Precision genome editing tools – including prime editing – enable scientists to model genetic variants in their native environment. Now, researchers have developed a framework for engineering and measuring the effects of thousands of genetic mutations simultaneously while accurately quantifying the efficiency of prime editing. They’ve even found that some mutations once considered to be inconsequential or nonpathogenic may contribute to cancers.
Hanna Gray Fellow, Massachusetts Institute of Technology
Precision genome editing tools – including prime editing – enable scientists to model genetic variants in their native environment. Now, researchers have developed a framework for engineering and measuring the effects of thousands of genetic mutations simultaneously while accurately quantifying the efficiency of prime editing. They’ve even found that some mutations once considered to be inconsequential or nonpathogenic may contribute to cancers.

Little more than a decade ago, CRISPRexternal link, opens in a new tab forever changed the landscape of genome editing. In the years since, scientists have continued to refine the editing toolkit, developing newer technologies that make it possible to modify the genome with greater efficiency and precision.

Excited by what these developments could mean for the future of medicine and the study of diseases, Howard Hughes Medical Institute Hanna Gray Fellow and Massachusetts Institute of Technology biologist Francisco Sánchez-Rivera is working to scale up some of these technologiesexternal link, opens in a new tab and make his team’s findings accessible to all scientists.

“To understand the influence of genetic variation in normal biology, as well as in disease, scientists need to be able to engineer diverse types of variants so that we can understand them, functionally,” says Sánchez-Rivera.

Many human diseases are caused by genetic mutations, permanent changes in our DNA makeup that can range in scale from a change to a single nucleobase – or DNA letter – in the genome, to complex chromosomal rearrangements. 

The human genome has roughly 20,000 genes that code for proteins, and each of those genes can be mutated in different ways. This means that two people might develop the same type of cancer as the result of a mutation to the same gene, but the mutations in that same gene could be different in each case. 

To get a clearer understanding of what drives cancer and other diseases, Sánchez-Rivera and other scientists – including those who inspired much of his recent work – are focused on what’s known as precision genome editing. The tools they work with build on CRISPR’s powerful genome editing technology, but with a degree of resolution that goes beyond what CRISPR alone can achieve. 

Using CRISPR, scientists generate a short strand of RNA, known as a “guide” RNA, to direct the Cas9 enzyme to a specific DNA sequence. Cas9 is a nuclease; it functions like a pair of molecular scissors that binds to DNA and cuts both strands, allowing scientists to inactivate a specific gene. 

But Sánchez-Rivera isn’t looking to merely inactivate genes. Instead, he and his colleagues aim to identify and study the specific alterations to a gene that drive different diseases. To do this, they need the ability to observe a mutation that might happen at the level of a single nucleotide – the basic building block of both DNA and RNA that comprises a nucleobase, a five-carbon sugar, and a phosphate group. 

In 2016, HHMI Investigator David R. Liu and Alexis Komor – then, a new postdoc in Liu’s lab at the Broad Institute of MIT and Harvard – paved the way for exactly this capability. They linked a version of Cas9 with another enzyme that allowed them to target a specific point on the genome and individually change the four letters (A, T, G, and C) that make up DNA. This technique, known as base editing, enabled scientists to switch C to T and G to A. A year later, Liu’s lab rolled out a new class of base editorsexternal link, opens in a new tab that allowed scientists to switch A to G and T to C.

In 2019, Liu and then-postdoc Andrew Anzalone took the field of precision genome editing even further. By tying Cas9 with a different kind of enzyme, the team created prime editingexternal link, opens in a new tab: a tool that allows scientists to make any kind of DNA “rewrite” possible at a target site of the genome in human cells, without the need to break DNA’s double strands. Prime editing enables all 12 possible single-letter DNA swaps, as well as insertions and deletions, at targeted genomic sites in living cells, including non-human primates and other mammals. The technology carries a lot of promise for the future of disease research and the development of new therapies. As Sánchez-Rivera notes, scientists still don’t fully understand the limits of prime editing in terms of scalability, efficiency, and precision. 

To help address this, Sánchez-Rivera and his team designed an approach that allows them to simultaneously deploy and quantify the efficiency of prime editing. Even more, this can be done for thousands of genetic mutations simultaneously, he says. 

The group’s technique uses a prime editing “sensor” to couple each prime editing guide RNA (pegRNA) to the target site, thereby allowing scientists to create a perfect synthetic copy of the native site in the genome. By sequencing the sensor target site from a population of cells, Sánchez-Rivera and his lab can get an accurate picture of the efficiency and precision of each pegRNA on a per-cell basis, he says.

Zeroing in on TP53

To test their platform, the team generated a library of nearly 30,000 pegRNAs designed to engineer more than a thousand variants of TP53, the gene most commonly mutated in cancer. TP53 is a tumor suppressor gene; its job is to provide instructions for making the p53 protein that counteracts cancer development. Roughly half of cancer patients have a TP53 mutation, but there are hundreds of different kinds of possible mutations and scientists don’t yet understand exactly what each does, Sánchez-Rivera says. 

Aware of this knowledge gap, he and his team hypothesized that some TP53 mutations previously considered to be inconsequential or non-pathogenic may have been misclassified. Further, prime editing could uncover types of disease-causing mutations that haven’t been studied due to a lack of appropriate technologies, Sánchez-Rivera says. 

Their hunch was correct. Using their platform, Sánchez-Rivera and his team made some surprising discoveries about certain types of variants – particularly, some that occurred in a region of p53 known as the oligomerization domain, which plays a crucial role in protein-protein interactions. Here, the team found that some variants proved to be pathogenic but would have previously been classified as nonpathogenic, or perhaps even benign. 

“This is an important discovery with both technical and clinical implications,” Sánchez-Rivera says says. “First, we show that studying genes and variants in their native context is critical to uncover true biology. Secondly, thousands of humans are born with mutations in the TP53 oligomerization domain, and many cancers acquire these same mutations. Understanding the precise biological mechanisms through which these mutations predispose humans to develop cancer is therefore imperative.”

Sánchez-Rivera’s group next plans to deploy this approach more broadly to study other cancer mutations and proteins. They also want to combine their approach with other methods, such as chromosome engineering, to investigate how large-scale chromosomal rearrangements interact with some of the point mutations and insertion-deletion mutations seen in cancer. 

Samuel Gould, a graduate student in Sánchez-Rivera’s lab and first author of the team’s paperexternal link, opens in a new tab, developed the computational pipeline needed to make the group’s work possible as well as accessible to others. The group’s publicly available Python package, Prime Editing Guide Generatorexternal link, opens in a new tab (PEGG), serves as a tool for scientists to create prime editing sensor libraries, advancing the field of precision genome editing at large. 

“This project is a proof-of-principle for what can be done with the prime editing sensor approach,” Gould says. “We’re excited to extend the method to model other cancer-associated variants to potentially identify specific variants that mediate resistance or sensitivity to therapies. We hope to use the approach to probe more basic questions about the effects of genetic diversity on various aspects of biology. I’m excited to see the works that will build upon this method, both from our group and others.”

The team’s work was first reported iexternal link, opens in a new tabn a preprint and subsequently publishedexternal link, opens in a new tab on March 12, 2024. 

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Citations

Preprint. “High Throughput Evaluation of Genetic Variants with Prime Editing Sensor Librariesexternal link, opens in a new tab.” Gould, Samuel I., Alexandra N. Wuest, Kexin Dong, Grace A. Johnson, Alvin Hsu, Varun K. Narendra, Stuart S. Levine, David R. Liu, and Francisco J. Sánchez Rivera. doi: 10.1101/2022.10.26.513842

Gould, Samuel I., Alexandra N. Wuest, Kexin Dong, Grace A. Johnson, Alvin Hsu, Varun K. Narendra, Ondine Atwa, Stuart S. Levine, David R. Liu, and Francisco J. Sánchez Rivera. 2024. “High-Throughput Evaluation of Genetic Variants with Prime Editing Sensor Librariesexternal link, opens in a new tab.” PMID: 38472508