PHYRN: a robust method for phylogenetic analysis of highly divergent sequences

A new lineage of segmented RNA viruses infecting animals

Metagenomic sequencing has revolutionised our knowledge of virus diversity, with new virus sequences being reported faster than ever before. However, virus discovery from metagenomic sequencing usually depends on detectable homology: without a sufficiently close relative, so-called 'dark' virus sequences remain unrecognisable. An alternative approach is to use virus-identification methods that do not depend on detecting homology, such as virus recognition by host antiviral immunity. For example, virus-derived small RNAs have previously been used to propose 'dark' virus sequences associated with the Drosophilidae (Diptera). Here, we combine published Drosophila data with a comprehensive search of transcriptomic sequences and selected meta-transcriptomic datasets to identify a completely new lineage of segmented positive-sense single-stranded RNA viruses that we provisionally refer to as the Quenyaviruses. Each of the five segments contains a single open reading frame, with most encoding proteins showing no detectable similarity to characterised viruses, and one sharing a small number of residues with the RNA-dependent RNA polymerases of single- and double-stranded RNA viruses. Using these sequences, we identify close relatives in approximately 20 arthropods, including insects, crustaceans, spiders, and a myriapod. Using a more conserved sequence from the putative polymerase, we further identify relatives in meta-transcriptomic datasets from gut, gill, and lung tissues of vertebrates, reflecting infections of vertebrates or of their associated parasites. Our data illustrate the utility of small RNAs to detect viruses with limited sequence conservation, and provide robust evidence for a new deeply divergent and phylogenetically distinct RNA virus lineage.

Genomic Characterization of Cyanophage vB_AphaS-CL131 Infecting Filamentous Diazotrophic Cyanobacterium Aphanizomenon flos-aquae Reveals Novel Insights into Virus-Bacterium Interactions

While filamentous cyanobacteria play a crucial role in food web dynamics and biogeochemical cycling of many aquatic ecosystems around the globe, the knowledge regarding the phages infecting them is limited. Here, we describe the complete genome of the virulent cyanophage vB_AphaS-CL131 (here, CL 131), a Siphoviridae phage that infects the filamentous diazotrophic bloom-forming cyanobacterium Aphanizomenon flos-aquae in the brackish Baltic Sea. CL 131 features a 112,793-bp double-stranded DNA (dsDNA) genome encompassing 149 putative open reading frames (ORFs), of which the majority (86%) lack sequence homology to genes with known functions in other bacteriophages or bacteria. Phylogenetic analysis revealed that CL 131 possibly represents a new evolutionary lineage within the group of cyanophages infecting filamentous cyanobacteria, which form a separate cluster from phages infecting unicellular cyanobacteria. CL 131 encodes a putative type V-U2 CRISPR-Cas system with one spacer (out of 10) targeting a DNA primase pseudogene in a cyanobacterium and a putative type II toxin-antitoxin system, consisting of a GNAT family N-acetyltransferase and a protein of unknown function containing the PRK09726 domain (characteristic of HipB antitoxins). Comparison of CL 131 proteins to reads from Baltic Sea and other available fresh- and brackish-water metagenomes and analysis of CRISPR-Cas arrays in publicly available A. flos-aquae genomes demonstrated that phages similar to CL 131 are present and dynamic in the Baltic Sea and share a common history with their hosts dating back at least several decades. In addition, different CRISPR-Cas systems within individual A. flos-aquae genomes targeted several sequences in the CL 131 genome, including genes related to virion structure and morphogenesis. Altogether, these findings revealed new genomic information for exploring viral diversity and provide a model system for investigation of virus-host interactions in filamentous cyanobacteria.IMPORTANCE The genomic characterization of novel cyanophage vB_AphaS-CL131 and the analysis of its genomic features in the context of other viruses, metagenomic data, and host CRISPR-Cas systems contribute toward a better understanding of aquatic viral diversity and distribution in general and of brackish-water cyanophages infecting filamentous diazotrophic cyanobacteria in the Baltic Sea in particular. The results of this study revealed previously undescribed features of cyanophage genomes (e.g., self-excising intein-containing putative dCTP deaminase and putative cyanophage-encoded CRISPR-Cas and toxin-antitoxin systems) and can therefore be used to predict potential interactions between bloom-forming cyanobacteria and their cyanophages.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks

Motivation

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure.

Results

The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families.

Availability and implementation

MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot.

Contact

emoriyama2@unl.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

PhyPA: Phylogenetic method with pairwise sequence alignment outperforms likelihood methods in phylogenetics involving highly diverged sequences

While pairwise sequence alignment (PSA) by dynamic programming is guaranteed to generate one of the optimal alignments, multiple sequence alignment (MSA) of highly divergent sequences often results in poorly aligned sequences, plaguing all subsequent phylogenetic analysis. One way to avoid this problem is to use only PSA to reconstruct phylogenetic trees, which can only be done with distance-based methods. I compared the accuracy of this new computational approach (named PhyPA for phylogenetics by pairwise alignment) against the maximum likelihood method using MSA (the ML+MSA approach), based on nucleotide, amino acid and codon sequences simulated with different topologies and tree lengths. I present a surprising discovery that the fast PhyPA method consistently outperforms the slow ML+MSA approach for highly diverged sequences even when all optimization options were turned on for the ML+MSA approach. Only when sequences are not highly diverged (i.e., when a reliable MSA can be obtained) does the ML+MSA approach outperforms PhyPA. The true topologies are always recovered by ML with the true alignment from the simulation. However, with MSA derived from alignment programs such as MAFFT or MUSCLE, the recovered topology consistently has higher likelihood than that for the true topology. Thus, the failure to recover the true topology by the ML+MSA is not because of insufficient search of tree space, but by the distortion of phylogenetic signal by MSA methods. I have implemented in DAMBE PhyPA and two approaches making use of multi-gene data sets to derive phylogenetic support for subtrees equivalent to resampling techniques such as bootstrapping and jackknifing.

GenFamClust: an accurate, synteny-aware and reliable homology inference algorithm

Background

Homology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity.

Results

In this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs.

Conclusions

The study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0684-2) contains supplementary material, which is available to authorized users.

Domain organization of DNase from Thioalkalivibrio sp. provides insights into retention of activity in high salt environments

Our study indicates that DNA binding domains are common in many halophilic or halotolerant bacterial DNases and they are potential activators of enzymatic activity at high ionic strength. Usually, proteins adapt to high ionic strength by increasing the number of negatively charged residues on the surface. However, in DNases such adaptation would hinder the binding to negatively charged DNA, a step critical for catalysis. In our study we demonstrate how evolution has solved this dilemma by engaging the DNA binding domain. We propose a mechanism, which enables the enzyme activity at salt concentrations as high as 4 M of sodium chloride, based on collected experimental data and domain structure analysis of a secreted bacterial DNase from the extremely halotolerant bacterium Thioalkalivibrio sp. K90mix. The enzyme harbors two domains: an N-terminal domain, that exhibits DNase activity, and a C-terminal domain, comprising a duplicate DNA binding helix-hairpin-helix motif. Here we present experimental data demonstrating that the C-terminal domain is responsible for the enzyme's resistance to high ionic strength.

Molecular dynamic simulations reveal the structural determinants of Fatty Acid binding to oxy-myoglobin

The mechanism(s) by which fatty acids are sequestered and transported in muscle have not been fully elucidated. A potential key player in this process is the protein myoglobin (Mb). Indeed, there is a catalogue of empirical evidence supporting direct interaction of globins with fatty acid metabolites; however, the binding pocket and regulation of the interaction remains to be established. In this study, we employed a computational strategy to elucidate the structural determinants of fatty acids (palmitic & oleic acid) binding to Mb. Sequence analysis and docking simulations with a horse (Equus caballus) structural Mb reference reveals a fatty acid-binding site in the hydrophobic cleft near the heme region in Mb. Both palmitic acid and oleic acid attain a "U" shaped structure similar to their conformation in pockets of other fatty acid-binding proteins. Specifically, we found that the carboxyl head group of palmitic acid coordinates with the amino group of Lys45, whereas the carboxyl group of oleic acid coordinates with both the amino groups of Lys45 and Lys63. The alkyl tails of both fatty acids are supported by surrounding hydrophobic residues Leu29, Leu32, Phe33, Phe43, Phe46, Val67, Val68 and Ile107. In the saturated palmitic acid, the hydrophobic tail moves freely and occasionally penetrates deeper inside the hydrophobic cleft, making additional contacts with Val28, Leu69, Leu72 and Ile111. Our simulations reveal a dynamic and stable binding pocket in which the oxygen molecule and heme group in Mb are required for additional hydrophobic interactions. Taken together, these findings support a mechanism in which Mb acts as a muscle transporter for fatty acid when it is in the oxygenated state and releases fatty acid when Mb converts to deoxygenated state.

Sequence analysis reveals a conserved extension in the capping enzyme of the alphavirus supergroup, and a homologous domain in nodaviruses

Background

Members of the alphavirus supergroup include human pathogens such as chikungunya virus, hepatitis E virus and rubella virus. They encode a capping enzyme with methyltransferase-guanylyltransferase (MTase-GTase) activity, which is an attractive drug target owing to its unique mechanism. However, its experimental study has proven very difficult.

Results

We examined over 50 genera of viruses by sequence analyses. Earlier studies showed that the MTase-GTase contains a “Core” region conserved in sequence. We show that it is followed by a long extension, which we termed “Iceberg” region, whose secondary structure, but not sequence, is strikingly conserved throughout the alphavirus supergroup. Sequence analyses strongly suggest that the minimal capping domain corresponds to the Core and Iceberg regions combined, which is supported by earlier experimental data. The Iceberg region contains all known membrane association sites that contribute to the assembly of viral replication factories. We predict that it may also contain an overlooked, widely conserved membrane-binding amphipathic helix. Unexpectedly, we detected a sequence homolog of the alphavirus MTase-GTase in taxa related to nodaviruses and to chronic bee paralysis virus. The presence of a capping enzyme in nodaviruses is biologically consistent, since they have capped genomes but replicate in the cytoplasm, where no cellular capping enzyme is present. The putative MTase-GTase domain of nodaviruses also contains membrane-binding sites that may drive the assembly of viral replication factories, revealing an unsuspected parallel with the alphavirus supergroup.

Conclusions

Our work will guide the functional analysis of the alphaviral MTase-GTase and the production of domains for structure determination. The identification of a homologous domain in a simple model system, nodaviruses, which replicate in numerous eukaryotic cell systems (yeast, flies, worms, mammals, and plants), can further help crack the function and structure of the enzyme.

Reviewers

This article was reviewed by Valerian Dolja, Eugene Koonin and Sebastian Maurer-Stroh.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0050-0) contains supplementary material, which is available to authorized users.

Quantitative synteny scoring improves homology inference and partitioning of gene families

Background

Clustering sequences into families has long been an important step in characterization of genes and proteins. There are many algorithms developed for this purpose, most of which are based on either direct similarity between gene pairs or some sort of network structure, where weights on edges of constructed graphs are based on similarity. However, conserved synteny is an important signal that can help distinguish homology and it has not been utilized to its fullest potential.

Results

Here, we present GenFamClust, a pipeline that combines the network properties of sequence similarity and synteny to assess homology relationship and merge known homologs into groups of gene families. GenFamClust identifies homologs in a more informed and accurate manner as compared to similarity based approaches. We tested our method against the Neighborhood Correlation method on two diverse datasets consisting of fully sequenced genomes of eukaryotes and synthetic data.

Conclusions

The results obtained from both datasets confirm that synteny helps determine homology and GenFamClust improves on Neighborhood Correlation method. The accuracy as well as the definition of synteny scores is the most valuable contribution of GenFamClust.

Elucidating the origin of the ExbBD components of the TonB system through Bayesian inference and maximum-likelihood phylogenies

Uptake of ferric siderophores, vitamin B12, and other molecules in gram-negative bacteria is mediated by a multi-protein complex known as the TonB system. The ExbB and ExbD protein components of the TonB system play key energizing roles and are homologous with the flagellar motor proteins MotA and MotB. Here, the phylogenetic relationships of ExbBD and MotAB were investigated using Bayesian inference and the maximum-likelihood method. Phylogenetic trees of these proteins suggest that they are separated into distinct monophyletic groups and have originated from a common ancestral system. Several horizontal gene transfer events for ExbB-ExbD are also inferred, and a model for the evolution of the TonB system is proposed.

Reevaluation of the evolutionary events within recA/RAD51 phylogeny

Background

The recA/RAD51 gene family encodes a diverse set of recombinase proteins that affect homologous recombination, DNA-repair, and genome stability. The recA gene family is expressed across all three domains of life - Eubacteria, Archaea, and Eukaryotes - and even in some viruses. To date, efforts to resolve the deep evolutionary origins of this ancient protein family have been hindered by the high sequence divergence between paralogous groups (i.e. ~30% average pairwise identity).

Results

Through large taxon sampling and the use of a phylogenetic algorithm designed for inferring evolutionary events in highly divergent paralogs, we obtained a robust, parsimonious and more refined phylogenetic history of the recA/RAD51 superfamily.

Conclusions

In summary, our model for the evolution of recA/RAD51 family provides a better understanding of the ancient origin of recA proteins and the multiple events that lead to the diversification of recA homologs in eukaryotes, including the discovery of additional RAD51 sub-families.