Modelling Cell Metabolism: a Review on Constraint-Based Steady-State and Kinetic Approaches
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bioRxiv preprint doi: https://doi.org/10.1101/2020.02.03.932855; this version posted February 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Assessing the impact of physicochemical parameters in the 2 predictive capabilities of thermodynamics-based stoichiometric 3 approaches under mesophilic and thermophilic conditions 4 5 Claudio Tomi-Andrino1,2,3, Rupert Norman2, Thomas Millat2, Philippe Soucaille2,4,5,6, 6 Klaus Winzer2, David A. Barrett1, John King3, Dong-Hyun Kim1 7 8 1Centre for Analytical Bioscience, Advanced Materials and Healthcare Technology Division, 9 School of Pharmacy, University of Nottingham, Nottingham, United Kingdom. 10 2Nottingham BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of Life 11 Sciences, BioDiscovery Institute, University of Nottingham, Nottingham, United Kingdom. 12 3Nottingham BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of 13 Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom. 14 4INSA, UPS, INP, Toulouse Biotechnology Institute, (TBI), Université de Toulouse, Toulouse, 15 France. 16 5INRA, UMR792, Toulouse, France. 17 6CNRS, UMR5504, Toulouse, France. 18 19 20 *Corresponding author 21 Email: [email protected] 22 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.03.932855; this version posted February 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. -
Quantitative Analysis of Amino Acid Metabolism in Liver Cancer Links Glutamate Excretion to Nucleotide Synthesis
Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis Avlant Nilssona,1, Jurgen R. Haanstrab,1, Martin Engqvista, Albert Gerdingc,d, Barbara M. Bakkerb,c, Ursula Klingmüllere, Bas Teusinkb, and Jens Nielsena,f,2 aDepartment of Biology and Biological Engineering, Chalmers University of Technology, SE41296 Gothenburg, Sweden; bSystems Biology Lab, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, NL1081HZ Amsterdam, The Netherlands; cLaboratory of Pediatrics, Systems Medicine of Metabolism and Signaling, University of Groningen, University Medical Center Groningen, NL-9713AV Groningen, The Netherlands dDepartment of Laboratory Medicine, University of Groningen, University Medical Center Groningen, NL-9713AV Groningen, The Netherlands; eDivision of Systems Biology and Signal Transduction, German Cancer Research Center, D-69120 Heidelberg, Germany; and fNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, DK2800, Denmark Contributed by Jens Nielsen, March 9, 2020 (sent for review November 4, 2019; reviewed by Eytan Ruppin and Matthew G. Vander Heiden) Many cancer cells consume glutamine at high rates; counterintu- the excretion of lactate, glutamate, alanine, and glycine (5). How- itively, they simultaneously excrete glutamate, the first interme- ever, a full genome-wide modeling approach is required to expand diate in glutamine metabolism. Glutamine consumption has been our knowledge of how metabolism functions beyond the canonical linked to replenishment of tricarboxylic acid cycle (TCA) interme- pathways and, in particular, to understand the intricate effects of diates and synthesis of adenosine triphosphate (ATP), but the metabolic compartmentalization and the interplay between ex- reason for glutamate excretion is unclear. Here, we dynamically change fluxes and synthesis of biomass. -
Dynamical Reduction of Metabolic Networks by Singular Perturbation Theory : Application to Microalgae Claudia Lopez Zazueta
Dynamical reduction of metabolic networks by singular perturbation theory : application to microalgae Claudia Lopez Zazueta To cite this version: Claudia Lopez Zazueta. Dynamical reduction of metabolic networks by singular perturbation theory : application to microalgae. Signal and Image processing. COMUE Université Côte d’Azur (2015 - 2019), 2018. English. NNT : 2018AZUR4108. tel-02411569 HAL Id: tel-02411569 https://tel.archives-ouvertes.fr/tel-02411569 Submitted on 15 Dec 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSE DE DOCTORAT Réduction dynamique de réseaux métaboliques par la théorie des perturbations singulières : Application aux microalgues Claudia LÓPEZ ZAZUETA Institut National de Recherche en Informatique et en Automatique (Inria) Équipe-Projet BIOCORE Présentée en vue de l’obtention Devant le jury, composé de : du grade de docteur en Sciences Alexander Bockmayr, Professeur, Freie d’Université Côte d’Azur Universität Berlin Mention : Automatique, Traitement du Diego Oyarzún, Lecturer in Computational Signal et des Images Biology, -
Metabolic Modelling of Wine-Making : a State of the Art
METABOLIC MODELLING OF WINE-MAKING : A STATE OF THE ART Robert David and Denis Dochain1, Alain Vande Wouwer2, Jean-Roch Mouret and Jean-Marie Sablayrolles3 1Université Catholique de Louvain, Belgium, 2Faculté Polytechnique de Mons, Belgium, 3INRA - Montpellier SupAgro, France Corresponding author: Robert David, Center for Systems Engineering and Applied Mechanics (CESAME) Université Catholique de Louvain, Avenue Georges Lemaître 4, 1348 Louvain-la-Neuve, Belgium, ÐÓÙÚÒº Abstract. The yeast Saccharomyces cerevisiae is one of the most studied micro-organism, due to its numerous applications (beer, wine, bakery, bioethanol). This good knowledge of the species was notably considered in modelling approaches where the intracellular behaviour is taken into account. Among them Metabolic Flux Analysis and Elementary Flux Modes are tools of interest to develop a mathematical model of the fermentation process including some characteristic flavour compounds. The present paper describes what has been done in the restrained field of wine-making/fermentation conditions, and underlines the potential of such approaches. 1 Introduction As in most food processes, there is a need to increase the development of efficient control tools in order to im- ºÓÖ prove the quality of food products. This is one of the issue of the EC CAFE project ( ). In the context of wine-making, an a priori attractive path may be to consider microbiological knowledge about the production of the important organoleptic properties of the wine in order to develop new appropriate control approaches that can help to guarantee the production of wine of defined quality. In the nineties, as technical progresses in biotechnology were decisive, Saccharomyces cerevisiae has become the first eukaryotic organism1 whose genome was fully sequenced, denoting the interest for its better understanding. -
Flux Balance Analysis to Model Microbial Metabolism for Electricity Generation
Lincoln University Digital Thesis Copyright Statement The digital copy of this thesis is protected by the Copyright Act 1994 (New Zealand). This thesis may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: you will use the copy only for the purposes of research or private study you will recognise the author's right to be identified as the author of the thesis and due acknowledgement will be made to the author where appropriate you will obtain the author's permission before publishing any material from the thesis. Flux balance analysis to model microbial metabolism for electricity generation A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy in Computational Biology and Bioengineering at Lincoln University by Longfei Mao Lincoln University 2013 Abstract of a thesis submitted in partial fulfilment of the requirements for the Degree of Philosophy Flux balance analysis to model microbial metabolism for electricity generation by Longfei Mao Abstract Microbial fuel cells (MFCs) are bioelectrochemcial devices that possess a similar design to a fuel cell, with an anode and a cathode connected through an electrical circuit. Unlike fuel cells, MFCs use microorganisms as biocatalysts to convert organic matter into electrons and protons, of which a portion can be transferred to electrode to generate electricity. Since all microorganisms transfer electrons during metabolism inside the cell, there could potentially be unlimited choices of biocatalyst candidates for MFCs for various applications. However, in reality, the application of MFCs is heavily restricted by their low current outputs. -
Profiling Cellular Processes in Adipose Tissue During Weight Loss Using Time Series Gene Expression
G C A T T A C G G C A T genes Article Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression Samar H. K. Tareen 1,* , Michiel E. Adriaens 1,* , Ilja C. W. Arts 1,2, Theo M. de Kok 1,3, Roel G. Vink 4, Nadia J. T. Roumans 4, Marleen A. van Baak 4, Edwin C. M. Mariman 4, Chris T. Evelo 1,5,* and Martina Kutmon 1,5,* 1 Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, 6211ER Maastricht, The Netherlands; [email protected] (I.C.W.A.); [email protected] (T.M.d.K.) 2 Department of Epidemiology, CARIM School for Cardiovascular Diseases, Maastricht University, 6211ER Maastricht, The Netherlands 3 Department of Toxicogenomics, GROW School of Oncology and Developmental Biology, Maastricht University, 6211ER Maastricht, The Netherlands 4 Department of Human Biology, NUTRIM Research School, Maastricht University, 6211ER Maastricht, The Netherlands; [email protected] (R.G.V.); [email protected] (N.J.T.R.); [email protected] (M.A.v.B.); [email protected] (E.C.M.M.) 5 Department of Bioinformatics—BiGCaT, NUTRIM Research School, Maastricht University, 6211ER Maastricht, The Netherlands * Correspondence: [email protected] (S.H.K.T.); [email protected] (M.E.A.); [email protected] (C.T.E.); [email protected] (M.K.) Received: 28 September 2018; Accepted: 22 October 2018; Published: 29 October 2018 Abstract: Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. -
Metabolic Flux Analysis—Linking Isotope Labeling and Metabolic Fluxes
H OH metabolites OH Review Metabolic Flux Analysis—Linking Isotope Labeling and Metabolic Fluxes Yujue Wang 1,2, Fredric E. Wondisford 1, Chi Song 3, Teng Zhang 4 and Xiaoyang Su 1,2,* 1 Department of Medicine, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA; [email protected] (Y.W.); [email protected] (F.E.W.) 2 Metabolomics Shared Resource, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA 3 Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH 43210, USA; [email protected] 4 Department of Mathematics, University of Central Florida, Orlando, FL 32816, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-732-235-5447 Received: 14 September 2020; Accepted: 4 November 2020; Published: 6 November 2020 Abstract: Metabolic flux analysis (MFA) is an increasingly important tool to study metabolism quantitatively. Unlike the concentrations of metabolites, the fluxes, which are the rates at which intracellular metabolites interconvert, are not directly measurable. MFA uses stable isotope labeled tracers to reveal information related to the fluxes. The conceptual idea of MFA is that in tracer experiments the isotope labeling patterns of intracellular metabolites are determined by the fluxes, therefore by measuring the labeling patterns we can infer the fluxes in the network. In this review, we will discuss the basic concept of MFA using a simplified upper glycolysis network as an example. We will show how the fluxes are reflected in the isotope labeling patterns. The central idea we wish to deliver is that under metabolic and isotopic steady-state the labeling pattern of a metabolite is the flux-weighted average of the substrates’ labeling patterns. -
A Critical View of Metabolic Network Adaptations
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DSpace at VU HFSP Journal PERSPECTIVE A critical view of metabolic network adaptations Balázs Papp,1 Bas Teusink,2,3,4,5 and Richard A. Notebaart2,4 1Institute of Biochemistry, Biological Research Center, H-6701 Szeged, Hungary 2Center for Molecular and Biomolecular Informatics ͑NCMLS͒, Radboud University Nijmegen Medical Center, 6500GL Nijmegen, The Netherlands 3TI Food and Nutrition, Wageningen / NIZO food research, 6710BA Ede, The Netherlands 4Kluyver Center for Genomics of Industrial Fermentation, 2628 BC Delft, The Netherlands 5Present address: The Center for Integrative Bioinformatics ͑IBIVU͒, Faculty of Earth and Life Science, Vrije University Amsterdam, 1081HV Amsterdam, The Netherlands ͑Received 18 August 2008; accepted 20 October 2008; published online 3 December 2008) There has been considerable recent interest in deciphering the adaptive properties underlying the structure and function of metabolic networks. Various features of metabolic networks such as the global topology, distribution of fluxes, and mutational robustness, have been proposed to have adaptive significance and hence reflect design principles. However, whether evolutionary processes alternative to direct selection on the trait under investigation also play a role is often ignored and the selection pressures maintaining a given metabolic trait often remain speculative. Some systems-level traits might simply arise as by-products of selection on other traits or even through random genetic drift. Here, we ask which systems-level aspects of metabolism are likely to have adaptive utility and which could be better explained as by-products of other evolutionary forces. We conclude that the global topological characteristics of metabolic networks and their mutational robustness are unlikely to be directly shaped by natural selection. -
Mathematical Models for Explaining the Warburg Effect: a Review Focussed on ATP and Biomass Production
Metabolic pathways analysis 2015 1187 Mathematical models for explaining the Warburg effect: a review focussed on ATP and biomass production Stefan Schuster*1, Daniel Boley†, Philip Moller*,¨ Heiko Stark*‡ and Christoph Kaleta§ *Department of Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany †Computer Science & Engineering, University of Minnesota, Minneapolis, MN 55455, U.S.A. ‡Institute of Systematic Zoology and Evolutionary Biology, Friedrich Schiller University Jena, Erbertstraße 1, 07737 Jena, Germany §Research Group Medical Systems Biology, Christian-Albrechts-University Kiel, Brunswiker Straße 10, Kiel 24105, Germany Abstract For producing ATP, tumour cells rely on glycolysis leading to lactate to about the same extent as on respiration. Thus, the ATP synthesis flux from glycolysis is considerably higher than in the corresponding healthy cells. This is known as the Warburg effect (named after German biochemist Otto H. Warburg) and also applies to striated muscle cells, activated lymphocytes, microglia, endothelial cells and several other cell types. For similar phenomena in several yeasts and many bacteria, the terms Crabtree effect and overflow metabolism respectively, are used. The Warburg effect is paradoxical at first sight because the molar ATP yield of glycolysis is much lower than that of respiration. Although a straightforward explanation is that glycolysis allows a higher ATP production rate, the question arises why cells do not re-allocate protein to the high-yield pathway of respiration. Mathematical modelling can help explain this phenomenon. Here, we review several models at various scales proposed in the literature for explaining the Warburg effect. These models support the hypothesis that glycolysis allows for a higher proliferation rate due to increased ATP production and precursor supply rates. -
Remodeling Adipose Tissue Through in Silico Modulation of Fat Storage For
Chénard et al. BMC Systems Biology (2017) 11:60 DOI 10.1186/s12918-017-0438-9 RESEARCHARTICLE Open Access Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes Thierry Chénard2, Frédéric Guénard3, Marie-Claude Vohl3,4, André Carpentier5, André Tchernof4,6 and Rafael J. Najmanovich1* Abstract Background: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. Results: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each -
Effective Dynamic Models of Metabolic Networks Michael Vilkhovoy∗, Mason Minot∗, Jeffrey D
bioRxiv preprint doi: https://doi.org/10.1101/047316; this version posted August 31, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Effective Dynamic Models of Metabolic Networks Michael Vilkhovoy∗, Mason Minot∗, Jeffrey D. Varner∗ ∗School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14850 USA Abstract—Mathematical models of biochemical networks are by a pseudo enzyme whose expression is controlled by an useful tools to understand and ultimately predict how cells utilize optimal decision) to achieve a physiological objective (Fig. nutrients to produce valuable products. Hybrid cybernetic models 1A). HCMs generate intracellular flux distributions consistent in combination with elementary modes (HCM) is a tool to model cellular metabolism. However, HCM is limited to reduced with other approaches such as metabolic flux analysis (MFA), metabolic networks because of the computational burden of and also describe dynamic extracellular measurements superior calculating elementary modes. In this study, we developed the to dynamic FBA (DFBA) [12]. However, HCMs are restricted hybrid cybernetic modeling with flux balance analysis or HCM- to networks which can be decomposed into EMs (or EPs). FBA technique which uses flux balance solutions instead of In this study, we developed the hybrid cybernetic modeling elementary modes to dynamically model metabolism. We show HCM-FBA has comparable performance to HCM for a proof with flux balance analysis (HCM-FBA) technique. HCM- of concept metabolic network and for a reduced anaerobic E. -
Understanding Carbon Metabolism in Hydrogen Production by Pns Bacteria
UNDERSTANDING CARBON METABOLISM IN HYDROGEN PRODUCTION BY PNS BACTERIA A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY EZGİ MELİS DOĞAN IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN CHEMICAL ENGINEERING AUGUST 2016 Approval of the Thesis; UNDERSTANDING CARBON METABOLISM IN HYDROGEN PRODUCTION BY PNS BACTERIA submitted by EZGİ MELİS DOĞAN in partial fulfillment of the requirements for the degree of Master of Science in Chemical Engineering Department, Middle East Technical University by, Prof. Dr. Gülbin Dural Ünver Dean, Graduate School of Natural and Applied Sciences Prof. Dr. Halil Kalıpçılar Head of the Department, Chemical Engineering Asst. Prof. Dr. Harun Koku Supervisor, Chemical Engineering Dept., METU Examining Committee Members: Prof. Dr. Ufuk Bölükbaşı Chemical Engineering Dept., METU Asst. Prof. Dr. Harun Koku Chemical Engineering Dept., METU Assoc. Prof. Dr. Serkan Kıncal Chemical Engineering Dept., METU Assoc. Prof. Dr. Demet Çetin Department of Primary Education, Gazi University Asst. Prof. Dr. Eda Çelik Akdur Chemical Engineering Dept., Hacettepe University Date: 17.08.2016 I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last name: Ezgi Melis Doğan Signature : iv ABSTRACT UNDERSTANDING CARBON METABOLISM IN HYDROGEN PRODUCTION BY PNS BACTERIA Doğan, Ezgi Melis M.Sc., Chemical Engineering Department Supervisor: Asst. Prof. Dr. Harun Koku August 2016, 164 pages In biological hydrogen production systems using purple non-sulfur bacteria (PNS bacteria), a thorough understanding of the metabolism of these microorganisms plays a vital role in assessing and improving efficiency and productivity.