Optimality of the genetic code with respect to protein stability and amino-acid frequencies

The influence of different types of translational inaccuracies on the genetic code structure

BACKGROUND

The standard genetic code is a recipe for assigning unambiguously 21 labels, i.e. amino acids and stop translation signal, to 64 codons. However, at early stages of the translational machinery development, the codons did not have to be read unambiguously and the early genetic codes could have contained some ambiguous assignments of codons to amino acids. Therefore, the goal of this work was to obtain the genetic code structures which could have evolved assuming different types of inaccuracy of the translational machinery starting from unambiguous assignments of codons to amino acids.

RESULTS

We developed a theoretical model assuming that the level of uncertainty of codon assignments can gradually decrease during the simulations. Since it is postulated that the standard code has evolved to be robust against point mutations and mistranslations, we developed three simulation scenarios assuming that such errors can influence one, two or three codon positions. The simulated codes were selected using the evolutionary algorithm methodology to decrease coding ambiguity and increase their robustness against mistranslation.

CONCLUSIONS

The results indicate that the typical codon block structure of the genetic code could have evolved to decrease the ambiguity of amino acid to codon assignments and to increase the fidelity of reading the genetic information. However, the robustness to errors was not the decisive factor that influenced the genetic code evolution because it is possible to find theoretical codes that minimize the reading errors better than the standard genetic code.

Rapid nickel(ii)-promoted cysteine S-arylation with arylboronic acids

Nickel salts catalyze fast cysteine arylation with 2-nitroarylboronic acids. The process uses cheap, readily-available reagents and allows introduction of diverse chemical handles.

The optimality of the standard genetic code assessed by an eight-objective evolutionary algorithm

BACKGROUND

The standard genetic code (SGC) is a unique set of rules which assign amino acids to codons. Similar amino acids tend to have similar codons indicating that the code evolved to minimize the costs of amino acid replacements in proteins, caused by mutations or translational errors. However, if such optimization in fact occurred, many different properties of amino acids must have been taken into account during the code evolution. Therefore, this problem can be reformulated as a multi-objective optimization task, in which the selection constraints are represented by measures based on various amino acid properties.

RESULTS

To study the optimality of the SGC we applied a multi-objective evolutionary algorithm and we used the representatives of eight clusters, which grouped over 500 indices describing various physicochemical properties of amino acids. Thanks to that we avoided an arbitrary choice of amino acid features as optimization criteria. As a consequence, we were able to conduct a more general study on the properties of the SGC than the ones presented so far in other papers on this topic. We considered two models of the genetic code, one preserving the characteristic codon blocks structure of the SGC and the other without this restriction. The results revealed that the SGC could be significantly improved in terms of error minimization, hereby it is not fully optimized. Its structure differs significantly from the structure of the codes optimized to minimize the costs of amino acid replacements. On the other hand, using newly defined quality measures that placed the SGC in the global space of theoretical genetic codes, we showed that the SGC is definitely closer to the codes that minimize the costs of amino acids replacements than those maximizing them.

CONCLUSIONS

The standard genetic code represents most likely only partially optimized systems, which emerged under the influence of many different factors. Our findings can be useful to researchers involved in modifying the genetic code of the living organisms and designing artificial ones.

Photocatalytic Modification of Amino Acids, Peptides, and Proteins

In the last decade, visible‐light photoredox catalysis has emerged as a powerful strategy to enable novel transformations in organic synthesis. Owing to mild reaction conditions (i.e., room temperature, use of visible light) and high functional‐group tolerance, photoredox catalysis could represent an ideal strategy for chemoselective biomolecule modification. Indeed, a recent trend in photoredox catalysis is its application to the development of novel methodologies for amino acid modification. Herein, an up‐to‐date overview of photocatalytic methodologies for the modification of single amino acids, peptides, and proteins is provided. The advantages offered by photoredox catalysis and its suitability in the development of novel biocompatible methodologies are described. In addition, a brief consideration of the current limitations of photocatalytic approaches, as well as future challenges to be addressed, are discussed.

Gene synthesis allows biologists to source genes from farther away in the tree of life

Gene synthesis enables creation and modification of genetic sequences at an unprecedented pace, offering enormous potential for new biological functionality but also increasing the need for biosurveillance. In this paper, we introduce a bioinformatics technique for determining whether a gene is natural or synthetic based solely on nucleotide sequence. This technique, grounded in codon theory and machine learning, can correctly classify genes with 97.7% accuracy on a novel data set. We then classify ∼19,000 unique genes from the Addgene non-profit plasmid repository to investigate whether natural and synthetic genes have differential use in heterologous expression. Phylogenetic analysis of distance between source and expression organisms reveals that researchers are using synthesis to source genes from more genetically-distant organisms, particularly for longer genes. We provide empirical evidence that gene synthesis is leading biologists to sample more broadly across the diversity of life, and we provide a foundational tool for the biosurveillance community.

Site-specific chelator-antibody conjugation for PET and SPECT imaging with radiometals

Antibodies and their derivatives radiolabelled with positron- and gamma-emitting radiometals enable sensitive and quantitative molecular Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) imaging of antibody distribution in vivo. Chelators that are covalently attached to antibodies allow radiolabelling with metallic PET and SPECT radioisotopes. Conventional strategies for chelator-protein conjugation generate heterogeneous mixtures of bioconjugates that can exhibit reduced affinity for their receptor targets, and undesirable biodistribution and pharmacokinetics. Recent advances in bioconjugation technology enable site-specific modification to generate well-defined constructs with superior properties. Herein we survey existing site-specific chelator-protein conjugation methods. These include chelator attachment to cysteines/disulfide bonds or the glycan region of the antibody, enzyme-mediated chelator conjugation, and incorporation of sequences of amino acids that chelate the radiometal. Such technology will allow better use of PET and SPECT imaging in the development of antibody-based therapies.

Development of Highly Chemoselective Oxidative Transformations by Designing Organoradicals

To conduct organic synthesis in the field of pharmaceutical science, methodologies that can easily and quickly supply compounds with high drug-likeness are highly desirable. Based on the original catalyst design concept "Radical-Conjugated Redox Catalysis (RCRC)" established during my research, various C(sp³)-H functionalizations and protein modifications have been developed, taking advantage of the high reactivity and chemoselectivity of the single-electron transfer process. This review focuses on the eight-year research efforts by my collaborators and me, from conception to results.

Optimization of the standard genetic code according to three codon positions using an evolutionary algorithm

Many biological systems are typically examined from the point of view of adaptation to certain conditions or requirements. One such system is the standard genetic code (SGC), which generally minimizes the cost of amino acid replacements resulting from mutations or mistranslations. However, no full consensus has been reached on the factors that caused the evolution of this feature. One of the hypotheses suggests that code optimality was directly selected as an advantage to preserve information about encoded proteins. An important feature that should be considered when studying the SGC is the different roles of the three codon positions. Therefore, we investigated the robustness of this code regarding the cost of amino acid replacements resulting from substitutions in these positions separately and the sum of these costs. We applied a modified evolutionary algorithm and included four models of the genetic code assuming various restrictions on its structure. The SGC was compared both with the codes that minimize the objective function and those that maximize it. This approach allowed us to place the SGC in the global space of possible codes, which is a more appropriate and unbiased comparison than that with randomly generated codes because they are characterized by relatively uniform amino acid assignments to codons. The SGC appeared to be well optimized at the global scale, but its individual positions were not fully optimized because there were codes that were optimized for only one codon position and simultaneously outperformed the SGC at the other positions. We also found that different code structures may lead to the same optimality and that random codes can show a tendency to minimize costs under some of the genetic code models. Our results suggest that the optimality of SGC could be a by-product of other processes.

Protein Sequences Recapitulate Genetic Code Evolution

Several hypotheses predict ranks of amino acid assignments to genetic code's codons. Analyses here show that average positions of amino acid species in proteins correspond to assignment ranks, in particular as predicted by Juke's neutral mutation hypothesis for codon assignments. In all tested protein groups, including co- and post-translationally folding proteins, 'recent' amino acids are on average closer to gene 5' extremities than 'ancient' ones. Analyses of pairwise residue contact energies matrices suggest that early amino acids stereochemically selected late ones that stablilize residue interactions within protein cores, presumably producing 5'-late-to-3'-early amino acid protein sequence gradients. The gradient might reduce protein misfolding, also after mutations, extending principles of neutral mutations to protein folding. Presumably, in self-perpetuating and self-correcting systems like the genetic code, initial conditions produce similarities between evolution of the process (the genetic code) and 'ontogeny' of resulting structures (here proteins), producing apparent teleonomy between process and product.

Horizontal transfer of code fragments between protocells can explain the origins of the genetic code without vertical descent

Theories of the origin of the genetic code typically appeal to natural selection and/or mutation of hereditable traits to explain its regularities and error robustness, yet the present translation system presupposes high-fidelity replication. Woese's solution to this bootstrapping problem was to assume that code optimization had played a key role in reducing the effect of errors caused by the early translation system. He further conjectured that initially evolution was dominated by horizontal exchange of cellular components among loosely organized protocells ("progenotes"), rather than by vertical transmission of genes. Here we simulated such communal evolution based on horizontal transfer of code fragments, possibly involving pairs of tRNAs and their cognate aminoacyl tRNA synthetases or a precursor tRNA ribozyme capable of catalysing its own aminoacylation, by using an iterated learning model. This is the first model to confirm Woese's conjecture that regularity, optimality, and (near) universality could have emerged via horizontal interactions alone.

Bijective codon transformations show genetic code symmetries centered on cytosine's coding properties

Homology of some RNAs with template DNA requires systematic exchanges between nucleotides. Such exchanges produce 'swinger' RNA along 23 bijective transformations (nine symmetric, X ↔ Y; and 14 asymmetric, X → Y → Z → X, for example A ↔ C and A → C → G → A, respectively). Here, analyses compare amino acids coded by swinger-transformed codons to those coded by untransformed codons, defining coding invariance after transformations. Swinger transformations cluster according to coding invariance in four groups characterized by transformations into cytosine (C = C, T → C, A → C, and G → C). C's central mutational coding role shows that swinger transformations constrained genetic code genesis. Coding invariance post-transformations correlate positively/negatively with mitochondrial swinger transcription/lepidosaurian body temperature. Presumably, low/high temperatures stabilize/revert rare swinger polymerization modes, producing long swinger sequences/point mutations, respectively. Coding invariance after swinger transformations might compensate effects of swinger polymerizations in species with low body temperatures. Hypothetically, swinger transcription increased coding potential of RNA self-replicating protolife systems under heating/cooling cycles.

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

Genetic Code Optimization for Cotranslational Protein Folding: Codon Directional Asymmetry Correlates with Antiparallel Betasheets, tRNA Synthetase Classes

A new codon property, codon directional asymmetry in nucleotide content (CDA), reveals a biologically meaningful genetic code dimension: palindromic codons (first and last nucleotides identical, codon structure XZX) are symmetric (CDA = 0), codons with structures ZXX/XXZ are 5'/3' asymmetric (CDA = - 1/1; CDA = - 0.5/0.5 if Z and X are both purines or both pyrimidines, assigning negative/positive (-/+) signs is an arbitrary convention). Negative/positive CDAs associate with (a) Fujimoto's tetrahedral codon stereo-table; (b) tRNA synthetase class I/II (aminoacylate the 2'/3' hydroxyl group of the tRNA's last ribose, respectively); and (c) high/low antiparallel (not parallel) betasheet conformation parameters. Preliminary results suggest CDA-whole organism associations (body temperature, developmental stability, lifespan). Presumably, CDA impacts spatial kinetics of codon-anticodon interactions, affecting cotranslational protein folding. Some synonymous codons have opposite CDA sign (alanine, leucine, serine, and valine), putatively explaining how synonymous mutations sometimes affect protein function. Correlations between CDA and tRNA synthetase classes are weaker than between CDA and antiparallel betasheet conformation parameters. This effect is stronger for mitochondrial genetic codes, and potentially drives mitochondrial codon-amino acid reassignments. CDA reveals information ruling nucleotide-protein relations embedded in reversed (not reverse-complement) sequences (5'-ZXX-3'/5'-XXZ-3').

Locating and Visualizing Crystals for X-Ray Diffraction Experiments

Macromolecular crystallography has advanced from using macroscopic crystals, which might be >1 mm on a side, to crystals that are essentially invisible to the naked eye, or even under a standard laboratory microscope. As crystallography requires recognizing crystals when they are produced, and then placing them in an X-ray, electron, or neutron beam, this provides challenges, particularly in the case of advanced X-ray sources, where beams have very small cross sections and crystals may be vanishingly small. Methods for visualizing crystals are reviewed here, and examples of different types of cases are presented, including: standard crystals, crystals grown in mesophase, in situ crystallography, and crystals grown for X-ray Free Electron Laser or Micro Electron Diffraction experiments. As most techniques have limitations, it is desirable to have a range of complementary techniques available to identify and locate crystals. Ideally, a given technique should not cause sample damage, but sometimes it is necessary to use techniques where damage can only be minimized. For extreme circumstances, the act of probing location may be coincident with collecting X-ray diffraction data. Future challenges and directions are also discussed.

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability

Background

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form.

The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution.

A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code.

The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered.

Results

The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape.

Conclusions

Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

Improved insights into protein thermal stability: from the molecular to the structurome scale

Despite the intense efforts of the last decades to understand the thermal stability of proteins, the mechanisms responsible for its modulation still remain debated. In this investigation, we tackle this issue by showing how a multiscale perspective can yield new insights. With the help of temperature-dependent statistical potentials, we analysed some amino acid interactions at the molecular level, which are suggested to be relevant for the enhancement of thermal resistance. We then investigated the thermal stability at the protein level by quantifying its modification upon amino acid substitutions. Finally, a large scale analysis of protein stability-at the structurome level-contributed to the clarification of the relation between stability and natural evolution, thereby showing that the mutational profile of proteins differs according to their thermal properties. Some considerations on how the multiscale approach could help in unravelling the protein stability mechanisms are briefly discussed.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Multi-omics Quantification of Species Variation of Escherichia coli Links Molecular Features with Strain Phenotypes

Escherichia coli strains are widely used in academic research and biotechnology. New technologies for quantifying strain-specific differences and their underlying contributing factors promise greater understanding of how these differences significantly impact physiology, synthetic biology, metabolic engineering, and process design. Here, we quantified strain-specific differences in seven widely used strains of E. coli (BL21, C, Crooks, DH5a, K-12 MG1655, K-12 W3110, and W) using genomics, phenomics, transcriptomics, and genome-scale modeling. Metabolic physiology and gene expression varied widely with downstream implications for productivity, product yield, and titer. These differences could be linked to differential regulatory structure. Analyzing high-flux reactions and expression of encoding genes resulted in a correlated and quantitative link between these sets, with strain-specific caveats. Integrated modeling revealed that certain strains are better suited to produce given compounds or express desired constructs considering native expression states of pathways that enable high-production phenotypes. This study yields a framework for quantitatively comparing strains in a species with implications for strain selection.

The neutral emergence of error minimized genetic codes superior to the standard genetic code

The standard genetic code (SGC) assigns amino acids to codons in such a way that the impact of point mutations is reduced, this is termed 'error minimization' (EM). The occurrence of EM has been attributed to the direct action of selection, however it is difficult to explain how the searching of alternative codes for an error minimized code can occur via codon reassignments, given that these are likely to be disruptive to the proteome. An alternative scenario is that EM has arisen via the process of genetic code expansion, facilitated by the duplication of genes encoding charging enzymes and adaptor molecules. This is likely to have led to similar amino acids being assigned to similar codons. Strikingly, we show that if during code expansion the most similar amino acid to the parent amino acid, out of the set of unassigned amino acids, is assigned to codons related to those of the parent amino acid, then genetic codes with EM superior to the SGC easily arise. This scheme mimics code expansion via the gene duplication of charging enzymes and adaptors. The result is obtained for a variety of different schemes of genetic code expansion and provides a mechanistically realistic manner in which EM has arisen in the SGC. These observations might be taken as evidence for self-organization in the earliest stages of life.

The rational search for selective anticancer derivatives of the peptide Trichogin GA IV: a multi-technique biophysical approach

Peptaibols are peculiar peptides produced by fungi as weapons against other microorganisms. Previous studies showed that peptaibols are promising peptide-based drugs because they act against cell membranes rather than a specific target, thus lowering the possibility of the onset of multi-drug resistance, and they possess non-coded α-amino acid residues that confer proteolytic resistance. Trichogin GA IV (TG) is a short peptaibol displaying antimicrobial and cytotoxic activity. In the present work, we studied thirteen TG analogues, adopting a multidisciplinary approach. We showed that the cytotoxicity is tuneable by single amino-acids substitutions. Many analogues maintain the same level of non-selective cytotoxicity of TG and three analogues are completely non-toxic. Two promising lead compounds, characterized by the introduction of a positively charged unnatural amino-acid in the hydrophobic face of the helix, selectively kill T67 cancer cells without affecting healthy cells. To explain the determinants of the cytotoxicity, we investigated the structural parameters of the peptides, their cell-binding properties, cell localization, and dynamics in the membrane, as well as the cell membrane composition. We show that, while cytotoxicity is governed by the fine balance between the amphipathicity and hydrophobicity, the selectivity depends also on the expression of negatively charged phospholipids on the cell surface.

Analysis of the optimality of the standard genetic code

Many theories have been proposed attempting to explain the origin of the genetic code. In this work, we compare performance of the standard genetic code against millions of randomly generated codes. On left, ability of genetic codes to encode additional information and their robustness to frameshift mutations.

Development of a Parametrized Force Field To Reproduce Semiempirical Geometries

Here we describe the development of a classical force field parameter set to reproduce the geometry of proteins minimized at the semiempirical quantum mechanical level. The overall goal of the development of this new force field is to provide an inexpensive, yet reliable, method to arrive at geometries that are more consistent with a semiempirical treatment of protein structures. Since the minimization of a large number of protein structures at the semiempirical level can become cost-prohibitive, a "preminimization" with an appropriately parametrized classical treatment could potentially lead to more computationally efficient methods for studying protein structures through semiempirical means. Here we demonstrate that this force field allows for more rapid and stable geometry optimizations at the semiempirical level and can aid in the adoption of quantum mechanical calculations for large biological systems.

Developments and recent advancements in the field of endogenous amino acid selective bond forming reactions for bioconjugation

Bioconjugation methodologies have proven to play a central enabling role in the recent development of biotherapeutics and chemical biology approaches. Recent endeavours in these fields shed light on unprecedented chemical challenges to attain bioselectivity, biocompatibility, and biostability required by modern applications. In this review the current developments in various techniques of selective bond forming reactions of proteins and peptides were highlighted. The utility of each endogenous amino acid-selective conjugation methodology in the fields of biology and protein science has been surveyed with emphasis on the most relevant among reported transformations; selectivity and practical use have been discussed.

Genetic code evolution reveals the neutral emergence of mutational robustness, and information as an evolutionary constraint

The standard genetic code (SGC) is central to molecular biology and its origin and evolution is a fundamental problem in evolutionary biology, the elucidation of which promises to reveal much about the origins of life. In addition, we propose that study of its origin can also reveal some fundamental and generalizable insights into mechanisms of molecular evolution, utilizing concepts from complexity theory. The first is that beneficial traits may arise by non-adaptive processes, via a process of "neutral emergence". The structure of the SGC is optimized for the property of error minimization, which reduces the deleterious impact of point mutations. Via simulation, it can be shown that genetic codes with error minimization superior to the SGC can emerge in a neutral fashion simply by a process of genetic code expansion via tRNA and aminoacyl-tRNA synthetase duplication, whereby similar amino acids are added to codons related to that of the parent amino acid. This process of neutral emergence has implications beyond that of the genetic code, as it suggests that not all beneficial traits have arisen by the direct action of natural selection; we term these "pseudaptations", and discuss a range of potential examples. Secondly, consideration of genetic code deviations (codon reassignments) reveals that these are mostly associated with a reduction in proteome size. This code malleability implies the existence of a proteomic constraint on the genetic code, proportional to the size of the proteome (P), and that its reduction in size leads to an "unfreezing" of the codon - amino acid mapping that defines the genetic code, consistent with Crick's Frozen Accident theory. The concept of a proteomic constraint may be extended to propose a general informational constraint on genetic fidelity, which may be used to explain variously, differences in mutation rates in genomes with differing proteome sizes, differences in DNA repair capacity and genome GC content between organisms, a selective pressure in the evolution of sexual reproduction, and differences in translational fidelity. Lastly, the utility of the concept of an informational constraint to other diverse fields of research is explored.

Identifying, studying and making good use of macromolecular crystals

As technology advances, the crystal volume that can be used to collect useful X-ray diffraction data decreases. The technologies available to detect and study growing crystals beyond the optical resolution limit and methods to successfully place the crystal into the X-ray beam are discussed.

Structural biology has contributed tremendous knowledge to the understanding of life on the molecular scale. The Protein Data Bank, a depository of this structural knowledge, currently contains over 100 000 protein structures, with the majority stemming from X-ray crystallography. As the name might suggest, crystallography requires crystals. As detectors become more sensitive and X-ray sources more intense, the notion of a crystal is gradually changing from one large enough to embellish expensive jewellery to objects that have external dimensions of the order of the wavelength of visible light. Identifying these crystals is a prerequisite to their study. This paper discusses developments in identifying these crystals during crystallization screening and distinguishing them from other potential outcomes. The practical aspects of ensuring that once a crystal is identified it can then be positioned in the X-ray beam for data collection are also addressed.

Unexpected reactivity and mechanism of carboxamide activation in bacterial N-linked protein glycosylation

The initial glycan transfer in asparagine-linked protein glycosylation is catalysed by the integral membrane enzyme oligosaccharyltransferase (OST). Here we study the mechanism of the bacterial PglB protein, a single-subunit OST, using chemically synthesized acceptor peptide analogues. We find that PglB can glycosylate not only asparagine but also glutamine, homoserine and the hydroxamate Asp(NHOH), although at much lower rates. In contrast, N-methylated asparagine or 2,4-diaminobutanoic acid (Dab) are not glycosylated. We find that of the various peptide analogues, only asparagine- or Dab-containing peptides bind tightly to PglB. Glycopeptide products are unable to bind, providing the driving force of product release. We find no suitably positioned residues near the active site of PglB that can activate the acceptor asparagine by deprotonation, making a general base mechanism unlikely and leaving carboxamide twisting as the most likely mechanistic proposal for asparagine activation.

Revisiting the physico-chemical hypothesis of code origin: an analysis based on code-sequence coevolution in a finite population

The origin of the genetic code marked a major transition from a plausible RNA world to the world of DNA and proteins and is an important milestone in our understanding of the origin of life. We examine the efficacy of the physico-chemical hypothesis of code origin by carrying out simulations of code-sequence coevolution in finite populations in stages, leading first to the emergence of ten amino acid code(s) and subsequently to 14 amino acid code(s). We explore two different scenarios of primordial code evolution. In one scenario, competition occurs between populations of equilibrated code-sequence sets while in another scenario; new codes compete with existing codes as they are gradually introduced into the population with a finite probability. In either case, we find that natural selection between competing codes distinguished by differences in the degree of physico-chemical optimization is unable to explain the structure of the standard genetic code. The code whose structure is most consistent with the standard genetic code is often not among the codes that have a high fixation probability. However, we find that the composition of the code population affects the code fixation probability. A physico-chemically optimized code gets fixed with a significantly higher probability if it competes against a set of randomly generated codes. Our results suggest that physico-chemical optimization may not be the sole driving force in ensuring the emergence of the standard genetic code.

Amino acid composition of proteins reduces deleterious impact of mutations

The evolutionary origin of amino acid occurrence frequencies in proteins (composition) is not yet fully understood. We suggest that protein composition works alongside the genetic code to minimize impact of mutations on protein structure. First, we propose a novel method for estimating thermodynamic stability of proteins whose sequence is constrained to a fixed composition. Second, we quantify the average deleterious impact of substituting one amino acid with another. Natural proteome compositions are special in at least two ways: 1) Natural compositions do not generate more stable proteins than the average random composition, however, they result in proteins that are less susceptible to damage from mutations. 2) Natural proteome compositions that result in more stable proteins (i.e. those of thermophiles) are also tuned to have a higher tolerance for mutations. This is consistent with the observation that environmental factors selecting for more stable proteins also enhance the deleterious impact of mutations.

Evolution of complete proteomes: guanine-cytosine pressure, phylogeny and environmental influences blend the proteomic architecture

Background

Guanine-cytosine (GC) composition is an important feature of genomes. Likewise, amino acid composition is a distinct, but less valued, feature of proteomes. A major concern is that it is not clear what valuable information can be acquired from amino acid composition data. To address this concern, in-depth analyses of the amino acid composition of the complete proteomes from 63 archaea, 270 bacteria, and 128 eukaryotes were performed.

Results

Principal component analysis of the amino acid matrices showed that the main contributors to proteomic architecture were genomic GC variation, phylogeny, and environmental influences. GC pressure drove positive selection on Ala, Arg, Gly, Pro, Trp, and Val, and adverse selection on Asn, Lys, Ile, Phe, and Tyr. The physico-chemical framework of the complete proteomes withstood GC pressure by frequency complementation of GC-dependent amino acid pairs with similar physico-chemical properties. Gln, His, Ser, and Val were responsible for phylogeny and their constituted components could differentiate archaea, bacteria, and eukaryotes. Environmental niche was also a significant factor in determining proteomic architecture, especially for archaea for which the main amino acids were Cys, Leu, and Thr. In archaea, hyperthermophiles, acidophiles, mesophiles, psychrophiles, and halophiles gathered successively along the environment-based principal component. Concordance between proteomic architecture and the genetic code was also related closely to genomic GC content, phylogeny, and lifestyles.

Conclusions

Large-scale analyses of the complete proteomes of a wide range of organisms suggested that amino acid composition retained the trace of GC variation, phylogeny, and environmental influences during evolution. The findings from this study will help in the development of a global understanding of proteome evolution, and even biological evolution.

The different interactions of lysine and arginine side chains with lipid membranes

The basic amino acids lysine (Lys) and arginine (Arg) play important roles in membrane protein activity, the sensing of membrane voltages, and the actions of antimicrobial, toxin, and cell-penetrating peptides. These roles are thought to stem from the strong interactions and disruptive influences of these amino acids on lipid membranes. In this study, we employ fully atomistic molecular dynamics simulations to observe, quantify, and compare the interactions of Lys and Arg with saturated phosphatidylcholine membranes of different thickness. We make use of both charged (methylammonium and methylguanidinium) and neutral (methylamine and methylguanidine) analogue molecules, as well as Lys and Arg side chains on transmembrane helix models. We find that the free energy barrier experienced by a charged Lys crossing the membrane is strikingly similar to that of a charged Arg (to within 2 kcal/mol), despite the two having different chemistries, H-bonding capability, and hydration free energies that differ by ∼10 kcal/mol. In comparison, the barrier for neutral Arg is higher than that for neutral Lys by around 5 kcal/mol, being more selective than that for the charged species. This can be explained by the different transport mechanisms for charged or neutral amino acid side chains in the membrane, involving membrane deformations or simple dehydration, respectively. As a consequence, we demonstrate that Lys would be deprotonated in the membrane, whereas Arg would maintain its charge. Our simulations also reveal that Arg attracts more phosphate and water in the membrane, and can form extensive H-bonding with its five H-bond donors to stabilize Arg-phosphate clusters. This leads to enhanced interfacial binding and membrane perturbations, including the appearance of a trans-membrane pore in a thinner membrane. These results highlight the special role played by Arg as an amino acid to bind to, disrupt, and permeabilize lipid membranes, as well as to sense voltages for a range of peptide and protein activities in nature and in engineered bionanodevices.

Linking great apes genome evolution across time scales using polymorphism-aware phylogenetic models

The genomes of related species contain valuable information on the history of the considered taxa. Great apes in particular exhibit variation of evolutionary patterns along their genomes. However, the great ape data also bring new challenges, such as the presence of incomplete lineage sorting and ancestral shared polymorphisms. Previous methods for genome-scale analysis are restricted to very few individuals or cannot disentangle the contribution of mutation rates and fixation biases. This represents a limitation both for the understanding of these forces as well as for the detection of regions affected by selection. Here, we present a new model designed to estimate mutation rates and fixation biases from genetic variation within and between species. We relax the assumption of instantaneous substitutions, modeling substitutions as mutational events followed by a gradual fixation. Hence, we straightforwardly account for shared ancestral polymorphisms and incomplete lineage sorting. We analyze genome-wide synonymous site alignments of human, chimpanzee, and two orangutan species. From each taxon, we include data from several individuals. We estimate mutation rates and GC-biased gene conversion intensity. We find that both mutation rates and biased gene conversion vary with GC content. We also find lineage-specific differences, with weaker fixation biases in orangutan species, suggesting a reduced historical effective population size. Finally, our results are consistent with directional selection acting on coding sequences in relation to exonic splicing enhancers.

A realistic model under which the genetic code is optimal

The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the mean square measure as a function quantifying error robustness, a value can be obtained for a genetic code which reflects the error robustness of that code. By comparing this value with a distribution of values belonging to codes generated by random permutations of amino acid assignments, the level of error robustness of a genetic code can be quantified. We present a calculation in which the standard genetic code is shown to be optimal. We obtain this result by (1) using recently updated values of polar requirement as input; (2) fixing seven assignments (Ile, Trp, His, Phe, Tyr, Arg, and Leu) based on aptamer considerations; and (3) using known biosynthetic relations of the 20 amino acids. This last point is reflected in an approach of subdivision (restricting the random reallocation of assignments to amino acid subgroups, the set of 20 being divided in four such subgroups). The three approaches to explain robustness of the code (specific selection for robustness, amino acid-RNA interactions leading to assignments, or a slow growth process of assignment patterns) are reexamined in light of our findings. We offer a comprehensive hypothesis, stressing the importance of biosynthetic relations, with the code evolving from an early stage with just glycine and alanine, via intermediate stages, towards 64 codons carrying todays meaning.

Low diversity in the mitogenome of sperm whales revealed by next-generation sequencing

Large population sizes and global distributions generally associate with high mitochondrial DNA control region (CR) diversity. The sperm whale (Physeter macrocephalus) is an exception, showing low CR diversity relative to other cetaceans; however, diversity levels throughout the remainder of the sperm whale mitogenome are unknown. We sequenced 20 mitogenomes from 17 sperm whales representative of worldwide diversity using Next Generation Sequencing (NGS) technologies (Illumina GAIIx, Roche 454 GS Junior). Resequencing of three individuals with both NGS platforms and partial Sanger sequencing showed low discrepancy rates (454-Illumina: 0.0071%; Sanger-Illumina: 0.0034%; and Sanger-454: 0.0023%) confirming suitability of both NGS platforms for investigating low mitogenomic diversity. Using the 17 sperm whale mitogenomes in a phylogenetic reconstruction with 41 other species, including 11 new dolphin mitogenomes, we tested two hypotheses for the low CR diversity. First, the hypothesis that CR-specific constraints have reduced diversity solely in the CR was rejected as diversity was low throughout the mitogenome, not just in the CR (overall diversity π = 0.096%; protein-coding 3rd codon = 0.22%; CR = 0.35%), and CR phylogenetic signal was congruent with protein-coding regions. Second, the hypothesis that slow substitution rates reduced diversity throughout the sperm whale mitogenome was rejected as sperm whales had significantly higher rates of CR evolution and no evidence of slow coding region evolution relative to other cetaceans. The estimated time to most recent common ancestor for sperm whale mitogenomes was 72,800 to 137,400 years ago (95% highest probability density interval), consistent with previous hypotheses of a bottleneck or selective sweep as likely causes of low mitogenome diversity.

Selection shapes the robustness of ligand-binding amino acids

The phenotypes of biological systems are to some extent robust to genotypic changes. Such robustness exists on multiple levels of biological organization. We analyzed this robustness for two categories of amino acids in proteins. Specifically, we studied the codons of amino acids that bind or do not bind small molecular ligands. We asked to what extent codon changes caused by mutation or mistranslation may affect physicochemical amino acid properties or protein folding. We found that the codons of ligand-binding amino acids are on average more robust than those of non-binding amino acids. Because mistranslation is usually more frequent than mutation, we speculate that selection for error mitigation at the translational level stands behind this phenomenon. Our observations suggest that natural selection can affect the robustness of very small units of biological organization.

Reengineering viruses and virus-like particles through chemical functionalization strategies

Increasing demands from nanotechnology require increasingly more rigorous methods to control nanoparticle traits such as assembly, size, morphology, monodispersity, stability, and reactivity. Viruses are a compelling starting point for engineering nanoparticles, as eons of natural biological evolution have instilled diverse and desirable traits. The next step is to reengineer these viruses into something functional and useful. These reengineered particles, or virus-based nanoparticles (VNPs), are the foundation for many promising new technologies in drug delivery, targeted delivery, vaccines, imaging, and biocatalysis. To achieve these end goals, VNPs must often be manipulated genetically and post-translationally. We review prevailing strategies of genetic and noncovalent functionalization and focus on the covalent modifications using natural and unnatural amino acid residues.

Some practical guidelines for UV imaging in the protein crystallization laboratory

High-throughput imaging of protein crystallization experiments with ultraviolet (UV) light has recently become commercially available and can enable crystallographers to differentiate between crystals of protein and those of salt, as the visualization of protein crystals is based on intrinsic tryptophan fluorescence. Unfortunately, UV imaging is not a panacea, as some protein crystals will not fluoresce under UV excitation and some salt crystals are UV-fluorescently active. As a new technology, there is little experience within the general community on how to use this technology effectively and what caveats to look out for. Here, an attempt is made to identify some of the common problems that may arise using UV-imaging technology by examining test proteins, common crystallization reagents and a range of proteins by assessing their UV-Vis absorbance spectra. Some pointers are offered as to which systems may not be appropriate for this methodology.

An alternative look at code evolution: using non-canonical codes to evaluate adaptive and historic models for the origin of the genetic code

The canonical code has been shown many times to be highly robust against point mutations; that is, mutations that change a single nucleotide tend to result in similar amino acids more often than expected by chance. There are two major types of models for the origin of the code, which explain how this sophisticated structure evolved. Adaptive models state that the primitive code was specifically selected for error minimization, while historic models hypothesize that the robustness of the code is an artifact or by-product of the mechanism of code evolution. In this paper, we evaluated the levels of robustness in existing non-canonical codes as well as codes that differ in only one codon assignment from the standard code. We found that the level of robustness of many of these codes is comparable or better than that of the standard code. Although these results do not preclude an adaptive origin of the genetic code, they suggest that the code was not selected for minimizing the effects of point mutations.

Codon usage bias as a function of generation time and life expectancy

It has recently been demonstrated that human natural codon usage bias is optimized towards a higher buffering capacity to mutations (measured as the tendency of single point mutations in a DNA sequence to yield the same or similar amino acids) compared to random sequences. In this work, we investigate this phenomenon further by analyzing the natural DNA of four different species (human, mouse, zebrafish and fruit fly) to determine whether such a tolerance to mutations is correlated with the life span and age of sexual maturation for the corresponding organisms. We also propose a new measure to quantify the buffering capacity of a DNA sequence to mutations that takes into account the observed mutation rates within every genome and the effect of the corresponding mutation.Our results suggest there is a propensity for tolerance to mutations that is positively correlated with the life expectancy of the considered organisms. Moreover, random sequences that are constrained to produce the same protein as the naturally occurring sequences are found to be more buffered than completely random sequences while being less buffered than the natural sequences. These results suggest that optimization toward protective mechanisms tolerant to mutations is correlated with both life expectancy and age to sexual maturity at both the levels of codon usage bias and the bias of the natural sequence of codons itself.

Analyses of the functional regions of DEAD-box RNA "helicases" with deletion and chimera constructs tested in vivo and in vitro

The DEAD-box family of putative RNA helicases is composed of ubiquitous proteins that are found in nearly all organisms and that are involved in virtually all processes involving RNA. They are characterized by two tandemly linked, RecA-like domains that contain 11 conserved motifs and highly variable amino- and carboxy-terminal flanking sequences. For this reason, they are often considered to be modular multi-domain proteins. We tested this by making extensive BLASTs and sequence alignments to elucidate the minimal functional unit in nature. We then used this information to construct chimeras and deletions of six essential yeast proteins that were assayed in vivo. We purified many of the different constructs and characterized their biochemical properties in vitro. We found that sequence elements can only be switched between closely related proteins and that the carboxy-terminal sequences are important for high ATPase and strand displacement activities and for high RNA binding affinity. The amino-terminal elements were often toxic when overexpressed in vivo, and they may play regulatory roles. Both the amino and the carboxyl regions have a high frequency of sequences that are predicted to be intrinsically disordered, indicating that the flanking regions do not form distinct modular domains but probably assume an ordered structure with ligand binding. Finally, the minimal functional unit of the DEAD-box core starts two amino acids before the isolated phenylalanine of the Q motif and extends to about 35 residues beyond motif VI. These experiments provide evidence for how a highly conserved structural domain can be adapted to different cellular needs.

Error compensation of tRNA misacylation by codon-anticodon mismatch prevents translational amino acid misinsertion

Codon-anticodon mismatches and tRNA misloadings cause translational amino acid misinsertions, producing dysfunctional proteins. Here I explore the original hypothesis whether mismatches tend to compensate misacylation, so as to insert the amino acid coded by the codon. This error compensation is promoted by the fact that codon-anticodon mismatch stabilities increase with tRNA misacylation potentials (predicted by 'tfam') by non-cognate amino acids coded by the mismatched codons for most tRNAs examined. Error compensation is independent of preferential misacylation by non-cognate amino acids physico-chemically similar to cognate amino acids, a phenomenon that decreases misinsertion impacts. Error compensation correlates negatively with (a) codon/anticodon abundance (in human mitochondria and Escherichia coli); (b) developmental instability (estimated by fluctuating asymmetry in bilateral counts of subdigital lamellae, in each of two lizard genera, Anolis and Sceloporus); and (c) pathogenicity of human mitochondrial tRNA polymorphisms. Patterns described here suggest that tRNA misacylation is sometimes compensated by codon-anticodon mismatches. Hence translation inserts the amino acid coded by the mismatched codon, despite mismatch and misloading. Results suggest that this phenomenon is sufficiently important to affect whole organism phenotypes, as shown by correlations with pathologies and morphological estimates of developmental stability.

Simulated evolution applied to study the genetic code optimality using a model of codon reassignments

Background

As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative.

Results

Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code.

Conclusions

Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the fact that the best possible codes show the patterns of the standard genetic code. Our results are in accordance with the postulates of the engineering approach and indicate that the main arguments of the statistical approach are not enough to its assertion of the extreme efficiency of the canonical genetic code.