52197587
Computational prediction of changes in brain metabolic fluxes during Parkinson’s disease from mRNA expression
Background Parkinson’s disease is a widespread neurodegenerative disorder which affects brain metabolism. Although changes in gene expression during disease are often measured, it is difficult to predict metabolic fluxes from gene expression data. Here we explore the hypothesis that changes in gene expression for enzymes tend to parallel flux changes in biochemical reaction pathways in the brain metabolic network. This hypothesis is the basis of a computational method to predict metabolic flux changes from post-mortem gene expression measurements in Parkinson’s disease (PD) brain. Results We use a network model of central metabolism and optimize the correspondence between relative changes in fluxes and in gene expression. To this end we apply the Least-squares with Equalities and Inequalities algorithm integrated with Flux Balance Analysis (Lsei-FBA). We predict for PD (1) decreases in glycolytic rate and oxygen consumption and an increase in lactate production in brain cortex that correspond with measurements (2) relative flux decreases in ATP synthesis, in the malate-aspartate shuttle and midway in the TCA cycle that are substantially larger than relative changes in glucose uptake in the substantia nigra, dopaminergic neurons and most other brain regions (3) shifts in redox shuttles between cytosol and mitochondria (4) in contrast to Alzheimer’s disease: little activation of the gamma-aminobutyric acid shunt pathway in compensation for decreased alpha-ketoglutarate dehydrogenase activity (5) in the globus pallidus internus, metabolic fluxes are increased, reflecting increased functional activity. Conclusion Our method predicts metabolic changes from gene expression data that correspond in direction and order of magnitude with presently available experimental observations during Parkinson’s disease, indicating that the hypothesis may be useful for some biochemical pathways. Lsei-FBA generates predictions of flux distributions in neurons and small brain regions for which accurate metabolic flux measurements are not yet possible.
5042874
Using Bioconductor Package BiGGR for Metabolic Flux Estimation Based on Gene Expression Changes in Brain
Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer’s disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.
45318155
Mitochondrial dysfunction in the limelight of Parkinson's disease pathogenesis.
Parkinson's disease (PD) is a progressive neurodegenerative movement disorder with unknown etiology. It is marked by widespread neurodegeneration in the brain with profound loss of A9 midbrain dopaminergic neurons in substantia nigra pars compacta. Several theories of biochemical abnormalities have been linked to pathogenesis of PD of which mitochondrial dysfunction due to an impairment of mitochondrial complex I and subsequent oxidative stress seems to take the center stage in experimental models of PD and in postmortem tissues of sporadic forms of illness. Recent identification of specific gene mutations and their influence on mitochondrial functions has further reinforced the relevance of mitochondrial abnormalities in disease pathogenesis. In both sporadic and familial forms of PD abnormal mitochondrial paradigms associated with disease include impaired functioning of the mitochondrial electron transport chain, aging associated damage to mitochondrial DNA, impaired calcium buffering, and anomalies in mitochondrial morphology and dynamics. Here we provide an overview of specific mitochondrial functions affected in sporadic and familial PD that play a role in disease pathogenesis. We propose to utilize these gained insights to further streamline and focus the research to better understand mitochondria's role in disease development and exploit potential mitochondrial targets for therapeutic interventions in PD pathogenesis.
32799013
The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels
Metabolic fluxes may be regulated “hierarchically,” e.g., by changes of gene expression that adjust enzyme capacities (Vmax) and/or “metabolically” by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the ≈10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50–20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75–100% of the regulation of protein levels.
18590657
Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism
Constraint-based models of metabolism are a widely used framework for predicting flux distributions in genome-scale biochemical networks. The number of published methods for integration of transcriptomic data into constraint-based models has been rapidly increasing. So far the predictive capability of these methods has not been critically evaluated and compared. This work presents a survey of recently published methods that use transcript levels to try to improve metabolic flux predictions either by generating flux distributions or by creating context-specific models. A subset of these methods is then systematically evaluated using published data from three different case studies in E. coli and S. cerevisiae. The flux predictions made by different methods using transcriptomic data are compared against experimentally determined extracellular and intracellular fluxes (from 13C-labeling data). The sensitivity of the results to method-specific parameters is also evaluated, as well as their robustness to noise in the data. The results show that none of the methods outperforms the others for all cases. Also, it is observed that for many conditions, the predictions obtained by simple flux balance analysis using growth maximization and parsimony criteria are as good or better than those obtained using methods that incorporate transcriptomic data. We further discuss the differences in the mathematical formulation of the methods, and their relation to the results we have obtained, as well as the connection to the underlying biological principles of metabolic regulation.
38249225
Multinuclear Magnetic Resonance Spectroscopy for in Vivo Assessment of Mitochondrial Dysfunction in Parkinson's Disease
Parkinson's disease (PD) is a common and often devastating neurodegenerative disease affecting up to one million individuals in the United States alone. Multiple lines of evidence support mitochondrial dysfunction as a primary or secondary event in PD pathogenesis; a better understanding, therefore, of how mitochondrial function is altered in vivo in brain tissue in PD is a critical step toward developing potential PD biomarkers. In vivo study of mitochondrial metabolism in human subjects has previously been technically challenging. However, proton and phosphorus magnetic resonance spectroscopy (1H and 31P MRS) are powerful noninvasive techniques that allow evaluation in vivo of lactate, a marker of anaerobic glycolysis, and high energy phosphates, such as adenosine triphosphate and phosphocreatine, directly reflecting mitochondrial function. This article reviews previous 1H and 31P MRS studies in PD, which demonstrate metabolic abnormalities consistent with mitochondrial dysfunction, and then presents recent 1H MRS data revealing abnormally elevated lactate levels in PD subjects.
10630494
Network-based prediction of human tissue-specific metabolism
Direct in vivo investigation of mammalian metabolism is complicated by the distinct metabolic functions of different tissues. We present a computational method that successfully describes the tissue specificity of human metabolism on a large scale. By integrating tissue-specific gene- and protein-expression data with an existing comprehensive reconstruction of the global human metabolic network, we predict tissue-specific metabolic activity in ten human tissues. This reveals a central role for post-transcriptional regulation in shaping tissue-specific metabolic activity profiles. The predicted tissue specificity of genes responsible for metabolic diseases and tissue-specific differences in metabolite exchange with biofluids extend markedly beyond tissue-specific differences manifest in enzyme-expression data, and are validated by large-scale mining of tissue-specificity data. Our results establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.
13930842
Complex I: Inhibitors, inhibition and neurodegeneration
Complex I is the first protein component of the mitochondrial respiratory chain and as such plays a crucial role in ATP production and mitochondrial function in general. Mitochondrial dysfunction has been identified in a number of neurodegenerative diseases. In some of these the mitochondrial abnormality is primary and in others secondary. Mitochondrial toxins are capable of producing relatively selective neuronal cell death and have been used to produce models of human neurodegenerative diseases e.g. 1-methyl 4-phenyl 1,2,3,6 tetrahydropyridine (MPTP) for Parkinson's disease, and 3-nitropropionic acid for Huntington's disease. Annonacin, an ingredient of local soursop, is a Complex I inhibitor and has been incriminated as the cause of a parkinsonian tauopathy disorder in Guadeloupe. A systematic analysis has identified several environmentally available potent lipophilic Complex I inhibitors that can induce neuronal cell death in striatal cultures and somatodendritic redistribution of tau protein. It is possible that these compounds may contribute to the pathogenesis of neurodegenerative disorders, although further work must be done to confirm their potential participation in pathogenesis.
4421515
Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases
Many lines of evidence suggest that mitochondria have a central role in ageing-related neurodegenerative diseases. Mitochondria are critical regulators of cell death, a key feature of neurodegeneration. Mutations in mitochondrial DNA and oxidative stress both contribute to ageing, which is the greatest risk factor for neurodegenerative diseases. In all major examples of these diseases there is strong evidence that mitochondrial dysfunction occurs early and acts causally in disease pathogenesis. Moreover, an impressive number of disease-specific proteins interact with mitochondria. Thus, therapies targeting basic mitochondrial processes, such as energy metabolism or free-radical generation, or specific interactions of disease-related proteins with mitochondria, hold great promise.
6635404
Mitochondrial Complex I Deficiency in Parkinson's Disease
Abstract: The structure and function of mitochondrial respiratory‐chain enzyme proteins were studied postmortem in the substantia nigra of nine patients with Parkinson's disease and nine matched controls. Total protein and mitochondrial mass were similar in the two groups. NADH‐ubiquinone reductase (Complex I) and NADH cytochrome c reductase activities were significantly reduced, whereas succinate cytochrome c reductase activity was normal. These results indicated a specific defect of Complex I activity in the substantia nigra of patients with Parkinson's disease. This biochemical defect is the same as that produced in animal models of parkinsonism by 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP) and adds further support to the proposition that Parkinson's disease may be due to an environmental toxin with action(s) similar to those of MPTP.
13077479
Complex I deficiency in Parkinson's disease frontal cortex
A study of complex I (NADH:ubiquinone oxidoreductase) activity in Parkinson's disease (PD) brain has identified loss of activity only in substantia nigra although loss of activity of this enzyme has been identified in a number of non-brain tissues. We investigated this paradox by studying complex I and other complexes of the mitochondrial electron transport chain in frontal cortex from PD and aged control brain using a variety of assay conditions and tissue preparations. We found increasingly significant losses of complex I activity in PD frontal cortex as increasingly pure mitochondria were studied. Complexes II, III, and IV were comparable in PD and controls. Inclusion of bovine serum albumin in the assay increased enzyme activity but lessened discrimination between PD and controls. Complex I deficiency in PD brain is not confined to substantia nigra. Methodological issues are critical in demonstrating this loss of activity.
206676400
PGC-1α, A Potential Therapeutic Target for Early Intervention in Parkinson’s Disease
Abnormal expression of genes for energy regulation in Parkinson’s disease patients identifies a master regulator as a possible therapeutic target for early intervention. Getting to the Root of Parkinson’s Disease Parkinson’s disease (PD) is a debilitating neurodegenerative disorder that results in the loss of dopamine neurons in the substantia nigra of the brain. Degeneration of these movement-related neurons predictably causes rigidity, slowness of movement, and resting tremor, but patients also show cognitive changes. Although gene mutations have been identified in several families with PD, the cause of the more common sporadic form is not known. Certain environmental factors, such as exposure to the pesticide rotenone, combined with a genetic susceptibility, are thought to confer risk for developing PD. A key pathological feature seen in postmortem brain tissue from PD patients is Lewy bodies, neuronal inclusions containing clumps of the α-synuclein protein (which is mutated in familial PD), as well as damaged mitochondria. Taking a systems biology approach to pinpoint the root cause of PD, Zheng et al. now implicate altered activity of the master transcription factor PGC-1α and the genes it regulates in the early stages of PD pathogenesis. To detect new sets of genes that may be associated with PD, the investigators did a meta-analysis of 17 independent genome-wide gene expression microarray studies that had been performed on a total of 322 postmortem brain tissue samples and 88 blood samples. The samples came from presymptomatic and symptomatic PD patients, as well as from control individuals who did not show any neurological deficits at autopsy. Nine genome-wide expression studies were conducted either on dopaminergic neurons obtained by laser capture from substantia nigra (three studies) or on substantia nigra homogenates (six studies). The authors then used a powerful tool called Gene Set Enrichment Analysis to sift through 522 gene sets (a gene set is a group of genes involved in one biological pathway or process). At the end of this tour-de-force analysis, they identified 10 gene sets that were all associated with PD. The gene sets with the strongest association contained nuclear genes encoding subunits of the electron transport chain proteins found in mitochondria. These genes all showed decreased expression in substantia nigra dopaminergic neurons (obtained by laser capture) even in the earliest stages of PD. Furthermore, a second gene set associated with PD and also underexpressed in the earliest stages of PD encodes enzymes involved in glucose metabolism. These results are compelling because many studies have already implicated dysfunctional mitochondria and altered energy metabolism as well as defective glucose metabolism in PD. The authors realized that these gene sets had in common the master transcriptional regulator, PGC-1α, and surmised that disruption of PGC-1α expression might be a root cause of PD. They tested this hypothesis in cultured dopaminergic neurons from embryonic rat midbrain forced to express a mutant form of α-synuclein. Overexpression of PGC-1α in these neurons resulted in activation of electron transport genes and protection against neuronal damage induced by mutant α-synuclein. In other cultured neurons treated with rotenone, overexpression of PGC-1α also was protective, blocking pesticide-induced neuronal cell death. These exciting findings identify altered expression of PGC-1α and the genes it regulates as key players during early PD pathogenesis. This potential new target could be exploited therapeutically to interfere with the pathological process during the earliest stages before permanent damage and neuronal loss occurs. Parkinson’s disease affects 5 million people worldwide, but the molecular mechanisms underlying its pathogenesis are still unclear. Here, we report a genome-wide meta-analysis of gene sets (groups of genes that encode the same biological pathway or process) in 410 samples from patients with symptomatic Parkinson’s and subclinical disease and healthy controls. We analyzed 6.8 million raw data points from nine genome-wide expression studies, and 185 laser-captured human dopaminergic neuron and substantia nigra transcriptomes, followed by two-stage replication on three platforms. We found 10 gene sets with previously unknown associations with Parkinson’s disease. These gene sets pinpoint defects in mitochondrial electron transport, glucose utilization, and glucose sensing and reveal that they occur early in disease pathogenesis. Genes controlling cellular bioenergetics that are expressed in response to peroxisome proliferator–activated receptor γ coactivator-1α (PGC-1α) are underexpressed in Parkinson’s disease patients. Activation of PGC-1α results in increased expression of nuclear-encoded subunits of the mitochondrial respiratory chain and blocks the dopaminergic neuron loss induced by mutant α-synuclein or the pesticide rotenone in cellular disease models. Our systems biology analysis of Parkinson’s disease identifies PGC-1α as a potential therapeutic target for early intervention.
17085290
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions
BackgroundGenome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use.DescriptionWe describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.ConclusionsBiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu.
11016714
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
23315338
Gene expression profiling of parkinsonian substantia nigra pars compacta; alterations in ubiquitin-proteasome, heat shock protein, iron and oxidative stress regulated proteins, cell adhesion/cellular matrix and vesicle trafficking genes
Summary.Gene expression profiling of human substantia nigra pars compacta (SNpc) from Parkinson’s disease (PD) patients, was examined employing high density microarrays. We identified alterations in the expression of 137 genes, with 68 down regulated and 69 up regulated. The down regulated genes belong to signal transduction, protein degradation (e.g. ubiquitin-proteasome subunits), dopaminergic transmission/metabolism, ion transport, protein modification/phosphorylation and energy pathways/glycolysis functional classes. Up-regulated genes, clustered mainly in biological processes involving cell adhesion/cytoskeleton, extracellular matrix components, cell cycle, protein modification/phosphorylation, protein metabolism, transcription and inflammation/stress (e.g. key iron and oxygen sensor EGLN1). One major finding in the present study is the particular decreased expression of SKP1A, a member of the SCF (E3) ligase complex specifically in the substantia nigra (SN) of sporadic parkinsonian patients, which may lead to a wide impairment in the function of an entire repertoire of proteins subjected to regulatory ubiquitination. These findings reveal novel players in the neurodegenerative scenario and provide potential targets for the development of novel drug compounds.
254807
Expression profiling of substantia nigra in Parkinson disease, progressive supranuclear palsy, and frontotemporal dementia with parkinsonism.
BACKGROUND
Parkinson disease (PD) is characterized by loss of dopaminergic neurons in the substantia nigra. Genes contributing to rare mendelian forms of PD have been identified, but the genes involved in the more common idiopathic PD are not well understood.


OBJECTIVES
To identify genes important to PD pathogenesis using microarrays and to investigate their potential to aid in diagnosing parkinsonism.


DESIGN
Microarray expression analysis of postmortem substantia nigra tissue.


PATIENTS
Substantia nigra samples from 14 unrelated individuals were analyzed, including 6 with PD, 2 with progressive supranuclear palsy, 1 with frontotemporal dementia with parkinsonism, and 5 control subjects.


MAIN OUTCOME MEASURES
Identification of genes significantly differentially expressed (P<.05) using Affymetrix U133A microarrays.


RESULTS
There were 142 genes that were significantly differentially expressed between PD cases and controls and 96 genes that were significantly differentially expressed between the combined progressive supranuclear palsy and frontotemporal dementia with parkinsonism cases and controls. The 12 genes common to all 3 disorders may be related to secondary effects. Hierarchical cluster analysis after exclusion of these 12 genes differentiated 4 of the 6 PD cases from progressive supranuclear palsy and frontotemporal dementia with parkinsonism.


CONCLUSIONS
Four main molecular pathways are altered in PD substantia nigra: chaperones, ubiquitination, vesicle trafficking, and nuclear-encoded mitochondrial genes. These results correlate well with expression analyses performed in several PD animal models. Expression analyses have promising potential to aid in postmortem diagnostic evaluation of parkinsonism.
24537019
Transcriptional analysis of multiple brain regions in Parkinson's disease supports the involvement of specific protein processing, energy metabolism, and signaling pathways, and suggests novel disease mechanisms
In both genetic and idiopathic forms of Parkinson's disease (PD), considerable evidence supports the involvement of α‐synuclein, electron transport chain complex I, protein aggregation, and the ubiquitin‐proteasome system. To investigate alterations in the transcription of genes that comprise these pathways, we performed gene expression profiling and functional gene group analysis of three brain regions (the substantia nigra, putamen, and area 9) in postmortem tissue from matched groups of PD or control subjects (n = 15/group). Verification of selected changes was performed using RT‐PCR, and visualization of selected changes in expression was accomplished using in situ hybridization (ISH). Our results provide strong support for the impairment of multiple electron transport chain complexes and the ubiquitin‐proteasomal system in PD, along with a robust induction of heat shock proteins and some anti‐apoptotic gene groups. Several novel gene and gene group findings were also obtained that offer new insight into the pathogenesis and potential treatment of PD. © 2005 Wiley‐Liss, Inc.
9788073
Whole genome expression profiling of the medial and lateral substantia nigra in Parkinson’s disease
We have used brain tissue from clinically well-documented and neuropathologically confirmed cases of sporadic Parkinson’s disease to establish the transcriptomic expression profile of the medial and lateral substantia nigra. In addition, the superior frontal cortex was analyzed in a subset of the same cases. DNA oligonucleotide microarrays were employed, which provide whole human genome coverage. A total of 570 genes were found to be differentially regulated at a high level of significance. A large number of differentially regulated expressed sequence tags were also identified. Levels of mRNA sequences encoded by genes of key interest were validated by means of quantitative real-time polymerase chain reaction (PCR). Comparing three different normalization procedures, results based on the recently published GeneChip Robust Multi Array algorithm were found to be the most accurate predictor of real-time PCR results. Several new candidate genes which map to PARK loci are reported. In addition, the DNAJ family of chaperones is discussed in the context of Parkinson’s disease pathogenesis.
24344567
Multiregional gene expression profiling identifies MRPS6 as a possible candidate gene for Parkinson's disease.
Combining large-scale gene expression approaches and bioinformatics may provide insights into the molecular variability of biological processes underlying neurodegeneration. To identify novel candidate genes and mechanisms, we conducted a multiregional gene expression analysis in postmortem brain. Gene arrays were performed utilizing Affymetrix HG U133 Plus 2.0 gene chips. Brain specimens from 21 different brain regions were taken from Parkinson's disease (PD) (n = 22) and normal aged (n = 23) brain donors. The rationale for conducting a multiregional survey of gene expression changes was based on the assumption that if a gene is changed in more than one brain region, it may be a higher probability candidate gene compared to genes that are changed in a single region. Although no gene was significantly changed in all of the 21 brain regions surveyed, we identified 11 candidate genes whose pattern of expression was regulated in at least 18 out of 21 regions. The expression of a gene encoding the mitochondria ribosomal protein S6 (MRPS6) had the highest combined mean fold change and topped the list of regulated genes. The analysis revealed other genes related to apoptosis, cell signaling, and cell cycle that may be of importance to disease pathophysiology. High throughput gene expression is an emerging technology for molecular target discovery in neurological and psychiatric disorders. The top gene reported here is the nuclear encoded MRPS6, a building block of the human mitoribosome of the oxidative phosphorylation system (OXPHOS). Impairments in mitochondrial OXPHOS have been linked to the pathogenesis of PD.
46090905
Transcriptional changes in multiple system atrophy and Parkinson's disease putamen
Multiple system atrophy (MSA) and sporadic, non-mendelian Parkinson's disease (PD) are progressive neurodegenerative disorders with overlapping clinical symptoms and pathology. The etiology of both disorders is unknown, and complex combinations of multiple susceptibility genes and environmental factors are thought to be involved. Both disorders are characterized by ubiquitous alpha-synuclein aggregates in distinct regions and cell types of the central nervous system. In PD, alpha-synuclein-positive aggregates appear to be largely neuronal while in MSA oligodendroglial inclusions prevail. In PD patients, the alpha-synuclein pathology is thought to evolve in a rather regular pattern, starting in the brainstem and olfactory bulb and extending gradually onto the substantia nigra and ultimately the cerebral cortex while the cerebellum is largely spared. MSA pathology has not been graded in a similar way yet; neuropathological analyses revealed neurodegeneration and gliosis primarily in the brainstem, midbrain and basal ganglia and the cerebellum, while the cortex is largely spared. To identify disease-specific transcriptional patterns in MSA, we chose CNS regions differentially affected in MSA and PD for comparative gene expression profiling: putamen, cerebellum and occipital cortex. Four genes were regulated in both MSA and PD putamen and twelve in MSA and PD cerebellum. Regulated transcripts were validated using real-time quantitative RT-PCR, and immunohistochemistry was performed for the most significantly downregulated transcripts in MSA and PD putamen, GPR86 and RGS14, associated with G protein signaling and transcriptional regulation.
32362062
Molecular markers of early Parkinson's disease based on gene expression in blood
Parkinson's disease (PD) progresses relentlessly and affects five million people worldwide. Laboratory tests for PD are critically needed for developing treatments designed to slow or prevent progression of the disease. We performed a transcriptome-wide scan in 105 individuals to interrogate the molecular processes perturbed in cellular blood of patients with early-stage PD. The molecular multigene marker here identified is associated with risk of PD in 66 samples of the training set comprising healthy and disease controls [third tertile cross-validated odds ratio of 5.7 (P for trend 0.005)]. It is further validated in 39 independent test samples [third tertile odds ratio of 5.1 (P for trend 0.04)]. Insights into disease-linked processes detectable in peripheral blood are offered by 22 unique genes differentially expressed in patients with PD versus healthy individuals. These include the cochaperone ST13, which stabilizes heat-shock protein 70, a modifier of α-synuclein misfolding and toxicity. ST13 messenger RNA copies are lower in patients with PD (mean ± SE 0.59 ± 0.05) than in controls (0.96 ± 0.09) (P = 0.002) in two independent populations. Thus, gene expression signals measured in blood can facilitate the development of biomarkers for PD.
15230265
Effects of gender on nigral gene expression and parkinson disease
To identify gene expression patterns in human dopamine (DA) neurons in the substantia nigra pars compacta (SNc) of male and female control and Parkinson disease (PD) patients, we harvested DA neurons from frozen SNc from 16 subjects (4 male PDs, 4 female PDs, 4 male and 4 female controls) using Laser Capture microdissection and microarrays. We assessed for enrichment of functional categories with a hypergeometric distribution. The data were validated with QPCR. We observed that gender has a pervasive effect on gene expression in DA neurons. Genes upregulated in females relative to males are mainly involved in signal transduction and neuronal maturation, while in males some of the upregulated genes (alpha-synuclein and PINK1) were previously implicated in the pathogenesis of PD. In females with PD we found alterations in genes with protein kinase activity, genes involved in proteolysis and WNT signaling pathway, while in males with PD there were alterations in protein-binding proteins and copper-binding proteins. Our data reveal broad gender-based differences in gene expression in human dopaminergic neurons of SNc that may underlie the predisposition of males to PD. Moreover, we show that gender influences the response to PD, suggesting that the nature of the disease and the response to treatment may be gender-dependent.
6432295
Mining Biological Pathways Using WikiPathways Web Services
WikiPathways is a platform for creating, updating, and sharing biological pathways [1]. Pathways can be edited and downloaded using the wiki-style website. Here we present a SOAP web service that provides programmatic access to WikiPathways that is complementary to the website. We describe the functionality that this web service offers and discuss several use cases in detail. Exposing WikiPathways through a web service opens up new ways of utilizing pathway information and assisting the community curation process.
458489
Presenting and exploring biological pathways with PathVisio
BackgroundBiological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs.ResultsPathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at http://www.pathvisio.org.ConclusionPathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.
7119757
Improving metabolic flux predictions using absolute gene expression data
BackgroundConstraint-based analysis of genome-scale metabolic models typically relies upon maximisation of a cellular objective function such as the rate or efficiency of biomass production. Whilst this assumption may be valid in the case of microorganisms growing under certain conditions, it is likely invalid in general, and especially for multicellular organisms, where cellular objectives differ greatly both between and within cell types. Moreover, for the purposes of biotechnological applications, it is normally the flux to a specific metabolite or product that is of interest rather than the rate of production of biomass per se.ResultsAn alternative objective function is presented, that is based upon maximising the correlation between experimentally measured absolute gene expression data and predicted internal reaction fluxes. Using quantitative transcriptomics data acquired from Saccharomyces cerevisiae cultures under two growth conditions, the method outperforms traditional approaches for predicting experimentally measured exometabolic flux that are reliant upon maximisation of the rate of biomass production.ConclusionDue to its improved prediction of experimentally measured metabolic fluxes, and of its lack of a requirement for knowledge of the biomass composition of the organism under the conditions of interest, the approach is likely to be of rather general utility. The method has been shown to predict fluxes reliably in single cellular systems. Subsequent work will investigate the method’s ability to generate condition- and tissue-specific flux predictions in multicellular organisms.
28469537
Cerebral blood flow and metabolic rate of oxygen, glucose, lactate, pyruvate, ketone bodies and amino acids
The cerebral blood flow (CBF) and cerebral metabolic rate (CMR) of oxygen, glucose, lactate, pyruvate, ketone bodies and 24 amino acids were examined in 12 patients with presenile dementia and in seven with normal‐pressure hydrocephalus.
20460921
Increased Pentose Phosphate Pathway Flux after Clinical Traumatic Brain Injury: A [1,2-13C2]glucose Labeling Study in Humans
Patients with traumatic brain injury (TBI) routinely exhibit cerebral glucose uptake in excess of that expected by the low levels of oxygen consumption and lactate production. This brings into question the metabolic fate of glucose. Prior studies have shown increased flux through the pentose phosphate cycle (PPC) during cellular stress. This study assessed the PPC after TBI in humans. [1,2-13C2]glucose was infused for 60 mins in six consented, severe-TBI patients (GCS < 9) and six control subjects. Arterial and jugular bulb blood sampled during infusion was analyzed for 13C-labeled isotopomers of lactate by gas chromatography/mass spectroscopy. The product of lactate concentration and fractional abundance of isotopomers was used to determine blood concentration of each isotopomer. The difference of jugular and arterial concentrations determined cerebral contribution. The formula PPC = (m1/m2)/(3 + (m1/m2)) was used to calculate PPC flux relative to glycolysis. There was enrichment of [1,2-13C2]glucose in arterial-venous blood (enrichment averaged 16.6% in TBI subjects and 28.2% in controls) and incorporation of 13C-label into lactate, showing metabolism of labeled substrate. The PPC was increased in TBI patients relative to controls (19.6 versus 6.9%, respectively; P = 0.002) and was excellent for distinguishing the groups (AUC = 0.944, P < 0.0001). No correlations were found between PPC and other clinical parameters, although PPC was highest in patients studied within 48 h of injury (averaging 33% versus 13% in others; P = 0.0006). This elevation in the PPC in the acute period after severe TBI likely represents a shunting of substrate into alternative biochemical pathways that may be critical for preventing secondary injury and initiating recovery.
17871573
Neuronal–Glial Glucose Oxidation and Glutamatergic–GABAergic Function
Prior 13C magnetic resonance spectroscopy (MRS) experiments, which simultaneously measured in vivo rates of total glutamate-glutamine cycling (Vcyc(tot)) and neuronal glucose oxidation (CMRglc(ox), N), revealed a linear relationship between these fluxes above isoelectricity, with a slope of ~1. In vitro glial culture studies examining glutamate uptake indicated that glutamate, which is cotransported with Na+, stimulated glial uptake of glucose and release of lactate. These in vivo and in vitro results were consolidated into a model: recycling of one molecule of neurotransmitter between glia and neurons was associated with oxidation of one glucose molecule in neurons; however, the glucose was taken up only by glia and all the lactate (pyruvate) generated by glial glycolysis was transferred to neurons for oxidation. The model was consistent with the 1:1 relationship between ΔCMRglc(ox), N and ΔVcyc(tot) measured by 13C MRS. However, the model could not specify the energetics of glia and γ-amino butyric acid (GABA) neurons because quantitative values for these pathways were not available. Here, we review recent 13C and 14C tracer studies that enable us to include these fluxes in a more comprehensive model. The revised model shows that glia produce at least 8% of total oxidative ATP and GABAergic neurons generate ~18% of total oxidative ATP in neurons. Neurons produce at least 88% of total oxidative ATP, and take up ~26% of the total glucose oxidized. Glial lactate (pyruvate) still makes the major contribution to neuronal oxidation, but ~30% less than predicted by the prior model. The relationship observed between ΔCMRglc(ox), N and ΔVcyc(tot) is determined by glial glycolytic ATP as before. Quantitative aspects of the model, which can be tested by experimentation, are discussed.
14272832
The contribution of GABA to glutamate/glutamine cycling and energy metabolism in the rat cortex in vivo.
Previous studies have shown that the glutamate/glutamine (Glu/Gln) neurotransmitter cycle and neuronal glucose oxidation are proportional (1:1), with increasing neuronal activity above isoelectricity. GABA, a product of Glu metabolism, is synthesized from astroglial Gln and contributes to total Glu/Gln neurotransmitter cycling, although the fraction contributed by GABA is unknown. In the present study, we used (13)C NMR spectroscopy together with i.v. infusions of [1,6-(13)C(2)]glucose and [2-(13)C]acetate to separately determine rates of Glu/Gln and GABA/Gln cycling and their respective tricarboxylic acid cycles in the rat cortex under conditions of halothane anesthesia and pentobarbital-induced isoelectricity. Under 1% halothane anesthesia, GABA/Gln cycle flux comprised 23% of total (Glu plus GABA) neurotransmitter cycling and 18% of total neuronal tricarboxylic acid cycle flux. In isoelectric cortex, glucose oxidation was reduced >3-fold in glutamatergic and GABAergic neurons, and neurotransmitter cycling was below detection. Hence, in both cell types, the primary energetic costs are associated with neurotransmission, which increase together as cortical activity is increased. The contribution of GABAergic neurons and inhibition to cortical energy metabolism has broad implications for the interpretation of functional imaging signals.
23616291
The effects of alternate optimal solutions in constraint-based genome-scale metabolic models.
Genome-scale constraint-based models of several organisms have now been constructed and are being used for model driven research. A key issue that may arise in the use of such models is the existence of alternate optimal solutions wherein the same maximal objective (e.g., growth rate) can be achieved through different flux distributions. Herein, we investigate the effects that alternate optimal solutions may have on the predicted range of flux values calculated using currently practiced linear (LP) and quadratic programming (QP) methods. An efficient LP-based strategy is described to calculate the range of flux variability that can be present in order to achieve optimal as well as suboptimal objective states. Sample results are provided for growth predictions of E. coli using glucose, acetate, and lactate as carbon substrates. These results demonstrate the extent of flux variability to be highly dependent on environmental conditions and network composition. In addition we examined the impact of alternate optima for growth under gene knockout conditions as calculated using QP-based methods. It was observed that calculations using QP-based methods can show significant variation in growth rate if the flux variability among alternate optima is high. The underlying biological significance and general source of such flux variability is further investigated through the identification of redundancies in the network (equivalent reaction sets) that lead to alternate solutions. Collectively, these results illustrate the variability inherent in metabolic flux distributions and the possible implications of this heterogeneity for constraint-based modeling approaches. These methods also provide an efficient and robust method to calculate the range of flux distributions that can be derived from quantitative fermentation data.
743150
Perfusion and metabolism imaging studies in Parkinson's disease.
Positron emission tomography (PET) and single photon emission computed tomography (SPECT) are important tools in the evaluation of brain blood flow and glucose metabolism in Parkinson's disease (PD). However, conflicting results are reported in the literature depending on the type of imaging data analysis employed. The present review gives a comprehensive summary of the perfusion and metabolism literature in the field of PD research, including quantitative PET studies, normalized PET and SPECT studies, autoradiography studies in animal models of PD, and simulation studies of PD data. It is concluded that PD most likely is characterized by widespread cortical hypometabolism, probably even at early disease stages. Widespread subcortical hypermetabolism is probably not a feature of PD, although certain small basal ganglia structures, such as the external pallidum, may display true hypermetabolism in the absolute sense. This observation is also in agreement with the animal literature.
23184932
Proton MR spectroscopy of the brain in 14 patients with Parkinson disease.
PURPOSE
To determine whether the proton spectra from patients with clinically diagnosed Parkinson disease differ from the spectra of age-matched healthy subjects with respect to the major cerebral metabolite resonances as well as lactate.


METHODS
Fourteen patients with Parkinson disease (38 to 81 years of age) and 13 healthy control subjects (37 to 81 years of age) were studied using image-guided, single-voxel (27-cm3 volume) proton MR spectroscopy of the occipital lobe.


RESULTS
The peak area ratios of N-acetyl aspartate to creatine and N-acetyl aspartate to choline for Parkinson patients did not show a statistically significant difference from the corresponding ratios for control subjects. There was a very significant increase in the ratio of lactate to N-acetyl aspartate for patients with Parkinson disease, with the greatest increase (threefold) manifested by the subgroup (n = 4) with dementia. The difference in N-acetyl aspartate to choline between women (n = 7) with Parkinson disease and healthy women (n = 9) approached significance. No dependence of the peak ratios on age, duration of Parkinson disease, or medication (L-dopa) regimen was found.


CONCLUSION
Preliminary results indicating an increase in cerebral lactate in patients with Parkinson disease support the hypothesis that Parkinson disease is a systemic disorder characterized by an impairment of oxidative energy metabolism. The larger increases for Parkinson patients with dementia may be diagnostically useful in assessing clinical course and in differentiating Parkinson disease from other causes of dementia. Additional studies are needed, though, to quantitate lactate changes and identify potential contributions from lipid resonances better.
9681054
Dysregulation of glucose metabolism is an early event in sporadic Parkinson's disease☆
Unlike most other cell types, neurons preferentially metabolize glucose via the pentose phosphate pathway (PPP) to maintain their antioxidant status. Inhibiting the PPP in neuronal cell models causes cell death. In rodents, inhibition of this pathway causes selective dopaminergic cell death leading to motor deficits resembling parkinsonism. Using postmortem human brain tissue, we characterized glucose metabolism via the PPP in sporadic Parkinson's disease (PD), Alzheimer's disease (AD), and controls. AD brains showed increased nicotinamide adenine dinucleotide phosphate (NADPH) production in areas affected by disease. In PD however, increased NADPH production was only seen in the affected areas of late-stage cases. Quantifying PPP NADPH-producing enzymes glucose-6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase by enzyme-linked immunosorbent assay, showed a reduction in the putamen of early-stage PD and interestingly in the cerebellum of early and late-stage PD. Importantly, there was no decrease in enzyme levels in the cortex, putamen, or cerebellum of AD. Our results suggest that down-regulation of PPP enzymes and a failure to increase antioxidant reserve is an early event in the pathogenesis of sporadic PD.
22057442
Role of mitochondria in the etiology and pathogenesis of Parkinson's disease.
We discuss the etiology and pathogenesis of Parkinson's disease (PD). Our group and others have found a decrease in complex I of the mitochondrial electron transfer complex in the substantia nigra of patients with PD; in addition, we reported loss of the alpha-ketoglutarate dehydrogenase complex (KGDHC) in the substantia nigra. Dual loss of complex I and the KGDHC will deleteriously affect the electron transport and ATP synthesis; we believe that energy crisis is the most important mechanism of nigral cell death in PD. Oxidative stress has also been implicated as an important contributor to nigral cell death in PD, but we believe that oxidative stress is a secondary phenomenon to respiratory failure, because respiratory failure will increase oxygen free-radical formation and consume glutathione. The primary cause of mitochondrial respiratory failure has not been elucidated yet, but additive effect of environmental neurotoxins in genetically predisposed persons appears to be the most likely possibility.
25517880
Deficits in a tricarboxylic acid cycle enzyme in brains from patients with Parkinson’s disease
Parkinson's disease (PD) is associated with mitochondrial dysfunction, specifically a deficiency of complex I of the electron transport chain. Most, although not all, studies indicate that this deficiency is limited to brain regions with neurodegeneration. The current studies tested for deficiencies in other mitochondrial components in PD brain in a neuropathologically unaffected region where the abnormality cannot be attributed to secondary effects of neurodegeneration. The activity of a key (and arguably rate-limiting) tricarboxylic acid cycle enzyme, the alpha-ketoglutarate dehydrogenase complex (KGDHC), was measured in the cerebellum of patients with PD. Activity in 19 PD brains was 50.5% of that in 18 controls matched for age, sex, post-mortem interval, and method of preservation (P<0.0019). The protein subunits of KGDHC were present in normal amounts in PD brains, indicating a relatively discrete abnormality in the enzyme. The activities of another mitochondrial enzyme, glutamate dehydrogenase (GDH), were normal in PD brains. These results demonstrate that specific reductions in KGDHC occur even in pathologically unaffected areas in PD, where the decline is unlikely to be a non-specific result of neurodegeneration. Reductions in the activity of this enzyme, if widespread in the brain, may predispose vulnerable regions to further damage.
32283067
Differential neuronal activity in segments of globus pallidus in Parkinson's disease patients
Microelectrode trajectories through the globus pallidus of 6 Parkinson's disease (PD) patients yielded neurophysiological ‘landmarks' which enabled the identification of neurones located in the external segment (GPe) and internal segments, exterior (GPi,e) and interior (GPi,i) of globus pallidus and the surrounding borders (Bor). Firing rate histograms and inter-spike interval time histograms were constructed for neurones in each region. The neuronal activity in GPi,i was higher than in the other segments, and a high degree of bursting was found in GPe and GPi neurones. This profile of neuronal activity is similar to that observed in monkeys treated with MPTP, suggesting that the observed level of activity of neurones in GPi,i is excessive, and contributes to the bradykinesia and rigidity of PD patients.
23980025
Quantification of the GABA Shunt and the Importance of the GABA Shunt Versus the 2‐Oxoglutarate Dehydrogenase Pathway in GABAergic Neurons
Abstract: We investigated the activity of the cerebral GABA shunt relative to the overall cerebral tricarboxylic acid (TCA) cycle and the importance of the GABA shunt versus 2‐oxoglutarate dehydrogenase for the conversion of 2‐oxoglutarate into succinate in GABAergic neurons. Awake mice were dosed with [1‐13C]glucose, and brain extracts were analyzed by 13C NMR spectroscopy. The percent enrichments of GABA C‐2 and glutamate C‐4 were the same: 5.0 ± 1.6 and 5.1 ± 0.2%, respectively (mean ± SD). This, together with previous data, indicates that the flux through the GABA shunt relative to the overall cerebral TCA cycle flux equals the GABA/glutamate pool size ratio, which in the mouse is 17%. It has previously been shown that under the experimental conditions used in this study, the 13C labeling of aspartate from [1‐13C]glucose specifically reflects the metabolic activity of GABAergic neurons. In the present study, the reduction in the formation of [13C]aspartate during inhibition of the GABA shunt by γ‐vinyl‐GABA indicated that not more than half the flux from 2‐oxoglutarate to succinate in GABAergic neurons goes via the GABA shunt. Therefore, because fluxes through the GABA shunt and 2‐oxoglutarate dehydrogenase in GABAergic neurons are approximately the same, the TCA cycle activity of GABAergic neurons could account for one‐third of the overall cerebral TCA cycle activity in the mouse. Treatment with γ‐vinyl‐GABA, which increased GABA levels dramatically, caused changes in the 13C labeling of glutamate and glutamine, which indicated a reduction in the transfer of glutamate from neurons to glia, implying reduced glutamatergic neurotransmission. In the most severely affected animals these alterations were associated with convulsions.
24583475
The operation of the gamma-aminobutyrate bypath of the tricarboxylic acid cycle in brain tissue in vitro.
1. Cerebral-cortex slices prelabelled with gamma-amino[1-(14)C]butyrate (GABA) were incubated in a glucose-saline medium. After the initial rapid uptake there was no appreciable re-entry of (14)C into the GABA pool, either from the medium or from labelled metabolites formed in the tissue. The kinetic constants of GABA metabolism were determined by computer simulation of the experimental results by using mathematical procedures. The GABA flux was estimated to be 0.03mumol per min/g, or about 8% of the total flux through the tricarboxylic acid cycle. It was found that the assumption of compartmentation did not greatly affect the estimates of the GABA flux. 2. The time-course of incorporation of (14)C into amino acids associated with the tricarboxylic acid cycle was followed with [1-(14)C]GABA and [U-(14)C]-glucose as labelled substrates. The results were consistent with the utilization of GABA via succinate. This was confirmed by determining the position of (14)C in the carbon skeletons of aspartate and glutamate formed after the oxidation of [1-(14)C]GABA. These results also indicated that under the experimental conditions the reversal of reactions catalysed by alpha-oxoglutarate dehydrogenase and glutamate decarboxylase respectively was negligible. The conversion of [(14)C]GABA into gamma-hydroxybutyrate was probably also of minor importance, but decarboxylation of oxaloacetate did occur at a relatively slow rate. 3. When [1-(14)C]GABA was the labelled substrate there was evidence of a metabolic compartmentation of glutamate since, even before the peak of the incorporation of (14)C into glutamate had been reached, the glutamine/glutamate specific-radioactivity ratio was greater than unity. When [U-(14)C]glucose was oxidized this ratio was less than unity. The heterogeneity of the glutamate pool was indicated also by the relatively high specific radioactivity of GABA, which was comparable with that of aspartate during the whole incubation time (40min). The rates of equilibration of labelled amino acids between slice and medium gave evidence that the permeability properties of the glutamate compartments labelled as a result of oxidation of [1-(14)C]GABA were different from those labelled by the metabolism of [(14)C]glucose. The results showed therefore that in brain tissue incubated under the conditions used, the organization underlying metabolic compartmentation was preserved. The observed concentration ratios of amino acids between tissue and medium were also similar to those obtaining in vivo. These ratios decreased in the order: GABA>acidic acids>neutral amino acids>glutamine. 4. The approximate pool sizes of the amino acids in the different metabolic compartments were calculated. The glutamate content of the pool responsible for most of the labelling of glutamine during oxidation of [1-(14)C]GABA was estimated to be not more than 30% of the total tissue glutamate. The GABA content of the ;transmitter pool' was estimated to be 25-30% of the total GABA in the tissue. The structural correlates of metabolic compartmentation were considered.
44818462
Large-scale in silico modeling of metabolic interactions between cell types in the human brain
Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimer's disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.
26082418
The Globus Pallidus, Deep Brain Stimulation, and Parkinson's Disease
Parkinson's disease (PD) is caused by the degeneration of the dopaminergic neurons in the substantia nigra. Loss of dopaminergic innervation leads to hyperactivity in the internal segment of the globus pallidus (GPi), the main output nucleus of the basal ganglia and to a profound disturbance in the function of motor circuits. Lesions of the GPi (or in its upstream modulator, the subthalamic nucleus) can greatly improve the motor symptoms of PD presumably by reducing this pathological activity. Paradoxically, high-frequency electrical stimulation of the GPi (deep brain stimulation, DBS) mimics the effects of pallidotomy and has become an accepted therapeutic technique. The mechanisms underlying the beneficial effects of pallidal DBS are not known. Various mechanisms that might account for inhibiting or disrupting the pathological pallidal outflow by high-frequency DBS have been proposed ranging from depolarization block to stimulation-evoked release of GABA, and these are discussed.
30216431
Effects of GPi and STN inactivation on physiological, motor, cognitive and motivational processes in animal models of Parkinson's disease.
Loss of the dopaminergic input to the striatum, characterizing Parkinson's disease, leads to the hyper-activity of two key nuclei of the basal ganglia (BG): the subthalamic nucleus (STN) and the internal segment of the globus pallidus (GPi). The anatomo-physiological organization of the BG and their output suggested that interfering with such hyper-activity could restore motor function and improve parkinsonism. Several animal models in rodents and primates, as well as clinical studies and neurosurgical treatments, have confirmed such hypothesis. This chapter will review the physiological and behavioural data obtained by inactivating the GPi or the STN by means of lesions, pharmacological approaches and deep brain stimulation. The consequences of these treatments will be examined at levels ranging from cellular to complex behavioural changes. Some of this experimental evidence suggested new and effective clinical treatments for PD, which are now routinely used worldwide. However, further studies are necessary to better understand the consequences of GPi and STN manipulation especially at the cognitive level in order to improve functional neurosurgical treatments for Parkinson's disease by minimizing risks of side-effects.
2914007
Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia
BackgroundIt is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons.ModelThe constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled.ResultsThe reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange) and 216 metabolites (183 internal, 33 external) distributed in and between astrocytes and neurons. Flux balance analysis (FBA) techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia) on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA). The results show the power of the constructed model to simulate disease behaviour on the flux level, and its potential to analyze cellular metabolic behaviour in silico.ConclusionThe predictive power of the constructed model for the key flux distributions, especially central carbon metabolism and glutamate-glutamine cycle fluxes, and its application to hypoxia is promising. The resultant acceptable predictions strengthen the power of such stoichiometric models in the analysis of mammalian cell metabolism.
1662584
Systems-level analysis of mechanisms regulating yeast metabolic flux
Quantitation of metabolic pathway regulation Although metabolic biochemical pathways are well understood, less is known about precisely how reaction rates or fluxes through the various enzymes are controlled. Hackett et al. developed a method to quantitate such regulatory influence in yeast. They monitored concentrations of metabolites, enzymes, and potential regulators by LC-MS/MS (liquid chromatography–tandem mass spectrometry) and isotope ratio measurements for 56 reactions, over 100 metabolites, and 370 metabolic enzymes in yeast in 25 different steady-state conditions. Bayesian analysis was used to examine the probability of regulatory interactions. Regulation of flux through the pathways was predominantly controlled by changes in the concentration of small-molecule metabolites rather than changes in enzyme abundance. The analysis also revealed previously unrecognized regulation between pathways. Science, this issue p. 432 Metabolomics, proteomics, and flux analysis are used to dissect quantitatively metabolic regulation in living yeast. INTRODUCTION Metabolism is among the most strongly conserved processes across all domains of life and is crucial for both bioengineering and disease research, yet we still have an unclear understanding of how metabolic rates (fluxes) are determined. Qualitatively, this deficiency involves missing knowledge of enzyme regulators. Quantitatively, it involves limited understanding of the relative contributions of enzyme and metabolite concentrations in controlling flux across physiological conditions. Addressing these gaps has been challenging because in vitro biochemical approaches lack the physiological context, whereas models of cellular metabolic dynamics have limited capacity for identifying or quantitating specific regulatory events because of overall model complexity. RATIONALE Flux through individual metabolic reactions is directly determined by the concentrations of enzyme, substrates, products, and any allosteric regulators, as captured quantitatively by a Michaelis-Menten–style reaction equation. Analogous to how experimental variation of reaction species in vitro allows for the inference of regulators and reaction equation kinetic parameters, physiological changes in flux entail a change in reaction species that can be used to determine reaction equations on the basis of cellular data. This requires measurement across multiple biological conditions of flux, enzyme concentrations, and metabolite concentrations. We reasoned that chemostat cultures could be used to induce predictable and strong flux changes, with changes in enzymes and metabolites measurable by proteomics and metabolomics. By directly relating cellular flux to the reaction species that determine it, we can carry out regulatory inference at the level of single metabolic reactions by using cellular data. An important benefit is that the physiological significance of any identified regulator is implicit from its role in determining cellular flux. RESULTS Here we introduce systematic identification of meaningful metabolic enzyme regulation (SIMMER). We measured fluxes, and metabolite and enzyme concentrations, in each of 25 yeast chemostats. For each of 56 reactions for which the flux, enzyme, and substrates were measured, we determined whether variation in measured flux could be explained by simple Michaelis-Menten kinetics. We also evaluated alternative models of each reaction’s kinetics that included a suite of allosteric regulators drawn from across all organisms. For 46 reactions, we were able to identify a useful kinetic model, with 17 reactions not including any regulation and 29 reactions being regulated by one to two allosteric regulators. Three previously unrecognized cross-pathway regulatory interactions were validated biochemically. These included inhibition of pyruvate kinase by citrate and inhibition of pyruvate decarboxylase by phenypyruvate. These metabolites accumulated and thereby curtailed glycolytic outflow and ethanol production in nitrogen-limited yeast. For well-supported reaction forms, we were able to determine the extent to which nutrient-based changes in flux were determined by changes in the concentrations of individual reaction species. We find that substrates are the most important determinant of fluxes in general, with enzymes and allosteric regulators having a comparably important role in the case of physiologically irreversible reactions. CONCLUSION By connecting changes in flux to their root cause, SIMMER parallels classic in vitro approaches, but it allows simultaneous testing of numerous regulators of many reactions under physiological conditions. Its application to yeast showed that changes in flux across nutrient conditions are predominantly due to metabolite, not enzyme, levels. Thus, yeast metabolism is substantially self-regulating. Integrative analysis of fluxes and metabolite and enzyme concentrations by SIMMER. Measured flux is related, on a reaction-by-reaction basis, to enzyme and metabolite concentrations through a Michaelis-Menten equation. The extent to which variation in flux across experimental conditions can be explained by the enzyme, substrates, and products is assessed. If unregulated kinetics disagrees with the measured flux, we test a set of possible allosteric regulators to determine which, if any, regulators are supported on the basis of improvement in fit. Cellular metabolic fluxes are determined by enzyme activities and metabolite abundances. Biochemical approaches reveal the impact of specific substrates or regulators on enzyme kinetics but do not capture the extent to which metabolite and enzyme concentrations vary across physiological states and, therefore, how cellular reactions are regulated. We measured enzyme and metabolite concentrations and metabolic fluxes across 25 steady-state yeast cultures. We then assessed the extent to which flux can be explained by a Michaelis-Menten relationship between enzyme, substrate, product, and potential regulator concentrations. This revealed three previously unrecognized instances of cross-pathway regulation, which we biochemically verified. One of these involved inhibition of pyruvate kinase by citrate, which accumulated and thereby curtailed glycolytic outflow in nitrogen-limited yeast. Overall, substrate concentrations were the strongest driver of the net rates of cellular metabolic reactions, with metabolite concentrations collectively having more than double the physiological impact of enzymes.
6263821
Context-Specific Metabolic Networks Are Consistent with Experiments
Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are “genome-scale” and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME) to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.
15236383
Genome-level transcription data of Yersinia pestis analyzed with a New metabolic constraint-based approach
BackgroundConstraint-based computational approaches, such as flux balance analysis (FBA), have proven successful in modeling genome-level metabolic behavior for conditions where a set of simple cellular objectives can be clearly articulated. Recently, the necessity to expand the current range of constraint-based methods to incorporate high-throughput experimental data has been acknowledged by the proposal of several methods. However, these methods have rarely been used to address cellular metabolic responses to some relevant perturbations such as antimicrobial or temperature-induced stress. Here, we present a new method for combining gene-expression data with FBA (GX-FBA) that allows modeling of genome-level metabolic response to a broad range of environmental perturbations within a constraint-based framework. The method uses mRNA expression data to guide hierarchical regulation of cellular metabolism subject to the interconnectivity of the metabolic network.ResultsWe applied GX-FBA to a genome-scale model of metabolism in the gram negative bacterium Yersinia pestis and analyzed its metabolic response to (i) variations in temperature known to induce virulence, and (ii) antibiotic stress. Without imposition of any a priori behavioral constraints, our results show strong agreement with reported phenotypes. Our analyses also lead to novel insights into how Y. pestis uses metabolic adjustments to counter different forms of stress.ConclusionsComparisons of GX-FBA predicted metabolic states with fluxomic measurements and different reported post-stress phenotypes suggest that mass conservation constraints and network connectivity can be an effective representative of metabolic flux regulation in constraint-based models. We believe that our approach will be of aid in the in silico evaluation of cellular goals under different conditions and can be used for a variety of analyses such as identification of potential drug targets and their action.
55419
Interpreting Expression Data with Metabolic Flux Models: Predicting Mycobacterium tuberculosis Mycolic Acid Production
Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression), extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB). Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.
14717764
RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations
Predicting cellular responses to perturbations is an important task in systems biology. We report a new approach, RELATCH, which uses flux and gene expression data from a reference state to predict metabolic responses in a genetically or environmentally perturbed state. Using the concept of relative optimality, which considers relative flux changes from a reference state, we hypothesize a relative metabolic flux pattern is maintained from one state to another, and that cells adapt to perturbations using metabolic and regulatory reprogramming to preserve this relative flux pattern. This constraint-based approach will have broad utility where predictions of metabolic responses are needed.
204980314
The GABA and substance P input to dopaminergic neurones in the substantia nigra of the rat
In order to examine the synaptic input to dopaminergic neurones in the substantia nigra from GABAergic terminals and terminals that contain substance P, double and triple immunocytochemical studies were carried out at the light and electron microscopic levels in the rat. In a first series of experiments sections of the substantia nigra were incubated to reveal axon terminals containing either substance P or glutamate decarboxylase and then incubated to reveal dopaminergic neurones using tyrosine hydroxylase immunocytochemistry. Examination of this material in the light microscope revealed that many substance P- and glutamate decarboxylase-immunoreactive boutons were associated with the dopaminergic cells. In the electron microscope it was found that the perikarya and dendrites of the dopaminergic neurons received symmetrical synaptic input from terminals that displayed immunoreactivity for substance P or glutamate decarboxylase. A small proportion of the substance P-positive boutons formed asymmetrical synapses. In a second series of experiments sections of the substantia nigra were processed by the pre-embedding immunocytochemical technique for tyrosine hydroxylase and then the post-embedding immunogold technique for gamma-aminobutyric acid (GABA). Examination in the electron microscope revealed that the tyrosine hydroxylase-positive neurons received symmetrical synaptic input from many GABA-positive terminals. Quantitative analyses demonstrated that a minimum of 50-70% of all boutons afferent to the dopaminergic neurones display glutamate decarboxylase or GABA immunoreactivity. Triple immunocytochemical studies i.e. pre-embedding immunocytochemistry for tyrosine hydroxylase and substance P, combined with post-embedding immunogold staining for GABA, revealed that some of the substance P-immunoreactive boutons that were in contact with the dopaminergic neurones also displayed GABA immunoreactivity. In a third series of experiments the combination of anterograde transport of lectin-conjugated horseradish peroxidase or biocytin with post-embedding GABA immunocytochemistry demonstrated that at least one of the sources of GABA-containing terminals in the substantia nigra is the striatum. The results of the present study: (1) demonstrate that dopaminergic neurones in the substantia nigra receive symmetrical synaptic input from GABAergic and substance P-containing terminals, (2) show that a proportion of these terminals contain both substance P and GABA and (3) suggest that the major synaptic input to dopaminergic neurones is from GABAergic terminals and that a part of this innervation is derived from the striatum.