A new mutation delivery system for genome-scale approaches in Bacillus subtilis

In Bacillus subtilis, although many genetic tools have been developed, gene replacement remains labour-intensive and not compatible with large-scale approaches. We have developed a new one-step gene replacement procedure that allows rapid alteration of any gene sequence or multiple gene sequences in B. subtilis without altering the chromosome in any other way. This novel approach relies on the use of upp, which encodes uracil phosphoribosyl-transferase, as a counter-selectable marker. We fused the upp gene to an antibiotic-resistance gene to create an 'upp-cassette'. A polymerase chain reaction (PCR)-generated fragment, consisting of the target gene with the desired mutation joined to the upp-cassette, was integrated into the chromosome by homologous recombination, using positive selection for antibiotic resistance. Then, the eviction of the upp-cassette from the chromosome by recombination between short repeated chromosomal sequences, included in the design of the transforming DNA molecule, was achieved by counter-selection of upp. This procedure was successfully used to deliver a point mutation, to generate in-frame deletions with reduced polar effects, and to combine deletions in three paralogous genes encoding two-component sensor kinases. Also, two chromosome regions carrying previously unrecognized essential functions were identified, and large deletions in two dispensable regions were combined. This work outlines a strategy for identifying essential functions that could be used at genome scale.     

Toward the automated generation of genome-scale metabolic networks in the SEED

Background  

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process.     

Further developments towards a genome-scale metabolic model of yeast

Background

To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity.

Results

We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions.

Conclusions

We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/.     

D-Tyrosine as a metabolic inhibitor of Bacillus subtilis

The d-isomer of tyrosine is a potent inhibitor of growth in transformable strain 168 of Bacillus subtilis. A d-tyrosine-resistant mutant of the inhibited strain was isolated which excreted l-tyrosine, had a diminished growth rate, and required l-phenylalanine to attain the growth rate of the wild-type parent. Mapping by deoxyribonucleate transformation located this resistance in the gene coding for prephenate dehydrogenase. This enzyme in the d-tyrosine-resistant mutant was insensitive to the usual feedback inhibition exerted by l-tyrosine in extracts of strain 168. In contrast, the growth of poorly transformable strain 23 of B. subtilis, as well as that of several other Bacillus species, was not affected by the analogue. Transformation mapping demonstrated no linkage of this latter natural resistance to several different aromatic markers. Prephenate dehydrogenase in extracts from strain 23 was as sensitive as that from strain 168 to feedback inhibition by l-tyrosine in vitro. The relationships of the latter results to the regulation of tyrosine biosynthesis and the possible nature of strain differences in d-tyrosine sensitivity are discussed.     

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).     

Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

Background  

Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO₂ and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network.     

Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus

The reconstructed cellular metabolic network of Mus musculus, based on annotated genomic data, pathway databases, and currently available biochemical and physiological information, is presented. Although incomplete, it represents the first attempt to collect and characterize the metabolic network of a mammalian cell on the basis of genomic data. The reaction network is generic in nature and attempts to capture the carbon, energy, and nitrogen metabolism of the cell. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, including transport reactions between the compartments and the extracellular medium. The reaction list consists of 872 internal metabolites involved in a total of 1220 reactions, whereof 473 relate to known open reading frames. Initial in silico analysis of the reconstructed model is presented.     

A genome-scale metabolic model of potato late blight suggests a photosynthesis suppression mechanism

Background

Phytophthora infestans is a plant pathogen that causes an important plant disease known as late blight in potato plants (Solanum tuberosum) and several other solanaceous hosts. This disease is the main factor affecting potato crop production worldwide. In spite of the importance of the disease, the molecular mechanisms underlying the compatibility between the pathogen and its hosts are still unknown.

Results

To explain the metabolic response of late blight, specifically photosynthesis inhibition in infected plants, we reconstructed a genome-scale metabolic network of the S. tuberosum leaf, PstM1. This metabolic network simulates the effect of this disease in the leaf metabolism. PstM1 accounts for 2751 genes, 1113 metabolic functions, 1773 gene-protein-reaction associations and 1938 metabolites involved in 2072 reactions. The optimization of the model for biomass synthesis maximization in three infection time points suggested a suppression of the photosynthetic capacity related to the decrease of metabolic flux in light reactions and carbon fixation reactions. In addition, a variation pattern in the flux of carboxylation to oxygenation reactions catalyzed by RuBisCO was also identified, likely to be associated to a defense response in the compatible interaction between P. infestans and S. tuberosum.

Conclusions

In this work, we introduced simultaneously the first metabolic network of S. tuberosum and the first genome-scale metabolic model of the compatible interaction of a plant with P. infestans.

     

Production of D-arabitol by a metabolic engineered strain of Bacillus subtilis

A novel method for D-arabitol production with a metabolically engineered Bacillus subtilis strain is described. A known transketolase-deficient and D-ribose-producing mutant of B. subtilis (ATCC 31094) was further modified by disruption of its rpi (D-ribose phosphate isomerase) gene to create a D-ribulose- and D-xylulose-producing B. subtilis strain. Expression of the D-arabitol phosphate dehydrogenase gene of Enterococcus avium in the D-ribulose- and D-xylulose-producing strain resulted in a strain of B. subtilis capable of converting D-glucose to D-arabitol with a high yield (38%) and little by-product formation.     

Control of key metabolic intersections in Bacillus subtilis

The remarkable ability of bacteria to adapt efficiently to a wide range of nutritional environments reflects their use of overlapping regulatory systems that link gene expression to intracellular pools of a small number of key metabolites. By integrating the activities of global regulators, such as CcpA, CodY and TnrA, Bacillus subtilis manages traffic through two metabolic intersections that determine the flow of carbon and nitrogen to and from crucial metabolites, such as pyruvate, 2-oxoglutarate and glutamate. Here, the latest knowledge on the control of these key intersections in B. subtilis is reviewed.     

Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretation of complex fermentation data, as L. plantarum is adapted to nutrient-rich environments and only grows in media supplemented with vitamins and amino acids. (i) Based on experimental input and output fluxes, maximal ATP production was estimated and related to growth rate. (ii) Optimization of ATP production further identified amino acid catabolic pathways that were not previously associated with free-energy metabolism. (iii) Genome-scale elementary flux mode analysis identified 28 potential futile cycles. (iv) Flux variability analysis supplemented the elementary mode analysis in identifying parallel pathways, e.g. pathways with identical end products but different co-factor usage. Strongly increased flexibility in the metabolic network was observed when strict coupling between catabolic ATP production and anabolic consumption was relaxed. These results illustrate how a genome-scale metabolic model and associated constraint-based modeling techniques can be used to analyze the physiology of growth on a complex medium rather than a minimal salts medium. However, optimization of biomass formation using the Flux Balance Analysis approach, reported to successfully predict growth rate and by product formation in Escherichia coli and Saccharomyces cerevisiae, predicted too high biomass yields that were incompatible with the observed lactate production. The reason is that this approach assumes optimal efficiency of substrate to biomass conversion, and can therefore not predict the metabolically inefficient lactate formation.     

Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data

In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genome-scale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.     

Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

Background  

In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates.     

C4GEM, a genome-scale metabolic model to study C4 plant metabolism

Leaves of C(4) grasses (such as maize [Zea mays], sugarcane [Saccharum officinarum], and sorghum [Sorghum bicolor]) form a classical Kranz leaf anatomy. Unlike C(3) plants, where photosynthetic CO(2) fixation proceeds in the mesophyll (M), the fixation process in C(4) plants is distributed between two cell types, the M cell and the bundle sheath (BS) cell. Here, we develop a C(4) genome-scale model (C4GEM) for the investigation of flux distribution in M and BS cells during C(4) photosynthesis. C4GEM, to our knowledge, is the first large-scale metabolic model that encapsulates metabolic interactions between two different cell types. C4GEM is based on the Arabidopsis (Arabidopsis thaliana) model (AraGEM) but has been extended by adding reactions and transporters responsible to represent three different C(4) subtypes (NADP-ME [for malic enzyme], NAD-ME, and phosphoenolpyruvate carboxykinase). C4GEM has been validated for its ability to synthesize 47 biomass components and consists of 1,588 unique reactions, 1,755 metabolites, 83 interorganelle transporters, and 29 external transporters (including transport through plasmodesmata). Reactions in the common C(4) model have been associated with well-annotated C(4) species (NADP-ME subtypes): 3,557 genes in sorghum, 11,623 genes in maize, and 3,881 genes in sugarcane. The number of essential reactions not assigned to genes is 131, 135, and 156 in sorghum, maize, and sugarcane, respectively. Flux balance analysis was used to assess the metabolic activity in M and BS cells during C(4) photosynthesis. Our simulations were consistent with chloroplast proteomic studies, and C4GEM predicted the classical C(4) photosynthesis pathway and its major effect in organelle function in M and BS. The model also highlights differences in metabolic activities around photosystem I and photosystem II for three different C(4) subtypes. Effects of CO(2) leakage were also explored. C4GEM is a viable framework for in silico analysis of cell cooperation between M and BS cells during photosynthesis and can be used to explore C(4) plant metabolism.     

Biologic characteristics of new Bacillus subtilis isolates

Characteristics of new Bacillus subtilis isolates from the environment and had high antagonistic activity were studied. Absence of virulence and toxin production allows to regard them as potential probiotic cultures. Growth media for cultivation of B.subtilis were chosen according to the principle of individual adequacy in system, which give the ability to optimize processes of cultivation, obtaining of inhibitory substances and antagonistic activity spectrum determination.     

Characterization of a new sporulation factor in Bacillus subtilis.

We report the existence and partial purification of sporulation factor, which stimulates sporulation of Bacillus subtilis at low cell density. Proline or arginine is required for stimulation under the conditions of our assay. Sporulation factor is a small heat-stable substance produced by the cells during exponential growth phase. It is required in small amounts and is resistant to various proteolytic agents. Several spo mutants were tested for the ability to produce functional sporulation factor. All of these mutants produce factor and do not sporulate in the presence of factor from wild-type cells. Sporulation factor is not involved in the induction of alpha-amylase synthesis at the initiation of sporulation.