A genome wide analysis of ubiquitin ligases in APP processing identifies a novel regulator of BACE1 mRNA levels

www.elsevier.com/locate/ymcne Mol. Cell. Neurosci. 33 (2006) 227 – 235

A genome wide analysis of ubiquitin ligases in APP processing identifies a novel regulator of BACE1 mRNA levels Amy S. Espeseth, a Qian Huang, a Adam Gates, a Min Xu, a Yuanjiang Yu, b Adam J. Simon, b Xiao-Ping Shi, b Xiaohua Zhang, c Paul Hodor, d David J. Stone, e Julja Burchard, f Guy Cavet, f Steven Bartz, f Peter Linsley, f William J. Ray, b and Daria Hazuda g,⁎ a

Department of Molecular and Cellular Technologies, Merck Research Laboratories, P.O. Box 4, West Point, PA 19486, USA Alzheimer’s Research, Merck Research Laboratories, P.O. Box 4, West Point, PA 19486, USA c Biometrics Research, Merck Research Laboratories, P.O. Box 4, West Point, PA 19486, USA d Molecular Profiling, Merck Research Laboratories, P.O. Box 4, West Point, PA 19486, USA e Department of Molecular Profiling, Rosetta Inpharmatics (a wholly owned subsidiary of Merck and Co., Inc.), 401 Terry Ave. N., Seattle, WA 98019, USA f Department of Biology, Rosetta Inpharmatics (a wholly owned subsidiary of Merck and Co., Inc.), 401 Terry Ave. N., Seattle, WA 98019, USA g Virus and Cell Biology WP42-211, Merck Research Laboratories, P.O. Box 4, West Point, PA 19486, USA b

Received 9 May 2006; accepted 7 July 2006 Available online 15 September 2006 Proteolysis of β-amyloid precursor protein (APP) into amyloid β peptide (Aβ) by β- and γ-secretases is a critical step in the pathogenesis of Alzheimer's Disease (AD), but the pathways regulating secretases are not fully characterized. Ubiquitinylation, which is dysregulated in AD, may affect APP processing. Here, we describe a screen for APP processing modulators using an siRNA library targeting 532 predicted ubiquitin ligases. Seven siRNA pools diminished Aβ production. Of these, siRNAs targeting PPIL2 (hCyp-60) suppressed β-site cleavage. Knockdown of PPIL2 mRNA decreased BACE1 mRNA, while overexpression of PPIL2 cDNA enhanced BACE1 mRNA levels. Microarray analysis of PPIL2 or BACE1 knockdown indicated that genes affected by BACE1 knockdown are a subset of those dependent upon PPIL2; suggesting that BACE1 expression is downstream of PPIL2. The association of PPIL2 with BACE expression and its requirement for Aβ production suggests new approaches to discover disease modifying agents for AD. © 2006 Elsevier Inc. All rights reserved. Keywords: Alzheimer's; BACE1 regulation; PPIL2; hCyp-60; siRNA screen

Introduction Alzheimer’s Disease (AD) is characterized histopathologically by the presence of senile plaques, which are proteinaceous aggregates in the brain (Selkoe, 2001). These deposits are primarily composed of a 39–43 amino acid peptide, amyloid beta (Aβ), Abbreviations: AD, Alzheimer's disease; APP, β-amyloid precursor protein; Aβ, amyloid β peptide. ⁎ Corresponding author. E-mail address: [email protected] (D. Hazuda). Available online on ScienceDirect (www.sciencedirect.com). 1044-7431/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.mcn.2006.07.003

which is the product of sequential proteolytic cleavage of the amyloid precursor protein (APP) by two proteases, β- (or BACE1) and γ-secretase (Hardy and Higgins, 1992; Walsh and Selkoe, 2004). Evidence suggests that secreted Aβ multimerizes into neurotoxic oligomers that disrupt neuronal function, leading to the cell death and memory loss associated with AD (Klein et al., 2001; Lacor et al., 2004). Current treatments for AD are primarily symptomatic and thus the development of disease modifying approaches continues to be an area of intense focus. Given the central role of Aβ in AD pathology, therapeutics that reduce Aβ levels have the potential to halt the progression of the disease. Efforts to reduce Aβ by inhibiting either the β- or γ-secretase have proven problematic thus far; γ-secretase inhibitors are associated with mechanism-based toxicity as a result of their effect on the processing of other substrates (De Strooper et al., 1999; Hadland et al., 2001; Lee et al., 2002; Marambaud et al., 2002; Ray et al., 1999; Searfoss et al., 2003), and data on the in vivo activity of BACE1 inhibitors is limited. Therefore, identifying other approaches to modulate APP processing is of interest. Previous efforts to identify potential targets in this pathways have included the biochemical analysis of secretase-associated proteins, as well as analysis of genetic interactions in patient cohorts (Bertoli-Avella et al., 2004; He et al., 2004). In multiple neurodegenerative diseases, aberrant protein trafficking, folding, and degradation are thought to play a central role in disease pathogenesis (Berke and Paulson, 2003). As the ubiquitin ligase system regulates all three of these cellular processes, there has been considerable interest in the relationship between ubiquitin and APP. Various proteasome inhibitors either increase or decrease Aβ production in cell lines and neuronal cultures (Christie et al., 1999; Flood et al., 2005; Nunan et al.,

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2001; Yamazaki et al., 1997). Proteasome and ubiquitin ligase activity is altered in postmortem brain samples from AD patients compared with controls (Keller et al., 2000; López Salon et al., 2000; von Rotz et al., 2005). BACE1 and components of the γ-secretase enzyme complex are ubiquitinated and degraded in a proteasome-dependent manner (Bergman et al., 2004; Crystal et al., 2004; Li et al., 2002; Qing et al., 2004). These observations, coupled with the large number of E3 ligases suggesting tightly controlled substrate specificity for this family of proteins, provide

strong rationale that ubiquitin ligases may play a specific role in Aβ metabolism. To identify ubiquitin ligases that regulate Aβ production, we screened a library of 532 siRNA pools directed against known and predicted ubiquitin ligases (Semple et al., 2003) in a cell based assay of APP processing. siRNAs were tested in HEK293T cells expressing an optimized β-secretase cleavage site (Shi et al., 2005) by monitoring for the secretion of sAPPα, sAPPβNF, Aβ40EV, Aβ42EV and assessing cell viability to generate an integrated

Fig. 1. Identification of siRNAs targeting ubiquitin ligases that affect APP processing. (A) Diagram of APP processing by secretases. Arrows indicate the cleavage sites for the different secretases and the secreted products measured in the assay are diagramed. (B) Profile of the entire screen (excluding controls) with BACE1 siRNA controls shown in red to reveal the profile of a β-secretase inhibiting siRNA. (C) Profile of the screen (excluding controls) with Pen2-targeting siRNAs in red to reveal the profile of a γ-secretase inhibiting siRNA. (D) Profile of the entire screen (excluding controls) with Adam10 siRNA controls shown in red to show the profile of an α-secretase inhibiting siRNA. (E) siRNA pools with profiles similar to BACE1-targeting siRNAs; HERC 6, CHFR, PPIL2, BFAR, RAD18, BIRC7 and TRIM25. (F) siRNA pools with profiles similar to Pen 2-targeting siRNAs, including UBE2B, RBX1, BTRC, CUL3, UBE2J2, DTX2, and TRIM52. (G) siRNA pools with profiles similar to Adam-10 siRNAs including USP47, USP20, RNF128, ZFPL1, DKFZp434E1818, and G16.

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profile for each siRNA. Among those siRNAs that affected APP processing, we found that siRNAs directed against the peptidylprolyl isomerase, PPIL2, robustly and reproducibly decreased sAPPβNF, Aβ40EV, and Aβ42EV levels without affecting viability or sAPPα secretion, as would be expected for disruption of β-site cleavage. Investigation into the mechanism for PPIL2 effects on BACE1 cleavage led to the surprising finding that PPIL2 directly or indirectly regulates the expression level of a number of genes, including BACE1.

Results An siRNA screen using a ubiquitin-ligase library to find modulators of APP processing identified PPIL2 We designed a library of siRNA pools targeting 532 ubiquitin ligases (see Materials and methods, (Semple et al., 2003)), and tested it in a cell-based APP processing assay. HEK293T cells expressing APPNFEV, which contains an enhanced β-site (Shi et al., 2005), were transfected with each siRNA pool, along with siRNAs directed against BACE1, Pen2, and Adam10 as controls for the inhibition of β-, γ-, and α-secretase activity, respectively (Fig. 1) (Cai et al., 2001; Kimberly et al., 2003; Lammich et al., 1999). Two days after transfection, conditioned media from the cells was assayed for the secreted products of APP processing, including sAPPβNF, sAPPα, Aβ40EV, and Aβ42EV as well as for viability. Having multiple assay readouts from each siRNA transfection allowed each siRNA pool to be profiled for specific effects on APP processing. For example, inhibition of BACE1 leads to decreased secretion of sAPPβNF, Aβ40EV, and Aβ42EV peptides, and increased secretion of sAPPα, thus knock down of genes associated with β-site cleavage is expected to result in a similar profile (Fig. 1B). Similarly, siRNA targeting of the γ-secretase component, Pen2, decreases levels of Aβ40EV, and Aβ42EV, increases sAPPα levels and does not affect sAPPβNF secretion (Fig. 1C). siRNAs resulting in this profile are thus expected to knock down genes associated with γ-secretase processing. Finally, Adam 10-directed siRNA decreases sAPPα secretion without inhibiting Aβ40EV, Aβ42EV, or sAPPβNF, which is the expected profile of siRNAs targeting α-secretase associated genes (Fig. 1D). Thus, the siRNAs tested could be characterized as affecting α-, β- or γ-site processing and those with undesirable effects on cell viability or global effects on secretion could be more easily eliminated. Following the primary screen, siRNA pools were profiled to determine whether they behaved as β-, γ-, or α-site cleavage effectors (Figs. 1B–G). Seven potential effectors of β-site cleavage were defined by a profile requiring sAPPβNF levels decreased by 60% or more and Aβ42EV by 25% or more relative to control, while having no effect on viability and no decrease in sAPPα (Fig. 1E). Six potential effectors of γ-site cleavage decreased Aβ42EV levels by 50% or more and also decreased Aβ40EV relative to control without decreasing sAPPβNF, sAPPα, or viability (Fig. 1F). Six potential effectors of α-site cleavage, USP47, USP20, RNF128, ZFPL1, DKFZp434E1818, and G16, decreased sAPPα secretion by 50% or more relative to control, without affecting Aβ40EV, Aβ42EV, sAPPβNF, or viability (Fig. 1G). As potential targets for AD the β- and γ-cleavage effectors were of greatest interest, and these siRNA pools were analyzed further. These targets were prioritized based on brain expression and consistency in the duplicate screens. On this basis, four siRNA

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pools that affected β-site processing (HERC6, PPIL2, BFAR, BIRC7) and seven siRNA pools that affected γ-site processing (UBE2B, RBX1, BTRC, CUL3, UBE2J2, DTX2, TRIM52) were selected for additional characterization. To validate the specificity of inhibition by these siRNA pools, HEK293T APPNFEV cells were transfected with a titration of each of the three siRNAs present in the original pools. If at least two siRNAs targeting a gene inhibited APP processing and showed evidence of a dose-response, the gene targeted by the siRNAs was considered likely to be involved in APP processing. Two siRNA pools, targeting PPIL2, and BIRC7 reproducibly affected β-site processing of APP, and five siRNA pools, targeting UBE2B, BTRC, CUL3, UBE2J2, and TRIM52 reproducibly affected γ-site processing (data not shown). The γ-secretase complex has been widely studied, but less is known about the regulation of β-site cleavage, so we elected to characterize one of the genes affecting β-site processing of APP (Iwatsubo, 2004). Of the two siRNAs identified in the screen to affect β-site processing, the most robust inhibition was observed with siRNA targeting PPIL2 (hCyp-60). siRNAs targeting PPIL2 had a profile similar to siRNAs targeting the β-secretase, BACE1

Fig. 2. PPIL2-targeting siRNAs affect APP processing similarly to BACE siRNAs. (A) Comparison of transfection of Luciferase (solid white bars), BACE1 (diagonal striped bars), Pen2 (dots), Adam 10 (horizontal striped bars), and PPIL2 (solid black bars) siRNAs on secretion of sAPPα, sAPPβNF, Aβ40EV, and Aβ42EV. Effects on APP processing are shown relative to transfection of a control siRNA targeting luciferase, which was set at 100% activity. The average and standard deviation of three separate experiments is shown. Similar to BACE1 siRNAs, PPIL2 siRNAs increased sAPPα, and decreased sAPPβNF, Aβ40EV and Aβ42EV production. (B) A titration of BACE1 and PPIL2 siRNAs showed increasing suppression of sAPPβNF with increasing concentration of siRNAs transfected. The experiment was repeated with ten different siRNAs directed against PPIL2. A representative experiment is shown using the siRNA, PPIL2 #3 (Materials and methods).

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targeting efficacy from 30% to 70% knockdown of PPIL2 mRNA (Fig. 3A). Comparing the effect of the panel of siRNAs on PPIL2 mRNA levels and sAPPβNF secretion revealed a trend in which the reduction in PPIL2 mRNA levels correlated with effects on sAPPβNF levels (Fig. 3B). Thus the suppression of APP β-site cleavage can be linked to the suppression of PPIL2 expression. Knockdown of PPIL2 mRNA leads to knockdown of BACE1 mRNA

Fig. 3. Inhibition of sAPPβNF secretion by PPIL2 siRNAs correlates with the degree of knockdown of PPIL2 mRNA. (A) A panel of 10 non-sequence related PPIL2 siRNAs was tested for inhibition of sAPPβNF secretion. Effects on sAPPβNF secretion are shown relative to transfection of a control siRNA targeting luciferase, which was set at 100% activity. The average and standard deviation of three separate experiments is shown. Negative controls (Luciferase and mock siRNAs) are shown in white solid bars, the positive control (BACE1 siRNA) is shown in black, and the PPIL2 siRNAs are shown in gray. (B) Each siRNA was transfected into HEK293T/APPNFEV cells, conditioned media was tested for sAPPβNF, cells were lysed and levels of PPIL2 mRNA were quantified. The average PPIL2 mRNA and sAPPβNF in three separate experiments is shown. Correlating the PPIL2 mRNA levels and sAPPβNF levels reveals a trend (R2 = 0.5775) in which siRNAs that knocked down PPIL2 levels also knocked down sAPPβNF secretion, while less effective siRNAs had less of an effect on sAPPβNF.

(Figs. 1B, E, 2). Both PPIL2 and BACE1-targeting siRNAs decreased sAPPβNF secretion by over 70%, increased sAPPα secretion over two-fold, and decreased Aβ40EV, and Aβ42EV levels (Fig. 2A). Additionally, both PPIL2 and BACE1-targeting siRNAs inhibited sAPPβNF levels in a dose-dependent fashion, increasing confidence in the specificity of the siRNAs (Fig. 2B). Knockdown of PPIL2 message correlates with Knockdown of APP processing Although siRNAs are designed to trigger the selective degradation of targeted mRNA, off-target activity, or degradation of non-targeted mRNAs has been shown (Jackson et al., 2003). To correlate PPIL2 mRNA knockdown with inhibition of APP processing, we tested a panel of ten PPIL2-directed siRNAs and one BACE1 siRNA for effects on both PPIL2 mRNA level and sAPPβNF secretion. The panel of PPIL2 siRNAs ranged in

The function of PPIL2 has not been well characterized. It was initially identified in a two-hybrid screen through its interaction with the proteinase inhibitor eglin c (Wang et al., 1996). Unlike the cyclophilins, and other peptidyl-prolyl cis-trans isomerase domain containing proteins, PPIL2 contains a “U-box” domain, present in many E2 ubiquitin ligases (Semple et al., 2003). Since ubiquitin ligases often modify the stability of their substrates, if BACE1 is a substrate of PPIL2, its stability may be increased or reduced by knockdown of PPIL2 expression. The effect of PPIL2 knockdown on APP processing resembles a BACE1 loss of function phenotype. We thus examined the effect of PPIL2 knockdown on BACE1 protein and mRNA levels in cells transfected with PPIL2 siRNAs. Western analysis of BACE1 protein levels in HEK293T APPNFEV showed more than a two-fold decrease in BACE1 protein levels after transfection with PPIL2 siRNA and no change after transfection of luciferase siRNA (data not shown). The observation of a decrease in BACE1 protein following knockdown of PPIL2 mRNA led to the question of whether BACE1 mRNA levels are affected by PPIL2 knockdown. Microarray experiments were carried out to assess the effect of three different

Fig. 4. Knockdown of PPIL2 mRNA levels using siRNA correlates with a decrease in BACE1 mRNA levels, while BACE1 siRNA has no effect on PPIL2 mRNA levels. Microarray analysis was carried out on three separate transfections of three independent PPIL2 siRNAs, one BACE1 siRNA, Mock-transfected, Luciferase siRNA-transfected, and NS1-transfected cells. RNA from each transfection was compared to RNA from non-transfected cells. For each sample, the expression level of BACE1 and PPIL2 was plotted as log fold change relative to non-transfected cells. A regression line describing the dependence of BACE1 on PPIL2 was constructed based on the PPIL2 siRNA-transfected samples only. The dotted lines define the 95% confidence interval for predicting BACE1 levels given PPIL2 levels. In all cells except the BACE1 siRNA transfected cells, there is a significant degree of correlation between the expression level of BACE1 and the expression level of PPIL2. In cells transfected with BACE1 siRNA, BACE1 expression is substantially decreased without affecting PPIL2 expression.

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PPIL2 siRNAs on the transcriptome in comparison to a number of control siRNAs. Strikingly, BACE1 mRNA levels were reduced by PPIL2 siRNA, and the degree of reduction of BACE1 mRNA was highly correlated to the degree of reduction of PPIL2 mRNA levels (Fig. 4, 5B). The negative control siRNAs, luciferase, and NS1, did not affect BACE1 mRNA levels unless PPIL2 mRNA levels were also affected. Of the siRNAs tested, only BACE1 siRNA lowered BACE1 mRNA levels without also affecting PPIL2 mRNA levels. The correlation between reduction in PPIL2 mRNA levels and reduction in BACE1 mRNA levels suggests that PPIL2 directly or indirectly maintains or enhances BACE1 mRNA levels. Reasoning that genes whose level of expression correlates with both PPIL2 and BACE1 RNA levels might represent additional targets of PPIL2 activity, further analysis of the microarray data to identify these genes was performed. Genes whose expression were positively or negatively correlated with either PPIL2 only or with both PPIL2 and BACE1 were identified (Fig. 5). A group of 72 genes were identified whose expression was positively correlated with PPIL2 but not with BACE1, with r > 0.75 and p < 0.01 (Fig. 5A), and a group of 29 genes were identified whose expression was negatively correlated with PPIL2 but not BACE1 using the same parameters (Fig. 5C). These genes may be targets of PPIL2 activity but are likely to be either unrelated to BACE1 expression or to come upstream of BACE1 expression. Among the genes positively or negatively correlated with PPIL2 alone are genes involved in hematopoiesis (HOXB3, which is upregulated in cells where PPIL2 has been knocked down, and ERMAP, ZNF521, SECTM1, SCIN,

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and CD1D, which are downregulated), and the ubiquitin proteasome system (FBXO4, USP10, and WDR18, which are downregulated in PPIL2 siRNA treated cells, and USP42 and RNF11, which are upregulated) (Fig. 5E). A group of 34 genes had expression that positively correlated with both PPIL2 and BACE1 in the cells transfected with PPIL2 siRNA but that correlate with BACE1 alone in the cells transfected with BACE1 siRNA (Fig. 5B) and 37 genes have expression that is similarly correlated negatively (Fig. 5D). These genes are likely to be downstream of BACE1 expression. Genes whose expression level is positively or negatively correlated with both PPIL2 and BACE1 are described in part in Fig. 5E and include those associated with mRNA processing (ADAR, which is downregulated with BACE1 or PPIL2 siRNAs, and DBR1 and PRPF4 which are both upregulated), cholesterol biosynthesis and fatty acid metabolism (ACLY and SLCO2A1 are downregulated, ELOVL1 and MVK are upregulated), and additional members of the ubiquitin proteasome system (MIB1 and USP44 are downregulated, ISGF3G, UBE2J2, and RNF103 are upregulated). Interestingly, UBE2J2 siRNAs disrupted γ-secretase processing in the original screen, and UBE2J2 expression was negatively correlated with PPIL2 and BACE1 expression (R = −0.789 for PPIL2, R = −0.7524 for BACE1). No clear link to known signal transduction pathways could be established for the genes whose expressions were correlated with both BACE1 and PPIL2 mRNA levels. The total number of genes positively or negatively correlated with PPIL2 expression with r > 0.75 and p < 0.01 was thus 172 and the total number of genes positively or negatively correlated with

Fig. 5. Microarrays reveal genes downstream of PPIL2 alone and a second set of genes downstream of both PPIL2 and BACE1. Microarray analysis was carried out as described in Fig. 4. The mean expression of three transfections is shown for genes whose expression is correlated to PPIL2 (A); genes whose expression is positively correlated to both PPIL2 and BACE1 (B); genes whose expression is negatively correlated to PPIL2 (C); genes whose expression is negatively correlated to both BACE1 and PPIL2 (D). The arrow indicates the expression level of PPIL2 and the arrow head indicates the expression level of BACE1. (E) Gene family members are shown as being either correlated (green font) or anticorrelated (red font) with PPIL2 only or with both PPIL2 and BACE1 mRNA expression.

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Fig. 6. Overexpression of PPIL2 cDNA rescues knockdown of BACE1 mRNA levels by transfection of PPIL2 siRNA. HEK293T/APPNFEV cells were transfected with PPIL2 cDNA (PPIL2 wt) or a PPIL2 with inactivating mutations in the peptidyl-prolyl isomerase domain (PPIL2 H322A/R323A). BACE1 mRNA levels were determined by Taqman and the resulting BACE1 mRNA levels after transfection are shown relative to vectortransfected cells. Following transfection with PPIL2 cDNA, BACE1 mRNA levels were significantly higher than vector-transfected cells (p < 0.01).

BACE1 with r > 0.75 and p < 0.01 was 112. If there were no genetic interaction between PPIL2 and BACE1, the number of overlapping genes correlated with both PPIL2 and BACE1 is expected to be (# PPIL2 / # genes on array) × (#BACE1 / # genes on array) × (# genes on array), or (172/23000) × (112/23000) × 23000 = ~ 1. The actual number of overlapping genes was 71. The substantial difference between the degree of overlap in correlation between the two genes and the amount of random overlap expected in the absence of a true interaction supports the interpretation of a link between PPIL2 and BACE1 (significance of p < 10−300). Further, the fact that the majority of genes correlating with BACE1 are also correlated with PPIL2 and the larger population of genes linked to PPIL2 that are independent of BACE1 suggests that BACE1 expression is downstream of PPIL2 expression. Overexpression of PPIL2 mRNA leads to increase in BACE1 mRNA levels To confirm that BACE1 mRNA is regulated by PPIL2, we examined the effect of overexpressing PPIL2 on BACE1 mRNA levels. HEK293T APPNFEV cells were transfected with pcDNA driving expression of either wild type or mutant PPIL2 cDNA. The PPIL2 mutant H322A/R323A contains mutations in the cyclophilin domain analogous to the cyclophilin A dominant negative mutation R55A, in order to assess whether the peptidyl-prolyl isomerase domain is essential for effects on BACE1 mRNA. Overexpression of wild type PPIL2 led to close to a three-fold increase in BACE1 mRNA levels (Fig. 6A), verifying that PPIL2 significantly (p < 0.01) enhances BACE1 expression. Interestingly, overexpression of the PPIL2 H322A/R323A mutant also enhanced BACE mRNA levels, though to a lesser extent, suggesting that the peptidyl-prolyl isomerase function of PPIL2 may not be required for its effects on BACE1. Discussion We have used a targeted siRNA screening approach to examine the role of specific ubiquitin ligases in APP processing. The use of unbiased, yet hypothesis-driven siRNA screening is a

powerful technology that may identify new interactions between genes and unlock novel biological pathways, thereby providing new targets for disease-modifying therapeutics. In particular, the ubiquitin ligase superfamily represents a large class of genes associated with diverse aspects of cell biology in which the function of many of the individual family members is unknown or poorly characterized. The strategy represented here, in which a ubiquitin ligase-targeting siRNA library is assessed for its role in a particular biological function, will link specific ligases to specific cellular processes. Most evidence points to secretion of Aβ as an underlying cause of AD. The proteases directly responsible for cleaving APP to produce Aβ have been characterized, but the underlying cell biology of APP metabolism is still not fully understood. The ubiquitin–proteasome system is affected in AD and associated with turnover of proteins directly responsible for metabolizing APP, but the specific ubiquitin ligases responsible have not been defined. The link between BACE1 and Pen2 ubiquitination and APP processing indicated that if an appropriate ubiquitin ligase could be identified, it could present an alternate target for modifying APP processing and reducing the secretion of Aβ (22–25). PPIL2 as a modulator of BACE1 expression Expression of BACE1 is tightly regulated, both transcriptionally and translationally (Christensen et al., 2004; Ge et al., 2004; Rogers et al., 2004; Sastre et al., 2006; Zhou and Song, 2006). We have demonstrated that BACE1 mRNA levels are affected by the expression of PPIL2, a U-box containing gene. PPIL2 is a member of the cyclophilin family that was originally identified in a twohybrid screen using the proteinase inhibitor eglin c as bait, and called hCYP-60 (Wang et al., 1996). The function of PPIL2 is poorly defined. Although the U-box motif qualifies it as a potential ubiquitin ligase, a role for this gene in ubiquitination or in the ubiquitin–proteasome system has not been described. Our data indicates that the peptidyl-prolyl isomerase function of PPIL2 may not be required for its effect on BACE1, leaving open the possibility of a role for the U-box in this function. PPIL2 is ubiquitously expressed, with low but detectable expression in brain (Wang et al., 1996). PPIL2 protein is localized to the nucleus, which has led to suggestions that it functions in nuclear protein folding or transport. The C. elegans homolog of PPIL2 is mog-6, which functions with other mog proteins to post-transcriptionally suppress expression of the sex-determining gene, fem-3 (Gallegos et al., 1998), so by analogy, PPIL2 may also play a role in directly or indirectly regulating gene expression. However, in mammalian cells, PPIL2 co-immunoprecipitates with CD147, and regulates the cell surface expression of this receptor, so it may also function as a chaperone for proteins expressed at the cell surface (Pushkarsky et al., 2005). Alternatively, the interaction between PPIL2 and CD147 may be critical for its regulation of BACE1 mRNA levels, since CD147 is itself a component of the γ-secretase protein complex and effects on its trafficking could conceivably feed back on and modulate BACE1 expression (Zhou et al., 2005). The disparate functions ascribed to PPIL2 and its homologs make it difficult to speculate about the molecular mechanism behind its modulation of BACE1 function. We have shown that knocking down PPIL2 knocks down BACE1 mRNA and overexpressing PPIL2 increases BACE1 mRNA. Additionally, microarray analysis of PPIL2 knockdown revealed a panel of genes whose expression level is dependent on PPIL2 expression. These data, coupled with the

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nuclear expression of PPIL2 (Wang et al., 1996) indicate that PPIL2 directly or indirectly regulates BACE1 expression at the mRNA level. The mechanism may or may not correlate with the molecular role of mog-6 in fem-3 regulation in C. elegans. An understanding of the molecular mechanism will require further studies.

CAUdTdT 3′), Adam 10 siRNA (a pool of 5′ GTCTGTTATTGATGGAAGAdTdT 3′, 5′CTGTGCAGATCATTCAGTAdTdT 3′, and 5′ CTTACAATGTGGATTCATTdTdT 3′ mixed at a 1:1:1 ratio), and a luciferase siRNA (5′ CGUACGCGGAAUACUUCGAdTdT3′). To sensitize the assay for γ-secretase modulators, a γ-secretase inhibitor (Compound 6 (Beher et al., 2001)) was included at its IC50 (0.5 nM). Assays were carried out 48 h post-transfection.

Role of ubiquitin ligases in APP processing

Detection of APP processing fragments

Components of the γ-secretase enzyme complex are also modulated by ubiquitination. Pen-2 is subject to ubiquitination follow by proteasomal degradation, although the ligases involved have not been characterized (Bergman et al., 2004; Crystal et al., 2004). PS-1 activity is also affected by ubiquitination. Human SEL-10 (FBXW7) binds PS-1 and enhances its ubiquitination (Li et al., 2002). Transfection of exogenous SEL-10 into HEK293 cells enhances Aβ secretion, thus one would expect transfection of SEL-10 siRNAs to decrease APP processing. Although it did not meet the predetermined cutoff, we did find SEL-10 siRNAs affected APP processing, enhancing sAPPα secretion three-fold and decreasing Aβ40EV and Aβ42EV secretion by 20–30%. The γ-secretase modifying ubiquitin ligases identified in our screen, UBE2B, BTRC, CUL3, UBE2J2, and TRIM52 may also be associated with trafficking and/or proteolysis of PS-1 or other members of the gamma secretase complex. Identification of one of these genes, UBE2J2, as having expression levels negatively correlated with BACE1 and PPIL2 suggests that there may be cross-regulation between the different secretase functions. In summary, the five γ-secretase modifying genes and two β-secretase modifying genes identified in this siRNA screen had no previous association with AD. By conducting a hypothesis driven, yet unbiased screen to search for novel regulators of a cellular process we have made new connections between APP processing and specific members of the ubiquitin proteasome system. Our ability to identify a relevant interaction between PPIL2 and BACE1 using a targeted library reinforces the validity of using siRNA screens to find new molecular pathways associated with AD. Applying this screen to larger scale libraries promises to broaden our knowledge of regulators of APP processing (Majercak et al., in preparation).

Assays for detecting and measuring sAPPβNF, Aβ42EV, Aβ40EV, and sAPPα were carried out as described in (Shi et al., 2005; Hazuda et al., 2003), and (Majercak et al., in preparation).

Experimental methods siRNA library 532 potential ubiquitin ligases and de-ubiquitinating enzymes were selected by literature and InterPro annotation (Semple et al., 2003, http:// www.ebi.ac.uk/interpro/). Three siRNAs per gene were designed to each transcript based on predictors of on- and off-target activity and were purchased from a commercial vendor (Sigma-Proligo). Individual siRNAs targeting each transcript were pooled prior to transfection.

Quantification of PPIL2 mRNA levels Quantification of PPIL2 mRNA levels was carried out by bDNA analysis (Genospectra). Briefly, cells were transfected with PPIL2 siRNAs (PPIL2 #1: 5′ CCCGUCUUAUUAUCUGAAAdTdT 3′, PPIL2 #2: 5′ CUCCCGAUGGCAUCGUCUUdTdT 3′, PPIL2 #3: 5′ GUGCCUACCUGGACAAGAAdTdT 3′, PPIL2 #4: 5′ CAGAUCCAUCCGGAACUUUdTdT 3′, PPIL2 #5: 5′ GAGAUUCUGGCAGCCACCAdTdT 3′, PPIL2 #6: 5′ CCCUUCUCCCGGCAGGACAdTdT 3′, PPIL2 #7: 5′ GCUACCAGUUUGUGAAGAAdTdT 3′, PPIL2 #8: 5′ GUACUGACAGCCAUGGAGAdTdT 3′, PPIL2 #9: 5′ CGCCUAUGAGGCAGUGGAAdTdT 3′, and PPIL2 #10 5′ GAACAUUGUUCCAUGGCUUdTdT 3′) as described above. Forty-eight hours following transfection, cell lysates were prepared and incubated with a probe for either a housekeeping gene (GAPDH), or a probe for PPIL2 (Genospectra). Probes and RNAs were incubated at 53°C overnight, and the assay was completed according to the manufacturer’s instructions. Relative levels of PPIL2 were determined by normalizing the PPIL2 signal to the signal obtained for GAPDH. Total RNA preparation Cells were transfected with siRNAs as described above. At 48 h post transfection, total RNA was prepared using RNeasy Mini (Qiagen). QIAshredder columns (Qiagen) were used to prepare the cell lysates before purification, and the columns were treated with DNAse I (Qiagen) prior to elution. Microarrays and analysis Microarrays were obtained from Agilent Technologies (Palo Alto, CA) and consisted of 23,500 60-mer oligonucleotides designed for broad coverage of the human genome. Total RNA from untransfected or siRNAtransfected cell cultures was reverse transcribed, followed by in vitro transcription, labeling with Cy3 and Cy5, and hybridization as described (Hughes et al., 2001). For each treatment triplicate RNA samples were processed and hybridized against a common reference pool derived from RNA of the untransfected cells. Scanned intensities were normalized and converted to log ratio values using the Rosetta Resolver system (Rosetta Biosoftware, Seattle, WA). Correlation analysis was performed on the transformed log ratio value. Genes correlated with either PPIL2 or BACE1 were identified based on both absolute correlation coefficient and p-value. Expression of PPIL2 cDNA

siRNA transfection HEK293T cells stably transfected with APP containing an enhanced βsecretase cleavage site (as in (Shi et al., 2005), but containing a wild type αsecretase site) were cultured in DMEM with 10%FBS and 2 μg/ml puromycin. Cells were transfected in 96-well plates using Oligofectamine (Invitrogen) according to the manufacturer’s instructions, with a final concentration of 0.6% Oligofectamine and 50 nM siRNA. Controls included on each plate were a BACE1 siRNA (5′ CCUUCGUUUGCCCAAGAAAdTdT 3′), Pen2 siRNA (5′ CCACGUUCUCUGCUGA-

PPIL2 cDNA was purchased from the Ultimate ORF collection and cloned into pCDNA 6.2/V5-DEST (Invitrogen). Mutations were introduced using QuikChange II XL site-directed mutagenesis kit (Strategene) using the primers 5′-GATGGCACCATCTTCGCAGCATCCATCCGGAAC-3′ and 5′GTTCCGGATGGATGCTGCGAAGATGGTGCCATC-3′. All cDNAs were sequenced confirmed and transfected using Oligofectamine following manufacturer’s guidelines for plasmid transfection. 24 h post-transfection, total RNA was prepared using RNeasy columns and 75 ng was analyzed using Mx3000P Real-Time PCR System (Stratagene). Human GAPDH,

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BACE1, and PPIL2 primers and probes were purchased from Applied Biosystems Assays-on-Demand service. Quantitative RT-PCR data were analyzed using custom-designed software that normalizes the cycles required to achieve target gene threshold signal level to that of GAPDH control gene and compares across samples. Normalized expression values were then compared between triplicate samples using ANOVA.

References Beher, D., Wrigley, J.D., Nadin, A., Evin, G., Masters, C.L., Harrison, T., Castro, J.L., Shearman, M.S., 2001. Pharmacological knock-down of the presenilin 1 heterodimer by a novel gamma-secretase inhibitor: implications for presenilin biology. J. Biol. Chem. 276, 45394–45402. Bergman, A., Hansson, E.M., Pursglove, S.E., Farmery, M.R., Lannfelt, L., Lendahl, U., Lundkvist, J., Naslund, J., 2004. Pen-2 is sequestered in the endoplasmic reticulum and subjected to ubiquitylation and proteasomemediated degradation in the absence of presenilin. J. Biol. Chem. 279, 16744–16753. Berke, S.J., Paulson, H.L., 2003. Protein aggregation and the ubiquitin proteasome pathway: gaining the UPPer hand on neurodegeneration. Curr. Opin. Genet. Dev. 13, 253–261. Bertoli-Avella, A., Oostra, B., Heutink, P., 2004. Chasing genes in Alzheimer's and Parkinson's disease. Hum. Genet. 114, 413–438. Cai, H., Wang, Y., McCarthy, D., Wen, H., Borchelt, D.R., Price, D.L., Wong, P.C., 2001. BACE1 is the major beta-secretase for generation of Abeta peptides by neurons. Nat. Neurosci. 4, 233–234. Christensen, M.A., Zhou, W., Qing, H., Lehman, A., Philipsen, S., Song, W., 2004. Transcriptional regulation of BACE1, the β-amyloid precursor protein β-secretase, by Sp1. Mol. Cell. Biol. 24, 865–874. Christie, G., Markwell, R.E., Gray, C.W., Smith, L., Godfrey, F., Mansfield, F., Wadsworth, H., King, R., McLaughlin, M., Cooper, D.G., Ward, R.V., Howlett, D.R., Hartmann, T., Lichtenthaler, S.F., Beyreuther, K., Underwood, J., Gribble, S.K., Cappai, R., Masters, C.L., Tamaoka, A., Gardner, R.L., Rivett, A.J., Karran, E.H., Allsop, D., 1999. Alzheimer's disease. Correlation of the suppression of β-Amyloid peptide secretion from cultured cells with inhibition of the chymotrypsin-like activity of the proteasome. J. Neurochem. 73, 195–204. Crystal, A.S., Morais, V.A., Fortna, R.R., Carlin, D., Pierson, T.C., Wilson, C.A., Lee, V.M.-Y., Doms, R.W., 2004. Presenilin modulates Pen-2 levels posttranslationally by protecting it from proteasomal degradation. Biochemistry 43, 3555–3563. De Strooper, B., Annaert, W., Cupers, P., Saftig, P., Craessaerts, K., Mumm, J.M., Schroeter, E.H., Schrijvers, V., Wolfe, M.S., Ray, W.J., Goate, A., Kopan, R., 1999. A presenilin-1-dependent gamma-secretase-like protease mediates release of Notch intracellular domain. Nature 398, 518–522. Flood, F., Murphy, S., Cowburn, R.F., Lannfelt, L., Walker, B., Johnston, J.A., 2005. Proteasome-mediated effects on amyloid precursor protein processing at the gamma-secretase site. Biochem. J. 385, 545–550. Gallegos, M., Ahringer, J., Crittenden, S., Kimble, J., 1998. Repression by the 3′ UTR of fem-3, a sex-determining gene, relies on a ubiquitous mog-dependent control in Caenorhabditis elegans. EMBO J. 17, 6337–6347. Ge, Y.-W., Maloney, B., Sambamurti, K., Lahiri, D.K., 2004. Functional characterization of the 5-prime flanking region of the BACE gene: identification of a 91 bp fragment involved in basal level of BACE promoter expression. FASEB J. 18, 1037–1039 (Electronic publication 2004 Apr 1). Hadland, B.K., Manley, N.R., Su, D., Longmore, G.D., Moore, C.L., Wolfe, M.S., Schroeter, E.H., Kopan, R., 2001. Gamma -secretase inhibitors repress thymocyte development. Proc. Natl. Acad. Sci. U. S. A. 98, 7487–7491. Hardy, J.A., Higgins, G.A., 1992. Alzheimer's disease: the amyloid cascade hypothesis. Science 256, 184–185. Hazuda, D., Dodson, E.C., Lai, M.-T., Xu, M., Shi, X.-P., Simon, Wu, A.G., Li, Y., Register, R.B., 2003. Assays using amyloid precursor proteins

with modified beta-secretase cleavage sites to monitor beta-secretase activity. Patent Application, USA. He, W., Lu, Y., Qahwash, I., Hu, X.Y., Chang, A., Yan, R., 2004. Reticulon family members modulate BACE1 activity and amyloid-beta peptide generation. Nat. Med. 10, 959–965. Hughes, T.R., Mao, M., Jones, A.R., Burchard, J., Marton, M.J., Shannon, K.W., Lefkowitz, S.M., Ziman, M., Schelter, J.M., Meyer, M.R., Kobayashi, S., Davis, C., Dai, H., He, Y.D., Stephaniants, S.B., Cavet, G., Walker, W.L., West, A., Coffey, E., Shoemaker, D.D., Stoughton, R., Blanchard, A.P., Friend, S.H., Linsley, P.S., 2001. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat. Biotechnol. 19, 342–347. Iwatsubo, T., 2004. The gamma-secretase complex: machinery for intramembrane proteolysis. Curr. Opin. Neurobiol. 14, 379–383. Jackson, A.L., Bartz, S.R., Schelter, J., Kobayashi, S.V., Burchard, J., Mao, M., Li, B., Cavet, G., Linsley, P.S., 2003. Expression profiling reveals off-target gene regulation by RNAi. Nat. Biotechnol. 21, 635–637 (Electronic publication 2003 May 2018). Keller, J.N., Hanni, K.B., Markesbery, W.R., 2000. Impaired proteasome function in Alzheimer's disease. J. Neurochem. 75, 436–439. Kimberly, W.T., LaVoie, M.J., Ostaszewski, B.L., Ye, W., Wolfe, M.S., Selkoe, D.J., 2003. γ-Secretase is a membrane protein complex comprised of presenilin, nicastrin, aph-1, and pen-2. Proc. Natl. Acad. Sci. U. S. A. 100, 6382–6387. Klein, W.L., Krafft, G.A., Finch, C.E., 2001. Targeting small Abeta oligomers: the solution to an Alzheimer's disease conundrum? Trends Neurosci. 24, 219–224. Lacor, P.N., Buniel, M.C., Chang, L., Fernandez, S.J., Gong, Y., Viola, K.L., Lambert, M.P., Velasco, P.T., Bigio, E.H., Finch, C.E., Krafft, G.A., Klein, W.L., 2004. Synaptic targeting by Alzheimer's-related amyloidbeta oligomers. Neurobiol. Dis. 24, 10191–10200. Lammich, S., Kojro, E., Postina, R., Gilbert, S., Pfeiffer, R., Jasionowski, M., Haass, C., Fahrenholz, F., 1999. Constitutive and regulated alpha -secretase cleavage of Alzheimer's amyloid precursor protein by a disintegrin metalloprotease. Proc. Natl. Acad. Sci. U. S. A. 96, 3922–3927. Lee,H.J.,Jung,K.M.,Huang,Y.Z.,Bennett,L.B.,Lee,J.S.,Mei,L.,Kim,T.W., 2002. Presenilin-dependent gamma-secretase-like intramembrane cleavage of ErbB4. J. Biol. Chem. 277, 6318–6323 (Electronic publication 2001 Dec 6310). Li, J., Pauley, A.M., Myers, R.L., Shuang, R., Brashler, J.R., Yan, R., Buhl, A.E., Ruble, C., Gurney, M.E., 2002. SEL-10 interacts with presenilin-1, facilitates its ubiquitination, and alters A-beta peptide production. J. Neurochem. 82, 1540–1548. López Salon, M., Morelli, L., Castaño, E.M., Soto, E.F., Pasquini, J.M., 2000. Defective ubiquitination of cerebral proteins in Alzheimer's disease. J. Neurosci. Res. 62, 302–310. Marambaud, P., Shioi, J., Serban, G., Georgakopoulos, A., Sarner, S., Nagy, V., Baki, L., Wen, P., Efthimiopoulos, S., Shao, Z., Wisniewski, T., Robakis, N.K., 2002. A presenilin-1/γ-secretase cleavage releases the E-cadherin intracellular domain and regulates disassembly of adherens junctions. EMBO J. 21, 1948–1956. Nunan, J., Shearman, M.S., Checler, F., Cappai, R., Evin, G., Beyreuther, K., Masters, C.L., Small, D.H., 2001. The C-terminal fragment of the Alzheimer's disease amyloid protein precursor is degraded by a proteasome-dependent mechanism distinct from gamma-secretase. Eur. J. Biochem. 268, 5329–5336. Pushkarsky, T., Yurchenko, V., Vanpouille, C., Brichacek, B., Vaisman, I., Hatakeyama, S., Nakayama, K.I., Sherry, B., Bukrinsky, M.I., 2005. Cell surface expression of CD147/EMMPRIN is regulated by cyclophilin 60. J. Biol. Chem. 280, 27866–27871. Qing, H., Zhou, W., Christensen, M.A., Sun, X., Tong, Y., Song, W., 2004. Degradation of BACE by the ubiquitin–proteasome pathway. FASEB J. 18, 1571–1573. Ray, W.J., Yao, M., Mumm, J.S., Schroeter, E.H., Saftig, P., Wolfe, M.S., Selkoe, D., Kopan, R., Goate, A., 1999. Cell surface presenilin-1 participates in the gamma-secretase-like cleavage of Notch. J. Biol. Chem. 274, 36801–36807.

A.S. Espeseth et al. / Mol. Cell. Neurosci. 33 (2006) 227–235 Rogers Jr., G.W., Edelman, G.M., Mauro, V.P., 2004. Differential utilization of upstream AUGs in the β-secretase mRNA suggests that a shunting mechanism regulates translation. Proc. Natl. Acad. Sci. U. S. A. 101, 2794–2799. Sastre, M., Dewachter, I., Rossner, S., Bogdanovic, N., Rosen, E., Borghgraef, P., Evert, B.O., Dumitrescu-Ozimek, L., Thal, D.R., Landreth, G., Walter, J., Klockgether, T., van Leuven, F., Heneka, M.T., 2006. Nonsteroidal anti-inflammatory drugs repress β-secretase gene promoter activity by the activation of PPARgγ. Proc. Natl. Acad. Sci. U. S. A. 103, 443–448. Searfoss, G.H., Jordan, W.H., Calligaro, D.O., Galbreath, E.J., Schirtzinger, L.M., Berridge, B.R., Gao, H., Higgins, M.A., May, P.C., Ryan, T.P., 2003. Adipsin, a biomarker of gastrointestinal toxicity mediated by a functional gamma-secretase inhibitor. J. Biol. Chem. 278, 46107–46116. Selkoe, D.J., 2001. Alzheimer's disease: genes, proteins, and therapy. Physiol. Rev. 81, 741–766. Semple, C.A.M., RIKEN GER Group, GSL Members, 2003. The comparative proteomics of ubiquitination in mouse. Genome Res. 13, 1389–1394. Shi, X.-P., Tugusheva, K., Bruce, J.E., Lucka, A., Chen Dodson, E., Hu, B., Wu, G., Price, E., Register, R.B., Lineberger, J., Gates, A.T., Miller, R., Tang, M., Espeseth, A., Kahana, J., Wolfe, A., Crouthamel, M.,

235

Sankaranarayanan, S., Simon, A., Chen, L., Lai, M.-T., Pietrak, B., Dimuzio-Mower, J., Li, Y., Xu, M., Huang, Q., Garsky, V., Sardana, M.K., Hazuda, D.J., 2005. Novel mutations introduced at the beta-site of amyloid precursor protein enhance the production of amyloid betapeptide by BACE1 in vitro and in cells. J. Alzheimer's Dis. 7, 139–148. von Rotz, R.C., Kins, S., Hipfel, R., von der Kammer, H., Nitsch, R.M., 2005. The novel cytosolic RING finger protein dactylidin is up-regulated in brains of patients with Alzheimer's disease. Eur. J. Neurosci. 21, 1289–1298. Walsh, D.M., Selkoe, D., 2004. Deciphering the molecular basis of memory failure in Alzheimer's disease. Neuron 44, 181–193. Wang, B.B., Hayenga, K.J., Payan, D.G., Fisher, J.M., 1996. Identification of a nuclear-specific cyclophilin which interacts with the proteinase inhibitor eglin c. Biochem. J. 314, 313–319. Yamazaki, T., Haas, C., Takaomi, C.S., Omura, S., Ihara, Y., 1997. Specific increase in Amyloid beta protein 42 secretion ratio by calpain inhibition. Biochemistry 36, 8377–8383. Zhou, W., Song, W., 2006. Leaky scanning and reinitiation regulate BACE1 gene expression. Mol. Cell. Biol. 26, 3353–3364. Zhou, S., Zhou, H., Walian, P.J., Jap, B.K., 2005. CD147 is a regulatory subunit of the γ-secretase complex in Alzheimer's disease amyloid β-peptide production. Proc. Natl. Acad. Sci. U. S. A. 102, 7499–7504.