Literature DB >> 24945638

Metabolomic analysis using porcine skin: a pilot study of analytical techniques.

Julie Wu, Oliver Fiehn, April W Armstrong1.   

Abstract

BACKGROUND: Metabolic byproducts serve as indicators of the chemical processes and can provide valuable information on pathogenesis by measuring the amplified output. Standardized techniques for metabolome extraction of skin samples serve as a critical foundation to this field but have not been developed.
OBJECTIVES: We sought to determine the optimal cell lysage techniques for skin sample preparation and to compare GC-TOF-MS and UHPLC-QTOF-MS for metabolomic analysis.
METHODS: Using porcine skin samples, we pulverized the skin via various combinations of mechanical techniques for cell lysage. After extraction, the samples were subjected to GC-TOF-MS and/or UHPLC-QTOF-MS.
RESULTS: Signal intensities from GC-TOF-MS analysis showed that ultrasonication (2.7x107) was most effective for cell lysage when compared to mortar-and-pestle (2.6x107), ball mill followed by ultrasonication (1.6x107), mortar-and-pestle followed by ultrasonication (1.4x107), and homogenization (trial 1: 8.4x106; trial 2: 1.6x107). Due to the similar signal intensities, ultrasonication and mortar-and-pestle were applied to additional samples and subjected to GC-TOF-MS and UHPLC-QTOF-MS. Ultrasonication yielded greater signal intensities than mortar-and-pestle for 92% of detected metabolites following GC-TOF-MS and for 68% of detected metabolites following UHPLC-QTOF-MS.
CONCLUSION: Overall, ultrasonication is the preferred method for efficient cell lysage of skin tissue for both metabolomic platforms. With standardized sample preparation, metabolomic analysis of skin can serve as a powerful tool in elucidating underlying biological processes in dermatological conditions.

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Year:  2014        PMID: 24945638

Source DB:  PubMed          Journal:  Dermatol Online J        ISSN: 1087-2108


  1 in total

1.  Explore the Anti-Acne Mechanism of Licorice Flavonoids Based on Metabonomics and Microbiome.

Authors:  Shi-Fa Ruan; Yi Hu; Wen-Feng Wu; Qun-Qun Du; Zhu-Xian Wang; Ting-Ting Chen; Qun Shen; Li Liu; Cui-Ping Jiang; Hui Li; Yankui Yi; Chun-Yan Shen; Hong-Xia Zhu; Qiang Liu
Journal:  Front Pharmacol       Date:  2022-02-08       Impact factor: 5.810

  1 in total

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