Dansylation isotope labeling liquid chromatography mass spectrometry for parallel profiling of human urinary and fecal submetabolomes

Human urine and feces can be non-invasively collected for metabolomics-based disease biomarker discovery research. Because urinary and fecal metabolomes are thought to be different, analysis of both biospecimens may generate a more comprehensive metabolomic profile that can be better related to the health state of an individual. Herein we describe a method of using differential chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) for parallel metabolomic profiling of urine and feces. Dansylation labeling was used to quantify the amine/phenol submetabolome changes among different samples based on ¹²C-labeling of individual samples and ¹³C-labeling of a pooled urine or pooled feces and subsequent analysis of the ¹³C-/¹²C-labeled mixture by LC-MS. The pooled urine and pooled feces are further differentially labeled, mixed and then analyzed by LC-MS in order to relate the metabolite concentrations of the common metabolites found in both biospecimens. This method offers a means of direct comparison of urinary and fecal submetabolomes. We evaluated the analytical performance and demonstrated the utility of this method in the analysis of urine and feces collected daily from three healthy individuals for 7 days. On average, 2534 ± 113 (n = 126) peak pairs or metabolites could be detected from a urine sample, while 2507 ± 77 (n = 63) peak pairs were detected from a fecal sample. In total, 5372 unique peak pairs were detected from all the samples combined; 3089 and 3012 pairs were found in urine and feces, respectively. These results reveal that the urine and fecal metabolomes are very different, thereby justifying the consideration of using both biospecimens to increase the probability of finding specific biomarkers of diseases. Furthermore, the CIL LC-MS method described can be used to perform parallel quantitative analysis of urine and feces, resulting in more complete coverage of the human metabolome.     

Development of versatile isotopic labeling reagents for profiling the amine submetabolome by liquid chromatography–mass spectrometry

Metabolomic profiling involves relative quantification of metabolites in comparative samples and identification of the significant metabolites that differentiate different groups (e.g., diseased vs. controls). Chemical isotope labeling (CIL) liquid chromatography–mass spectrometry (LC–MS) is an enabling technique that can provide improved metabolome coverage and metabolite quantification. However, chemical identification of labeled metabolites can still be a challenge. In this work, a new set of isotopic labeling reagents offering versatile properties to enhance both detection and identification are described. They were prepared by a glycine molecule (or its isotopic counterpart) and an aromatic acid with varying structures through a simple three-step synthesis route. In addition to relatively low costs of synthesizing the reagents, this reaction route allows adjusting reagent property in accordance with the desired application objective. To date, two isotopic reagents, 4-dimethylaminobenzoylamido acetic acid N-hydroxylsuccinimide ester (DBAA-NHS) and 4-methoxybenzoylamido acetic acid N-hydroxylsuccinimide ester (MBAA-NHS), for labeling the amine-containing metabolites (i.e., amine submetabolome) have been synthesized. The labeling conditions and the related LC–MS method have been optimized. We demonstrate that DBAA labeling can increase the metabolite detectability because of the presence of an electrospray ionization (ESI)-active dimethylaminobenzoyl group. On the other hand, MBAA labeled metabolites can be fragmented in MS/MS and pseudo MS³ experiments to provide structural information on metabolites of interest. Thus, these reagents can be tailored to quantitative profiling of the amine submetabolome as well as metabolite identification in metabolomics applications.     

Quantification of steroids and endocrine disrupting chemicals in rat ovaries by LC-MS/MS for reproductive toxicology assessment

Reproductive function is controlled by a finely tuned balance of androgens and estrogens. Environmental toxicants, notably endocrine disrupting chemicals (EDCs), appear to be involved in the disruption of hormonal balance in several studies. To further describe the effects of selected EDCs on steroid secretion in female rats, we aim to simultaneously investigate the EDC concentration and the sex hormone balance in the ovaries. Therefore, an effective method has been developed for the quantification of the sex steroid hormones (testosterone, androstenedione, estradiol, and estrone) and four endocrine disrupting chemicals (bisphenol A, atrazine, and the active metabolites of methoxychlor and vinclozolin) in rat ovaries. The sample preparation procedure is based on the so-called "quick, easy, cheap, effective, rugged, and safe" approach, and an analytical method was developed to quantify these compounds with low detection limits by liquid chromatography coupled with a tandem mass spectrometer. This analytical method, applied to rat ovary samples following subacute EDC exposure, revealed some new findings for toxicological evaluation. In particular, we showed that EDCs with the same described in vitro mechanisms of action have different effects on the gonadal steroid balance. These results highlight the need to develop an integrative evaluation with the simultaneous measurement of EDCs and numerous steroids for good risk assessment.     

Monitoring of environmental phenolic endocrine disrupting compounds in treatment effluents and river waters, Korea

The last two decades have witnessed growing scientific and public concerns over endocrine disrupting compounds (EDCs) that have the potential to alter the normal structure or functions of the endocrine system in wildlife and humans. In this study, the phenolic EDCs such as alkylphenol, chlorinated phenol and bisphenol A were considered. They are commonly found in wastewater discharges and in sewage treatment plant. In order to monitor the levels and seasonal variations of phenolic EDCs in various aquatic environments, a total of 15 water samples from the discharged effluent from sewage and wastewater treatment plants and river water were collected for 3 years. Ten environmental phenolic EDCs were determined by GC-MS and laser-induced fluorescence (LIF). GC-MS analysis revealed that most abundant phenolic EDCs were 4-n-heptylphenol, followed by nonlyphenol and bisphenol A during 2002-2003, while 4-t-butylphenol and 4-t-octylphenol were newly detected in aquatic environments in 2004.The category of phenolic EDCs showed similar fluorescence spectra and nearly equal fluorescence decay time. This makes it hard to distinguish each phenolic EDC from the EDCs mixture by LIF. Therefore, the results obtained from LIF analysis were expressed in terms of the fluorescence intensity of the total phenolic EDCs rather than that of the individual EDC. However, LIF monitoring and GC-MS analysis showed consistent result in that the river water samples had lower phenolic EDCs concentration compared to the effluent sample. This revealed a lower fluorescence intensity and the phenolic EDCs concentration in summer was lower than that in winter. For the validation of LIF monitoring for the phenolic EDCs, the correlation between EDCs concentration acquired from GC-MS and fluorescence intensity from LIF was obtained (R = 0.7379). This study supports the feasibility of the application of LIF into EDCs monitoring in aquatic systems.     

Simultaneous analysis of 28 urinary VOC metabolites using ultra high performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (UPLC-ESI/MSMS)

Volatile organic compounds (VOCs) are ubiquitous in the environment, originating from many different natural and anthropogenic sources, including tobacco smoke. Long-term exposure to certain VOCs may increase the risk for cancer, birth defects, and neurocognitive impairment. Therefore, VOC exposure is an area of significant public health concern. Urinary VOC metabolites are useful biomarkers for assessing VOC exposure because of non-invasiveness of sampling and longer physiological half-lives of urinary metabolites compared with VOCs in blood and breath. We developed a method using reversed-phase ultra high performance liquid chromatography (UPLC) coupled with electrospray ionization tandem mass spectrometry (ESI/MSMS) to simultaneously quantify 28 urinary VOC metabolites as biomarkers of exposure. We describe a method that monitors metabolites of acrolein, acrylamide, acrylonitrile, benzene, 1-bromopropane, 1,3-butadiene, carbon-disulfide, crotonaldehyde, cyanide, N,N-dimethylformamide, ethylbenzene, ethylene oxide, propylene oxide, styrene, tetrachloroethylene, toluene, trichloroethylene, vinyl chloride and xylene. The method is accurate (mean accuracy for spiked matrix ranged from 84 to104%), sensitive (limit of detection ranged from 0.5 to 20 ng mL⁻¹) and precise (the relative standard deviations ranged from 2.5 to 11%). We applied this method to urine samples collected from 1203 non-smokers and 347 smokers and demonstrated that smokers have significantly elevated levels of tobacco-related biomarkers compared to non-smokers. We found significant (p < 0.0001) correlations between serum cotinine and most of the tobacco-related biomarkers measured. These findings confirm that this method can effectively quantify urinary VOC metabolites in a population exposed to volatile organics.     

Progress and Challenges in Quantifying Carbonyl-Metabolomic Phenomes with LC-MS/MS

Carbonyl-containing metabolites widely exist in biological samples and have important physiological functions. Thus, accurate and sensitive quantitative analysis of carbonyl-containing metabolites is crucial to provide insight into metabolic pathways as well as disease mechanisms. Although reversed phase liquid chromatography electrospray ionization mass spectrometry (RPLC-ESI-MS) is widely used due to the powerful separation capability of RPLC and high specificity and sensitivity of MS, but it is often challenging to directly analyze carbonyl-containing metabolites using RPLC-ESI-MS due to the poor ionization efficiency of neutral carbonyl groups in ESI. Modification of carbonyl-containing metabolites by a chemical derivatization strategy can overcome the obstacle of sensitivity; however, it is insufficient to achieve accurate quantification due to instrument drift and matrix effects. The emergence of stable isotope-coded derivatization (ICD) provides a good solution to the problems encountered above. Thus, LC-MS methods that utilize ICD have been applied in metabolomics including quantitative targeted analysis and untargeted profiling analysis. In addition, ICD makes multiplex or multichannel submetabolome analysis possible, which not only reduces instrument running time but also avoids the variation of MS response. In this review, representative derivatization reagents and typical applications in absolute quantification and submetabolome profiling are discussed to highlight the superiority of the ICD strategy for detection of carbonyl-containing metabolites.     

Metabolite Dysregulation by Pranlukast in Mycobacterium tuberculosis

Mycobacterium tuberculosis has been infecting millions of people worldwide over the years, causing tuberculosis. Drugs targeting distinct cellular mechanisms including synthesis of the cell wall, lipids, proteins, and nucleic acids in Mtb are currently being used for the treatment of TB. Although extensive research is being carried out at the molecular level in the infected host and pathogen, the identification of suitable drug targets and drugs remains under explored. Pranlukast, an allosteric inhibitor of MtArgJ (Mtb ornithine acetyltransferase) has previously been shown to inhibit the survival and virulence of Mtb. The main objective of this study was to identify the altered metabolic pathways and biological processes associated with the differentially expressed metabolites by PRK in Mtb. Here in this study, metabolomics was carried out using an LC-MS/MS-based approach. Collectively, 50 metabolites were identified to be differentially expressed with a significant p-value through a global metabolomic approach using a high-resolution mass spectrometer. Metabolites downstream of argJ were downregulated in the arginine biosynthetic pathway following pranlukast treatment. Predicted human protein interactors of pranlukast-treated Mtb metabolome were identified in association with autophagy, inflammation, DNA repair, and other immune-related processes. Further metabolites including N-acetylglutamate, argininosuccinate, L-arginine, succinate, ergothioneine, and L-phenylalanine were validated by multiple reaction monitoring, a targeted mass spectrometry-based metabolomic approach. This study facilitates the understanding of pranlukast-mediated metabolic changes in Mtb and holds the potential to identify novel therapeutic approaches using metabolic pathways in Mtb.     

The Effect of Blood Contained in the Samples on the Metabolomic Profile of Mouse Brain Tissue: A Study by NMR Spectroscopy

(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1^® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency ¹H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student’s test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.     

Widely-Targeted Metabolic Profiling in Lycium barbarum Fruits under Salt-Alkaline Stress Uncovers Mechanism of Salinity Tolerance

Wolfberry (Lycium barbarum L.) is an important economic crop widely grown in China. The effects of salt-alkaline stress on metabolites accumulation in the salt-tolerant Ningqi1 wolfberry fruits were evaluated across 12 salt-alkaline stress gradients. The soil pH, Na⁺, K⁺, Ca²⁺, Mg^2+, and HCO₃⁻ contents decreased at a gradient across the salt-alkaline stress gradients. Based on the widely-targeted metabolomics approach, we identified 457 diverse metabolites, 53% of which were affected by salt-alkaline stress. Remarkably, soil salt-alkaline stress enhanced metabolites accumulation in wolfberry fruits. Amino acids, alkaloids, organic acids, and polyphenols contents increased proportionally across the salt-alkaline stress gradients. In contrast, nucleic acids, lipids, hydroxycinnamoyl derivatives, organic acids and derivatives and vitamins were significantly reduced by high salt-alkaline stress. A total of 13 salt-responsive metabolites represent potential biomarkers for salt-alkaline stress tolerance in wolfberry. Specifically, we found that constant reductions of lipids and chlorogenic acids; up-regulation of abscisic acid and accumulation of polyamines are essential mechanisms for salt-alkaline stress tolerance in Ningqi1. Overall, we provide for the first time some extensive metabolic insights into salt-alkaline stress tolerance and key metabolite biomarkers which may be useful for improving wolfberry tolerance to salt-alkaline stress.     

Binding interactions of EDCs to human estrogen-related receptor gamma deciphered by multiple molecular dynamics and energy calculations

Dichloro-diphenyl-trichloroethane (DDT) analogs, classified as environmental endocrine disrupting compounds (EDCs), have been extensively employed as potent insecticides that can cause endocrine system disruption. However, the precise dynamic structural characteristics and interactions between human estrogen-related receptor gamma (hERRγ) and DDT analogs are not yet fully understood. In this study, we comprehensively investigate the impact of these EDCs (DDT, dichloro-diphenyl-dichloroethane (DDD), 2,2-bis(4-chlorophenyl)ethanol (DDOH), O,P′-DDT (2,4′-DDT), 4,4′-dichlorobenzophenone (DCBP), and 4-hydrotamoxifen (4-OHT) on the structural changes of hERRγ and their interaction mechanisms by employing multiple molecular dynamics (MD) simulations coupled with MM-PBSA and SIE approaches. The consequence manifested that overall structures of these six complexes did not transform markedly, but these compounds can affect the local hERRγ structure, leading to essential changes in interactions with pivotal residues nearby L268, V313, L309, Y326, and F435. And van der Waals interactions are the key to how these EDCs interact with hERRγ. These outcomes contribute to our comprehension the risks of DDT analogues to human health.     

Survey of low-level endocrine disrupting pesticides in food matrices in Slovakia

The search on endocrine disrupting chemicals (EDCs) in non-fatty food was evaluated. A fast, high-throughput, accurate, multiresidue method for the analysis of selected EDC pesticides in fruit and vegetable food samples was developed. The QuEChERS technique was used for sample preparation. Fast GC-MS was performed with a narrow-bore capillary column and a quadrupole benchtop detector with electron ionization (EI) and negative chemical ionization (NCI). A part of the work was devoted to the comparison of NCI versus EI approach concerning the sensitivity of detection and to the study of selectivity enhancement in NCI mode. Matrix-matched standard solutions were utilized for calibration. The methods validation was performed. Fortification studies at 1, 5, 10 and 250?µg?kg^?1 for 35 pesticides in EI mode and 0.1, 1, 5 and 250?µg?kg^?1 for 28 pesticides in NCI mode were performed. Average recoveries for each fortification level ranged from 70 to 110% with >80% of recoveries between 90 and 110%. Limits of quantification (LOQs) were established at 5?µg?kg^?1 for EI and at 1?µg?kg^?1 for NCI mode, which is lower than the lowest maximum residue level (MRL) value set by the European Commission in fruit and vegetables. The developed and validated fast GC-MS method was successfully applied to the search of EDC pesticides at ultratrace concentration level in real fruit and vegetable samples in Slovakia. Thirty-four samples of 20 different commodities were analyzed. Seven samples contained residues of three or more EDCs pesticides.     

基于超高效液相色谱-质谱分析的代谢组学在小檗碱治疗多囊卵巢综合征研究中的应用

多囊卵巢综合征（polycystic ovary syndrome,PCOS）是妇女最常见的内分泌和代谢紊乱性疾病,合理的药物治疗非常重要。本研究中,超重/肥胖的多囊卵巢综合征患者经过小檗碱治疗3个月,采集治疗前后的血样进行分析,利用超高效液相色谱-质谱联用技术（UHPLC-MS）对治疗前后血清中的内源性物质进行了相对含量测定。正交信号校正的偏最小二乘模式识别分析结果显示治疗前后有明显的区分。多变量分析结合非参数检验找出的与小檗碱治疗相关的差异代谢物均与脂类代谢有关。临床生化数据结合代谢组学数据显示,小檗碱治疗超重/肥胖型的多囊卵巢综合征患者可以增加机体胰岛素敏感性、改善脂类代谢。上述研究结果表明代谢组学是研究中药治疗疾病效果的有效工具之一。     

Automated annotation and quantification of metabolites in <Superscript>1</Superscript>H NMR data of biological origin

In ¹H NMR metabolomic datasets, there are often over a thousand peaks per spectrum, many of which change position drastically between samples. Automatic alignment, annotation, and quantification of all the metabolites of interest in such datasets have not been feasible. In this work we propose a fully automated annotation and quantification procedure which requires annotation of metabolites only in a single spectrum. The reference database built from that single spectrum can be used for any number of ¹H NMR datasets with a similar matrix. The procedure is based on the generalized fuzzy Hough transform (GFHT) for alignment and on Principal-components analysis (PCA) for peak selection and quantification. We show that we can establish quantities of 21 metabolites in several ¹H NMR datasets and that the procedure is extendable to include any number of metabolites that can be identified in a single spectrum. The procedure speeds up the quantification of previously known metabolites and also returns a table containing the intensities and locations of all the peaks that were found and aligned but not assigned to a known metabolite. This enables both biopattern analysis of known metabolites and data mining for new potential biomarkers among the unknowns.     

Expression,Purification, and Characterization of Endo-β-N-Acetylglucosaminidase H Using Baculovirus-Mediated Silkworm Protein Expression System

Endo-β-N-acetylglucosaminidase (Endo H) from Streptomyces plicatus hydrolyzes the core di-GlcNAc units of asparagine-linked oligosaccharides and is regarded as an important tool for glycobiology research. In the present study, we established a large-scale system to produce secreted Endo H using a silkworm-baculovirus expression system (silkworm-BES). The recombinant Endo H purified from silkworm hemolymph had activity comparable to that from recombinant Escherichia coli. As well as its well-characterized substrate RNase B, the Endo H from silkworm-BES was able to deglycosylate the high-mannose glycoproteins from silkworm hemolymph. Interestingly, the secretion amount of recombinant Endo H was significantly varied among the different silkworm strains, which could provide valuable information for larger-scale protein productions from silkworm-BES.     

Optimisation of derivatisation for the analysis of estrogenic compounds in water by solid-phase extraction gas chromatography-mass spectrometry

An optimisation of derivatisation methods for the simultaneous determination of endocrine disrupting chemicals (EDCs) in water by solid-phase extraction (SPE) gas chromatography-mass spectrometry (GC-MS) was developed in this study. Seven highly potent EDCs including 17β-estradiol (E2), estrone (E1), 16α-hydroxyestrone, 17α-ethynylestradiol (EE2), bisphenol A, 4-nonylphenol and 4-tert-octylphenol were selected as the target compounds. The SPE technique, followed by the derivatisation with N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) was used for the extraction recoveries of compounds from water and effluent samples. The stability of the silylation derivatives under different reaction conditions was investigated. The combined use of BSTFA and pyridine as derivatisation reagents, together with the use of hexane as the final solvent, was preferred in order to generate more stable derivatives of EDCs. The relative response factor (RRF) of all derivatives except that of EE2 was stable 120 h after derivatisation. The addition of pyridine as derivatisation reagent with BSTFA can prevent the conversion of EE2 to other products during the reaction. Several parameters that may affect the recovery of EDCs, such as the SPE flow rate, and water properties including aquatic colloid content and surfactant concentration were tested. The results showed that the flow rate (1-25 mL min⁻¹), colloid concentration (0-50 mg L⁻¹) and surfactants concentration (0-10 μg L⁻¹) did not cause significant decrease in the EDCs recovery.     

Application of comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry method to identify potential biomarkers of perinatal asphyxia in a non-human primate model

Perinatal asphyxia is a leading cause of brain injury in infants, occurring in 2-4 per 1000 live births. The clinical response to asphyxia is variable and difficult to predict with current diagnostic tests. Reliable biomarkers are needed to help predict the timing and severity of asphyxia, as well as response to treatment. Two-dimensional gas chromatography-time-of-flight-mass spectrometry (GC×GC-TOFMS) was used herein, in conjunction with chemometric data analysis approaches for metabolomic analysis in order to identify significant metabolites affected by birth asphyxia. Blood was drawn before and after 15 or 18 min of cord occlusion in a Macaca nemestrina model of perinatal asphyxia. Postnatal samples were drawn at 5 min of age (n=20 subjects). Metabolomic profiles of asphyxiated animals were compared to four controls delivered at comparable gestational age. Fifty metabolites with the greatest change pre- to post-asphyxia were identified and quantified. The metabolic profile of post-asphyxia samples showed marked variability compared to the pre-asphyxia samples. Fifteen of the 50 metabolites showed significant elevation in response to asphyxia, ten of which remained significant upon comparison to the control animals. This metabolomic analysis confirmed lactate and creatinine as markers of asphyxia and discovered new metabolites including succinic acid and malate (intermediates in the Krebs cycle) and arachidonic acid (a brain fatty acid and inflammatory marker) as potential biomarkers. GC×GC-TOFMS coupled with chemometric data analysis are useful tools to identify acute biomarkers of brain injury. Further study is needed to correlate these metabolites with severity of disease, and response to treatment.     

Sorption of bisphenol A, 17alpha-ethynylestradiol and estrone to mineral surfaces

Sorption of the endocrine disrupting chemicals (EDCs) bisphenol A (BPA), 17alpha-ethynylestradiol (EE2) and estrone (E1) from 3 microM aqueous solutions in 10 mM KNO3 to goethite, kaolinite and montmorillonite was investigated at 25 degrees C. Uptake of the EDCs by goethite and kaolinite suspensions was <20%, and little affected by pH. Sorption by montmorillonite was greater, ranging from 20 to 60%, and steadily increased from about pH 7. The amount of EDC sorbed to the mineral phases generally increased in the order of decreasing solubility (BPA相似文献   

An improved method for the simultaneous analysis of phenolic and steroidal estrogens in water and sediment

This paper describes an improved method for the extraction and analysis of seven endocrine disrupting chemicals with wide-ranging polarities from water and sediments using gas chromatography-tandem mass spectrometry (GC-MS/MS). The analytes were 4-tert-octylphenol, 4-nonylphenol, bisphenol A, estrone, 17β-estradiol, 17α-ethynylestradiol and 16α-hydroxyestrone. The optimised GC-MS/MS method produces increased selectivity and sensitivity compared to GC-MS, with limit of detection ranging from 0.01 to 0.49 ng L⁻¹ in water and from 0.05 to 0.14 ng g⁻¹ in sediment. Extraction from aqueous samples was performed by solid-phase extraction (SPE) and from sediment samples by microwave-assisted extraction (MAE). The improved method for the clean-up of sediment extracts carried out by SPE enhanced EDC recovery (86-102%) while reducing matrix interference and sample drying time. Derivatisation of final sample extracts was achieved using N,O-bis(trimethylsilyl)trifluoroacetamide and pyridine, and their stability was enhanced by reconstituting the derivatised extracts with hexane. The method was validated by spiking experiments which showed good recovery and reproducibility. The method was applied to samples taken from the Medway estuary in Kent, UK, where non-conservative behaviour of EDCs was demonstrated.     

Novel Detection Method of Endocrine Disrupting Chemicals Utilizing Liposomes as Cell Membrane Model

Abstract

A novel detection method of endocrine disrupting chemicals (EDCs) is proposed. Liposomes encapsulating fluorescence dye was prepared as a cell membrane model and applied to detect EDCs. Leakages of dye from liposomes were observed after their exposure to EDCs. Fluorescence intensity increased significantly when the liposomes were exposed to 5 ppm EDCs. The increases showed a good correlation with EDCs' dipole moment. Therefore, polarizability is suggested as one of the factors of the liposome-EDC interaction. At lower than 5 ppm, the increases depended on EDCs' concentration. The tendency of the results was in accordance with reported estrogenic activity of EDCs.     

Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry

With the technique of metabolomics, gas chromatography/mass spectrometry (GC/MS), urine or serum metabolites can be assayed to explore disease biomarkers. In this work, we present a metabolomic method to investigate the urinary metabolic difference between hepatocellular carcinoma (HCC, n = 20) male patients and normal male subjects (n = 20). The urinary endogenous metabolome was assayed using chemical derivatization followed by GC/MS. After GC/MS analysis, 103 metabolites were detected, of which 66 were annotated as known compounds. By a two sample t-test statistics with p < 0.05, 18 metabolites were shown to be significantly different between the HCC and control groups. A diagnostic model was constructed with a combination of 18 marker metabolites or together with alphafetoprotein, using principal component analysis and receiver-operator characteristic curves. The multivariate statistics of the diagnostic model yielded a separation between the two groups with an area under the curve value of 0.9275. This non-invasive technique of identifying HCC biomarkers from urine may have clinical utility.