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HomeEnvironmentCustomized Microbial Ecosystems: Crafting Nature's Little Helpers

Customized Microbial Ecosystems: Crafting Nature’s Little Helpers

How can computer models assist in the creation of microbial communities? Researchers have explored the future of synthetic biology, detailing the significant role of computer-aided biology in a recent article.
How can computer models assist in crafting microbial communities? Within the framework of the Collaborative Research Centre CRC1535 “MibiNet,” coordinated by Heinrich Heine University Düsseldorf (HHU), a research group from Aachen, Düsseldorf, and East Lansing, USA, investigated the prospects of synthetic biology. In their publication in the scientific journal Synthetic Biology, they discuss the critical role that computer-aided biology plays in this field.

Microbial communities, which include bacteria, fungi, and viruses, are ubiquitous and serve various essential functions, particularly within living organisms. For instance, the microbial community known as the microbiome in the human gut is vital for metabolism, as these microorganisms help unlock and make many nutrients accessible to the body. An imbalance in the microbiome’s composition can lead to significant health issues.

The research area known as “synthetic biology” is increasingly examining these microbial networks. The goal is to apply engineering principles to design and create new biological systems and organisms capable of performing specific tasks. Techniques in genetic engineering facilitate the modification and transfer of DNA and RNA between different organisms. While synthetic biology initially focused on creating individual synthetic organisms, its ability to design complex networks, such as artificial communities of synthetic organisms, is becoming clearer.

These artificial communities have a wide array of potential applications, including disease prevention, improved agricultural productivity, and the creation of valuable biomolecules.

The researchers from CRC1535 “MibiNet” draw inspiration from natural lichens, where phototrophic cyanobacteria or algae engage in a close symbiotic relationship with heterotrophic fungi. They aim to replicate the microbial networking observed in lichens for future applications. Their findings are intended to contribute to developing interdisciplinary methods and technologies for processes that capture CO2 from the atmosphere. In another research initiative called ACCeSS, they plan to utilize solar energy to treat wastewater.

In the journal Synthetic Biology, the researchers from Aachen University of Technology (RWTH), HHU, and Michigan State University (MSU) in East Lansing detail a prospective future for synthetic biology. They highlight the critical role of computational biology, which can significantly streamline the creation of artificial communities.

Professor Dr. Ilka Axmann from HHU, the study’s corresponding author, states: “We advocate for a shift from focusing on individual organisms to highlighting each organism’s contributions within the community.” Regarding their research approach, she adds: “The emphasis is on the function that the community as a whole needs to perform, rather than the specific organisms it contains. The organisms act merely as chassis that provide the necessary metabolic pathways and functional roles.”

Dr. Daniel C. Ducat, a Professor of Biochemistry and Molecular Biology at MSU, remarks: “Increasing examples demonstrate that, although the specific species within complex microbial communities can vary over time or between locations, the overall functions of the community remain stable on a broader scale.”

Dr. Anna MatuszyÅ„ska, the lead author of the study and a Junior Professor of Computational Life Science at RWTH, states: “Computational biology can enhance modularization in synthetic biology, which is beneficial as it reduces complexity and fosters adaptable, scalable frameworks designed for specific roles within biological communities. Through mathematical models, we can foresee and refine such systems to ensure their consistent and efficient operation. Our aim is to implement this ‘in silico design’ during the earliest phases of developing a synthetic community.”