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Neurotransmitters (NTs) and their metabolites play crucial roles in the regulation of the sleep-wake cycle. Thus, a comprehensive quantitative analysis of NTs would be useful in elucidating the potential mechanisms involved in sedative-hypnotic activities. In this study, we developed a high-throughput quantitative method based on a two-dimensional chromatography-mass spectrometry technique to simultaneously analyze 63 NTs and their metabolites in rat plasma, brain homogenate, and microdialysis samples from five different sleep-associated regions of the brain. Moreover, this method was used to study the neurochemical mechanism of an adenosine analog sedative-hypnotic candidate YZG-331. Most of the correlations between NTs were lost after the administration of the sedative, particularly in the caudate putamen (CPu) and dorsal raphe nucleus (DRN), indicating that the sleep-wake balance was affected. Administration of the adenosine analog YZG-331 could act similar as accumulation of adenosine, inducing adenosine and its metabolite adenine were decreased significantly in the CPu, accompanying with GABA, aspartate, and glutamate changed slightly by the communications between different neurons to further promote sleep. In addition, YZG-331 affected the metabolism of tryptophan and serotonin (5-HT) in the DRN and orbital frontal cortex (OFC). Melatonin and 5-hydroxyindole-3-acetic acid (a metabolite of 5-HT) were significantly increased in the OFC, and the levels of glutamate/glutamine, asparagine, and adrenaline were altered. Sleep homeostasis is a balance between the duration of sleep and wakefulness and is coordinated by all NTs. The high-throughput quantitative method introduced in this study may aid in revealing the temporal cohesion among NTs, evaluating sleep homeostasis, and determining the effects of sedative-hypnotic drugs., (Copyright © 2022. Published by Elsevier B.V.)

A simple and sensitive liquid chromatography/electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) method was developed and validated for determination of two highly lipophilic anticancer drug candidates, LG1980 and GH501, in rat plasma and tissues (liver, kidney and femur bones). LG1980 and GH501 were extracted from rat plasma and tissue homogenates using liquid-liquid extraction. The method provided a linear range of 1.0-200.0 ng/mL for GH501 in plasma and LG1980 in plasma and liver. For both analytes in other tissue homogenates the linear range was 2.0-400.0 ng/mL. The method was validated with precision within 15% relative standard deviation, accuracy within 15% relative error and a consistent recovery. This method has been successfully applied in two preclinical studies for LG1980 and GH501 to determine their concentrations in rat plasma, liver, kidney and bone over 24 h after intravenous injection of compounds., (Copyright © 2017 John Wiley & Sons, Ltd.)

Aim: In metabolomics research, the use of different blood collection methods may influence endogenous metabolites., Materials & Methods: Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants., Results: Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.

Rationale: Acquiring global information on plasma-endogenous metabolites challenges metabolomics. This study has been designed to investigate the suitability of integrated ionization rapid-resolution liquid chromatography/tandem mass spectrometry (RRLC/MS/MS) for different kinds of metabolites in complex plasma, and provides an approach for plasma metabolomics in acquiring more comprehensive data of metabolites., Methods: Integrated ionization of electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) combined with RRLC/MS/MS has been carried out to perform analysis on the global plasma metabolome of healthy volunteers. The contributions to the total numbers of ion features by RRLC/MS with ESI, APCI, and APPI in positive and negative ion modes were calculated. Representative unique and identical ions were identified. The intensities of identical ions were compared., Results: Each of ESI, APCI, and APPI coupled with RRLC/MS has its own advantage over the other two techniques for certain types of metabolites in plasma. LC/ESI-MS is very sensitive for detecting glycerophosphocholines, glycerophosphoethanolamines, acyl carnitines, bile acids, sulfate, etc. LC/APCI-MS is suitable for analyzing cyclic alcohols, fatty acids, and linoleic acids. LC/APPI-MS proves to be appropriate in detecting steroids, sphingolipids, some amino acids, nucleosides, and purines in plasma., Conclusions: It is suggested that the integrated ionization LC/MS approach should be applied for global plasma metabolomics. Moreover, the results obtained demonstrate that it is preferable to choose certain techniques from LC/ESI-MS, LC/APCI-MS, and LC/APPI-MS for metabolite target analysis., (Copyright © 2013 John Wiley & Sons, Ltd.)

A metabolomics strategy based on rapid resolution liquid chromatography/tandem mass spectrometry (RRLC-MS/MS) and multivariate statistics has been implemented to identify potential biomarkers in uterine cervix cancer. Due to the importance of the data pre-processing method, three popular software packages have been compared. Then they have been used to acquire respective data matrices from the same LC-MS/MS data. Multivariate statistics was subsequently used to identify significantly changed biomarkers for uterine cervix cancer from the resulting data matrices. The reliabilities of the identified discriminated metabolites have been further validated on the basis of manually extracted data and ROC curves. Nine potential biomarkers have been identified as having a close relationship with uterine cervix cancer. Considering these in combination as a biomarker group, the AUC amounted to 0.997, with a sensitivity of 92.9% and a specificity of 95.6%. The prediction accuracy was 96.6%. Among these potential biomarkers, the amounts of four purine derivatives were greatly decreased, which might be related to a P2 receptor that might lead to a decrease in cell number through apoptosis. Moreover, only two of them were identified simultaneously by all of the pre-processing tools. The results have demonstrated that the data pre-processing method could seriously bias the metabolomics results. Therefore, application of two or more data pre-processing methods would reveal a more comprehensive set of potential biomarkers in non-targeted metabolomics, before a further validation with LC-MS/MS based targeted metabolomics in MRM mode could be conducted.

Metabonomics is an important platform for investigating the metabolites of integrated living systems and their dynamic responses to changes caused by both endogenous and exogenous factors. A metabonomics strategy based on liquid chromatography-mass spectrometry/mass spectrometry in both positive and negative ion modes was applied to investigate the short-term and long-term stability of metabolites in plasma. Principal components analysis and ten types of identified metabolites were used to summarize the time-dependent change rules in metabolites systematically at different temperatures. The long-term stability of metabolites in plasma specimens stored at -80 °C for five years was also studied. Analysis of these subjects identified 36 metabolites with statistically significant changes in expression (p < 0.05) and found a kind of metabolite with a hundred-fold change. The stability of metabolites in blood at 4 °C for 24 h was also investigated. These studies show that a thorough understanding of the effects of metabolite stability are necessary for improving the reliability of potential biomarkers.

An integrated approach combining data acquisition using MS(E) and multi-period product ion scan (mpMS/MS), with high-resolution characteristic extracted ion chromatograms (hcXIC) as a data mining method, was developed for in vivo drug metabolites screening and identification. This approach is illustrated by analyzing metabolites of a potential anticancer agent, 3,6,7-trimethoxyphenanthroindolizidine (CAT) in rat urine based on rapid resolution liquid chromatography combined with tandem mass spectrometry (RRLC-MS/MS). Untargeted full-scan MS(E) enabled the high-throughput acquisition of potential metabolites, and targeted mpMS/MS contributed to the sensitivity and specificity of the acquisition of molecules of interest. The data processing method hcXIC, based on the structure of CAT, was shown to be highly effective for the metabolite discovery. Through the double-filtering effect of the characteristic ion and accurate mass, conventional extracted ion chromatograms that contained a substantial number of false-positive peaks were simplified into chromatograms essentially free of endogenous interferences. As a result, 21 metabolites were detected in rat urine after oral administration of CAT. Based on the characteristic fragmentation patterns of the phenanthroindolizidine alkaloid, the structures of 9 metabolites were identified. Furthermore, the interpretation of the MS/MS spectra of these metabolites enabled the determination of demethylation position as well as the differentiation between N-oxidized and hydroxylated metabolites., (Copyright © 2012 Elsevier B.V. All rights reserved.)

A rapid, sensitive, specific and accurate analytical method of ultra-fast liquid chromatography combined with tandem mass spectrometry (UFLC-MS/MS) was established for simultaneous quantitative analysis of 16 distinct endogenous estrogens and their metabolites (EMs) in postmenopausal female urine. The quantitative method utilized a hydrolysis/extraction/derivatization step and a UFLC system to achieve separation in 16 min. The lower limit of quantitation for each estrogen metabolite was 2 pg mL(-1) with the percent recovery of a known added amount of estrogen at 93.2-109.3%. The intra-batch accuracy and precision for all analytes were 87.5-107.7% and 0.6-11.7%, respectively, while inter-batch accuracy and precision were 87.0-105.8% and 1.2-10.2%, respectively. Using this developed and validated method, the comprehensive metabolic profiling of 16 EMs in urine samples of 86 postmenopausal female breast cancer patients and 36 healthy controls was investigated by systematic statistical analysis. As a result, the circulating levels of 6 EMs were found to be different by a comparison of patients and healthy controls. The parent estrogens, estrone (E1) and 17β-estradiol (E2), as well as 2-hydroxyestradiol (2-OHE2) and 4-hydroxyestradiol (4-OHE2) were produced in higher abundance, whereas 16α-hydroxyestrone (16α-OHE1) and 2-methoxyestradiol (2-MeOE2) were decreased in the breast cancer group. 2-OHE2 and 4-OHE2 in particular showed significant elevation in patients, which are consistent with the carcinogenic mechanism hypothesis that catechol estrogens can react with DNA via quinones, resulting in mutations to induce breast cancer. Thus, 2,4-hydroxylation may be the dominant metabolic pathway for parent estrogens rather than 16α-hydroxylation. The lower level of 2-MeOE2 in the breast cancer group was believed to correlate with its protective effect against tumor formation. This study could provide valuable information on the association of the EM metabolic pathway with carcinogenesis as well as identify potential biomarkers for estrogen-induced breast cancer risk., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Abstract Targeted quantification and untargeted global profiling are the two mainstream approaches, a merging of which could provide enhanced analytical potential in metabolomics research. Here, a simultaneous targeted quantification and untargeted metabolomics (STQUM) strategy was developed for more efficient, accurate and comprehensive metabolomics research by using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS). First, we selected 110 cancer-related metabolites as targets and established a dual LC sequential separation method for simultaneous analysis of strong and weak polar metabolites. In order to achieve efficient acquisition for synchronous qualitative and quantitative analysis, high-resolution, data-dependent parallel reaction monitoring (PRM) method and data-independent all ion fragmentation (AIF) method were established. Their performance in targeted confirmation and quantification, and untargeted analysis were systematically investigated and assessed. In total, 78 metabolites were confidently confirmed in positive ion mode in both PRM and AIF assays, in which 73 metabolites can be accurately quantified. In addition, simultaneously untargeted profiling of 4651 features of high reliability and validity were achieved. Both AIF and PRM methods revealed high confidence, sensitivity and accuracy. In the STQUM approach, another 15 metabolites could be accurately quantified in negative ion mode. The method offers a new perspective for merging the hypothesis-based targeted quantitative validation and untargeted biomarkers discovery in one run for improved analysis efficiency and integrity. Graphical abstract Image 1 Highlights • A simultaneous targeted quantification and untargeted metabolomics (STQUM) strategy based on dual LC-MS/MS was developed. • Efficient separation for both strong and weak polar metabolites was achieved in one injection. • PRM and AIF methods were respectively established and systematically evaluated. • The STQUM approach contributes to improved efficiency and comprehensiveness in metabolomics study. [ABSTRACT FROM AUTHOR]

Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications. [ABSTRACT FROM AUTHOR]

In the study, a simple and selective method based on magnetic separation technology is presented for the extraction of sulfonamides (SAs) from environmental water, followed by liquid chromatography-tandem mass spectrometry. In this method, magnetic surface molecularly imprinted polymers (FeO@SiO@MIPs) with super-paramagnetic property and high selectivity toward SAs were developed as magnetic adsorbents. The FeO@SiO@MIPs were then applied to the selective extraction of SAs from environmental water. The extraction and enrichment were accomplished simultaneously in a single step by simply stirring the mixture of adsorbents and water samples. The FeO@SiO@MIPs were characterized by scanning electron microscopy, Fourier-transform infrared spectrometry, and vibrating sample magnetometry. The adsorption thermodynamics and kinetics were employed to study the adsorption mechanism of the FeO@SiO@MIPs. And the matrix effect of the method was evaluated. Calibration curves obtained by analyzing matrix-matched standards show excellent linear relationship ( R = 0.9994-0.9999) in the concentration range of 10-1000 ng L, and the limits of detection are in the range of 1.4-2.8 ng L. The relative standard deviations of intra- and inter-day obtained are in the range of 2.8 to 7.8 and 3.1 to 7.9%, respectively . The proposed method was successfully applied to determine SAs in six environmental water samples, and SAs were detectable in four of them with the concentration from 10.5 to 120.2 ng L. [ABSTRACT FROM AUTHOR]

A simple and rapid method based on multi-throughput dynamic microwave-assisted extraction coupled online with salting-out-assisted liquid–liquid extraction was developed for the analysis of chlorpyrifos in soil. First, the chlorpyrifos was extracted with acetonitrile aqueous (50%, v/v) under the action of microwave energy. Then the obtained extract was separated clearly and easily into an acetonitrile phase and an aqueous phase with the assistance of ammonium acetate. The acetonitrile phase containing chlorpyrifos was concentrated and determined by liquid chromatography–tandem mass spectrometry. The effects of parameters on extraction efficiency including microwave power, extraction solvent, volumes and flow rate of extraction solvent, sample pH, types and amount of salt were studied and optimised. To eliminate the matrix effect, validation of the method was carried out using the matrix-based calibration curve. The limits of detection and quantification for chlorpyrifos were 0.17 and 0.5 ng g−1, respectively. The proposed method was applied to analyse chlorpyrifos in five soil samples and verified by the recovery test. The recoveries of chlorpyrifos at three spiked levels (5, 50, 200 ng g−1) were in the range of 90.0–100.5%, with relative standard deviations varying from 1.3% to 5.7%. Compared with the methods reported previously, the proposed method can simplify the operation procedure and reduce solvent consumption in sample pretreatment. [ABSTRACT FROM PUBLISHER]