metabolic flux analysis

Summary

Summary: Measurement of cells' substrate utilization and biosynthetic output for modeling of METABOLIC NETWORKS.

Top Publications

  1. Ahn J, Bang J, Kim W, Lee S. Formic acid as a secondary substrate for succinic acid production by metabolically engineered Mannheimia succiniciproducens. Biotechnol Bioeng. 2017;114:2837-2847 pubmed publisher
    ..08?g/L/h, respectively, using sucrose and FA as dual carbon sources. The strategy employed here will be similarly applicable in developing microorganisms to utilize FA and to produce valuable chemicals and materials from FA...
  2. Thompson R, Trinh C. Overflow metabolism and growth cessation in Clostridium thermocellum DSM1313 during high cellulose loading fermentations. Biotechnol Bioeng. 2017;114:2592-2604 pubmed publisher
    ..thermocellum production of chemicals and biofuels. Biotechnol. Bioeng. 2017;114: 2592-2604. © 2017 Wiley Periodicals, Inc. ..
  3. Li L, Jiang H, Qiu Y, Ching W, Vassiliadis V. Discovery of metabolite biomarkers: flux analysis and reaction-reaction network approach. BMC Syst Biol. 2013;7 Suppl 2:S13 pubmed publisher
    ..Two efficient and effective computational methods are proposed for the identification of biomarkers in this article. Furthermore, the biomarkers found by our proposed methods are shown to be significant determinants for diabetes. ..
  4. Wu H, Cheng M, Lai J, Wu H, Chen M, Liu W, et al. Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a. PLoS Comput Biol. 2017;13:e1005618 pubmed publisher
  5. Morales Y, Tortajada M, Picó J, Vehí J, Llaneras F. Validation of an FBA model for Pichia pastoris in chemostat cultures. BMC Syst Biol. 2014;8:142 pubmed publisher
    ..A constraint-based model of P. pastoris was previously validated using metabolic flux analysis (MFA)...
  6. Chiappino Pepe A, Tymoshenko S, Ataman M, Soldati Favre D, Hatzimanikatis V. Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks. PLoS Comput Biol. 2017;13:e1005397 pubmed publisher
    ..The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention. ..
  7. Acevedo A, Conejeros R, Aroca G. Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis. PLoS ONE. 2017;12:e0180074 pubmed publisher
    ..Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC. ..
  8. Labena A, Ye Y, Dong C, Zhang F, Guo F. SSER: Species specific essential reactions database. BMC Syst Biol. 2017;11:50 pubmed publisher
    ..Users can browse, search, compare and download the essential reactions of organisms of their interest through the website http://cefg.uestc.edu.cn/sser . ..
  9. Fyson N, King J, Belcher T, Preston A, Colijn C. A curated genome-scale metabolic model of Bordetella pertussis metabolism. PLoS Comput Biol. 2017;13:e1005639 pubmed publisher
    ..The model predicts essentiality with an accuracy of 83% and correctly predicts improvements in growth under increased glutamate:fumarate ratios. We provide the model in SBML format, along with gene essentiality predictions. ..

More Information

Publications38

  1. Bauer E, Zimmermann J, Baldini F, Thiele I, Kaleta C. BacArena: Individual-based metabolic modeling of heterogeneous microbes in complex communities. PLoS Comput Biol. 2017;13:e1005544 pubmed publisher
    ..Additionally, we could provide novel hypothesis concerning the metabolic interactions between the microbes. These results demonstrate the importance of spatial and temporal multi-scale modeling approaches such as BacArena. ..
  2. Fernandez Rodriguez J, Moser F, Song M, Voigt C. Engineering RGB color vision into Escherichia coli. Nat Chem Biol. 2017;13:706-708 pubmed publisher
    ..We use this system to produce 'color photographs' on bacterial culture plates by controlling pigment production and to redirect metabolic flux by expressing CRISPRi guide RNAs. ..
  3. Cankorur Cetinkaya A, Dikicioglu D, Oliver S. Metabolic modeling to identify engineering targets for Komagataella phaffii: The effect of biomass composition on gene target identification. Biotechnol Bioeng. 2017;114:2605-2615 pubmed publisher
  4. André S, Lagresle S, Da Sliva A, Heimendinger P, Hannas Z, Calvosa É, et al. Developing global regression models for metabolite concentration prediction regardless of cell line. Biotechnol Bioeng. 2017;114:2550-2559 pubmed publisher
    ..In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc. ..
  5. Pandey D, Kumar A, Rathore J, Singh N, Chaudhary B. Recombinant overexpression of dihydroneopterin aldolase catalyst potentially regulates folate-biofortification. J Basic Microbiol. 2017;57:517-524 pubmed publisher
    ..These data are veritable inspecting metabolic flux in both bacterial and plant systems, thus providing directions for future research on folate agri-fortification. ..
  6. Mairinger T, Hann S. Implementation of data-dependent isotopologue fragmentation in 13C-based metabolic flux analysis. Anal Bioanal Chem. 2017;409:3713-3718 pubmed publisher
    ..Graphical abstract Schematic overview of data-dependent isotopologue fragmentation for acquisition of isotopologue and tandem mass isotopomer fractions. ..
  7. Quek L, Nielsen L. A depth-first search algorithm to compute elementary flux modes by linear programming. BMC Syst Biol. 2014;8:94 pubmed publisher
    ..Unlike the Double Description method, the algorithm enables accelerated enumeration of all EFMs satisfying a set of constraints. ..
  8. Heiske M, Letellier T, Klipp E. Comprehensive mathematical model of oxidative phosphorylation valid for physiological and pathological conditions. FEBS J. 2017;284:2802-2828 pubmed publisher
    ..Moreover, it could be a useful tool to study the role of OXPHOS and its capacity to compensate or enhance physiopathologies of the mitochondrial and cellular energy metabolism. ..
  9. Okahashi N, Matsuda F, Yoshikawa K, Shirai T, Matsumoto Y, Wada M, et al. Metabolic engineering of isopropyl alcohol-producing Escherichia coli strains with 13 C-metabolic flux analysis. Biotechnol Bioeng. 2017;114:2782-2793 pubmed publisher
    ..of isopropyl alcohol (IPA)-producing Escherichia coli strains was conducted along with 13 C-metabolic flux analysis (MFA). A metabolically engineered E...
  10. Huang Z, Lee D, Yoon S. Quantitative intracellular flux modeling and applications in biotherapeutic development and production using CHO cell cultures. Biotechnol Bioeng. 2017;114:2717-2728 pubmed publisher
    ..Constraint-based modeling, such as flux balance analysis (FBA) and metabolic flux analysis (MFA), has been developing rapidly for the quantification of intracellular metabolic flux distribution at ..
  11. Kuehne A, Mayr U, Sévin D, Claassen M, Zamboni N. Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data. PLoS Comput Biol. 2017;13:e1005577 pubmed publisher
  12. Zhao X, Kasbi M, Chen J, Pérès S, Jolicoeur M. A dynamic metabolic flux analysis of ABE (acetone-butanol-ethanol) fermentation by Clostridium acetobutylicum ATCC 824, with riboflavin as a by-product. Biotechnol Bioeng. 2017;114:2907-2919 pubmed publisher
    ..metabolic model, developed to simulate ABE biosystem, with riboflavin production, revealed from a dynamic metabolic flux analysis (dMFA) simultaneous increase of riboflavin (ribA) and GTP (precursor of riboflavin) (PurM) synthesis flux ..
  13. Damiani C, Colombo R, Gaglio D, Mastroianni F, Pescini D, Westerhoff H, et al. A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect. PLoS Comput Biol. 2017;13:e1005758 pubmed publisher
    ..Taken together these findings offer new understanding of the logic of the metabolic reprogramming that underlies cancer cell growth. ..
  14. Niu H, Jost L, Pirlot N, Sassi H, Daukandt M, Rodriguez C, et al. A quantitative study of methanol/sorbitol co-feeding process of a Pichia pastoris Mut?/pAOX1-lacZ strain. Microb Cell Fact. 2013;12:33 pubmed publisher
    ..Based on a simplified metabolic network, metabolic flux analysis (MFA) was performed to quantify intracellular metabolic flux distributions during the transient ..
  15. Fritzemeier C, Hartleb D, Szappanos B, Papp B, Lercher M. Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal. PLoS Comput Biol. 2017;13:e1005494 pubmed publisher
    ..We present efficient computational methods (i) to identify energy generating cycles, using FBA, and (ii) to identify minimal sets of model changes that eliminate them, using a variant of the GlobalFit algorithm. ..
  16. Anderson K, Huynh F, Fisher Wellman K, Stuart J, Peterson B, Douros J, et al. SIRT4 Is a Lysine Deacylase that Controls Leucine Metabolism and Insulin Secretion. Cell Metab. 2017;25:838-855.e15 pubmed publisher
    ..These findings identify a robust enzymatic activity for SIRT4, uncover a mechanism controlling branched-chain amino acid flux, and position SIRT4 as a crucial player maintaining insulin secretion and glucose homeostasis during aging. ..
  17. Kamminga T, Slagman S, Bijlsma J, Martins Dos Santos V, Suárez Diez M, Schaap P. Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate. Biotechnol Bioeng. 2017;114:2339-2347 pubmed publisher
    ..The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339-2347. © 2017 Wiley Periodicals, Inc. ..
  18. Boyle N, Sengupta N, Morgan J. Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii. PLoS ONE. 2017;12:e0177292 pubmed publisher
    ..In this study, 13C-metabolic flux analysis (13C-MFA) was used to determine and quantify the metabolic pathways of primary metabolism in C...
  19. Theorell A, Leweke S, Wiechert W, Nöh K. To be certain about the uncertainty: Bayesian statistics for 13 C metabolic flux analysis. Biotechnol Bioeng. 2017;114:2668-2684 pubmed publisher
    ..In addition, the widely applied chi-square test, as a means of testing whether the model reproduces the data, is examined closer. ..
  20. Basu A, Xin F, Lim T, Lin Q, Yang K, He J. Quantitative proteome profiles help reveal efficient xylose utilization mechanisms in solventogenic Clostridium sp. strain BOH3. Biotechnol Bioeng. 2017;114:1959-1969 pubmed publisher
    ..Biotechnol. Bioeng. 2017;114: 1959-1969. © 2017 Wiley Periodicals, Inc. ..
  21. Hu Y, Xin J, Hu Y, Zhang L, Wang J. Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach. Alzheimers Res Ther. 2017;9:29 pubmed publisher
    ..In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes. ..
  22. Lee J, Reier J, Heffner K, Barton C, Spencer D, Schmelzer A, et al. Production and characterization of active recombinant human factor II with consistent sialylation. Biotechnol Bioeng. 2017;114:1991-2000 pubmed publisher
    ..The process was successfully implemented at the 2000?L scale where a high Gla level and sialylation levels were achieved in all GMP lots. Biotechnol. Bioeng. 2017;114: 1991-2000. © 2017 Wiley Periodicals, Inc. ..
  23. Alvarez Silva M, Álvarez Yela A, Gómez Cano F, Zambrano M, Husserl J, Danies G, et al. Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils. PLoS ONE. 2017;12:e0181826 pubmed publisher
  24. Labhsetwar P, Melo M, Cole J, Luthey Schulten Z. Population FBA predicts metabolic phenotypes in yeast. PLoS Comput Biol. 2017;13:e1005728 pubmed publisher
    ..We find that a core set of 51 constraints are essential but that additional constraints are still necessary to recover the observed growth rate distribution in SD medium. ..
  25. He L, Xiao Y, Gebreselassie N, Zhang F, Antoniewiez M, Tang Y, et al. Central metabolic responses to the overproduction of fatty acids in Escherichia coli based on 13C-metabolic flux analysis. Biotechnol Bioeng. 2014;111:575-85 pubmed
    ..coli and its control strain using tracer ([1,2-13C]glucose) experiments and 13C-metabolic flux analysis. Cofactor (NADPH) and energy (ATP) balances were also investigated for both strains based on estimated ..
  26. Hendry J, Prasannan C, Ma F, Möllers K, Jaiswal D, Digmurti M, et al. Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non-stationary 13 C metabolic flux analysis. Biotechnol Bioeng. 2017;114:2298-2308 pubmed publisher
    ..In the present study, we have performed isotopically non-stationary 13 C metabolic flux analysis (INST-13 C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (..
  27. Chan S, Simons M, Maranas C. SteadyCom: Predicting microbial abundances while ensuring community stability. PLoS Comput Biol. 2017;13:e1005539 pubmed publisher
    ..SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment. ..
  28. Sabra W, Bommareddy R, Maheshwari G, Papanikolaou S, Zeng A. Substrates and oxygen dependent citric acid production by Yarrowia lipolytica: insights through transcriptome and fluxome analyses. Microb Cell Fact. 2017;16:78 pubmed publisher
    ..This study provides interesting targets for metabolic engineering of this industrial yeast. ..
  29. Daurio N, Wang S, Chen Y, Zhou H, McLaren D, Roddy T, et al. Enhancing Studies of Pharmacodynamic Mechanisms via Measurements of Metabolic Flux: Fundamental Concepts and Guiding Principles for Using Stable Isotope Tracers. J Pharmacol Exp Ther. 2017;363:80-91 pubmed publisher