Virtual DNA replicates

By Kimberly Patch, Technology Research News

The key to life is self-replication. If an organism can't keep its genetic material going by passing it on to another generation, it fades from view rather quickly. Replication also underpins evolution: throw in a little change variation over a large amount of time, and you get many different organisms.

Self-replication is all around us, but it's not a simple process.

Artificial life researchers from the Canadian National Research Council and the University of Waterloo have found a way to examine the phenomenon more closely using a computer simulation of self-replicating strings of symbols that work as a simplified sort of DNA.

The work promises to provide a better understanding of the nature and origins of life. It also lays the groundwork for inexpensive and flexible manufacturing processes that borrow from life's vast experience, including the possibility of growing machines in vats of chemicals.

The simulation consists of T-shaped virtual objects that exist in a two-dimensional virtual space, and are affected by several forces. The objects "form chains and the chains replicate, much like DNA replicates," said Peter Turney, a senior research officer of at the Canadian National Research Council.

The objects are like DNA's codons, said Turney. Codons are sequences of three nucleotides in a string of genetic code; the portion of DNA that makes up a gene is much longer. Genes provide a blueprint for making a specific protein. Each codon specifies a particular amino acid needed for that protein. The virtual objects assemble into patterns similar to the way codons make up strands of DNA or RNA.

The researchers' simulation, named JohnnyVon after John von Neumann, a founder of the field of computing who did some early work on self-replicating cellular automata, consists of a virtual soup of two types of particles the drift about in a simulated liquid.

The researchers programmed into the simulation several forces that affect interactions among the particles, allowing them to make and break bonds with each other.

The forces are attraction; repulsion; Brownian motion, or random jostling by water molecules; viscosity, or the tendency of water to impede motion; and momentum. The attraction and repulsion forces were inspired by the electrostatic attraction and repulsion of atoms and molecules, but are modeled more like the motion of a spring, said Turney. The objects are also affected by spring dampening -- the oscillations slow down over time because a certain amount of motion converts into heat.

The simulation takes place in a two-dimensional space rather than the three dimensions of reality for practical reasons. It's "a trade-off between computational complexity and realism," said Turney. "It is easier to compute a two-dimensional model than a three-dimensional model," he said.

When the researchers seeded the simulation with a pattern of already-bonded virtual objects, the pattern replicated itself -- the separate particles arranged themselves into the same type of chain, according to Turney. "In nature a seed pattern -- a particular string of DNA -- can replicate," he said.

Evolution requires that patterns -- in the form of DNA -- replicate with characteristics that are inherited, that mutate, and that they do so using a selection process that favors the replication of some patterns over others based on inherited characteristics. The seed pattern results show that JohnnyVon has the properties required for evolution, said Turney.

Achieving self-replication is the first step toward bringing life processes to manufacturing, said Turney.

The same principles could eventually lead to real, nano-scale objects self-assembling in vats of liquid in a manufacturing plant, he said. A nanometer is one millionth of a millimeter, or the size of 10 hydrogen atoms in a row.

"Imagine manufacturing an automobile by dropping a seed pattern into a vat of nanobots suspended in liquid. Different seeds would yield different automobiles or entirely different objects," said Turney.

Self-replication is only the first step toward that end, he added. The specific patterns of DNA represent plans for building proteins, which eventually assemble into cells and bodies. In JohnnyVon, however "seed patterns can only replicate; they do not yet encode plans for building things," said Turney.

Making the self-replicating simulation meant solving several challenges, said Turney. One problem was finding the right balance between realism and computational complexity, he said. The researchers had to make a model that could plausibly be converted to a real physical system, but efficient enough to run on a desktop computer, he said.

They also found balancing the different forces difficult, he said. "It was... a challenge to tune the model to yield reliable, stable, orderly self-replication and avoid spontaneous and chaotic behavior, such as excessive mutation," he said.

Another difficulty was keeping the model purely local and distributed, meaning no centralized control system was directing the process, he said. This is important because local control systems are more lifelike, and also more scalable and robust, or adaptable, than centralized control systems, he added.

The work is a useful contribution to artificial life research, said Jason Lohn, a computer scientist at NASA. "I've done and seen similar work... the novelty [here is] the set of rules the authors have devised that govern interactions," he said.

These rules are potentially useful "in our quest to understand how much complexity is required for self-replication," said Lohn. They also may help in advancing researchers' knowledge of self-assembly techniques, he said.

The researchers' next step is to come up with patterns that encode instructions for building things, rather than merely replicating themselves, said Turney. "In technical terms, we currently have pure genotypes, e.g. raw DNA, with no phenotypes e.g. protein, cells, bodies," he said. "The next step is to add phenotypes."

It will be more than a decade before this type of work could be ready for use in practical manufacturing processes, said Turney.

Turney's research colleagues were Arnold Smith of the Canadian National Research Council, and Robert Ewaschuk of the University of Waterloo in Canada. The research is scheduled to appear in the winter, 2003 issue of the journal Artificial Life. The research was funded by The National Research Council of Canada.

Timeline:   > 10 years
Funding:   Government
TRN Categories:  Artificial Life and Evolutionary Computing; Nanotechnology
Story Type:   News
Related Elements:   Technical paper, "Self-Replicating Machines in Continuous Space with Virtual Physics," Artificial Life, winter, 2003; technical paper, "JohnnyVon: Self-Replicating Automata in Continuous Two-Dimensional Space,"; JohnnyVon Java applet and movies


February 26/March 5, 2003

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