Over the past decade or so, there has been increasing evidence that RNA molecules are responsible for a wide range of functions in living cells, from the physical conveyance and interpretation of genetic information, structural support for molecular machines, and regulation/silencing of gene expression, to essential catalytic roles. These functions are realized through control of the expression level and stability, both temporally and spatially, of specific RNAs in a cell. The ability to acquire complete spatial-temporal profiles of RNA synthesis, processing, and transport is therefore of critical importance to our understanding of cell function and behavior in conditions of health and disease and in response to external stimuli. This level of insight could offer unprecedented opportunities for advancement in molecular biology, disease pathophysiology, drug discovery, and medical diagnostics.
The important role RNA plays in dictating cell behavior has led to the development of numerous methods for measuring gene expression and/or measuring differences in gene expression levels between cell populations. Several of the more widely adopted methods include polymerase chain reaction (PCR) (64
), Northern hybridization (or Northern blotting) (3
), expressed sequence tag (EST) (1
), serial analysis of gene expression (SAGE) (89
), representational difference analysis (RDA) (44
), differential display (43
), suppression subtractive hybridization (SSH) (18
), and DNA microarrays (69
). These technologies, combined with the rapidly increasing availability of genomic data for numerous biological entities, present exciting possibilities for understanding human health and disease. In fact, gene expression profiling has already led to the identification of numerous pathogenic and carcinogenic sequences that are being evaluated as clinical markers for diseased states. However, the ability to detect and identify foreign or mutated nucleic acids in a clinical setting remains challenging due to the low abundance of diseased cells in blood, sputum, and stool samples, combined with the need to lyse a population of cells in order to obtain an adequate amount of genetic material for analysis. This can result in many genetic alterations being overlooked or lost.
Although each of the aforementioned RNA detection methods can provide the relative change in gene expression for a population of cells, they generally cannot provide a measure of RNA expression at the single-cell level. Under many circumstances, it is the aberrant behavior of only a few cells or the stochasticity of RNA expression within a population that may be of interest (9
). Arduous techniques such as single-cell reverse transcriptase-polymerase chain reaction (RT-PCR) can provide a closer look at RNA transcripts within single cells, but the RNA must still be extracted from the actual cell and processed prior to analysis. The shortcomings associated with RNA handling have been highlighted in several recent studies, which have shown that up to 90% of transcripts can be lost during RNA purification, cDNA synthesis, and other steps required for PCR (34
Due to the complexity of single-cell RT-PCR, single-cell analysis of RNA expression (and localization) is typically carried out by in situ hybridization (ISH), whereby labeled linear oligonucleotide (ODN) probes are used to label intracellular RNA in cells that are fixed and permeabilized (5
). Unbound probes are removed by washing to reduce background and to achieve specificity (14
). To enhance the signal level, multiple probes targeting the same messenger RNA (mRNA) can be used (5
). If a sufficient number of probes are used to target each mRNA, it has been found that individual mRNAs within single cells can be visualized, and the absolute number of RNA per cell can be quantified (24
). Clearly, this strategy can allow for unique insight into mRNA abundance; however, RNA-ISH can provide only very limited temporal resolution of RNA expression. Further, these techniques are laborious and very time consuming, image analysis is not trivial, and heterogeneity between samples remains a possibility. Specifically, fixation agents and other supporting chemicals can have considerable effect on signal level (7
) and possibly on the integrity of certain organelles, such as mitochondria. Thus, fixation of cells, by either cross-linking or denaturing agents, and the use of proteases in ISH assays may lead to an inaccurate description of intracellular mRNA expression.
To obtain detailed spatial and temporal information on RNA dynamics, including the expression, localization, degradation, and storage of RNA molecules, much effort has recently been devoted to developing nanostructured molecular probes for imaging RNA in living cells. Live cell imaging not only eliminates the need to handle RNA, but also provides an opportunity to analyze gene expression at the single-cell level without arduous fixation, permeabilization, and washing steps. Clearly, live cell imaging strategies that are capable of providing a more complete spatial-temporal profile of gene expression would be of significant value in our understanding of the role genetic processing plays in cellular function and disease. However, in order to detect RNA molecules in living cells, the RNA imaging probes must exhibit a high specificity, sensitivity, and signal-to-background ratio, especially for low abundance genes and clinical samples containing a small number of diseased cells. The imaging probes need to recognize RNA targets with high specificity, convert target recognition directly into a measurable signal, and differentiate between true- and false-positive signals. For real-time measurements of RNA expression, it is also important for the probes to associate and dissociate from target RNA with fast kinetics. For detecting genetic alterations such as mutations, insertions, and deletions, the ability to recognize single nucleotide polymorphisms (SNPs) is essential. To achieve this optimal performance, it is necessary to have a good understanding of the structure-function relationship of the probes, probe stability, and RNA target accessibility in living cells. It is also necessary to achieve efficient cellular delivery of probes with minimal probe degradation.
In the remaining sections, we review commonly used fluorescent probes for RNA detection in living cells and subsequently discuss some of the critical issues that are faced by all of these approaches, including target accessibility, fluorophore selection, and the cellular delivery of probes.