Modeling of cell signaling pathways in macrophages by semantic networks

Background  

Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways.     

Inorganic pyrophosphatase in uncultivable hemotrophic mycoplasmas: identification and properties of the enzyme from <Emphasis Type="Italic">Mycoplasma suis</Emphasis>

Background  

Mycoplasma suis belongs to a group of highly specialized hemotrophic bacteria that attach to the surface of host erythrocytes. Hemotrophic mycoplasmas are uncultivable and the genomes are not sequenced so far. Therefore, there is a need for the clarification of essential metabolic pathways which could be crucial barriers for the establishment of an in vitro cultivation system for these veterinary significant bacteria.     

Energy metabolism of <Emphasis Type="Italic">Heliobacterium modesticaldum</Emphasis> during phototrophic and chemotrophic growth

Background  

Heliobacterium modesticaldum is a gram-positive nitrogen-fixing phototrophic bacterium that can grow either photoheterotrophically or chemotrophically but not photoautotrophically. Surprisingly, this organism is lacking only one gene for the complete reverse tricarboxylic acid (rTCA) cycle required for autotrophic carbon fixation. Along with the genomic information reported recently, we use multiple experimental approaches in this report to address questions regarding energy metabolic pathways in darkness, CO₂ fixation, sugar assimilation and acetate metabolism.     

Gene and pathway identification with <Emphasis Type="Italic">L</Emphasis><Subscript><Emphasis Type="Italic">p</Emphasis></Subscript>penalized Bayesian logistic regression

Background  

Identifying genes and pathways associated with diseases such as cancer has been a subject of considerable research in recent years in the area of bioinformatics and computational biology. It has been demonstrated that the magnitude of differential expression does not necessarily indicate biological significance. Even a very small change in the expression of particular gene may have dramatic physiological consequences if the protein encoded by this gene plays a catalytic role in a specific cell function. Moreover, highly correlated genes may function together on the same pathway biologically. Finally, in sparse logistic regression withL _p (p< 1) penalty, the degree of the sparsity obtained is determined by the value of the regularization parameter. Usually this parameter must be carefully tuned through cross-validation, which is time consuming.     

A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis

Background  

Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention.     

Differential proteomic analysis highlights metabolic strategies associated with balhimycin production in <Emphasis Type="Italic">Amycolatopsis balhimycina</Emphasis> chemostat cultivations

Background  

Proteomics was recently used to reveal enzymes whose expression is associated with the production of the glycopeptide antibiotic balhimycin in Amycolatopsis balhimycina batch cultivations. Combining chemostat fermentation technology, where cells proliferate with constant parameters in a highly reproducible steady-state, and differential proteomics, the relationships between physiological status and metabolic pathways during antibiotic producing and non-producing conditions could be highlighted.     

Structural characterization of CA1462, the <Emphasis Type="Italic">Candida albicans</Emphasis> thiamine pyrophosphokinase

Background  

In search of new antifungal targets of potential interest for pharmaceutical companies, we initiated a comparative genomics study to identify the most promising protein-coding genes in fungal genomes. One criterion was the protein sequence conservation between reference pathogenic genomes. A second criterion was that the corresponding gene in Saccharomyces cerevisiae should be essential. Since thiamine pyrophosphate is an essential product involved in a variety of metabolic pathways, proteins responsible for its production satisfied these two criteria.     

Metabolic pathways of the wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>) endosperm amyloplast revealed by proteomics

Background  

By definition, amyloplasts are plastids specialized for starch production. However, a proteomic study of amyloplasts isolated from wheat (Triticum aestivum Butte 86) endosperm at 10 days after anthesis (DPA) detected enzymes from many other metabolic and biosynthetic pathways. To better understand the role of amyloplasts in food production, the data from that study were evaluated in detail and an amyloplast metabolic map was outlined.     

Metabolic regulation analysis of an ethanologenic <Emphasis Type="Italic">Escherichia coli</Emphasis> strain based on RT-PCR and enzymatic activities

Background  

A metabolic regulation study was performed, based upon measurements of enzymatic activities, fermentation performance, and RT-PCR analysis of pathways related to central carbon metabolism, in an ethanologenic Escherichia coli strain (CCE14) derived from lineage C. In comparison with previous engineered strains, this E coli derivative has a higher ethanol production rate in mineral medium, as a result of the elevated heterologous expression of the chromosomally integrated genes encoding PDC _Zm and ADH _Zm (pyruvate decarboxylase and alcohol dehydrogenase from Zymomonas mobilis). It is suggested that this behavior might be due to lineage differences between E. coli W and C.     

Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction

Background  

Infections with Salmonella cause significant morbidity and mortality worldwide. Replication of Salmonella typhimurium inside its host cell is a model system for studying the pathogenesis of intracellular bacterial infections. Genome-scale modeling of bacterial metabolic networks provides a powerful tool to identify and analyze pathways required for successful intracellular replication during host-pathogen interaction.     

Systemic resistance and lipoxygenase-related defence response induced in tomato by <Emphasis Type="Italic">Pseudomonas putida</Emphasis>strain BTP1

Background  

Previous studies showed the ability of Pseudomonas putida strain BTP1 to promote induced systemic resistance (ISR) in different host plants. Since ISR is long-lasting and not conducive for development of resistance of the targeted pathogen, this phenomenon can take part of disease control strategies. However, in spite of the numerous examples of ISR induced by PGPR in plants, only a few biochemical studies have associated the protective effect with specific host metabolic changes.     

The genome-scale metabolic network analysis <Emphasis Type="Italic">of Zymomonas mobilis</Emphasis> ZM4 explains physiological features and suggests ethanol and succinic acid production strategies

Background  

Zymomonas mobilis ZM4 is a Gram-negative bacterium that can efficiently produce ethanol from various carbon substrates, including glucose, fructose, and sucrose, via the Entner-Doudoroff pathway. However, systems metabolic engineering is required to further enhance its metabolic performance for industrial application. As an important step towards this goal, the genome-scale metabolic model of Z. mobilis is required to systematically analyze in silico the metabolic characteristics of this bacterium under a wide range of genotypic and environmental conditions.     

Metabolism as means for hypoxia adaptation: metabolic profiling and flux balance analysis

Background  

Cellular hypoxia is a component of many diseases, but mechanisms of global hypoxic adaptation and resistance are not completely understood. Previously, a population of Drosophila flies was experimentally selected over several generations to survive a chronically hypoxic environment. NMR-based metabolomics, combined with flux-balance simulations of genome-scale metabolic networks, can generate specific hypotheses for global reaction fluxes within the cell. We applied these techniques to compare metabolic activity during acute hypoxia in muscle tissue of adapted versus "na?ve" control flies.     

Influence of media selection on NMR based metabolic profiling of human cell lines

Introduction

Comparative metabolic profiling of different human cancer cell lines can reveal metabolic pathways up-regulated or down-regulated in each cell line, potentially providing insight into distinct metabolism taking place in different types of cancer cells. It is noteworthy, however, that human cell lines available from public repositories are deposited with recommended media for optimal growth, and if cell lines to be compared are cultured on different growth media, this introduces a potentially serious confounding variable in metabolic profiling studies designed to identify intrinsic metabolic pathways active in each cell line.

Objectives

The goal of this study was to determine if the culture media used to grow human cell lines had a significant impact on the measured metabolic profiles.

Methods

NMR-based metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, AsPC-1, MiaPaCa-2 and Panc-1, were compared after culture on Dulbecco’s Modified Eagle Medium (DMEM) or Roswell Park Memorial Institute (RPMI-1640) medium.

Results

Comparisons of the same cell lines cultured on different media revealed that the concentrations of many metabolites depended strongly on the choice of culture media. Analyses of different cell lines grown on the same media revealed insight into their metabolic differences.

Conclusion

The choice of culture media can significantly impact metabolic profiles of human cell lines and should be considered an important variable when designing metabolic profiling studies. Also, the metabolic differences of cells cultured on media recommended for optimal growth in comparison to a second growth medium can reveal critical insight into metabolic pathways active in each cell line.

     

Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

Background  

The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published in silico method PAAS was applied for prediction of interactions between protein kinases and their substrates.