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NHS-based Tandem Mass Tagging of Proteins at the Level of Whole Cells: A Critical Evaluation in Comparison to Conventional TMT-Labeling Approaches for Quantitative Proteome Analysis

Overview of attention for article published in Analytical Sciences, December 2017
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Title
NHS-based Tandem Mass Tagging of Proteins at the Level of Whole Cells: A Critical Evaluation in Comparison to Conventional TMT-Labeling Approaches for Quantitative Proteome Analysis
Published in
Analytical Sciences, December 2017
DOI 10.2116/analsci.33.1387
Pubmed ID
Authors

Dominik A Megger, Leona L Pott, Kristin Rosowski, Birgit Zülch, Stephanie Tautges, Thilo Bracht, Barbara Sitek

Abstract

Tandem mass tags (TMT) are usually introduced at the levels of isolated proteins or peptides. Here, for the first time, we report the labeling of whole cells and a critical evaluation of its performance in comparison to conventional labeling approaches. The obtained results indicated that TMT protein labeling using intact cells is generally possible, if it is coupled to a subsequent enrichment using anti-TMT antibody. The quantitative results were similar to those obtained after labeling of isolated proteins and both were found to be slightly complementary to peptide labeling. Furthermore, when using NHS-based TMT, no specificity towards cell surface proteins was observed in the case of cell labeling. In summary, the conducted study revealed first evidence for the general possibility of TMT cell labeling and highlighted limitations of NHS-based labeling reagents. Future studies should therefore focus on the synthesis and investigation of membrane impermeable TMTs to increase specificity towards cell surface proteins.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Student > Bachelor 1 7%
Student > Doctoral Student 1 7%
Student > Master 1 7%
Unknown 6 43%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 3 21%
Biochemistry, Genetics and Molecular Biology 1 7%
Agricultural and Biological Sciences 1 7%
Immunology and Microbiology 1 7%
Medicine and Dentistry 1 7%
Other 1 7%
Unknown 6 43%
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 07 August 2018.
All research outputs
#17,922,331
of 23,011,300 outputs
Outputs from Analytical Sciences
#687
of 906 outputs
Outputs of similar age
#307,384
of 439,745 outputs
Outputs of similar age from Analytical Sciences
#7
of 14 outputs
Altmetric has tracked 23,011,300 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 906 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 22nd percentile – i.e., 22% 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 439,745 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.