Change search
ReferencesLink to record
Permanent link

Direct link
Optimized Nonlinear Gradients for Reversed-Phase Liquid Chromatography in Shotgun Proteomics
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Show others and affiliations
2013 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 85, no 16, 7777-7785 p.Article in journal (Refereed) Published
Abstract [en]

Reversed-phase liquid chromatography has become the preferred method for separating peptides in most of the mass spectrometry-based proteomics workflows of today. In the way the technique is typically applied, the peptides are released from the chromatography column by the gradual addition of an organic buffer according to a linear function. However, when applied to complex peptide mixtures, this approach leads to unequal spreads of the peptides over the chromatography time. To address this, we investigated the use of nonlinear gradients, customized for each setup at hand. We developed an algorithm to generate optimized gradient functions for shotgun proteomics experiments and evaluated it for two data sets consisting each of four replicate runs of a human complex sample. Our results show that the optimized gradients produce a more even spread of the peptides over the chromatography run, while leading to increased numbers of confident peptide identifications. In addition, the list of peptides identified using nonlinear gradients differed considerably from those found with the linear ones, suggesting that such gradients can be a valuable tool for increasing the proteome coverage of mass spectrometry-based experiments.

Place, publisher, year, edition, pages
2013. Vol. 85, no 16, 7777-7785 p.
National Category
Analytical Chemistry
URN: urn:nbn:se:su:diva-94188DOI: 10.1021/ac401145qISI: 000323471800024OAI: diva2:652556


Funding Agencies:

Science for Life Laboratory;  European Commission;   Austrian Science Fund via the Special Research Program Chromosome Dynamics  SFBF3402; Translational-Research-Program  TRP308 

Available from: 2013-10-01 Created: 2013-09-30 Last updated: 2013-10-16Bibliographically approved
In thesis
1. Chromatographic retention time prediction and its applications in mass spectrometry-based proteomics
Open this publication in new window or tab >>Chromatographic retention time prediction and its applications in mass spectrometry-based proteomics
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Mass spectrometry-based methods are among the most commonly used techniques to characterize proteins in biological samples. With rapid technological developments allowing increasing throughput, thousands of proteins can now be monitored in a matter of hours. However, these advances brought a whole new set of analytical challenges. At the moment, it is no longer possible to rely on human experts to process the data. Instead, accurate computational tools are required.

In line with these observations, my research work has involved development of computational methods to facilitate the analysis of mass spectrometry-based experiments. In particular, the projects included in this thesis revolve around the chromatography step of such experiments, where peptides are separated according to their hydrophobicity.

The first part of the thesis describes an algorithm to predict retention time from peptide sequences. The method provides more accurate predictions compared to previous approaches, while being easily transferable to other chromatography setups. In addition, it gives equally good predictions for peptides carrying arbitrary posttranslational modifications as for unmodified peptides.

The second part of the thesis includes two applications of retention time predictions in the context of mass spectrometry-based proteomics experiments. First, we show how theoretical calculations of masses and retention times can be used to infer proteins in shotgun proteomics experiments. Secondly, we illustrate the use of retention time predictions to calculate optimized gradient functions for reversed-phase liquid chromatography.

Place, publisher, year, edition, pages
Department of Biochemistry and Biophysics. Stockholm University, 2013. 58 p.
mass spectrometry; reversed-phase liquid chromatography; retention time prediction; bioinfomatics; computational mass spectrometry
National Category
Bioinformatics and Systems Biology
Research subject
Biochemistry towards Bioinformatics
urn:nbn:se:su:diva-94800 (URN)978-91-7447-775-7 (ISBN)
Public defence
2013-11-29, Magnelisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)

A the time of the doctoral defence the paper nr. 4 had a status Epubl. ahead of  print.

Available from: 2013-11-07 Created: 2013-10-14 Last updated: 2013-10-23Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Moruz, Luminita
By organisation
Department of Biochemistry and BiophysicsScience for Life Laboratory (SciLifeLab)
In the same journal
Analytical Chemistry
Analytical Chemistry

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 32 hits
ReferencesLink to record
Permanent link

Direct link