Biology subjects

Faulon, J.-L.

Publications and source records attributed to Faulon, J.-L..

5 recordsLinked to original sources

bioRxiv2018

Plug-and-Play Metabolic Transducers Expand the Chemical Detection Space of Cell-Free Biosensors

Cell-free transcription-translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a framework to expand the range of molecules detectable by cell-free biosensors by combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors are highly-sensitive and have a fast response and high-dynamic range. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.

synthetic biology↗

bioRxiv2017

Selenzyme: Enzyme selection tool for pathway design

Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions; and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries. The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http://selenzyme.synbiochem.co.uk.

bioinformatics↗

bioRxiv2017

PartsGenie: an integrated tool for optimising and sharing synthetic biology parts

Synthetic biology is typified by developing novel genetic constructs from the assembly of reusable synthetic DNA parts, which contain one or more features such as promoters, ribosome binding sites, coding sequences and terminators. While repositories of such parts exist to promote their reuse, there is still a need to design novel parts from scratch.\n\nPartsGenie, freely available at http://parts.synbiochem.co.uk, is introduced to facilitate the computational design of such synthetic biology parts. PartsGenie has been designed to bridge the gap between optimisation tools for the design of novel parts, the representation of such parts in community-developed data standards such as Synthetic Biology Open Language (SBOL), and their sharing in journal-recommended data repositories.\n\nConsisting of a drag-and-drop web interface, a number of DNA optimisation algorithms, and an interface to the well-used data repository JBEI ICE, PartsGenie facilitates the design, optimisation and dissemination of reusable synthetic biology parts through a single, integrated application. PartsGenie can therefore be used as a single, stand-alone tool, or integrated into larger synthetic biology pipelines that are being developed in the SYNBIOCHEM centre and elsewhere.

synthetic biology↗

bioRxiv2017

Molecular structures enumeration and virtual screening in the chemical space with RetroPath2.0

BackgroundNetwork generation tools coupled with chemical reaction rules have been mainly developed for synthesis planning and more recently for metabolic engineering. Using the same core algorithm, these tools apply a set of rules to a source set of compounds, stopping when a sink set of compounds has been produced. When using the appropriate sink, source and rules, this core algorithm can be used for a variety of applications beyond those it has been developed for.\n\nResultsHere, we showcase the use of the open source workflow RetroPath2.0. First, we mathematically prove that we can generate all structural isomers of a molecule using a reduced set of reaction rules. We then use this enumeration strategy to screen the chemical space around a set of monomers and predict their glass transition temperatures, as well as around aminoglycosides to search structures maximizing antibacterial activity. We also perform a screening around aminoglycosides with enzymatic reaction rules to ensure biosynthetic accessibility. We finally use our workflow on an E. coli model to complete E. coli metabolome, with novel molecules generated using promiscuous enzymatic reaction rules. These novel molecules are searched on the MS spectra of an E. coli cell lysate interfacing our workflow with OpenMS through the KNIME analytics platform.\n\nConclusionWe provide an easy to use and modify, modular, and open-source workflow. We demonstrate its versatility through a variety of use cases including, molecular structure enumeration, virtual screening in the chemical space, and metabolome completion. Because it is open source and freely available on MyExperiment.org, workflow community contributions should likely expand further the features of the tool, even beyond the use cases presented in the paper.

systems biology↗

bioRxiv2017

RetroPath2.0: A retrosynthesis workflow for metabolic engineers

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 bioproduction 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 of this tool a valuable addition into 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.\n\nHighlightsO_LIState-of-the-art Computer-Aided Design retrosynthesis solutions lack open source and ease of use\nC_LIO_LIWe propose RetroPath2.0 a modular and open-source workflow to perform retrosynthesis\nC_LIO_LIRetroPath2.0 computes reaction network between Source and Sink sets of compounds\nC_LIO_LIRetroPath2.0 is distributed as a KNIME workflow for desktop computers\nC_LIO_LIRetroPath2.0 is ready-for-use and distributed with reaction rules\nC_LI\n\nFundingThis work was supported by the French National Research Agency [ANR-15-CE1-0008], the Biotechnology and Biological Sciences Research Council, Centre for synthetic biology of fine and speciality chemicals [BB/M017702/1]; Synthetic Biology Applications for Protective Materials [EP/N025504/1], and GIP Genopole.

systems biology↗