Báo cáo khoa học: Gene expression silencing with ‘specific’ small interfering RNA goes beyond specificity – a study of key parameters to take into account in the onset of small interfering RNA off-target effects potx

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Gene expression silencing with ‘specific’ small interferingRNA goes beyond specificity a study of key parametersto take into account in the onset of small interfering RNAoff-target effectsSe´bastien Vankoningsloo1, Franc¸oise de Longueville2, Ste´phanie Evrard2, Pierre Rahier2, Andre´eHoubion1, Antoine Fattaccioli1,Me´lanie Gastellier1, Jose´Remacle2, Martine Raes1, Patricia Renard1and Thierry Arnould11 Laboratoire de Biochimie et Biologie Cellulaire, University of Namur (F.U.N.D.P), Belgium2 Eppendorf Array Technologies, Namur, BelgiumRNA interference (RNAi) is a recently discoveredgene-silencing pathway [1] triggered by dsRNA-derived molecules such as small interfering RNAs(siRNAs) or microRNAs, leading to the degradationof a particular mRNA (slicing) or to repression oftranslation [2,3]. Thereafter, the use of chemicallysynthesized siRNAs as a new loss-of-function strategyexploded during the last decade, mainly because theRNAi pathway is believed to apply to all genes inseveral species. Therefore, siRNAs became usefultools for the silencing of genes playing a role in manybiological processes.The extensive use of siRNAs, designed to matchperfectly with a particular mRNA target, is based onthe assumption of their high specificity. Indeed, it wasinitially suggested that only one mismatch could abol-ish the siRNA-induced slicing activity [4]. However,several studies using DNA microarray and ⁄ or compu-tational approaches have shown that siRNAs cangenerate side effects, by inducing the degradation ofnontarget mRNAs sharing sequence homology withthe siRNA seed region, or by repressing the translationof unintended proteins [5–10]. Indeed, in some circum-stances, and especially in immune cells, siRNAs areKeywordscell type; gene expression; off-targeteffects; silencing; siRNACorrespondenceT. Arnould, Laboratoire de Biochimie etBiologie Cellulaire, University of Namur(F.U.N.D.P), 61 rue de Bruxelles, 5000Namur, BelgiumFax: +32 81 724125Tel: +32 81 724129E-mail: thierry.arnould@fundp.ac.be(Received 10 January 2008, revised 12March 2008, accepted 19 March 2008)doi:10.1111/j.1742-4658.2008.06415.xRNA-mediated gene silencing (RNA interference) is a powerful way toknock down gene expression and has revolutionized the fields of cellularand molecular biology. Indeed, the transfection of cultured cells with smallinterfering RNAs (siRNAs) is currently considered to be the best and easi-est approach to loss-of-function experiments. However, several recent stud-ies underscore the off-target and potential cytotoxic effects of siRNAs,which can lead to the silencing of unintended mRNAs. In this study, weused a low-density microarray to assess gene expression modifications inresponse to five different siRNAs in various cell types and transfection con-ditions. We found major differences in off-target signature according to:(a) siRNA sequence; (b) cell type; (c) duration of transfection; and (d)post-transfection time before analysis. These results contribute to a betterunderstanding of important parameters that could impact on siRNA sideeffects in knockdown experiments.AbbreviationsDF, DharmaFECT1; IFN, interferon; IRF, interferon responsive factor; LAMP2, lysosome-associated membrane protein 2; NT, nontargeting;RISC, RNA-induced silencing complex; RNAi, RNA interference; siRNA, small interfering RNA; SREBF1, sterol-responsive element-bindingprotein 1; TLR3, Toll-like receptor 3.2738 FEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBSalso able to trigger an ‘interferon (IFN) response’through the activation of cytosolic proteins such asdsRNA-dependent protein kinase and ⁄ or membranereceptors such as Toll-like receptor 3 (TLR3), leadingto a general repression of translation [11]. An inflam-matory response was also observed in primary humanchondrocytes transfected with siRNAs [12]. These con-siderations cast some doubts on the validity of severalresults previously published particularly on the strictspecificity for targets supposed to be responsible for abiological response and highlight the importance ofstudies intended to increase our understanding of theextent of siRNA nonspecific effects and the conditionsunder which they occur.In this work, we used a low-density DNA micro-array that allows gene expression analysis of 273 genes,in order to determine the off-target effects generatedby five siRNAs in different cell types and experimentalconditions. We first studied the side effects of twodifferent siRNAs targeting the sterol-responsiveelement-binding protein 1 (SREBF1) mRNA encodinga transcription factor, two different siRNAs targetingthe lysosome-associated membrane protein 2 (LAMP2)mRNA encoding a lysosomal glycoprotein, and a non-targeting (NT) siRNA. Gene expression profiles weredetermined for each siRNA in transiently transfectedhuman osteosarcoma 143B cells, lung adenocarci-noma A549 cells, and lung IMR-90 fibroblasts.Furthermore, in 143B cells, we studied the effects ofdifferent transfection and post-transfection periods onthe modifications in gene expression triggered bysiRNA.ResultsVerification of siRNA efficiencyWe used two siRNAs designed to specifically knockdown expression of the transcription factor SREBF1(SREBF1 ⁄ siRNA1 and SREBF1 ⁄ siRNA2), and twosiRNAs targeting the transcript coding for the lyso-somal glycoprotein LAMP2, which is not known to bedirectly involved in transcription events (LAMP2 ⁄ siR-NA1 and LAMP2 ⁄ siRNA2). The particular targetswere chosen on the basis of their interest for otherresearch programmes in our laboratory. The efficiencyof these siRNAs at concentrations ranging from 5 nmto 100 nm was first demonstrated by real-time PCR in143B, A549 and IMR-90 cells (Fig. 1). The choice ofthese cell types was based on the selection of trans-formed or nontransformed cells expressing or notexpressing the siRNA-responsive TLR3 receptor.Indeed, 143B and A549 are tumor-derived cell lines,the latter being reported to express TLR3 [13], whereasIMR-90 is a nonimmortalized cell type. We observedthat the transfection reagent DharmaFECT1 (DF) hasno or little effect on the abundance of SREBF1(Fig. 1A,B) or LAMP2 (Fig. 1C) transcript in thesecell types. The SREBF1-specific siRNAs (100 nm) wereboth very efficient at decreasing SREBF1 transcriptabundance, with reductions of 81%, 66% and 69% forSREBF1 ⁄ siRNA1 and reductions of 79%, 78% and71% for SREBF1 ⁄ siRNA2 in 143B, A549 and IMR-90 cells, respectively (Fig. 1A). Under these conditions,the effect of the SREBF1-targeting siRNA was pro-longed, at least, up to 72 h post-transfection, as dem-onstrated in 143B (Fig. 1B). Both LAMP2-specificsiRNAs (100 nm) were also efficient, as the abundanceof the corresponding transcript was decreased by 89%,78% and 86% for LAMP2 ⁄ siRNA1 and by 64%, 58%and 66% for LAMP2 ⁄ siRNA2 in 143B, A549 andIMR-90 cells, respectively (Fig. 1C). In contrast, ansiRNA with an NT sequence did not dramatically alterthe abundance of SREBF1 or LAMP2 mRNAs inthese conditions. The main observed effect was even aslight increase in the abundance of SREBF1 transcriptin each cell type.The efficiency of SREBF1 ⁄ siRNA1 was also investi-gated at the protein level by western blotting analysisof SREBF1 abundance in 143B cells (Fig. 2). Wefound a concentration-dependent and time-sustaineddecrease in SREBF1 protein abundance in 143B cells.The signals present at 48 h and 72 h after cell transfec-tion with SREBF1 ⁄ siRNA1 (100 nm), apparently notcorrelated with mRNA levels (Fig. 1B), probably resultfrom differences in exposure times during western blot-ting. We also observed a slight increase in SREBF1protein level triggered in the presence of the NTsiRNA, in agreement with the slight increase inSREBF1 mRNA observed under the same conditions(Fig. 1A,B).Off-target signatures elicited by five siRNAs inthree different cell typesWe next studied the effects of DF and of the fivesiRNAs at 100 nm on gene expression. The side effectsof these siRNAs were systematically investigated in143B (Fig. 3), A549 (Fig. 4) and IMR-90 cells (Fig. 5)transiently transfected for 24 h before total RNAextraction and microarray analysis. Please note thatthe scales are different for each heat map. Each experi-ment was performed on biological triplicates, and thecomplete lists of relative transcript level values andcorresponding standard deviations are provided in sup-plementary Tables S1–S12. Several transcripts wereS. Vankoningsloo et al. siRNA off-target effects in different cell typesFEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS 27390.00.51.01.52.02.5Relative SREBF1 mRNA abundance2407248 2407248 2407248DFSREBF1/siRNA1(100 nM)NT siRNA(100 nM)Time post-transfection (h)0.00.20.40.60.81.01.21.41.60.00.20.40.60.81.01.21.41.6Relative SREBF1 mRNA abundanceDF 100 20 5SREBF1siRNA1(nM)100 20 5SREBF1siRNA2(nM)100 20 5NT siRNA (nM)DF 100 20 5SREBF1siRNA1(nM)100 20 5SREBF1siRNA2(nM)100 20 5NT siRNA (nM)DF 100 20 5SREBF1siRNA1(nM)100 20 5SREBF1siRNA2(nM)100 20 5NT siRNA (nM)143BA549 IMR90Relative LAMP2 mRNA abundance143BA549 IMR90DF 100 20 5LAMP2siRNA1(nM)100 20 5LAMP2siRNA2(nM)100 20 5NT siRNA (nM)DF 100 20 5LAMP2siRNA1(nM)100 20 5LAMP2siRNA2(nM)100 20 5NT siRNA (nM)DF 100 20 5LAMP2siRNA1(nM)100 20 5LAMP2siRNA2 (nM)100 20 5NT siRNA (nM)ABCFig. 1. Effect of the SREBF1-targeting and the LAMP2-targeting siRNAs on SREBF1 and LAMP2 mRNA levels analyzed by real-time PCR in143B, A549 and IMR-90 cells. (A) 143B, A549 and IMR-90 cells were incubated for 24 h with DF or transfected for 24 h with SREBF1 ⁄ siR-NA1, SREBF1 ⁄ siRNA2 or the NT siRNA at the indicated concentrations before RNA extraction, reverse transcription, and amplification in thepresence of SYBR Green and specific primers. (B) 143B cells were incubated for 24 h with DF or transfected for 24 h with SREBF1 ⁄ siRNA1or the NT siRNA at 100 nM. RNA was extracted 0, 24, 48 and 72 h post-transfection and processed for real-time PCR analysis. (C) 143B,A549 and IMR-90 cells were incubated for 24 h with DF or transfected for 24 h with LAMP2 ⁄ siRNA1, LAMP2 ⁄ siRNA2 or the NT siRNA atthe indicated concentrations before RNA extraction and processing for real-time PCR analysis. TBP was used as a housekeeping gene fordata normalization. Results are expressed as relative SREBF1 or LAMP2 transcript abundance in treated cells as compared to untreated con-trol cells (n = 1).siRNA off-target effects in different cell types S. Vankoningsloo et al.2740 FEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBSnot detected, most probably because of their absenceor low abundance: depending on the experiment, thetotal number of mRNAs detected ranged between 185and 260 out of 273. The results discussed here beloware only related to genes for which mRNA relativeabundance in siRNA-transfected cells was found to besignificantly different when compared with the mRNAabundance determined in DF-treated cells.First, we observed that treatment with DF aloneaffected the expression of a few genes, especially inIMR-90 cells, such as IGFBP3 (insulin-like growth fac-tor-binding protein 3) (3.3-fold decrease), ICAM1(intercellular adhesion molecule 1) (1.9-fold decrease)and PCNA (proliferating cell nuclear antigen) (1.8-folddecrease) (supplementary Table S9). Second, we estab-lished gene expression profiles for the five siRNAs inthe three cell types. The number of genes differentiallyexpressed in response to siRNAs with statistical signifi-cance ranged between one and 12, according to thecondition. The main conclusion drawn from theseexperiments is that each siRNA is associated with aunique molecular signature on gene expression. Forexample, transcripts that are downregulated byLAMP2 ⁄ siRNA2 in A549 cells, such as JUN (junoncogene), PLAU (plasminogen activator, urokinase),PLAUR (plasminogen activator, urokinase receptor),RRM1 (ribonucleotide reductase M1 polypeptide),TERF1 (telomeric repeat binding factor 1) andTGFBR2 (transforming growth factor, beta recep-tor II) (Fig. 4), were not systematically downregulatedby either LAMP2 ⁄ siRNA1, SREBF1 ⁄ siRNA1,SREBF1 ⁄ siRNA2 or the NT siRNA. Importantly, thefact that two different siRNAs targeting the same tran-script do not provide the same gene expression profiles(see Venn diagrams in Figs 3–5) rules out potentialsecondary effects due to target knockdown, and indi-cates that the unintended mRNA downregulationsobserved are most probably siRNA off-target effects.To some extent, the signatures of siRNAs also seemto be dependent on the cell type in which siRNAs areintroduced. Indeed, whereas several mRNAs were con-sistently downregulated by a given siRNA in every celltype, we found that the abundance of some transcriptswas clearly differently affected by siRNA according tothe cell type, as illustrated by the 2.3-fold downregula-tion of SOD2 (superoxide dismutase 2) found exclu-sively in IMR-90 cells transfected withSREBF1 ⁄ siRNA2. A global analysis of all data cross-ing siRNAs and cell types revealed that about 60% ofthe siRNA off-target effects observed in this studyappear to be cell type-specific.Finally, in order to validate these data with anothermethod, we performed real-time PCR analyses forsome selected transcripts (CTGF, JUN, PLAU ,SPARC, TGFBR2) on samples used for microarrayexperiments (RNAs extracted directly after a 24 htransfection of 143B or A549 cells with SREBF1 ⁄ siR-NA2 or LAMP2 ⁄ siRNA2) (supplementary Table S13).We observed that mRNA abundances were modifiedsimilarly with both methods, attesting to the reliabilityof the results.Kinetics of off-target effects induced by siRNAIn order to determine the time-course of siRNA sideeffects in 143B cells transfected for 24 h withSREBF1 ⁄ siRNA1 or the NT siRNA (100 nm), geneexpression data obtained at 0, 24 and 48 h post-trans-fection were compared in experiments performed onbiological triplicates (Fig. 6). Again, we observed thatthe transfection reagent alone induced only small vari-ations in the abundance of gene transcripts, no matterwhat the post-transfection time was (Fig. 6, col-umns 1–3). In contrast, the relative abundance of sev-eral mRNAs (between two and 15) was significantlymodified in response to the introduction ofSREBF1 ⁄ siRNA1 (Fig. 6, columns 4–6) or the NTsiRNA (Fig. 6, columns 7–9) into 143B cells. In theseconditions, the highest number of modifications wasobserved 24 h post-transfection (Fig. 6, columns 5 andCTL DF 100 50 20 5 100 50 20 5SREBF1siRNA1 (nM)NTsiRNA (nM)SREBF1α-tubulinSREBF1α-tubulinSREBF1α-tubulinSREBF1α-tubulin0 h post-transfection24 h post-transfection48 h post-transfection72 h post-transfectionFig. 2. Effect of the SREBF1-targeting siRNA on SREBF1 proteinlevel analyzed by western blotting in 143B cells. 143B cells wereincubated for 24 h with DF or transfected for 24 h withSREBF1 ⁄ siRNA1 or the NT siRNA at the indicated concentrations.Clear cell lysates were prepared 0, 24, 48 or 72 h post-transfection.SREBF1 abundance was determined by western blotting on 25 lgof protein, and immunodetection of a-tubulin was used as a loadingcontrol.S. Vankoningsloo et al. siRNA off-target effects in different cell typesFEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS 27418) (see also supplementary Tables S1 and S14). Repre-sentative results are presented in Fig. 7, which summa-rizes and illustrates each kind of kinetic profile that weobtained. As shown in Fig. 7A a moderate but sus-tained upregulation of CDKN1B (cyclin-dependentkinase inhibitor 1B, also known as p27Kip1) wasobserved after the transfection of 143B cells withSREBF1 ⁄ siRNA1. In Fig. 7B, we illustrate the upregu-lation of PLAU (plasminogen activator urokinase) incells responding to either SREBF1-specific or the NTsiRNA. A similar profile was also obtained forSPARC (secreted protein acidic cysteine-rich, alsoknown as osteonectin). The abundance of several tran-scripts was also decreased in cells transfected withSREBF1 ⁄ siRNA1, such as CCND2 (cyclin D2)(Fig. 7C), UNG (uracil-DNA glycosylase), ALDOA(aldolase A), CENPF (centromere protein F), CKB(brain creatine kinase) or CTGF (connective tissuegrowth factor). The NT siRNA also downregulatedthe expression of several genes, such as EGFR (epider-mal growth factor receptor) (Fig. 7D), MAP2K1 (alsoknown as MEK1, mitogen-activated protein kinasekinase 1) and RAF1 (murine leukemia viral oncogenehomolog 1). Finally, downregulation of IGFBP3 wasobserved in cells transfected with either SREBF1 ⁄siRNA1 or the NT siRNA (Fig. 7E).Effect of duration of transfection period on siRNAoff-target signatureTo assess the putative effect of the transfection periodon the siRNA nonspecific effects, gene expression pro-files in 143B cells transfected for 24 or 48 h withSREBF1 ⁄ siRNA1 or the NT siRNA at 100 nm werenext determined in three independent experiments.RNA extractions were performed between 0 and 48 hpost-transfection (see also supplementary Tables S14and S15). As shown in Fig. 8, the number of genesdifferentially expressed was higher after a 48 h thanafter a 24 h transfection period. The heat map (Fig. 9)compares, in all tested conditions, the relativeabundances of mRNAs differentially expressed in atleast one condition. In the presence of SREBF1 ⁄siRNA1, we usually observed higher upregulation orSPARCNT_siRNASREBF1-siRNA2SREBF1-siRNA1DFNT_siRNALAMP2-siRNA1LAMP2-siRNA2DFPLAUCCND3CANXCAV1MAP2K1IGFBP3RAF1TNFRSF10BUNGYWHAZCCND1PLAUREGFRDUSP1CTGFJUNSPARCCCND3CCND1CANXCAV1MAP2K1IGFBP3RAF1TNFRSF10BUNGYWHAZPLAUPLAUREGFRDUSP1CTGFJUNABFig. 3. Effect of the SREBF1-targeting and the LAMP2-targeting siRNAs on gene expression profiles analysed by microarray in 143B cells.Cells were incubated for 24 h with DF or transfected for 24 h with SREBF1 ⁄ siRNA1, SREBF1 ⁄ siRNA2 (A), LAMP2 ⁄ siRNA1, LAMP2 ⁄ siRNA2(B) or the NT siRNA at 100 nM before RNA extraction, reverse transcription, and processing for microarray analysis. Expression plots presentthe genes displaying significant differences in relative transcript level between siRNA-transfected cells and DF-treated cells (n = 3). Colorkey: green, downregulation; red, upregulation. A scale for heat maps as minimum and maximum fold differences is presented. The Venndiagrams present the numbers of mRNAs differentially expressed with statistical significance in the presence of the indicated siRNAs in143B cells. The numbers of transcripts differentially expressed in the presence of both siRNAs specific for the same target are indicated indiagram intersections.siRNA off-target effects in different cell types S. Vankoningsloo et al.2742 FEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBSdownregulation magnitudes after a 48 h transfection(Fig. 9, columns 7 and 8) than after a 24 h transfection(Fig. 9, columns 5 and 6). Similar conclusions can bedrawn from data obtained for cells transfected withthe NT siRNA (Fig. 9, columns 11 and 12 versus 9and 10). Therefore, it seems that the longer the trans-fection period, the stronger the off-target effects ofsiRNA on gene expression.mRNA homology with siRNA seed regionPerfect mRNA ⁄ siRNA pairing is not necessary forsiRNA off-target effects. Indeed, homology betweenmRNA and siRNA seed region (encompassing nucleo-tides 2–8 or 2–7 of the antisense strand) was shown tobe sufficient to induce off-target silencing [6,7,10].Hence, we searched for regions of sequence homologybetween the guide strands of the five siRNAs used inthis study and their respective unspecific targets(Fig. 10). The transcripts used for this analysis werefound to be significantly downregulated in 143B, A549and IMR-90 cells transfected for 24 h with the siRNAs(Figs 3–5 and supplementary Tables S1–S12). For sev-eral mRNAs, we found small stretches of sequenceidentity with the 3¢-end of siRNA sense sequences(5¢-end of antisense sequences). However, only 65% ofthem (21 of 33) can lead to perfect mRNA pairingwith siRNA seed regions, as defined above. Therefore,an important proportion (about 35%) of the siRNAside effects observed here cannot be directly explainedby seed homology. This analysis was also repeatedwith the siRNA passenger strands, but no perfect seedmatch was found in these conditions (data not shown).DiscussionIt is now well established that off-target silencing is afundamental feature of siRNAs [5,6,9,14]. The presentinvestigation was conducted in order to increase ourknowledge about siRNA off-target effects under vari-ous experimental conditions. Molecular signatures ofsiRNAs were determined with a commercial low-density microarray designed for siRNA side effectstudies. This microarray comprises 273 capture probes0.50 2.10 0.50 2.00 00 12 SREBF1 siRNA1 SREBF1 siRNA2 80 10 LAMP2 siRNA1 LAMP2 siRNA2 NT_siRNA SREBF1-siRNA2 SREBF1-siRNA1 DF RAF1 GPX1 TERF1 MAP2K1 IGFBP3 CTNNB1 TGFBR2 YWHAZ CCND1 RRM1 PLAUR IL8 JUND CDKN1A PLAU BIN1 MYC JUN CSF1 GADD45A EGFR NT_siRNA LAMP2-siRNA2 LAMP2-siRNA1 DF RAF1 GPX1 MAP2K1 TGFBR2 TERF1 RRM1 CTNNB1 IGFBP3YWHAZ CCND1 PLAUR IL8 JUND CDKN1A PLAU BIN1 MYC JUN CSF1 GADD45A EGFR ABFig. 4. Effect of the SREBF1-targeting and the LAMP2-targeting siRNAs on gene expression profiles analyzed by microarray in A549 cells.Cells were incubated for 24 h with DF or transfected for 24 h with SREBF1 ⁄ siRNA1, SREBF1 ⁄ siRNA2 (A), LAMP2 ⁄ siRNA1, LAMP2 ⁄ siRNA2(B) or the NT siRNA at 100 nM before RNA extraction, reverse transcription, and processing for microarray analysis. Expression plots presentthe genes displaying significant differences in relative transcript level between siRNA-transfected cells and DF-treated cells (n = 3). Colorkey: green, downregulation, red, upregulation. A scale for heat maps as minimum and maximum fold differences is presented. The Venndiagrams present the numbers of mRNAs differentially expressed with statistical significance in the presence of the indicated siRNAs inA549 cells. The numbers of transcripts differentially expressed in the presence of both siRNAs specific for the same target are indicated indiagram intersections.S. Vankoningsloo et al. siRNA off-target effects in different cell typesFEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS 2743allowing the expression analysis, at the transcriptomiclevel, of genes mainly involved in cell responses toIFN challenge, apoptosis, DNA repair, cell cycle, andmetabolism.The few effects of DF on gene expression werefound to be dependent on cell type. Indeed, whereasvariations observed in both 143B and A549 cells incu-bated with DF alone were generally negligible, theywere more numerous in IMR-90 cells, as illustrated bythe slight but reproducible downregulation of ADPRT(ADP-ribosyltransferase), CCNB1 (cyclin B1), DDIT3(DNA-damage-inducible transcript 3), ICAM1, IG-FBP3, PCNA, PRKDC (protein kinase, DNA-acti-vated, catalytic polypeptide), SERPINE1 ⁄ PAI-1(serpin peptidase inhibitor 1 ⁄ plasminogen activatorinhibitor-1), TFDP1 (transcription factor Dp-1),TNFRSF10B (tumor necrosis factor receptor super-family, member 10b) and TYMS (thymidylate synthe-tase). This transfection reagent might therefore altersome cellular processes in a cell type-dependent man-ner. For instance, an increase in the cell cycle timingcould be expected following the downregulation ofPCNA, coding for a protein involved in the control ofDNA replication and CDK2-cyclin A activity [15].In most cases (about 70%), and as expected,DF-induced effects on gene expression were alsoobserved in the presence of any tested siRNA, as illus-trated by the comparable downregulation of ADPRTin IMR-90 cells in the presence of DF alone(0.68 ± 0.25) or in combination with LAMP2 ⁄siRNA2 (0.64 ± 0.17) or the NT siRNA (0.64 ± 0.12)(supplementary Table S12; see also supplementaryTables S9–S11). However, additional or antagonisticeffects of DF and siRNAs were also observed. Forexample, the SERPINE1 mRNA level was reduced byDF alone (0.65 ± 0.08) but was increased with statisti-cal significance by LAMP2 ⁄ siRNA1 (2.24 ± 0.82) inIMR-90 cells (supplementary Table S11).The four targeting siRNAs used in this study pro-vide efficient knockdown of their respective targets at100 nm. This concentration might seem rather high,but was chosen in order to generate side effects allow-ing a comparative study of the importance of siRNAsequence, cell type, transfection period and post-trans-fection time before analysis. The differences in siRNAon-target efficiencies observed between 143B, A549and IMR-90 cells (Fig. 1), as previously found forother cell lines [16], could probably be explained by0.35 1.50 0.35 2.40 703 SREBF1 siRNA1 SREBF1 siRNA2 90 1 LAMP2 siRNA1 LAMP2 siRNA2 NT_siRNA SREBF1-siRNA2SREBF1-siRNA1DF NT_siRNA LAMP2-siRNA2 LAMP2-siRNA1 DF MYBL2 BAD UNG MADH3 WARS SERPINE1 ICAM1 IGFBP3 HIST1H3ITGFBR2HSPCA MAPK1 SOD2 EGFR JUND MYBL2 BAD UNG MADH3 WARS SERPINE1 ICAM1 IGFBP3 HIST1H3ITGFBR2 HSPCA MAPK1 SOD2 EGFR JUND ABFig. 5. Effect of the SREBF1-argeting and the LAMP2-targeting siRNAs on gene expression profiles analyzed by microarray in IMR-90 cells.Cells were incubated for 24 h DF or transfected for 24 h with SREBF1 ⁄ siRNA1, SREBF1 ⁄ siRNA2 (A), LAMP2 ⁄ siRNA1, LAMP2 ⁄ siRNA2 (B)or the NT siRNA at 100 nM before RNA extraction, reverse transcription, and processing for microarray analysis. Expression plots presentthe genes displaying significant differences in relative transcript level between siRNA-transfected cells and DF-treated cells (n = 3). Colorkey: green, downregulation; red, upregulation. A scale for heat maps as minimum and maximum fold differences is presented. The Venndiagrams present the numbers of mRNAs differentially expressed with statistical significance in the presence of the indicated siRNAs inIMR-90 cells. The numbers of transcripts differentially expressed in the presence of both siRNAs specific for the same target are indicatedin diagram intersections.siRNA off-target effects in different cell types S. Vankoningsloo et al.2744 FEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBSthe expression level of the RNAi pathway componentsin each cell type and ⁄ or by different transfection effi-ciencies. These hypotheses highlight the importance ofthe cellular environment in the determination of bothefficiency and specificity of siRNA molecules, not onlyfor in vitro studies, but also when siRNA-based thera-peutic approaches are considered. Moreover, it wassuggested that the cellular background could modifythe degree of siRNA off-target effects elicited through12 34 56 78 9 PLAU NT_48h NT_24h NT_0h SREBF1_48h SREB1F_24h SREB1F_0h DF_48hDF_24hDF_0hSPARC CTGF CDKN1B HSPB1 MLH1 IGFBP2 BCL2L1 HSPCB BIN1 K-ALPHA-1 ADPRT ALDOA CKB CENPF HPRT1 UNG CCND2 CANX CASP3 RAF1 UBE2V1 MAP2K1 EGFR PLAUR IGFBP3 A B Fig. 6. Kinetics of the gene expression profiles induced bySREBF1 ⁄ siRNA1 in 143B cells. (A) Design of the experiment. The24 h transfection period is indicated on a gray background. (B)143B cells were incubated for 24 h with DF or transfected for 24 hwith SREBF1 ⁄ siRNA1 or the NT siRNA at 100 nM. RNA wasextracted 0, 24 or 48 h post-transfection, reverse transcribed, andprocessed for microarray analysis. Expression plots present thegenes displaying significant differences in relative transcript levelbetween siRNA-transfected cells and DF-treated cells (n = 3). Colorkey: green, downregulation; red, upregulation. A scale for heatmaps as minimum and maximum fold differences is presented.0.00.20.40.60.81.01.21.41.6ABCDERel. mRNA abundance0 h 24 h 48 h0 h 24 h 48 h0 h 24 h 48 h0 h 24 h 48 h0 h 24 h 48 h0.00.51.01.52.02.53.03.5Rel. mRNA abundance0.00.20.40.60.81.01.20.00.20.40.60.81.01.20.00.20.40.60.81.01.21.4Rel. mRNA abundanceRel. mRNA abundanceRel. mRNA abundanceFig. 7. Representative kinetic profiles of gene expression in 143Bcells incubated with DF (circles) or transfected with SREBF1 ⁄ siR-NA1 (squares) or the NT siRNA (triangles). Gene expression wasanalyzed by microarray 0, 24 and 48 h post-transfection, and pro-files are illustrated for CDKN1B (A), PLAU (B), CCND2 (C), EGFR(D) and IGFBP3 (E).S. Vankoningsloo et al. siRNA off-target effects in different cell typesFEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS 2745an IFN response pathway, as the IFN response wasfound to be stronger in TLR3-expressing cells [11] andin nontumor cells [17]. However, genes classically asso-ciated with the siRNA-induced IFN response, such asIFITM2 (interferon-induced transmembrane protein 2),IFNAR1 (interferon receptor 1) or IRF1 (interferon-responsive factor 1), were not upregulated in thepresence of siRNAs, even in the TLR3-expressingA549 cells or in the nonimmortalized IMR-90 cells.We showed that two different siRNAs designed toknock down SREBF1 can also modify the expressionof unintended genes in 143B, A549 and IMR-90 cells.Interestingly, the sets of misregulated genes are not thesame for each siRNA. This lack of overlapping effectsrules out an indirect effect resulting from the silencingof the transcription factor SREBF1, which wouldmodify gene expression in an siRNA-independentmanner. Therefore, these variations in mRNA abun-dance can be considered as real siRNA off-targeteffects. Similar conclusions can be drawn from experi-ments performed with two other siRNAs targeting theLAMP2 transcript. Furthermore, we observed that anNT siRNA, used as a negative control in our experi-ments, unexpectedly altered the expression of severalgenes affected or not affected by the siRNAs targetingSREBF1 or LAMP2. Thus, the unique nonspecificmolecular signature generated by each siRNA supportsprevious studies showing that off-target effects aredependent on siRNA sequence [6,7]. The role ofsequence pairing in siRNA side effects is alsosupported by data showing that these effects can bedramatically reduced in the presence of another con-trol, the RNA-induced silencing complex (RISC)-freesiRNA (data not shown). Unlike the NT siRNA, thisnegative control is not loaded onto RISC, is unable tointeract with mRNA, and thus cannot direct slicing. Itis also important to note that the unexpected effects ofthe NT siRNA on gene expression underline the diffi-culty of choosing the most relevant control in RNAiexperiments in order to obtain reliable results, asemphasized recently [18].The seed region is particularly important in siRNAside effects, because mRNA ⁄ siRNA pairing in thisshort region may be sufficient to induce mRNA deg-radation [6,19]. Thus, we investigated whether siRNAseed regions share homology with the sequences ofmRNAs downregulated directly after cell transfectionwith SREBF1 ⁄ siRNA1, SREBF1 ⁄ siRNA2, LAMP2 ⁄siRNA1, LAMP2 ⁄ siRNA2 or the NT siRNA. Wedetermined that about 35% of these downregulatedmRNAs do not show perfect sequence matching withthe seed region of the corresponding siRNA, suggest-ing that these off-target effects are not directed byseed pairing. These results might seem inconsistentwith the current description of siRNA off-targetingmechanisms, in which seed regions play a predomi-nant role [6,10]. It is possible that these 35% of seed-independent variations represent a secondary effectresulting from the downregulation of the 65% seed-matching off-targets. However, as these variationswere observed at the earliest tested time point (0 hpost-transfection), we could not establish whetherthese two categories of genes have different kinetics,and thus could not determine the mechanisms gener-ating all siRNA side effects, a point that will requirefurther investigation.Sequence-dependent side effects of siRNAs on geneexpression are expected to be identical in different celltypes. Gene expression profiles obtained for 143B,A549 and IMR-90 cells allow a cell type-to-cell typecomparison of siRNA side effects, but only for0 h 24 h 48 h 72 h0 h 24 h 48 h 72 hTrans-ABfectionExtraction24 h post-TExtraction48 h post-T20 genes10 genes4 genes3 genesSREBF1/siRNA1NT siRNATrans-fectionExtraction0 h post-TExtraction24 h post-T26 genes27 genes12 genes15 genesNT siRNASREBF1/siRNA1Fig. 8. Effect of two different transfection periods on gene expres-sion profiles in 143B cells transfected with SREBF1 ⁄ siRNA1 or theNT siRNA at 100 nM. (A) Twenty-four hours of transfection andRNA extraction 24 or 48 h post-transfection. (B) Forty-eight hoursof transfection and RNA extraction 0 or 24 h post-transfection.Design of the experiments and number of genes differentiallyexpressed in siRNA-transfected cells when compared withDF- treated cells.siRNA off-target effects in different cell types S. Vankoningsloo et al.2746 FEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS0.355.60IGFBP5DF_T24_E24DF_T24_E48DF_T48_E0DF_T48_E24SREBF1_T24_E24SREBF1_T24_E48SREBF1_T48_E0SREBF_T48_E24NT_T24_E24NT_T24_E48NT_T48_E0NT_T48_E24SPARCMMP2BCL6S100A4FOSTFRCENPP1PLAUIGFBP4CTGFCDH11GSNHSPB1ITGA5MMP14CDKN1BFGF2PCNADHFRUNGKIF23HSPCBMLH1IGFBP2CAV1EF21BCL2L1CDC42PRAMEMADH1BAXCANXMAPK9UBE2CRAD51TFDP1ADPRTBIN1K-ALPHA-1CKBALDOACDK2CENPFTFDP2TERTTGFBR2FGFR1CASP3CTSLABL1UBE2V1RAF1BSGTIMP1COL6A2MAP2K1EGFRCDH13PLAURJUNITGA6HPRT1PLATWARSTNFRSF10BCCND2TK1DUSP1Fig. 9. Effect of two different transfectionperiods on gene expression profiles in 143Bcells transfected with SREBF1 ⁄ siRNA1 orthe NT siRNA at 100 nM. 143B cells wereincubated for 24 h (T24) or 48 h (T48) withDF or transfected for 24 h (T24) or 48 h(T48) with SREBF1 ⁄ siRNA1 or the NT siRNAat 100 nM. RNA was extracted 0 h (E0),24 h (E24) or 48 h (E48) post-transfection,reverse transcribed, and processed formicroarray analysis. Expression plots pres-ent the genes displaying significant differ-ences in relative transcript level betweensiRNA-transfected cells and DF-treated cells(n = 3). Color key: green, downregulation;red, upregulation. A scale for heat maps asminimum and maximum fold differences ispresented.S. Vankoningsloo et al. siRNA off-target effects in different cell typesFEBS Journal 275 (2008) 2738–2753 ª 2008 The Authors Journal compilation ª 2008 FEBS 2747[...]... statistical analysis The data were normalized in a two-step procedure First, a correction was applied using a factor calculated from the intensity ratios of internal standards in the test and reference samples The presence of the internal standard probes at different locations of the array allowed quantification of the local background and evaluation of the array homogeneity, which is taken into account in the. .. TTGTTGCACATATAA-3¢), CTGF (forward, 5¢-CA AGCTGCCCGGGAAAT-3¢; reverse, 5¢-GGACCAGGCA GTTGGCTCTA-3¢), JUN (forward, 5¢-GGATCAAGGC GGAGAGGAA-3¢; reverse, 5¢-TCCAGCCGGGCGATT-3¢), PLAU (forward, 5¢-CTGTGACCAGCACTGTCT CAGTTT-3¢; reverse, 5¢-CCCAGTGAGGATTGGATGA ACTA-3¢), SPARC (forward, 5¢-GAGACCTGTGACCT GGACAATG-3¢; reverse, 5¢-GGAAGGAGTGGATTTAG ATCACAAGA-3¢), TGFBR2 (forward, 5¢-TGGACCCT ACTCTGTCTGTGGAT-3¢;... LAMP2 ⁄ siRNA1 and LAMP2 ⁄ siRNA2 are 5¢UGACUUCCCUGGCCUAUUUUU-3¢, 5¢-ACAUUGAGC UCCUCUCUUGUU-3¢, 5¢-GAUAAGGUUGCUUCAGU UAUU-3¢ and 5¢-ACAGUACGCUAUGAAACUAUU-3¢, respectively As a negative control, we used an NT siRNA (5¢-UAGCGACUAAACACAUCAA-3¢) or a RISC-free siRNA (proprietary sequence) from Dharmacon Cells were transfected with DF (T-2001; Dharmacon) at 1.5 lLÆlg)1 siRNA The transfection efficiency in 143B... extraction kit (Promega, Madison, WI, USA) mRNA contained in 5 lg of total RNA was reverse transcribed using SuperScript II Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions Forward and reverse primers for SREBF1 (forward, 5¢-GGCCCAG GTGACTCAGCTATT-3¢; reverse, 5¢-AGGGCATCCGA GAATTCCTT-3¢), LAMP2 (forward, 5¢-TCAGCATTGC AAATAACAATCTCA-3¢; reverse, 5¢-CAGTCTGCTCT... within the spot) was calculated using local mean background subtraction A signal was only accepted when the average intensity after background subtraction was at least two times higher than the local background around the spot Intensity values of triplicate fluorescent signals were averaged and used to calculate the intensity ratio between the test and the reference Data normalization and statistical analysis... upregulation of several mRNAs, although the underlying mechanisms are unclear siRNAs can activate dsRNA-dependent protein kinase and TLR3 pathways, leading to the activation of transcription factors involved in the IFN response, such as IRFs and nuclear factor-jB [11,20] However, as mentioned above, no IFN response was observed in 143B, A5 49 or IMR-90 cells In fact, the IFN response is activated by dsRNAs... transfected with DF for 24 or 48 h with 100 or 20 nm siRNA Total RNA was extracted 0, 24 or 48 h posttransfection and then processed for microarray analysis FEBS Journal 275 (2008) 273 8–2 753 ª 2008 The Authors Journal compilation ª 2008 FEBS 2749 siRNA off-target effects in different cell types S Vankoningsloo et al Real-time PCR After cell transfection with siRNAs, total RNA was extracted using the Total RNAgent... 15 s and 65 °C for 1 min using an ABI PRISM 7000 SDS thermal cycler (Applied Biosystems) TBP ⁄ TFIID was used as the reference gene for normalization and relative mRNA steady-state level quantification Melting curves were generated after amplification, and data were analyzed using the thermal cycler software Each sample was tested in duplicate Clear cell lysate preparation and western blotting analysis... microarray RNA reverse transcription and cDNA hybridization After cell transfection with siRNAs, total RNA was extracted with the Total RNAgents extraction kit (Promega), quality was checked with a bioanalyzer (Agilent Technologies, Santa Clara, CA, USA), and 10 lg (143B cells) or 20 lg (IMR-90 and A5 49 cells) was used for reverse transcription in the presence of biotin-11-dCTP, biotin-11-dATP (Perkin-Elmer,... Small RNAs: regulators and guardians of the genome J Cell Physiol 213, 41 2–4 19 3 Martin SE & Caplen NJ (2007) Applications of RNA interference in mammalian systems Annu Rev Genomics Hum Genet 8, 8 1–1 08 4 Elbashir SM, Martinez J, Patkaniowska A, Lendeckel W & Tuschl T (2001) Functional anatomy of siRNAs for mediating efficient RNAi in Drosophila melanogaster embryo lysate EMBO J 20, 687 7–6 888 5 Summerton . Gene expression silencing with ‘specific’ small interfering RNA goes beyond specificity – a study of key parameters to take into account in the onset of. transfection with siRNAs, total RNA wasextracted using the Total RNAgent extraction kit (Pro-mega, Madison, WI, USA). mRNA contained in 5 lgoftotal RNA was reverse
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Xem thêm: Báo cáo khoa học: Gene expression silencing with ‘specific’ small interfering RNA goes beyond specificity – a study of key parameters to take into account in the onset of small interfering RNA off-target effects potx, Báo cáo khoa học: Gene expression silencing with ‘specific’ small interfering RNA goes beyond specificity – a study of key parameters to take into account in the onset of small interfering RNA off-target effects potx, Báo cáo khoa học: Gene expression silencing with ‘specific’ small interfering RNA goes beyond specificity – a study of key parameters to take into account in the onset of small interfering RNA off-target effects potx