What changes to viral genomes would allow them to infect new species? And, what are the natural processes – mutation, recombination, and natural selection – that permit their evolution? My lab group uses experimental evolution of viruses to find answers to these questions. We are able to culture viruses in the laboratory, watch them evolve in real time, and on occasion, witness them gain access to new host species. Our studies combine methods from many fields of biology. We typically begin research by modifying classic ecological niche theory to make predictions for viral host-range evolution. Next we test the theory by culturing viruses under controlled conditions. We sequence the evolved viral genomes to identify adaptive mutations, and then we determine the effects of the mutations by introducing them into naïve viral genomes using Multiplexed Automated Genome Engineering. Lastly, we characterize their newly evolved qualities by using single molecule biophysics assays. Altogether, the studies provide a complete picture for how gain-of-function mutations evolve in viruses.
Most of our work to date has been preformed on the virus Bacteriophage λ, which infects E. coli. We have observed λ evolve to exploit a novel receptor, the outer-membrane protein OmpF. Typically λ only targets another protein, LamB, however under the right conditions it naturally evolves this innovation. Which receptors a virus exploits largely determine their host-range, and so, acquiring a new receptor constitutes a major transition for the virus. Currently our research group is continuing to test hypotheses for how this evolved, but we are also applying the tools we developed to study λ to other viral systems.
Image by Brian Wade
Image by Justin Meyer
Justin Meyer received his Ph.D. from Michigan State University and was a Systems Biology Departmental Fellow at Harvard Medical School, where he was awarded the James S. McDonnell Foundation Fellowship for Studying Complex Systems. He joined the faculty of Ecology Behavior and Evolution and the Quantitative Biology Initiative in 2014.