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The groundbreaking work promises to augment the production of pharmaceuticals, vitamins and health-enhancing functional foods as well as other organic and chemical substances that can be produced by genetically engineered microbes.
Foods enhanced with probiotic microorganisms and functional organic substances, for example, could play a significant role in developing novel approaches to mitigating hypertension, diabetes and obesity as well as age-related diseases.
The research, conducted at the University of California, San Diego, has been supported by the development of cutting-edge computational tools for bioengineering by Andreas Dräger, a bioinformatics researcher at the University of Tübingen in Germany.
In the AMBICON project, Dräger led the development of advanced algorithms, specialised software and new encoding standards to create powerful multi-level computational models of biological systems, leveraging vast amounts of genomic, cellular and experimental data.
“These models are able to predict the growth rate of cells such as bacteria taking into account the effects of different physico-chemical conditions and genetic modifications, demonstrating how genetically improved microorganisms can be designed while maintaining their ability to sustain a healthy life,” Dräger says. “In other words, with this technique there is no longer a conflict between increasing the production rate of desired biological products and the ability of the manipulated organism to sustain its fundamental functions.”
Previous approaches to designing enhanced microorganisms by making changes to the genetic makeup of a cell often inadvertently impacted the ‘paleome’ — the core set of genes that microbes need to function and survive.
Enhancing healthy, functional cells
Rather than risk compromising the cell’s core genes and functions, the novel engineering approach based on the AMBICON computational models enables the cell to be defined with the essential set of genes and then extra desired functions added, such as increased production of vitamins, nutrients or other bio-products and chemical substances.
Similarly, the project also contributed to a novel method to determine the minimal set of proteins that a microorganism needs for healthy growth, and to further increase the production rate of desired bio-products.
In trials, the tools enabled a genome-scale computational model to be developed to define the paleome of the bacteria E. coli. Using this model, researchers simulated the growth of a well-studied strain of E. coli across 333 different growth conditions, varying the nutrient source of the growth medium across elements such as carbon, nitrogen, phosphorus and sulphur.
The team observed which set of genes was consistently expressed throughout all the different growth environments and used this set to construct the paleome, identifying 356 genes that are essential to the function and survival of at least two strains of E. coli and three other microorganisms.
“Building highly detailed computer models of biological systems is a laborious and difficult endeavour. These models are very complex, comprising large numbers of detailed biochemical interactions, complicated mathematical equations and vast data sets drawn from a growing body of high-quality biological information,” Dräger explains. “With the new computational tools and encoding standards this plethora of data can now be organised into a coherent model that precisely describes the structure of cells and enables computer simulations, visualisations and analysis of numerous biological systems.”
Dräger was funded through the EU’s Marie Skłodowska-Curie fellowship programme. AMBICON resulted in the publication of 17 articles in noted scientific journals and has led to two ongoing studies in the field, providing a fruitful basis for further projects.
Dräger has also been elected as an editor for the development of the SBML standard, a common format for systems biology software in which the AMBICON models are encoded. The models and tools, which are freely available for download and use, have been adopted by leading developers of bioinformatics software, opening up new avenues for a broad range of future research.