2021 Global Biofoundries Webinar Series

April 20th , 2021 at 1-2 pm


Johannes Kabisch organizes together with Nicola Patron the Webinar series "2021 Global Biofoundries Alliance Webinar Series“ am 20. April 2021 @ 1-2 pm CET. Information about the speakers can be found below. Please register here in advance for this webinar A recording of the webinar will be made publicly available after the event for those unable to attend.

Please Join us for our next GBA webinar. Dr Le Feuvre will discuss Rapid prototyping and automated strain engineering for next-generation sustainable biomanufacturing. Dr Mark Dörr will be discussing Robot and machine learning assisted protein engineering on the high-throughput screening platform LARA.

Dr Rosalind Le Feuvre, Director of Operations, SYNBIOCHEM and Future BRH, Manchester Institute of Biotechnology, UK.

The application of predictive synthetic biology to rapidly engineer microbial cell factories promises to deliver new sustainable chemicals biomanufacture across industrial sectors (e.g., pharmaceuticals, green chemistry, novel materials, and advanced synthetic fuels).

In this Manchester Biofoundry talk I will discuss the development of an automated compound agnostic Design/Build/Test/Learn pipeline that integrates design software tools, automated build workflows and optimised analytical test screening to rapidly prototype microbial production routes for diverse chemicals/materials manufacture.

The transition from laboratory prototyping to production at scale and delivery of next-generation sustainable biomanufacturing processes requires major technical, scientific and economic challenges to be overcome.

Global Biofoundries will play a central role in the development of agile pipelines and reduce the delivery time from initial strain screening and prototyping towards industrial production that will accelerate the delivery of economically attractive, robust and scalable biomanufacturing processes to meet societal and commercial demand.

Dr. Mark Dörr, Head of LARA Platform, Institute for Biochemistry, University Greifswald, Germany.

The University Greifswald robotic platform LARA (lara.uni-greifswald.de) is designed for high-throughput protein/enzyme screening. It consists of a central industrial robotic arm (Fanuc) serving 4 incubators (Thermo Cytomat 2), one centrifuge (Hettich Rotanta 460 R), one liquid handling station (Agilent bravo) and two plate readers (Thermo varioskan). Currently the platform is driven by Thermo's propitiatory control software Momentum. In my talk I will present our efforts to completely move towards python based open source solutions, only using open standards, like SiLA (sila-standard.org) and AnIML (animl.org). For this purpose, a free and open source software suite, the LARAsuite (gitlab.com/LARAsuite) is developed. It shall be used to plan and structure the current project with its project-management modules, operate the (automated) experiments with the LARA process manager (gitlab.com/opensourcelab/pythonlabscheduler) and finally store and visualize the data, fully supporting the requirements of the FAIR principles. The LARAsuite provides a semantically annotated database of most aspects of experimentation, it is therefore perfectly suited to structure and organize the data, including most information about the performed experiments. The LARAsuite also contains modules to exchange selected data sets and processes in a standardized way (SiLA, gRPC, SPARQL). These data exchange modules will be used to transfer automatable protocols, which are developed at one partner to the other partner. Lab- and automation processes are stored in a device-independent lab process description language (pythonLab, gitlab.com/opensourcelab/pythonLab). The process steps can then be mapped to a specific laboratory / lab automation system. With the mapping at hand, it is possible to execute the same processes on the target system, if all required lab instrumentation interfaces (SiLA servers) are available. This enables a transfer of processes from one laboratory to another platform.