Selection for robustness in mutagenized RNA viruses.
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ABSTRACT:
SUBMITTER: Sanjuan R
PROVIDER: S-EPMC1892351 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Two key features of RNA viruses are their compacted genomes and their high mutation rate. Accordingly, deleterious mutations are common and have an enormous impact on viral fitness. In their multicellular hosts, robustness can be achieved by genomic redundancy, including gene duplication, diploidy, alternative metabolic pathways and biochemical buffering mechanisms. However, here we review evidence suggesting that during RNA virus evolution, alternative robustness mechanisms may have been selected. After briefly describing how genetic robustness can be quantified, we discuss mechanisms of intrinsic robustness arising as consequences of RNA-genome architecture, replication peculiarities and quasi-species population dynamics. These intrinsic robustness mechanisms operate efficiently at the population level, despite the mutational sensitivity shown by individual genomes. Finally, we discuss the possibility that viruses might exploit cellular buffering mechanisms for their own benefit, producing a sort of extrinsic robustness.
| S-EPMC1369264 | biostudies-literature
Project description:The accumulation of mutations in RNA viruses is thought to facilitate rapid adaptation to changes in the environment. However, most mutations have deleterious effects on fitness, especially for viruses. Thus, tolerance to mutations should determine the nature and extent of genetic diversity that can be maintained in the population. Here, we combine population genetics theory, computer simulation, and experimental evolution to examine the advantages and disadvantages of tolerance to mutations, also known as mutational robustness. We find that mutational robustness increases neutral diversity and, as expected, can facilitate adaptation to a new environment. Surprisingly, under certain conditions, robustness may also be an impediment for viral adaptation, if a highly diverse population contains a large proportion of previously neutral mutations that are deleterious in the new environment. These findings may inform therapeutic strategies that cause extinction of otherwise robust viral populations.
| S-EPMC4142091 | biostudies-literature
Project description:RNA viruses are responsible for some of the worst pandemics known to mankind, including outbreaks of Influenza, Ebola, and COVID-19. One major challenge in tackling RNA viruses is the fact they are extremely genetically diverse. Nevertheless, they share common features that include their dependence on host cells for replication, and high mutation rates. We set out to search for shared evolutionary characteristics that may aid in gaining a broader understanding of RNA virus evolution, and constructed a phylogeny-based data set spanning thousands of sequences from diverse single-stranded RNA viruses of animals. Strikingly, we found that the vast majority of these viruses have a skewed nucleotide composition, manifested as adenine rich (A-rich) coding sequences. In order to test whether A-richness is driven by selection or by biased mutation processes, we harnessed the effects of incomplete purifying selection at the tips of virus phylogenies. Our results revealed consistent mutational biases toward U rather than A in genomes of all viruses. In +ssRNA viruses, we found that this bias is compensated by selection against U and selection for A, which leads to A-rich genomes. In -ssRNA viruses, the genomic mutational bias toward U on the negative strand manifests as A-rich coding sequences, on the positive strand. We investigated possible reasons for the advantage of A-rich sequences including weakened RNA secondary structures, codon usage bias, and selection for a particular amino acid composition, and conclude that host immune pressures may have led to similar biases in coding sequence composition across very divergent RNA viruses.
| S-EPMC7543401 | biostudies-literature
Project description:Analysis of the pattern of nucleotide diversity in 222 independent viral sequence datasets showed the prevalence of purifying selection. In spite of the higher mutation rate of RNA viruses, our analyses revealed stronger evidence of the action of purifying selection in RNA viruses than in DNA viruses. The ratio of nonsynonymous to synonymous nucleotide diversity was significantly lower in RNA viruses than in DNA viruses, indicating that nonsynonymous mutations have been removed at a greater rate (relative to the mutation rate) in the former than in the latter. Moreover, statistics that measure the occurrence of rare polymorphisms revealed significantly a greater excess of rare nonsynonymous polymorphisms in RNA viruses than in DNA viruses but no difference with respect to synonymous polymorphisms. Since rare nonsynonymous polymorphisms are likely to be undergoing the effects of purifying selection acting to eliminate them, this result implies a stronger signature of ongoing purifying selection in RNA viruses than in DNA viruses. Across datasets from both DNA viruses and RNA viruses, we found a negatively allometric relationship between nonsynonymous and synonymous nucleotide diversity; in other words, nonsynonymous nucleotide diversity increased with synonymous nucleotide diversity at a less than linear rate. These findings are most easily explained by the occurrence of slightly deleterious mutations. The fact that the negative allometry was more pronounced in RNA viruses than in DNA viruses provided additional evidence that purifying selection is more effective in the former than in the latter.
| S-EPMC2756238 | biostudies-literature
Project description:BACKGROUND:The molecular events and evolutionary forces underlying lethal mutagenesis of virus (or virus extinction through an excess of mutations) are not well understood. Here we apply for the first time phylogenetic methods and Partition Analysis of Quasispecies (PAQ) to monitor genetic distances and intra-population structures of mutant spectra of foot-and-mouth disease virus (FMDV) quasispecies subjected to mutagenesis by base and nucleoside analogues. RESULTS:Phylogenetic and PAQ analyses have revealed a highly dynamic variation of intrapopulation diversity of FMDV quasispecies. The population diversity first suffers striking expansions in the presence of mutagens and then compressions either when the presence of the mutagenic analogue was discontinued or when a mutation that decreased sensitivity to a mutagen was selected. The pattern of mutations found in the populations was in agreement with the behavior of the corresponding nucleotide analogues with FMDV in vitro. Mutations accumulated at preferred genomic sites, and dn/ds ratios indicate the operation of negative (or purifying) selection in populations subjected to mutagenesis. No evidence of unusually elevated genetic distances has been obtained for FMDV populations approaching extinction. CONCLUSION:Phylogenetic and PAQ analysis provide adequate procedures to describe the evolution of viral sequences subjected to lethal mutagenesis. These methods define the changes of intra-population structure more precisely than mutation frequencies and Shannon entropies. PAQ is very sensitive to variations of intrapopulation genetic distances. Strong negative (or purifying) selection operates in FMDV populations subjected to enhanced mutagenesis. The quantifications provide evidence that extinction does not imply unusual increases of intrapopulation complexity, in support of the lethal defection model of virus extinction.
| S-EPMC2515104 | biostudies-literature
Project description:Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/.
| S-EPMC1933138 | biostudies-literature
Project description:Despite environmental, social and ecological dependencies, emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential. RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen--as reflected by the recent emergence of SARS and Influenza for example. Here, we show how feature selection techniques can be used to reliably classify viral sequences by host species, and to identify the crucial minority of host-specific sites in pathogen genomic data. The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host. We illustrate the power of these methods by: 1) identifying the sites explaining SARS coronavirus differences between human, bat and palm civet samples; 2) showing how cross species jumps of rabies virus among bat populations can be readily identified; and 3) de novo identification of likely functional influenza host discriminant markers.
| S-EPMC3794897 | biostudies-literature
Project description:BackgroundLoss of CpG dinucleotides in genomic DNA through methylation-induced mutation is characteristic of vertebrates and plants. However, these and other eukaryotic phyla show a range of other dinucleotide frequency biases with currently uncharacterized underlying mutational or selection mechanisms. We developed a parameterized Markov process to identify what neighbour context-dependent mutations best accounted for patterns of dinucleotide frequency biases in genomic and cytoplasmically expressed mRNA sequences of different vertebrates, other eukaryotic groups and RNA viruses that infect them.ResultsConsistently, 11- to 14-fold greater frequencies of the methylation-associated mutation of C to T upstream of G (depicted as C?T,G) than other transitions best modelled dinucleotide frequencies in mammalian genomic DNA. However, further mutations such as G?T,T (5-fold greater than the default transversion rate) were required to account for the full spectrum of dinucleotide frequencies in mammalian sequence datasets. Consistent with modeling predictions for these two mutations, instability of both CpG and CpT dinucleotides was identified through SNP frequency analysis of human DNA sequences. Different sets of context-dependent mutations were modelled in other eukaryotes with non-methylated genomic DNA. In contrast to genomic DNA, best-fit models of dinucleotide frequencies in transcribed RNA sequences expressed in the cytoplasm from all organisms were dominated by mutations that eliminated UpA dinucleotides, observations consistent with cytoplasmically driven selection for mRNA stability. Surprisingly, mRNA sequences from organisms with methylated genomes showed evidence for additional selection against CpG through further context-dependent mutations (eg. C?A,G). Similar mutation or selection processes were identified among single-stranded mammalian RNA viruses; these potentially account for their previously described but unexplained under-representations of CpG and UpA dinucleotides.ConclusionsMethods we have developed identify mutational processes and selection pressures in organisms that provide new insights into nucleotide compositional constraints and a wealth of biochemical and evolutionarily testable predictions for the future.
| S-EPMC3829696 | biostudies-literature
Project description:BackgroundGene selection is an important part of microarray data analysis because it provides information that can lead to a better mechanistic understanding of an investigated phenomenon. At the same time, gene selection is very difficult because of the noisy nature of microarray data. As a consequence, gene selection is often performed with machine learning methods. The Random Forest method is particularly well suited for this purpose. In this work, four state-of-the-art Random Forest-based feature selection methods were compared in a gene selection context. The analysis focused on the stability of selection because, although it is necessary for determining the significance of results, it is often ignored in similar studies.ResultsThe comparison of post-selection accuracy of a validation of Random Forest classifiers revealed that all investigated methods were equivalent in this context. However, the methods substantially differed with respect to the number of selected genes and the stability of selection. Of the analysed methods, the Boruta algorithm predicted the most genes as potentially important.ConclusionsThe post-selection classifier error rate, which is a frequently used measure, was found to be a potentially deceptive measure of gene selection quality. When the number of consistently selected genes was considered, the Boruta algorithm was clearly the best. Although it was also the most computationally intensive method, the Boruta algorithm's computational demands could be reduced to levels comparable to those of other algorithms by replacing the Random Forest importance with a comparable measure from Random Ferns (a similar but simplified classifier). Despite their design assumptions, the minimal optimal selection methods, were found to select a high fraction of false positives.
| S-EPMC3897925 | biostudies-literature
Project description:Self-replicating single-stranded RNA viruses such as alphaviruses, flaviviruses, measles viruses, and rhabdoviruses provide efficient delivery and high-level expression of therapeutic genes due to their high capacity of RNA replication. This has contributed to novel approaches for therapeutic applications including vaccine development and gene therapy-based immunotherapy. Numerous studies in animal tumor models have demonstrated that self-replicating RNA viral vectors can generate antibody responses against infectious agents and tumor cells. Moreover, protection against challenges with pathogenic Ebola virus was obtained in primates immunized with alphaviruses and flaviviruses. Similarly, vaccinated animals have been demonstrated to withstand challenges with lethal doses of tumor cells. Furthermore, clinical trials have been conducted for several indications with self-amplifying RNA viruses. In this context, alphaviruses have been subjected to phase I clinical trials for a cytomegalovirus vaccine generating neutralizing antibodies in healthy volunteers, and for antigen delivery to dendritic cells providing clinically relevant antibody responses in cancer patients, respectively. Likewise, rhabdovirus particles have been subjected to phase I/II clinical trials showing good safety and immunogenicity against Ebola virus. Rhabdoviruses have generated promising results in phase III trials against Ebola virus. The purpose of this review is to summarize the achievements of using self-replicating RNA viruses for RNA therapy based on preclinical animal studies and clinical trials in humans.
| S-EPMC6321401 | biostudies-other