Computer models can play a significant role in designing microbial communities, according to a recent paper published by a team within the Collaborative Research Centre CRC1535 “MibiNet.” The team, which is coordinated across several universities by Heinrich Heine University Düsseldorf (HHU), highlighted how computational biology can advance the development of synthetic biology in the journal, Synthetic Biology 

Microorganisms, such as bacteria, fungi, and viruses, form complex communities found in various environments, including within organisms where they perform critical functions. For example, the human gut microbiome is essential for metabolism, helping break down nutrients that the body needs. If the microbial composition is imbalanced, it can cause harm to the organism.

The growing field of synthetic biology aims to design and build new biological systems that perform specific tasks using engineering principles. Initially, this discipline focused on creating single synthetic organisms, but its potential to design artificial microbial communities is becoming increasingly clear. These engineered communities could have a range of applications, including disease treatment, boosting crop productivity, and producing valuable biomolecules.

Researchers in the CRC1535 project draw inspiration from natural systems like lichens, where cyanobacteria or algae form symbiotic relationships with fungi. They aim to replicate these microbial networks for future applications, including CO2-negative processes that capture carbon from the atmosphere. Another related project, ACCeSS, seeks to use solar energy for wastewater treatment.

In Synthetic Biology, the researchers outline how computational biology can simplify the design of these synthetic communities. Professor Dr. Ilka Axmann from HHU states: “We propose a shift in perspective from single-organism-centred approaches to emphasising the functional contributions of organisms within the community.” She adds, “The focus lies on the function the community as a whole should perform. It is irrelevant which specific organisms it contains: Organisms are merely the chassis containing necessary metabolic pathways, providing required functional roles.”

Dr. Daniel C. Ducat from MSU explains, “Increasing numbers of examples show that, although the specific species composition of complex microbial communities can change over time or at different locations, the specific functions of the community are stable on a larger scale.”

Dr. Anna Matuszyńska, lead author and Junior Professor at RWTH Aachen emphasizes how computational models can simplify synthetic biology by reducing complexity. “With the help of mathematical models, we can predict and optimise such systems to ensure they work reliably and efficiently. The intention is to use this ‘in silico design’ in the earliest stages of developing a synthetic community,” she explains.

This interdisciplinary approach could pave the way for new technological breakthroughs in microbial community design.