Polz and former graduate student Dana Hunt, now a postdoctoral researcher at the University of Hawaii, created a large and accurate genetic data set by isolating and identifying over 1,000 strains of vibrio bacteria from a sample of eight liters of seawater gathered near Plum Island, Mass., in the spring and fall. To achieve accuracy in their identification of strains, they selected a gene whose molecular clockthe rate at which a gene accumulates random mutations over timewas well-suited to the task.
The trick in many ways is choosing a gene that has a molecular clock that ticks at the right rate, said Polz. In particular, if its too slow, you might lump organisms into a single group that you would actually like to differentiate. We chose a gene that accumulates mutations fairly fast and thus allowed us to differentiate closely related groups of individuals and map the ecological data we collected onto their family tree.
Alm and graduate student Lawrence David wrote an algorithm to make a conservative estimate of the minimum number of different habitats occupied by the vibrios (whether they live on small or large particles and thrive in the cool or warm months, etc.). They then combined information about habitat with phylogeny (the evolutionary history of groups of genes), and apportioned the original strains into 25 distinct populations and mapped their habitats back to a common ancestor, showing when and how each group diverged from the ancestral lifestyle.
What is really new about our approach is that we were able to combine both molecular data (DNA sequences) with ecological data in a single mathematical framework, said Alm. This allowed us to solve the inverse problem of taking samples
|Contact: Denise Brehm|
Massachusetts Institute of Technology, Department of Civil and Environmental Engineering