scholarly journals Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Beibei Ma ◽  
Jiameng Li ◽  
Tianyu Lou ◽  
Yaoyue Liang ◽  
Chenxiao Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Neutral Loss ◽  
Negative Ion ◽  
Chromatographic Retention ◽  
Data Sets ◽  
Screening And Identification ◽  
Q Exactive ◽  
Novel Strategy

Phillyrin, a well-known bisepoxylignan, has been shown to have many critical pharmacological activities. In this study, a novel strategy for the extensive acquisition and use of data was established based on UHPLC-Q-Exactive mass spectrometry to analyze and identify the in vivo metabolites of phillyrin and to elucidate the in vivo metabolic pathways of phillyrin. Among them, the generation of data sets was mainly due to multichannel data mining methods, such as high extracted ion chromatogram (HEIC), diagnostic product ion (DPI), and neutral loss filtering (NLF). A total of 60 metabolites (including the prototype compound) were identified in positive and negative ion modes based on intuitive and useful data such as the standard’s cleavage rule, accurate molecular mass, and chromatographic retention time. The results showed that a series of biological reactions of phillyrin in vivo mainly included methylation, hydroxylation, hydrogenation, sulfonation, glucuronidation, demethylation, and dehydrogenation and their composite reactions. In summary, this study not only comprehensively explained the in vivo metabolism of phillyrin, but also proposed an effective strategy to quickly analyze and identify the metabolites of natural pharmaceutical ingredients in nature.

scholarly journals A Comprehensive Screening and Identification of Genistin Metabolites in Rats Based on Multiple Metabolite Templates Combined with UHPLC-HRMS Analysis

Molecules ◽  
2018 ◽  
Vol 23 (8) ◽  
pp. 1862 ◽  
Author(s):  
Yaoyue Liang ◽  
Wenjing Zhao ◽  
Chenxiao Wang ◽  
Zijian Wang ◽  
Zhibin Wang ◽  
...  
Keyword(s):  
Neutral Loss ◽  
Negative Ion ◽  
Ring Cleavage ◽  
Therapeutic Effects ◽  
Data Sets ◽  
Orbitrap Mass Spectrometer ◽  
Product Ions ◽  
Screening And Identification ◽  
Acquisition Method

Genistin, an isoflavone belonging to the phytoestrogen family, has been reported to possess various therapeutic effects. In the present study, the genistin metabolites in rats were investigated by UHPLC-LTQ-Orbitrap mass spectrometer in both positive and negative ion modes. Firstly, the data sets were obtained based on data-dependent acquisition method and then 10 metabolite templates were established based on the previous reports. Then diagnostic product ions (DPIs) and neutral loss fragments (NLFs) were proposed to efficiently screen and ascertain the major-to-trace genistin metabolites. Meanwhile, the calculated Clog P values were used to identify the positional isomers with different retention times. Consequently, a total of 64 metabolites, including prototype drug, were positively or putatively characterized. Among them, 40 metabolites were found according to the templates of genistin and genistein, which was the same as the previous research method. After using other metabolite templates, 24 metabolites were added. The results demonstrated that genistin mainly underwent methylation, hydrogenation, hydroxylation, glucosylation, glucuronidation, sulfonation, acetylation, ring-cleavage and their composite reactions in vivo biotransformation. In conclusion, the research not only revealed the genistein metabolites and metabolic pathways in vivo comprehensively, but also proposed a method based on multiple metabolite templates to screen and identify metabolites of other natural compounds.

Detection and identification of Catalpol metabolites in the rat plasma, urine and faeces using ultra-high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry

2020 ◽  
Vol 21 ◽  
Author(s):  
Zedong Xiang ◽  
Shaoping Wang ◽  
Haoran Li ◽  
Pingping Dong ◽  
Fan Dong ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
High Performance ◽  
Mass Measurement ◽  
Neutral Loss ◽  
Rat Plasma ◽  
Accurate Mass ◽  
Chromatographic Retention ◽  
Rat Urine ◽  
Q Exactive

Background:: Catalpol, an iridoid glycoside, is one of the richest bioactive components present in Rehmannia glutinosa. More and more metabolites of drugs have exhibit various pharmacological effects, thus providing guidance for clinical application. However, few researches have paid attention on the metabolism of catalpol. Objective:: This study aimed to establish a rapid and effective method to identify catalpol metabolites and evaluate the biotransformation pathways of catalpol in rats. Methods:: In this study, catalpol metabolites in rat urine, plasma and faeces were analyzed by UHPLC-Q-Exactive MS for the characterization of metabolism of catalpol. Based on high-resolution extracted ion chromatograms (HREICs) and parallel reaction monitoring mode (PRM), metabolites of catalpol were identified by comparing the diagnostic product ions (DPIs), chromatographic retention times, neutral loss fragments (NLFs) and accurate mass measurement with those of catalpol reference standard. Results: A total of 29 catalpol metabolites were detected and identified in both negative and positive ion modes. Nine metabolic reactions including deglycosylation, hydroxylation, dihydroxylation, hydrogenation, dehydrogenation, oxidation of methylene to ketone, glucuronidation, glycine conjugation and cysteine conjugation were proposed. Conclusion:: A rapid and effective method based on UHPLC-Q-Exactive MS was developed to mine the metabolism information of catalpol. Results of metabolites and biotransformation pathways of catalpol suggested that when orally administrated, catalpol was firstly metabolized into catalpol aglycone, after which phase Ⅰ and phase Ⅱ reactions occurred. However, hydrophilic chromatography-mass spectrometry still needed to further find the polar metabolites of catalpol.

Comprehensive and Rapid Identification of Astilbin Metabolites in Rats Based on Multiple Metabolite Templates Combined with UHPLC-Q-ExactiveMass Spectrometry

2021 ◽  
Vol 22 ◽  
Author(s):  
Shan Jiang ◽  
Haoran Li ◽  
Ailin Yang ◽  
Hongbing Zhang ◽  
Pingping Dong ◽  
...  
Keyword(s):  
Mass Spectrometer ◽  
Biological Effects ◽  
Rat Plasma ◽  
Rapid Identification ◽  
Negative Ion ◽  
Ring Cleavage ◽  
Rat Urine ◽  
Q Exactive ◽  
Negative Ion Mode

Background : Astilbin, a dihydroflavonoid compound widely found in plants, exhibits a variety of pharmacological activities and biological effects. However, little is known about the metabolism of this active compound in vivo, which is very helpful for elucidating the pharmacodynamic material basis and application of astilbin. Objective: To establish a rapid profiling and identification method for metabolites in rat urine, faeces and plasma using a UHPLC-Q-Exactive mass spectrometer in negative ion mode. Methods: In this study, a simple and rapid systematic strategy and 7 metabolite templates, which were established based on previous reports, were utilized to screen and identify astilbin metabolites. Results: As a result, a total of 72 metabolites were detected and characterized, among which 33 metabolites were found in rat urine, while 28 and 38 metabolites were characterized from rat plasma and faeces, respectively. These metabolites were presumed to be generated through ring cleavage, sulfation, dehydrogenation, methylation, hydroxylation, glucuronidation, dehydroxylation and their composite reactions. Conclusion: This study illustrated the capacity of the sensitive UHPLC-Q-Exactive mass spectrometer analytical system combined with the data-mining methods to rapidly elucidate the unknown metabolism. Moreover, the comprehensive metabolism study of astilbin provided an overall metabolic profile, which will be of great help in predicting the in vivo pharmacokinetic profiles and understanding the action mechanism of this active ingredient.

scholarly journals Analytical Variables Affecting Analysis of F2-Isoprostanes and F4-Neuroprostanes in Human Cerebrospinal Fluid by Gas Chromatography/Mass Spectrometry

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Hsiu-Chuan Yen ◽  
Hsing-Ju Wei ◽  
Ting-Wei Chen
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Cerebrospinal Fluid ◽  
Chemical Ionization ◽  
Negative Ion ◽  
Gas Chromatography Mass Spectrometry ◽  
Ionization Mass ◽  
Negative Ion Chemical Ionization ◽  
Gold Marker

F2-isoprostanes (F2-IsoPs) are a gold marker of lipid peroxidationin vivo, whereas F4-neuroprostanes (F4-NPs) measured in cerebrospinal fluid (CSF) or brain tissue selectively indicate neuronal oxidative damage. Gas chromatography/negative-ion chemical-ionization mass spectrometry (GC/NICI-MS) is the most sensitive and robust method for quantifying these compounds, which is essential for CSF samples because abundance of these compounds in CSF is very low. The present study revealed potential interferences on the analysis of F2-IsoPs and F4-NPs in CSF by GC/NICI-MS due to the use of improper analytical methods that have been employed in the literature. First, simultaneous quantification of F2-IsoPs and F4-NPs in CSF samples processed for F4-NPs analysis could cause poor chromatographic separation and falsely higher F2-IsoPs values for CSF samples with high levels of F2-IsoPs and F4-NPs. Second, retention of unknown substances in GC columns from CSF samples during F4-NPs analysis and from plasma samples during F2-IsoPs analysis might interfere with F4-NPs analysis of subsequent runs, which could be solved by holding columns at a high temperature for a period of time after data acquisition. Therefore, these special issues should be taken into consideration when performing analysis of F2-IsoPs and F4-NPs in CSF to avoid misleading results.

scholarly journals Chemical Constituent Profiling of Paecilomyces cicadae Liquid Fermentation for Astragli Radix

Molecules ◽  
2019 ◽  
Vol 24 (16) ◽  
pp. 2948 ◽  
Author(s):  
Wang ◽  
Mei ◽  
Liu ◽  
Li ◽  
Zhang ◽  
...  
Keyword(s):  
Chemical Interaction ◽  
Chemical Constituents ◽  
Neutral Loss ◽  
Chemical Constituent ◽  
Negative Ion ◽  
Chemical Components ◽  
Data Sets ◽  
Bioactive Constituents ◽  
Fermentation Liquid ◽  
Product Ions

Astragli Radix (AR) is one of the most popular traditional Chinese medicines with chemical constituents including flavonoids and saponins. As recently evidenced, some fungi or their fermentation liquid may have the potential to affect the bioactive constituents and different pharmacological effects of AR. Thus, the composition of fermented AR (FAR) produced by Paecilomyces cicadae (Miquel) Samson in liquid-state fermentation was investigated using a UHPLC-LTQ-Orbitrap mass spectrometer in both positive and negative ion modes. Firstly, the MSn data sets were obtained based on a data-dependent acquisition method and a full scan–parent ions list–dynamic exclusion (FS-PIL-DE) strategy. Then, diagnostic product ions (DPIs) and neutral loss fragments (NLFs) were proposed for better constituent detection and structural characterization. Consequently, 107 constituents in total, particularly microconstituents in FAR and AR, were characterized and compared in parallel on the same LTQ–Orbitrap instrument. Our results indicated that AR fermentation with Paecilomyces significantly influenced the production of saponins and flavonoids, especially increasing the content of astragaloside IV. In conclusion, this research was not only the first to show changes in the chemical components of unfermented AR and FAR, but it also provides a foundation for further studies on the chemical interaction between microbiota and AR.

scholarly journals Rapid screening and characterization of caffeic acid metabolites in rats by UHPLC-Q-TOF mass spectrometry

2022 ◽  
Vol 20 (2) ◽  
pp. 389-401
Author(s):  
Jiaqi Yuan ◽  
Yunting Wang ◽  
Shengquan Mi ◽  
Jiayu Zhang ◽  
Yaxuan Sun
Keyword(s):  
Mass Spectrometry ◽  
Caffeic Acid ◽  
Biological Samples ◽  
Solid Phase ◽  
Biological Activities ◽  
Negative Ion ◽  
Rapid Screening ◽  
Sprague Dawley ◽  
Acid Metabolites

Purpose: To determine the metabolism of caffeic acid in rats. Methods: Sprague-Dawley rats were intragastrically administered caffeic acid in saline suspension, and biological samples collected. After sample pretreatment by solid phase extraction, ultra-high performance liquid chromatography combined with quadrupole-time of flight mass spectrometry system (UHPLC-Q-TOF-MS/MS) was established to rapidly screen and characterize caffeic acid metabolites in rats. Waters HSS T3 UPLC chromatographic column (2.1 mm × 100 mm, 1.7 μm) was applied for the gradient elution with aqueous solution of formic acid (A)-acetonitrile (B). Mass spectral data for the biological samples in electrospray positive and negative ion modes were collected and analyzed by SCIEX OS 1.3 workstation. Results: Based on their precise molecular weights and multistage mass spectrometry cleavage information, caffeic acid and 21 metabolites in vivo were identified. The results demonstrate that the biotransformation of caffeic acid in vivo was mainly achieved via hydrogenation, hydroxylation, methylation, sulfonation, glucuronidation, acetylation, and composite reactions. Conclusion: The metabolites and metabolic pathways of caffeic acid in rats have been rapidly elucidated, and its potential pharmacodynamics forms have been clarified. This provides a valuable and meaningful reference for the study of caffeic acid metabolites, biological activities, and its medicinal material basis in vivo.

scholarly journals Data mining in mass spectrometry-based proteomics studies

2020 ◽  
Vol 2 (4) ◽  
pp. 258-276
Author(s):  
Vu Anh Le ◽  
Cam Quyen Thi Phan ◽  
Thuy Huong Nguyen
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Biomedical Research ◽  
Protein Level ◽  
Protein Identification ◽  
Biomarker Discovery ◽  
Data Sets ◽  
Biological Processes ◽  
Data Mining Techniques ◽  
Analytical Technique

The post-genomic era consists of experimental and computational efforts to meet the challenge of clarifying and understanding the function of genes and their products. Proteomic studies play a key role in this endeavour by complementing other functional genomics approaches, encompasses the large-scale analysis of complex mixtures, including the identification and quantification of proteins expressed under different conditions, the determination of their properties, modifications and functions. Understanding how biological processes are regulated at the protein level is crucial to understanding the molecular basis of diseases and often highlights the prevention, diagnosis and treatment of diseases. High-throughput technologies are widely used in proteomics to perform the analysis of thousands of proteins. Specifically, mass spectrometry (MS) is an analytical technique for characterizing biological samples and is increasingly used in protein studies because of its targeted, nontargeted, and high performance abilities. However, as large data sets are created, computational methods such as data mining techniques are required to analyze and interpret the relevant data. More specifically, the application of data mining techniques in large proteomic data sets can assist in many interpretations of data; it can reveal protein-protein interactions, improve protein identification, evaluate the experimental methods used and facilitate the diagnosis and biomarker discovery. With the rapid advances in mass spectrometry devices and experimental methodologies, MS-based proteomics has become a reliable and necessary tool for elucidating biological processes at the protein level. Over the past decade, we have witnessed a great expansion of our knowledge of human diseases with the adoption of proteomic technologies based on MS, which leads to many interesting discoveries. Here, we review recent advances of data mining in MS-based proteomics in biomedical research. Recent research in many fields shows that proteomics goes beyond the simple classification of proteins in biological systems and finally reaches its initial potential – as an essential tool to aid related disciplines, notably biomedical research. From here, there is great potential for data mining in MS-based proteomics to move beyond basic research, into clinical research and diagnostics.

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