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Single cell cytometry of protein function in RNAi treated cells and in native populations.

LaPan P, Zhang J, Pan J, Hill A, Haney SA - BMC Cell Biol. (2008)

Bottom Line: In a third example, reduction of STAT3 levels by siRNA causes an accumulation of cells in the G1 phase of the cell cycle, but does not induce apoptosis or necrosis when compared to control cells that express the same levels of STAT3.In a final example, the effect of reduced p53 levels on increased adriamycin sensitivity for colon carcinoma cells was demonstrated at the whole-well level using siRNA knockdown and in control and untreated cells at the single cell level.Biological differences that result from changes in protein level or pathway activation state can be modulated directly by RNAi treatment or extracted from the natural variability intrinsic to cells grown under normal culture conditions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Technologies, Oncology Research, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA. plapan@wyeth.cpm

ABSTRACT

Background: High Content Screening has been shown to improve results of RNAi and other perturbations, however significant intra-sample heterogeneity is common and can complicate some analyses. Single cell cytometry can extract important information from subpopulations within these samples. Such approaches are important for immune cells analyzed by flow cytometry, but have not been broadly available for adherent cells that are critical to the study of solid-tumor cancers and other disease models.

Results: We have directly quantitated the effect of resolving RNAi treatments at the single cell level in experimental systems for both exogenous and endogenous targets. Analyzing the effect of an siRNA that targets GFP at the single cell level permits a stronger measure of the absolute function of the siRNA by gating to eliminate background levels of GFP intensities. Extending these methods to endogenous proteins, we have shown that well-level results of the knockdown of PTEN results in an increase in phospho-S6 levels, but at the single cell level, the correlation reveals the role of other inputs into the pathway. In a third example, reduction of STAT3 levels by siRNA causes an accumulation of cells in the G1 phase of the cell cycle, but does not induce apoptosis or necrosis when compared to control cells that express the same levels of STAT3. In a final example, the effect of reduced p53 levels on increased adriamycin sensitivity for colon carcinoma cells was demonstrated at the whole-well level using siRNA knockdown and in control and untreated cells at the single cell level.

Conclusion: We find that single cell analysis methods are generally applicable to a wide range of experiments in adherent cells using technology that is becoming increasingly available to most laboratories. It is well-suited to emerging models of signaling dysfunction, such as oncogene addition and oncogenic shock. Single cell cytometry can demonstrate effects on cell function for protein levels that differ by as little as 20%. Biological differences that result from changes in protein level or pathway activation state can be modulated directly by RNAi treatment or extracted from the natural variability intrinsic to cells grown under normal culture conditions.

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Single cell analysis of siRNA knockdown of GFP. siRNAs transfected at increasing doses into RWPE-1 cells stably transduced to constitutively express GFP, are correlated with the reduction of GFP expression, as determined by fluorescence intensity. A. GFP-siRNA accumulation and correlation with GFP levels observed by fluorescence microscopy. B. Average GFP fluorescence levels of wells treated with a GFP-specific siRNA or a non-targeting control siRNA, as indicated. Each box plot displays the median and intrerquartile range of 8 wells. C. For the transfection of siRNAs at a concentration of 3.13 nM, the cells of one well are plotted individually for both GFP and rhodamine fluorescence intensities.
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Figure 1: Single cell analysis of siRNA knockdown of GFP. siRNAs transfected at increasing doses into RWPE-1 cells stably transduced to constitutively express GFP, are correlated with the reduction of GFP expression, as determined by fluorescence intensity. A. GFP-siRNA accumulation and correlation with GFP levels observed by fluorescence microscopy. B. Average GFP fluorescence levels of wells treated with a GFP-specific siRNA or a non-targeting control siRNA, as indicated. Each box plot displays the median and intrerquartile range of 8 wells. C. For the transfection of siRNAs at a concentration of 3.13 nM, the cells of one well are plotted individually for both GFP and rhodamine fluorescence intensities.

Mentions: The reduction of GFP levels in cells by the transfection of siRNAs targeting the GFP mRNA sequence is a common and robust system for the study of RNAi biology and mechanism [33]. Its intrinsic robustness notwithstanding, a high degree of variability is frequently observed in experiments modulating GFP expression. We have used this system to understand the extent of variability on experimental results by analyzing the knockdown of GFP levels at the whole well and single cell level. A prostate epithelial cell line (RWPE-1) that constitutively expressed GFP was treated with an siRNA that targets GFP. Despite carefully optimizing transfection efficiency, an appreciable level of heterogeneity was evident in the cells transfected with the GFP-targeting siRNA, the samples treated with an non-targeting control siRNA (NTC) and even in untreated samples. In all cases, a high range of GFP expression can be observed, despite clear overall differences in the samples treated with an siRNA that targets GFP. This heterogeneity is evident in the case of cells transfected with a rhodamine-labeled siRNA that targets GFP, shown in Figure 1A. As can be observed in the figure, siRNAs effectively transfected localize near the nucleus in P-bodies [34-36]. In these studies, the siRNA is labeled with rhodamine on the sense strand, which allows uptake to be monitored, but the label itself does not interfere with silencing, at least in part because the label is on the passenger, or non-targeting, strand. Instead, it allows uptake to be quantitated on a per-cell basis. Perinuclear accumulation of the sense strand is frequently observed in cationic liposome-mediated siRNA transfections [37], and its accumulation enables limiting the evaluation of GFP levels to only those cells that had been transfected effectively. Box plots were generated using eight independent transfections for each siRNA concentration, as shown in Figure 1B. More GFP expression remains in this experiment than in GFP knockdown experiments reported by others (which can report greater than 90% reduction in GFP levels, [11,38]), however these studies evaluated the effectiveness of targeting sequences in co-transfection experiments, which limits GFP expression to only those cells transfected with the RNAi reagents. Studies that examine RNAi knockdown in cell lines stably expressing GFP show knockdown levels consistent with the data in Figure 1B[39-41]. Some of the difficulties of working with RNAi can be observed in Figure 1B, where average effects of siRNA treatment are subject to limitations in transfection reagent concentrations. In particular, in the specific conditions as set up in the experiment, the higher concentrations produce a small reduction in functional knockdown. We have observed this in specific combinations of cell type, transfection reagent and conditions. Overall, transfection reagents have limited ranges of optimal effectiveness, but the exact ranges are highly dependent on the configuration of the experiment, including source of the cell line used. As such, each experiment needs to be individually optimized, as factors that limit the effective range can be either toxicity or siRNA:lipid and complex:cell number ratios that result in suboptimal introduction of the siRNA (Lapan, P. Zhang, J., Pan, J. and Haney, S.A., manuscript in preparation). In the results shown here, the higher siRNA levels are changing the siRNA:lipid ratio, which is the most likely source of diminished efficacy at the higher siRNA levels.


Single cell cytometry of protein function in RNAi treated cells and in native populations.

LaPan P, Zhang J, Pan J, Hill A, Haney SA - BMC Cell Biol. (2008)

Single cell analysis of siRNA knockdown of GFP. siRNAs transfected at increasing doses into RWPE-1 cells stably transduced to constitutively express GFP, are correlated with the reduction of GFP expression, as determined by fluorescence intensity. A. GFP-siRNA accumulation and correlation with GFP levels observed by fluorescence microscopy. B. Average GFP fluorescence levels of wells treated with a GFP-specific siRNA or a non-targeting control siRNA, as indicated. Each box plot displays the median and intrerquartile range of 8 wells. C. For the transfection of siRNAs at a concentration of 3.13 nM, the cells of one well are plotted individually for both GFP and rhodamine fluorescence intensities.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2529295&req=5

Figure 1: Single cell analysis of siRNA knockdown of GFP. siRNAs transfected at increasing doses into RWPE-1 cells stably transduced to constitutively express GFP, are correlated with the reduction of GFP expression, as determined by fluorescence intensity. A. GFP-siRNA accumulation and correlation with GFP levels observed by fluorescence microscopy. B. Average GFP fluorescence levels of wells treated with a GFP-specific siRNA or a non-targeting control siRNA, as indicated. Each box plot displays the median and intrerquartile range of 8 wells. C. For the transfection of siRNAs at a concentration of 3.13 nM, the cells of one well are plotted individually for both GFP and rhodamine fluorescence intensities.
Mentions: The reduction of GFP levels in cells by the transfection of siRNAs targeting the GFP mRNA sequence is a common and robust system for the study of RNAi biology and mechanism [33]. Its intrinsic robustness notwithstanding, a high degree of variability is frequently observed in experiments modulating GFP expression. We have used this system to understand the extent of variability on experimental results by analyzing the knockdown of GFP levels at the whole well and single cell level. A prostate epithelial cell line (RWPE-1) that constitutively expressed GFP was treated with an siRNA that targets GFP. Despite carefully optimizing transfection efficiency, an appreciable level of heterogeneity was evident in the cells transfected with the GFP-targeting siRNA, the samples treated with an non-targeting control siRNA (NTC) and even in untreated samples. In all cases, a high range of GFP expression can be observed, despite clear overall differences in the samples treated with an siRNA that targets GFP. This heterogeneity is evident in the case of cells transfected with a rhodamine-labeled siRNA that targets GFP, shown in Figure 1A. As can be observed in the figure, siRNAs effectively transfected localize near the nucleus in P-bodies [34-36]. In these studies, the siRNA is labeled with rhodamine on the sense strand, which allows uptake to be monitored, but the label itself does not interfere with silencing, at least in part because the label is on the passenger, or non-targeting, strand. Instead, it allows uptake to be quantitated on a per-cell basis. Perinuclear accumulation of the sense strand is frequently observed in cationic liposome-mediated siRNA transfections [37], and its accumulation enables limiting the evaluation of GFP levels to only those cells that had been transfected effectively. Box plots were generated using eight independent transfections for each siRNA concentration, as shown in Figure 1B. More GFP expression remains in this experiment than in GFP knockdown experiments reported by others (which can report greater than 90% reduction in GFP levels, [11,38]), however these studies evaluated the effectiveness of targeting sequences in co-transfection experiments, which limits GFP expression to only those cells transfected with the RNAi reagents. Studies that examine RNAi knockdown in cell lines stably expressing GFP show knockdown levels consistent with the data in Figure 1B[39-41]. Some of the difficulties of working with RNAi can be observed in Figure 1B, where average effects of siRNA treatment are subject to limitations in transfection reagent concentrations. In particular, in the specific conditions as set up in the experiment, the higher concentrations produce a small reduction in functional knockdown. We have observed this in specific combinations of cell type, transfection reagent and conditions. Overall, transfection reagents have limited ranges of optimal effectiveness, but the exact ranges are highly dependent on the configuration of the experiment, including source of the cell line used. As such, each experiment needs to be individually optimized, as factors that limit the effective range can be either toxicity or siRNA:lipid and complex:cell number ratios that result in suboptimal introduction of the siRNA (Lapan, P. Zhang, J., Pan, J. and Haney, S.A., manuscript in preparation). In the results shown here, the higher siRNA levels are changing the siRNA:lipid ratio, which is the most likely source of diminished efficacy at the higher siRNA levels.

Bottom Line: In a third example, reduction of STAT3 levels by siRNA causes an accumulation of cells in the G1 phase of the cell cycle, but does not induce apoptosis or necrosis when compared to control cells that express the same levels of STAT3.In a final example, the effect of reduced p53 levels on increased adriamycin sensitivity for colon carcinoma cells was demonstrated at the whole-well level using siRNA knockdown and in control and untreated cells at the single cell level.Biological differences that result from changes in protein level or pathway activation state can be modulated directly by RNAi treatment or extracted from the natural variability intrinsic to cells grown under normal culture conditions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Technologies, Oncology Research, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA. plapan@wyeth.cpm

ABSTRACT

Background: High Content Screening has been shown to improve results of RNAi and other perturbations, however significant intra-sample heterogeneity is common and can complicate some analyses. Single cell cytometry can extract important information from subpopulations within these samples. Such approaches are important for immune cells analyzed by flow cytometry, but have not been broadly available for adherent cells that are critical to the study of solid-tumor cancers and other disease models.

Results: We have directly quantitated the effect of resolving RNAi treatments at the single cell level in experimental systems for both exogenous and endogenous targets. Analyzing the effect of an siRNA that targets GFP at the single cell level permits a stronger measure of the absolute function of the siRNA by gating to eliminate background levels of GFP intensities. Extending these methods to endogenous proteins, we have shown that well-level results of the knockdown of PTEN results in an increase in phospho-S6 levels, but at the single cell level, the correlation reveals the role of other inputs into the pathway. In a third example, reduction of STAT3 levels by siRNA causes an accumulation of cells in the G1 phase of the cell cycle, but does not induce apoptosis or necrosis when compared to control cells that express the same levels of STAT3. In a final example, the effect of reduced p53 levels on increased adriamycin sensitivity for colon carcinoma cells was demonstrated at the whole-well level using siRNA knockdown and in control and untreated cells at the single cell level.

Conclusion: We find that single cell analysis methods are generally applicable to a wide range of experiments in adherent cells using technology that is becoming increasingly available to most laboratories. It is well-suited to emerging models of signaling dysfunction, such as oncogene addition and oncogenic shock. Single cell cytometry can demonstrate effects on cell function for protein levels that differ by as little as 20%. Biological differences that result from changes in protein level or pathway activation state can be modulated directly by RNAi treatment or extracted from the natural variability intrinsic to cells grown under normal culture conditions.

Show MeSH
Related in: MedlinePlus