Work in the Griffin group focuses on developing mass spectrometry-based technologies for the molecular analysis of biological systems and disease. An additional emphasis is on the development of bioinformatic software tools (see galaxyp.org) for integrating multi-omics information - including genomic, transcriptomic, proteomic and metabolomic data. With an emphasis on collaborative, interdisciplinary research, these tools are used to investigate molecular mechanisms underlying basic biology and translational studies of human disease and cancer.
Work in my group focuses on 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. My group also works on the Galaxy for proteomics, or Galaxy-P project, which focuses on “multi-omic” analysis integrating genomic, proteomic and metabolomic data to gain new insights into biological systems. Our work is highly interdisciplinary and collaborative, working across the fields of analytical chemistry, computer science and biochemistry. We work with numerous researchers to apply our tools and technologies to problems of biological and biomedical importance.
For more information on the Galaxy-P project and research team go to: galaxyp.org
Thuy-Boun PS, Mehta S, Gruening B, McGowan T, Nguyen A, Rajczewski AT, Johnson JE, Griffin TJ, Wolan DW, Jagtap PD. (2021) Metaproteomics Analysis of SARS-CoV-2-Infected Patient Samples Reveals Presence of Potential Coinfecting Microorganisms. J Proteome Res. PMID: 33393790 2.
Rajczewski AT, Mehta S, Nguyen DDA, Grüning B, Johnson JE, McGowan T, Griffin TJ, Jagtap PD. (2021) A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19). Clin Proteomics. 18:15. PMID: 33971807 3.
Sajulga R, Easterly C, Riffle M, Mesuere B, Muth T, Mehta S, Kumar P, Johnson J, Gruening BA, Schiebenhoefer H, Kolmeder CA, Fuchs S, Nunn BL, Rudney J, Griffin TJ, Jagtap PD. (2020) Survey of metaproteomics software tools for functional microbiome analysis. PLoS One. 15:e0241503. PMID: 33170893 4.
Mehta S, Easterly CW, Sajulga R, Millikin RJ, Argentini A, Eguinoa I, Martens L, Shortreed MR, Smith LM, McGowan T, Kumar P, Johnson JE, Griffin TJ, Jagtap PD. (2020) Precursor Intensity-Based Label-Free Quantification Software Tools for Proteomic and Multi-Omic Analysis within the Galaxy Platform. Proteomes. 8:15. PMID: 32650610. 5.
Kumar P, Johnson JE, Easterly C, Mehta S, Sajulga R, Nunn B, Jagtap PD, Griffin TJ. (2020) A Sectioning and Database Enrichment Approach for Improved Peptide Spectrum Matching in Large, Genome-Guided Protein Sequence Databases. J Proteome Res. 19:2772-2785. PMID: 32396365 6.
McGowan T, Johnson JE, Kumar P, Sajulga R, Mehta S, Jagtap PD, Griffin TJ. (2020) Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration. Gigascience. 9:giaa025. PMID: 32236523 7.
Easterly CW, Sajulga R, Mehta S, Johnson J, Kumar P, Hubler S, Mesuere B, Rudney J, Griffin TJ, Jagtap PD. metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes. (2019) Mol Cell Proteomics. 18(8 suppl 1):S82-S91 8.
Kumar P, Panigrahi P, Johnson J, Weber WJ, Mehta S, Sajulga R, Easterly C, Crooker BA, Heydarian M, Anamika K, Griffin TJ, Jagtap P. QuanTP: A software resource for quantitative proteo-transcriptomic comparative data analysis and informatics. (2019) J Proteome Res.18:782-790. PMID: 30582332 9.
Sajulga R, Mehta S, Kumar P, Johnson JE, Guerrero CR, Ryan MC, Karchin R, Jagtap PD, Griffin TJ. Bridging the Chromosome-centric and Biology/Disease-driven Human Proteome Projects: Accessible and Automated Tools for Interpreting the Biological and Pathological Impact of Protein Sequence Variants Detected via Proteogenomics (2018) J Proteome Res. 17:4329 4336. PMID: 30130115 10.
Afiuni-Zadeh S, Boylan KLM, Jagtap PD, Griffin TJ, Rudney JD, Peterson ML, Skubitz APN. Evaluating the potential of residual Pap test fluid as a resource for the metaproteomic analysis of the cervical-vaginal microbiome (2018) Sci Rep. 8:10868 PMID: 30022083 11.
Sandri BJ, Kaplan A, Hodgson SW, Peterson M, Avdulov S, Higgins L, Markowski T, Yang P, Limper AH, Griffin TJ, Bitterman P, Lock EF, Wendt CH. Multi-omic molecular profiling of lung cancer in COPD. (2018) Eur Respir J. 52: 1702665 PMID: 29794131 12.
Blank C, Easterly C, Gruening B, Johnson J, Kolmeder CA, Kumar P, May D, Mehta S, Mesuere B, Brown Z, Elias JE, Hervey WJ, McGowan T, Muth T, Nunn B, Rudney J, Tanca A, Griffin TJ, Jagtap PD. Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework. (2018) Proteomes. 6: E7. PMID: 29385081 13.
Chambers MC, Jagtap PD, Johnson JE, McGowan T, Kumar P, Onsongo G, Guerrero CR, Barsnes H, Vaudel M, Martens L, Grüning B, Cooke IR, Heydarian M, Reddy KL, Griffin TJ. An accessible proteogenomics informatics resource for cancer researchers (2017) Cancer Res 77:e43-6. PMID: 29092937 14.
Afiuni-Zadeh, S., Rogers, J.C., Snovida, S.I., Bomgarden, R.D., Griffin, T.J. (2016) AminoxyTMT: A novel multi-functional reagent for proteomic characterization of protein carbonylation BioTechniques,60:186-196. PMID: 27071607 15.
Van Riper, S.K., Higgins, L., Carlis, J.V. and Griffin, T.J. (2016) RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification, Bioinformatics,32:2035-7. PMID: 27153682
Education and background
Ph.D., University of Wisconsin, 1999
Director, Center for Mass Spectrometry and Proteomics Ph.D., University of Wisconsin, 1999
Postdoctoral Research, University of Washington and Institute for Systems Biology, 1999-2003