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  • 1.
    Allard, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Metabolic Studies with Liquid Separation Coupled to Mass Spectrometry2008Licentiate thesis, comprehensive summary (Other academic)
  • 2.
    Allard, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Metabolic Studies with Liquid Separation Coupled to Mass Spectrometry2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Metabolism is the sum of all chemical processes with the purpose to maintain life, as well as enable reproduction, in a living organism. Through the study of metabolism, increased understanding of pharmacological mechanisms and diseases can be achieved. This thesis describes several ways of doing so, including targeted analysis of selected metabolites and investigations of systematic metabolic differences between selected groups through pattern recognition.

    A method for exploring metabolic patterns in urine samples after intake of coffee or tea was developed. The methodology was later used with the aim to find biomarkers for prostate cancer and urinary bladder cancer.

    Furthermore, a fully automated quantitative method was developed for concentration measurements of the double prodrug ximelagatran and its metabolites in pig liver. The method was then used to study the roll of active transporters in pig liver cells.

    Moreover, a fundamental study was conducted to investigate how monitoring of small, doubly charged analytes can improve the limit of detection and precision in a quantitative method.

    The techniques used for the experiments were liquid separation coupled to electrospray mass spectrometry. Extra efforts were made to make the separation and the ionization as compatible as possible to each other for increased quality of the collected data.

    List of papers
    1. Comparing capillary electrophoresis: mass spectrometry fingerprints of urine samples obtained after intake of coffee, tea, or water.
    Open this publication in new window or tab >>Comparing capillary electrophoresis: mass spectrometry fingerprints of urine samples obtained after intake of coffee, tea, or water.
    Show others...
    2008 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 80, no 23, p. 8946-8955Article in journal (Refereed) Published
    Abstract [en]

    Metabolomic fingerprinting is a growing strategy for characterizing complex biological samples without detailed prior knowledge about the metabolic system. A two-way analysis system with liquid separation and mass spectrometric detection provides detail-rich data suitable for such fingerprints. As a model study, human urine samples, obtained after intake of coffee, tea, or water, were analyzed with capillary electrophoresis electrospray ionization time-of-flight mass spectrometry (CE−ESI-TOF-MS). In-house-developed software (in Matlab) was utilized to manage and explore the large amount of data acquired (230 CE−MS runs, each with 50−100 million nonzero data points). After baseline and noise reduction, followed by suitable binning in time and m/z, the data sets comprised 9 and 14 million data points in negative and positive ESI mode, respectively. Finally, a signal threshold was applied, further reducing the number to about 100 000 data points per data set. A set of interactive exploratory tools, utilizing principal component analysis (PCA) and analysis of variance (ANOVA) results based on a general linear model, facilitated visual interpretation with score plots (for group assessment) and differential fingerprints (for “hot spot” detection). In the model study highly significant differences due to beverage intake were obtained among the 10 first principal components (p < 10−6 for two of the components in both ESI modes). Especially, the contrasts between “coffee” and “tea or water” indicated several “hot spots” with highly elevated intensities (e.g., for uncharged masses 93, 94, 109, 119, 123, 132, 148, 169, 178, 187, 190, and 193) suitable for further analysis, for example, with tandem MS.

    National Category
    Analytical Chemistry
    Research subject
    Analytical Chemistry
    Identifiers
    urn:nbn:se:uu:diva-100706 (URN)10.1021/ac801012y (DOI)000261335600015 ()18954082 (PubMedID)
    Available from: 2009-04-06 Created: 2009-04-06 Last updated: 2017-12-13Bibliographically approved
    2. Online capillary solid phase extraction and liquid chromatographic separation with quantitative tandem mass spectrometric detection (SPE-LC-MS/MS) of ximelagatran and its metabolites in a complex matrix.
    Open this publication in new window or tab >>Online capillary solid phase extraction and liquid chromatographic separation with quantitative tandem mass spectrometric detection (SPE-LC-MS/MS) of ximelagatran and its metabolites in a complex matrix.
    Show others...
    2009 (English)In: Journal of chromatography. B, ISSN 1570-0232, E-ISSN 1873-376X, Vol. 877, no 3, p. 291-297Article in journal (Refereed) Published
    Abstract [en]

    This work presents the development and validation of a fully automated quantitative analysis method of melagatran, its prodrug ximelagatran, and its major metabolites for the study of drug behavior in biofluids. The method involves online sample clean-up and enrichment on a C4 capillary column followed by separation on a capillary C18 column. Electrospray ionization tandem mass spectrometric detection in positive ion mode was performed with multiple reactions monitoring of eight different transients, divided into two time segments with four transients each. The structural similarity, the complexity of the matrix (pig liver extract) and the formation of isobaric fragment ions, made efficient chromatographic separation necessary. The analysis method provides valid accuracy (<9%; RSD%), precision (<8%; RSD%), linearity (<1.2 nM–1 μM; R2 > 0.999), limit of quantitation (<3.6 nM), retention repeatability (<1.2%; RSD%), selectivity, as well as analyte and column stabilities over a wide concentration range.

    Keywords
    Online, solid phase extraction, liquid chromatography, mass spectrometry, ximelagatran, metabolites, pig liver
    National Category
    Chemical Sciences
    Identifiers
    urn:nbn:se:uu:diva-88170 (URN)10.1016/j.jchromb.2008.12.017 (DOI)000262877500026 ()19117807 (PubMedID)
    Available from: 2009-01-22 Created: 2009-01-22 Last updated: 2017-12-14Bibliographically approved
    3. Hepatic disposition of ximelagatran and its metabolites in pig; prediction of the impact of membrane transporters through a simple disposition model
    Open this publication in new window or tab >>Hepatic disposition of ximelagatran and its metabolites in pig; prediction of the impact of membrane transporters through a simple disposition model
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    2010 (English)In: Pharmaceutical research, ISSN 0724-8741, E-ISSN 1573-904X, Vol. 27, no 4, p. 597-607Article in journal (Refereed) Published
    Abstract [en]

    Purpose: The double prodrug ximelagatran is bioconverted, via the intermediates ethylmelagatran and N-hydroxymelagatran, to the direct thrombin inhibitor melagatran. The aims of this study were 1) to investigate the hepatic metabolism and disposition of ximelagatran and the intermediates in pig; and 2) to test a simple in vitro methodology for quantitative investigations of membrane transporters impact on the disposition of metabolized drugs. Methods: Porcine S1 (supernatant fraction obtained by centrifuging at 1000g for 10 min) liver fractions and hepatocytes were incubated in absence and presence of known membrane transporter inhibitors. The in vitro kinetics and disposition were determined by simultaneously fitting of the disappearance of ximelagatran and appearance of ethylmelagatran, N-hydroxymelagatran and melagatran. Results: In S1 liver fractions, the metabolism was significant inhibited by co-incubation of verapamil and ketoconazole but not by erythromycin, quinine and quinidine. The disposition of ximelagatran and the intermediate metabolites in hepatocytes were influenced, to various degrees, by carrier-mediated distribution processes. Conclusion: This work demonstrates that it is possible to obtain profound information of the general mechanisms important in the drug liver disposition with the combination of common in vitro systems and the simple disposition model proposed in this study.

    Keywords
    melagatran, prodrug, hepatic disposition, kinetic modeling, hepatocytes
    National Category
    Pharmacology and Toxicology
    Research subject
    Drug Metabolism
    Identifiers
    urn:nbn:se:uu:diva-110319 (URN)10.1007/s11095-009-0016-y (DOI)000275556000007 ()20140637 (PubMedID)
    Available from: 2009-11-10 Created: 2009-11-10 Last updated: 2018-01-12Bibliographically approved
    4. Exploring liquid chromatography-mass spectrometry fingerprints of urine samples from patients with prostate or urinary bladder cancer
    Open this publication in new window or tab >>Exploring liquid chromatography-mass spectrometry fingerprints of urine samples from patients with prostate or urinary bladder cancer
    2011 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 108, no 1, p. 33-48Article in journal (Refereed) Published
    Abstract [en]

    Data processing and analysis have become true rate and success limiting factors for molecular research where a large number of samples of high complexity are included in the data set. In general rather complicated methodologies are needed for the combination and comparison of information as obtained from selected analytical platforms. Although commercial as well as freely accessible software for high-throughput data processing are available for most platforms, tailored in-house solutions for data management and analysis can provide the versatility and transparency eligible for e.g. method development and pilot studies. This paper describes a procedure for exploring metabolic fingerprints in urine samples from prostate and bladder cancer patients with a set of in-house developed Matlab tools. In spite of the immense amount of data produced by the LC-MS platform, in this study more than 1010 data points, it is shown that the data processing tasks can be handled with reasonable computer resources. The preprocessing steps include baseline subtraction and noise reduction, followed by an initial time alignment. In the data analysis the fingerprints are treated as 2-D images, i.e. pixel by pixel, in contrast to the more common list-based approach after peak or feature detection. Although the latter approach greatly reduces the data complexity, it also involves a critical step that may obscure essential information due to undetected or misaligned peaks. The effects of remaining time shifts after the initial alignment are reduced by a binning and [‘]blurring’ procedure prior to the comparative multivariate and univariate data analyses. Other factors than cancer assignment were taken into account by ANOVA applied to the PCA scores as well as to the individual variables (pixels). It was found that the analytical day-to-day variations in our study had a large confounding effect on the cancer related differences, which emphasizes the role of proper normalization and/or experimental design. While PCA could not establish significant cancer related patterns, the pixel-wise univariate analysis could provide a list of about a hundred [‘]hotspots’ indicating possible biomarkers. This was also the limited goal for this study, with focus on the exploration of a really huge and complex data set. True biomarker identification, however, needs thorough validation and verification in separate patient sets.

    Keywords
    Urine profile, LC MS, Metabolic fingerprinting
    National Category
    Analytical Chemistry
    Research subject
    Analytical Chemistry
    Identifiers
    urn:nbn:se:uu:diva-110321 (URN)10.1016/j.chemolab.2011.03.008 (DOI)000293430300005 ()
    Available from: 2009-11-10 Created: 2009-11-10 Last updated: 2017-12-12Bibliographically approved
    5. Quantitative aspects of analyzing small molecules - monitoring singly or doubly charged ions?: A case study of ximelagatran.
    Open this publication in new window or tab >>Quantitative aspects of analyzing small molecules - monitoring singly or doubly charged ions?: A case study of ximelagatran.
    2010 (English)In: Rapid Communications in Mass Spectrometry, ISSN 0951-4198, E-ISSN 1097-0231, Vol. 24, no 4, p. 429-435Article in journal (Refereed) Published
    Abstract [en]

    Precision, reproducibility and lower limit of quantitation (LLOQ) are important characteristics of a quantitative method. We have investigated these properties for Ximelagatran (Xi), which has a high tendency to form doubly charged ions in electrospray ionization (ESI), by studying the percentage of doubly charged species formed when varying the formic acid (FA) concentration, analyte concentration, amount of organic modifier and flow rate. It was found that the percentage of [Xi + 2H]2+ can be controlled to be more than 90% or less than 10% by varying the amount of FA present, and that the change between these values is dramatic. Furthermore, the percentage of [Xi + 2H]2+ formed decreases with increased analyte concentration and increased flow rate. No apparent relationship with the amount of organic modifier was found. The results have the implication that, by carefully controlling the selected parameters, the LLOQ, precision and reproducibility can be improved. We have compared the fragmentation of the singly and doubly charged species and concluded that the [Xi + 2H]2+ ion is more inclined to undergo fragmentation than [Xi + H]+. As a consequence, unusual instrumental settings had to be used for the experiments. The fragmentation patterns are to a great extent similar, but the doubly charged species is more inclined to generate low-mass product ions.

    Keywords
    Charge state, ximelagatran, quantitation, ESI
    National Category
    Chemical Sciences
    Research subject
    Analytical Chemistry
    Identifiers
    urn:nbn:se:uu:diva-110320 (URN)10.1002/rcm.4414 (DOI)000274585000006 ()20069691 (PubMedID)
    Available from: 2009-11-10 Created: 2009-11-10 Last updated: 2017-12-12Bibliographically approved
  • 3.
    Danielsson, Rolf
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Allard, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Sjöberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Bergquist, Jonas
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Physical and Analytical Chemistry, Analytical Chemistry.
    Exploring liquid chromatography-mass spectrometry fingerprints of urine samples from patients with prostate or urinary bladder cancer2011In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 108, no 1, p. 33-48Article in journal (Refereed)
    Abstract [en]

    Data processing and analysis have become true rate and success limiting factors for molecular research where a large number of samples of high complexity are included in the data set. In general rather complicated methodologies are needed for the combination and comparison of information as obtained from selected analytical platforms. Although commercial as well as freely accessible software for high-throughput data processing are available for most platforms, tailored in-house solutions for data management and analysis can provide the versatility and transparency eligible for e.g. method development and pilot studies. This paper describes a procedure for exploring metabolic fingerprints in urine samples from prostate and bladder cancer patients with a set of in-house developed Matlab tools. In spite of the immense amount of data produced by the LC-MS platform, in this study more than 1010 data points, it is shown that the data processing tasks can be handled with reasonable computer resources. The preprocessing steps include baseline subtraction and noise reduction, followed by an initial time alignment. In the data analysis the fingerprints are treated as 2-D images, i.e. pixel by pixel, in contrast to the more common list-based approach after peak or feature detection. Although the latter approach greatly reduces the data complexity, it also involves a critical step that may obscure essential information due to undetected or misaligned peaks. The effects of remaining time shifts after the initial alignment are reduced by a binning and [‘]blurring’ procedure prior to the comparative multivariate and univariate data analyses. Other factors than cancer assignment were taken into account by ANOVA applied to the PCA scores as well as to the individual variables (pixels). It was found that the analytical day-to-day variations in our study had a large confounding effect on the cancer related differences, which emphasizes the role of proper normalization and/or experimental design. While PCA could not establish significant cancer related patterns, the pixel-wise univariate analysis could provide a list of about a hundred [‘]hotspots’ indicating possible biomarkers. This was also the limited goal for this study, with focus on the exploration of a really huge and complex data set. True biomarker identification, however, needs thorough validation and verification in separate patient sets.

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