Adam Ząbek

Serum and urine metabolomic fingerprinting in diagnostics of inflammatory bowel diseases.

AIM To evaluate the utility of serum and urine metabolomic analysis in diagnosing and monitoring of inflammatory bowel diseases (IBD). METHODS Serum and urine samples were collected from 24 patients with ulcerative colitis (UC), 19 patients with the Crohns disease (CD) and 17 healthy controls. The activity of UC was assessed with the Simple Clinical Colitis Activity Index, while the activity of CD was determined using the Harvey-Bradshaw Index. The analysis of serum and urine samples was performed using proton nuclear magnetic resonance (NMR) spectroscopy. All spectra were exported to Matlab for preprocessing which resulted in two data matrixes for serum and urine. Prior to the chemometric analysis, both data sets were unit variance scaled. The differences in metabolite fingerprints were assessed using partial least-squares-discriminant analysis (PLS-DA). Receiver operating characteristic curves and area under curves were used to evaluate the quality and prediction performance of the obtained PLS-DA models. Metabolites responsible for separation in models were tested using STATISTICA 10 with the Mann-Whitney-Wilcoxon test and the Students t test (α = 0.05). RESULTS The comparison between the group of patients with active IBD and the group with IBD in remission provided good PLS-DA models (P value 0.002 for serum and 0.003 for urine). The metabolites that allowed to distinguish these groups were: N-acetylated compounds and phenylalanine (up-regulated in serum), low-density lipoproteins and very low-density lipoproteins (decreased in serum) as well as glycine (increased in urine) and acetoacetate (decreased in urine). The significant differences in metabolomic profiles were also found between the group of patients with active IBD and healthy control subjects providing the PLS-DA models with a very good separation (P value < 0.001 for serum and 0.003 for urine). The metabolites that were found to be the strongest biomarkers included in this case: leucine, isoleucine, 3-hydroxybutyric acid, N-acetylated compounds, acetoacetate, glycine, phenylalanine and lactate (increased in serum), creatine, dimethyl sulfone, histidine, choline and its derivatives (decreased in serum), as well as citrate, hippurate, trigonelline, taurine, succinate and 2-hydroxyisobutyrate (decreased in urine). No clear separation in PLS-DA models was found between CD and UC patients based on the analysis of serum and urine samples, although one metabolite (formate) in univariate statistical analysis was significantly lower in serum of patients with active CD, and two metabolites (alanine and N-acetylated compounds) were significantly higher in serum of patients with CD when comparing jointly patients in the remission and active phase of the diseases. Contrary to the results obtained from the serum samples, the analysis of urine samples allowed to distinguish patients with IBD in remission from healthy control subjects. The metabolites of importance included in this case up-regulated acetoacetate and down-regulated citrate, hippurate, taurine, succinate, glycine, alanine and formate. CONCLUSION NMR-based metabolomic fingerprinting of serum and urine has the potential to be a useful tool in distinguishing patients with active IBD from those in remission.

Metabolic profiles of exudates from chronic leg ulcerations.

&NA; Chronic leg ulceration is a disease usually associated with other comorbidities, and significantly reduces patient quality of life. Infected leg ulcers can lead to limb‐threatening sequelae or mortality. Leg ulcerations are colonized by a number of microbes that are able to cause life‐threating infections in susceptible patients. Wound exudate is a body fluid that collects metabolites from patient eukaryotic cells and from prokaryotic bacterial communities inhabiting the wound. This study aimed at identification of metabolites in exudates collected from chronic leg ulcers, and correlation of this metabolome with patient comorbidities and microbiological status of the wound. By means of NMR spectroscopy we detected 42 metabolites of microbial or patient origin. The metabolites that were in abundance in exudates analyzed were lactate, lysine, and leucine. Metabolites were associated with the presence of neutrophils in wounds and destruction of high quantities of microbes, but also with hypoxia typical for venous insufficiency. The combination of nuclear magnetic resonance spectroscopy technique and partial least squares discriminant analysis allowed us to further discriminate groups of metabolites with regards to potential clinical meaning. For example, to discriminate between S.aureus versus all other isolated microbial species, or between patients suffering from type I or II diabetes versus patients without diabetes. Therefore, wound exudate seems to be highly applicable material for discriminant analysis performed with the use of NMR technique to provide for rapid metabolomics of chronic wound status. HighlightsNMR technique is highly applicable for evaluation of processes taking place within a wound.The wound exudate is a very useful material for these analyses.Wound exudate metabolites might be used as biomarkers of wound status.

Application of nuclear magnetic resonance spectroscopy for the detection of metabolic disorders in patients with moderate kidney insufficiency

Graphical abstract Figure. No caption available. HighlightsUsing 1H NMR spectroscopy and multivariate analysis we found significant differences in metabolite profiles of patients and healthy controls.Our study provided a valuable insight into interactions between renal function and metabolite profile of human serum.MetPA analysis demonstrated significant intergroup differences in 5 potential target pathways and 14 metabolites. ABSTRACT Chronic kidney disease (CKD) is one of the major problems of modern medicine and a huge socioeconomic burden. Thorough knowledge of metabolic alterations associated with this condition is vital to prevent its progression. However, still little is known about metabolic disorders associated with CKD. In this study, we used 1H NMR spectroscopy and multivariate analysis to identify alterations in serum metabolites of patients with various stages of CKD. 1H NMR spectroscopy followed by multivariate analysis showed that CKD patients differed from the controls in terms of 15 endogenous metabolites, and MetPA analysis demonstrated significant intergroup differences in 5 potential target pathways and 14 metabolites. Owing a good performance of discriminant models, these findings suggest that CKD patients and healthy controls differ in terms of their metabolic fingerprints. In turn, the results of MetPA analysis imply that CKD and its progression exert an effect on selected metabolic pathways. This study provided a better insight into metabolic alterations associated with CKD, and identified some target pathways that can be potentially modified to slow down the progression of this serious and debilitating disease.

Biodiversity in targeted metabolomics analysis of filamentous fungal pathogens by 1H NMR-based studies

The taxonomical classification among fungi kingdom in the last decades was evolved. In this work the targeted metabolomics study based on 1H NMR spectroscopy combined with chemometrics tools was reported to be useful for differentiation of three model of fungal strains, which represent various genus of Ascomycota (Aspergillus pallidofulvus, Fusarium oxysporum, Geotrichum candidum) were selected in order to perform metabolomics studies. Each tested species, revealed specific metabolic profile of primary endo-metabolites. The species of A. pallidofulvus is represented by the highest concentration of glycerol, glucitol and Unk5. While, F. oxysporum species is characterised by increased level of propylene glycol, ethanol, 4-aminobutyrate, succinate, xylose, Unk1 and Unk4. In G. candidum, 3-methyl-2-oxovalerate, glutamate, pyruvate, glutamine and citrate were elevated. Additionally, a detailed analysis of metabolic changes among A. pallidofulvus, F. oxysporum and G. candidum showed that A. pallidofulvus seems to be the most pathogenic fungi. The obtained results demonstrated that targeted metabolomics analysis could be utilized in the future as a supporting taxonomical tool for currently methods.Graphical Abstract

1H NMR-based metabolic profiling for evaluating poppy seed rancidity and brewing.

Abstract Poppy seeds are widely used in household and commercial confectionery. The aim of this study was to demonstrate the application of metabolic profiling for industrial monitoring of the molecular changes which occur during minced poppy seed rancidity and brewing processes performed on raw seeds. Both forms of poppy seeds were obtained from a confectionery company. Proton nuclear magnetic resonance (1H NMR) was applied as the analytical method of choice together with multivariate statistical data analysis. Metabolic fingerprinting was applied as a bioprocess control tool to monitor rancidity with the trajectory of change and brewing progressions. Low molecular weight compounds were found to be statistically significant biomarkers of these bioprocesses. Changes in concentrations of chemical compounds were explained relative to the biochemical processes and external conditions. The obtained results provide valuable and comprehensive information to gain a better understanding of the biology of rancidity and brewing processes, while demonstrating the potential for applying NMR spectroscopy combined with multivariate data analysis tools for quality control in food industries involved in the processing of oilseeds. This precious and versatile information gives a better understanding of the biology of these processes.

Serum NMR metabolomics to differentiate haematologic malignancies

Haematological malignancies are a frequently diagnosed group of neoplasms and a significant cause of cancer deaths. The successful treatment of these diseases relies on early and accurate detection. Specific small molecular compounds released by malignant cells and the simultaneous response by the organism towards the pathological state may serve as diagnostic/prognostic biomarkers or as a tool with relevance for cancer therapy management. To identify the most important metabolites required for differentiation, an 1H NMR metabolomics approach was applied to selected haematological malignancies. This study utilized 116 methanol serum extract samples from AML (n= 38), nHL (n= 26), CLL (n= 21) and HC (n= 31). Multivariate and univariate data analyses were performed to identify the most abundant changes among the studied groups. Complex and detailed VIP-PLS-DA models were calculated to highlight possible changes in terms of biochemical pathways and discrimination ability. Chemometric model prediction properties were validated by receiver operating characteristic (ROC) curves and statistical analysis. Two sets of eight important metabolites in HC/AML/CLL/nHL comparisons and five in AML/CLL/nHL comparisons were selected to form complex models to represent the most significant changes that occurred.

Metabolomics analysis of fungal biofilm development and of arachidonic acid-based quorum sensing mechanism

The infections caused by filamentous fungi are becoming worldwide problem of healthcare systems due to increasing drug‐resistance of this microorganism and increasing number of immunocompromised nosocomial patients. These infections are related with Aspergillus ability to form sessile communities referred to as the biofilms. The small compounds known as quorum sensing (QS) molecules allow this microorganism to coordinate all processes taking place during biofilm formation and maturation. In the study presented, the HRMAS 1H NMR metabolomic approach was applied to define composition of extra and intracellular metabolites produced by biofilmic and planktonic (aka free‐swimming) cultures of this microorganism and to evaluate impact of quorum sensing molecule, arachidonic acid (AA) on biofilm formation. The Scanning Electron Microscopy was used to confirm Aspergillus ability to form biofilm in vitro, while multivariate and univariate data analysis was applied to analyze data obtained. The Aspergillus strain was able to form strong biofilm structures in vitro. The statistical analysis revealed significant changes of metabolite production depending on Aspergillus culture type (biofilm vs. plankton), time and presence of QS molecules. The data obtained, if developed, might be used in future NMR diagnostics as markers of Aspergillus biofilm‐related infections and lead to shorten time between pathogen identification and introduction of treatment.

Metabolomics provides new information on the changes occurring in thyroid tumours

Metabolomics is a part of systems biology dealing with the determination of qualitative and quantitative profile of low molecular weight compounds (metabolites) present in body fluids and tissues of living organisms. Metabolic composition is strongly dependent on the state of homeostasis and any deregulation should affect it. For this reason, there is now increased interest in metabolomics as a potential tool to support cancer research. At the same time the analysis of metabolic pathways involved in the process of carcinogenesis provides the possibility of a more complete understanding of the mechanisms that are critical for tumour biology. In this study, 1H NMR measurements were performed for thyroid tumour tissue and healthy tissue homogenates and analyzed by chemometric manner. Multivariate analysis of the data using the PCA, PLS-DA and OPLS-DA methods allowed a precise separation from normal thyroid tissue of all tumours originating in both benign and malignant lesions. In addition, classification of nodular goiter, follicular adenoma and malignant tumours was possible with comparable efficacy.

The evaluation of metabolomics studies in the diagnostic of viral infections

The numerous of the various viral infections is a serious problem for mankind all over the world. Despite a number of various diagnostic tests there is still strong need for rapid detection methods of many infectious diseases. The novel approach for diagnostic methods prove that metabolomics, which is the interdisciplinary science consisting of the combination of analytical methods (nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS)) and chemometrics tools allows to understand the mechanisms of disease at the level of biochemical pathways.