Niemann Pick Disease Type C (NP-C), a rare neurogenetic disease with no known cure, is caused by mutations in the cholesterol trafficking protein NPC1. Brain microvascular endothelial cells (BMEC) are thought to play a critical role in the pathogenesis of several neurodegenerative diseases; however, little is known about how these cells are altered in NP-C. In this study, we investigated how NPC1 inhibition perturbs BMEC metabolism in human induced pluripotent stem cell-derived BMEC (hiBMEC).
View Article and Find Full Text PDFTrends Biochem Sci
June 2023
Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output).
View Article and Find Full Text PDFCell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured.
View Article and Find Full Text PDFStable isotope-assisted metabolic flux analysis (MFA) is a powerful method to estimate carbon flow and partitioning in metabolic networks. At its core, MFA is a parameter estimation problem wherein the fluxes and metabolite pool sizes are model parameters that are estimated, via optimization, to account for measurements of steady-state or isotopically-nonstationary isotope labeling patterns. As MFA problems advance in scale, they require efficient computational methods for fast and robust convergence.
View Article and Find Full Text PDFDisrupted endothelial metabolism is linked to endothelial dysfunction and cardiovascular disease. Targeted metabolic inhibitors are potential therapeutics; however, their systemic impact on endothelial metabolism remains unknown. In this study, we combined stable isotope labeling with C metabolic flux analysis (C MFA) to determine how targeted inhibition of the polyol (fidarestat), pentose phosphate (DHEA), and hexosamine biosynthetic (azaserine) pathways alters endothelial metabolism.
View Article and Find Full Text PDFDiatoms are photosynthetic microalgae that fix a significant fraction of the world's carbon. Because of their photosynthetic efficiency and high-lipid content, diatoms are priority candidates for biofuel production. Here, we report that sporulating Bacillus thuringiensis and other members of the Bacillus cereus group, when in co-culture with the marine diatom Phaeodactylum tricornutum, significantly increase diatom cell count.
View Article and Find Full Text PDFMetab Eng Commun
June 2021
Genome-scale stoichiometric models (GSMs) have been widely utilized to predict and understand cellular metabolism. GSMs and the flux predictions resulting from them have proven indispensable to fields ranging from metabolic engineering to human disease. Nonetheless, it is challenging to parse these flux predictions due to the inherent size and complexity of the GSMs.
View Article and Find Full Text PDFFlux balance analysis (FBA) of large, genome-scale stoichiometric models (GSMs) is a powerful and popular method to predict cell-wide metabolic activity. FBA typically generates a flux vector containing O(1,000) fluxes. The interpretation of such a flux vector is difficult, even for expert users, because of the large size and complex topology of the underlying metabolic network.
View Article and Find Full Text PDFThe bovine cell line, cow trophectoderm-1 (CT-1), provides an excellent in-vitro cell culture model to study early embryonic development. Obtaining consistent attachment and outgrowth, however, is difficult because enzymatic disassociation into single cells is detrimental; therefore, CT-1 cells must be passaged in clumps, which do not attach readily to the surface of the dish. We tested whether magnetic nanoparticles, NanoShuttle™-PL, could be used to improve cell attachment and subsequent proliferation of the cattle trophectoderm cell line without altering cellular metabolism or immunofluorescent detection of the lineage marker Caudal Type Homeobox 2 (CDX2).
View Article and Find Full Text PDFGlycerol kinase (GK) is a multifunctional enzyme located at the interface of carbohydrate and fat metabolism. It contributes to both central carbon metabolism and adipogenesis; specifically, through its role as the ATP-stimulated translocation promoter (ASTP). GK overexpression leads to increased ASTP activity and increased fat storage in H4IIE cells.
View Article and Find Full Text PDFReduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple 'omics methodologies on cell suspensions of hybrid poplar (Populus tremula × Populus alba).
View Article and Find Full Text PDFMathematical modeling approaches have been commonly used in complex signaling pathway studies such as the insulin signal transduction pathway. Our expanded mathematical model of the insulin signal transduction pathway was previously shown to effectively predict glucose clearance rates using mRNA levels of key components of the pathway in a mouse model. In this study, we re-optimized and applied our expanded model to study insulin sensitivity in other species and tissues (human skeletal muscle) with altered protein activities of insulin signal transduction pathway components.
View Article and Find Full Text PDFSeasonal nitrogen (N) cycling in temperate deciduous trees involves the accumulation of bark storage proteins (BSPs) in phloem parenchyma and xylem ray cells. BSPs are anabolized using recycled N during autumn leaf senescence and later become a source of N during spring shoot growth as they are catabolized. Little is known about the catabolic processes involved in remobilization and reutilization of N from BSPs in trees.
View Article and Find Full Text PDFMathematical models of biological pathways facilitate a systems biology approach to medicine. However, these models need to be updated to reflect the latest available knowledge of the underlying pathways. We developed a mathematical model of the insulin signal transduction pathway by expanding the last major previously reported model and incorporating pathway components elucidated since the original model was reported.
View Article and Find Full Text PDFIsotope-assisted metabolic flux analysis (MFA) is a powerful methodology to quantify intracellular fluxes via isotope labeling experiments (ILEs). In batch cultures, which are often convenient, inexpensive or inevitable especially for eukaryotic systems, MFA is complicated by the presence of the initially present biomass. This unlabeled biomass may either mix with the newly synthesized labeled biomass or reflux into the metabolic network, thus masking the true labeling patterns in the newly synthesized biomass.
View Article and Find Full Text PDFBackground: Gene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities.
View Article and Find Full Text PDFBackground: Heterotrophic fermentation using simple sugars such as glucose is an established and cost-effective method for synthesizing bioproducts from bacteria, yeast and algae. Organisms incapable of metabolizing glucose have limited applications as cell factories, often despite many other advantageous characteristics. Therefore, there is a clear need to investigate glucose metabolism in potential cell factories.
View Article and Find Full Text PDFMetabolic flux analysis (MFA) is a powerful tool for exploring and quantifying carbon traffic in metabolic networks. Accurate flux quantification requires (1) high-quality isotopomer measurements, usually of biomass components including proteinogenic/free amino acids or central carbon metabolites, and (2) a mathematical model that relates the unknown fluxes to the measured isotopomers. Modeling requires a thorough knowledge of the structure of the underlying metabolic network, often available from many databases, as well as the ability to make reasonable assumptions that will enable simplification of the model.
View Article and Find Full Text PDFA genome-scale model (GSM) is an in silico metabolic model comprising hundreds or thousands of chemical reactions that constitute the metabolic inventory of a cell, tissue, or organism. A complete, accurate GSM, in conjunction with a simulation technique such as flux balance analysis (FBA), can be used to comprehensively predict cellular metabolic flux distributions for a given genotype and given environmental conditions. Apart from enabling a user to quantitatively visualize carbon flow through metabolic pathways, these flux predictions also facilitate the hypothesis of new network properties.
View Article and Find Full Text PDFMethods Mol Biol
June 2014
Isotope labeling experiments (ILEs) offer a powerful methodology to perform metabolic flux analysis. However, the task of interpreting data from these experiments to evaluate flux values requires significant mathematical modeling skills. Toward this, this chapter provides background information and examples to enable the reader to (1) model metabolic networks, (2) simulate ILEs, and (3) understand the optimization and statistical methods commonly used for flux evaluation.
View Article and Find Full Text PDFSynthetic biology enables metabolic engineering of industrial microbes to synthesize value-added molecules. In this, a major challenge is the efficient redirection of carbon to the desired metabolic pathways. Pinpointing strategies toward this goal requires an in-depth investigation of the metabolic landscape of the organism, particularly primary metabolism, to identify precursor and cofactor availability for the target compound.
View Article and Find Full Text PDFFluxomics, through its core methodology of metabolic flux analysis (MFA), enables quantification of carbon traffic through cellular biochemical pathways. Isotope labeling experiments aid MFA by providing information on intracellular fluxes, especially through parallel and cyclic pathways. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are two complementary methods to measure abundances of isotopomers generated in these experiments.
View Article and Find Full Text PDFMetabolic fluxes are powerful indicators of cell physiology and can be estimated by isotope-assisted metabolic flux analysis (MFA). The complexity of the compartmented metabolic networks of plants has constrained the application of isotope-assisted MFA to them, principally because of poor identifiability of fluxes from the measured isotope labeling patterns. However, flux identifiability can be significantly improved by a priori design of isotope labeling experiments (ILEs).
View Article and Find Full Text PDFJ Biomed Biotechnol
October 2010
Mathematical modeling plays an important and often indispensable role in synthetic biology because it serves as a crucial link between the concept and realization of a biological circuit. We review mathematical modeling concepts and methodologies as relevant to synthetic biology, including assumptions that underlie a model, types of modeling frameworks (deterministic and stochastic), and the importance of parameter estimation and optimization in modeling. Additionally we expound mathematical techniques used to analyze a model such as sensitivity analysis and bifurcation analysis, which enable the identification of the conditions that cause a synthetic circuit to behave in a desired manner.
View Article and Find Full Text PDFGlycerol kinase (GK) is an enzyme with diverse (moonlighting) cellular functions. GK overexpression affects central metabolic fluxes substantially; therefore, to elucidate the mechanism underlying these changes, we employed a systems-level evaluation of GK overexpression in H4IIE rat hepatoma cells. Microarray analysis revealed altered expression of genes in metabolism (central carbon and lipid), which correlated with previous flux analysis, and of genes regulated by the glucocorticoid receptor (GR).
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