Ultra-Performance Liquid Chromatography High-Resolution Mass Spectrometry and Direct Infusion-High-Resolution Mass Spectrometry for Combined Exploratory and Targeted Metabolic Profiling of Human Urine

被引:17
|
作者
Chekmeneva, Elena [1 ,5 ]
Correia, Goncalo dos Santos [1 ,5 ]
Gomez-Romero, Maria [1 ,5 ]
Stamler, Jeremiah [2 ]
Chan, Queenie [3 ,4 ]
Elliott, Paul [3 ,4 ]
Nicholson, Jeremy K. [1 ,5 ]
Holmes, Elaine [1 ,4 ]
机构
[1] Imperial Coll London, Dept Surg & Canc, Div Integrat Syst & Digest Med, Sir Alexander Fleming Bldg, London SW7 2AZ, England
[2] Northwestern Univ, Dept Prevent Med, Feinberg Sch Med, Chicago, IL 60611 USA
[3] Imperial Coll London, Sch Publ Hlth, Dept Epidemiol & Biostat, St Marys Campus, London W2 1PG, England
[4] Imperial Coll London, Sch Publ Hlth, MRC PHE Ctr Environm & Hlth, St Marys Campus, London W2 1PG, England
[5] Imperial Coll London, Dept Surg & Canc, NIHR BRC Clin Phenotyping Ctr, Sir Alexander Fleming Bldg, London SW7 2AZ, England
基金
英国医学研究理事会; 美国国家卫生研究院;
关键词
ultra performance liquid chromatography; direct infusion mass spectrometry; metabolic profiling; exploratory analysis; quantitative analysis; high-throughput analysis; LARGE-SCALE; NMR-SPECTROSCOPY; BIOLOGICAL SAMPLES; MS; IDENTIFICATION; PLASMA; SERUM; ANNOTATION; PHENOTYPE; DILUTION;
D O I
10.1021/acs.jproteome.8b00413
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here direct infusion nanoelectrospray (DI-nESI) was compared with an ultra performance liquid chromatography (UPLC)-high-resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimized to allow the simultaneous collection of high-resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was 5 days compared with 9 h by DI-nESI-HRMS. To compare the classification ability of the two MS methods, we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data, we showed that 10 metabolites have strong correlation (Pearson's r > 0.9 and Passing-Bablok regression slope of 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus can be measured using a cheaper and less sample- and time-consuming method. A further twenty metabolites showed acceptable correlation between the two methods with only five metabolites showing weak correlation (Pearson's r < 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS.
引用
收藏
页码:3492 / 3502
页数:11
相关论文
共 50 条
  • [21] Metabolic profiling of senkyunolide A and identification of its metabolites in hepatocytes by ultra-high-performance liquid chromatography combined with diode-array detector and high-resolution mass spectrometry
    Zhang, Hui
    Liu, Chunjuan
    Wang, Minghua
    Sui, Yong
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2020, 34 (21)
  • [22] Characterization of the metabolites of dichotomitin in rat, monkey and human by ultra-high-performance liquid chromatography/high-resolution mass spectrometry
    Zhang, Kai-Xuan
    Dong, Na
    Guo, Le
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2021, 35 (21)
  • [23] Ultra performance liquid chromatography and high resolution mass spectrometry for the analysis of plant lipids
    Hummel, Jan
    Segu, Shruthi
    Li, Yan
    Irgang, Susann
    Jueppner, Jessica
    Giavalisco, Patrick
    FRONTIERS IN PLANT SCIENCE, 2011, 2
  • [24] Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry
    Salah Abdelrazig
    Catharine A. Ortori
    Michael Doherty
    Ana M. Valdes
    Victoria Chapman
    David A. Barrett
    Metabolomics, 2021, 17
  • [25] Rapid detection and quantification of aminoglycoside phosphorylation products using direct-infusion high-resolution and ultra-high-performance liquid chromatography/mass spectrometry
    Perez, Johnny J.
    Chen, Chin-Yi
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2018, 32 (20) : 1822 - 1828
  • [26] Targeted and Untargeted Detection of DNA Adducts of Aromatic Amine Carcinogens in Human Bladder by Ultra-Performance Liquid Chromatography-High-Resolution Mass Spectrometry
    Guo, Jingshu
    Villalta, Peter W.
    Weight, Christopher J.
    Bonala, Radha
    Johnson, Francis
    Rosenquist, Thomas A.
    Turesky, Robert J.
    CHEMICAL RESEARCH IN TOXICOLOGY, 2018, 31 (12) : 1382 - 1397
  • [27] MASS SPECTROMETRY -A SPOTLIGHT ON HIGH-RESOLUTION MASS SPECTROMETRY
    Cook, Brandoch
    Lab Manager, 2024, 19 (01): : 54 - 55
  • [28] Metabolic profile of Fructus Gardeniae in human plasma and urine using ultra high-performance liquid chromatography coupled with high-resolution LTQ-orbitrap mass spectrometry
    Wang, Gao-Wa
    Bao, Burenbatu
    Han, Zhi-Qiang
    Han, Qing-Yu
    Yang, Xiu-Lan
    XENOBIOTICA, 2016, 46 (10) : 901 - 912
  • [29] Metabolic profile of Rhizoma coptidis in human plasma determined using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry
    Zhang, Qing-Shan
    Wang, Gao-Wa
    Han, Zhi-Qiang
    Chen, Xiang-Mei
    Na, Risu
    Jin, Haburi
    Li, Ping
    Bu, Renbatu
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2018, 32 (01) : 63 - 73
  • [30] Lipidomic profiling of targeted oxylipins with ultra-performance liquid chromatography-tandem mass spectrometry
    Zhi-Xin Yuan
    Sharon Majchrzak-Hong
    Gregory S. Keyes
    Michael J. Iadarola
    Andrew J. Mannes
    Christopher E. Ramsden
    Analytical and Bioanalytical Chemistry, 2018, 410 : 6009 - 6029