A reconstruction of the metabolism of Methanococcus jannaschii from sequence data

An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter

Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

Characterization of feedback-resistant mevalonate kinases from the methanogenic archaeons Methanosaeta concilii and Methanocella paludicola

The inhibition of mevalonate kinase (MVK) by downstream metabolites is an important mechanism in the regulation of isoprenoid production in a broad range of organisms. The first feedback-resistant MVK was previously discovered in the methanogenic archaeon Methanosarcinamazei. Here, we report the cloning, expression, purification, kinetic characterization and inhibition analysis of MVKs from two other methanogens, Methanosaetaconcilii and Methanocellapaludicola. Similar to the M. mazei MVK, these enzymes were not inhibited by diphosphomevalonate (DPM), dimethylallyl diphosphate (DMAPP), isopentenyldiphosphate (IPP), geranylpyrophosphate (GPP) or farnesylpyrophosphate (FPP). However, they exhibited significantly higher affinity to mevalonate and higher catalytic efficiency than the previously characterized enzyme.

Stoichiometric model and flux balance analysis for a mixed culture of Leptospirillum ferriphilum and Ferroplasma acidiphilum

The oxidation process of sulfide minerals in natural environments is achieved by microbial communities from the Archaea and Bacteria domains. A metabolic reconstruction of two dominant species, Leptospirillum ferriphilum and Ferroplasma acidiphilum, which are always found together as a mixed culture in this natural environments, was made. The metabolic model, composed of 152 internal reactions and 29 transport reactions, describes the main interactions between these species, assuming that both use ferrous iron as energy source, and F. acidiphilum takes advantage of the organic compounds secreted by L. ferriphilum for chemomixotrophic growth. A first metabolic model for a mixed culture used in bacterial leaching is proposed in this article, which pretends to represent the characteristics of the mixed culture in a simplified manner. It was evaluated with experimental data through flux balance analysis (FBA) using as objective function the maximization of biomass. The growth yields on ferrous iron obtained for each microorganism are consistent with experimental data, and the flux distribution obtained allows understanding of the metabolic capabilities of both microorganisms growing together in a bioleaching process. The model was used to simulate the growth of F. acidiphilum on different substrates, to determine in silico which compounds maximize cell growth, and which are essential. Knockout simulations were carried out for L. ferriphilum and F. acidiphilum metabolic models, predicting key enzymes of central metabolism. The results of this analysis are consistent with experimental data from literature, showing a robust behavior of the metabolic model.

Carbohydrate metabolism in Archaea: current insights into unusual enzymes and pathways and their regulation

The metabolism of Archaea, the third domain of life, resembles in its complexity those of Bacteria and lower Eukarya. However, this metabolic complexity in Archaea is accompanied by the absence of many "classical" pathways, particularly in central carbohydrate metabolism. Instead, Archaea are characterized by the presence of unique, modified variants of classical pathways such as the Embden-Meyerhof-Parnas (EMP) pathway and the Entner-Doudoroff (ED) pathway. The pentose phosphate pathway is only partly present (if at all), and pentose degradation also significantly differs from that known for bacterial model organisms. These modifications are accompanied by the invention of "new," unusual enzymes which cause fundamental consequences for the underlying regulatory principles, and classical allosteric regulation sites well established in Bacteria and Eukarya are lost. The aim of this review is to present the current understanding of central carbohydrate metabolic pathways and their regulation in Archaea. In order to give an overview of their complexity, pathway modifications are discussed with respect to unusual archaeal biocatalysts, their structural and mechanistic characteristics, and their regulatory properties in comparison to their classic counterparts from Bacteria and Eukarya. Furthermore, an overview focusing on hexose metabolic, i.e., glycolytic as well as gluconeogenic, pathways identified in archaeal model organisms is given. Their energy gain is discussed, and new insights into different levels of regulation that have been observed so far, including the transcript and protein levels (e.g., gene regulation, known transcription regulators, and posttranslational modification via reversible protein phosphorylation), are presented.

Unpredictability of metabolism--the key role of metabolomics science in combination with next-generation genome sequencing

Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype-phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N. This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science--the quantitative measurement of metabolism in conjunction with metabolic modelling--is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype-phenotype relationship.

'Unknown' proteins and 'orphan' enzymes: the missing half of the engineering parts list--and how to find it

Like other forms of engineering, metabolic engineering requires knowledge of the components (the 'parts list') of the target system. Lack of such knowledge impairs both rational engineering design and diagnosis of the reasons for failures; it also poses problems for the related field of metabolic reconstruction, which uses a cell's parts list to recreate its metabolic activities in silico. Despite spectacular progress in genome sequencing, the parts lists for most organisms that we seek to manipulate remain highly incomplete, due to the dual problem of 'unknown' proteins and 'orphan' enzymes. The former are all the proteins deduced from genome sequence that have no known function, and the latter are all the enzymes described in the literature (and often catalogued in the EC database) for which no corresponding gene has been reported. Unknown proteins constitute up to about half of the proteins in prokaryotic genomes, and much more than this in higher plants and animals. Orphan enzymes make up more than a third of the EC database. Attacking the 'missing parts list' problem is accordingly one of the great challenges for post-genomic biology, and a tremendous opportunity to discover new facets of life's machinery. Success will require a co-ordinated community-wide attack, sustained over years. In this attack, comparative genomics is probably the single most effective strategy, for it can reliably predict functions for unknown proteins and genes for orphan enzymes. Furthermore, it is cost-efficient and increasingly straightforward to deploy owing to a proliferation of databases and associated tools.

Recent developments in parameter estimation and structure identification of biochemical and genomic systems

The organization, regulation and dynamical responses of biological systems are in many cases too complex to allow intuitive predictions and require the support of mathematical modeling for quantitative assessments and a reliable understanding of system functioning. All steps of constructing mathematical models for biological systems are challenging, but arguably the most difficult task among them is the estimation of model parameters and the identification of the structure and regulation of the underlying biological networks. Recent advancements in modern high-throughput techniques have been allowing the generation of time series data that characterize the dynamics of genomic, proteomic, metabolic, and physiological responses and enable us, at least in principle, to tackle estimation and identification tasks using 'top-down' or 'inverse' approaches. While the rewards of a successful inverse estimation or identification are great, the process of extracting structural and regulatory information is technically difficult. The challenges can generally be categorized into four areas, namely, issues related to the data, the model, the mathematical structure of the system, and the optimization and support algorithms. Many recent articles have addressed inverse problems within the modeling framework of Biochemical Systems Theory (BST). BST was chosen for these tasks because of its unique structural flexibility and the fact that the structure and regulation of a biological system are mapped essentially one-to-one onto the parameters of the describing model. The proposed methods mainly focused on various optimization algorithms, but also on support techniques, including methods for circumventing the time consuming numerical integration of systems of differential equations, smoothing overly noisy data, estimating slopes of time series, reducing the complexity of the inference task, and constraining the parameter search space. Other methods targeted issues of data preprocessing, detection and amelioration of model redundancy, and model-free or model-based structure identification. The total number of proposed methods and their applications has by now exceeded one hundred, which makes it difficult for the newcomer, as well as the expert, to gain a comprehensive overview of available algorithmic options and limitations. To facilitate the entry into the field of inverse modeling within BST and related modeling areas, the article presented here reviews the field and proposes an operational 'work-flow' that guides the user through the estimation process, identifies possibly problematic steps, and suggests corresponding solutions based on the specific characteristics of the various available algorithms. The article concludes with a discussion of the present state of the art and with a description of open questions.

Structure and synthesis of polyisoprenoids used in N-glycosylation across the three domains of life

N-linked protein glycosylation was originally thought to be specific to eukaryotes, but evidence of this post-translational modification has now been discovered across all domains of life: Eucarya, Bacteria, and Archaea. In all cases, the glycans are first assembled in a step-wise manner on a polyisoprenoid carrier lipid. At some stage of lipid-linked oligosaccharide synthesis, the glycan is flipped across a membrane. Subsequently, the completed glycan is transferred to specific asparagine residues on the protein of interest. Interestingly, though the N-glycosylation pathway seems to be conserved, the biosynthetic pathways of the polyisoprenoid carriers, the specific structures of the carriers, and the glycan residues added to the carriers vary widely. In this review we will elucidate how organisms in each basic domain of life synthesize the polyisoprenoids that they utilize for N-linked glycosylation and briefly discuss the subsequent modifications of the lipid to generate a lipid-linked oligosaccharide.

Uncovering metabolic pathways relevant to phenotypic traits of microbial genomes

Identifying the biochemical basis of microbial phenotypes is a main objective of comparative genomics. Here we present a novel method using multivariate machine learning techniques for comparing automatically derived metabolic reconstructions of sequenced genomes on a large scale. Applying our method to 266 genomes directly led to testable hypotheses such as the link between the potential of microorganisms to cause periodontal disease and their ability to degrade histidine, a link also supported by clinical studies.

Methanogens with pseudomurein use diaminopimelate aminotransferase in lysine biosynthesis

Methanothermobacter thermautotrophicus uses lysine for both protein synthesis and cross-linking pseudomurein in its cell wall. A diaminopimelate aminotransferase enzyme from this methanogen (MTH0052) converts tetrahydrodipicolinate to l,l-diaminopimelate, a lysine precursor. This gene complemented an Escherichia coli diaminopimelate auxotrophy, and the purified protein catalyzed the transamination of diaminopimelate to tetrahydrodipicolinate. Phylogenetic analysis indicated this gene was recruited from anaerobic Gram-positive bacteria. These results expand the family of diaminopimelate aminotransferases to a diverse set of plant, bacterial and archaeal homologs. In contrast marine methanogens from the Methanococcales, which lack pseudomurein, appear to use a different diaminopimelate pathway for lysine biosynthesis.

Promiscuous anaerobes: new and unconventional metabolism in methanogenic archaea

The development of an oxygenated atmosphere on earth resulted in the polarization of life into two major groups, those that could live in the presence of oxygen and those that could not-the aerobes and the anaerobes. The evolution of aerobes from the earliest anaerobic prokaryotes resulted in a variety of metabolic adaptations. Many of these adaptations center on the need to sustain oxygen-sensitive reactions and cofactors to function in the new oxygen-containing atmosphere. Still other metabolic pathways that were not sensitive to oxygen also diverged. This is likely due to the physical separation of the organisms, based on their ability to live in the presence of oxygen, which allowed for the independent evolution of the pathways. Through the study of metabolic pathways in anaerobes and comparison to the more established pathways from aerobes, insight into metabolic evolution can be gained. This, in turn, can allow for extra- polation to those metabolic pathways occurring in the Last Universal Common Ancestor (LUCA). Some of the unique and uncanonical metabolic pathways that have been identified in the archaea with emphasis on the biochemistry of an obligate anaerobic methanogen, Methanocaldococcus jannaschii are reviewed.

The primordial metabolism: an ancestral interconnection between leucine, arginine, and lysine biosynthesis

BACKGROUND

It is generally assumed that primordial cells had small genomes with simple genes coding for enzymes able to react with a wide range of chemically related substrates, interconnecting different metabolic routes. New genes coding for enzymes with a narrowed substrate specificity arose by paralogous duplication(s) of ancestral ones and evolutionary divergence. In this way new metabolic pathways were built up by primordial cells. Useful hints to disclose the origin and evolution of ancestral metabolic routes and their interconnections can be obtained by comparing sequences of enzymes involved in the same or different metabolic routes. From this viewpoint, the lysine, arginine, and leucine biosynthetic routes represent very interesting study-models. Some of the lys, arg and leu genes are paralogs; this led to the suggestion that their ancestor genes might interconnect the three pathways. The aim of this work was to trace the evolutionary pathway leading to the appearance of the extant biosynthetic routes and to try to disclose the interrelationships existing between them and other pathways in the early stages of cellular evolution.

RESULTS

The comparative analysis of the genes involved in the biosynthesis of lysine, leucine, and arginine, their phylogenetic distribution and analysis revealed that the extant metabolic "grids" and their interrelationships might be the outcome of a cascade of duplication of ancestral genes that, according to the patchwork hypothesis, coded for unspecific enzymes able to react with a wide range of substrates. These genes belonged to a single common pathway in which the three biosynthetic routes were highly interconnected between them and also to methionine, threonine, and cell wall biosynthesis. A possible evolutionary model leading to the extant metabolic scenarios was also depicted.

CONCLUSION

The whole body of data obtained in this work suggests that primordial cells synthesized leucine, lysine, and arginine through a single common metabolic pathway, whose genes underwent a set of duplication events, most of which can have predated the appearance of the last common universal ancestor of the three cell domains (Archaea, Bacteria, and Eucaryotes). The model proposes a relative timing for the appearance of the three routes and also suggests a possible evolutionary pathway for the assembly of bacterial cell-wall.

Comparative genomics of bacterial and plant folate synthesis and salvage: predictions and validations

BACKGROUND

Folate synthesis and salvage pathways are relatively well known from classical biochemistry and genetics but they have not been subjected to comparative genomic analysis. The availability of genome sequences from hundreds of diverse bacteria, and from Arabidopsis thaliana, enabled such an analysis using the SEED database and its tools. This study reports the results of the analysis and integrates them with new and existing experimental data.

RESULTS

Based on sequence similarity and the clustering, fusion, and phylogenetic distribution of genes, several functional predictions emerged from this analysis. For bacteria, these included the existence of novel GTP cyclohydrolase I and folylpolyglutamate synthase gene families, and of a trifunctional p-aminobenzoate synthesis gene. For plants and bacteria, the predictions comprised the identities of a 'missing' folate synthesis gene (folQ) and of a folate transporter, and the absence from plants of a folate salvage enzyme. Genetic and biochemical tests bore out these predictions.

CONCLUSION

For bacteria, these results demonstrate that much can be learnt from comparative genomics, even for well-explored primary metabolic pathways. For plants, the findings particularly illustrate the potential for rapid functional assignment of unknown genes that have prokaryotic homologs, by analyzing which genes are associated with the latter. More generally, our data indicate how combined genomic analysis of both plants and prokaryotes can be more powerful than isolated examination of either group alone.

Characterization of cofactor-dependent and cofactor-independent phosphoglycerate mutases from Archaea

Phosphoglycerate mutases (PGM) catalyze the reversible conversion of 3-phosphoglycerate and 2-phosphoglycerate as part of glycolysis and gluconeogenesis. Two structural and mechanistically unrelated types of PGMs are known, a cofactor (2,3-bisphosphoglycerate)-dependent (dPGM) and a cofactor-independent enzyme (iPGM). Here, we report the characterization of the first archaeal cofactor-dependent PGM from Thermoplasma acidophilum, which is encoded by ORF TA1347. This ORF was cloned and expressed in Escherichia coli and the recombinant protein was characterized as functional dPGM. The enzyme constitutes a 46 kDa homodimeric protein. Enzyme activity required 2,3-bisphosphoglycerate as cofactor and was inhibited by vanadate, a specific inhibitor of dPGMs in bacteria and eukarya; inhibition could be partially relieved by EDTA. Histidine 23 of the archaeal dPGM of T. acidophilum, which corresponds to active site histidine in dPGMs from bacteria and eukarya, was exchanged for alanine by site directed mutagenesis. The H23A mutant was catalytically inactive supporting the essential role of H23 in catalysis of the archaeal dPGM. Further, an archaeal cofactor-independent PGM encoded by ORF AF1751 from the hyperthermophilic sulfate reducer Archaeoglobus fulgidus was characterized after expression in E. coli. The monomeric 46 kDa protein showed cofactor-independent PGM activity and was stimulated by Mn(2+) and exhibited high thermostability up to 70 degrees C. A comprehensive phylogenetic analysis of both types of archaeal phosphoglycerate mutases is also presented.

Insights into the autotrophic CO2 fixation pathway of the archaeon Ignicoccus hospitalis: comprehensive analysis of the central carbon metabolism

Ignicoccus hospitalis is an autotrophic hyperthermophilic archaeon that serves as a host for another parasitic/symbiotic archaeon, Nanoarchaeum equitans. In this study, the biosynthetic pathways of I. hospitalis were investigated by in vitro enzymatic analyses, in vivo (13)C-labeling experiments, and genomic analyses. Our results suggest the operation of a so far unknown pathway of autotrophic CO(2) fixation that starts from acetyl-coenzyme A (CoA). The cyclic regeneration of acetyl-CoA, the primary CO(2) acceptor molecule, has not been clarified yet. In essence, acetyl-CoA is converted into pyruvate via reductive carboxylation by pyruvate-ferredoxin oxidoreductase. Pyruvate-water dikinase converts pyruvate into phosphoenolpyruvate (PEP), which is carboxylated to oxaloacetate by PEP carboxylase. An incomplete citric acid cycle is operating: citrate is synthesized from oxaloacetate and acetyl-CoA by a (re)-specific citrate synthase, whereas a 2-oxoglutarate-oxidizing enzyme is lacking. Further investigations revealed that several special biosynthetic pathways that have recently been described for various archaea are operating. Isoleucine is synthesized via the uncommon citramalate pathway and lysine via the alpha-aminoadipate pathway. Gluconeogenesis is achieved via a reverse Embden-Meyerhof pathway using a novel type of fructose 1,6-bisphosphate aldolase. Pentosephosphates are formed from hexosephosphates via the suggested ribulose-monophosphate pathway, whereby formaldehyde is released from C-1 of hexose. The organism may not contain any sugar-metabolizing pathway. This comprehensive analysis of the central carbon metabolism of I. hospitalis revealed further evidence for the unexpected and unexplored diversity of metabolic pathways within the (hyperthermophilic) archaea.

A subsystems-based approach to the identification of drug targets in bacterial pathogens

This chapter describes a three-stage approach to target identification based upon subsystem analysis. Subsystems analysis focuses on related metabolic pathways as a unit and is a biochemically-informed approach to target selection. The process involves three stages of analysis; the first stage, selection of the target subsystem, is guided by information about its essentiality and on the predicted vulnerability of the targeted pathway or enzyme to inhibition. The second stage involves analysis of the target subsystem by means of comparative genomics, including genome context analysis and metabolic reconstruction. The third stage evaluates the selection of the specific target genes within the subsystem by target prioritization and validation. The whole process allows for a careful consideration of spectrum, drugability, biological rationale and the metabolic role of the specific target within the context of an integrated circuit within a specific metabolic pathway.

Identification of genes encoding tRNA modification enzymes by comparative genomics

As the molecular adapters between codons and amino acids, transfer-RNAs are pivotal molecules of the genetic code. The coding properties of a tRNA molecule do not reside only in its primary sequence. Posttranscriptional nucleoside modifications, particularly in the anticodon loop, can modify cognate codon recognition, affect aminoacylation properties, or stabilize the codon-anticodon wobble base pairing to prevent ribosomal frameshifting. Despite a wealth of biophysical and structural knowledge of the tRNA modifications themselves, their pathways of biosynthesis had been until recently only partially characterized. This discrepancy was mainly due to the lack of obvious phenotypes for tRNA modification-deficient strains and to the difficulty of the biochemical assays used to detect tRNA modifications. However, the availability of hundreds of whole-genome sequences has allowed the identification of many of these missing tRNA-modification genes. This chapter reviews the methods that were used to identify these genes with a special emphasis on the comparative genomic approaches. Methods that link gene and function but do not rely on sequence homology will be detailed, with examples taken from the tRNA modification field.

Biosynthesis of phosphoserine in the Methanococcales

Methanococcus maripaludis and Methanocaldococcus jannaschii produce cysteine for protein synthesis using a tRNA-dependent pathway. These methanogens charge tRNA(Cys) with l-phosphoserine, which is also an intermediate in the predicted pathways for serine and cystathionine biosynthesis. To establish the mode of phosphoserine production in Methanococcales, cell extracts of M. maripaludis were shown to have phosphoglycerate dehydrogenase and phosphoserine aminotransferase activities. The heterologously expressed and purified phosphoglycerate dehydrogenase from M. maripaludis had enzymological properties similar to those of its bacterial homologs but was poorly inhibited by serine. While bacterial enzymes are inhibited by micromolar concentrations of serine bound to an allosteric site, the low sensitivity of the archaeal protein to serine is consistent with phosphoserine's position as a branch point in several pathways. A broad-specificity class V aspartate aminotransferase from M. jannaschii converted the phosphohydroxypyruvate product to phosphoserine. This enzyme catalyzed the transamination of aspartate, glutamate, phosphoserine, alanine, and cysteate. The M. maripaludis homolog complemented a serC mutation in the Escherichia coli phosphoserine aminotransferase. All methanogenic archaea apparently share this pathway, providing sufficient phosphoserine for the tRNA-dependent cysteine biosynthetic pathway.

Methanocaldococcus jannaschii uses a modified mevalonate pathway for biosynthesis of isopentenyl diphosphate

Archaea have been shown to produce isoprenoids from mevalonate; however, genome analysis has failed to identify several genes in the mevalonate pathway on the basis of sequence similarity. A predicted archaeal kinase, coded for by the MJ0044 gene, was associated with other mevalonate pathway genes in the archaea and was predicted to be the "missing" phosphomevalonate kinase. The MJ0044-derived protein was tested for phosphomevalonate kinase activity and was found not to catalyze this reaction. The MJ0044 gene product was found to phosphorylate isopentenyl phosphate, generating isopentenyl diphosphate. Unlike other known kinases associated with isoprene biosynthesis, Methanocaldococcus jannaschii isopentenyl phosphate kinase is predicted to be a member of the aspartokinase superfamily.

Comparative genomics of NAD biosynthesis in cyanobacteria

Biosynthesis of NAD(P) cofactors is of special importance for cyanobacteria due to their role in photosynthesis and respiration. Despite significant progress in understanding NAD(P) biosynthetic machinery in some model organisms, relatively little is known about its implementation in cyanobacteria. We addressed this problem by a combination of comparative genome analysis with verification experiments in the model system of Synechocystis sp. strain PCC 6803. A detailed reconstruction of the NAD(P) metabolic subsystem using the SEED genomic platform (http://theseed.uchicago.edu/FIG/index.cgi) helped us accurately annotate respective genes in the entire set of 13 cyanobacterial species with completely sequenced genomes available at the time. Comparative analysis of operational variants implemented in this divergent group allowed us to elucidate both conserved (de novo and universal pathways) and variable (recycling and salvage pathways) aspects of this subsystem. Focused genetic and biochemical experiments confirmed several conjectures about the key aspects of this subsystem. (i) The product of the slr1691 gene, a homolog of Escherichia coli gene nadE containing an additional nitrilase-like N-terminal domain, is a NAD synthetase capable of utilizing glutamine as an amide donor in vitro. (ii) The product of the sll1916 gene, a homolog of E. coli gene nadD, is a nicotinic acid mononucleotide-preferring adenylyltransferase. This gene is essential for survival and cannot be compensated for by an alternative nicotinamide mononucleotide (NMN)-preferring adenylyltransferase (slr0787 gene). (iii) The product of the slr0788 gene is a nicotinamide-preferring phosphoribosyltransferase involved in the first step of the two-step non-deamidating utilization of nicotinamide (NMN shunt). (iv) The physiological role of this pathway encoded by a conserved gene cluster, slr0787-slr0788, is likely in the recycling of endogenously generated nicotinamide, as supported by the inability of this organism to utilize exogenously provided niacin. Positional clustering and the co-occurrence profile of the respective genes across a diverse collection of cellular organisms provide evidence of horizontal transfer events in the evolutionary history of this pathway.

Role of the precorrin 6-X reductase gene in cobamide biosynthesis in Methanococcus maripaludis

In Methanococcus maripaludis strain JJ, deletion of the homolog to cbiJ, which encodes the corrin biosynthetic enzyme precorrin 6-X reductase, yielded an auxotroph that required either cobamide or acetate for good growth. This phenotype closely resembled that of JJ117, a mutant in which tandem repeats were introduced into the region immediately downstream of the homolog of cbiJ. Mutant JJ117 also produced low quantities of cobamides, about 15 nmol g(-1) protein or 1-2% of the amount found in wild-type cells. These results confirm the role of the cbiJ homolog in cobamide biosynthesis in the Archaea and suggest the presence of low amounts of a bypass activity in these organisms.

PUMA2--grid-based high-throughput analysis of genomes and metabolic pathways

The PUMA2 system (available at ) is an interactive, integrated bioinformatics environment for high-throughput genetic sequence analysis and metabolic reconstructions from sequence data. PUMA2 provides a framework for comparative and evolutionary analysis of genomic data and metabolic networks in the context of taxonomic and phenotypic information. Grid infrastructure is used to perform computationally intensive tasks. PUMA2 currently contains precomputed analysis of 213 prokaryotic, 22 eukaryotic, 650 mitochondrial and 1493 viral genomes and automated metabolic reconstructions for >200 organisms. Genomic data is annotated with information integrated from >20 sequence, structural and metabolic databases and ontologies. PUMA2 supports both automated and interactive expert-driven annotation of genomes, using a variety of publicly available bioinformatics tools. It also contains a suite of unique PUMA2 tools for automated assignment of gene function, evolutionary analysis of protein families and comparative analysis of metabolic pathways. PUMA2 allows users to submit batch sequence data for automated functional analysis and construction of metabolic models. The results of these analyses are made available to the users in the PUMA2 environment for further interactive sequence analysis and annotation.

PathAligner: metabolic pathway retrieval and alignment

MOTIVATION

Analysis of metabolic pathways is a central topic in understanding the relationship between genotype and phenotype. The rapid accumulation of biological data provides the possibility of studying metabolic pathways at both the genomic and the metabolic levels. Retrieving metabolic pathways from current biological data sources, reconstructing metabolic pathways from rudimentary pathway components, and aligning metabolic pathways with each other are major tasks. Our motivation was to develop a conceptual framework and computational system that allows the retrieval of metabolic pathway information and the processing of alignments to reveal the similarities between metabolic pathways.

RESULTS

PathAligner extracts metabolic information from biological databases via the Internet and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites etc. It provides an easy-to-use interface to retrieve, display and manipulate metabolic information. PathAligner also provides an alignment method to compare the similarity between metabolic pathways.

AVAILABILITY

PathAligner is available at http://bibiserv.techfak.uni-bielefeld.de/pathaligner.

Ribose-5-phosphate biosynthesis in Methanocaldococcus jannaschii occurs in the absence of a pentose-phosphate pathway

Recent work has raised a question as to the involvement of erythrose-4-phosphate, a product of the pentose phosphate pathway, in the metabolism of the methanogenic archaea (R. H. White, Biochemistry 43:7618-7627, 2004). To address the possible absence of erythrose-4-phosphate in Methanocaldococcus jannaschii, we have assayed cell extracts of this methanogen for the presence of this and other intermediates in the pentose phosphate pathway and have determined and compared the labeling patterns of sugar phosphates derived metabolically from [6,6-2H2]- and [U-13C]-labeled glucose-6-phosphate incubated with cell extracts. The results of this work have established the absence of pentose phosphate pathway intermediates erythrose-4-phosphate, xylose-5-phosphate, and sedoheptulose-7-phosphate in these cells and the presence of D-arabino-3-hexulose-6-phosphate, an intermediate in the ribulose monophosphate pathway. The labeling of the D-ara-bino-3-hexulose-6-phosphate, as well as the other sugar-Ps, indicates that this hexose-6-phosphate was the precursor to ribulose-5-phosphate that in turn was converted into ribose-5-phosphate by ribose-5-phosphate isomerase. Additional work has demonstrated that ribulose-5-phosphate is derived by the loss of formaldehyde from D-arabino-3-hexulose-6-phosphate, catalyzed by the protein product of the MJ1447 gene.

Inferring meaningful pathways in weighted metabolic networks

An approach is presented for computing meaningful pathways in the network of small molecule metabolism comprising the chemical reactions characterized in all organisms. The metabolic network is described as a weighted graph in which all the compounds are included, but each compound is assigned a weight equal to the number of reactions in which it participates. Path finding is performed in this graph by searching for one or more paths with lowest weight. Performance is evaluated systematically by computing paths between the first and last reactions in annotated metabolic pathways, and comparing the intermediate reactions in the computed pathways to those in the annotated ones. For the sake of comparison, paths are computed also in the un-weighted raw (all compounds and reactions) and filtered (highly connected pool metabolites removed) metabolic graphs, respectively. The correspondence between the computed and annotated pathways is very poor (<30%) in the raw graph; increasing to approximately 65% in the filtered graph; reaching approximately 85% in the weighted graph. Considering the best-matching path among the five lightest paths increases the correspondence to 92%, on average. We then show that the average distance between pairs of metabolites is significantly larger in the weighted graph than in the raw unfiltered graph, suggesting that the small-world properties previously reported for metabolic networks probably result from irrelevant shortcuts through pool metabolites. In addition, we provide evidence that the length of the shortest path in the weighted graph represents a valid measure of the "metabolic distance" between enzymes. We suggest that the success of our simplistic approach is rooted in the high degree of specificity of the reactions in metabolic pathways, presumably reflecting thermodynamic constraints operating in these pathways. We expect our approach to find useful applications in inferring metabolic pathways in newly sequenced genomes.

Automated metabolic reconstruction for Methanococcus jannaschii

We present the computational prediction and synthesis of the metabolic pathways in Methanococcus jannaschii from its genomic sequence using the PathoLogic software. Metabolic reconstruction is based on a reference knowledge base of metabolic pathways and is performed with minimal manual intervention. We predict the existence of 609 metabolic reactions that are assembled in 113 metabolic pathways and an additional 17 super-pathways consisting of one or more component pathways. These assignments represent significantly improved enzyme and pathway predictions compared with previous metabolic reconstructions, and some key metabolic reactions, previously missing, have been identified. Our results, in the form of enzymatic assignments and metabolic pathway predictions, form a database (MJCyc) that is accessible over the World Wide Web for further dissemination among members of the scientific community.

Transaldolase of Methanocaldococcus jannaschii

The Methanocaldococcus jannaschii genome contains putative genes for all four nonoxidative pentose phosphate pathway enzymes. Open reading frame (ORF) MJ0960 is a member of the mipB/talC family of 'transaldolase-like' genes, so named because of their similarity to the well-characterized transaldolase B gene family. However, recently, it has been reported that both the mipB and the talC genes from Escherichia coli encode novel enzymes with fructose-6-phosphate aldolase activity, not transaldolase activity (Schürmann and Sprenger 2001). The same study reports that other members of the mipB/talC family appear to encode transaldolases. To confirm the function of MJ0960 and to clarify the presence of a nonoxidative pentose phosphate pathway in M. jannaschii, we have cloned ORF MJ0960 from M. jannaschii genomic DNA and purified the recombinant protein. MJ0960 encodes a transaldolase and displays no fructose-6-phosphate aldolase activity. It etained full activity for 4 h at 80 degrees C, and for 3 weeks at 25 degrees C. Methanocaldococcus jannaschii transaldolase has a maximal velocity (Vmax) of 1.0 +/- 0.2 micromol min(-1) mg(-1) at 25 degrees C, whereas Vmax = 12.0 +/- 0.5 micromol min(-1) mg(-1) at 50 degrees C. Apparent Michaelis constants at 50 degrees C were Km = 0.65 +/- 0.09 mM for fructose-6-phosphate and Km = 27.8 +/- 4.3 microM for erythrose-4-phosphate. When ribose-5-phosphate replaced erythrose-4-phosphate as an aldose acceptor, Vmax decreased twofold, whereas the Km was 150-fold higher. The molecular mass of the active enzyme is 271 +/- 27 kDa as estimated by gel filtration, whereas the predicted monomer size is 23.96 kDa, suggesting that the native form of the protein is probably a decamer. A readily available source of thermophilic pentose phosphate pathway enzymes including transaldolase may have direct application in enzymatic biohydrogen production.

Biosynthesis of ribose-5-phosphate and erythrose-4-phosphate in archaea: a phylogenetic analysis of archaeal genomes

A phylogenetic analysis of the genes encoding enzymes in the pentose phosphate pathway (PPP), the ribulose monophosphate (RuMP) pathway, and the chorismate pathway of aromatic amino acid biosynthesis, employing data from 13 complete archaeal genomes, provides a potential explanation for the enigmatic phylogenetic patterns of the PPP genes in archaea. Genomic and biochemical evidence suggests that three archaeal species (Methanocaldococcus jannaschii, Thermoplasma acidophilum and Thermoplasma volcanium) produce ribose-5-phosphate via the nonoxidative PPP (NOPPP), whereas nine species apparently lack an NOPPP but may employ a reverse RuMP pathway for pentose synthesis. One species (Halobacterium sp. NRC-1) lacks both the NOPPP and the RuMP pathway but may possess a modified oxidative PPP (OPPP), the details of which are not yet known. The presence of transketolase in several archaeal species that are missing the other two NOPPP genes can be explained by the existence of differing requirements for erythrose-4-phosphate (E4P) among archaea: six species use transketolase to make E4P as a precursor to aromatic amino acids, six species apparently have an alternate biosynthetic pathway and may not require the ability to make E4P, and one species (Pyrococcus horikoshii) probably does not synthesize aromatic amino acids at all.

metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux system and requires only a set of raw DNA sequences (genomic, expressed sequence tag and/or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10(-20), our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5x to 7.5x. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella.

Web-based information retrieval system for the prediction of metabolic pathways

Analysis of metabolic pathways is a central topic in understanding the relationship between genotype and phenotype. The rapid accumulation of biological data provides the possibility of studying metabolic pathways both at the genomic and metabolic levels. Our motivation is to develop a conceptual framework and computational system that will allow retrieval of metabolic information and prediction of metabolic pathways. In this paper, we introduce a metabolic pathway prediction framework that extracts metabolic information from biological databases via the Internet, and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites, etc. It provides an easy-to-use interface to retrieve, display, and manipulate metabolic information. The system has been implemented into PathAligner, available at http://bibiserv.techfak.uni-bielefeld. de/pathaligner/.

A Methanocaldococcus jannaschii archaeal signature gene encodes for a 5-formaminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate synthetase. A new enzyme in purine biosynthesis

We have identified and characterized a new member of the ATP-grasp enzyme family that catalyzes the ATP- and formate-dependent formylation of 5-aminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate (AICAR) to 5-formaminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate (FAICAR) in the absence of folates. The enzyme, which we designate as PurP, is the product of the Methanocaldococcus jannaschii purP gene (MJ0136), which is a signature gene for Archaea. As is characteristic of reactions catalyzed by this family of enzymes, the other products of the reaction, ADP and P(i), were produced stoichiometrically with the amount of ATP, formate, and AICAR used. Formyl phosphate was found to substitute for ATP and formate in the reaction, yet the methylene analog, phosphonoacetaldehyde, was not an inhibitor or substrate for the reaction. The enzyme, along with PurO, which catalyzes the cyclization of FAICAR to inosine 5'-monophosphate, catalyzes the same overall transformation in purine biosynthesis as is accomplished by PurH in bacteria and eukaryotes. No homology exists between PurH and either PurO or PurP. 1H NMR and gas chromatography-mass spectrometry analysis of an M. jannaschii cell extract showed the presence of free formate that can be used by the enzyme for purine biosynthesis. This formate arises by the reduction of CO2 with hydrogen; this was demonstrated by incorporating 13C into the formate when M. jannaschii cell extracts were incubated with H13CO3- and hydrogen gas. The presence of this signature gene in all of the Archaea indicates the presence of a purine biosynthetic pathway proceeding in the absence of folate coenzymes.

A novel method for visualizing nuclear hormone receptor networks relevant to drug metabolism

The increasing generation of biological data represents a challenge to understanding the complexity of systems, resulting in scientists increasingly focused on a relatively narrow area of study, thereby limiting insight that can be gained from a broader perspective. In the field of drug metabolism and toxicology we are witnessing the characterization of many proteins. Most of the key enzymes and transporters are recognized as transcriptionally regulated by the nuclear hormone receptors such as pregnane X receptor, constitutive androstane receptor, vitamin D receptor, glucocorticoid receptor, and others. There is apparent cross talk in regulation, since multiple receptors may modulate expression of a single enzyme or transporter, representing one of many areas of active research interest. We have used published data on nuclear hormone receptors, enzymes, ligands, and other biological information to manually annotate an Oracle database, forming the basis of a platform for querying (MetaDrug). Using algorithms, we have demonstrated how nuclear hormone receptors alone can form a network of direct interactions, and when expanded, this network increases in complexity to describe the interactions with target genes as well as small molecules known to bind a receptor, enzyme, or transporter. We have also described how the database can be used for visualizing high-throughput microarray data derived from a published study of MCF-7 cells treated with 4-hydroxytamoxifen, to highlight potential downstream effects of molecule treatment. The database represents a novel knowledge mining and analytical tool that, to be relevant, requires continual updating to evolve alongside other key storage systems and sources of biological knowledge.

Complete genome sequence of the genetically tractable hydrogenotrophic methanogen Methanococcus maripaludis

The genome sequence of the genetically tractable, mesophilic, hydrogenotrophic methanogen Methanococcus maripaludis contains 1,722 protein-coding genes in a single circular chromosome of 1,661,137 bp. Of the protein-coding genes (open reading frames [ORFs]), 44% were assigned a function, 48% were conserved but had unknown or uncertain functions, and 7.5% (129 ORFs) were unique to M. maripaludis. Of the unique ORFs, 27 were confirmed to encode proteins by the mass spectrometric identification of unique peptides. Genes for most known functions and pathways were identified. For example, a full complement of hydrogenases and methanogenesis enzymes was identified, including eight selenocysteine-containing proteins, with each being paralogous to a cysteine-containing counterpart. At least 59 proteins were predicted to contain iron-sulfur centers, including ferredoxins, polyferredoxins, and subunits of enzymes with various redox functions. Unusual features included the absence of a Cdc6 homolog, implying a variation in replication initiation, and the presence of a bacterial-like RNase HI as well as an RNase HII typical of the Archaea. The presence of alanine dehydrogenase and alanine racemase, which are uniquely present among the Archaea, explained the ability of the organism to use L- and D-alanine as nitrogen sources. Features that contrasted with the related organism Methanocaldococcus jannaschii included the absence of inteins, even though close homologs of most intein-containing proteins were encoded. Although two-thirds of the ORFs had their highest Blastp hits in Methanocaldococcus jannaschii, lateral gene transfer or gene loss has apparently resulted in genes, which are often clustered, with top Blastp hits in more distantly related groups.

Two biosynthetic pathways for aromatic amino acids in the archaeon Methanococcus maripaludis

Methanococcus maripaludis is a strictly anaerobic, methane-producing archaeon. Aromatic amino acids (AroAAs) are biosynthesized in this autotroph either by the de novo pathway, with chorismate as an intermediate, or by the incorporation of exogenous aryl acids via indolepyruvate oxidoreductase (IOR). In order to evaluate the roles of these pathways, the gene that encodes the third step in the de novo pathway, 3-dehydroquinate dehydratase (DHQ), was deleted. This mutant required all three AroAAs for growth, and no DHQ activity was detectible in cell extracts, compared to 6.0 +/- 0.2 mU mg(-1) in the wild-type extract. The growth requirement for the AroAAs could be fulfilled by the corresponding aryl acids phenylacetate, indoleacetate, and p-hydroxyphenylacetate. The specific incorporation of phenylacetate into phenylalanine by the IOR pathway was demonstrated in vivo by labeling with [1-(13)C]phenylacetate. M. maripaludis has two IOR homologs. A deletion mutant for one of these homologs contained 76, 74, and 42% lower activity for phenylpyruvate, p-hydoxyphenylpyruvate, and indolepyruvate oxidation, respectively, than the wild type. Growth of this mutant in minimal medium was inhibited by the aryl acids, but the AroAAs partially restored growth. Genetic complementation of the IOR mutant also restored much of the wild-type phenotype. Thus, aryl acids appear to regulate the expression or activity of the de novo pathway. The aryl acids did not significantly inhibit the activity of the biosynthetic enzymes chorismate mutase, prephenate dehydratase, and prephenate dehydrogenase in cell extracts, so the inhibition of growth was probably not due to an effect on these enzymes.

Metabolic database systems for the analysis of genome-wide function

Genome sequencing projects provide an inventory of molecular components for a wide variety of organisms. Metabolic databases integrate these functional descriptions of individual modules into a higher-level characterization of cellular metabolism. This article reviews efforts related to the development of metabolic databases and discusses how such systems have aided the delineation of genome properties. We illustrate the design features of metabolic databases and discuss the challenges facing metabolic as well as databases of other functional type.

Reconstruction of the central carbohydrate metabolism of Thermoproteus tenax by use of genomic and biochemical data

The hyperthermophilic, facultatively heterotrophic crenarchaeum Thermoproteus tenax was analyzed using a low-coverage shotgun-sequencing approach. A total of 1.81 Mbp (representing 98.5% of the total genome), with an average gap size of 100 bp and 5.3-fold coverage, are reported, giving insights into the genome of T. tenax. Genome analysis and biochemical studies enabled us to reconstruct its central carbohydrate metabolism. T. tenax uses a variant of the reversible Embden-Meyerhof-Parnas (EMP) pathway and two different variants of the Entner-Doudoroff (ED) pathway (a nonphosphorylative variant and a semiphosphorylative variant) for carbohydrate catabolism. For the EMP pathway some new, unexpected enzymes were identified. The semiphosphorylative ED pathway, hitherto supposed to be active only in halophiles, is found in T. tenax. No evidence for a functional pentose phosphate pathway, which is essential for the generation of pentoses and NADPH for anabolic purposes in bacteria and eucarya, is found in T. tenax. Most genes involved in the reversible citric acid cycle were identified, suggesting the presence of a functional oxidative cycle under heterotrophic growth conditions and a reductive cycle for CO2 fixation under autotrophic growth conditions. Almost all genes necessary for glycogen and trehalose metabolism were identified in the T. tenax genome.

Shotgun Proteomics of Methanococcus jannaschii and Insights into Methanogenesis

Methanococcus jannaschii is an autotrophic hyperthermophilic archaeon isolated from an oceanic hydrothermal vent. Its primary pathway for energy production is methanogenesis from H2 and CO2. High-throughput Multidimensional Protein Identification Technology based on microcapillary LC/LC/ MS/MS was used to investigate the proteome of M. jannaschii and the methanogenesis pathway in cells grown in complex medium with high H2 supply. A total of 963 proteins have been unambiguously identified. The identified proteins represent approximately 54% of the whole genome of M. jannaschii. About 44% of the identified proteins are either conserved hypothetical or hypothetical proteins. We identified 83-95% of the proteins predicted to be involved in amino acid biosynthesis, cellular processes, central intermediary metabolism, energy metabolism, protein synthesis, transcription, and purine, pyridine, nucleoside, and nucleotide synthesis. Over 40% of these proteins have better than 50% sequence coverage. Approximately 90% of the predicted methanogenesis proteins were detected. In contrast, only 27-37% of predicted hypothetical proteins, proteins involved in transport and binding, and proteins with regulatory functions were identified. High peptide number, spectrum count, and sequence coverage have been used as indicators of high expression levels and are in good agreement with codon bias analysis. Predicted intein peptides were detected in MJ1043 (DNA-directed RNA polymerase, subunit A"), MJ0542 (phosphoenolpyruvate synthase), MJ0782 (transcription initiation factor IIB), and MJ1422 (putative replication factor C subunit). New peptides created by protein splicing were detected in MJ0885 (DNA dependent DNA polymerase), MJ0542, and MJ0782. The methanogenesis pathway and the enzymes involved are also discussed.

Description and interpretation of adaptive evolution of Escherichia coli K-12 MG1655 by using a genome-scale in silico metabolic model

Genome-scale in silico metabolic networks of Escherichia coli have been reconstructed. By using a constraint-based in silico model of a reconstructed network, the range of phenotypes exhibited by E. coli under different growth conditions can be computed, and optimal growth phenotypes can be predicted. We hypothesized that the end point of adaptive evolution of E. coli could be accurately described a priori by our in silico model since adaptive evolution should lead to an optimal phenotype. Adaptive evolution of E. coli during prolonged exponential growth was performed with M9 minimal medium supplemented with 2 g of alpha-ketoglutarate per liter, 2 g of lactate per liter, or 2 g of pyruvate per liter at both 30 and 37 degrees C, which produced seven distinct strains. The growth rates, substrate uptake rates, oxygen uptake rates, by-product secretion patterns, and growth rates on alternative substrates were measured for each strain as a function of evolutionary time. Three major conclusions were drawn from the experimental results. First, adaptive evolution leads to a phenotype characterized by maximized growth rates that may not correspond to the highest biomass yield. Second, metabolic phenotypes resulting from adaptive evolution can be described and predicted computationally. Third, adaptive evolution on a single substrate leads to changes in growth characteristics on other substrates that could signify parallel or opposing growth objectives. Together, the results show that genome-scale in silico metabolic models can describe the end point of adaptive evolution a priori and can be used to gain insight into the adaptive evolutionary process for E. coli.

Diversity, taxonomy and evolution of medium-chain dehydrogenase/reductase superfamily

A comprehensive, structural and functional, in silico analysis of the medium-chain dehydrogenase/reductase (MDR) superfamily, including 583 proteins, was carried out by use of extensive database mining and the blastp program in an iterative manner to identify all known members of the superfamily. Based on phylogenetic, sequence, and functional similarities, the protein members of the MDR superfamily were classified into three different taxonomic categories: (a) subfamilies, consisting of a closed group containing a set of ideally orthologous proteins that perform the same function; (b) families, each comprising a cluster of monophyletic subfamilies that possess significant sequence identity among them and might share or not common substrates or mechanisms of reaction; and (c) macrofamilies, each comprising a cluster of monophyletic protein families with protein members from the three domains of life, which includes at least one subfamily member that displays activity related to a very ancient metabolic pathway. In this context, a superfamily is a group of homologous protein families (and/or macrofamilies) with monophyletic origin that shares at least a barely detectable sequence similarity, but showing the same 3D fold. The MDR superfamily encloses three macrofamilies, with eight families and 49 subfamilies. These subfamilies exhibit great functional diversity including noncatalytic members with different subcellular, phylogenetic, and species distributions. This results from constant enzymogenesis and proteinogenesis within each kingdom, and highlights the huge plasticity that MDR superfamily members possess. Thus, through evolution a great number of taxa-specific new functions were acquired by MDRs. The generation of new functions fulfilled by proteins, can be considered as the essence of protein evolution. The mechanisms of protein evolution inside MDR are not constrained to conserve substrate specificity and/or chemistry of catalysis. In consequence, MDR functional diversity is more complex than sequence diversity. MDR is a very ancient protein superfamily that existed in the last universal common ancestor. It had at least two (and probably three) different ancestral activities related to formaldehyde metabolism and alcoholic fermentation. Eukaryotic members of this superfamily are more related to bacterial than to archaeal members; horizontal gene transfer among the domains of life appears to be a rare event in modern organisms.

Potential genomic determinants of hyperthermophily

We searched for genes that could be important for hyperthermophily using a flexible approach to phyletic pattern analysis. We identified 290 clusters of orthologous groups of proteins (COGs) that are preferentially present in archaeal and bacterial hyperthermophiles. Of these, 58 COGs include proteins from at least one bacterium and two archaea, and these were considered to be the best candidates for a specific association with the hyperthermophilic phenotype. Detailed sequence and genome-context analysis of these COGs led to functional predictions for several previously uncharacterized protein families, including a novel group of putative molecular chaperones and a unique transcriptional regulator.

Metabolomics in systems biology

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems. For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology. The aim of this review is to (a) provide an in-depth overview about metabolomic technology, (b) explore how metabolomic networks can be connected to the underlying reaction pathway structure, and (c) discuss the need to investigate integrative biochemical networks.

Ribosylnicotinamide kinase domain of NadR protein: identification and implications in NAD biosynthesis

NAD is an indispensable redox cofactor in all organisms. Most of the genes required for NAD biosynthesis in various species are known. Ribosylnicotinamide kinase (RNK) was among the few unknown (missing) genes involved with NAD salvage and recycling pathways. Using a comparative genome analysis involving reconstruction of NAD metabolism from genomic data, we predicted and experimentally verified that bacterial RNK is encoded within the 3' region of the nadR gene. Based on these results and previous data, the full-size multifunctional NadR protein (as in Escherichia coli) is composed of (i) an N-terminal DNA-binding domain involved in the transcriptional regulation of NAD biosynthesis, (ii) a central nicotinamide mononucleotide adenylyltransferase (NMNAT) domain, and (iii) a C-terminal RNK domain. The RNK and NMNAT enzymatic activities of recombinant NadR proteins from Salmonella enterica serovar Typhimurium and Haemophilus influenzae were quantitatively characterized. We propose a model for the complete salvage pathway from exogenous N-ribosylnicotinamide to NAD which involves the concerted action of the PnuC transporter and NRK, followed by the NMNAT activity of the NadR protein. Both the pnuC and nadR genes were proven to be essential for the growth and survival of H. influenzae, thus implicating them as potential narrow-spectrum drug targets.

Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth

Annotated genome sequences can be used to reconstruct whole-cell metabolic networks. These metabolic networks can be modelled and analysed (computed) to study complex biological functions. In particular, constraints-based in silico models have been used to calculate optimal growth rates on common carbon substrates, and the results were found to be consistent with experimental data under many but not all conditions. Optimal biological functions are acquired through an evolutionary process. Thus, incorrect predictions of in silico models based on optimal performance criteria may be due to incomplete adaptive evolution under the conditions examined. Escherichia coli K-12 MG1655 grows sub-optimally on glycerol as the sole carbon source. Here we show that when placed under growth selection pressure, the growth rate of E. coli on glycerol reproducibly evolved over 40 days, or about 700 generations, from a sub-optimal value to the optimal growth rate predicted from a whole-cell in silico model. These results open the possibility of using adaptive evolution of entire metabolic networks to realize metabolic states that have been determined a priori based on in silico analysis.

Computational identification of operons in microbial genomes

By applying graph representations to biochemical pathways, a new computational pipeline is proposed to find potential operons in microbial genomes. The algorithm relies on the fact that enzyme genes in operons tend to catalyze successive reactions in metabolic pathways. We applied this algorithm to 42 microbial genomes to identify putative operon structures. The predicted operons from Escherichia coli were compared with a selected metabolism-related operon dataset from the RegulonDB database, yielding a prediction sensitivity (89%) and specificity (87%) relative to this dataset. Several examples of detected operons are given and analyzed. Modular gene cluster transfer and operon fusion are observed. A further use of predicted operon data to assign function to putative genes was suggested and, as an example, a previous putative gene (MJ1604) from Methanococcus jannaschii is now annotated as a phosphofructokinase, which was regarded previously as a missing enzyme in this organism. GC content changes in the operon region and nonoperon region were examined. The results reveal a clear GC content transition at the boundaries of putative operons. We looked further into the conservation of operons across genomes. A trp operon alignment is analyzed in depth to show gene loss and rearrangement in different organisms during operon evolution.

From genetic footprinting to antimicrobial drug targets: examples in cofactor biosynthetic pathways

Novel drug targets are required in order to design new defenses against antibiotic-resistant pathogens. Comparative genomics provides new opportunities for finding optimal targets among previously unexplored cellular functions, based on an understanding of related biological processes in bacterial pathogens and their hosts. We describe an integrated approach to identification and prioritization of broad-spectrum drug targets. Our strategy is based on genetic footprinting in Escherichia coli followed by metabolic context analysis of essential gene orthologs in various species. Genes required for viability of E. coli in rich medium were identified on a whole-genome scale using the genetic footprinting technique. Potential target pathways were deduced from these data and compared with a panel of representative bacterial pathogens by using metabolic reconstructions from genomic data. Conserved and indispensable functions revealed by this analysis potentially represent broad-spectrum antibacterial targets. Further target prioritization involves comparison of the corresponding pathways and individual functions between pathogens and the human host. The most promising targets are validated by direct knockouts in model pathogens. The efficacy of this approach is illustrated using examples from metabolism of adenylate cofactors NAD(P), coenzyme A, and flavin adenine dinucleotide. Several drug targets within these pathways, including three distantly related adenylyltransferases (orthologs of the E. coli genes nadD, coaD, and ribF), are discussed in detail.

Methanococcus jannaschii uses a pyruvoyl-dependent arginine decarboxylase in polyamine biosynthesis

The genome sequence of the hyperthermophilic methanogen Methanococcus jannaschii contains homologs of most genes required for spermidine polyamine biosynthesis. Yet genomes from neither this organism nor any other euryarchaeon have orthologs of the pyridoxal 5'-phosphate-dependent ornithine or arginine decarboxylase genes, required to produce putrescine. Instead, as shown here, these organisms have a new class of arginine decarboxylase (PvlArgDC) formed by the self-cleavage of a proenzyme into a 5-kDa subunit and a 12-kDa subunit that contains a reactive pyruvoyl group. Although this extremely thermostable enzyme has no significant sequence similarity to previously characterized proteins, conserved active site residues are similar to those of the pyruvoyl-dependent histidine decarboxylase enzyme, and its subunits form a similar (alphabeta)(3) complex. Homologs of PvlArgDC are found in several bacterial genomes, including those of Chlamydia spp., which have no agmatine ureohydrolase enzyme to convert agmatine (decarboxylated arginine) into putrescine. In these intracellular pathogens, PvlArgDC may function analogously to pyruvoyl-dependent histidine decarboxylase; the cells are proposed to import arginine and export agmatine, increasing the pH and affecting the host cell's metabolism. Phylogenetic analysis of Pvl- ArgDC proteins suggests that this gene has been recruited from the euryarchaeal polyamine biosynthetic pathway to function as a degradative enzyme in bacteria.