Software tools help companies to engineer microbes efficiently

Tuesday 13 Nov 18
by Anders Mønsted, Anne Lykke

Establishing performant cell factories by trial-and-error may possibly lead to frustration and the loss of the single most valuable resource, our time. But what if there was a way to eliminate dead-end strategies before spending weeks in the lab? Here are three tools, that together allow you to do just that.

The Novo Nordisk Foundation Center for Biosustainability at Technical University of Denmark (DTU) is maintaining and developing a range of software tools that are open source and promote open science. Hence, the tools are free to use ­– so jump right in!

"COBRApy is a foundational tool for both systems and synthetic biology and I could not do my work without it"
Joshua Lerman, Scientist 2 at Amyris

COBRApy is a package for constraint-based modeling of metabolic networks written in Python. The tool strives to become the reference software library for doing genome-scale metabolic modeling by providing the essentials (data structures, simulation methods, and model import/export) that others can base their more specialized software tools on.

“If you have a techno-economic analysis and you know that you need to reach a certain production goal in order to be commercially interesting, then a metabolic model can tell you whether you are even able to reach your goal. These models are in general very good at telling you what definitely won’t work,” says Nikolaus Sonnenschein, Senior Researcher at The Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) at Technical University of Denmark.

Joshua Lerman, Scientist 2 at the pharmaceutical biotech company Amyris, is using COPRApy for a broad range of tasks. For instance, to predict knock-out targets, to find high yield routes to target molecules in yeast, to calculate maximum theoretical yields and productivities and to evaluate which reactions might drain flux off the pathway:

“This software is amazing and setting the standard for genome scale modeling. COBRApy is a foundational tool for both systems and synthetic biology and I could not do my work without it," he says.

At the bioinformatics company Zymergen, PhD in Chemical Engineering Janet Matsen also uses COBRApy:

“When we aim to increase the rate of chemical production, we are really aiming to change the rates of chemical reactions in the cell.  Thus, information about fluxes is extremely valuable. COBRApy is the most useful software available to get such information.”

She emphasizes that it is an extremely valuable tool for them:

“Writing an equivalent tool to support our needs would take the time of 1-2 full-time employees.”

At LanzaTech, Senior Scientist in Computational Biology James Daniell and his colleagues also use COBRApy to run computer models that predict the behaviour of microbes. For example, they use the tool daily to prototype the design of new microbes.

“We can predict whether a proposed new microbe would be able to achieve commercially viable product yields,” he says.

During the microbe optimization process, LanzaTech uses COBRApy to simulate the construction and growth of millions of microbial strains to identify those most likely to perform well in the fermentation process.


Cameo is a high-level python library developed to aid the strain design process in metabolic engineering projects. The library provides a modular framework of simulation and strain design methods that targets developers that want to develop new design algorithms and custom analysis workflows as well as cell factory engineers that have coding skills.

“COBRApy is the computer game and Cameo is an expansion pack that allows you to be more specific in all cell factory engineering aspects of genome-scale modelling. It can, for example, help you to predict knock-out targets or a metabolic pathway that you might want to introduce from another organism,” says Nikolaus Sonnenschein.


Memote is a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation.

Memote has been developed by the two Postdocs Christian Lieven and Moritz Beber from The Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) as a tool to test the quality of different scientific models.

If you work with yeast or E. coli you are in luck because there are great models available that are quite predictive, but some other published models have many flaws. Memote will help you in discovering those flaws. And even better, when building your own model, Memote helps you to maintain a consistently high quality by testing it with every change,” Christian Lieven explains.

At the biotech company LanzaTech, Senior Scientist in Computational Biology James Daniell and his colleagues develop microbes that ferment pollution into useful products. James Daniell uses Memote to incorporate new knowledge about the microbes into genome scale models.

We use Memote as a quality assurance tool to ensure that updated models remain valid and can accurately predict different scenarios, “says he.

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