↓ Skip to main content

American Chemical Society

Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial

Overview of attention for article published in Journal of Proteome Research, November 2022
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
57 X users

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
97 Mendeley
Title
Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial
Published in
Journal of Proteome Research, November 2022
DOI 10.1021/acs.jproteome.2c00407
Pubmed ID
Authors

Juraj Lenčo, Siddharth Jadeja, Denis K. Naplekov, Oleg V. Krokhin, Maria A. Khalikova, Petr Chocholouš, Jiří Urban, Ken Broeckhoven, Lucie Nováková, František Švec

Abstract

The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 57 X users 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 97 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 18%
Researcher 15 15%
Other 6 6%
Student > Master 6 6%
Unspecified 5 5%
Other 13 13%
Unknown 35 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 24%
Chemistry 13 13%
Agricultural and Biological Sciences 8 8%
Unspecified 5 5%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 6 6%
Unknown 38 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 09 June 2023.
All research outputs
#1,003,485
of 24,954,788 outputs
Outputs from Journal of Proteome Research
#104
of 6,360 outputs
Outputs of similar age
#22,318
of 434,596 outputs
Outputs of similar age from Journal of Proteome Research
#3
of 89 outputs
Altmetric has tracked 24,954,788 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,360 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 98% of its peers.
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 434,596 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.