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Synthetic Metabolic Pathways

Overview of attention for book
Cover of 'Synthetic Metabolic Pathways'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Parts Characterization for Tunable Protein Expression
  3. Altmetric Badge
    Chapter 2 Enzyme Nicotinamide Cofactor Specificity Reversal Guided by Automated Structural Analysis and Library Design
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    Chapter 3 Bacterial Genome Editing Strategy for Control of Transcription and Protein Stability
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    Chapter 4 An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization
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    Chapter 5 Computational Approaches on Stoichiometric and Kinetic Modeling for Efficient Strain Design
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    Chapter 6 Extended Metabolic Space Modeling
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    Chapter 7 Computational Methods to Assess the Production Potential of Bio-Based Chemicals
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    Chapter 8 Multiplex Genome Editing in Escherichia coli
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    Chapter 9 Designing and Implementing Algorithmic DNA Assembly Pipelines for Multi-Gene Systems
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    Chapter 10 An Adaptive Laboratory Evolution Method to Accelerate Autotrophic Metabolism
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    Chapter 11 CRISPR-Cas9 Toolkit for Actinomycete Genome Editing
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    Chapter 12 Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR
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    Chapter 13 A Modified Gibson Assembly Method for Cloning Large DNA Fragments with High GC Contents
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    Chapter 14 Coupling Yeast Golden Gate and VEGAS for Efficient Assembly of the Violacein Pathway in Saccharomyces cerevisiae
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    Chapter 15 Multi-capillary Column Ion Mobility Spectrometry of Volatile Metabolites for Phenotyping of Microorganisms
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    Chapter 16 Selection of Highly Expressed Gene Variants in Escherichia coli Using Translationally Coupled Antibiotic Selection Markers
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    Chapter 17 Design, Engineering, and Characterization of Prokaryotic Ligand-Binding Transcriptional Activators as Biosensors in Yeast
  19. Altmetric Badge
    Chapter 18 A Capture-SELEX Strategy for Multiplexed Selection of RNA Aptamers Against Small Molecules
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    Chapter 19 High-Throughput Microfluidics for the Screening of Yeast Libraries
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    Chapter 20 Growth-Coupled Carotenoids Production Using Adaptive Laboratory Evolution
  22. Altmetric Badge
    Chapter 21 Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering
Attention for Chapter 12: Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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Chapter title
Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR
Chapter number 12
Book title
Synthetic Metabolic Pathways
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7295-1_12
Pubmed ID
Book ISBNs
978-1-4939-7294-4, 978-1-4939-7295-1
Authors

Tadas Jakočiūnas, Emil D. Jensen, Michael K. Jensen, Jay D. Keasling

Abstract

Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 24%
Researcher 6 21%
Student > Doctoral Student 3 10%
Professor > Associate Professor 3 10%
Student > Master 2 7%
Other 4 14%
Unknown 4 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 45%
Agricultural and Biological Sciences 8 28%
Engineering 2 7%
Immunology and Microbiology 1 3%
Chemical Engineering 1 3%
Other 0 0%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2018.
All research outputs
#12,764,378
of 23,008,860 outputs
Outputs from Methods in molecular biology
#3,174
of 13,157 outputs
Outputs of similar age
#199,350
of 442,295 outputs
Outputs of similar age from Methods in molecular biology
#258
of 1,498 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,295 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.