What do expression dynamics tell us about the mechanism of transcription?

Abstract

Single-cell microscopy studies have the potential to provide an unprecedented view of gene expression with exquisite spatial and temporal sensitivity. However, there is a challenge to connect the holistic cellular view with a reductionist biochemical view. In particular, experimental efforts to characterize the in vivo regulation of transcription have focused primarily on measurements of the dynamics of transcription factors and chromatin modifying factors. Such measurements have elucidated the transient nature of many nuclear interactions. In the past few years, experimental approaches have emerged that allow for interrogation of the output of transcription at the single-molecule, single-cell level. Here, I summarize the experimental results and models that aim to provide an integrated view of transcriptional regulation.

Figure 1

Single-Cell Gene Expression. A) Dynamics of the prolactin promoter in rat pituitary cells observed by measuring the activity of a luciferase reporter (Scale=25 μm). [7]. B) Live-cell visualization of transcription of the POL1 gene in S. cerevisae using the PP7 system (Scale=3μm) [6]. C) Time-lapse imaging of CCAAT-luciferase in the H1 NIH-3T3 cell line (Scale=20 μm) [8]. D) Single molecule FISH of P_lac promoter gene expression level in E. coli (Scale=2 μm) [5].

Figure 2

The two-state model of gene expression. A) The promoter activity (red line) toggles between two states, “off” and “on”. During the active state (promoter “on”), transcripts are produced, indicated by vertical green lines. B) A special case of the two-state model is the random telegraph model, where the rates of transition and transcription initiation are all determined by single rate-limiting steps (a, b, c), resulting in average intervals of a^-1, b^-1, c^-1. Rate constants a, b, c are units of inverse time, but often the RNA decay rate in the cytosol is used to normalize these rates to produce unit-less quantities. The “burst parameter” is the number of transcripts produced per active state (c/b). Frequency modulation results from changing a; burst-size modulation results from changing either c or b; transcription rate modulation results from changing c. C) The opposite extreme of the telegraph model is the case where transitions are determined by many sequential steps, none of which are rate limiting. Each “step” is depicted by an arrow. D) The intermediate case is one in which activation requires many steps, corresponding to sequential activation or ordered recruitment, but the de-activation is determined by a single rate-limiting step. This scheme is consistent with the observation that transcription in higher eukaryotes is hard to turn on but easy to turn off.

Figure 3

A hypothetical view of the relationship between nuclear dynamics and transcriptional regulation. The left column depicts the activity of the gene as a two-state process, and the right column is a schematic of corresponding events occurring at the gene. The model of promoter progression relies on fast activator dynamics (i.e. green hexagon coming on and off chromatin), resulting in recruitment of chromatin modifying enzymes (yellow hexagon), leading to meta-stable modifications of chromatin (yellow star). Many such sequential events result in a particular set of modifications (yellow, blue, brown stars), ending in recruitment of the basal transcription machinery and initiation of transcription (elongating RNAPII = green oval). The gene transitions to an inactive state after loss of an activating chromatin mark (i.e. the brown star) or possibly by turnover of the nucleosome.