Deying Chen

Metabonomic Profiles Discriminate Hepatocellular Carcinoma from Liver Cirrhosis by Ultraperformance Liquid Chromatography–Mass Spectrometry

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and usually develops in patients with liver cirrhosis (LC). Biomarkers that discriminate HCC from LC are important but are limited. In the present study, an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS)-based metabonomics approach was used to characterize serum profiles from HCC (n = 82), LC (n = 48), and healthy subjects (n = 90), and the accuracy of UPLC-MS profiles and alpha-fetoprotein (AFP) levels were compared for their use in HCC diagnosis. By multivariate data and receiver operating characteristic curves analysis, metabolic profiles were capable of discriminating not only patients from the controls but also HCC from LC with 100% sensitivity and specificity. Thirteen potential biomarkers were identified and suggested that there were significant disturbances of key metabolic pathways, such as organic acids, phospholipids, fatty acids, bile acids, and gut flora metabolism, in HCC patients. Canavaninosuccinate was first identified as a metabolite that exhibited a significant decrease in LC and an increase in HCC. In addition, glycochenodeoxycholic acid was suggested to be an important indicator for HCC diagnosis and disease prognosis. UPLC-MS signatures, alone or in combination with AFP levels, could be an efficient and convenient tool for early diagnosis and screening of HCC in high-risk populations.

Fecal metabolome profiling of liver cirrhosis and hepatocellular carcinoma patients by ultra performance liquid chromatography-mass spectrometry.

Fecal metabolome of healthy humans and patients suffering from liver cirrhosis and hepatocellular carcinoma (HCC) were studied using ultra performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF MS). Metabolic features detected by the method were then statistically treated using partial least squares to latent structure-discriminant analysis (PLS-DA) models to discriminate between healthy and diseased states. PLS-DA was also used to discriminate between cirrhosis and HCC stressed fecal metabolomes and to identify potential biomarkers for cirrhosis and HCC that are expressed at significantly different amounts in fecal metabolomes. Score plots of pattern recognition analysis distinguished liver cirrhosis and HCC patients from healthy humans. Based on the variable of importance in the project (VIP) values and S-plots, six metabolites were considered as potential biomarkers with a strong increase in lysophosphatidylcholines and a dramatic decrease in bile acids and bile pigments in patients with liver cirrhosis and HCC in comparison with healthy humans. Results demonstrate the potential of UPLC-MS as an efficient and convenient method that can be applied to screen fecal samples and aid in the early diagnosis of cirrhosis and hepatocellular carcinoma.

Development of High-Performance Chemical Isotope Labeling LC–MS for Profiling the Human Fecal Metabolome

Human fecal samples contain endogenous human metabolites, gut microbiota metabolites, and other compounds. Profiling the fecal metabolome can produce metabolic information that may be used not only for disease biomarker discovery, but also for providing an insight about the relationship of the gut microbiome and human health. In this work, we report a chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS) method for comprehensive and quantitative analysis of the amine- and phenol-containing metabolites in fecal samples. Differential (13)C2/(12)C2-dansyl labeling of the amines and phenols was used to improve LC separation efficiency and MS detection sensitivity. Water, methanol, and acetonitrile were examined as an extraction solvent, and a sequential water-acetonitrile extraction method was found to be optimal. A step-gradient LC-UV setup and a fast LC-MS method were evaluated for measuring the total concentration of dansyl labeled metabolites that could be used for normalizing the sample amounts of individual samples for quantitative metabolomics. Knowing the total concentration was also useful for optimizing the sample injection amount into LC-MS to maximize the number of metabolites detectable while avoiding sample overloading. For the first time, dansylation isotope labeling LC-MS was performed in a simple time-of-flight mass spectrometer, instead of high-end equipment, demonstrating the feasibility of using a low-cost instrument for chemical isotope labeling metabolomics. The developed method was applied for profiling the amine/phenol submetabolome of fecal samples collected from three families. An average of 1785 peak pairs or putative metabolites were found from a 30 min LC-MS run. From 243 LC-MS runs of all the fecal samples, a total of 6200 peak pairs were detected. Among them, 67 could be positively identified based on the mass and retention time match to a dansyl standard library, while 581 and 3197 peak pairs could be putatively identified based on mass match using MyCompoundID against a Human Metabolome Database and an Evidence-based Metabolome Library, respectively. This represents the most comprehensive profile of the amine/phenol submetabolome ever detected in human fecal samples. The quantitative metabolome profiles of individual samples were shown to be useful to separate different groups of samples, illustrating the possibility of using this method for fecal metabolomics studies.

Alterations and correlations of the gut microbiome, metabolism and immunity in patients with primary biliary cirrhosis.

We selected 42 early-stage primary biliary cirrhosis (PBC) patients and 30 healthy controls (HC). Metagenomic sequencing of the 16S rRNA gene was used to characterize the fecal microbiome. UPLC-MS/MS assaying of small molecules was used to characterize the metabolomes of the serum, urine and feces. Liquid chip assaying of serum cytokines was used to characterize the immune profiles. The gut of PBC patients were depleted of some potentially beneficial bacteria, such as Acidobacteria, Lachnobacterium sp., Bacteroides eggerthii and Ruminococcus bromii, but were enriched in some bacterial taxa containing opportunistic pathogens, such as γ-Proteobacteria, Enterobacteriaceae, Neisseriaceae, Spirochaetaceae, Veillonella, Streptococcus, Klebsiella, Actinobacillus pleuropneumoniae, Anaeroglobus geminatus, Enterobacter asburiae, Haemophilus parainfluenzae, Megasphaera micronuciformis and Paraprevotella clara. Several altered gut bacterial taxa exhibited potential interactions with PBC through their associations with altered metabolism, immunity and liver function indicators, such as those of Klebsiella with IL-2A and Neisseriaceae with urinary indoleacrylate. Many gut bacteria, such as some members of Bacteroides, were altered in their associations with the immunity and metabolism of PBC patients, although their relative abundances were unchanged. Consequently, the gut microbiome is altered and may be critical for the onset or development of PBC by interacting with metabolism and immunity.

Lipidomic profiling and discovery of lipid biomarkers in Stephanodiscus sp. under cold stress

Changes in membrane lipid composition play multiple roles in plant adaptation and survival in the face of chilling and freezing damage. The ultra-performance liquid chromatography/quadrupole-TOF-MS (UPLC/Q-TOF-MS)-based approach was developed for investigating the lipid changes during cold exposure in Stephanodiscus sp. followed by multivariate statistical analysis including principal components analysis, partial least squares discriminant analysis and orthogonal projection on latent structure discriminant analysis for data classification and potential biomarkers selection. The analysis demonstrated dramatic lipid alterations take place in both extraplastidic and plastidic membranes. Thirty-eight lipid molecules were selected and identified as putative biomarkers, including chlorophyll a degradation products, triacylglycerol, phosphatidylcholine, phosphatidylglycerol, sulfo-quinovosyldiacylglycerol, monogalactosyldiacylglyceroll, lyso-phosphatidylglycerol, lyso-phosphatidylcholine, lyso-monogalactosyldiacylglycerol and lyso-sulfoquinovosyldiacylglycerol. These metabolites have been shown previously to function in energy storage, membrane stability and photosynthesis efficiency. This study is the first one using UPLC/Q-TOF-MS-based lipidomic profiling with multivariate statistical analysis to explore the lipidomic changes of microalgae in response to stress conditions, which promotes better understanding of their physiology and ecology.

A novel-configuration multi-wavelength Brillouin erbium fiber laser and its application in switchable high-frequency microwave generation

A novel configuration of compound-cavity multi-wavelength Brillouin erbium fiber laser is proposed and experimentally demonstrated. With an incident optical carrier power of 8 dBm, at least 14 lasing lines are obtained with a wavelength spacing of ∼0.08 nm. Stability and power uniformity of the multi-wave-length lasing are ensured by the flat hybrid gain of Brillouin and erbium, the compound-cavity structure, and the four-wave mixing suppression using a long (10 km) single-mode fiber. A stable and frequency-switchable microwave can be achieved by incorporating a fiber Bragg grating filter to select the desired nth-order Stokes wave and beating it with the optical carrier at a photodetector. In our experiment, the 1st-4th-order Stokes waves are filtered respectively and hence a high-quality microwave with a switchable frequency from ∼10 to ∼40 GHz and a tuning step of ∼10 GHz is achieved. The signal-to-noise ratio is measured to be >25 dB.

Quasi-distributed fiber Bragg grating sensor system based on a Fourier domain mode locking fiber laser

A novel quasi-distributed fiber Bragg grating (FBG) sensor system based on Fourier domain mode locking (FDML) fiber laser is proposed and demonstrated. The low reflectivity FBGs with the same Bragg wavelength are connected cascaded in a long fiber working as the sensing elements of the sensor system as well as the wavelength and cavity length selecting elements of the FDML laser. By adjusting the driving frequency of the FDML fiber laser, lasing with different selected cavity lengths will be achieved correspondingly. When the wavelength of the working FBG shifts which includes the sensing information, FBG interrogation can be realized both in wavelength and time domain.

Serum metabolomic signatures discriminate early liver inflammation and fibrosis stages in patients with chronic hepatitis B

Chronic HBV (CHB) infected patients with intermediate necroinflammation and fibrosis are recommended to receive antiviral treatment. However, other than liver biopsy, there is a lack of sensitive and specific objective method to determine the necroinflammation and fibrosis stages in CHB patients. This study aims to identify unique serum metabolomic profile associated with histological progression in CHB patients and to develop novel metabolite biomarker panels for early CHB detection and stratification. A comprehensive metabolomic profiling method was established to compare serum samples collected from health donor (n = 67), patients with mild (G < 2 and S < 2, CHB1, n = 52) or intermediate (G ≥ 2 or S ≥ 2, CHB2, n = 36) necroinflammation and fibrosis. Multivariate models were developed to differentiate CHB1 and CHB2 from controls. A set of CHB-associated biomarkers was identified, including lysophosphatidylcholines, phosphatidylcholines, phosphatidylinositol, phosphatidylserine, and bile acid metabolism products. Stratification of CHB1 and CHB2 patients by a simple logistic index, the PIPSindex, based on phosphatidylinositol (PI) and phosphatidylserine (PS), was achieved with an AUC of 0.961, which outperformed all currently available markers. A panel of serum metabolites that differentiate health control, CHB1 and CHB2 patients has been identified. The proposed metabolomic biosignature has the potential to be used as indicator for antiviral treatment for CHB management.

A serum metabolomic analysis for diagnosis and biomarker discovery of primary biliary cirrhosis and autoimmune hepatitis.

BACKGROUND Because of the diversity of the clinical and laboratory manifestations, the diagnosis of autoimmune liver disease (AILD) remains a challenge in clinical practice. The value of metabolomics has been studied in the diagnosis of many diseases. The present study aimed to determine whether the metabolic profiles, based on ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), differed between autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), to identify specific metabolomic markers, and to establish a model for the diagnosis of AIH and PBC. METHODS Serum samples were collected from 20 patients with PBC, 19 patients with AIH, and 25 healthy individuals. UPLC-MS data of the samples were analyzed using principal component analysis, partial least squares discrimination analysis and orthogonal partial least squares discrimination analysis. RESULTS The partial least squares discrimination analysis model (R2Y=0.991, Q2=0.943) was established between the AIH and PBC groups and exhibited both sensitivity and specificity of 100%. Five groups of biomarkers were identified, including bile acids, free fatty acids, phosphatidylcholines, lysolecithins and sphingomyelin. Bile acids significantly increased in the AIH and PBC groups compared with the healthy control group. The other biomarkers decreased in the AIH and PBC groups compared with those in the healthy control group. In addition, the biomarkers were downregulated in the AIH group compared with the PBC group. CONCLUSIONS The biomarkers identified revealed the pathophysiological changes in AILD and helped to discriminate between AIH and PBC. The predictability of this method suggests its potential application in the diagnosis of AILD.

Efficacy of Fluidized Bed Bioartificial Liver in Treating Fulminant Hepatic Failure in Pigs: A Metabolomics Study.

Bioartificial livers may act as a promising therapy for fulminant hepatic failure (FHF) with better accessibility and less injury compared to orthotopic liver transplantation. This study aims to evaluate the efficacy and safety of a fluidized bed bioartificial liver (FBBAL) and to explore its therapeutic mechanisms based on metabolomics. FHF was induced by D-galactosamine. Eighteen hours later, pigs were treated with an FBBAL containing encapsulated primary porcine hepatocytes (B group), with a sham FBBAL (containing cell-free capsules, S group) or with only intensive care (C group) for 6 h. Serum samples were assayed using ultra-performance liquid chromatography-mass spectrometry. The difference in survival time (51.6 ± 7.9 h vs. 49.3 ± 6.6 h) and serum metabolome was negligible between the S and C groups, whereas FBBAL treatment significantly prolonged survival time (70.4 ± 11.5h, P < 0.01) and perturbed the serum metabolome, resulting in a marked decrease in phosphatidylcholines, lysophosphatidylcholines, sphingomyelinase, and fatty acids and an increase in conjugated bile acids. The FBBAL exhibits some liver functions and may exert its therapeutic effect by altering the serum metabolome of FHF pigs. Moreover, alginate–chitosan capsules have less influence on serum metabolites. Nevertheless, the alterations were not universally beneficial, revealing that much should be done to improve the FBBAL.