New generation of DRSC dsRNA libraries
The overriding conclusion from previous studies was that the best way to provide better accuracy in RNAi screening with long dsRNAs was to design the dsRNAs as specifically as possible and use more than one dsRNA to rule out false positives [18
] (Supplementary Figure 2 in [26
]). To achieve this goal, we assembled a new dsRNA collection in which all (7,692) dsRNAs from the initial DRSC1.0 collection predicted to cross-hybridize with unintended targets were replaced with new, independently synthesized dsRNAs free of OTs. These new dsRNAs were combined with the rest of the original dsRNAs that target only the intended genes to make the 'DRSC 2.0' collection. For each new dsRNA, we selected a region that: was shared by all isoforms (if more than one transcript was transcribed from that gene); and was devoid of any predicted 19 nt sequence identity to other genes. Unique primers flanked with the T7 promoter were designed and used to amplify fly genomic DNA. Each PCR product was purified and an aliquot was transcribed in vitro
to yield the corresponding dsRNA. In addition, approximately 6,000 dsRNAs in the original DRSC1.0 collection targeted genes solely predicted computationally (the so-called Heidelberg dsRNAs [2
]. We removed the vast majority of these dsRNAs from the DRSC2.0 collection as there was little evidence to support the idea that their targets corresponded to bona fide
genes, and kept only those (about 10%) for which there was independent confirmation of expression or of the validity of gene prediction in subsequent releases of the Drosophila
genome annotation [31
Furthermore, to confirm the effects of dsRNAs identified in the initial screens, we decided to generate DRSC-v, which is composed of a set of second or third independent dsRNAs targeting a gene identified in a screen, even if the original dsRNA had no predicted OTs. To date, this ever expanding library contains about 7,000 distinct dsRNAs targeting 4,100 genes. The major consideration that went into the design of the validation dsRNAs was that, other than being free of predicted OTs, they should, if possible, not overlap with any of the dsRNAs used in the original DRSC1.0 collection. This was necessary to fulfill the requirement that a set of completely independent dsRNAs be used to confirm the original findings in a primary screen. However, because of the design restrictions, the regions of each gene that were available for targeting were much smaller than what was used for the original DRSC1.0 set. As a result, a majority of the validation dsRNAs are about 200-300 bp in length, as opposed to an average size of 400-500 bp for dsRNAs in the DRSC1.0 screening collection. Although we have failed to observe a strong correlation between size and efficacy in experiments reported here, it remains to be determined whether the smaller size of the validation dsRNAs might lead in some cases to lesser efficiency in knock-down as the probability of generating efficient siRNAs in vivo might be proportional to length.
Re-screening candidate dsRNAs isolated in the screen for regulators of the Wg and Hh pathway with OT-free dsRNAs
To examine the issue of false positives in previously published screens for the Wg and Hh signaling pathways [3
], we have re-assessed the effect of knocking down candidate genes using the new validation dsRNAs (Figure ). We used the same dual luciferase-reporter assays as previously reported [3
]. Since the efficacy of target knockdown could depend on the specific region of a given gene towards which a given dsRNA is designed, we used two independent OT-free dsRNAs for most candidate genes identified in the original screens.
Figure 1 Re-screening the candidate genes identified in previous Wg and Hh screens using the DRSC-v dsRNAs. (a-c) Wg assay: 148 of 204 (73%) dsRNAs screened had reproducible effects on the Wg responsive reporter activity (a); 58% of the DRSC1.0 dsRNAs that were (more ...)
-optimized dTF12 and mammalian-cell optimized STF16 reporters were used for validation screening of the candidate Wg-regulators. In this analysis, we re-screened only 204 of 238 dsRNAs that were previously reported in the Wg screen. The 34 dsRNAs that were omitted from the validation screen were those that targeted the in silico
predicted (Heidelberg annotated) genes [2
]. For 73% (148 of 204) of the genes isolated in the original Wg screen, at least one new DRSC-v dsRNA showed similar effects on the activity of the Wnt/Wg-responsive luciferase reporter as the original dsRNA (Figure ; Additional data files 1&4). In addition, for approximately 40% (80 of the 204) of the original candidate genes tested, two independent OT-free dsRNAs had the same effect on the Wg reporter assay as the original dsRNA (Additional data file 1). Thus, while using multiple independent validation dsRNAs are useful to confirm hits, this approach alone is not definitive in confirming hits because in 68 cases (of the 204 genes screened), one out of three dsRNAs tested failed to give consistent results with the other two. This discrepancy most likely reflects that dsRNAs are not equally effective in knocking down target genes, perhaps as a result of differences in properties between original and validation dsRNAs. In our previous Wnt/Wg screen, we had identified 91 dsRNAs that shared greater than 5 possible 19 nt exact overlaps with other genes that could potentially result in non-specific, OT-related effects on Wg signaling activity (as described in Supplementary Figure S1A and Supplementary Table 2 in [3
]). Interestingly, 58% (53 of 91) of those candidate dsRNAs were validated in the re-screen using independent dsRNAs that do not share 19 nt homology with other transcribed genes (Figure ). On the other hand, of the 113 dsRNAs originally identified as candidate 'hits' in the Wg screen that had ≥5 19 nt OT identities, 85% (95 of 113) repeated using DRSC-v dsRNAs (Additional data file 2). In conclusion, our data suggest that much better reproducibility is observed with dsRNAs that lack any predicted 19 nt sequence overlap with other transcripts.
The GL3-ptcΔ136 reporter described by Nybakken et al
] was used for re-screening the candidate genes isolated in the Hh-signaling screen. For the Hh assay, one or two new dsRNAs were generated targeting 351 of the genes found in the original screen (as with the Wg screen, it should be noted that the Heidelberg annotated presumptive genes were left out of the set to which new validation dsRNAs were generated). Of the 351 candidate Hh signaling genes targeted by the DRSC-v dsRNAs, 51% (179) had at least one new dsRNA score as a hit again in the GL3 assay (Figure , Additional data file 3). Of the 351 genes retested, 285 had two, separate dsRNAs in the DRSC-v collection, and 66 had only one DRSV-v dsRNA. Of the 66 genes, 34 (52%) were re-confirmed with the single available DRSC-v dsRNA. Of the 285 genes re-tested with 2 new dsRNAs, 82 (29%) repeated as hits with both validation dsRNAs, while 22% (63) repeated as a hit with 1 one of the 2 validation dsRNAs (Additional data file 3). In the original Hh screen, 39% (197) of the candidate genes had >5 potential OTs when looking at possible 19 nt overlaps with other genes. Of these 197, 110 were re-tested in the DRSC-v screen (Additional data file 3). Only 24% (26 of 110) were found to have at least one new dsRNA that gave a similar effect as the original dsRNA in the GL3 assay (Figure , Additional data file 3). Of the 241 genes that we retested that had ≥5 potential 19 nt OTs in the original screen, 64% (153) were validated using DRSC-v dsRNAs (Figure ). Thus, similar to the Wg screen, much better reproducibility was observed in the Hh screen with genes that, in the original screen, had been identified using dsRNAs lacking significant 19 nt sequence identity to other transcripts.
Analysis of in silico prediction of OTs and 'repeat-rate' in Wg and Hh validation screens
Our results suggest that there is not necessarily a strict correlation between the rate of false-positives and dsRNAs with multiple potential OT sequences. For the Wg screen, 58% of the genes isolated in the original screen that had >5 potential OT sequences can be revalidated using multiple, independent OT-free dsRNAs (Figure ), while only 24% of the genes found in the Hh screen that had >5 potential OTs could be revalidated using multiple, independent OT-free dsRNAs (Figure ). Given a lack of strict correlation between the presence of in silico predicted 19 nt homologies and false positives, results obtained with dsRNAs containing sequence homologies to other genes should not be disregarded as artifacts without further testing. Indeed, in the Hh screen, two very strong hits, combgap (cg), a known regulator of Hh signaling, and Smrter (Smr), a novel regulator of Hh signaling, were initially identified using dsRNAs with >400 potential 19 nt OTs. Retesting with two validation dsRNAs demonstrated that both are indeed strong regulators of Hh signaling.
Conversely, our data also argue that not all dsRNAs targeting a gene are effective in knocking down that gene, regardless of possible OTEs. This notion is supported by the fact that, in the Wg screen, the use of independent dsRNAs confirmed 84% of DRSC1.0 dsRNAs that were not predicted to harbor any 19 nt homology (Figure ). The remaining 16% that could not be confirmed could be due to the fact that certain dsRNAs may not be effective at knocking down their cognate target or that additional contributing features in these dsRNAs (other than the strict 19 nt homology) might cause OTEs. Similarly, in the Hh screen independent dsRNAs confirmed 64% of the DRSC1.0 dsRNAs that were not predicted to harbor any 19 nt homology (Figure ). However, it is also important to consider the possibility that for those dsRNAs with no predicted 19 nt OT that failed to repeat with validation dsRNAs, they might in fact have an OT effect at less than 19 nt, perhaps in the 13-18 nt window.
Overall, the validation rate for the entire Wg screen (73%) is similar to the average repeat rate between the >5 19 nt homology containing (58%) and the OT-free candidate dsRNAs (85%) reported in the previous Wg screen using the DRSC1.0 library. Furthermore, it is similar to the validation rates reported in another published screen [4
]. Similarly, for the Hh screen, 51% of the candidate dsRNAs could be re-validated using the OT-free validation dsRNAs from the DRSC-v library, a proportion similar to that passing secondary assays using the DRSC1.0 library [6
Properties of dsRNAs and luciferase reporters that may affect assay sensitivity
cell culture studies have suggested that the efficacy of knockdown of any given target mRNA is directly proportional to the length of the dsRNA introduced into a cell [17
]. A longer dsRNA would typically produce a greater number of siRNAs upon Dicer-mediated cleavage and, hence, increase the likelihood that one or more of the siRNAs produced would efficiently knock down the targeted gene. However, in our overall analysis we could not find a statistically significant correlation between size of dsRNAs and magnitude of phenotype and we have clear examples where the converse is true. For example, knockdown of supernumerary limbs (slmb)
, a known negative regulator of the Wg-pathway, using a shorter validation dsRNA from the DRSC-v collection had a greater effect in increasing reporter activity compared to the original DRSC1.0 dsRNA, suggesting that the difference in length alone could not always explain the reduced efficiency in the generation of a phenotype (Figure , DRSC-v2 dsRNA for slmb
Figure 2 Properties of dsRNAs and reporter genes can influence the sensitivity of the RNAi assay. (a-c) The dynamic range of validation dsRNAs is smaller than that of the DRSC1.0 dsRNAs, which could potentially increase the rate of false negatives. The effects (more ...)
However, in the Wg assay, we do see a rough correlation between dsRNA size and dynamic range. In fact, when we compared the effects of dsRNAs from the DRSC1.0 collection targeting some of the known or newly identified candidate modulators of the Wg signaling pathway with those from the DRSC-v collection, we observed a surprising difference in the dynamic range in the effect of dsRNA knockdown on Wg-luciferase reporter activity (Figure ). In many cases, it was significantly reduced when DRSC-v dsRNAs were used when compared to the corresponding DRSC1.0 dsRNAs (Figure ). For example, using dsRNAs directed towards positive effectors for the Wg signaling pathway, we found that knocking down armadillo (arm) with a DRSC-v dsRNA reduced reporter activity by 90% as opposed to 99% with the DRSC1.0 dsRNA, in spite of transfection with equal amounts (100 ng) of the two dsRNAs (Figure ). Similarly, knocking down pathway activity using a DRSC-v wg dsRNA reduced reporter activity by approximately 55-60%, which was in sharp contrast to the DRSC1.0 wg dsRNA that reduced pathway activity by 90% (Figure ). On the other hand, knocking down some of the Wg-specific negative regulators, such as slmb, skpA and dally-like protein (dlp), or a novel candidate regulator CG7177 resulted in a moderate increase in reporter activity with only one of two DRSC-v dsRNAs. In the case of axin (axn), neither of the two DRSC-v dsRNAs re-validated in spite of axn RNAi having a robust effect on reporter activity with the DRSC1.0 dsRNA (Figure ).
Although more work needs to be done, one possibility to explain the trend is that what really matters is the chance of generating siRNAs with high specificity and efficacy after processing by Dicer. It would be logical to assume in these cases that having a longer dsRNA will increase the chance of getting a better knockdown efficiency. The specificity and efficiency of targeting could be tested at the molecular level by assessing the microarray profile of cells upon knockdown of target genes using dsRNAs of varying lengths. Taken together, these data imply that the region towards which any given dsRNA is directed is also important and that a larger dsRNA may not necessarily be efficient in knocking down the intended target if its sequence intrinsically leads to the generation of poor siRNAs.
Finally, we also noticed that the Wg-responsive luciferase reporter (dTF12 or STF16) used in the screen for novel interactors of the Wg pathway can be highly sensitive to the number of Tcf multimerized sites cloned into the reporter vector. We tested the activity of STF8, STF12 and STF16 using the dual-glo luciferase assay upon the induction of the pathway by co-transfection of cDNA encoding the wg gene in clone 8 cells (Figure ). We find that increasing the number of multimerized Tcf sites from 8× to 16× significantly increased the activation level of the reporter and, hence, the sensitivity of the assay. Addition of more than 16 Tcf binding sites did not enhance the pathway activity any further (data not shown).
Importance of proper normalization
An important aspect of any quantitative measurement of a biological phenomenon derived from cell-based assays is the need for normalization to account for experimental variations introduced by non-specific factors affecting assay readout. For example, most transient transfection assays need to be normalized for cell viability and transfection efficiency. Luciferase assay normalization is typically achieved by co-transfection of a control reporter expressing Renilla luciferase (RL) along with the experimental firefly luciferase expressing reporter. Two factors are especially important in the design of the control RL. First, the RL should be driven by a ubiquitously expressed promoter that is inert to the activity of the signaling pathway being analyzed. Second, the control Renilla vector should have activity significantly higher than background so that it is immune to background fluctuations inherent to most assays. The choice of the promoters driving RL thus becomes a matter of utmost importance, especially for large genome-scale RNAi screens, as poor normalization can lead to the introduction of significant artifacts in the screen, skewing data analysis and leading to erroneous conclusions.
Control reporters that have been used in various studies include Actin5C-RL (Act-RL), PolIII-RL, pIZT-RL, Copia-RL, TK-RL, SV40-RL and pCMV-RL. We tested the applicability of these vectors in a Drosophila RNAi-mediated HTS (in 96-well plates) by measuring their activity in clone 8 cell transient transfections (Figure ). The transfection protocol and assay conditions were the same as those used in our previously reported Wg and Hh HTSs. As shown in Figure , the raw luciferase values for TK-RL, Copia-RL and SV40-RL either showed no activity or were barely above background. CMV-RL displayed moderate levels of activity. IZT-RL, Act-RL, and PolIII-RL on the other hand displayed robust luciferase activity, although PolIII-RL displayed a three- to five-fold higher activity compared to Act-RL and IZT-RL. Our results suggest that the lack of robust basal activity of TK-RL, Copia-RL or SV40-RL render them unsuitable for HTSs since minute changes in their activity could introduce profound changes in the normalized (N) luciferase activity or 'relative luciferase units' (RLU) as measured by the ratio of firefly and RL (RLU = firefly luciferase/RL). Moreover, the absolute RL counts would not be within the linear range of luciferase activity. PolIII-RL, Act-RL, and IZT-RL, on the other hand, serve as robust control reporters: they have high basal activity and display a broad dynamic range that can accommodate variations in reporter activity due to changes in cell viability, cell proliferation and transfection efficiency. These properties make them well suited for rigorous normalization protocols.
Figure 3 Importance of proper normalization for luciferase assays. (a) Assessment of basal activity of the RL vectors that are commonly used in luciferase reporter assays in Drosophila clone 8 cells in 96-well plate format. The SV40-RL, TK-RL, and Copia-RL vectors (more ...)
However, for control vectors to be effective tools for normalization of signaling assays, they should not respond to the ligands that induce the activity of signaling pathways. Thus, we tested several control Renilla vectors for their effects on Wg and Hh induction. For Wg activation, PolIII-RL [3
], pIZT-RL [3
], Copia-RL [7
], and TK-RL (Promega) did not display any changes in activity upon Wg-stimulation (data not shown). However, the Act-RL vector was strongly activated by Wg induction in S2R+ cells (Figure ). To test if the effect on the Act promoter was specific to activation of Wg-signaling, we induced the pathway by dsRNA-mediated knockdown of GSK3β and APC, which are known to be strong negative regulators of the Wg-pathway. RNAi of both GSK3β and APC in S2R+ cells significantly activated Act-RL. Interestingly, scanning the sequence of the Actin5C promoter revealed at least two consensus Tcf binding sites, AaATCAAAG and cGATCAAAG. Whether these sites are true binding sites for Tcf proteins on the Actin promoter needs further testing. However, Act-RL should be avoided for normalization of Wg-induced reporters since its activity is sensitive to the activation of the Wg pathway.
Sensitivity to pathway activation was also tested for RL normalization constructs used in the Hh assay. Hh assays were conducted using the Act-RL [33
], PolIII-RL [3
], and IZT-RL [3
] normalization constructs. Only PolIII-RL gave RL counts greater than 500, while the Pol II-RL, IZT-RL, and Act-RL constructs all gave less than 500 counts in green fluorescent protein (GFP) dsRNA treated control wells (Figure ). As background counts are typically between 50 and 100 in our Hh assays, RL levels for these latter three control constructs did not exceed the threshold of ten times background counts that we feel sufficient to put RL counts in the linear range. Firefly luciferase activity produced by the ptcΔ136 reporter in transfections with the appropriate positive and negative control dsRNAs yielded the expected levels of ptcΔ136 activity when using the PolII-RL, Act-RL, and PolIII-RL control reporters. However, for cells cotransfected with the IZT-RL control reporter, firefly luciferase activity in general is higher for all dsRNA treatments, but is considerably higher than normal in the Smo and Ci dsRNA treated cells (Figure ). This is apparently due to transactivation of the ptcΔ136 reporter by the IZT-RL construct itself, thus rendering the IZT-RL unsuitable for use in the Hh signaling assay. Indeed, this can be seen more clearly when the fold differences between GFP dsRNA treated (Hh pathway activated) and Smo dsRNA treated (Hh pathway inactivated) wells are compared. Whereas there is normally a five- to seven-fold difference between these two values in assays in which PolIII-RL or Act-RL vectors are used for normalization, this difference falls to <1.7-fold in assays in which IZT-RL is used as the normalization vector (Figure ). While the sensitivity of Act-RL and IZT-RL towards other signaling pathways such as Notch (N) and JAK/STAT and receptor tysosine kinase await further testing, it is imperative that all control RL vectors be subjected to similar tests before using them for normalizing any HTS luciferase-based assays.
Cell type specificity and robustness of pathway activity for signaling pathways: implications for whole genome RNAi screens
The specificity of proteins regulating the activity of cell signaling pathways is exquisitely regulated in space and time during animal development. Cell type specificity is achieved by the presence of a unique set of proteins and their isoforms, their sub-cellular localization, temporal modulation of their activity, and the quantitative differences in the expression levels of similar sets of factors. Therefore, the choice of a specific cell line in an RNAi HTS screen can result in the identification of different sets of genes in different cell types.
This important issue comes to the forefront especially when comparing similar RNAi screens for the same pathway in two different cell types. For example, three of the dsRNAs (CG6606/l(1)G003, CG5402, CG12993) that were identified as 'candidate hits' in the previously published DasGupta et al
] screen in clone 8 cells were reported to have no effect on reporter gene activity in S2R+ cells (Supplementary Table S3 in [3
]) - an observation independently confirmed by Ma et al
]. This is a good example of where cell-type specific differences may factor into screen data obtained from two very different cell lines.
In order to further address this issue, we investigated the effect of dsRNA-mediated knockdown of known positive and negative regulators of the Wg pathway in a variety of Drosophila cells (Figure ). First, we tested four Drosophila cell types, namely clone 8, SL2, S2R+ and Kc167, for their responsiveness towards transfection of wg and ΔNLrp6 (a constitutively activated form of the human ortholog of Lrp6 co-receptor; Figure ). While the Wg-responsive reporter could be activated by co-transfecting cDNAs expressing either wg or ΔNLrp6 in clone 8 and SL2 cells (Figure ), Kc167 and S2R+ responded to Wg only and not to the addition of ΔNLrp6 (Figure ). This suggests that for a given signaling pathway, there are important differences in the responsiveness of different cell types to different components of the same signal transduction pathway. Moreover, the fold-change in normalized RLUs between Wg-stimulated and Wg-unstimulated was the greatest in the imaginal-disc derived clone 8 epithelial cells, with a 20-25× activation over baseline, followed by S2R+ (10-15× activation), Kc167 and SL2. Thus, for the Wg pathway, different cell types display both qualitative and quantitative differences in their ability to be activated by the Wg pathway.
Figure 4 Cell type specificity for signaling pathways. The basal activity and fold induction by Wg or ΔNLrp6 is different in the variety of Drosophila cell lines tested. (a-d) The wg reporter can be induced by the expression of both Wg and ΔNLrp6 (more ...)
Additionally, dsRNA-mediated knockdown of several known positive and negative regulators of the Wg pathway showed different effects on modulating pathway activity in the different Drosophila cell lines (Figure ). Whereas downregulation of pygo and legless (lgs) in S2R+ cells had a stronger effect in reducing reporter activity compared to clone 8 or Kc167 cells, RNAi-mediated knockdown of fz inhibited reporter activity more efficiently in clone 8 cells than in S2R+ or Kc167 cells (Figure ). With respect to the known negative regulators, axn knockdown in S2R+ cells did not result in as significant an increase in reporter activity as in clone 8 or Kc167 cells. Dlp knockdown, on the other hand, had a greater effect in S2R+ than in clone 8 or Kc167 cells (Figure ).
It was particularly interesting to note the failure of robust pathway activation in S2R+ cells by dsRNA-mediated knockdown of axn
in the light of our observation that ΔNLrp6 fails to activate the Wg-responsive luciferase reporter in S2R+ cells (Figure ). Recent studies have suggested that constitutively activated ΔNLrp6 or a chimera between the Frizzled2
) receptor and intracellular cytoplasmic tail of the Drosophila
ortholog of Lrp6 (encoded by the arrow
) gene) can activate the Wg pathway in a ligand-, GSK-3β-, and disheveled
)-independent manner [34
]. It was also demonstrated that expression of activated Lrp6 could recruit Axn to the plasma membrane and cause its degradation. Taken together, it is possible that the expression levels of axn
are much higher or that the protein is more stable in S2R+ cells than in clone 8 cells. This could potentially result in an ineffective knockdown of axn
levels using RNAi, hence explaining the inability of ΔNLrp6 to activate the wg-reporter in S2R+ cells. In order to test this hypothesis, we performed western blot analysis on cellular protein extracts derived from clone 8, Kc167 and S2R+ cells and assessed the expression levels of the Axn protein using anti-Axn antibodies. As shown in Figure , the level of Axn protein is significantly higher in S2R+ and Kc167 cells compared to that in clone 8 cells.
Higher levels of Axn in S2R+ cells could be a result of high levels of Dfz2 expression, which was used as a basis for isolating the S2R+ cell line as a cell-based model for the Wg pathway [35
]. Increased Fz2 activity could subsequently activate expression of axn
, which in mammalian cells, has been shown to be a target of the β-catenin pathway [36
]. In fact, the basal activity of the wg
pathway in S2R+ cells is approximately ten-fold greater than in clone 8 cells (data not shown). It is thus tempting to speculate that the presence of the Dfz2 receptor might promote higher basal activity of the pathway in S2R+ and Kc167 cells and more potently activate expression of axn
compared to that in SL2 or clone 8 cells. This might explain why ΔNLrp6 can efficiently activate the wg reporter in clone 8 and SL2 cells but not in S2R+ or Kc167 cells (Figure ). In agreement with this notion, dsRNA-mediated knockdown of Dfz2 strongly inhibited the wg responsive luciferase reporter activity in S2R+ cells but not in clone 8 cells, which is most likely why we did not isolate Dfz2 in the previously reported Wg screen (Figure ; Figure S1 in [3
]). Moreover, knockdown of axn
in clone 8 cells led to a stronger activation of the luciferase reporter compared to S2R+ cells (Figure ).
Taken together, the activity of signaling pathways and their modulation by regulatory proteins within the cell can be highly variable in different cell types, depending on the specific cellular context, the quantitative levels of expression of various proteins and their sub-cellular localization. Hence, caution needs to be exercised when comparing the candidate 'hits' obtained in whole-genome screens for any given pathway performed in different cell types.
Another variable that can affect transfection-based luciferase assays is the interval between reporter transfection and the luciferase assay. This interval can be important in allowing time for protein expression/accumulation, recovery from transfection, and post-translational modifications. It has recently been suggested that the interval between reporter gene transfection and luciferase assay may affect reporter activity in Hh luciferase based assays. Specifically, Ma et al
] have found that longer incubation periods after transfection reduces the fold difference in luciferase activity between the Hh stimulated and unstimulated states of their conditioned media-based Hh assays. In our initial characterization of the Hh assay, we had examined this possibility by how a one-day versus a four-day interval between transfection and luciferase assay might affect the Hh assay in clone 8 cells. As expected, we found that conducting the luciferase assays one day after transfection gave firefly luciferase values considerably lower than those obtained when the assays were conducted four days after transfection (Figure ). RL values were similarly lower in the one day assay compared to the four day assay (Figure ), and, in most cases, were near 10× background, which tends to average between 50 and 100 counts in cells not transfected with any reporters (KN, data not shown). Interestingly, the normalized values were very similar for the one day and four day assays, indicating that the interval between transfection and luciferase assay is not a strong modulator of Hh reporter activity (Figure ). However, since we find that it is best to keep control reporter activity well above ten times background levels, we opted for a greater than four day interval between transfection and luciferase assay. The strong effect that Ma et al
. saw in their assay is likely due to the fact that they used conditioned media containing the artificially truncated form of Hh, Hh-N, as the source of Hh stimulus. This Hh-N source is likely highly labile in addition to being of undetermined Hh activity, and probably accounts for the reduction in fold difference of their Hh assay with longer incubation periods.
Figure 5 Hh assay timing. Hh signaling assays were conducted on identical assays plates with luciferase assays being scored after one or four days. (a) Comparison of RL counts when luciferase activity was assayed after one or four days in the presence of the indicated (more ...)