Epigenomic profiling of histone turnover kinetics in mammalian cells We have developed a revolutionary technology, CATCH-IT (for Covalent Attachment of Tags to Capture Histones and Identify Turnover) to directly measure nucleosome turnover. The CATCH-IT method involves labeling of newly synthesized proteins with an amino acid analog, derivatization with a biotin moiety, selective extraction of nucleosome core particles, affinity purification with streptavidin, and extraction of DNA for genome-wide profiling. We have successfully obtained genome-wide CATCH-IT profiles for Drosophila cultured cells, and we have used these data to address the relationship between histone turnover and fundamental processes, including transcriptional initiation and elongation, epigenetic regulation and determination of replication origins. In the present proposal, we aim to apply CATCH-IT technology to mammals, and to survey nucleosome turnover dynamics in a range of cell types and epigenetic processes.
In Aim 1, we will apply CATCH-IT to pluripotent stem cells and early steps in differentiation.
In Aim 2, we will apply CATCH-IT to cancer studies, using the E5-Myc mouse model of Burkitt's lymphoma and other mouse models of epithelial cells.
In Aim 3, we will apply CATCH-IT to examine the effects of environmental perturbation, including steroid hormone treatment, DNA damage and heat shock on histone turnover kinetics. As CATCH-IT does not require transgenic lines, antibodies or tags, it has the potential of becoming both an invaluable tool for understanding chromatin dynamics and a general system for monitoring epigenetic changes relevant to human health and disease.
The epigenome is dynamic, in that the proteins that package and compact DNA about one million-fold must be transiently removed in order for processes such as DNA replication, transcription into RNA and DNA repair to occur. Our novel CATCH-IT method is the first to directly measure the dynamics of removal and replacement of these proteins in vivo, and so has the potential of providing a genome-wide map of epigenome dynamics. Our project will explore the application of CATCH-IT to measuring dynamic changes in the epigenome involved developmental regulation, cancer, and DNA damage, with broad diagnostic potential.
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