Measuring transcription dynamics in living cells using fluctuation analysis

Abstract

Single-cell studies of gene regulation suggest that transcription dynamics play a fundamental role in determining expression heterogeneity within a population. In addition, the three-dimensional organization of the nucleus seems to both reflect and influence expression patterns in the cell. Therefore, to gain a holistic understanding of transcriptional regulation, it is necessary to develop methods for studying transcription of single genes in living cells with high spatial and temporal resolution. In this chapter, we describe a recently developed approach for visualizing and quantifying pre-mRNA synthesis at a single active gene in the nucleus. The approach is based on the high-affinity interaction between MS2/PP7 bacteriophage coat proteins and RNA hairpins which are transcribed by the gene of interest. The MS2/PP7 coat protein is fused to a fluorescent protein and binds the nascent mRNA, allowing for detection of single transcription events in the fluorescence microscope. By time-lapse fluorescence imaging and quantitative image analysis, one can generate a time trace of fluorescence intensity at the site of transcription. By temporal autocorrelation analysis, one can determine enzymatic activities of RNAP such as initiation rate and elongation rate. In this protocol, we summarize the experimental concept, design, and execution for real-time observation of transcription in living cells.

Figure 1.

Scheme for observing nascent RNA in living cells. The approach is based on the high affinity binding of bacteriophage coat protein (i.e. MS2) to hairpins in the nascent RNA. Each stem loop binds a dimer of the coat protein, and each coat protein is labeled with a fluorescent protein (i.e. GFP). A) 5’ UTR labeling. When stem loops are located in the 5’ UTR, it is possible to visualize the RNA shortly after elongation commences. Here, three nascent RNAs are visible, resulting in a signal which is three times brighter than a single RNA. B) 3’ UTR labeling. When stem loops are located in the 3’ UTR, the nascent RNA is only visible once the polymerase proceeds to the end of the gene. Here, only a single nascent RNA contributes to the fluorescence signal.

Figure 2.

Visualization of nascent RNA in living cells. A) DIC image of U2-OS cells containing a reporter gene inserted randomly into the genome. Nucleoli are visible as dense bodies within the nucleus. B) Fluorescence image of PP7-mCherry coat protein with a nuclear localization signal. The coat protein accumulates in the nucleus. The nascent transcription site is visible as a punctate spot (white arrows). At high coat protein expression levels, one frequently observes nucleolus staining as well. The box indicates the region which is magnified in panel D. C) Merge of panels A, B. Transcription sites are indicated with white arrows. D) Magnification of the demarcated region in panel B. The transcription site is visible near the edge of the nucleus.

Figure 3.

Fluctuation analysis of transcription activity. A) Representative individual fluorescence image from a single transcription site time series. Scale bar = 1.5 μm. B) Surface plot of panel A. C) Two-dimensional Gaussian fit to the data in panel A. D) Transcription site intensity trajectory. Each data point in the curve comes from a determination of spot intensity using the Gaussian mask algorithm. The spot is tracked over many frames, and missing frames are interpolated based on the last known position of the spot. The final output of the tracking program is the fluorescence of the transcription site as a function of time. E) Autocorrelation. The time series intensity trajectory is autocorrelated using a multi-tau correlation algorithm. The x-axis is the correlation decay; the y-axis is the amplitude of the autocorrelation. The fit parameters for the 5’ UTR case are shown graphically: the amplitude of the autocorrelation is related to the number of polymerases (cT), and the characteristic decay is related to the dwell time of the polymerase (T).