LC–MS/MS analysis of the central energy and carbon metabolites in biological samples following derivatization by dimethylaminophenacyl bromide

Willacey, Cornelius C.W.; Naaktgeboren, Martijn; Moreno, Edinson Lucumi; Wegrzyn, Agnieszka B.; Es, Daan van der; Karu, Naama; Fleming, Ronan M. T.; Harms, Amy C.; Hankemeier, Thomas

doi:10.1016/j.chroma.2019.460413

Cited by 29 publications

(27 citation statements)

References 39 publications

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“…Fresh and spent cell culture media samples were analysed using four complementary mass spectrometry platforms, resulting in quantification of a total of 104 metabolites. Where platforms measured the same metabolite, the measurement from the platform with the lowest relative standard deviation was employed for comparison with model predictions (55 from DmPABr [92], 16 from BzCl [93] 11 from GC-MS [42] and 7 from Accq-Tag [15]). Although a further 13 metabolites were measured by these platforms, there was no stoichiometrically and flux consistent reaction corresponding to it within the generic model of human metabolism, so they were excluded from further analyses (Fig.…”

Section: Figure 6: Venn Diagram Summarising Metabolomic Measurementsmentioning

confidence: 99%

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

Preciat

Moreno

Wegrzyn

et al. 2021

Preprint

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Patient-derived cellular models are a powerful approach to study human disease, especially neurodegenerative diseases, such as Parkinson's disease, where affected primary neurons, e.g., substantia nigra dopaminergic neurons, are almost inaccessible. Starting with a comprehensive generic reconstruction of human metabolism, Recon3D, we generated a high-quality, constraint-based, genome-scale, in silico model of human dopaminergic neuronal metabolism (iDopaNeuro1). It is a synthesis of extensive manual curation of the biochemical literature on neuronal metabolism, together with novel, quantitative, transcriptomic and targeted exometabolomic data from human stem cell-derived, midbrain-specific, dopaminergic neurons in vitro. Thermodynamic constraint-based modelling with iDopaNeuro1 is qualitatively accurate (92% correct) and quantitatively accurate (Spearman rank 0.7) at predicting metabolite secretion or uptake, given quantitative exometabolomic constraints on uptakes, or secretions, respectively. iDopaNeuro1 is also qualitatively accurate at predicting the consequences of metabolic perturbations, e.g., complex I inhibition (Spearman rank 0.69) in a manner consistent with literature on monogenic mitochondrial Parkinson's disease. The iDopaNeuro1 model provides a foundation for a quantitative systems biochemistry approach to metabolic dysfunction in Parkinson's disease. Moreover, the plethora of novel mathematical and computational approaches required to develop it are generalisable to study any other disease associated with metabolic dysfunction.

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Section: Figure 6: Venn Diagram Summarising Metabolomic Measurementsmentioning

confidence: 99%

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

Preciat

Moreno

Wegrzyn

et al. 2021

Preprint

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“…The hepatoprotective effects in vivo were evaluated using CCl 4 -induced hepatotoxicity model [16,17]. Male Kunming mice with body weight (BW) of 20 ± 2 g were provided by the Experimental Animal Center of Xinjiang Medical University, Urumqi, China.…”

Section: Liver Injury Model Construction and Treatmentmentioning

confidence: 99%

A GC-MS-based Metabolomic Strategy to Investigate the Protective Effects of Mulberry Polysaccharide on CCl4-induced Acute Liver Injury in Mice

Ma¹,

Yang²,

Baker³

et al. 2021

Preprint

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BackgroundMulberry (Morus alba) fruits of the woody mulberry tree (family: Moraceae Morus) is a type of mulberry fruit grown in the southern Xinjiang region,which polysaccharides have antioxidant and liver protective effects.This article further preliminary study on the protective effects of mulberry polysaccharide (MP) on liver.MethodsA detection kit was used to assess serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), liver malondialdehyde (MDA), superoxide dismutase (SOD) and other indicators. Liver tissue sections were stained with hematoxylin and eosin (H&E) and observed under a microscope. The entire endogenous metabolite proﬁling was acquired via metabolomics strategy using gas chromatography-mass spectrometry (GC-MS) to assess the underlying protective mechanisms of MPs. ResultsResults indicated that MPs exerted a hepatoprotective effect on acute liver injury by decreasing serum ALT and AST levels, hepatic MDA, and restored hepatic SOD glutathione peroxidase (GSH-Px) activities. A total of 33 possible endogenous metabolites associated with lipid, glucose, and energy metabolism including amino acids, sugars, and fatty acids, were found.ConclusionsThe results of the present study provide a reference for elucidating the protective mechanisms of MPs against acute liver injury.

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“…The derivatization reaction was performed in a biosafety cabinet to avoid interference from the surrounding environment (Awad, Allen, Adamko, & El‐Aneed, ). Very recently, Willacey et al () realized the full potential of DmPA of not only being able to derivatize carboxylic acids but also being capable of labeling amines and thiols. They utilized 2 H 0 / 2 H 6 ‐DmPA for the ICD of carboxylic acid, amino acids, and thiols in various biological samples.…”

Section: Isotope‐coded Derivatization Reagents For Lc–ms Analysismentioning

confidence: 99%

Current trends in isotope‐coded derivatization liquid chromatographic‐mass spectrometric analyses with special emphasis on their biomedical application

El-Maghrabey

Kishikawa

Kuroda

2020

Biomedical Chromatography

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Currently, LC–MS has various applications in different areas such as metabolomics, pharmacokinetics, and pathological studies. Yet, matrix effects resulting from co‐existing constituents remain a major problem for LC–MS [or LC–tandem mass spectrometry (LC–MS/MS)]. Moreover, technical problems and instrumental drifts may lead to ion abundance variance. Thus, an internal standard (IS) is required to guarantee the accuracy and precision of the method. Because of their limited number, isotope‐coded derivatization (ICD) has been recently introduced to overcome this problem. For ICD, a stable heavy isotope‐coded moiety is used for labeling the standard or the control sample and the formed products can act as ISs. A light form of the reagent is used for labeling the sample. Then, both are mixed and analyzed by LC–MS(/MS). This strategy permits the identification of different unknown analytes including potential metabolites and disease biomarkers. All these attributes lead to persistent growth in the applications of ICD LC–MS(/MS) in various biomedical branches. In this article we review the ICD methods published in the last eight years for biomedical applications as well as briefly summarize other applications for environmental and food analyses as some of their used ICD reagents were further applied for analyzing biological specimens or have the potential for that.

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LC–MS/MS analysis of the central energy and carbon metabolites in biological samples following derivatization by dimethylaminophenacyl bromide

Cited by 29 publications

References 39 publications

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

A GC-MS-based Metabolomic Strategy to Investigate the Protective Effects of Mulberry Polysaccharide on CCl4-induced Acute Liver Injury in Mice

Current trends in isotope‐coded derivatization liquid chromatographic‐mass spectrometric analyses with special emphasis on their biomedical application

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