RNA codewords and protein synthesis, 8. Nucleotide sequences of synonym codons for arginine, valine, cysteine, and alanine

History of advances in genetic engineering of viruses before COVID-19 pandemic

Background

On December 31, 2019, the World Health Organization's China Country Office was alerted to cases of pneumonia of unknown cause detected in Wuhan City, Hubei Province of China.

Methods

Due to the fact that to date, the question of the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been resolved yet, the author analyzed the main advances in the development of genetic engineering of viruses that took place before the onset of the COVID-19 pandemic.

Results

The first artificial genetically modified viruses could appear in nature in the mid-1950s. The technique of nucleic acid hybridization was developed by the end-1960s. In the late 1970s, a method called the "reverse genetics" emerged to synthesize ribonucleic acid and deoxyribonucleic acid molecules. In the early 1980-s, it became possible to combine the genes of different viruses and insert the genes of one virus into the genome of another virus. Since that time, the production of vector vaccines began. At present, by modern technologies one can assemble any virus based on the nucleotide sequence available in the virus database or designed by a computer as a virtual model.

Conclusion

Scientists around the world are invited to answer the call of Neil Harrison and Jeffrey Sachs of Columbia University, for a thorough and independent investigation into the origin of SARS-CoV-2. Only a full understanding of the origin of the new virus can minimize the likelihood of a similar pandemic in the future.

A Code Within a Code: How Codons Fine-Tune Protein Folding in the Cell

The genetic code sets the correspondence between the sequence of a given nucleotide triplet in an mRNA molecule, called a codon, and the amino acid that is added to the growing polypeptide chain during protein synthesis. With four bases (A, G, U, and C), there are 64 possible triplet codons: 61 sense codons (encoding amino acids) and 3 nonsense codons (so-called, stop codons that define termination of translation). In most organisms, there are 20 common/standard amino acids used in protein synthesis; thus, the genetic code is redundant with most amino acids (with the exception of Met and Trp) are being encoded by more than one (synonymous) codon. Synonymous codons were initially presumed to have entirely equivalent functions, however, the finding that synonymous codons are not present at equal frequencies in mRNA suggested that the specific codon choice might have functional implications beyond coding for amino acid. Observation of nonequivalent use of codons in mRNAs implied a possibility of the existence of auxiliary information in the genetic code. Indeed, it has been found that genetic code contains several layers of such additional information and that synonymous codons are strategically placed within mRNAs to ensure a particular translation kinetics facilitating and fine-tuning co-translational protein folding in the cell via step-wise/sequential structuring of distinct regions of the polypeptide chain emerging from the ribosome at different points in time. This review summarizes key findings in the field that have identified the role of synonymous codons and their usage in protein folding in the cell.

The Cipher of the Genetic Code

A new approach to understanding of the genetic code is developed. In order to overcome the key paradox (and Darwinian selection problem) that the highly complex amino acid Phe is encoded by the simplest codons (UUY), and the simplest Gly encoded by the most complex codons (GGN); as well as the paradox of the duplication of some amino acids in the encoding process (Leu, Ser, Arg), we proposed an extension of the notion (and concept) of genetic code. For a better (and lighter) understanding of genetic coding, we proposed a hypothesis after that (under the conditions of allowed metaphoricity and modeling in biology) genetic code has to be understood, analogously in cryptology, as the unity of three entities: the code, the cipher of the code and the key of the cipher. In this hierarchy the term (and notion) "genetic code" remains what has been from the beginning: a connection between four-letter alphabet (four Py-Pu nucleotides, in form of codons) and a twenty-letter alphabet (twenty amino acids); the cipher is a specific chemical complementarity in chemical properties of molecules in the form: similarity in dissimilarity versus dissimilarity in similarity ("Sim in Diss vs Diss in Sim") and the key of cipher: the complementarity on the binary tree of the genetic code in the form: 0-15, 1-14, 2-13, …, 6-9, 7-8. These concepts improve understanding that within the two main Genetic Code Tables (of the nucleotide doublets and nucleotide Triplets) exists a sophisticated nuancing and balancing in the properties of the constituents of GC, including the balance of the number of molecules, atoms, and nucleons.

Visualizing tRNA-dependent mistranslation in human cells

High-fidelity translation and a strictly accurate proteome were originally assumed as essential to life and cellular viability. Yet recent studies in bacteria and eukaryotic model organisms suggest that proteome-wide mistranslation can provide selective advantages and is tolerated in the cell at higher levels than previously thought (one error in 6.9 × 10^-4 in yeast) with a limited impact on phenotype. Previously, we selected a tRNA^Pro containing a single mutation that induces mistranslation with alanine at proline codons in yeast. Yeast tolerate the mistranslation by inducing a heat-shock response and through the action of the proteasome. Here we found a homologous human tRNA^Pro (G3:U70) mutant that is not aminoacylated with proline, but is an efficient alanine acceptor. In live human cells, we visualized mistranslation using a green fluorescent protein reporter that fluoresces in response to mistranslation at proline codons. In agreement with measurements in yeast, quantitation based on the GFP reporter suggested a mistranslation rate of up to 2-5% in HEK 293 cells. Our findings suggest a stress-dependent phenomenon where mistranslation levels increased during nutrient starvation. Human cells did not mount a detectable heat-shock response and tolerated this level of mistranslation without apparent impact on cell viability. Because humans encode ∼600 tRNA genes and the natural population has greater tRNA sequence diversity than previously appreciated, our data also demonstrate a cell-based screen with the potential to elucidate mutations in tRNAs that may contribute to or alleviate disease.

The path to the genetic code

In December of 1966 the last nucleotide triplet in the genetic code has been assigned (Brenner et al., 1967 [1]) thus completing years of studies aimed at deciphering the nature of the relationship between the sequences of genes and proteins. The end product, the table of the genetic code, was a crowning achievement of the quest to unravel the basic mechanisms underlying functioning of all living organisms on the molecular level.

The Yin and Yang of codon usage

The genetic code is degenerate. With the exception of two amino acids (Met and Trp), all other amino acid residues are each encoded by multiple, so-called synonymous codons. Synonymous codons were initially presumed to have entirely equivalent functions, however, the finding that synonymous codons are not present at equal frequencies in genes/genomes suggested that codon choice might have functional implications beyond amino acid coding. The pattern of non-uniform codon use (known as codon usage bias) varies between organisms and represents a unique feature of an organism. Organism-specific codon choice is related to organism-specific differences in populations of cognate tRNAs. This implies that, in a given organism, frequently used codons will be translated more rapidly than infrequently used ones and vice versa A theory of codon-tRNA co-evolution (necessary to balance accurate and efficient protein production) was put forward to explain the existence of codon usage bias. This model suggests that selection favours preferred (frequent) over un-preferred (rare) codons in order to sustain efficient protein production in cells and that a given un-preferred codon will have the same effect on an organism's fitness regardless of its position within an mRNA's open reading frame. However, many recent studies refute this prediction. Un-preferred codons have been found to have important functional roles and their effects appeared to be position-dependent. Synonymous codon usage affects the efficiency/stringency of mRNA decoding, mRNA biogenesis/stability, and protein secretion and folding. This review summarizes recent developments in the field that have identified novel functions of synonymous codons and their usage.

DNA hybridization of cervical tissues

The increasing frequency of cervical neoplasia among younger women and the increased invasiveness of these tumors has led to a considerable growth in research into this disease. Conventional methods (epidemiology, cytology, and immunology), while being extremely useful, also have significant limitations. Recent advances in techniques for the manipulation of DNA now make it possible to analyze tissues for the presence of viral genomes. This review introduces these techniques and describes their application to the search for herpes simplex virus and human papillomavirus sequences in cervical tissue. The significance of the findings both for the mechanism of transmission of the disease, and also the consequences for early detection and hence more successful treatment, are also discussed.

Symmetry characteristics of the genetic code

The symmetric pattern of codon degeneracies is discussed by using empirical arguments processed within a group-theoretic framework. It is reasoned that the genetic code is a relation rather than a mapping, and the symmetry of a relation defined on the codons is investigated. The principal results are (i) a new extraction of the basic symmetry inherent in the standard genetic code; (ii) the unification of the symmetry of ambiguous codon assignments with that of the standard genetic code; and (iii) the primacy of the concept of a biological context as that device which degenerates the code relation to a mapping.

The effect of tRNA concentration on the rate of protein synthesis

Two in vitro protein-synthesizing systems derived from E. coli have been utilized to demonstrate that the concentration of a tRNA species can regulate the rate of translation of a messenger RNA. (a) The rate of poly-U-directed C(14)-phenylalanine incorporation into protein is stimulated by concentrations of tRNA(Phe) from 1.5 x 10(-8) M to 3.0 x 10(-6) M, the latter representing a tRNA(Phe)/70S ribosome ratio of 7. (b) The rate of translation of poly A,G in a S-30 protein-synthesizing system derived from E. coli is limited by the amount of tRNA(Arg) recognizing the codewords AGA and AGG present in the extract. Polypeptide synthesis can be stimulated in direct proportion to the amount of this tRNA(Arg) species added to the reaction mixture. A mechanism for regulating the rate of protein synthesis at the translational level may be the slowing of polypeptide chain propagation at certain codons due to the presence of rate-limiting tRNA species.

Amino acid coding in Sarcina lutea and Saccharomyces cerevisiae

Aminoacyl-tRNA's from Sarcina lutea were tested for incorporation into protein in a heterologous system from Escherichia coli or for biniding in a homologous system from Sarcina lutea. Aminoacyl-tRNA's from Saccharomyces cerevisiae were tested for biniding in a homologous Saccharomyces cerevisiae system. Synthetic polyribonucleotides were used as messengers. The code which exists in Sarcina lutea and Saccharomyces cerevisiae is the same as in Escherichia coli.

Fine structure of RNA codewords recognized by bacterial, amphibian, and mammalian transfer RNA

Nucleotide sequences of 50 RNA codons recognized by amphibian and mammalian liver transfer RNA preparations were determined and compared with those recognized by Escherichia coli transfer RNA. Almost identical translations were obtained with transfer RNA from guinea pig liver, Xenopus laevis liver (South African clawed toad), and E. coli. However, guinea pig and Xenopus transfer RNA differ markedly from E. coli transfer RNA in relative response to certain trinucleotides. Transfer RNA from mammalian liver, amphibian liver, and amphibian muscle respond similarly to trinucleotide codons. Thus the genetic code is essentially universal, but transfer RNA from one organism may differ from that of another in relative response to some codons.

Mechanism of antibody synthesis: size differences between mouse kappa chains

Structural analysis of immunoglobulin light chains has been carried out in an attempt to elucidate the genetic mechanisms involved in antibody synthesis. Analysis of two mouse kappa-chain proteins is almost complete. The differences are localized in one-half of the molecules, and do not reflect the operation of any one mutational mechanism. The peculiar character of the differences is discussed with reference to various theories of antibody formation. The finding that the two proteins differ in size is incompatible with certain proposed theories.

Hemoglobins in sheep: multiple differences in amino acid sequences of three beta-chains and possible origins

Among the three adult sheep hemoglobins (A, B, and C), two (A and B) are reportedly products of alleles. The beta-chains of A and B differ by at least seven scattered amino acid residues whereas the beta-sequence of C differs from A by at least 16 residues and from B by at least 21 residues. These changes suggest that the origin of C-beta antedated the divergence of A and B. Five shared differences between A-beta and C-beta with respect to B-beta can be interpreted as the result of selective advantage in favor of B. A complex of additional mechanisms has possibly been involved in maintaining the A-B- C porymorphism.

A chemical difference between human transferrins B2 and C

Images

Genetic code: aspects of organization

The pattern of organization of the genetic code decreases to a minimum the phenotypic effects of mutation and of base-pairing errors in protein synthesis. Single base changes, especially transitions, usually cause either no amino acid change or the change to a chemically similar amino acid. The degree of degeneracy of the codons for an amino acid is correlated with their guanine-cytosine content. The code gives greater protection (by both degeneracy and guaninecytosine content of codons) to those amino acids that appear more frequently in proteins. Increased reliability of the protein-synthesis system afforded by this pattern of organization nay have determined the fitness of the present code.

Problems in protein biosynthesis

Outline of the steps in protein synthesis. Nature of the genetic code. The use of synthetic oligo- and polynucleotides in deciphering the code. Structure of the code: relatedness of synonym codons. The wobble hypothesis. Chain initiation and N-formyl-methionine. Chain termination and nonsense codons. Mistakes in translation: ambiguity in vitro. Suppressor mutations resulting in ambiguity. Limitations in the universality of the code. Attempts to determine the particular codons used by a species. Mechanisms of suppression, caused by (a) abnormal aminoacyl-tRNA, (b) ribosomal malfunction. Effect of streptomycin. The problem of "reading" a nucleic acid template. Different ribosomal mutants and DNA polymerase mutants might cause different mistakes. The possibility of involvement of allosteric proteins in template reading.

Immunoglobulin structure: variation in the sequence of Bence Jones proteins

Analysis of the amino acid sequence of one Bence Jones protein is almost comtplete. Many points of interchange occur in the amino terminal. portion of the molecule relative to partial-sequence data for other proteins. Most, but not all, are, compartible with one-step mutations. Such structural variation in immunoglobulin light chains may result from many related genes.