Analysis of the Thermotoga maritima genome combining a variety of sequence similarity and genome context tools

Active Site Metal Occupancy and Cyclic Di-GMP Phosphodiesterase Activity of Thermotoga maritima HD-GYP

HD-GYPs make up a subclass of the metal-dependent HD phosphohydrolase superfamily and catalyze conversion of cyclic di(3',5')-guanosine monophosphate (c-di-GMP) to 5'-phosphoguanylyl-(3'→5')-guanosine (pGpG) and GMP. Until now, the only reported crystal structure of an HD-GYP that also exhibits c-di-GMP phosphodiesterase activity contains a His/carboxylate ligated triiron active site. However, other structural and phylogenetic correlations indicate that some HD-GYPs contain dimetal active sites. Here we provide evidence that an HD-GYP c-di-GMP phosphodiesterase, TM0186, from Thermotoga maritima can accommodate both di- and trimetal active sites. We show that an as-isolated iron-containing TM0186 has an oxo/carboxylato-bridged diferric site, and that the reduced (diferrous) form is necessary and sufficient to catalyze conversion of c-di-GMP to pGpG, but that conversion of pGpG to GMP requires more than two metals per active site. Similar c-di-GMP phosphodiesterase activities were obtained with divalent iron or manganese. On the basis of activity correlations with several putative metal ligand residue variants and molecular dynamics simulations, we propose that TM0186 can accommodate both di- and trimetal active sites. Our results also suggest that a Glu residue conserved in a subset of HD-GYPs is required for formation of the trimetal site and can also serve as a labile ligand to the dimetal site. Given the anaerobic growth requirement of T. maritima, we suggest that this HD-GYP can function in vivo with either divalent iron or manganese occupying di- and trimetal sites.

Using comparative genomics to uncover new kinds of protein-based metabolic organelles in bacteria

Bacterial microcompartment (MCP) organelles are cytosolic, polyhedral structures consisting of a thin protein shell and a series of encapsulated, sequentially acting enzymes. To date, different microcompartments carrying out three distinct types of metabolic processes have been characterized experimentally in various bacteria. In the present work, we use comparative genomics to explore the existence of yet uncharacterized microcompartments encapsulating a broader set of metabolic pathways. A clustering approach was used to group together enzymes that show a strong tendency to be encoded in chromosomal proximity to each other while also being near genes for microcompartment shell proteins. The results uncover new types of putative microcompartments, including one that appears to encapsulate B(12) -independent, glycyl radical-based degradation of 1,2-propanediol, and another potentially involved in amino alcohol metabolism in mycobacteria. Preliminary experiments show that an unusual shell protein encoded within the glycyl radical-based microcompartment binds an iron-sulfur cluster, hinting at complex mechanisms in this uncharacterized system. In addition, an examination of the computed microcompartment clusters suggests the existence of specific functional variations within certain types of MCPs, including the alpha carboxysome and the glycyl radical-based microcompartment. The findings lead to a deeper understanding of bacterial microcompartments and the pathways they sequester.

TREP_DB: transcriptional regulatory elements pattern database

Predicting and assigning functions for putative genes and hypothetical proteins are important goals in the post-genomic era. Many methods have been developed for this challenge, among which the straightforward way is function prediction using sequence homology. Homology-based function prediction applies sequence-alignment tools to find homology relationships between functions of known genes and putative genes, and transfers the most similar functions of known genes to putative genes. This approach fails completely for about 30% of genes, and only 3% have any supporting experimental evidence. According to supporting evidence, genes are known to be regulated by a common transcriptional regulatory element if the expression profiles of the coregulated genes are highly correlated. We propose a new conceptual approach and method for nonhomology-based function-prediction methods for putative genes and hypothetical proteins. We have established patterns, also considered to be combinations, of common transcriptional regulatory elements for functional classes of mouse (Mus musculus) transcripts (the TREP_DB). Using these results, we have also established a function-prediction method for putative genes and hypothetical proteins.

Microbial biochemistry, physiology, and biotechnology of hyperthermophilic Thermotoga species

High-throughput sequencing of microbial genomes has allowed the application of functional genomics methods to species lacking well-developed genetic systems. For the model hyperthermophile Thermotoga maritima, microarrays have been used in comparative genomic hybridization studies to investigate diversity among Thermotoga species. Transcriptional data have assisted in prediction of pathways for carbohydrate utilization, iron-sulfur cluster synthesis and repair, expolysaccharide formation, and quorum sensing. Structural genomics efforts aimed at the T. maritima proteome have yielded hundreds of high-resolution datasets and predicted functions for uncharacterized proteins. The information gained from genomics studies will be particularly useful for developing new biotechnology applications for T. maritima enzymes.

An expression-driven approach to the prediction of carbohydrate transport and utilization regulons in the hyperthermophilic bacterium Thermotoga maritima

Comprehensive analysis of genome-wide expression patterns during growth of the hyperthermophilic bacterium Thermotoga maritima on 14 monosaccharide and polysaccharide substrates was undertaken with the goal of proposing carbohydrate specificities for transport systems and putative transcriptional regulators. Saccharide-induced regulons were predicted through the complementary use of comparative genomics, mixed-model analysis of genome-wide microarray expression data, and examination of upstream sequence patterns. The results indicate that T. maritima relies extensively on ABC transporters for carbohydrate uptake, many of which are likely controlled by local regulators responsive to either the transport substrate or a key metabolic degradation product. Roles in uptake of specific carbohydrates were suggested for members of the expanded Opp/Dpp family of ABC transporters. In this family, phylogenetic relationships among transport systems revealed patterns of possible duplication and divergence as a strategy for the evolution of new uptake capabilities. The presence of GC-rich hairpin sequences between substrate-binding proteins and other components of Opp/Dpp family transporters offers a possible explanation for differential regulation of transporter subunit genes. Numerous improvements to T. maritima genome annotations were proposed, including the identification of ABC transport systems originally annotated as oligopeptide transporters as candidate transporters for rhamnose, xylose, beta-xylan, and beta-glucans and identification of genes likely to encode proteins missing from current annotations of the pentose phosphate pathway. Beyond the information obtained for T. maritima, the present study illustrates how expression-based strategies can be used for improving genome annotation in other microorganisms, especially those for which genetic systems are unavailable.

The ERGO genome analysis and discovery system

The ERGO (http://ergo.integratedgenomics.com/ERGO/) genome analysis and discovery suite is an integration of biological data from genomics, biochemistry, high-throughput expression profiling, genetics and peer-reviewed journals to achieve a comprehensive analysis of genes and genomes. Far beyond any conventional systems that facilitate functional assignments, ERGO combines pattern-based analysis with comparative genomics by visualizing genes within the context of regulation, expression profiling, phylogenetic clusters, fusion events, networked cellular pathways and chromosomal neighborhoods of other functionally related genes. The result of this multifaceted approach is to provide an extensively curated database of the largest available integration of genomes, with a vast collection of reconstructed cellular pathways spanning all domains of life. Although access to ERGO is provided only under subscription, it is already widely used by the academic community. The current version of the system integrates 500 genomes from all domains of life in various levels of completion, 403 of which are available for subscription.

Draft sequencing and comparative genomics of Xylella fastidiosa strains reveal novel biological insights

Draft sequencing is a rapid and efficient method for determining the near-complete sequence of microbial genomes. Here we report a comparative analysis of one complete and two draft genome sequences of the phytopathogenic bacterium, Xylella fastidiosa, which causes serious disease in plants, including citrus, almond, and oleander. We present highlights of an in silico analysis based on a comparison of reconstructions of core biological subsystems. Cellular pathway reconstructions have been used to identify a small number of genes, which are likely to reside within the draft genomes but are not captured in the draft assembly. These represented only a small fraction of all genes and were predominantly large and small ribosomal subunit protein components. By using this approach, some of the inherent limitations of draft sequence can be significantly reduced. Despite the incomplete nature of the draft genomes, it is possible to identify several phage-related genes, which appear to be absent from the draft genomes and not the result of insufficient sequence sampling. This region may therefore identify potential host-specific functions. Based on this first functional reconstruction of a phytopathogenic microbe, we spotlight an unusual respiration machinery as a potential target for biological control. We also predicted and developed a new defined growth medium for Xylella.

Whole-genome comparative analysis of three phytopathogenic Xylella fastidiosa strains

Xylella fastidiosa (Xf) causes wilt disease in plants and is responsible for major economic and crop losses globally. Owing to the public importance of this phytopathogen we embarked on a comparative analysis of the complete genome of Xf pv citrus and the partial genomes of two recently sequenced strains of this species: Xf pv almond and Xf pv oleander, which cause leaf scorch in almond and oleander plants, respectively. We report a reanalysis of the previously sequenced Xf 9a5c (CVC, citrus) strain and the two "gapped" Xf genomes revealing ORFs encoding critical functions in pathogenicity and conjugative transfer. Second, a detailed whole-genome functional comparison was based on the three sequenced Xf strains, identifying the unique genes present in each strain, in addition to those shared between strains. Third, an "in silico" cellular reconstruction of these organisms was made, based on a comparison of their core functional subsystems that led to a characterization of their conjugative transfer machinery, identification of potential differences in their adhesion mechanisms, and highlighting of the absence of a classical quorum-sensing mechanism. This study demonstrates the effectiveness of comparative analysis strategies in the interpretation of genomes that are closely related.

Dictionary-driven protein annotation

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

Genome sequence and analysis of the oral bacterium Fusobacterium nucleatum strain ATCC 25586

We present a complete DNA sequence and metabolic analysis of the dominant oral bacterium Fusobacterium nucleatum. Although not considered a major dental pathogen on its own, this anaerobe facilitates the aggregation and establishment of several other species including the dental pathogens Porphyromonas gingivalis and Bacteroides forsythus. The F. nucleatum strain ATCC 25586 genome was assembled from shotgun sequences and analyzed using the ERGO bioinformatics suite (http://www.integratedgenomics.com). The genome contains 2.17 Mb encoding 2,067 open reading frames, organized on a single circular chromosome with 27% GC content. Despite its taxonomic position among the gram-negative bacteria, several features of its core metabolism are similar to that of gram-positive Clostridium spp., Enterococcus spp., and Lactococcus spp. The genome analysis has revealed several key aspects of the pathways of organic acid, amino acid, carbohydrate, and lipid metabolism. Nine very-high-molecular-weight outer membrane proteins are predicted from the sequence, none of which has been reported in the literature. More than 137 transporters for the uptake of a variety of substrates such as peptides, sugars, metal ions, and cofactors have been identified. Biosynthetic pathways exist for only three amino acids: glutamate, aspartate, and asparagine. The remaining amino acids are imported as such or as di- or oligopeptides that are subsequently degraded in the cytoplasm. A principal source of energy appears to be the fermentation of glutamate to butyrate. Additionally, desulfuration of cysteine and methionine yields ammonia, H(2)S, methyl mercaptan, and butyrate, which are capable of arresting fibroblast growth, thus preventing wound healing and aiding penetration of the gingival epithelium. The metabolic capabilities of F. nucleatum revealed by its genome are therefore consistent with its specialized niche in the mouth.

Comparative genome analysis and pathway reconstruction

Pathway reconstruction builds on genome and biochemical data with the aim of reconstructing higher level interactions between identified enzymes in a specific genome, in particular the different enzyme pathways (species or individual/patient). Metabolite flow in a pathway is analyzed by different tools, such as elementary mode analysis. This reveals key enzymes and pharmacological targets in the enzyme network. An overview of bioinformatic tools and algorithms for these tasks, application examples and recent results from these techniques are presented. Target selection, drug development and optimization can all be sped up using these approaches.

The genome sequence of the facultative intracellular pathogen Brucella melitensis

Brucella melitensis is a facultative intracellular bacterial pathogen that causes abortion in goats and sheep and Malta fever in humans. The genome of B. melitensis strain 16M was sequenced and found to contain 3,294,935 bp distributed over two circular chromosomes of 2,117,144 bp and 1,177,787 bp encoding 3,197 ORFs. By using the bioinformatics suite ERGO, 2,487 (78%) ORFs were assigned functions. The origins of replication of the two chromosomes are similar to those of other alpha-proteobacteria. Housekeeping genes, including those involved in DNA replication, transcription, translation, core metabolism, and cell wall biosynthesis, are distributed on both chromosomes. Type I, II, and III secretion systems are absent, but genes encoding sec-dependent, sec-independent, and flagella-specific type III, type IV, and type V secretion systems as well as adhesins, invasins, and hemolysins were identified. Several features of the B. melitensis genome are similar to those of the symbiotic Sinorhizobium meliloti.

The past, present and future of genome-wide re-annotation

Annotation, the process by which structural or functional information is inferred for genes or proteins, is crucial for obtaining value from genome sequences. We define the process of annotating a previously annotated genome sequence as 're-annotation', and examine the strengths and weaknesses of current manual and automatic genome-wide re-annotation approaches.

Medical target prediction from genome sequence: combining different sequence analysis algorithms with expert knowledge and input from artificial intelligence approaches

By exploiting the rapid increase in available sequence data, the definition of medically relevant protein targets has been improved by a combination of: (i) differential genome analysis (target list): and (ii) analysis of individual proteins (target analysis). Fast sequence comparisons, data mining, and genetic algorithms further promote these procedures. Mycobacterium tuberculosis proteins were chosen as applied examples.