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Evaluation of protein extraction methods for enhanced proteomic analysis of tomato leaves and roots

Overview of attention for article published in Anais da Academia Brasileira de Ciências, August 2015
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Title
Evaluation of protein extraction methods for enhanced proteomic analysis of tomato leaves and roots
Published in
Anais da Academia Brasileira de Ciências, August 2015
DOI 10.1590/0001-3765201520150116
Pubmed ID
Authors

Milca B Vilhena, Mônica R Franco, Daiana Schmidt, Giselle Carvalho, Ricardo A Azevedo

Abstract

Proteomics is an outstanding area in science whose increasing application has advanced to distinct purposes. A crucial aspect to achieve a good proteome resolution is the establishment of a methodology that results in the best quality and wide range representation of total proteins. Another important aspect is that in many studies, limited amounts of tissue and total protein in the tissue to be studied are found, making difficult the analysis. In order to test different parameters, combinations using minimum amount of tissue with 4 protocols for protein extraction from tomato (Solanum lycopersicum L.) leaves and roots were evaluated with special attention to their capacity for removing interferents and achieving suitable resolution in bidimensional gel electrophoresis, as well as satisfactory protein yield. Evaluation of the extraction protocols revealed large protein yield differences obtained for each one. TCA/acetone was shown to be the most efficient protocol, which allowed detection of 211 spots for leaves and 336 for roots using 500 µg of leaf protein and 800 µg of root protein per gel.

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Mendeley readers

The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 <1%
Mauritius 1 <1%
Unknown 146 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 19%
Student > Bachelor 27 18%
Student > Master 24 16%
Researcher 13 9%
Student > Doctoral Student 6 4%
Other 14 9%
Unknown 36 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 32%
Biochemistry, Genetics and Molecular Biology 30 20%
Chemistry 7 5%
Immunology and Microbiology 2 1%
Pharmacology, Toxicology and Pharmaceutical Science 2 1%
Other 15 10%
Unknown 45 30%