While working on a COVID-19-related project during the lockdown, Kärt Tomberg, PhD, found herself thinking about introns. She was part of a team working on the spike protein used in vaccines. Her task was to make the expression construct for the protein. “I’m a geneticist and I’d been looking at genes for 19 years but I’d never had to design the transgene,” she told GEN. Searching through S-protein designs shared by other scientists, she could not quite figure out why they were designed the way they were.
“Fifty years ago, [before] we sequenced human genomes let alone other genomes, we had no idea how genes looked,” she said. Yet “we are using genes and gene structures that look more like viruses and bacterial structure than human genes. Surely we could make them look more like human genes.” A clear difference is that natural viral genes do not have introns. A self-described “classic nerd,” Tomberg began running some experiments of her own to try “to figure out what makes an intron from the spliceosomes point of view” and “to predict it,” something which really had not been done before, she said.
It took several months but she eventually came up with a way to boost protein expression from viral genes by inserting introns. When she tested her approach on spike protein expression, there was an almost 10-fold increase in protein production. Her work forms the basis of the technology that underlies ExpressionEdits, a company co-founded by Tomberg and genome engineering expert Allan Bradley, PhD. The company’s Genetic Syntax Engine is an artificial intelligence-powered platform that uses “intronization” to enhance gene expression. Specifically, it creates in-cDNA with optimal sites and introns that increase protein production without altering the underlying genetic sequence.
This week, the company announced its first collaboration and licensing agreement with a major pharmaceutical company, Boehringer Ingelheim, that is focused on developing enhanced gene therapies. Under the terms of the partnership, Boehringer will leverage ExpressionEdits’ Genetic Syntax Engine, an AI-powered platform that generates optimized introns that boost protein expression without altering the underlying genetic sequence. The partners are not disclosing which therapies they will collaborate on at this time.
The inner workings of ExpressionEdits’ engine are complex but Tomberg offered some insights into how the platform makes predictions. “Nature doesn’t have perfect introns [meaning] it doesn’t care to splice carefully or to express things in a single form. If I trained a model to predict a good intron [using] data that is already in nature, we wouldn’t get good rules,” she explained. That meant that “we had to make the data ourselves.”
Scientists at ExpressionEdits spent the last two years building a training dataset by generating billions of data points on different combinations of introns and exons that could be used to learn patterns that indicate good splicing and bad splicing. They then used this dataset to train AI models to make predictions about where introns should be added, how many are needed, which particular introns work best, and what should happen to the surrounding exons. Sometimes, the splicing decision makes sense because it removes something toxic, Tomberg said. In other cases, it’s less clear why a particular prediction results in greater protein production suggesting that the computer may be picking up a biological pattern that scientists don’t understand yet.
The default setting for the system is to generate a single intron design but there is room for customization. For example, it can be instructed to generate multiple designs but to restrict them to a specific number of base pairs. It can also generate designs based on datasets on codons found in nature rather than ExpressionEdits’ internally generated data, Tomberg said.
Besides the Boehringer deal, ExpressionEdits is open to exploring other relationships with others in the gene therapy space, specifically larger, more mature companies. “We don’t have the capacity to develop the drugs,” Tomberg said. “We want to partner with someone who has the capability of taking these candidates all the way because then we can learn the most about our technology within that space.” Also given the current uncertainty in the gene therapy market, for a small company of about 14 people, “we have to be focused on who we choose.”
