Richard Lenski – Observing evolution in action EAST LANSING, Mich. ‐‐ Evolution takes on a whole new look and feel when it comes to the work of evolutionary biologist Richard Lenski. Most study evolution from fossils or by comparing different species. Lenski studies evolution by doing experiments with fast‐reproducing organisms that allow him watch evolution in action. “Evolution is like a game that combines luck and skill, and I thought that, perhaps, bacteria could teach me some interesting new games,” recalled Lenski, the Hannah Professor of Microbial Ecology at Michigan State University, and associated with the Michigan Agricultural Experiment Station. In 1988, Lenski started an experiment with 12 populations of E. coli bacteria ‐‐ all starting with the same ancestral strain and all living in identical environments ‐‐ to see just how similarly or differently they would evolve. He wanted to keep the experiment going for at least a year and culture about 2,000 bacterial generations. Twenty‐one years and almost 50,000 generations later, the experiment is still growing strong. Every day, Lenski or someone in his laboratory has fed the bacteria by transferring a few drops of grown‐up culture into fresh culture medium. Each day, the bacteria grow for over six generations before they run out of food, and then the process is repeated day in and day out, year after year. If a mutation occurs that gives one of the cells an advantage in competition for the limited food, that cell will leave more descendents and may eventually take over the entire culture. That’s the idea behind Charles Darwin’s theory of natural selection. While that theory has been confirmed by many previous studies, it has never before been studied for so many generations and in such detail by direct experimentation. Freezing time Along the way, Lenski and his team would periodically freeze samples of the bacteria for future study, what he likes to call a “frozen fossil record.” As the years went by, powerful technologies were invented to analyze the genetics of bacteria, culminating in the ability to sequence their entire genomes. “I had no idea then that new technologies would help us find all of the changes in the DNA,” Lenski said. “But since we saved bacterial samples throughout the experiment in a deep‐freezer, it’s like time travel because we can now directly compare their genomes across tens of thousands of generations.” Other teams also use genome sequencing to find mutations, but what sets this new work apart are the questions that can be answered by Lenski’s long‐running experiment. For example, do the rates of change in the bacteria’s genome and their fitness – how well adapted they are to their environment – slow down or speed up in tandem? Or do they each march to a different drummer? Jihyun Kim, senior scientist at the Korea Research Institute of Bioscience and Biotechnology, leads a team of genomics experts working with the Lenski lab. The first challenge they faced was to sequence the genome of the ancestral strain that Lenski used to start the experiment. They then tried different methods for sequencing the evolved bacterial genomes, finally settling on an approach with the accuracy to find a few tens or hundreds of mutations among the several million bits in each genome. “It’s an exciting time for biology,” Kim said, “as we have a technology to read out the code of DNA so much at a time and so fast.” To interpret the data, Jeffrey Barrick, an MSU postdoctoral researcher in the Department of Microbiology and Molecular Genetics, developed computational tools to discover and validate the mutations, including complex mutations that rearrange the order of some genetic bits. Some of these complex mutations, on first impression, look like mistakes in the sequencing technology, but in fact they are important changes that could otherwise be overlooked. “We know an astounding amount about the details of evolution in these little Erlenmeyer flasks,” Barrick said. Gene sequencing tracks mutations The researchers sequenced genomes from seven time points including the ancestral strain and bacteria sampled from 2,000, 5,000, 10,000, 15, 000, 20,000 and 40,000 generations. By 20,000 generations, there were a total of 45 mutations. Although millions of mutations had occurred in the daily cultures to that point in time, the vast majority of the mutations were eliminated from the surviving lineage because they were harmful or just plain unlucky. The pattern of evolution changed suddenly, however, during the second half of the experiment. Around generation 26,000, a mutation hit a gene involved in DNA metabolism. That mutation caused the mutation rate everywhere else in the genome to increase dramatically. As a result, the number of mutations jumped to 653 at generation 40,000. Almost all of the later mutations had a tell‐tale signature that was caused by the defect in DNA metabolism. The researchers surmise that, unlike the earlier mutations, most of these late‐evolving mutations were not actually helpful to the bacteria. In humans, mutations in genes involved in DNA replication are involved in some cancers. Many of the same patterns observed in this experiment also “occur in certain microbial infections, and cancer progression is a fundamentally similar evolutionary process,” Barrick noted. “So what we learn here can help us better understand the course of these diseases.” Those mutations that survived, according to Darwin’s theory, should have been those that gave cells some advantage. That’s exactly what the researchers found, based on several lines of evidence. For example, when the scientists moved individual mutations from later generations back into the ancestor, they observed that most of those evolved mutations gave the bacteria a competitive advantage. The results “beautifully emphasize the succession of mutational events that allowed these organisms to climb towards higher and higher efficiency in their environment,” said Dominique Schneider, another international research collaborator. Schneider is a molecular geneticist at the Université Joseph Fourier in Grenoble, France. He led the research to analyze what effects the mutations have, including how they help the bacteria to grow faster and compete better than their ancestors. “We are now at the crossroads of many research opportunities,” Schneider said. One is to understand how those successive changes are connected at the molecular level to produce “organisms that are so exquisitely adapted to their habitat.” A new strain emerges A stunning example of evolution occurring before researchers’ eyes occurred last year, when one of the 12 populations of E. coli being studied evolved the ability to eat a chemical called citrate – a compound that, until now, E. coli could not grow on. “This development was particularly exciting because it showed that, in a relatively short period of time – a couple of decades – a brand new function could evolve,” Lenski said. Although he pursues basic research, Lenski’s work has led others to think about various applications, including microbial forensics, strain improvement and computational evolution. “After the anthrax attacks, which shortly followed the 9/11 terrorist attacks, it became imperative to understand how to track the source of bacterial populations that might be used in bio‐terrorism,” Lenski said. “Because of this long‐term experiment, we now have the best data on how quickly strains change at the genomic level and how much genetic variation exists within a sample. This study has become a reference point for understanding the evolution of other bacteria.” Further, Lenski said, it’s increasingly recognized that evolution can be used alone or, better, in combination with genetic engineering, to produce bacterial strains that have desirable features such as producing alternative fuels or remediating pollution. The research “is not only useful in understanding the tempo and mode of evolution, but can serve as a nice framework for practical applications in biotechnology, such as improving the performance or productivity of an industrial strain,” collaborator Jihyun Kim added. Going digital Lenski’s work also crosses into in the digital world. Over the last decade, Lenski has teamed up with MSU computer scientist Charles Ofria, MSU philosopher Rob Pennock and Chris Adami, a physicist from Keck Graduate Institute in Claremont, Calif., to study computer programs that self‐replicate, mutate and evolve new abilities. “Computer scientists and engineers are looking to evolution to inform their endeavors and garner new ways of solving problems,” Lenski said. “My colleagues have developed software that can be used to demonstrate and explain evolutionary mechanisms and help develop new technologies in the areas of networks, communication systems and robotics. Darwin would be amazed to see where his ideas have led.” This year is the sesquicentennial of the first publication of Darwin’s magnum opus, The Origin of Species. “It’s extra nice now to be able to show precisely how selection has changed the genomes of these bacteria, step by step over tens of thousands of generations,” Lenski said. “Like a lot of science,” he said, “our study answers some questions but raises many others.” ### From the Summer/Fall 2009 issue of Futures published by the Michigan Agricultural Experiment Station, with additional content by Richard Lenski. .