Curing the bystander effect: A new base editing tool minimizes unwanted edits to DNA
The trajectory of base editing has been remarkable, progressing from the laboratory to patient care, treating debilitating or terminal illnesses, in less than a decade. A type of gene editing that makes chemical changes to our DNA, base editing was developed by Alexis Komor, associate professor in the Department of Biochemistry and Molecular Biophysics at the University of California San Diego.
For all of base editing’s success, it is still a relatively new technology, and researchers like Komor are working to improve its efficiency, while lowering the incidence of unwanted edits. One type of unwanted edit is called a bystander edit. This occurs when a base editor not only edits the desired nucleobase, but also edits surrounding bases as well. Komor’s lab has developed a way to minimize bystander edits. This work appears in Nature Biotechnology.
The Bystander Effect
Base editing works by making an edit to a single strand of DNA. In the case of adenine base editors (ABEs), a target adenine (A) nucleobase can be edited to guanine. However, if there are multiple A bases neighboring the target, sometimes all the A bases are edited, even if there was only one A target. These bystander edits may be harmless or “silent,” or they may bring about unwanted consequences, including cell death.
One way to lower bystander editing is to narrow the “editing window,” or the stretch of bases the ABE is capable of effectively editing. However, research has shown that narrowing the editing window usually lowers the efficiency of desired on-target editing as well. Komor wanted to develop a way to lower the incidence of bystander editing while maintaining the efficiency of on-target editing.
“Especially for therapeutic applications, it’s important to optimize both properties. A genome editor could be quite efficient at installing a desired edit, but if it does so concurrently with other, unwanted edits, then it won’t be safe to use as a therapeutic,” she said.
For this work, Mallory Evanoff, a chemistry alumna and former postdoctoral scholar in Komor’s lab, focused attention on an initial version of ABE called ABE7.10. ABE7.10 has a narrower editing window than more recently engineered ABE8.20 and ABE8e editors, but also has a lower editing efficiency. The ABE 8 variants have higher on-target editing and, thus, are more widely used (including in clinical trials), but they also have much higher bystander editing. Evanoff wanted the best of both worlds.
To convert A bases to G bases, ABE7.10 uses an engineered enzyme with 14 point mutations installed that were previously identified to be important for effective base editing. The process that introduced and selected for these important mutations (a technique called directed evolution that won the Nobel Prize in Chemistry in 2018) was completed in E. coli bacteria cells, and done in such a way that it was unclear how each of the 14 mutations contributed to editing activity.
To untangle these effects, Evanoff used reversion analysis, in which she reverted each mutation back to its original “wild type” sequence. She then characterized the activity of all 14 of the individually reverted mutations in both human cells and E. coli bacteria cells.
She noticed that while some of these mutations behaved similarly in bacteria, others had disparate effects in the two host systems. Given most researchers’ usage of ABEs is in human cells, Evanoff identified five mutations that, when reverted individually, either had no impact or increased editing activity in human cells. She then combined those five together to create what she calls a minimally evolved ABE, or ME-ABE.
The resulting ME-ABE keeps a narrow editing window, but gains editing activity similar to the two ABE 8 variants that are more commonly used.
“This is one of the first times that we have been able to decouple the characteristics of efficiency and editing window. In other work, increasing editing activity has always come with the cost of a wider editing window, and thus more bystander editing,” stated Komor. “We’re excited to offer this tool to the community to help researchers who want to model or correct mutations and have unacceptable bystander bases next to their target A’s”.
Cracking the Code
There are millions of genetic variations possible between any two people, and although many are harmless, others can lead to debilitating or terminal genetic diseases. Figuring out which mutations or combinations of mutations are responsible for a disease can feel like medical detective work, but when they are successful, scientists can create precise gene therapies for individual treatments.
“The thing about building these precision tools is that we can install those mutations in model organisms and ask the right questions before we try any therapies in patients,” stated Evanoff. “Or we can tease apart, very specifically, the fact that many people might have a whole host of mutations, but only a handful of them are contributing to whatever symptom or disease we're working on.”
She calls the ME-ABEs a “cuts-both-ways” tool because it helps researchers better model and understand possible genetic mutations, and also lets them implement potential corrections and build personalized medicines that can cure specific diseases.
While Komor and Evanoff work on developing new base editors — particularly by evolving them in mammalian cells instead of bacteria — they also hope ME-ABEs are a jumping off point for other researchers seeking to develop effective gene-editing tools.
“One of the great things about working in the tool development world, is that you're making something that allows other people to answer their own questions,” stated Evanoff. “These tools are going to be available for researchers who are really, really well-informed on their particular disease or their particular system and now have an ability to model a cure.”
Plasmids for this and other work from Komor’s lab can be found on AddGene (https://www.addgene.org/Alexis_Komor/).
END
For all of base editing’s success, it is still a relatively new technology, and researchers like Komor are working to improve its efficiency, while lowering the incidence of unwanted edits. One type of unwanted edit is called a bystander edit. This occurs when a base editor not only edits the desired nucleobase, but also edits surrounding bases as well. Komor’s lab has developed a way to minimize bystander edits. This work appears in Nature Biotechnology.
The Bystander Effect
Base editing works by making an edit to a single strand of DNA. In the case of adenine base editors (ABEs), a target adenine (A) nucleobase can be edited to guanine. However, if there are multiple A bases neighboring the target, sometimes all the A bases are edited, even if there was only one A target. These bystander edits may be harmless or “silent,” or they may bring about unwanted consequences, including cell death.
One way to lower bystander editing is to narrow the “editing window,” or the stretch of bases the ABE is capable of effectively editing. However, research has shown that narrowing the editing window usually lowers the efficiency of desired on-target editing as well. Komor wanted to develop a way to lower the incidence of bystander editing while maintaining the efficiency of on-target editing.
“Especially for therapeutic applications, it’s important to optimize both properties. A genome editor could be quite efficient at installing a desired edit, but if it does so concurrently with other, unwanted edits, then it won’t be safe to use as a therapeutic,” she said.
For this work, Mallory Evanoff, a chemistry alumna and former postdoctoral scholar in Komor’s lab, focused attention on an initial version of ABE called ABE7.10. ABE7.10 has a narrower editing window than more recently engineered ABE8.20 and ABE8e editors, but also has a lower editing efficiency. The ABE 8 variants have higher on-target editing and, thus, are more widely used (including in clinical trials), but they also have much higher bystander editing. Evanoff wanted the best of both worlds.
To convert A bases to G bases, ABE7.10 uses an engineered enzyme with 14 point mutations installed that were previously identified to be important for effective base editing. The process that introduced and selected for these important mutations (a technique called directed evolution that won the Nobel Prize in Chemistry in 2018) was completed in E. coli bacteria cells, and done in such a way that it was unclear how each of the 14 mutations contributed to editing activity.
To untangle these effects, Evanoff used reversion analysis, in which she reverted each mutation back to its original “wild type” sequence. She then characterized the activity of all 14 of the individually reverted mutations in both human cells and E. coli bacteria cells.
She noticed that while some of these mutations behaved similarly in bacteria, others had disparate effects in the two host systems. Given most researchers’ usage of ABEs is in human cells, Evanoff identified five mutations that, when reverted individually, either had no impact or increased editing activity in human cells. She then combined those five together to create what she calls a minimally evolved ABE, or ME-ABE.
The resulting ME-ABE keeps a narrow editing window, but gains editing activity similar to the two ABE 8 variants that are more commonly used.
“This is one of the first times that we have been able to decouple the characteristics of efficiency and editing window. In other work, increasing editing activity has always come with the cost of a wider editing window, and thus more bystander editing,” stated Komor. “We’re excited to offer this tool to the community to help researchers who want to model or correct mutations and have unacceptable bystander bases next to their target A’s”.
Cracking the Code
There are millions of genetic variations possible between any two people, and although many are harmless, others can lead to debilitating or terminal genetic diseases. Figuring out which mutations or combinations of mutations are responsible for a disease can feel like medical detective work, but when they are successful, scientists can create precise gene therapies for individual treatments.
“The thing about building these precision tools is that we can install those mutations in model organisms and ask the right questions before we try any therapies in patients,” stated Evanoff. “Or we can tease apart, very specifically, the fact that many people might have a whole host of mutations, but only a handful of them are contributing to whatever symptom or disease we're working on.”
She calls the ME-ABEs a “cuts-both-ways” tool because it helps researchers better model and understand possible genetic mutations, and also lets them implement potential corrections and build personalized medicines that can cure specific diseases.
While Komor and Evanoff work on developing new base editors — particularly by evolving them in mammalian cells instead of bacteria — they also hope ME-ABEs are a jumping off point for other researchers seeking to develop effective gene-editing tools.
“One of the great things about working in the tool development world, is that you're making something that allows other people to answer their own questions,” stated Evanoff. “These tools are going to be available for researchers who are really, really well-informed on their particular disease or their particular system and now have an ability to model a cure.”
Plasmids for this and other work from Komor’s lab can be found on AddGene (https://www.addgene.org/Alexis_Komor/).
END