Identification of genomic islands in the genome ofBacillus cereusby comparative analysis withBacillus anthracis

Characterization of a Deep Sea Bacillus toyonensis Isolate: Genomic and Pathogenic Features

Bacillus toyonensis is a group of Gram-positive bacteria belonging to the Bacillus cereus group and used in some cases as probiotics or biocontrol agents. To our knowledge, B. toyonensis from the deep sea (depth >1,000 m) has not been documented. Here, we report the isolation and characterization of a B. toyonensis strain, P18, from a deep sea hydrothermal field. P18 is aerobic, motile, and able to grow at low temperatures (4°C) and high concentrations of NaCl (8%). P18 possesses a circular chromosome of 5,250,895 bp and a plasmid of 536,892 bp, which encode 5,380 and 523 genes, respectively. Of these genes, 2,229 encode hypothetical proteins that could not be annotated based on the COG database. Comparative genomic analysis showed that P18 is most closely related to the type strain of B. toyonensis, BCT-7112^T. Compared to BCT-7112^T, P18 contains 1,401 unique genes, 441 of which were classified into 20 COG functional categories, and the remaining 960 genes could not be annotated. A total of 319 putative virulence genes were identified in P18, including toxin-related genes, and 24 of these genes are absent in BCT-7112^T. P18 exerted strong cytopathic effects on fish and mammalian cells that led to rapid cell death. When inoculated via injection into fish and mice, P18 rapidly disseminated in host tissues and induced acute infection and mortality. Histopathology revealed varying degrees of tissue lesions in the infected animals. Furthermore, P18 could survive in fish and mouse sera and possessed hemolytic activity. Taken together, these results provide the first evidence that virulent B. toyonensis exists in deep sea environments.

Inside the Pan-genome - Methods and Software Overview

The number of genomes that have been deposited in databases has increased exponentially after the advent of Next-Generation Sequencing (NGS), which produces high-throughput sequence data; this circumstance has demanded the development of new bioinformatics software and the creation of new areas, such as comparative genomics. In comparative genomics, the genetic content of an organism is compared against other organisms, which helps in the prediction of gene function and coding region sequences, identification of evolutionary events and determination of phylogenetic relationships. However, expanding comparative genomics to a large number of related bacteria, we can infer their lifestyles, gene repertoires and minimal genome size. In this context, a powerful approach called Pan-genome has been initiated and developed. This approach involves the genomic comparison of different strains of the same species, or even genus. Its main goal is to establish the total number of non-redundant genes that are present in a determined dataset. Pan-genome consists of three parts: core genome; accessory or dispensable genome; and species-specific or strain-specific genes. Furthermore, pan-genome is considered to be “open” as long as new genes are added significantly to the total repertoire for each new additional genome and “closed” when the newly added genomes cannot be inferred to significantly increase the total repertoire of the genes. To perform all of the required calculations, a substantial amount of software has been developed, based on orthologous and paralogous gene identification.

Identification of Horizontally-transferred Genomic Islands and Genome Segmentation Points by Using the GC Profile Method

The nucleotide composition of genomes undergoes dramatic variations among all three kingdoms of life. GC content, an important characteristic for a genome, is related to many important functions, and therefore GC content and its distribution are routinely reported for sequenced genomes. Traditionally, GC content distribution is assessed by computing GC contents in windows that slide along the genome. Disadvantages of this routinely used window-based method include low resolution and low sensitivity. Additionally, different window sizes result in different GC content distribution patterns within the same genome. We proposed a windowless method, the GC profile, for displaying GC content variations across the genome. Compared to the window-based method, the GC profile has the following advantages: 1) higher sensitivity, because of variation-amplifying procedures; 2) higher resolution, because boundaries between domains can be determined at one single base pair; 3) uniqueness, because the GC profile is unique for a given genome and 4) the capacity to show both global and regional GC content distributions. These characteristics are useful in identifying horizontally-transferred genomic islands and homogenous GC-content domains. Here, we review the applications of the GC profile in identifying genomic islands and genome segmentation points, and in serving as a platform to integrate with other algorithms for genome analysis. A web server generating GC profiles and implementing relevant genome segmentation algorithms is available at: www.zcurve.net.

A Brief Review: The Z-curve Theory and its Application in Genome Analysis

In theoretical physics, there exist two basic mathematical approaches, algebraic and geometrical methods, which, in most cases, are complementary. In the area of genome sequence analysis, however, algebraic approaches have been widely used, while geometrical approaches have been less explored for a long time. The Z-curve theory is a geometrical approach to genome analysis. The Z-curve is a three-dimensional curve that represents a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z-curve, therefore, contains all the information that the corresponding DNA sequence carries. The analysis of a DNA sequence can then be performed through studying the corresponding Z-curve. The Z-curve method has found applications in a wide range of areas in the past two decades, including the identifications of protein-coding genes, replication origins, horizontally-transferred genomic islands, promoters, translational start sides and isochores, as well as studies on phylogenetics, genome visualization and comparative genomics. Here, we review the progress of Z-curve studies from aspects of both theory and applications in genome analysis.

Recognition of prokaryotic promoters based on a novel variable-window Z-curve method

Transcription is the first step in gene expression, and it is the step at which most of the regulation of expression occurs. Although sequenced prokaryotic genomes provide a wealth of information, transcriptional regulatory networks are still poorly understood using the available genomic information, largely because accurate prediction of promoters is difficult. To improve promoter recognition performance, a novel variable-window Z-curve method is developed to extract general features of prokaryotic promoters. The features are used for further classification by the partial least squares technique. To verify the prediction performance, the proposed method is applied to predict promoter fragments of two representative prokaryotic model organisms (Escherichia coli and Bacillus subtilis). Depending on the feature extraction and selection power of the proposed method, the promoter prediction accuracies are improved markedly over most existing approaches: for E. coli, the accuracies are 96.05% (σ⁷⁰ promoters, coding negative samples), 90.44% (σ⁷⁰ promoters, non-coding negative samples), 92.13% (known sigma-factor promoters, coding negative samples), 92.50% (known sigma-factor promoters, non-coding negative samples), respectively; for B. subtilis, the accuracies are 95.83% (known sigma-factor promoters, coding negative samples) and 99.09% (known sigma-factor promoters, non-coding negative samples). Additionally, being a linear technique, the computational simplicity of the proposed method makes it easy to run in a matter of minutes on ordinary personal computers or even laptops. More importantly, there is no need to optimize parameters, so it is very practical for predicting other species promoters without any prior knowledge or prior information of the statistical properties of the samples.

Accurate localization of the integration sites of two genomic islands at single-nucleotide resolution in the genome of Bacillus cereus ATCC 10987

We have identified two genomic islands, that is, BCEGI-1 and BCEGI-2, in the genome of Bacillus cereus ATCC 10987, based on comparative analysis with Bacillus cereus ATCC 14579. Furthermore, by using the cumulative GC profile and performing homology searches between the two genomes, the integration sites of the two genomic islands were determined at single-nucleotide resolution. BCEGI-1 is integrated between 159705 bp and 198000 bp, whereas BCEGI-2 is integrated between the end of ORF BCE4594 and the start of the intergenic sequence immediately following BCE4626, that is, from 4256803 bp to 4285534 bp. BCEGI-1 harbors two bacterial Tn7 transposons, which have two sets of genes encoding TnsA, B, C, and D. It is generally believed that unlike the TnsABC+E pathway, the TnsABC+D pathway would only promote vertical transmission to daughter cells. The evidence presented in this paper, however, suggests a role of the TnsABC+D pathway in the horizontal transfer of some genomic islands.

'Genome order index' should not be used for defining compositional constraints in nucleotide sequences--a case study of the Z-curve

Background

The Z-curve is a three dimensional representation of DNA sequences proposed over a decade ago and has been extensively applied to sequence segmentation, horizontal gene transfer detection, and sequence analysis. Based on the Z-curve, a "genome order index," was proposed, which is defined as S = a²+ c²+t²+g², where a, c, t, and g are the nucleotide frequencies of A, C, T, and G, respectively. This index was found to be smaller than 1/3 for almost all tested genomes, which was taken as support for the existence of a constraint on genome composition. A geometric explanation for this constraint has been suggested. Each genome was represented by a point P whose distance from the four faces of a regular tetrahedron was given by the frequencies a, c, t, and g. They claimed that an inscribed sphere of radius r = 1/ contains almost all points corresponding to various genomes, implying that S <r². The distribution of the points P obtained by S was studied using the Z-curve.

Results

In this work, we studied the basic properties of the Z-curve using the "genome order index" as a case study. We show that (1) the calculation of the radius of the inscribed sphere of a regular tetrahedron is incorrect, (2) the S index is narrowly distributed, (3) based on the second parity rule, the S index can be derived directly from the Shannon entropy and is, therefore, redundant, and (4) the Z-curve suffers from over dimensionality, and the dimension stands for GC content alone suffices to represent any given genome.

Conclusion

The "genome order index" S does not represent a constraint on nucleotide composition. Moreover, S can be easily computed from the Gini-Simpson index and be directly derived from entropy and is redundant. Overall, the Z-curve and S are over-complicated measures to GC content and Shannon H index, respectively.

Reviewers

This article was reviewed by Claus Wilke, Joel Bader, Marek Kimmel and Uladzislau Hryshkevich (nominated by Itai Yanai).

Siderophore-mediated iron acquisition systems in Bacillus cereus: Identification of receptors for anthrax virulence-associated petrobactin

During growth under iron limitation, Bacillus cereus and Bacillus anthracis, two human pathogens from the Bacillus cereus group of Gram-positive bacteria, secrete two siderophores, bacillibactin (BB) and petrobactin (PB), for iron acquisition via membrane-associated substrate-binding proteins (SBPs) and other ABC transporter components. Since PB is associated with virulence traits in B. anthracis, the PB-mediated iron uptake system presents a potential target for antimicrobial therapies; its characterization in B. cereus is described here. Separate transporters for BB, PB, and several xenosiderophores are suggested by (55)Fe-siderophore uptake studies. The PB precursor, 3,4-dihydroxybenzoic acid (3,4-DHB), and the photoproduct of FePB (FePB(nu)) also mediate iron delivery into iron-deprived cells. Putative SBPs were recombinantly expressed, and their ligand specificity and binding affinity were assessed using fluorescence spectroscopy. The noncovalent complexes of the SBPs with their respective siderophores were characterized using ESI-MS. The differences between solution phase behavior and gas phase measurements are indicative of noncovalent interactions between the siderophores and the binding sites of their respective SBPs. These studies combined with bioinformatics sequence comparison identify SBPs from five putative transporters specific for BB and enterobactin (FeuA), 3,4-DHB and PB (FatB), PB (FpuA), schizokinen (YfiY), and desferrioxamine and ferrichrome (YxeB). The two PB receptors show different substrate ranges: FatB has the highest affinity for ferric 3,4-DHB, iron-free PB, FePB, and FePB(nu), whereas FpuA is specific to only apo- and ferric PB. The biochemical characterization of these SBPs provides the first identification of the transporter candidates that most likely play a role in the B. cereus group pathogenicity.

Metabolic capacity of Bacillus cereus strains ATCC 14579 and ATCC 10987 interlinked with comparative genomics

Bacillus cereus is an important food-borne pathogen and spoilage organism. In this study, numerous phenotypes and the genomes of B. cereus strains ATCC 14579 and ATCC 10987 were analysed to compare their metabolic capacity and stress resistance potential. The growth performance of the two strains was assessed for nearly 2000 phenotypes, including use of nutrient sources, performance in acid and basic environments, osmo-tolerance and antibiotic resistance. Several food-relevant phenotypic differences were found between ATCC 14579 and ATCC 10987, such as differences in utilization of carbohydrates, peptides, amino acids and ammonia. Subsequently, the genomes of both strains were analysed with INPARANOID to search for strain-specific open reading frames (ORFs). B. cereus ATCC 14579 and ATCC 10987 were found to harbour 983 and 1360 strain-specific ORFs respectively. The strain-specific phenotypic features were interlinked with corresponding genetic features and for several phenotypic differences a related strain-specific genetic feature could be identified. In conclusion, the combination of phenotypic data with strain-specific genomic differences has led to detailed insight into the performance of the two B. cereus strains, and may supply indicators for the performance of these bacteria in different environments and ecological niches.

The role of laterally transferred genes in adaptive evolution

Background

Bacterial genomes develop new mechanisms to tide them over the imposing conditions they encounter during the course of their evolution. Acquisition of new genes by lateral gene transfer may be one of the dominant ways of adaptation in bacterial genome evolution. Lateral gene transfer provides the bacterial genome with a new set of genes that help it to explore and adapt to new ecological niches.

Methods

A maximum likelihood analysis was done on the five sequenced corynebacterial genomes to model the rates of gene insertions/deletions at various depths of the phylogeny.

Results

The study shows that most of the laterally acquired genes are transient and the inferred rates of gene movement are higher on the external branches of the phylogeny and decrease as the phylogenetic depth increases. The newly acquired genes are under relaxed selection and evolve faster than their older counterparts. Analysis of some of the functionally characterised LGTs in each species has indicated that they may have a possible adaptive role.

Conclusion

The five Corynebacterial genomes sequenced to date have evolved by acquiring between 8 – 14% of their genomes by LGT and some of these genes may have a role in adaptation.

Using the nucleotide substitution rate matrix to detect horizontal gene transfer

BACKGROUND

Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conferring antibiotic resistance, improved detection of horizontally transferred genes from sequence data would be an important advance. Existing sequence-based methods for detecting HGT focus on changes in nucleotide composition or on differences between gene and genome phylogenies; these methods have high error rates.

RESULTS

First, we introduce a new class of methods for detecting HGT based on the changes in nucleotide substitution rates that occur when a gene is transferred to a new organism. Our new methods discriminate simulated HGT events with an error rate up to 10 times lower than does GC content. Use of models that are not time-reversible is crucial for detecting HGT. Second, we show that using combinations of multiple predictors of HGT offers substantial improvements over using any single predictor, yielding as much as a factor of 18 improvement in performance (a maximum reduction in error rate from 38% to about 3%). Multiple predictors were combined by using the random forests machine learning algorithm to identify optimal classifiers that separate HGT from non-HGT trees.

CONCLUSION

The new class of HGT-detection methods introduced here combines advantages of phylogenetic and compositional HGT-detection techniques. These new techniques offer order-of-magnitude improvements over compositional methods because they are better able to discriminate HGT from non-HGT trees under a wide range of simulated conditions. We also found that combining multiple measures of HGT is essential for detecting a wide range of HGT events. These novel indicators of horizontal transfer will be widely useful in detecting HGT events linked to the evolution of important bacterial traits, such as antibiotic resistance and pathogenicity.

The fate of laterally transferred genes: life in the fast lane to adaptation or death

Large-scale genome arrangement plays an important role in bacterial genome evolution. A substantial number of genes can be inserted into, deleted from, or rearranged within genomes during evolution. Detecting or inferring gene insertions/deletions is of interest because such information provides insights into bacterial genome evolution and speciation. However, efficient inference of genome events is difficult because genome comparisons alone do not generally supply enough information to distinguish insertions, deletions, and other rearrangements. In this study, homologous genes from the complete genomes of 13 closely related bacteria were examined. The presence or absence of genes from each genome was cataloged, and a maximum likelihood method was used to infer insertion/deletion rates according to the phylogenetic history of the taxa. It was found that whole gene insertions/deletions in genomes occur at rates comparable to or greater than the rate of nucleotide substitution and that higher insertion/deletion rates are often inferred to be present at the tips of the phylogeny with lower rates on more ancient interior branches. Recently transferred genes are under faster and relaxed evolution compared with more ancient genes. Together, this implies that many of the lineage-specific insertions are lost quickly during evolution and that perhaps a few of the genes inserted by lateral transfer are niche specific.

The impact of comparative genomics on infectious disease research

The past decade has witnessed a revolution in infectious disease research, fuelled by the accumulation of a huge amount of DNA sequence data. The avalanche of genome sequence information has largely promoted the development of comparative genomics, which exploits available genome sequences to perform either inter- or intra-species comparisons of bacterial genome contents, or performs comparisons between the human genome and those of other organisms. This review aims to summarize how comparative genomics is being extensively used in infectious disease research, such as in the studies to identify virulence determinants, antimicrobial drug targets, vaccine candidates and new markers for diagnostics. These applications hold considerable promise for alleviating the burden of infectious diseases in the coming years.

Dynamic analysis of a genomic island inMagnetospirillumsp. strain AMB-1 reveals how magnetosome synthesis developed

The entire structure of a 98 kb genomic region that abounds in genes related to magnetosome synthesis was first described in the Magnetospirillum sp. strain AMB-1. The deletion of this 98 kb genomic region and the circular form after excision from the chromosome was detected by PCR amplification. This strongly suggests that the region has undergone a lateral gene transfer. The region has the characteristics of a genomic island: low GC content, location between two repetitive sequences, and the presence of an integrase in the flanking region of the first repetitive sequence. This 98 kb genomic region has the potential for transfer by the integrase activity. Comparative genome analysis revealed other regions with a high concentration of orthologs in magnetic bacteria besides the 98 kb region, and magnetosome synthesis seemed to need not only the exogenous 98 kb region, but also other orthologs and individually originating genes.

Genome evolution in bacteria: order beneath chaos

Bacterial genomes have been viewed as collections of genes, with each gene and genome evolving more-or-less independently through the acquisition of mutational changes. This historical view has been overturned by the finding that genomes of even closely-related taxa differ widely in gene content. Yet, genomes are more than ever-shuffling collections of genes. Some genes within a genome are more transient than others, conferring a layer of phenotypic lability over a core of genotypic stability; this core decreases in size as the taxa included become increasingly diverse. In addition, some lineages no longer experience high rates of gene turnover, and gene content alters primarily through slow rates of gene loss. More importantly, the cell and molecular biology of the bacterial cell imposes constraints on chromosome composition, maintaining a stable architecture in the face of gene turnover. As a result, genomes reflect the sum of processes that introduce variability, which is then arbitrated by processes that maintain stability.

In vitro and intra-macrophage gene expression by Rhodococcus equi strain 103

Rhodococcus equi is a facultative intracellular respiratory pathogen of foals that persists and multiplies within macrophages. In foals, virulence is associated with 80-90 kb plasmids, which include a pathogenicity island (PI) containing the virulence-associated protein (vap) gene family, but detailed understanding of the basis of virulence is still poor. A 60 spot-based DNA microarray was developed containing eight PI genes and 42 chromosomal putative virulence or virulence-associated genes selected from a recent partial genome sequence in order to study transcription of these genes by R. equi grown inside macrophages and under in vitro conditions thought to simulate those of macrophages. In addition to seven PI genes, nine chromosomal genes involved in fatty acid and lipid metabolism (choD, fadD13, fbpB), heme biosynthesis (hemE), iron utilization (mbtF), heat shock resistance and genes encoding chaperones (clpB, groEL), a sigma factor (sigK), and a transcriptional regulator (moxR) were significantly induced in R. equi growing inside macrophages. The pattern of R. equi chromosomal genes significantly transcribed inside macrophages largely differed from those transcribed under in vitro conditions (37 degrees C, pH 5.0 or 50mM H2O2 for 30 min). This study has identified genes, other than those of the virulence plasmid, the transcription of which is enhanced within equine macrophages. These genes should be investigated further to improve understanding of how this organism survives intracellularly.

Genomic islands in the Corynebacterium efficiens genome

Corynebacterium efficiens is a gram-positive nonpathogenic bacterium which can grow and produce glutamate at 40 degrees C or above. By using the cumulative GC profile method, we have identified four genomic islands which have many unifying genomic island-specific features in the C. efficiens genome. The presence of the gene encoding an aspartate kinase in a genomic island helps explain the unexpected low thermal stability of this enzyme; i.e., the adaptive mutations have not occurred extensively due to the recent horizontal gene transfer.

Identification of replication origins in archaeal genomes based on the Z-curve method

The Z-curve is a three-dimensional curve that constitutes a unique representation of a DNA sequence, i.e., both the Z-curve and the given DNA sequence can be uniquely reconstructed from the other. We employed Z-curve analysis to identify one replication origin in the Methanocaldococcus jannaschii genome, two replication origins in the Halobacterium species NRC-1 genome and one replication origin in the Methanosarcina mazei genome. One of the predicted replication origins of Halobacterium species NRC-1 is the same as a replication origin later identified by in vivo experiments. The Z-curve analysis of the Sulfolobus solfataricus P2 genome suggested the existence of three replication origins, which is also consistent with later experimental results. This review aims to summarize applications of the Z-curve in identifying replication origins of archaeal genomes, and to provide clues about the locations of as yet unidentified replication origins of the Aeropyrum pernix K1, Methanococcus maripaludis S2, Picrophilus torridus DSM 9790 and Pyrobaculum aerophilum str. IM2 genomes.