| 1. |
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- 2019
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Journal article (peer-reviewed)
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| 2. |
- Lojewski, Tobias, et al.
(author)
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The interplay of local electron correlations and ultrafast spin dynamics in fcc Ni
- 2023
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In: Materials Research Letters. - : Taylor & Francis. - 2166-3831. ; 11:8, s. 655-661
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Journal article (peer-reviewed)abstract
- The complex electronic structure of metallic ferromagnets is determined by a balance between exchange interaction, electron hopping leading to band formation, and local Coulomb repulsion. By combining high energy and temporal resolution in femtosecond time-resolved X-ray absorption spectroscopy with ab initio time-dependent density functional theory we analyze the electronic structure in fcc Ni on the time scale of these interactions in a pump-probe experiment. We distinguish transient broadening and energy shifts in the absorption spectra, which we demonstrate to be captured by electron repopulation respectively correlation-induced modifications of the electronic structure, requiring to take the local Coulomb interaction into account.
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| 3. |
- Bergenholm, David, 1987, et al.
(author)
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Rational gRNA design based on transcription factor binding data
- 2021
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In: Synthetic Biology. - : Oxford University Press (OUP). - 2397-7000 .- 1939-7267. ; 6:1
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Journal article (peer-reviewed)abstract
- The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has become a standard tool in many genome engineering endeavors. The endonuclease-deficient version of Cas9 (dCas9) is also a powerful programmable tool for gene regulation. In this study, we made use of Saccharomyces cerevisiae transcription factor (TF) binding data to obtain a better understanding of the interplay between TF binding and binding of dCas9 fused to an activator domain, VPR. More specifically, we targeted dCas9-VPR toward binding sites of Gcr1-Gcr2 and Tye7 present in several promoters of genes encoding enzymes engaged in the central carbon metabolism. From our data, we observed an upregulation of gene expression when dCas9-VPR was targeted next to a TF binding motif, whereas a downregulation or no change was observed when dCas9 was bound on a TF motif. This suggests a steric competition between dCas9 and the specific TF. Integrating TF binding data, therefore, proved to be useful for designing guide RNAs for CRISPR interference or CRISPR activation applications.
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| 4. |
- Jullesson, David, 1987, et al.
(author)
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Impact of synthetic biology and metabolic engineering on industrial production of fine chemicals
- 2015
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In: Biotechnology Advances. - : Elsevier BV. - 0734-9750. ; 33:7, s. 1395-1402
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Research review (peer-reviewed)abstract
- Industrial bio-processes for fine chemical production are increasingly relying on cell factories developed through metabolic engineering and synthetic biology. The use of high throughput techniques and automation for the design of cell factories, and especially platform strains, has played an important role in the transition from laboratory research to industrial production. Model organisms such as Saccharomyces cerevisiae and Escherichia coli remain widely used host strains for industrial production due to their robust and desirable traits. This review describes some of the bio-based fine chemicals that have reached the market, key metabolic engineering tools that have allowed this to happen and some of the companies that are currently utilizing these technologies for developing industrial production processes.
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| 5. |
- Zrimec, Jan, 1981, et al.
(author)
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Controlling gene expression with deep generative design of regulatory DNA
- 2022
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1, s. 5099-
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Journal article (peer-reviewed)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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| 6. |
- Clausen Lind, Andrea, 1995, et al.
(author)
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Evaluation and comparison of colorimetric outputs for yeast-based biosensors in laboratory and point-of-use settings
- 2024
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In: FEMS Microbiology Letters. - 1574-6968 .- 0378-1097. ; 371
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Journal article (peer-reviewed)abstract
- Recent research has shown the potential of yeast-based biosensors (YBBs) for point-of-use detection of pathogens and target molecules in saliva, blood, and urine samples. The choice of output can greatly affect the sensitivity, dynamic range, detection time, and ease-of-use of a sensor. For visual detection without the need for additional reagents or machinery, colorimetric outputs have shown great potential. Here, we evaluated the inducible generation of prodeoxyviolacein and proviolacein as colorimetric YBB outputs and benchmarked these against lycopene. The outputs were induced via the yeast mating pathway and were compared on agar plates, in liquid culture, and on paper slips. We found that all three outputs produced comparable pigment intensity on agar plates, making them applicable for bioengineering settings. In liquid media and on paper slips, lycopene resulted in a higher intensity pigment and a decreased time-of-detection.
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| 7. |
- Dabirian, Yasaman, 1992, et al.
(author)
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Does co-expression of Yarrowia lipolytica genes encoding Yas1p, Yas2p and Yas3p make a potential alkane-responsive biosensor in Saccharomyces cerevisiae?
- 2020
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In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 15:12 December
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Journal article (peer-reviewed)abstract
- Alkane-based biofuels are desirable to produce at a commercial scale as these have properties similar to current petroleum-derived transportation fuels. Rationally engineering microorganisms to produce a desirable compound, such as alkanes, is, however, challenging. Metabolic engineers are therefore increasingly implementing evolutionary engineering approaches combined with high-throughput screening tools, including metabolite biosensors, to identify productive cells. Engineering Saccharomyces cerevisiae to produce alkanes could be facilitated by using an alkane-responsive biosensor, which can potentially be developed from the native alkane-sensing system in Yarrowia lipolytica, a well-known alkaneassimilating yeast. This putative alkane-sensing system is, at least, based on three different transcription factors (TFs) named Yas1p, Yas2p and Yas3p. Although this system is not fully elucidated in Y. lipolytica, we were interested in evaluating the possibility of translating this system into an alkane-responsive biosensor in S. cerevisiae. We evaluated the alkanesensing system in S. cerevisiae by developing one sensor based on the native Y. lipolytica ALK1 promoter and one sensor based on the native S. cerevisiae CYC1 promoter. In both systems, we found that the TFs Yas1p, Yas2p and Yas3p do not seem to act in the same way as these have been reported to do in their native host. Additional analysis of the TFs suggests that more knowledge regarding their mechanism is needed before a potential alkane-responsive sensor based on the Y. lipolytica system can be established in S. cerevisiae. Copyright:
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| 8. |
- Dabirian, Yasaman, 1992, et al.
(author)
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Expanding the Dynamic Range of a Transcription Factor-Based Biosensor in Saccharomyces cerevisiae
- 2019
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In: ACS Synthetic Biology. - : American Chemical Society (ACS). - 2161-5063. ; 8:9, s. 1968-1975
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Journal article (peer-reviewed)abstract
- Metabolite biosensors are useful tools for high-throughput screening approaches and pathway regulation approaches. An important feature of biosensors is the dynamic range. To expand the maximum dynamic range of a transcription factor-based biosensor in Saccharomyces cerevisiae, using the fapO/FapR system from Bacillus subtilis as an example case, five native promoters, including constitutive and glucose-regulated ones, were modified. By evaluating different binding site (BS) positions in the core promoters, we identified locations that resulted in a high maximum dynamic range with low expression under repressed conditions. We further identified BS positions in the upstream element region of the TEF1 promoter that did not influence the native promoter strength but resulted in repression in the presence of a chimeric repressor consisting of FapR and the yeast repressor Mig1. These modified promoters with broad dynamic ranges will provide useful information for the engineering of future biosensors and their use in complex genetic circuits.
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| 9. |
- Dabirian, Yasaman, 1992, et al.
(author)
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FadR-Based Biosensor-Assisted Screening for Genes Enhancing Fatty Acyl-CoA Pools in Saccharomyces cerevisiae
- 2019
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In: ACS Synthetic Biology. - : American Chemical Society (ACS). - 2161-5063. ; 8:8, s. 1788-1800
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Journal article (peer-reviewed)abstract
- Fatty acid-derived compounds have a range of industrial applications, from chemical building blocks to biofuels. Due to the highly dynamic nature of fatty acid metabolism, it is difficult to identify genes modulating fatty acyl-CoA levels using a rational approach. Metabolite biosensors can be used to screen genes from large-scale libraries in vivo in a high throughput manner. Here, a fatty acyl-CoA sensor based on the transcription factor FadR from Escherichia coli was established in Saccharomyces cerevisiae and combined with a gene overexpression library to screen for genes increasing the fatty acyl-CoA pool. Fluorescence-activated cell sorting, followed by data analysis, identified genes enhancing acyl-CoA levels. From these, overexpression of RTC3, GGA2, and LPP1 resulted in about 80% increased fatty alcohol levels. Changes in fatty acid saturation and chain length distribution could also be observed. These results indicate that the use of this acyl-CoA biosensor combined with a gene overexpression library allows for identification of gene targets improving production of fatty acids and derived products.
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| 10. |
- David, Florian, 1981, et al.
(author)
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A Perspective on Synthetic Biology in Drug Discovery and Development - Current Impact and Future Opportunities
- 2021
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In: SLAS Discovery. - : Elsevier BV. - 2472-5552 .- 2472-5560. ; 26:5, s. 581-603
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Research review (peer-reviewed)abstract
- The global impact of synthetic biology has been accelerating, because of the plummeting cost of DNA synthesis, advances in genetic engineering, growing understanding of genome organization, and explosion in data science. However, much of the discipline’s application in the pharmaceutical industry remains enigmatic. In this review, we highlight recent examples of the impact of synthetic biology on target validation, assay development, hit finding, lead optimization, and chemical synthesis, through to the development of cellular therapeutics. We also highlight the availability of tools and technologies driving the discipline. Synthetic biology is certainly impacting all stages of drug discovery and development, and the recognition of the discipline’s contribution can further enhance the opportunities for the drug discovery and development value chain.
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