Quantitative imaging of pre-mRNA splicing factors in living cells.

Abstract

The recent development of techniques for visualizing structures and processes in the living cell has paved the way for studies of the functional organization of the cell nucleus in vivo. Live cell studies generate complex data, which require computational approaches for time-resolved analysis and visual interpretation of dynamic processes (Marshall et al., 1997 ; Misteli and Spector, 1997 ). Here we review recently developed concepts for quantification and visual display of time- and space-resolved processes, in particular the dynamics of pre-mRNA splicing factors in the nucleus of mammalian cells. Until recently, most studies on nuclear architecture were carried out in fixed cells (for a comprehensive review, see Lamond and Earnshaw, 1998 ). In situ hybridization methods have revealed that chromosomes occupy distinct territories, whereby actively transcribing genes are preferentially positioned at their periphery (Eils et al., 1996 ; Kurz et al., 1996 ). The machinery for pre-mRNA processing is localized in a distinct pattern of 20–40 nuclear speckles, which typically do not coincide with sites of active splicing (Spector, 1993 ). Hence, the highest concentration of pre-mRNA splicing factors is found at sites where no or very little splicing seems to occur. The mechanisms of how transcription and pre-mRNA splicing are coordinated in space and time in vivo are poorly characterized. Even less is known about the mechanisms and forces involved in the assembly and dynamics of functional subnuclear compartments in response to metabolic requirements. To analyze how the various steps of gene expression are related to the structure of the nucleus, it is crucial to reveal the spatial and temporal interplay of transcription, pre-mRNA splicing and 3′ processing. Live cell analysis using fusion proteins of the green fluorescent protein (GFP) linked to splicing factors has recently shown that nuclear speckles are highly dynamic (Misteli et al., 1997 ). Movements and morphological alterations of nuclear speckles under various experimental conditions have been investigated by visual inspection. It has been observed that dynamics of nuclear speckles depend on RNA polymerase II activity, because inhibition of RNA polymerase II by drugs such as α-amanitin clearly reduces dynamics. High structural dynamics are often correlated with the budding of small structures from speckles. These budding structures might be interpreted as splicing factor aggregates transported to sites of transcribed genes. Experiments with triggered transcriptional gene activation have provided clues that transcriptional activation leads to subnuclear redistribution of splicing factors. This supports a model of nuclear speckles as transient storage and/or assembly sites for pre-mRNA splicing factors that are delivered to sites of active transcription (Misteli et al., 1998 ; Misteli and Spector, 1998 ). The targeting mechanism from storage and/or assembly sites to the actual site of transcription involves the serine phosphorylation of SR protein splicing factors and subsequent binding to the C-terminal domain of the large subunit of RNA polymerase II (Misteli and Spector, 1999 ). These studies were based on purely qualitative studies of time-lapse movies in living cells. Such an evaluation is very time consuming and also limited by the perception of the manual inspector. Because the total light exposure during in vivo observation must be minimized to avoid disruptions of nuclear processes, the signal-to-noise ratio and more importantly the number of sequential images taken in a particular experiment is considerably reduced, leading to a loss in spatiotemporal resolution. Displaying time series as movies is a widely used method for visual interpretation. However, this approach does not improve temporal resolution, because additional information about the continuous development of the processes between imaged time steps is not obtained. More importantly, quantitative information is not revealed by such a visual approach. A quantitative analysis requires the isolation and tracking of fluorescent structures in the time series. In many studies in fixed cells fully automated isolation of fluorescent structures was achieved by background subtraction followed by thresholding. In live cell studies with typically low signal-to-noise-ratio an approach based on gray value maxima only often fails. We recently developed a fully automated system for time-resolved analysis of dynamic processes in living cells (Tvaruskoet al., 1999 ), which is based on the assumption that structures of interest can be characterized by regions of locally homogeneous gray value distribution rather than by absolutely maximal intensity. By image reconstruction in time and space, it has been shown that it is possible to partially regain both temporal and spatial resolution. Here we discuss a recently developed quantitative approach to the study of the dynamics of pre-mRNA splicing factors in living cells. This approach is widely applicable and will be generally useful in the analysis of biological time-lapse microscopy data.