Self-improvement a Never-ending Cycle for Bacteria in their 58,000 Generation

It's an endless cycle of self-improvement for the bacteria in the lab of Richard Lenski, a professor of microbiology and molecular genetics at Michigan State University.

For a quarter of a century, Lenski has been watching a group of bacteria generate 58,000 generations in a controlled environment. And while conventional wisdom has long held that adaptation eventually peters out in a stagnant environment, Lenski says the bacteria are still becoming more and more fit.

"There doesn't seem to be any end in sight," he said. "We used to think the bacteria's fitness was leveling off, but now we see it's slowing down but not really leveling off."

Stored in a deep freezer is an entire frozen fossil record going all the way back to generation zero. Unlike most fossils, however, these are alive, allowing the researchers to easily compare the older generations with the newest arrivals.

"I call this the experiment that keeps on giving," Lenski said. "Even after 25 years, it's still generating new and exciting discoveries. From the models, we can predict how things will evolve - how fit the bacteria will become - if future generations of scientists continue the experiment long after I'm gone."

Michael Wiser, lead author and graduate student in Lenski's lab, compares it to hiking.

"When hiking, it's easy to start climbing toward what seems to be a peak, only to discover that the real peak is far off in the distance," Wiser said. "Now imagine you've been climbing for 25 years, and you're still nowhere near the peak."

Noah Ribeck, co-author and postdoctoral researcher, developed a model using a number of well-established principles.

"It was surprising to me that a simple theory can describe the entirety of a long evolutionary trajectory that includes initially fast and furious adaptation that later slowed to a crawl," Ribeck said. "It's encouraging that despite all the complications inherent to biological systems, they are governed by general principles that can be described quantitatively."