SIGI: score-based identification of genomic islands

Complete genome sequence of the erythromycin-producing bacterium Saccharopolyspora erythraea NRRL23338

Saccharopolyspora erythraea is used for the industrial-scale production of the antibiotic erythromycin A, derivatives of which play a vital role in medicine. The sequenced chromosome of this soil bacterium comprises 8,212,805 base pairs, predicted to encode 7,264 genes. It is circular, like those of the pathogenic actinomycetes Mycobacterium tuberculosis and Corynebacterium diphtheriae, but unlike the linear chromosomes of the model actinomycete Streptomyces coelicolor A3(2) and the closely related Streptomyces avermitilis. The S. erythraea genome contains at least 25 gene clusters for production of known or predicted secondary metabolites, at least 72 genes predicted to confer resistance to a range of common antibiotic classes and many sets of duplicated genes to support its saprophytic lifestyle. The availability of the genome sequence of S. erythraea will improve insight into its biology and facilitate rational development of strains to generate high-titer producers of clinically important antibiotics.

Complete genome sequence of the prototype lactic acid bacterium Lactococcus lactis subsp. cremoris MG1363

Lactococcus lactis is of great importance for the nutrition of hundreds of millions of people worldwide. This paper describes the genome sequence of Lactococcus lactis subsp. cremoris MG1363, the lactococcal strain most intensively studied throughout the world. The 2,529,478-bp genome contains 81 pseudogenes and encodes 2,436 proteins. Of the 530 unique proteins, 47 belong to the COG (clusters of orthologous groups) functional category "carbohydrate metabolism and transport," by far the largest category of novel proteins in comparison with L. lactis subsp. lactis IL1403. Nearly one-fifth of the 71 insertion elements are concentrated in a specific 56-kb region. This integration hot-spot region carries genes that are typically associated with lactococcal plasmids and a repeat sequence specifically found on plasmids and in the "lateral gene transfer hot spot" in the genome of Streptococcus thermophilus. Although the parent of L. lactis MG1363 was used to demonstrate lysogeny in Lactococcus, L. lactis MG1363 carries four remnant/satellite phages and two apparently complete prophages. The availability of the L. lactis MG1363 genome sequence will reinforce its status as the prototype among lactic acid bacteria through facilitation of further applied and fundamental research.

Whole-genome sequence of Listeria welshimeri reveals common steps in genome reduction with Listeria innocua as compared to Listeria monocytogenes

We present the complete genome sequence of Listeria welshimeri, a nonpathogenic member of the genus Listeria. Listeria welshimeri harbors a circular chromosome of 2,814,130 bp with 2,780 open reading frames. Comparative genomic analysis of chromosomal regions between L. welshimeri, Listeria innocua, and Listeria monocytogenes shows strong overall conservation of synteny, with the exception of the translocation of an F(o)F(1) ATP synthase. The smaller size of the L. welshimeri genome is the result of deletions in all of the genes involved in virulence and of "fitness" genes required for intracellular survival, transcription factors, and LPXTG- and LRR-containing proteins as well as 55 genes involved in carbohydrate transport and metabolism. In total, 482 genes are absent from L. welshimeri relative to L. monocytogenes. Of these, 249 deletions are commonly absent in both L. welshimeri and L. innocua, suggesting similar genome evolutionary paths from an ancestor. We also identified 311 genes specific to L. welshimeri that are absent in the other two species, indicating gene expansion in L. welshimeri, including horizontal gene transfer. The species L. welshimeri appears to have been derived from early evolutionary events and an ancestor more compact than L. monocytogenes that led to the emergence of nonpathogenic Listeria spp.

P-value based visualization of codon usage data

Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. Experimental results on four microbial genomes indicate that the new method is well-suited for the analysis of horizontal gene transfer and translational selection. As compared with the widely-used correspondence analysis, our method did not suffer from outlier sensitivity and showed a better clustering of putative alien genes in most cases.

Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models

Background

Horizontal gene transfer (HGT) is considered a strong evolutionary force shaping the content of microbial genomes in a substantial manner. It is the difference in speed enabling the rapid adaptation to changing environmental demands that distinguishes HGT from gene genesis, duplications or mutations. For a precise characterization, algorithms are needed that identify transfer events with high reliability. Frequently, the transferred pieces of DNA have a considerable length, comprise several genes and are called genomic islands (GIs) or more specifically pathogenicity or symbiotic islands.

Results

We have implemented the program SIGI-HMM that predicts GIs and the putative donor of each individual alien gene. It is based on the analysis of codon usage (CU) of each individual gene of a genome under study. CU of each gene is compared against a carefully selected set of CU tables representing microbial donors or highly expressed genes. Multiple tests are used to identify putatively alien genes, to predict putative donors and to mask putatively highly expressed genes. Thus, we determine the states and emission probabilities of an inhomogeneous hidden Markov model working on gene level. For the transition probabilities, we draw upon classical test theory with the intention of integrating a sensitivity controller in a consistent manner. SIGI-HMM was written in JAVA and is publicly available. It accepts as input any file created according to the EMBL-format.

It generates output in the common GFF format readable for genome browsers. Benchmark tests showed that the output of SIGI-HMM is in agreement with known findings. Its predictions were both consistent with annotated GIs and with predictions generated by different methods.

Conclusion

SIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes. It allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired genes.

A comparative categorization of gene flux in diverse microbial species

Microbial genomes harbor genomic islands (GIs), genes presumably acquired via horizontal gene transfer (HGT). We compared GIs of hyperthermophilic, thermophilic, mesophilic, and pathogenic/nonpathogenic species and of small and large genomes. The COG database was used to characterize gene-encoded functions. Putative donors were determined to quantify gene flux between superkingdoms. In hyperthermophiles, more than 10% of the genes were on average acquired across the superkingdom border. For thermophiles and particularly mesophiles, we identified a nearly unidirectional export from bacteria to archaea. Additionally, we analyzed GI composition for Escherichia, and pairs of Listeria, Rhizobiales, Methanosarcinaceae, and Thermus thermophilus/Deinococcus radiodurans. For Escherichia and Listeria, the composition of GIs in pathogenic and nonpathogenic species did not differ significantly with respect to encoded COG classes. The analysis of related genomes showed that the composition of GIs cannot be explained with trends of gene content known to depend on genome size.

The genome sequence of Methanosphaera stadtmanae reveals why this human intestinal archaeon is restricted to methanol and H2 for methane formation and ATP synthesis

Methanosphaera stadtmanae has the most restricted energy metabolism of all methanogenic archaea. This human intestinal inhabitant can generate methane only by reduction of methanol with H2 and is dependent on acetate as a carbon source. We report here the genome sequence of M. stadtmanae, which was found to be composed of 1,767,403 bp with an average G+C content of 28% and to harbor only 1,534 protein-encoding sequences (CDS). The genome lacks 37 CDS present in the genomes of all other methanogens. Among these are the CDS for synthesis of molybdopterin and for synthesis of the carbon monoxide dehydrogenase/acetyl-coenzyme A synthase complex, which explains why M. stadtmanae cannot reduce CO2 to methane or oxidize methanol to CO2 and why this archaeon is dependent on acetate for biosynthesis of cell components. Four sets of mtaABC genes coding for methanol:coenzyme M methyltransferases were found in the genome of M. stadtmanae. These genes exhibit homology to mta genes previously identified in Methanosarcina species. The M. stadtmanae genome also contains at least 323 CDS not present in the genomes of all other archaea. Seventy-three of these CDS exhibit high levels of homology to CDS in genomes of bacteria and eukaryotes. These 73 CDS include 12 CDS which are unusually long (>2,400 bp) with conspicuous repetitive sequence elements, 13 CDS which exhibit sequence similarity on the protein level to CDS encoding enzymes involved in the biosynthesis of cell surface antigens in bacteria, and 5 CDS which exhibit sequence similarity to the subunits of bacterial type I and III restriction-modification systems.

A comparative categorization of protein function encoded in bacterial or archeal genomic islands

Genomes of prokaryotes harbor genomic islands (GIs), which are frequently acquired via horizontal gene transfer (HGT). Here I present an analysis of GIs with respect to gene-encoded functions. GIs were identified by statistical analysis of codon usage and clustering. Genes classified as putatively alien (pA) or putatively native (pN) were categorized according to the COG database. Among pA and pN genes, the distribution of COG functions and classes were studied for different groupings of prokaryotes. Groups were formed according to taxonomical relation or habitats. In all groups, genes related to class L (replication, recombination, and repair) were statistically significantly overrepresented in GIs. GIs of bacteria and archaea showed a distinct pattern of preferences. In archeal GIs, genes belonging to COG class M (cell wall/membrane/envelope biogenesis) or Q (secondary metabolites biosynthesis, transport, and catabolism) were more frequent. In bacterial GIs, genes of classes U (intracellular trafficking, secretion, and vesicular transport), N (cell motility), and V (defense mechanisms) were predominant. Underrepresentation was strongest for genes belonging to class J (translation, ribosomal structure, and biogenesis). Among single COG functions overrepresented in GIs were transferases and transporters. In both superkingdoms, HGT enhances genomic content by meeting demands that are independent of the studied habitats. These findings are in agreement with the complexity theory, which predicts the preferential import of operational genes. However, only specific subsets of operational genes were enriched in GIs. Modification of the cell envelope, cell motility, secretion, and protection of cellular DNA are major issues in HGT.

Evidence of a large novel gene pool associated with prokaryotic genomic islands

Microbial genes that are “novel” (no detectable homologs in other species) have become of increasing interest as environmental sampling suggests that there are many more such novel genes in yet-to-be-cultured microorganisms. By analyzing known microbial genomic islands and prophages, we developed criteria for systematic identification of putative genomic islands (clusters of genes of probable horizontal origin in a prokaryotic genome) in 63 prokaryotic genomes, and then characterized the distribution of novel genes and other features. All but a few of the genomes examined contained significantly higher proportions of novel genes in their predicted genomic islands compared with the rest of their genome (Paired t test = 4.43E-14 to 1.27E-18, depending on method). Moreover, the reverse observation (i.e., higher proportions of novel genes outside of islands) never reached statistical significance in any organism examined. We show that this higher proportion of novel genes in predicted genomic islands is not due to less accurate gene prediction in genomic island regions, but likely reflects a genuine increase in novel genes in these regions for both bacteria and archaea. This represents the first comprehensive analysis of novel genes in prokaryotic genomic islands and provides clues regarding the origin of novel genes. Our collective results imply that there are different gene pools associated with recently horizontally transmitted genomic regions versus regions that are primarily vertically inherited. Moreover, there are more novel genes within the gene pool associated with genomic islands. Since genomic islands are frequently associated with a particular microbial adaptation, such as antibiotic resistance, pathogen virulence, or metal resistance, this suggests that microbes may have access to a larger “arsenal” of novel genes for adaptation than previously thought.

More than 250 microbial genomes have been sequenced to date. A significant proportion of the genes in these genomes have no apparent similarity to known genes and their functions are unknown (i.e., they appear to be novel). As the number of sequenced genomes increases, the number of these novel genes continues to increase. In this paper, the authors now show, through an analysis of a diverse range of prokaryotic genomes, that novel genes are more prevalent in regions called genomic islands. Genomic islands are clusters of genes in genomes that show evidence of horizontal origins. This study is notable since genomic islands disproportionately contain many genes of medical, agricultural, and environmental importance (e.g., animal and plant pathogen virulence factors, antibiotic resistance genes, phenolic degradation genes, etc.). The observation that high proportions of novel genes are also localized to genomic islands suggests that microbes may have access to a larger “arsenal” of novel genes for important adaptations than previously thought. These results also imply that there are different gene pools associated with recently horizontally transmitted genomic regions versus regions that are primarily vertically inherited. The authors suggest that further studies involving large-scale environmental genomic sampling are required to help characterize this understudied gene pool.

A computational approach for identifying pathogenicity islands in prokaryotic genomes

Background

Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs.

Results

We present a computational method for detecting potential PAIs in complete prokaryotic genomes by combining sequence similarities and abnormalities in genomic composition. We first collected 207 GenBank accessions containing either part or all of the reported PAI loci. In sequenced genomes, strips of PAI-homologs were defined based on the proximity of the homologs of genes in the same PAI accession. An algorithm reminiscent of sequence-assembly procedure was then devised to merge overlapping or adjacent genomic strips into a large genomic region. Among the defined genomic regions, PAI-like regions were identified by the presence of homolog(s) of virulence genes. Also, GIs were postulated by calculating G+C content anomalies and codon usage bias. Of 148 prokaryotic genomes examined, 23 pathogenic and 6 non-pathogenic bacteria contained 77 candidate PAIs that partly or entirely overlap GIs.

Conclusion

Supporting the validity of our method, included in the list of candidate PAIs were thirty four PAIs previously identified from genome sequencing papers. Furthermore, in some instances, our method was able to detect entire PAIs for those only partial sequences are available. Our method was proven to be an efficient method for demarcating the potential PAIs in our study. Also, the function(s) and origin(s) of a candidate PAI can be inferred by investigating the PAI queries comprising it. Identification and analysis of potential PAIs in prokaryotic genomes will broaden our knowledge on the structure and properties of PAIs and the evolution of bacterial pathogenesis.

Insights in the Pathogenic Potential of Propionibacterium acnes From Its Complete Genome

One of the long-lasting open questions in understanding acne is the role of the skin bacterium Propionibacterium acnes. Opinions within the scientific community diverge regarding the importance of this Gram-positive bacterium not only in acne but also in other P. acnes-associated diseases. The recently decoded genome gives us some clues with respect to its pathogenic potential and its strategies to survive in the harsh environment of human skin. This review focuses on the major findings of the genome sequence. Special attention has been drawn to the cell surface composition of P. acnes, its antigenic potential, and to enzymes that are potentially involved in degrading skin-derived substances.

The genome of the heartwater agent Ehrlichia ruminantium contains multiple tandem repeats of actively variable copy number

Heartwater, a tick-borne disease of domestic and wild ruminants, is caused by the intracellular rickettsia Ehrlichia ruminantium (previously known as Cowdria ruminantium). It is a major constraint to livestock production throughout subSaharan Africa, and it threatens to invade the Americas, yet there is no immediate prospect of an effective vaccine. A shotgun genome sequencing project was undertaken in the expectation that access to the complete protein coding repertoire of the organism will facilitate the search for vaccine candidate genes. We report here the complete 1,516,355-bp sequence of the type strain, the stock derived from the South African Welgevonden isolate. Only 62% of the genome is predicted to be coding sequence, encoding 888 proteins and 41 stable RNA species. The most striking feature is the large number of tandemly repeated and duplicated sequences, some of continuously variable copy number, which contributes to the low proportion of coding sequence. These repeats have mediated numerous translocation and inversion events that have resulted in the duplication and truncation of some genes and have also given rise to new genes. There are 32 predicted pseudogenes, most of which are truncated fragments of genes associated with repeats. Rather then being the result of the reductive evolution seen in other intracellular bacteria, these pseudogenes appear to be the product of ongoing sequence duplication events.

GenomeViz: visualizing microbial genomes

Background

An increasing number of microbial genomes are being sequenced and deposited in public databases. In addition, several closely related strains are also being sequenced in order to understand the genetic basis of diversity and mechanisms that lead to the acquisition of new genetic traits. These exercises have necessitated the requirement for visualizing microbial genomes and performing genome comparisons on a finer scale. We have developed GenomeViz to enable rapid visualization and subsequent comparisons of several microbial genomes in an interactive environment.

Results

Here we describe a program that allows visualization of both qualitative and quantitative information from complete and partially sequenced microbial genomes. Using GenomeViz, data deriving from studies on genomic islands, gene/protein classifications, GC content, GC skew, whole genome alignments, microarrays and proteomics may be plotted. Several genomes can be visualized interactively at the same time from a comparative genomic perspective and publication quality circular genome plots can be created.

Conclusions

GenomeViz should allow researchers to perform visualization and comparative analysis of up to eight different microbial genomes simultaneously.

The Complete Genome Sequence of Bacillus licheniformis DSM13, an Organism with Great Industrial Potential

The genome of Bacillus licheniformis DSM13 consists of a single chromosome that has a size of 4,222,748 base pairs. The average G+C ratio is 46.2%. 4,286 open reading frames, 72 tRNA genes, 7 rRNA operons and 20 transposase genes were identified. The genome shows a marked co-linearity with Bacillus subtilis but contains defined inserted regions that can be identified at the sequence as well as at the functional level. B. licheniformis DSM13 has a well-conserved secretory system, no polyketide biosynthesis, but is able to form the lipopeptide lichenysin. From the further analysis of the genome sequence, we identified conserved regulatory DNA motives, the occurrence of the glyoxylate bypass and the presence of anaerobic ribonucleotide reductase explaining that B. licheniformis is able to grow on acetate and 2,3-butanediol as well as anaerobically on glucose. Many new genes of potential interest for biotechnological applications were found in B. licheniformis; candidates include proteases, pectate lyases, lipases and various polysaccharide degrading enzymes.