five

Bay et al. 2022 Figure 1

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
http://flowrepository.org/id/FR-FCM-Z5CR
下载链接
链接失效反馈
官方服务:
资源简介:
To optimize a flow cytometry method that could accurately determine RNAPII levels on chromatin in individual cells, we took advantage of the loss of RNAPII from chromatin in mitosis. Chromatin extraction was performed using a mild detergent (0.5% TX-100) with various NaCl concentrations. To visualize mitotic cells, we co-stained RNAPII with the mitotic marker phosphorylated Histone H3 on Serine 10 (pH3S10). MRC5 cells expressing knock-in GFP-tagged RNAPII (Steurer et al. Proc. Nat. Ac. Sc. (2018) 115, E4368) were used to verify that the pattern of RNAPII antibody staining corresponded to endogenous RNAPII levels. To validate that the flow cytometry method could be used to accurately quantify RNAPII levels on chromatin, we compared RNAPII levels in nocodazole-synchronized mitotic cells measured by flow cytometry versus quantitative western blotting (see published manuscript). Conclusion: Mitotic cells clearly showed lower RNAPII staining after extraction with 140 mM NaCl and above. We chose to use 140 mM NaCl as it is close to physiological conditions and the chromatin levels of RNAPII were clearly lower in the mitotic fraction. Analysis of the GFP signal in MRC5 cells expressing knock-in GFP tagged RNAPII verified that the pattern of RNAPII antibody staining corresponded to endogenous RNAPII levels. Similar levels of RNAPII on chromatin was observed with flow cytometry and quantitative western blotting (see paper). Notes: Cells were extracted prior to fixation to release unbound factors. Indicated samples were treated with 1 ug/mL nocodazole for 16h prior to harvest and barcoded with chromatin extracted cells. Barcoding with non-extracted control cells were used as an internal standard for accurate quantifications and to determine extraction strength. CST was performed prior to analysis
创建时间:
2022-06-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作