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Zeptomole electrochemical detection of metallothioneins.

By Vojtech Adam, Jitka Petrlova, Joseph Wang, Tomas Eckschlager, Libuse Trnkova and Rene Kizek

Abstract

BACKGROUND: Thiol-rich peptides and proteins possess a large number of biological activities and may serve as markers for numerous health problems including cancer. Metallothionein (MT), a small molecular mass protein rich in cysteine, may be considered as one of the promising tumour markers. The aim of this paper was to employ chronopotentiometric stripping analysis (CPSA) for highly sensitive detection of MT. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we used adsorptive transfer stripping technique coupled with CPSA for detection of cysteine, glutathione oxidized and reduced, phytochelatin, bovine serum albumin, and metallothionein. Under the optimal conditions, we were able to estimate detection limits down to tens of fg per ml. Further, this method was applied to detect metallothioneins in blood serum obtained from patients with breast cancer and in neuroblastoma cells resistant and sensitive to cisplatin in order to show the possible role of metallothioneins in carcinogenesis. It was found that MT level in blood serum was almost twice higher as compared to the level determined in healthy individuals. CONCLUSIONS/SIGNIFICANCE: This paper brings unique results on the application of ultra-sensitive electroanalytical method for metallothionein detection. The detection limit and other analytical parameters are the best among the parameters of other techniques. In spite of the fact that the paper is mainly focused on metallothionein, it is worth mentioning that successful detection of other biologically important molecules is possible by this method. Coupling of this method with simple isolation methods such as antibody-modified paramagnetic particles may be implemented to lab-on-chip instrument

Topics: Medicine, R, Science, Q
Publisher: Public Library of Science (PLoS)
DOI identifier: 10.1371/journal.pone.0011441
OAI identifier: oai:doaj.org/article:e5ab660a411243648ae28be1c96a6763
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