Dynamics of single-cell gene expression

Abstract

Cellular behavior has traditionally been investigated by utilizing bulk-scale methods that measure average values for a population of cells. Such population-wide studies mask the behavior of individual cells and are often insufficient for characterizing biological processes in which cellular heterogeneity plays a key role. A unifying theme of many recent studies has been a focus on the development and utilization of single-cell experimental techniques that are capable of probing key biological phenomena in individual living cells. Recently, novel information about gene expression dynamics has been obtained from single-cell experiments that draw upon the unique capabilities of fluorescent reporter proteins.

Figure 1

p53–Mdm2 pulses in individual cells. (A) p53-CFP expression levels in two individual cells in response to DNA damage (Lahav et al, 2004). (B) At the population level, the response (p53-CFP levels) appears to increase with increasing DNA damage (Lahav et al, 2004). (C) Observations of p53-CFP levels at the single-cell level for limited experimental durations (up to 16 h) suggest that the number of pulses increases with the increase in DNA damage (Lahav et al, 2004). (D) Longer observations (several days) of p53-CFP and Mdm2-YFP expression levels in individual cells in response to DNA damage (Geva-Zatorsky et al, 2006). (E) The results of long observations on cells at four different radiation doses show that the fraction of cells that oscillate increases with gamma dosage (Geva-Zatorsky et al, 2006).

Figure 2

Tracking oscillations in gene expression with GFP reporter proteins. (A) Oscillations in promoter activity. (B) Simulated GFP levels for three different systems: The blue curve represents GFP levels for a system that utilizes a destabilized GFP variant using the following parameter values (Elowitz and Leibler, 2000): transcription rate of 0.5 transcripts per second, translation rate of 20 proteins per transcript, mRNA half-life of 2 min, GFP half-life of 90 min (destabilized GFP variant). The orange curve represents GFP levels for a system that utilizes a stable GFP protein with a half-life of several hours (480 min). This system will quickly approach fluorescent saturation levels. The green curve represents GFP levels for a system that utilizes a destabilized GFP variant and has a lower translation rate (5 proteins per transcript). This system will produce a fluorescent signal that is harder to distinguish from background fluorescence.

Figure 3

Steps involved in processing time-lapse images (Cookson et al, 2005). The first step in the image analysis process involves filtering high-frequency noise and subtracting background and cellular autofluorescence values. Next, each image is segmented into individual cells by using a seeding technique to determine approximate cell locations, producing a set of dams that separate the cell seeds, and expanding the cellular area from the seed to a specified intensity level. A cell tracking algorithm is applied to a time series of segmented images to obtain a time course for each cell.

Figure 4

Diagram of the main steps involved in fabricating a microfluidic device. The first step in the fabrication process is to develop a photomask design using a computer drawing package and to print the design onto transparency film at high resolution. The second step is to coat a silicon support with photoresist and expose the photoresist to ultraviolet light through the photomask. The third step is to dissolve the unexposed photoresist to obtain a reusable master. The master consists of cured photoresist on the silicon support with a pattern defined by the photomask. The fourth step is to pour PDMS over the master and cure the PDMS by baking at 80°C for 1 h. The fifth step is to release the hardened PDMS from the master. The sixth step is to bind the PDMS to the glass coverslip.