Highly selective apo-arginase based method for sensitive enzymatic assay of manganese (II) and cobalt (II) ions

Abstract : A novel enzymatic method of manganese (II) and cobalt (II) ions assay, based on using apo-enzyme of Mn2+-dependent recombinant arginase I (arginase) and 2,3-butanedione monoxime (DMO) as a chemical reagent is proposed. The principle of the method is the evaluation of the activity of L-arginine-hydrolyzing of arginase holoenzyme after the specific binding of Mn2+ or Co2+ with apo-arginase. Urea, which is the product of enzymatic hydrolysis of L-arginine (Arg), reacts with DMO and the resulted compound is detected by both fluorometry and visual spectrophotometry. Thus, the content of metal ions in the tested samples can be determined by measuring the level of urea generated after enzymatic hydrolysis of Arg by reconstructed arginase holoenzyme in the presence of tested metal ions. The linearity range of the fluorometric apo-arginase-DMO method in the case of Mn2+ assay is from 4pM to 1.10nM with a limit of detection of 1pM Mn2+, whereas the linearity range of the present method in the case of Co2+ assay is from 8pM to 45nM with a limit of detection of 2.5pM Co2+. The proposed method being highly sensitive, selective, valid and low-cost, may be useful to monitor Mn2+ and Co2+ content in clinical laboratories, food industry and environmental control service.
Document type :
Journal articles
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01767674
Contributor : Agnès Bussy <>
Submitted on : Monday, April 16, 2018 - 2:16:13 PM
Last modification on : Tuesday, April 17, 2018 - 1:22:24 AM

Identifiers

Collections

Citation

Nataliya Stasyuk, Galina Gayda, Andriy Zakalskiy, Oksana Zakalska, Abdelhamid Errachid, et al.. Highly selective apo-arginase based method for sensitive enzymatic assay of manganese (II) and cobalt (II) ions. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Elsevier, 2018, 193, pp.349 - 356. 〈10.1016/j.saa.2017.12.031〉. 〈hal-01767674〉

Share

Metrics

Record views

32