Physics of Life Reviews 7 (2010) 379–380
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Comment

Topological, statistical, and dynamical origins of genetic code
Comment on “A colorful origin for the genetic code: Information
theory, statistical mechanics and the emergence of molecular codes”
by T. Tlusty
Hiroaki Takagi a , Kunihiko Kaneko b,∗
a Department of Physics, School of Medicine, Nara Medical University, 840 Shijo-cho, Kashihara, Nara, 634-8521, Japanb Department of Basic Science, University of Tokyo, Komaba, Meguro, Tokyo 153-8902, Japan

Received 3 August 2010; accepted 4 August 2010
Available online 5 August 2010
Communicated by E. Shakhnovich

Keywords: Genetic code; Evolution; Dynamical systems; Endosymbiosis

How has the genetic code evolved to link genetic sequences to corresponding amino acids? Why are only 20 aminoacids used from 64 possible triplet codes when forming proteins? Since the discovery of codons, these two questions have been integral to evolutionary biology, and addressed by distinguished biologists. For example, a beautiful
theory by Crick et al. [1] to explain the number 20 from the optimal code without stopping symbol (comma) wasselected as the most elegant ‘wrong’ theory ever to be proposed in science by Maynard-Smith [2]. Later on, Crickhimself described the ‘universal’ genetic code as luck with the ‘frozen accident’ in the common ancestor of livingorganisms [3].
In the present paper [4], the author presented a statistical-physics based explanation for the evolution of the genetic
code by using a more sophisticated mathematical theory than that of Crick et al. Topological and information-theoretic
approaches were adopted by imposing the optimization of a certain quantity that consists of diverse amino acids, errortolerance and minimal energy cost. A second-order phase transition from random to non-random mapping between
codons and amino acids was found to coincide with changes in this quantity. This resembles known behavior inmagnetic spin systems, which is analogous to the error-catastrophe seen in chemical evolutions [5]. Furthermore,
the author introduced the topology of the codon graph determining the lowest modes of the graph-Laplacian andrelated it to the mathematical map coloring problem. By removing the ambiguity in the third position of the codonand considering the optimization process under this topological constraint, the maximum number of amino acids tobe coded is predicted to be 25. This is an elegant theory that can be experimentally verified.

DOI of original article: 10.1016/j.plrev.2010.06.002.
* Corresponding author. Tel./fax: +81 3 5454 6746.

E-mail address: kaneko@complex.c.u-tokyo.ac.jp (K. Kaneko).
1571-0645/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.plrev.2010.08.001

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H. Takagi, K. Kaneko / Physics of Life Reviews 7 (2010) 379–380

Now, are these topological and statistical-physical arguments sufficient for understanding the evolution of genetic
code? In general, it is hard to determine what quantity should be optimized through the evolution. Furthermore, it
is not easy to answer whether the coding system can reach and stay near its optimal point through the system’s
evolution. To address these two points, a dynamical-systems-study of evolving cells is necessary. In fact, we havealready simulated a model consisting of reaction processes among tRNA-amino acid complexes, aaRSs, and otherenzymes and metabolites with variable mapping between codons and amino acids [6], finding that a stable genetic
code with fixed mapping evolves through transcription and translation dynamics and cell–cell interactions.
The emergence of the fitness function and a possible mechanism to keep the genetic code system in the uppervicinity of its phase transition point, as postulated in the present paper, can potentially be discussed from such
dynamical-systems point of view. In this regard, co-evolution between the reading matrix rij and the genetic code,
as the author mentioned, is an important issue to be pursued. Along this line, endosymbiosis between two biologicalsystems should cause a drastic change in chemical states for both systems, which might alter the reading matrix and thegenetic code of each. This appears true in mitochondria, where non-universal coding is known to exist. A preliminary
discussion about the causes of this coding is given in [6]. By combining the beautiful statistical-physics approach theauthor proposes with the dynamical-systems approach mentioned above, it is hoped that the evolutionary dynamics ofgenetic code will be elucidated and later verified with in-vitro artificial experiments.
References[1] Crick FHC, Griffith JS, Orgel LE. Codes without commas. Proceedings of the National Academy of Sciences of the United States of America
1957;43:416–21.
[2] Maynard-Smith J. Too good to be true. Nature 1999;400:223.
[3] Crick FHC. The origin of the genetic code. Journal of Molecular Biology 1968;38:367–79.
[4] Tlusty T. A colorful origin for the genetic code: Information theory, statistical mechanics and the emergence of molecular codes. Physics ofLife Reviews 2010;7(3):362–76, this issue.
[5] Eigen M. Selforganization of matter and the evolution of biological macromolecules. Naturwissenschaften 1971;58:465–523.
[6] Takagi H, Kaneko K, Yomo T. Evolution of genetic codes through isologous diversification of cellular states. Artificial Life 2000;6:283–305.