Assistant Professor Dr. Claus Wilke, who taught biostatistics last spring and will be teaching molecular evolution this fall, studies the evolution of viruses and proteins, using mathematical models to ascertain how they change and adapt over time. Wilke is particularly interested in RNA (Ribonucleic acid) viruses, which have a high mutation rate and can rapidly evolve.
A typical example of an RNA virus is avian influenza. Avian influenza has recently been in the news, as pockets of people in Asia have become infected with the virus that until 1997, when the first human case was discovered in Hong Kong, was thought to only infect birds. The fear now is that this virus will mutate to be able to easily jump from one human to another, possibly resulting in a pandemic that could affect several million people worldwide. “In order to understand how these viral diseases progress in a patient and in a population we need to study them from the perspective of evolutionary biology,” Wilke said.
As a case in point, Wilke was recently approached by Robert Siliciano from the Johns Hopkins University School of Medicine concerning a question about the evolution of HIV, another RNA virus of significant public health interest. Siliciano studies the HIV infection in patients undergoing long-term highly active anti-retroviral therapy (HAART). These patients usually manage to eradicate the virus almost completely from their blood. However, Siliciano's group can detect and amplify a few remaining virus particles in the blood plasma, using highly accurate methods. They found that in several patients, the remaining plasma viruses are dominated by a single sequence.
“The importance of this observation was that HIV is also maintained in resting T-cells of the immune system. The sequences they found in this latent reservoir of infection did not match the sequence found in the plasma viruses,” said Wilke.
The group asked Wilke whether it was possible that the single dominant plasma sequence was maintained by ongoing replication in the blood or if it was generated by some other reservoir that is still unknown. Wilke and Ahmad Sedaghat, a graduate student in Siliciano's group, developed a mathematical model to address this question. “We found that, given the high mutation rate of HIV, ongoing viral replication is very likely not the source of the dominant plasma virus. Instead, all evidence points to a second latent reservoir. However, we currently have no idea what this reservoir could be,” said Wilke. The existence of a second reservoir would be of importance for ongoing efforts to cure patients of the HIV infection.
Wilke is also researching the evolutionary rate of proteins. “Brewer's yeast is the best studied model organism, and we notice the dramatic differences in the rates with which genes accumulate mutations in this organism. In yeast, the fastest evolving genes evolve a thousand times faster than the slowest!” said Wilke. What is the pressure causing this difference? What has been known is that the more highly expressed genes evolve slower. Together with former Caltech graduate student Allan Drummond (currently at UT over the summer, before moving to Harvard to set up his own lab), Wilke has come up with a model that might explain this observation.
The translation process from messenger RNA to protein is fairly error prone. There is approximately a 15% chance that an average-length protein has at least one translation mistake. Mistranslated proteins frequently misfold, and misfolded proteins can be highly toxic for the cell. This toxic effect is stronger the more highly expressed the gene is.
“The hypothesis is that highly expressed proteins should be selected to be tolerant to translation errors in the sense that if an error occurs the protein still folds and functions normally. The paradox lies in the fact that mutations that destroy this tolerance are selected against, so that the proteins that are the most tolerant to mutations actually evolve the slowest,” explained Wilke.
To test their theory, Wilke and Drummond have developed a simulation of the genome evolution of yeast in which protein misfolding is the only fitness cost. “The similarities between the yeast data and the simulation results are striking,” said Wilke. Since fitness costs in yeast are the equivalent of genetic diseases in humans, the greater implication of this work is that it suggests a general and dominant mechanism of genetic disease. There is now evidence that approximately 80% of known human mutations causing disease directly affect protein folding. “The famous misfolding diseases such as Alzheimer’s and Parkinson’s are just the tip of the iceberg,” said Wilke.
Wilke and Drummond have coauthored seven papers on protein biophysics and evolution, and continue to work closely. "Claus is a skeptical and generous collaborator," said Drummond. “He is a skeptical and generous collaborator: quick to identify sloppy thinking, focused on getting the result rather than governing the process, willing to let you follow your nose. He's that rare physicist-crossover who embraces and worries about the biology in all its messy complexity, and produces quantitatively correct work which honors that complexity. He is hands-down the scientist I most enjoy working with.”
Wilke is also a member of the center for Computational Biology and Bioinformatics, and involved in both the Cellular Molecular Biology and Integrative Biology graduate programs.