Rainer Merkl

The genome sequence of the extreme thermophile Thermus thermophilus

Thermus thermophilus HB27 is an extremely thermophilic, halotolerant bacterium, which was originally isolated from a natural thermal environment in Japan. This organism has considerable biotechnological potential; many thermostable proteins isolated from members of the genus Thermus are indispensable in research and in industrial applications. We present here the complete genome sequence of T. thermophilus HB27, the first for the genus Thermus. The genome consists of a 1,894,877 base pair chromosome and a 232,605 base pair megaplasmid, designated pTT27. The 2,218 identified putative genes were compared to those of the closest relative sequenced so far, the mesophilic bacterium Deinococcus radiodurans. Both organisms share a similar set of proteins, although their genomes lack extensive synteny. Many new genes of potential interest for biotechnological applications were found in T. thermophilus HB27. Candidates include various proteases and key enzymes of other fundamental biological processes such as DNA replication, DNA repair and RNA maturation.

The genome sequence of Clostridium tetani, the causative agent of tetanus disease

Tetanus disease is one of the most dramatic and globally prevalent diseases of humans and vertebrate animals, and has been reported for over 24 centuries. The manifestation of the disease, spastic paralysis, is caused by the second most poisonous substance known, the tetanus toxin, with a human lethal dose of ≈1 ng/kg. Fortunately, this disease is successfully controlled through immunization with tetanus toxoid; nevertheless, according to the World Health Organization, an estimated 400,000 cases still occur each year, mainly of neonatal tetanus. The causative agent of tetanus disease is Clostridium tetani, an anaerobic spore-forming bacterium, whose natural habitat is soil, dust, and intestinal tracts of various animals. Here we report the complete genome sequence of toxigenic C. tetani E88, a variant of strain Massachusetts. The genome consists of a 2,799,250-bp chromosome encoding 2,372 ORFs. The tetanus toxin and a collagenase are encoded on a 74,082-bp plasmid, containing 61 ORFs. Additional virulence-related factors could be identified, such as an array of surface-layer and adhesion proteins (35 ORFs), some of them unique to C. tetani. Comparative genomics with the genomes of Clostridium perfringens, the causative agent of gas gangrene, and Clostridium acetobutylicum, a nonpathogenic solvent producer, revealed a remarkable capacity of C. tetani: The organism can rely on an extensive sodium ion bioenergetics. Additional candidate genes involved in the establishment and maintenance of a pathogenic lifestyle of C. tetani are presented.

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.

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

BackgroundHorizontal 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.ResultsWe 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.ConclusionSIGI-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.

Gene Islands Integrated into tRNA(Gly) Genes Confer Genome Diversity on a Pseudomonas aeruginosa Clone

Intraclonal genome diversity of Pseudomonas aeruginosa was studied in one of the most diverse mosaic regions of the P. aeruginosa chromosome. The ca. 110-kb large hypervariable region located near the lipH gene in two members of the predominant P. aeruginosa clone C, strain C and strain SG17M, was sequenced. In both strains the region consists of an individual strain-specific gene island of 111 (strain C) or 106 (SG17M) open reading frames (ORFs) and of a 7-kb stretch of clone C-specific sequence of 9 ORFs. The gene islands are integrated into conserved tRNA(Gly) genes and have a bipartite structure. The first part adjacent to the tRNA gene consists of strain-specific ORFs encoding metabolic functions and transporters, the majority of which have homologs of known function in other eubacteria, such as hemophores, cytochrome c biosynthesis, or mercury resistance. The second part is made up mostly of ORFs of yet-unknown function. Forty-seven of these ORFs are mutual homologs with a pairwise amino acid sequence identity of 35 to 88% and are arranged in the same order in the two gene islands. We hypothesize that this novel type of gene island derives from mobile elements which, upon integration, endow the recipient with strain-specific metabolic properties, thus possibly conferring on it a selective advantage in its specific habitat.

Identification and characterization of two novel primate-specific histone H3 variants, H3.X and H3.Y

The expression of a new histone variant H3.Y increases during cellular stress to regulate cell cycle progression and gene expression.

SIGI: score-based identification of genomic islands.

AbstractBackgroundGenomic islands can be observed in many microbial genomes. These stretches of DNA have a conspicuous composition with regard to sequence or encoded functions. Genomic islands are assumed to be frequently acquired via horizontal gene transfer. For the analysis of genome structure and the study of horizontal gene transfer, it is necessary to reliably identify and characterize these islands.ResultsA scoring scheme on codon frequencies Score_G1G2(cdn) = log(f_G2(cdn) / f_G1(cdn)) was utilized. To analyse genes of a species G1 and to test their relatedness to species G2, scores were determined by applying the formula to log-odds derived from mean codon frequencies of the two genomes. A non-redundant set of nearly 400 codon usage tables comprising microbial species was derived; its members were used alternatively at position G2. Genes having at least one score value above a species-specific and dynamically determined cut-off value were analysed further. By means of cluster analysis, genes were identified that comprise clusters of statistically significant size. These clusters were predicted as genomic islands. Finally and individually for each of these genes, the taxonomical relation among those species responsible for significant scores was interpreted. The validity of the approach and its limitations were made plausible by an extensive analysis of natural genes and synthetic ones aimed at modelling the process of gene amelioration.ConclusionsThe method reliably allows to identify genomic island and the likely origin of alien genes.

Turning catalytically inactive human Argonaute proteins into active slicer enzymes

Argonaute proteins interact with small RNAs that guide them to complementary target RNAs, thus leading to inhibition of gene expression. Some but not all Argonaute proteins are endonucleases and can cleave the complementary target RNA. Here, we have mutated inactive human Ago1 and Ago3 and generated catalytic Argonaute proteins. We find that two short sequence elements at the N terminus are important for activity. In addition, PIWI-domain mutations in Ago1 may misarrange the catalytic center. Our work helps in understanding of the structural requirements that make an Argonaute protein an active endonucleolytic enzyme.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

BackgroundKernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals.ResultsWe propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon.ConclusionsWe showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems.

Comparative genomics and transcriptomics of lineages I, II, and III strains of Listeria monocytogenes

BackgroundListeria monocytogenes is a food-borne pathogen that causes infections with a high-mortality rate and has served as an invaluable model for intracellular parasitism. Here, we report complete genome sequences for two L. monocytogenes strains belonging to serotype 4a (L99) and 4b (CLIP80459), and transcriptomes of representative strains from lineages I, II, and III, thereby permitting in-depth comparison of genome- and transcriptome -based data from three lineages of L. monocytogenes. Lineage III, represented by the 4a L99 genome is known to contain strains less virulent for humans.ResultsThe genome analysis of the weakly pathogenic L99 serotype 4a provides extensive evidence of virulence gene decay, including loss of several important surface proteins. The 4b CLIP80459 genome, unlike the previously sequenced 4b F2365 genome harbours an intact inlB invasion gene. These lineage I strains are characterized by the lack of prophage genes, as they share only a single prophage locus with other L. monocytogenes genomes 1/2a EGD-e and 4a L99. Comparative transcriptome analysis during intracellular growth uncovered adaptive expression level differences in lineages I, II and III of Listeria, notable amongst which was a strong intracellular induction of flagellar genes in strain 4a L99 compared to the other lineages. Furthermore, extensive differences between strains are manifest at levels of metabolic flux control and phosphorylated sugar uptake. Intriguingly, prophage gene expression was found to be a hallmark of intracellular gene expression. Deletion mutants in the single shared prophage locus of lineage II strain EGD-e 1/2a, the lma operon, revealed severe attenuation of virulence in a murine infection model.ConclusionComparative genomics and transcriptome analysis of L. monocytogenes strains from three lineages implicate prophage genes in intracellular adaptation and indicate that gene loss and decay may have led to the emergence of attenuated lineages.