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Quantitative Tracking of Combinatorially Engineered Populations with Multiplexed Binary Assemblies.

Ramsey I Zeitoun1, Gur Pines1, Willliam C Grau1

  • 1Department of Chemical and Biomolecular Engineering, University of Colorado , 596 UCB Boulder, Colorado 80303, United States.

ACS Synthetic Biology
|January 20, 2017
PubMed
Summary
This summary is machine-generated.

Scientists developed barcoded-TRACE (bTRACE), a new method to map engineered genomes and track performance in microbial populations. This advance aids complex biological system engineering and biofuel development.

Keywords:
DNA assemblygenome engineeringhigh throughput sequencingsynthetic biology

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Area of Science:

  • Synthetic biology
  • Genomics
  • Metabolic engineering

Background:

  • Genome engineering advances enable rapid manipulation of microbial systems.
  • Lack of system-wide performance mapping hinders complex biological engineering.
  • Sophisticated algorithms require robust methods to link genotype to phenotype.

Purpose of the Study:

  • To develop a quantitative method for mapping engineered genomes at system-wide scales.
  • To enable the adoption of advanced algorithms for engineering complex biological systems.
  • To assess engineered microbial populations and track their performance during selection.

Main Methods:

  • Developed barcoded-TRACE (bTRACE), a method to assemble engineered genome sites with cell-specific barcodes.
  • Formatted data for high-throughput sequencing compatibility.
  • Applied bTRACE to assess E. coli populations engineered with up to 31 target sites.

Main Results:

  • Successfully mapped combinatorially engineered populations at scales up to 31 target sites.
  • Tracked engineered E. coli populations during growth selection with and without isopentenol.
  • Quantified the influence of technical and biological noise on genome engineering outcomes.

Conclusions:

  • bTRACE provides a robust approach for quantitative genome-wide mapping of engineered populations.
  • This method facilitates the engineering of complex biological systems and the development of next-generation biofuels.
  • bTRACE enables detailed analysis of noise factors impacting genome engineering efficiency.