publication . Article . 2017

ProteoModlR for functional proteomic analysis.

Sagar Chhangawala; Alex Kentsis; Alex Kentsis; Mojdeh Shakiba; Paolo Cifani;
Open Access
  • Published: 01 Mar 2017 Journal: BMC Bioinformatics, volume 18 (eissn: 1471-2105, Copyright policy)
  • Publisher: Springer Science and Business Media LLC
Abstract
Background High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries of quantified synthetic peptides are becoming available, enabling absolute quantification of chemically modified proteoforms, and therefore systems-level analyses of changes of their absolute abundance and stoichiometry. Existing computational methods provide advanced tools for mass spectral analysis and statistical inference, but lack integrated functions for quantitative analysis of post-translationally modified proteins and their modification...
Subjects
free text keywords: Biochemistry, Applied Mathematics, Molecular Biology, Structural Biology, Computer Science Applications, Software, Mass spectrometry, Post-translational modification stoichiometry, Functional analysis, R, Biology, Computational biology, Normalization (statistics), Bioinformatics, Proteome, Quantitative proteomics, Imputation (statistics), Proteomics, Quantitative analysis (chemistry), Statistical inference, Missing data
Funded by
NIH| Phosphoproteomic signatures for early detection and stratification of AML
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R21CA188881-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| MOUSE GENETICS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2P30CA008748-43
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Aberrant activation of HGF/MET signaling as a therapeutic target in AML
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K08CA160660-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Aberrant signaling in acute myeloid leukemia
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01CA204396-03
  • Funding stream: NATIONAL CANCER INSTITUTE
21 references, page 1 of 2

Aebersold, R, Mann, M. Mass spectrometry-based proteomics. Nature. 2003; 422 (6928): 198-207 [PubMed] [DOI]

Zhou, F, Lu, Y, Ficarro, SB, Adelmant, G, Jiang, W, Luckey, CJ, Marto, JA. Genome-scale proteome quantification by DEEP SEQ mass spectrometry. Nat Commun. 2013; 4: 2171 [OpenAIRE] [PubMed]

Hebert, AS, Richards, AL, Bailey, DJ, Ulbrich, A, Coughlin, EE, Westphall, MS, Coon, JJ. The one hour yeast proteome. Mol Cell Proteomics. 2014; 13 (1): 339-347 [OpenAIRE] [PubMed] [DOI]

Eng, JK, McCormack, AL, Yates, JR. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom. 1994; 5 (11): 976-989 [OpenAIRE] [PubMed] [DOI]

Steen, H, Mann, M. The ABC‘s (and XYZ’s) of peptide sequencing. Nat Rev Mol Cell Biol. 2004; 5 (9): 699-711 [OpenAIRE] [PubMed] [DOI]

Kirkpatrick, DS, Gerber, SA, Gygi, SP. The absolute quantification strategy: a general procedure for the quantification of proteins and post-translational modifications. Methods. 2005; 35 (3): 265-273 [OpenAIRE] [PubMed] [DOI]

Graumann, J, Hubner, NC, Kim, JB, Ko, K, Moser, M, Kumar, C, Cox, J, Scholer, H, Mann, M. Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins. Mol Cell Proteomics. 2007; 7 (4): 672-683 [PubMed] [DOI]

Wu, R, Dephoure, N, Haas, W, Huttlin, EL, Zhai, B, Sowa, ME, Gygi, SP. Correct interpretation of comprehensive phosphorylation dynamics requires normalization by protein expression changes. Mol Cell Proteomics. 2011; 10 (8): M111.009654 [OpenAIRE] [PubMed] [DOI]

Cox, J, Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008; 26 (12): 1367-1372 [OpenAIRE] [PubMed] [DOI]

Cox, J, Neuhauser, N, Michalski, A, Scheltema, RA, Olsen, JV, Mann, M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011; 10 (4): 1794-1805 [OpenAIRE] [PubMed] [DOI]

MacLean, B, Tomazela, DM, Shulman, N, Chambers, M, Finney, GL, Frewen, B, Kern, R, Tabb, DL, Liebler, DC, MacCoss, MJ. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 2010; 26 (7): 966-968 [OpenAIRE] [PubMed] [DOI]

Choi, M, Chang, C-Y, Clough, T, Broudy, D, Killeen, T, MacLean, B, Vitek, O. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics. 2014; 30 (17): 2524-2526 [OpenAIRE] [PubMed] [DOI]

Linding, R, Jensen, LJ, Pasculescu, A, Olhovsky, M, Colwill, K, Bork, P, Yaffe, MB, Pawson, T. NetworKIN: a resource for exploring cellular phosphorylation networks. Nucleic Acids Res. 2008; 36 (Database issue): D695-9 [OpenAIRE] [PubMed]

14.R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. 2014. http://www.R-project.org/.

Gerber, SA, Rush, J, Stemman, O, Kirschner, MW, Gygi, SP. Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc Natl Acad Sci U S A. 2003; 100 (12): 6940-6945 [OpenAIRE] [PubMed] [DOI]

21 references, page 1 of 2
Abstract
Background High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries of quantified synthetic peptides are becoming available, enabling absolute quantification of chemically modified proteoforms, and therefore systems-level analyses of changes of their absolute abundance and stoichiometry. Existing computational methods provide advanced tools for mass spectral analysis and statistical inference, but lack integrated functions for quantitative analysis of post-translationally modified proteins and their modification...
Subjects
free text keywords: Biochemistry, Applied Mathematics, Molecular Biology, Structural Biology, Computer Science Applications, Software, Mass spectrometry, Post-translational modification stoichiometry, Functional analysis, R, Biology, Computational biology, Normalization (statistics), Bioinformatics, Proteome, Quantitative proteomics, Imputation (statistics), Proteomics, Quantitative analysis (chemistry), Statistical inference, Missing data
Funded by
NIH| Phosphoproteomic signatures for early detection and stratification of AML
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R21CA188881-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| MOUSE GENETICS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2P30CA008748-43
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Aberrant activation of HGF/MET signaling as a therapeutic target in AML
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K08CA160660-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Aberrant signaling in acute myeloid leukemia
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01CA204396-03
  • Funding stream: NATIONAL CANCER INSTITUTE
21 references, page 1 of 2

Aebersold, R, Mann, M. Mass spectrometry-based proteomics. Nature. 2003; 422 (6928): 198-207 [PubMed] [DOI]

Zhou, F, Lu, Y, Ficarro, SB, Adelmant, G, Jiang, W, Luckey, CJ, Marto, JA. Genome-scale proteome quantification by DEEP SEQ mass spectrometry. Nat Commun. 2013; 4: 2171 [OpenAIRE] [PubMed]

Hebert, AS, Richards, AL, Bailey, DJ, Ulbrich, A, Coughlin, EE, Westphall, MS, Coon, JJ. The one hour yeast proteome. Mol Cell Proteomics. 2014; 13 (1): 339-347 [OpenAIRE] [PubMed] [DOI]

Eng, JK, McCormack, AL, Yates, JR. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom. 1994; 5 (11): 976-989 [OpenAIRE] [PubMed] [DOI]

Steen, H, Mann, M. The ABC‘s (and XYZ’s) of peptide sequencing. Nat Rev Mol Cell Biol. 2004; 5 (9): 699-711 [OpenAIRE] [PubMed] [DOI]

Kirkpatrick, DS, Gerber, SA, Gygi, SP. The absolute quantification strategy: a general procedure for the quantification of proteins and post-translational modifications. Methods. 2005; 35 (3): 265-273 [OpenAIRE] [PubMed] [DOI]

Graumann, J, Hubner, NC, Kim, JB, Ko, K, Moser, M, Kumar, C, Cox, J, Scholer, H, Mann, M. Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins. Mol Cell Proteomics. 2007; 7 (4): 672-683 [PubMed] [DOI]

Wu, R, Dephoure, N, Haas, W, Huttlin, EL, Zhai, B, Sowa, ME, Gygi, SP. Correct interpretation of comprehensive phosphorylation dynamics requires normalization by protein expression changes. Mol Cell Proteomics. 2011; 10 (8): M111.009654 [OpenAIRE] [PubMed] [DOI]

Cox, J, Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008; 26 (12): 1367-1372 [OpenAIRE] [PubMed] [DOI]

Cox, J, Neuhauser, N, Michalski, A, Scheltema, RA, Olsen, JV, Mann, M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011; 10 (4): 1794-1805 [OpenAIRE] [PubMed] [DOI]

MacLean, B, Tomazela, DM, Shulman, N, Chambers, M, Finney, GL, Frewen, B, Kern, R, Tabb, DL, Liebler, DC, MacCoss, MJ. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 2010; 26 (7): 966-968 [OpenAIRE] [PubMed] [DOI]

Choi, M, Chang, C-Y, Clough, T, Broudy, D, Killeen, T, MacLean, B, Vitek, O. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics. 2014; 30 (17): 2524-2526 [OpenAIRE] [PubMed] [DOI]

Linding, R, Jensen, LJ, Pasculescu, A, Olhovsky, M, Colwill, K, Bork, P, Yaffe, MB, Pawson, T. NetworKIN: a resource for exploring cellular phosphorylation networks. Nucleic Acids Res. 2008; 36 (Database issue): D695-9 [OpenAIRE] [PubMed]

14.R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. 2014. http://www.R-project.org/.

Gerber, SA, Rush, J, Stemman, O, Kirschner, MW, Gygi, SP. Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc Natl Acad Sci U S A. 2003; 100 (12): 6940-6945 [OpenAIRE] [PubMed] [DOI]

21 references, page 1 of 2
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