPRi). Therefore, we created a sorted CRISPRi library targeting all 1,515 metabolic genes in the most recent genome-scale metabolic model of E. coli (iML151515). In a first step, we screened the metabolome of the CRISPRi library with a fast flow-injection mass spectrometry, which revealed strong and specific accumulation of 36% of the predicted metabolites in the iML1515 model. The accumulating metabolites were unique to certain knockdowns, especially those metabolites associated with the CRISPRi targeted-pathway.
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Project description:Assess the on- and off-target effects of dox-inducible CRISPR/Cas9 and CRISPRi constructs in a human iPS cell line. Transcript quantification of 3 cell lines, each plus or minus doxycycline and with or without specific single guide RNAs (sgRNAs), with 2 biological replicates each.
2016-01-19 | E-GEOD-76980 | biostudies-arrayexpress
Project description:In this study, we developed a workflow to systematically and selectively induce increases in metabolites by knocking down enzymes with CRISPR interference (CRISPRi). Therefore, we created a sorted CRISPRi library targeting all 1,515 metabolic genes in the most recent genome-scale metabolic model of E. coli (iML1515). In a first step, we screened the metabolome of the CRISPRi library with a fast flow-injection mass spectrometry, which revealed strong and specific accumulation of 36% of the predicted metabolites in the iML1515 model. The accumulating metabolites were unique to certain knockdowns, especially those metabolites associated with the CRISPRi targeted-pathway. Therefore, we followed-up on accumulating metabolites that were directly associated to the CRISPRi target-gene (i.e. all reactants of the respective enzyme) and measured their fragmentation spectra and chromatographic retention times with LC-MS2. This resulted in experimental fragmentation spectra and chromatographic retention times of 111 metabolites.
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