MSE with mass defect filtering for in vitro and in vivo metabolite identification

Bateman, Kevin P.; Castro-Perez, José; Wrona, Mark; Shockcor, John P.; Yu, Kate; Oballa, Renata M.; Nicoll‐Griffith, Deborah A.

doi:10.1002/rcm.2996

Cited by 242 publications

(186 citation statements)

References 20 publications

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Section: Mass Detection Conditionsmentioning

confidence: 94%

“…The mass detection conditions were optimized according to our previous work . The precision and reproducibility of peak integration was good for the final results and the ability to collect the MS and MS/MS data in one analytical run was clearly demonstrated (Kevin et al 2007) and the sampling rate is sufficient to provide an accurate representation of the chromatographic separation.The accurate mass measurement and MS/MS analysis of saponins in this study was performed at different collision energies ranging from 5 to 40 eV with MS E (E represents low-high collision energy) approach ) in order to provide sufficient information necessary to distinguish saponins with the same molecular weight, accurate MS and available standards were used to verify these important marker ions. Mass measurement of the TOF mass spectrometer (Chan et al 2007) with a group of known low-molecule-weight (between 100 and 1,500 m/z) compounds was determined according to our previous work .…”

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confidence: 94%

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Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal Panax herbs

Xie

Ming

et al. 2008

Metabolomics

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Abstract:The morphological appearance and some ingredients of Panax ginseng, Panax notoginseng and Panax japonicus of the Panax genus are similar. However, their pharmacological activities are obviously different due to the significant differences in the types and quantity of saponins in each herb. In the present study, ultra-performance liquid chromatography-quadrupole time-offlight mass spectrometry (UPLC-QTOFMS) was used to profile the abundances of metabolites in the three medicinal Panax herbs. Multivariate statistical analysis technique, that is, principle component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discriminate between the Panax samples. PCA of the analytical data showed a clear separation of compositions among the three medicinal herbs. The critical markers such as chikusetsusaponin IVa, ginsenoside R0, ginsenoside Rc, ginsenoside Rb1, ginsenoside Rb2 and ginsenoside Rg2 accountable for such variations were identified through the corresponding loading weights, and the tentative identification of biomarkers is completed by the accurate mass of TOFMS and high resolution and high retention time reproducibility performed by UPLC. The proposed analytical method coupled with multivariate statistical analysis is reliable to analyze a group of metabolites present in the herbal extracts and other natural products. This method can be further utilized to evaluate chemical components obtained from different plants and/or the plants of different geographical locations, thereby classifying the medicinal plant resources and potentially elucidating the mechanism of inherent phytochemical diversity. Article:INTRODUCTION It is estimated that about 65-80% of the world's population is using traditional medicine as the primary form of healthcare (Akerele 1992). Traditional Chinese medicines (TCMs) are gaining more and more attention in many fields because of their low toxicity and good therapeutic performance. The quality and contents of herbs are highly variable depending on geographical origins, climate, cultivation, and the growth stage when harvested (Mahady et al. 2001). The profiling of natural products requires an analytical system capable of generating an information rich data set and needs to identify the compounds of interest, compare different batches of material to be compared and contrasted and isolate the compounds of interest from bulk solution. However, because of the chemical diversity of the metabolome, which for any given multicellular species comprises a mixture of thousands of compounds differing in size, polarity etc., and varying in abundance by several orders of magnitude, the need for multiparallel analytical techniques is obvious and well-accepted (Goodacre et al. 2004;Hall 2006). A number of techniques including nuclear magnetic resonance (NMR), liquid chromatography (LC) or gas chromatography (GC) coupled with mass spectrometry (MS) have been employed for metabolite profiling (Fiehn et al. 2000;Want et al. 2005;Fukusaki et al. 2006;Nordstrom et al...

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Section: Mass Detection Conditionsmentioning

confidence: 94%

mentioning

confidence: 94%

Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal Panax herbs

Xie

Ming

et al. 2008

Metabolomics

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“…In this way, two mass chromatograms are generated, one with information on the intact molecules from the first function, and the other with the fragmented ion information from the second function. A variety of data-processing algorithms can be used to extract metabolite information from these data [12,13]. In other words, MS E can provide parallel alternating scans for acquisition at either low collision energies to obtain precursor ion information or high collision energies to obtain full-scan accurate mass fragment, precursor ion, and small neutral molecules.…”

Section: Uplc-ms Techniquementioning

confidence: 99%

UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry

Zhao

Cheng

Vaziri

et al. 2014

Clinical Biochemistry

118

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a b s t r a c t a r t i c l e i n f oObjectives: Metabonomics is a powerful and promising analytic tool that allows assessment of global lowmolecular-weight metabolites in biological systems. It has a great potential for identifying useful biomarkers for early diagnosis, prognosis and assessment of therapeutic interventions in clinical practice. The aim of this review is to provide a brief summary of the recent advances in UPLC-based metabonomic approach for biomarker discovery in a variety of diseases, and to discuss their significance in clinical chemistry.Design and methods: All the available information on UPLC-based metabonomic applications for discovering biomarkers of diseases were collected via a library and electronic search (using Web of Science, Pubmed, ScienceDirect, Springer, Google Scholar, etc.).Results: Metabonomics has been used in clinical chemistry to identify and evaluate potential biomarkers and therapeutic targets in various diseases affecting the liver (hepatocarcinoma and liver cirrhosis), lung (lung cancer and pneumonia), gastrointestinal tract (colorectal cancer) and urogenital tract (prostate cancer, ovarian cancer and chronic kidney disease), as well as metabolic diseases (diabetes) and neuropsychiatric disorders (Alzheimer's disease and schizophrenia), etc.Conclusions: The information provided highlights the potential value of determination of endogenous lowmolecular-weight metabolites and the advantages and potential drawbacks of the application of UPLC-based metabonomics in clinical setting.

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“…The collision energy ramp causes fragmentation of molecules as they pass the collision cell. The MS E mode provides precursor and product ion information for every detectable component in the mixture (Bateman et al 2007). Leucine enkephalin ([M + H] + 556.2771) was utilized for lock mass correction.…”

Section: Uplc-esi-qtof-ms Analysismentioning

confidence: 99%

Chronic caloric restriction partially protects against age-related alteration in serum metabolome

Guzman

Fahey

et al. 2012

AGE

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Calorie restriction (CR) remains the most robust metabolic intervention to extend lifespan and improve healthspan in several species. Using global and targeted mass spectrometry-based metabolomics approaches, here we show that chronic CR prevents age-related changes in specific metabolic signatures. Global metabolomic analysis using ultra-performance liquid chromatography-tandem mass spectrometry detected more than 7,000 metabolites in sera from ad-libitum-fed young, aged, and aged C57BL/6 mice maintained on 40 % CR. Multivariate statistical analysis of mass spectrometry data revealed a clear separation among the young, aged, and aged-CR mice demonstrating the potential of this approach for producing reliable metabolic profiles that discriminate based on age and diet. We have identified 168 discriminating features with high statistical significance (p≤0.001) and validated and quantified three of these metabolites using targeted metabolite analysis. Calorie restriction prevented the age-related alteration in specific metabolites, namely lysophosphatidylcholines (16:1 and 18:4), sphingomyelin (d18:1/12:0), tetracosahexaenoic acid, and 7α-dihydroxy-4-cholesten-3-one, in the serum. Pathway analysis revealed that CR impacted the age-related changes in metabolic byproducts of lipid metabolism, fatty acid metabolism, and bile acid biosynthesis. Our data suggest that metabolomics approach has the potential to elucidate the metabolic mechanism of CR's potential anti-aging effects in larger-scale investigations.

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MS^E with mass defect filtering for in vitro and in vivo metabolite identification

Cited by 242 publications

References 20 publications

Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal Panax herbs

Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal Panax herbs

UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry

Chronic caloric restriction partially protects against age-related alteration in serum metabolome

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