Ontology highlight
ABSTRACT:
PROVIDER: PRJNA728203 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14471400.fastq.gz | Fastqsanger.gz | |||
| SRR14471500.fastq.gz | Fastqsanger.gz | |||
| SRR14471600.fastq.gz | Fastqsanger.gz | |||
| SRR14471700.fastq.gz | Fastqsanger.gz | |||
| SRR14471800.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 1138 |
Similar Datasets
Project description:Escherichia coli is the leading cause of catheter-associated urinary tract infections, caused by biofilm formation on implanted biomaterial surfaces. Understanding the genes that cause cellular adhesion to diverse biomaterial surfaces may aid in the design of targeting anti-biofouling chemicals to prevent these biofilm infections, but our current knowledge on such surfaces is limited. Here, we incorporate a platform of six biomaterials of varying hydrophilicities and stiffnesses and a comprehensive genome-wide CRISPR interference (CRISPRi) library to elucidate genotype-phenotype relationships for cellular adhesion to physicochemically varied biomaterial surfaces in E. coli MG1655. After characterization of the biomaterials and CRISPRi tool, we designed a CRISPRi library of 34,315 unique designs targeting 99.0% of the genome in MG1655 (up to 8 designs per gene). We then performed pooled selections for adhesion to each biomaterial surface, elucidating over 400 novel gene hits to each biomaterial surface. Data analysis revealed greater correlations between biomaterials of the same hydrophilicity rather than stiffness, in addition to more gene hits associated with decreased adhesion across all six surfaces than increased adhesion. Monoclonal verification of select designs from the library exhibited strong correlations between results from the pooled selections and individual measurements for adhesion to each gel for most designs. The results from this study provide comprehensive gene sets for cellular adhesion to physicochemically diverse biomaterial surfaces that may be potential gene targets for the design of targeting anti-biofouling agents and offer insight that could be used for the design of “smart” biomaterials, both with potential to prevent biofilm infections.
2024-12-31 | GSE274727 | GEO
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 (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 | GNPS
Project description:Genome-wide screens have discovered a large set of essential genes in the human pathogen Streptococcus pneumoniae. However, the function of many essential genes is still unknown, hampering vaccine and drug development programs. Based on results from transposon-sequencing (Tn-Seq), we refined the list of essential genes in S. pneumoniae serotype 2 strain D39. Next, we created a knockdown library targeting all 391 potentially essential genes using CRISPR interference (CRISPRi). Using high-content microscopy screening, we searched for essential genes of unknown function with clear phenotypes in cell morphology upon CRISPRi-based depletion. We identified SPD1416 and SPD1417 (named to MurT and GatD, respectively) as essential peptidoglycan synthesis proteins and we show that SPD1198 and SPD1197 (named to TarP and TarQ, respectively) are responsible for the polymerization of teichoic acid (TA) precursors. This knowledge enabled us to reconstruct the unique pneumococcal TA biosynthetic pathway. Our CRISPRi library provides a valuable tool for characterization of pneumococcal genes and pathways and revealed several promising antibiotic targets. This RNA-Seq dataset is aimed to show that induction of the CRISPRi system very selectively represses its target gene, firefly luciferase, without other observable transcriptional effects.
2017-03-03 | GSE89763 | GEO
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.
2024-08-07 | MSV000095538 | MassIVE
Project description:Genome-scale CRISPR interference (CRISPRi) is widely utilized to study cellular processes in a variety of organisms. To date, a genome-wide CRISPRi library, optimized for targeting the Saccharomyces cerevisiae genome, has not been presented. Here, we have generated a comprehensive, inducible CRISPRi library, based on spacer design rules optimized for yeast. We have validated this library for genome-wide interrogation of gene function across a variety of applications, including accurate discovery of haploinsufficient genes and identification of enzymatic and regulatory genes involved in adenine and arginine biosynthesis. The comprehensive nature of the library also revealed refined spacer design parameters for transcriptional repression, including location, nucleosome occupancy and nucleotide features. CRISPRi screens using this library can identify genes and pathways with high precision and low false discovery rate across a variety of experimental conditions, enabling rapid and reliable genome-wide assessment of genetic function and interactions in S. cerevisiae.
2020-11-27 | GSE159409 | GEO
Project description:This project aims to compare gRNA design algorithms and single- versus dual-targeting using a benchmark CRISPR-knockout library composed of gRNAs targeting essential and non-essential genes.
2025-02-12 | E-MTAB-13981 | 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.
2024-08-07 | MSV000095536 | GNPS