Literature DB >> 32419109

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry.

Mohammad Khodadadi1, Morteza Pourfarzam2.   

Abstract

BACKGROUND: Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR. AIM OF REVIEW: This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Entities:  

Keywords:  Derivatization; Gas chromatography; Mass spectrometry; Metabolomics; Urine

Mesh:

Year:  2020        PMID: 32419109     DOI: 10.1007/s11306-020-01687-x

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  9 in total

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

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Review 8.  Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

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Journal:  Diabetes Metab Syndr Obes       Date:  2022-01-29       Impact factor: 3.168

9.  Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method.

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Journal:  PLoS One       Date:  2022-10-06       Impact factor: 3.752

  9 in total

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