Two-dimensional comprehensive GC-MS (GC×GC-MS) is the most advanced GC platform, among other, presenting a great potential for metabolomic studies because of its uncomparable separation power, sensitivity and possibility to obtain structured 2D patterns that can be adopted for. GC×GC-MS profiles can successfully be used for samples cross-comparisons to provide more extensive information than with 1D-GC-MS enabling to run simultaneously sample profiling and fingerprinting. However, the great diversity of chemical properties and the wide concentration ranges of these compounds in tissues and biological fluids is a significant challenge since methods need to be robust, reproducible, accurate and informative to enable samples to be reliably compared. In this perspective, the system configuration is a critical but challenging aspect requiring a careful tuning of columns diameters to avoid 2D column overloading and to improve quantitation accuracy and response linearity over a wider range of concentration [1]. This study investigates the advantages of a GC×2GC system in the metabolite profiling of urine samples from murine models of diet-induced metabolic derangements, characterized by hyperlipidemia, impaired glucose tolerance and insulin resistance. [2]. The system consists of a conventional first dimension column (1D - 30 m x 0.25 mm ID) coupled to two second dimension columns of variable lengths (2D-FID 1.6 m x 0.1 mm ID and 2D-MS 1.8 m x 0.1 mm ID) and combined with parallel MS and FID detection. In particular, male C57BL/6J mice were maintained on control rodent diet or high-fat high-fructose diet (HFHF, 45 kcal% Fat and 24 kcal% Fructose) for 22 weeks and urine samples were collected at different steps of the study. Our preliminary results show that urine sample profiles offer pivotal and comparative data on the presence and on the relative distribution of early markers of metabolic disease. Besides, samples collected at the end of the experiments provide information on the global impact of the dietary manipulation on the systemic metabolism. Experimental results emphasized the advantages of the adopted configuration in terms of quantitation accuracy and precision in targeted profiling, maximization of the informative potentials due to the increased 2D column loadability and selectivity, reliability of untargeted fingerprinting performed by template matching approaches [3] on dual patterns. References [1] M.F. Almstetter, P.J. Oefner, K. Dettmer Analytical and Bioanalytical Chemistry 2012;402 (6):1993-2013. [2] M. Collino, M. Aragno , S. Castiglia, G. Miglio, C. Tomasinelli et al. Br J Pharmacol. 160, 1892-902 (2010) [3] S.E. Reichenbach, X. Tian , A.A. Boateng, C.A. Mullen , C. Cordero, Q. Tao, Anal Chem.

DUAL SECOND DIMENSION COLUMN-DUAL DETECTION IN TWO-DIMENSIONAL COMPREHENSIVE GAS CHROMATOGRAPHY (GC×2GC-MS/FID): INCREASED INFORMATION IN OPTIMIZED SEPARATION CONDITIONS IN METABOLOMICS

Fausto Chiazza;
2014-01-01

Abstract

Two-dimensional comprehensive GC-MS (GC×GC-MS) is the most advanced GC platform, among other, presenting a great potential for metabolomic studies because of its uncomparable separation power, sensitivity and possibility to obtain structured 2D patterns that can be adopted for. GC×GC-MS profiles can successfully be used for samples cross-comparisons to provide more extensive information than with 1D-GC-MS enabling to run simultaneously sample profiling and fingerprinting. However, the great diversity of chemical properties and the wide concentration ranges of these compounds in tissues and biological fluids is a significant challenge since methods need to be robust, reproducible, accurate and informative to enable samples to be reliably compared. In this perspective, the system configuration is a critical but challenging aspect requiring a careful tuning of columns diameters to avoid 2D column overloading and to improve quantitation accuracy and response linearity over a wider range of concentration [1]. This study investigates the advantages of a GC×2GC system in the metabolite profiling of urine samples from murine models of diet-induced metabolic derangements, characterized by hyperlipidemia, impaired glucose tolerance and insulin resistance. [2]. The system consists of a conventional first dimension column (1D - 30 m x 0.25 mm ID) coupled to two second dimension columns of variable lengths (2D-FID 1.6 m x 0.1 mm ID and 2D-MS 1.8 m x 0.1 mm ID) and combined with parallel MS and FID detection. In particular, male C57BL/6J mice were maintained on control rodent diet or high-fat high-fructose diet (HFHF, 45 kcal% Fat and 24 kcal% Fructose) for 22 weeks and urine samples were collected at different steps of the study. Our preliminary results show that urine sample profiles offer pivotal and comparative data on the presence and on the relative distribution of early markers of metabolic disease. Besides, samples collected at the end of the experiments provide information on the global impact of the dietary manipulation on the systemic metabolism. Experimental results emphasized the advantages of the adopted configuration in terms of quantitation accuracy and precision in targeted profiling, maximization of the informative potentials due to the increased 2D column loadability and selectivity, reliability of untargeted fingerprinting performed by template matching approaches [3] on dual patterns. References [1] M.F. Almstetter, P.J. Oefner, K. Dettmer Analytical and Bioanalytical Chemistry 2012;402 (6):1993-2013. [2] M. Collino, M. Aragno , S. Castiglia, G. Miglio, C. Tomasinelli et al. Br J Pharmacol. 160, 1892-902 (2010) [3] S.E. Reichenbach, X. Tian , A.A. Boateng, C.A. Mullen , C. Cordero, Q. Tao, Anal Chem.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/104604
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact