BackgroundCorynebacterium ulcerans has been detected as a commensal in domestic and wild animals that may serve as reservoirs for zoonotic infections. During the last decade, the frequency and severity of human infections associated with C. ulcerans appear to be increasing in various countries. As the knowledge of genes contributing to the virulence of this bacterium was very limited, the complete genome sequences of two C. ulcerans strains detected in the metropolitan area of Rio de Janeiro were determined and characterized by comparative genomics: C. ulcerans 809 was initially isolated from an elderly woman with fatal pulmonary infection and C. ulcerans BR-AD22 was recovered from a nasal sample of an asymptomatic dog.ResultsThe circular chromosome of C. ulcerans 809 has a total size of 2,502,095 bp and encodes 2,182 predicted proteins, whereas the genome of C. ulcerans BR-AD22 is 104,279 bp larger and comprises 2,338 protein-coding regions. The minor difference in size of the two genomes is mainly caused by additional prophage-like elements in the C. ulcerans BR-AD22 chromosome. Both genomes show a highly similar order of orthologous coding regions; and both strains share a common set of 2,076 genes, demonstrating their very close relationship. A screening for prominent virulence factors revealed the presence of phospholipase D (Pld), neuraminidase H (NanH), endoglycosidase E (EndoE), and subunits of adhesive pili of the SpaDEF type that are encoded in both C. ulcerans genomes. The rbp gene coding for a putative ribosome-binding protein with striking structural similarity to Shiga-like toxins was additionally detected in the genome of the human isolate C. ulcerans 809.ConclusionsThe molecular data deduced from the complete genome sequences provides considerable knowledge of virulence factors in C. ulcerans that is increasingly recognized as an emerging pathogen. This bacterium is apparently equipped with a broad and varying set of virulence factors, including a novel type of a ribosome-binding protein. Whether the respective protein contributes to the severity of human infections (and a fatal outcome) remains to be elucidated by genetic experiments with defined bacterial mutants and host model systems.

Corynebacterium pseudotuberculosis is a facultative intracellular pathogen and the causative agent of several infectious and contagious chronic diseases, including caseous lymphadenitis, ulcerative lymphangitis, mastitis, and edematous skin disease, in a broad spectrum of hosts. In addition, Corynebacterium pseudotuberculosis infections pose a rising worldwide economic problem in ruminants. The complete genome sequences of 15 C. pseudotuberculosis strains isolated from different hosts and countries were comparatively analyzed using a pan-genomic strategy. Phylogenomic, pan-genomic, core genomic, and singleton analyses revealed close relationships among pathogenic corynebacteria, the clonal-like behavior of C. pseudotuberculosis and slow increases in the sizes of pan-genomes. According to extrapolations based on the pan-genomes, core genomes and singletons, the C. pseudotuberculosis biovar ovis shows a more clonal-like behavior than the C. pseudotuberculosis biovar equi. Most of the variable genes of the biovar ovis strains were acquired in a block through horizontal gene transfer and are highly conserved, whereas the biovar equi strains contain great variability, both intra- and inter-biovar, in the 16 detected pathogenicity islands (PAIs). With respect to the gene content of the PAIs, the most interesting finding is the high similarity of the pilus genes in the biovar ovis strains compared with the great variability of these genes in the biovar equi strains. Concluding, the polymerization of complete pilus structures in biovar ovis could be responsible for a remarkable ability of these strains to spread throughout host tissues and penetrate cells to live intracellularly, in contrast with the biovar equi, which rarely attacks visceral organs. Intracellularly, the biovar ovis strains are expected to have less contact with other organisms than the biovar equi strains, thereby explaining the significant clonal-like behavior of the biovar ovis strains.

Bacteria are highly diverse organisms that are able to adapt to a broad range of environments and hosts due to their high genomic plasticity. Horizontal gene transfer plays a pivotal role in this genome plasticity and in evolution by leaps through the incorporation of large blocks of genome sequences, ordinarily known as genomic islands (GEIs). GEIs may harbor genes encoding virulence, metabolism, antibiotic resistance and symbiosis-related functions, namely pathogenicity islands (PAIs), metabolic islands (MIs), resistance islands (RIs) and symbiotic islands (SIs). Although many software for the prediction of GEIs exist, they only focus on PAI prediction and present other limitations, such as complicated installation and inconvenient user interfaces. Here, we present GIPSy, the genomic island prediction software, a standalone and user-friendly software for the prediction of GEIs, built on our previously developed pathogenicity island prediction software (PIPS). We also present four application cases in which we crosslink data from literature to PAIs, MIs, RIs and SIs predicted by GIPSy. Briefly, GIPSy correctly predicted the following previously described GEIs: 13 PAIs larger than 30kb in Escherichia coli CFT073; 1 MI for Burkholderia pseudomallei K96243, which seems to be a miscellaneous island; 1 RI of Acinetobacter baumannii AYE, named AbaR1; and, 1 SI of Mesorhizobium loti MAFF303099 presenting a mosaic structure. GIPSy is the first life-style-specific genomic island prediction software to perform analyses of PAIs, MIs, RIs and SIs, opening a door for a better understanding of bacterial genome plasticity and the adaptation to new traits.

Background Corynebacterium pseudotuberculosis, a Gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity.Methodology and FindingsWe characterized two C. pseudotuberculosis genomes (Cp1002, isolated from goats; and CpC231, isolated from sheep). Analysis of the predicted genomes showed high similarity in genomic architecture, gene content and genetic order. When C. pseudotuberculosis was compared with other Corynebacterium species, it became evident that this pathogenic species has lost numerous genes, resulting in one of the smallest genomes in the genus. Other differences that could be part of the adaptation to pathogenicity include a lower GC content, of about 52%, and a reduced gene repertoire. The C. pseudotuberculosis genome also includes seven putative pathogenicity islands, which contain several classical virulence factors, including genes for fimbrial subunits, adhesion factors, iron uptake and secreted toxins. Additionally, all of the virulence factors in the islands have characteristics that indicate horizontal transfer.ConclusionsThese particular genome characteristics of C. pseudotuberculosis, as well as its acquired virulence factors in pathogenicity islands, provide evidence of its lifestyle and of the pathogenicity pathways used by this pathogen in the infection process. All genomes cited in this study are available in the NCBI Genbank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers CP001809 and CP001829.

The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.

The genus Campylobacter contains pathogens causing a wide range of diseases, targeting both humans and animals. Among them, the Campylobacter fetus subspecies fetus and venerealis deserve special attention, as they are the etiological agents of human bacterial gastroenteritis and bovine genital campylobacteriosis, respectively. We compare the whole genomes of both subspecies to get insights into genomic architecture, phylogenetic relationships, genome conservation and core virulence factors. Pan-genomic approach was applied to identify the core- and pan-genome for both C. fetus subspecies and members of the genus. The C. fetus subspecies conserved (76%) proteome were then analyzed for their subcellular localization and protein functions in biological processes. Furthermore, with pathogenomic strategies, unique candidate regions in the genomes and several potential core-virulence factors were identified. The potential candidate factors identified for attenuation and/or subunit vaccine development against C. fetus subspecies contain: nucleoside diphosphate kinase (Ndk), type IV secretion systems (T4SS), outer membrane proteins (OMP), substrate binding proteins CjaA and CjaC, surface array proteins, sap gene, and cytolethal distending toxin (CDT). Significantly, many of those genes were found in genomic regions with signals of horizontal gene transfer and, therefore, predicted as putative pathogenicity islands. We found CRISPR loci and dam genes in an island specific for C. fetus subsp. fetus, and T4SS and sap genes in an island specific for C. fetus subsp. venerealis. The genomic variations and potential core and unique virulence factors characterized in this study would lead to better insight into the species virulence and to more efficient use of the candidates for antibiotic, drug and vaccine development.

Pan-genome is defined as the set of orthologous and unique genes of a specific group of organisms. The pan-genome is composed by the core genome, accessory genome, and species- or strain-specific genes. The pan-genome is considered open or closed based on the alpha value of the Heap law. In an open pan-genome, the number of gene families will continuously increase with the addition of new genomes to the analysis, while in a closed pan-genome, the number of gene families will not increase considerably. The first step of a pan-genome analysis is the homogenization of genome annotation. The same software should be used to annotate genomes, such as GeneMark or RAST. Subsequently, several software are used to calculate the pan-genome such as BPGA, GET_HOMOLOGUES, PGAP, among others. This review presents all these initial steps for those who want to perform a pan-genome analysis, explaining key concepts of the area. Furthermore, we present the pan-genomic analysis of 9 bacterial species. These are the species with the highest number of genomes deposited in GenBank. We also show the influence of the identity and coverage parameters on the prediction of orthologous and paralogous genes. Finally, we cite the perspectives of several research areas where pan-genome analysis can be used to answer important issues.

Helicobacter pylori is a human gastric pathogen implicated as the major cause of peptic ulcer and second leading cause of gastric cancer (~70%) around the world. Conversely, an increased resistance to antibiotics and hindrances in the development of vaccines against H. pylori are observed. Pan-genome analyses of the global representative H. pylori isolates consisting of 39 complete genomes are presented in this paper. Phylogenetic analyses have revealed close relationships among geographically diverse strains of H. pylori. The conservation among these genomes was further analyzed by pan-genome approach; the predicted conserved gene families (1,193) constitute ~77% of the average H. pylori genome and 45% of the global gene repertoire of the species. Reverse vaccinology strategies have been adopted to identify and narrow down the potential core-immunogenic candidates. Total of 28 nonhost homolog proteins were characterized as universal therapeutic targets against H. pylori based on their functional annotation and protein-protein interaction. Finally, pathogenomics and genome plasticity analysis revealed 3 highly conserved and 2 highly variable putative pathogenicity islands in all of the H. pylori genomes been analyzed.