Epistasis and the adaptability of an RNA virus

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterised using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.

Epistasis and evolution: recent advances and an outlook for prediction

As organisms evolve, the effects of mutations change as a result of epistatic interactions with other mutations accumulated along the line of descent. This can lead to shifts in adaptability or robustness that ultimately shape subsequent evolution. Here, we review recent advances in measuring, modeling, and predicting epistasis along evolutionary trajectories, both in microbial cells and single proteins. We focus on simple patterns of global epistasis that emerge in this data, in which the effects of mutations can be predicted by a small number of variables. The emergence of these patterns offers promise for efforts to model epistasis and predict evolution.

Viral Fitness, Population Complexity, Host Interactions, and Resistance to Antiviral Agents

Fitness of viruses has become a standard parameter to quantify their adaptation to a biological environment. Fitness determinations for RNA viruses (and some highly variable DNA viruses) meet with several uncertainties. Of particular interest are those that arise from mutant spectrum complexity, absence of population equilibrium, and internal interactions among components of a mutant spectrum. Here, concepts, fitness measurements, limitations, and current views on experimental viral fitness landscapes are discussed. The effect of viral fitness on resistance to antiviral agents is covered in some detail since it constitutes a widespread problem in antiviral pharmacology, and a challenge for the design of effective antiviral treatments. Recent evidence with hepatitis C virus suggests the operation of mechanisms of antiviral resistance additional to the standard selection of drug-escape mutants. The possibility that high replicative fitness may be the driver of such alternative mechanisms is considered. New broad-spectrum antiviral designs that target viral fitness may curtail the impact of drug-escape mutants in treatment failures. We consider to what extent fitness-related concepts apply to coronaviruses and how they may affect strategies for COVID-19 prevention and treatment.

Prevalence and mechanisms of evolutionary contingency in human influenza H3N2 neuraminidase

Neuraminidase (NA) of human influenza H3N2 virus has evolved rapidly and been accumulating mutations for more than half-century. However, biophysical constraints that govern the evolutionary trajectories of NA remain largely elusive. Here, we show that among 70 natural mutations that are present in the NA of a recent human H3N2 strain, >10% are deleterious for an ancestral strain. By mapping the permissive mutations using combinatorial mutagenesis and next-generation sequencing, an extensive epistatic network is revealed. Biophysical and structural analyses further demonstrate that certain epistatic interactions can be explained by non-additive stability effect, which in turn modulates membrane trafficking and enzymatic activity of NA. Additionally, our results suggest that other biophysical mechanisms also contribute to epistasis in NA evolution. Overall, these findings not only provide mechanistic insights into the evolution of human influenza NA and elucidate its sequence-structure-function relationship, but also have important implications for the development of next-generation influenza vaccines.

An "Uncharacterized" Australian Virus Is the Earliest Known Example of Ross River Virus with Changes in the nsP3 Protein Associated with the Explosive Outbreak of Ross River Virus Infection in the Pacific Region from 1979 to 1980

Ross River virus recovered from a South Australian patient during an outbreak of epidemic polyarthritis in 1971 is the earliest known genome sequence with the duplicated 12-amino-acid motif in the nsP3 protein that was found in strains responsible for the outbreak of epidemic polyarthritis in the Pacific region from 1979 to 1980.

High-Order Epistasis and Functional Coupling of Infection Steps Drive Virus Evolution toward Independence from a Host Pathway

The phosphatidylinositol-4 kinase IIIβ (PI4KB)/oxysterol-binding protein (OSBP) family I pathway serves as an essential host pathway for the formation of viral replication complex for viral plus-strand RNA synthesis; however, poliovirus (PV) could evolve toward substantial independence from this host pathway with four mutations. Recessive epistasis of the two mutations (3A-R54W and 2B-F17L) is essential for viral RNA replication. Quantitative analysis of effects of the other two mutations (2B-Q20H and 2C-M187V) on each step of infection reveals functional couplings between viral replication, growth, and spread conferred by the 2B-Q20H mutation, while no enhancing effect was conferred by the 2C-M187V mutation. The effects of the 2B-Q20H mutation occur only via another recessive epistasis between the 3A-R54W/2B-F17L mutations. These mutations confer enhanced replication in PI4KB/OSBP-independent infection concomitantly with an increased ratio of viral plus-strand RNA to the minus-strand RNA. This work reveals the essential roles of the functional coupling and high-order, multi-tiered recessive epistasis in viral evolution toward independence from an obligatory host pathway.

IMPORTANCE Each virus has a different strategy for its replication, which requires different host factors. Enterovirus, a model RNA virus, requires host factors PI4KB and OSBP, which form an obligatory functional axis to support viral replication. In an experimental evolution system in vitro, virus mutants that do not depend on these host factors could arise only with four mutations. The two mutations (3A-R54W and 2B-F17L) are required for the replication but are not sufficient to support efficient infection. Another mutation (2B-Q20H) is essential for efficient spread of the virus. The order of introduction of the mutations in the viral genome is essential (known as “epistasis”), and functional couplings of infection steps (i.e., viral replication, growth, and spread) have substantial roles to show the effects of the 2B-Q20H mutation. These observations would provide novel insights into an evolutionary pathway of the virus to require host factors for infection.

Ongoing global and regional adaptive evolution of SARS-CoV-2

Understanding the trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high-quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the region of the nucleocapsid protein associated with nuclear localization signals (NLS) are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS-associated variants across multiple partitions rose to global prominence in March to July, during a period of stasis in terms of interregional diversity. Finally, beginning in July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.

Selection for cooperativity causes epistasis predominately between native contacts and enables epistasis-based structure reconstruction

Epistasis and cooperativity of folding both result from networks of energetic interactions in proteins. Epistasis results from energetic interactions among mutants, whereas cooperativity results from energetic interactions during folding that reduce the presence of intermediate states. The two concepts seem intuitively related, but it is unknown how they are related, particularly in terms of selection. To investigate their relationship, we simulated protein evolution under selection for cooperativity and separately under selection for epistasis. Strong selection for cooperativity created strong epistasis between contacts in the native structure but weakened epistasis between nonnative contacts. In contrast, selection for epistasis increased epistasis in both native and nonnative contacts and reduced cooperativity. Because epistasis can be used to predict protein structure only if it preferentially occurs in native contacts, this result indicates that selection for cooperativity may be key for predicting structure using epistasis. To evaluate this inference, we simulated the evolution of guanine nucleotide-binding protein (GB1) with and without cooperativity. With cooperativity, strong epistatic interactions clearly map out the native GB1 structure, while allowing the presence of intermediate states (low cooperativity) obscured the structure. This indicates that using epistasis measurements to reconstruct protein structure may be inappropriate for proteins with stable intermediates.

Global epistasis emerges from a generic model of a complex trait

Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread ‘microscopic’ epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the origin of this ‘global’ epistasis remains unknown. Here, we show that diminishing-returns and increasing-costs epistasis emerge generically as a consequence of pervasive microscopic epistasis. Our model predicts a specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis, which we confirm by reanalyzing existing data. We further show that the distribution of fitness effects takes on a universal form when epistasis is widespread and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.

Increased RNA virus population diversity improves adaptability

The replication machinery of most RNA viruses lacks proofreading mechanisms. As a result, RNA virus populations harbor a large amount of genetic diversity that confers them the ability to rapidly adapt to changes in their environment. In this work, we investigate whether further increasing the initial population diversity of a model RNA virus can improve adaptation to a single selection pressure, thermal inactivation. For this, we experimentally increased the diversity of coxsackievirus B3 (CVB3) populations across the capsid region. We then compared the ability of these high diversity CVB3 populations to achieve resistance to thermal inactivation relative to standard CVB3 populations in an experimental evolution setting. We find that viral populations with high diversity are better able to achieve resistance to thermal inactivation at both the temperature employed during experimental evolution as well as at a more extreme temperature. Moreover, we identify mutations in the CVB3 capsid that confer resistance to thermal inactivation, finding significant mutational epistasis. Our results indicate that even naturally diverse RNA virus populations can benefit from experimental augmentation of population diversity for optimal adaptation and support the use of such viral populations in directed evolution efforts that aim to select viruses with desired characteristics.

Ongoing Global and Regional Adaptive Evolution of SARS-CoV-2

Understanding the trends in SARS-CoV-2 evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the nuclear localization signal (NLS) associated region of the nucleocapsid protein are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS associated variants across multiple partitions rose to global prominence in March-July, during a period of stasis in terms of inter-regional diversity. Finally, beginning July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.

Single molecule, near full-length genome sequencing of dengue virus

Current methods for dengue virus (DENV) genome amplification, amplify parts of the genome in at least 5 overlapping segments and then combine the output to characterize a full genome. This process is laborious, costly and requires at least 10 primers per serotype, thus increasing the likelihood of PCR bias. We introduce an assay to amplify near full-length dengue virus genomes as intact molecules, sequence these amplicons with third generation “nanopore” technology without fragmenting and use the sequence data to differentiate within-host viral variants with a bioinformatics tool (Nano-Q). The new assay successfully generated near full-length amplicons from DENV serotypes 1, 2 and 3 samples which were sequenced with nanopore technology. Consensus DENV sequences generated by nanopore sequencing had over 99.5% pairwise sequence similarity to Illumina generated counterparts provided the coverage was > 100 with both platforms. Maximum likelihood phylogenetic trees generated from nanopore consensus sequences were able to reproduce the exact trees made from Illumina sequencing with a conservative 99% bootstrapping threshold (after 1000 replicates and 10% burn-in). Pairwise genetic distances of within host variants identified from the Nano-Q tool were less than that of between host variants, thus enabling the phylogenetic segregation of variants from the same host.

A synthesis of virus-vector associations reveals important deficiencies in studies on host and vector manipulation by plant viruses

Plant viruses face many challenges in agricultural environments. Although crop fields appear to be abundant resources for these pathogens, it may be difficult for viruses to "escape" from crop environments prior to host senescence or harvesting. One way for viruses to increase the odds of persisting outside of agricultural fields across seasons is by evolving traits that increase transmission opportunities between crops and wild plant communities. There is accumulating evidence that some viruses can achieve this by manipulating crop plant phenotypes in ways that enhance transmission by vectors. Putative manipulations occur through alteration of plant cues (color, size, texture, foliar volatiles, in-leaf metabolites, defenses, and leaf cuticles) that mediate vector orientation, feeding, and dispersal behaviors. Virus effects on host phenotypes are not uniform but appear to exhibit convergence depending on virus traits underlying transmission, particularly the duration of probing and feeding required to acquire and inoculate distinct types of plant viruses. This shared congruence in manipulation strategies and mechanisms across divergent virus lineages suggests that such effects may be adaptive. To discern if this is the case, researchers must consider molecular and environmental constraints on virus evolution, including those imposed by insect vectors from organismal to landscape scales. In this review, we synthesize applied research on vector-borne virus transmission in laboratory and field settings to identify the main factors determining transmission opportunities for plant viruses, and thus, selection pressure to evolve manipulative traits. We then examine these outputs in the context of studies reporting putative instances of plant virus manipulation. Our synthesis reveals important disconnects between virus manipulation studies and actual selection pressures imposed by vectors in real-world contexts.

Moderate Amounts of Epistasis are Not Evolutionarily Stable in Small Populations

High mutation rates select for the evolution of mutational robustness where populations inhabit flat fitness peaks with little epistasis, protecting them from lethal mutagenesis. Recent evidence suggests that a different effect protects small populations from extinction via the accumulation of deleterious mutations. In drift robustness, populations tend to occupy peaks with steep flanks and positive epistasis between mutations. However, it is not known what happens when mutation rates are high and population sizes are small at the same time. Using a simple fitness model with variable epistasis, we show that the equilibrium fitness has a minimum as a function of the parameter that tunes epistasis, implying that this critical point is an unstable fixed point for evolutionary trajectories. In agent-based simulations of evolution at finite mutation rate, we demonstrate that when mutations can change epistasis, trajectories with a subcritical value of epistasis evolve to decrease epistasis, while those with supercritical initial points evolve towards higher epistasis. These two fixed points can be identified with mutational and drift robustness, respectively.

Feature Learning of Virus Genome Evolution With the Nucleotide Skip-Gram Neural Network

Recent studies reveal that even the smallest genomes such as viruses evolve through complex and stochastic processes, and the assumption of independent alleles is not valid in most applications. Advances in sequencing technologies produce multiple time-point whole-genome data, which enable potential interactions between these alleles to be investigated empirically. To investigate these interactions, we represent alleles as distributed vectors that encode for relationships with other alleles in the course of evolution and apply artificial neural networks to time-sampled whole-genome datasets for feature learning. We build this platform using methods and algorithms derived from natural language processing (NLP), and we denote it as the nucleotide skip-gram neural network. We learn distributed vectors of alleles using the changes in allele frequency of echovirus 11 in the presence or absence of the disinfectant (ClO₂) from the experimental evolution data. Results from the training using a new open-source software TensorFlow show that the learned distributed vectors can be clustered using principal component analysis and hierarchical clustering to reveal a list of non-synonymous mutations that arise on the structural protein VP1 in connection to the candidate mutation for ClO₂ adaptation. Furthermore, this method can account for recombination rates by setting the extent of interactions as a biological hyper-parameter, and the results show that the most realistic scenario of mid-range interactions across the genome is most consistent with the previous studies.

Dynamic interactions between RNA viruses and human hosts unravelled by a decade of next generation sequencing

BACKGROUND

Next generation sequencing (NGS) methods have significantly contributed to a paradigm shift in genomic research for nearly a decade now. These methods have been useful in studying the dynamic interactions between RNA viruses and human hosts.

SCOPE OF THE REVIEW

In this review, we summarise and discuss key applications of NGS in studying the host - pathogen interactions in RNA viral infections of humans with examples.

MAJOR CONCLUSIONS

Use of NGS to study globally relevant RNA viral infections have revolutionized our understanding of the within host and between host evolution of these viruses. These methods have also been useful in clinical decision-making and in guiding biomedical research on vaccine design.

GENERAL SIGNIFICANCE

NGS has been instrumental in viral genomic studies in resolving within-host viral genomic variants and the distribution of nucleotide polymorphisms along the full-length of viral genomes in a high throughput, cost effective manner. In the future, novel advances such as long read, single molecule sequencing of viral genomes and simultaneous sequencing of host and pathogens may become the standard of practice in research and clinical settings. This will also bring on new challenges in big data analysis.

Engineered Functional Redundancy Relaxes Selective Constraints upon Endogenous Genes in Viral RNA Genomes

Functional redundancy, understood as the functional overlap of different genes, is a double-edge sword. At the one side, it is thought to serve as a robustness mechanism that buffers the deleterious effect of mutations hitting one of the redundant copies, thus resulting in pseudogenization. At the other side, it is considered as a source of genetic and functional innovation. In any case, genetically redundant genes are expected to show an acceleration in the rate of molecular evolution. Here, we tackle the role of functional redundancy in viral RNA genomes. To this end, we have evaluated the rates of compensatory evolution for deleterious mutations affecting an essential function, the suppression of RNA silencing plant defense, of tobacco etch potyvirus (TEV). TEV genotypes containing deleterious mutations in presence/absence of engineered functional redundancy were evolved and the pattern of fitness and pathogenicity recovery evaluated. Genetically redundant genotypes suffered less from the effect of deleterious mutations and showed relatively minor changes in fitness and pathogenicity. By contrast, nongenetically redundant genotypes had very low fitness and pathogenicity at the beginning of the evolution experiment that were fully recovered by the end. At the molecular level, the outcome depended on the combination of the actual mutations being compensated and the presence/absence of functional redundancy. Reversions to wild-type alleles were the norm in the nonredundant genotypes while redundant ones either did not fix any mutation at all or showed a higher nonsynonymous mutational load.

Experimental Studies of Evolutionary Dynamics in Microbes

Evolutionary dynamics in laboratory microbial evolution experiments can be surprisingly complex. In the past two decades, observations of these dynamics have challenged simple models of adaptation and have shown that clonal interference, hitchhiking, ecological diversification, and contingency are widespread. In recent years, advances in high-throughput strain maintenance and phenotypic assays, the dramatically reduced cost of genome sequencing, and emerging methods for lineage barcoding have made it possible to observe evolutionary dynamics at unprecedented resolution. These new methods can now begin to provide detailed measurements of key aspects of fitness landscapes and of evolutionary outcomes across a range of systems. These measurements can highlight challenges to existing theoretical models and guide new theoretical work towards the complications that are most widely important.

Evolutionary Determinants of Host and Vector Manipulation by Plant Viruses

Plant viruses possess adaptations for facilitating acquisition, retention, and inoculation by vectors. Until recently, it was hypothesized that these adaptations are limited to virus proteins that enable virions to bind to vector mouthparts or invade their internal tissues. However, increasing evidence suggests that viruses can also manipulate host plant phenotypes and vector behaviors in ways that enhance their own transmission. Manipulation of vector-host interactions occurs through virus effects on host cues that mediate vector orientation, feeding, and dispersal behaviors, and thereby, the probability of virus transmission. Effects on host phenotypes vary by pathosystem but show a remarkable degree of convergence among unrelated viruses whose transmission is favored by the same vector behaviors. Convergence based on transmission mechanism, rather than phylogeny, supports the hypothesis that virus effects are adaptive and not just by-products of infection. Based on this, it has been proposed that viruses manipulate hosts through multifunctional proteins that facilitate exploitation of host resources and elicitation of specific changes in host phenotypes. But this proposition is rarely discussed in the context of the numerous constraints on virus evolution imposed by molecular and environmental factors, which figure prominently in research on virus-host interactions not dealing with host manipulation. To explore the implications of this oversight, we synthesized available literature to identify patterns in virus effects among pathogens with shared transmission mechanisms and discussed the results of this synthesis in the context of molecular and environmental constraints on virus evolution, limitations of existing studies, and prospects for future research.

Translational regulation of ribosomal protein S15 drives characteristic patterns of protein-mRNA epistasis

Do coding and regulatory segments of a gene co-evolve with each-other? Seeking answers to this question, here we analyze the case of Escherichia coli ribosomal protein S15, that represses its own translation by specifically binding its messenger RNA (rpsO mRNA) and stabilizing a pseudoknot structure at the upstream untranslated region, thus trapping the ribosome into an incomplete translation initiation complex. In the absence of S15, ribosomal protein S1 recognizes rpsO and promotes translation by melting this very pseudoknot. We employ a robust statistical method to detect signatures of positive epistasis between residue site pairs and find that biophysical constraints of translational regulation (S15-rpsO and S1-rpsO recognition, S15-mediated rpsO structural rearrangement, and S1-mediated melting) are strong predictors of positive epistasis. Transforming the epistatic pairs into a network, we find that signatures of two different, but interconnected regulatory cascades are imprinted in the sequence-space and can be captured in terms of two dense network modules that are sparsely connected to each other. This network topology further reflects a general principle of how functionally coupled components of biological networks are interconnected. These results depict a model case, where translational regulation drives characteristic residue-level epistasis-not only between a protein and its own mRNA but also between a protein and the mRNA of an entirely different protein.

Inferring genetic interactions from comparative fitness data

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

Comparative analysis of protein evolution in the genome of pre-epidemic and epidemic Zika virus

Zika virus (ZIKV) causes microcephaly in congenital infection, neurological disorders, and poor pregnancy outcome and no vaccine is available for use in humans or approved. Although ZIKV was first discovered in 1947, the exact mechanism of virus replication and pathogenesis remains unknown. Recent outbreaks of Zika virus in the Americas clearly suggest a human-mosquito cycle or urban cycle of transmission. Understanding the conserved and adaptive features in the evolution of ZIKV genome will provide a hint on the mechanism of ZIKV adaptation to a new cycle of transmission. Here, we show comprehensive analysis of protein evolution of ZIKV strains including the current 2015-16 outbreak. To identify the constraints on ZIKV evolution, selection pressure at individual codons, immune epitopes and co-evolving sites were analyzed. Phylogenetic trees show that the ZIKV strains of the Asian genotype form distinct cluster and share a common ancestor with African genotype. The TMRCA (Time to the Most Recent Common Ancestor) for the Asian lineage and the subsequently evolved Asian human strains was calculated at 88 and 34years ago, respectively. The proteome of current 2015/16 epidemic ZIKV strains of Asian genotype was found to be genetically conserved due to genome-wide negative selection, with limited positive selection. We identified a total of 16 amino acid substitutions in the epidemic and pre-epidemic strains from human, mosquito, and monkey hosts. Negatively selected amino acid sites of Envelope protein (E-protein) (positions 69, 166, and 174) and NS5 (292, 345, and 587) were located in central dimerization domains and C-terminal RNA-directed RNA polymerase regions, respectively. The predicted 137 (92 CD4 TCEs; 45 CD8 TCEs) immunogenic peptide chains comprising negatively selected amino acid sites can be considered as suitable target for sub-unit vaccine development, as these sites are less likely to generate immune-escape variants due to strong functional constrains operating on them. The targeted changes at the amino acid level may contribute to better adaptation of ZIKV strains to human-mosquito cycle or urban cycle of transmission.

Dynamics of molecular evolution in RNA virus populations depend on sudden versus gradual environmental change

Understanding the dynamics of molecular adaptation is a fundamental goal of evolutionary biology. While adaptation to constant environments has been well characterized, the effects of environmental complexity remain seldom studied. One simple but understudied factor is the rate of environmental change. Here we used experimental evolution with RNA viruses to investigate whether evolutionary dynamics varied based on the rate of environmental turnover. We used whole-genome next-generation sequencing to characterize evolutionary dynamics in virus populations adapting to a sudden versus gradual shift onto a novel host cell type. In support of theoretical models, we found that when populations evolved in response to a sudden environmental change, mutations of large beneficial effect tended to fix early, followed by mutations of smaller beneficial effect; as predicted, this pattern broke down in response to a gradual environmental change. Early mutational steps were highly parallel across replicate populations in both treatments. The fixation of single mutations was less common than sweeps of associated "cohorts" of mutations, and this pattern intensified when the environment changed gradually. Additionally, clonal interference appeared stronger in response to a gradual change. Our results suggest that the rate of environmental change is an important determinant of evolutionary dynamics in asexual populations.

Large-Scale Phylogenomic Analysis Reveals the Complex Evolutionary History of Rabies Virus in Multiple Carnivore Hosts

The natural evolution of rabies virus (RABV) provides a potent example of multiple host shifts and an important opportunity to determine the mechanisms that underpin viral emergence. Using 321 genome sequences spanning an unprecedented diversity of RABV, we compared evolutionary rates and selection pressures in viruses sampled from multiple primary host shifts that occurred on various continents. Two major phylogenetic groups, bat-related RABV and dog-related RABV, experiencing markedly different evolutionary dynamics were identified. While no correlation between time and genetic divergence was found in bat-related RABV, the evolution of dog-related RABV followed a generally clock-like structure, although with a relatively low evolutionary rate. Subsequent molecular clock dating indicated that dog-related RABV likely underwent a rapid global spread following the intensification of intercontinental trade starting in the 15^th century. Strikingly, although dog RABV has jumped to various wildlife species from the order Carnivora, we found no clear evidence that these host-jumping events involved adaptive evolution, with RABV instead characterized by strong purifying selection, suggesting that ecological processes also play an important role in shaping patterns of emergence. However, specific amino acid changes were associated with the parallel emergence of RABV in ferret-badgers in Asia, and some host shifts were associated with increases in evolutionary rate, particularly in the ferret-badger and mongoose, implying that changes in host species can have important impacts on evolutionary dynamics.

Zoonoses account for most recently emerged infectious diseases of humans, although little is known about the evolutionary mechanisms involved in cross-species virus transmission. Understanding the evolutionary patterns and processes that underpin such cross-species transmission is of importance for predicting the spread of zoonotic infections, and hence to their ultimate control. We present a large-scale and detailed reconstruction of the evolutionary history of rabies virus (RABV) in domestic and wildlife animal species. RABV is of particular interest as it is capable of infecting many mammals but, paradoxically, is only maintained in distinct epidemiological cycles associated with animal species from the orders Carnivora and Chiroptera. We show that bat-related RABV and dog-related RABV have experienced very different evolutionary dynamics, and that host jumps are sometimes characterized by significant increases in evolutionary rate. Among Carnivora, the association between RABV and particular host species most likely arose from a combination of the historical human-mediated spread of the virus and jumps into new primary host species. In addition, we show that changes in host species are associated with multiple evolutionary pathways including the occurrence of host-specific parallel evolution. Overall, our data indicate that the establishment of dog-related RABV in new carnivore hosts may only require subtle adaptive evolution.

Reconstruction of Haplotype-Blocks Selected during Experimental Evolution

The genetic analysis of experimentally evolving populations typically relies on short reads from pooled individuals (Pool-Seq). While this method provides reliable allele frequency estimates, the underlying haplotype structure remains poorly characterized. With small population sizes and adaptive variants that start from low frequencies, the interpretation of selection signatures in most Evolve and Resequencing studies remains challenging. To facilitate the characterization of selection targets, we propose a new approach that reconstructs selected haplotypes from replicated time series, using Pool-Seq data. We identify selected haplotypes through the correlated frequencies of alleles carried by them. Computer simulations indicate that selected haplotype-blocks of several Mb can be reconstructed with high confidence and low error rates, even when allele frequencies change only by 20% across three replicates. Applying this method to real data from D. melanogaster populations adapting to a hot environment, we identify a selected haplotype-block of 6.93 Mb. We confirm the presence of this haplotype-block in evolved populations by experimental haplotyping, demonstrating the power and accuracy of our haplotype reconstruction from Pool-Seq data. We propose that the combination of allele frequency estimates with haplotype information will provide the key to understanding the dynamics of adaptive alleles.

Constrained evolvability of interferon suppression in an RNA virus

Innate immunity responses controlled by interferon (IFN) are believed to constitute a major selective pressure shaping viral evolution. Viruses encode a variety of IFN suppressors, but these are often multifunctional proteins that also play essential roles in other steps of the viral infection cycle, possibly limiting their evolvability. Here, we experimentally evolved a vesicular stomatitis virus (VSV) mutant carrying a defect in the matrix protein (M∆51) that abolishes IFN suppression and that has been previously used in the context of oncolytic virotherapy. Serial transfers of this virus in normal, IFN-secreting cells led to a modest recovery of IFN blocking capacity and to weak increases in viral fitness. Full-genome ultra-deep sequencing and phenotypic analysis of population variants revealed that the anti-IFN function of the matrix protein was not restored, and that the Mdelta51 defect was instead compensated by changes in the viral phosphoprotein. We also show that adaptation to IFN-secreting cells can be driven by the selection of fast-growing viruses with no IFN suppression capacity, and that these population variants can be trans-complemented by other, IFN-suppressing variants. Our results thus suggest that virus-virus interactions and alternative strategies of innate immunity evasion can determine the evolution of IFN suppression in a virus.

Coupling high-throughput genetics with phylogenetic information reveals an epistatic interaction on the influenza A virus M segment

Background

Epistasis is one of the central themes in viral evolution due to its importance in drug resistance, immune escape, and interspecies transmission. However, there is a lack of experimental approach to systematically probe for epistatic residues.

Results

By utilizing the information from natural occurring sequences and high-throughput genetics, this study established a novel strategy to identify epistatic residues. The rationale is that a substitution that is deleterious in one strain may be prevalent in nature due to the presence of a naturally occurring compensatory substitution. Here, high-throughput genetics was applied to influenza A virus M segment to systematically identify deleterious substitutions. Comparison with natural sequence variation showed that a deleterious substitution M1 Q214H was prevalent in circulating strains. A coevolution analysis was then performed and indicated that M1 residues 121, 207, 209, and 214 naturally coevolved as a group. Subsequently, we experimentally validated that M1 A209T was a compensatory substitution for M1 Q214H.

Conclusions

This work provided a proof-of-concept to identify epistatic residues by coupling high-throughput genetics with phylogenetic information. In particular, we were able to identify an epistatic interaction between M1 substitutions A209T and Q214H. This analytic strategy can potentially be adapted to study any protein of interest, provided that the information on natural sequence variants is available.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2358-7) contains supplementary material, which is available to authorized users.

Elucidating the molecular architecture of adaptation via evolve and resequence experiments

Evolve and resequence (E&R) experiments use experimental evolution to adapt populations to a novel environment, then next-generation sequencing to analyse genetic changes. They enable molecular evolution to be monitored in real time on a genome-wide scale. Here, we review the field of E&R experiments across diverse systems, ranging from simple non-living RNA to bacteria, yeast and the complex multicellular organism Drosophila melanogaster. We explore how different evolutionary outcomes in these systems are largely consistent with common population genetics principles. Differences in outcomes across systems are largely explained by different starting population sizes, levels of pre-existing genetic variation, recombination rates and adaptive landscapes. We highlight emerging themes and inconsistencies that future experiments must address.

The rule of declining adaptability in microbial evolution experiments

One of the most recurrent observations after two decades of microbial evolution experiments regards the dynamics of fitness change. In a given environment, low-fitness genotypes are recurrently observed to adapt faster than their more fit counterparts. Since adaptation is the main macroscopic outcome of Darwinian evolution, studying its patterns of change could potentially provide insight into key issues of evolutionary theory, from fixation dynamics to the genetic architecture of organisms. Here, we re-analyze several published datasets from experimental evolution with microbes and show that, despite large differences in the origin of the data, a pattern of inverse dependence of adaptability with fitness clearly emerges. In quantitative terms, it is remarkable to observe little if any degree of idiosyncrasy across systems as diverse as virus, bacteria and yeast. The universality of this phenomenon suggests that its emergence might be understood from general principles, giving rise to the exciting prospect that evolution might be statistically predictable at the macroscopic level. We discuss these possibilities in the light of the various theories of adaptation that have been proposed and delineate future directions of research.

The movement protein (NSm) of Tomato spotted wilt virus is the avirulence determinant in the tomato Sw-5 gene-based resistance

The avirulence determinant triggering the resistance conferred by the tomato gene Sw-5 against Tomato spotted wilt virus (TSWV) is still unresolved. Sequence comparison showed two substitutions (C118Y and T120N) in the movement protein NSm present only in TSWV resistance-breaking (RB) isolates. In this work, transient expression of NSm of three TSWV isolates [RB1 (T120N), RB2 (C118Y) and non-resistance-breaking (NRB)] in Nicotiana benthamiana expressing Sw-5 showed a hypersensitive response (HR) only with NRB. Exchange of the movement protein of Alfalfa mosaic virus (AMV) with NSm supported cell-to-cell and systemic transport of the chimeric AMV RNAs into N. tabacum with or without Sw-5, except for the constructs with NBR when Sw-5 was expressed, although RB2 showed reduced cell-to-cell transport. Mutational analysis revealed that N120 was sufficient to avoid the HR, but the substitution V130I was required for systemic transport. Finally, co-inoculation of RB and NRB AMV chimeric constructs showed different prevalence of RB or NBR depending on the presence or absence of Sw-5. These results indicate that NSm is the avirulence determinant for Sw-5 resistance, and mutations C118Y and T120N are responsible for resistance breakdown and have a fitness penalty in the context of the heterologous AMV system.

The environment affects epistatic interactions to alter the topology of an empirical fitness landscape

The fitness effect of mutations can be influenced by their interactions with the environment, other mutations, or both. Previously, we constructed 32 ( = 2⁵) genotypes that comprise all possible combinations of the first five beneficial mutations to fix in a laboratory-evolved population of Escherichia coli. We found that (i) all five mutations were beneficial for the background on which they occurred; (ii) interactions between mutations drove a diminishing returns type epistasis, whereby epistasis became increasingly antagonistic as the expected fitness of a genotype increased; and (iii) the adaptive landscape revealed by the mutation combinations was smooth, having a single global fitness peak. Here we examine how the environment influences epistasis by determining the interactions between the same mutations in two alternative environments, selected from among 1,920 screened environments, that produced the largest increase or decrease in fitness of the most derived genotype. Some general features of the interactions were consistent: mutations tended to remain beneficial and the overall pattern of epistasis was of diminishing returns. Other features depended on the environment; in particular, several mutations were deleterious when added to specific genotypes, indicating the presence of antagonistic interactions that were absent in the original selection environment. Antagonism was not caused by consistent pleiotropic effects of individual mutations but rather by changing interactions between mutations. Our results demonstrate that understanding adaptation in changing environments will require consideration of the combined effect of epistasis and pleiotropy across environments.

The fitness effect of beneficial mutations can depend on how they interact with their genetic and external environment. The form of these interactions is important because it can alter adaptive outcomes, selecting for or against certain combinations of beneficial mutations. Here, we examine how interactions between beneficial mutations favored during adaptation of a lab strain of Escherichia coli to one simple environment are altered when the strain is grown in two novel environments. We found that fitness effects were greatly influenced by both the genetic and external environments. In several instances a change in environment reversed the effect of a mutation from beneficial to deleterious or caused combinations of beneficial mutations to become deleterious. Our results suggest that a complex or fluctuating environment may favor combinations of mutations whose interactions may be less sensitive to external conditions.

Evolution at increased error rate leads to the coexistence of multiple adaptive pathways in an RNA virus

Background

When beneficial mutations present in different genomes spread simultaneously in an asexual population, their fixation can be delayed due to competition among them. This interference among mutations is mainly determined by the rate of beneficial mutations, which in turn depends on the population size, the total error rate, and the degree of adaptation of the population. RNA viruses, with their large population sizes and high error rates, are good candidates to present a great extent of interference. To test this hypothesis, in the current study we have investigated whether competition among beneficial mutations was responsible for the prolonged presence of polymorphisms in the mutant spectrum of an RNA virus, the bacteriophage Qβ, evolved during a large number of generations in the presence of the mutagenic nucleoside analogue 5-azacytidine.

Results

The analysis of the mutant spectra of bacteriophage Qβ populations evolved at artificially increased error rate shows a large number of polymorphic mutations, some of them with demonstrated selective value. Polymorphisms distributed into several evolutionary lines that can compete among them, making it difficult the emergence of a defined consensus sequence. The presence of accompanying deleterious mutations, the high degree of recurrence of the polymorphic mutations, and the occurrence of epistatic interactions generate a highly complex interference dynamics.

Conclusions

Interference among beneficial mutations in bacteriophage Qβ evolved at increased error rate permits the coexistence of multiple adaptive pathways that can provide selective advantages by different molecular mechanisms. In this way, interference can be seen as a positive factor that allows the exploration of the different local maxima that exist in rugged fitness landscapes.

Cancer in light of experimental evolution

Cancer initiation, progression, and the emergence of therapeutic resistance are evolutionary phenomena of clonal somatic cell populations. Studies in microbial experimental evolution and the theoretical work inspired by such studies are yielding deep insights into the evolutionary dynamics of clonal populations, yet there has been little explicit consideration of the relevance of this rapidly growing field to cancer biology. Here, we examine how the understanding of mutation, selection, and spatial structure in clonal populations that is emerging from experimental evolution may be applicable to cancer. Along the way, we discuss some significant ways in which cancer differs from the model systems used in experimental evolution. Despite these differences, we argue that enhanced prediction and control of cancer may be possible using ideas developed in the context of experimental evolution, and we point out some prospects for future research at the interface between these traditionally separate areas.

Epistasis from functional dependence of fitness on underlying traits

Epistasis between mutations in two genes is thought to reflect an interdependence of their functions. While sometimes epistasis is predictable using mechanistic models, its roots seem, in general, hidden in the complex architecture of biological networks. Here, we ask how epistasis can be quantified based on the mathematical dependence of a system-level trait (e.g. fitness) on lower-level traits (e.g. molecular or cellular properties). We first focus on a model in which fitness is the difference between a benefit and a cost trait, both pleiotropically affected by mutations. We show that despite its simplicity, this model can be used to analytically predict certain properties of the ensuing distribution of epistasis, such as a global negative bias, resulting in antagonism between beneficial mutations, and synergism between deleterious ones. We next extend these ideas to derive a general expression for epistasis given an arbitrary functional dependence of fitness on other traits. This expression demonstrates how epistasis relative to fitness can emerge despite the absence of epistasis relative to lower level traits, leading to a formalization of the concept of independence between biological processes. Our results suggest that epistasis may be largely shaped by the pervasiveness of pleiotropic effects and modular organization in biological networks.

Advances in plant virus evolution: translating evolutionary insights into better disease management

Recent studies in plant virus evolution are revealing that genetic structure and behavior of virus and viroid populations can explain important pathogenic properties of these agents, such as host resistance breakdown, disease severity, and host shifting, among others. Genetic variation is essential for the survival of organisms. The exploration of how these subcellular parasites generate and maintain a certain frequency of mutations at the intra- and inter-host levels is revealing novel molecular virus-plant interactions. They emphasize the role of host environment in the dynamic genetic composition of virus populations. Functional genomics has identified host factors that are transcriptionally altered after virus infections. The analyses of these data by means of systems biology approaches are uncovering critical plant genes specifically targeted by viruses during host adaptation. Also, a next-generation resequencing approach of a whole virus genome is opening new avenues to study virus recombination and the relationships between intra-host virus composition and pathogenesis. Altogether, the analyzed data indicate that systematic disruption of some specific parameters of evolving virus populations could lead to more efficient ways of disease prevention, eradication, or tolerable virus-plant coexistence.

Cellular effects and epistasis among three determinants of adaptation in experimental populations of Saccharomyces cerevisiae

Epistatic interactions in which the phenotypic effect of an allele is conditional on its genetic background have been shown to play a central part in various evolutionary processes. In a previous study (J. B. Anderson et al., Curr. Biol. 20:1383-1388, 2010; J. R. Dettman, C. Sirjusingh, L. M. Kohn, and J. B. Anderson, Nature 447:585-588, 2007), beginning with a common ancestor, we identified three determinants of fitness as mutant alleles (each designated with the letter "e") that arose in replicate Saccharomyces cerevisiae populations propagated in two different environments, a low-glucose and a high-salt environment. In a low-glucose environment, MDS3e and MKT1e interacted positively to confer a fitness advantage. Also, PMA1e from a high-salt environment interacted negatively with MKT1e in a low-glucose environment, an example of a Dobzhansky-Muller incompatibility that confers reproductive isolation. Here we showed that the negative interaction between PMA1e and MKT1e is mediated by alterations in intracellular pH, while the positive interaction between MDS3e and MKT1e is mediated by changes in gene expression affecting glucose transporter genes. We specifically addressed the evolutionary significance of the positive interaction by showing that the presence of the MDS3 mutation is a necessary condition for the spread and fixation of the new mutations at the identical site in MKT1. The expected mutations in MKT1 rose to high frequencies in two of three experimental populations carrying MDS3e but not in any of three populations carrying the ancestral allele. These data show how positive and negative epistasis can contribute to adaptation and reproductive isolation.

Negative epistasis between beneficial mutations in an evolving bacterial population

Epistatic interactions between mutations play a prominent role in evolutionary theories. Many studies have found that epistasis is widespread, but they have rarely considered beneficial mutations. We analyzed the effects of epistasis on fitness for the first five mutations to fix in an experimental population of Escherichia coli. Epistasis depended on the effects of the combined mutations--the larger the expected benefit, the more negative the epistatic effect. Epistasis thus tended to produce diminishing returns with genotype fitness, although interactions involving one particular mutation had the opposite effect. These data support models in which negative epistasis contributes to declining rates of adaptation over time. Sign epistasis was rare in this genome-wide study, in contrast to its prevalence in an earlier study of mutations in a single gene.

Fitness recovery and compensatory evolution in natural mutant lines of C. elegans

Deleterious mutation accumulation plays a central role in evolutionary genetics, conservation biology, human health, and evolutionary medicine (e.g., methods of viral attenuation for live vaccines). It is therefore important to understand whether and how quickly populations with accumulated deleterious mutational loads can recover fitness through adaptive evolution. We used laboratory experimental evolution with four long-term mutation-accumulation (MA) lines of Caenorhabditis elegans nematodes to study the dynamics of such fitness evolution. We previously showed that when homozygous mutant populations are evolved in large population sizes, they can rapidly achieve wild-type fitness through the accumulation of new beneficial or compensatory epistatic mutations. Here, we expand this approach to demonstrate that when replicate lineages are initiated from the same mutant genotype, phenotypic evolution is only sometimes repeatable. MA genotypes that recovered ancestral fitness in the previous experiment did not always do so here. Further, the pattern of adaptive evolution in independently evolved replicates was contingent upon the MA genotype and varied among fitness-related traits. Our findings suggest that new beneficial mutations can drive rapid fitness evolution, but that the adaptive process is rendered somewhat unpredictable by its susceptibility to chance events and sensitivity to the evolutionary history of the starting population.

Prevalence of epistasis in the evolution of influenza A surface proteins

The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs.

Epistasis describes non-additive interactions among genetic sites: the consequence of a mutation at one site may depend on the status of the genome at other sites. In an extreme case, a mutation may have no effect if it arises on one genetic background, but a strong effect on another background. Epistatic mutations in viruses and bacteria that live under severe conditions, such as antibiotic treatments or immune pressure, often allow pathogens to develop drug resistance or escape the immune system. In this paper we develop a new phylogenetic method for detecting epistasis, and we apply this method to the surface proteins of the influenza A virus, which are important targets of the immune system and drug treatments. The authors identify and characterize hundreds of epistatic mutations in these proteins. Among those identified, we find the specific epistatic mutations that were recently shown, experimentally, to confer resistance to the drug Tamiflu. The results of this study may help to predict the course of influenza's antigenic evolution and to select more appropriate vaccines and drugs.

X-autosome incompatibilities in Drosophila melanogaster: tests of Haldane's rule and geographic patterns within species

Substantial genetic variation exists in natural populations of Drosophila melanogaster. This segregating variation includes alleles at different loci that interact to cause lethality or sterility (synthetic incompatibilities). Fitness epistasis in natural populations has important implications for speciation and the rate of adaptive evolution. To assess the prevalence of epistatic fitness interactions, we placed naturally occurring X chromosomes into genetic backgrounds derived from different geographic locations. Considerable amounts of synthetic incompatibilities were observed between X chromosomes and autosomes: greater than 44% of all combinations were either lethal or sterile. Sex-specific lethality and sterility were also tested to determine whether Haldane's rule holds for within-species variation. Surprisingly, we observed an excess of female sterility in genotypes that were homozygous, but not heterozygous, for the X chromosome. The recessive nature of these incompatibilities is similar to that predicted for incompatibilities underlying Haldane's rule. Our study also found higher levels of sterility and lethality for genomes that contain chromosomes from different geographical regions. These findings are consistent with the view that genomes are coadapted gene complexes and that geography affects the likelihood of epistatic fitness interactions.

Simple genomes, complex interactions: epistasis in RNA virus

Owed to their reduced size and low number of proteins encoded, RNA viruses and other subviral pathogens are often considered as being genetically too simple. However, this structural simplicity also creates the necessity for viral RNA sequences to encode for more than one protein and for proteins to carry out multiple functions, all together resulting in complex patterns of genetic interactions. In this work we will first review the experimental studies revealing that the architecture of viral genomes is dominated by antagonistic interactions among loci. Second, we will also review mathematical models and provide a description of computational tools for the study of RNA virus dynamics and evolution. As an application of these tools, we will finish this review article by analyzing a stochastic bit-string model of in silico virus replication. This model analyzes the interplay between epistasis and the mode of replication on determining the population load of deleterious mutations. The model suggests that, for a given mutation rate, the deleterious mutational load is always larger when epistasis is predominantly antagonistic than when synergism is the rule. However, the magnitude of this effect is larger if replication occurs geometrically than if it proceeds linearly.

The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts

Despite efforts from a range of disciplines, our ability to predict and combat the evolution of antibiotic resistance in pathogenic bacteria is limited. This is because resistance evolution involves a complex interplay between the specific drug, bacterial genetics and both natural and treatment ecology. Incorporating details of the molecular mechanisms of drug resistance and ecology into evolutionary models has proved useful in predicting the dynamics of resistance evolution. However, putting these models to practical use will require extensive collaboration between mathematicians, molecular biologists, evolutionary ecologists and clinicians.

On the classification of epistatic interactions

Modern genomewide association studies are characterized by the problem of "missing heritability." Epistasis, or genetic interaction, has been suggested as a possible explanation for the relatively small contribution of single significant associations to the fraction of variance explained. Of particular concern to investigators of genetic interactions is how to best represent and define epistasis. Previous studies have found that the use of different quantitative definitions for genetic interaction can lead to different conclusions when constructing genetic interaction networks and when addressing evolutionary questions. We suggest that instead, multiple representations of epistasis, or epistatic "subtypes," may be valid within a given system. Selecting among these epistatic subtypes may provide additional insight into the biological and functional relationships among pairs of genes. In this study, we propose maximum-likelihood and model selection methods in a hypothesis-testing framework to choose epistatic subtypes that best represent functional relationships for pairs of genes on the basis of fitness data from both single and double mutants in haploid systems. We gauge the performance of our method with extensive simulations under various interaction scenarios. Our approach performs reasonably well in detecting the most likely epistatic subtype for pairs of genes, as well as in reducing bias when estimating the epistatic parameter (epsilon). We apply our approach to two available data sets from yeast (Saccharomyces cerevisiae) and demonstrate through overlap of our identified epistatic pairs with experimentally verified interactions and functional links that our results are likely of biological significance in understanding interaction mechanisms. We anticipate that our method will improve detection of epistatic interactions and will help to unravel the mysteries of complex biological systems.

Compensatory molecular evolution of HC-Pro, an RNA-silencing suppressor from a plant RNA virus

RNA silencing is a eukaryotic mechanism involved in several cellular processes, one example being a sequence-specific antiviral defense. Many plant viruses have developed counterdefensive proteins that in many instances are multifunctional, such as helper component protease (HC-Pro) of Tobacco etch virus (TEV). In a previous work, a collection of mutants with amino acid replacements in TEV HC-Pro was generated, and their effects in the capacity of suppressing RNA silencing were quantified in a transient expression assay. In this study, three mutations that caused a reduction in suppression activity and three that increased it were used to create replicate experimental lineages that were evolved through serial passages. We have evaluated the number of genotypic changes that occurred during evolution in HC-Pro and their phenotypic effects on virus viability, virulence, and suppression of RNA silencing. In no instance did the original mutation revert to the wildtype (WT) sequence. In several cases, fixed mutations were canonical compensatory changes, returning the suppressor activity to the WT HC-Pro value, pointing to the existence of stabilizing selection pressures and pleiotropic effects of the introduced original mutations. However, in other instances, the fixed mutations were overcompensatory, driving the activity of the mutant beyond the optimal value. Negative epistatic effects among beneficial mutations as well as decompensatory epistasis also play an important role during compensatory evolution of RNA-silencing suppression.

Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region

Fitness epistasis, the interaction among alleles at different loci in their effects on fitness, has potentially important consequences for adaptive evolution. We investigated fitness epistasis among amino acids of a functionally important region of the human immunodeficiency virus type 1 (HIV-1) exterior envelope glycoprotein (gp120). Seven mutations putatively involved in the adaptation of the second conserved to third variable protein region (C2-V3) to the use of an alternative host-cell chemokine coreceptor (CXCR4) for cell entry were engineered singly and in combinations on the wild-type genetic background and their effects on viral infectivity were measured. Epistasis was found to be common and complex, involving not only pairwise interactions, but also higher-order interactions. Interactions could also be surprisingly strong, changing fitness by more than 9 orders of magnitude, which is explained by some single mutations being practically lethal. A consequence of the observed epistasis is that many of the minimum-length mutational trajectories between the wild type and the mutant with highest fitness on cells expressing the alternative coreceptor are selectively inaccessible. These results may help explain the difficulty of evolving viruses that use the alternative coreceptor in culture and the delayed evolution of this phenotype in natural infection. Knowledge of common, complex, and strong fitness interactions among amino acids is necessary for a full understanding of protein evolution.

Predicting epistasis: an experimental test of metabolic control theory with bacterial transcription and translation

Epistatic interactions between mutations are thought to play a crucial role in a number of evolutionary processes, including adaptation and sex. Evidence for epistasis is abundant, but tests of general theoretical models that can predict epistasis are lacking. In this study, I test the ability of metabolic control theory to predict epistasis using a novel experimental approach that combines phenotypic and genetic perturbations of enzymes involved in gene expression and protein synthesis in the bacterium Pseudomonas aeruginosa. These experiments provide experimental support for two key predictions of metabolic control theory: (i) epistasis between genes involved in the same pathway is antagonistic; (ii) epistasis becomes increasingly antagonistic as mutational severity increases. Metabolic control theory is a general theory that applies to any set of genes that are involved in the same linear processing chain, not just metabolic pathways, and I argue that this theory is likely to have important implications for predicting epistasis between functionally coupled genes, such as those involved in antibiotic resistance. Finally, this study highlights the fact that phenotypic manipulations of gene activity provide a powerful method for studying epistasis that complements existing genetic methods.

Mixed infections of Pepino mosaic virus strains modulate the evolutionary dynamics of this emergent virus

Pepino mosaic virus (PepMV) is an emerging pathogen that causes severe economic losses in tomato crops (Solanum lycopersicum L.) in the Northern hemisphere, despite persistent attempts of control. In fact, it is considered one of the most significant viral diseases for tomato production worldwide, and it may constitute a good model for the analysis of virus emergence in crops. We have combined a population genetics approach with an analysis of in planta properties of virus strains to explain an observed epidemiological pattern. Hybridization analysis showed that PepMV populations are composed of isolates of two types (PepMV-CH2 and PepMV-EU) that cocirculate. The CH2 type isolates are predominant; however, EU isolates have not been displaced but persist mainly in mixed infections. Two molecularly cloned isolates belonging to each type have been used to examine the dynamics of in planta single infections and coinfection, revealing that the CH2 type has a higher fitness than the EU type. Coinfections expand the range of susceptible hosts, and coinfected plants remain symptomless several weeks after infection, so a potentially important problem for disease prevention and management. These results provide an explanation of the observed epidemiological pattern in terms of genetic and ecological interactions among the different viral strains. Thus, mixed infections appear to be contributing to shaping the genetic structure and dynamics of PepMV populations.

Adaptation rates of lytic viruses depend critically on whether host cells survive the bottleneck

We use a branching process approach to estimate the substitution rate, the rate at which beneficial mutations occur and fix, in populations of lytic viruses whose growth is controlled by periodic population bottlenecks. Our model predicts that substitution rates, and by extension adaptation rates, are profoundly affected by the survival of infected host cells at the bottleneck. In particular, we find that direct transfer (or environmental) bottlenecks, in which some fraction of both free virus and host cells are preserved, are associated with relatively slow adaptation rates for the virus. In contrast, viruses can adapt much more quickly when only free virus is transferred to a new host population, as is typical in an epidemiological setting. Finally, when premature lysis of the host-cell population is induced at the bottleneck, we predict that adaptation rates for the virus will, in general, be faster still. These results hold irrespective of the life-history trait affected by the beneficial mutation. The substitution rates in the presence of environmental bottlenecks are predicted to be as much as an order of magnitude lower than in the other two cases.