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A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites

Alexander Koch (UGent) , Daria Fijalkowska (UGent) , Sandra Steyaert (UGent) , Elvis Ndah (UGent) , Jeroen Crappé (UGent) , Sarah De Keulenaer (UGent) , Ellen De Meester (UGent) , Ming Ma, Ben Shen, Kris Gevaert (UGent) , et al.
(2014) PROTEOMICS. 14(23-24). p.2688-2698
Author
Organization
Abstract
Next-generation transcriptome sequencing is increasingly integrated with MS to enhance MS-based protein and peptide identification. Recently, a breakthrough in transcriptome analysis was achieved with the development of ribosome profiling (ribo-seq). This technology is based on the deep sequencing of ribosome-protected mRNA fragments, thereby enabling the direct observation of in vivo protein synthesis at the transcript level. In order to explore the impact of a ribo-seq-derived protein sequence search space on MS/MS spectrum identification, we performed a comprehensive proteome study on a human cancer cell line, using both shotgun and N-terminal proteomics, next to ribosome profiling, which was used to delineate (alternative) translational reading frames. By including protein-level evidence of sample-specific genetic variation and alternative translation, this strategy improved the identification score of 69 proteins and identified 22 new proteins in the shotgun experiment. Furthermore, we discovered 18 new alternative translation start sites in the N-terminal proteomics data and observed a correlation between the quantitative measures of ribo-seq and shotgun proteomics with a Pearson correlation coefficient ranging from 0.483 to 0.664. Overall, this study demonstrated the benefits of ribosome profiling for MS-based protein and peptide identification and we believe this approach could develop into a common practice for next-generation proteomics.
Keywords
INITIATION, SEQUENCES, DEEP PROTEOME, GENE-EXPRESSION, HUMAN-CELLS, SPECTROMETRY-BASED PROTEIN, Translation initiation, RNA-SEQ DATA, Ribosome profiling, Proteogenomics, N-terminomics, Bioinformatics, MICRORNAS, PEPTIDES, DATABASE

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MLA
Koch, Alexander, et al. “A Proteogenomics Approach Integrating Proteomics and Ribosome Profiling Increases the Efficiency of Protein Identification and Enables the Discovery of Alternative Translation Start Sites.” PROTEOMICS, vol. 14, no. 23–24, 2014, pp. 2688–98, doi:10.1002/pmic.201400180.
APA
Koch, A., Fijalkowska, D., Steyaert, S., Ndah, E., Crappé, J., De Keulenaer, S., … Menschaert, G. (2014). A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites. PROTEOMICS, 14(23–24), 2688–2698. https://doi.org/10.1002/pmic.201400180
Chicago author-date
Koch, Alexander, Daria Fijalkowska, Sandra Steyaert, Elvis Ndah, Jeroen Crappé, Sarah De Keulenaer, Ellen De Meester, et al. 2014. “A Proteogenomics Approach Integrating Proteomics and Ribosome Profiling Increases the Efficiency of Protein Identification and Enables the Discovery of Alternative Translation Start Sites.” PROTEOMICS 14 (23–24): 2688–98. https://doi.org/10.1002/pmic.201400180.
Chicago author-date (all authors)
Koch, Alexander, Daria Fijalkowska, Sandra Steyaert, Elvis Ndah, Jeroen Crappé, Sarah De Keulenaer, Ellen De Meester, Ming Ma, Ben Shen, Kris Gevaert, Wim Van Criekinge, Petra Van Damme, and Gerben Menschaert. 2014. “A Proteogenomics Approach Integrating Proteomics and Ribosome Profiling Increases the Efficiency of Protein Identification and Enables the Discovery of Alternative Translation Start Sites.” PROTEOMICS 14 (23–24): 2688–2698. doi:10.1002/pmic.201400180.
Vancouver
1.
Koch A, Fijalkowska D, Steyaert S, Ndah E, Crappé J, De Keulenaer S, et al. A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites. PROTEOMICS. 2014;14(23–24):2688–98.
IEEE
[1]
A. Koch et al., “A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites,” PROTEOMICS, vol. 14, no. 23–24, pp. 2688–2698, 2014.
@article{5822064,
  abstract     = {{Next-generation transcriptome sequencing is increasingly integrated with MS to enhance MS-based protein and peptide identification. Recently, a breakthrough in transcriptome analysis was achieved with the development of ribosome profiling (ribo-seq). This technology is based on the deep sequencing of ribosome-protected mRNA fragments, thereby enabling the direct observation of in vivo protein synthesis at the transcript level. In order to explore the impact of a ribo-seq-derived protein sequence search space on MS/MS spectrum identification, we performed a comprehensive proteome study on a human cancer cell line, using both shotgun and N-terminal proteomics, next to ribosome profiling, which was used to delineate (alternative) translational reading frames. By including protein-level evidence of sample-specific genetic variation and alternative translation, this strategy improved the identification score of 69 proteins and identified 22 new proteins in the shotgun experiment. Furthermore, we discovered 18 new alternative translation start sites in the N-terminal proteomics data and observed a correlation between the quantitative measures of ribo-seq and shotgun proteomics with a Pearson correlation coefficient ranging from 0.483 to 0.664. Overall, this study demonstrated the benefits of ribosome profiling for MS-based protein and peptide identification and we believe this approach could develop into a common practice for next-generation proteomics.}},
  author       = {{Koch, Alexander and Fijalkowska, Daria and Steyaert, Sandra and Ndah, Elvis and Crappé, Jeroen and De Keulenaer, Sarah and De Meester, Ellen and Ma, Ming and Shen, Ben and Gevaert, Kris and Van Criekinge, Wim and Van Damme, Petra and Menschaert, Gerben}},
  issn         = {{1615-9853}},
  journal      = {{PROTEOMICS}},
  keywords     = {{INITIATION,SEQUENCES,DEEP PROTEOME,GENE-EXPRESSION,HUMAN-CELLS,SPECTROMETRY-BASED PROTEIN,Translation initiation,RNA-SEQ DATA,Ribosome profiling,Proteogenomics,N-terminomics,Bioinformatics,MICRORNAS,PEPTIDES,DATABASE}},
  language     = {{eng}},
  number       = {{23-24}},
  pages        = {{2688--2698}},
  title        = {{A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites}},
  url          = {{http://doi.org/10.1002/pmic.201400180}},
  volume       = {{14}},
  year         = {{2014}},
}
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