Development of a mass spectrometry-based pseudotargeted metabolomics strategy to analyze hormone-stimulated gastric cancer cells

Li, Juan; Wang, Qingli; Zheng, Yi-Chao; Zhou, Piao; Xu, Xia; Liu, Xueqi; Zhao, Longfei; Liu, Hong‐Min

doi:10.1016/j.jpba.2019.113041

Cited by 16 publications

(17 citation statements)

References 29 publications

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“…Metabolomics is a high-throughput tool for quantitatively analyzing the small-molecule metabolites in biospecimens such as blood, tissue, urine, or saliva ( Cheng et al, 2018 ). It has been increasingly applied to discovering potential biomarkers and related metabolic pathways ( Johnson et al, 2016 ), the investigations of polypharmacological mechanisms of drug combination therapy ( Li et al, 2021a ), and the host response to the drug therapy ( Wang et al, 2018 ; Li et al, 2020 ), and explorations of complicated pathophysiologic mechanisms of diseases ( Johnson et al, 2016 ; Wu et al, 2020 ). Generally, the widely targeted metabolomics method can achieve accurate quantification of targeted metabolites by defining ion-pairs information derived from untargeted metabolomics or obtained from relevant references and existing mass spectrum public databases ( Heikkinen et al, 2019 ; Zhou et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

Zhu

Huang

et al. 2021

Front. Mol. Biosci.

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Alcohol dependence (AD) is a condition of alcohol use disorder in which the drinkers frequently develop emotional symptoms associated with a continuous alcohol intake. AD characterized by metabolic disturbances can be quantitatively analyzed by metabolomics to identify the alterations in metabolic pathways. This study aimed to: i) compare the plasma metabolic profiling between healthy and AD-diagnosed individuals to reveal the altered metabolic profiles in AD, and ii) identify potential biological correlates of alcohol-dependent inpatients based on metabolomics and interpretable machine learning. Plasma samples were obtained from healthy (n = 42) and AD-diagnosed individuals (n = 43). The plasma metabolic differences between them were investigated using liquid chromatography-tandem mass spectrometry (AB SCIEX® QTRAP 4500 system) in different electrospray ionization modes with scheduled multiple reaction monitoring scans. In total, 59 and 52 compounds were semi-quantitatively measured in positive and negative ionization modes, respectively. In addition, 39 metabolites were identified as important variables to contribute to the classifications using an orthogonal partial least squares-discriminant analysis (OPLS-DA) (VIP > 1) and also significantly different between healthy and AD-diagnosed individuals using univariate analysis (p-value < 0.05 and false discovery rate < 0.05). Among the identified metabolites, indole-3-carboxylic acid, quinolinic acid, hydroxy-tryptophan, and serotonin were involved in the tryptophan metabolism along the indole, kynurenine, and serotonin pathways. Metabolic pathway analysis revealed significant changes or imbalances in alanine, aspartate, glutamate metabolism, which was possibly the main altered pathway related to AD. Tryptophan metabolism interactively influenced other metabolic pathways, such as nicotinate and nicotinamide metabolism. Furthermore, among the OPLS-DA-identified metabolites, normetanephrine and ascorbic acid were demonstrated as suitable biological correlates of AD inpatients from our model using an interpretable, supervised decision tree classifier algorithm. These findings indicate that the discriminatory metabolic profiles between healthy and AD-diagnosed individuals may benefit researchers in illustrating the underlying molecular mechanisms of AD. This study also highlights the approach of combining metabolomics and interpretable machine learning as a valuable tool to uncover potential biological correlates. Future studies should focus on the global analysis of the possible roles of these differential metabolites and disordered metabolic pathways in the pathophysiology of AD.

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Section: Introductionmentioning

confidence: 99%

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

Zhu

Huang

et al. 2021

Front. Mol. Biosci.

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“…Metabolomics allows the analysis of as many metabolites as possible, it is impossible to obtain a standard for each metabolite. In this work, the ~500 MRM ion pairs for pseudotargeted analysis were acquired by some metabolite standards or published literatures [16][17][18][19]22 , the ~350 MRM ion pairs were selected for the quantitative MRM transition, along with a second transition for identity con rmation. The mass spectometry parameters and retention time (RT) are summarized in supplementary Table S1.…”

Section: Resultsmentioning

confidence: 99%

“…The test cells were gently washed with PBS, and quickly frozen with liquid nitrogen (N 2 ) for metabolic quenching. Pretreatment procedure of the cells was applied according to our previous studies 22 . Brie y, methanol/acetonitrile/water (40/40/20, v/v/v) was added to cell dishes, the cell/solvent mixture were collected and transferred to clean tubes.…”

Section: Methodsmentioning

confidence: 99%

MS-Based Metabolomics Reveals Metabolic Dysregulation in Erastin-Induced Gastric Adenocarcinoma Cells

Liu

Asmamaw

et al. 2021

Preprint

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Gastric cancer (GC) is one of the most malignant tumors with high morbidity and mortality in the world, particularly in China. Erastin, a classical ferroptosis inducer, exerts cytotoxicity in several types of cancer cells including gastric cancer cells. However, the mechanism of erastin in regulating metabolic pathways in gastric cancer remains largely unclear. To investigate the gastric cellular response to erastin therapy, we adopted a cell pseudotargeted metabolomics method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). The developed method was used to investigate the differential metabolites between erastin-treated MGC-803 cells and the controls at different time points. We found that erastin induced tremendous impact on the metabolome of gastric cells by affecting key metabolic processes, such as cysteine and methionine metabolism, glutathione (GSH) biosynthesis, glycolysis and TCA cycle. Interestingly, S-adenosylmethionine (SAM), methionine, serine, glycine and cysteine were obviously increasing treads after erastin treatment, but S-adenosylhomocysteine (SAH) and GSH were always down-regulated up to 48 h. The results indicated that DNA methylation was activated and glutathione biosynthesis was blocked in erastin-treated MGC-803 gastric cells, highlighting the importance of erastin as a promising drug candidate for in vivo treatment of gastric tumor.

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“…Pseudotargeted lipidomics, firstly proposed by Xu et al ( Chen et al, 2013 ), combines the advantages of both targeted and untargeted strategies ( Cao et al, 2020 ). Both known and unknown metabolites in samples can be measured by using the retention time locking-selected ions monitoring, which offers an efficient means to semi-quantitatively investigate endogenous lipids in different matrices and has been applied to discovery of diseases biomarkers ( Wang et al, 2018a ; Li et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Lipidomics Analysis Indicates Disturbed Hepatocellular Lipid Metabolism in Reynoutria multiflora-Induced Idiosyncratic Liver Injury

Zhang

Qiu

et al. 2020

Front. Pharmacol.

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The root of Reynoutria multiflora (Thunb.) Moldenke (syn.: Polygonum multiflorum Thunb., HSW) is a distinguished herb that has been popularly used in traditional Chinese medicine (TCM). Evidence of its potential side effect on liver injury has accumulated and received much attention. The objective of this study was to profile the metabolic characteristics of lipids in injured liver of rats induced by HSW and to find out potential lipid biomarkers of toxic consequence. A lipopolysaccharide (LPS)-induced rat model of idiosyncratic drug-induced liver injury (IDILI) was constructed and evident liver injury caused by HSW was confirmed based on the combination of biochemical, morphological, and functional tests. A lipidomics method was developed for the first time to investigate the alteration of lipid metabolism in HSW-induced IDILI rat liver by using ultra-high-performance liquid chromatography/Q-exactive Orbitrap mass spectrometry coupled with multivariate analysis. A total of 202 characterized lipids, including phosphatidylcholine (PC), lysophosphatidylcholine (LPC), phosphatidylethanolamine (PE), lysophosphatidylethanolamine (LPE), sphingomyelin (SM), phosphatidylinositol (PI), lysophosphatidylinositol (LPI), phosphatidylserine (PS), phosphoglycerols (PG), and ceramide (Cer), were compared among groups of LPS and LPS + HSW. A total of 14 out 26 LPC, 22 out of 47 PC, 19 out of 29 LPE, 16 out of 36 PE, and 10 out of 15 PI species were increased in HSW-treated rat liver, which indicated that HSW may cause liver damage via interfering the phospholipid metabolism. The present work may assist lipid biomarker development of HSW-induced DILI and it also provide new insights into the relationships between phospholipid perturbation and herbal-induced idiosyncratic DILI.

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Development of a mass spectrometry-based pseudotargeted metabolomics strategy to analyze hormone-stimulated gastric cancer cells

Cited by 16 publications

References 29 publications

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

MS-Based Metabolomics Reveals Metabolic Dysregulation in Erastin-Induced Gastric Adenocarcinoma Cells

Lipidomics Analysis Indicates Disturbed Hepatocellular Lipid Metabolism in Reynoutria multiflora-Induced Idiosyncratic Liver Injury

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