Literature DB >> 26947242

Thousand and one ways to quantify and compare protein abundances in label-free bottom-up proteomics.

Mélisande Blein-Nicolas1, Michel Zivy2.   

Abstract

How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g. peptide counting, spectral counting), while the second makes use of extracted ion currents to quantify chromatographic peaks and infer protein abundances based on peptide quantification. These two approaches actually refer to multiple methods which have been developed during the last decade, but were submitted to deep evaluations only recently. In this paper, we compiled these different methods as exhaustively as possible. We also summarized the way they address the different problems raised by bottom-up protein quantification such as normalization, the presence of shared peptides, unequal peptide measurability and missing data. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.
Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords:  Data processing; Mass spectrometry; Peptide; Statistics

Mesh:

Substances:

Year:  2016        PMID: 26947242     DOI: 10.1016/j.bbapap.2016.02.019

Source DB:  PubMed          Journal:  Biochim Biophys Acta        ISSN: 0006-3002


  24 in total

1.  StPeter: Seamless Label-Free Quantification with the Trans-Proteomic Pipeline.

Authors:  Michael R Hoopmann; Jason M Winget; Luis Mendoza; Robert L Moritz
Journal:  J Proteome Res       Date:  2018-02-14       Impact factor: 4.466

2.  Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data.

Authors:  Karin Schork; Katharina Podwojski; Michael Turewicz; Christian Stephan; Martin Eisenacher
Journal:  Methods Mol Biol       Date:  2021

3.  The ciliary membrane-associated proteome reveals actin-binding proteins as key components of cilia.

Authors:  Priyanka Kohli; Martin Höhne; Christian Jüngst; Sabine Bertsch; Lena K Ebert; Astrid C Schauss; Thomas Benzing; Markus M Rinschen; Bernhard Schermer
Journal:  EMBO Rep       Date:  2017-07-14       Impact factor: 8.807

4.  Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages.

Authors:  R Zhu; L Zacharias; K M Wooding; W Peng; Y Mechref
Journal:  Methods Enzymol       Date:  2017-01-16       Impact factor: 1.600

5.  Simultaneous Quantification of Protein Expression and Modifications by Top-down Targeted Proteomics: A Case of the Sarcomeric Subproteome.

Authors:  Ziqing Lin; Liming Wei; Wenxuan Cai; Yanlong Zhu; Trisha Tucholski; Stanford D Mitchell; Wei Guo; Stephen P Ford; Gary M Diffee; Ying Ge
Journal:  Mol Cell Proteomics       Date:  2018-12-27       Impact factor: 5.911

6.  Deciphering the Role of EGL-3 for Neuropeptides Processing in Caenorhabditis elegans Using High-Resolution Quadrupole-Orbitrap Mass Spectrometry.

Authors:  Jennifer Ben Salem; Bruno Nkambeu; Dina N Arvanitis; Francis Beaudry
Journal:  Neurochem Res       Date:  2018-09-18       Impact factor: 3.996

7.  Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools.

Authors:  Antonio Palomba; Marcello Abbondio; Giovanni Fiorito; Sergio Uzzau; Daniela Pagnozzi; Alessandro Tanca
Journal:  J Proteome Res       Date:  2021-05-26       Impact factor: 4.466

8.  Evaluating Spatiotemporal Dynamics of Phosphorylation of RNA Polymerase II Carboxy-Terminal Domain by Ultraviolet Photodissociation Mass Spectrometry.

Authors:  Edwin E Escobar; Mukesh Kumar Venkat Ramani; Yan Zhang; Jennifer S Brodbelt
Journal:  J Am Chem Soc       Date:  2021-05-31       Impact factor: 16.383

9.  Urinary Proteomic Profile of Arterial Stiffness Is Associated With Mortality and Cardiovascular Outcomes.

Authors:  Dongmei Wei; Jesus D Melgarejo; Lutgarde Thijs; Xander Temmerman; Thomas Vanassche; Lucas Van Aelst; Stefan Janssens; Jan A Staessen; Peter Verhamme; Zhen-Yu Zhang
Journal:  J Am Heart Assoc       Date:  2022-04-12       Impact factor: 6.106

10.  Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum.

Authors:  Kaspar Valgepea; Gert Talbo; Nobuaki Takemori; Ayako Takemori; Christina Ludwig; Vishnuvardhan Mahamkali; Alexander P Mueller; Ryan Tappel; Michael Köpke; Séan Dennis Simpson; Lars Keld Nielsen; Esteban Marcellin
Journal:  mSystems       Date:  2022-04-06       Impact factor: 7.324

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