Graph-based modeling of tandem repeats improves global multiple sequence alignment

The Dual Role of the Innate Immune System in the Effectiveness of mRNA Therapeutics

Advances in molecular biology have revolutionized the use of messenger RNA (mRNA) as a therapeutic. The concept of nucleic acid therapy with mRNA originated in 1990 when Wolff et al. reported successful expression of proteins in target organs by direct injection of either plasmid DNA or mRNA. It took decades to bring the transfection efficiency of mRNA closer to that of DNA. The next few decades were dedicated to turning in vitro-transcribed (IVT) mRNA from a promising delivery tool for gene therapy into a full-blown therapeutic modality, which changed the biotech market rapidly. Hundreds of clinical trials are currently underway using mRNA for prophylaxis and therapy of infectious diseases and cancers, in regenerative medicine, and genome editing. The potential of IVT mRNA to induce an innate immune response favors its use for vaccination and immunotherapy. Nonetheless, in non-immunotherapy applications, the intrinsic immunostimulatory activity of mRNA directly hinders the desired therapeutic effect since it can seriously impair the target protein expression. Targeting the same innate immune factors can increase the effectiveness of mRNA therapeutics for some indications and decrease it for others, and vice versa. The review aims to present the innate immunity-related 'barriers' or 'springboards' that may affect the development of immunotherapies and non-immunotherapy applications of mRNA medicines.

Ehrlichia SLiM ligand mimetic activates Hedgehog signaling to engage a BCL-2 anti-apoptotic cellular program

Ehrlichia chaffeensis (E. chaffeensis) has evolved eukaryotic ligand mimicry to repurpose multiple cellular signaling pathways for immune evasion. In this investigation, we demonstrate that TRP120 has a novel repetitive short linear motif (SLiM) that activates the evolutionarily conserved Hedgehog (Hh) signaling pathway to inhibit apoptosis. In silico analysis revealed that TRP120 has sequence and functional similarity with Hh ligands and a candidate Hh ligand SLiM was identified. siRNA knockdown of Hh signaling and transcriptional components significantly reduced infection. Co-immunoprecipitation and surface plasmon resonance demonstrated that rTRP120-TR interacted directly with Hh receptor Patched-2 (PTCH2). E. chaffeensis infection resulted in early upregulation of Hh transcription factor GLI-1 and regulation of Hh target genes. Moreover, soluble recombinant TRP120 (rTRP120) activated Hh and induced gene expression consistent with the eukaryotic Hh ligand. The TRP120-Hh-SLiM (NPEVLIKD) induced nuclear translocation of GLI-1 in THP-1 cells and primary human monocytes and induced a rapid and expansive activation of Hh pathway target genes. Furthermore, Hh activation was blocked by an α-TRP120-Hh-SLiM antibody. TRP120-Hh-SLiM significantly increased levels of Hh target, anti-apoptotic protein B-cell lymphoma 2 (BCL-2), and siRNA knockdown of BCL-2 dramatically inhibited infection. Blocking Hh signaling with the inhibitor Vismodegib, induced a pro-apoptotic cellular program defined by decreased mitochondria membrane potential, significant reductions in BCL-2, activation of caspase 3 and 9, and increased apoptotic cells. This study reveals a novel E. chaffeensis SLiM ligand mimetic that activates Hh signaling to maintain E. chaffeensis infection by engaging a BCL-2 anti-apoptotic cellular program.

A New Census of Protein Tandem Repeats and Their Relationship with Intrinsic Disorder

Protein tandem repeats (TRs) are often associated with immunity-related functions and diseases. Since that last census of protein TRs in 1999, the number of curated proteins increased more than seven-fold and new TR prediction methods were published. TRs appear to be enriched with intrinsic disorder and vice versa. The significance and the biological reasons for this association are unknown. Here, we characterize protein TRs across all kingdoms of life and their overlap with intrinsic disorder in unprecedented detail. Using state-of-the-art prediction methods, we estimate that 50.9% of proteins contain at least one TR, often located at the sequence flanks. Positive linear correlation between the proportion of TRs and the protein length was observed universally, with Eukaryotes in general having more TRs, but when the difference in length is taken into account the difference is quite small. TRs were enriched with disorder-promoting amino acids and were inside intrinsically disordered regions. Many such TRs were homorepeats. Our results support that TRs mostly originate by duplication and are involved in essential functions such as transcription processes, structural organization, electron transport and iron-binding. In viruses, TRs are found in proteins essential for virulence.

Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases

The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with 'ready-to-use' deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others.

A Graph-Based Approach for Detecting Sequence Homology in Highly Diverged Repeat Protein Families

Reconstructing evolutionary relationships in repeat proteins is notoriously difficult due to the high degree of sequence divergence that typically occurs between duplicated repeats. This is complicated further by the fact that proteins with a large number of similar repeats are more likely to produce significant local sequence alignments than proteins with fewer copies of the repeat motif. Furthermore, biologically correct sequence alignments are sometimes impossible to achieve in cases where insertion or translocation events disrupt the order of repeats in one of the sequences being aligned. Combined, these attributes make traditional phylogenetic methods for studying protein families unreliable for repeat proteins, due to the dependence of such methods on accurate sequence alignment.We present here a practical solution to this problem, making use of graph clustering combined with the open-source software package HH-suite, which enables highly sensitive detection of sequence relationships. Carrying out multiple rounds of homology searches via alignment of profile hidden Markov models, large sets of related proteins are generated. By representing the relationships between proteins in these sets as graphs, subsequent clustering with the Markov cluster algorithm enables robust detection of repeat protein subfamilies.

Progressive multiple sequence alignment with indel evolution

Background

Sequence alignment is crucial in genomics studies. However, optimal multiple sequence alignment (MSA) is NP-hard. Thus, modern MSA methods employ progressive heuristics, breaking the problem into a series of pairwise alignments guided by a phylogeny. Changes between homologous characters are typically modelled by a Markov substitution model. In contrast, the dynamics of indels are not modelled explicitly, because the computation of the marginal likelihood under such models has exponential time complexity in the number of taxa. But the failure to model indel evolution may lead to artificially short alignments due to biased indel placement, inconsistent with phylogenetic relationship.

Results

Recently, the classical indel model TKF91 was modified to describe indel evolution on a phylogeny via a Poisson process, termed PIP. PIP allows to compute the joint marginal probability of an MSA and a tree in linear time. We present a new dynamic programming algorithm to align two MSAs –represented by the underlying homology paths– by full maximum likelihood under PIP in polynomial time, and apply it progressively along a guide tree. We have corroborated the correctness of our method by simulation, and compared it with competitive methods on an illustrative real dataset.

Conclusions

Our MSA method is the first polynomial time progressive aligner with a rigorous mathematical formulation of indel evolution. The new method infers phylogenetically meaningful gap patterns alternative to the popular PRANK, while producing alignments of similar length. Moreover, the inferred gap patterns agree with what was predicted qualitatively by previous studies. The algorithm is implemented in a standalone C++ program: https://github.com/acg-team/ProPIP. Supplementary data are available at BMC Bioinformatics online.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2357-1) contains supplementary material, which is available to authorized users.

Insights into the Evolution of Hydroxyproline-Rich Glycoproteins from 1000 Plant Transcriptomes

The carbohydrate-rich cell walls of land plants and algae have been the focus of much interest given the value of cell wall-based products to our current and future economies. Hydroxyproline-rich glycoproteins (HRGPs), a major group of wall glycoproteins, play important roles in plant growth and development, yet little is known about how they have evolved in parallel with the polysaccharide components of walls. We investigate the origins and evolution of the HRGP superfamily, which is commonly divided into three major multigene families: the arabinogalactan proteins (AGPs), extensins (EXTs), and proline-rich proteins. Using motif and amino acid bias, a newly developed bioinformatics pipeline, we identified HRGPs in sequences from the 1000 Plants transcriptome project (www.onekp.com). Our analyses provide new insights into the evolution of HRGPs across major evolutionary milestones, including the transition to land and the early radiation of angiosperms. Significantly, data mining reveals the origin of glycosylphosphatidylinositol (GPI)-anchored AGPs in green algae and a 3- to 4-fold increase in GPI-AGPs in liverworts and mosses. The first detection of cross-linking (CL)-EXTs is observed in bryophytes, which suggests that CL-EXTs arose though the juxtaposition of preexisting SPn EXT glycomotifs with refined Y-based motifs. We also detected the loss of CL-EXT in a few lineages, including the grass family (Poaceae), that have a cell wall composition distinct from other monocots and eudicots. A key challenge in HRGP research is tracking individual HRGPs throughout evolution. Using the 1000 Plants output, we were able to find putative orthologs of Arabidopsis pollen-specific GPI-AGPs in basal eudicots.

Historian: accurate reconstruction of ancestral sequences and evolutionary rates

Motivation

Reconstruction of ancestral sequence histories, and estimation of parameters like indel rates, are improved by using explicit evolutionary models and summing over uncertain alignments. The previous best tool for this purpose (according to simulation benchmarks) was ProtPal, but this tool was too slow for practical use.

Results

Historian combines an efficient reimplementation of the ProtPal algorithm with performance-improving heuristics from other alignment tools. Simulation results on fidelity of rate estimation via ancestral reconstruction, along with evaluations on the structurally informed alignment dataset BAliBase 3.0, recommend Historian over other alignment tools for evolutionary applications.

Availability and Implementation

Historian is available at https://github.com/evoldoers/historian under the Creative Commons Attribution 3.0 US license.

Contact

ihholmes+historian@gmail.com.

Evolution of Protein Domain Repeats in Metazoa

Repeats are ubiquitous elements of proteins and they play important roles for cellular function and during evolution. Repeats are, however, also notoriously difficult to capture computationally and large scale studies so far had difficulties in linking genetic causes, structural properties and evolutionary trajectories of protein repeats. Here we apply recently developed methods for repeat detection and analysis to a large dataset comprising over hundred metazoan genomes. We find that repeats in larger protein families experience generally very few insertions or deletions (indels) of repeat units but there is also a significant fraction of noteworthy volatile outliers with very high indel rates. Analysis of structural data indicates that repeats with an open structure and independently folding units are more volatile and more likely to be intrinsically disordered. Such disordered repeats are also significantly enriched in sites with a high functional potential such as linear motifs. Furthermore, the most volatile repeats have a high sequence similarity between their units. Since many volatile repeats also show signs of recombination, we conclude they are often shaped by concerted evolution. Intriguingly, many of these conserved yet volatile repeats are involved in host-pathogen interactions where they might foster fast but subtle adaptation in biological arms races. KEY WORDS: protein evolution, domain rearrangements, protein repeats, concerted evolution.

RareVariantVis: new tool for visualization of causative variants in rare monogenic disorders using whole genome sequencing data

MOTIVATION

The search for causative genetic variants in rare diseases of presumed monogenic inheritance has been boosted by the implementation of whole exome (WES) and whole genome (WGS) sequencing. In many cases, WGS seems to be superior to WES, but the analysis and visualization of the vast amounts of data is demanding.

RESULTS

To aid this challenge, we have developed a new tool-RareVariantVis-for analysis of genome sequence data (including non-coding regions) for both germ line and somatic variants. It visualizes variants along their respective chromosomes, providing information about exact chromosomal position, zygosity and frequency, with point-and-click information regarding dbSNP IDs, gene association and variant inheritance. Rare variants as well as de novo variants can be flagged in different colors. We show the performance of the RareVariantVis tool in the Genome in a Bottle WGS data set.

AVAILABILITY AND IMPLEMENTATION

https://www.bioconductor.org/packages/3.3/bioc/html/RareVariantVis.html

CONTACT

tomasz.stokowy@k2.uib.no

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functional assignment to positively selected sites in the core type III effector RipG7 from Ralstonia solanacearum

The soil-borne pathogen Ralstonia solanacearum causes bacterial wilt in a broad range of plants. The main virulence determinants of R. solanacearum are the type III secretion system (T3SS) and its associated type III effectors (T3Es), translocated into the host cells. Of the conserved T3Es among R. solanacearum strains, the Fbox protein RipG7 is required for R. solanacearum pathogenesis on Medicago truncatula. In this work, we describe the natural ripG7 variability existing in the R. solanacearum species complex. We show that eight representative ripG7 orthologues have different contributions to pathogenicity on M. truncatula: only ripG7 from Asian or African strains can complement the absence of ripG7 in GMI1000 (Asian reference strain). Nonetheless, RipG7 proteins from American and Indonesian strains can still interact with M. truncatula SKP1-like/MSKa protein, essential for the function of RipG7 in virulence. This indicates that the absence of complementation is most likely a result of the variability in the leucine-rich repeat (LRR) domain of RipG7. We identified 11 sites under positive selection in the LRR domains of RipG7. By studying the functional impact of these 11 sites, we show the contribution of five positively selected sites for the function of RipG7CMR15 in M. truncatula colonization. This work reveals the genetic and functional variation of the essential core T3E RipG7 from R. solanacearum. This analysis is the first of its kind on an essential disease-controlling T3E, and sheds light on the co-evolutionary arms race between the bacterium and its hosts.

DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment

BACKGROUND

Alignment of large and diverse sequence sets is a common task in biological investigations, yet there remains considerable room for improvement in alignment quality. Multiple sequence alignment programs tend to reach maximal accuracy when aligning only a few sequences, and then diminish steadily as more sequences are added. This drop in accuracy can be partly attributed to a build-up of error and ambiguity as more sequences are aligned. Most high-throughput sequence alignment algorithms do not use contextual information under the assumption that sites are independent. This study examines the extent to which local sequence context can be exploited to improve the quality of large multiple sequence alignments.

RESULTS

Two predictors based on local sequence context were assessed: (i) single sequence secondary structure predictions, and (ii) modulation of gap costs according to the surrounding residues. The results indicate that context-based predictors have appreciable information content that can be utilized to create more accurate alignments. Furthermore, local context becomes more informative as the number of sequences increases, enabling more accurate protein alignments of large empirical benchmarks. These discoveries became the basis for DECIPHER, a new context-aware program for sequence alignment, which outperformed other programs on large sequence sets.

CONCLUSIONS

Predicting secondary structure based on local sequence context is an efficient means of breaking the independence assumption in alignment. Since secondary structure is more conserved than primary sequence, it can be leveraged to improve the alignment of distantly related proteins. Moreover, secondary structure predictions increase in accuracy as more sequences are used in the prediction. This enables the scalable generation of large sequence alignments that maintain high accuracy even on diverse sequence sets. The DECIPHER R package and source code are freely available for download at DECIPHER.cee.wisc.edu and from the Bioconductor repository.

The discovery, function and development of the variable number tandem repeats in different Mycobacterium species

The method of genotyping by variable number tandem repeats (VNTRs) facilitates the epidemiological studies of different Mycobacterium species worldwide. Until now, the VNTR method is not fully understood, for example, its discovery, function and classification. The inconsistent nomenclature and terminology of VNTR is especially confusing. In this review, we first describe in detail the VNTRs in Mycobacterium tuberculosis (M. tuberculosis), as this pathogen resulted in more deaths than any other microbial pathogen as well as for which extensive studies of VNTRs were carried out, and then we outline the recent progress of the VNTR-related epidemiological research in several other Mycobacterium species, such as M. abscessus, M. africanum, M. avium, M. bovis, M. canettii, M. caprae, M. intracellulare, M. leprae, M. marinum, M. microti, M. pinnipedii and M. ulcerans from different countries and regions. This article is aimed mainly at the practical notes of VNTR to help the scientists in better understanding and performing this method.

A depauperate immune repertoire precedes evolution of sociality in bees

Background

Sociality has many rewards, but can also be dangerous, as high population density and low genetic diversity, common in social insects, is ideal for parasite transmission. Despite this risk, honeybees and other sequenced social insects have far fewer canonical immune genes relative to solitary insects. Social protection from infection, including behavioral responses, may explain this depauperate immune repertoire. Here, based on full genome sequences, we describe the immune repertoire of two ecologically and commercially important bumblebee species that diverged approximately 18 million years ago, the North American Bombus impatiens and European Bombus terrestris.

Results

We find that the immune systems of these bumblebees, two species of honeybee, and a solitary leafcutting bee, are strikingly similar. Transcriptional assays confirm the expression of many of these genes in an immunological context and more strongly in young queens than males, affirming Bateman’s principle of greater investment in female immunity. We find evidence of positive selection in genes encoding antiviral responses, components of the Toll and JAK/STAT pathways, and serine protease inhibitors in both social and solitary bees. Finally, we detect many genes across pathways that differ in selection between bumblebees and honeybees, or between the social and solitary clades.

Conclusions

The similarity in immune complement across a gradient of sociality suggests that a reduced immune repertoire predates the evolution of sociality in bees. The differences in selection on immune genes likely reflect divergent pressures exerted by parasites across social contexts.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0628-y) contains supplementary material, which is available to authorized users.

Maximum-Likelihood Tree Estimation Using Codon Substitution Models with Multiple Partitions

Many protein sequences have distinct domains that evolve with different rates, different selective pressures, or may differ in codon bias. Instead of modeling these differences by more and more complex models of molecular evolution, we present a multipartition approach that allows maximum-likelihood phylogeny inference using different codon models at predefined partitions in the data. Partition models can, but do not have to, share free parameters in the estimation process. We test this approach with simulated data as well as in a phylogenetic study of the origin of the leucin-rich repeat regions in the type III effector proteins of the pythopathogenic bacteria Ralstonia solanacearum. Our study does not only show that a simple two-partition model resolves the phylogeny better than a one-partition model but also gives more evidence supporting the hypothesis of lateral gene transfer events between the bacterial pathogens and its eukaryotic hosts.

Statistical approaches to detecting and analyzing tandem repeats in genomic sequences

Tandem repeats (TRs) are frequently observed in genomes across all domains of life. Evidence suggests that some TRs are crucial for proteins with fundamental biological functions and can be associated with virulence, resistance, and infectious/neurodegenerative diseases. Genome-scale systematic studies of TRs have the potential to unveil core mechanisms governing TR evolution and TR roles in shaping genomes. However, TR-related studies are often non-trivial due to heterogeneous and sometimes fast evolving TR regions. In this review, we discuss these intricacies and their consequences. We present our recent contributions to computational and statistical approaches for TR significance testing, sequence profile-based TR annotation, TR-aware sequence alignment, phylogenetic analyses of TR unit number and order, and TR benchmarks. Importantly, all these methods explicitly rely on the evolutionary definition of a tandem repeat as a sequence of adjacent repeat units stemming from a common ancestor. The discussed work has a focus on protein TRs, yet is generally applicable to nucleic acid TRs, sharing similar features.

Distribution on contingency of alignment of two literal sequences under constrains

The case of ungapped alignment of two literal sequences under constrains is considered. The analysis lead to general formulas for probability mass function and cumulative distribution function for the general case of using an alphabet with a chosen number of letters (e.g. 4 for deoxyribonucleic acid sequences) in the expression of the literal sequences. Formulas for three statistics including mean, mode, and standard deviation were obtained. Distributions are depicted for three important particular cases: alignment on binary sequences, alignment of trinomial series (such as coming from generalized Kronecker delta), and alignment of genetic sequences (with four literals in the alphabet). A particular case when sequences contain each letter of the alphabet at least once in both sequences has also been analyzed and some statistics for this restricted case are given.

QueTAL: a suite of tools to classify and compare TAL effectors functionally and phylogenetically

Transcription Activator-Like (TAL) effectors from Xanthomonas plant pathogenic bacteria can bind to the promoter region of plant genes and induce their expression. DNA-binding specificity is governed by a central domain made of nearly identical repeats, each determining the recognition of one base pair via two amino acid residues (a.k.a. Repeat Variable Di-residue, or RVD). Knowing how TAL effectors differ from each other within and between strains would be useful to infer functional and evolutionary relationships, but their repetitive nature precludes reliable use of traditional alignment methods. The suite QueTAL was therefore developed to offer tailored tools for comparison of TAL effector genes. The program DisTAL considers each repeat as a unit, transforms a TAL effector sequence into a sequence of coded repeats and makes pair-wise alignments between these coded sequences to construct trees. The program FuncTAL is aimed at finding TAL effectors with similar DNA-binding capabilities. It calculates correlations between position weight matrices of potential target DNA sequence predicted from the RVD sequence, and builds trees based on these correlations. The programs accurately represented phylogenetic and functional relationships between TAL effectors using either simulated or literature-curated data. When using the programs on a large set of TAL effector sequences, the DisTAL tree largely reflected the expected species phylogeny. In contrast, FuncTAL showed that TAL effectors with similar binding capabilities can be found between phylogenetically distant taxa. This suite will help users to rapidly analyse any TAL effector genes of interest and compare them to other available TAL genes and should improve our understanding of TAL effectors evolution. It is available at http://bioinfo-web.mpl.ird.fr/cgi-bin2/quetal/quetal.cgi.

Antibody-specific model of amino acid substitution for immunological inferences from alignments of antibody sequences

Antibodies are glycoproteins produced by the immune system as a dynamically adaptive line of defense against invading pathogens. Very elegant and specific mutational mechanisms allow B lymphocytes to produce a large and diversified repertoire of antibodies, which is modified and enhanced throughout all adulthood. One of these mechanisms is somatic hypermutation, which stochastically mutates nucleotides in the antibody genes, forming new sequences with different properties and, eventually, higher affinity and selectivity to the pathogenic target. As somatic hypermutation involves fast mutation of antibody sequences, this process can be described using a Markov substitution model of molecular evolution. Here, using large sets of antibody sequences from mice and humans, we infer an empirical amino acid substitution model AB, which is specific to antibody sequences. Compared with existing general amino acid models, we show that the AB model provides significantly better description for the somatic evolution of mice and human antibody sequences, as demonstrated on large next generation sequencing (NGS) antibody data. General amino acid models are reflective of conservation at the protein level due to functional constraints, with most frequent amino acids exchanges taking place between residues with the same or similar physicochemical properties. In contrast, within the variable part of antibody sequences we observed an elevated frequency of exchanges between amino acids with distinct physicochemical properties. This is indicative of a sui generis mutational mechanism, specific to antibody somatic hypermutation. We illustrate this property of antibody sequences by a comparative analysis of the network modularity implied by the AB model and general amino acid substitution models. We recommend using the new model for computational studies of antibody sequence maturation, including inference of alignments and phylogenetic trees describing antibody somatic hypermutation in large NGS data sets. The AB model is implemented in the open-source software CodonPhyML (http://sourceforge.net/projects/codonphyml) and can be downloaded and supplied by the user to ProGraphMSA (http://sourceforge.net/projects/prographmsa) or other alignment and phylogeny reconstruction programs that allow for user-defined substitution models.

Deep conservation of human protein tandem repeats within the eukaryotes

Tandem repeats (TRs) are a major element of protein sequences in all domains of life. They are particularly abundant in mammals, where by conservative estimates one in three proteins contain a TR. High generation-scale duplication and deletion rates were reported for nucleic TR units. However, it is not known whether protein TR units can also be frequently lost or gained providing a source of variation for rapid adaptation of protein function, or alternatively, tend to have conserved TR unit configurations over long evolutionary times. To obtain a systematic picture, we performed a proteome-wide analysis of the mode of evolution for human protein TRs. For this purpose, we propose a novel method for the detection of orthologous TRs based on circular profile hidden Markov models. For all detected TRs, we reconstructed bispecies TR unit phylogenies across 61 eukaryotes ranging from human to yeast. Moreover, we performed additional analyses to correlate functional and structural annotations of human TRs with their mode of evolution. Surprisingly, we find that the vast majority of human TRs are ancient, with TR unit number and order preserved intact since distant speciation events. For example, ≥61% of all human TRs have been strongly conserved at least since the root of all mammals, approximately 300 Ma. Further, we find no human protein TR that shows evidence for strong recent duplications and deletions. The results are in contrast to the high generation-scale mutability of nucleic TRs. Presumably, most protein TRs fold into stable and conserved structures that are indispensable for the function of the TR-containing protein. All of our data and results are available for download from http://www.atgc-montpellier.fr/TRE.

Repertoire, unified nomenclature and evolution of the Type III effector gene set in the Ralstonia solanacearum species complex

Background

Ralstonia solanacearum is a soil-borne beta-proteobacterium that causes bacterial wilt disease in many food crops and is a major problem for agriculture in intertropical regions. R. solanacearum is a heterogeneous species, both phenotypically and genetically, and is considered as a species complex. Pathogenicity of R. solanacearum relies on the Type III secretion system that injects Type III effector (T3E) proteins into plant cells. T3E collectively perturb host cell processes and modulate plant immunity to enable bacterial infection.

Results

We provide the catalogue of T3E in the R. solanacearum species complex, as well as candidates in newly sequenced strains. 94 T3E orthologous groups were defined on phylogenetic bases and ordered using a uniform nomenclature. This curated T3E catalog is available on a public website and a bioinformatic pipeline has been designed to rapidly predict T3E genes in newly sequenced strains. Systematical analyses were performed to detect lateral T3E gene transfer events and identify T3E genes under positive selection. Our analyses also pinpoint the RipF translocon proteins as major discriminating determinants among the phylogenetic lineages.

Conclusions

Establishment of T3E repertoires in strains representatives of the R. solanacearum biodiversity allowed determining a set of 22 T3E present in all the strains but provided no clues on host specificity determinants. The definition of a standardized nomenclature and the optimization of predictive tools will pave the way to understanding how variation of these repertoires is correlated to the diversification of this species complex and how they contribute to the different strain pathotypes.