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Untargeted UPLC-MS profiling pipeline to expand tissue metabolome coverage: application to cardiovascular disease.
Vorkas, Panagiotis A; Isaac, Giorgis; Anwar, Muzaffar A; Davies, Alun H; Want, Elizabeth J; Nicholson, Jeremy K; Holmes, Elaine.
Afiliação
  • Vorkas PA; †Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, U.K.
  • Isaac G; ‡Pharmaceutical Discovery and Life Sciences, Waters Corporations, Milford, Massachusetts 01757, United States.
  • Anwar MA; §Academic Section of Vascular Surgery, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London W6 8RF, U.K.
  • Davies AH; §Academic Section of Vascular Surgery, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London W6 8RF, U.K.
  • Want EJ; †Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, U.K.
  • Nicholson JK; †Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, U.K.
  • Holmes E; ∥MRC-NIHR National Phenome Centre, IRDB Building, Imperial College London, Hammersmith Hospital, London W12 0NN, U.K.
Anal Chem ; 87(8): 4184-93, 2015 Apr 21.
Article em En | MEDLINE | ID: mdl-25664760
ABSTRACT
Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (n = 120) of arterial tissue could be distinguished based on their metabolic profiles.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artérias Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artérias Idioma: En Ano de publicação: 2015 Tipo de documento: Article