Profiling thiol metabolites and quantification of cellular glutathione using FT-ICR-MS spectrometry

Gori, Sadakatali S.; Lorkiewicz, Pawel; Ehringer, Daniel S.; Belshoff, Alex; Higashi, Richard M.; Fan, Teresa W.‐M.; Nantz, Michael H.

doi:10.1007/s00216-014-7810-z

Cited by 24 publications

(15 citation statements)

References 63 publications

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“…Isotopically enriched reagents can be designed to react with particular functional groups present in metabolites, such as carboxylate (Ye et al, 2009), carbonyl (Fu et al, 2011; Mattingly et al, 2012), amino (Guo and Li, 2009), and sulfhydryl (Gori et al, 2014). Figure 1A shows the carbonyl-selective aminooxy reagent for simultaneous MS and NMR chemical editing.…”

Section: Introductionmentioning

confidence: 99%

Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

et al. 2014

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Large-scale identification of metabolites is key to elucidating and modeling metabolism at the systems level. Advances in metabolomics technologies, particularly ultra-high resolution mass spectrometry (MS) enable comprehensive and rapid analysis of metabolites. However, a significant barrier to meaningful data interpretation is the identification of a wide range of metabolites including unknowns and the determination of their role(s) in various metabolic networks. Chemoselective (CS) probes to tag metabolite functional groups combined with high mass accuracy provide additional structural constraints for metabolite identification and quantification. We have developed a novel algorithm, Chemically Aware Substructure Search (CASS) that efficiently detects functional groups within existing metabolite databases, allowing for combined molecular formula and functional group (from CS tagging) queries to aid in metabolite identification without a priori knowledge. Analysis of the isomeric compounds in both Human Metabolome Database (HMDB) and KEGG Ligand demonstrated a high percentage of isomeric molecular formulae (43 and 28%, respectively), indicating the necessity for techniques such as CS-tagging. Furthermore, these two databases have only moderate overlap in molecular formulae. Thus, it is prudent to use multiple databases in metabolite assignment, since each major metabolite database represents different portions of metabolism within the biosphere. In silico analysis of various CS-tagging strategies under different conditions for adduct formation demonstrate that combined FT-MS derived molecular formulae and CS-tagging can uniquely identify up to 71% of KEGG and 37% of the combined KEGG/HMDB database vs. 41 and 17%, respectively without adduct formation. This difference between database isomer disambiguation highlights the strength of CS-tagging for non-lipid metabolite identification. However, unique identification of complex lipids still needs additional information.

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Section: Introductionmentioning

confidence: 99%

Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

et al. 2014

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“…13 C 2 H 3 ‐QDE was synthesized using 13 C 2 H 3 I. The reaction of QDE/ 13 C 2 H 3 ‐QDE was carried out at pH 4.0 for enhancement of the chemoselectivity toward thiols over cellular amines, phenols, and carboxylate salts (Gori et al, ). In the same context, commercially available 2‐iodoacetanilide (IAN) and 13 C 6 ‐IAN were also used for the determination of hydrogen sulfide and thiol metabolites (cysteine, homocysteine, and GSH) in a cellular extract.…”

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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“…The assignment can be based on the functional group and the combined 1 H and 15 N chemical shifts [33,34]. Other CS probes have been developed by us that select for functional groups including thiols [35] and carbonyls (aldehydes and ketones) [36,37]. The resulting adducts in biological extracts are optimized for both MS analysis, and 15 N edited 1 H NMR analysis that makes use of long range 2 and 3-bond couplings [31].…”

Section: Nmr Is a Powerful Tool For Metabolite Identification And mentioning

confidence: 99%

“…For tagging carbonyl and sulfhydryl functional groups, we have respectively developed QDA ( Q uaternary ammonium D odecyl dimethyl A minooxy) [37] and QDE ( Q uaternary ammonium D odecyl dimethyl E thyl iodoacetamide) [201] probes. The 15 N labeled QDA was employed to tag carbonyl-containing metabolites such as pyruvate (Fig.…”

Section: Sample Preparation Considerationsmentioning

confidence: 99%

Applications of NMR spectroscopy to systems biochemistry

Fan

Lane

2016

Progress in Nuclear Magnetic Resonance Spectroscopy

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The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other ‘omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

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Profiling thiol metabolites and quantification of cellular glutathione using FT-ICR-MS spectrometry

Cited by 24 publications

References 63 publications

Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

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

Applications of NMR spectroscopy to systems biochemistry

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