Little evidence the standard genetic code is optimized for resource conservation.
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ABSTRACT:
SUBMITTER: Rozhonova H
PROVIDER: S-EPMC8557452 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The causes and consequences of the nonrandom structure of the standard genetic code (SGC) have been of long-standing interest. A recent study reported that mutations in present-day protein-coding sequences are less likely to increase proteomic nitrogen and carbon uses under the SGC than under random genetic codes, concluding that the SGC has been selectively optimized for resource conservation. If true, this finding might offer important information on the environment in which the SGC and some of the earliest life forms evolved. However, we here show that the hypothesis of optimization of a genetic code for resource conservation is theoretically untenable. We discover that the aforementioned study estimated the expected mutational effect by inappropriately excluding mutations lowering resource consumptions and including mutations involving stop codons. After remedying these problems, we find no evidence that the SGC is optimized for nitrogen or carbon conservation.
| S-EPMC8557414 | biostudies-literature
Project description:A near-universal Standard Genetic Code (SGC) implies a single origin for present Earth life. To study this unique event, I compute paths to the SGC, comparing different plausible histories. Notably, SGC-like coding emerges from traditional evolutionary mechanisms, and a superior route can be identified. To objectively measure evolution, progress values from 0 (random coding) to 1 (SGC-like) are defined: these measure fractions of random-code-to-SGC distance. Progress types are spacing/distance/delta Polar Requirement, detecting space between identical assignments/mutational distance to the SGC/chemical order, respectively. The coding system is based on selected RNAs performing aminoacyl-RNA synthetase reactions. Acceptor RNAs exhibit SGC-like Crick wobble; alternatively, non-wobbling triplets uniquely encode 20 amino acids/start/stop. Triplets acquire 22 functions by stereochemistry, selection, coevolution, or at random. Assignments also propagate to an assigned triplet's neighborhood via single mutations, but can also decay. A vast code universe makes futile evolutionary paths plentiful. Thus, SGC evolution is critically sensitive to disorder from random assignments. Evolution also inevitably slows near coding completion. The SGC likely avoided these difficulties, and two suitable paths are compared. In late wobble, a majority of non-wobble assignments are made before wobble is adopted. In continuous wobble, a uniquely advantageous early intermediate yields an ordered SGC. Revised coding evolution (limited randomness, late wobble, concentration on amino acid encoding, chemically conservative coevolution with a chemically ordered elite) produces varied full codes with excellent joint progress values. A population of only 600 independent coding tables includes SGC-like members; a Bayesian path toward more accurate SGC evolution is available.
| S-EPMC7884377 | biostudies-literature
Project description:The ribosomal incorporation of nonnative amino acids into polypeptides in living cells provides the opportunity to endow therapeutic proteins with unique pharmacological properties. We report here the first clinical study of a biosynthetic protein produced using an expanded genetic code. Incorporation of p-acetylphenylalanine (pAcF) at distinct locations in human growth hormone (hGH) allowed site-specific conjugation with polyethylene glycol (PEG) to produce homogeneous hGH variants. A mono-PEGylated mutant hGH modified at residue 35 demonstrated favorable pharmacodynamic properties in GH-deficient rats. Clinical studies in GH-deficient adults demonstrated efficacy and safety comparable to native human growth hormone therapy but with increased potency and reduced injection frequency. This example illustrates the utility of nonnative amino acids to optimize protein therapeutics in an analogous fashion to the use of medicinal chemistry to optimize conventional natural products, low molecular weight drugs, and peptides.
| S-EPMC3107295 | biostudies-literature
Project description:The standard genetic code (SGC) has been extensively analyzed for the biological ramifications of its nonrandom structure. For instance, mismatch errors due to point mutation or mistranslation have an overall smaller effect on the amino acid polar requirement under the SGC than under random genetic codes (RGCs). A similar observation was recently made for frameshift errors, prompting the assertion that the SGC has been shaped by natural selection for frameshift-robustness-conservation of certain amino acid properties upon a frameshift mutation or translational frameshift. However, frameshift-robustness confers no benefit because frameshifts usually create premature stop codons that cause nonsense-mediated mRNA decay or production of nonfunctional truncated proteins. We here propose that the frameshift-robustness of the SGC is a byproduct of its mismatch-robustness. Of 564 amino acid properties considered, the SGC exhibits mismatch-robustness in 93-133 properties and frameshift-robustness in 55 properties, respectively, and that the latter is largely a subset of the former. For each of the 564 real and 564 randomly constructed fake properties of amino acids, there is a positive correlation between mismatch-robustness and frameshift-robustness across one million RGCs; this correlation arises because most amino acid changes resulting from a frameshift are also achievable by a mismatch error. Importantly, the SGC does not show significantly higher frameshift-robustness in any of the 55 properties than RGCs of comparable mismatch-robustness. These findings support that the frameshift-robustness of the SGC need not originate through direct selection and can instead be a site effect of its mismatch-robustness.
| S-EPMC8476161 | biostudies-literature
Project description: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.
| S-EPMC6293558 | biostudies-other
Project description:BACKGROUND: The arrangement of the amino acids in the genetic code is such that neighbouring codons are assigned to amino acids with similar physical properties. Hence, the effects of translational error are minimized with respect to randomly reshuffled codes. Further inspection reveals that it is amino acids in the same column of the code (i.e. same second base) that are similar, whereas those in the same row show no particular similarity. We propose a 'four-column' theory for the origin of the code that explains how the action of selection during the build-up of the code leads to a final code that has the observed properties. RESULTS: The theory makes the following propositions. (i) The earliest amino acids in the code were those that are easiest to synthesize non-biologically, namely Gly, Ala, Asp, Glu and Val. (ii) These amino acids are assigned to codons with G at first position. Therefore the first code may have used only these codons. (iii) The code rapidly developed into a four-column code where all codons in the same column coded for the same amino acid: NUN = Val, NCN = Ala, NAN = Asp and/or Glu, and NGN = Gly. (iv) Later amino acids were added sequentially to the code by a process of subdivision of codon blocks in which a subset of the codons assigned to an early amino acid were reassigned to a later amino acid. (v) Later amino acids were added into positions formerly occupied by amino acids with similar properties because this can occur with minimal disruption to the proteins already encoded by the earlier code. As a result, the properties of the amino acids in the final code retain a four-column pattern that is a relic of the earliest stages of code evolution. CONCLUSION: The driving force during this process is not the minimization of translational error, but positive selection for the increased diversity and functionality of the proteins that can be made with a larger amino acid alphabet. Nevertheless, the code that results is one in which translational error is minimized. We define a cost function with which we can compare the fitness of codes with varying numbers of amino acids, and a barrier function, which measures the change in cost immediately after addition of a new amino acid. We show that the barrier is positive if an amino acid is added into a column with dissimilar properties, but negative if an amino acid is added into a column with similar physical properties. Thus, natural selection favours the assignment of amino acids to the positions that they occupy in the final code.
| S-EPMC2689856 | biostudies-other
Project description:A modified BioBrick™ assembly method was developed with higher fidelity than current protocols. The method utilizes a PCR reaction with a standard primer set to amplify the inserted part. Background colonies are reduced by a combination of dephosphorylation and digestion with DpnI restriction endonuclease to reduce vector and insert background respectively. The molar ratio of the insert to vector in the ligation was also optimized, with the accuracy of the transformed construct approaching 100%.
| S-EPMC3287150 | biostudies-literature
Project description:With few-nanometer resolution recently achieved by a new generation of fluorescence nanoscopes (MINFLUX and MINSTED), the size of the tags used to label proteins will increasingly limit the ability to dissect nanoscopic biological structures. Bioorthogonal (click) chemical groups are powerful tools for the specific detection of biomolecules. Through the introduction of an engineered aminoacyl-tRNA synthetase/tRNA pair (tRNA: transfer ribonucleic acid), genetic code expansion allows for the site-specific introduction of amino acids with "clickable" side chains into proteins of interest. Well-defined label positions and the subnanometer scale of the protein modification provide unique advantages over other labeling approaches for imaging at molecular-scale resolution. We report that, by pairing a new N-terminally optimized pyrrolysyl-tRNA synthetase (chPylRS2020) with a previously engineered orthogonal tRNA, clickable amino acids are incorporated with improved efficiency into bacteria and into mammalian cells. The resulting enhanced genetic code expansion machinery was used to label β-actin in U2OS cell filopodia for MINFLUX imaging with minimal separation of fluorophores from the protein backbone. Selected data were found to be consistent with previously reported high-resolution information from cryoelectron tomography about the cross-sectional filament bundling architecture. Our study underscores the need for further improvements to the degree of labeling with minimal-offset methods in order to fully exploit molecular-scale optical three-dimensional resolution.
| S-EPMC9304028 | biostudies-literature
Project description: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.
| S-EPMC6084934 | biostudies-literature
Project description:The apparent clustering of human cases of influenza A (H5N1) among blood relatives has been considered as evidence of genetic variation in susceptibility. We show that, by chance alone, a high proportion of clusters are expected to be limited to blood relatives when infection is a rare event.
| S-EPMC2878232 | biostudies-literature