Mass spectrometry and metabolomics data analysis for synthetic biology
Maria Vinaixa, Synthetic Biology for Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology.
- 14/07/2017 10:00 - 11:00
- Institute for Bioengineering of Catalonia (IBEC)
- IBEC: Baldiri Reixac 4-8, floor 11, Tower I ; 08028 Barcelona, Spain
Maria Vinaixa from the Manchester Institute of Biotechnology will be talking about her work on metabolomics data analysis pipelines to better understand fundamental biological processes.
Synthetic biology builds upon the creation of new biologically inspired standardized parts that can be put together using design or simulations tools to build circuits that will create de-novo biological functions or modify existing ones. Using synthetic biology, microbial cell factories can be engineered to provide new sustainable bio-routes for the production of fuels, biopharmaceuticals, fragrances, and food flavors among others. In this regard, the SYNBIOCHEM Centre (www.synbiochem.co.uk) has set-up an automated Design/Build/Test/Learn pipeline designed to provide access to target fine chemicals through iterative, rapid and predictable engineering of production pathways and microbial strains. This pipeline moves from Design of new parts (e.g. enzymes, regulatory circuits, metabolic pathways), through to combinatorial high-throughput Build approaches (directed evolution, components, pathways and strain assembly) and high-throughput analytics in Test (product extraction, instrumental analysis, data analysis and sharing) feeding back to improved designs via an active Learning stage at each cycle iteration. This pipeline allows unprecedented possibilities for retro biosynthesis of non-natural products and for the expansion of natural products chemical diversity. Screening for the small-molecule structure diversity emanating from such pipeline is an analytically daunting challenge. In this regard, mass spectrometry (MS) is a key analytical technology offering the high throughput screening capabilities as well as the versatility needed to cope with such chemical diversity. However, curating MS data and merging it with all other types of data generated through iterative D/B/T/L cycle so that it can be used to learn and redesign remains a challenge. Despite Metabolomics has powered computational solutions for MS data analysis; such solutions do only partially cover the needs within a synthetic biology context. Thus, we are building the next generation computational toolbox for MS data analysis and storage so it can be harvested across the entire pipeline. In this seminar, main capabilities and functionalities on such toolbox are going to be discussed.