Weidong Dai

Dalian Institute of Chemical Physics, Lü-ta-shih, Liaoning, China

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Publications (12)43.16 Total impact

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    ABSTRACT: Pseudo-targeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from Q-TOF MS by information-dependent acquisition (IDA), then picks targeted ion-pair and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of pseudo-targeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS2 spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was firstly analyzed and the representative ion pairs were correctly picked out, then pooled serum samples were further studied and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer, 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudo-targeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.
    Analytical Chemistry 04/2015; DOI:10.1021/acs.analchem.5b00615 · 5.83 Impact Factor
  • Hongwei Kong, Weidong Dai, Guowang Xu
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    ABSTRACT: Liquid chromatography-mass spectrometry (LC-MS) based metabolomics has become an important approach in life science research due to its powerful separation and high sensitivity detection. However, because of the lack of an effective mass spectra library for metabolite identification, a vast amount of detected metabolites are unable to be identified. The improvement of the metabolite coverage and the discovery of biomarkers are harmed, leading to the severe loss of chemical and biological information. The metabolite identification has become a major bottleneck in metabolomics studies. This review describes recent advances of metabolite identification based on atmospheric pressure ionization (API)-MS data. In particular, it focuses on the advances in mass spectrometer instruments, assignment of elemental compositions, database and spectral search, computer-aided spectral interpretation, etc.
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    ABSTRACT: Modifications of genes and proteins have been extensively studied in systems biology using comprehensive analytical strategies. Although metabolites are frequently modified, these modifications have not been studied using -omics approaches. Here a general strategy for the nontargeted profiling of modified metabolites, which we call "nontargeted modification-specific metabolomics", is reported. A key aspect of this strategy was the combination of in-source collision-induced dissociation liquid chromatography-mass spectrometry (LC-MS) and global nontargeted LC-MS-based metabolomics. Characteristic neutral loss fragments that are specific for acetylation, sulfation, glucuronidation, glucosidation, or ribose conjugation were reproducibly detected using human urine as a model specimen for method development. The practical application of this method was demonstrated by profiling urine samples from liver cirrhosis patients. Approximately 900 features were identified as modified endogenous metabolites and xenobiotics. Moreover, this strategy supports the identification of compounds not included in traditional metabolomics databases (HMDB, Metlin, and KEGG), which are currently referred to as "unknowns" in metabolomics projects. Nontargeted modification-specific metabolomics opens a new perspective in systems biology.
    Analytical Chemistry 09/2014; 86(18). DOI:10.1021/ac502045j · 5.83 Impact Factor
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    ABSTRACT: Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Discovery of novel biomarkers for early HCC from other liver diseases such as cirrhosis is of great clinical benefit. In this study, a novel steroid hormone metabolomic method based on liquid chromatography-mass spectrometry combined with logistic regression analysis was applied to study the steroid hormone disorders and to screen potential urinary steroid hormone biomarkers of early HCC. Thirty-six urinary steroid hormones were detected and quantified in healthy controls, cirrhotic patients, and early HCC patients. Heat map analysis and multivariate statistical analysis suggested severe disorders of steroid hormone network and holistically decreased urinary steroid hormone pattern in cirrhotic and early HCC patients. Logistic regression analysis reveals that a panel of two urinary steroid hormones (epitestosterone and allotetrahydrocortisol) displayed excellent diagnostic capability for distinguishing early HCC from cirrhosis with area under the curve (AUC) = 0.938 of receiver operating characteristic (ROC) analysis. These results help to overcome the disadvantage of lower sensitivity and specificity of alpha-fetoprotein for distinguishing early HCC from cirrhosis. Our work shows that steroid hormone metabolomics is a promising biomarker tool for biomarker study of early HCC.
    Analytical and Bioanalytical Chemistry 05/2014; 406(18). DOI:10.1007/s00216-014-7843-3 · 3.58 Impact Factor
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    ABSTRACT: A systematic approach for the fusion of associated ions from a common molecule was developed to generate 'one feature for one peak' metabolomics data. This approach guarantees that each molecule is equally selected as a potential biomarker, and may largely enhance the chance to obtain reliable findings without employing redundant ion information. The ion fusion is based on low mass variation in contrast to the theoretical calculation measured by a high-resolution mass spectrometer, such as LTQ orbitrap, and a high correlation of ion pairs from the same molecule. The mass characteristics of isotopic distribution, neutral loss and adduct ions were simultaneously applied to inspect each extracted ion in the range of a pre-defined retention time window. The correlation coefficient was computed with the corresponding intensities of each ion pair amongst all experimental samples. Serum metabolomics data for the investigation of hepatocellular carcinoma (HCC) and healthy controls were utilized as an example to demonstrate this strategy. In total, 609 and 1084 ion pairs were respectively found meeting one or more criteria for fusion, and therefore fused to 106 and 169 metabolite features of the datasets in the positive and negative modes, respectively. The important metabolite features were separately discovered and compared to distinguish the HCC from the healthy controls using the two datasets with and without ion fusion. The results show that the developed method can be an effective tool to process high-resolution mass spectrometry data in 'omics' studies.
    Analytical Chemistry 03/2014; 86(8). DOI:10.1021/ac500878x · 5.83 Impact Factor
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    ABSTRACT: The present study aimed to investigate the anti-depressive effect of the traditional Chinese medicine Allium macrostemon in a rat model of depression induced by exposure to chronic immobilization stress. Lipid and acylcarnitine metabolism were set into the focus of this study due to their key role in the pathogenesis of depression. Plasma lipid profiling was performed by ultra fast liquid chromatography/ion trap-time of flight mass spectrometry. Ultra-high performance liquid chromatography/triple quadrupole mass spectrometry was used to characterize the plasma acylcarnitine profile. Principal component analysis (PCA) revealed distinct differences in plasma lipid and acylcarnitine profiles of depressed rats from those in the control rats, which were also validated by univariate analysis. Several lysophosphatidylcholines (LPC (18:1→:2), LPC (20:1), LPC (O-16:2), and LPC (O-18:3)) as well as most medium- and long-chain acylcarnitines were elevated, while some phosphatidylcholines (PC (32:1), PC (36:4→:5), PC (37:4), PC (38:4→:6), PC (40:6), PC (O-36:4), and PC (O-38:5)) and triglycerides (TG (58:12), TG (60:12), and TG (62:13→:14)) were decreased in the plasma of depressed rats. These changes indicate that depressed rats were associated with inflammatory conditions and an incomplete β-oxidation of fatty acids. Most of these dysregulated metabolites were returned to their normal levels after treatment with A. macrostemon according to PCA and univariate analysis, highlighting the anti-depressive effect of this traditional Chinese medicine. These results show that liquid chromatography/mass spectrometry-based quantitative metabolic profiling method is a useful tool to investigate the metabolic changes in depression and the anti-depressive effect of traditional Chinese medicine.
    Journal of pharmaceutical and biomedical analysis 11/2013; 89C:122-129. DOI:10.1016/j.jpba.2013.10.045 · 2.83 Impact Factor
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    ABSTRACT: Sphingolipids are a family of bioactive molecules with high structural diversity and complexity. They not only serve as integral components of cellular membrane, but also play pivotal roles in signaling and other cellular events. It is desirable for the development of sensitive, robust and structural-specific analytical approaches enabling rapid determination of as many sphingolipid species as possible. Herein we present an analytical method for large-scaled profiling of sphigolipids in human serum, which consisted of an improved extraction protocol using tert-butyl methyl ether combined with mild alkaline hydrolysis, and an ultra high performance reversed-phase liquid chromatography-dynamic multiple reaction monitoring-mass spectrometric (RPLC-dynamic MRM-MS) method. In total 84 endogenous sphingolipid species covering six subcategories (i.e. free sphingoid base, dihydroceramide, ceramide, hexosylceramide, lactosylceramide, and sphingomyelin), were separated and quantified in a single run within 10min. A broad linear range over 2.5-4 orders of magnitude (r(2)>0.99), a limit of detection of 0.01-0.17pmol/mL, and a limit of quantitation of 0.02-0.42pmol/mL were obtained for each subcategory. Average recovery of each subcategory was within 85.6-95.6%. Median values of coefficient of variation (CV) of all detected 84 sphingolipids were 3.9% and 6.8% for intraday and interday precision, respectively. This method was exemplarily applied in a study regarding dysregulated sphingolipid homeostasis in hepatocellular carcinoma. The establishment of this method provides a useful tool for serum-based high throughput screening of sphingolipid biomarkers and mechanism investigation of sphingolipid metabolic regulation in human disease.
    Journal of Chromatography A 10/2013; 1320. DOI:10.1016/j.chroma.2013.10.064 · 4.26 Impact Factor
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    ABSTRACT: A novel strategy was developed to assess the quality of TCM (traditional Chinese medicine) based on the correlation analysis of the chemical fingerprint and biological effect. Using Rehmanniae glutinosa (RG) to treat the kidney yin deficiency as an example, chemical fingerprints of 27 RG samples were analyzed by liquid chromatography-mass spectrometry (LC-MS), and urinary metabolic profiling of RG treatment of kidney yin deficiency in rats was explored by using LC-MS. A correlation analysis between the chemical fingerprints and efficacy evaluation was developed to identify quality marker components to assess TCM quality. Thirty-four variables in chemical fingerprints were successfully defined to have a close relationship with the efficacy of RG. The validation test with a new RG sample indicated that these efficacy-related components could be used to evaluate the integral quality of RG accurately. Compared with conventional chemical fingerprint methodology, not only is the proposed approach a powerful tool to identify efficacy-related components for the quality evaluation of TCM, but the approach can also be used to predict the therapeutic efficacy of TCMs.
    Journal of pharmaceutical and biomedical analysis 05/2013; 83C:57-64. DOI:10.1016/j.jpba.2013.04.035 · 2.83 Impact Factor
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    ABSTRACT: Steroid hormones are crucial substances that mediate a wide range of vital physiological functions of the body. Determination of the levels of steroid hormones plays an important role in understanding the mechanism of the steroid hormone-related diseases. In this study, we present a novel targeted metabolic profiling method based on the introduction of an easily protonated stable isotope tag to a hydroxyl-containing steroid hormone with a synthesized derivatization reagent, deuterium 4-(dimethylamino)-benzoic acid (d4-DMBA), and liquid chromatography mass spectrometry. Different from other reported derivatization reagents that have been used to enhance the sensitivities for estrogens or androgens, our method is comprehensive with the capability of covering hydroxyl-containing androgens, estrogens, corticoids and progestogens. Furthermore, the non-derivatized steroid hormones (e.g., 17α-hydroxyprogesterone, progesterone and androstenedion) were not destroyed during the derivatization process, and their levels could still be obtained in one LC-MS run. We were able to detect 24 steroid hormones at sub-ng/mL levels (the lower limit of detection could reach 5 pg/mL for estrone and 16α-hydroxy estrone, which is equivalent to 0.1 pg on column) with maximum sensitivity enhancement factors of more than 103- to 104-fold after derivatization. The method was successfully applied to the measurement of free (unconjugated) steroid hormones in urine samples of males, females and pregnant women. Because the significant role of steroid hormone pathway plays in humans, a comprehensive, sensitive, specific and accurate method for profiling the steroid hormone metabolome shall offer new insights into hormone-related diseases.
    Analytical Chemistry 10/2012; 84(23). DOI:10.1021/ac301984t · 5.83 Impact Factor
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    ABSTRACT: Objective The aim is to characterize subgroups or phenotypes of rheumatoid arthritis (RA) patients using a systems biology approach. The discovery of subtypes of rheumatoid arthritis patients is an essential research area for the improvement of response to therapy and the development of personalized medicine strategies. Methods In this study, 39 RA patients are phenotyped using clinical chemistry measurements, urine and plasma metabolomics analysis and symptom profiles. In addition, a Chinese medicine expert classified each RA patient as a Cold or Heat type according to Chinese medicine theory. Multivariate data analysis techniques are employed to detect and validate biochemical and symptom relationships with the classification. Results The questionnaire items ‘Red joints’, ‘Swollen joints’, ‘Warm joints’ suggest differences in the level of inflammation between the groups although c-reactive protein (CRP) and rheumatoid factor (RHF) levels were equal. Multivariate analysis of the urine metabolomics data revealed that the levels of 11 acylcarnitines were lower in the Cold RA than in the Heat RA patients, suggesting differences in muscle breakdown. Additionally, higher dehydroepiandrosterone sulfate (DHEAS) levels in Heat patients compared to Cold patients were found suggesting that the Cold RA group has a more suppressed hypothalamic-pituitary-adrenal (HPA) axis function. Conclusion Significant and relevant biochemical differences are found between Cold and Heat RA patients. Differences in immune function, HPA axis involvement and muscle breakdown point towards opportunities to tailor disease management strategies to each of the subgroups RA patient.
    PLoS ONE 09/2012; 7(9). DOI:10.1371/journal.pone.0044331 · 3.53 Impact Factor
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    ABSTRACT: Excess fatigue is a pathological state of continuing accumulation of fatigue, which may cause the deterioration of body health, occurrence of diseases, and even lead to death. A metabonomics study was performed on the excess fatigue rats treated with traditional Chinese medicine Tongxinluo or ginseng based on ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC-IT-TOF-MS). The plasma metabolic profiling data of the control rats, excess fatigue rats, and excess fatigue rats treated with Tongxinluo or ginseng were acquired. The orthogonal partial least squares analysis (OPLS) was applied for the multivariate statistics and the discovery of important differential metabolites distinguishing the excess fatigue rats treated with Tongxinluo or ginseng from the control rats and excess fatigue rats. The results showed tryptophan, bile acid, lysophosphatidylcholine metabolism were disturbed in the excess fatigue rats. The metabolic pattern including the related metabolic pathways of the rats, being treated with Tongxinluo or ginseng, was adjusted towards the normal state.
    Se pu = Chinese journal of chromatography / Zhongguo hua xue hui 11/2011; 29(11):1049-54.
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    ABSTRACT: A urinary metabonomic method based on ultra-fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC/MS-IT-TOF) was employed to study the preventive efficacy and the metabolic changes caused by simavastatin and the traditional Chinese medicine tongxinluo in endothelial dysfunction rats. Principal component analysis (PCA) was applied to study metabolic patterns of endothelial dysfunction rats and healthy control rats. 1-Methyladenosine, indoxyl sulfate, hippuric acid, riboflavin, coproporphyrin, and p-cresol glucuronide were identified as potential biomarkers, indicating that pathways of adenine, tryptophan, phenylalanine, riboflavin and porphyrin metabolism were disturbed in endothelial dysfunction rats. Applications of simvastatin and tongxinluo to endothelial dysfunction rats improved endothelial function according to the results of histopathology and measurements of endothelin-1 and nitric oxide. Metabonomic studies suggested that tongxinluo prevents endothelial dysfunction by regulating multiple metabolic pathways to their normal state, whereas simvastatin only altered selected metabolic pathways. This research demonstrated that metabonomics is a powerful and promising tool for disease investigation and the efficacy evaluation of complex traditional Chinese medicines.
    Journal of pharmaceutical and biomedical analysis 08/2011; 56(1):86-92. DOI:10.1016/j.jpba.2011.04.020 · 2.83 Impact Factor

Publication Stats

55 Citations
43.16 Total Impact Points


  • 2011–2014
    • Dalian Institute of Chemical Physics
      Lü-ta-shih, Liaoning, China
  • 2012
    • Chinese Academy of Sciences
      • Laboratory of Analytical Chemistry for Life Science
      Peping, Beijing, China