New algorithms make CRISPR as easy as point-and-click
Biotechnologists are jumping at the chance to use the revolutionary gene-editing tool known as CRISPR. The molecular gadget can be programmed to accurately tweak the DNA of any organism, but scientists need software algorithms to hasten the programming process. Dozens of teams are developing such software, and each faces the task of keeping up with rapidly evolving science and an increasingly crowded field.
CRISPR—short for Clustered, Regularly Interspaced, Short Palindromic Repeats—is a genetic phenomenon found in microbes that scientists adapted to disable a gene or add DNA at precise locations in the genetic code. CRISPR isn’t the first gene-editing tool on the block, but it is by far the simplest and cheapest, and since its adaptation four years ago, it has proliferated globally. Researchers can use it to knock out genes in animal models to study their function, give crops new agronomic traits, synthesize microbes that produce drugs, create gene therapies to treat disease, and potentially—after some serious ethical debate—to genetically correct heritable diseases in human embryos.
In less than four years, CRISPR “has transformed labs around the world,” says Jing-Ruey Joanna Yeh, a chemical biologist at Massachusetts General Hospital’s Cardiovascular Research Center, in Charlestown, who contributed to the development of the technology. “Because this system is so simple and efficient, any lab can do it.” Traditional genome modification techniques involve shuttling DNA into cells without knowing where in the genome it will stick. Editing with CRISPR is like placing a cursor between two letters in a word processing document and hitting “delete” or clicking “paste.” And the tool can cost less than US $50 to assemble. There are other genome-editing systems that are as precise as CRISPR, but they must be customized for every use and require far more expertise and resources to assemble.
As good as CRISPR is compared to its predecessors, the tool doesn’t always work, says Jacob Corn, scientific director at the Innovative Genomics Initiative at the University of California, Berkeley. “We don’t really understand why that is,” he says. That’s where software comes in. Algorithms can help researchers design their CRISPR tools in a way that is statistically more likely to succeed.
CRISPR systems are equipped with two main features: a short strand of programmable genetic code (called a guide RNA) and a protein (usually an enzyme called Cas9) that acts as a pair of molecular scissors. Once the complex is introduced into a cell, the guide RNA ushers Cas9 to a precise location in an organism’s DNA sequence (or genome), sticks to it like Velcro, and lets the Cas9 snip the DNA. The cell’s own machinery then repairs the cut, chewing up a bit of DNA or adding some in the process, thus disrupting the gene. Researchers can also intentionally introduce a piece of new genetic code to the site.
Guide RNAs find their targets in an organism’s genome by looking for a DNA segment with a complementary code of molecules. The molecules are called bases and are represented by the letters A (adenine), T (thymine), G (guanine), and C (cytosine).
