EXPERIMENTAL MOLECULAR EVOLUTION OF BACTERIOPHAGE T7

Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families

The construction of a high-quality multiple sequence alignment (MSA) from copies of a transposable element (TE) is a critical step in the characterization of a new TE family. Most studies of MSA accuracy have been conducted on protein or RNA sequence families, where structural features and strong signals of selection may assist with alignment. Less attention has been given to the quality of sequence alignments involving neutrally evolving DNA sequences such as those resulting from TE replication. Transposable element sequences are challenging to align due to their wide divergence ranges, fragmentation, and predominantly-neutral mutation patterns. To gain insight into the effects of these properties on MSA accuracy, we developed a simulator of TE sequence evolution, and used it to generate a benchmark with which we evaluated the MSA predictions produced by several popular aligners, along with Refiner, a method we developed in the context of our RepeatModeler software. We find that MAFFT and Refiner generally outperform other aligners for low to medium divergence simulated sequences, while Refiner is uniquely effective when tasked with aligning high-divergent and fragmented instances of a family.

Evolutionary selection against short nucleotide sequences in viruses and their related hosts

Viruses are under constant evolutionary pressure to effectively interact with the host intracellular factors, while evading its immune system. Understanding how viruses co-evolve with their hosts is a fundamental topic in molecular evolution and may also aid in developing novel viral based applications such as vaccines, oncologic therapies, and anti-bacterial treatments. Here, based on a novel statistical framework and a large-scale genomic analysis of 2,625 viruses from all classes infecting 439 host organisms from all kingdoms of life, we identify short nucleotide sequences that are under-represented in the coding regions of viruses and their hosts. These sequences cannot be explained by the coding regions’ amino acid content, codon, and dinucleotide frequencies. We specifically show that short homooligonucleotide and palindromic sequences tend to be under-represented in many viruses probably due to their effect on gene expression regulation and the interaction with the host immune system. In addition, we show that more sequences tend to be under-represented in dsDNA viruses than in other viral groups. Finally, we demonstrate, based on in vitro and in vivo experiments, how under-represented sequences can be used to attenuated Zika virus strains.

Whole plastomes are not enough: phylogenomic and morphometric exploration at multiple demographic levels of the bee orchid clade Ophrys sect. Sphegodes

Plastid sequences have long dominated phylogeny reconstruction at all time depths, predicated on a usually untested assumption that they accurately represent the evolutionary histories of phenotypically circumscribed species. We combined detailed in situ morphometrics (124 plants) and whole-plastome sequencing through genome skimming (71 plants) in order to better understand species-level diversity and speciation in arguably the most challenging monophyletic group within the taxonomically controversial, pseudo-copulatory bee orchid genus Ophrys. Using trees and ordinations, we interpreted the data at four nested demographic levels-macrospecies, mesospecies, microspecies, and local population-seeking the optimal level for bona fide species. Neither morphological nor molecular discontinuities are evident at any level below macrospecies, the observed overlap among taxa suggesting that both mesospecies and microspecies reflect arbitrary division of a continuum of variation. Plastomes represent geographic location more strongly than taxonomic assignment and correlate poorly with morphology, suggesting widespread plastid capture and possibly post-glacial expansion from multiple southern refugia. As they are rarely directly involved in the speciation process, plastomes depend on extinction of intermediate lineages to provide phylogenetic signal and so cannot adequately document evolutionary radiations. The popular 'ethological' evolutionary model recognizes as numerous 'ecological species' (microspecies) lineages perceived as actively diverging as a result of density-dependent selection on very few features that immediately dictate extreme pollinator specificity. However, it is assumed rather than demonstrated that the many microspecies are genuinely diverging. We conversely envisage a complex four-dimensional reticulate network of lineages, generated locally and transiently through a wide spectrum of mechanisms, but each unlikely to maintain an independent evolutionary trajectory long enough to genuinely speciate by escaping ongoing gene flow. The frequent but localized microevolution that characterizes the Ophrys sphegodes complex is often convergent and rarely leads to macroevolution. Choosing between the contrasting 'discontinuity' and 'ethology' models will require next-generation sequencing of nuclear genomes plus ordination of corresponding morphometric matrices, seeking the crucial distinction between retained ancestral polymorphism-consistent with lineage divergence-and polymorphisms reflecting gene flow through 'hybridization'-more consistent with lineage convergence.

Repeated outbreaks drive the evolution of bacteriophage communication

Recently, a small-molecule communication mechanism was discovered in a range of Bacillus-infecting bacteriophages, which these temperate phages use to inform their lysis-lysogeny decision. We present a mathematical model of the ecological and evolutionary dynamics of such viral communication and show that a communication strategy in which phages use the lytic cycle early in an outbreak (when susceptible host cells are abundant) but switch to the lysogenic cycle later (when susceptible cells become scarce) is favoured over a bet-hedging strategy in which cells are lysogenised with constant probability. However, such phage communication can evolve only if phage-bacteria populations are regularly perturbed away from their equilibrium state, so that acute outbreaks of phage infections in pools of susceptible cells continue to occur. Our model then predicts the selection of phages that switch infection strategy when half of the available susceptible cells have been infected.

Bacteriophages, or phages for short, are viruses that need to infect bacteria to multiply. Once inside a cell, phages follow one of two strategies. They either start to replicate quickly, killing the host in the process; or they lay dormant, their genetic material slowly duplicating as the bacterium divides. These two strategies are respectively known as a ‘lytic’ or a ‘lysogenic’ infection.

In 2017, scientists discovered that, during infection, some phages produce a signalling molecule that influences the strategy other phages will use. Generally, a high concentration of the signal triggers lysogenic infection, while a low level prompts the lytic type. However, it is still unclear what advantages this communication system brings to the viruses, and how it has evolved.

Here, Doekes et al. used a mathematical model to explore how communication changes as phages infect a population of bacteria, rigorously testing earlier theories. The simulations showed that early in an outbreak, when only a few cells have yet been infected, the signalling molecule levels are low: lytic infections are therefore triggered and the phages quickly multiply, killing their hosts in the process. This is an advantageous strategy since many bacteria are available for the viruses to prey on. Later on, as more phages are being produced and available bacteria become few and far between, the levels of the signalling molecule increase. The viruses then switch to lysogenic infections, which allows them to survive dormant, inside their host.

Doekes et al. also discovered that this communication system only evolves if phages regularly cause large outbreaks in new, uninfected bacterial populations. From there, the model was able to predict that phages switch from lytic to lysogenic infections when about half the available bacteria have been infected.

As antibiotic resistance rises around the globe, phages are increasingly considered as a new way to fight off harmful bacteria. Deciphering the way these viruses communicate could help to understand how they could be harnessed to control the spread of bacteria.

SpartaABC: a web server to simulate sequences with indel parameters inferred using an approximate Bayesian computation algorithm

Many analyses for the detection of biological phenomena rely on a multiple sequence alignment as input. The results of such analyses are often further studied through parametric bootstrap procedures, using sequence simulators. One of the problems with conducting such simulation studies is that users currently have no means to decide which insertion and deletion (indel) parameters to choose, so that the resulting sequences mimic biological data. Here, we present SpartaABC, a web server that aims to solve this issue. SpartaABC implements an approximate-Bayesian-computation rejection algorithm to infer indel parameters from sequence data. It does so by extracting summary statistics from the input. It then performs numerous sequence simulations under randomly sampled indel parameters. By computing a distance between the summary statistics extracted from the input and each simulation, SpartaABC retains only parameters behind simulations close to the real data. As output, SpartaABC provides point estimates and approximate posterior distributions of the indel parameters. In addition, SpartaABC allows simulating sequences with the inferred indel parameters. To this end, the sequence simulators, Dawg 2.0 and INDELible were integrated. Using SpartaABC we demonstrate the differences in indel dynamics among three protein-coding genes across mammalian orthologs. SpartaABC is freely available for use at http://spartaabc.tau.ac.il/webserver.

Exploring the evolution of multicellularity in Saccharomyces cerevisiae under bacteria environment: An experimental phylogenetics approach

There have been over 25 independent unicellular to multicellular evolutionary transitions, which have been transformational in the complexity of life. All of these transitions likely occurred in communities numerically dominated by unicellular organisms, mostly bacteria. Hence, it is reasonable to expect that bacteria were involved in generating the ecological conditions that promoted the stability and proliferation of the first multicellular forms as protective units. In this study, we addressed this problem by analyzing the occurrence of multicellularity in an experimental phylogeny of yeasts (Sacharomyces cerevisiae) a model organism that is unicellular but can generate multicellular clusters under some conditions. We exposed a single ancestral population to periodic divergences, coevolving with a cocktail of environmental bacteria that were inoculated to the environment of the ancestor, and compared to a control (no bacteria). We quantified culturable microorganisms to the level of genera, finding up to 20 taxa (all bacteria) that competed with the yeasts during diversification. After 600 generations of coevolution, the yeasts produced two types of multicellular clusters: clonal and aggregative. Whereas clonal clusters were present in both treatments, aggregative clusters were only present under the bacteria treatment and showed significant phylogenetic signal. However, clonal clusters showed different properties if bacteria were present as follows: They were more abundant and significantly smaller than in the control. These results indicate that bacteria are important modulators of the occurrence of multicellularity, providing support to the idea that they generated the ecological conditions-promoting multicellularity.

Sources of Variation in Ancestral Sequence Reconstruction for HIV-1 Envelope Genes

We characterized the variation in the reconstructed ancestor of 118 HIV-1 envelope gene sequences arising from the methods used for (a) estimating and (b) rooting the phylogenetic tree, and (c) reconstructing the ancestor on that tree, from (d) the sequence format, and from (e) the number of input sequences. The method of rooting the tree was responsible for most of the sequence variation both among the reconstructed ancestral sequences and between the ancestral and observed sequences. Variation in predicted 3-D structural properties of the ancestors mirrored their sequence variation. The observed sequence consensus and ancestral sequences from center-rooted trees were most similar in all predicted attributes. Only for the predicted number of N-glycosylation sites was there a difference between MP and ML methods of reconstruction. Taxon sampling effects were observed only for outgroup-rooted trees, not center-rooted, reflecting the occurrence of several divergent basal sequences. Thus, for sequences exhibiting a radial phylogenetic tree, as does HIV-1, most of the variation in the estimated ancestor arises from the method of rooting the phylogenetic tree. Those investigating the ancestors of genes exhibiting such a radial tree should pay particular attention to alternate rooting methods in order to obtain a representative sample of ancestors.

Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda

Deciphering the way gene expression regulatory aspects are encoded in viral genomes is a challenging mission with ramifications related to all biomedical disciplines. Here, we aimed to understand how the evolution shapes the bacteriophage lambda genes by performing a high resolution analysis of ribosomal profiling data and gene expression related synonymous/silent information encoded in bacteriophage coding regions.

We demonstrated evidence of selection for distinct compositions of synonymous codons in early and late viral genes related to the adaptation of translation efficiency to different bacteriophage developmental stages. Specifically, we showed that evolution of viral coding regions is driven, among others, by selection for codons with higher decoding rates; during the initial/progressive stages of infection the decoding rates in early/late genes were found to be superior to those in late/early genes, respectively. Moreover, we argued that selection for translation efficiency could be partially explained by adaptation to Escherichia coli tRNA pool and the fact that it can change during the bacteriophage life cycle.

An analysis of additional aspects related to the expression of viral genes, such as mRNA folding and more complex/longer regulatory signals in the coding regions, is also reported. The reported conclusions are likely to be relevant also to additional viruses.

VIRULENCE

Why do parasites harm their hosts? Intuition suggests that parasites should evolve to be benign whenever the host is needed for transmission. Yet a growing theoretical literature offers several models to explain why natural selection may favor virulent parasites over avirulent ones. This perspective first organizes these models into a simple framework and then evaluates the empirical evidence for and against the models. There is relatively scant evidence to support any of the models rigorously, and indeed, there are only a few unequivocal observations of virulence actually evolving in parasite populations. These shortcomings are surmountable, however, and empirical models of host-parasite interactions have been developed for many kinds of pathogens so that the relevant data could be acquired in the near future.

Inferring Indel Parameters using a Simulation-based Approach

In this study, we present a novel methodology to infer indel parameters from multiple sequence alignments (MSAs) based on simulations. Our algorithm searches for the set of evolutionary parameters describing indel dynamics which best fits a given input MSA. In each step of the search, we use parametric bootstraps and the Mahalanobis distance to estimate how well a proposed set of parameters fits input data. Using simulations, we demonstrate that our methodology can accurately infer the indel parameters for a large variety of plausible settings. Moreover, using our methodology, we show that indel parameters substantially vary between three genomic data sets: Mammals, bacteria, and retroviruses. Finally, we demonstrate how our methodology can be used to simulate MSAs based on indel parameters inferred from real data sets.

Evolutionary genomics of host-use in bifurcating demes of RNA virus phi-6

BACKGROUND

Viruses are exceedingly diverse in their evolved strategies to manipulate hosts for viral replication. However, despite these differences, most virus populations will occasionally experience two commonly-encountered challenges: growth in variable host environments, and growth under fluctuating population sizes. We used the segmented RNA bacteriophage ϕ6 as a model for studying the evolutionary genomics of virus adaptation in the face of host switches and parametrically varying population sizes. To do so, we created a bifurcating deme structure that reflected lineage splitting in natural populations, allowing us to test whether phylogenetic algorithms could accurately resolve this 'known phylogeny'. The resulting tree yielded 32 clones at the tips and internal nodes; these strains were fully sequenced and measured for phenotypic changes in selected traits (fitness on original and novel hosts).

RESULTS

We observed that RNA segment size was negatively correlated with the extent of molecular change in the imposed treatments; molecular substitutions tended to cluster on the Small and Medium RNA chromosomes of the virus, and not on the Large segment. Our study yielded a very large molecular and phenotypic dataset, fostering possible inferences on genotype-phenotype associations. Using further experimental evolution, we confirmed an inference on the unanticipated role of an allelic switch in a viral assembly protein, which governed viral performance across host environments.

CONCLUSIONS

Our study demonstrated that varying complexities can be simultaneously incorporated into experimental evolution, to examine the combined effects of population size, and adaptation in novel environments. The imposed bifurcating structure revealed that some methods for phylogenetic reconstruction failed to resolve the true phylogeny, owing to a paucity of molecular substitutions separating the RNA viruses that evolved in our study.

Deep phylogeny--how a tree can help characterize early life on Earth

The Darwinian concept of biological evolution assumes that life on Earth shares a common ancestor. The diversification of this common ancestor through speciation events and vertical transmission of genetic material implies that the classification of life can be illustrated in a tree-like manner, commonly referred to as the Tree of Life. This article describes features of the Tree of Life, such as how the tree has been both pruned and become bushier throughout the past century as our knowledge of biology has expanded. We present current views that the classification of life may be best illustrated as a ring or even a coral with tree-like characteristics. This article also discusses how the organization of the Tree of Life offers clues about ancient life on Earth. In particular, we focus on the environmental conditions and temperature history of Precambrian life and show how chemical, biological, and geological data can converge to better understand this history."You know, a tree is a tree. How many more do you need to look at?"--Ronald Reagan (Governor of California), quoted in the Sacramento Bee, opposing expansion of Redwood National Park, March 3, 1966.

The effect of ambiguous data on phylogenetic estimates obtained by maximum likelihood and Bayesian inference

Although an increasing number of phylogenetic data sets are incomplete, the effect of ambiguous data on phylogenetic accuracy is not well understood. We use 4-taxon simulations to study the effects of ambiguous data (i.e., missing characters or gaps) in maximum likelihood (ML) and Bayesian frameworks. By introducing ambiguous data in a way that removes confounding factors, we provide the first clear understanding of 1 mechanism by which ambiguous data can mislead phylogenetic analyses. We find that in both ML and Bayesian frameworks, among-site rate variation can interact with ambiguous data to produce misleading estimates of topology and branch lengths. Furthermore, within a Bayesian framework, priors on branch lengths and rate heterogeneity parameters can exacerbate the effects of ambiguous data, resulting in strongly misleading bipartition posterior probabilities. The magnitude and direction of the ambiguous data bias are a function of the number and taxonomic distribution of ambiguous characters, the strength of topological support, and whether or not the model is correctly specified. The results of this study have major implications for all analyses that rely on accurate estimates of topology or branch lengths, including divergence time estimation, ancestral state reconstruction, tree-dependent comparative methods, rate variation analysis, phylogenetic hypothesis testing, and phylogeographic analysis.

Experimental evolution yields hundreds of mutations in a functional viral genome

Two lines of the bacteriophage T7 were grown to fix mutations indiscriminately, using a combination of population bottlenecks and mutagenesis. Complete genome sequences revealed 404 and 299 base substitutions in the two lines, the largest number characterized in functional microbial genomes so far. Missense substitutions outnumbered silent substitutions. Silent substitutions occurred at similar rates between essential and nonessential genes, but missense substitutions occurred at a higher rate in nonessential genes than in essential genes, as expected if they were less deleterious in the nonessential genes. Viral fitness declined during this protocol, and subsequent passaging of each mutated line in large population sizes restored some of the lost fitness. Substitution levels during these recoveries were less than 6% of those during the bottleneck phase, and only two changes during recovery were reversions of the original mutations. Exchanges of genomic fragments between the two recovered lines revealed that fitness effects of some substitutions were not additive-that interactions were accumulating which could lead to incompatibility between the diverged genomes. Based on these results, unprecedented high rates of nucleotide and functional divergence in viral genomes should be attainable experimentally by using repeated population bottlenecks at a high mutation rate interspersed with recovery.

Distinguishing between selection and population expansion in an experimental lineage of bacteriophage T7

Experimental evolution of short-lived organisms offers the opportunity to study the dynamics of polymorphism over time in a controlled environment. Here, we characterize DNA polymorphism data over time for four genes in bacteriophage T7. Our experiment ran for 2500 generations and populations were sampled after 500, 2000, and 2500 generations. We detect positive selection, purifying ("negative") selection, and population expansion in our experiment. We also present a statistical test that is able to distinguish demographic from selective events, processes that are hard to identify individually because both often produce an excess of rare mutations. Our "heterogeneity test" modifies common statistics measuring the frequency spectrum of polymorphism (e.g., Fu and Li's D) by looking for processes producing different patterns on nonsynonymous and synonymous mutations. Test results agree with the known conditions of the experiment, and we are therefore confident that this test offers a tool to evaluate natural populations. Our results suggest that instances of segregating deleterious mutations may be common, but as yet undetected, in nature.

Experimental phylogeny of neutrally evolving DNA sequences generated by a bifurcate series of nested polymerase chain reactions

A known phylogeny was generated using a four-step serial bifurcate PCR method. The ancestor sequence (SSU rDNA) evolved in vitro for 280 nested PCR cycles, and the resulting 15 ancestor and 16 terminal sequences (2,238 bp each) were determined. Parsimony, distance, and maximum likelihood analysis of the terminal sequences reconstructed the topology of the real phylogeny and branch lengths accurately. Divergence dates and ancestor sequences were estimated with very small error, particularly at the base of the phylogeny, mostly due to insertion and deletion changes. The substitution patterns along the known phylogeny are not described by reversible models, and accordingly, the probability substitution matrix, based on the observed substitutions from ancestor to terminal nodes along the known phylogeny, was calculated. This approach is an extension of previous studies using bacteriophage serial propagation, because here mutations were allowed to occur neutrally rather than by addition of a mutagenic agent, which produced biased mutational changes. These results provide for the first time biochemical experimental support for phylogenies, divergence date estimates, and an irreversible substitution model based on neutrally evolving DNA sequences. The substitution preferences observed here (A to G and T to C) are consistent with the high G+C content of the Thermus aquaticus genome. This suggests, at least in part, that the method here described, which explores the high Taq DNA polymerase error rate, simulates the evolution of a DNA segment in a thermophilic organism. These organisms include the bacterial rod T. aquaticus and several Archaea, and thus, the method and data set described here may well contribute new insights about the genome evolution of these organisms.

Replicability and recurrence in the experimental evolution of a group I ribozyme

In order to explore the variety of possible responses available to a ribozyme population evolving a novel phenotype, five Tetrahymena thermophila group I intron ribozyme pools were evolved in parallel for cleavage of a DNA oligonucleotide. These ribozyme populations were propagated under identical conditions and characterized when they reached apparent phenotypic plateaus; the populations that reached the highest plateau showed a near 100-fold improvement in DNA cleavage activity. A detailed characterization of the evolved response in these populations reveals at least two distinct phenotypic trajectories emerging as a result of the imposed selection. Not only do these distinct solutions exhibit differential DNA cleavage activity, but they also exhibit a very different correlation with a related, but unselected, phenotype: RNA cleavage activity. In turn, each of these trajectories is underwritten by differing genotypic profiles. This study underscores the complex network of possible trajectories through sequence space available to an evolving population and uncovers the diversity of solutions that result when the process of experimental evolution is repeated multiple times in a simple, engineered system.

Application and accuracy of molecular phylogenies

Molecular investigations of evolutionary history are being used to study subjects as diverse as the epidemiology of acquired immune deficiency syndrome and the origin of life. These studies depend on accurate estimates of phylogeny. The performance of methods of phylogenetic analysis can be assessed by numerical simulation studies and by the experimental evolution of organisms in controlled laboratory situations. Both kinds of assessment indicate that existing methods are effective at estimating phylogenies over a wide range of evolutionary conditions, especially if information about substitution bias is used to provide differential weightings for character transformations.