A small genome editing nuclease packs a punch

INWhen a chef develops a new recipe, he or she methodically adds and removes individual ingredients to see how each will change the final dish. When scientists try to understand the role of genes in the body, they use a similar tactic using genome editing. Currently the most popular tool in their toolbox is CRISPRwith a wide range of applications, from cancer therapy to the treatment of genetic diseases such as sickle cell anemia and β-thalassemia.¹ However, this basic genome editing still has its limitations.

“It’s really difficult to package the genes that code for these proteins into the viruses that are used to deliver them to cells,” he said Tautvydas Karvelisgenome biologist at Vilnius University. Even when CRISPR nucleases are delivered directly into cells, their large protein sizes pose limitations. For example, the commonly used Cas9 is approximately 1,400 amino acid residues long.

In a recent study published in Nature’s methods, Gerald SchwankA genome biologist at the University of Zurich and his team have described a small but efficient nuclease that works as well as some current Cas proteins but is less than half the size.²

“It’s like a new class of tools that can be used to edit the genome, not just as a principle,” said Karvelis, who was not involved in the study.

In 2021, Karvelis discovered a compact RNA-guided protein capable of cutting DNA: TnpB.³ Compared to other CRISPR nucleases, TnpB is much smaller and contains approximately 400 amino acid residues. However, TnpB has lower editing efficiency and limited target range.

Therefore, Schwank decided to improve the efficiency of TnpB. He and his team optimized TnpB for mammalian gene editing and engineered protein variants to improve target range. They also built a machine learning model to predict how well a guide RNA would perform for a set of target sequences, saving future users the headache of multiple attempts.

In the intact state, the TnpB editing efficiency ranges from zero to 20 percent, which is lower than that of the smallest CRISPR-Cas9 ortholog, CjCas9. “We asked if we could really make TnpB efficient enough to use,” Schwank said. So the team did two things. They optimized the codon sequence of TnpB for mammalian cells and attached a small tag to the protein that directed it to the nucleus. The team observed a 4.4-fold increase in the editing efficiency of this modified nuclease, superior to most commonly used RNA-directed endonucleases, including CjCas9. They called this variant TnpBmax.

Tested on a large library of target sites introduced into mammalian cells, TnpBmax performed exceptionally, causing insertions and deletions of DNA sequences at a rate of approximately 70 percent. However, any change in an essential five-base region upstream of the target DNA resulted in a dramatic drop in efficiency. This short region of 5’TTGAT 3′ sequence, called the transposon adjacent motif (TAM), is rare and limits where TnpBmax can work its magic.

To alleviate these limitations, Schwank and team tested interactions between different versions of the TnpBmax and TAM variants. Replacement of lysine with alanine in 76^vol position allowed TnpBmax to recognize TAMs that had cytosine or thymine in the second position and guanine or thymine in the third position. This sequence is four times more abundant in the genome than the original TAM sequence. Changes in TnpBmax or TAM did not affect editing performance.

Schwank wanted to add an additional feature to the tool. He and his team built a model that can predict whether a guide RNA sequence can edit a given DNA sequence with an efficiency of at least 70 percent. “Before, it was more or less a gamble. Having a TAM site meant you could basically target it, but you weren’t really sure it would be effective,” Schwank said. “Now with this model, it’s much easier to determine whether you can use this tool or not.”

“Having this model so people can design their own guides will increase the usability of the system,” he said Omar Abudayyeha genome engineer at Harvard Medical School who was not involved in the study.

Finally, to put the tool to the ultimate test, the authors looked at genes in the brain and liver of mice. They observed editing efficiency of 65% and 75%, respectively. In the liver, the team modified a gene involved in cholesterol metabolism and observed a consequent decrease in blood cholesterol levels in mice.

“At the time of their discovery, there was a big question about how effective TnpB would be as genome-editing enzymes,” he said Jonathan Gootenberga genome engineer at Harvard Medical School who was not involved in the study. “This engineering makes them really competitive.”