Forbidden FRUITS



Humanity shares the collective responsibility to reduce the ecological footprint as much as possible. For many years we have been taking our natural resources for granted, consumption has been growing and the atmosphere has been filling up with CO2. The conversion of CO2 into products is the foundation of the bio-based economy, which has the potential to replace the use of oils. Therefore, the need for a bio-based economy has gained much interest over recent years. Right now, we see that the industry is growing and has diversified by using a variety of microorganisms to produce compounds, which we call “cell factories”. 

A major problem with cell factories is the genetic instability of engineered strainsthat eventually lead to phenotypic instability. This basically means that genetic changes leading to production are not essential and cost energy for microorganisms. Over time, evolution will enter the stage and a faster-growing non-producing microorganism will outcompete the producing microorganism.

Reducing instability by coupling growth to production

In order to maintain production within a cell factory, we have to make it beneficial or obligatory for cells to grow. Coupling production to growth could be achieved by metabolic engineering experts doing extensive research. The most recent insights in metabolic networks and enzymatic reactions need to be combined in order to get the best design but this can take up a significant amount of time. An algorithm that can formulate genetic strategies for stable production within any microorganism like our project “Forbidden FRUITS” could allow for faster and safer development of cell factories and could potentially revolutionize biotechnology.

Do current algorithms not suffice?

Metabolic engineering suffers from the complexity of metabolic networks. Many tools have been designed to perform simulations on metabolic networks to design gene knockout strategies to obtain phenotypically improved industrial strains. However, the problem of finding optimal genetic strategies is combinatorial and, consequently, the computational time increases exponentially with the size of the problem. Besides computational complexity, biological complexity adds another layer to the implementation of these strategies. Most existing pipelines focus on solving aspects of either one, which means that they do not take most things into account.

How do we solve this?

Our in silico tool “Forbidden FRUITS” has been constructed with a design philosophy that includes: 1) modularity, to break large problems in smaller parts and dividing the responsibilities, and 2) extendability, to separate general and specific aspects which allow for variation. Additionally, we aim to use the most up-to-date metabolic information from multiple databases, incorporate gene protein reaction associations (GPRAs) and incorporate optimization steps. In this way, we hope to develop a tool that can predict genetic strategies for the production of any compound within any microorganism in a faster and more accurate way.

Future prospect

The acceleration of climate change and pollution leads to a growing need for sustainable alternatives. Therefore, we envision a faster implementation of genetically engineered microbial production systems within the industry. Which pace still partially depends on the discussion surrounding GMOs and legislation. With Forbidden FRUITS we already have the infrastructure in place to provide the world with safer and stable genetically engineered production systems. During this year of iGEM, our team has more confidence than ever that Forbidden FRUITS will revolutionize biotechnology.

Human Practices

In this section we stored and summarized all the valuable conversations we had with experts in the field of biotechnology to help us prioritize the needs for our Forbidden FRUITS project.

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Education & Engagement

Here we will demonstrate how we tried to engage with the general public and teach them about sustainable microbial production systems and the details of our project.

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The parts for the Forbidden FRUITS algorithm have all been developed separately. Here we present our biggest successes: the merger, the network transformation based on gene-protein-reaction associations and the ‘cheap-lunch’ strategy-finder. 

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The genetic strategies generated by Forbidden FRUITS need to be validated in the lab. Therefore, we came up with a proof-of-concept to check the viability of producing different compounds in a variety of microorganisms.

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Forbidden FRUITS

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