Mass spectrometry technology has the potential to revolutionize the biological sciences by enabling quantitative and comprehensive assessment of proteins (proteomics) and metabolites (metabolomics). A major challenge, however, is converting raw mass spectrometry data into information useful to biologists. This project represents an effort to transform proteomics and metabolomics by providing an open-source platform for analysis of mass spectrometry-based metabolomics and proteomics data which capitalizes on cyberinfrastructure to accelerate biological discovery. Specifically, the project will develop a unified platform for identification and quantitation of metabolites, peptides, and proteins (the MS-Omics Hub) that (1) allows the user to enter mass spectrometry data from diverse instrumentation and returns to the user identities and quantities of assignable metabolite, peptide, and protein peaks, (2) highlights novel, biologically significant species whose importance emerged through cyber-enabled integration of data from diverse users, and (3) provides enhanced computational algorithms for identification of covalently-modified proteins. These algorithms will revolve around an integer linear optimization framework that the PIs have recently shown can substantially improve proteomic data analysis. The utility of the MS-Omics Hub will be demonstrated through its application to a broad spectrum of data, generated both by the grant team and by a diversity of scientists nationwide.
Intellectual Merit: This effort tackles a barrier preventing proteomics and metabolomics from broadly impacting biological research: the difficulty of extracting compound identities and quantities from raw data. It furthermore addresses the intellectually challenging aspect of proteomic data analysis: computational identification of peaks arising from covalently modified proteins. Finally, it applies cyber-infrastructure to accelerate the identification of peaks arising from novel, biologically-significant metabolites and protein covalent modification sites. The diversity of intellectual challenges involved is mirrored by the multidisciplinary nature of the research team: Floudas, Garcia, and Rabinowitz come from three different departments at Princeton University (Chemical Engineering, Molecular Biology, and Chemistry, respectively), and bring expertise spanning global optimization, scientific computing, mathematical modeling, proteomics, metabolomics, and analytical chemistry. They are unified by their interest in comprehensive, quantitative, computationally-enabled analysis of biochemical systems.
Broader Impacts:
This research has the potential to transform the biological sciences, by accelerating progress in proteomics and metabolomics and by rendering the power of these emerging fields accessible to a broad spectrum of scientists nationwide. Impact on Society: By enabling a larger research community to conduct state-of-the-art metabolomic and proteomic data analysis, the MS-Omics Hub will expedite global research efforts. By providing an archive of biologically significant peaks, it will accelerate discovery of novel metabolites and protein covalent modification sites. These will likely include novel biomarkers and bioactive compounds. Areas in which improved metabolomic and proteomic capabilities will be applied include medicine, drug discovery, agriculture, bioenergy, and environmental science. Integration of Research and Education: This effort will integrate participation of undergraduate and graduate students in all aspects of the research program, include underrepresented minorities and visiting students from small colleges. The students will receive training in mass spectrometry, computational biology, systems biology, and scientific computation. In addition, as an open-source platform, the MS-Omics Hub will be available as an educational tool to scholars nationwide. The PIs also plan to host an annual ?users? conference to interact with and train the outside MS-Omics Hub users, and to recruit new users to the Hub. Broaden Representation of Underrepresented Groups: Each of the PIs will actively recruit minority students for summer research. Dissemination: In addition to dissemination through standard channels (journals, refereed proceedings, conferences), the MS-Omics Hub will be introduced to the community through a network of mass spectrometry experts, biological beta-testers, and the summer conference. The MS-Omics Hub itself will be open-source (code available on web) and freely accessible to scientists worldwide.
