Galaxy-SynBioCAD: Synthetic Biology Design Automation tools in Galaxy workflows

Abstract

Many computer-aided design tools are available for synthetic biology and metabolic engineering. Yet, these tools can be difficult to apprehend, sometimes requiring a level of expertise that limits their use by a wider community. Furthermore, some of the tools, although complementary, rely on different input and output formats and cannot communicate with one another. Scientific workflows address these shortcomings while offering a novel design strategy. Among the workflow systems available, Galaxy is a web-based platform for performing findable and accessible data analyses for all scientists regardless of their informatics expertise, along with interoperable and reproducible computations regardless of the particular platform that is being used.Here, we introduce the Galaxy-SynBioCAD a portal, the first Galaxy toolshed for synthetic biology and metabolic engineering. It allows one to easily create workflows or use those already developed by the community. The portal is a growing community effort where developers can add new tools and users can evaluate the tools performing design for their specific projects. The tools and workflows currently shared on the Galaxy-SynBioCAD portal cover an end-to-end metabolic pathway design process from the selection of strain and target to the calculation of DNA parts to be assembled to build libraries of strains to be engineered to produce the target.Standard formats are used throughout to enforce the compatibility of the tools. These include SBML for strain and pathway and SBOL for genetic layouts. The portal has been benchmarked on a galaxy-synbiocad.org 81 literature pathways, overall, we find we have a 65% (and 88%) success rate in retrieving the literature pathways among the top 10 (50) pathways predicted and generated by the workflows.

Recent trends in biocatalysis

“…Another webtool of this kind in the realm of synthetic biology pathway design is Galaxy SynbioCAD ( ). 18 SynbioCAD starts with a retrosynthetic pathway of a target compound. It then proposes the best biosynthetic pathways for the transformation, cloning strategies of the corresponding enzymes into target vectors and finally liquid handling protocols to execute the assembly of the complex vector constructs.…”

“…The model contains a hidden knowledge of protein architecture and could be by that a very powerful tool to annotate or even improve protein activity. Very powerful algorithms for predicting protein structures – one foundation of enzyme activity prediction – have been developed by DeepMind, a Google.com company: AlphaFold 2, 26 a community version of the AlphaFold algorithms with open source code is maintained by Wendy Billings et al 18 AlphaFold and related algorithms learn and predict distances between pairs of amino acids and bond angles within amino acid residues from large protein structure databases, like the PDB, by feeding deep neural networks. AlphaFold 2 won the 2020 Critical Assessment of Protein Structure Prediction contest (CASP14) with a highest Global Distance Test (GDT) score of 92.4.…”

Systems Biology in ELIXIR: modelling in the spotlight

“…Examples of workflows for systems and synthetic biology are embedded in the ESFRI IBISBA . SynBioCAD ( du Lac et al , 2020 ) is the first Galaxy toolshed for synthetic biology and metabolic engineering. These workflows are registered in workflowhub.eu .…”