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A Sample Preparation Method for the Simultaneous Profiling of Signaling Lipids and Polar Metabolites in Small Quantities of Muscle Tissues from a Mouse Model for Sarcopenia.
He, Yupeng; van Mever, Marlien; Yang, Wei; Huang, Luojiao; Ramautar, Rawi; Rijksen, Yvonne; Vermeij, Wilbert P; Hoeijmakers, Jan H J; Harms, Amy C; Lindenburg, Peter W; Hankemeier, Thomas.
Afiliação
  • He Y; Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
  • van Mever M; Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
  • Yang W; Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
  • Huang L; Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
  • Ramautar R; Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
  • Rijksen Y; Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands.
  • Vermeij WP; Oncode Institute, 3521 AL Utrecht, The Netherlands.
  • Hoeijmakers JHJ; Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands.
  • Harms AC; Oncode Institute, 3521 AL Utrecht, The Netherlands.
  • Lindenburg PW; Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands.
  • Hankemeier T; Oncode Institute, 3521 AL Utrecht, The Netherlands.
Metabolites ; 12(8)2022 Aug 12.
Article em En | MEDLINE | ID: mdl-36005613
ABSTRACT
The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1∆/- mouse mutant exhibiting multiple-morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article