Print Email Facebook Twitter Characterization of anti-inflammatory compounds using transcriptions, proteomics, and metabolics in combination with multivariate data analysis Title Characterization of anti-inflammatory compounds using transcriptions, proteomics, and metabolics in combination with multivariate data analysis Author Verhoeckx, K.C.M. Bijlsma, S. Jespersen, S. Ramaker, R. Verheij, E.R. Witkamp, R.F. van der Greef, J. Rodenburg, R.J.T. TNO Voeding Centraal Instituut voor Voedingsonderzoek TNO Publication year 2004 Abstract The discovery of new anti-inflammatory drugs is often based on an interaction with a specific target, although other pathways often play a primary or secondary role. Anti-inflammatory drugs can be categorized into classes, based on their mechanism of action. In this article we investigate the possibility to characterize novel anti-inflammatory compounds by three holistic methods. For this purpose, we make use of macrophage-like U937 cells which are stimulated with LPS in the absence or presence of an anti-inflammatory compound. Using micro-arrays, 2-D gel electrophoresis and a LC-MS method for lipids the effects on the transcriptome, proteome and metabolome of the exposed cells is investigated. The expression patterns are subsequently analyzed using in-house developed pattern recognition tools. Using the methods described above, we have examined the effects of six anti-inflammatory compounds. Our results demonstrate that different classes of anti-inflammatory compounds show distinct and characteristic mRNA, protein, and lipid expression patterns, which can be used to categorise known molecules and to discover and classify new leads. The potential of our approach is illustrated by the analysis of several beta (2)-adrenergic agonists (β2-agonists). In addition to their primary pharmacological target, β2-agonists posses certain anti-inflammatory properties. We were able to show that zilpaterol, a poorly characterized β2-agonist, gives rise to an almost identical expression pattern as the β2-agonists clenbuterol and salbutamol. Furthermore we have identified specific mRNA, protein and lipid markers for the anti-inflammatory compounds investigated in this study. © 2004 Elsevier B.V. All rights reserved. Chemicals/CAS: 4 (4 fluorophenyl) 2 (4 methylsulfinylphenyl) 5 (4 pyridyl)imidazole, 152121-47-6; clenbuterol, 21898-19-1, 37148-27-9; dexamethasone, 50-02-2; formoterol, 73573-87-2; salbutamol, 18559-94-9; Adrenergic beta-Agonists; Anti-Inflammatory Agents; Lipids; lipopolysaccharide, Escherichia coli 0111 B4; Lipopolysaccharides; Proteome; Receptors, Adrenergic, beta-2; RNA, Messenger Subject Pharmacology Health2-D gel electrophoresisAnti-inflammatory drugsMetabolomicsMicro-arrayMultivariate data analysisPrincipal component discriminant analysis4 (4 fluorophenyl) 2 (4 methylsulfinylphenyl) 5 (4 pyridyl)imidazoleAntiinflammatory agentBeta 2 adrenergic receptor stimulating agentClenbuterolDexamethasoneFormoterolLipopolysaccharideSalbutamolUnclassified drugZilpaterolAntiinflammatory activitycontrolled studyData analysisDNA microarrayDrug determinationGel electrophoresisGenetic transcriptionHumanHuman cellLipogenesisLiquid chromatographyMass spectrometryMetabolismMethodologyMoleculeMonocyteMultivariate analysisPriority journalProtein expressionProteomicsAdrenergic beta-AgonistsAnti-Inflammatory AgentsCell Line, TumorElectrophoresis, Gel, Two-DimensionalGas Chromatography-Mass SpectrometryHumansLipidsLipopolysaccharidesMacrophage ActivationMacrophagesMultivariate AnalysisOligonucleotide Array Sequence AnalysisProteomeReceptors, Adrenergic, beta-2RNA, Messenger To reference this document use: http://resolver.tudelft.nl/uuid:f8b1418f-65e5-43e1-9e24-9e9b25c7094f DOI https://doi.org/10.1016/j.intimp.2004.07.008 TNO identifier 88523 Source International Immunopharmacology, 4, 1499-1514 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.