Related Bacterial Genomes Research Articles

C-Sibelia: an easy-to-use and highly accurate tool for bacterial genome comparison.

We present C-Sibelia, a highly accurate and easy-to-use software tool for comparing two closely related bacterial genomes, which can be presented as either finished sequences or fragmented assemblies. C-Sibelia takes as input two FASTA files and produces: (1) a VCF file containing all identified single nucleotide variations and indels; (2) an XMFA file containing alignment information. The software also produces Circos diagrams visualizing high level genomic architecture for rearrangement analyses. C-Sibelia is a part of the Sibelia comparative genomics suite, which is freely available under the GNU GPL v.2 license at http://sourceforge.net/projects/sibelia-bio. C-Sibelia is compatible with Unix-like operating systems. A web-based version of the software is available at http://etool.me/software/csibelia.

Testing the Infinitely Many Genes Model for the Evolution of the Bacterial Core Genome and Pangenome

When groups of related bacterial genomes are compared, the number of core genes found in all genomes is usually much less than the mean genome size, whereas the size of the pangenome (the set of genes found on at least one of the genomes) is much larger than the mean size of one genome. We analyze 172 complete genomes of Bacilli and compare the properties of the pangenomes and core genomes of monophyletic subsets taken from this group. We then assess the capabilities of several evolutionary models to predict these properties. The infinitely many genes (IMG) model is based on the assumption that each new gene can arise only once. The predictions of the model depend on the shape of the evolutionary tree that underlies the divergence of the genomes. We calculate results for coalescent trees, star trees, and arbitrary phylogenetic trees of predefined fixed branch length. On a star tree, the pangenome size increases linearly with the number of genomes, as has been suggested in some previous studies, whereas on a coalescent tree, it increases logarithmically. The coalescent tree gives a better fit to the data, for all the examples we consider. In some cases, a fixed phylogenetic tree proved better than the coalescent tree at reproducing structure in the gene frequency spectrum, but little improvement was gained in predictions of the core and pangenome sizes. Most of the data are well explained by a model with three classes of gene: an essential class that is found in all genomes, a slow class whose rate of origination and deletion is slow compared with the time of divergence of the genomes, and a fast class showing rapid origination and deletion. Although the majority of genes originating in a genome are in the fast class, these genes are not retained for long periods, and the majority of genes present in a genome are in the slow or essential classes. In general, we show that the IMG model is useful for comparison with experimental genome data both for species level and widely divergent taxonomic groups. Software implementing the described formulae is provided at http://github.com/rec3141/pangenome.

The ecology of bacterial genes and the survival of the new.

Much of the observed variation among closely related bacterial genomes is attributable to gains and losses of genes that are acquired horizontally as well as to gene duplications and larger amplifications. The genomic flexibility that results from these mechanisms certainly contributes to the ability of bacteria to survive and adapt in varying environmental challenges. However, the duplicability and transferability of individual genes imply that natural selection should operate, not only at the organismal level, but also at the level of the gene. Genes can be considered semiautonomous entities that possess specific functional niches and evolutionary dynamics. The evolution of bacterial genes should respond both to selective pressures that favor competition, mostly among orthologs or paralogs that may occupy the same functional niches, and cooperation, with the majority of other genes coexisting in a given genome. The relative importance of either type of selection is likely to vary among different types of genes, based on the functional niches they cover and on the tightness of their association with specific organismal lineages. The frequent availability of new functional niches caused by environmental changes and biotic evolution should enable the constant diversification of gene families and the survival of new lineages of genes.

RegPrecise web services interface: programmatic access to the transcriptional regulatory interactions in bacteria reconstructed by comparative genomics

Web services application programming interface (API) was developed to provide a programmatic access to the regulatory interactions accumulated in the RegPrecise database (http://regprecise.lbl.gov), a core resource on transcriptional regulation for the microbial domain of the Department of Energy (DOE) Systems Biology Knowledgebase. RegPrecise captures and visualize regulogs, sets of genes controlled by orthologous regulators in several closely related bacterial genomes, that were reconstructed by comparative genomics. The current release of RegPrecise 2.0 includes >1400 regulogs controlled either by protein transcription factors or by conserved ribonucleic acid regulatory motifs in >250 genomes from 24 taxonomic groups of bacteria. The reference regulons accumulated in RegPrecise can serve as a basis for automatic annotation of regulatory interactions in newly sequenced genomes. The developed API provides an efficient access to the RegPrecise data by a comprehensive set of 14 web service resources. The RegPrecise web services API is freely accessible at http://regprecise.lbl.gov/RegPrecise/services.jsp with no login requirements.

Robustness Assessment of Whole Bacterial Genome Segmentations

Comparison of closely related bacterial genomes has revealed the presence of highly conserved sequences forming a "backbone" that is interrupted by numerous, less conserved, DNA fragments. Segmentation of bacterial genomes into backbone and variable regions is particularly useful to investigate, among other things, bacterial genome evolution. Several software tools have been designed to compare complete bacterial chromosomes and a few online databases store pre-computed genome comparisons. However, very few statistical methods are available to evaluate the reliability of these software tools and to compare the results obtained with them. To fill this gap, we have developed two local scores to measure the robustness of bacterial genome segmentations. Our method uses a simulation procedure based on random perturbations of the compared genomes. The two scores described in this article provide useful information and are easy to implement, and their interpretation is intuitive. We show that they are suited to discriminate between robust and non-robust segmentations when genome aligners such as MAUVE and MGA are used.

Alignment-free detection of horizontal gene transfer between closely related bacterial genomes

Bacterial epidemics are often caused by strains that have acquired their increased virulence through horizontal gene transfer. Due to this association with disease, the detection of horizontal gene transfer continues to receive attention from microbiologists and bioinformaticians alike. Most software for detecting transfer events is based on alignments of sets of genes or of entire genomes. But despite great advances in the design of algorithms and computer programs, genome alignment remains computationally challenging. We have therefore developed an alignment-free algorithm for rapidly detecting horizontal gene transfer between closely related bacterial genomes. Our implementation of this algorithm is called alfy for "ALignment Free local homologY" and is freely available from http://guanine.evolbio.mpg.de/alfy/. In this comment we demonstrate the application of alfy to the genomes of Staphylococcus aureus. We also argue that-contrary to popular belief and in spite of increasing computer speed-algorithmic optimization is becoming more, not less, important if genome data continues to accumulate at the present rate.

Leaderless genes in bacteria: clue to the evolution of translation initiation mechanisms in prokaryotes

BackgroundShine-Dalgarno (SD) signal has long been viewed as the dominant translation initiation signal in prokaryotes. Recently, leaderless genes, which lack 5'-untranslated regions (5'-UTR) on their mRNAs, have been shown abundant in archaea. However, current large-scale in silico analyses on initiation mechanisms in bacteria are mainly based on the SD-led initiation way, other than the leaderless one. The study of leaderless genes in bacteria remains open, which causes uncertain understanding of translation initiation mechanisms for prokaryotes.ResultsHere, we study signals in translation initiation regions of all genes over 953 bacterial and 72 archaeal genomes, then make an effort to construct an evolutionary scenario in view of leaderless genes in bacteria. With an algorithm designed to identify multi-signal in upstream regions of genes for a genome, we classify all genes into SD-led, TA-led and atypical genes according to the category of the most probable signal in their upstream sequences. Particularly, occurrence of TA-like signals about 10 bp upstream to translation initiation site (TIS) in bacteria most probably means leaderless genes.ConclusionsOur analysis reveals that leaderless genes are totally widespread, although not dominant, in a variety of bacteria. Especially for Actinobacteria and Deinococcus-Thermus, more than twenty percent of genes are leaderless. Analyzed in closely related bacterial genomes, our results imply that the change of translation initiation mechanisms, which happens between the genes deriving from a common ancestor, is linearly dependent on the phylogenetic relationship. Analysis on the macroevolution of leaderless genes further shows that the proportion of leaderless genes in bacteria has a decreasing trend in evolution.

Prediction of small non-coding RNA in bacterial genomes using support vector machines

Small non-coding RNA genes have been shown to play important regulatory roles in a variety of cellular processes, but prediction of non-coding RNA genes is a great challenge, using either an experimental or a computational approach, due to the characteristics of sRNAs, which are that sRNAs are small in size, are not translated into proteins and show variable stability. Most known sRNAs have been identified in Escherichia coli and have been shown to be conserved in closely related organisms. We have developed an integrative approach that searches highly conserved intergenic regions among related bacterial genomes for combinations of characteristics that have been extracted from known E. coli sRNA genes. Support vector machines (SVM) were then used with these characteristics to predict novel sRNA genes.

Screening of strain-specific Actinobacillus pleuropneumoniae genes using a combination method

We describe a three-step method designed to identify distinct antigen-coding genes between two related bacterial genomes by: (a) constructing a subtractive library using Representational Difference Analysis (RDA), (b) characterization of gene expression in vitro using a ribosome display system combined with antibody screening and (c) gene recovery and confirmation using RT-PCR and reverse Southern hybridization, respectively. To test the efficacy of this strategy we screened the antigen-coding gene profile of Actinobacillus pleuropneumoniae (APP) strains CCVC259 and CCVC263 that do not elicit cross-protective immunity. This strategy identified six different DNA fragments from CCVC259 and 10 different DNA fragments from CCVC263. Of six sequences identified from CCVC259, 2 were not significantly similar, two were 74% and 87% homologous to the sequences encoding for the Ralstonia eutropha H16 conserved membrane protein and transcriptional regulator respectively, and two were > 96% homologous to the Pseudomonas alcaligenes putative transposase subunit genes IS1474 and IS1475. Among ten unique DNA fragments identified from strain CCVC263, eight were homologous to DNA fragments encoding the TBP 1 precursor, ATP-dependent helicase HepA, glycosylase, methyltransferase and GTPase in the APP L20 genome and two genes identified had no significant similarity. Our findings indicated that the three-step method could be utilized to identify unique antigen-coding genes and may be a powerful and efficient technique for serotype-specific identification of pathogens and polyvalent vaccine design.

MOSAIC: an online database dedicated to the comparative genomics of bacterial strains at the intra-species level

BackgroundThe recent availability of complete sequences for numerous closely related bacterial genomes opens up new challenges in comparative genomics. Several methods have been developed to align complete genomes at the nucleotide level but their use and the biological interpretation of results are not straightforward. It is therefore necessary to develop new resources to access, analyze, and visualize genome comparisons.DescriptionHere we present recent developments on MOSAIC, a generalist comparative bacterial genome database. This database provides the bacteriologist community with easy access to comparisons of complete bacterial genomes at the intra-species level. The strategy we developed for comparison allows us to define two types of regions in bacterial genomes: backbone segments (i.e., regions conserved in all compared strains) and variable segments (i.e., regions that are either specific to or variable in one of the aligned genomes). Definition of these segments at the nucleotide level allows precise comparative and evolutionary analyses of both coding and non-coding regions of bacterial genomes. Such work is easily performed using the MOSAIC Web interface, which allows browsing and graphical visualization of genome comparisons.ConclusionThe MOSAIC database now includes 493 pairwise comparisons and 35 multiple maximal comparisons representing 78 bacterial species. Genome conserved regions (backbones) and variable segments are presented in various formats for further analysis. A graphical interface allows visualization of aligned genomes and functional annotations. The MOSAIC database is available online at .

A high-throughput percentage-of-binding strategy to measure binding energies in DNA–protein interactions: application to genome-scale site discovery

Quantifying the binding energy in DNA–protein interactions is of critical importance to understand transcriptional regulation. Based on a simple computational model, this study describes a high-throughput percentage-of-binding strategy to measure the binding energy in DNA–protein interactions between the Shewanella oneidensis ArcA two-component transcription factor protein and a systematic set of mutants in an ArcA-P (phosphorylated ArcA) binding site. The binding energies corresponding to each of the 4 nt at each position in the 15-bp binding site were used to construct a position-specific energy matrix (PEM) that allowed a reliable prediction of ArcA-P binding sites not only in Shewanella but also in related bacterial genomes.

SIGffRid: A tool to search for sigma factor binding sites in bacterial genomes using comparative approach and biologically driven statistics

BackgroundMany programs have been developed to identify transcription factor binding sites. However, most of them are not able to infer two-word motifs with variable spacer lengths. This case is encountered for RNA polymerase Sigma (σ) Factor Binding Sites (SFBSs) usually composed of two boxes, called -35 and -10 in reference to the transcription initiation point. Our goal is to design an algorithm detecting SFBS by using combinational and statistical constraints deduced from biological observations.ResultsWe describe a new approach to identify SFBSs by comparing two related bacterial genomes. The method, named SIGffRid (SIGma Factor binding sites Finder using R'MES to select Input Data), performs a simultaneous analysis of pairs of promoter regions of orthologous genes. SIGffRid uses a prior identification of over-represented patterns in whole genomes as selection criteria for potential -35 and -10 boxes. These patterns are then grouped using pairs of short seeds (of which one is possibly gapped), allowing a variable-length spacer between them. Next, the motifs are extended guided by statistical considerations, a feature that ensures a selection of motifs with statistically relevant properties. We applied our method to the pair of related bacterial genomes of Streptomyces coelicolor and Streptomyces avermitilis. Cross-check with the well-defined SFBSs of the SigR regulon in S. coelicolor is detailed, validating the algorithm. SFBSs for HrdB and BldN were also found; and the results suggested some new targets for these σ factors. In addition, consensus motifs for BldD and new SFBSs binding sites were defined, overlapping previously proposed consensuses. Relevant tests were carried out also on bacteria with moderate GC content (i.e. Escherichia coli/Salmonella typhimurium and Bacillus subtilis/Bacillus licheniformis pairs). Motifs of house-keeping σ factors were found as well as other SFBSs such as that of SigW in Bacillus strains.ConclusionWe demonstrate that our approach combining statistical and biological criteria was successful to predict SFBSs. The method versatility autorizes the recognition of other kinds of two-box regulatory sites.

Distribution and evolution of short tandem repeats in closely related bacterial genomes

Simultaneous identification and comparison of perfect and imperfect microsatellites within a genome is a valuable tool both to overcome the lack of a consensus definition of SSRs and to assess repeat history. Detailed analysis of the overall distribution of perfect and imperfect microsatellites in closely related bacterial taxa is expected to give new insight into the evolution of prokaryotic genomes. We have performed a genome-wide analysis of microsatellite distribution in four Escherichia coli and seven Chlamydial strains. Chlamydial strains generally have a higher density of SSRs and show greater intra-group differences of SSR distribution patterns than E. coli genomes. In most investigated genomes the distribution of the total lengths of matching perfect and imperfect trinucleotide repeats are highly similar, with the notable exception of C. muridarum. Closely related strains show more similar repeat distribution patterns than strains separated by a longer divergence time. The discrepancy between the preferred classes of perfect and imperfect repeats in C. muridarum implies accelerated evolution of SSRs in this particular strain. Our results suggest that microsatellites, although considerably less abundant than in eukaryotic genomes, may nevertheless play an important role in the evolution of prokaryotic genomes and several gene families.

Universal patterns of purifying selection at noncoding positions in bacteria

To investigate the dependence of the number of regulatory sites per intergenic region on genome size, we developed a new method for detecting purifying selection at noncoding positions in clades of related bacterial genomes. We comprehensively quantified evidence of purifying selection at noncoding positions across bacteria and found several striking universal patterns. Consistent with selection acting at transcriptional regulatory elements near the transcription start, we find a universal positional profile of selection with respect to gene starts and ends, showing most evidence of selection immediately upstream and least immediately downstream from genes. A further set of universal features indicates that selection for translation initiation efficiency is the major determinant of the sequence composition around translation start in all clades. In addition to a peak in selection at ribosomal binding sites, the region immediately around translation start shows a universal pattern of high adenine frequency, significant selection at silent positions, and avoidance of RNA secondary structure. Surprisingly, although the number of transcription factors (TF) increases quadratically with genome size, we present several lines of evidence that small and large genomes have the same average number of regulatory sites per intergenic region. By comparing the sequence diversity of the most and least conserved DNA words in intergenic regions across clades we provide evidence that the structure of transcription regulatory networks changes dramatically with genome size: Small genomes have a small number of TFs with a large number of target sites, whereas large genomes have a large number of TFs with a small number of target sites each.

Evolution of Paralogous Genes: Reconstruction of Genome Rearrangements Through Comparison of Multiple Genomes Within Staphylococcus aureus

Analysis of evolution of paralogous genes in a genome is central to our understanding of genome evolution. Comparison of closely related bacterial genomes, which has provided clues as to how genome sequences evolve under natural conditions, would help in such an analysis. With species Staphylococcus aureus, whole-genome sequences have been decoded for seven strains. We compared their DNA sequences to detect large genome polymorphisms and to deduce mechanisms of genome rearrangements that have formed each of them. We first compared strains N315 and Mu50, which make one of the most closely related strain pairs, at the single-nucleotide resolution to catalogue all the middle-sized (more than 10 bp) to large genome polymorphisms such as indels and substitutions. These polymorphisms include two paralogous gene sets, one in a tandem paralogue gene cluster for toxins in a genomic island and the other in a ribosomal RNA operon. We also focused on two other tandem paralogue gene clusters and type I restriction-modification (RM) genes on the genomic islands. Then we reconstructed rearrangement events responsible for these polymorphisms, in the paralogous genes and the others, with reference to the other five genomes. For the tandem paralogue gene clusters, we were able to infer sequences for homologous recombination generating the change in the repeat number. These sequences were conserved among the repeated paralogous units likely because of their functional importance. The sequence specificity (S) subunit of type I RM systems showed recombination, likely at the homology of a conserved region, between the two variable regions for sequence specificity. We also noticed novel alleles in the ribosomal RNA operons and suggested a role for illegitimate recombination in their formation. These results revealed importance of recombination involving long conserved sequence in the evolution of paralogous genes in the genome.

Leaner and meaner genomes in Escherichia coli

A streamlined Escherichia coli K-12 has been engineered in which 15% of the genome has been deleted

Selection for Unequal Densities of σ70 Promoter-Like Signals in Different Regions of Large Bacterial Genomes

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.

Comparisons of d N/d S are time dependent for closely related bacterial genomes

The ratio of non-synonymous (d N) to synonymous (d S) changes between taxa is frequently computed to assay the strength and direction of selection. Here we note that for comparisons between closely related strains and/or species a second parameter needs to be considered, namely the time since divergence of the two sequences under scrutiny. We demonstrate that a simple time lag model provides a general, parsimonious explanation of the extensive variation in the d N/d S ratio seen when comparing closely related bacterial genomes. We explore this model through simulation and comparative genomics, and suggest a role for hitch-hiking in the accumulation of non-synonymous mutations. We also note taxon-specific differences in the change of d N/d S over time, which may indicate variation in selection, or in population genetics parameters such as population size or the rate of recombination. The effect of comparing intra-species polymorphism and inter-species substitution, and the problems associated with these concepts for asexual prokaryotes, are also discussed. We conclude that, because of the critical effect of time since divergence, inter-taxa comparisons are only possible by comparing trajectories of d N/d S over time and it is not valid to compare taxa on the basis of single time points.

Amplified Intergenic Locus Polymorphism as a Basis for Bacterial Typing of Listeria spp. and Escherichia coli

DNA-based methods are increasingly important for bacterial typing. The high number of polymorphic sites present among closely related bacterial genomes is the basis for the presented method. The method identifies multilocus genomic polymorphisms in intergenic regions termed AILP (amplified intergenic locus polymorphism). For each locus, a pair of unique PCR primers was designed to amplify an intergenic sequence from one open reading frame (ORF) to the adjacent ORF. Presence, absence, and size variation of the amplification products were identified and used as genetic markers for rapidly differentiating among strains. Polymorphism was evaluated using 18 AILP sites among 28 strains of Listeria monocytogenes and 6 strains of Listeria spp. and 30 AILP markers among 27 strains of Escherichia coli. Up to four alleles per locus were identified among Listeria strains, and up to six were identified among E. coli strains. In both species, more than half of the AILP sites revealed intraspecies polymorphism. The AILP data were applied to phylogenetic analysis among Listeria and E. coli strains. A clear distinction between L. monocytogenes and Listeria spp. was demonstrated. In addition, the method separated L. monocytogenes into the three known lineages and discriminated the most common virulent serotypic group, 4b. In E. coli, AILP analysis separated the known groups as well as the virulent O157:H7 isolates. These findings for both Listeria and E. coli are in agreement with other phylogenetic studies using molecular markers. The AILP method was found to be rapid, simple, reproducible, and a low-cost method for initial bacterial typing that could serve as a basis for epidemiological investigation.

DNA repeats lead to the accelerated loss of gene order in bacteria

Genetic rearrangements and horizontal transfer make it difficult to study the evolution of bacterial chromosomes. The analysis of closely related bacterial genomes shows that extensively rearranged genomes contain large numbers of repeats. Here, I have quantified these observations by correlating the degree of gene order loss among 22 γ-proteobacteria genomes with the numbers of repeats they contain. Chromosomes containing a higher repeat density have higher rates of rearrangements leading to accelerated loss of gene order.