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Dissecting plasmodesmata molecular composition by mass spectrometry-based proteomics

Overview of attention for article published in Frontiers in Plant Science, January 2013
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Dissecting plasmodesmata molecular composition by mass spectrometry-based proteomics
Published in
Frontiers in Plant Science, January 2013
DOI 10.3389/fpls.2012.00307
Pubmed ID
Authors

Magali S. Salmon, Emmanuelle M. F. Bayer

Abstract

In plants, the intercellular communication through the membranous channels called plasmodesmata (PD; singular plasmodesma) plays pivotal roles in the orchestration of development, defence responses, and viral propagation. PD are dynamic structures embedded in the plant cell wall that are defined by specialized domains of the endoplasmic reticulum (ER) and the plasma membrane (PM). PD structure and unique functions are guaranteed by their particular molecular composition. Yet, up to recent years and despite numerous approaches such as mutant screens, immunolocalization, or screening of random cDNAs, only few PD proteins had been conclusively identified and characterized. A clear breakthrough in the search of PD constituents came from mass-spectrometry-based proteomic approaches coupled with subcellular fractionation strategies. Due to their position, firmly anchored in the extracellular matrix, PD are notoriously difficult to isolate for biochemical analysis. Proteomic-based approaches have therefore first relied on the use of cell wall fractions containing embedded PD then on "free" PD fractions whereby PD membranes were released from the walls by enzymatic degradation. To discriminate between likely contaminants and PD protein candidates, bioinformatics tools have often been used in combination with proteomic approaches. GFP fusion proteins of selected candidates have confirmed the PD association of several protein families. Here we review the accomplishments and limitations of the proteomic-based strategies to unravel the functional and structural complexity of PD. We also discuss the role of the identified PD-associated proteins.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
France 1 1%
Unknown 75 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 25%
Researcher 16 21%
Student > Master 8 10%
Student > Doctoral Student 7 9%
Student > Bachelor 6 8%
Other 9 12%
Unknown 12 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 44%
Biochemistry, Genetics and Molecular Biology 17 22%
Medicine and Dentistry 5 6%
Environmental Science 2 3%
Chemistry 2 3%
Other 4 5%
Unknown 13 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2013.
All research outputs
#18,325,190
of 22,691,736 outputs
Outputs from Frontiers in Plant Science
#13,529
of 19,888 outputs
Outputs of similar age
#217,955
of 280,664 outputs
Outputs of similar age from Frontiers in Plant Science
#216
of 517 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 19,888 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,664 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 517 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.