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The DNA inside human cells provides instructions for all of the processes that happen inside the body. Errors in the DNA may lead to cancer, sickle cell disease, cystic fibrosis, Huntington’s disease, or other genetic disorders. Medical researchers are exploring whether it is possible to replace or repair the faulty DNA (an approach known as gene therapy) to reduce the symptoms, or even cure individuals, of these conditions. Over the last ten years, a new technology known as CRISPR-Cas9 gene editing has proved to be a reliable and efficient way to make small and precise changes to DNA in living cells. First, an enzyme called Cas9 searches for a segment of target DNA segment that matches a template molecule the enzyme carries. Cas9 then cuts the target DNA, which is repaired to match a new customized DNA sequence: this changes the genetic information of the cell. The Cas9 protein is made of a succession of building blocks called amino acids that create long chains which then fold to form the final three-dimensional shape of the enzyme. A region of Cas9 known as the HNH domain is responsible for cutting the target DNA. However, it remains unclear exactly which amino acids within this domain work together to sever the DNA. Here, Zuo et al. combined computational and experimental approaches to reveal the three-dimensional structure of the Cas9 enzyme when the HNH domain is poised to cut the target DNA. The findings were used to generate a computational model of Cas9 and this model predicted that the HNH domain relies on a group of three amino acids known collectively as D839-H840-N863 to cleave DNA strands. This knowledge is useful to understand exactly how Cas9 modifies genetic information. Ultimately, this may help to improve CRISPR-Cas9 technology so it could be safely used in geneediting therapies.
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Comprehensive phylogenetic analysis of the ribonucleotide reductase family reveals an ancestral clade
Billions of years ago, the Earth’s atmosphere had very little oxygen. It was only after some bacteria and early plants evolved to harness energy from sunlight that oxygen began to fill the Earth’s environment. Oxygen is highly reactive and can interfere with enzymes and other molecules that are essential to life. Organisms living at this point in history therefore had to adapt to survive in this new oxygen-rich world. An ancient family of enzymes known as ribonucleotide reductases are used by all free-living organisms and many viruses to repair and replicate their DNA. Because of their essential role in managing DNA, these enzymes have been around on Earth for billions of years. Understanding how they evolved could therefore shed light on how nature adapted to increasing oxygen levels and other environmental changes at the molecular level. One approach to study how proteins evolved is to use computational analysis to construct a phylogenetic tree. This reveals how existing members of a family are related to one another based on the chain of molecules (known as amino acids) that make up each protein. Despite having similar structures and all having the same function, ribonucleotide reductases have remarkably diverse sequences of amino acids. This makes it computationally very demanding to build a phylogenetic tree. To overcome this, Burnim, Spence, Xu et al. created a phylogenetic tree using structural information from a part of the enzyme that is relatively similar in many modern-day ribonucleotide reductases. The final result took seven continuous months on a supercomputer to generate, and includes over 6,000 members of the enzyme family. The phylogenetic tree revealed a new distinct group of ribonucleotide reductases that may explain how one adaptation to increasing levels of oxygen emerged in some family members, while another adaptation emerged in others. The approach used in this work also opens up a new way to study how other highly diverse enzymes and other protein families evolved, potentially revealing new insights about our planet’s past.
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- Award ID(s):
- 1942668
- PAR ID:
- 10387891
- Date Published:
- Journal Name:
- eLife
- Volume:
- 11
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.79790
