Journal article
The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS
Journal of proteome research, Vol.7(1), pp.164-169
01/2008
Handle:
https://hdl.handle.net/2376/108957
PMID: 18001079
Abstract
Assessment of differential protein abundance from the observed properties of detected peptides is an essential part of protein profiling based on shotgun proteomics. However, the abundance observed for shared peptides may be due to contributions from multiple proteins that are affected differently by a given treatment. Excluding shared peptides eliminates this ambiguity but may significantly decrease the number of proteins for which abundance estimates can be obtained. Peptide sharing within a family of biologically related proteins does not cause ambiguity if family members have a common response to treatment. On the basis of this concept, we have developed an approach for including shared peptides in the analysis of differential protein abundance in protein profiling. Data from a recent proteomics study of lung tissue from mice exposed to lipopolysaccharide, cigarette smoke, and a combination of these agents are used to illustrate our method. Starting from data where about half of the implicated database protein involved shared peptides, 82% of the affected proteins were grouped into families, based on FASTA annotation, with closure on peptide sharing. In many cases, a common abundance relative to control was sufficient to explain ion-current peak areas for peptides, both unique and shared, that identified biologically related proteins in a peptide-sharing closure group. On the basis of these results, we propose that peptide-sharing closure groups provide a way to include abundance data for shared peptides in quantitative protein profiling by high-throughput mass spectrometry.
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Details
- Title
- The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS
- Creators
- Shuangshuang Jin - School of Electrical Engineering and Computer Science, Washington State University Tri-Cities, 2710 University Drive, Richland, Washington 99352, USADonald S DalyDavid L SpringerJohn H Miller
- Publication Details
- Journal of proteome research, Vol.7(1), pp.164-169
- Academic Unit
- Engineering and Applied Sciences (TRIC), School of
- Publisher
- United States
- Identifiers
- 99900547174601842
- Language
- English
- Resource Type
- Journal article