Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis

The annotated full DNA sequence is becoming available for a growing number of organisms. This information along with additional biochemical and strain-specific data can be used to define metabolic genotypes and reconstruct cellular metabolic networks. The first free-living organism for which the entire genomic sequence was established was Haemophilus influenzae. Its metabolic network is reconstructed herein and contains 461 reactions operating on 367 intracellular and 84 extracellular metabolites. With the metabolic reaction network established, it becomes necessary to determine its underlying pathway structure as defined by the set of extreme pathways. The H. influenzae metabolic network was subdivided into six subsystems and the extreme pathways determined for each subsystem based on stoichiometric, thermodynamic, and systems-specific constraints. Positive linear combinations of these pathways can be taken to determine the extreme pathways for the complete system. Since these pathways span the capabilities of the full system, they could be used to address a number of important physiological questions. First, they were used to reconcile and curate the sequence annotation by identifying reactions whose function was not supported in any of the extreme pathways. Second, they were used to predict gene products that should be co-regulated and perhaps co-expressed. Third, they were used to determine the composition of the minimal substrate requirements needed to support the production of 51 required metabolic products such as amino acids, nucleotides, phospholipids, etc. Fourth, sets of critical gene deletions from core metabolism were determined in the presence of the minimal substrate conditions and in more complete conditions reflecting the environmental niche of H. influenzae in the human host. In the former case, 11 genes were determined to be critical while six remained critical under the latter conditions. This study represents an important milestone in theoretical biology, namely the establishment of the first extreme pathway structure of a whole genome.     

Phylogenetic analysis based on genome-scale metabolic pathway reaction content

Phylogenetic classifications based on single genes such as rRNA genes do not provide a complete and accurate picture of evolution because they do not account for evolutionary leaps caused by gene transfer, duplication, deletion and functional replacement. Here, we present a whole-genome-scale phylogeny based on metabolic pathway reaction content. From the genome sequences of 42 microorganisms, we deduced the metabolic pathway reactions and used the relatedness of these contents to construct a phylogenetic tree that represents the similarity of metabolic profiles (relatedness) as well as the extent of metabolic pathway similarity (evolutionary distance). This method accounts for horizontal gene transfer and specific gene loss by comparison of whole metabolic subpathways, and allows evaluation of evolutionary relatedness and changes in metabolic pathways. Thus, a tree based on metabolic pathway content represents both the evolutionary time scale (changes in genetic content) and the evolutionary process (changes in metabolism).     

Detecting and investigating substrate cycles in a genome-scale human metabolic network

Substrate cycles, also known as futile cycles, are cyclic metabolic routes that dissipate energy by hydrolysing cofactors such as ATP. They were first described to occur in the muscles of bumblebees and brown adipose tissue in the 1970s. A popular example is the conversion of fructose?6-phosphate to fructose?1,6-bisphosphate and back. In the present study, we analyze a large number of substrate cycles in human metabolism that consume ATP and discuss their statistics. For this purpose, we use two recently published methods (i.e. EFMEvolver and the K-shortest EFM method) to calculate samples of 100?000 and 15?000 substrate cycles, respectively. We find an unexpectedly high number of substrate cycles in human metabolism, with up to 100 reactions per cycle, utilizing reactions from up to six different compartments. An analysis of tissue-specific models of liver and brain metabolism shows that there is selective pressure that acts against the uncontrolled dissipation of energy by avoiding the coexpression of enzymes belonging to the same substrate cycle. This selective force is particularly strong against futile cycles that have a high flux as a result of thermodynamic principles.     

Porin OmpP2 of Haemophilus influenzae shows specificity for nicotinamide-derived nucleotide substrates

Haemophilus influenzae has an absolute requirement for NAD (factor V) because it lacks all biosynthetic enzymes necessary for de novo synthesis of that cofactor. Therefore, growth in vitro requires the presence of NAD itself, NMN, or nicotinamide riboside (NR). To address uptake abilities of these compounds, we investigated outer membrane proteins. By analyzing ompP2 knockout mutants, we found that NAD and NMN uptake was prevented, whereas NR uptake was not. Through investigation of the properties of purified OmpP2 in artificial lipid membrane systems, the substrate specificity of OmpP2 for NAD and NMN was determined, with KS values of approximately 8 and 4mm, respectively, in 0.1 m KCl, whereas no interaction was detected for the nucleoside NR and other purine or pyrimidine nucleotide or nucleoside species. Based on our analysis, we assume that an intrinsic binding site within OmpP2 exists that facilitates diffusion of these compounds across the outer membrane, recognizing carbonyl and exposed phosphate groups. Because OmpP2 was formerly described as a general diffusion porin, an additional property of acting as a facilitator for nicotinamide-based nucleotide transport may have evolved to support and optimize utilization of the essential cofactor sources NAD and NMN in H. influenzae.     

Systems properties of the Haemophilus influenzae Rd metabolic genotype.

Haemophilus influenzae Rd was the first free-living organism for which the complete genomic sequence was established. The annotated sequence and known biochemical information was used to define the H. influenzae Rd metabolic genotype. This genotype contains 488 metabolic reactions operating on 343 metabolites. The stoichiometric matrix was used to determine the systems characteristics of the metabolic genotype and to assess the metabolic capabilities of H. influenzae. The need to balance cofactor and biosynthetic precursor production during growth on mixed substrates led to the definition of six different optimal metabolic phenotypes arising from the same metabolic genotype, each with different constraining features. The effects of variations in the metabolic genotype were also studied, and it was shown that the H. influenzae Rd metabolic genotype contains redundant functions under defined conditions. We thus show that the synthesis of in silico metabolic genotypes from annotated genome sequences is possible and that systems analysis methods are available that can be used to analyze and interpret phenotypic behavior of such genotypes.     

Identification of genome-scale metabolic network models using experimentally measured flux profiles

Genome-scale metabolic network models can be reconstructed for well-characterized organisms using genomic annotation and literature information. However, there are many instances in which model predictions of metabolic fluxes are not entirely consistent with experimental data, indicating that the reactions in the model do not match the active reactions in the in vivo system. We introduce a method for determining the active reactions in a genome-scale metabolic network based on a limited number of experimentally measured fluxes. This method, called optimal metabolic network identification (OMNI), allows efficient identification of the set of reactions that results in the best agreement between in silico predicted and experimentally measured flux distributions. We applied the method to intracellular flux data for evolved Escherichia coli mutant strains with lower than predicted growth rates in order to identify reactions that act as flux bottlenecks in these strains. The expression of the genes corresponding to these bottleneck reactions was often found to be downregulated in the evolved strains relative to the wild-type strain. We also demonstrate the ability of the OMNI method to diagnose problems in E. coli strains engineered for metabolite overproduction that have not reached their predicted production potential. The OMNI method applied to flux data for evolved strains can be used to provide insights into mechanisms that limit the ability of microbial strains to evolve towards their predicted optimal growth phenotypes. When applied to industrial production strains, the OMNI method can also be used to suggest metabolic engineering strategies to improve byproduct secretion. In addition to these applications, the method should prove to be useful in general for reconstructing metabolic networks of ill-characterized microbial organisms based on limited amounts of experimental data.     

Crystal structure of dephospho-coenzyme A kinase from Haemophilus influenzae

Dephospho-coenzyme A kinase catalyzes the final step in CoA biosynthesis, the phosphorylation of the 3'-hydroxyl group of ribose using ATP as a phosphate donor. The protein from Haemophilus influenzae was cloned and expressed, and its crystal structure was determined at 2.0-A resolution in complex with ATP. The protein molecule consists of three domains: the canonical nucleotide-binding domain with a five-stranded parallel beta-sheet, the substrate-binding alpha-helical domain, and the lid domain formed by a pair of alpha-helices. The overall topology of the protein resembles the structures of nucleotide kinases. ATP binds in the P-loop in a manner observed in other kinases. The CoA-binding site is located at the interface of all three domains. The double-pocket structure of the substrate-binding site is unusual for nucleotide kinases. Amino acid residues implicated in substrate binding and catalysis have been identified. The structure analysis suggests large domain movements during the catalytic cycle.     

Metabolite coupling in genome-scale metabolic networks

Background  

Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜ ^T, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S.     

The structure of the capsular antigen from Haemophilus influenzae type A.

Structural investigation of the capsular antigen from Haemophilus influenzae type a has shown it to be composed of 4-O-beta-D-glucopyranosyl-D-ribitol residues joined through phosphoric diester linkages between O-4 of D-glucose and O-5 of D-ribitol. Chemical degradations and 13C-n.m.r. spectroscopy were the main methods used.     

Reconstruction of a genome-scale metabolic network of Rhodococcus erythropolis for desulfurization studies

The remarkable catabolic diversity of Rhodococcus erythropolis makes it an interesting organism for bioremediation and fuel desulfurization. However, a model that can describe and explain the combined influence of various intracellular metabolic activities on its desulfurizing capabilities is missing from the literature. Such a model can greatly aid the development of R. erythropolis as an effective desulfurizing biocatalyst. This work reports the reconstruction of the first genome-scale metabolic model for R. erythropolis using the available genomic, experimental, and biochemical information. We have validated our in silico model by successfully predicting cell growth results and explaining several experimental observations in the literature on biodesulfurization using dibenzothiophene. We report several in silico experiments and flux balance analyses to propose minimal media, determine gene and reaction essentiality, and compare effectiveness of carbon, nitrogen, and sulfur sources. We demonstrate the usefulness of our model by studying a few in silico mutants of R. erythropolis for improved biodesulfurization, and comparing the desulfurization abilities of R. erythropolis with an in silico mutant of E. coli.     

Haemophilus influenzae Meningitis in Adults

Haemophilus influenzae meningitis though common in childhood is rarely seen in the adult. During the past four years eight cases of H. influenzae meningitis have been seen in St. Thomas''s Hospital and four of these were in patients over 20 years old. There was a possible predisposing condition in two patients. In each case there was difficulty in identification of the organism in the Gram-stained film of the cerebrospinal fluid deposit.     

Crystal structure of a novel shikimate dehydrogenase from Haemophilus influenzae

To date two classes of shikimate dehydrogenases have been identified and characterized, YdiB and AroE. YdiB is a bifunctional enzyme that catalyzes the reversible reductions of dehydroquinate to quinate and dehydroshikimate to shikimate in the presence of either NADH or NADPH. In contrast, AroE catalyzes the reversible reduction of dehydroshikimate to shikimate in the presence of NADPH. Here we report the crystal structure and biochemical characterization of HI0607, a novel class of shikimate dehydrogenase annotated as shikimate dehydrogenase-like. The kinetic properties of HI0607 are remarkably different from those of AroE and YdiB. In comparison with YdiB, HI0607 catalyzes the oxidation of shikimate but not quinate. The turnover rate for the oxidation of shikimate is approximately 1000-fold lower compared with that of AroE. Phylogenetic analysis reveals three independent clusters representing three classes of shikimate dehydrogenases, namely AroE, YdiB, and this newly characterized shikimate dehydrogenase-like protein. In addition, mutagenesis studies of two invariant residues, Asp-103 and Lys-67, indicate that they are important catalytic groups that may function as a catalytic pair in the shikimate dehydrogenase reaction. This is the first study that describes the crystal structure as well as mutagenesis and mechanistic analysis of this new class of shikimate dehydrogenase.     

The structure and function of the 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase from Haemophilus influenzae

The gene encoding the 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase of Haemophilus influenzae has been cloned and expressed in Escherichia coli. A complex of the purified protein with a substrate analog has been crystallized and its structure solved by multiple anomalous dispersion using phase information obtained from a single crystal of selenomethione-labeled protein. The enzyme folds into a four-stranded antiparallel beta-sheet flanked on one side by two alpha-helices and on the other by three consecutive alpha-helices, giving a novel beta1alpha1beta2beta3alpha2beta4alpha3alpha4alpha5 polypeptide topology. The three-dimensional structure of a binary complex has been refined at 2.1 A resolution. The location of the substrate analog and a sulfate ion gives important insight into the molecular mechanism of the enzyme.     

Plasmid-to-plasmid recombination in Haemophilus influenzae.

No recombination between plasmids was observed after conjugal transfer of a plasmid into a cell carrying another plasmid. Two types of such recombination took place after transformation, one type being Rec+ dependent and suggesting a preferred site of recombination. The other much rarer type was at least partially Rec+ independent.     

Plasmid transformation in Haemophilus influenzae.

Purified 34-megadalton-plasmid deoxyribonucleic acid from antibiotic-resistant strains of Haemophilus influenzae transforms competent strains of H. influenzae more efficiently if the recipient strains contain certain other 30-megadalton plasmids.