Recent news from the Griffin lab
- A recent publication, authored by Dr. Griffin and members of the Galaxy-P team, and a team of co-authors from around the globe, describes the use of the Galaxy platform for multi-omic data analysis (Nat Biotechnol. 33:137-9)
- A recent publication describes the use of Galaxy-P for approaches merging genomic and proteomic data, also known as proteogenomics (J Proteome Res. 13:5898-908)
- A study reveals new insights into molecules underlying oral cancer progression (PLoS One 9:e95389)
- Griffin lab members will present at the upcoming U.S. Human Proteome Organization (USHUPO) annual conference
Work in our group involves the development and application of mass spectrometry-based tools to study proteins and proteomes. The goal of this work is to provide the necessary tools to enable the system-wide characterization of proteins expressed within a cell, tissue, biological fluid or organism, in order to better understand basic mechanisms of biological function and disease. These tools must be capable of measuring the many properties of proteins that collectively determine their function. These properties include protein abundance, sub-cellular localization, post-translational modifications, associations in non-covalent complexes and biochemical activity. Mass spectrometry provides a highly powerful tool that can aid in measuring these various protein properties, in a high-throughput manner. The development and application of these tools is highly interdisciplinary in nature, integrating front-end molecular biology and biochemical methods, protein and peptide chemistry, analytical separations, instrumental analysis, and back-end computation and bioinformatics for data analysis and biological interpretation.
Ongoing research projects in the laboratory include:
- Development of new bioinformatics tools implemented in the Galaxy software management framework, focusing on applications that integrate genomic and proteomic data (e.g. proteogenomics and metaproteomics). This work is supported by the NSF. We are utilizing these bioinformatics tools in a variety of collaborative projects with UofM investigators.
- Studies of oral cancer progression and the salivary proteome using a variety of quantitative proteomic strategies, in collaboration with researchers from the Dental School, Medical School, Computer Science and Biostatistics at the University of Minnesota.
- Studies of protein post-translational modifications. These studies include characterization of protein phosphorylation and glycosylation, as well as under-appreciated oxidative stress-induced reactive carbonyl modifications to amino acid side chains.
Boekel,J., Chilton, J.M., Cooke, I.R., Horvatovich, P.L., Jagtap P.D, Käll, L., Lehtiö, J., Lukasse, P., Moerland, P.D. and Griffin, T.J. (2015) Multi-omic data analysis using Galaxy, Nature Biotechnology, 33: 137–139 PMID: 25658277
Jagtap PD, Johnson JE, Onsongo G, Sadler FW, Murray K, Wang Y, Sheynkman GM, Bandhakavi S, Smith LM, Griffin TJ. (2014) Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework. J Proteome Res, 13: 5898-908 PMID: 25301683 PMCID: PMC4261978
Sheynkman GM, Johnson JE, Jagtap PD, Shortreed MR, Onsongo G, Frey BL, Griffin TJ, Smith LM. (2014) Using Galaxy-P to leverage RNA-Seq for the discovery of novel protein variations, BMC Genomics 15: 703. PMID: 25149441; PMCID: PMC4158061
Yang, Y., Rhodus, N.L., Ondrey, F.G., Wuertz, B.R.K., Chen, X., Zhu, Y., and Griffin, T.J. (2014) Quantitative proteomic analysis of oral brush biopsies identifies secretory leukocyte protease inhibitor as a promising, mechanism-based oral cancer biomarker PLoSONE, 9, e95389. PMID: 24748380; PMCID: PMC3991667
Van Riper, S.K., de Jong, E.P., Higgins, L., Carlis, J.V. and Griffin, T.J. (2014) Improved intensity-based label free quantification via proximity-based intensity normalization (PIN) J Proteome Res, 13:1281-92. PMID: 22950739 PMCID; PMCID: PMC3487405
Jagtap P., Goslinga J., Kooren J.A., McGowan T., Wroblewski M.S., Seymour S.L., Griffin T.J. (2013) A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies. Proteomics, 13: 1352-7. PMID: 23412978; PMCID: PMC3633484
Jagtap, P., McGowan, T., Bandhakavi, S., Tu, Z. J., Seymour, S., Griffin, T.J. and Rudney, J.D. (2012) Deep metaproteomic analysis of human salivary supernatant. Proteomics 12: 992-1001. PMID: 22522805; PMCID: PMC3517020
de Jong E, Griffin T.J. (2012) Online nanoscale ERLIC-MS outperforms RPLC-MS for shotgun proteomics in complex mixtures. J Proteome Res, 11, 5059-64. PMID: 22950739; PMCID: PMC3487405
Kim, Y.M., Stone, M., Hwang, T.H., Kim, Y.G., Dunlevy, J.R., Griffin, T.J. and Kim, D.H. (2012) SH3BP4 is a negative regulator of amino acid-Rag GTPase-mTORC1 signaling. Molecular Cell 46. (PDF)