The Proteomics Core enhances the research productivity of KCI members by providing the equipment and trained personnel necessary for analysis of cellular proteome composition, protein modification, protein quantitation and protein interaction. The Proteomics Core is grouped in the Basic Research Core Cluster which, in addition to the Proteomics Core, includes the Microscopy, Imaging and Cytometry Resources Core and the Animal Model and Therapeutics Evaluation Core. The services provided by the Proteomics Core have contributed to 16 peer-reviewed publications during the current review period. Proteome profiling and protein identification services utilize state-of-the-art mass spectrometer-based methods. The platforms for analyses are the Thermo Fisher Orbitrap Fusion equipped with Electron Transfer Dissociation and the Thermo Fisher Q Exactive Orbitrap. Isolated protein, gel plug and full proteome analysis are supported. Sample preparation is achieved by robotic or manual depletion of high abundance proteins, chemical labeling, digestion and solid phase extraction (SPE). A full range of sorbents including specialized sorbents such as TiO2 for isolation of phosphopeptides are available for SPE. Nanoflow HPLC from Easy-nLC 1000 and Michrom H4 platforms is utilized for analyses with a Triversa Nanomate robot available as needed. Data analysis is achieved using Mascot, Sequest-HT, X!Tandem, MaxQuant and PEAKS algorithms with secondary data analysis by Scaffold Q+ and Scaffold PTM. Results are distributed electronically using our ftp server. The Core enhances research productivity by providing a clear and easily accessible process for protein identification and for relative quantitation of proteins based on isotopic labels. Quantitation technologies supported include Spectral Counting, cICAT, iTraq, TMT, SILAC and Multiple Reaction Monitoring (MRM). Analysis of isotopically labeled samples is achieved using Proteome Discoverer, MaxQuant and the Mascot Quantitation package as appropriate. MRM analysis is achieved using the TSQ Vantage with Skyline software for experimental design and data analysis. The protein identification and quantitation component of the Proteomics Core provides KCI members access to technology for protein identification, proteomic profiling and biomarker identification. The protein interactions component of the Core provides instrumentation and services for detection of protein binding by Fluorescence Polarization (FP). The instruments in the Core produce sensitive, accurate and real time measurements of protein binding events. Thus, the protein interactions component of the Core supports investigators in interrogating protein-protein interactions and the effects of those interactions on signaling pathways and cellular function.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA022453-36
Application #
9384728
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
36
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Wayne State University
Department
Type
DUNS #
001962224
City
Detroit
State
MI
Country
United States
Zip Code
48202
Burl, Rayanne B; Ramseyer, Vanesa D; Rondini, Elizabeth A et al. (2018) Deconstructing Adipogenesis Induced by ?3-Adrenergic Receptor Activation with Single-Cell Expression Profiling. Cell Metab 28:300-309.e4
Dedigama-Arachchige, Pavithra M; Acharige, Nuwan P N; Pflum, Mary Kay H (2018) Identification of PP1-Gadd34 substrates involved in the unfolded protein response using K-BIPS, a method for phosphatase substrate identification. Mol Omics 14:121-133
Desai, Pinkal; Wallace, Robert; Anderson, Matthew L et al. (2018) An analysis of the association between statin use and risk of endometrial and ovarian cancers in the Women's Health Initiative. Gynecol Oncol 148:540-546
Thakur, Manish K; Ruterbusch, Julie J; Schwartz, Ann G et al. (2018) Risk of Second Lung Cancer in Patients with Previously Treated Lung Cancer: Analysis of Surveillance, Epidemiology, and End Results (SEER) Data. J Thorac Oncol 13:46-53
Ma, Huiyan; Ursin, Giske; Xu, Xinxin et al. (2018) Body mass index at age 18 years and recent body mass index in relation to risk of breast cancer overall and ER/PR/HER2-defined subtypes in white women and African-American women: a pooled analysis. Breast Cancer Res 20:5
Mitrea, Cristina; Wijesinghe, Priyanga; Dyson, Greg et al. (2018) Integrating 5hmC and gene expression data to infer regulatory mechanisms. Bioinformatics 34:1441-1447
Simon, Michael S; Beebe-Dimmer, Jennifer L; Hastert, Theresa A et al. (2018) Cardiometabolic risk factors and survival after breast cancer in the Women's Health Initiative. Cancer 124:1798-1807
Luca, Francesca; Kupfer, Sonia S; Knights, Dan et al. (2018) Functional Genomics of Host-Microbiome Interactions in Humans. Trends Genet 34:30-40
Hastert, T A; de Oliveira Otto, M C; Lê-Scherban, F et al. (2018) Association of plasma phospholipid polyunsaturated and trans fatty acids with body mass index: results from the Multi-Ethnic Study of Atherosclerosis. Int J Obes (Lond) 42:433-440
Bock, Cathryn H; Jay, Allison M; Dyson, Gregory et al. (2018) The effect of genetic variants on the relationship between statins and breast cancer in postmenopausal women in the Women's Health Initiative observational study. Breast Cancer Res Treat 167:741-749

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