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PubMed2006

Pathway analysis of kidney cancer using proteomics and metabolic profiling.

BACKGROUND: Renal cell carcinoma (RCC) is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC). We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. RESULTS: Using 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values < 2.0 E-05) in glycolysis, propanoate metabolism, pyruvate metabolism, urea cycle and arginine/proline metabolism, as well as in the non-metabolic p53 and FAS pathways. In a pilot study using random urine samples from both ccRCC and control patients, we performed metabolic profiling and found that only sorbitol, a component of an alternative glycolysis pathway, is significantly elevated at 5.4-fold in RCC patients as compared to controls. CONCLUSION: Extensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.

Adult↗
PubMed2005

STEP (Statistical Test of Equivalent Pathways) analysis: a mass spectrometric method for carbohydrates and peptides.

We have recently developed a new mass spectrometry method, the STEP (statistical test of equivalent pathways) analysis that uses ion abundances in two tandem mass spectrometry experiments to obtain genealogy information about product ions present in mass spectra. The method requires minimal sample, and it can be performed using a conventional quadrupole ion trap mass spectrometer. To obtain genealogy information, STEP ratios are calculated by comparing the relative abundances of product ions in two MS/MS experiments. These ratios are directly related to the origin of the product ions. Product ions that result directly from the precursor ion always have STEP ratios that are </=1. Ions that result from secondary fragmentation pathways have STEP ratios that are significantly larger than the primary ions, based on a Q test of statistical significance. Consequently, the type (primary or secondary) of all the product ions in an MS/MS experiment can easily be identified in this analysis. The STEP method is applied herein to peptides and carbohydrates, and the STEP results are consistent with validation data for 95% of the ions in this study. This new method has many applications in carbohydrate and peptide analysis. It can be used to support mechanistic studies of peptide fragmentation, and it is useful for discriminating among various isomeric carbohydrates, without the need for reference standards. Several examples are presented to demonstrate the reliability of this method, and an example showing how the method benefits carbohydrate sequencing is also provided.

Amino Acid Sequence↗
PubMed2004

Metabolic pathway analysis of yeast strengthens the bridge between transcriptomics and metabolic networks.

Central carbon metabolism of the yeast Saccharomyces cerevisiae was analyzed using metabolic pathway analysis tools. Elementary flux modes for three substrates (glucose, galactose, and ethanol) were determined using the catabolic reactions occurring in yeast. Resultant elementary modes were used for gene deletion phenotype analysis and for the analysis of robustness of the central metabolism and network functionality. Control-effective fluxes, determined by calculating the efficiency of each mode, were used for the prediction of transcript ratios of metabolic genes in different growth media (glucose-ethanol and galactose-ethanol). A high correlation was obtained between the theoretical and experimental expression levels of 38 genes when ethanol and glucose media were considered. Such analysis was shown to be a bridge between transcriptomics and fluxomics. Control-effective flux distribution was found to be promising in in silico predictions by incorporating functionality and regulation into the metabolic network structure.

Biomass↗
PubMed2006

Phenotype-based screening of mechanistically annotated compounds in combination with gene expression and pathway analysis identifies candidate drug targets in a human squamous carcinoma cell model.

The squamous cell carcinoma HeLa cell line and an epithelial cell line hTERT-RPE with a nonmalignant phenotype were interrogated for HeLa cell selectivity in response to 1267 annotated compounds representing 56 pharmacological classes. Selective cytotoxic activity was observed for 14 of these compounds dominated by cyclic adenosine monophosphate (cAMP) selective phosphodiesterase (PDE) inhibitors, which tended to span a representation of the chemical descriptor space of the library. The PDE inhibitors induced delayed cell death with features compatible with classical apoptosis. The PDE inhibitors were largely inactive when tested against a cell line panel consisting of hematological and nonsquamous epithelial phenotypes. In a genome-wide DNA microarray analysis, PDE3A and PDE2A were found to be significantly increased in HeLa cells compared to the other cell lines. The pathway analysis software PathwayAssist was subsequently used to extract a list of proteins and small molecules retrieved from Medline abstracts associated with the hit compounds. The resulting list consisted of major parts of the cAMP-protein kinase A pathway linking to ERK, P38, and AKT. This molecular network may provide a basis for further exploitation of novel candidate targets for the treatment of squamous cell carcinoma.

Carcinoma, Squamous Cell↗
PubMed2002

Determination of redundancy and systems properties of the metabolic network of Helicobacter pylori using genome-scale extreme pathway analysis.

The capabilities of genome-scale metabolic networks can be described through the determination of a set of systemically independent and unique flux maps called extreme pathways. The first study of genome-scale extreme pathways for the simultaneous formation of all nonessential amino acids or ribonucleotides in Helicobacter pylori is presented. Three key results were obtained. First, the extreme pathways for the production of individual amino acids in H. pylori showed far fewer internal states per external state than previously found in Haemophilus influenzae, indicating a more rigid metabolic network. Second, the degree of pathway redundancy in H. pylori was essentially the same for the production of individual amino acids and linked amino acid sets, but was approximately twice that of the production of the ribonucleotides. Third, the metabolic network of H. pylori was unable to achieve extensive conversion of amino acids consumed to the set of either nonessential amino acids or ribonucleotides and thus diverted a large portion of its nitrogen to ammonia production, a potentially important result for pH regulation in its acidic habitat. Genome-scale extreme pathways elucidate emergent system-wide properties. Extreme pathway analysis is emerging as a potentially important method to analyze the link between the metabolic genotype and its phenotypes.

Amino Acids↗
PubMed2002

Framework for the uncertainty assessment in the impact pathway analysis with an application on a local scale in Spain.

The estimation of damage estimates due to air emissions gives important basic knowledge for decision-making on the level of environmental politics and business strategies. Nowadays, a frequently applied method to estimate environmental damages is the Impact Pathway Analysis (IPA), which can be easily carried out using models such as EcoSense or PathWays. These models produce results in a relatively short term. However, there is a lack of reliability in the results. As in many other environmental software tools, the uncertainty is the key problem that makes it difficult to convince decision-makers by the outcomes of a study. Therefore, a framework that allows assessing the uncertainties within studies in which the IPA is applied on a local scale has been developed. In this assessment framework, the uncertainties of the used parameters, including their spatial and temporal variability, are taken into account. As the model is processing a huge quantity of data, one step of the assessment consists of a screening procedure to determine the parameters that are supposed to be fixed. For the other data, probability distributions have to be selected and classified into two groups: extensively available data for which average and standard deviation can be calculated and data based on little information. A quantification of the uncertainty can be completed by a stochastic model in the form of Monte Carlo (MC) simulation on the basis of the framework. As an illustration of the framework, we have applied it to a study on the installation of an advanced gas treatment in the municipal waste incinerator of Tarragona. It can be shown that the presented stochastic approach gives a lower geometric deviation than the analytical one and that the new gas treatment reduces the environmental damages without any doubt.

Costs and Cost Analysis↗
PubMed2004

Development of a clinical pathways analysis system with adaptive Bayesian nets and data mining techniques.

The use and development of software in the medical field offers tremendous opportunities for making health care delivery more efficient, more effective, and less error-prone. We discuss and explore the use of clinical pathways analysis with Adaptive Bayesian Networks and Data Mining Techniques to perform such analyses. The computation of "lift" (a measure of completed pathways improvement potential) leads us to optimism regarding the potential for this approach.

Bayes Theorem↗
PubMed2004

Metabolic pathway analysis of enzyme-deficient human red blood cells.

Five enzymopathies (G6PDH, TPI, PGI, DPGM and PGK deficiencies) in the human red blood cells are investigated using a stoichiometric modeling approach, i.e., metabolic pathway analysis. Elementary flux modes (EFMs) corresponding to each enzyme deficiency case are analyzed in terms of functional capabilities. When available, experimental findings reported in literature related to metabolic behavior of the human red blood cells are compared with the results of EFM analysis. Control-effective flux (CEF) calculation, a novel approach which allows quantification and interpretation of determined EFMs, is performed for further analysis of enzymopathies. Glutathione reductase reaction is found to be the most effective reaction in terms of its CEF value in all enzymopathies in parallel with its known essential role for red blood cells. Efficiency profiles of the enzymatic reactions upon the degree of enzyme deficiency are obtained by the help of the CEF approach, as a basis for future experimental studies. CEF analysis, which is found to be promising in the analysis of erythrocyte enzymopathies, has the potential to be used in modeling efforts of human metabolism.

Bisphosphoglycerate Mutase↗
PubMedDate not supplied

Pathway analysis and metabolic engineering in Corynebacterium glutamicum.

The gram-positive bacterium Corynebacterium glutamicum is used for the industrial production of amino acids, e.g. of L-glutamate and L-lysine. During the last 15 years, genetic engineering and amplification of genes have become fascinating methods for studying metabolic pathways in greater detail and for the construction of strains with the desired genotypes. In order to obtain a better understanding of the central metabolism and to quantify the in vivo fluxes in C. glutamicum, the [13C]-labelling technique was combined with metabolite balancing to achieve a unifying comprehensive pathway analysis. These methods can determine the flux distribution at the branch point between glycolysis and the pentose phosphate pathway. The in vivo fluxes in the oxidative part of the pentose phosphate pathway calculated on the basis of intracellular metabolite concentrations and the kinetic constants of the purified glucose-6-phosphate and 6-phosphogluconate dehydrogenases determined in vitro were in full accordance with the fluxes measured by the [13C]-labelling technique. These data indicate that the oxidative pentose phosphate pathway in C. glutamicum is mainly regulated by the ratio of NADPH/NADP concentrations and the specific activity of glucose-6-phosphate dehydrogenase. The carbon flux via the oxidative pentose phosphate pathway correlated with the NADPH demand for L-lysine synthesis. Although it has generally been accepted that phosphoenolpyruvate carboxylase fulfills a main anaplerotic function in C. glutamicum, we recently detected that a biotin-dependent pyruvate carboxylase exists as a further anaplerotic enzyme in this bacterium. In addition to the activities of these two carboxylases three enzymes catalysing the decarboxylation of the C4 metabolites oxaloacetate or malate are also present in this bacterium. The individual flux rates at this complex anaplerotic node were investigated by using [13C]-labelled substrates. The results indicate that both carboxylation and decarboxylation occur simultaneously in C. glutamicum so that a high cyclic flux of oxaloacetate via phosphoenolpyruvate to pyruvate was found. Furthermore, we detected that in C. glutamicum two biosynthetic pathways exist for the synthesis of DL-diaminopimelate and L-lysine. As shown by NMR spectroscopy the relative use of both pathways in vivo is dependent on the ammonium concentration in the culture medium. Mutants defective in one pathway are still able to synthesise enough L-lysine for growth, but the L-lysine yields with overproducers were reduced. The luxury of having these two pathways gives C. glutamicum an increased flexibility in response to changing environmental conditions and is also related to the essential need for DL-diaminopimelate as a building block for the synthesis of the murein sacculus.

Corynebacterium↗
PubMed1999

Critical radionuclide/critical pathway analysis for the U.S. Department of Energy's Savannah River Site.

Many different radionuclides have been released to the environment from the Savannah River Site (SRS) during the facility's operational history. However, as shown by this analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to off-site people. This article documents the radiological critical contaminant/critical pathway analysis performed for SRS. If site missions and operations remain constant over the next 30 years, only tritium oxide releases are projected to exceed a maximally exposed individual (MEI) risk of 1.0E-06 for either the airborne or liquid pathways. The critical exposure pathways associated with site airborne releases are inhalation and vegetation consumption, whereas the critical exposure pathways associated with liquid releases are drinking water and fish consumption. For the SRS-specific, nontypical exposure pathways (i.e., recreational fishing and deer and hog hunting), cesium-137 is the critical radionuclide.

Air Pollutants, Radioactive↗
PubMed2006

Microarray-assisted pathway analysis identifies mitogen-activated protein kinase signaling as a mediator of resistance to the green tea polyphenol epigallocatechin 3-gallate in her-2/neu-overexpressing breast cancer cells.

Overexpression of the epidermal growth factor receptor family member Her-2/neu in breast cancer leads to autophosphorylation of the receptor and induction of multiple downstream signaling pathways, including the Akt kinase to nuclear factor-kappaB (NF-kappaB) cascade that is associated with poor prognosis. Previously, we showed that the green tea polyphenol epigallocatechin 3-gallate (EGCG) inhibits growth of NF639 Her-2/neu-driven breast cancer cells via reducing receptor autophosphorylation and downstream Akt and NF-kappaB activities. Interestingly, upon prolonged culture in the presence of EGCG, cells resistant to the polyphenol could be isolated. Here, we report that resistant cells have lost tyrosine phosphorylation on the Her-2/neu receptor. Surprisingly, they displayed elevated NF-kappaB activity, and inhibition of this activity sensitized cells to EGCG. Data from microarray studies of the original and resistant NF639 populations of cells were subjected to Gene Set Enrichment Analysis pathway assessment, which revealed that the mitogen activated protein kinase (MAPK) pathway was activated in the resistant cells. Treatment of the resistant cells with the MAPK inhibitor U0216 reduced growth in soft agar and invasive phenotype, whereas the combination of EGCG and U0216 resulted in cells with a cobblestone epithelial phenotype. Thus, activation of the MAPK pathway mediates resistance to EGCG.

Animals↗
PubMedDate not supplied

Mapping molecular responses to xenoestrogens through Gene Ontology and pathway analysis of toxicogenomic data.

The recent sequencing of mammalian genomes has driven the development of genomic technologies, including microarray-based gene expression profiling, that allow simultaneous measurement of the expression levels of thousands of genes. Gene expression profiling applied to toxicology (toxicogenomics) has the potential to reveal, holistically, the molecular pathways and cellular processes that mediate the adverse responses to a toxicant. However, the initial output of a toxicogenomics experiment consists of a list of genes whose expression is altered upon toxicant exposure. In order to interpret these data in a biological context, new bioinformatic methods must be developed to place gene expression changes in the context of the underlying pathways and processes affected. One emerging approach is the application of Gene Ontology (GO) mapping and pathway analysis to gene expression profiling data. The utility of this in mechanistic toxicology will be illustrated using examples in which GO mapping of toxicogenomic data has provided novel insights into the molecular mechanisms induced by exposure to xenoestrogens.

Animals↗
PubMed2005

Assessment of the risk of introduction of Anoplophora glabripennis (Coleoptera: Cerambycidae) in municipal solid waste from the quarantine area of New York City to landfills outside of the quarantine area: a pathway analysis of the risk of spread and establishment.

The risk associated with spread of Asian longhorned beetle, Anoplophora glabripennis (Motschulsky), from infested areas in New York City to the wide array of landfills across the eastern United States contracted by the city since 1997 was unknown, but of great concern. Landfills, some as far as South Carolina, Virginia, and Ohio, occupied forest types and climates at high risk of Asian longhorned beetle establishment. The city proposed a separate waste wood collection known as the "311 System;" this was estimated to cost federal and state agencies $6.1 to $9.1 million per year, including the cost of processing and disposal of the wood. Pathway analysis was used to quantify the probability that Asian longhorned beetle present in wood waste collected at curbside would survive transport, compaction, and burial to form a mated pair. The study found that in seven alternate management scenarios, risks with most pathways are very low, especially given existing mitigations. Mitigations included chemical control, removal of infested trees, and burial of wood waste in managed landfills that involved multiple-layering, compaction, and capping of dumped waste with a 15-cm soil cover at the end of each day. Although the risk of business-as-usual collection and disposal practices was virtually nil, any changes of policy or practice such as illegal dumping or disposal at a single landfill increased the risk many thousandfold. By rigorously maintaining and monitoring existing mitigations, it was estimated that taxpayers would save $75 to $122 million dollars over the next decade.

Animals↗
PubMed1998

Technologically enhanced naturally occurring radioactive material (NORM): pathway analysis and radiological impact.

The main pathways by which technologically enhanced radioactive materials can impact on human health have been examined. Analytical methods are presented for calculation of the radiation doses for the dominant pathways for external and internal exposure. The application of computer modelling to the assessment of the radiological impact of NORM is also discussed.

Background Radiation↗
PubMedDate not supplied

Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems.

The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an example network and to core metabolism of Escherichia coli demonstrating the connections between the extreme pathways, optimal flux distributions, and phenotypic phase planes. The consequences of changing environmental and internal conditions of the network are examined for growth on glucose and succinate in the face of a variety of gene deletions. The convergence of the calculation of optimal phenotypes through linear programming and the definition of extreme pathways establishes a different perspective for the understanding of how a defined metabolic network is best used under different environmental and internal conditions or, in other words, a pathway basis for the interpretation of the metabolic reaction norm.

Glucose↗
PubMed2026

Subphenogroups of acute heart failure with preserved ejection fraction: comprehensive proteomics and pathway analysis.

BACKGROUND: Heterogeneity of heart failure with preserved ejection fraction (HFpEF) results in significant challenges for treatment development. Identifying and characterising distinct HFpEF phenogroups may aid in tailoring therapeutic strategies for these patients. The objective of this study was to assess proteomic patterns of HFpEF phenogroups identified through a machine-learning-based clustering model, with the aim of uncovering specific biological pathways associated with each phenogroup. METHODS: This study represents a post-hoc analysis of the ongoing Prospective mUlticenteR obServational stUdy of patIenTs with Heart Failure with preserved Ejection Fraction (PURSUIT-HFpEF) study, which is a multicentre prospective observational study of hospitalised patients with acute decompensated HFpEF. Of the overall cohort (N=1238), this study analysed 198 patients with HFpEF with available proteomics data. These patients were classified into four phenogroups using the machine-learning-based clustering model. The SomaScan assay V.4.1 was used to measure levels of >7000 plasma proteins, and subsequent pathway analysis was conducted to determine the biological differences among the phenogroups. RESULTS: We identified four distinct phenogroups: Phenogroup 1 ('rhythm trouble'), Phenogroup 2 ('ventricular-arterial uncoupling'), Phenogroup 3 ('low output and systemic congestion') and Phenogroup 4 ('systemic failure'). The proteomics revealed distinct protein expression profiles among the phenogroups, with ribonuclease 4, tax1-binding protein 1, regenerating islet-derived protein 3-gamma and alpha-1-antichymotrypsin being the most significant markers to specific identified phenogroups. Pathway analysis suggested differences in immune response, autonomic activation, cellular homeostasis and tissue repair mechanisms across the phenogroups. CONCLUSIONS: Using a comprehensive plasma proteomics approach, our study identified distinct proteomic profiles of HFpEF phenogroups, which in turn suggest specific underlying biological processes. These profiles suggest the involvement of inflammatory activation, tissue injury and regenerative responses, immune modulation and systemic stress signalling as key components of HFpEF pathophysiology. TRIAL REGISTRATION NUMBER: UMIN-CTR ID: UMIN000021831.

Humans↗
PubMed2005

[Application of a metabolic-pathway-analysis based breeding strategy enhances the production of pyruvate by Torulopsis glabrata].

To further enhance the pyruvate productivity by multi-vitamin auxotrophic yeast Torulopsis glabrata, a breeding strategy aiming at decreasing the activity of pyruvate decarboxylase but increasing the activity of acetyl-CoA synthetase was developed based on analysis of pyruvate-related metabolic pathways. Nitrosoguanidine mutagenized cells of T. glabrata WSH-IP303 were screened for mutants that require acetate for complete growth on glucose minimum medium. A mutant, T. glabrata CCTCC M202019, produced pyruvate 21% higher than that of the parent strain and was genetically stable in flask cultures, was selected as a working strain. To elucidate the metabolic changes that led to the increase of pyruvate production, the activities of enzymes that involved in pyruvate-related metabolic pathways of the mutant and the parent strain were determined. Enzymatic analysis revealed that, compared with the parent strain WSH-IP303, the activity of pyruvate decarboxylase of the mutant strain CCTCC M202019 decreased by roughly 40%, while the activity of acetyl-CoA synthetase of the latter increased by 103.5% or 57.4%, respectively, in the presence or absence of acetate. When 6 g/L sodium acetate was added to the medium, pyruvate production by the mutant strain CCTCC M202019 reached 68.7 g/L at 62 h (yield on glucose, 0.651 g/g) in fermentations performed in a 7-L jar fermentor, indicating the shortage of cytosolic acetyl-CoA resulted from the disruption of pyruvate decarboxylase was properly compensated by the increase of the activity of acetyl-CoA synthetase.

Acetates↗
PubMed2004

Comparison of network-based pathway analysis methods.

Network-based definitions of biochemical pathways have emerged in recent years. These pathway definitions insist on the balanced use of a whole network of biochemical reactions. Two such related definitions, elementary modes and extreme pathways, have generated novel hypotheses regarding biochemical network function. The relationship between these two approaches can be illustrated by comparing and contrasting the elementary modes and extreme pathways of previously published metabolic reconstructions of the human red blood cell (RBC) and the human pathogen Helicobacter pylori. Descriptions of network properties generated by using these two approaches in the analysis of realistic metabolic networks need careful interpretation.

Algorithms↗