SYNBIOCHEM Design-Build-Test-Learn pipeline

Published: 2 May 2018| Version 1 | DOI: 10.17632/8g4wfwtd43.1
Contributors:
Pablo Carbonell,
Adrian Jervis,
Christopher J Robinson,
Cunyu Yan,
Mark Dunstan,
Neil Swainston,
Maria Vinaixa,
Katherine Hollywood,
Andrew Currin,
Nicholas Rattray,
Sandra Taylor,
Reynard Spiess,
Rehana Sung,
Alan Williams,
Donal Fellows,
Natalie Stanford,
Paul Mulherin,
Ros Le Feuvre,
Perdita Barran,
Royston Goodacre,
Nicholas Turner,
Carole Goble,
George G Chen,
Douglas B Kell,
Jason Micklefield,
Rainer Breitling,
Eriko Takano,
Jean-Loup Faulon,
Nigel S Scrutton

Description

Quantified titers and peak values measured through different rounds of the SYNBIOCHEM Design-Build-Test-Learn (DBTL) pipeline for microbial production of fine chemicals. The pipeline was applied for the production of flavonoids and alkaloids in Escherichia coli. The flavonoids data contains cinnamate and (2S)-pinocembrin measurements for combinatorial libraries for: a) DBT round 1; b) DBT round 2; c) Chassis selection; d) Media screening; e) Optimization. The alkaloids data provides (S)-reticuline and (S)-scoulerine measurements for a combinatorial library corresponding to one DBTL round.

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Institutions

The University of Manchester

Categories

Synthetic Biology, Metabolic Engineering

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