Researchers at the Chalmers University of Technology in Sweden have created synthetic DNA that directs the cellular production of proteins with the aid of artificial intelligence.
With the help of technology, vaccines, drugs for severe diseases, and alternative food proteins could all be developed and produced much more quickly and cost-effectively than they are now.
The function of cells in all living organisms is fundamentally dependent on how human genes are expressed. Simply put, the messenger RNA (mRNA) molecule receives instructions from the DNA’s genetic code about which proteins to produce and in what quantities. This process is known as transcription.
Since it can, among other things, aid in the creation of protein-based medicines, researchers have invested a lot of time and energy into trying to regulate gene expression. A current illustration is the mRNA vaccine against Covid-19, which gave instructions to the body’s cells to produce the same protein found on the coronavirus’ surface.
The immune system could then learn to produce antibodies against the virus. Likewise, by comprehending the genetic code that controls the production of particular proteins, it is possible to instruct the body’s immune system to eradicate cancer cells or other complex diseases.
The majority of today’s new medicines are protein-based, but because it is challenging to regulate how the DNA is expressed, the methods used to make them are both expensive and time-consuming.
Aleksej Zelezniak, Associate Professor of Systems Biology at Chalmers University, and his team made significant progress last year toward understanding and managing the amount of a protein produced from a specific DNA sequence.
First it was about being able to fully ‘read’ the DNA molecule's instructions. Now we have succeeded in designing our own DNA that contains the exact instructions to control the quantity of a specific protein.
Aleksej Zelezniak, Associate Professor, Department of Biology and Biological Engineering, Chalmers University
DNA Molecules Made-to-Order
When an AI creates faces that resemble real people, it works on a similar principle. The AI can then produce entirely new but realistic-looking faces by learning what a wide range of faces looks like.
Then, it is simple to alter a face by telling it to have a different hairstyle or to appear older. But programming a realistic face from scratch without the aid of AI would have been much more challenging and time-consuming.
Similarly, the AI used by the researchers has been taught the regulatory structure of DNA. The AI then creates synthetic DNA that can easily have its regulatory information modified to point gene expression in the desired direction. Simply put, the desired amount of a gene is communicated to the AI, which then “prints” the correct DNA sequence.
DNA is an incredibly long and complex molecule. It is thus experimentally extremely challenging to make changes to it by iteratively reading and changing it, then reading and changing it again. This way it takes years of research to find something that works. Instead, it is much more effective to let an AI learn the principles of navigating DNA. What otherwise takes years is now shortened to weeks or days.
Jan Zrimec, Study First Author and Research Associate, National Institute of Biology
Saccharomyces cerevisiae, a yeast whose cells resemble those of mammals, is where the researchers developed their methodology. After that, human cells will be used. The researchers are hopeful that their work will influence both the creation of new drugs and the continued use of already existing ones.
Zelezniak stated, “Protein-based drugs for complex diseases or alternative sustainable food proteins can take many years and can be extremely expensive to develop. Some are so expensive that it is impossible to obtain a return on investment, making them economically nonviable. With our technology, it is possible to develop and manufacture proteins much more efficiently so that they can be marketed.”
Jan Zrimec, Xiaozhi Fu, Azam Sheikh Muhammad, Christos Skrekas, Vykintas Jauniskis, Nora K. Speicher, Christoph S. Börlin, Vilhelm Verendel, Morteza Haghir Chehreghani, Devdatt Dubhashi, Verena Siewers, Florian David, Jens Nielsen, and Aleksej Zelezniak are the study authors.
The researchers work at the National Institute of Biology in Slovenia, King’s College London, UK, Biomatter Designs in Lithuania, the Institute of Biotechnology in Lithuania, the BioInnovation Institute in Denmark, and Chalmers University of Technology in Sweden.
Zrimec, J., et al. (2022) Controlling gene expression with deep generative design of regulatory DNA. Nature Communications. doi:10.1038/s41467-022-32818-8