Digital Organisms Used To Confirm Evolutionary Process
- Date:
- July 19, 2001
- Source:
- Michigan State University
- Summary:
- Using a revolutionary computer program that gives scientists the opportunity to watch evolution take place before their eyes using "digital organisms," a team of researchers from Michigan State University and Caltech has confirmed an evolutionary process long suspected but, until now, unproven.
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EAST LANSING, Mich. - Using a revolutionary computer program that gives scientists the opportunity to watch evolution take place before their eyes using "digital organisms," a team of researchers from Michigan State University and Caltech has confirmed an evolutionary process long suspected but, until now, unproven.
In a paper published in the July 19 edition of the journal Nature, MSU researchers Richard Lenski and Charles Ofria, along with colleagues at Caltech, provided some insight into one aspect of Darwin's theory of natural selection that they dubbed "survival of the flattest."
The paper's title: "Evolution of Digital Organisms at High Mutation Rates Leads to Survival of the Flattest."
This play on Darwin's own "survival of the fittest" incorporates the fact that fitness depends not only on the quantity of offspring an organism can produce in its lifetime, but also how fit those offspring will be.
Lenski and colleagues make the analogy to mountain climbing: the height of the peak you are on is your speed of replication, and the strength of the winds your mutation rate. If there were only a gentle breeze, you would be most fit by climbing to the highest peak you can. But in a more turbulent hurricane, you would want to find someplace where there is not such a long distance to fall - someplace flat.
A fast replicator may be producing many children, but if it's too susceptible to the harmful effects of mutations, it won't contribute to future generations much beyond that. As Lenski put it, "It would have lots of children but not lots of grandchildren."
Specifically, the researchers found that there is tradeoff between producing offspring faster and making them better able to withstand the harmful effects of most mutations. The bottom line: When mutation rates are high, it is better for a species to reproduce more slowly if this allows its offspring to avoid being seriously harmed by mutations.
"Theory predicts that genomes that have evolved at a high mutation rate will have become more robust to the harmful effects of mutations than genomes that have evolved at a low mutation rate," said Lenski, MSU Hannah Professor of Microbial Ecology. "However, theory also predicts that there is a price to be paid for this robustness, which is that more robust genomes will tend to replicate more slowly than genomes that are less robust."
"A species that can reproduce quickly, but loses most of its offspring due to frequent, deleterious mutations may be out-competed by a slower, but more robust species," said Ofria, assistant professor in MSU's Center for Microbial Ecology.
The computer software that creates the digital organisms used to do this work is called "Avida" - A for artificial and vida is Spanish for life. It gives scientists the chance to watch over a period of a few hours a natural evolutionary process that would normally take years.
"Using Avida, the digital organisms can mutate at a rate that we can control in our experiments," Lenski said. "Hence, we let some populations evolve at low and others at high mutation rates and examine the effects on growth and susceptibility to mutation."
The digital organisms are comparable to computer viruses, "except digital organisms are harmless because their programs are meaningless outside the special operating environment in Avida," he said.
The researchers do not put any outside constraints on the computational abilities of these programs.
"Theoretically, any possible algorithm can evolve," said Ofria, the creator of the Avida system. "In fact, in each experiment, the population proceeds along a new evolutionary pathway."
Teaming with Lenski and Ofria on this paper were Christoph Adami of the Jet Propulsion Laboratory, Caltech; and Claus Wilke and Jialan Wang of Caltech's Digital Life Laboratory.
The National Science Foundation funded the work.
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