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HOW AI IS HELPING SYNTHETIC BIOLOGY COME OF AGE
Technology entrepreneur and AI researcher Mustafa Suleyman in his book, ‘The Coming Wave: AI, Power and the 21st Century’s Greatest Dilemma’, posits that the world will soon see a wave “defined by two core technologies: artificial intelligence and synthetic biology”, which together “will usher in a new dawn for humanity, creating wealth and surplus unlike anything ever seen”.
He cautions, though, that the rapid spread of these two technologies will unleash a wave of “disruption, instability, and even catastrophe on an unimaginable scale.” He believes that the world’s future “both depends on these technologies and is imperilled by them”.
Mustafa Suleyman, CEO and co-founder of Inflection AI. Picture courtesy of LinkedIn
Suleyman is the CEO and co-founder of Inflection AI, which is being presented as “an AI studio creating a personal AI for everyone”, and a venture partner at Greylock Partners. Prior to this, he had co-founded DeepMind–an AI company that Google acquired in 2014–and was also VP of AI products and AI policy at Google. Given these multiple roles, he understands the implications of these technologies well enough to suggest ways to handle them with care and caution.
As the term suggests, synthetic biology, as opposed to the natural study of life, or the biology that we learnt in school, involves artificially redesigning organisms with new abilities (human-made from chemical parts), and has applications in fields such as medicine, manufacturing, and agriculture. Synthetic biology combines multiple areas including molecular biology, biophysics, biotechnology, and genetic engineering, and typically uses two techniques: top-down and bottom-up.
The top-down technique involves redesigning and fabricating existing biology systems to produce synthetic products, while the bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behaviour. Scientists, of late, have begun exploring combining the two approaches for best results.
In a recent interview, Frank Diana–a futurist at India’s largest IT services company, Tata Consultancy Services–argued that synthetic biology will soon play a crucial role in shaping our world.
“Synthetic biology will give us the ability to manipulate and create life. At the molecular level, synthetic biology and genetics allow us to modify foods, modify animals, and eventually people,” he said.
“Again, it’s a dual path. It gives us the ability to deal with a genetic deformity early, and even before it happens. What parent would not want to do that if they knew that their child might be born with some kind of genetic defect? Of course, there is always a chaotic conversation around the benefits and the downside of those kinds of things.”
Frank Diana, Futurist at TCS
Applications of synthetic biology
Products created in the synthetic biology system are used in multiple industries including pharmaceuticals, diagnostics, and bioplastics.
According to the National Human Genome Research Institute, scientists are using synthetic biology to develop microorganisms that can clean pollutants from our water, soil and air; to modify rice that can produce beta-carotene–a nutrient usually associated with carrots that prevents vitamin A deficiency; and to engineer yeast to produce rose oil as an eco-friendly and sustainable substitute for real roses that perfumers use to make luxury scents.
Consider another example. Impossible Foods produces a plant protein called leghaemaglobin to provide flavour and other properties to its plant-based meat replacement products. The plant-based meat is made by placing the plant gene in a microbe and then brewing up the gene-encoded protein, similar to how beer is made. The protein is extracted from the brew and blended with other plant-based components to deliver the burger patty. Beyond sparing animal lives, these alternatives can help transform industries by reducing the carbon footprint.
The size of the global synthetic biology market was pegged at $13.4 billion in 2022, and is forecast to rise to around $116.04 billion by 2032, according to Precedence Research. Synthetic biology is predominantly implemented in the drug development process in North America, which accounts for 40% of the total market, according to the research firm.
The demand for synthetic biology is expected to rise due to factors such as increasing investments in synthetic biology companies, growing demand for bio-based products, and more R&D funding. In addition, governments in the region are focusing on the development of personalised therapeutics.
Just like genome editing
That said, synthetic biology is being likened by some to genome editing since both these technologies involve altering an organism’s genetic code. But there’s a difference. In genome editing (CRISPR being the most-popular technique), scientists typically use tools to make small changes to an organism’s own DNA, or even delete or add small stretches of DNA in the genome.
The genome-editing CRISPR-Cas9 technology has enabled the editing of disease-associated genes in the genome. CRISPR, which stands for ‘Clusters of Regularly Interspaced Short Palindromic Repeats’, is a tool that allows researchers to easily alter DNA sequences and modify gene function. The protein Cas9 (CRISPR-associated, or Cas) is an enzyme that acts like a pair of molecular scissors, capable of cutting strands of DNA.
With synthetic biology, scientists use the technology to typically stitch together long stretches of DNA and insert them into an organism’s genome. These synthesised pieces of DNA could be genes found in other organisms or be entirely novel.
The first synthetic bacterial genome was completed in 2008 with the synthesis of the genome of Mycoplasm genitalium, a bacterium that can cause urinary and genital tract infections in humans, according to the National Human Genome Research Institute. Nine years later, another group of scientists partially synthesised the genome of Saccharomyces cerevisiae–the yeast used to make bread and brew wine and beer.
Further, Genome Project-Write (GP-Write) is seeking to synthesise, or ‘write’, whole genomes from human cell lines as well as the genomes of plants and animals important to agriculture and public health.
The project’s name is a play on the Human Genome Project. In 2003, scientists working on HGP sequenced, or ‘read’, the more than 3 billion DNA letters, or base pairs, that make up the human genome. The research in GP-Write involving human genomes will occur only in cells, and no human embryos will be used.
Such research raises important ethical questions about potential harms and benefits to society. In 2002, scientists in the US synthesised a viral genome, and showed that it was possible to create the polio virus from scratch, underscoring the risk that synthetic biology could be used to develop biological weapons. Eight years later, scientists at the J. Craig Venter Institute announced the creation of the world’s first self-replicating synthetic genome in a bacterial cell of a different species. Given the risks of generating AI hallucinations (confidently providing wrong data), any AI intended to provide advice on biotech will have to be moderated by human experts.
AI is boosting synthetic biology growth
The legitimate fears notwithstanding, AI holds the promise of advancing biological research, and biotechnology has the potential to power the next wave of AI and benefit humans. The reason is that generative AI can not only analyse data but also create new designs and propose ways to improve upon existing ones. For example, it can suggest ways to make an enzyme work better at a higher temperature, according to an article in Synbiobeta.
Foundational, or general-purpose, models are trained on mountains of biological datasets, such as protein sequences stored in protein data banks, typically using an unsupervised learning process to uncover the underlying rules and learn the language of biology.
Specialised models, on the other hand, are trained on smaller, often proprietary, datasets to accomplish a specific task such as improving the stability of an enzyme, according to the Synbiobeta article cited above.
Picture courtesy of Mint
DeepMind’s AI AlphaFold, as an example, successfully forecasted the structures of nearly every scientifically catalogued protein within 18 months–a feat that would have taken years to accomplish. This, according to scientists, has helped advancements in addressing malaria, battling antibiotic resistance, reducing plastic waste, and potentially accelerating drug discovery. Researchers have also used AlphaFold, which is free to use for anyone in the research community, to engineer new enzymes to break down plastic waste and learn more about the proteins that make bacteria resistant to antibiotics.
AI models can propose sequences for testing by understanding the correlation between a protein’s sequence and its function, which would assist scientists in uncovering improved variants that traditional methods might overlook. Protein Evolution, for instance, collaborated with the US Department of Energy’s Agile BioFoundry project and the Joint BioEnergy Institute to develop AI-optimised enzymes that can break down plastic and textile waste.
Another synthetic biology company, Arzeda, is working with Unilever to create new cleaning enzymes with increased stability, performance, and sustainability benefits.
AI models can also help design other types of proteins, such as materials with improved properties or animal product alternatives. A Berlin-based synthetic biology materials startup, Cambrium, is using AI to make new sustainable skin-identical micromolecular collagen made in yeast cells.
Given all these, regulators will have to consider if the benefits outweigh the harms, and devise policies accordingly.
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