Identifying pathogenicity islands in bacterial pathogenomics using computational approaches

Genome sequencing and analysis of Salmonella enterica subsp. enterica serotype Enteritidis PT4 578: insights into pathogenicity and virulence

Salmonella enterica serotype Enteritidis is a generalist serotype that adapts to different hosts and transmission niches. It has significant epidemiological relevance and is among the most prevalent serotypes distributed in several countries. Salmonella Enteritidis causes self-limited gastroenteritis in humans, which can progress to systemic infection in immunocompromised individuals. The Salmonella pathogenicity mechanism is multifactorial and complex, including the presence of virulence factors that are encoded by virulence genes. Poultry products are considered significant reservoirs of many Salmonella serotypes, and Salmonella Enteritidis infections are often related to the consumption of chicken meat and eggs. This study reports the whole-genome sequence of Salmonella Enteritidis PT4 strain 578. A total of 165 genes (3.66%) of the 4506 coding sequences (CDS) predicted in its genome are virulence factors associated with cell invasion, intestinal colonization, and intracellular survival. The genome harbours twelve Salmonella pathogenicity islands (SPIs), with the SPI-1 and SPI-2 genes encoding type III secretion systems (T3SS) showing high conservation. Six prophage-related sequences were found, with regions of intact prophages corresponding to Salmon_118970_sal3 and Gifsy-2. The genome also contains two CRISPR systems. Comparative genome analysis with Salmonella Enteritidis ATCC 13076, Salmonella Typhimurium ATCC 13311, and Salmonella Typhimurium ATCC 14028 demonstrates that most unshared genes are related to metabolism, membrane, and hypothetical proteins. Finally, the phenotypic characterization evidenced differences among Salmonella Enteritidis PT4 578 and the other three serotypes regarding the expression of the red, dry, and rough (rdar) morphotype and biofilm formation. Overall, the genomic characterization and phenotypic properties expand knowledge of the mechanisms of pathogenicity in Salmonella Enteritidis PT4 578.

Mosquitocidal toxin-like islands in Bacillus thuringiensis S2160-1 revealed by complete-genome sequence and MS proteomic analysis

Here, we present the whole genome sequence of Bt S2160-1, a potential alternative to the mosquitocidal model strain, Bti. One chromosome genome and four mega-plasmids were contained in Bt S2160-1, and 13 predicted genes encoding predicted insecticidal crystal proteins were identified clustered on one plasmid pS2160-1p2 containing two pathogenic islands (PAIs) designed as PAI-1 (Cry54Ba, Cry30Ea4, Cry69Aa-like, Cry50Ba2-like, Cry4Ca1-like, Cry30Ga2, Cry71Aa-like, Cry72Aa-like, Cry70Aa-like, Cyt1Da2-like and Vpb4C1-like) and PAI-2 (Cyt1Aa-like, and Tpp80Aa1-like). The clusters appear to represent mosquitocidal toxin islands similar to pathogenicity islands. Transcription/translation of 10 of the 13 predicted genes was confirmed by whole-proteome analysis using LTQ-Orbitrap LC-MS/MS. In summary, the present study identified the existence of a mosquitocidal toxin island in Bacillus thuringiensis, and provides important genomic information for understanding the insecticidal mechanism of B. thuringiensis.

Genomic islands and their role in fitness traits of two key sepsis-causing bacterial pathogens

To survive and establish a niche for themselves, bacteria constantly evolve. Toward that, they not only insert point mutations and promote illegitimate recombinations within their genomes but also insert pieces of 'foreign' deoxyribonucleic acid, which are commonly referred to as 'genomic islands' (GEIs). The GEIs come in several forms, structures and types, often providing a fitness advantage to the harboring bacterium. In pathogenic bacteria, some GEIs may enhance virulence, thus altering disease burden, morbidity and mortality. Hence, delineating (i) the GEIs framework, (ii) their encoded functions, (iii) the triggers that help them move, (iv) the mechanisms they exploit to move among bacteria and (v) identification of their natural reservoirs will aid in superior tackling of several bacterial diseases, including sepsis. Given the vast array of comparative genomics data, in this short review, we provide an overview of the GEIs, their types and the compositions therein, especially highlighting GEIs harbored by two important pathogens, viz. Acinetobacter baumannii and Klebsiella pneumoniae, which prominently trigger sepsis in low- and middle-income countries. Our efforts help shed some light on the challenges these pathogens pose when equipped with GEIs. We hope that this review will provoke intense research into understanding GEIs, the cues that drive their mobility across bacteria and the ways and means to prevent their transfer, especially across pathogenic bacteria.

Horizontal transfer of probable chicken-pathogenicity chromosomal islands between Staphylococcus aureus and Staphylococcus agnetis

Staphylococcus agnetis is an emerging pathogen in chickens but has been most commonly isolated from sub-clinical mastitis in bovines. Previous whole-genome analyses for known virulence genes failed to identify determinants for the switch from mild ductal infections in cattle to severe infections in poultry. We now report identification of a family of 15 kbp, 17-19 gene mobile genetic elements (MGEs) specific to chicken osteomyelitis and dermatitis isolates of S. agnetis. These MGEs can be present in multiple copies per genome. The MGE has been vectored on a Staphylococcus phage that separately lysogenized two S. agnetis osteomyelitis strains. The S. agnetis genome from a broiler breeder case of ulcerative dermatitis contains 2 orthologs of this MGE, not associated with a prophage. BLASTn and phylogenetic analyses show that there are closely related intact MGEs found in genomes of S. aureus. The genome from a 1980s isolate from chickens in Ireland contains 3 copies of this MGE. More recent chicken isolates descended from that genome (Poland 2009, Oklahoma 2010, and Arkansas 2018) contain 2 to 4 related copies. Many of the genes of this MGE can be identified in disparate regions of the genomes of other chicken isolates of S. aureus. BLAST searches of the NCBI databases detect no similar MGEs outside of S. aureus and S. agnetis. These MGEs encode no proteins related to those produced by Staphylococcus aureus Pathogenicity Islands, which have been associated with the transition of S. aureus from human to chicken hosts. Other than mobilization functions, most of the genes in these new MGEs annotate as hypothetical proteins. The MGEs we describe appear to represent a new family of Chromosomal Islands (CIs) shared amongst S. agnetis and S. aureus. Further work is needed to understand the role of these CIs/MGEs in pathogenesis. Analysis of horizontal transfer of genetic elements between isolates and species of Staphylococci provides clues to evolution of host-pathogen interactions as well as revealing critical determinants for animal welfare and human diseases.

Phylotypic Profiling, Distribution of Pathogenicity Island Markers, and Antimicrobial Susceptibility of Escherichia coli Isolated from Retail Chicken Meat and Humans

Escherichia coli (E.coli) found in retail chicken meat could be causing a wide range of infections in humans and constitute a potential risk. This study aimed to evaluate 60 E. coli isolates from retail chicken meat (n = 34) and human urinary tract infections (UTIs, n = 26) for phylogenetic diversity, presence of pathogenicity island (PAI) markers, antimicrobial susceptibility phenotypes, and antimicrobial resistance genes, and to evaluate their biofilm formation capacity. In that context, confirmed E.coli isolates were subjected to phylogrouping analysis using triplex PCR, antimicrobial susceptibility testing using the Kirby–Bauer disc diffusion method; PAI distribution was investigated by using two multiplex PCRs. Most of the chicken isolates (22/34, 64.7%) were identified as commensal E. coli (A and B1), while 12 isolates (35.3%) were classified as pathogenic virulent E. coli (B2 and D). Similarly, the commensal group dominated in human isolates. Overall, 23 PAIs were detected in the chicken isolates; among them, 39.1% (9/23) were assigned to group B1, 34.8% (8/23) to group A, 4.34% (1/23) to group B2, and 21.7% (5/23) to group D. However, 25 PAIs were identified from the human isolates. PAI IV536 was the most prevalent (55.9%, 69.2%) PAI detected in both sources. In total, 37 (61.7%) isolates of the chicken and human isolates were biofilm producers. Noticeably, 100% of E. coli isolates were resistant to penicillin and rifamycin. Markedly, all E. coli isolates displayed multiple antibiotic resistance (MAR) phenotypes, and the multiple antibiotic resistance index (MARI) among E. coli isolates ranged between 0.5 and 1. Several antibiotic resistance genes (ARGs) were identified by a PCR assay; the sul2 gene was the most prevalent (38/60, 63.3%) from both sources. Interestingly, a significant positive association (r = 0.31) between biofilm production and resistance to quinolones by the qnr gene was found by the correlation analysis. These findings were suggestive of the transmission of PAI markers and antibiotic resistance genes from poultry to humans or humans to humans through the food chain. To avoid the spread of virulent and multidrug-resistant E. coli, intensive surveillance of retail chicken meat markets is required.

Comparative genomic analysis of Canadian Mycoplasma bovis strains isolated from Bison and Cattle

Mycoplasma bovis (M. bovis) in cattle causes pneumonia, arthritis, otitis media, and mastitis. In addition, multiple outbreaks have been recorded in North American bison. The genomic data on Canadian M. bovis in bison and cattle to date is limited. Whole-genome sequencing (WGS) was used to assess the degree of genome conservation across four Canadian M. bovis strains recovered from bison and cattle. Whole-genome sequences of four M. bovis isolates (Mb1, Mb160, Mb300, Mb304) and the PG45 reference genome were utilized to identify the M. bovis genomic similarity, whole-genome single nucleotide polymorphism (WGS-SNP), virulence determinants, and genomic islands. The pan-genome analysis showed that M. bovis encodes a minimum of 971 genes, while the core genome contained 637 genes. Comparative genomics revealed limited diversity in gene content between bison and cattle isolates. Whole-genome SNP analysis showed that the four M. bovis isolates differed from each other and to PG45. A total of 40 putative virulence genes associated with adhesion, colonization, and destruction of tissues were found in the bison and cattle isolates using the virulence factors database (VFDB). These putative virulence factors were equally distributed among isolates. Genomic Islands (GIs) ranging from 4 to 9 and associated with transposases, restriction-modification, ribosomal hypothetical proteins, variable surface lipoproteins, and unknowns were also identified. Overall, the genomic characterization of these isolates may provide new insights into the mechanisms of pathogenicity in M. bovis.

Bioinformatic and experimental characterization of SEN1998: a conserved gene carried by the Enterobacteriaceae-associated ROD21-like family of genomic islands

Genomic islands (GIs) are horizontally transferred elements that shape bacterial genomes and contributes to the adaptation to different environments. Some GIs encode an integrase and a recombination directionality factor (RDF), which are the molecular GI-encoded machinery that promotes the island excision from the chromosome, the first step for the spread of GIs by horizontal transfer. Although less studied, this process can also play a role in the virulence of bacterial pathogens. While the excision of GIs is thought to be similar to that observed in bacteriophages, this mechanism has been only studied in a few families of islands. Here, we aimed to gain a better understanding of the factors involved in the excision of ROD21 a pathogenicity island of the food-borne pathogen Salmonella enterica serovar Enteritidis and the most studied member of the recently described Enterobacteriaceae-associated ROD21-like family of GIs. Using bioinformatic and experimental approaches, we characterized the conserved gene SEN1998, showing that it encodes a protein with the features of an RDF that binds to the regulatory regions involved in the excision of ROD21. While deletion or overexpression of SEN1998 did not alter the expression of the integrase-encoding gene SEN1970, a slight but significant trend was observed in the excision of the island. Surprisingly, we found that the expression of both genes, SEN1998 and SEN1970, were negatively correlated to the excision of ROD21 which showed a growth phase-dependent pattern. Our findings contribute to the growing body of knowledge regarding the excision of GIs, providing insights about ROD21 and the recently described EARL family of genomic islands.

High prevalence and diversity of Bartonella in small mammals from the biodiverse Western Ghats

Bartonella species are recognized globally as emerging zoonotic pathogens. Small mammals such as rodents and shrews are implicated as major natural reservoirs for these microbial agents. Nevertheless, in several tropical countries, like India, the diversity of Bartonella in small mammals remain unexplored and limited information exists on the natural transmission cycles (reservoirs and vectors) of these bacteria. Using a multi-locus sequencing approach, we investigated the prevalence, haplotype diversity, and phylogenetic affinities of Bartonella in small mammals and their associated mites in a mixed-use landscape in the biodiverse Western Ghats in southern India. We sampled 141 individual small mammals belonging to eight species. Bartonella was detected in five of the eight species, including three previously unknown hosts. We observed high interspecies variability of Bartonella prevalence in the host community. However, the overall prevalence (52.5%) and haplotype diversity (0.9) was high for the individuals tested. Of the seven lineages of Bartonella identified in our samples, five lineages were phylogenetically related to putative zoonotic species–B. tribocorum, B. queenslandensis, and B. elizabethae. Haplotypes identified from mites were identical to those identified from their host species. This indicates that these Bartonella species may be zoonotic, but further work is necessary to confirm whether these are pathogenic and pose a threat to humans. Taken together, these results emphasize the presence of hitherto unexplored diversity of Bartonella in wild and synanthropic small mammals in mixed-use landscapes. The study also highlights the necessity to assess the risk of spillover to humans and other incidental hosts.

Zoonotic bacterial infections cause both economic and health burdens to humans, especially in developing countries. Bartonella is a diverse group with several species that are infectious to humans. There is limited knowledge of Bartonella diversity and subsequent risk for spillover in several tropical countries, including India. This study, set in a biodiversity hotspot with high human density, reveals a high prevalence and diversity of Bartonella in the most common, and synanthropic small mammals. Several lineages identified are phylogenetically related to zoonotic species known to cause infections in humans. We suggest that there is unexplored diversity of Bartonella in small mammals that reside in human-modified landscapes in India, demonstrating an urgent need for further investigation. By identifying the natural reservoirs of pathogens, their ecology, and their relationship and proximity to humans, we will be able to proactively survey for these under-detected bacterial infections and minimize the burden.

Microbial genomic island discovery, visualization and analysis

Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.

Comparative genome characterization of the periodontal pathogen Tannerella forsythia

BACKGROUND

Tannerella forsythia is a bacterial pathogen implicated in periodontal disease. Numerous virulence-associated T. forsythia genes have been described, however, it is necessary to expand the knowledge on T. forsythia's genome structure and genetic repertoire to further elucidate its role within pathogenesis. Tannerella sp. BU063, a putative periodontal health-associated sister taxon and closest known relative to T. forsythia is available for comparative analyses. In the past, strain confusion involving the T. forsythia reference type strain ATCC 43037 led to discrepancies between results obtained from in silico analyses and wet-lab experimentation.

RESULTS

We generated a substantially improved genome assembly of T. forsythia ATCC 43037 covering 99% of the genome in three sequences. Using annotated genomes of ten Tannerella strains we established a soft core genome encompassing 2108 genes, based on orthologs present in > = 80% of the strains analysed. We used a set of known and hypothetical virulence factors for comparisons in pathogenic strains and the putative periodontal health-associated isolate Tannerella sp. BU063 to identify candidate genes promoting T. forsythia's pathogenesis. Searching for pathogenicity islands we detected 38 candidate regions in the T. forsythia genome. Only four of these regions corresponded to previously described pathogenicity islands. While the general protein O-glycosylation gene cluster of T. forsythia ATCC 43037 has been described previously, genes required for the initiation of glycan synthesis are yet to be discovered. We found six putative glycosylation loci which were only partially conserved in other bacteria. Lastly, we performed a comparative analysis of translational bias in T. forsythia and Tannerella sp. BU063 and detected highly biased genes.

CONCLUSIONS

We provide resources and important information on the genomes of Tannerella strains. Comparative analyses enabled us to assess the suitability of T. forsythia virulence factors as therapeutic targets and to suggest novel putative virulence factors. Further, we report on gene loci that should be addressed in the context of elucidating T. forsythia's protein O-glycosylation pathway. In summary, our work paves the way for further molecular dissection of T. forsythia biology in general and virulence of this species in particular.

Horizontally Acquired Homologs of Xenogeneic Silencers: Modulators of Gene Expression Encoded by Plasmids, Phages and Genomic Islands

Acquisition of mobile elements by horizontal gene transfer can play a major role in bacterial adaptation and genome evolution by providing traits that contribute to bacterial fitness. However, gaining foreign DNA can also impose significant fitness costs to the host bacteria and can even produce detrimental effects. The efficiency of horizontal acquisition of DNA is thought to be improved by the activity of xenogeneic silencers. These molecules are a functionally related group of proteins that possess affinity for the acquired DNA. Binding of xenogeneic silencers suppresses the otherwise uncontrolled expression of genes from the newly acquired nucleic acid, facilitating their integration to the bacterial regulatory networks. Even when the genes encoding for xenogeneic silencers are part of the core genome, homologs encoded by horizontally acquired elements have also been identified and studied. In this article, we discuss the current knowledge about horizontally acquired xenogeneic silencer homologs, focusing on those encoded by genomic islands, highlighting their distribution and the major traits that allow these proteins to become part of the host regulatory networks.

Improved genomic island predictions with IslandPath-DIMOB

Motivation

Genomic islands (GIs) are clusters of genes of probable horizontal origin that play a major role in bacterial and archaeal genome evolution and microbial adaptability. They are of high medical and industrial interest, due to their enrichment in virulence factors, some antimicrobial resistance genes and adaptive metabolic pathways. The development of more sensitive but precise prediction tools, using either sequence composition-based methods or comparative genomics, is needed as large-scale analyses of microbial genomes increase.

Results

IslandPath-DIMOB, a leading GI prediction tool in the IslandViewer webserver, has now been significantly improved by modifying both the decision algorithm to determine sequence composition biases, and the underlying database of HMM profiles for associated mobility genes. The accuracy of IslandPath-DIMOB and other major software has been assessed using a reference GI dataset predicted by comparative genomics, plus a manually curated dataset from literature review. Compared to the previous version (v0.2.0), this IslandPath-DIMOB v1.0.0 achieves 11.7% and 5.3% increase in recall and precision, respectively. IslandPath-DIMOB has the highest Matthews correlation coefficient among individual prediction methods tested, combining one of the highest recall measures (46.9%) at high precision (87.4%). The only method with higher recall had notably lower precision (55.1%). This new IslandPath-DIMOB v1.0.0 will facilitate more accurate studies of GIs, including their key roles in microbial adaptability of medical, environmental and industrial interest.

Availability and implementation

IslandPath-DIMOB v1.0.0 is freely available through the IslandViewer webserver {{http://www.pathogenomics.sfu.ca/islandviewer/}} and as standalone software {{https://github.com/brinkmanlab/islandpath/}} under the GNU-GPLv3.

Supplementary information

Supplementary data are available at Bioinformatics online.

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

Genomic Islands in the Full-Genome Sequence of an NAD-Hemin-Independent Avibacterium paragallinarum Strain Isolated from Peru

Here, we report the full-genome sequence of an NAD-hemin-independent Avibacterium paragallinarum serovar C-2 strain, FARPER-174, isolated from layer hens in Peru. This genome contained 12 potential genomic islands that include ribosomal protein-coding genes, a nadR gene, hemocin-coding genes, sequences of fagos, an rtx operon, and drug resistance genes.

Coagulase-Negative Staphylococci Pathogenomics

Coagulase-negative Staphylococci (CoNS) are skin commensal bacteria. Besides their role in maintaining homeostasis, CoNS have emerged as major pathogens in nosocomial settings. Several studies have investigated the molecular basis for this emergence and identified multiple putative virulence factors with regards to Staphylococcus aureus pathogenicity. In the last decade, numerous CoNS whole-genome sequences have been released, leading to the identification of numerous putative virulence factors. Koch’s postulates and the molecular rendition of these postulates, established by Stanley Falkow in 1988, do not explain the microbial pathogenicity of CoNS. However, whole-genome sequence data has shed new light on CoNS pathogenicity. In this review, we analyzed the contribution of genomics in defining CoNS virulence, focusing on the most frequent and pathogenic CoNS species: S. epidermidis, S. haemolyticus, S. saprophyticus, S. capitis, and S. lugdunensis.

Comparative Genomic Analyses Reveal Core-Genome-Wide Genes Under Positive Selection and Major Regulatory Hubs in Outlier Strains of Pseudomonas aeruginosa

Genomic information for outlier strains of Pseudomonas aeruginosa is exiguous when compared with classical strains. We sequenced and constructed the complete genome of an environmental strain CR1 of P. aeruginosa and performed the comparative genomic analysis. It clustered with the outlier group, hence we scaled up the analyses to understand the differences in environmental and clinical outlier strains. We identified eight new regions of genomic plasticity and a plasmid pCR1 with a VirB/D4 complex followed by trimeric auto-transporter that can induce virulence phenotype in the genome of strain CR1. Virulence genotype analysis revealed that strain CR1 lacked hemolytic phospholipase C and D, three genes for LPS biosynthesis and had reduced antibiotic resistance genes when compared with clinical strains. Genes belonging to proteases, bacterial exporters and DNA stabilization were found to be under strong positive selection, thus facilitating pathogenicity and survival of the outliers. The outliers had the complete operon for the production of vibrioferrin, a siderophore present in plant growth promoting bacteria. The competence to acquire multidrug resistance and new virulence factors makes these strains a potential threat. However, we identified major regulatory hubs that can be used as drug targets against both the classical and outlier groups.

Pathogenomics of Virulence Traits of Plesiomonas shigelloides That Were Deemed Inconclusive by Traditional Experimental Approaches

One of the major challenges of modern medicine includes the failure of conventional protocols to characterize the pathogenicity of emerging pathogens. This is particularly apparent in the case of Plesiomonas shigelloides. Although a number of infections have been linked to this microorganism, experimental evidence of its virulence factors (VFs), obtained by traditional approaches, is somewhat inconclusive. Hence, it remains unclear whether P. shigelloides is a true or opportunistic one. In the current study, four publicly available whole-genome sequences of P. shigelloides (GN7, NCTC10360, 302-73, and LS1) were profiled using bioinformatics platforms to determine the putative candidate VFs to characterize the bacterial pathogenicity. Overall, 134 unique open reading frames (ORFs) were identified that were homologous or orthologous to virulence genes identified in other pathogens. Of these, 52.24% (70/134) were jointly shared by the strains. The numbers of strain-specific virulence traits were 4 in LS1; 7 in NCTC10360; 10 in 302-73; and 15 in GN7. The pathogenicity islands (PAIs) common to all the strains accounted for 24.07% ORFs. The numbers of PAIs exclusive to each strain were 8 in 302-73; 11 in NCTC10360; 14 in GN7; and 18 in LS1. A PAI encoding Vibrio cholerae ToxR-activated gene d protein was specific to 302-73, GN7, and NCTC10360 strains. Out of 33 antibiotic multi-resistance genes identified, 16 (48.48%) genes were intrinsic to all strains. Further, 17 (22.08%) of 77 antibiotic resistance islands were found in all the strains. Out of 23 identified distinct insertion sequences, 13 were only harbored by strain LS1. The number of intact prophages identified in the strains was 1 in GN7; 2 in 302-73; and 2 in NCTC10360. Further, 1 CRISPR element was identified in LS1; 2 in NCTC10360; and 8 in 302-73. Fifteen (78.95%) of 19 secretion systems and secretion effector variants were identified in all the strains. In conclusion, certain P. shigelloides strains might possess VFs associated with gastroenteritis and extraintestinal infections. However, the role of host factors in the onset of infections should not be undermined.

Comparative Analysis of Genomic Island Prediction Tools

Tools for genomic island prediction use strategies for genomic comparison analysis and sequence composition analysis. The goal of comparative analysis is to identify unique regions in the genomes of related organisms, whereas sequence composition analysis evaluates and relates the composition of specific regions with other regions in the genome. The goal of this study was to qualitatively and quantitatively evaluate extant genomic island predictors. We chose tools reported to produce significant results using sequence composition prediction, comparative genomics, and hybrid genomics methods. To maintain diversity, the tools were applied to eight complete genomes of organisms with distinct characteristics and belonging to different families. Escherichia coli CFT073 was used as a control and considered as the gold standard because its islands were previously curated in vitro. The results of predictions with the gold standard were manually curated, and the content and characteristics of each predicted island were analyzed. For other organisms, we created GenBank (GBK) files using Artemis software for each predicted island. We copied only the amino acid sequences from the coding sequence and constructed a multi-FASTA file for each predictor. We used BLASTp to compare all results and generate hits to evaluate similarities and differences among the predictions. Comparison of the results with the gold standard revealed that GIPSy produced the best results, covering ~91% of the composition and regions of the islands, followed by Alien Hunter (81%), IslandViewer (47.8%), Predict Bias (31%), GI Hunter (17%), and Zisland Explorer (16%). The tools with the best results in the analyzes of the set of organisms were the same ones that presented better performance in the tests with the gold standard.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

A plasmid-encoded mobile genetic element from Pseudomonas aeruginosa that confers heavy metal resistance and virulence

Mobile plasmid-encoded elements are DNA segments that are transferred for horizontal gene transfer and that confer adaptive proprieties, as well as virulence and antibiotic and heavy metal resistance to bacteria. The conjugative plasmid pUM505, isolated from a clinical strain of Pseudomonas aeruginosa, possesses a putative 31.292 kb mobile element (denominated Mpe: Mobile plasmid- encoded element) that, in addition to possessing chr genes that confer chromate resistance to Pseudomonas, contains two putative mer operons that could confer mercury resistance. Moreover, the Mpe contains genes related previously with the virulence of both P. aeruginosa and Escherichia coli strains. In this work, we determined that Mpe from pUM505 was able to independently move to another DNA molecule, conferring chromate and mercury resistance to P. aeruginosa PAO1 and mercury resistance to E. coli JM101, suggesting that its transference might be beneficial to bacteria under certain environmental conditions. Additionally, the transference of Mpe increased the virulence of P. aeruginosa PAO1 against the nematode Caenorhabditis elegans, suggesting its contribution to the pathogenicity of P. aeruginosa. In this work, we describe a new mobile plasmid-encoded element that possesses the potential to be transferred by horizontal gene transference, which could provide bacteria with a wide variety of adaptive traits such as heavy metal resistance and virulence, which can be selective factors for the distribution and prevalence of this plasmid in diverse environments, including hospitals and heavy metal contaminated soils.

Comparative and phylogenetic analysis of a novel family of Enterobacteriaceae-associated genomic islands that share a conserved excision/integration module

Genomic Islands (GIs) are DNA regions acquired through horizontal gene transfer that encode advantageous traits for bacteria. Many GIs harbor genes that encode the molecular machinery required for their excision from the bacterial chromosome. Notably, the excision/integration dynamics of GIs may modulate the virulence of some pathogens. Here, we report a novel family of GIs found in plant and animal Enterobacteriaceae pathogens that share genes with those found in ROD21, a pathogenicity island whose excision is involved in the virulence of Salmonella enterica serovar Enteritidis. In these GIs we identified a conserved set of genes that includes an excision/integration module, suggesting that they are excisable. Indeed, we found that GIs within carbapenem-resistant Klebsiella pneumoniae ST258 KP35 and enteropathogenic Escherichia coli O127:H6 E2348/69 are excised from the bacterial genome. In addition to putative virulence factors, these GIs encode conjugative transfer-related proteins and short and full-length homologues of the global transcriptional regulator H-NS. Phylogenetic analyses suggest that the identified GIs likely originated in phytopathogenic bacteria. Taken together, our findings indicate that these GIs are excisable and may play a role in bacterial interactions with their hosts.

Distribution of pathogenicity island markers and virulence factors in new phylogenetic groups of uropathogenic Escherichia coli isolates

The present study was aimed at investigating the relationship between the new Clermont's phylogenetic groups, virulence factors, and pathogenicity island markers (PAIs) among uropathogenic Escherichia coli (UPEC) in Iran. This cross-sectional study was carried out on 140 UPEC isolates collected from patients with urinary tract infections in Bushehr, Iran. All isolates were subjected to phylogenetic typing using a new quadruplex-PCR method. The presence of PAI markers and virulence factors in UPEC strains was evaluated by multiplex PCR. The most predominant virulence gene was fimH (85%), followed by iucC (61.4%), papC (38.6%), hlyA (22.1%), cnf-1 (18.6%), afa (10.7%), papG and neuC (each 9.3%), ibeA (3.6%), and sfa/foc (0.7%). The most common phylogenetic group was related to B2 (39.3%), and the least common to A (0.7%). The most prevalent PAI marker was PAI IV536 (77.14%), while markers for PAI III536 (13.57%), PAI IIJ96 (12.86%), and PAI II536 (12.14%) were the least frequent among the UPEC strains. Meanwhile, the PAI IJ96 marker was not detected. There was a significant association between the phylogenetic group B2 and all the studied virulence genes and PAI markers. To our knowledge, this is the first study to compare the relationship between new phylogenetic groups, virulence genes and PAI markers in UPEC strains in Iran. The phylogenetic group B2 was predominantly represented among the studied virulence genes and PAI markers, indicating the preference of particular strains to carry virulence genes.

Genomic features, phylogenetic relationships, and comparative genomics of Elizabethkingia anophelis strain EM361-97 isolated in Taiwan

Elizabethkingia anophelis has become an emerging infection in humans. Recent research has shown that previous reports of E. meningoseptica infections might in fact be caused by E. anophelis. We aimed to investigate the genomic features, phylogenetic relationships, and comparative genomics of this emerging pathogen. Elizabethkingia anophelis strain EM361-97 was isolated from the blood of a cancer patient in Taiwan. The total length of the draft genome was 4,084,052 bp. The whole-genome analysis identified the presence of a number of antibiotic resistance genes, which corresponded with the antibiotic susceptibility phenotype of this strain. Based on the average nucleotide identity, the phylogenetic analysis revealed that E. anophelis EM361-97 was a sister group to E. anophelis FMS-007, which was isolated from a patient with T-cell non-Hodgkin's lymphoma in China. Knowledge of the genomic characteristics and comparative genomics of E. anophelis will provide researchers and clinicians with important information to understand this emerging microorganism.

Whole-Genome Sequencing of Seven Strains of Staphylococcus lugdunensis Allows Identification of Mobile Genetic Elements

Coagulase negative staphylococci are normal inhabitant of the human skin flora that account for an increasing number of infections, particularly hospital-acquired infections. Staphylococcus lugdunensis has emerged as a most virulent species causing various infections with clinical characteristics close to what clinicians usually observe with Staphylococcus aureus and both bacteria share more than 70% of their genome. Virulence of S. aureus relies on a large repertoire of virulence factors, many of which are encoded on mobile genetic elements. S. lugdunensis also bears various putative virulence genes but only one complete genome with extensive analysis has been published with one prophage sequence (φSL2) and a unique plasmid was previously described. In this study, we performed de novo sequencing, whole genome assembly and annotation of seven strains of S. lugdunensis from VISLISI clinical trial. We searched for the presence of virulence genes and mobile genetics elements using bioinformatics tools. We identified four new prophages, named φSL2 to φSL4, belonging to the Siphoviridae class and five plasmids, named pVISLISI_1 to pVISLISI_5. Three plasmids are homologous to known plasmids that include, amongst others, one S. aureus plasmid. The two other plasmids were not described previously. This study provides a new context for the study of S. lugdunensis virulence suggesting the occurrence of several genetic recombination’ with other staphylococci.

Culture-independent genomics of a novel chlamydial pathogen of fish provides new insight into host-specific adaptations utilized by these intracellular bacteria

Several Chlamydiales families are associated with epitheliocystis, a common condition of the fish gill epithelium. These families share common ancestors with the Chlamydiaceae and environmental Chlamydiae. Due to the lack of culture systems, little is known about the biology of these chlamydial fish pathogens. We investigated epitheliocystis in cultured Orange-spotted grouper (Epinephelus coioides) from North Queensland, Australia. Basophilic inclusions were present in the gills of 22/31 fish and the presence of the chlamydial pathogen in the cysts was confirmed by in situ hybridization. Giant grouper (Epinephelus lanceolatus) cultured in the same systems were epitheliocystis free. 16S rRNA gene sequencing revealed a novel member of the Candidatus Parilichlamydiaceae: Ca. Similichlamydia epinephelii. Using metagenomic approaches, we obtained an estimated 68% of the chlamydial genome, revealing that this novel chlamydial pathogen shares a number of key pathogenic hallmarks with the Chlamydiaceae, including an intact Type III Secretion system and several chlamydial virulence factors. This provides additional evidence that these pathogenic mechanisms were acquired early in the evolution of this unique bacterial phylum. The identification and genomic characterization of Ca. S. epinephelii provides new opportunities to study the biology of distantly-related chlamydial pathogens while shining a new light on the evolution of pathogenicity of the Chlamydiaceae.

The contribution of genome mining strategies to the understanding of active principles of PGPR strains

Pathogenic microorganisms and insects affecting plant health are a major and chronic threat to food production and the ecosystem worldwide. As agricultural production has intensified over the years, the use of agrochemicals has in turn increased. However, this extensive usage has had several detrimental effects, with a pervasive environmental impact and the emergence of pathogen resistance. In addition, there is an increasing tendency among consumers to give preference to pesticide-free food products. Biological control, through the employment of plant growth-promoting rhizobacteria (PGPR), is therefore considered a possible route to the reduction, even the elimination, of the use of agrochemicals. PGPR exert their beneficial influence by a multitude of mechanisms, often involving antibiotics and proteins, to defend the host plant against pathogens. To date, these key metabolites have been uncovered only by systematic investigation or by serendipity; their discovery has nevertheless been propelled by the genomic revolution of recent years, as increasing numbers of genomic studies have been integrated into this field, facilitating a holistic view of this topic and the rapid identification of ecologically important metabolites. This review surveys the highlights and advances of genome-driven compound and protein discovery in the field of bacterial PGPR strains, and aims to advocate for the benefits of this strategy.

Identification of Novel Genomic Islands in Liverpool Epidemic Strain of Pseudomonas aeruginosa Using Segmentation and Clustering

Pseudomonas aeruginosa is an opportunistic pathogen implicated in a myriad of infections and a leading pathogen responsible for mortality in patients with cystic fibrosis (CF). Horizontal transfers of genes among the microorganisms living within CF patients have led to highly virulent and multi-drug resistant strains such as the Liverpool epidemic strain of P. aeruginosa, namely the LESB58 strain that has the propensity to acquire virulence and antibiotic resistance genes. Often these genes are acquired in large clusters, referred to as "genomic islands (GIs)." To decipher GIs and understand their contributions to the evolution of virulence and antibiotic resistance in P. aeruginosa LESB58, we utilized a recursive segmentation and clustering procedure, presented here as a genome-mining tool, "GEMINI." GEMINI was validated on experimentally verified islands in the LESB58 strain before examining its potential to decipher novel islands. Of the 6062 genes in P. aeruginosa LESB58, 596 genes were identified to be resident on 20 GIs of which 12 have not been previously reported. Comparative genomics provided evidence in support of our novel predictions. Furthermore, GEMINI unraveled the mosaic structure of islands that are composed of segments of likely different evolutionary origins, and demonstrated its ability to identify potential strain biomarkers. These newly found islands likely have contributed to the hyper-virulence and multidrug resistance of the Liverpool epidemic strain of P. aeruginosa.

A hypervariable genomic island identified in clinical and environmental Mycobacterium avium subsp. hominissuis isolates from Germany

Mycobacterium avium subsp. hominissuis (MAH) is an opportunistic human pathogen widespread in the environment. Genomic islands (GI)s represent a part of the accessory genome of bacteria and influence virulence, drug-resistance or fitness and trigger bacterial evolution. We previously identified a novel GI in four MAH genomes. Here, we further explored this GI in a larger collection of MAH isolates from Germany (n=41), including 20 clinical and 21 environmental isolates. Based on comparative whole genome analysis, we detected this GI in 39/41 (95.1%) isolates. Although all these GIs integrated in the same insertion hotspot, there is high variability in the genetic structure of this GI: eight different types of GI have been identified, designated A-H (sized 6.2-73.3kb). These GIs were arranged as single GI (23/41, 56.1%), combination of two different GIs (14/41, 34.1%) or combination of three different GIs (2/41, 4.9%) in the insertion hotspot. Moreover, two GI types shared more than 80% sequence identity with sequences of M. canettii, responsible for Tuberculosis. A total of 253 different genes were identified in all GIs, among which the previously documented virulence-related genes mmpL10 and mce. The diversity of the GI and the sequence similarity with other mycobacteria suggests cross-species transfer, involving also highly pathogenic species. Shuffling of potential virulence genes such as mmpL10 via this GI may create new pathogens that can cause future outbreaks.

Computational methods for predicting genomic islands in microbial genomes

Clusters of genes acquired by lateral gene transfer in microbial genomes, are broadly referred to as genomic islands (GIs). GIs often carry genes important for genome evolution and adaptation to niches, such as genes involved in pathogenesis and antibiotic resistance. Therefore, GI prediction has gradually become an important part of microbial genome analysis. Despite inherent difficulties in identifying GIs, many computational methods have been developed and show good performance. In this mini-review, we first summarize the general challenges in predicting GIs. Then we group existing GI detection methods by their input, briefly describe representative methods in each group, and discuss their advantages as well as limitations. Finally, we look into the potential improvements for better GI prediction.

(Meta)genomic insights into the pathogenome of Cellulosimicrobium cellulans

Despite having serious clinical manifestations, Cellulosimicrobium cellulans remain under-reported with only three genome sequences available at the time of writing. Genome sequences of C. cellulans LMG16121, C. cellulans J36 and Cellulosimicrobium sp. strain MM were used to determine distribution of pathogenicity islands (PAIs) across C. cellulans, which revealed 49 potential marker genes with known association to human infections, e.g. Fic and VbhA toxin-antitoxin system. Oligonucleotide composition-based analysis of orthologous proteins (n = 791) across three genomes revealed significant negative correlation (P < 0.05) between frequency of optimal codons (F_opt) and gene G+C content, highlighting the G+C-biased gene conversion (gBGC) effect across Cellulosimicrobium strains. Bayesian molecular-clock analysis performed on three virulent PAI proteins (Fic; D-alanyl-D-alanine-carboxypeptidase; transposase) dated the divergence event at 300 million years ago from the most common recent ancestor. Synteny-based annotation of hypothetical proteins highlighted gene transfers from non-pathogenic bacteria as a key factor in the evolution of PAIs. Additonally, deciphering the metagenomic islands using strain MM’s genome with environmental data from the site of isolation (hot-spring biofilm) revealed (an)aerobic respiration as population segregation factor across the in situ cohorts. Using reference genomes and metagenomic data, our results highlight the emergence and evolution of PAIs in the genus Cellulosimicrobium.

The Complete Genome Sequence of the Murine Pathobiont Helicobacter typhlonius

Background: Immuno-compromised mice infected with Helicobacter typhlonius are used to model microbially inducted inflammatory bowel disease (IBD). The specific mechanism through which H. typhlonius induces and promotes IBD is not fully understood. Access to the genome sequence is essential to examine emergent properties of this organism, such as its pathogenicity. To this end, we present the complete genome sequence of H. typhlonius MIT 97-6810, obtained through single-molecule real-time sequencing.

Results: The genome was assembled into a single circularized contig measuring 1.92 Mbp with an average GC content of 38.8%. In total 2,117 protein-encoding genes and 43 RNA genes were identified. Numerous pathogenic features were found, including a putative pathogenicity island (PAIs) containing components of type IV secretion system, virulence-associated proteins and cag PAI protein. We compared the genome of H. typhlonius to those of the murine pathobiont H. hepaticus and human pathobiont H. pylori. H. typhlonius resembles H. hepaticus most with 1,594 (75.3%) of its genes being orthologous to genes in H. hepaticus. Determination of the global methylation state revealed eight distinct recognition motifs for adenine and cytosine methylation. H. typhlonius shares four of its recognition motifs with H. pylori.

Conclusion: The complete genome sequence of H. typhlonius MIT 97-6810 enabled us to identify many pathogenic features suggesting that H. typhlonius can act as a pathogen. Follow-up studies are necessary to evaluate the true nature of its pathogenic capabilities. We found many methylated sites and a plethora of restriction-modification systems. The genome, together with the methylome, will provide an essential resource for future studies investigating gene regulation, host interaction and pathogenicity of H. typhlonius. In turn, this work can contribute to unraveling the role of Helicobacter in enteric disease.

A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm

Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP—Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.

Distribution of pathogenicity island (PAI) markers and phylogenetic groups in diarrheagenic and commensal Escherichia coli from young children

AIM

This case-control study investigated the various PAI markers, phylogenetic groups and antimicrobial susceptibility among DEC and commensal E. coli isolates.

BACKGROUND

Diarrheagenic Escherichia coli (DEC) is an emerging agent among pathogens that cause diarrheal diseases and represents a major public health problem in developing countries. The major difference in virulence among DEC pathotype and commensals may be related to the presence of specific genomic segments, termed pathogenicity islands (PAIs).

PATIENTS AND METHODS

A total of 600 stool specimens from children (450 with and 150 without diarrhea) were collected and various PAI markers, phylogenetic groups and antimicrobial resistance profile among DEC and commensal E. coli isolates were detected.

RESULTS

One hundred sixty eight (90.3%) isolates were resistant to one or more antimicrobial agents. PAI markers were detected in a substantial percentage of commensal (90%) and DEC isolates (99.3%) (P> 0.05). The most prevalent PAI marker among DEC and commensal isolates was HPI (91.9% DEC vs. 68% commensal). We found a high number of PAI markers such as SHI-2, She and LEE that were significantly associated with DEC. Several different combinations of PAIs were found among DEC isolates. Comparison of PAIs among DEC and commensal isolates showed that many DEC isolates (94.8%) carried two or more PAI markers, while 76% of commensals had only one PAI marker (P<0.05). According to the phylogenetic classification, group B2 was the most commonly found in the DEC isolates. Furthermore, our results showed that group B2 can be present in commensal isolates (18%).

CONCLUSION

These results indicate that PAI markers are widespread among commensal and DEC isolates and these commensal isolates may be reservoirs for transmission of these markers.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.

Distribution of pathogenicity island markers in commensal and uropathogenic Escherichia coli isolates

Uropathogenic Escherichia coli (UPEC) isolates contain large genomic segments, termed pathogenicity islands (PAIs), that contribute to their virulence. A total of 150 UPEC and 50 commensal E. coli isolates from outpatients were investigated for antimicrobial susceptibility and the presence of eight PAI markers. One hundred ninety (95 %) isolates were resistant to one or more antimicrobial agents. The most frequent resistance found against amoxicillin (68 %), amoxicillin/clavulanic acid (55 %), aztreonam (50 %), trimethoprim/sulfamethoxazole (46 %) and tetracycline (43.5 %). Antimicrobial resistance among UPEC isolates was higher than that of commensals. PAI markers were detected in substantial percentage of commensal (88 %) and UPEC isolates (98.6 %) (P > 0.05). The most prevalent PAI marker among UPEC and commensal isolates was PAI IV536 (98.7 % UPEC vs. 84 % commensal). We found a high number of PAI markers such as PAI ICFT073, PAI IICFT073, PAI I536, PAI II536, PAI III536 and PAI IIJ96 significantly associated with UPEC. PAI III536 (21.3 %) and PAI IIJ96 (8 %) were detected only in the uropathogenic isolates. Several different combinations of PAIs were found among UPEC isolates. Comparison of PAIs among UPEC and commensal isolates showed that many UPEC isolates (79.3 %) carried two or more PAI markers, while 6 % of commensals had two PAI markers (P < 0.05). The most frequent combinations of PAI markers in UPEC isolates were PAI IV536 + PAI IICFT073 (18 %) and PAI IV536 + PAI ICFT073 + PAI IICFT073 (18 %). These results indicate that PAI markers are widespread among commensal and UPEC isolates and these commensal isolates may be reservoirs for transmission of these markers.

Insights into the Evolutionary Relationships of LytA Autolysin and Ply Pneumolysin-Like Genes in Streptococcus pneumoniae and Related Streptococci

Streptococcus pneumoniae (pneumococcus) is a major human pathogen. The main pneumococcal autolysin LytA and the pneumolysin Ply are two of the bacterium's most important virulence factors. The lytA- and ply-related genes are also found in other streptococci of the Mitis group (SMG). The precise characteristics of the lytA-related-but not the ply-related-genes of SMG and their prophages have been previously described. A search of the more than 400 SMG genomic sequences available in public databases (ca. 300 for S. pneumoniae), showed Streptococcus pseudopneumoniae IS7493 to harbor four ply-related genes, two of which (plyA and plyB) have 98% identical nucleotides. The plyA homolog of S. pseudopneumoniae is conserved in all S. pneumoniae strains, and seems to be included in a pathogenicity island together with the lytA gene. However, only nonencapsulated S. pneumoniae strains possess a plyB gene, which is part of an integrative and conjugative element. Notably, the existence of a bacterial lytA-related gene in a genome is linked to the presence of plyA and vice versa. The present analysis also shows there are eight main types of plyA-lytA genomic islands. A possible stepwise scenario for the evolution of the plyA-lytA island in S. pneumoniae is proposed.

Individuality, phenotypic differentiation, dormancy and 'persistence' in culturable bacterial systems: commonalities shared by environmental, laboratory, and clinical microbiology

For bacteria, replication mainly involves growth by binary fission. However, in a very great many natural environments there are examples of phenotypically dormant, non-growing cells that do not replicate immediately and that are phenotypically 'nonculturable' on media that normally admit their growth. They thereby evade detection by conventional culture-based methods. Such dormant cells may also be observed in laboratory cultures and in clinical microbiology. They are usually more tolerant to stresses such as antibiotics, and in clinical microbiology they are typically referred to as 'persisters'. Bacterial cultures necessarily share a great deal of relatedness, and inclusive fitness theory implies that there are conceptual evolutionary advantages in trading a variation in growth rate against its mean, equivalent to hedging one's bets. There is much evidence that bacteria exploit this strategy widely. We here bring together data that show the commonality of these phenomena across environmental, laboratory and clinical microbiology. Considerable evidence, using methods similar to those common in environmental microbiology, now suggests that many supposedly non-communicable, chronic and inflammatory diseases are exacerbated (if not indeed largely caused) by the presence of dormant or persistent bacteria (the ability of whose components to cause inflammation is well known). This dormancy (and resuscitation therefrom) often reflects the extent of the availability of free iron. Together, these phenomena can provide a ready explanation for the continuing inflammation common to such chronic diseases and its correlation with iron dysregulation. This implies that measures designed to assess and to inhibit or remove such organisms (or their access to iron) might be of much therapeutic benefit.

Individuality, phenotypic differentiation, dormancy and 'persistence' in culturable bacterial systems: commonalities shared by environmental, laboratory, and clinical microbiology

For bacteria, replication mainly involves growth by binary fission. However, in a very great many natural environments there are examples of phenotypically dormant, non-growing cells that do not replicate immediately and that are phenotypically 'nonculturable' on media that normally admit their growth. They thereby evade detection by conventional culture-based methods. Such dormant cells may also be observed in laboratory cultures and in clinical microbiology. They are usually more tolerant to stresses such as antibiotics, and in clinical microbiology they are typically referred to as 'persisters'. Bacterial cultures necessarily share a great deal of relatedness, and inclusive fitness theory implies that there are conceptual evolutionary advantages in trading a variation in growth rate against its mean, equivalent to hedging one's bets. There is much evidence that bacteria exploit this strategy widely. We here bring together data that show the commonality of these phenomena across environmental, laboratory and clinical microbiology. Considerable evidence, using methods similar to those common in environmental microbiology, now suggests that many supposedly non-communicable, chronic and inflammatory diseases are exacerbated (if not indeed largely caused) by the presence of dormant or persistent bacteria (the ability of whose components to cause inflammation is well known). This dormancy (and resuscitation therefrom) often reflects the extent of the availability of free iron. Together, these phenomena can provide a ready explanation for the continuing inflammation common to such chronic diseases and its correlation with iron dysregulation. This implies that measures designed to assess and to inhibit or remove such organisms (or their access to iron) might be of much therapeutic benefit.

Validation and Application of a Real-time PCR Protocol for the Specific Detection and Quantification of Clavibacter michiganensis subsp. sepedonicus in Potato

Clavibacter michiganensis subsp. sepedonicus (Cms) multiplies very rapidly, passing through the vascular strands and into the stems and petioles of a diseased potato. Therefore, the rapid and specific detection of this pathogen is highly important for the effective control of the pathogen. Although several PCR assays have been developed for detection, they cannot afford specific detection of Cms. Therefore, in this study, a computational genome analysis was performed to compare the sequenced genomes of the C. michiganensis subspecies and to identify an appropriate gene for the development of a subspecies-specific PCR primer set (Cms89F/R). The specificity of the primer set based on the putative phage-related protein was evaluated using genomic DNA from seven isolates of Cms and 27 other reference strains. The Cms89F/R primer set was more specific and sensitive than the existing assays in detecting Cms in in vitro using Cms cells and its genomic DNA. This assay was also able to detect at least 1.47×10(2) copies/μl of cloned-amplified target DNA, 5 fg of DNA using genomic DNA or 10(-6) dilution point of 0.12 at OD600 units of cells per reaction using a calibrated cell suspension.

PAIDB v2.0: exploration and analysis of pathogenicity and resistance islands

Pathogenicity is a complex multifactorial process confounded by the concerted activity of genetic regions associated with virulence and/or resistance determinants. Pathogenicity islands (PAIs) and resistance islands (REIs) are key to the evolution of pathogens and appear to play complimentary roles in the process of bacterial infection. While PAIs promote disease development, REIs give a fitness advantage to the host against multiple antimicrobial agents. The Pathogenicity Island Database (PAIDB, http://www.paidb.re.kr) has been the only database dedicated to providing comprehensive information on all reported PAIs and candidate PAIs in prokaryotic genomes. In this study, we present PAIDB v2.0, whose functionality is extended to incorporate REIs. PAIDB v2.0 contains 223 types of PAIs with 1331 accessions, and 88 types of REIs with 108 accessions. With an improved detection scheme, 2673 prokaryotic genomes were analyzed to locate candidate PAIs and REIs. With additional quantitative and qualitative advancements in database content and detection accuracy, PAIDB will continue to facilitate pathogenomic studies of both pathogenic and non-pathogenic organisms.