Profiling Cellular Processes in Adipose Tissue During Weight Loss Using Time Series Gene Expression
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Fine–Mapping Identifies NAD–ME1 As a Candidate Underlying a Major
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.07.285429; this version posted September 9, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. 1 Fine–mapping identifies NAD–ME1 as a candidate underlying 2 a major locus controlling temporal variation in primary and 3 specialized metabolism in Arabidopsis 4 5 Marta Francisco1, Daniel J. Kliebenstein2,3, Víctor M. Rodríguez1, Pilar Soengas1, 6 Rosaura Abilleira1, María E. Cartea1 7 1Misión Biológica de Galicia, (MBG-CSIC), P.O. Box 28, 36080, Pontevedra, Spain 8 2Department of Plant Sciences, University of California at Davis, Davis, CA 95616, 9 USA. 10 3DynaMo Center of Excellence, University of Copenhagen, Thorvaldsensvej 40, DK- 11 1871 Frederiksberg C, Denmark. 12 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.07.285429; this version posted September 9, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. 13 Summary 14 Plant metabolism is modulated by a complex interplay between internal signals and 15 external cues. A major goal of all quantitative metabolomic studies is to clone the 16 underlying genes to understand the mechanistic basis of this variation. Using fine-scale 17 genetic mapping, in this work we report the identification and initial characterization of 18 NAD-DEPENDENT MALIC ENZYME 1 (NAD-ME1) as the candidate gene underlying 19 the pleiotropic network Met.II.15 QTL controlling variation in plant metabolism and 20 circadian clock outputs in the Bay × Sha Arabidopsis population. -
Microrna Expression Signature of Oral Squamous Cell Carcinoma: Functional Role of Microrna-26A&Sol;B in the Modulation of No
FULL PAPER British Journal of Cancer (2015) 112, 891–900 | doi: 10.1038/bjc.2015.19 Keywords: microRNA; oral squamous cell carcinoma; miR-26a; miR-26b; tumour suppressor; TMEM184B; expression signature MicroRNA expression signature of oral squamous cell carcinoma: functional role of microRNA-26a/b in the modulation of novel cancer pathways I Fukumoto1,2, T Hanazawa2, T Kinoshita1,2, N Kikkawa2, K Koshizuka1,2, Y Goto1, R Nishikawa1, T Chiyomaru3, H Enokida3, M Nakagawa3, Y Okamoto2 and N Seki*,1 1Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan; 2Department of Otorhinolaryngology/Head and Neck Surgery, Chiba University Graduate School of Medicine, Chiba, Japan and 3Department of Urology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan Background: MicroRNAs (miRNAs) have been shown to play major roles in carcinogenesis in a variety of cancers. The aim of this study was to determine the miRNA expression signature of oral squamous cell carcinoma (OSCC) and to investigate the functional roles of miR-26a and miR-26b in OSCC cells. Methods: An OSCC miRNA signature was constructed by PCR-based array methods. Functional studies of differentially expressed miRNAs were performed to investigate cell proliferation, migration, and invasion in OSCC cells. In silico database and genome-wide gene expression analyses were performed to identify molecular targets and pathways mediated by miR-26a/b. Results: miR-26a and miR-26b were significantly downregulated in OSCC. Restoration of both miR-26a and miR-26b in cancer cell lines revealed that these miRNAs significantly inhibited cancer cell migration and invasion. Our data demonstrated that the novel transmembrane TMEM184B gene was a direct target of miR-26a/b regulation. -
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. -
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. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
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. -
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 -
Role and Regulation of the P53-Homolog P73 in the Transformation of Normal Human Fibroblasts
Role and regulation of the p53-homolog p73 in the transformation of normal human fibroblasts Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg vorgelegt von Lars Hofmann aus Aschaffenburg Würzburg 2007 Eingereicht am Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Dr. Martin J. Müller Gutachter: Prof. Dr. Michael P. Schön Gutachter : Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am Erklärung Hiermit erkläre ich, dass ich die vorliegende Arbeit selbständig angefertigt und keine anderen als die angegebenen Hilfsmittel und Quellen verwendet habe. Diese Arbeit wurde weder in gleicher noch in ähnlicher Form in einem anderen Prüfungsverfahren vorgelegt. Ich habe früher, außer den mit dem Zulassungsgesuch urkundlichen Graden, keine weiteren akademischen Grade erworben und zu erwerben gesucht. Würzburg, Lars Hofmann Content SUMMARY ................................................................................................................ IV ZUSAMMENFASSUNG ............................................................................................. V 1. INTRODUCTION ................................................................................................. 1 1.1. Molecular basics of cancer .......................................................................................... 1 1.2. Early research on tumorigenesis ................................................................................. 3 1.3. Developing -
Modelling Cell Metabolism: a Review on Constraint-Based Steady-State and Kinetic Approaches
processes Review Modelling Cell Metabolism: A Review on Constraint-Based Steady-State and Kinetic Approaches Mohammadreza Yasemi and Mario Jolicoeur * Research Laboratory in Applied Metabolic Engineering, Department of Chemical Engineering, École Polytechnique de Montréal, P.O. Box 6079, Centre-ville Station, Montréal, QC H3C 3A7, Canada; [email protected] * Correspondence: [email protected] Abstract: Studying cell metabolism serves a plethora of objectives such as the enhancement of bio- process performance, and advancement in the understanding of cell biology, of drug target discovery, and in metabolic therapy. Remarkable successes in these fields emerged from heuristics approaches, for instance, with the introduction of effective strategies for genetic modifications, drug develop- ments and optimization of bioprocess management. However, heuristics approaches have showed significant shortcomings, such as to describe regulation of metabolic pathways and to extrapolate experimental conditions. In the specific case of bioprocess management, such shortcomings limit their capacity to increase product quality, while maintaining desirable productivity and reproducibility levels. For instance, since heuristics approaches are not capable of prediction of the cellular functions under varying experimental conditions, they may lead to sub-optimal processes. Also, such ap- proaches used for bioprocess control often fail in regulating a process under unexpected variations of external conditions. Therefore, methodologies inspired by the systematic mathematical formulation of cell metabolism have been used to address such drawbacks and achieve robust reproducible results. Mathematical modelling approaches are effective for both the characterization of the cell Citation: Yasemi, M.; Jolicoeur, M. physiology, and the estimation of metabolic pathways utilization, thus allowing to characterize Modelling Cell Metabolism: A a cell population metabolic behavior. -
Differential Effects of Insulin Signaling on Individual Carbon Fluxes for Fatty Acid Synthesis in Brown Adipocytes
Differential effects of insulin signaling on individual carbon fluxes for fatty acid synthesis in brown adipocytes Hyuntae Yoo*, Maciek Antoniewicz†, Joanne K. Kelleher†, and Gregory Stephanopoulos† Departments of Chemistry* and Chemical Engineering†, Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A. events of type II diabetes [1]. Therefore, understanding the Abstract— Considering the major role of insulin signaling detailed mechanism of regulation for fat synthesis and its on fatty acid synthesis via stimulation of lipogenic enzymes, relationship with insulin signaling may provide insights differential effects of insulin signaling on individual carbon into the pathogenesis of the two diseases and help fluxes for fatty acid synthesis have been investigated by preventing them. comparing the individual lipogenic fluxes in WT and IRS-1 knockout (IRS-1 KO) brown adipocytes. Results from Insulin signaling has long been associated with elevating experiments on WT and IRS-1 KO cells incubated with [5- overall lipogenic activity through increased activity of 13C] glutamine were consistent with the existence of reductive lipogenic enzymes [2]. Evidences have been accumulated carboxylation pathway. Analysis of isotopomer distribution that many of these enzymes are stimulated directly by of nine metabolites related to the lipogenic routes from insulin signaling via insulin response element at their glucose and glutamine in IRS-1 KO cells using [U-13C] transcription level or indirectly by insulin signaling to glutamine as compared to that in WT cells indicated that flux through reductive carboxylation pathway was diminished transcription factors [3]. However, studies on stimulation while flux through conventional TCA cycle was stimulated of lipogenic enzymes’ activity by insulin signaling have due to absence of insulin signaling in IRS-1 KO cells. -
Mouse Me1 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Me1 Knockout Project (CRISPR/Cas9) Objective: To create a Me1 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Me1 gene (NCBI Reference Sequence: NM_001198933 ; Ensembl: ENSMUSG00000032418 ) is located on Mouse chromosome 9. 14 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 14 (Transcript: ENSMUST00000185374). Exon 2~3 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a spontaneous allele exhibit decreased body weight on a medium fat diet, altered cytoplasmic malic enzyme activity, and a male-specific reduction in food intake on a high fat diet. Exon 2 starts from about 1.15% of the coding region. Exon 2~3 covers 17.15% of the coding region. The size of effective KO region: ~2089 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 14 Legends Exon of mouse Me1 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis.