Programming Cells By Multiplex Genome Engineering And Accelerated Evolution Pdf

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Protocol DOI: Generating mutant strains is an essential component of microbial genetics. Natural genetic transformation, a process for the uptake and integration of foreign DNA, is shared by diverse microbial species and can be exploited for making mutant strains.

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Multiplex Genome Engineering Methods for Yeast Cell Factory Development

Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments 1 , 2.

However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales 3.

Although in vitro and directed evolution methods 4 , 5 , 6 , 7 , 8 , 9 have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes.

Here, we describe multiplex automated genome engineering MAGE for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes mismatches, insertions, deletions.

We applied MAGE to optimize the 1-deoxy- d -xylulosephosphate DXP biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.

Venter, J. Environmental genome shotgun sequencing of the Sargasso Sea. Science , 66—74 Tringe, S. Comparative metagenomics of microbial communities. Science , — Elena, S. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation.

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Nature Biotechnol. Cadwell, R. Randomization of genes by PCR mutagenesis. PCR Methods Appl. Shendure, J. Accurate multiplex polony sequencing of an evolved bacterial genome. A new logic for DNA engineering using recombination in Escherichia coli. Nature Genet. Costantino, N. Natl Acad. USA , — Sharan, S. Recombineering: a homologous recombination-based method of genetic engineering. Nature Protocols 4 , — Ellis, H. High efficiency mutagenesis, repair, and engineering of chromosomal DNA using single-stranded oligonucleotides.

USA 98 , — Markham, N. DINAMelt web server for nucleic acid melting prediction. Nucleic Acids Res. Jin, Y. Multi-dimensional gene target search for improving lycopene biosynthesis in Escherichia coli.

Kang, M. Identification of genes affecting lycopene accumulation in Escherichia coli using a shot-gun method. Chen, H. Determination of the optimal aligned spacing between the Shine — Dalgarno sequence and the translation initiation codon of Escherichia coli mRNAs. Alper, H. Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli. Construction of lycopene-overproducing E. Farmer, W. Precursor balancing for metabolic engineering of lycopene production in Escherichia coli.

Kim, S. Metabolic engineering of the nonmevalonate isopentenyl diphosphate synthesis pathway in Escherichia coli enhances lycopene production. Yuan, L. Chromosomal promoter replacement of the isoprenoid pathway for enhancing carotenoid production in E. Khosla, C. Metabolic engineering for drug discovery and development. Drug Discov. Cropp, T. An expanding genetic code. Trends Genet. Gibson, D. Complete chemical synthesis, assembly, and cloning of a Mycoplasma genitalium genome.

Metzgar, D. Acinetobacter sp. ADP1: an ideal model organism for genetic analysis and genome engineering. Nakayama, M. Improvement of recombination efficiency by mutation of Red proteins.

Biotechniques 38 , — Datta, S. Identification and analysis of recombineering functions from Gram-negative and Gram-positive bacteria and their phages. Tian, J. Accurate multiplex gene synthesis from programmable DNA microchips. Yu, D. An efficient recombination system for chromosome engineering in Escherichia coli. USA 97 , — Cunningham, F.

Molecular structure and enzymatic function of lycopene cyclase from the cyanobacterium Synechococcus sp strain PCC Plant Cell 6 , — Download references. We are grateful to J. Jacobson for his insights and advice throughout this work. We thank D. Court for his insights and sharing strain DY, N. Reppas for advice and sharing strain EcNR2, F. Sterling for assistance in constructing the EcFI5 strain. We also thank M.

Recent advances in genetic engineering tools based on synthetic biology

Metrics details. We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies. Genome editing and DNA synthesis technologies are enabling the construction of engineered organisms with synthetic metabolic pathways [ 1 ], reduced and refactored genomes [ 2 , 3 , 4 , 5 ], and expanded genetic codes [ 6 , 7 ].

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Here, we describe multiplex automated genome engineering (MAGE) for large-​scale programming and evolution of cells. MAGE simultaneously targets many by multiplex genome engineering. and accelerated evolution.

Multiplex Automated Genome Engineering (MAGE)

Genome-scale engineering is a crucial methodology to rationally regulate microbiological system operations, leading to expected biological behaviors or enhanced bioproduct yields. Over the past decade, innovative genome modification technologies have been developed for effectively regulating and manipulating genes at the genome level. Here, we discuss the current genome-scale engineering technologies used for microbial engineering.

Conjugative Assembly Genome Engineering (CAGE)

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As biotechnological applications of synthetic biology tools including multiplex genome engineering are expanding rapidly, the construction of strategically designed yeast cell factories becomes increasingly possible. Multiplex genome engineering approaches can expedite the construction and fine tuning of effective heterologous pathways in yeast cell factories. Numerous multiplex genome editing techniques have emerged to capitalize on this recently. This review focuses on recent advancements in such tools, such as delta integration and rDNA cluster integration coupled with CRISPR-Cas tools to greatly enhance multi-integration efficiency. Examples of pre-placed gate systems which are an innovative alternative approach for multi-copy gene integration were also reviewed.

The system can't perform the operation now. Try again later. Citations per year. Duplicate citations. The following articles are merged in Scholar. Their combined citations are counted only for the first article.

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    Programming cells by multiplex genome engineering and accelerated evolution. Harris H. Wang.

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