Scientists Uncover Rules That Govern The Rate Of Protein Evolution

Now, a team of researchers at the California Institute of Technology, applying novel data-mining methods to the now-completed sequence of the yeast genome, have uncovered a surprising reason why different proteins evolve at different rates.

Reporting in the September 19 edition of the journal Proceedings of the National Academy of Sciences (PNAS), lead author Allan Drummond and his coauthors from Caltech and the Keck Graduate Institute show that the evolution of protein is governed by their ability to tolerate mistakes during their production. This finding disputes the longstanding assumption that functionally important proteins evolve slowly, while less-important proteins evolve more quickly.

"The reason proteins evolve at different rates has been a mystery for decades in biology," Drummond explains. But with the recent flood of sequenced genomes and inventories of all the pieces and parts making up cells, the mystery deepened. Researchers discovered that the more of a protein that was produced, the slower it evolved, a trend that applies to all living things. But the reason for this trend remained obscure, despite many attempts to explain it.

Biologists have long known that the production machinery that translates the genetic code into proteins is sloppy. So much so, in fact, that on average about one in five proteins in yeast is mistranslated, the equivalent of translating the Spanish word "Adios" as "Goofbye." The more copies of a protein produced, the more potential errors. And mistakes can be costly: some translation errors turn proteins into useless junk that can even be harmful (like miscopying a digit in an important phone number), while other errors can be tolerated. So the more protein copies per cell, the more potential harm-unless those abundant proteins themselves can evolve to tolerate more errors.

"That was the 'Aha!'" says Drummond. "We knew from our experiments with manipulating proteins in the lab that some had special properties that allowed them to tolerate more changes than other proteins. They were more robust." So, what if proteins could become robust to translation errors? That would mean fewer harmful errors, and thus a more fit organism.

To test predictions of this hypothesis, the team turned to the lowly baker's yeast, a simple one-celled organism that likes to suck up the nutrients in bread dough, and then expels gas to give baked bread its fluffy texture. Baker's yeast is not only a simple organism, it is also extraordinarily well understood. Just as biologists have now sequenced the human genome, they have also sequenced the yeast genome. Moreover, the numbers of every type of protein in the yeast cell have been painstakingly measured.

For example, there's a protein in the yeast cell called PMA1 that acts as a transformer, converting stored energy into more useful forms. Since nothing living can do without energy, this is a very fundamental and important component of the yeast cell. And every yeast cell churns out about 1.26 million individual PMA1 molecules, making it the second-most abundant cellular protein.

The old assumption was that PMA1 changed slowly because its energy-transforming function was so fundamental to survival. But the Caltech team's new evidence suggests that the sheer number of PMA1 molecules produced is the reason that the protein doesn't evolve very quickly.

"The key insight is that natural selection targets the junk proteins, not the functional proteins," says Drummond. "If translation errors turned 5 percent of the PMA1 proteins in a yeast cell into junk, those junk proteins would be more abundant than 97 percent of all the other proteins in the cell. That's a huge amount of toxic waste to dispose of."

So instead, Darwinian evolution favors yeast cells with a version of PMA1 that continues to function despite errors, producing less junk. That version of PMA1 evolves slowly because the slightest changes destroy its crucial ability to withstand errors.

Consider two competing computer factories. Both make the same number of mistakes on their assembly lines, but one company's computers are designed such that the inevitable mistakes result in computers that still work, while with the other company's design, one mistake and the computer must be tossed on the recycling heap. In the cutthroat marketplace, the former company, with lower costs and higher output, will quickly outcompete the latter.

Likewise, viewing yeast cells as miniature factories, the yeast whose most-abundant proteins are least likely to be destroyed by production mistakes will outcompete its less-efficient rivals. The more optimized those high-abundance proteins are--the more rigid the specifications that make them so error-resistant-the slower they evolve. Hence, high abundance means slow evolution.

The team is now exploring other predictions of this surprising hypothesis, such as what specific chemical changes allow proteins to resist translation errors. "It's the tip of the iceberg," Drummond says.

Drummond is a graduate student in Caltech's interdisciplinary Computation and Neural Systems program. The other authors of the paper include his two advisors: Frances Arnold, the Dickinson Professor of Chemical Engineering and Biochemistry at Caltech, and Chris Adami, an expert in population genetics who is now at the Keck Graduate Institute in Claremont, California. The other authors are Jesse D. Bloom, a graduate student in chemistry at Caltech; and Claus Wilke, a former postdoctoral researcher of Adami's who has recently joined the University of Texas at Austin as an assistant professor.

The title of the PNAS paper is "Why highly expressed proteins evolve slowly."