Mutation-Driven Parallel Evolution during Viral Adaptation

Targeting Pseudomonas aeruginosa biofilm with an evolutionary trained bacteriophage cocktail exploiting phage resistance trade-offs

Spread of multidrug-resistant Pseudomonas aeruginosa strains threatens to render currently available antibiotics obsolete, with limited prospects for the development of new antibiotics. Lytic bacteriophages, the viruses of bacteria, represent a path to combat this threat. In vitro-directed evolution is traditionally applied to expand the bacteriophage host range or increase bacterial suppression in planktonic cultures. However, while up to 80% of human microbial infections are biofilm-associated, research towards targeted improvement of bacteriophages' ability to combat biofilms remains scarce. This study aims at an in vitro biofilm evolution assay to improve multiple bacteriophage parameters in parallel and the optimisation of bacteriophage cocktail design by exploiting a bacterial bacteriophage resistance trade-off. The evolved bacteriophages show an expanded host spectrum, improved antimicrobial efficacy and enhanced antibiofilm performance, as assessed by isothermal microcalorimetry and quantitative polymerase chain reaction, respectively. Our two-phage cocktail reveals further improved antimicrobial efficacy without incurring dual-bacteriophage-resistance in treated bacteria. We anticipate this assay will allow a better understanding of phenotypic-genomic relationships in bacteriophages and enable the training of bacteriophages against other desired pathogens. This, in turn, will strengthen bacteriophage therapy as a treatment adjunct to improve clinical outcomes of multidrug-resistant bacterial infections.

Parallel evolution of picobirnaviruses from distinct ancestral origins

IMPORTANCE

Picobirnaviruses (PBVs) are highly heterogeneous viruses encoding a capsid and RdRp. Detected in a wide variety of animals with and without disease, their association with gastrointestinal and respiratory infections, and consequently their public health importance, has rightly been questioned. Determining the "true" host of Picobirnavirus lies at the center of this debate, as evidence exists for them having both vertebrate and prokaryotic origins. Using integrated and time-stamped phylogenetic approaches, we show they are contemporaneous viruses descending from two different ancestors: avian Reovirus and fungal Partitivirus. The fungal PBV-R2 species emerged with a single segment (RdRp) until it acquired a capsid from vertebrate PBV-R1 and PBV-R3 species. Protein and RNA folding analyses revealed how the former came to resemble the latter over time. Thus, parallel evolution from disparate hosts has driven the adaptation and genetic diversification of the Picobirnaviridae family.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

Mutation and Selection Induce Correlations between Selection Coefficients and Mutation Rates

AbstractThe joint distribution of selection coefficients and mutation rates is a key determinant of the genetic architecture of molecular adaptation. Three different distributions are of immediate interest: (1) the "nominal" distribution of possible changes, prior to mutation or selection; (2) the "de novo" distribution of realized mutations; and (3) the "fixed" distribution of selectively established mutations. Here, we formally characterize the relationships between these joint distributions under the strong-selection/weak-mutation (SSWM) regime. The de novo distribution is enriched relative to the nominal distribution for the highest rate mutations, and the fixed distribution is further enriched for the most highly beneficial mutations. Whereas mutation rates and selection coefficients are often assumed to be uncorrelated, we show that even with no correlation in the nominal distribution, the resulting de novo and fixed distributions can have correlations with any combination of signs. Nonetheless, we suggest that natural systems with a finite number of beneficial mutations will frequently have the kind of nominal distribution that induces negative correlations in the fixed distribution. We apply our mathematical framework, along with population simulations, to explore joint distributions of selection coefficients and mutation rates from deep mutational scanning and cancer informatics. Finally, we consider the evolutionary implications of these joint distributions together with two additional joint distributions relevant to parallelism and the rate of adaptation.

Sequence Analysis of Hot Spot Regions of Spike and RNA-dependent-RNA polymerase (RdRp) Genes of SARS-CoV-2 in Kerman, Iran

Background

Mutations in the SARS-CoV-2 genome might influence pathogenicity, transmission rate, and evasion of the host immune system. Therefore, the purpose of the present study was to investigate the genetic alteration as well as assess their effects on the receptor binding domain (RBD) of the spike and the putative RNA binding site of the RdRp genes of SARS-CoV-2 using bioinformatics tools.

Materials and Method

In this cross-sectional study, 45 confirmed COVID-19 patients using qRT-PCR were included and divided into mild, severe, and critical groups based on the severity of the disease. RNA was extracted from nasopharyngeal swab samples using a commercial kit. RT-PCR was performed to amplify the target sequences of the spike and RdRp genes and sequence them by the Sanger method. Clustal OMEGA, MEGA 11 software, I-mutant tools, SWISS-MODEL, and HDOCK web servers were used for bioinformatics analyses.

Results

The mean age of the patients was 50.68±2.73. The results showed that four of six mutations (L452R, T478K, N501Y, and D614G) in RBD and three of eight in the putative RNA binding site (P314L, E1084D, V1883T) were missense. In the putative RNA binding site, another deletion was discovered. Among missense mutations, N501Y and V1883T were responsible for increasing structural stability, while others were responsible for decreasing it. The various homology models designed showed that these homologies were like the Wuhan model. The molecular docking analysis revealed that the T478K mutation in RBD had the highest binding affinity. In addition, 35 RBD samples (89.7%) and 33 putative RNA binding site samples (84.6%) were similar to the Delta variant.

Conclusion

Our results indicated that double mutations (T478K and N501Y) in the S protein might increase the binding affinity of SARS-CoV-2 to human ACE2 compared to the wild-type (WT) strain. Moreover, variations in the spike and RdRp genes might influence the stability of encoded proteins.

Mutation bias and the predictability of evolution

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Evolutionary repeatability of emergent properties of ecological communities

Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

A Deeper Insight into Evolutionary Patterns and Phylogenetic History of ORF Virus through the Whole Genome Sequencing of the First Italian Strains

Orf virus (ORFV) is distributed worldwide and is the causative agent of contagious ecthyma that mainly occurs in sheep and goats. This disease was reported for the first time at the end of 18th century in Europe but very little is currently known about the temporal and geographic origins of this virus. In the present study, the use of new Italian whole genomes allowed for better inference on the evolutionary history of ORFV. In accordance with previous studies, two genome types (S and G) were described for infection of sheep and goats, respectively. These two well-differentiated groups of genomes originated for evolutive convergence in the late 1800s in two different areas of the world (Europe for S type and Asia for G type), but it was only in the early 1900s that the effective size of ORFV increased among hosts and the virus spread across the whole European continent. The Italian strains which were sequenced in the present study were isolated on the Mediterranean island of Sardinian and showed to be exclusive to this geographic area. One of them is likely representative of the early European forms of ORFV which infected sheep and became extinct about one century ago. Such an ancient Sardinian strain may have reached the island simple by chance, where it quickly adapted to the new habitat.

Genome sequence analysis of nsp15 from SARS-CoV-2

SARS-CoV-2 (Severe Acute Respiratory Syndrome), a causative agent of COVID-19 disease created a pandemic situation worldwide. Nsp15 is a uridine specific endoribonuclease encoded by the genome of SARS-CoV-2. It plays important role in processing viral RNA and, thus evades the host immune system. Therefore, it is of interest to identify mutants of nsp15 amongst Asian SARS-CoV-2 isolates, where a total of 1795 mutations, from 7793 sequences of Asia submitted till 31st January 2022, amongst which A231V, H234Y, K109N, K259R and S261A mutations were found frequent. Hence, we report data on the predicted secondary structure of wild type form followed by hydropathy plot, physiochemical properties, Ramachandran plot, B-cell epitopes prediction and protein modeling of wild type and mutant of nsp15 protein. Data shows that nsp15 of SARS-CoV-2 is a pontential candidate for the development of vaccine to control the infections of SARS-CoV-2.

Widespread Interspecific Phylogenetic Tree Incongruence Between Mosquito-Borne and Insect-Specific Flaviviruses at Hotspots Originally Identified in Zika Virus

Intraspecies (homologous) phylogenetic incongruence, or ‘tree conflict’ between different loci within the same genome of mosquito-borne flaviviruses (MBFV), was first identified in dengue virus (DENV) and subsequently in Japanese encephalitis virus (JEV), St Louis encephalitis virus, and Zika virus (ZIKV). Recently, the first evidence of phylogenetic incongruence between interspecific members of the MBFV was reported in ZIKV and its close relative, Spondweni virus. Uniquely, these hybrid proteomes were derived from four incongruent trees involving an Aedes-associated DENV node (1 tree) and three different Culex-associated flavivirus nodes (3 trees). This analysis has now been extended across a wider spectrum of viruses within the MBFV lineage targeting the breakpoints between phylogenetic incongruent loci originally identified in ZIKV. Interspecies phylogenetic incongruence at these breakpoints was identified in 10 of 50 viruses within the MBFV lineage, representing emergent Aedes and Culex-associated viruses including JEV, West Nile virus, yellow fever virus, and insect-specific viruses. Thus, interspecies phylogenetic incongruence is widespread amongst the flaviviruses and is robustly associated with the specific breakpoints that coincide with the interspecific phylogenetic incongruence previously identified, inferring they are ‘hotspots’. The incongruence amongst the emergent MBFV group was restricted to viruses within their respective associated epidemiological boundaries. This MBFV group was RY-coded at the third codon position (‘wobble codon’) to remove transition saturation. The resulting ‘wobble codon’ trees presented a single topology for the entire genome that lacked any robust evidence of phylogenetic incongruence between loci. Phylogenetic interspecific incongruence was therefore observed for exactly the same loci between amino acid and the RY-coded ‘wobble codon’ alignments and this incongruence represented either a major part, or the entire genomes. Maximum likelihood codon analysis revealed positive selection for the incongruent lineages. Positive selection could result in the same locus producing two opposing trees. These analyses for the clinically important MBFV suggest that robust interspecific phylogenetic incongruence resulted from amino acid selection. Convergent or parallel evolutions are evolutionary processes that would explain the observation, whilst interspecific recombination is unlikely.

Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution

Mutations with large fitness benefits and mutations occurring at high rates may both cause parallel evolution, but their contribution is predicted to depend on population size. Moreover, high-rate and large-benefit mutations may have different long-term adaptive consequences. We show that small and 100-fold larger bacterial populations evolve resistance to a β-lactam antibiotic by using similar numbers, but different types of mutations. Small populations frequently substitute similar high-rate structural variants and loss-of-function point mutations, including the deletion of a low-activity β-lactamase, and evolve modest resistance levels. Large populations more often use low-rate, large-benefit point mutations affecting the same targets, including mutations activating the β-lactamase and other gain-of-function mutations, leading to much higher resistance levels. Our results demonstrate the separation by clonal interference of mutation classes with divergent adaptive consequences, causing a shift from high-rate to large-benefit mutations with increases in population size.

Mutation bias shapes the spectrum of adaptive substitutions

How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes

Mutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify. In this work, we reveal that a near-deterministic genetic hotspot can be built and broken by a handful of silent mutations. We observe this when studying homologous immotile variants of the bacteria Pseudomonas fluorescens, AR2 and Pf0-2x. AR2 resurrects motility through highly repeatable de novo mutation of the same nucleotide in >95% lines in minimal media (ntrB A289C). Pf0-2x, however, evolves via a number of mutations meaning the two strains diverge significantly during adaptation. We determine that this evolutionary disparity is owed to just 6 synonymous variations within the ntrB locus, which we demonstrate by swapping the sites and observing that we are able to both break (>95% to 0%) and build (0% to 80%) a deterministic mutational hotspot. Our work reveals a key role for silent genetic variation in determining adaptive outcomes.

Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations

Accumulation of mutations within the genome is the primary driving force in viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility, and antigenic shifts to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we carried out a genome-wide analysis of circulating SARS-CoV-2 strains to detect the emergence of novel co-existing mutations and trace their geographical distribution within India. Comprehensive analysis of whole genome sequences of 837 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 18 of which were unique to India. Novel mutations were observed in the S glycoprotein (6/33), NSP3 (5/33), RdRp/NSP12 (4/33), NSP2 (2/33), and N (1/33). Non-synonymous mutations were found to be 3.07 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on their co-existing mutations. Phylogenetic analysis revealed that the representative strains of each group were divided into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. The A2a clade was found to be dominant in India (71.34%), followed by A3 (23.29%) and B (5.36%), but a heterogeneous distribution was observed among various geographical regions. The A2a clade was highly predominant in East India, Western India, and Central India, whereas the A2a and A3 clades were nearly equal in prevalence in South and North India. This study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations will pave the way for vaccine formulation and the design of antiviral drugs.

Identification and characterization of mutations in the SARS-CoV-2 RNA-dependent RNA polymerase as a promising antiviral therapeutic target

The causative agent of COVID-19 is a novel betacoronavirus or severe acute respiratory syndrome coronavirus (SARS-CoV-2), which has emerged as a pandemic of global concern. Considering its rapid transmission, WHO has declared public health emergency on 11th March 2020 worldwide. SARS-CoV-2 is a genetically diverse positive sense RNA virus that typically exhibit high rates of mutation than DNA viruses. Higher rates of mutation bring higher genomic variability which may lead to viral evolution and enabling viruses to evade the pre-existing immunity of host and quickly acquire drug resistance properties. The objective of our study was to compare the SARS-CoV-2 RdRp sequences of Indian SARS-CoV-2 isolates with those of Wuhan type virus. A total of 384 point mutations were detected from 488 sequence of the RdRp protein of Indian SARS-CoV-2 genome, out of which seven were used for subsequent study. Furthermore, prediction of secondary structure, protein modeling and its dynamics were performed which revealed that seven mutations (R118C, T148I, Y149C, E802A, Q822H, V880I and D893Y) significantly altered the stability and flexibility of RdRp protein. Present study was therefore, undertaken to analyze the variations occurring in RdRp due to multiple mutations leading to the alterations in the structure and function of RNA-dependent RNA polymerase which is essential for the replication /transcription of this virus and hence can be utilized as a promising therapeutic target to curb SARS-CoV-2 infections.

Mutation bias can shape adaptation in large asexual populations experiencing clonal interference

The extended evolutionary synthesis invokes a role for development in shaping adaptive evolution, which in population genetics terms corresponds to mutation-biased adaptation. Critics have claimed that clonal interference makes mutation-biased adaptation rare. We consider the behaviour of two simultaneously adapting traits, one with larger mutation rate U, the other with larger selection coefficient s, using asexual travelling wave models. We find that adaptation is dominated by whichever trait has the faster rate of adaptation v in isolation, with the other trait subject to evolutionary stalling. Reviewing empirical claims for mutation-biased adaptation, we find that not all occur in the 'origin-fixation' regime of population genetics where v is only twice as sensitive to s as to U. In some cases, differences in U are at least ten to twelve times larger than differences in s, as needed to cause mutation-biased adaptation even in the 'multiple mutations' regime. Surprisingly, when U > s in the 'diffusive-mutation' regime, the required sensitivity ratio is also only two, despite pervasive clonal interference. Given two traits with identical v, the benefit of having higher s is surprisingly small, occurring largely when one trait is at the boundary between the origin-fixation and multiple mutations regimes.

Identification of novel mutations in RNA-dependent RNA polymerases of SARS-CoV-2 and their implications on its protein structure

The rapid development of the SARS-CoV-2 mediated COVID-19 pandemic has been the cause of significant health concern, highlighting the immediate need for effective antivirals. SARS-CoV-2 is an RNA virus that has an inherently high mutation rate. These mutations drive viral evolution and genome variability, thereby facilitating viruses to have rapid antigenic shifting to evade host immunity and to develop drug resistance. Viral RNA-dependent RNA polymerases (RdRp) perform viral genome duplication and RNA synthesis. Therefore, we compared the available RdRp sequences of SARS-CoV-2 from Indian isolates and the ‘Wuhan wet sea food market virus’ sequence to identify, if any, variation between them. Our data revealed the occurrence of seven mutations in Indian isolates of SARS-CoV-2. The secondary structure prediction analysis of these seven mutations shows that three of them cause alteration in the structure of RdRp. Furthermore, we did protein modelling studies to show that these mutations can potentially alter the stability of the RdRp protein. Therefore, we propose that RdRp mutations in Indian SARS-CoV-2 isolates might have functional consequences that can interfere with RdRp targeting pharmacological agents.

Parallel evolution of HIV-1 in a long-term experiment

One of the most intriguing puzzles in biology is the degree to which evolution is repeatable. The repeatability of evolution, or parallel evolution, has been studied in a variety of model systems, but has rarely been investigated with clinically relevant viruses. To investigate parallel evolution of HIV-1, we passaged two replicate HIV-1 populations for almost 1 year in each of two human T-cell lines. For each of the four evolution lines, we determined the genetic composition of the viral population at nine time points by deep sequencing the entire genome. Mutations that were carried by the majority of the viral population accumulated continuously over 1 year in each evolution line. Many majority mutations appeared in more than one evolution line, that is, our experiments showed an extreme degree of parallel evolution. In one of the evolution lines, 62% of the majority mutations also occur in another line. The parallelism impairs our ability to reconstruct the evolutionary history by phylogenetic methods. We show that one can infer the correct phylogenetic topology by including minority mutations in our analysis. We also find that mutation diversity at the beginning of the experiment is predictive of the frequency of majority mutations at the end of the experiment.

Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis

Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of the rates and spectra of spontaneous mutations. However, demonstrating the role of transition bias in adaptive evolution remains challenging. In particular, it is unclear whether such biases direct the evolution of bacterial pathogens adapting to treatment. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis (MTB). We found strong evidence for transition bias in two independently curated data sets comprising 152 and 208 antibiotic-resistance mutations. This was true at the level of mutational paths (distinct adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes) and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the 16S ribosomal RNA gene rrs) and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.

Some types of mutations occur more frequently than expected. This study shows that such bias —an excess of transitions over transversions—influences the evolution of antibiotic resistance in a key global pathogen, Mycobacterium tuberculosis.

The mystery of the phylogeographic structural pattern in rodent-borne hantaviruses

Hantaviruses (order Bunyavirales, family Hantaviridae) are important zoonotic pathogens. Because of the great diversity of their reservoir hosts, hantaviruses are excellent models to evaluate the dynamics of virus-host co-evolution. To understand the mechanisms behind the evolutionary history of hantaviruses through virus-reservoir interactions, it is important to know how the radiation and diversity of hantaviruses occurred. In this paper, we evaluate the pattern of hantavirus diversification based on a complete S segment representing major groups of hantaviruses found in the Americas. Phylogenetic analyses revealed a high degree of phylogeographic structure and a surprising pattern of geographical distribution of New World hantaviruses. The available data suggest that hantaviruses related to the Arvicolinae rodent subfamily in North America probably emerged and initially adapted from a shared common ancestor of the Tula virus. The first clade of hantaviruses associated with Neotominae occupied a stem lineage, especially those that emerged in Central America or Mexico. Hantaviruses from Central America and Mexico found in Neotominae rodents spread northward and probably gave rise to the first phylogroup of hantaviruses associated with Sigmodontinae in North America. Two preferential host-switching transmissions in hantaviruses apparently gave rise to two different paraphyletic group in Neotominae and Sigmodontinae. Our study supports a probable epicenter of diversification in Central America and/or Mexico for hantaviruses related to both the Neotominae and Sigmodontinae subfamilies.

Molecular analyses and phylogeny of the herpes simplex virus 2 US9 and glycoproteins gE/gI obtained from infected subjects during the Herpevac Trial for Women

Herpes simplex virus 2 (HSV-2) is a large double-stranded DNA virus that causes genital sores when spread by sexual contact and is a principal cause of viral encephalitis in newborns and infants. Viral glycoproteins enable virion entry into and spread between cells, making glycoproteins a prime target for vaccine development. A truncated glycoprotein D2 (gD2) vaccine candidate, recently tested in the phase 3 Herpevac Trial for Women, did not prevent HSV-2 infection in initially seronegative women. Some women who became infected experienced multiple recurrences during the trial. The HSV US7, US8, and US9 genes encode glycoprotein I (gI), glycoprotein E (gE), and the US9 type II membrane protein, respectively. These proteins participate in viral spread across cell junctions and facilitate anterograde transport of virion components in neurons, prompting us to investigate whether sequence variants in these genes could be associated with frequent recurrence. The nucleotide sequences and dN/dS ratios of the US7-US9 region from viral isolates of individuals who experienced multiple recurrences were compared with those who had had a single episode of disease. No consistent polymorphism(s) distinguished the recurrent isolates. In frequently recurring isolates, the dN/dS ratio of US7 was low while greater variation (higher dN/dS ratio) occurred in US8, suggesting conserved function of the former during reactivation. Phylogenetic reconstruction of the US7-US9 region revealed eight strongly supported clusters within the 55 U.S. HSV-2 strains sampled, which were preserved in a second global phylogeny. Thus, although we have demonstrated evolutionary diversity in the US7-US9 complex, we found no molecular evidence of sequence variation in US7-US9 that distinguishes isolates from subjects with frequently recurrent episodes of disease.

The phylogenomics of evolving virus virulence

How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

Gene Birth Contributes to Structural Disorder Encoded by Overlapping Genes

The same nucleotide sequence can encode two protein products in different reading frames. Overlapping gene regions encode higher levels of intrinsic structural disorder (ISD) than nonoverlapping genes (39% vs. 25% in our viral dataset). This might be because of the intrinsic properties of the genetic code, because one member per pair was recently born de novo in a process that favors high ISD, or because high ISD relieves increased evolutionary constraint imposed by dual-coding. Here, we quantify the relative contributions of these three alternative hypotheses. We estimate that the recency of de novo gene birth explains [Formula: see text] or more of the elevation in ISD in overlapping regions of viral genes. While the two reading frames within a same-strand overlapping gene pair have markedly different ISD tendencies that must be controlled for, their effects cancel out to make no net contribution to ISD. The remaining elevation of ISD in the older members of overlapping gene pairs, presumed due to the need to alleviate evolutionary constraint, was already present prior to the origin of the overlap. Same-strand overlapping gene birth events can occur in two different frames, favoring high ISD either in the ancestral gene or in the novel gene; surprisingly, most de novo gene birth events contained completely within the body of an ancestral gene favor high ISD in the ancestral gene (23 phylogenetically independent events vs. 1). This can be explained by mutation bias favoring the frame with more start codons and fewer stop codons.

Parallel Evolution of Host-Attachment Proteins in Phage PP01 Populations Adapting to Escherichia coli O157:H7

The emergence of antibiotic resistance has sparked interest in phage therapy, which uses virulent phages as antibacterial agents. Bacteriophage PP01 has been studied for potential bio-control of Escherichia coli O157:H7, its natural host, but in the laboratory, PP01 can be inefficient at killing this bacterium. Thus, the goal of this study was to improve the therapeutic potential of PP01 through short-term experimental evolution. Four replicate populations of PP01 were serially passaged 21 times on non-evolving E. coli O157:H7 with the prediction that the evolved phage populations would adsorb faster and more efficiently kill the host bacteria. Dead-cell adsorption assays and in vitro killing assays confirmed that evolved viruses improved their adsorption ability on E. coli O157:H7, and adapted to kill host bacteria faster than the wildtype ancestor. Sequencing of candidate tail-fiber genes revealed that the phage populations evolved in parallel; the lineages shared two point mutations in gp38 that encodes a host recognition protein, and surprisingly shared a ~600 bp deletion in gp37 that encodes the distal tail fibers. In contrast, no mutations were observed in the gp12 gene encoding PP01’s short tail fibers. We discuss the functional role of the observed mutations, including the possible adaptive role of the evolved deletions. This study demonstrates how experimental evolution can be used to select for viral traits that improve phage attack of an important bacterial pathogen, and that the molecular targets of selection include loci contributing to cell attachment and phage virulence.

Mapping the Evolutionary Potential of RNA Viruses

The deterministic force of natural selection and stochastic influence of drift shape RNA virus evolution. New deep-sequencing and microfluidics technologies allow us to quantify the effect of mutations and trace the evolution of viral populations with single-genome and single-nucleotide resolution. Such experiments can reveal the topography of the genotype-fitness landscapes that shape the path of viral evolution. By combining historical analyses, like phylogenetic approaches, with high-throughput and high-resolution evolutionary experiments, we can observe parallel patterns of evolution that drive important phenotypic transitions. These developments provide a framework for quantifying and anticipating potential evolutionary events. Here, we examine emerging technologies that can map the selective landscapes of viruses, focusing on their application to pathogenic viruses. We identify areas where these technologies can bolster our ability to study the evolution of viruses and to anticipate and possibly intervene in evolutionary events and prevent viral disease.

Divergent and parallel routes of biochemical adaptation in high-altitude passerine birds from the Qinghai-Tibet Plateau

When different species experience similar selection pressures, the probability of evolving similar adaptive solutions may be influenced by legacies of evolutionary history, such as lineage-specific changes in genetic background. Here we test for adaptive convergence in hemoglobin (Hb) function among high-altitude passerine birds that are native to the Qinghai-Tibet Plateau, and we examine whether convergent increases in Hb-O₂ affinity have a similar molecular basis in different species. We documented that high-altitude parid and aegithalid species from the Qinghai-Tibet Plateau have evolved derived increases in Hb-O₂ affinity in comparison with their closest lowland relatives in East Asia. However, convergent increases in Hb-O₂ affinity and convergence in underlying functional mechanisms were seldom attributable to the same amino acid substitutions in different species. Using ancestral protein resurrection and site-directed mutagenesis, we experimentally confirmed two cases in which parallel substitutions contributed to convergent increases in Hb-O₂ affinity in codistributed high-altitude species. In one case involving the ground tit (Parus humilis) and gray-crested tit (Lophophanes dichrous), parallel amino acid replacements with affinity-enhancing effects were attributable to nonsynonymous substitutions at a CpG dinucleotide, suggesting a possible role for mutation bias in promoting recurrent changes at the same site. Overall, most altitude-related changes in Hb function were caused by divergent amino acid substitutions, and a select few were caused by parallel substitutions that produced similar phenotypic effects on the divergent genetic backgrounds of different species.