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      Exchange of endogenous and heterogeneous yeast terminators in Pichia pastoris to tune mRNA stability and gene expression

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          Abstract

          In the yeast Saccharomyces cerevisiae, terminator sequences not only terminate transcription but also affect expression levels of the protein-encoded upstream of the terminator. The non-conventional yeast Pichia pastoris (syn. Komagataella phaffii) has frequently been used as a platform for metabolic engineering but knowledge regarding P. pastoris terminators is limited. To explore terminator sequences available to tune protein expression levels in P. pastoris, we created a ‘terminator catalog’ by testing 72 sequences, including terminators from S. cerevisiae or P. pastoris and synthetic terminators. Altogether, we found that the terminators have a tunable range of 17-fold. We also found that S. cerevisiae terminator sequences maintain function when transferred to P. pastoris. Successful tuning of protein expression levels was shown not only for the reporter gene used to define the catalog but also using betaxanthin production as an example application in pathway flux regulation. Moreover, we found experimental evidence that protein expression levels result from mRNA abundance and in silico evidence that levels reflect the stability of mRNA 3′-UTR secondary structure. In combination with promoter selection, the novel terminator catalog constitutes a basic toolbox for tuning protein expression levels in metabolic engineering and synthetic biology in P. pastoris.

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          ViennaRNA Package 2.0

          Background Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties. Results The ViennaRNA Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the Turner 2004 parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying RNAlib and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as centroid structures and maximum expected accuracy structures derived from base pairing probabilities, or z-scores for locally stable secondary structures, and support for input in fasta format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions. Conclusions The ViennaRNA Package 2.0, supporting concurrent computations via OpenMP, can be downloaded from http://www.tbi.univie.ac.at/RNA.
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            Tuning genetic control through promoter engineering.

            Gene function is typically evaluated by sampling the continuum of gene expression at only a few discrete points corresponding to gene knockout or overexpression. We argue that this characterization is incomplete and present a library of engineered promoters of varying strengths obtained through mutagenesis of a constitutive promoter. A multifaceted characterization of the library, especially at the single-cell level to ensure homogeneity, permitted quantitative assessment correlating the effect of gene expression levels to improved growth and product formation phenotypes in Escherichia coli. Integration of these promoters into the chromosome can allow for a quantitative accurate assessment of genetic control. To this end, we used the characterized library of promoters to assess the impact of phosphoenolpyruvate carboxylase levels on growth yield and deoxy-xylulose-P synthase levels on lycopene production. The multifaceted characterization of promoter strength enabled identification of optimal expression levels for ppc and dxs, which maximized the desired phenotype. Additionally, in a strain preengineered to produce lycopene, the response to deoxy-xylulose-P synthase levels was linear at all levels tested, indicative of a rate-limiting step, unlike the parental strain, which exhibited an optimum expression level, illustrating that optimal gene expression levels are variable and dependent on the genetic background of the strain. This promoter library concept is illustrated as being generalizable to eukaryotic organisms (Saccharomyces cerevisiae) and thus constitutes an integral platform for functional genomics, synthetic biology, and metabolic engineering endeavors.
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              Engineering Cellular Metabolism.

              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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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                16 December 2020
                01 December 2020
                01 December 2020
                : 48
                : 22
                : 13000-13012
                Affiliations
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Engineering Biology Research Center, Kobe University , Kobe 657-8501, Japan
                Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo , Chiba 277-8561, Japan
                Technology Research Association of Highly Efficient Gene Design , Kobe 650-0047, Japan
                Technology Research Association of Highly Efficient Gene Design , Kobe 650-0047, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Engineering Biology Research Center, Kobe University , Kobe 657-8501, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Engineering Biology Research Center, Kobe University , Kobe 657-8501, Japan
                Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo , Chiba 277-8561, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Engineering Biology Research Center, Kobe University , Kobe 657-8501, Japan
                Graduate School of Science, Technology and Innovation, Kobe University , Kobe 657-8501, Japan
                Engineering Biology Research Center, Kobe University , Kobe 657-8501, Japan
                Department of Chemical Science and Engineering, Graduate School of Engineering, Kobe University , Kobe 657-8501, Japan
                Author notes
                To whom correspondence should be addressed. Tel: +81 78 803 6356; Fax: +81 78 803 6192; Email: junjun@ 123456port.kobe-u.ac.jp
                Correspondence may also be addressed to Akihiko Kondo. Tel: +81 78 803 6196; Fax: +81 78 803 6196; Email: akondo@ 123456kobe-u.ac.jp
                Author information
                http://orcid.org/0000-0002-1059-2519
                http://orcid.org/0000-0003-0909-4982
                http://orcid.org/0000-0003-2568-515X
                Article
                gkaa1066
                10.1093/nar/gkaa1066
                7736810
                33257988
                e15d1d28-04de-42c3-a117-effe6fc8255b
                © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 22 October 2020
                : 15 October 2020
                : 28 April 2020
                Page count
                Pages: 13
                Funding
                Funded by: Japan Agency for Medical Research and Development, DOI 10.13039/100009619;
                Award ID: JP19ae0101055
                Award ID: JP19ae0101060
                Funded by: New Energy and Industrial Technology Development Organization, DOI 10.13039/501100001863;
                Award ID: P16009
                Funded by: Japan Science and Technology Agency, DOI 10.13039/501100002241;
                Award ID: JPMJMI17EJ
                Categories
                AcademicSubjects/SCI00010
                Synthetic Biology and Bioengineering

                Genetics
                Genetics

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