Why does nature use a 4-level system (DNA) to encode information?
Short answer: Ease of manufacture, simplicity of matching, sufficiency for requirements. Fewer simple bases take less effort to create, provide fewer possible matches, yet is complex enough to code what is required while retaining sufficient degeneracy for success. Also it was the coincidence of replicase–alphabet co-evolution, both occurring in the same place at the same time.
Longer answer:
First, I am not a biologist, so this question might be naive:
Beginners and experts are welcome at SE.
All of our information processing and storing is based on 2-level logic, bits with 0 and 1.
Euler's number ($e$) is defined as the sum of an infinite series $\sum_{n=0}^\infty \frac{1}{n!}$ and has the lowest radix economy, but it's not convenient to implement in logic circuits. With the radix economy of $e$ set at 1.000, ternary is 1.0046 and binary is 1.0615.
Ternary computers have been constructed using ternary logic and while they are uncommon ternary logic is used in SQL; even in binary based computers.
Most, but not all of our information processing and storing is based on 2-level logic.
Now, DNA stores the information in a 4-level system: A, C, G, T. Three basepairs form a codon and can encode 4^3 amino acids.
Most, but not all.
The five canonical, or primary, nucleobases are: adenine (A), cytosine (C), guanine (G), thymine (T), and uracil (U). DNA uses A, G, C, and T while RNA uses A, G, C, and U.
In the laboratory DNA has been created with 6 and 8 bases, it is functional.
See the (paywall) report: "Hachimoji DNA and RNA: A genetic system with eight building blocks", Feb 22 2019, by Shuichi Hoshika, Nicole A. Leal, Myong-Jung Kim, Myong-Sang Kim, Nilesh B. Karalkar, Hyo-Joong Kim, Alison M. Bates, Norman E. Watkins Jr., Holly A. SantaLucia, Adam J. Meyer, Saurja DasGupta, Joseph A. Piccirilli, Andrew D. Ellington, John SantaLucia Jr., Millie M. Georgiadis, and Steven A. Benner. (Google Cache version).
"Fig. 4 Structure and fluorescent properties of hachimoji RNA molecules.
(A) Schematic showing the full hachimoji spinach variant aptamer; additional nucleotide components of the hachimoji system are shown as black letters at positions 8, 10, 76, and 78 (B, Z, P, and S, respectively). The fluor binds in loop L12 (25). (B to E) Fluorescence of various species in equal amounts as determined by UV. Fluorescence was visualized under a blue light (470 nm) with an amber (580 nm) filter.
(B) Control with fluor only, lacking RNA.
(C) Hachimoji spinach with the sequence shown in (A).
(D) Native spinach aptamer with fluor.
(E) Fluor and spinach aptamer containing Z at position 50, replacing the A:U pair at positions 53:29 with G:C to restore the triple observed in the crystal structure. This places the quenching Z chromophore near the fluor; CD spectra suggest that this variant had the same fold as native spinach (fig. S8).".
Centrifuge tube C contains the spinach with the DNA containing eight bases.
Is there a good reason for why during early evolution, a 4-level system (which can store 2 bits per encoding entity) is favoured over a 2-level system or over larger systems?
Yes.
Copying fidelity decreases roughly exponentially with increasing size (N pairs) of the alphabet (keeping the length of the genome fixed). The reason for this is that as one adds more letters to the alphabet, they will resemble each other more and more, and hence the chance of mispairing and mutagenesis increases.
Overall metabolic efficiency and fitness are determined by the size, we have 20 amino acids to code for (smaller makes 16 or less) and 3 stop codons. So we have a space for 64, and rely on degeneracy to provide a degree of 'error correction' (synonymization) where errors are converted, usually to produce non-fatal errors. While seldom fatal translation errors can still cause rare diseases.
We are already running inefficiently, going to a larger number of pairs introduces unnecessary complexity and going smaller isn't available for the number of amino acids that must be coded for. Increasing the codon length makes DNA larger, as it is it must already be coiled to stuff it into the cells; one third larger DNA would better fit cells that are also one third larger.
In the opinion piece "Why are there four letters in the genetic alphabet?", Nature Reviews Genetics volume 4, pages 995–1001 (2003), by Eörs Szathmáry there are the following observations:
Page 995:
"There are four main constraints on the successful incorporation of a new base pair$^{[6–8]}$:
chemical stability (the base should not readily decompose);
thermodynamic stability (new base pairs should not destabilize nucleic-acid structures);
enzymatic processability (polymerases should accept the base pairs as substrates, catalyse addition to the primer and be able to carry on the process); and
kinetic selectivity (orthogonality to other base pairs).
All four criteria are important but the combination of the last two, which we might call replicability, has received particular attention
because it is the main obstacle to adding to the genetic alphabet.".
Page 997:
"Theoretical arguments
The feasibility of alternative base pairs raises the question: why are there four bases in the natural genetic alphabet? As Orgel pointed out, there are two types of answer: either evolution has never experimented with alternative base pairs or four bases ‘were enough’$^{[20]}$. The first option might hold for the hydrophobic base pairs discussed above (an adequate early synthesis might be lacking), but it is unlikely to be true for all of the hydrogen-bonding bases in a prebiotic ‘chemical mayhem’. At any rate, it does not explain why we do not have only two bases$^{[21–24]}$. It therefore seems worthwhile to pursue the second option: why might four bases be enough? If ‘enough’ is understood in terms of evolutionary stability, it means optimality within the frame of the structural constraints that are afforded by natural selection. Here, I describe attempts to show that four bases are optimal under STABILIZING SELECTION, especially when we consider MUTATION–SELECTION EQUILIBRIUM. I then discuss evidence for the optimal size of the genetic code obtained from in silico DIRECTIONAL SELECTION and finally analyse a more abstract contribution from so-called ERROR-CODING THEORY.".
Page 1000:
"Theoretical investigations based on structural, energetic and information-theoretic studies confirm the view that increased alphabet size
decreases copying fidelity while increasing information density. This indicates that there must be an optimum alphabet size in terms of fitness, whether we assume that the genetic.alphabet was fixed in an RNA world or not.
...
According to the RNA-world-based view, the genetic alphabet became fixed more than 3 billion years ago$^{[31]}$, and the origin of the genetic code and translation happened subsequently$^{[42]}$. This line of reasoning indicates that the informational/operational division of labour between nucleic acids and proteins$^{[43}]$ has uncoupled the genetic alphabet from
enzymatic functionality constraints. As the genetic code evolved in the context of a certain genetic alphabet, any further change of the alphabet would have been unnecessary and/or extremely unlikely.
If, however, the genetic code originated by the simultaneous co-evolution of nucleic acids and proteins (a much more complicated model), then the fixation of the genetic alphabet must be considered in this complex context. Here, the general insight of Mac Dónaill$^{[38]}$ helps: the information density of the alphabet is a useful concept, whether the exercised function is ribozymic or a messenger function in protein synthesis. In this case, the problem of the size of the ‘catalytic alphabet’ (the number of encoded amino acids) readily arises: why do we have 20 rather than, for example, 16 or 25
different amino acids? It has been pointed out that some of the considerations discussed in this article (effects on catalytic efficiency and translation fidelity) apply to this related problem$^{[32}]$. However, another crucial factor is likely to be involved: the metabolic cost of producing amino acids. An amino acid that belongs to the same biosynthetic family$^{[43]}$ is expected to increase catalytic efficiency only modestly and its metabolic cost is likely to be small. By contrast, an amino acid from a new biosynthetic family is likely to confer a high enzymatic advantage, but is expected to incur high metabolic costs (for instance, many new ATP-requiring steps).".
References:
$[6.]$ Mathis, G. & Hunziker, J. Towards a DNA-like duplex without hydrogen-bonded base pairs. Angew. Chem. Int. Ed. 41, 3203–3205 (2002).
$[7.]$ Ogawa, A. K., Wu, Y., Berger, M., Schultz, P. G. & Romesberg, F. E. Rational design of an unnatural base pair with increased kinetic selectivity. J. Am. Chem. Soc. 122, 8803–8804 (2000).
$[8.]$ Kool, E. T. Synthetically modified DNAs as substrates for polymerases. Curr. Opin. Chem. Biol. 4, 602–608 (2000).
$[20.]$ Orgel, L. E. Nucleic acids — adding to the genetic alphabet. Nature 343, 18–20 (1990).
$[21.]$ Orgel, L. E. Evolution of the genetic apparatus. J. Mol.
Bio . 38, 381–393 (1968).
$[22.]$ Crick, F. H. C. The origin of the genetic code. J. Mol. Biol. 38, 367–379 (1968).
$[23.]$ Wächtershäuser, G. An all-purine precursor of nucleic acids. Proc. Natl Acad. Sci. USA 85, 1134–1135 (1988).
$[24.]$ Zubay, G. An all-purine precursor of nucleic acids. Chemtracts 2, 439–442 (1991).
$[31.]$ Szathmáry, E. Four letters in the genetic alphabet: a frozen evolutionary optimum? Proc. R. Soc. Lond. B 245, 91–99 (1991).
$[32.]$ Szathmáry, E. What is the optimum size for the genetic alphabet? Proc. Natl Acad. Sci. USA 89, 2614–2618 (1992).
$[38.]$ Mac Dónaill, D. A. Why nature chose A, C, G and U/T: an error-coding perspective of nucleotide alphabet composition. Orig. Life Evol. Biosphere 33, 433–455 (2003).
$[42.]$ Szathmáry, E. The origin of the genetic code: amino acids as cofactors in an RNA world. Trends Genet. 15, 223–229 (1999).
$[43.]$ Wong, J. T. A coevolution theory of the genetic code. Proc. Natl Acad. Sci. USA 72, 1909–1912 (1975).
Further Information:
Eörs Szathmáry’s Wikipedia web page
http://www.colbud.hu/fellows/szathmary.shtml
- The Collegium Budapest is closed.
Scripps Research Institute
Steven Benner’s web page
http://www.chem.ufl.edu/benner.html
- Dr. Benner left UoF in 2005.
Asked differently: Why did evolution not prefer to have a binary system to store and process data? For us, binary is much easier, and the very few tests of exotic higher-level data processing were not really successful.
Binary has nothing to do with evolution. Few of us can count to 255 in binary, we prefer decimal. Both ternary computers and SQL are "really successful", people prefer the alternatives.
This is intended to be an answer suitable for a layperson. Eörs Szathmáry’s article and it's associated references can be consulted for more details.