Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling

Abstract

Two-dimensional gas chromatography mass spectrometry (GCxGC-MS) is utilized to an increasing extent in biomedical metabolomics. Here, we established and adapted metabolite extraction and derivatization protocols for cell/tissue biopsy, serum and urine samples according to their individual properties. GCxGC-MS analysis revealed detection of ~600 molecular features from which 165 were characterized representing different classes such as amino acids, fatty acids, lipids, carbohydrates, nucleotides and small polar components of glycolysis and the Krebs cycle using electron impact (EI) spectrum matching and validation using external standard compounds. Advantages of two-dimensional gas chromatography based resolution were demonstrated by optimizing gradient length and separation through modulation between the first and second column, leading to a marked increase in metabolite identification due to improved separation as exemplified for lactate versus pyruvate, talopyranose versus methyl palmitate and inosine versus docosahexaenoic acid. Our results demonstrate that GCxGC-MS represents a robust metabolomics platform for discovery and targeted studies that can be used with samples derived from the clinic.

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

“…In addition, various databases have been developed to aid in assigning structures to spectral peaks observed in metabolomics experiments [78][79][80]. Furthermore, limitations of GC-MS have recently been improved by the development of two-dimensional GC × GC coupled with high resolution mass spectrometry [81][82][83][84]. In this approach, two columns with different properties (non-polar vs. polar) are connected through a modulator, allowing further separation of compounds that co-elute from the first column, thereby giving rise to enhanced resolution and peak capacity [85,86].…”

Current status of retention time prediction in metabolite identification

“…This increases the peak capacity dramatically and allows for the detection of more substances. Although methods like GC×GC [27] and LC×LC [28] are gaining more attention, they are mostly used by specialist laboratories. While the use of RT in GC has been standardized, e.g., by the use of the Kovats index; in contrast, LC–MS shows much higher variation.…”

Autophagy in T cells from aged donors is maintained by spermidine, and correlates with function and vaccine responses

“…The derivatization product was dried, re-suspended in 30 µL isopropanol and transferred to glass loading-vials. The samples were analyzed using a GCxGC-MS system as described 41 . The following parameters were used for quantification of the 1D-GC-qMS data: Slope: 1000/min, width: 0.04 s, drift 0/min and T. DBL: 1000 min without any smoothing methods used.…”