Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling
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...
| Main Authors: | , , , , , , , |
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| Format: | Journal article |
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Elsevier
2017
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| _version_ | 1797076642819997696 |
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| author | Yu, Z Huang, H Reim, A Charles, P Northage, A Jackson, D Parry, I Kessler, B |
| author_facet | Yu, Z Huang, H Reim, A Charles, P Northage, A Jackson, D Parry, I Kessler, B |
| author_sort | Yu, Z |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T00:06:38Z |
| format | Journal article |
| id | oxford-uuid:77c3b9d5-0b50-47ae-9b6f-caa876f3018d |
| institution | University of Oxford |
| last_indexed | 2024-03-07T00:06:38Z |
| publishDate | 2017 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:77c3b9d5-0b50-47ae-9b6f-caa876f3018d2022-03-26T20:26:16ZOptimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profilingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:77c3b9d5-0b50-47ae-9b6f-caa876f3018dSymplectic Elements at OxfordElsevier2017Yu, ZHuang, HReim, ACharles, PNorthage, AJackson, DParry, IKessler, BTwo-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. |
| spellingShingle | Yu, Z Huang, H Reim, A Charles, P Northage, A Jackson, D Parry, I Kessler, B Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title | Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title_full | Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title_fullStr | Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title_full_unstemmed | Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title_short | Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling |
| title_sort | optimizing 2d gas chromatography mass spectrometry for robust tissue serum and urine metabolite profiling |
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