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Quantitative Analysis of Protein Levels in RNAi Experiments Using the DeltaVision Restoration Microscope Paul D. Andrews, Ph.D., Division of Gene Regulation and Expression, Wellcome Trust Biocentre, University of Dundee Summary RNA interference (RNAi) is now a commonplace technique for „knocking down“ or eliminating target gene expression as a means of determining gene function. RNAi can now be performed in a wide range of organisms, from worms and flies to human cells, at the level of a single gene or on the whole-genome scale. As well as representing an essential research tool, RNAi may have an important future in the treatment of human diseases. RNAi is used in different ways by different researchers. RNAi is often used to determine the effect of loss of target gene expression in a population-based biochemical assay, a sledgehammer approach that can yield little meaningful information regarding the effect of genetic loss. A much more powerful approach is to combine RNAi with quantitative high-resolution, single-cell analysis of both protein levels and cellular phenotypes using a suitable microscope. In this article, the advantages of a cell-bycell approach are considered, with illus-trations of how this was used to elucidate the downstream effectors of the Aurora B protein kinase (Andrews et al, 2004). Introduction Over the last five years RNA interference (RNAi) has moved from an obscure phenomenon in plants to a key component in the mammalian cell biologist‘s toolbox (reviewed in Madema, 2004). The number of publications listed in Pubmed involving RNAi has risen meteorically from 5 in 1998, to over 800 in 2003. As well as holding the promise of genome-wide reverse genetics to determine gene function, RNAi may have use in the clinic for the treatment of disease. The future for RNAi technology looks golden.

For many years cell biologists working with model organisms have performed loss-of-function experiments to determine gene function, using an array of techniques ranging from complete gene deletion, regulated gene expression cassettes or protein depletion, use of conditional mutants, dominant negative mutants, antibody microinjection, small molecule inhibitors and antisense technologies. Each approach has its own advantages and limitations. The latest addition to the armory is RNA interference, which can, if performed correctly, selectively and effectively down-regulate mRNA levels encoded by a gene of interest and hence drastically reduce the level of protein product (assuming the protein encoded by that mRNA is turned over at an appreciable rate). The cellular mechanism underlying the technique of RNAi is now well understood but somewhat outside the scope of this article (see review by Madema, 2004). RNAi made its mark initially in C. elegans, with the realization that the mRNA levels transcribed from a selected gene could be down-regulated by feeding worms bacteria harboring a plasmid expressing long double-stranded (ds) RNAs. The utility of this approach in vertebrate cells was hampered by the fact that dsRNA activates the interferon response which in turn shuts down protein synthesis. Over the last two years, technological developments in the synthesis and design of short interfering RNAs (siRNAs) has enabled efficient knockdown of protein expression in vertebrate cells, thereby allowing RNAi to enter the mainstream with vengeance. RNAi Experiments: The Good, the Bad and the Ugly Early adopters of RNAi often failed to appreciate the need for appropriate controls and failed to give appropriate attention to the execution of RNAi experiments. However, now the scientific community is increasingly aware of the necessity to apply rigor in the design and interpretation of RNAi experiments. If manuscripts involving the use of RNAi are to be acceptable for publication in reputable journals, these stringent criteria should be met (for a publishers viewpoint see Nature Cell Biology Editorial).

Aurora B RNAi

Scrambled RNAi

Figure 1. RNAi at the Single Cell Level. HeLa cells were transfected either with siRNA for human Aurora B (left column) or a scrambled control siRNA (right column). 12 hours post-transfection cells were fixed and stained with antibodies against Aurora B, MCAK and CREST. Images are single optical sections from a deconvolved 3D data set saved as a Photoshop file from within SoftWoRx software. For further details see Andrews et al., 2004.

The readout of a particular RNAi study will vary, depending on how the experiment is performed. A popular form of RNAi experiment is one performed on a population of cells growing in a tissue culture dish, which are then harvested, extracts are made and biochemical assays and/or western blots are performed. This type of experiment assays the average „knock down“ and average phenotypic consequence (e.g., changes in overall DNA content, pathway activation/inhibition and so on). The drawbacks of this type of approach are obvious. There is a lack of information on the transfection efficiency, the degree of depletion in individual cell subpopulations, and no correlation between target protein levels and phenotypic consequences. By its very nature, RNAi is a non-amplified response, so there can be intrinsic limitations to the degree of mRNA depletion. This coupled with the fact that different proteins turnover at different rates and proteins may have dramatically different turnover rates under different conditions, or in different parts of the same cell, often means that RNAi produces a hypomorphic mutant, making the experimental results difficult to interpret. An alternative and more rigorous approach is to analyze RNAi experiments on a cell-by-cell basis. Levels of depletion can then be quantified and correlated with phenotype, as determined by some other set of measurements. An example of such an experiment is shown in Figure 1 where Aurora B protein kinase is depleted from HeLa cells and then localization of a downstream substrate is monitored.

Quantitative RNAi Analysis: How Low is Low? The very nature of RNAi means that 100% depletion of a target protein is not likely. Therefore, the ability to accurately quantify the levels of target protein expression on a cell-by-cell basis is essential for the interpretation of the experiment. Critical factors are signal-to-noise ratio and dynamic range, areas where wide-field microscopes excel over laser-scanning confocals (Swedlow et al., 2002). Furthermore, the DeltaVision Restoration Microscope offers many significant advantages over other wide-field configurations. In our lab, we have used the DeltaVision system because of its flexibility, integrated operation, superior illumination characteristics, rapid and accurate deconvolution algorithm and the image analysis software suite. When RNAi is used to dissect the intricacies of protein function in cells, the ability to make accurate measurements at a variety of levels becomes of paramount importance. The measurement of target protein levels is merely the first step which precedes myriad further measurements, such as fluorescence density, degrees of co-localization, distances between structures, their lengths, volumes, shapes and so on. Digital deconvolution can increase contrast and signal-to-noise levels, thereby aiding quantitative analyses. However, deconvolution methods differ considerably (reviewed in Wallace et al, 2001; Andrews et al, 2002). The implementation of the constrained iterative deconvolution algorithm used at the core of the DeltaVision Restoration Microscope technology, performs well with many data types and, coupled with the software tools available within the softWoRx suite, allows the user to thoroughly characterize the phenotypic consequences of loss of target gene expression. The accuracy of the restored image is critical for these types of measurements.

Fig. 2A

Fig. 2B

Fig. 2C

Figure 2. Measuring Protein Expression Levels in Cells. A) Quantifying protein levels in an Aurora B RNAi cell using the Polygon Tool. B) Measuring the colocalization of a downstream substrate of Aurora B with a secondary marker in a cell lacking Aurora B. C) Quantitative measurement of Aurora B-dependent substrate phosphorylation using phospho-specific antibody staining using Polygon tools, showing both tabular and graphic outputs. D) Qualitative line profile analysis of Aurora B and MCAK phosphorylation levels of two cells - one largely lacking Aurora B and one with wildtype levels of Aurora B.

Fig. 2D

Examples of such analyses are shown in Figures 2A through 2D. We routinely inspect intensities in ROIs using Data Inspector and, when necessary, we can quantify the fluorescent intensity in a whole cell in 3D using the Edit Polygon tool coupled with 3D Object Builder, outputting the data to a spreadsheet format for subsequent further analysis. We validated this approach by showing that the results obtained with the cell-by-cell approach mirror those from a biochemical analysis of protein levels by 1D and 2D gel electrophoresis and western blotting (Andrews et al., 2004). Furthermore, with the softWoRx software, colocalization of two other signals in a 2D ROI or in a 3D image can be assessed in RNAi and control cells (Figure 2B). RNAi AND LIVE CELL IMAGING While the majority of RNAi experiments are currently performed on cells that ultimately will be fixed and stained, increasingly cell biologists are asking questions relating to dynamic processes and therefore they have begun to analyze RNAi experiments in living cells. Unfortunately, all too often, analysis is performed without adequate controls to ensure the individual cells being observed have been successfully transfected with the RNAi reagent. One approach that can be used to find cells that have taken up siRNA, is to fluorescently label the siRNA - the positively transfected cells can then be found readily. Transfected cells can be followed by time-lapse microscopy using a readout of choice - fluorescence,

phase contrast or differential interference contrast microscopy. An alternative and more attractive approach is to use short hairpin RNAs expressed from a plasmid-based system. If this plasmid also expresses a fluorescent marker such as EGFP or EGFP fused to Histone H2B (I.M. Porter, personal communication), then individual cells expressing the RNAi molecule can be tracked readily. In the case of EGFP-H2B, chromosome movement and cell cycle progression can also be monitored (See Figure 3). In pilot experiments in fixed cells, the percentage of GFP-expressing cells that have also lost expression of the target protein can be measured, giving one a confidence level for interpreting the experimental data. Inevitably, to interpret these types of experiments large datasets need to be obtained and analyzed. The DeltaVision Restoration Microscope has many advantages over laser scanning microscopes for this type of experiment - the combination of high dynamic range, high sensitivity cooled CCD image acquisition, low signal-to-noise and the rapidity of image acquisition, mean exposure times can be kept low, making it more likely that cells remain viable during the experiment. Moreover, the DeltaVision‘s ability to image large numbers of cells in one experiment using its Point Visiting function is of significant importance. Analysis of more cells means more data, better statistics and greater insight.

Figure 3. RNAi in Live Cells Using EGFP-H2B as a Marker. A. Several EGFP-expressing cells are monitored by epifluorescence as they progress through the cell cycle. B. A single EGFP-H2B-expressing cell is observed using both differential interference contrast (DIC) and fluorescence.

THE FUTURE OF RNAi An emerging extension of the basic RNAi experiment is to introduce a stably integrated inducible RNAi cassette into cells and perform a real genetic complementation experiment by introducing mutant versions of the target gene into these cells (Lens et al, 2003). This powerful approach will undoubtedly revolutionize the analysis of protein function in mammalian cells. An interesting development is the combination of RNAi with measurements of intracellular protein dynamics, using techniques such as FRAP and FLIP. These types of experiment can be performed on both wide-field and laser-scanning confocal microscopes, although in our experience measurement of high speed recovery at high spatial resolution is better suited to the spotbleaching performed by the DeltaVision RT QLM module (Andrews et al, 2004 and unpublished observations). Complementary approaches combine RNAi with the use of photo-activatable GFP fusions, to measure the dynamics of discrete protein populations and FRET, to Measure RNAi is a useful and versatile tool for loss-offunction analysis. When RNAi experiments are properly controlled, protein levels accurately quantified at the single cell level and phenotypes thoughtfully analyzed, the technique is extremely powerful and promises much for the future.

References Andrews, P.D., Harper, I. and Swedlow, J.R. (2002) To 5D and Beyond: Quantitative Fluorescence Microscopy in the Post-genomic Era. Traffic 3, 29-36 Andrews, P.D. Ovechkina, Y., Morrice, N., Duncan, K., Wagenbach, M., Wordeman, L. and Swedlow, J.R. (2004) Aurora B Regulates MCAK at the Mitotic Centromere. Developmental Cell, 6, 253-268. Lens, S. M., Wolthuis, R. M., Klompmaker, R., Kauw, J., Agami, R., Brummelkamp, T., Kops, G. and Medema, R. H. (2003) Survivin is required for a sustained spindle checkpoint arrest in response to lack of tension. EMBO J. 22, 2934-2947. Madema, R.H. (2004) Biochem. J. Immediate Publication, doi:10.1042/BJ20040260. 1st April 2004. Swedlow, J.R., Hu, K., Andrews, P.D., Roos, D.S. and Murray, J.M. (2002) Measuring tubulin content in Toxoplasma gondii: A comparison of laser-scanning confocal and wide-field fluorescence microscopy. Proc. Natl. Acad. Sci. (USA) 99, 2014-2019. Wallace, W., Schaefer, L.H., and Swedlow, J.R. 2001. A working persons guide to deconvolution in light microscopy. Biotechniques. 31, 1076-1097. Editorial (2003) Wither RNAi. Nature Cell Biol. 5 (6), 489490.

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Quantitative Analysis