Modeling Neisseria meningitidis B metabolism at different specific growth rates

Activation of Canine, Mouse and Human TLR2 and TLR4 by Inactivated Leptospira Vaccine Strains

Canine Leptospira vaccines contain inactivated strains of pathogenic Leptospira, the causative agents of leptospirosis. For an effective response to vaccination, activation of the innate immune system via pattern recognition receptors such as TLRs is crucial. However, it is not known which TLRs are activated by Leptospira in dogs. To investigate the involvement of canine TLR2, TLR4, and TLR5 in the recognition of Leptospira, we stimulated canine moDC and reporter cells expressing canine TLR2 with either whole-inactivated bacteria or purified LPS of Leptospira strains, representing the serogroups generally used in canine leptospirosis vaccines. Using the endotoxin neutralizing reagent polymyxin B and TLR4 antagonist RS-LPS, we demonstrate that Leptospira LPS and canine TLR4 are involved in IL-1β production as well as in the uptake of inactivated Leptospira in canine moDC. Furthermore, polymyxin B only partially inhibited IL-1β production induced by inactivated Leptospira, suggesting that next to TLR4, also other TLRs may be involved. The observed activation of canine TLR2-expressing reporter cells by inactivated Leptospira strains indicates that TLR2 could be one of these TLRs. Next, we analyzed TLR2 and TLR4 activating capabilities by the same Leptospira strains using human and mouse TLR-expressing reporter cells. Inactivated Leptospira and leptospiral LPS activated not only mouse, but also human TLR4 and this activation was shown to be LPS dependent in both cases. Additionally, inactivated Leptospira activated mouse and human TLR2-expressing reporter cell lines. In our study, we could not identify significant species differences in the recognition of Leptospira by TLR2 and TLR4 between dog, human and mouse. Lastly, we show that these inactivated Leptospira strains are recognized by both mouse and human TLR5 reporter cells only after exposure to additional heat-treatment. Unfortunately, we were not able to confirm this in the canine system. Our data show that TLR2 and TLR4 are involved in the recognition of Leptospira strains used in the production of canine Leptospira vaccines. This study contributes to the understanding of Leptospira-induced innate immune responses in dogs, humans, and mice. Future studies are needed to further explore the role of canine TLR2, TLR4 and TLR5 in the induction of vaccine-mediated immunity against Leptospira.

Metabolic competition as a driver of bacterial population structure

Understanding the processes whereby diversity arises and is maintained in pathogen populations is pivotal for designing disease control interventions. A particular problem is the maintenance of strain structure in bacterial pathogen populations despite frequent genetic exchange. Although several theoretical frameworks have been put forward to explain this widespread phenomenon, few have focused on the role of genes encoding metabolic functions, despite an increasing recognition of their importance in pathogenesis and transmission. In this article, we review the literature for evidence of metabolic niches within the host and discuss theoretical frameworks which examine ecological interactions between metabolic genes. We contend that metabolic competition is an important phenomenon which contributes to the maintenance of population structure and diversity of many bacterial pathogens.

Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates

Pseudomonas aeruginosa is a metabolically versatile wide-ranging opportunistic pathogen. In humans P. aeruginosa causes infections of the skin, urinary tract, blood, and the lungs of Cystic Fibrosis patients. In addition, P. aeruginosa's broad environmental distribution, relatedness to biotechnologically useful species, and ability to form biofilms have made it the focus of considerable interest. We used ¹³C metabolic flux analysis (MFA) and flux balance analysis to understand energy and redox production and consumption and to explore the metabolic phenotypes of one reference strain and five strains isolated from the lungs of cystic fibrosis patients. Our results highlight the importance of the oxidative pentose phosphate and Entner-Doudoroff pathways in P. aeruginosa growth. Among clinical strains we report two divergent metabolic strategies and identify changes between genetically related strains that have emerged during a chronic infection of the same patient. MFA revealed that the magnitude of fluxes through the glyoxylate cycle correlates with growth rates.

Vaccine-Mediated Activation of Human TLR4 Is Affected by Modulation of Culture Conditions during Whole-Cell Pertussis Vaccine Preparation

The potency of whole-cell pertussis (wP) vaccines is still determined by an intracerebral mouse protection test. To allow development of suitable in vitro alternatives to this test, insight into relevant parameters to monitor the consistency of vaccine quality is essential. To this end, a panel of experimental wP vaccines of varying quality was prepared by sulfate-mediated suppression of the BvgASR master virulence regulatory system of Bordetella pertussis during cultivation. This system regulates the transcription of a range of virulence proteins, many of which are considered important for the induction of effective host immunity. The protein compositions and in vivo potencies of the vaccines were BvgASR dependent, with the vaccine containing the highest amount of virulence proteins having the highest in vivo potency. Here, the capacities of these vaccines to stimulate human Toll-like receptors (hTLR) 2 and 4 and the role these receptors play in wP vaccine-mediated activation of antigen-presenting cells in vitro were studied. Prolonged BvgASR suppression was associated with a decreased capacity of vaccines to activate hTLR4. In contrast, no significant differences in hTLR2 activation were observed. Similarly, vaccine-induced activation of MonoMac-6 and monocyte-derived dendritic cells was strongest with the highest potency vaccine. Blocking of TLR2 and TLR4 showed that differences in antigen-presenting cell activation could be largely attributed to vaccine-dependent variation in hTLR4 signalling. Interestingly, this BvgASR-dependent decrease in hTLR4 activation coincided with a reduction in GlcN-modified lipopolysaccharides in these vaccines. Accordingly, expression of the lgmA-C genes, required for this glucosamine modification, was significantly reduced in bacteria exposed to sulfate. Together, these findings demonstrate that the BvgASR status of bacteria during wP vaccine preparation is critical for their hTLR4 activation capacity and suggest that including such parameters to assess consistency of newly produced vaccines could bring in vitro testing of vaccine quality a step closer.

On-line modeling intracellular carbon and energy metabolism of Nannochloropsis sp. in nitrogen-repletion and nitrogen-limitation cultures

In this study, a photobioreactor cultivation system and a calculation method for on-line monitoring of carbon and energy metabolism of microalgae were developed using Nannochloropsis sp. in nitrogen-repletion and nitrogen-limitation cultures. Only 30-60% of carbon fixed in Calvin cycle was used for biomass and the rest was lost in light respiration. The net fixed carbon was assumed to be incorporated into protein, lipids, carbohydrates, and nucleic acids, whose contents calculated on-line fitted well with the experimental measurements. Intracellular ATPs were quantitatively divided for biomass production and cell maintenance, and the result is in accordance with known reports. Due to light limitation induced by high cell concentration in batch cultures, the proportion of CO2 loss in light respiration and the proportion of energy for maintenance rapidly increased in culturing process. Nitrogen starvation reduced the light respiration, thus decreasing CO2 loss and maintenance energy, but no effect on ATP requirement for cell growth.

Promise and reality in the expanding field of network interaction analysis: metabolic networks

In the last few decades, metabolic networks revealed their capabilities as powerful tools to analyze the cellular metabolism. Many research fields (eg, metabolic engineering, diagnostic medicine, pharmacology, biochemistry, biology and physiology) improved the understanding of the cell combining experimental assays and metabolic network-based computations. This process led to the rise of the “systems biology” approach, where the theory meets experiments and where two complementary perspectives cooperate in the study of biological phenomena. Here, the reconstruction of metabolic networks is presented, along with established and new algorithms to improve the description of cellular metabolism. Then, advantages and limitations of modeling algorithms and network reconstruction are discussed.

Reconciling in vivo and in silico key biological parameters of Pseudomonas putida KT2440 during growth on glucose under carbon-limited condition

Background

Genome scale metabolic reconstructions are developed to efficiently engineer biocatalysts and bioprocesses based on a rational approach. However, in most reconstructions, due to the lack of appropriate measurements, experimentally determined growth parameters are simply taken from literature including other organisms, which reduces the usefulness and suitability of these models. Pseudomonas putida KT2440 is an outstanding biocatalyst given its versatile metabolism, its ability to generate sufficient energy and turnover of NADH and NAD. To apply this strain optimally in industrial production, a previously developed genome-scale metabolic model (iJP815) was experimentally assessed and streamlined to enable accurate predictions of the outcome of metabolic engineering approaches.

Results

To substantially improve the accuracy of the genome scale model (iJP815), continuous bioreactor cultures on a mineral medium with glucose as a sole carbon source were carried out at different dilution rates, which covered pulling analysis of the macromolecular composition of the biomass. Besides, the maximum biomass yield (on substrate) of 0.397 g_DCW · g_glc^-1, the maintenance coefficient of 0.037 g_glc · g_DCW^-1 · h^-1 and the maximum specific growth rate of 0.59 h^-1 were determined. Only the DNA fraction increased with the specific growth rate. This resulted in reliable estimation for the Growth-Associated Maintenance (GAM) of 85 mmol_ATP · g_DCW^-1 and the Non Growth-Associated Maintenance (NGAM) of 3.96 mmol_ATP · g_DCW^-1 · h^-1. Both values were found significantly different from previous assignment as a consequence of a lower yield and higher maintenance coefficient than originally assumed. Contrasting already published ¹³C flux measurements and the improved model allowed for constraining the solution space, by eliminating futile cycles. Furthermore, the model predictions were compared with transcriptomic data at overall good consistency, which helped to identify missing links.

Conclusions

By careful interpretation of growth stoichiometry and kinetics when grown in the presence of glucose, this work reports on an accurate genome scale metabolic model of Pseudomonas putida, providing a solid basis for its use in designing superior strains for biocatalysis. By consideration of substrate specific variation in stoichiometry and kinetics, it can be extended to other substrates and new mutants.

Improved production process for native outer membrane vesicle vaccine against Neisseria meningitidis

An improved detergent-free process has been developed to produce vaccine based on native outer membrane vesicles (NOMV) against Neisseria meningitidis serogroup B. Performance was evaluated with the NonaMen vaccine concept, which provides broad coverage based on nine distinct PorA antigens. Scalable aseptic equipment was implemented, replacing undesirable steps like ultracentrifugation, inactivation with phenol, and the use of preservatives. The resulting process is more consistent and gives a higher yield than published reference processes, enabling NOMV production at commercial scale. Product quality met preliminary specifications for 9 consecutive batches, and an ongoing study confirmed real-time stability up to 12 months after production. As the NOMV had low endotoxic activity and induced high bactericidal titres in mice, they are expected to be safe and effective in humans. The production process is not limited to NonaMen and may be applicable for other N. meningitidis serogroups and other gram-negative pathogens. The current results therefore facilitate the late-stage development and clinical evaluation of NOMV vaccines.

Cysteine depletion causes oxidative stress and triggers outer membrane vesicle release by Neisseria meningitidis; implications for vaccine development

Outer membrane vesicles (OMV) contain immunogenic proteins and contribute to in vivo survival and virulence of bacterial pathogens. The first OMV vaccines successfully stopped Neisseria meningitidis serogroup B outbreaks but required detergent-extraction for endotoxin removal. Current vaccines use attenuated endotoxin, to preserve immunological properties and allow a detergent-free process. The preferred process is based on spontaneously released OMV (sOMV), which are most similar to in vivo vesicles and easier to purify. The release mechanism however is poorly understood resulting in low yield. This study with N. meningitidis demonstrates that an external stimulus, cysteine depletion, can trigger growth arrest and sOMV release in sufficient quantities for vaccine production (±1500 human doses per liter cultivation). Transcriptome analysis suggests that cysteine depletion impairs iron-sulfur protein assembly and causes oxidative stress. Involvement of oxidative stress is confirmed by showing that addition of reactive oxygen species during cysteine-rich growth also triggers vesiculation. The sOMV in this study are similar to vesicles from natural infection, therefore cysteine-dependent vesiculation is likely to be relevant for the in vivo pathogenesis of N. meningitidis.

The metabolic blueprint of Phaeodactylum tricornutum reveals a eukaryotic Entner-Doudoroff glycolytic pathway

Diatoms are one of the most successful groups of unicellular eukaryotic algae. Successive endosymbiotic events contributed to their flexible metabolism, making them competitive in variable aquatic habitats. Although the recently sequenced genomes of the model diatoms Phaeodactylum tricornutum and Thalassiosira pseudonana have provided the first insights into their metabolic organization, the current knowledge on diatom biochemistry remains fragmentary. By means of a genome-wide approach, we developed DiatomCyc, a detailed pathway/genome database of P. tricornutum. DiatomCyc contains 286 pathways with 1719 metabolic reactions and 1613 assigned enzymes, spanning both the central and parts of the secondary metabolism of P. tricornutum. Central metabolic pathways, such as those of carbohydrates, amino acids and fatty acids, were covered. Furthermore, our understanding of the carbohydrate model in P. tricornutum was extended. In particular we highlight the discovery of a functional Entner-Doudoroff pathway, an ancient alternative for the glycolytic Embden-Meyerhof-Parnas pathway, and a putative phosphoketolase pathway, both uncommon in eukaryotes. DiatomCyc is accessible online (http://www.diatomcyc.org), and offers a range of software tools for the visualization and analysis of metabolic networks and 'omics' data. We anticipate that DiatomCyc will be key to gaining further understanding of diatom metabolism and, ultimately, will feed metabolic engineering strategies for the industrial valorization of diatoms.

Metabolic modeling of Chlamydomonas reinhardtii: energy requirements for photoautotrophic growth and maintenance

In this study, a metabolic network describing the primary metabolism of Chlamydomonas reinhardtii was constructed. By performing chemostat experiments at different growth rates, energy parameters for maintenance and biomass formation were determined. The chemostats were run at low irradiances resulting in a high biomass yield on light of 1.25 g  mol(-1). The ATP requirement for biomass formation from biopolymers (K(x)) was determined to be 109 mmol g(-1) (18.9 mol mol(-1)) and the maintenance requirement (m(ATP)) was determined to be 2.85 mmol g(-1) h(-1). With these energy requirements included in the metabolic network, the network accurately describes the primary metabolism of C. reinhardtii and can be used for modeling of C. reinhardtii growth and metabolism. Simulations confirmed that cultivating microalgae at low growth rates is unfavorable because of the high maintenance requirements which result in low biomass yields. At high light supply rates, biomass yields will decrease due to light saturation effects. Thus, to optimize biomass yield on light energy in photobioreactors, an optimum between low and high light supply rates should be found. These simulations show that metabolic flux analysis can be used as a tool to gain insight into the metabolism of algae and ultimately can be used for the maximization of algal biomass and product yield. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10811-011-9674-3) contains supplementary material, which is available to authorized users.

Genome-scale metabolic models: reconstruction and analysis

Metabolism can be defined as the complete set of chemical reactions that occur in living organisms in order to maintain life. Enzymes are the main players in this process as they are responsible for catalyzing the chemical reactions. The enzyme-reaction relationships can be used for the reconstruction of a network of reactions, which leads to a metabolic model of metabolism. A genome-scale metabolic network of chemical reactions that take place inside a living organism is primarily reconstructed from the information that is present in its genome and the literature and involves steps such as functional annotation of the genome, identification of the associated reactions and determination of their stoichiometry, assignment of localization, determination of the biomass composition, estimation of energy requirements, and definition of model constraints. This information can be integrated into a stoichiometric model of metabolism that can be used for detailed analysis of the metabolic potential of the organism using constraint-based modeling approaches and hence is valuable in understanding its metabolic capabilities.

Interrogation of global mutagenesis data with a genome scale model of Neisseria meningitidis to assess gene fitness in vitro and in sera

Background

Neisseria meningitidis is an important human commensal and pathogen that causes several thousand deaths each year, mostly in young children. How the pathogen replicates and causes disease in the host is largely unknown, particularly the role of metabolism in colonization and disease. Completed genome sequences are available for several strains but our understanding of how these data relate to phenotype remains limited.

Results

To investigate the metabolism of N. meningitidis we generated and then selected a representative Tn5 library on rich medium, a minimal defined medium and in human serum to identify genes essential for growth under these conditions. To relate these data to a systems-wide understanding of the pathogen's biology we constructed a genome-scale metabolic network: Nmb_iTM560. This model was able to distinguish essential and non-essential genes as predicted by the global mutagenesis. These essentiality data, the library and the Nmb_iTM560 model are powerful and widely applicable resources for the study of meningococcal metabolism and physiology. We demonstrate the utility of these resources by predicting and demonstrating metabolic requirements on minimal medium, such as a requirement for phosphoenolpyruvate carboxylase, and by describing the nutritional and biochemical status of N. meningitidis when grown in serum, including a requirement for both the synthesis and transport of amino acids.

Conclusions

This study describes the application of a genome scale transposon library combined with an experimentally validated genome-scale metabolic network of N. meningitidis to identify essential genes and provide novel insight into the pathogen's metabolism both in vitro and during infection.

The renaissance of continuous culture in the post-genomics age

The development of continuous culture techniques 60 years ago and the subsequent formulation of theory and the diversification of experimental systems revolutionised microbiology and heralded a unique period of innovative research. Then, progressively, molecular biology and thence genomics and related high-information-density omics technologies took centre stage and microbial growth physiology in general faded from educational programmes and research funding priorities alike. However, there has been a gathering appreciation over the past decade that if the claims of systems biology are going to be realised, they will have to be based on rigorously controlled and reproducible microbial and cell growth platforms. This revival of continuous culture will be long lasting because its recognition as the growth system of choice is firmly established. The purpose of this review, therefore, is to remind microbiologists, particularly those new to continuous culture approaches, of the legacy of what I call the first age of continuous culture, and to explore a selection of researches that are using these techniques in this post-genomics age. The review looks at the impact of continuous culture across a comprehensive range of microbiological research and development. The ability to establish (quasi-) steady state conditions is a frequently stated advantage of continuous cultures thereby allowing environmental parameters to be manipulated without causing concomitant changes in the specific growth rate. However, the use of continuous cultures also enables the critical study of specified transition states and chemical, physical or biological perturbations. Such dynamic analyses enhance our understanding of microbial ecology and microbial pathology for example, and offer a wider scope for innovative drug discovery; they also can inform the optimization of batch and fed-batch operations that are characterized by sequential transitions states.

Expression of phosphofructokinase in Neisseria meningitidis

Neisseria meningitidis serogroup B is a pathogen that can infect diverse sites within the human host. According to the N. meningitidis genomic information and experimental observations, glucose can be completely catabolized through the Entner-Doudoroff pathway and the pentose phosphate pathway. The Embden-Meyerhof-Parnas pathway is not functional, because the gene for phosphofructokinase (PFK) is not present. The phylogenetic distribution of PFK indicates that in most obligate aerobic organisms, PFK is lacking. We conclude that this is because of the limited contribution of PFK to the energy supply in aerobically grown organisms in comparison with the energy generated through oxidative phosphorylation. Under anaerobic or microaerobic conditions, the available energy is limiting, and PFK provides an advantage, which explains the presence of PFK in many (facultatively) anaerobic organisms. In accordance with this, in silico flux balance analysis predicted an increase of biomass yield as a result of PFK expression. However, analysis of a genetically engineered N. meningitidis strain that expressed a heterologous PFK showed that the yield of biomass on substrate decreased in comparison with a pfkA-deficient control strain, which was associated mainly with an increase in CO(2) production, whereas production of by-products was similar in the two strains. This might explain why the pfkA gene has not been obtained by horizontal gene transfer, since it is initially unfavourable for biomass yield. No large effects related to heterologous expression of pfkA were observed in the transcriptome. Although our results suggest that introduction of PFK does not contribute to a more efficient strain in terms of biomass yield, achievement of a robust, optimal metabolic network that enables a higher growth rate or a higher biomass yield might be possible after adaptive evolution of the strain, which remains to be investigated.