To adapt, we integrate

The Cambridge 2022 iGEM Team

Gold Medal

Nomination for the Best New Basic Part (Special Prize)

Who are we?

We are Cambridge iGEM 2022, an undergraduate team, entirely organised and managed by PhD students. To tackle the problem of variability in cells we have designed a set of easily implementable integral controller circuits with applications across synthetic biology!

What is the problem?

Synthetic biology is incredible! It is the field which combines biology and engineering. It allows us the ability to design and create biology with crazy and new abilities. This includes applications to producing what we eat, our heath to space exploration! However, synthetic biology is fragile! Often what is done in the lab is not the same when applied to the real-world! One challenge is that biology is sensitive to perturbations!

Sad weak cell

What is our solution

To help tackle this fundamental challenge we are applying engineering principles from control theory to synthetic biology. This is the budding field of cybergenetics. We are creating a genetically encoded integral controller. An integral controller acts to hold production of a product at a reference level, and is robust to perturbations!

Happy strong cell

How did we do this?

Our project was split into three prongs: (1) modelling the circuits, (2) building circuits using JUMP cloning, (3) testing capacity for robustness. Within our project we used the core iGEM basis of the design-build-test-learn cycle. Integrating human practices in our design was crucial to ensure that our project has real-world value. Our factorial, combinatorial design is exemplar of the power of using engineering principles in synthetic biology design.

The three prongs of our project

What are its uses?

Our project is important to the field of synthetic biology as a whole! Specifically, our circuits could have direct applications in metabolic engineering, biomanufacturing and microbial drug delivery to name just a few! We designed a system that can be easily and quickly implemented, using any desired gene.

To adapt, we integrate