Posted by: Dan | May 17, 2006

Reducing Complexity

One of the principal challenges to Evolutionary Theory, particular since the advent of molecular biology, has been the question of whether Evolution can explain the origin of complex biochemical and genetic features. Back in March, Bridgham et al. offered one exceptional answer by elucidating the molecular evolution of two supposedly irreducibly complex hormone receptors. Another answer has been out for a few years now, using “digital organisms” – computer programs that self-replicate, mutate, compete and evolve.

In what is a very interesting paper, Lenski et al. (2003), took software originally developed in 1991 to isolate and test the development of computer viruses, and pared this software down to emphasize a few essential features necessary for evolution: replication, variation (via mutation), and differential fitness (competition).

By using digital organisms, Lenski et al. traced the exact genealogy, without any ‘missing links,’ from a simple ancestor that could replicate only, to descendants able to perform multiple logic functions requiring coordinated execution of many inherited instructions. In the process, they observed the arisal of complexity by modifying existing structures and functions, or by “Variations on a theme.”

Lenski et al. also addressed anticipated concerns that they “stacked the deck” by studying “the evolution of a complex feature that could be built on simpler functions that were also useful,” but as they note, that is exactly what Evolution is and does, and indeed, their “experiments showed that the complex feature never evolved when simpler functions were not rewarded.”

As Christoph Adami notes in his recent review of digital biology, this realization of Darwinian mechanisms in computational chemistry is critically different from a simulation (such as genetic algorithms), because the fitness of a digital organism is not determined a priori by the programmer, other than by its ability to execute its program and replicate (survival and fitness). “Instead, as for biochemical life, those lineages that survive the competition for space, time and resources are most fit – in hindsight.”

Further similiarities with actual biochemical life include the observation of sympatric speciation, mutational robustness, genetic drift and Muller’s ratchet, as well as testing of hypotheses previously inaccessable to biochemistry, including clonal interference resulting in a quasi-species model, the arisal of sexual speciation within Kondrashov’s mutational deterministic hypothesis, and the Red Queen effect.

In summary, digital biology is just cool, because as Bill O’Neill noted, “It’s a phenomenally good tool, because it’s evolution in a bottle.”

References

  • Digital Evolution. O’Neill B. PLoS Biol. 2003 Oct; 1(1):E18. Epub 2003 Oct 13. Pubmed
  • Digital genetics: unravelling the genetic basis of evolution. Adami C. Nat Rev Genet. 2006 Feb; 7(2):109-18. Pubmed
  • The evolutionary origin of complex features. Lenski RE, Ofria C, Pennock RT, Adami C. Nature. 2003 May 8; 423(6936):139-44. Pubmed
  • Evolution of hormone-receptor complexity by molecular exploitation. Bridgham JT, Carroll SM, Thornton JW. Science. 2006 Apr 7; 312(5770):97-101. Pubmed
  • Evolution: Reducible complexity. Adami C. Science. 2006 Apr 7; 312(5770):61-3. Pubmed

and Selected Blog Commentary on Bridgham et al


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