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  • 1. Bengtsson, Anders A.
    et al.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Wuttge, Dirk M.
    Sturfelt, Gunnar
    Theander, Elke
    Donten, Magdalena
    Moritz, Thomas
    Sennbro, Carl-Johan
    Torell, Frida
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Lood, Christian
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Rännar, Stefan
    Lundstedt, Torbjörn
    Metabolic Profiling of Systemic Lupus Erythematosus and Comparison with Primary Sjögren’s Syndrome and Systemic Sclerosis2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 7, article id e0159384Article in journal (Refereed)
    Abstract [en]

    Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease which can affect most organ systems including skin, joints and the kidney. Clinically, SLE is a heterogeneous disease and shares features of several other rheumatic diseases, in particular primary Sjögrens syndrome (pSS) and systemic sclerosis (SSc), why it is difficult to diag- nose The pathogenesis of SLE is not completely understood, partly due to the heterogeneity of the disease. This study demonstrates that metabolomics can be used as a tool for improved diagnosis of SLE compared to other similar autoimmune diseases. We observed differences in metabolic profiles with a classification specificity above 67% in the comparison of SLE with pSS, SSc and a matched group of healthy individuals. Selected metabolites were also significantly different between studied diseases. Biochemical pathway analysis was conducted to gain understanding of underlying pathways involved in the SLE pathogenesis. We found an increased oxidative activity in SLE, supported by increased xanthine oxidase activity and an increased turnover in the urea cycle. The most discriminatory metabolite observed was tryptophan, with decreased levels in SLE patients compared to control groups. Changes of tryptophan levels were related to changes in the activity of the aromatic amino acid decarboxylase (AADC) and/or to activation of the kynurenine pathway. 

  • 2. Checa, A.
    et al.
    Idborg, H.
    Zandian, A.
    Sar, D. Garcia
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Svenungsson, E.
    Jakobsson, P-J
    Nilsson, P.
    Gunnarsson, I.
    Wheelock, C. E.
    Dysregulations in circulating sphingolipids associate with disease activity indices in female patients with systemic lupus erythematosus: a cross-sectional study2017In: Lupus, ISSN 0961-2033, E-ISSN 1477-0962, Vol. 26, no 10, p. 1023-1033Article in journal (Refereed)
    Abstract [en]

    Objective The objective of this study was to investigate the association of clinical and renal disease activity with circulating sphingolipids in patients with systemic lupus erythematosus.

    Methods We used liquid chromatography tandem mass spectrometry to measure the levels of 27 sphingolipids in plasma from 107 female systemic lupus erythematosus patients and 23 controls selected using a design of experiment approach. We investigated the associations between sphingolipids and two disease activity indices, the Systemic Lupus Activity Measurement and the Systemic Lupus Erythematosus Disease Activity Index. Damage was scored according to the Systemic Lupus International Collaborating Clinics damage index. Renal activity was evaluated with the British Island Lupus Activity Group index. The effects of immunosuppressive treatment on sphingolipid levels were evaluated before and after treatment in 22 female systemic lupus erythematosus patients with active disease.

    Results Circulating sphingolipids from the ceramide and hexosylceramide families were increased, and sphingoid bases were decreased, in systemic lupus erythematosus patients compared to controls. The ratio of C-16:0-ceramide to sphingosine-1-phosphate was the best discriminator between patients and controls, with an area under the receiver-operating curve of 0.77. The C-16:0-ceramide to sphingosine-1-phosphate ratio was associated with ongoing disease activity according to the Systemic Lupus Activity Measurement and the Systemic Lupus Erythematosus Disease Activity Index, but not with accumulated damage according to the Systemic Lupus International Collaborating Clinics Damage Index. Levels of C-16:0- and C-24:1-hexosylceramides were able to discriminate patients with current versus inactive/no renal involvement. All dysregulated sphingolipids were normalized after immunosuppressive treatment.

    Conclusion We provide evidence that sphingolipids are dysregulated in systemic lupus erythematosus and associated with disease activity. This study demonstrates the utility of simultaneously targeting multiple components of a pathway to establish disease associations.

  • 3.
    Karimpour, Masoumeh
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Wu, Junfang
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Gouveia-Figueira, Sandra
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Pharmacology.
    Pinto, Rui
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Bioinformatics Infrastructure for Life Sciences, Sweden.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Zivkovic, Angela M.
    Nording, Malin L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal2016In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 908, p. 121-131Article in journal (Refereed)
    Abstract [en]

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.

  • 4. Orikiiriza, Judy
    et al.
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Lindquist, Elisabeth
    Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Bonde, Mari
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Magambo, Jimmy
    Muhinda, Charles
    Bergström, Sven
    Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR).
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Normark, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Infectious Diseases. Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria2017In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, no 4, article id 41Article in journal (Refereed)
    Abstract [en]

    Introduction: Several studies have observed serum lipid changes during malaria infection in humans. All of them were focused at analysis of lipoproteins, not specific lipid molecules. The aim of our study was to identify novel patterns of lipid species in malaria infected patients using lipidomics profiling, to enhance diagnosis of malaria and to evaluate biochemical pathways activated during parasite infection.

    Methods: Using a multivariate characterization approach, 60 samples were representatively selected, 20 from each category (mild, severe and controls) of the 690 study participants between age of 0.5–6 years. Lipids from patient’s plasma were extracted with chloroform/methanol mixture and subjected to lipid profiling with application of the LCMS-QTOF method.

    Results: We observed a structured plasma lipid response among the malaria-infected patients as compared to healthy controls, demonstrated by higher levels of a majority of plasma lipids with the exception of even-chain length lysophosphatidylcholines and triglycerides with lower mass and higher saturation of the fatty acid chains. An inverse lipid profile relationship was observed when plasma lipids were correlated to parasitaemia.

    Conclusions: This study demonstrates how mapping the full physiological lipid response in plasma from malaria-infected individuals can be used to understand biochemical processes during infection. It also gives insights to how the levels of these molecules relate to acute immune responses.

  • 5.
    Skotare, Tomas
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Sjögren, Rickard
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Nilsson, David
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Sartorius Stedim Data Analytics, 907 36 Umeå, Sweden.
    Visualization of descriptive multiblock analysis2018In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128XArticle in journal (Refereed)
    Abstract [en]

    Abstract Understanding and making the most of complex data collected from multiple sources is a challenging task. Data integration is the procedure of describing the main features in multiple data blocks, and several methods for multiblock analysis have been previously developed, including OnPLS and JIVE. One of the main challenges is how to visualize and interpret the results of multiblock analyses because of the increased model complexity and sheer size of data. In this paper, we present novel visualization tools that simplify interpretation and overview of multiblock analysis. We introduce a correlation matrix plot that provides an overview of the relationships between blocks found by multiblock models. We also present a multiblock scatter plot, a metadata correlation plot, and a variation distribution plot, that simplify the interpretation of multiblock models. We demonstrate our visualizations on an industrial case study in vibration spectroscopy (NIR, UV, and Raman datasets) as well as a multiomics integration study (transcript, metabolite, and protein datasets). We conclude that our visualizations provide useful tools to harness the complexity of multiblock analysis and enable better understanding of the investigated system.

  • 6.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Gjesdal, Clara Gram
    Jonsson, Grete
    Norheim, Katrine Braekke
    Lundstedt, Torbjorn
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Omdal, Roald
    Metabolomics study of fatigue in patients with rheumatoid arthritis na < ve to biological treatment2016In: Rheumatology International, ISSN 0172-8172, E-ISSN 1437-160X, Vol. 36, no 5, p. 703-711Article in journal (Refereed)
    Abstract [en]

    Fatigue occurs in all chronic inflammatory diseases, in cancer, and in some neurological conditions. Patients often regard fatigue as one of their most debilitating problems, but currently there is no established treatment and the mechanisms that lead to and regulate fatigue are incompletely understood. Our objective was to more completely understand the physiology of this phenomenon. Twenty-four patients with rheumatoid arthritis (RA) na < ve to treatment with biological drugs were enrolled for the study. Fatigue was measured with a fatigue visual analogue scale (fVAS). Ethylenediaminetetraacetic acid (EDTA) plasma samples were subjected to gas chromatography-time-of-flight mass spectrometry (GC/MS-TOF)-based metabolite profiling. Obtained metabolite data were evaluated by multivariate data analysis with orthogonal projections to latent structures (OPLS) method to pinpoint metabolic changes related to fatigue severity. A significant multivariate OPLS model was obtained between the fVAS scores and the measured metabolic levels. Increasing fatigue scores were associated with a metabolic pattern characterized by down-regulation of metabolites from the urea cycle, fatty acids, tocopherols, aromatic amino acids, and hypoxanthine. Uric acid levels were increased. Apart from fatigue, we found no other disease-related variables that might be responsible for these changes. Our MS-based metabolomic approach demonstrated strong associations between fatigue and several biochemical patterns related to oxidative stress.

  • 7.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Gouveia-Figueira, Sandra
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Orikiiriza, Judy
    Lindquist, Elisabeth
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Bonde, Mari
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Magambo, Jimmy
    Muhinda, Charles
    Bergström, Sven
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR).
    Normark, Johan
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Infectious Diseases.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children2017In: Malaria Journal, ISSN 1475-2875, E-ISSN 1475-2875, Vol. 16, article id 358Article in journal (Refereed)
    Abstract [en]

    Background: Oxylipins and endocannabinoids are low molecular weight bioactive lipids that are crucial for initiation and resolution of inflammation during microbial infections. Metabolic complications in malaria are recognized contributors to severe and fatal malaria, but the impact of malaria infection on the production of small lipid derived signalling molecules is unknown. Knowledge of immunoregulatory patterns of these molecules in malaria is of great value for better understanding of the disease and improvement of treatment regimes, since the action of these classes of molecules is directly connected to the inflammatory response of the organism.

    Methods: Detection of oxylipins and endocannabinoids from plasma samples from forty children with uncomplicated and severe malaria as well as twenty controls was done after solid phase extraction followed by chromatography mass spectrometry analysis. The stable isotope dilution method was used for compound quantification. Data analysis was done with multivariate (principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA (R)) and univariate approaches (receiver operating characteristic (ROC) curves, t tests, correlation analysis).

    Results: Forty different oxylipin and thirteen endocannabinoid metabolites were detected in the studied samples, with one oxylipin (thromboxane B2, TXB2) in significantly lower levels and four endocannabinoids (OEA, PEA, DEA and EPEA) at significantly higher levels in infected individuals as compared to controls according to t test analysis with Bonferroni correction. Three oxylipins (13-HODE, 9-HODE and 13-oxo-ODE) were higher in severe compared to uncomplicated malaria cases according to the results from multivariate analysis. Observed changes in oxylipin levels can be connected to activation of cytochrome P450 (CYP) and 5-lipoxygenase (5-LOX) metabolic pathways in malaria infected individuals compared to controls, and related to increased levels of all linoleic acid oxylipins in severe patients compared to uncomplicated ones. The endocannabinoids were extremely responsive to malaria infection with majority of this class of molecules found at higher levels in infected individuals compared to controls.

    Conclusions: It was possible to detect oxylipin and endocannabinoid molecules that can be potential biomarkers for differentiation between malaria infected individuals and controls and between different classes of malaria. Metabolic pathways that could be targeted towards an adjunctive therapy in the treatment of malaria were also pinpointed.

  • 8.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Johansson, Erik
    Stenlund, Hans
    Rantapää-Dahlqvist, Solbritt
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Rheumatology.
    Bergström, Sven
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Normark, Johan
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Sartorius Stedim Data Analytics, Umeå, Sweden.
    Quantification of run order effect on chromatography: mass spectrometry profiling data2018In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1568, p. 229-234Article in journal (Refereed)
    Abstract [en]

    Chromatographic systems coupled with mass spectrometry detection are widely used in biological studies investigating how levels of biomolecules respond to different internal and external stimuli. Such changes are normally expected to be of low magnitude and therefore all experimental factors that can influence the analysis need to be understood and minimized. Run order effect is commonly observed and constitutes a major challenge in chromatography-mass spectrometry based profiling studies that needs to be addressed before the biological evaluation of measured data is made. So far there is no established consensus, metric or method that quickly estimates the size of this effect. In this paper we demonstrate how orthogonal projections to latent structures (OPLS®) can be used for objective quantification of the run order effect in profiling studies. The quantification metric is expressed as the amount of variation in the experimental data that is correlated to the run order. One of the primary advantages with this approach is that it provides a fast way of quantifying run-order effect for all detected features, not only internal standards. Results obtained from quantification of run order effect as provided by the OPLS can be used in the evaluation of data normalization, support the optimization of analytical protocols and identification of compounds highly influenced by instrumental drift. The application of OPLS for quantification of run order is demonstrated on experimental data from plasma profiling performed on three analytical platforms: GCMS metabolomics, LCMS metabolomics and LCMS lipidomics.

  • 9.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Johansson, Erik
    Sartorius Stedim Data Analytics AB, Umeå, Sweden.
    Torell, Frida
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Idborg, Helena
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Gunnarsson, Iva
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Svenungsson, Elisabet
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Jakobsson, Per-Johan
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Sartorius Stedim Data Analytics AB, Umeå, Sweden.
    Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics2017In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, no 10, article id 114Article in journal (Refereed)
    Abstract [en]

    Introduction Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput 'omics' technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

    Objectives We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

    Methods Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC-TOFMS). For each batch OPLS-DA (R) was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

    Results A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

    Conclusion Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

  • 10.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Karimpour, Masoumeh
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Gouveia-Figueira, Sandra
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Wu, Junfang
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Unosson, Jon
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Bosson, Jenny A.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Blomberg, Anders
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Pourazar, Jamshid
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Sandström, Thomas
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Behndig, Annelie F.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Nording, Malin L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study2016In: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 408, no 17, p. 4751-4764Article in journal (Refereed)
    Abstract [en]

    Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure.

  • 11.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Nowik, Witold
    Moritz, Thomas
    Mass spectrometric identification of new minor indigoids in shellfish purple dye from Hexaplex trunculus2012In: Dyes and pigments, ISSN 0143-7208, E-ISSN 1873-3743, Vol. 94, no 2, p. 363-369Article in journal (Refereed)
    Abstract [en]

    Analysis of natural dyes in historical objects is important for both conservation purposes and to determine the origin and culture that produced it. Identification of a particular dye is usually made based on the presence of its main components, while consideration of minor components is important for differentiating between dyes originating from closely related species. Tyrian purple is one of the oldest dyes known to man and derives from different species of marine molluscs. In all of these species, indigotin, indirubin and their brominated analogues are the main colouring compounds. Here, we describe the identification of minor indigoids found in extracts of the pigment obtained from one of the Tyrian purple species, Hexaplex trunculus. Identification of these compounds was made based on isotopic patterns and accurate mass measurements of protonated molecular ions and their high collision energy fragments obtained in LC-MS/MS experiments. The unknown compounds appeared to be analogues of indirubin and its mono- and dibrominated derivatives with one CO group in the indirubin backbone substituted by a CNH group. Identification of these compounds facilitates the detection of dyestuffs from H. trunculus in historical objects and increases our knowledge about the dye biosynthesis and technology of Tyrian purple production. (C) 2012 Elsevier Ltd. All rights reserved.

  • 12.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Orikiiriza, Judy
    Karlsson, Elisabeth
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Nelson, Maria
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Bonde, Mari
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Kyamanwa, Patrick
    Karenzi, Ben
    Bergström, Sven
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS).
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Normark, Johan
    Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Infectious Diseases. nfectious Diseases Institute, School of Medicine and Health Sciences, Makerere University, Uganda.
    Metabolic signature profiling as a diagnostic and prognostic tool in paediatric Plasmodium falciparum malaria2015In: Open Forum Infectious Diseases, ISSN 2328-8957, Vol. 2, no 2Article in journal (Refereed)
    Abstract [en]

    Background: Accuracy in malaria diagnosis and staging is vital in order to reduce mortality and post infectious sequelae. Herein we present a metabolomics approach to diagnostic staging of malaria infection, specifically Plasmodium falciparum infection in children. Methods: A group of 421 patients between six months and six years of age with mild and severe states of malaria with age-matched controls were included in the study, 107, 192 and 122 individuals respectively. A multivariate design was used as basis for representative selection of twenty patients in each category. Patient plasma was subjected to Gas Chromatography-Mass Spectrometry analysis and a full metabolite profile was produced from each patient. In addition, a proof-of-concept model was tested in a Plasmodium berghei in-vivo model where metabolic profiles were discernible over time of infection. Results: A two-component principal component analysis (PCA) revealed that the patients could be separated into disease categories according to metabolite profiles, independently of any clinical information. Furthermore, two sub-groups could be identified in the mild malaria cohort who we believe represent patients with divergent prognoses. Conclusion: Metabolite signature profiling could be used both for decision support in disease staging and prognostication.

  • 13.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Vikström, Ludvig
    Hector, Gustaf
    Johansson, Erik
    Vikström, Conny
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Generalized Subset Designs in Analytical Chemistry2017In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 89, no 12, p. 6491-6497Article in journal (Refereed)
    Abstract [en]

    Design of experiments (DOE) is an established methodology in research, development, manufacturing, and production for screening, optimization, and robustness testing. Two-level fractional factorial designs remain the preferred approach due to high information content while keeping the number of experiments low. These types of designs, however, have never been extended to a generalized multilevel reduced design type that would be capable to include both qualitative and quantitative factors. In this Article we describe a novel generalized fractional factorial design. In addition, it also provides complementary and balanced subdesigns analogous to a fold-over in two-level reduced factorial designs. We demonstrate how this design type can be applied with good results in three different applications in analytical chemistry including (a) multivariate calibration using microwave resonance spectroscopy for the determination of water in tablets, (b) stability study in drug product development, and (c) representative sample selection in clinical studies. This demonstrates the potential of generalized fractional factorial designs to be applied in many other areas of analytical chemistry where representative, balanced, and complementary subsets are required, especially when a combination of quantitative and qualitative factors at multiple levels exists.

  • 14.
    Surowiec, Izabella
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Ärlestig, Lisbeth
    Rantapää-Dahlqvist, Solbritt
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Metabolite and Lipid Profiling of Biobank Plasma Samples Collected Prior to Onset of Rheumatoid Arthritis2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 10, article id e0164196Article in journal (Refereed)
    Abstract [en]

    Objective: The early diagnosis of rheumatoid arthritis (RA) is desirable to install treatment to prevent disease progression and joint destruction. Autoantibodies and immunological markers pre-date the onset of symptoms by years albeit not all patients will present these factors, even at disease onset. Additional biomarkers would be of high value to improve early diagnosis and understanding of the process, leading to disease development. Methods: Plasma samples donated before the onset of RA were identified in the Biobank of Northern Sweden, a collection within national health survey programs. Thirty samples from pre-symptomatic individuals and nineteen from controls were subjected to liquid chromatography-mass spectrometry (LCMS) metabolite and lipid profiling. Lipid and metabolite profiles discriminating samples from pre-symptomatic individuals from controls were identified after univariate and multivariate OPLS-DA based analyses. Results: The OPLS-DA models including pre-symptomatic individuals and controls identified profiles differentiating between the groups that was characterized by lower levels of acyl-carnitines and fatty acids, with higher levels of lysophospatidylcholines (LPCs) and metabolites from tryptophan metabolism in pre-symptomatic individuals compared with controls. Lipid profiling showed that the majority of phospholipids and sphingomyelins were at higher levels in pre-symptomatic individuals in comparison with controls. Conclusions: Our LCMS based approach demonstrated that there are changes in small molecule and lipid profiles detectable in plasma samples collected from the pre-symptomatic individuals who subsequently developed RA, which point to an up-regulation of levels of lysophospatidylcholines, and of tryptophan metabolism, perturbation of fatty acid beta-oxidation and increased oxidative stress in pre-symptomatic individuals' years before onset of symptoms.

  • 15.
    Wibom, Carl
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Surowiec, Izabella
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Mörén, Lina
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Bergström, Per
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Johansson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Bergenheim, A Tommy
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Metabolomic patterns in glioblastoma and changes during radiotherapy: a clinical microdialysis study2010In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 9, no 6, p. 2909-2919Article in journal (Refereed)
    Abstract [en]

    We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.

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