QSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells

W -K. Cho,J. O. Andrews,W. Conway,J. Thaler,J -H. Spille,S. Mullen,A. Narayanan,N. Jayanth,T. Inoue,I. I. Cissé

doi:10.1038/s41598-018-25454-0

Abstract

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.

Highlights

We have developed qSR, a software package for quantitative super-resolution data analysis. qSR integrates complementary algorithms that together form a unique tool for the quantitative analysis of single molecule based super-resolution—PALM1,2 and STORM3—data from living cells
Examining the loci with live cell super-resolution imaging [Fig. 2(c)] and quantifying the dynamics of individual loci using time-correlated photoactivated localization microscopy (tcPALM) reveals that these foci are stable [Fig. 2(d)]
A gradual plateau in the tcPALM time trace suggests that the cluster is still present, but the pool of photoconvertible fluorescent proteins is being gradually depleted by activation and bleaching during the imaging process

Summary

Introduction

We have developed qSR, a software package for quantitative super-resolution data analysis. qSR integrates complementary algorithms that together form a unique tool for the quantitative analysis of single molecule based super-resolution—PALM1,2 and STORM3—data from living cells. We have developed qSR, a software package for quantitative super-resolution data analysis. QSR integrates complementary algorithms that together form a unique tool for the quantitative analysis of single molecule based super-resolution—PALM1,2 and STORM3—data from living cells. Recent open software packages integrate tools for visualization, molecular counting and density based clustering[9,10,11,12]. These tools do not readily utilize temporal dynamics of protein clustering in living cells[13,14]. The pointillist data obtained from single-molecule based super-resolution microscopy techniques—such as photoactivated localization microscopy (PALM)[1,2], stochastic optical reconstruction microscopy (STORM)[3] and direct STORM24—can be imported into qSR for visualization and analysis [Fig. 1(b)].

Methods

Results

Conclusion