Symplectic ID:
384546
Source:
PubMed
This is the preferred source?:
1
Last Synced with Symplectic:
Sunday, 26 April, 2026 - 15:13
DOI:
10.1016/j.jprot.2012.10.009
Publication Date:
Friday, 2 August, 2013
First Page:
14
Last Page:
26
Keywords:
AGC
AP-MS
Affinity Purification based Mass Spectrometry
Automatic Gain Control
CID
Collision induced dissociation
Dimethyl labeling
FDR
False Discovery Rate
HCD
Higher energy C-trap dissociation
Isobaric Tag for Relative and Absolute Quantification
Isobaric labeling
MS/MS
NCE
Normalized Collision Energy
PSMs
Peptide to Spectrum Matches
Quantitation
SCX
SILAC
Stable Isotope Labeling by Amino acids in Cell culture
Strong Cation Exchange
TMT
Tandem Mass Spectrometry
Tandem Mass Tag
iTRAQ
Algorithms
Databases, Protein
HeLa Cells
Humans
Isotope Labeling
Mass Spectrometry
Proteome
Proteomics
Editors list has been truncated:
Abstract:
Several quantitative mass spectrometry based technologies have recently evolved to interrogate the complexity, interconnectivity and dynamic nature of proteomes. Currently, the most popular methods use either metabolic or chemical isotope labeling with MS based quantification or chemical labeling using isobaric tags with MS/MS based quantification. Here, we assess the performance of three of the most popular approaches through systematic independent large scale quantitative proteomics experiments, comparing SILAC, dimethyl and TMT labeling strategies. Although all three methods have their strengths and weaknesses, our data indicate that all three can reach a similar depth in number of identified proteins using a classical (MS2 based) shotgun approach. TMT quantification using only MS2 is heavily affected by co-isolation leading to compromised precision and accuracy. This issue may be partly resolved by using an MS3 based acquisition; however, at the cost of a significant reduction in number of proteins quantified. Interestingly, SILAC and chemical labeling with MS based quantification produce almost indistinguishable results, independent of which database search algorithm used.
Journal Title:
J Proteomics
eISSN:
1876-7737
Volume:
88
ID at Source:
23085607
Publication Status:
Published
Open access:
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SSO preference:
chem0943