Team:Marburg/MedalCriteria

A C H I E V E M E N T S

“Great things are not done by impulse, but by a series of small things brought together.” -Vincent van Gogh

Bronze

  • Competition deliverables
    • We successfully took part in the competition and the Giant Jamboree by creating our wiki, designing our poster, holding our presentation and delivering our judging form.
  • Attributions
    • Since we could not have carried out our project without the support of many people, we would like to thank them for their support and are glad that we can honour them on our attributions page.
  • Project inspiration and description
    • Finding an interesting project on which everybody is passionate to work on can be a long way. We gave an insight into our inspiration and motivation for the project.
  • Contribution/Characterization
    • We expanded the Marburg Collection by 55 parts.
    • We added two new features for genetic engineering of cyanobacteria.
      • CRIPSR/Cas12a system.
      • M.E.G.A. expansion for homologue integrations into the cyano genome.
    • We designed two novel integration sites based on RNA-seq data.
    • We created the first MoClo compatible shuttle vector for cyanobacteria.
      • We used it to build standardized devices for characterization of BioBricks in cyanobacterial chassis. (Containing Spaceholders)
    • We chose to implement luminescence reporters for measurement of cyanobacteria because of the higher accuracy that is reasoned in the reduced background noise

Silver

  • Validated parts
    • We successfully built and validated our new spaceholder parts.
      • Which can reduce the costs and the workload significantly.
      • Calculated the amount of work required to assemble a promoter library with 20 parts compared to the same workload without our spaceholders (see "Workload and cost for placeholder").
  • Collaboration
    • Created the colony pictures collaboration.
      • We used the data received by the teams to build an open source colonie picker which can be used by all iGEM Teams with an Opentron OT-2.
    • Golden Gate Collaboration
      • Our team made itself the goal to introduce other iGEM Teams to Golden Gate. Therefore we hosted a webinar, build up a communication platform and made an interlab study to find the best Golden Gate Assembly protocol.
    • Smaller collaborations
      • Further we took part in different smaller collaborations and meet ups.
  • Human Practices
    • Since a large part of the population is not aware of green genetic engineering and often has a bad attitude towards it, we have tried to provide more information and insights into this topic by presenting our project at a local plant market and by organizing a panel discussion.
    • Further we talked to politicians to see their views and concerns on this topic.
  • Public Engagement
    • Hessian Day
      • On the Hessian Day we laid the foundation for the upcoming generation of synthetic biologists by showing the visitors (mainly children and teenagers) how to read the genetic code, how to do microscopy, showed pH indication and extracted DNA out of pepper.
    • March for Science
      • We joined over 200 other people in Frankfurt’s edition of the march for science and had the opportunity to engage with the general public about our research and iGEM.
    • Mayor Meeting
      • We were able to talk to the mayor of Marburg about iGEm in general, our project and the long term support for iGEM in Marburg concerning the financial and infrastructural support.

Gold

  • Integrated Human Practices
    • During our igem year we were able to establish many interesting contacts with companies and scientists. For many experts in the field of cyanobacteria, the standardization of cultivation conditions was a major factor, which is why we decided to take a closer look at it. During our igem year we were able to establish many interesting contacts with companies and scientists. For many experts in the field of cyanobacteria, the standardization of cultivation conditions was a major factor.
      • This is why we decided to take a closer look at it and analyzed growth conditions with our growth curve model to make firsts steps in the standardization process.
    • During the contact with Promega and other experts in the field, we were made aware of the potential of automated plasmid purification. During our iGEM year we were able to integrate the information we received into our project and were able to address the problems and automate the process.
      • Automated the plasmid purification for up to 48 samples.
    • Opentrons (Kristin Ellis), Keoni Gandall and Doulix took part in our biggest cooperation while we worked on making the Opentrons OT-2 pick single colonies by adding a camera and a raspberry pi to its arm and training an A.I. with colony pictures.
      • Through the contact with them we were able to integrate and successfully implement important points in our project.
  • Improve a previous part or project.
    • Implementing NanoLuc and TeLuc as improved reporters to reduce the background noise experienced by measuring with fluorescent proteins in plants.
  • Model your project
    • We modeled the light intensities of our incubator.
      • As the light intensity is measured with different methods and devices in each publication we wanted to show a good standardized measurement method and created our model based on this data. With our model we were able to cultivate our different cultures at the same light conditions.
    • Growth curve model
      • We measured a lot of growth curves with varying parameters during our project and used the gained data to feed a growth curve model that should predict the growth of UTEX 2973 at specific conditions.
    • Terminator model
      • As terminators play a important role especially in S. elongatus and because of the high interest of the cyano community we modelled terminators by using different bioinformatic tools and later tested three candidates by measuring their efficiency in vivo.
    • Finding two new neutral integration sites.
      • We searched for new integration sites that are independent of the genomic and cellular context. Therefore we analyzed gene transcription data for possible regions in the genome by developing a custom Python based algorithm and found two new sites.

Additionals

  • We optimized the growth of UTEX 2973 and reached a doubling time of under 80 min.