It Takes a Village: Automating Plasmid Purification for iGEM

Today’s blog is guest-written by Wihan Adi, a Master’s student majoring in physics at Justus-Liebig-University in Giessen and team member of iGEM Marburg. Although his background is in nuclear and particle physics, his research interests shifted toward affordable biosensors for point-of-care cancer detection, which is how he ended up doing microbiology for iGEM.


Back in March when the iGEM season had just started, Maurice, a fellow iGEM Marburg team member, told me that he was exchanging emails with Margaretha Schwartz from Promega. Given my background as a physics student, Promega was not a household name for me at the time. “So, are you interested in automating a plasmid purification protocol?” asked Maurice. He told me that Promega was willing to supply the Wizard® MagneSil® Plasmid Purification System for this purpose; that was another name that added to my confusion.

This year, iGEM Marburg is aiming to establish a fast phototrophic organism as a synthetic biology chassis. For this goal we chose Synechococcus elongatus UTEX 2973, with a reported doubling time of 90 minutes. More specifically, we are creating an easy to use toolbox to empower rapid design testing, including genome engineering tools, self-replicating plasmid systems, natural competence and a Golden Gate-based part library. Our team chose to work on phototrophic organisms because we envision accelerating research in this particular field. (Note: Last year, Marburg’s iGEM project won the Grand Prize!)

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Overcoming Challenges When Scaling Antibody Production

Tradeoffs are a constant source of challenge in any research lab. To get faster results, you will probably need to use more resources (people, money, supplies). The powerful lasers used to do live cell imaging may well kill those cells in the process. Purifying DNA often leaves you to choose between purity and yield.

Robot performing autosampling

Working with biologics also involves a delicate balancing act. Producing compounds in biological models rather than by chemical synthesis offers many advantages, but it is not without certain challenges. One of those tradeoffs results from scaling up; the more plasmid that is produced, the greater probability of endotoxin contamination.

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