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Quantitative Tracking of Combinatorially Engineered Populations with Multiplexed Binary Assemblies.
Zeitoun, Ramsey I; Pines, Gur; Grau, Willliam C; Gill, Ryan T.
Afiliação
  • Zeitoun RI; Department of Chemical and Biomolecular Engineering, University of Colorado , 596 UCB Boulder, Colorado 80303, United States.
  • Pines G; Department of Chemical and Biomolecular Engineering, University of Colorado , 596 UCB Boulder, Colorado 80303, United States.
  • Grau WC; Department of Chemical and Biomolecular Engineering, University of Colorado , 596 UCB Boulder, Colorado 80303, United States.
  • Gill RT; Department of Chemical and Biomolecular Engineering, University of Colorado , 596 UCB Boulder, Colorado 80303, United States.
ACS Synth Biol ; 6(4): 619-627, 2017 04 21.
Article em En | MEDLINE | ID: mdl-28103008
ABSTRACT
Advances in synthetic biology and genomics have enabled full-scale genome engineering efforts on laboratory time scales. However, the absence of sufficient approaches for mapping engineered genomes at system-wide scales onto performance has limited the adoption of more sophisticated algorithms for engineering complex biological systems. Here we report on the development and application of a robust approach to quantitatively map combinatorially engineered populations at scales up to several dozen target sites. This approach works by assembling genome engineered sites with cell-specific barcodes into a format compatible with high-throughput sequencing technologies. This approach, called barcoded-TRACE (bTRACE) was applied to assess E. coli populations engineered by recursive multiplex recombineering across both 6-target sites and 31-target sites. The 31-target library was then tracked throughout growth selections in the presence and absence of isopentenol (a potential next-generation biofuel). We also use the resolution of bTRACE to compare the influence of technical and biological noise on genome engineering efforts.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Engenharia Genética Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Engenharia Genética Idioma: En Ano de publicação: 2017 Tipo de documento: Article