| 1. |
- Jensen, E. D., et al.
(författare)
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Transcriptional reprogramming in yeast using dCas9 and combinatorial gRNA strategies
- 2017
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Ingår i: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 16:1, s. 46-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Transcriptional reprogramming is a fundamental process of living cells in order to adapt to environmental and endogenous cues. In order to allow flexible and timely control over gene expression without the interference of native gene expression machinery, a large number of studies have focused on developing synthetic biology tools for orthogonal control of transcription. Most recently, the nuclease-deficient Cas9 (dCas9) has emerged as a flexible tool for controlling activation and repression of target genes, by the simple RNA-guided positioning of dCas9 in the vicinity of the target gene transcription start site. Results: In this study we compared two different systems of dCas9-mediated transcriptional reprogramming, and applied them to genes controlling two biosynthetic pathways for biobased production of isoprenoids and triacylglycerols (TAGs) in baker's yeast Saccharomyces cerevisiae. By testing 101 guide-RNA (gRNA) structures on a total of 14 different yeast promoters, we identified the best-performing combinations based on reporter assays. Though a larger number of gRNA-promoter combinations do not perturb gene expression, some gRNAs support expression perturbations up to similar to threefold. The best-performing gRNAs were used for single and multiplex reprogramming strategies for redirecting flux related to isoprenoid production and optimization of TAG profiles. From these studies, we identified both constitutive and inducible multiplex reprogramming strategies enabling significant changes in isoprenoid production and increases in TAG. Conclusion: Taken together, we show similar performance for a constitutive and an inducible dCas9 approach, and identify multiplex gRNA designs that can significantly perturb isoprenoid production and TAG profiles in yeast without editing the genomic context of the target genes. We also identify a large number of gRNA positions in 14 native yeast target pomoters that do not affect expression, suggesting the need for further optimization of gRNA design tools and dCas9 engineering.\
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| 2. |
- Jessop-Fabre, Mathew M., et al.
(författare)
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EasyClone-MarkerFree: A vector toolkit for marker-less integration of genes into Saccharomyces cerevisiae via CRISPR-Cas9
- 2016
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Ingår i: Biotechnology journal. - : Wiley. - 1860-6768 .- 1860-7314. ; 11:8, s. 1110-1117
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Tidskriftsartikel (refereegranskat)abstract
- Saccharomyces cerevisiae is an established industrial host for production of recombinant proteins, fuels and chemicals. To enable stable integration of multiple marker-free overexpression cassettes in the genome of S. cerevisiae, we have developed a vector toolkit EasyClone-MarkerFree. The integration of linearized expression cassettes into defined genomic loci is facilitated by CRISPR/Cas9. Cas9 is recruited to the chromosomal location by specific guide RNAs (gRNAs) expressed from a set of gRNA helper vectors. Using our genome engineering vector suite, single and triple insertions are obtained with 90–100% and 60–70% targeting efficiency, respectively. We demonstrate application of the vector toolkit by constructing a haploid laboratory strain (CEN.PK113-7D) and a diploid industrial strain (Ethanol Red) for production of 3-hydroxypropionic acid, where we tested three different acetyl-CoA supply strategies, requiring overexpression of three to six genes each. Among the tested strategies was a bacterial cytosolic pyruvate dehydrogenase complex, which was integrated into the genome in a single transformation. The publicly available EasyClone-MarkerFree vector suite allows for facile and highly standardized genome engineering, and should be of particular interest to researchers working on yeast chassis with limited markers available.
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| 3. |
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| 4. |
- Nielsen, Jens B, 1962, et al.
(författare)
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Engineering Cellular Metabolism
- 2016
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Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 164:6, s. 1185-1197
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Forskningsöversikt (refereegranskat)abstract
- Metabolic engineering is the science of rewiring the metabolism of cells to enhance production of native metabolites or to endow cells with the ability to produce new products. The potential applications of such efforts are wide ranging, including the generation of fuels, chemicals, foods, feeds, and pharmaceuticals. However, making cells into efficient factories is challenging because cells have evolved robust metabolic networks with hard-wired, tightly regulated lines of communication between molecular pathways that resist efforts to divert resources. Here, we will review the current status and challenges of metabolic engineering and will discuss how new technologies can enable metabolic engineering to be scaled up to the industrial level, either by cutting off the lines of control for endogenous metabolism or by infiltrating the system with disruptive, heterologous pathways that overcome cellular regulation.
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| 5. |
- Nielsen, Jens B, 1962, et al.
(författare)
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Engineering synergy in biotechnology
- 2014
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Ingår i: Nature Chemical Biology. - : Springer Science and Business Media LLC. - 1552-4450 .- 1552-4469. ; 10:5, s. 319-322
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 6. |
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| 7. |
- Qin, Jiufu, 1985, et al.
(författare)
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Engineering yeast metabolism for the discovery and production of polyamines and polyamine analogues
- 2021
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Ingår i: Nature Catalysis. - : Springer Science and Business Media LLC. - 2520-1158. ; 4:6, s. 498-509
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Tidskriftsartikel (refereegranskat)abstract
- Structurally complex and diverse polyamines and polyamine analogues are potential therapeutics and agrochemicals that can address grand societal challenges, for example, healthy ageing and sustainable food production. However, their structural complexity and low abundance in nature hampers either bulk chemical synthesis or extraction from natural resources. Here we reprogrammed the metabolism of baker’s yeast Saccharomyces cerevisiae and recruited nature’s diverse reservoir of biochemical tools to enable a complete biosynthesis of multiple polyamines and polyamine analogues. Specifically, we adopted a systematic engineering strategy to enable gram-per-litre-scale titres of spermidine, a central metabolite in polyamine metabolism. To demonstrate the potential of our polyamine platform, various polyamine synthases and ATP-dependent amide-bond-forming systems were introduced for the biosynthesis of natural and unnatural polyamine analogues. The yeast platform serves as a resource to accelerate the discovery and production of polyamines and polyamine analogues, and thereby unlocks this chemical space for further pharmacological and insecticidal studies. [Figure not available: see fulltext.]
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| 8. |
- Rajkumar, Arun S., et al.
(författare)
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Engineering of synthetic, stress-responsive yeast promoters
- 2016
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 44:17, s. e136-
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Tidskriftsartikel (refereegranskat)abstract
- Advances in synthetic biology and our understanding of the rules of promoter architecture have led to the development of diverse synthetic constitutive and inducible promoters in eukaryotes and prokaryotes. However, the design of promoters inducible by specific endogenous or environmental conditions is still rarely undertaken. In this study, we engineered and characterized a set of strong, synthetic promoters for budding yeast Saccharomyces cerevisiae that are inducible under acidic conditions (pH ? 3). Using available expression and transcription factor binding data, literature on transcriptional regulation, and known rules of promoter architecture we improved the low-pH performance of the YGP1 promoter by modifying transcription factor binding sites in its upstream activation sequence. The engineering strategy outlined for the YGP1 promoter was subsequently applied to create a response to low pH in the unrelated CCW14 promoter. We applied our best promoter variants to low-pH fermentations, enabling ten-fold increased production of lactic acid compared to titres obtained with the commonly used, native TEF1 promoter. Our findings outline and validate a general strategy to iteratively design and engineer synthetic yeast promoters inducible to environmental conditions or stresses of interest.
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| 9. |
- Zhan, Chunjun, 1986, et al.
(författare)
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Reprogramming methanol utilization pathways to convert Saccharomyces cerevisiae to a synthetic methylotroph
- 2023
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Ingår i: Nature Catalysis. - 2520-1158. ; 6:5, s. 435-450
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Tidskriftsartikel (refereegranskat)abstract
- Methanol, an organic one-carbon (C1) compound, represents an attractive alternative carbon source for microbial fermentation. Despite considerable advancements in methanol utilization by prokaryotes such as Escherichia coli, engineering eukaryotic model organisms such as Saccharomyces cerevisiae into synthetic methylotrophs remains challenging. Here, an engineered module circuit strategy combined with adaptive laboratory evolution was applied to engineer S. cerevisiae to use methanol as the sole carbon source. We revealed that the evolved glyoxylate-based serine pathway plays an important role in methanol-dependent growth by promoting formaldehyde assimilation. Further, we determined that the isoprenoid biosynthetic pathway was upregulated, resulting in an increased concentration of squalene and ergosterol in our evolved strain. These changes could potentially alleviate cell membrane damage in the presence of methanol. This work sets the stage for expanding the potential of exploiting S. cerevisiae as a potential organic one-carbon platform for biochemical or biofuel production. [Figure not available: see fulltext.].
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| 10. |
- Zhang, J., et al.
(författare)
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Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.
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