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Updated: Jul 16, 2026

Visualization of Protein-protein Interaction in Nuclear and Cytoplasmic Fractions by Co-immunoprecipitation and In Situ Proximity Ligation Assay
Published on: January 16, 2017
The nuclear proteome and DNA-binding fraction of human Raji lymphoma cells
Silke Henrich1, Stuart J Cordwell, Ben Crossett
1School of Molecular and Microbial Biosciences, University of Sydney, Sydney, NSW, Australia.
Abstract:
Purification of organelles and analysis of their proteins is an important initial step for biological proteomics, simplifying the proteome prior to analysis by established techniques such as two-dimensional liquid chromatography (2-DLC) or two-dimensional gel electrophoresis (2-DE). Nuclear proteins play a central role in regulating gene expression, but are often under-represented in proteomic studies due to their lower abundance in comparison to cellular 'housekeeping' metabolic enzymes and structural proteins. A reliable procedure for separation and proteomic analysis of nuclear proteins would be useful for investigations of cell proliferation and differentiation during disease processes (e.g., human cancer). In this study, we have purified nuclei from the human Burkitt's lymphoma B-cell line, Raji, using sucrose density gradient centrifugation. The integrity and purity of the nuclei were assessed by light microscopy and proteins from the nuclear fractions were separated by 2-DE and identified using matrix assisted laser desorption ionization mass spectrometry (MALDI-MS). A total of 124 unique proteins were identified, of which 91% (n=110) were predicted to be nuclear using PSORT. Proteins from the nuclear fraction were subjected to affinity chromatography on DNA-agarose to isolate DNA-binding proteins. From this purified fraction, 131 unique proteins were identified, of which 69% (n=90) were known or predicted DNA-binding proteins. Purification of nuclei and subsequent enrichment of DNA-binding proteins allowed identification of a total of 209 unique proteins, many involved in transcription and/or correlated with lymphoma, leukemia or cancer in general. The data obtained should be valuable for identification of biomarkers and targets for cancer therapy, and for furthering our understanding of the molecular mechanisms underlying lymphoma development and progression.
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