Breeding Computer Code
An interdisciplinary team of scientists at Michigan State University and the California Institute of Technology, with the help of powerful computers, has used a kind of artificial life, or ALife, to create a road map detailing the evolution of complex organisms, an old problem in biology.
In an article in the May 8 issue of the international journal Nature, Richard Lenski, Charles Ofria, Robert Pennock, and Christoph Adami report that the path to complex organisms is paved with a long series of simple functions, each unremarkable if viewed in isolation.
|Dr. Chris Adami Credit: SpaceDaily.com|
One Step Back, Two Leaps Forward
Moreover, the article states, some mutations that cause damage in the short term ultimately become a positive force in the genetic pedigree of a complex organism.
"The little things, they definitely count," said Lenski, MSU Hannah Distinguished Professor of Microbial Ecology and the paper’s lead author. "Our work allowed us to see how the most complex functions are built up from simpler and simpler functions. We also saw that some mutations looked like bad events when they happened, but turned out to be really important for the evolution of the population over a long period of time."
In the key phrase, "a long period of time," lies the magic of ALife. Lenski teamed up with Adami, a faculty associate and principal scientist at Caltech’s Jet Propulsion Laboratory and Ofria, an MSU assistant professor of computer science and engineering, after a chance meeting with a colleague on the squash court led him to hear a seminar about their work.
|An "artificial petri-dish" studied by Adami and his colleagues.|
Their first Nature paper on digital evolution was published in 1999. Pennock, an MSU associate professor of philosophy, now joins the team as they study an artificial world inside a computer, a world in which computer programs take the place of living organisms. They go forth and multiply, they mutate and they adapt by natural selection.
The program, called Avida, is basically an artificial petri dish in which organisms not only reproduce, but also perform mathematical calculations to obtain rewards. Their reward is more computer time that they can use for making copies of themselves. Avida randomly adds mutations to the copies, thus spurring natural selection and evolution. The research team watches how the bugs adapt and evolve in different environments inside their artificial world.
Avida is the platform to watch evolution as it might appear in most living organisms requiring thousands of years without blinking. The organisms exist as sequences of self-replicating computer code. The digital bugs evolve at lightning speed, and they leave tracks for scientists to study.
"The cool thing is that we can trace the line of descent," Lenski said. "Out of a big population of organisms you can work back to see the pivotal mutations that really mattered during the evolutionary history of the population. The human mind can’t sort through so much data, but we developed a tool to find these pivotal events."
Humans create the digital creatures by writing their initial computer code. But, says Adami, "they usually shed that coding after a few tens of generations, basically because it’s inane as far as they’re concerned. They just throw it away immediately and come up with something that is much more adapted to the kind of conditions that they live in."
There are no missing links with this technology. Evolutionary theory sometimes struggles to explain the most complex features of organisms. Lenski uses the human eye as an example. It’s obviously used for seeing, and it has all sorts of parts like a lens that can be focused at different distances that make it well suited for that use. But how did something so complicated as the eye come to be?
|View Streaming Video. The still-frames depict a competition for resources between two strains of digital organism. Species A (green) replicates twice as fast as Species B (blue), but Species B is more robust. In the top series (View movie as downloadable mpeg-7 MB), which represents a mutation rate of 0.5 mutations per generation, the faster-replicating Species A easily wins out over Species B. In the bottom frame (View movie as downloadable mpeg-7 MB), which represents a mutation rate of 1.5 mutations per generation, the more-robust Species B triumphs. |
Credit: courtesy of C.O. Wilke
Since Charles Darwin, biologists have concluded that such features must have arisen through lots of intermediates and, moreover, that these intermediate structures may once have served different functions from what we see today. The crystalline proteins that make up the lens of the eye, for example, are related to those that serve enzymatic functions unrelated to vision. So, the theory goes, evolution borrowed an existing protein and used it for a new function.
"Over time," Lenski said, "an old structure could be tweaked here and there to improve it for its new function, and that’s a lot easier than inventing something entirely new."
That’s where ALife sheds light.
"Darwinian evolution is a process that doesn’t specify exactly how the evolving information is coded," says Adami, who leads the Digital Life Laboratory at Caltech. "It affects DNA and computer code in much the same way, which allows us to study evolution in this electronic medium."
Many computer scientists and engineers are now using processes based on principles of genetics and evolution to solve complex problems, design working robots, and more. Ofria, a computer scientist, says: "We can then apply these concepts when trying to decide how best to solve computational problems."
"Evolutionary design," says Pennock, "can often solve problems better than we can using our own intelligence."
As Darwin wrote in The Origin of Species: "The great power of this principle of selection is not hypothetical…By a similar process of selection, and by careful training, the whole body of English racehorses have come to surpass in fleetness and size the parent Arab stock. Breeders habitually speak of an animal’s organisation as something quite plastic, which they can model almost as they please. But it is very far from true that the principle is a modern discovery. "
"This project addresses a fundamental criticism of the theory of evolution, how complex functions arise from mutation and natural selection," said Sam Scheiner program director in the NSF’s division of environmental biology. "These simulations will help direct research on living systems and will provide understanding of the origins of biocomplexity."
Adami believes that his research may also prove useful in the search for extraterrestrial life. One of the difficult questions that astrobiologists struggle with is how they will be able to recognize the biosignature of life forms on other worlds that may have a different chemical foundation than life on Earth.
Adami thinks his digital organisms can help. As he points out, "We’re the only ones who have an alien form of life at our disposal." He has found, for example, that digital organisms that have evolved through many generations display a curious pattern of instructions. "Some instructions are used much more often and some other instructions are used much, much, much less than their random occurrence."
A similar pattern can be seen among amino acids on Earth. Wherever life is at work, the amino acids favored by biological organisms appear in much higher concentrations than they do in the absence of life. Even if you knew nothing about the chemistry of life on Earth, Adami suggests, seeing an atypical abundance of some amino acids, regardless of their specific chemistry, could signal that some type of life was present.
Adami, who is working with Ken Nealson at JPL’s Center for Life Detection and Evan Dorn at Caltech, believes that understanding life’s patterns in this generalized, abstract way can help researchers develop a non-Earth-centric approach to the search for life on other worlds.
"If you are interested in discovering life on other planets, then clearly you would like to be as non-specific as you can about how you go about it," Adami says. "Because you can’t assume that life [elsewhere] is coded in nucleic acids and proteins just as it is on Earth."
This research was supported by the U.S. National Science Foundation under its biocomplexity initiative, with additional funding from The MSU Foundation.
Related Web Pages
Studying Evolution with Digital Organisms
Digital Life Laboratory
Researchers Mutate Digital Organisms
Survival of the Flattest
Digital Organisms Used to Confirm Evolutionary Process