Prediction of amino acid pairs sensitive to mutations in the spike protein from SARS related coronavirus

In this study, we analyzed the amino acid pairs affected by mutations in two spike proteins from human coronavirus strains 229E and OC43 by means of random analysis in order to gain some insight into the possible mutations in the spike protein from SARS-CoV. The results demonstrate that the randomly unpredictable amino acid pairs are more sensitive to the mutations. The larger is the difference between actual and predicted frequencies, the higher is the chance of mutation occurring. The effect induced by mutations is to reduce the difference between actual and predicted frequencies. The amino acid pairs whose actual frequencies are larger than their predicted frequencies are more likely to be targeted by mutations, whereas the amino acid pairs whose actual frequencies are smaller than their predicted frequencies are more likely to be formed after mutations. These findings are identical to our several recent studies, i.e. the mutations represent a process of degeneration inducing human diseases.     

Evolution of the aminoacyl-tRNA synthetases and the origin of the genetic code

The aminoacyl-tRNA synthetases exist as two enzyme families which were apparently generated by divergent evolution from two primordial synthetases. The two classes of enzymes exhibit intriguing familial relationships, in that they are distributed nonrandomly within the codon-amino acid matrix of the genetic code. For example, all XCX codons code for amino acids handled by class II synthetases, and all but one of the XUX codons code for amino acids handled by class I synthetases. One interpretation of these patterns is that the synthetases coevolved with the genetic code. The more likely explanation, however, is that the synthetases evolved in the context of an already-established genetic code—a code which developed earlier in an RNA world. The rules which governed the development of the genetic code, and led to certain patterns in the coding catalog between codons and amino acids, would also have governed the subsequent evolution of the synthetases in the context of a fixed code, leading to patterns in synthetase distribution such as those observed. These rules are (1) conservative evolution of amino acid and adapter binding sites and (2) minimization of the disruptive effects on protein structure caused by codon meaning changes.     

Are rare variants responsible for susceptibility to complex diseases?

Little is known about the nature of genetic variation underlying complex diseases in humans. One popular view proposes that mapping efforts should focus on identification of susceptibility mutations that are relatively old and at high frequency. It is generally assumed-at least for modeling purposes-that selection against complex disease mutations is so weak that it can be ignored. In this article, I propose an explicit model for the evolution of complex disease loci, incorporating mutation, random genetic drift, and the possibility of purifying selection against susceptibility mutations. I show that, for the most plausible range of mutation rates, neutral susceptibility alleles are unlikely to be at intermediate frequencies and contribute little to the overall genetic variance for the disease. Instead, it seems likely that the bulk of genetic variance underlying diseases is due to loci where susceptibility mutations are mildly deleterious and where there is a high overall mutation rate to the susceptible class. At such loci, the total frequency of susceptibility mutations may be quite high, but there is likely to be extensive allelic heterogeneity at many of these loci. I discuss some practical implications of these results for gene mapping efforts.     

Lineage-Specific Differences in the Amino Acid Substitution Process

In Darwinian evolution, mutations occur approximately at random in a gene, turned into amino acid mutations by the genetic code. Some mutations are fixed to become substitutions and some are eliminated from the population. Partitioning pairs of closely related species with complete genome sequences by average population size of each pair, we looked at the substitution matrices generated for these partitions and compared the substitution patterns between species. We estimated a population genetic model that relates the relative fixation probabilities of different types of mutations to the selective pressure and population size. Parameterizations of the average and distribution of selective pressures for different amino acid substitution types in different population size comparisons were generated with a Bayesian framework. We found that partitions in population size as well as in substitution type are required to explain the substitution data. Selection coefficients were found to decrease with increasingly radical amino acid substitution and with increasing effective population size.To further explore the role of underlying processes in amino acid substitution, we analyzed embryophyte (plant) gene families from TAED (The Adaptive Evolution Database), where solved structures for at least one member exist in the Protein Data Bank. Using PAML, we assigned branches to three categories: strong negative selection, moderate negative selection/neutrality, and positive diversifying selection. Focusing on the first and third categories, we identified sites changing along gene family lineages and observed the spatial patterns of substitution. Selective sweeps were expected to create primary sequence clustering under positive diversifying selection. Co-evolution through direct physical interaction was expected to cause tertiary structural clustering. Under both positive and negative selection, the substitution patterns were found to be nonrandom. Under positive diversifying selection, significant independent signals were found for primary and tertiary sequence clustering, suggesting roles for both selective sweeps and direct physical interaction. Under strong negative selection, the signals were not found to be independent. All together, a complex interplay of population genetic and protein thermodynamics forces is suggested.     

Selectionism and neutralism in molecular evolution

Charles Darwin proposed that evolution occurs primarily by natural selection, but this view has been controversial from the beginning. Two of the major opposing views have been mutationism and neutralism. Early molecular studies suggested that most amino acid substitutions in proteins are neutral or nearly neutral and the functional change of proteins occurs by a few key amino acid substitutions. This suggestion generated an intense controversy over selectionism and neutralism. This controversy is partially caused by Kimura's definition of neutrality, which was too strict (|2Ns|< or =1). If we define neutral mutations as the mutations that do not change the function of gene products appreciably, many controversies disappear because slightly deleterious and slightly advantageous mutations are engulfed by neutral mutations. The ratio of the rate of nonsynonymous nucleotide substitution to that of synonymous substitution is a useful quantity to study positive Darwinian selection operating at highly variable genetic loci, but it does not necessarily detect adaptively important codons. Previously, multigene families were thought to evolve following the model of concerted evolution, but new evidence indicates that most of them evolve by a birth-and-death process of duplicate genes. It is now clear that most phenotypic characters or genetic systems such as the adaptive immune system in vertebrates are controlled by the interaction of a number of multigene families, which are often evolutionarily related and are subject to birth-and-death evolution. Therefore, it is important to study the mechanisms of gene family interaction for understanding phenotypic evolution. Because gene duplication occurs more or less at random, phenotypic evolution contains some fortuitous elements, though the environmental factors also play an important role. The randomness of phenotypic evolution is qualitatively different from allele frequency changes by random genetic drift. However, there is some similarity between phenotypic and molecular evolution with respect to functional or environmental constraints and evolutionary rate. It appears that mutation (including gene duplication and other DNA changes) is the driving force of evolution at both the genic and the phenotypic levels.     

Analysis of the evolution and variation of the human influenza A virus nucleoprotein gene from 1933 to 1990.

This study examined the evolution and variation of the human influenza virus nucleoprotein gene from the earliest isolates to the present. Phylogenetic reconstruction of the most parsimonious evolutionary path connecting 49 nucleoprotein sequences yielded a single lineage. The average calculated rate of mutation was 3.6 nucleotide substitutions per year (2.3 x 10(-3) substitutions per site per year). Thirty-two percent of these mutations resulted in amino acid substitutions, and the remainder were silent mutations. Analysis of virus isolates from China and elsewhere showed no significant differences in their rate of evolution, genetic diversity, or mean survival time. The nearly constant rate of change was maintained through the two antigenic shifts, and there were no obvious changes in the number or types of mutations associated with the changes in the surface proteins. A detailed comparison of the changes that have occurred on the main evolutionary path with those that have occurred on the side branches of the phylogenetic tree was made. This showed that while 35% of the mutations on the side branches resulted in amino acid changes, only 21% of those on the main path affected the protein sequence. These results suggest that although the rate of change of the human influenza virus nucleoprotein is much higher than that previously described for avian influenza viruses, there are measurable constraints on the evolution of the surviving virus lineage. Comparison of the nucleoproteins of virus isolates adapted to chicken embryos with the nucleoproteins of those grown only in MDCK cells revealed no consistent differences between the virus pairs. Thus, although the nucleoprotein is known to be critical for host specificity, its adaptation to growth in eggs apparently involves no immediate selective pressures, such as are found with hemagglutinin.     

Contrasting patterns of nonneutral evolution in proteins encoded in nuclear and mitochondrial genomes

We report that patterns of nonneutral DNA sequence evolution among published nuclear and mitochondrially encoded protein-coding loci differ significantly in animals. Whereas an apparent excess of amino acid polymorphism is seen in most (25/31) mitochondrial genes, this pattern is seen in fewer than half (15/36) of the nuclear data sets. This differentiation is even greater among data sets with significant departures from neutrality (14/15 vs. 1/6). Using forward simulations, we examined patterns of nonneutral evolution using parameters chosen to mimic the differences between mitochondrial and nuclear genetics (we varied recombination rate, population size, mutation rate, selective dominance, and intensity of germ line bottleneck). Patterns of evolution were correlated only with effective population size and strength of selection, and no single genetic factor explains the empirical contrast in patterns. We further report that in Arabidopsis thaliana, a highly self-fertilizing plant with effectively low recombination, five of six published nuclear data sets also exhibit an excess of amino acid polymorphism. We suggest that the contrast between nuclear and mitochondrial nonneutrality in animals stems from differences in rates of recombination in conjunction with a distribution of selective effects. If the majority of mutations segregating in populations are deleterious, high linkage may hinder the spread of the occasional beneficial mutation.     

The genetic code constrains yet facilitates Darwinian evolution

An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution. Here, we address the extent to which the structure of the standard genetic code constrains evolution by analyzing adaptive mutations of the antibiotic resistance gene TEM-1 β-lactamase and the fitness distribution of codon substitutions in two influenza hemagglutinin inhibitor genes. We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space. However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations. Our findings support the hypothesis that the standard genetic code was shaped by selective pressure to minimize the deleterious effects of mutation yet facilitate the evolution of proteins through imposing an adaptive mutation bias.     

Gain and loss of phosphorylation sites in human cancer

MOTIVATION: Coding-region mutations in human genes are responsible for a diverse spectrum of diseases and phenotypes. Among lesions that have been studied extensively, there are insights into several of the biochemical functions disrupted by disease-causing mutations. Currently, there are more than 60 000 coding-region mutations associated with inherited disease catalogued in the Human Gene Mutation Database (HGMD, August 2007) and more than 70 000 polymorphic amino acid substitutions recorded in dbSNP (dbSNP, build 127). Understanding the mechanism and contribution these variants make to a clinical phenotype is a formidable problem. RESULTS: In this study, we investigate the role of phosphorylation in somatic cancer mutations and inherited diseases. Somatic cancer mutation datasets were shown to have a significant enrichment for mutations that cause gain or loss of phosphorylation when compared to our control datasets (putatively neutral nsSNPs and random amino acid substitutions). Of the somatic cancer mutations, those in kinase genes represent the most enriched set of mutations that disrupt phosphorylation sites, suggesting phosphorylation target site mutation is an active cause of phosphorylation deregulation. Overall, this evidence suggests both gain and loss of a phosphorylation site in a target protein may be important features for predicting cancer-causing mutations and may represent a molecular cause of disease for a number of inherited and somatic mutations.     

Species-specific and mutant MWFE proteins. Their effect on the assembly of a functional mammalian mitochondrial complex I

The MWFE protein (70 amino acids) is highly conserved in evolution, but the human protein (80% identical to hamster) does not complement a null mutation in Chinese hamster cells. We have identified a small protein segment where significant differences exist between rodents and primates, illustrating very specifically the need for compatibility of the nuclear and mitochondrial genomes in the assembly of complex I. The segment between amino acids 39 and 46 appears to be critical for species-specific compatibility. Amino acid substitutions in this region were tested that caused a reduction of activity of the hamster protein or converted the inactive human protein into a partially active one. Such mutations could be useful in making mice with partial complex I activity as models for mitochondrial diseases. Their potential as dominant negative mutants was explored. More deleterious mutations in the NDUFA1 gene were also characterized. A conservative substitution, R50K, or a short C-terminal deletion makes the protein completely inactive. In the absence of MWFE, no high molecular weight complex was detectable by Blue Native-gel electrophoresis. The MWFE protein itself is unstable in the absence of assembled mitochondrially encoded integral membrane proteins of complex I.     

Relationship between mitochondrial DNA mutations and clinical characteristics in human lung cancer

Mitochondrial DNA (mtDNA) is known for its high frequencies of polymorphisms and mutations, some of which are related to various diseases, including cancers. However, roles of mutations and polymorphisms in some diseases are among heated debate, especially for cancer. To investigate the possible role of mtDNA mutations in lung cancer, we sequenced complete mtDNA of lung cancer tissues, corresponding normal (i.e., non-cancerous) lung tissues, and peripheral blood samples from 55 lung cancer patients and examined the relationship between mtDNA mutations or polymorphisms and clinical parameters. We identified 56 mutations in 33 (60%) of the 55 patients, including 48 point mutations, four single-nucleotide insertions, and four single-nucleotide deletions. Nineteen of these mutations resulted in amino acid substitution. These missense mtDNA mutations were distributed in 9 of 13 mitochondrial DNA coding genes. Three hundred eighty eight polymorphisms were identified among the 55 patients. Seventy-three polymorphisms resulted in amino acid substitution. There was no association of incidence of specific mtDNA mutation or polymorphism with patients' gender, age at diagnosis, smoking history, tumor type or tumor stage (P>0.05). This study revealed a variety of mtDNA mutations and mtDNA polymorphisms in human lung cancer, some of which might be involved in human lung carcinogenesis.     

Ionizing radiation and genetic risks. XII. The concept of "potential recoverability correction factor" (PRCF) and its use for predicting the risk of radiation-inducible genetic disease in human live births

Genetic risks of radiation exposure of humans are generally expressed as expected increases in the frequencies of genetic diseases over those that occur naturally in the population as a result of spontaneous mutations. Since human data on radiation-induced germ cell mutations and genetic diseases remain scanty, the rates derived from the induced frequencies of mutations in mouse genes are used for this purpose. Such an extrapolation from mouse data to the risk of genetic diseases will be valid only if the average rates of inducible mutations in human genes of interest and the average rates of induced mutations in mice are similar. Advances in knowledge of human genetic diseases and in molecular studies of radiation-induced mutations in experimental systems now question the validity of the above extrapolation. In fact, they (i) support the view that only in a limited number of genes in the human genome, induced mutations may be compatible with viability and hence recoverable in live births and (ii) suggest that the average rate of induced mutations in human genes of interest from the disease point of view will be lower than that assumed from mouse results. Since, at present, there is no alternative to the use of mouse data on induced mutation rates, there is a need to bridge the gap between these and the risk of potentially inducible genetic diseases in human live births.In this paper, we advance the concept of what we refer to here as "the potential recoverability correction factor" (PRCF) to bridge the above gap in risk estimation and present a method to estimate PRCF. In developing the concept of PRCF, we first used the available information on radiation-induced mutations recovered in experimental studies to define some criteria for assessing potential recoverability of induced mutations and then applied these to human genes on a gene-by-gene basis. The analysis permitted us to estimate unweighted PRCFs (i.e. the fraction of genes among the total studied that might contribute to recoverable induced mutations) and weighted PRCFs (i.e. PRCFs weighted by the incidences of the respective diseases). The estimates are: 0.15 (weighted) to 0.30 (unweighted) for autosomal dominant and X-linked diseases and 0.02 (weighted) to 0.09 (unweighted) for chronic multifactorial diseases. The PRCF calculations are unnecessary for autosomal recessive diseases since the risks projected for the first few generations even without using PRCFs are already very small. For congenital abnormalities, PRCFs cannot be reliably estimated.With the incorporation of PRCF into the equation used for predicting risk, the risk per unit dose becomes the product of four quantities (risk per unit dose=Px(1/DD)xMCxPRCF) where P is the baseline frequency of the genetic disease, 1/DD is the relative mutation risk per unit dose, MC is the mutation component and PRCF is the disease-class-specific potential recoverability correction factor instead of the first three (as has been the case thus far). Since PRCF is a fraction, it is obvious that the estimate of risk obtained with the revised risk equation will be smaller than previously calculated values.     

Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa

Understanding adaptation by natural selection requires understanding the genetic factors that determine which beneficial mutations are available for selection. Here, using experimental evolution of rifampicin-resistant Pseudomonas aeruginosa, we show that different genotypes vary in their capacity for adaptation to the cost of antibiotic resistance. We then use sequence data to show that the beneficial mutations associated with fitness recovery were specific to particular genetic backgrounds, suggesting that genotypes had access to different sets of beneficial mutations. When we manipulated the supply rate of beneficial mutations, by altering effective population size during evolution, we found that it constrained adaptation in some selection lines by restricting access to rare beneficial mutations, but that the effect varied among the genotypes in our experiment. These results suggest that mutational neighbourhood varies even among genotypes that differ by a single amino acid change, and this determines their capacity for adaptation as well as the influence of population biology processes that alter mutation supply rate.     

Challenges of the genetic code for exploring sequence space in directed protein evolution

Directed protein evolution is the most versatile method for studying protein structure-function relationships, and for tailoring a protein's properties to the needs of industrial applications. In this review, we performed a statistical analysis on the genetic code to study the extent and consequence of the organization of the genetic code on amino acid substitution patterns generated in directed evolution experiments. In detail, we analyzed amino acid substitution patterns caused by (a) a single nucleotide (nt) exchange at each position of all 64 codons, and (b) two subsequent nt exchanges (first and second nt, first and third nt, second and third nt). Additionally, transitions and transversions mutations were compared at the level of amino acid substitution patterns. The latter analysis showed that single nucleotide substitution in a codon generates only 39.5% of the natural diversity on the protein level with 5.2-7 amino acid substitutions per codon. Transversions generate more complex amino acid substitution patterns (increased number and chemically more diverse amino acid substitutions) than transitions. Simultaneous nt exchanges at both first and second nt of a codon generates very diverse amino acid substitution patterns, achieving 83.2% of the natural diversity. The statistical analysis described in this review sets the objectives for novel random mutagenesis methods that address the consequences of the organization of the genetic code. Random mutagenesis methods that favor transversions or introduce consecutive nt exchanges can contribute in this regard.     

ESEfinder: A web resource to identify exonic splicing enhancers

Point mutations frequently cause genetic diseases by disrupting the correct pattern of pre-mRNA splicing. The effect of a point mutation within a coding sequence is traditionally attributed to the deduced change in the corresponding amino acid. However, some point mutations can have much more severe effects on the structure of the encoded protein, for example when they inactivate an exonic splicing enhancer (ESE), thereby resulting in exon skipping. ESEs also appear to be especially important in exons that normally undergo alternative splicing. Different classes of ESE consensus motifs have been described, but they are not always easily identified. ESEfinder (http://exon.cshl.edu/ESE/) is a web-based resource that facilitates rapid analysis of exon sequences to identify putative ESEs responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.     

Protein evolution within and between species

Protein evolution can be seen as the successive replacement of amino acids by other amino acids. In general, it is a very slow process which is triggered by point mutations in the nucleotide sequence. These mutations can transform into single nucleotide polymorphisms (SNPs) within populations and diverging proteins between species. It is well known that in many cases amino acids can be replaced by others without impeding the functioning of the protein, even if these are of quite different physico-chemical character. In some cases, however, almost any replacement would result in a functionally deficient protein. Based upon comprehensive published SNP data and applying correlation analysis we quantified the two antagonist factors controlling the process of amino acid replacement and thus protein evolution: First, the degenerate structure of the genetic code which facilitates the exchange of certain amino acids and, second, the physico-chemical forces which limit the range of possible exchanges to maintain a functional protein. We found that the observed frequencies of amino acid exchanges within species are best explained by the genetic code and that the conservation of physico-chemical properties plays a subordinate role, but has nevertheless to be considered as a key factor. Between moderately diverged species genetic code and physico-chemical properties exert comparable influence on amino acid exchanges. We furthermore studied amino acid exchanges in more detail for six species (four mammals, one bird, and one insect) and found that the profiles are highly correlated across all examined species despite their large evolutionary divergence of up to 800 million years. The species specific exchange profiles are also correlated to the exchange profile observed between different species. The currently available huge body of SNP data allows to characterize the role of two major shaping forces of protein evolution more quantitatively than before.     

Challenges of the genetic code for exploring sequence space in directed protein evolution

Directed protein evolution is the most versatile method for studying protein structure–function relationships, and for tailoring a protein's properties to the needs of industrial applications. In this review, we performed a statistical analysis on the genetic code to study the extent and consequence of the organization of the genetic code on amino acid substitution patterns generated in directed evolution experiments. In detail, we analyzed amino acid substitution patterns caused by (a) a single nucleotide (nt) exchange at each position of all 64 codons, and (b) two subsequent nt exchanges (first and second nt, first and third nt, second and third nt). Additionally, transitions and transversions mutations were compared at the level of amino acid substitution patterns. The latter analysis showed that single nucleotide substitution in a codon generates only 39.5% of the natural diversity on the protein level with 5.2–7 amino acid substitutions per codon. Transversions generate more complex amino acid substitution patterns (increased number and chemically more diverse amino acid substitutions) than transitions. Simultaneous nt exchanges at both first and second nt of a codon generates very diverse amino acid substitution patterns, achieving 83.2% of the natural diversity. The statistical analysis described in this review sets the objectives for novel random mutagenesis methods that address the consequences of the organization of the genetic code. Random mutagenesis methods that favor transversions or introduce consecutive nt exchanges can contribute in this regard.     

The evolution of biased codon and amino acid usage in nematode genomes

Despite the degeneracy of the genetic code, whereby different codons encode the same amino acid, alternative codons and amino acids are utilized nonrandomly within and between genomes. Such biases in codon and amino acid usage have been demonstrated extensively in prokaryote genomes and likely reflect a balance between the action of mutation, selection, and genetic drift. Here, we quantify the effects of selection and mutation drift as causes of codon and amino acid-usage bias in a large collection of nematode partial genomes from 37 species spanning approximately 700 Myr of evolution, as inferred from expressed sequence tag (EST) measures of gene expression and from base composition variation. Average G + C content at silent sites among these taxa ranges from 10% to 63%, and EST counts range more than 100-fold, underlying marked differences between the identities of major codons and optimal codons for a given species as well as influencing patterns of amino acid abundance among taxa. Few species in our sample demonstrate a dominant role of selection in shaping intragenomic codon-usage biases, and these are principally free living rather than parasitic nematodes. This suggests that deviations in effective population size among species, with small effective sizes among parasites, are partly responsible for species differences in the extent to which selection shapes patterns of codon usage. Nevertheless, a consensus set of optimal codons emerges that is common to most taxa, indicating that, with some notable exceptions, selection for translational efficiency and accuracy favors similar sets of codons regardless of the major codon-usage trends defined by base compositional properties of individual nematode genomes.