Acidic Nα-acylarginine derivatives in apple and pear trees

Kasai, Takanori; Sakamura, Sadao

doi:10.1016/0031-9422(84)83069-1

Cited by 9 publications

(6 citation statements)

References 2 publications

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“…N2-Succinylarginine has previously been found in twigs of wintering pear trees where it serves as a storage form of nitrogen (15). N-Succinylglutamate accumulates in Bacillus during the initial phase of sporulation (16).…”

Section: Methodsmentioning

confidence: 99%

N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

Jann

Stalon²,

Wauven³

et al. 1986

Proc. Natl. Acad. Sci. U.S.A.

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Arginine-nonutilizing (aru) mutants of Pseudomonas aeruginosa strain PAO converted L-arginine to N2-succinylarginine or N-succinylglutamate, which were identified by high-voltage electrophoresis and HPLC. Addition of aminooxyacetate, an inhibitor of pyridoxal phosphate-dependent enzymes, to resting cells of the wild-type PAO1 in arginine medium led to the accumulation of N2-succinylornithine. Enzyme assays with crude P. aeruginosa extracts established the

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Section: Methodsmentioning

confidence: 99%

N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

Jann

Stalon²,

Wauven³

et al. 1986

Proc. Natl. Acad. Sci. U.S.A.

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“…(2) was already identified in bulbs of lilies (Lilium maximowiczii) and annual shoots of pear trees in 1983 and 1984, but has not yet been found in any other sample to the best of our knowledge. 28,29 The detailed identification process, including all spectroscopic data of both compounds, is shown below.…”

Section: Resultsmentioning

confidence: 99%

SMART-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

Watermann

Bode

Hackl

2022

Preprint

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Due to the large number of metabolites of various compound classes present in natural products, which in addition occur in high concentration differences, the identification of individual metabolites from either 1H NMR spectra or MS spectra is hardly possible due to signal overlap and the lack of information from interrelated signals of the same compound. This paper presents a method for the three-dimensional correlation of NMR and MS data over the third dimension of the time course of a chromatographic fractionation. Compounds do not need to be isolated individually, but the NMR and MS signals of the individual compounds can be correlated mathematically. The app SMART-metabolite-ID (Semi-automatic Mixture Analysis for Reliable and direcT metabolite IDentification) was implemented in MATLAB and provides semi-automatic detection of correlated NMR and MS data. Thereby, the app enables fast and reliable dereplication of known metabolites and facilitates the dynamic analysis for the identification of unknown compounds in any complex mixture. The strategy was validated using an artificial mixture and tested further on a polar extract of a pine nut sample. Straightforward identification of 40 metabolites could be shown, including the identification of β-D- glucopyranosyl-1-N-indole-3-acetyl-N-L-aspartic acid (1) and Nα-(2-hydroxy-2-carboxymethylsuccinyl)-L-arginine (2), the latter being identified in a food sample for the first time.

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“…knowledge. 29,30 The detailed identification process, including all spectroscopic data of both compounds, is shown below.…”

Section: Resultsmentioning

confidence: 99%

SCORE-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

Watermann

Bode

Hackl

2022

Preprint

View full text Add to dashboard Cite

Due to the large number of metabolites of various compound classes present in natural products, which in addition occur in high concentration differences, the identification of individual metabolites from either 1H NMR spectra or MS spectra is hardly possible due to signal overlap and the lack of information from interrelated signals of the same compound. This paper presents a method for the three-dimensional correlation of NMR and MS data over the third dimension of the time course of a chromatographic fractionation. Compounds do not need to be isolated individually, but the NMR and MS signals of the individual compounds can be correlated mathematically. The app SCORE-metabolite-ID (Semi-automatic COrrelation analysis for REliable metabolite IDentification) was implemented in MATLAB and provides semi-automatic detection of correlated NMR and MS data. Thereby, the app enables fast and reliable dereplication of known metabolites and facilitates the dynamic analysis for the identification of unknown compounds in any complex mixture. The strategy was validated using an artificial mixture and tested further on a polar extract of a pine nut sample. Straightforward identification of 40 metabolites could be shown, including the identification of β-D-glucopyranosyl-1-N-indole-3-acetyl-N-L-aspartic acid (1) and Nα-(2-hydroxy-2-carboxymethylsuccinyl)-L-arginine (2), the latter being identified in a food sample for the first time.

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Acidic Nα-acylarginine derivatives in apple and pear trees

Cited by 9 publications

References 2 publications

N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

SMART-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

SCORE-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

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Acidic Nα-acylarginine derivatives in apple and pear trees

Cited by 9 publications

References 2 publications

N 2 -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

N 2 -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

SMART-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

SCORE-metabolite-ID: Semi-automatic and reliable identification of metabolites from complex mixtures by correlation of 1H NMR, MS and LC data

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N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa

N ² -Succinylated intermediates in an arginine catabolic pathway of Pseudomonas aeruginosa