Optimisation of Urine Sample Preparation for Headspace-Solid Phase Microextraction Gas Chromatography-Mass Spectrometry: Altering Sample pH, Sulphuric Acid Concentration and Phase Ratio

Metabolites

MarkT. Boyd¹  ElinorA. Chapman²  James Baker²  Prashant Aggarwal²  Chris Probert²  Séamus Coyle³ 

[1]Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK

[2]Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK

[3]Palliative Care Institute Liverpool, Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK

关键词: volatile organic compounds;    VOCs;    H₂SO₄;    NaOH;    HCl;    sodium hydroxide;   

DOI  :  10.3390/metabo10120482

来源: DOAJ

【 摘 要 】

Headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) can be used to measure volatile organic compounds (VOCs) in human urine. However, there is no widely adopted standardised protocol for the preparation of urine samples for analysis resulting in an inability to compare studies reliably between laboratories. This paper investigated the effect of altering urine sample pH, volume, and vial size for optimising detection of VOCs when using HS-SPME-GC-MS. This is the first, direct comparison of H₂SO₄, HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H₂SO₄ is more effective at optimising detection of VOCs than HCl or NaOH. H₂SO₄ resulted in a significantly larger mean number of VOCs being identified per sample (on average, 33.5 VOCs to 24.3 in HCl or 12.2 in NaOH treated urine) and more unique VOCs, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H₂SO₄ to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification.

【 授权许可】

Unknown