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  Selective Enrichment of Slow-Growing Bacteria in a Metabolism-Wide CRISPRi Library with a TIMER Protein

Beuter, D., Gomes, J., Randau, L., Diaz-Pascual, F., Drescher, K., & Link, H. (2018). Selective Enrichment of Slow-Growing Bacteria in a Metabolism-Wide CRISPRi Library with a TIMER Protein. ACS SYNTHETIC BIOLOGY, 7(12), 2775-2782. doi:10.1021/acssynbio.8b00379.

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Beuter, D.1, Author           
Gomes, J.2, Author
Randau, L.2, Author           
Diaz-Pascual, Francisco3, Author           
Drescher, K.3, Author           
Link, H.1, Author           
Affiliations:
1Emmy Noether Research Group Dynamic Control of Metabolic Networks, Max Planck Institute for Terrestrial Microbiology, Max Planck Society, Karl-von-Frisch-Strasse 10, D-35043 Marburg, DE, ou_3266292              
2Max Planck Research Group Prokaryotic small RNA Biology, Alumni, Max Planck Institute for Terrestrial Microbiology, Max Planck Society, Karl-von-Frisch-Strasse 10, D-35043 Marburg, ou_3266318              
3Max Planck Research Group Bacterial Biofilms, Max Planck Institute for Terrestrial Microbiology, Max Planck Society, Karl-von-Frisch-Strasse 10, D-35043 Marburg, DE, ou_3266298              

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 Abstract: Construction of pooled genetic variant libraries has become very fast and versatile. The current limitation of this technique is to select cells with a desired phenotype from very large libraries. Especially cells with poor fitness and slow growth are difficult to select because they are rapidly outcompeted by fitter cells. Here, we demonstrate selective and high-throughput enrichment of slow-growing strains using a fluorescent TIMER protein and flow cytometry. As a proof of principle, we created a metabolism-wide CRISPR interference library for Escherichia coli and enriched targets that interfere with amino acid metabolism. After enrichment of slow-growing cells, the CRISPRi library consisted almost entirely of targets that block amino acid biosynthesis. These results provide general guidelines for how to enrich slow-growing strains from a large pool of genetic variants, with applications in genetic screens, metabolic engineering, and synthetic biology.

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 Dates: 2018-12
 Publication Status: Issued
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 Rev. Type: -
 Identifiers: eDoc: 747948
ISI: 000454568100009
DOI: 10.1021/acssynbio.8b00379
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Title: ACS SYNTHETIC BIOLOGY
Source Genre: Journal
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Pages: - Volume / Issue: 7 (12) Sequence Number: - Start / End Page: 2775 - 2782 Identifier: ISSN: 2161-5063