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      Inducible expression of large gRNA arrays for multiplexed CRISPRai applications

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          Abstract

          CRISPR gene activation and inhibition (CRISPRai) has become a powerful synthetic tool for influencing the expression of native genes for foundational studies, cellular reprograming, and metabolic engineering. Here we develop a method for near leak-free, inducible expression of a polycistronic array containing up to 24 gRNAs from two orthogonal CRISPR/Cas systems to increase CRISPRai multiplexing capacity and target gene flexibility. To achieve strong inducibility, we create a technology to silence gRNA expression within the array in the absence of the inducer, since we found that long gRNA arrays for CRISPRai can express themselves even without promoter. Using this method, we create a highly tuned and easy-to-use CRISPRai toolkit in the industrially relevant yeast, Saccharomyces cerevisiae, establishing the first system to combine simultaneous activation and repression, large multiplexing capacity, and inducibility. We demonstrate this toolkit by targeting 11 genes in central metabolism in a single transformation, achieving a 45-fold increase in succinic acid, which could be precisely controlled in an inducible manner. Our method offers a highly effective way to regulate genes and rewire metabolism in yeast, with principles of gRNA array construction and inducibility that should extend to other chassis organisms.

          Abstract

          CRISPR gene activation and inhibition has become a powerful synthetic tool for influencing the expression of native genes for foundational studies, cellular reprograming, and metabolic engineering. Here the authors demonstrate near leak-free, inducible expression of a polycistronic array containing up to 24 gRNAs from two orthogonal CRISPR/Cas systems.

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          Most cited references41

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          Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression.

          Targeted gene regulation on a genome-wide scale is a powerful strategy for interrogating, perturbing, and engineering cellular systems. Here, we develop a method for controlling gene expression based on Cas9, an RNA-guided DNA endonuclease from a type II CRISPR system. We show that a catalytically dead Cas9 lacking endonuclease activity, when coexpressed with a guide RNA, generates a DNA recognition complex that can specifically interfere with transcriptional elongation, RNA polymerase binding, or transcription factor binding. This system, which we call CRISPR interference (CRISPRi), can efficiently repress expression of targeted genes in Escherichia coli, with no detectable off-target effects. CRISPRi can be used to repress multiple target genes simultaneously, and its effects are reversible. We also show evidence that the system can be adapted for gene repression in mammalian cells. This RNA-guided DNA recognition platform provides a simple approach for selectively perturbing gene expression on a genome-wide scale. Copyright © 2013 Elsevier Inc. All rights reserved.
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            CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes.

            The genetic interrogation and reprogramming of cells requires methods for robust and precise targeting of genes for expression or repression. The CRISPR-associated catalytically inactive dCas9 protein offers a general platform for RNA-guided DNA targeting. Here, we show that fusion of dCas9 to effector domains with distinct regulatory functions enables stable and efficient transcriptional repression or activation in human and yeast cells, with the site of delivery determined solely by a coexpressed short guide (sg)RNA. Coupling of dCas9 to a transcriptional repressor domain can robustly silence expression of multiple endogenous genes. RNA-seq analysis indicates that CRISPR interference (CRISPRi)-mediated transcriptional repression is highly specific. Our results establish that the CRISPR system can be used as a modular and flexible DNA-binding platform for the recruitment of proteins to a target DNA sequence, revealing the potential of CRISPRi as a general tool for the precise regulation of gene expression in eukaryotic cells. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation.

              While the catalog of mammalian transcripts and their expression levels in different cell types and disease states is rapidly expanding, our understanding of transcript function lags behind. We present a robust technology enabling systematic investigation of the cellular consequences of repressing or inducing individual transcripts. We identify rules for specific targeting of transcriptional repressors (CRISPRi), typically achieving 90%-99% knockdown with minimal off-target effects, and activators (CRISPRa) to endogenous genes via endonuclease-deficient Cas9. Together they enable modulation of gene expression over a ∼1,000-fold range. Using these rules, we construct genome-scale CRISPRi and CRISPRa libraries, each of which we validate with two pooled screens. Growth-based screens identify essential genes, tumor suppressors, and regulators of differentiation. Screens for sensitivity to a cholera-diphtheria toxin provide broad insights into the mechanisms of pathogen entry, retrotranslocation and toxicity. Our results establish CRISPRi and CRISPRa as powerful tools that provide rich and complementary information for mapping complex pathways. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                r.ledesma-amaro@imperial.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                25 August 2022
                25 August 2022
                2022
                : 13
                : 4984
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Imperial College Centre for Synthetic Biology, , Imperial College London, ; London, SW7 2AZ UK
                [2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Bioengineering, , Imperial College London, ; London, SW7 2AZ UK
                Author information
                http://orcid.org/0000-0001-9303-1778
                http://orcid.org/0000-0001-5392-976X
                http://orcid.org/0000-0003-2631-5898
                Article
                32603
                10.1038/s41467-022-32603-7
                9411621
                36008396
                04103665-4a44-4a60-8fbb-eedfc5e42a73
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 13 October 2021
                : 9 August 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/R01602X/1, BB/T011408/1, BB/T013176/1,
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: ERC-949080, BBI-101022370
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                metabolic engineering,synthetic biology,crispr-cas9 genome editing
                Uncategorized
                metabolic engineering, synthetic biology, crispr-cas9 genome editing

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