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mRuby, a Bright Monomeric Red Fluorescent Protein for Labeling of Subcellular Structures

Overview of attention for article published in PLOS ONE, February 2009
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Title
mRuby, a Bright Monomeric Red Fluorescent Protein for Labeling of Subcellular Structures
Published in
PLOS ONE, February 2009
DOI 10.1371/journal.pone.0004391
Pubmed ID
Authors

Simone Kredel, Franz Oswald, Karin Nienhaus, Karen Deuschle, Carlheinz Röcker, Michael Wolff, Ralf Heilker, G. Ulrich Nienhaus, Jörg Wiedenmann

Abstract

A monomeric variant of the red fluorescent protein eqFP611, mRuby, is described. With excitation and emission maxima at 558 nm and 605 nm, respectively, and a large Stokes shift of 47 nm, mRuby appears particularly useful for imaging applications. The protein shows an exceptional resistance to denaturation at pH extremes. Moreover, mRuby is about ten-fold brighter compared to EGFP when being targeted to the endoplasmic reticulum. The engineering process of eqFP611 revealed that the C-terminal tail of the protein acts as a natural peroxisomal targeting signal (PTS). Using an mRuby variant carrying the eqFP611-PTS, we discovered that ordered inheritance of peroxisomes is widespread during mitosis of different mammalian cell types. The ordered partitioning is realized by the formation of peroxisome clusters around the poles of the mitotic spindle and ensures that equal numbers of the organelle are inherited by the daughter cells. The unique spectral properties make mRuby the marker of choice for a multitude of cell biological applications. Moreover, the use of mRuby has allowed novel insights in the biology of organelles responsible for severe human diseases.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 444 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 1%
Switzerland 3 <1%
Japan 3 <1%
Belgium 3 <1%
United Kingdom 2 <1%
Germany 2 <1%
Netherlands 2 <1%
Russia 1 <1%
Czechia 1 <1%
Other 2 <1%
Unknown 420 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 120 27%
Researcher 101 23%
Student > Master 53 12%
Student > Bachelor 50 11%
Student > Doctoral Student 23 5%
Other 58 13%
Unknown 39 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 191 43%
Biochemistry, Genetics and Molecular Biology 84 19%
Neuroscience 30 7%
Chemistry 26 6%
Physics and Astronomy 17 4%
Other 50 11%
Unknown 46 10%