An efficient protein extraction method applied to mangrove plant Kandelia obovata leaves for proteomic analysis.
Plant Methods
; 17(1): 100, 2021 Sep 29.
Article
em En
| MEDLINE
| ID: mdl-34587982
BACKGROUND: Mangroves plants, an important wetland system in the intertidal shores, play a vital role in estuarine ecosystems. However, there is a lack of a very effective method for extracting protein from mangrove plants for proteomic analysis. Here, we evaluated the efficiency of three different protein extraction methods for proteomic analysis of total proteins obtained from mangrove plant Kandelia obovata leaves. RESULTS: The protein yield of the phenol-based (Phe-B) method (4.47 mg/g) was significantly higher than the yields of the traditional phenol (Phe) method (2.38 mg/g) and trichloroacetic acid-acetone (TCA-A) method (1.15 mg/g). The Phe-B method produced better two-dimensional electrophoresis (2-DE) protein patterns with high reproducibility regarding the number, abundance and coverage of protein spots. The 2-DE gels showed that 847, 650 and 213 unique protein spots were separated from the total K. obovata leaf proteins extracted by the Phe-B, Phe and TCA-A methods, respectively. Fourteen pairs of protein spots were randomly selected from 2-DE gels of Phe- and Phe-B- extracted proteins for identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS) technique, and the results of three pairs were consistent. Further, oxygen evolving enhancer protein and elongation factor Tu could be observed in the 2-DE gels of Phe and Phe-B methods, but could only be detected in the results of the Phe-B methods, showing that Phe-B method might be the optimized choice for proteomic analysis. CONCLUSION: Our data provides an improved Phe-B method for protein extraction of K. obovata and other mangrove plant tissues which is rich in polysaccharides and polyphenols. This study might be expected to be used for proteomic analysis in other recalcitrant plants.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article