Dataset Information

CRISPR Gene Perturbations Provide Insights for Improving Bacterial Biofuel Tolerance.

ABSTRACT: Economically-viable biofuel production is often limited by low levels of microbial tolerance to high biofuel concentrations. Here we demonstrate the first application of deactivated CRISPR perturbations of gene expression to improve Escherichia coli biofuel tolerance. We construct a library of 31 unique CRISPR inhibitions and activations of gene expression in E. coli and explore their impacts on growth during 10 days of exposure to n-butanol and n-hexane. We show that perturbation of metabolism and membrane-related genes induces the greatest impacts on growth in n-butanol, as does perturbation of redox-related genes in n-hexanes. We identify uncharacterized genes yjjZ and yehS with strong potential for improving tolerance to both biofuels. Perturbations demonstrated significant temporal dependencies, suggesting that rationally designing time-sensitive gene circuits can optimize tolerance. We also introduce a sgRNA-specific hyper-mutator phenotype (~2,600-fold increase) into our perturbation strains using error-prone Pol1. We show that despite this change, strains exhibited similar growth phenotypes in n-butanol as before, demonstrating the robustness of CRISPR perturbations during prolonged use. Collectively, these results demonstrate the potential of CRISPR manipulation of gene expression for improving biofuel tolerance and provide constructive starting points for optimization of biofuel producing microorganisms.

SUBMITTER: Otoupal PB

PROVIDER: S-EPMC6131188 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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CRISPR Gene Perturbations Provide Insights for Improving Bacterial Biofuel Tolerance.

Otoupal Peter B PB Chatterjee Anushree A

Frontiers in bioengineering and biotechnology 20180904

Economically-viable biofuel production is often limited by low levels of microbial tolerance to high biofuel concentrations. Here we demonstrate the first application of deactivated CRISPR perturbations of gene expression to improve <i>Escherichia coli</i> biofuel tolerance. We construct a library of 31 unique CRISPR inhibitions and activations of gene expression in <i>E. coli</i> and explore their impacts on growth during 10 days of exposure to n-butanol and n-hexane. We show that perturbation ...[more]

PMID: 30234107

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Project description:This dataset contains transcription profiles of TOP10 E.coli transformed with 85 rewired network plasmids first described in: Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:840-5 (2008). The data are described and analysed in an accompanying paper Baumstark et al.,The propagation of perturbations in shuffled bacterial gene networks (Submitted, 2015). 260 raw data microarrays are provided in total, representing biological triplicates (a,b and c; independent colonies grown from the same transformation, under standard growth conditions; LB, 16h). This is done for each of 255 promoter-ORF constructs (e.g. appY-crp, etc.) and 5 control construct microarrays (empty plasmid; Co). Co controls are provided for comparison, to show the relative effect of the rewiring genetic perturbation. The final processed data compares the number of perturbed genes, comparing between the average expression values of each rewired construct and Co. Methods: The 85 rewiring plasmids (Isalan et al, 2008) were transformed into E. coli TOP10 cells and grown under standardised conditions: bacteria were freshly plated onto LB Agar plates (with 100 μg/ml Ampicillin and 50 μg/ml Streptomycin) and incubated overnight at 37oC to form colonies. Single colonies (<3 days old) were used to inoculate 2 ml of LB in 14 ml culture tubes, containing 100 μg/ml Ampicillin and 50 μg/ml Streptomycin. Constructs were grown for 16h at 37oC, at 220 rpm in an orbital shaker. 10 μg of extracted total bacterial RNA (integrity number > 7.0) was used with Affymetrix GeneChip E. coli Genome 2.0 Arrays. Key to names: RAW DATA samples 1-260 _Co_1a.CEL = Control Co, colony a _Co_1b.CEL = Control Co, colony b etc. appY_O_30a.CEL = appY-promoter only, colony a appY_O_30b.CEL = appY-promoter only, colony b etc. appY_crp_34a.CEL = rewired construct, appY-promoter expressing crp ORF, colony a appY_crp_34b.CEL = rewired construct, appY-promoter expressing crp ORF, colony b appY_crp_34b.CEL = rewired construct, appY-promoter expressing crp ORF, colony c etc. PROCESSED DATA sample 261: probe_set_expression_value_norm_all - normalised data for all samples, for all E. coli K12 genes sample 262: probe_set_expression_value_norm_MG1655 - normalised data for all samples, for E. coli MG1655 subset of genes

Dataset Information

CRISPR Gene Perturbations Provide Insights for Improving Bacterial Biofuel Tolerance.

Publications

CRISPR Gene Perturbations Provide Insights for Improving Bacterial Biofuel Tolerance.

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