Emory biochemist Eric Ortlund participated in a study that was recently published in Proceedings of the National Academy of Sciences, which involves tinkering with billions of years of evolution by introducing mutations into DNA polymerase.
DNA polymerases, enzymes that replicate and repair DNA, assemble individual letters in the genetic code on a template. The PNAS paper describes efforts to modify Taq DNA polymerase to get it to accept “reversible terminators.” (Taq = Thermus aquaticus, a variety of bacteria that lives in hot springs and thus has heat-resistant enzymes, a useful property for DNA sequencing)
Ortlund was involved because he specializes in looking at how evolution shapes protein structure. Along with co-author Eric Gaucher, Ortlund is part of the Fundamental and Applied Molecular Evolution Center at Emory and the Georgia Institute of Technology.
To sequence DNA faster and more cheaply, scientists are trying to get DNA polymerases to accept new building blocks. This could facilitate next-generation sequencing technology that uses “reversible terminators” to sequence many DNA templates in parallel.
Conventional DNA sequencing uses dye-terminators: building blocks that can’t be extended, attached to a dye that is different for each base (A,G,C or T). That way the polymerase creates a mixture of strings of building blocks. Each string has a different size and ends in a terminator.
Evolution has fine-tuned DNA polymerases’ ability to discriminate DNA building blocks (deoxyribonucleoside triphosphates) from RNA building blocks (ribonucleoside triphosphates), even though both types of building blocks are floating around in the cell. The right kinds of building blocks fit, and the wrong ones don’t.
That means that any time scientists mess around “under the hood,” they’re messing with some sensitive machinery. A method called “reconstructing adaptive evolutionary paths”, developed by Gaucher, was key to identifying parts of the polymerase that could be changed without destroying its function.
More on next-generation sequencing