Identification Of Genomic Islands Research Articles

Genome characterisation and comparative analysis of Schaalia dentiphila sp. nov. and its subspecies, S. dentiphila subsp. denticola subsp. nov., from the human oral cavity.

Schaalia species are primarily found among the oral microbiota of humans and other animals. They have been associated with various infections through their involvement in biofilm formation, modulation of host responses, and interaction with other microorganisms. In this study, two strains previously indicated as Actinomyces spp. were found to be novel members of the genus Schaalia based on their whole genome sequences. Whole-genome sequencing revealed both strains with a genome size of 2.3 Mbp and GC contents of 65.5%. Phylogenetics analysis for taxonomic placement revealed strains NCTC 9931 and C24 as distinct species within the genus Schaalia. Overall genome-relatedness indices including digital DNA-DNA hybridization (dDDH), and average nucleotide/amino acid identity (ANI/AAI) confirmed both strains as distinct species, with values below the species boundary thresholds (dDDH < 70%, and ANI and AAI < 95%) when compared to nearest type strain Schaalia odontolytica NCTC 9935T. Pangenome and orthologous analyses highlighted their differences in gene properties and biological functions compared to existing type strains. Additionally, the identification of genomic islands (GIs) and virulence-associated factors indicated their genetic diversity and potential adaptive capabilities, as well as potential implications for human health. Notably, CRISPR-Cas systems in strain NCTC 9931 underscore its adaptive immune mechanisms compared to strain C24. Based on these findings, strain NCTC 9931T (= ATCC 17982T = DSM 43331T = CIP 104728T = CCUG 18309T = NCTC 14978T = CGMCC 1.90328T) represents a novel species, for which the name Schaalia dentiphila subsp. dentiphila sp. nov. subsp. nov. is proposed, while strain C24T (= NCTC 14980T = CGMCC 1.90329T) represents a distinct novel subspecies, for which the name Schaalia dentiphila subsp. denticola. subsp. nov. is proposed. This study enriches our understanding of the genomic diversity of Schaalia species and paves the way for further investigations into their roles in oral health. This research reveals two Schaalia strains, NCTC 9931T and C24T, as novel entities with distinct genomic features. Expanding the taxonomic framework of the genus Schaalia, this study offers a critical resource for probing the metabolic intricacies and resistance patterns of these bacteria. This work stands as a cornerstone for microbial taxonomy, paving the way for significant advances in clinical diagnostics.

2SigFinder: the combined use of small-scale and large-scale statistical testing for genomic island detection from a single genome

BackgroundGenomic islands are associated with microbial adaptations, carrying genomic signatures different from the host. Some methods perform an overall test to identify genomic islands based on their local features. However, regions of different scales will display different genomic features.ResultsWe proposed here a novel method “2SigFinder “, the first combined use of small-scale and large-scale statistical testing for genomic island detection. The proposed method was tested by genomic island boundary detection and identification of genomic islands or functional features of real biological data. We also compared the proposed method with the comparative genomics and composition-based approaches. The results indicate that the proposed 2SigFinder is more efficient in identifying genomic islands.ConclusionsFrom real biological data, 2SigFinder identified genomic islands from a single genome and reported robust results across different experiments, without annotated information of genomes or prior knowledge from other datasets. 2SigHunter identified 25 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats from 27 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats, and detected 101 Phage and 28 HEG out of 130 Phage and 36 HEGs in S. enterica Typhi CT18, which shows that it is more efficient in detecting functional features associated with GIs.

Identification of genomic islands in Chilean Piscirickettsia salmonis strains and analysis of gene expression involved in virulence.

Piscirickettsia salmonis, an agent of Piscirickettsiosis, is the cause of major losses in the Chilean salmon industry. We identified, characterized and bioinformatically analysed genomic islands in field strains of P.Salmonis, using the bioinformatic software PIPS, that uses the characteristics of the islands of pathogenicity to identify them. We analysed nine partially sequenced genomes in different new field strains, and compared them with the LF-89 (Type strain) genome, selecting a genomic island present in all of them. We then evaluated the relative expression of three genes present in that island. From the obtained results, we conclude that the expression of the tcf gene is directly proportional to the cytopathogenicity invitro of the bacteria; the product of the dnsa gene could contribute to its pathogenicity, but would be potentiated by one or more factors. The product of the gene liso is necessary for the virulence process and could have functions in early stages of infection. Regarding the strains, the IBM-040 strain showed a significant increase in the expression of all the genes in the study. Contrarily, LF-89 only presented a significant increase in expression of the gene liso, which correlates with the cytopathogenicity invitro observed in the SHK-1 cells.

A Novel Approach to Helicobacter pylori Pan-Genome Analysis for Identification of Genomic Islands.

Genomes of a given bacterial species can show great variation in gene content and thus systematic analysis of the entire gene repertoire, termed the pan-genome, is important for understanding bacterial intra-species diversity, population genetics, and evolution. Here, we analyzed the pan-genome from 30 completely sequenced strains of the human gastric pathogen Helicobacter pylori belonging to various phylogeographic groups, focusing on 991 accessory (not fully conserved) orthologous groups (OGs). We developed a method to evaluate the mobility of genes within a genome, using the gene order in the syntenically conserved regions as a reference, and classified the 991 accessory OGs into five classes: Core, Stable, Intermediate, Mobile, and Unique. Phylogenetic networks based on the gene content of Core and Stable classes are highly congruent with that created from the concatenated alignment of fully conserved core genes, in contrast to those of Intermediate and Mobile classes, which show quite different topologies. By clustering the accessory OGs on the basis of phylogenetic pattern similarity and chromosomal proximity, we identified 60 co-occurring gene clusters (CGCs). In addition to known genomic islands, including cag pathogenicity island, bacteriophages, and integrating conjugative elements, we identified some novel ones. One island encodes TerY-phosphorylation triad, which includes the eukaryote-type protein kinase/phosphatase gene pair, and components of type VII secretion system. Another one contains a reverse-transcriptase homolog, which may be involved in the defense against phage infection through altruistic suicide. Many of the CGCs contained restriction-modification (RM) genes. Different RM systems sometimes occupied the same (orthologous) locus in the strains. We anticipate that our method will facilitate pan-genome studies in general and help identify novel genomic islands in various bacterial species.

Barcode Server: A Visualization-Based Genome Analysis System

We have previously developed a computational method for representing a genome as a barcode image, which makes various genomic features visually apparent. We have demonstrated that this visual capability has made some challenging genome analysis problems relatively easy to solve. We have applied this capability to a number of challenging problems, including (a) identification of horizontally transferred genes, (b) identification of genomic islands with special properties and (c) binning of metagenomic sequences, and achieved highly encouraging results. These application results inspired us to develop this barcode-based genome analysis server for public service, which supports the following capabilities: (a) calculation of the k-mer based barcode image for a provided DNA sequence; (b) detection of sequence fragments in a given genome with distinct barcodes from those of the majority of the genome, (c) clustering of provided DNA sequences into groups having similar barcodes; and (d) homology-based search using Blast against a genome database for any selected genomic regions deemed to have interesting barcodes. The barcode server provides a job management capability, allowing processing of a large number of analysis jobs for barcode-based comparative genome analyses. The barcode server is accessible at http://csbl1.bmb.uga.edu/Barcode.

High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions.

N-Gram characterization of genomic islands in bacterial genomes

The paper presents a novel, n-gram-based method for analysis of bacterial genome segments known as genomic islands (GIs). Identification of GIs in bacterial genomes is an important task since many of them represent inserts that may contribute to bacterial evolution and pathogenesis. In order to characterize and distinguish GIs from rest of the genome, binary classification of islands based on n-gram frequency distribution have been performed. It consists of testing the agreement of islands n-gram frequency distributions with the complete genome and backbone sequence. In addition, a statistic based on the maximal order Markov model is used to identify significantly overrepresented and underrepresented n-grams in islands. The results may be used as a basis for Zipf-like analysis suggesting that some of the n-grams are overrepresented in a subset of islands and underrepresented in the backbone, or vice versa, thus complementing the binary classification. The method is applied to strain-specific regions in the Escherichia coli O157:H7 EDL933 genome (O-islands), resulting in two groups of O-islands with different n-gram characteristics. It refines a characterization based on other compositional features such as G + C content and codon usage, and may help in identification of GIs, and also in research and development of adequate drugs targeting virulence genes in them.

Identification of genomic islands in six plant pathogens

Genomic islands (GIs) play important roles in microbial evolution, which are acquired by horizontal gene transfer. In this paper, the GIs of six completely sequenced plant pathogens are identified using a windowless method based on Z curve representation of DNA sequences. Consequently, four, eight, four, one, two and four GIs are recognized with the length greater than 20-Kb in plant pathogens Agrobacterium tumefaciens str. C58, Rolstonia solanacearum GMI1000, Xanthomonas axonopodis pv. citri str. 306 ( Xac), Xanthomonas campestris pv. campestris str. ATCC33913 ( Xcc), Xylella fastidiosa 9a5c and Pseudomonas syringae pv. tomato str. DC3000, respectively. Most of these regions share a set of conserved features of GIs, including an abrupt change in GC content compared with that of the rest of the genome, the existence of integrase genes at the junction, the use of tRNA as the integration sites, the presence of genetic mobility genes, the difference of codon usage, codon preference and amino acid usage, etc. The identification of these GIs will benefit the research for the six important phytopathogens.

Genomic island identification in Vibrio vulnificus reveals significant genome plasticity in this human pathogen

Genomic islands (GIs) are large chromosomal regions present in a subset of bacterial strains that increase the fitness of the organism under specific conditions. We compared the complete genome sequences of two Vibrio vulnificus strains YJ016 and CMCP6 and identified 14 regions (ranging in size from 14 to 117 kb), which had the characteristics of GIs. Bioinformatic analysis of these 14 GI regions identified the presence of phage-like integrase genes, aberrant GC content and genome signature (dinucleotide frequency) within each GI compared with the core genome indicating that these regions were acquired from an anomalous source. We examined the distribution of the nine GIs from strain YJ016 among 27 V. vulnificus isolates and found that most GIs were absent from the majority of these isolates. The chromosomal insertion sites of three GIs were adjacent to tRNA sites, which contained novel horizontally acquired DNA in all six available sequenced Vibrionaceae genomes. Supplementary data are available at Bioinformatics online.