qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells
| Autor: | Jan-Hendrik Spille, Ibrahim I Cisse, Won-Ki Cho, William Conway, Arjun Narayanan, Takuma Inoue, Jesse D. Thaler, Namrata Jayanth, Susan Mullen, J. O. Andrews |
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| Přispěvatelé: | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology. Department of Physics, Andrews, James Owen, Conway, W., Cho, Won-ki, Narayanan, Arjun, Spille, Jan Hendrik, Jayanth, Namrata, Inoue, Takuma, Thaler, Jesse, Cisse, Ibrahim I, Mullen, Susan |
| Rok vydání: | 2017 |
| Předmět: |
Data Analysis
0301 basic medicine Transcription Genetic Cell Survival Nucleolus Science RNA polymerase II Computational biology Article 03 medical and health sciences RNA Polymerase I Transcription (biology) Cell Line Tumor Gene expression RNA polymerase I Humans Benzothiazoles Naphthyridines Gene Mitosis Enzyme Assays Multidisciplinary biology Cell Cycle Cell cycle 3. Good health 030104 developmental biology biology.protein Medicine Algorithms Software |
| Zdroj: | Nature Scientific Reports Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018) |
| Popis: | We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell. National Institutes of Health (U.S.) National Cancer Institute (U.S.) (NIH Director’s New Innovator Award DP2-CA195769) Massachusetts Institute of Technology. Department of Physics |
| Databáze: | OpenAIRE |
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