Inference and characterization of horizontally transferred gene families using stochastic mapping

Timescale and genetic linkage explain the variable impact of defense systems on horizontal gene transfer

Prokaryotes have evolved a wide repertoire of defense systems to prevent invasion by mobile genetic elements (MGEs). However, because MGEs are vehicles for the exchange of beneficial accessory genes, defense systems could consequently impede rapid adaptation in microbial populations. Here, we study how defense systems impact horizontal gene transfer (HGT) in the short term and long term. By combining comparative genomics and phylogeny-aware statistical methods, we quantify the association between the presence of seven widespread defense systems and the abundance of MGEs in the genomes of 196 bacterial and one archaeal species. We also calculate the differences in the rates of gene gain and loss between lineages that possess and lack each defense system. Our results show that the impact of defense systems on HGT is highly taxon and system dependent and, in most cases, not statistically significant. Timescale analysis reveals that defense systems must persist in a lineage for a relatively long time to exert an appreciable negative impact on HGT. In contrast, for shorter evolutionary timescales, frequent coacquisition of MGEs and defense systems results in a net positive association of the latter with HGT. Given the high turnover rates experienced by defense systems, we propose that the inhibitory effect of most defense systems on HGT is masked by their strong linkage with MGEs. These findings help explain the contradictory conclusions of previous research by pointing at mobility and within-host retention times as key factors that determine the impact of defense systems on genome plasticity.

Persistent, Private, and Mobile Genes: A Model for Gene Dynamics in Evolving Pangenomes

The pangenome of a species is the set of all genes carried by at least one member of the species. In bacteria, pangenomes can be much larger than the set of genes carried by a single organism. Many questions remain unanswered regarding the evolutionary forces shaping the patterns of the presence/absence of genes in pangenomes of a given species. We introduce a new model for bacterial pangenome evolution along a species phylogeny that explicitly describes the timing of appearance of each gene in the species and accounts for three generic types of gene evolutionary dynamics: persistent genes that are present in the ancestral genome, private genes that are specific to a given clade, and mobile genes that are imported once into the gene pool and then undergo frequent horizontal gene transfers. We call this model the Persistent-Private-Mobile (PPM) model. We develop an algorithm fitting the PPM model and apply it to a dataset of 902 Salmonella enterica genomes. We show that the best fitting model is able to reproduce the global pattern of some multivariate statistics like the gene frequency spectrum and the parsimony vs. frequency plot. Moreover, the gene classification induced by the PPM model allows us to study the position of accessory genes on the chromosome depending on their category, as well as the gene functions that are most present in each category. This work paves the way for a mechanistic understanding of pangenome evolution, and the PPM model developed here could be used for dynamics-aware gene classification.

A global survey of prokaryotic genomes reveals the eco-evolutionary pressures driving horizontal gene transfer

Horizontal gene transfer, the exchange of genetic material through means other than reproduction, is a fundamental force in prokaryotic genome evolution. Genomic persistence of horizontally transferred genes has been shown to be influenced by both ecological and evolutionary factors. However, there is limited availability of ecological information about species other than the habitats from which they were isolated, which has prevented a deeper exploration of ecological contributions to horizontal gene transfer. Here we focus on transfers detected through comparison of individual gene trees to the species tree, assessing the distribution of gene-exchanging prokaryotes across over a million environmental sequencing samples. By analysing detected horizontal gene transfer events, we show distinct functional profiles for recent versus old events. Although most genes transferred are part of the accessory genome, genes transferred earlier in evolution tend to be more ubiquitous within present-day species. We find that co-occurring, interacting and high-abundance species tend to exchange more genes. Finally, we show that host-associated specialist species are most likely to exchange genes with other host-associated specialist species, whereas species found across different habitats have similar gene exchange rates irrespective of their preferred habitat. Our study covers an unprecedented scale of integrated horizontal gene transfer and environmental information, highlighting broad eco-evolutionary trends.

Comparison of gene clustering criteria reveals intrinsic uncertainty in pangenome analyses

BACKGROUND

A key step for comparative genomics is to group open reading frames into functionally and evolutionarily meaningful gene clusters. Gene clustering is complicated by intraspecific duplications and horizontal gene transfers that are frequent in prokaryotes. In consequence, gene clustering methods must deal with a trade-off between identifying vertically transmitted representatives of multicopy gene families, which are recognizable by synteny conservation, and retrieving complete sets of species-level orthologs. We studied the implications of adopting homology, orthology, or synteny conservation as formal criteria for gene clustering by performing comparative analyses of 125 prokaryotic pangenomes.

RESULTS

Clustering criteria affect pangenome functional characterization, core genome inference, and reconstruction of ancestral gene content to different extents. Species-wise estimates of pangenome and core genome sizes change by the same factor when using different clustering criteria, allowing robust cross-species comparisons regardless of the clustering criterion. However, cross-species comparisons of genome plasticity and functional profiles are substantially affected by inconsistencies among clustering criteria. Such inconsistencies are driven not only by mobile genetic elements, but also by genes involved in defense, secondary metabolism, and other accessory functions. In some pangenome features, the variability attributed to methodological inconsistencies can even exceed the effect sizes of ecological and phylogenetic variables.

CONCLUSIONS

Choosing an appropriate criterion for gene clustering is critical to conduct unbiased pangenome analyses. We provide practical guidelines to choose the right method depending on the research goals and the quality of genome assemblies, and a benchmarking dataset to assess the robustness and reproducibility of future comparative studies.

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens.

Differences in genetic flux in invasive Streptococcus pneumoniae associated with bacteraemia and meningitis

Background

Genetic flux, a crucial process of pneumococcal evolution, is an essential aspect of bacterial physiology during human pathogenesis. However, the role of these genetic changes and the selective forces that drive them is not fully understood. Elucidating the underlying selective forces that determine the magnitude and direction (gene gain or loss) of gene transfer is important for better understanding the pathogenesis process, and may also highlight potential therapeutic and diagnostic targets.

Methods

Here, we leveraged data from high throughput genome sequencing and robust probabilistic models to discover the magnitude and likely direction of genetic flux events, but not the source, in 209 multi-lineage invasive pneumococcal genomes generated from blood (n = 147) and CSF (n = 62) isolates, associated with bacteremia and meningitis respectively. The Gain and Loss Mapping Engine (GLOOME) was used to infer gene gain and loss more accurately by taking into account differences in rates of gene gain and loss among gene families, as well as independent evolution within and across lineages.

Results

Our results show the likely extent and direction of gene fluctuations at different niche, during pneumococcal pathogenesis, highlighting that evolutionary dynamics are important for tissue-specific host invasion and survival.

Conclusion

These findings improve insights on evolutionary dynamics during invasive pneumococcal disease, and highlight potential diagnostic and therapeutic targets.

Evolution of the connectivity and indispensability of a transferable gene: the simplicity hypothesis

BACKGROUND

The number of interactions between a transferable gene or its protein product and genes or gene products native to its microbial host is referred to as connectivity. Such interactions impact the tendency of the gene to be retained by evolution following horizontal gene transfer (HGT) into a microbial population. The complexity hypothesis posits that the protein product of a transferable gene with lower connectivity is more likely to function in a way that is beneficial to a new microbial host compared to the protein product of a transferable gene with higher connectivity. A gene with lower connectivity is consequently more likely to be fixed in any microbial population it enters by HGT. The more recently proposed simplicity hypothesis posits that the connectivity of a transferable gene might increase over time within any single microbial population due to gene-host coevolution, but that differential rates of colonization of microbial populations by HGT in accordance with differences in connectivity might act to counter this and even reduce connectivity over time, comprising an evolutionary trade-off.

RESULTS

We present a theoretical model that can be used to predict the conditions under which gene-host coevolution might increase or decrease the connectivity of a transferable gene over time. We show that the opportunity to enter new microbial populations by HGT can cause the connectivity of a transferable gene to evolve toward lower values, particularly in an environment that is unstable with respect to the function of the gene's protein product. We also show that a lack of such opportunity in a stable environment can cause the connectivity of a transferable gene to evolve toward higher values.

CONCLUSION

Our theoretical model suggests that the connectivity of a transferable gene can change over time toward higher values corresponding to a more sessile state of lower transferability or lower values corresponding to a more itinerant state of higher transferability, depending on the ecological milieu in which the gene exists. We note, however, that a better understanding of gene-host coevolutionary dynamics in natural microbial systems is required before any further conclusions about the veracity of the simplicity hypothesis can be drawn.

Realistic Gene Transfer to Gene Duplication Ratios Identify Different Roots in the Bacterial Phylogeny Using a Tree Reconciliation Method

The rooting of phylogenetic trees permits important inferences about ancestral states and the polarity of evolutionary events. Recently, methods that reconcile discordance between gene-trees and species-trees—tree reconciliation methods—are becoming increasingly popular for rooting species trees. Rooting via reconciliation requires values for a particular parameter, the gene transfer to gene duplication ratio (T:D), which in current practice is estimated on the fly from discordances observed in the trees. To date, the accuracy of T:D estimates obtained by reconciliation analyses has not been compared to T:D estimates obtained by independent means, hence the effect of T:D upon inferences of species tree roots is altogether unexplored. Here we investigated the issue in detail by performing tree reconciliations of more than 10,000 gene trees under a variety of T:D ratios for two phylogenetic cases: a bacterial (prokaryotic) tree with 265 species and a fungal-metazoan (eukaryotic) tree with 31 species. We show that the T:D ratios automatically estimated by a current tree reconciliation method, ALE, generate virtually identical T:D ratios across bacterial genes and fungal-metazoan genes. The T:D ratios estimated by ALE differ 10- to 100-fold from robust, ALE-independent estimates from real data. More important is our finding that the root inferences using ALE in both datasets are strongly dependent upon T:D. Using more realistic T:D ratios, the number of roots inferred by ALE consistently increases and, in some cases, clearly incorrect roots are inferred. Furthermore, our analyses reveal that gene duplications have a far greater impact on ALE’s preferences for phylogenetic root placement than gene transfers or gene losses do. Overall, we show that obtaining reliable species tree roots with ALE is only possible when gene duplications are abundant in the data and the number of falsely inferred gene duplications is low. Finding a sufficient sample of true gene duplications for rooting species trees critically depends on the T:D ratios used in the analyses. T:D ratios, while being important parameters of genome evolution in their own right, affect the root inferences with tree reconciliations to an unanticipated degree.

Mirage: estimation of ancestral gene-copy numbers by considering different evolutionary patterns among gene families

Motivation

Reconstruction of gene copy number evolution is an essential approach for understanding how complex biological systems have been organized. Although various models have been proposed for gene copy number evolution, existing evolutionary models have not appropriately addressed the fact that different gene families can have very different gene gain/loss rates.

Results

In this study, we developed Mirage (MIxtuRe model for Ancestral Genome Estimation), which allows different gene families to have flexible gene gain/loss rates. Mirage can use three models for formulating heterogeneous evolution among gene families: the discretized Γ model, probability distribution-free model and pattern mixture (PM) model. Simulation analysis showed that Mirage can accurately estimate heterogeneous gene gain/loss rates and reconstruct gene-content evolutionary history. Application to empirical datasets demonstrated that the PM model fits genome data from various taxonomic groups better than the other heterogeneous models. Using Mirage, we revealed that metabolic function-related gene families displayed frequent gene gains and losses in all taxa investigated.

Availability and implementation

The source code of Mirage is freely available at https://github.com/fukunagatsu/Mirage.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Molecular Evolution of Pseudomonas syringae Type III Secreted Effector Proteins

Diverse Gram-negative pathogens like Pseudomonas syringae employ type III secreted effector (T3SE) proteins as primary virulence factors that combat host immunity and promote disease. T3SEs can also be recognized by plant hosts and activate an effector triggered immune (ETI) response that shifts the interaction back toward plant immunity. Consequently, T3SEs are pivotal in determining the virulence potential of individual P. syringae strains, and ultimately help to restrict P. syringae pathogens to a subset of potential hosts that are unable to recognize their repertoires of T3SEs. While a number of effector families are known to be present in the P. syringae species complex, one of the most persistent challenges has been documenting the complex variation in T3SE contents across a diverse collection of strains. Using the entire pan-genome of 494 P. syringae strains isolated from more than 100 hosts, we conducted a global analysis of all known and putative T3SEs. We identified a total of 14,613 putative T3SEs, 4,636 of which were unique at the amino acid level, and show that T3SE repertoires of different P. syringae strains vary dramatically, even among strains isolated from the same hosts. We also find substantial diversification within many T3SE families, and in many cases find strong signatures of positive selection. Furthermore, we identify multiple gene gain and loss events for several families, demonstrating an important role of horizontal gene transfer (HGT) in the evolution of P. syringae T3SEs. These analyses provide insight into the evolutionary history of P. syringae T3SEs as they co-evolve with the host immune system, and dramatically expand the database of P. syringae T3SEs alleles.

Avoiding Regions Symptomatic of Conformational and Functional Flexibility to Identify Antiviral Targets in Current and Future Coronaviruses

Within the last 15 years, two related coronaviruses (Severe Acute Respiratory Syndrome [SARS]-CoV and Middle East Respiratory Syndrome [MERS]-CoV) expanded their host range to include humans, with increased virulence in their new host. Coronaviruses were recently found to have little intrinsic disorder compared with many other virus families. Because intrinsically disordered regions have been proposed to be important for rewiring interactions between virus and host, we investigated the conservation of intrinsic disorder and secondary structure in coronaviruses in an evolutionary context. We found that regions of intrinsic disorder are rarely conserved among different coronavirus protein families, with the primary exception of the nucleocapsid. Also, secondary structure predictions are only conserved across 50–80% of sites for most protein families, with the implication that 20–50% of sites do not have conserved secondary structure prediction. Furthermore, nonconserved structure sites are significantly less constrained in sequence divergence than either sites conserved in the secondary structure or sites conserved in loop. Avoiding regions symptomatic of conformational flexibility such as disordered sites and sites with nonconserved secondary structure to identify potential broad-specificity antiviral targets, only one sequence motif (five residues or longer) remains from the >10,000 starting sites across all coronaviruses in this study. The identified sequence motif is found within the nonstructural protein (NSP) 12 and constitutes an antiviral target potentially effective against the present day and future coronaviruses. On shorter evolutionary timescales, the SARS and MERS clades have more sequence motifs fulfilling the criteria applied. Interestingly, many motifs map to NSP12 making this a prime target for coronavirus antivirals.

From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer

Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.

The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar.

IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.

Estimation of Gene Insertion/Deletion Rates with Missing Data

Lateral gene transfer is an important mechanism for evolution among bacteria. Here, genome-wide gene insertion and deletion rates are modeled in a maximum-likelihood framework with the additional flexibility of modeling potential missing data. The performance of the models is illustrated using simulations and a data set on gene family phyletic patterns from Gardnerella vaginalis that includes an ancient taxon. A novel application involving pseudogenization/genome reduction magnitudes is also illustrated, using gene family data from Mycobacterium spp. Finally, an R package called indelmiss is available from the Comprehensive R Archive Network at https://cran.r-project.org/package=indelmiss, with support documentation and examples.

SICLE: a high-throughput tool for extracting evolutionary relationships from phylogenetic trees

We present the phylogeny analysis software SICLE (Sister Clade Extractor), an easy-to-use, high-throughput tool to describe the nearest neighbors to a node of interest in a phylogenetic tree as well as the support value for the relationship. The application is a command line utility that can be embedded into a phylogenetic analysis pipeline or can be used as a subroutine within another C++ program. As a test case, we applied this new tool to the published phylome of Salinibacter ruber, a species of halophilic Bacteriodetes, identifying 13 unique sister relationships to S. ruber across the 4,589 gene phylogenies. S. ruber grouped with bacteria, most often other Bacteriodetes, in the majority of phylogenies, but 91 phylogenies showed a branch-supported sister association between S. ruber and Archaea, an evolutionarily intriguing relationship indicative of horizontal gene transfer. This test case demonstrates how SICLE makes it possible to summarize the phylogenetic information produced by automated phylogenetic pipelines to rapidly identify and quantify the possible evolutionary relationships that merit further investigation. SICLE is available for free for noncommercial use at http://eebweb.arizona.edu/sicle/.

The Landscape of A-to-I RNA Editome Is Shaped by Both Positive and Purifying Selection

The hydrolytic deamination of adenosine to inosine (A-to-I editing) in precursor mRNA induces variable gene products at the post-transcription level. How and to what extent A-to-I RNA editing diversifies transcriptome is not fully characterized in the evolution, and very little is known about the selective constraints that drive the evolution of RNA editing events. Here we present a study on A-to-I RNA editing, by generating a global profile of A-to-I editing for a phylogeny of seven Drosophila species, a model system spanning an evolutionary timeframe of approximately 45 million years. Of totally 9281 editing events identified, 5150 (55.5%) are located in the coding sequences (CDS) of 2734 genes. Phylogenetic analysis places these genes into 1,526 homologous families, about 5% of total gene families in the fly lineages. Based on conservation of the editing sites, the editing events in CDS are categorized into three distinct types, representing events on singleton genes (type I), and events not conserved (type II) or conserved (type III) within multi-gene families. While both type I and II events are subject to purifying selection, notably type III events are positively selected, and highly enriched in the components and functions of the nervous system. The tissue profiles are documented for three editing types, and their critical roles are further implicated by their shifting patterns during holometabolous development and in post-mating response. In conclusion, three A-to-I RNA editing types are found to have distinct evolutionary dynamics. It appears that nervous system functions are mainly tested to determine if an A-to-I editing is beneficial for an organism. The coding plasticity enabled by A-to-I editing creates a new class of binary variations, which is a superior alternative to maintain heterozygosity of expressed genes in a diploid mating system.

One prevalent form of RNA editing is the deamination of adenosines (A-to-I editing) in the precursor mRNA molecules, pertaining to most organisms in the metazoan lineage. While examples of A-to-I editing on critical genes have been known for years, it has not been fully characterized how A-to-I editing shapes the transcriptome and proteome in the evolution. To understand how A-to-I editing affects genes’ evolution and how itself is constrained by selection, we generated a global profile of A-to-I editing for a phylogeny of seven fly species, a model system representing an evolutionary timeframe of about 45 million years. We are focused on 5150 editing sites (of totally 9281 identified) located in the coding region of 2734 genes. Our analysis revealed the evolution dynamics of A-to-I editing sites and functional specificity of targeted genes. The shifting patterns of A-to-I editing are documented during holometabolous development and in post-mating response in flies. This work points to the important roles of regulated RNA editing in animal development and offers new insight into the evolution of A-to-I editing events and their harboring genes.

Genome-scale phylogenetic analysis finds extensive gene transfer among fungi

Although the role of lateral gene transfer is well recognized in the evolution of bacteria, it is generally assumed that it has had less influence among eukaryotes. To explore this hypothesis, we compare the dynamics of genome evolution in two groups of organisms: cyanobacteria and fungi. Ancestral genomes are inferred in both clades using two types of methods: first, Count, a gene tree unaware method that models gene duplications, gains and losses to explain the observed numbers of genes present in a genome; second, ALE, a more recent gene tree-aware method that reconciles gene trees with a species tree using a model of gene duplication, loss and transfer. We compare their merits and their ability to quantify the role of transfers, and assess the impact of taxonomic sampling on their inferences. We present what we believe is compelling evidence that gene transfer plays a significant role in the evolution of fungi.

Regulation of genetic flux between bacteria by restriction-modification systems

Restriction-modification (R-M) systems are often regarded as bacteria's innate immune systems, protecting cells from infection by mobile genetic elements (MGEs). Their diversification has been recently associated with the emergence of particularly virulent lineages. However, we have previously found more R-M systems in genomes carrying more MGEs. Furthermore, it has been suggested that R-M systems might favor genetic transfer by producing recombinogenic double-stranded DNA ends. To test whether R-M systems favor or disfavor genetic exchanges, we analyzed their frequency with respect to the inferred events of homologous recombination and horizontal gene transfer within 79 bacterial species. Genetic exchanges were more frequent in bacteria with larger genomes and in those encoding more R-M systems. We created a recognition target motif predictor for Type II R-M systems that identifies genomes encoding systems with similar restriction sites. We found more genetic exchanges between these genomes, independently of their evolutionary distance. Our results reconcile previous studies by showing that R-M systems are more abundant in promiscuous species, wherein they establish preferential paths of genetic exchange within and between lineages with cognate R-M systems. Because the repertoire and/or specificity of R-M systems in bacterial lineages vary quickly, the preferential fluxes of genetic transfer within species are expected to constantly change, producing time-dependent networks of gene transfer.

Evolutionary assembly patterns of prokaryotic genomes

Evolutionary innovation must occur in the context of some genomic background, which limits available evolutionary paths. For example, protein evolution by sequence substitution is constrained by epistasis between residues. In prokaryotes, evolutionary innovation frequently happens by macrogenomic events such as horizontal gene transfer (HGT). Previous work has suggested that HGT can be influenced by ancestral genomic content, yet the extent of such gene-level constraints has not yet been systematically characterized. Here, we evaluated the evolutionary impact of such constraints in prokaryotes, using probabilistic ancestral reconstructions from 634 extant prokaryotic genomes and a novel framework for detecting evolutionary constraints on HGT events. We identified 8228 directional dependencies between genes and demonstrated that many such dependencies reflect known functional relationships, including for example, evolutionary dependencies of the photosynthetic enzyme RuBisCO. Modeling all dependencies as a network, we adapted an approach from graph theory to establish chronological precedence in the acquisition of different genomic functions. Specifically, we demonstrated that specific functions tend to be gained sequentially, suggesting that evolution in prokaryotes is governed by functional assembly patterns. Finally, we showed that these dependencies are universal rather than clade-specific and are often sufficient for predicting whether or not a given ancestral genome will acquire specific genes. Combined, our results indicate that evolutionary innovation via HGT is profoundly constrained by epistasis and historical contingency, similar to the evolution of proteins and phenotypic characters, and suggest that the emergence of specific metabolic and pathological phenotypes in prokaryotes can be predictable from current genomes.

Unique β-Glucuronidase Locus in Gut Microbiomes of Crohn's Disease Patients and Unaffected First-Degree Relatives

Crohn's disease, an incurable chronic inflammatory bowel disease, has been attributed to both genetic predisposition and environmental factors. A dysbiosis of the gut microbiota, observed in numerous patients but also in at least one hundred unaffected first-degree relatives, was proposed to have a causal role. Gut microbiota β-D-glucuronidases (EC 3.2.1.33) hydrolyse β-D-glucuronate from glucuronidated compounds. They include a GUS group, that is homologous to the Escherichia coli GusA, and a BG group, that is homologous to metagenomically identified H11G11 BG and has unidentified natural substrates. H11G11 BG is part of the functional core of the human gut microbiota whereas GusA, known to regenerate various toxic products, is variably found in human subjects. We investigated potential risk markers for Crohn's disease using DNA-sequence-based exploration of the β-D-glucuronidase loci (GUS or Firmicute H11G11-BG and the respective co-encoded glucuronide transporters). Crohn's disease-related microbiomes revealed a higher frequency of a C7D2 glucuronide transporter (12/13) compared to unrelated healthy subjects (8/32). This transporter was in synteny with the potential harmful GUS β-D-glucuronidase as only observed in a Eubacterium eligens plasmid. A conserved NH2-terminal sequence in the transporter (FGDFGND motif) was found in 83% of the disease-related subjects and only in 12% of controls. We propose a microbiota-pathology hypothesis in which the presence of this unique β-glucuronidase locus may contribute to an increase risk for Crohn's disease.

Genomic analysis of 38 Legionella species identifies large and diverse effector repertoires

Infection by the human pathogen Legionella pneumophila relies on the translocation of ∼ 300 virulence proteins, termed effectors, which manipulate host cell processes. However, almost no information exists regarding effectors in other Legionella pathogens. Here we sequenced, assembled and characterized the genomes of 38 Legionella species and predicted their effector repertoires using a previously validated machine learning approach. This analysis identified 5,885 predicted effectors. The effector repertoires of different Legionella species were found to be largely non-overlapping, and only seven core effectors were shared by all species studied. Species-specific effectors had atypically low GC content, suggesting exogenous acquisition, possibly from the natural protozoan hosts of these species. Furthermore, we detected numerous new conserved effector domains and discovered new domain combinations, which allowed the inference of as yet undescribed effector functions. The effector collection and network of domain architectures described here can serve as a roadmap for future studies of effector function and evolution.

markophylo: Markov chain analysis on phylogenetic trees

SUMMARY

Continuous-time Markov chain models with finite state space are routinely used for analysis of discrete character data on phylogenetic trees. Examples of such discrete character data include restriction sites, gene family presence/absence, intron presence/absence and gene family size data. While models with constrained substitution rate matrices have been used to good effect, more biologically realistic models have been increasingly implemented in the recent literature combining, e.g., site rate variation, site partitioning, branch-specific rates, allowing for non-stationary prior root probabilities, correcting for sampling bias, etc. to name a few. Here, a flexible and fast R package is introduced that infers evolutionary rates of discrete characters on a tree within a probabilistic framework. The package, markophylo, fits maximum-likelihood models using Markov chains on phylogenetic trees. The package is efficient, with the workhorse functions written in C++ and the interface in user-friendly R.

AVAILABILITY AND IMPLEMENTATION

markophylo is available as a platform-independent R package from the Comprehensive R Archive Network at https://cran.r-project.org/web/packages/markophylo/. A vignette with numerous examples is also provided with the R package.

CONTACT

udang@mcmaster.ca

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evidence of ancient genome reduction in red algae (Rhodophyta)

Red algae (Rhodophyta) comprise a monophyletic eukaryotic lineage of ~6,500 species with a fossil record that extends back 1.2 billion years. A surprising aspect of red algal evolution is that sequenced genomes encode a relatively limited gene inventory (~5-10 thousand genes) when compared with other free-living algae or to other eukaryotes. This suggests that the common ancestor of red algae may have undergone extensive genome reduction, which can result from lineage specialization to a symbiotic or parasitic lifestyle or adaptation to an extreme or oligotrophic environment. We gathered genome and transcriptome data from a total of 14 red algal genera that represent the major branches of this phylum to study genome evolution in Rhodophyta. Analysis of orthologous gene gains and losses identifies two putative major phases of genome reduction: (i) in the stem lineage leading to all red algae resulting in the loss of major functions such as flagellae and basal bodies, the glycosyl-phosphatidylinositol anchor biosynthesis pathway, and the autophagy regulation pathway; and (ii) in the common ancestor of the extremophilic Cyanidiophytina. Red algal genomes are also characterized by the recruitment of hundreds of bacterial genes through horizontal gene transfer that have taken on multiple functions in shared pathways and have replaced eukaryotic gene homologs. Our results suggest that Rhodophyta may trace their origin to a gene depauperate ancestor. Unlike plants, it appears that a limited gene inventory is sufficient to support the diversification of a major eukaryote lineage that possesses sophisticated multicellular reproductive structures and an elaborate triphasic sexual cycle.

Pre_GI: a global map of ontological links between horizontally transferred genomic islands in bacterial and archaeal genomes

The Predicted Genomic Islands database (Pre_GI) is a comprehensive repository of prokaryotic genomic islands (islands, GIs) freely accessible at http://pregi.bi.up.ac.za/index.php. Pre_GI, Version 2015, catalogues 26 744 islands identified in 2407 bacterial/archaeal chromosomes and plasmids. It provides an easy-to-use interface which allows users the ability to query against the database with a variety of fields, parameters and associations. Pre_GI is constructed to be a web-resource for the analysis of ontological roads between islands and cartographic analysis of the global fluxes of mobile genetic elements through bacterial and archaeal taxonomic borders. Comparison of newly identified islands against Pre_GI presents an alternative avenue to identify their ontology, origin and relative time of acquisition. Pre_GI aims to aid research on horizontal transfer events and materials through providing data and tools for holistic investigation of migration of genes through ecological niches and taxonomic boundaries.

Phylogenomic study indicates widespread lateral gene transfer in Entamoeba and suggests a past intimate relationship with parabasalids

Lateral gene transfer (LGT) has impacted the evolutionary history of eukaryotes, though to a lesser extent than in bacteria and archaea. Detecting LGT and distinguishing it from single gene tree artifacts is difficult, particularly when considering very ancient events (i.e., over hundreds of millions of years). Here, we use two independent lines of evidence--a taxon-rich phylogenetic approach and an assessment of the patterns of gene presence/absence--to evaluate the extent of LGT in the parasitic amoebozoan genus Entamoeba. Previous work has suggested that a number of genes in the genome of Entamoeba spp. were acquired by LGT. Our approach, using an automated phylogenomic pipeline to build taxon-rich gene trees, suggests that LGT is more extensive than previously thought. Our analyses reveal that genes have frequently entered the Entamoeba genome via nonvertical events, including at least 116 genes acquired directly from bacteria or archaea, plus an additional 22 genes in which Entamoeba plus one other eukaryote are nested among bacteria and/or archaea. These genes may make good candidates for novel therapeutics, as drugs targeting these genes are less likely to impact the human host. Although we recognize the challenges of inferring intradomain transfers given systematic errors in gene trees, we find 109 genes supporting LGT from a eukaryote to Entamoeba spp., and 178 genes unique to Entamoeba spp. and one other eukaryotic taxon (i.e., presence/absence data). Inspection of these intradomain LGTs provide evidence of a common sister relationship between genes of Entamoeba (Amoebozoa) and parabasalids (Excavata). We speculate that this indicates a past close relationship (e.g., symbiosis) between ancestors of these extant lineages.

Evolutionary patterns of Escherichia coli small RNAs and their regulatory interactions

Most bacterial small RNAs (sRNAs) are post-transcriptional regulators of gene expression, exerting their regulatory function by base-pairing with their target mRNAs. While it has become evident that sRNAs play central regulatory roles in the cell, little is known about their evolution and the evolution of their regulatory interactions. Here we used the prokaryotic phylogenetic tree to reconstruct the evolutionary history of Escherichia coli sRNAs and their binding sites on target mRNAs. We discovered that sRNAs currently present in E. coli mainly accumulated inside the Enterobacteriales order, succeeding the appearance of other types of noncoding RNAs and concurrently with the evolution of a variant of the Hfq protein exhibiting a longer C-terminal region. Our analysis of the evolutionary ages of sRNA-mRNA interactions revealed that while all sRNAs were evolutionarily older than most of their known binding sites on mRNA targets, for quite a few sRNAs there was at least one binding site that coappeared with or preceded them. It is conceivable that the establishment of these first interactions forced selective pressure on the sRNAs, after which additional targets were acquired by fitting a binding site to the active region of the sRNA. This conjecture is supported by the appearance of many binding sites on target mRNAs only after the sRNA gain, despite the prior presence of the target gene in ancestral genomes. Our results suggest a selective mechanism that maintained the sRNAs across the phylogenetic tree, and shed light on the evolution of E. coli post-transcriptional regulatory network.

The extent of genome flux and its role in the differentiation of bacterial lineages

Horizontal gene transfer (HGT) and gene loss are key processes in bacterial evolution. However, the role of gene gain and loss in the emergence and maintenance of ecologically differentiated bacterial populations remains an open question. Here, we use whole-genome sequence data to quantify gene gain and loss for 27 lineages of the plant-associated bacterium Pseudomonas syringae. We apply an extensive error-control procedure that accounts for errors in draft genome data and greatly improves the accuracy of patterns of gene occurrence among these genomes. We demonstrate a history of extensive genome fluctuation for this species and show that individual lineages could have acquired thousands of genes in the same period in which a 1% amino acid divergence accrues in the core genome. Elucidating the dynamics of genome fluctuation reveals the rapid turnover of gained genes, such that the majority of recently gained genes are quickly lost. Despite high observed rates of fluctuation, a phylogeny inferred from patterns of gene occurrence is similar to a phylogeny based on amino acid replacements within the core genome. Furthermore, the core genome phylogeny suggests that P. syringae should be considered a number of distinct species, with levels of divergence at least equivalent to those between recognized bacterial species. Gained genes are transferred from a variety of sources, reflecting the depth and diversity of the potential gene pool available via HGT. Overall, our results provide further insights into the evolutionary dynamics of genome fluctuation and implicate HGT as a major factor contributing to the diversification of P. syringae lineages.

Cross-species gene-family fluctuations reveal the dynamics of horizontal transfers

Prokaryotes vary their protein repertoire mainly through horizontal transfer and gene loss. To elucidate the links between these processes and the cross-species gene-family statistics, we perform a large-scale data analysis of the cross-species variability of gene-family abundance (the number of members of the family found on a given genome). We find that abundance fluctuations are related to the rate of horizontal transfers. This is rationalized by a minimal theoretical model, which predicts this link. The families that are not captured by the model show abundance profiles that are markedly peaked around a mean value, possibly because of specific abundance selection. Based on these results, we define an abundance variability index that captures a family's evolutionary behavior (and thus some of its relevant functional properties) purely based on its cross-species abundance fluctuations. Analysis and model, combined, show a quantitative link between cross-species family abundance statistics and horizontal transfer dynamics, which can be used to analyze genome ‘flux’. Groups of families with different values of the abundance variability index correspond to genome sub-parts having different plasticity in terms of the level of horizontal exchange allowed by natural selection.

Auxiliary tRNAs: large-scale analysis of tRNA genes reveals patterns of tRNA repertoire dynamics

Decoding of all codons can be achieved by a subset of tRNAs. In bacteria, certain tRNA species are mandatory, while others are auxiliary and are variably used. It is currently unknown how this variability has evolved and whether it provides an adaptive advantage. Here we shed light on the subset of auxiliary tRNAs, using genomic data from 319 bacteria. By reconstructing the evolution of tRNAs we show that the auxiliary tRNAs are highly dynamic, being frequently gained and lost along the phylogenetic tree, with a clear dominance of loss events for most auxiliary tRNA species. We reveal distinct co-gain and co-loss patterns for subsets of the auxiliary tRNAs, suggesting that they are subjected to the same selection forces. Controlling for phylogenetic dependencies, we find that the usage of these tRNA species is positively correlated with GC content and may derive directly from nucleotide bias or from preference of Watson-Crick codon-anticodon interactions. Our results highlight the highly dynamic nature of these tRNAs and their complicated balance with codon usage.

Cultivation and complete genome sequencing of Gloeobacter kilaueensis sp. nov., from a lava cave in Kīlauea Caldera, Hawai'i

The ancestor of Gloeobacter violaceus PCC 7421(T) is believed to have diverged from that of all known cyanobacteria before the evolution of thylakoid membranes and plant plastids. The long and largely independent evolutionary history of G. violaceus presents an organism retaining ancestral features of early oxygenic photoautotrophs, and in whom cyanobacteria evolution can be investigated. No other Gloeobacter species has been described since the genus was established in 1974 (Rippka et al., Arch Microbiol 100:435). Gloeobacter affiliated ribosomal gene sequences have been reported in environmental DNA libraries, but only the type strain's genome has been sequenced. However, we report here the cultivation of a new Gloeobacter species, G. kilaueensis JS1(T), from an epilithic biofilm in a lava cave in Kīlauea Caldera, Hawai'i. The strain's genome was sequenced from an enriched culture resembling a low-complexity metagenomic sample, using 9 kb paired-end 454 pyrosequences and 400 bp paired-end Illumina reads. The JS1(T) and G. violaceus PCC 7421(T) genomes have little gene synteny despite sharing 2842 orthologous genes; comparing the genomes shows they do not belong to the same species. Our results support establishing a new species to accommodate JS1(T), for which we propose the name Gloeobacter kilaueensis sp. nov. Strain JS1(T) has been deposited in the American Type Culture Collection (BAA-2537), the Scottish Marine Institute's Culture Collection of Algae and Protozoa (CCAP 1431/1), and the Belgian Coordinated Collections of Microorganisms (ULC0316). The G. kilaueensis holotype has been deposited in the Algal Collection of the US National Herbarium (US# 217948). The JS1(T) genome sequence has been deposited in GenBank under accession number CP003587. The G+C content of the genome is 60.54 mol%. The complete genome sequence of G. kilaueensis JS1(T) may further understanding of cyanobacteria evolution, and the shift from anoxygenic to oxygenic photosynthesis.

Examining marginal sequence similarities between bacterial type III secretion system components and Trypanosoma cruzi surface proteins: horizontal gene transfer or convergent evolution?

The cell invasion mechanism of Trypanosoma cruzi has similarities with some intracellular bacterial taxa especially regarding calcium mobilization. This mechanism is not observed in other trypanosomatids, suggesting that the molecules involved in this type of cell invasion were a product of (1) acquisition by horizontal gene transfer (HGT); (2) secondary loss in the other trypanosomatid lineages of the mechanism inherited since the bifurcation Bacteria-Neomura (1.9 billion to 900 million years ago); or (3) de novo evolution from non-homologous proteins via convergent evolution. Similar to T. cruzi, several bacterial genera require increased host cell cytosolic calcium for intracellular invasion. Among intracellular bacteria, the mechanism of host cell invasion of genus Salmonella is the most similar to T. cruzi. The invasion of Salmonella occurs by contact with the host's cell surface and is mediated by the type III secretion system (T3SS) that promotes the contact-dependent translocation of effector proteins directly into host's cell cytoplasm. Here we provide evidence of distant sequence similarities and structurally conserved domains between T. cruzi and Salmonella spp T3SS proteins. Exhaustive database searches were directed to a wide range of intracellular bacteria and trypanosomatids, exploring sequence patterns for comparison of structural similarities and Bayesian phylogenies. Based on our data we hypothesize that T. cruzi acquired genes for calcium mobilization mediated invasion by ancient HGT from ancestral Salmonella lineages.

CoPAP: Coevolution of presence-absence patterns

Evolutionary analysis of phyletic patterns (phylogenetic profiles) is widely used in biology, representing presence or absence of characters such as genes, restriction sites, introns, indels and methylation sites. The phyletic pattern observed in extant genomes is the result of ancestral gain and loss events along the phylogenetic tree. Here we present CoPAP (coevolution of presence–absence patterns), a user-friendly web server, which performs accurate inference of coevolving characters as manifested by co-occurring gains and losses. CoPAP uses state-of-the-art probabilistic methodologies to infer coevolution and allows for advanced network analysis and visualization. We developed a platform for comparing different algorithms that detect coevolution, which includes simulated data with pairs of coevolving sites and independent sites. Using these simulated data we demonstrate that CoPAP performance is higher than alternative methods. We exemplify CoPAP utility by analyzing coevolution among thousands of bacterial genes across 681 genomes. Clusters of coevolving genes that were detected using our method largely coincide with known biosynthesis pathways and cellular modules, thus exhibiting the capability of CoPAP to infer biologically meaningful interactions. CoPAP is freely available for use at http://copap.tau.ac.il/.

Uncovering the co-evolutionary network among prokaryotic genes

MOTIVATION

Correlated events of gains and losses enable inference of co-evolution relations. The reconstruction of the co-evolutionary interactions network in prokaryotic species may elucidate functional associations among genes.

RESULTS

We developed a novel probabilistic methodology for the detection of co-evolutionary interactions between pairs of genes. Using this method we inferred the co-evolutionary network among 4593 Clusters of Orthologous Genes (COGs). The number of co-evolutionary interactions substantially differed among COGs. Over 40% were found to co-evolve with at least one partner. We partitioned the network of co-evolutionary relations into clusters and uncovered multiple modular assemblies of genes with clearly defined functions. Finally, we measured the extent to which co-evolutionary relations coincide with other cellular relations such as genomic proximity, gene fusion propensity, co-expression, protein-protein interactions and metabolic connections. Our results show that co-evolutionary relations only partially overlap with these other types of networks. Our results suggest that the inferred co-evolutionary network in prokaryotes is highly informative towards revealing functional relations among genes, often showing signals that cannot be extracted from other network types.

AVAILABILITY AND IMPLEMENTATION

Available under GPL license as open source.

CONTACT

talp@post.tau.ac.il.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Meta-analysis of general bacterial subclades in whole-genome phylogenies using tree topology profiling

In the last two decades, a large number of whole-genome phylogenies have been inferred to reconstruct the Tree of Life (ToL). Underlying data models range from gene or functionality content in species to phylogenetic gene family trees and multiple sequence alignments of concatenated protein sequences. Diversity in data models together with the use of different tree reconstruction techniques, disruptive biological effects and the steadily increasing number of genomes have led to a huge diversity in published phylogenies. Comparison of those and, moreover, identification of the impact of inference properties (underlying data model, inference technique) on particular reconstructions is almost impossible. In this work, we introduce tree topology profiling as a method to compare already published whole-genome phylogenies. This method requires visual determination of the particular topology in a drawn whole-genome phylogeny for a set of particular bacterial clans. For each clan, neighborhoods to other bacteria are collected into a catalogue of generalized alternative topologies. Particular topology alternatives found for an ordered list of bacterial clans reveal a topology profile that represents the analyzed phylogeny. To simulate the inhomogeneity of published gene content phylogenies we generate a set of seven phylogenies using different inference techniques and the SYSTERS-PhyloMatrix data model. After tree topology profiling on in total 54 selected published and newly inferred phylogenies, we separate artefactual from biologically meaningful phylogenies and associate particular inference results (phylogenies) with inference background (inference techniques as well as data models). Topological relationships of particular bacterial species groups are presented. With this work we introduce tree topology profiling into the scientific field of comparative phylogenomics.

Measuring microsatellite conservation in mammalian evolution with a phylogenetic birth-death model

Microsatellites make up ∼3% of the human genome, and there is increasing evidence that some microsatellites can have important functions and can be conserved by selection. To investigate this conservation, we performed a genome-wide analysis of human microsatellites and measured their conservation using a binary character birth--death model on a mammalian phylogeny. Using a maximum likelihood method to estimate birth and death rates for different types of microsatellites, we show that the rates at which microsatellites are gained and lost in mammals depend on their sequence composition, length, and position in the genome. Additionally, we use a mixture model to account for unequal death rates among microsatellites across the human genome. We use this model to assign a probability-based conservation score to each microsatellite. We found that microsatellites near the transcription start sites of genes are often highly conserved, and that distance from a microsatellite to the nearest transcription start site is a good predictor of the microsatellite conservation score. An analysis of gene ontology terms for genes that contain microsatellites near their transcription start site reveals that regulatory genes involved in growth and development are highly enriched with conserved microsatellites.

The evolution of an ancient metazoan biomineralization strategy was supported by a horizontal gene transfer

The molecular mechanisms that generate morphological novelty are of great interest to evolutionary biologists because these are the processes that can explain how the diversity of life on earth arose. With advances in sequencing technologies, the high-throughput analysis and comparison of entire genomes is now possible. Bioinformatic mining of such genome-wide data sets often includes a search for horizontal gene transfers (HGTs) as these events can provide exciting insight into how morphological, or physiological novelties may have arisen. A recent paper by Jackson et al.1 demonstrates that a HGT into the genome of the sponge Astrosclera willeyana likely supported the evolution of this animal's biomineralization strategy. This HGT, which occurred deep in time, was perhaps a key event in the evolution of this animal's body form and would not have been detected by certain in silico methods commonly used to screen large data sets.

Interkingdom gene transfer may contribute to the evolution of phytopathogenicity in botrytis cinerea

The ascomycete Botrytis cinerea is a phytopathogenic fungus infecting and causing significant yield losses in a number of crops. The genome of B. cinerea has been fully sequenced while the importance of horizontal gene transfer (HGT) to extend the host range in plant pathogenic fungi has been recently appreciated. However, recent data confirm that the B. cinerea fungus shares conserved virulence factors with other fungal plant pathogens with narrow host range. Therefore, interkingdom HGT may contribute to the evolution of phytopathogenicity in B. cinerea. In this study, a stringent genome comparison pipeline was used to identify potential genes that have been obtained by B. cinerea but not by other fungi through interkingdom HGT. This search led to the identification of four genes: a UDP-glucosyltransferase (UGT), a lipoprotein and two alpha/beta hydrolase fold proteins. Phylogenetic analysis of the four genes suggests that B. cinerea acquired UGT from plants and the other 3 genes from bacteria. Based on the known gene functions and literature searching, a correlation between gene acquision and the evolution of pathogenicity in B. cinerea can be postulated.

A Bayesian model for gene family evolution

BACKGROUND

A birth and death process is frequently used for modeling the size of a gene family that may vary along the branches of a phylogenetic tree. Under the birth and death model, maximum likelihood methods have been developed to estimate the birth and death rate and the sizes of ancient gene families (numbers of gene copies at the internodes of the phylogenetic tree). This paper aims to provide a Bayesian approach for estimating parameters in the birth and death model.

RESULTS

We develop a Bayesian approach for estimating the birth and death rate and other parameters in the birth and death model. In addition, a Bayesian hypothesis test is developed to identify the gene families that are unlikely under the birth and death process. Simulation results suggest that the Bayesian estimate is more accurate than the maximum likelihood estimate of the birth and death rate. The Bayesian approach was applied to a real dataset of 3517 gene families across genomes of five yeast species. The results indicate that the Bayesian model assuming a constant birth and death rate among branches of the phylogenetic tree cannot adequately explain the observed pattern of the sizes of gene families across species. The yeast dataset was thus analyzed with a Bayesian heterogeneous rate model that allows the birth and death rate to vary among the branches of the tree. The unlikely gene families identified by the Bayesian heterogeneous rate model are different from those given by the maximum likelihood method.

CONCLUSIONS

Compared to the maximum likelihood method, the Bayesian approach can produce more accurate estimates of the parameters in the birth and death model. In addition, the Bayesian hypothesis test is able to identify unlikely gene families based on Bayesian posterior p-values. As a powerful statistical technique, the Bayesian approach can effectively extract information from gene family data and thereby provide useful information regarding the evolutionary process of gene families across genomes.

Characterization and inference of gene gain/loss along burkholderia evolutionary history

A comparative analysis of 60 complete Burkholderia genomes was conducted to obtain insight in the evolutionary history behind the diversity and pathogenicity at species level. A concatenated multiprotein phyletic pattern and a dataset with Burkholderia clusters of orthologous genes (BuCOGs) were constructed. The extent of horizontal gene transfer (HGT) was assessed using a Markov based probabilistic method. A reconstruction of the gene gains and losses history shows that more than half of the Burkholderia genes families are inferred to have experienced HGT at least once during their evolution. Further analysis revealed that the number of gene gain and loss was correlated with the branch length. Genomic islands (GEIs) analysis based on evolutionary history reconstruction not only revealed that most genes in ancient GEIs were gained but also suggested that the fraction of the genome located in GEIs in the small chromosomes is higher than in the large chromosomes in Burkholderia. The mapping of coexpressed genes onto biological pathway schemes revealed that pathogenicity of Burkholderia strains is probably mainly determined by the gained genes in its ancestor. Taken together, our results strongly support that gene gain and loss especially in ancient evolutionary history play an important role in strain divergence, pathogenicity determinants of Burkholderia and GEIs formation.

Phage-bacteria relationships and CRISPR elements revealed by a metagenomic survey of the rumen microbiome

Viruses are the most abundant biological entities on the planet and play an important role in balancing microbes within an ecosystem and facilitating horizontal gene transfer. Although bacteriophages are abundant in rumen environments, little is known about the types of viruses present or their interaction with the rumen microbiome. We undertook random pyrosequencing of virus-enriched metagenomes (viromes) isolated from bovine rumen fluid and analysed the resulting data using comparative metagenomics. A high level of diversity was observed with up to 28,000 different viral genotypes obtained from each environment. The majority (~78%) of sequences did not match any previously described virus. Prophages outnumbered lytic phages approximately 2:1 with the most abundant bacteriophage and prophage types being associated with members of the dominant rumen phyla (Firmicutes and Proteobacteria). Metabolic profiling based on SEED subsystems revealed an enrichment of sequences with putative functional roles in DNA and protein metabolism, but a surprisingly low proportion of sequences assigned to carbohydrate and amino acid metabolism. We expanded our analysis to include previously described metagenomic data and 14 reference genomes. Clustered regularly interspaced short palindromic repeats (CRISPR) were detected in most of the microbial genomes, suggesting previous interactions between viral and microbial communities.

Inference of gain and loss events from phyletic patterns using stochastic mapping and maximum parsimony--a simulation study

Bacterial evolution is characterized by frequent gain and loss events of gene families. These events can be inferred from phyletic pattern data-a compact representation of gene family repertoire across multiple genomes. The maximum parsimony paradigm is a classical and prevalent approach for the detection of gene family gains and losses mapped on specific branches. We and others have previously developed probabilistic models that aim to account for the gain and loss stochastic dynamics. These models are a critical component of a methodology termed stochastic mapping, in which probabilities and expectations of gain and loss events are estimated for each branch of an underlying phylogenetic tree. In this work, we present a phyletic pattern simulator in which the gain and loss dynamics are assumed to follow a continuous-time Markov chain along the tree. Various models and options are implemented to make the simulation software useful for a large number of studies in which binary (presence/absence) data are analyzed. Using this simulation software, we compared the ability of the maximum parsimony and the stochastic mapping approaches to accurately detect gain and loss events along the tree. Our simulations cover a large array of evolutionary scenarios in terms of the propensities for gene family gains and losses and the variability of these propensities among gene families. Although in all simulation schemes, both methods obtain relatively low levels of false positive rates, stochastic mapping outperforms maximum parsimony in terms of true positive rates. We further studied the factors that influence the performance of both methods. We find, for example, that the accuracy of maximum parsimony inference is substantially reduced when the goal is to map gain and loss events along internal branches of the phylogenetic tree. Furthermore, the accuracy of stochastic mapping is reduced with smaller data sets (limited number of gene families) due to unreliable estimation of branch lengths. Our simulator and simulation results are additionally relevant for the analysis of other types of binary-coded data, such as the existence of homologues restriction sites, gaps, and introns, to name a few. Both the simulation software and the inference methodology are freely available at a user-friendly server: http://gloome.tau.ac.il/.

A horizontal gene transfer supported the evolution of an early metazoan biomineralization strategy

BACKGROUND

The synchronous and widespread adoption of the ability to biomineralize was a defining event for metazoan evolution during the late Precambrian/early Cambrian 545 million years ago. However our understanding on the molecular level of how animals first evolved this capacity is poor. Because sponges are the earliest branching phylum of biomineralizing metazoans, we have been studying how biocalcification occurs in the coralline demosponge Astrosclera willeyana.

RESULTS

We have isolated and characterized a novel protein directly from the calcified spherulites of A. willeyana. Using three independent lines of evidence (genomic architecture of the gene in A. willeyana, spatial expression of the gene product in A. willeyana and genomic architecture of the gene in the related demosponge Amphimedon queenslandica), we show that the gene that encodes this protein was horizontally acquired from a bacterium, and is now highly and exclusively expressed in spherulite forming cells.

CONCLUSIONS

Our findings highlight the ancient and close association that exists between sponges and bacteria, and provide support for the notion that horizontal gene transfer may have been an important mechanism that supported the evolution of this early metazoan biomineralisation strategy.

Pervasive sign epistasis between conjugative plasmids and drug-resistance chromosomal mutations

Multidrug-resistant bacteria arise mostly by the accumulation of plasmids and chromosomal mutations. Typically, these resistant determinants are costly to the bacterial cell. Yet, recently, it has been found that, in Escherichia coli bacterial cells, a mutation conferring resistance to an antibiotic can be advantageous to the bacterial cell if another antibiotic-resistance mutation is already present, a phenomenon called sign epistasis. Here we study the interaction between antibiotic-resistance chromosomal mutations and conjugative (i.e., self-transmissible) plasmids and find many cases of sign epistasis (40%)—including one of reciprocal sign epistasis where the strain carrying both resistance determinants is fitter than the two strains carrying only one of the determinants. This implies that the acquisition of an additional resistance plasmid or of a resistance mutation often increases the fitness of a bacterial strain already resistant to antibiotics. We further show that there is an overall antagonistic interaction between mutations and plasmids (52%). These results further complicate expectations of resistance reversal by interdiction of antibiotic use.

Bacteria can become resistant to antibiotics by spontaneous mutation of chromosomal genes or through the acquisition of horizontally mobile genetic elements, mainly conjugative plasmids. Plasmid-borne resistance is widespread among bacterial pathogens. Plasmids generally entail a cost to the host, associated with the replication and maintenance of the genetic element and with the expression of its genes. Therefore, in the absence of antibiotic, both plasmids and resistance mutations are often deleterious and confer a fitness cost to the cell. Here we studied epistatic interactions between five natural conjugative plasmids and ten chromosomal mutations conferring resistance to three types of antibiotics, making a total of 50 different combinations of chromosomal mutations and conjugative plasmids. We show that sometimes plasmids confer an advantage to bacterial strains carrying resistance mutations in their chromosome. This occurs in 32% (16 out of 50) of tested combinations. Furthermore, in 5 out of 50 plasmid-mutations combinations studied (10%), we observed an increased fitness when a plasmid-bearing bacterial cell acquires a drug-resistant mutation. These examples of sign epistasis are highly unexpected. This work explains, at least in part, how multidrug resistance evolved so rapidly.

Analysis of coevolving gene families using mutually exclusive orthologous modules

Coevolutionary networks can encapsulate information about the dynamics of presence and absence of gene families in organisms. Analysis of such networks should reveal fundamental principles underlying the evolution of cellular systems and the functionality of sets of genes. In this study, we describe a new approach for analyzing coevolutionary networks. Our method detects Mutually Exclusive Orthologous Modules (MEOMs). A MEOM is composed of two sets of gene families, each including gene families that tend to appear in the same organisms, such that the two sets tend to mutually exclude each other (if one set appears in a certain organism the second set does not). Thus, a MEOM reflects the evolutionary replacement of one set of genes by another due to reasons such as lineage/environmental specificity, incompatibility, or functional redundancy. We use our method to analyze a coevolutionary network that is based on 383 microorganisms from the three domains of life. As we demonstrate, our method is useful for detecting meaningful evolutionary clades of organisms as well as sets of proteins that interact with each other. Among our results, we report that: 1) MEOMs tend to include gene families whose cellular functions involve transport, energy production, metabolism, and translation, suggesting that changes in the metabolic environments that require adaptation to new sources of energy are central triggers of complex/pathway replacement in evolution. 2) Many MEOMs are related to outer membrane proteins, such proteins are involved in interaction with the environment and could thus be replaced as a result of adaptation. 3) MEOMs tend to separate organisms with large phylogenetic distance but they also separate organisms that live in different ecological niches. 4) Strikingly, although many MEOMs can be identified, there are much fewer cases where the two cliques in the MEOM completely mutually exclude each other, demonstrating the flexibility of protein evolution. 5) CO dehydrogenase and thymidylate synthase and the glycine cleavage genes mutually exclude each other in archaea; this may represent an alternative route for generation of methyl donors for thymidine synthesis.

Towards an Evolutionary Model of Animal-Associated Microbiomes

Second-generation sequencing technologies have granted us greater access to the diversity and genetics of microbial communities that naturally reside endo- and ecto-symbiotically with animal hosts. Substantial research has emerged describing the diversity and broader trends that exist within and between host species and their associated microbial ecosystems, yet the application of these data to our evolutionary understanding of microbiomes appears fragmented. For the most part biological perspectives are based on limited observations of oversimplified communities, while mathematical and/or computational modeling of these concepts often lack biological precedence. In recognition of this disconnect, both fields have attempted to incorporate ecological theories, although their applicability is currently a subject of debate because most ecological theories were developed based on observations of macro-organisms and their ecosystems. For the purposes of this review, we attempt to transcend the biological, ecological and computational realms, drawing on extensive literature, to forge a useful framework that can, at a minimum be built upon, but ideally will shape the hypotheses of each field as they move forward. In evaluating the top-down selection pressures that are exerted on a microbiome we find cause to warrant reconsideration of the much-maligned theory of multi-level selection and reason that complexity must be underscored by modularity.