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Characterization and quantification of thiol-peptides in Arabidopsis thaliana using combined dilution and high
Erika Bellini1, Marco Borsò2, Camilla Betti3
1Dipartimento di Biologia, Università di Pisa, Italy; Dipartimento di Biologia, Università di Roma "Tor Vergata", Italy.
Abstract:
Although thiol-peptide compounds, such as reduced glutathione (GSH), γ-glutamylcysteine (γ-EC), and phytochelatins, play fundamental roles in plants, their analytical determination and characterization is still somewhat problematic, mainly due to their high polarity and oxidation propensity. Thus, in this work a reliable and sensitive HPLC-ESI-MS-MS method was developed, in order to simultaneously assay, within 14-min instrumental runs, γ-EC, GSH, and phytochelatins up to phytochelatin 4. This analytical method was validated in shoot and root extracts of the model plant Arabidopsis thaliana (Brassicaceae) and guaranteed accurate quantification by using specific isotope labelled-internal standards for both GSH and phytochelatins, as well as standards for external calibration. Good linearities in the method performance were observed (R > 0.99), with a dynamic range over three orders of magnitude in thiol-peptide concentrations. In MRM mode, the detection sensitivity of the thiol-peptides was equal to approximately 16, 6, 7, 13, 10 fmol for γ-EC, GSH, phytochelatin 2, phytochelatin 3, and phytochelatin 4, respectively (20 μl injection each). The reproducibility of the method was confirmed by high intra- and inter-day accuracy and precision values. The recovery rates were estimated approximately in the range of 73.8-91.0% and the matrix effect evaluation revealed that all analytes exhibited ionization suppression. The use of stable isotope-labelled analogs of the thiol-peptides as internal standards was particularly worthy of note: it offered the considerable advantage of overcoming the consequences of matrix effect and thiol-peptide loss through sample preparation, by normalizing the analyte signal during the quantification process. Thus, by validating the method's sensitivity, accuracy, precision, reproducibility, stability, recovery, and matrix effect, data reliability and robustness were ensured.
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