(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.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Sheeley, Douglas
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Indiana University Bloomington
Other Domestic Higher Education
United States
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Masellis, Chiara; Khanal, Neelam; Kamrath, Michael Z et al. (2017) Cryogenic Vibrational Spectroscopy Provides Unique Fingerprints for Glycan Identification. J Am Soc Mass Spectrom 28:2217-2222
DeGraan-Weber, Nick; Ward, Sarah A; Reilly, James P (2017) A Novel Triethylphosphonium Charge Tag on Peptides: Synthesis, Derivatization, and Fragmentation. J Am Soc Mass Spectrom 28:1889-1900
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
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
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
Li, Sujun; Dabir, Aditi; Misal, Santosh A et al. (2016) Impact of Amidination on Peptide Fragmentation and Identification in Shotgun Proteomics. J Proteome Res 15:3656-3665
Li, Sujun; Tang, Haixu (2016) Computational Methods in Mass Spectrometry-Based Proteomics. Adv Exp Med Biol 939:63-89
Ji, Chao; Li, Sujun; Reilly, James P et al. (2016) XLSearch: a Probabilistic Database Search Algorithm for Identifying Cross-Linked Peptides. J Proteome Res 15:1830-41
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
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

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