| 1. |
- Zrimec, Jan, 1981, et al.
(författare)
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Controlling gene expression with deep generative design of regulatory DNA
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1, s. 5099-
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Tidskriftsartikel (refereegranskat)abstract
- Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.
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| 2. |
- Scott, Louis, 1987, et al.
(författare)
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Genetically Encoded Whole Cell Biosensor for Drug Discovery of HIF-1 Interaction Inhibitors
- 2022
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Ingår i: ACS Synthetic Biology. - : American Chemical Society (ACS). - 2161-5063. ; 11:10, s. 3182-3189
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Tidskriftsartikel (refereegranskat)abstract
- The heterodimeric transcription factor, hypoxia inducible factor-1 (HIF-1), is an important anticancer target as it supports the adaptation and response of tumors to hypoxia. Here, we optimized the repressed transactivator yeast two-hybrid system to further develop it as part of a versatile yeast-based drug discovery platform and validated it using HIF-1. We demonstrate both fluorescence-based and auxotrophy-based selections that could detect HIF-1α/HIF-1β dimerization inhibition. The engineered genetic selection is tunable and able to differentiate between strong and weak interactions, shows a large dynamic range, and is stable over different growth phases. Furthermore, we engineered mechanisms to control for cellular activity and off-target drug effects. We thoroughly characterized all parts of the biosensor system and argue this tool will be generally applicable to a wide array of protein-protein interaction targets. We anticipate this biosensor will be useful as part of a drug discovery platform, particularly when screening DNA-encoded new modality drugs.
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| 3. |
- Skrekas, Christos, 1990, et al.
(författare)
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Fluorescence-Activated Cell Sorting as a Tool for Recombinant Strain Screening
- 2022
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Ingår i: Methods in Molecular Biology. - New York, NY : Springer US. - 1940-6029 .- 1064-3745. ; , s. 39-57
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Metabolic engineering of microbial cells is the discipline of optimizing microbial metabolism to enable and improve the production of target molecules ranging from biofuels and chemical building blocks to high-value pharmaceuticals. The advances in genetic engineering have eased the construction of highly engineered microbial strains and the generation of genetic libraries. Intracellular metabolite-responsive biosensors facilitate high-throughput screening of these libraries by connecting the levels of a metabolite of interest to a fluorescence output. Fluorescent-activated cell sorting (FACS) enables the isolation of highly fluorescent single cells and thus genotypes that produce higher levels of the metabolite of interest. Here, we describe a high-throughput screening method for recombinant yeast strain screening based on intracellular biosensors and FACS.
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