Of all the world-class bets on the genome-editing tool known as Crispr, none is perhaps more tempting than its potential to extract some of humanity's worst diseases directly from the history books. Just this week, Crispr Therapeutics announced that it has begun treating patients with a hereditary blood disorder called beta-thalassemia. This was the first test of the western pharmaceutical industry to test the technology for genetic disease. Despite the progress, however, there is still a multitude of unknowns that prevent Crispr-based drugs from becoming mainstream, especially safety.
This is because the classic, most widely used version of Crispr, by cutting a DNA strand, works at a certain point in the genome and lets the cell sew it together again. The biggest concern is that an army of DNA-disrupting enzymes sometimes goes astray and causes unwanted mutations in places where it should not. In 201
Now it seems that this is premature. Using a new method of measuring unplanned processing, a team of American, Chinese, and European scientists has found that the same basic editor that researchers often use nowadays actually raises the genome with an eyebrow.
The report published today in Science, claims a 20-fold increase in mutations over what would be expected in the normal course of cell division and repair in mouse embryos. "This number depends on a number of factors, but if you want to put this particular editor in a clinical setting, you should probably be concerned," says Stanford biochemist Lars Steinmetz, co-author of the paper. This advice goes above and beyond to scientists who might be tempted to override rules and regulations in order to accelerate the editing of principles to humans, a concern that has occupied them since Crispr's baby scandal broke in November.
The WIRED Guide to Crispr
David Liu, the biochemist whose laboratory at Harvard and The Broad Institute has developed the underlying editor in question, is not so sure of the clinical implications. Steinmetz & # 39; group found nearly 300 other mutations in processed cells as opposed to unprocessed cells. Three hundred errors over six billion bases in the mouse genome give a mutation rate of one in 20 million. Liu points out that the number of mistakes your cells spontaneously make is more than neurons, but less than skin cells. Nevertheless, he says, the article Science is an important step forward in an area that is still working on its security standards. "It's a clever, elegant way to amplify the signal so we can recognize and understand these rare types of independent target events."
A Brief History: In 2017 Nature Methods published a one-page letter claiming that a Crispr treatment that cured two blindness mice also caused a large number of unintentional mutations. The Crispr populations crashed, and scientists dwarfed the dramatic results that were based on sequencing each of the mice and comparing their DNA with unedited siblings. The paper was finally withdrawn and it was found that the changes were only the natural genetic variation between different individuals of the same laboratory. However, the episode pointed to an important blind spot in these error detection technologies. Practically all use an algorithm to select locations in the genome where Crispr probably accidentally goes to work and observe what happened there. "This is an area where you only see what you are looking for," says David Jay Segal, a molecular genetic scientist who studied these effects at the UC Davis Genome Center and was not involved in any of the studies. It would be ideal to search the entire genome for changes. But no one had come up with a good way to do this in living animals with proper controls until the group came from Steinmetz.
The trick was to make each animal its own control. Stay with me. The scientists used mouse embryos that were only one cell division old – so only a total of two cells. In one cell they injected Crispr editing constructs and a reporter protein called tdTomato. The other cell left her alone. And then they let the embryos grow for 14 days. Under a special type of microscope, all the cells that had been processed glowed bright red, while all unprocessed cells remained dark. They used this fluorescence to sort, sequence, and compare all six billion base pairs.
The idea was to develop a method that could detect any unintentional change for any type of Crispr system, Steinmetz says. "We wanted to retrieve changes that are mediated by mechanisms we do not yet understand." Think of it like a red flare gun. It can send a warning signal even if nobody is sure what is going on.
Well, not exactly nobody. The authors speculate that one of Liu & # 39; s base editors tends to acquire naked, single-stranded DNA. In a rapidly dividing embryo, cells have exposed a lot of this type of DNA, giving the basic editor more ways to get confused. Liu, who knows more than anyone, says that's just right.
Since this editor can bind DNA so well even without Crispr's guide, "it's not surprising to see these unwanted edits." Liu, His base editors were from a $ 87 million start-up licensed, which he co-founded. His lab has already developed a number of more accurate versions of his original basic machining approach. This work is still in preparation for publication, he says.
"I do not think this will be a quick fix," says Steve Murray, senior researcher at the Jackson Laboratory, Bar Harbor, Maine. He is part of a consortium of 17 academic research organizations that received $ 190 million from the National Institutes of Health over the next six years to develop protective measures and standards for the treatment of genome therapies. He says there is indeed a bigger story with the new Science paper. In addition to the basic editors, the group of Steinmetz also tested the good "ol Crispr 1.0", the work horse for the processing of genes in the biological research world. And they found it passed with flying colors. In Murray's eyes, this is the first time that convincing evidence has shown that Crispr Classic is not troubled by mechanistic mysterious mistakes. As long as you do a good job and tell him where to go, he'll do the job you designed him for. "It helps to regulate this debate about indefinite goals for which no previous study was really likely to respond properly."
The question in Murray's eyes is, "how many mistakes are there too many?" They tend to make their own mistakes – on the order of once per million to 100 million base pairs, with more for skin cells and less for sperm and eggs. Is it important for an overactive gene editor to bring that number closer to one in 500,000? What is a jumbled gene in a cell of $ 37 trillion? What if the mistake in this one cell turns into cancer? And when a patient is about to die, how important is that?
Murray and his colleagues in the NIH Consortium will address some of these issues over the next six years. He imagines that someday they will be able to calculate risk curves to help doctors and regulators assess the trade-offs between Crispr-based medicines. "I do not think we or anyone can make a strict and fast rule, that after a certain number of mistakes, nothing is useful for anything, and below that it is useful to everything. Every illness is different. Every therapy is different. Every patient is different, "says Murray. "But you have to have the data first to start the discussion." Crispr therapies, it seems, now have another test they need to pass.
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