(Not modified) Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) is a widely used platform for high-throughput identification and quantification of proteins in biological samples. In addition to experimental steps in the pipeline, computational and statistical procedures play important roles in determining the content of the mixture. However, even with the best analytical platforms and modern software, only a small fraction of spectra are typically identified, thus directly impacting the quality of the biological sample analysis. If high- throughput proteomics techniques are to become routinely used in biomedical applications on the population scale, it is critical to address analytical and computational factors that contribute to the inadequate identification coverage and sensitivity. Over the past several years, we and others have spent a significant amount of research activity to understand and model analytical platforms and subsequently improve computational methods for the analyses of complex biological mixtures. While our original grant application has resulted in methods and programs already accepted by the community, there is a need and significant room for further key contributions. We see many of these contributions being related to the analyses of dynamic changes in cells and tissues, and involving changes in protein quantities, protein post-translational modifications (PTMs) and transient protein-protein interactions. Mass spectrometry-based proteomics provides an excellent platform to address each of these challenges. Thus, we plan to continue to develop novel methods for label-free quantification and remain close to our core strengths, but also strongly focus on PTMs and protein-protein interactions as new directions of this renewal application. This application includes a considerably closer collaboration between computational (Dr. Radivojac, Dr. Tang) and experimental (Dr. Arnold, Dr. Clemmer, Dr. Reilly) scientists than did our original application. The investigators bring complementary expertise and experience in a range of disciplines involving protein bioinformatics, algorithms, machine learning, as well as analytical chemistry and instrumentation. Overall, we believe that this proposal will result in significant advances for mass spectrometry-based proteomics.

Public Health Relevance

(Not modified) We propose to develop novel and theoretically sound methodology for several important yet challenging problems in mass spectrometry-based proteomics, including the identification of peptides containing post- translational modifications and cross-linked peptides, and the absolute quantification of proteins in complex samples.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
9R01GM103725-04
Application #
8373375
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Sheeley, Douglas
Project Start
2007-05-01
Project End
2016-07-31
Budget Start
2012-09-30
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$448,534
Indirect Cost
$142,044
Name
Indiana University Bloomington
Department
Type
Other Domestic Higher Education
DUNS #
006046700
City
Bloomington
State
IN
Country
United States
Zip Code
47401
Fuller, Daniel R; Glover, Matthew S; Pierson, Nicholas A et al. (2016) Cis→Trans Isomerization of Pro(7) in Oxytocin Regulates Zn(2+) Binding. J Am Soc Mass Spectrom 27:1376-82
Glover, Matthew S; Dilger, Jonathan M; Acton, Matthew D et al. (2016) Examining the Influence of Phosphorylation on Peptide Ion Structure by Ion Mobility Spectrometry-Mass Spectrometry. J Am Soc Mass Spectrom 27:786-94
Li, Sujun; Bandeira, Nuno; Wang, Xiaofeng et al. (2016) On the privacy risks of sharing clinical proteomics data. AMIA Jt Summits Transl Sci Proc 2016:122-31
DeGraan-Weber, Nick; Zhang, Jun; Reilly, James P (2016) Distinguishing Aspartic and Isoaspartic Acids in Peptides by Several Mass Spectrometric Fragmentation Methods. J Am Soc Mass Spectrom 27:2041-2053
Shi, Liuqing; Holliday, Alison E; Bohrer, Brian C et al. (2016) ""Wet"" Versus ""Dry"" Folding of Polyproline. J Am Soc Mass Spectrom 27:1037-47
DeGraan-Weber, Nick; Ashley, Daniel C; Keijzer, Karlijn et al. (2016) Factors Affecting the Production of Aromatic Immonium Ions in MALDI 157 nm Photodissociation Studies. J Am Soc Mass Spectrom 27:834-46
Shi, Liuqing; Holliday, Alison E; Khanal, Neelam et al. (2015) Configurationally-Coupled Protonation of Polyproline-7. J Am Chem Soc 137:8680-3
Khanal, Neelam; Pejaver, Vikas; Li, Zhiyu et al. (2015) Position of Proline Mediates the Reactivity of S-Palmitoylation. ACS Chem Biol 10:2529-36
Glover, Matthew S; Shi, Liuqing; Fuller, Daniel R et al. (2015) On the split personality of penultimate proline. J Am Soc Mass Spectrom 26:444-52
Glover, Matthew S; Bellinger, Earl P; Radivojac, Predrag et al. (2015) Penultimate proline in neuropeptides. Anal Chem 87:8466-72

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