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A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
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Validation of RetroPath, a computer-aided design tool for metabolic pathway engineering
Tamás Fehér1, Anne-Gaëlle Planson, Pablo Carbonell
1Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Evry Cedex, France.
Biotechnology Journal
|September 17, 2014
Summary
Computer-aided design (CAD) tool RetroPath rationalizes metabolic engineering by identifying optimal biosynthetic pathways. This tool successfully guided the production of pinocembrin, demonstrating its effectiveness in discovering novel compound biosynthesis.
Area of Science:
- Metabolic Engineering
- Synthetic Biology
- Computational Biology
Background:
- Metabolic engineering for compound biosynthesis often relies on ad hoc pathway selection or expert knowledge.
- Rationalizing strain engineering requires systematic approaches to pathway and enzyme identification.
Purpose of the Study:
- To develop a computer-aided design (CAD) tool, RetroPath, for exploring and enumerating metabolic pathways.
- To validate RetroPath's efficacy in identifying efficient biosynthetic routes for target compounds.
Main Methods:
- RetroPath queries metabolic databases for enzymes based on annotated and predicted activities.
- Pathways are ranked by predicted enzyme efficiency, intermediate toxicity, and maximum product flux.
- Experimental validation involved constructing and testing enzyme combinations for pinocembrin production.
Main Results:
- RetroPath identified 12 enzyme combinations for pinocembrin biosynthesis from millions of possibilities.
- Four of the tested combinations yielded significant amounts of pinocembrin.
- Metabolic network optimization based on RetroPath output increased pinocembrin titers 17-fold.
- Enzyme performance generally matched RetroPath's predictions.
Conclusions:
- RetroPath effectively rationalizes metabolic engineering by predicting and ranking biosynthetic pathways.
- The tool's ranking function is validated, enabling its use for novel compound biosynthesis.
