Xue Shi

Chronic Alcohol Exposure Stimulates Adipose Tissue Lipolysis in Mice: Role of Reverse Triglyceride Transport in the Pathogenesis of Alcoholic Steatosis

Alcohol consumption induces liver steatosis; therefore, this study investigated the possible role of adipose tissue dysfunction in the pathogenesis of alcoholic steatosis. Mice were pair-fed an alcohol or control liquid diet for 8 weeks to evaluate the alcohol effects on lipid metabolism at the adipose tissue-liver axis. Chronic alcohol exposure reduced adipose tissue mass and adipocyte size. Fatty acid release from adipose tissue explants was significantly increased in alcohol-fed mice in association with the activation of adipose triglyceride lipase and hormone-sensitive lipase. Alcohol exposure induced insulin intolerance and inactivated adipose protein phosphatase 1 in association with the up-regulation of phosphatase and tensin homolog (PTEN) and suppressor of cytokine signaling 3 (SOCS3). Alcohol exposure up-regulated fatty acid transport proteins and caused lipid accumulation in the liver. To define the mechanistic link between adipose triglyceride loss and hepatic triglyceride gain, mice were first administered heavy water for 5 weeks to label adipose triglycerides with deuterium, and then pair-fed alcohol or control diet for 2 weeks. Deposition of deuterium-labeled adipose triglycerides in the liver was analyzed using Fourier transform ion cyclotron mass spectrometry. Alcohol exposure increased more than a dozen deuterium-labeled triglyceride molecules in the liver by up to 6.3-fold. These data demonstrate for the first time that adipose triglycerides due to alcohol-induced hyperlipolysis are reverse transported and deposited in the liver.

Diabetes-Induced Hepatic Pathogenic Damage, Inflammation, Oxidative Stress, and Insulin Resistance Was Exacerbated in Zinc Deficient Mouse Model

Objectives Zinc (Zn) deficiency often occurs in the patients with diabetes. Effects of Zn deficiency on diabetes-induced hepatic injury were investigated. Methods Type 1 diabetes was induced in FVB mice with multiple low-dose streptozotocin. Hyperglycemic and age-matched control mice were treated with and without Zn chelator, N,N,N′,N′-tetrakis (2-pyridylemethyl) ethylenediamine (TPEN), at 5 mg/kg body-weight daily for 4 months. Hepatic injury was examined by serum alanine aminotransferase (ALT) level and liver histopathological and biochemical changes. Results Hepatic Zn deficiency (lower than control level, p<0.05) was seen in the mice with either diabetes or TPEN treatment and more evident in the mice with both diabetes and TPEN. Zn deficiency exacerbated hepatic injuries, shown by further increased serum ALT, hepatic lipid accumulation, inflammation, oxidative damage, and endoplasmic reticulum stress-related cell death in Diabetes/TPEN group compared to Diabetes alone. Diabetes/TPEN group also showed a significant decrease in nuclear factor-erythroid 2-related factor 2 (Nrf2) expression and transcription action along with significant increases in Akt negative regulators, decrease in Akt and GSK-3β phosphorylation, and increase in nuclear accumulation of Fyn (a Nrf2 negative regulator). In vitro study with HepG2 cells showed that apoptotic effect of TPEN at 0.5–1.0 µM could be completely prevented by simultaneous Zn supplementation at the dose range of 30–50 µM. Conclusions Zn is required for maintaining Akt activation by inhibiting the expression of Akt negative regulators; Akt activation can inhibit Fyn nuclear translocation to export nuclear Nrf2 to cytoplasm for degradation. Zn deficiency significantly enhanced diabetes-induced hepatic injury likely through down-regulation of Nrf2 function.

MetSign: a computational platform for high-resolution mass spectrometry-based metabolomics.

Data analysis in metabolomics is currently a major challenge, particularly when large sample sets are analyzed. Herein, we present a novel computational platform entitled MetSign for high-resolution mass spectrometry-based metabolomics. By converting the instrument raw data into mzXML format as its input data, MetSign provides a suite of bioinformatics tools to perform raw data deconvolution, metabolite putative assignment, peak list alignment, normalization, statistical significance tests, unsupervised pattern recognition, and time course analysis. MetSign uses a modular design and an interactive visual data mining approach to enable efficient extraction of useful patterns from data sets. Analysis steps, designed as containers, are presented with a wizard for the user to follow analyses. Each analysis step might contain multiple analysis procedures and/or methods and serves as a pausing point where users can interact with the system to review the results, to shape the next steps, and to return to previous steps to repeat them with different methods or parameter settings. Analysis of metabolite extract of mouse liver with spiked-in acid standards shows that MetSign outperforms the existing publically available software packages. MetSign has also been successfully applied to investigate the regulation and time course trajectory of metabolites in hepatic liver.

Metabolomic analysis of the effects of polychlorinated biphenyls in nonalcoholic fatty liver disease

Polychlorinated biphenyls (PCBs) are persistent organic pollutants and have been associated with abnormal liver enzymes and suspected nonalcoholic fatty liver disease (NAFLD), obesity, and the metabolic syndrome in epidemiological studies. In epidemiological surveys of human PCB exposure, PCB 153 has the highest serum levels among PCB congeners. To determine the hepatic effects of PCB 153 in mice, C57BL/6J mice were fed either a control diet (CD) or a high fat diet (HFD) for 12 weeks, with or without PCB 153 coexposure. The metabolite extracts from mouse livers were analyzed using linear trap quadrupole-Fourier transform ion cyclotron resonance mass spectrometer (LTQ-FTICR MS) via direct infusion nanoelectrospray ionization (DI-nESI) mass spectrometry. The metabolomics analysis indicated no difference in the metabolic profile between mice fed the control diet with PCB 153 exposure (CD+PCB 153) and mice fed the control diet (CD) without PCB 153 exposure. However, compared with CD group, levels of 10 metabolites were increased and 15 metabolites were reduced in mice fed HFD. Moreover, compared to CD+PCB 153 group, the abundances of 6 metabolites were increased and 18 metabolites were decreased in the mice fed high fat diet with PCB 153 exposure (HFD+PCB 153). Compared with HFD group, the abundances of 2 metabolites were increased and of 12 metabolites were reduced in HFD+PCB 153 group. These observations agree with the histological results and indicate that the metabolic effects of PCB 153 were highly dependent on macronutrient interactions with HFD. Antioxidant depletion is likely to be an important consequence of this interaction, as this metabolic disturbance has previously been implicated in obesity and NAFLD.

Compound identification using partial and semipartial correlations for gas chromatography-mass spectrometry data.

Compound identification is a key component of data analysis in the applications of gas chromatography-mass spectrometry (GC-MS). Currently, the most widely used compound identification is mass spectrum matching, in which the dot product and its composite version are employed as spectral similarity measures. Several forms of transformations for fragment ion intensities have also been proposed to increase the accuracy of compound identification. In this study, we introduced partial and semipartial correlations as mass spectral similarity measures and applied them to identify compounds along with different transformations of peak intensity. The mixture versions of the proposed method were also developed to further improve the accuracy of compound identification. To demonstrate the performance of the proposed spectral similarity measures, the National Institute of Standards and Technology (NIST) mass spectral library and replicate spectral library were used as the reference library and the query spectra, respectively. Identification results showed that the mixture partial and semipartial correlations always outperform both the dot product and its composite measure. The mixture similarity with semipartial correlation has the highest accuracy of 84.6% in compound identification with a transformation of (0.53,1.3) for fragment ion intensity and m/z value, respectively.

Metabolomic Analysis of the Effects of Chronic Arsenic Exposure in a Mouse Model of Diet-Induced Fatty Liver Disease

Arsenic is a widely distributed environmental component that is associated with a variety of cancer and non-cancer adverse health effects. Additional lifestyle factors, such as diet, contribute to the manifestation of disease. Recently, arsenic was found to increase inflammation and liver injury in a dietary model of fatty liver disease. The purpose of the present study was to investigate potential mechanisms of this diet-environment interaction via a high-throughput metabolomics approach. GC×GC-TOF MS was used to identify metabolites that were significantly increased or decreased in the livers of mice fed a Western diet (a diet high in fat and cholesterol) and co-exposed to arsenic-contaminated drinking water. The results showed that there are distinct hepatic metabolomic profiles associated with eating a high fat diet, drinking arsenic-contaminated water, and the combination of the two. Among the metabolites that were decreased when arsenic exposure was combined with a high fat diet were short-chain and medium-chain fatty acid metabolites and the anti-inflammatory amino acid, glycine. These results are consistent with the observed increase in inflammation and cell death in the livers of these mice and point to potentially novel mechanisms by which these metabolic pathways could be altered by arsenic in the context of diet-induced fatty liver disease.

Data Preprocessing Method for Liquid Chromatography–Mass Spectrometry Based Metabolomics

A set of data preprocessing algorithms for peak detection and peak list alignment are reported for analysis of liquid chromatography-mass spectrometry (LC-MS)-based metabolomics data. For spectrum deconvolution, peak picking is achieved at the selected ion chromatogram (XIC) level. To estimate and remove the noise in XICs, each XIC is first segmented into several peak groups based on the continuity of scan number, and the noise level is estimated by all the XIC signals, except the regions potentially with presence of metabolite ion peaks. After removing noise, the peaks of molecular ions are detected using both the first and the second derivatives, followed by an efficient exponentially modified Gaussian-based peak deconvolution method for peak fitting. A two-stage alignment algorithm is also developed, where the retention times of all peaks are first transferred into the z-score domain and the peaks are aligned based on the measure of their mixture scores after retention time correction using a partial linear regression. Analysis of a set of spike-in LC-MS data from three groups of samples containing 16 metabolite standards mixed with metabolite extract from mouse livers demonstrates that the developed data preprocessing method performs better than two of the existing popular data analysis packages, MZmine2.6 and XCMS(2), for peak picking, peak list alignment, and quantification.

MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics

MOTIVATION Due to the high complexity of metabolome, the comprehensive 2D gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) is considered as a powerful analytical platform for metabolomics study. However, the applications of GC×GC-TOF MS in metabolomics are not popular owing to the lack of bioinformatics system for data analysis. RESULTS We developed a computational platform entitled metabolomics profiling pipeline (MetPP) for analysis of metabolomics data acquired on a GC×GC-TOF MS system. MetPP can process peak filtering and merging, retention index matching, peak list alignment, normalization, statistical significance tests and pattern recognition, using the peak lists deconvoluted from the instrument data as its input. The performance of MetPP software was tested with two sets of experimental data acquired in a spike-in experiment and a biomarker discovery experiment, respectively. MetPP not only correctly aligned the spiked-in metabolite standards from the experimental data, but also correctly recognized their concentration difference between sample groups. For analysis of the biomarker discovery data, 15 metabolites were recognized with significant concentration difference between the sample groups and these results agree with the literature results of histological analysis, demonstrating the effectiveness of applying MetPP software for disease biomarker discovery. AVAILABILITY The source code of MetPP is available at http://metaopen.sourceforge.net CONTACT xiang.zhang@louisville.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Hepatic and Fecal Metabolomic Analysis of the Effects of Lactobacillus rhamnosus GG on Alcoholic Fatty Liver Disease in Mice

The interactions among the gut, liver, and immune system play an important role in liver disease. Probiotics have been used for the treatment and prevention of many pathological conditions, including liver diseases. Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) was used herein, in conjunction with chemometric data analysis, to identify metabolites significantly affected by probiotics in mice fed with or without alcohol. The metabolomics analysis indicates that the levels of fatty acids increased in mouse liver and decreased in mouse feces when mice were chronically exposed to alcohol. Supplementing the alcohol-fed mice with culture supernatant from Lactobacillus rhamnosus GG (LGGs) normalized these alcohol-induced abnormalities and prevented alcoholic liver disease (ALD). These results agree well with previous studies. In addition to diet-derived long chain fatty acids (LCFAs), LGGs may positively modify the guts bacterial population to stimulate LCFA synthesis, which has been shown to enhance intestinal barrier function, reduce endotoxemia, and prevent ALD. We also found that several amino acids, including l-isoleucine, a branched chain amino acid, were downregulated in the liver and fecal samples from animals exposed to alcohol and that the levels of these amino acids were corrected by LGGs. These results demonstrate that LGGs alleviates alcohol-induced fatty liver by mechanisms involving increasing intestinal and decreasing hepatic fatty acids and increasing amino acid concentration.

Chronic Alcohol Exposure Disturbs Lipid Homeostasis at the Adipose Tissue-Liver Axis in Mice: Analysis of Triacylglycerols Using High-Resolution Mass Spectrometry in Combination with In Vivo Metabolite Deuterium Labeling

A method of employing high-resolution mass spectrometry in combination with in vivo metabolite deuterium labeling was developed in this study to investigate the effects of alcohol exposure on lipid homeostasis at the white adipose tissue (WAT)-liver axis in a mouse model of alcoholic fatty liver. In order to differentiate the liver lipids synthesized from the fatty acids that were transported back from adipose tissue and the lipids synthesized from other sources of fatty acids, a two-stage mouse feeding experiment was performed to incorporate deuterium into metabolites. Hepatic lipids extracted from mouse liver, epididymal white adipose tissue (eWAT) and subcutaneous white adipose tissue (sWAT) were analyzed. It was found that 13 and 10 triacylglycerols (TGs) incorporated with a certain number of deuterium were significantly increased in alcohol induced fatty liver at two and four weeks of alcohol feeding periods, respectively. The concentration changes of these TGs ranged from 1.7 to 6.3-fold increase. A total of 14 deuterated TGs were significantly decreased in both eWAT and sWAT at the two and four weeks and the fold-change ranged from 0.19 to 0.77. The increase of deuterium incorporated TGs in alcohol-induced fatty liver and their decrease in both eWAT and sWAT indicate that alcohol exposure induces hepatic influx of fatty acids which are released from WATs. The results of time course analysis further indicate a mechanistic link between adipose fat loss and hepatic fat gain in alcoholic fatty liver.