This paper is published in Proceedings of the Genetic and Evolutionary Computation Conference (v 2, p 1444), W. Banzhaf et al., eds., Morgan Kaufmann Publishers, San Francisco, 1999 [PDF]; and was presented at that conference, GECCO-99, in Orlando, Florida, 13-17 July 1999.|
In Real or Artificial Life, Is Evolutionary Progress in a Closed System Possible? What'sNEW | Lenski et al.
Assumptions are more striking than ideas — Alexander Hiam
Evolutionary progress in life on Earth is evident in the long series of steps that lead from prokaryotic life almost four billion years ago to the variety of multi-celled eukaryotic creatures with specialized organs, tissues, systems and features that exist here today. It is driven by the accumulation of new genes, the encoded instructions for life. We would like to understand this progress.
Energy reaches Earth from the sun, of course, but encoded instructions do not. We have long believed that evolutionary progress takes place in a biologically closed system, because we thought, until recently, that space was a perfect barrier to life, making our whole planet a closed biological system.
Today, however, we know that space is an imperfect barrier to life. We now know that cells can survive in space and could be delivered in viable form to Earth's surface (NASA, 1999). We now know that dormant bacterial spores can remain viable for at least 25 million years (Cano and Borucki, 1995); it is reasonable to suppose that they are immortal (Postgate, 1994). There is growing evidence that Mars once harbored bacteria, and that rocks containing them have reached Earth (McKay et al., 1996). It is no longer certain, nor even likely, that Earth's biological system is closed.
Closed-system demonstrations of evolutionary progress in biology are not difficult in principle, but they have not been convincingly done. The most ambitious demonstration to date is a series of experiments on E. coli that have cumulatively run for 24,000 generations. Although mutation and recombination were rampant, no new genes or suites of genes with new functions were reported to have evolved. Only microevolution or sideways adaptations by mutations that enabled, disabled, or slightly changed existing genes took place (Papadopoulos et al., 1999; Vulic et al., 1999).
Meanwhile, biologists are finding more and more evidence, like viral genes in humans (Sverdlov, 1998), indicating that the lateral transfer of genes is a ubiquitous process. The biological means to make evolutionary progress in an open system are becoming well known (Lake et al., 1999).
At this point, the case for evolutionary progress in a biologically closed system depends heavily on the remotest evidence of all, the new perfect barrier to life, the big bang. If the whole universe is a permanently closed system that began in a lifeless state a finite time ago, then evolutionary progress, including the origin of life, must have subsequently happened in it. But the big bang theory is plagued with frequent surprises (e.g. Glanz, 1998). In some versions, big bangs are preceded by other big bangs ad infinitum (Guth, 1997), and ways for life to persist through big bangs have been proposed (Frautschi, 1982; Krauss and Starkman, 1999). In any case, to understand evolutionary progress biology should be able to cite firmer and more immediate evidence than the big bang!
With its basis insecure and under revision, and with an alternative becoming apparent, the theory that life makes evolutionary progress in a closed system needs additional support.
Computers, like life, rely on encoded instructions. They also exhibit evolutionary progress. Accumulated improvements have made commercial software far more powerful today than only fifteen years ago. Of course, this evolution has occurred in an open system, because people installed the improvements. But computer experiments that attempt to model evolutionary progress in closed systems are under way (e.g. Ray, 1996). The work is called "artificial life" and various other names, and the experimental environment is not restricted to conventional software. Obviously, a closed-system model that exhibited lifelike, sustained evolutionary progress would have profound importance for biology. In fact, many closed-system computer models exhibit surprising behavior or solve preestablished problems. But in spite of much honest effort, none has achieved ongoing, open-ended evolutionary progress. They all remain confined within their original parameters.
Nevertheless, computer scientists are confident that an unquestionable demonstration of evolutionary progress in artificial life is imminent, because they think they are only trying to model a phenomenon already proven in biology. Many biologists, on the other hand, are under the impression that computer models have already corroborated evolutionary progress in a closed system.
Yet the phenomenon has not been unequivocally demonstrated in either medium. Until it is, one can reasonably doubt that evolutionary progress in a closed system is possible, in real or artificial life.
AcknowledgmentsThe author thanks Max Garzon, Chris Langton and Dan McShea for their advice and encouragement.
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What'sNEW: Lenski et al.
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Molecular evolution: No escape from the tangled bank by Joshua B. Plotkin, Nature, online 18 Oct 2017. ...in many genes, mutations quickly provide their maximum possible fitness gain for the cell. After this, further mutations in the gene hold no adaptive benefit.
Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria by Alejandro Couce, Larissa Viraphong Caudwell et al., doi:10.1073/pnas.1705887114, PNAS, 10 Oct 2017. These findings suggest the need to reexamine current ideas about the evolution of bacterial genomes, and they have implications for other hypermutable systems such as viruses and cancer cells.
Specificity of genome evolution in experimental populations of Escherichia coli evolved at different temperatures by Daniel E. Deatherage et al., doi:10.1073/pnas.1616132114, PNAS, 15 Feb 2017. These findings demonstrate that genomic signatures of adaptation can be highly specific, even with respect to subtle environmental differences, but that this imprint may become obscured over longer timescales as populations continue to change and adapt to the shared features of their environments.
Tempo and mode of genome evolution in a 50,000-generation experiment by Olivier Tenaillon, Jeffrey E. Barrick, Richard E. Lenski et al., doi:10.1038/nature18959, p 165-170 v 536, Nature, 11 Aug 2016. ...We analysed complete genomes of 264 clones from 12 populations across 50,000 generations of the long-term evolution experiment (LTEE) with E. coli. These populations have evolved in a defined medium with scarce resources since 1988. Mean fitness measured in competition with their ancestor increased by ~70% in that time.
After 50,000 generations, average genome length declined by 63 kb (~1.4%) relative to the ancestor....
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12 Aug 2014: ...The set of known underground reactions has a significant potential both to increase fitness in existing environments and to exploit new nutrient sources.
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Michael J. Wiser, Noah Ribeck and Richard E. Lenski, "Long-Term Dynamics of Adaptation in Asexual Populations" [abstract], doi:10.1126/science.1243357, Science, online 14 Nov 2013; and commentary:
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20 Sep 2012: Richard Lenski's research group has analysed the evolution of aerobic citrate metabolism among cloned bacteria.
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29 Apr 2011: An analysis of long-running evolution experiments has been done by biochemist Michael Behe.
13 Apr 2011: Nothing yet. That's what we observe from an experiment at Michigan State University.
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29 Oct 2009: 40,000 generations of E. Coli have been monitored in a long-term experiment.
5 Jun 2008: Cloned bacteria evolved an unexpected feature in a long-running experiment led by Richard Lenski.
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2003, May 11: Computer model evolves complex functions?
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1999, August 12: New computer model of evolution
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