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Data in support of the proteomic analysis of plasma membrane and tonoplast from the leaves of mangrove plant Avicennia officinalis.

Krishnamurthy P, Tan XF, Lim TK, Lim TM, Kumar PP, Loh CS, Lin Q - Data Brief (2015)

Bottom Line: The data provides information in support of the research article, Proteomics 2014, 14, 2545-2557 [1].Raw data is available from the ProteomeXchange Consortium via the PRIDE partnerRepository [2] with the dataset identifier PXD000837.Based on GO annotation, identified proteins were predicted to be involved in various biological processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, 117543, Singapore ; NUS Environmental Research Institute (NERI), National University of Singapore, Singapore.

ABSTRACT
The data provides information in support of the research article, Proteomics 2014, 14, 2545-2557 [1]. Raw data is available from the ProteomeXchange Consortium via the PRIDE partnerRepository [2] with the dataset identifier PXD000837. Plasma membrane and tonoplast proteins from the leaves of Avicennia officinalis were identified using gel electrophoresis (one and two dimensional) combined with LC-MS analysis. Based on GO annotation, identified proteins were predicted to be involved in various biological processes.

No MeSH data available.


Experimental design of the membrane proteomic analysis.
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f0005: Experimental design of the membrane proteomic analysis.

Mentions: Fig. 1 shows the general workflow of the membrane proteomic analysis. Leaves were collected from the mangrove trees and plasma membrane fraction was isolated using an aqueous two-phase partitioning method while the tonoplast fraction was isolated by density gradient centrifugation. The membrane proteins were fractionated by one- and two-dimensional gel electrophoresis. The trypsin digested fragments from the gels were used for LC–MS/MS analysis. MS data was acquired using a TripleTOF 5600 system and the peptide identification was carried out using the ProteinPilot 4.5 software.


Data in support of the proteomic analysis of plasma membrane and tonoplast from the leaves of mangrove plant Avicennia officinalis.

Krishnamurthy P, Tan XF, Lim TK, Lim TM, Kumar PP, Loh CS, Lin Q - Data Brief (2015)

Experimental design of the membrane proteomic analysis.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644245&req=5

f0005: Experimental design of the membrane proteomic analysis.
Mentions: Fig. 1 shows the general workflow of the membrane proteomic analysis. Leaves were collected from the mangrove trees and plasma membrane fraction was isolated using an aqueous two-phase partitioning method while the tonoplast fraction was isolated by density gradient centrifugation. The membrane proteins were fractionated by one- and two-dimensional gel electrophoresis. The trypsin digested fragments from the gels were used for LC–MS/MS analysis. MS data was acquired using a TripleTOF 5600 system and the peptide identification was carried out using the ProteinPilot 4.5 software.

Bottom Line: The data provides information in support of the research article, Proteomics 2014, 14, 2545-2557 [1].Raw data is available from the ProteomeXchange Consortium via the PRIDE partnerRepository [2] with the dataset identifier PXD000837.Based on GO annotation, identified proteins were predicted to be involved in various biological processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, 117543, Singapore ; NUS Environmental Research Institute (NERI), National University of Singapore, Singapore.

ABSTRACT
The data provides information in support of the research article, Proteomics 2014, 14, 2545-2557 [1]. Raw data is available from the ProteomeXchange Consortium via the PRIDE partnerRepository [2] with the dataset identifier PXD000837. Plasma membrane and tonoplast proteins from the leaves of Avicennia officinalis were identified using gel electrophoresis (one and two dimensional) combined with LC-MS analysis. Based on GO annotation, identified proteins were predicted to be involved in various biological processes.

No MeSH data available.