Mechanism of mRNA transport in the nucleus

Vargas et al. 10.1073/pnas.0505580102.

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Fig. 5. Comparison of number of mRNP particles obtained from particle counting and real-time RT-PCR. (A) Counting the number of molecules of GFP-mRNA-96-mer expressed in CHO cells. The image was obtained after performing in situ hybridization on the cells by using a fluorescently labeled DNA probe that was specific for the repeated sequence in GFP-mRNA-96-mer. On average, there were 65 molecules of GFP-mRNA-96-mer in each cell. (B) Determination of the average number of GFP-mRNA-96-mer molecules expressed per cell by real-time RT-PCR by using the same batch of cells as in A. A segment of the GFP coding sequence was amplified, and the resulting amplicons were detected by using GFP-specific molecular beacons. RNA extracted from 10,000 cells was used to initiate the amplification reactions. The threshold cycles obtained from two samples (red circles) were plotted against a standard curve (open circles) generated from known amounts of in vitro-transcribed GFP-mRNA. The results indicated that there were ≈80 molecules of GFP-mRNA-96-mer per cell. Cells from clone CHO-GFP-96-mer were cultured in a plastic dish containing gelatin-coated glass coverslips. The cells on each coverslip were then fixed, and in situ hybridization was performed by using a 50-deoxynucleotide-long probe that was complementary to the repeat sequence and was labeled with tetramethylrhodamine at six evenly spaced thymidine residues. In situ hybridization was performed on fixed cells by using probes specific for the repeated sequence, rather than by using molecular beacons in live cells, to ensure that both cytoplasmic and nuclear particles would be counted. After hybridization, individual GFP mRNA molecules were visible as distinct fluorescent spots. For each randomly chosen field, we obtained 22 adjacent z-axis optical sections that were 0.2 mm apart and combined them into a single composite image from which the total number of mRNA particles per cell was counted by using the image-analysis program VOLOCITY (Improvision, Lexington, MA). The remaining cells were detached from the dish and counted in a hemocytometer, after which the RNA in the cells was extracted. Real-time RT-PCR, using this RNA as a template, was then carried out by using primers and molecular beacons that were specific to the GFP coding sequence. Different quantities of GFP-mRNA transcript were used as templates in parallel RT-PCRs to provide a standard curve.

Movie 1. Time-lapse images of individual mRNP particles moving within a cell. This cell is expressing GFP-mRNA-96-mer, which was visualized by the fluorescence of molecular beacons that are complementary to 96 tandemly repeated sequences in the 3' untranslated region of the mRNA. The time interval between each frame is 420 msec.

Movie 2. Tracks of mRNP particles in relation to the chromatin. Chromatin (shown in red) was visualized by the expression of a stably integrated gene for histone H2B fused to GFP. The paths taken by some of the particles during the course of imaging are shown in yellow, and the particles are colored green. To obtain the chromatin image, nine optical sections, each 0.2 mm from the other, were acquired, and deconvolution was performed with respect to the central plane. A set of optical sections for chromatin were acquired just before the initiation of the high-speed time-lapse sequence, and another set of optical sections was acquired at the end of the time-lapse series to confirm that no shift in chromatin position occurred while imaging the motion of the particles.

Movie 3. Locations visited by mRNP particles in relation to the chromatin. The movie on the left contains time-lapse images of mRNP particles (green) superimposed on an image of the chromatin in the nucleus (red). The movie on the right shows the same time-lapse series in the form of "cumulative difference images" to highlight the locations that were visited by mobile particles. This movie was obtained by first subtracting each image from the image that appears 10 frames earlier in the original time-lapse series. From this series of difference images, we obtained cumulative difference images in which each image was colored blue and merged with all of the previous images, which were colored green. Thus, blue dots show the current location of each mRNP particle and green dots show their previous locations. The two large areas that remain relatively dark are nucleoli (Fig. 4C). This movie shows that mRNP particles travel mostly within the interchromatin spaces.

Movie 4. Effects of temperature reduction on the mobility of mRNP particles. Chromatin is shown in red, and the mRNP particles are shown in green.

Movie 5. Effects of ATP depletion on the mobility of mRNP particles. Chromatin is shown in red, and the mRNP particles are shown in green.

Table 2. Statistical parameters associated with particle tracking

The mRNP particles were tracked by using custom software developed in MATLAB (MathWorks Natick, MA). The images in a time series were first passed through a linear filter that enhances particulate objects. The particles were visually identified in the first frame, after which a local threshold was applied to reveal each particle’s outline. The centroid of each outline was used as that particle’s position. Its position in subsequent frames was determined with the aid of a nearest maximum algorithm. If the algorithm failed to correctly identify a particle in the subsequent frame, then provision was made for manual identification. The precision of the particle location was higher than the limit of optical resolution. Tracking was stopped if two particles came so close to each other that their identities became confused.

The MSD of each mRNP particle was determined by averaging the squares of all displacements of the particle between frames separated by a given time interval. The time intervals ranged from the time elapsed between two successive frames to the full duration of the time series. In the averaging, we considered all pairs of time points, rather than just independent pairs of time points. Only MSD measurements determined from time intervals shorter than 25% of the length of time during which each particle was tracked were used to calculate the particle’s diffusion constant because statistical variations become so large for longer intervals that artifactual corrals were predicted to be present where none existed (1). The diffusion constant of corralled particles (identified by the leveling off of their MSD at longer time intervals) was determined in the same manner but only from data obtained during the shorter intervals in which they diffused freely.

The average diffusion constants determined for each condition were computed by taking the weighted average of the diffusion constants for each particle track, where the weight of each track was proportional to its length, because longer tracks yielded statistically more significant data. Whereas this weighting may introduce a bias in the determination of the average diffusion constant in that less mobile particles are more likely to be able to be followed for longer periods, it also minimizes the influence of measurements made on particles whose movements are more difficult to resolve. Although the magnitude of the SDs of these measurements was similar to the magnitude of the diffusion constants, wide variations in diffusion constants are natural features of single-particle tracking measurements due to the stochastic nature of diffusion as well as to differences in the microenvironments through which the particles move (1).

1. Saxton, M. J. (1997) Biophys. J. 72, 1744–1753.

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