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vol.35 issue1  suppl.1A simple, economical and reproducible protein extraction protocol for proteomics studies of soybean roots author indexsubject indexarticles search
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Genetics and Molecular Biology

Print version ISSN 1415-4757

Abstract

MESQUITA, Rosilene Oliveira; SOARES, Eduardo de Almeida; BARROS, Everaldo Gonçalves de  and  LOUREIRO, Marcelo Ehlers. Method optimization for proteomic analysis of soybean leaf: improvements in identification of new and low-abundance proteins. Genet. Mol. Biol. [online]. 2012, vol.35, n.1, suppl.1, pp. 353-361. ISSN 1415-4757.  http://dx.doi.org/10.1590/S1415-47572012000200017.

The most critical step in any proteomic study is protein extraction and sample preparation. Better solubilization increases the separation and resolution of gels, allowing identification of a higher number of proteins and more accurate quantitation of differences in gene expression. Despite the existence of published results for the optimization of proteomic analyses of soybean seeds, no comparable data are available for proteomic studies of soybean leaf tissue. In this work we have tested the effects of modification of a TCA-acetone method on the resolution of 2-DE gels of leaves and roots of soybean. Better focusing was obtained when both mercaptoethanol and dithiothreitol were used in the extraction buffer simultaneously. Increasing the number of washes of TCA precipitated protein with acetone, using a final wash with 80% ethanol and using sonication to ressuspend the pellet increased the number of detected proteins as well the resolution of the 2-DE gels. Using this approach we have constructed a soybean protein map. The major group of identified proteins corresponded to genes of unknown function. The second and third most abundant groups of proteins were composed of photosynthesis and metabolism related genes. The resulting protocol improved protein solubility and gel resolution allowing the identification of 122 soybean leaf proteins, 72 of which were not detected in other published soybean leaf 2-DE gel datasets, including a transcription factor and several signaling proteins.

Keywords : proteomics; Glycine max; 2-DE; protein extraction; leaf proteome.

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