RetroPath2.0: A retrosynthesis workflow for metabolic engineers

Abstract

Synthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering, the research and development process still remains costly. In order to expand the chemical repertoire for the production of next generation compounds, a major engineering biology effort is required in the development of novel design tools that target chemical diversity through rapid and predictable protocols. Addressing that goal involves retrosynthesis approaches that explore the chemical biosynthetic space. However, the complexity associated with the large combinatorial retrosynthesis design space has often been recognized as the main challenge hindering the approach. Here, we provide RetroPath2.0, an automated open source workflow for retrosynthesis based on generalized reaction rules that perform the retrosynthesis search from chassis to target through an efficient and well-controlled protocol. Its easiness of use and the versatility of its applications make this tool a valuable addition to the biological engineer bench desk. We show through several examples the application of the workflow to biotechnological relevant problems, including the identification of alternative biosynthetic routes through enzyme promiscuity or the development of biosensors. We demonstrate in that way the ability of the workflow to streamline retrosynthesis pathway design and its major role in reshaping the design, build, test and learn pipeline by driving the process toward the objective of optimizing bioproduction. The RetroPath2.0 workflow is built using tools developed by the bioinformatics and cheminformatics community, because it is open source we anticipate community contributions will likely expand further the features of the workflow.

An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals

“…For any given target compound, tools for automated pathway and enzyme selections are RetroPath 9 and Selenzyme 10 (http://selenzyme.synbiochem.co.uk), respectively. Reusable DNA parts are then designed with the simultaneous optimization of bespoke ribosome-binding sites and enzyme coding regions using the in-house-developed PartsGenie software 11 (https://parts.synbiochem.co.uk).…”

“…The pipeline uses the retrosynthesis workflow of RetroPath 9 , and the enzyme sequence selection tool Selenzyme 10 (http://selenzyme.synbiochem.co.uk) to mine available biochemical knowledge 26 and allow the initial selection of production pathway(s) through the application of reaction rules-based retrosynthesis; and of enzymes based on biochemical reaction similarity at each transformation step in the pathway. Initial synthetic pathways for pinocembrin were selected based on a RetroPath design 21 ; genes for reticuline/scoulerine biosynthesis were selected from Coptis japonica 27 .…”

Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non‐traditional microorganisms

“…A much needed further step into this direction would be to rationally combine the different tools so far developed for genome engineering and experimentally curated computational prediction [e.g. retrosynthesis approaches (Delépine et al ., )] for designing entirely novel (i.e. synthetic) metabolic architectures that can be plugged‐in into any given bacterial chassis .…”

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data‐Driven Metabolic Engineering

“…Much work has been pursued to integrate mining processes, reaction rule generation, rule ranking, and final pathway proposal into cohesive, user‐friendly pipelines . For more in‐depth coverage on de novo pathway design, several other review areas are available on the subject …”