Casting polymer nets to optimize noisy molecular codes

Match fitness landscapes for macromolecular interaction networks: Selection for translational accuracy and rate can displace tRNA-binding interfaces of non-cognate aminoacyl-tRNA synthetases

Advances in structural biology of aminoacyl-tRNA synthetases (aaRSs) have revealed incredible diversity in how aaRSs bind their tRNA substrates. The causes of this diversity remain mysterious. We developed a new class of highly rugged fitness landscape models called match landscapes, through which genes encode the assortative interactions of their gene products through the complementarity and identifiability of their structural features. We used results from coding theory to prove bounds and equalities on fitness in match landscapes assuming additive interaction energies, macroscopic aminoacylation kinetics including proofreading, site-specific modifiers of interaction, and selection for translational accuracy in multiple, perfectly encoded site-types. Using genotypes based on extended Hamming codes we show that over a wide array of interface sizes and numbers of encoded cognate pairs, selection for translational accuracy alone is insufficient to displace the tRNA-binding interfaces of aaRSs. Yet, under combined selection for translational accuracy and rate, site-specific modifiers are selected to adaptively displace the tRNA-binding interfaces of non-cognate aaRS-tRNA pairs. We describe a remarkable correspondence between the lengths of perfect RNA (quaternary) codes and the modal sizes of small non-coding RNA families.

Genetic code asymmetry supports diversity through experimentation with posttranslational modifications

Protein N-glycosylation has been identified in all three domains of life presumably conserved for its early role in glycoprotein folding. However, the N-glycans added to proteins in the secretory pathway of multicellular organisms are remodeling in the Golgi, increasing structural diversity exponentially and adding new layers of functionality in immunity, metabolism and other systems. The branching and elongation of N-glycan chains found on cell surface receptors generates a gradation of affinities for carbohydrate-binding proteins, the galectin, selectin and siglec families. These interactions adapt cellular responsiveness to environmental conditions, but their complexity presents a daunting challenge to drug design. To gain further insight, I review how N-glycans biosynthesis and biophysical properties provide a selective advantage in the form of tunable and ultrasensitive stimulus-response relationships. In addition, the N-glycosylation motif favors step-wise mutational experimentation with sites. Glycoproteins display accelerated evolution during vertebrate radiation, and the encoding asymmetry of NXS/T(X≠P) has left behind phylogenetic evidence suggesting that the genetic code may have been selected to optimize diversity in part through emerging posttranslational modifications.

Encoding asymmetry of the N-glycosylation motif facilitates glycoprotein evolution

Protein N-glycosylation is found in all domains of life and has a conserved role in glycoprotein folding and stability. In animals, glycoproteins transit through the Golgi where the N-glycans are trimmed and rebuilt with sequences that bind lectins, an innovation that greatly increases structural diversity and redundancy of glycoprotein-lectin interaction at the cell surface. Here we ask whether the natural tension between increasing diversity (glycan-protein interactions) and site multiplicity (backup and status quo) might be revealed by a phylogenic examination of glycoproteins and NXS/T(X≠P) N-glycosylation sites. Site loss is more likely by mutation at Asn encoded by two adenosine (A)-rich codons, while site gain is more probable by generating Ser or Thr downstream of an existing Asn. Thus mutations produce sites at novel positions more frequently than the reversal of recently lost sites, and therefore more paths though sequence space are made available to natural selection. An intra-species comparison of secretory and cytosolic proteins revealed a departure from equilibrium in sequences one-mutation-away from NXS/T and in (A) content, indicating strong selective pressures and exploration of N-glycosylation positions during vertebrate evolution. Furthermore, secretory proteins have evolved at rates proportional to N-glycosylation site number, indicating adaptive interactions between the N-glycans and underlying protein. Given the topology of the genetic code, mutation of (A) is more often nonsynonomous, and Lys, another target of many PTMs, is also encoded by two (A)-rich codons. An examination of acetyl-Lys sites in proteins indicated similar evolutionary dynamics, consistent with asymmetry of the target and recognition portions of modified sites. Our results suggest that encoding asymmetry is an ancient mechanism of evolvability that increases diversity and experimentation with PTM site positions. Strong selective pressures on PTMs may have contributed to the A+T→G+C shift in genome-wide nucleotide composition during metazoan radiation.

Molecular codes in biological and chemical reaction networks

Shannon’s theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio-) chemical systems able to process “meaningful” information from those that do not. Here, we present a formal method to assess a system’s semantic capacity by analyzing a reaction network’s capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries), biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades), an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems posses different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

Expanding the modern synthesis

The Modern Evolutionary Synthesis formalizes the role of variation, heredity, differential reproduction and mutation in population genetics. Here we explore a mathematical structure, based on the asymptotic limit theorems of communication theory, that instantiates the punctuated dynamic relations of organisms with their embedding environments, including the possibility of the transfer of heritage information between different classes of organism. The approach applies a standard coevolutionary argument to genes, environment, and gene expression reconfigured as interacting information sources. In essence, we provide something of a formal roadmap for the modernization of the Modern Synthesis, making applications to both relatively rapid evolutionary punctuated equilibrium and to the conservation of ecological interactions across deep evolutionary time.

Codon size reduction as the origin of the triplet genetic code

The genetic code appears to be optimized in its robustness to missense errors and frameshift errors. In addition, the genetic code is near-optimal in terms of its ability to carry information in addition to the sequences of encoded proteins. As evolution has no foresight, optimality of the modern genetic code suggests that it evolved from less optimal code variants. The length of codons in the genetic code is also optimal, as three is the minimal nucleotide combination that can encode the twenty standard amino acids. The apparent impossibility of transitions between codon sizes in a discontinuous manner during evolution has resulted in an unbending view that the genetic code was always triplet. Yet, recent experimental evidence on quadruplet decoding, as well as the discovery of organisms with ambiguous and dual decoding, suggest that the possibility of the evolution of triplet decoding from living systems with non-triplet decoding merits reconsideration and further exploration. To explore this possibility we designed a mathematical model of the evolution of primitive digital coding systems which can decode nucleotide sequences into protein sequences. These coding systems can evolve their nucleotide sequences via genetic events of Darwinian evolution, such as point-mutations. The replication rates of such coding systems depend on the accuracy of the generated protein sequences. Computer simulations based on our model show that decoding systems with codons of length greater than three spontaneously evolve into predominantly triplet decoding systems. Our findings suggest a plausible scenario for the evolution of the triplet genetic code in a continuous manner. This scenario suggests an explanation of how protein synthesis could be accomplished by means of long RNA-RNA interactions prior to the emergence of the complex decoding machinery, such as the ribosome, that is required for stabilization and discrimination of otherwise weak triplet codon-anticodon interactions.