MMTV is a type B betaretrovirus which preassembles intracellularly, a phenomenon distinct from retroviruses that assemble the progeny virion at cell surface just before budding such as the type C human and feline immunodeficiency viruses (HIV and FIV). Studies of FIV and Mason-Pfizer monkey virus (MPMV), a type D betaretrovirus with similar intracellular virion assembly processes as MMTV, have shown that the 5′ untranslated region (5′ UTR) and 5′ end of gag or 5′ UTR sequences, or incremental amounts of 5′ UTR in the presence of 400 nucleotides (nt) of gag were constructed to delineate the extent of 5′ sequences that may be involved in MMTV gRNA packaging. Real time PCR measured the packaging efficiency of these vector RNAs into MMTV particles generated by co-transfection of MMTV Gag/Pol, vesicular stomatitis virus envelope glycoprotein (VSV-G Env), and individual transfer vectors into human 293T cells. Transfer vector RNA propagation was monitored by measuring transduction of target HeLaT4 cells following infection with viral particles containing a hygromycin resistance gene expression cassette on the packaged RNA.Three series of MMTV transfer vectors containing incremental amounts of gag for not only efficient gRNA packaging but also propagation of MMTV-based transfer vector RNAs. Vector RNAs without the entire 5′ UTR were defective for both efficient packaging and propagation into target cells.MMTV requires the entire 5′ UTR and a minimum of ∼120 nucleotide (nt) at the 5′ end of These results reveal that the 5′ end of MMTV genome is critical for both gRNA packaging and propagation, unlike the recently delineated FIV and MPMV packaging determinants that have been shown to be of bipartite nature. However, early MMTV studies showed that MMTV genome containing deletion in the gag sequences important in these processes. Using several series of MMTV sub-genomic vectors in a biologically relevant in vivo packaging and transduction assay, our results reveal that unlike retroviruses such as FIV gag, for efficient gRNA packaging and propagation of the packaged transfer vector RNA into the infected cells.In order to further map the minimum viral sequences important for MMTV gRNA packaging and transfer vector RNA propagation, a systematic deletion approach was employed to delineate the extent of 5′ UTR and in vivo RNA packaging and propagation assay for MMTV was employed that utilizes an MMTV gag/pol expression construct (JA10) for the production of viral structural and enzymatic proteins To study MMTV RNA packaging, the newly developed hygromycin resistance gene driven from the simian virus 40 (SV40) promoter as a marker for successful propagation, a truncated MMTV env gene, and the 3′ MMTV LTR  even with the vector DA07 containing the entire 5′ UTR and 400 nt of gag  that could be propagated, although inefficiently, was tested. Reverse transcriptase (RT) PCR of the DA series of vector RNAs packaged by the virus particles revealed that the vector RNAs could be packaged, but quite inefficiently with some of the samples requiring Southern blotting for visualization of the packaged RNA  regulatory export pathway. This pathway has recently been described in MMTV To circumvent any potential problems with poor MMTV promoter efficiency in human cells and RNA export defects, the 5′ MMTV LTR was modified by replacing the U3 region (containing the promoter) with the constitutively active human cytomegalovirus (hCMV) promoter that has been classically used as a high efficiency promoter in mammalian cells . A similenv expression vector MD.G for virus production into 293T cells. Following transfection, virus particles were isolated from each transfected cultures to quantify the effect of the introduced mutations on both gRNA packaging and propagation. However, before quantifying the viral RNA contents in the viral particles, it was imperative to determine whether each vector RNA was expressed stably and transported to the cytoplasm successfully.The modified transfer vectors  were co-In order to ascertain stable expression and efficient nuclear export of transfer vector RNAs, nuclear and cytoplasmic RNA fractions were prepared from the transfected cells and DNase-treated to ensure removal of any contaminating plasmid DNA ; panel IThe relative expression of the various transfer vector RNAs in the cytoplasm was tested using a custom-made MMTV Taqman real time PCR assay in combination with a commercially-available-endogenous β-actin Taqman assay (Applied Biosystems). The custom MMTV Taqman assay was designed within the U5 region of the transfer vector RNAs, enabling detection of all mutant transfer vector RNAs via a single primer/probe combination. To allow a relative comparison of the transfer vector RNA expression using β-actin as an endogenous control, we determined whether the amplification efficiencies of the two assays were equivalent. This was accomplished by first determining the value of the threshold cycle, Ct , followeTest of the cDNAs prepared from the cytoplasmic RNA fractions revealed that the transfer vector RNAs were stably expressed between Ct values of 23.5–27.5 and efficiently exported to the cytoplasm . AlongsiNext, the packaging efficiency of the transfer vector RNAs into the pseudotyped MMTV particles was assessed by the same custom-made real time PCR assay as described above. Towards this end, the first question asked was whether a cellular housekeeping β-actin mRNA could be used as an endogenous control in our assays since it is not a recognized virion-associated mRNA. It has now been well-established that cellular RNAs can be packaged into retroviral particles as has been shown for several RNAs such as 7SL RNA, U6 snRNA, tRNA, or mRNAs for cyclophilin A and for several types of ribosomal proteins, and even ribosomal RNA itself As opposed to β-actin mRNA, all transfer vector RNAs were encapsidated with widely different packaging efficiencies, encompassing raw Ct values between 23–36, depending upon the amount and type of sequence present at the 5′ end of the sub-genomic RNAs (see boxed region in 10 Relative Quantification (RQ) units (∼ three-folds above the mock level).Further normalization of the transfer vector RNAs packaged into the virus particles was performed to take into account differences in transfection efficiency observed using the luciferase expression vector in each transfected cultures . The samgag were the most efficiently packaged  compared to vector series with incremental amounts of 5′ UTR either without gag (FA series) or with gag (NS series) except for NS12 (gag) that was efficiently packaged and comparable to the DA series of vectors. Overall, these results revealed that the intact 5′ UTR is critical for efficient RNA packaging but is not sufficient by itself for this crucial step of MMTV life cycle.Normalization of the data revealed that the DA series of transfer vectors with the entire 5′ UTR and incremental amounts of for NS12 . In factfor NS12 , packagigag sequences increased, so did the packaging efficiency with DA24 containing 400 nt gag being the vector packaged most efficiently (gag respectively and these vector RNAs were packaged within < one log of DA24 (p<0.01). These results corroborated well the observations made earlier using MMTV vectors harboring similar sequences and containing wild type MMTV LTR as the promoter , as the incremental amount of iciently . Howeverpromoter  that 120 compare  and 5C.gag (comparable to DA24), showed lower packaging efficiency  and was similar to DA22 and DA23, vectors with 120 and 150 nt of gag sequences, respectively  resulted in greater than 100-fold (∼2 log) drop in RNA packaging efficiency compared to the vector RNA with the entire 5′ UTR, NS12 (gag (FA26) was packaged at a greater than 10-fold (1 log) lower efficiency than NS12 and greater than 60-fold (∼1.8 log) lower efficiency than DA24, vectors containing the entire 5′ UTR in the presence of 400 nt of gag (p<0.01), confirming that gag sequences are indeed required during MMTV gRNA packaging  contains elements critical for proper completion of steps in vector RNA propagation, such as RNA dimerization, encapsidation, reverse transcription, and integration since our readout assay for RNA propagation was dependent on the successful completion of these crucial steps in virus life cycle, and 2) the entire 5′ UTR itself is not sufficient and requires ∼120–400 nt of gag for efficient vector RNA propagation. Overall, these results mimicked the RNA packaging and propagation results obtained with the wild type MMTV LTR vectors and further validated that the intact 5′ UTR is as critical for efficient RNA propagation as it is for successful RNA packaging  LTR gag sequences, 2) the insensitivity of the assays used to study RNA packaging. In their assay, RNA from a 100 ml of a wild type virus stock containing 2×107 virions/ml  was required to observe packaging efficiently on a dot blot assay. In contrast, in our real time-based PCR assay, we could efficiently observe packaged retroviral subgenomic RNAs from vectors that gave rise to even 25 CFU/ml   or provide stability to the RNA higher order structure that the 5′ region may assume. Consistent with this, it has recently been shown that at least for FIV and MPMV, the gag sequences are involved in long range interaction (LRI) with sequences at the 5′ end of the gRNA gag sequences results in destabilization of the overall RNA secondary structure and consequently, RNA packaging and propagation gag sequences is not so clear in the case of SIV since most of the studies conducted on SIV RNA packaging have maintained gag sequences gag region (9 nts) may be required for efficient RNA packaging without affecting RNA dimerization or nucleocapsid binding Spe I restriction site insertion between the end of 5′ UTR and gag AUG had resulted in lower packaging efficiency of the NS12 vector compared to the DA24  . Considethe DA24 .Over the years, it is becoming increasingly clear that retroviral RNA packaging and dimerization, regardless of the primary sequence, are dependent on RNA structural motifs of the packaging determinants and their interaction(s) at the structural level (RNA-RNA interactions during dimerization and RNA-protein interactions during packaging) (reviewed in gag/pol genes in the presence of the MPMV CTE using the hCMV promoter and the bovine growth hormone (BGH) poly A sequences. The transfer vectors were created as three series: the DA series with incremental deletions of gag sequences in the presence of the entire 5′ UTR, the FA series with incremental deletions of the 5′ UTR sequences in the absence of gag, and the NS series with incremental deletions of the 5′ UTR sequences in the presence of 400 nt of gag  by the pseudotyped virus particles and selection for hygromycin-resistant colonies, as described previously The human epithelial kidney cell line, 293T, was used for the production of VSV-G-pseudotyped-MMTV virus particles containing RNA from the various constructs using a modified calcium phosphate method as described Transfected cells were fractionated into nuclear and cytoplasmic fractions to allow separate analysis of RNA residing within the two cellular compartments as described earlier GTC CTA ATA TTC ACG TCT CGT GTG, nt 1179–1202 and OTR 672 (−) CTG TTC GGG CGC CAG CTG CCG CAG, nt 1298–1321. Hybridization was performed using the AlkPhos Direct Labeling Kit  as per manufacturer's directions.Some of the packaged viral RNA samples were subjected to Southern blot analysis as described earlier TCGCCATCCCGTCTCC ; Forward primer (MTV-1LTR-SITEF): CGTCTCGTGTGTTTGTGTTTGTGTCTGT ; Reverse primer (MTV-1LTR-SITER): CCTCTGGAAAGTGAAGGATAAGTGA . The assay was validated in silico using the Primer Express tool as well as the ABI design pipeline bioinformatic tools that ensure specificity, reproducibility, and amplification efficiency of the assay performance. Further validation of the PCR amplification efficiency was conducted by testing the assay using the online web tool “pcrEfficiency” To test the relative levels of transfer vector RNAs expressed within the cytoplasm and packaged into the viral particles, a real time PCR custom expression assay was developed using the minor groove binding (MGB)/FAM and MGB/VIC chemistry from Applied Biosystems, USA. Additionally, the ABI real time PCR assays use ROX as an internal fluorescence reference dye to which the target reporter dye signal  is normalized to during data analysis, to correct for fluorescence fluctuations caused by changes in concentration or volume. The PCR primers were designed to anneal within a region at the beginning of the MMTV U5 region (nt 1192–1259), a 68 nt region common to all the constructs, enabling their relative quantitative assessment using the same probe/primer combination concomitantly. The sequence of the probe and primers were as follows: Probe (MTV-1LTR-SITEM1 FAM): To determine which method to use for the Relative Quantification analysis, the standard curve or the comparative (ΔΔCt) method, a 10- and serial 2-fold dilutions of a cDNA prepared from 293T cells expressing DA24 were tested in non-multiplex RT-PCRs in triplicates assuming conservatively that 1 ug of input RNA results in ∼100 ng of single stranded cDNA using random hexamers as primers and MMLV RT Promega; . The resth of the total viral RNA preparations were first DNase-treated, confirmed for the absence of DNA by PCR using vector RNA specific primers, and then reverse transcribed into cDNA, as previously described For the final relative quantification analysis, each viral RNA sample was tested in triplicates in multiple assays using the Taqman Universal Master Mix , while the cytoplasmic RNA was tested in duplicates. As mentioned earlier for the cytoplasmic RNA fractions, 1/5ttest was performed between various constructs using the Microsoft Excel software. A value of p<0.01 was considered statistically significant.To determine whether the observed differences in the normalized packaging efficiencies were statistically significant, a standard, paired, two-tailed Student's


We therefore conclude that hypoxia-induced edited RNAs of F11R are preferentially stabilized and accumulate in the nucleus preventing their export to the cytoplasm for translation. This mechanism may be used by additional proteins in the cell as part of the cell's effort to reduce metabolism upon hypoxic stress. F11R is a cell adhesion molecule found on the surface of human platelets. It plays a role in platelet aggregation, cell migration and cell proliferation. F11R is subjected to RNA editing, a post-transcriptional modification which affects RNA structure, stability, localization, translation and splicing. RNA editing in the 3'UTR of F11R and RNA levels are increased upon hypoxia. We therefore set to examine if RNA editing plays a role in the increase of F11R RNA seen upon hypoxic conditions. We show that ADAR1, but not ADAR2, takes part in the editing of F11R however editing alone is not sufficient for obtaining an elevation in RNA levels. In addition we show that hyper-edited mature mRNAs are retained in the nucleus and are associated with p54 The complexity of higher organisms is achieved by a variety of post-transcriptional and post-translational mechanisms that enhance gene and protein diversity through the generation of alternative products from a single gene and by their effects on RNA and protein processing. RNA editing is one of the post-transcriptional mechanisms that introduces changes in RNA sequences allowing organisms to produce many more gene products and functions than predicted based on the number of genes within their genome. RNA ediAlu elements, non-coding short interspersed elements (SINEs) about 280bp long, which account for more than 10% of the human genome [Alu subfamilies share relatively high homology, which renders them as ideal templates for RNA editing as oppositely oriented Alu elements can form dsRNA structures [nrb protein that binds inosine-containing RNAs has been shown to cause the retention of some highly edited RNAs within the nucleus, thereby preventing their export and translation [The site-selective modification of adenosines to inosines in RNA molecules is mediated by a family of enzymes termed ADAR (adenosine deaminase acting on RNA). In humans two ADARs (ADAR1 and ADAR2) are responsible for all currently known A-to-I editing activity and they modify RNAs with distinct but overlapping specificities . ADAR1 en genome . Alu subructures . A nuclenslation ,12. In tnslation . In addinslation ,14,15.Alu sequence embedded in the 3'UTR of the gene [It has been previously shown that the F11 receptor (F11R) gene is subjected to A-to-I RNA editing in an the gene ,17. F11Rthe gene . F11R isthe gene . Park anthe gene . Gene exthe gene . In breathe gene . We havethe gene .Alu element embedded in the 3'UTR of F11R. In addition we found that hypoxic conditions and editing of F11R are required for the elevated RNA levels of the gene. Upon hypoxia highly edited F11R transcripts were retained in the nucleus associated with p54nrb. Our results suggest a mechanism for controlling F11R expression upon hypoxic conditions. In the current study we asked if A-to-I RNA editing plays a role in the hypoxia-induced expression of F11R. To address this question we silenced or overexpressed ADAR1 or ADAR2 and examined their effect on F11R expression. In addition we inhibited RNA synthesis in the cell in order to understand if increased F11R expression is due to the synthesis of new RNA molecules. We have found that ADAR1 plays a role in the editing of the Alu element embedded in the 3'UTR of the gene. We have previously shown that upon treatment of a lymphoblastoid (LB) cell line with DFO, RNA editing in F11R is increased. Concomitant to the increased editing, we observed an increase in the mRNA levels of the gene [The F11R (JAM-A) gene undergoes A-to-I RNA editing in an the gene . A Western blot of protein extracts from LB cells revealed that, in contrast to the increase in F11R RNA obtained following treatment with DFO, F11R protein levels in treated cells were slightly reduced . -p150 RNA was increased 2.5-fold , only in reactions conducted on RNA extracted from the nuclei of DFO-treated cells precipitated with a p54nrb-specific antibody implying that upon hypoxic conditions F11R RNA binds the p54nrb protein in the nucleus enabling the stabilization of these molecules  or by the small amount of ADAR that remained in the cell despite the silencing . However, the lower editing levels in the 3'UTR of F11R did not prevent the hypoxia-dependent increase in F11R RNA implying that an additional hypoxia-dependent factor is required for the elevated levels of RNA. Accordingly we have found that overexpressing ADAR1-p150 by means other than hypoxia caused a slight increase in the editing of F11R with no concomitant change in it's RNA levels corroborating our conclusion that hypoxia is required for the elevated levels of F11R RNA. It is worth noting that upon normoxia, silencing of either ADARs and the low editing levels that followed did not affect the amount of F11R RNA implying that these are not a requirement for F11R RNA expression upon normoxia. In addition we show that transcription nrb  approved human involvement and cell line creation in this study. Written consent to participate in this study was obtained from donor.The cell line used in this work is an Epstein-Barr virus (EBV)-transformed lymphoblastoid (LB) cell line originating from the B cells of a healthy male donor. Cells were cultured in RPMI supplemented with penicillin-streptomycin and 10% fetal bovine serum.To mimic hypoxia, cells were treated with 1000μM Deferoxamine (Sigma-Aldrich). To inhibit RNA polymerase II transcription cells were treated with 10μg/ml α-amanitin (Sigma-Aldrich). To increase ADAR1-p150, cells were treated with 2000units/ml of Interferon-α (Peprotech Inc.).6 per well) were pelleted and resuspended in 90μl of Ingenio Electroporation Solution (Mirus) and 10μl of siRNA or plasmid. Each sample was electroporated in the Nucleofactor Device (Amaxa Biosystems) using the R-13 program. Cells were transferred into 2ml medium and cultured for a period of 24-72h; subsequently the expression of mRNA and proteins was analyzed. All experiments were repeated at least three times.LB cells  was obtained from Origene. An empty pRc/CMV plasmid was used as control. Transfection were carried out using 1μg plasmid.Total RNA was extracted from cells using the TRIzol reagent (Invitrogen) according to the manufacture’s protocol. cDNA was prepared from 2μg of total RNA with the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the manufacture’s protocol.PCR amplifications were performed using ReddyMix PCR Master Mix (ABgene). For sequencing reactions, PCR fragments were extracted and purified from the gel using Zymoclean Gel DNA Recovery Kit (Zymo Research) according to the manufacture’s protocol. Purified DNA was fluorescently labeled using the BigDye terminator V1.1 cycle enzyme (Applied Biosystems). Following precipitation, fragments were sequenced using the ABI Prism 3100 Genetic Analyzer Biosystem.Inosine is similar in structure to guanine and is therefore read by the automatic DNA sequencer as “G”. A-to-I RNA editing is identified as a site in the cDNA sequence with overlapping A and G peeks. The percentage of RNA editing was measured using the Accelrys Gene software by calculating the level of guanine expression at a certain sequence position divided by the total expression of adenine and guanine at the same point. Edited sites are only those sites that exhibited more than 5% editing. Alu sequence embedded in the 3'UTR of the F11R gene. Average editing is the average percentage of editing at 12 sites (listed below). The amplified region from the Alu sequence is positioned at chr1: 160967771-160968006 according to the UCSC genome assembly (February 2009).Editing in F11R was examined in an RQ-PCR was performed in order to determine the levels of mRNA expression of ADAR1-p110, ADAR1-p150, ADAR2 (ADARB1) and F11R. We used the ABL gene as a reference gene, which showed stable levels of expression in our treated and non-treated samples (data not shown). In the experiments performed with α–amanitin the 18S gene was used as a reference gene as it was not affected by the treatment. Primers were designed according to Primer-Express software guidelines (Applied Biosystems) to enable the amplification of mature mRNA only. The sequences of all the primers and probes used for RQ-PCR are listed below. All probes carried a 5'FAM and a 3'BHQ. The RQ-PCR reactions were run on ABI 7900HT genetic analyzer utilizing SDS 2.3 software (Applied Biosystems). All reactions were run as triplicates. Reactions were performed in a total volume of 20 μl containing cDNA equivalent to 100 ng of RNA from each sample. The PCR conditions consisted of 2 min at 50°C, 10 min at 95°C, 40 cycles of 15 sec at 95°C, 1 min at 60°C. Analysis of the results was performed by the SDS RQ manager 1.2 software using the ΔΔCt method. Proteins were extracted from cells using RIPA buffer (Sigma-Aldrich) supplemented with protease inhibitor (Roche). Following separation on a SDS-PAGE, proteins were transferred to a nitrocellulose membrane using the iBlot Dry Blotting System (Invitrogen). Membranes were stained with a primary antibody over night at 4°C, washed and incubated with the appropriate secondary antibody for 45'-60' at room temperature. Specific reactive bands were detected using the SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific). Relative quantification of the proteins was performed using the Image-J software. The Antibodies used were: anti-ADAR1 (Santa Cruz sc-73408), anti-JAM-A (Santa Cruz sc-53623) and anti-Actin (Epitomics 1184-1). Fractionation was carried out using the PARIS kit  according to the manufacturer's protocol. Fractionation quality was verified by carrying out relative quantification analysis of a snoRNA and by western blot analysis with an antibody against the nuclear protein emerin (data not shown).2 + 250mj/cm2) and fractionated using the PARIS buffer followed by sonication of the nuclear extracts. Precleared lysates were subjected to the anti-p54nrb antibody or anti-mouse IgG antibody conjugated beads (anti-mouse IgG agarose beads) for 2h at 4°C in binding buffer  + 10mM DTT + 400uM RVC + 20mM EDTA). The beads were then washed 5 times with wash buffer  and extracted with elution buffer  at room temperature for 10min. The IP material was used for RNA extraction with TRIzol. cDNA synthesis was performed as mentioned above.LB cells were UV cross-linked . Comparative means were calculated by one-way ANOVA  test, with significance level of p ≤ 0.01.Primers used for the amplification of cDNA for checking A-to-I RNA editing.CCAAAAGGATTTAAAACCGCTGC; F11Redit-R: GAGCTGGAGT-TTTGCTCTTGTTGC; F11Rexon-F: CCCGAAGTGAAGGAGAATTCAAAC; F11Rintron-F: GTGAGGAGATTTCTAGCCCATGTTF11Redit-F: Primers used in RQ-PCR analysis.TGGAGATAACACTCTAAGCATAACTAAAGGT; ABL-R: GATGTAG-TTGGGACCCA; ADAR110-F: GTGTCCCGAGGAAGTGCAA; ADAR110-R: TGTCTGTGCTCATAGCCTTGAAA; ADAR150-F: CGGGCGCAATGAATCC; ADAR150-R: TGTGCTCATAGCCTTGAAATGG; ADAR2-F: CGCTGCGCACA-ACCAA; ADAR2-R: GTTGCCCCTTAAGCTCTCCAT; F11Rmature-F: GCCCG-AAGTGAAGGAGAATTC; F11Rmature-R: CAGATGATAGGCGGTGAGCC; 18S-F: CGGCTACCACATCCAAGGAA; 18S-R: GCTGGAATTACCGCGGCT; SnoRD57-F: GGAGGTGATGAACTGTCTGAGC; SnoRD57-R: GGATCAGGCT-CATTAAATCAGTTTABL-F: Probes used in RQ-PCR analysisCCATTTTTGGTTTGGGCTTCACACCATT; ADAR110-P: TTCCCTCA-GCGGATACTACACCCATCC; ADAR2-P: AGACTGCGGCCGAAGCGTGGABL-P: Position of the editing sites used for the average editing according to UCSC genome assembly, February 2009:1-160967833; 2-160967848; 3-160967854; 4-160967855; 5-160967856; 6-160967857; 7-160967860; 8-160967890; 9-160967891; 10-160967896; 11-160967899; 12-160967938; Position of the additional editing sites that appeared upon α-amanitin treatment according to UCSC genome assembly, February 2009: a-160967839; b-160967843; c-160967918; d-160967935; e-160967936; f-160967941; g-160967952;


Preferences are traditionally assumed to be stable. However, empirical evidence such as preference modulation following choices calls this assumption into question. The evolution of such postchoice preference over long time spans, even when choices have been explicitly forgotten, has so far not been studied. In two experiments, we investigated this question by using a variant of the free choice paradigm: In a first session, participants evaluated the pleasantness of a number of odors. We then formed pairs of similarly rated odors, and asked participants to choose their favorite, for each pair. Participants were then presented with all odors again, and asked for another pleasantness rating. In a second session 1 week later, a third pleasantness rating was obtained, and participants were again asked to choose between the same options. Results suggested postchoice preference modulation immediately and 1 week after choice for both chosen and rejected options, even when choices were not explicitly remembered. A third experiment, using another paradigm, confirmed that choice can have a modulatory impact on preferences, and that this modulation can be long-lasting. Taken together, these findings suggest that although preferences appear to be flexible because they are modulated by choices, this modulation also appears to be stable over time and even without explicit recollection of the choice. These results bring a new argument to the idea that postchoice preference modulation could rely on implicit mechanisms, and are consistent with the recent proposal that cognitive dissonance reduction could to some extent be implicit. The results showed a significant increase in the quality ratings of the two most important attributes related to the chosen alternative after 1 week but not immediately after the decision. Gilbert and Ebert Although the free-choice paradigm has been widely used during the last 50 years However, the results of all the above-mentioned studies have been recently rendered ambiguous. The methodology of the free-choice paradigm has indeed been under lively discussion recently, with a focus on what controls are appropriate when analyzing whether the choice phase truly causes a modulation in preferences e.g., .Chen and Risen p = .06) between these sequences of measurement (RCR vs. RRC), suggesting the existence of choice-induced preference changes.On the empirical side, Chen and Risen Recent works have addressed Chen and Risen’s rests on the unwarranted assumption that the…] choice provides a perfectly reliable measure of subjects’ preference for the chosen item over the unchosen item”. They formally showed that the more random the choices, the less important Chen and Risen’s argument. How randomly choices reflect “true” preferences for similarly rated stimuli remains an empirical question–that is, the results derived with standard methodology are not necessarily rendered meaningless by Chen and Risen’s argument.On the theoretical side, Sagarin and Skrowonski when choice is manipulated, thus establishing the effect in circumstances in which Chen and Risen’s argument does not seem to apply. Sharot et al. were not actually making, even if they had the feeling that they did. Note that this strategy has also been recognized by Risen and Chen Moreover, two recent studies experienced utilitypredicted utility, that is, the beliefs about the subjective pleasure experience with a stimulus. In Ritov’s study The present series of experiments emphasizes four aspects that were not included as the main focus in the studies previously described. The first and most crucial aspect is that in the research we report here, we added a control (Experiment 3) for this issue raised by Chen and Risen. This control confirms the robustness of postchoice preference change to settings in which Chen and Risen’s for both chosen and rejected stimuli and during the experienced pleasantness elicited by an actual presentation of these stimuli–is not an epiphenomenon, fading away after some time has passed. Crucially, no study so far have investigated postchoice preference modulation in long time spans in controlling that this effect is not an artifact of the free-choice paradigm In summary, no study, to the best of our knowledge, has thoroughly rejected the possibility that postchoice preference modulation–We conducted a series of three experiments in order to address these questions. Specifically, in the first two experiments, using an adapted version of the free-choice paradigm, we tested whether postchoice preference modulation can be robust for a 1-week interval and whether results vary depending on participants’ explicit memory of their initial choices. In the third experiment, using a paradigm addressing recent criticisms regarding the true impact of choices on preferences This first experiment, as well as Experiments 2 and 3, part of the EmOdor project, have been approved by the ethics committee of the Faculty of Psychology and Sciences of Education (FPSE) at the University of Geneva. All participants were over 18 and gave a written consent form.Forty-one University of Geneva students  took part in this experiment. Before starting the experiment, participants completed a written consent form. All participants reported a normal sense of smell. They were individually tested and were paid 15 Swiss Francs (about 15 US Dollars) for their participation. During the days of testing, they were asked not to wear any fragrance.Sixteen odorants  were selected on the basis of their ratings of pleasantness, familiarity, and intensity obtained from previous studies The present experiment was divided into two parts, separated by 1 week. The time of day of the experimental session was unchanged for a given participant.First, we assessed the individual’s ratings of pleasantness, familiarity, and intensity for 8 of the 16 odors (target odors). On the basis of these first pleasantness ratings, four pairs were created for the choice phase. During this choice phase, participants were presented with two kinds of odor pairs: (a) two pairs of odors that they had rated as very similarly pleasant , and (b) two pairs of odors that they had rated very differently for pleasantness . Second, for each pair, participants were required to choose the odor they preferred. Third, after these choices had been made, participants were again requested to assess the pleasantness, familiarity, and intensity of the eight odors see . FinallyFirst, participants were asked to assess the pleasantness of the eight odorants already used during the first session. Second, they were asked to choose the odor they preferred for the same pairs of odors that they were presented with during the first session, 1 week before. These pairs were specific to a given participant, as they were created during the first session on the basis of participant’s first pleasantness ratings.very unpleasant  to very pleasant ; the subjective familiarity from not familiar at all (left) to very familiar (right); and the subjective intensity from not perceived (left) to very strong (right).After each odorant presentation (except during the choice phases), participants were asked to rate the pleasantness, familiarity, and intensity on continuous scales presented on a computer screen. Participants had to move a vertical marker with the mouse across a horizontal line and click to indicate their rating. Participants judged the pleasantness of the odor from The difference between prechoice and postchoice ratings was calculated for each of the eight target odors. For each participant, we assessed odor recognition memory performance by using parameters based on signal detection theory F = 21.94, p<.001, η2 = .35], revealing the classical effect of pleasantness rating modulation after choice. Pleasantness ratings were significantly decreased for rejected odors , and pleasantness ratings were significantly increased for chosen odors . An identical analysis performed on the pleasantness scores in the easy-choice condition revealed only a significant main effect of choice , which reflected significantly higher pleasantness ratings for chosen odors than for rejected ones.Choice-induced changes are typically reported when the choice is difficult, that is, in this case, when the difference between the pleasantness ratings of the two paired odors obtained before the choices is small. We performed a repeated measures ANOVA with the factors period  and choice  on the pleasantness scores in the difficult-choice condition. The interaction between these factors was significant . This result critically indicates that pleasantness rating modulation was still present 1 week after the choice  = 7.94, p = .007, η2 = .17] and pleasantness ratings increased significantly for chosen odors .We performed a repeated measures ANOVA with the factors period  and choice  on the pleasantness scores in the difficult-choice condition. Results were similar to those obtained just after the choice: the interaction between these factors was significant . Taken together, these results indicate that pleasantness rating changes were not statistically different immediately after and 1 week after the choice, which argues for stability over time.The repeated measures ANOVA with the factors period  and choice  performed on the difference between prechoice and postchoice ratings revealed no significant interaction between these factors .We checked whether the pleasantness of the odor before the choice varied as a function of the participant’s choice. A repeated measures ANOVA with the factor choice  performed on pleasantness scores before the choice was marginally significant , independently of whether participants remembered which smell they chose 1 week earlier (80%) or not (79%) .The likelihood of making the same choice (either chosen or rejected) again in the second session was far above chance  nor between the intensity ratings . It is then very unlikely that choices could have been based on a priori differences in the familiarity or intensity ratings of the paired odors. There was a statistical difference in familiarity ratings between chosen and rejected odors immediately after the first choice . There was neither a difference in intensity ratings immediately after the choice  nor 1 week later , showing again the well-documented effect of pleasantness rating change following difficult choices. Pleasantness ratings were significantly increased for chosen odors ; the decrease in pleasantness ratings for rejected odors was not significant . An identical analysis performed on the pleasantness scores in the easy-choice condition revealed only a significant main effect of choice . This result indicates that pleasantness rating modulation was still present 1 week after the choice. Pleasantness ratings were significantly increased for chosen odors ; the decrease in pleasantness ratings for rejected odors did not reach significance .The same analyses were performed 1 week after choice. The repeated measures ANOVA with the factors period  and choice  performed on the pleasantness scores was significant . Taken together, these results indicate that pleasantness ratings changes were not statistically different immediately after and 1 week after the choice, which suggests stability over time.The repeated measures ANOVA with the factors period  and choice  performed on the difference between prechoice and postchoice ratings revealed no significant interaction between these factors , which reflected significantly higher pleasantness ratings for chosen odors than for rejected ones.In the easy-choice condition, the repeated measures ANOVA with the factor period  and choice  on the pleasantness scores only revealed a main effect of choice , showing that the difference between the pleasantness evaluation increase of the chosen odors and the pleasantness evaluation decrease of the rejected odors was significant for forgotten and remembered choices combined. Two repeated measures ANOVAs conducted on the difference scores for the forgotten and remembered difficult choices separately confirmed significant postchoice pleasantness rating change for remembered choices, but critically, also for forgotten choices   and memory  was performed on the difference score in the difficult-choice condition (after choice - before choice). This analysis revealed a main effect only of choice, [ely] see .F = 7.54, p = .012, η2 = .27]. Two repeated measures ANOVAs conducted on the difference scores for the forgotten and remembered difficult choices separately confirmed significant postchoice pleasantness rating change for remembered choices, but critically, also for forgotten choices   and memory  on the difference scores in the difficult-choice condition (1 week after choice – before choice). This analysis revealed a main effect of choice [ely] see .t test for single mean: t(35) = 6.29, p<.001; remembered condition: t test for single mean: t(35) = 7.04, p<.001], independently of whether participants remembered which smell they chose 1 week earlier (82%) or not (79%) .The likelihood of making the same choice again in the second session was far above chance  – odors evaluated as the most pleasant before choice tend to be chosen during the choice phase.We checked whether the pleasantness of the odor before the choice varied as a function of the participant’s choice. The repeated measures ANOVA with the factor choice  performed on pleasantness scores before the choice was marginally significant , nor between the intensity ratings . Familiarity ratings between chosen and rejected odors were not significantly different either just after the first choice  or 1 week after the first choice . Intensity ratings between chosen and rejected odors were marginally significantly different just after the first choice  and significantly different 1 week after the first choice , rejected odors being rated on average as more intense than chosen odors.There was a difference neither between the familiarity ratings of the chosen and the rejected odors prior to difficult choices . Unpleasant odors on which participants chose to spend 5 CHF were evaluated as significantly more pleasant than odors for which participants did not spend money on  performed on the difference between pleasantness prechoice and postchoice ratings was significant . Unpleasant odors on which participants chose to spend 5 CHF were evaluated as significantly more pleasant one week later than odors for which participants did not spend money on.A repeated measures ANOVA with the factor choice  performed on the difference between prechoice and postchoice ratings was significant . Taken together, these results indicate that pleasantness ratings changes were not statistically different immediately after and 1 week after the choice, which suggests stability over time.The repeated measures ANOVA with the factors period  and choice  performed on the difference between prechoice and postchoice ratings revealed no significant interaction between these factors  nor 1 week after the first choice . Likewise, intensity ratings between odors for which participants spent 0 vs. 5 CHF were neither significantly different just after the first choice , nor 1 week after the first choice [F and rejected odors were evaluated less positively (Experiment 1) compared with a first pleasantness evaluation.before smelling them. In this context, choice cannot be a reflection of pre-existing preferences. The issue raised by Chen and Risen removing the information from choice” (the third strategy proposed by Risen & Chen before the actual presentation of the stimuli on which a choice is made, proves to be potentially promising for future work.In Experiment 3, a design derived from the effort-justification paradigm In Experiments 1 and 2, choice coherence–the likelihood of making a second choice similar to the first one–was high, even after 1 week. Such a result has a limited impact because we cannot exclude that this high choice coherence is based on a preexisting difference in pleasantness between chosen and rejected odors before the second choice. In other words, following the first choice phase, chosen odors were on average rated as much more pleasant than the rejected ones. It could have made the second choice an “easy” one, mainly driven by this pleasantness difference between the paired odors.A growing body of research has explored the implicit mechanisms underlying preference modulation by choice e.g.,  and whenAldrovandi and Heussen long-term effect on preferences, and that this is true even if the triggering decisions are forgotten. The asymmetry between the fleetingness of the cause and the long-lastingness of its effect is particularly striking because it can operate independently from conscious recollection.Our results have implications for a link between flexibility and stability of preferences: The current findings reveal how arbitrary-seeming momentary decisions can have a surprisingly


Driven by the need to detect the presence of HCV, as an essential factor in diagnostic medicine, the monitoring of viral protein has been of great interest in developing simple and reliable HCV detection methods. Despite considerable advances in viral protein detection as an HCV disease marker, the current enzyme linked immunosorbent assay (ELISA) based detection methods using antibody treatment have several drawbacks. To overcome this bottleneck, an RNA aptamer become to be emerged as an antibody substitute in the application of biosensor for detection of viral protein. In this study, we demonstrated a streptavidin-biotin conjugation method, namely, the RNA aptamer sensor system that can quantify viral protein with detection level of 700 pg mL−1 using a biotinylated RNA oligonucleotide on an Octet optical biosensor. Also, we showed this method can be used to screen inhibitors of viral protein rapidly and simply on a biotinylated RNA oligonucleotide biosensor. Among the inhibitors screened, (−)-Epigallocatechin gallate showed high binding inhibition effect on HCV NS5B viral protein. The proposed method can be considered a real-time monitoring method for inhibitor screening of HCV viral protein and is expected to be applicable to other types of diseases.Globally, over 170 million people ( Globally, approximately 3% of the world’s population or more than 170 million people are infected. HCV infection causes serious liver diseases such as chronic hepatitis, which can evolve into subsequent more serious health problems . HCV RNAThere is a need for a feasible method to detects the presence of an HCV infection, such as a direct RNA-based HCV viral protein detection method. Driven by the need to detect the presence of the HCV diseases, in this study, we demonstrate for the first time that biotinylated RNA oligonucleotide with a functional signal sequence can be used for screening and quantifying HCV RNA with selectivity and specificity. We also show that biotin-tagged RNA oligonucleotide can be used as a probe for the detection HCV viral protein NS5B and inhibitor screening on forteBio’s Octet optical biosensor system. The goal of this study is to investigate direct HCV viral protein detection and rapid inhibitor screening with a specific biotinylated RNA oligonucleotide using a streptavidin-biotin conjugation method on forteBio’s Octet optical biosensor system.2.2.1.(−)-Epigallocatechin gallate and cyclosporin A were purchased from Sigma-Aldrich Chemical Co. . The biotinylated group with terminal modification of NS5B RNA oligonucleotide was synthesized by BIONEER Co. Ltd. . The biotinylated sequences of NS5B RNA oligonucleotide (NS5B: 5′-ggccacauugugaggggcuc-3′-biotin) were used as a specific probe. All other chemicals were of the highest grade.2.2.+ , and transformed into E. coli DH5 α . The transformant was grown in a 250 mL flask containing a 50 mL Luria-Bertani (LB) medium supplemented with 50 μg mL−1 of kanamycin at 37 °C until the cell concentration reached an OD600nm of 0.6, and isopropylthio-β-d-galactopyranoside (IPTG) to a final concentration of 0.1 mmol L−1, followed by additional growth overnight at 25 °C while shaking at 180 rpm. The harvested cells were lysed using a Sonicator . The supernatant was collected and the recombinant viral protein was purified using a Ni-nitrilotriacetic acid (Ni-NTA) affinity chromatography column . The supernatant was equilibrated with buffer A . The bound protein was then eluted with buffer B  at 4 °C. The purity of the purified protein was estimated using SDS-PAGE in the eluted fractions, using 10% polyacrylamide running gels [2+ affinity column. The protein concentration was determined as described by Bradford with a bovine serum albumin (BSA) as standard [The HCV NS5B gene, except for the hydrophobic C terminus 21 amino acids, was amplified using polymerase chain reaction (PCR) with a primer set, sense (5′-cgcgaattcatgtcctacacatggacagg-3′) and antisense (5′-tttctcgagtcggttggggagcaggta-3′), containing restriction enzyme sites of EcoRI/XhoI. The PCR product was digested using EcoRI/XhoI, and then ligated into EcoRI/XhoI digested expression vector pET 28aing gels . The HCV2.3.−1 biotinylated RNA oligonucleotide (15 min). The typical capture levels were 2.65 ± 0.32 nm with the standard deviation being within the instrument noise. A 10 min washing step was added. To study the interactions with biotinylated RNA oligonucleotide on the tip, a viral protein was also prepared as a five-member tenfold serial dilution with a highest concentration of 7 × 100 μg mL−1 by 7 × 10−4 μg mL−1. Then, a viral protein of 7 × 100 μg mL−1 to 7 × 10−4 μg mL−1 was bound to the biotinylated RNA oligonucleotide for 10 min and allowed to dissociate into a buffer  for 10 min. Blank binding cycles containing no RNA oligonucleotide were used to correct for the baseline drift. Temperature control of the Octet was accomplished by keeping the instrument in a 22 °C temperature-controlled room so that it could be heated to 25 °C. Sensor tips were pre-wetted for 2 min in a buffer immediately prior to use, and the 96 well microplate used in the Octet was filled with 200 μL of the sample or buffer per well and agitated at 1,000 rpm. For the inhibition activity, the RNA oligonucleotide and inhibitor were facilitated through by adding on an Octet platform. The value of the signal intensity was obtained by calculating and expressing it as the mean intensity.For the study, Octet QK, equipped with streptavidin (FA) biosensor tips, was purchased from forteBio . Streptavidin-coated FA tips were saturated with 0.1 μg mL3.3.1.Specific detection of a viral protein was demonstrated using a biotinylated RNA oligonucleotide via the streptavidin-biotin conjugation method, which makes a simple analysis of RNA-protein interactions possible. The design of a sensor for effective detection of HCV viral protein using the streptavidin-biotin conjugation method is illustrated in 3.2.Detection technology of BioLayer Interferometry (BLI) invented by Lotze  is a labIn −1 biotinylated NS5B RNA oligonucleotide for 900 s. The washing step allowed the removal of unspecific binding of biotinylated RNA oligonucleotide. The viral protein NS5B was prepared with a serial dilution of 7 × 100 μg mL−1 to 7 × 10−4 μg mL−1 to study the interactions with biotinylated RNA oligonucleotide on the streptavidin sensor tip. The samples were allowed to associate for 900 s. Dissociation was measured for 600 s.We demonstrated the specific interaction between biotinylated RNA oligonucleotide and HCV viral protein on forteBio’s Octet platform, which uses biolayer interferometry to detect and quantify molecular interactions using disposable streptavidin biosensor that addresses biotinylated RNA oligonucleotide and viral protein interactions from open shaking 96 well microplates without a labeling procedure. An assay for the biotinylated RNA oligonucleotide conjugation was created on a streptavidin sensor. Streptavidin-coated FA tips were saturated with 0.1 μg mL3.3.E. coli expression system was expressed and purified using Ni-NTA affinity chromatography. In the purification step, the protein was eluted in a 1 mL fraction with a 250 mmol L−1 imidazole buffer. To verify the purity and homogeneity of the eluted NS5B, aliquots of eluted fractions were analyzed using Coomassie blue staining on SDS-PAGE. Eluates with the highest purity of 95% were pooled, dialyzed and stored with 50% glycerol in aliquots at −80 °C. The HCV NS5B viral protein was purified using a single chromatography step on a Ni2+ affinity column. The C-terminally his-tagged HCV NS5B was purified with a molecular mass of approximately 66 kDa.In 3.4.−1. The signal intensity was found to increase gradually by up to 7 μg mL−1 of protein concentration. −1 level. These results suggest the NS5B RNA oligonucleotide can specifically target the HCV NS5B viral protein on an Octet platform. The reason of this result will be postulated RNA oligonucleotide (5′-ggccacauugugaggggcuc-3′) used as a specific probe may interact to the active site of HCV NS5B viral protein. These results show that biotinylated RNA oligonucleotide can be effective for the quantification of HCV NS5B viral protein. In −1 [−1 for the evaluation of HCV viral protein NS5B [−1. This result suggests that the biotinylated RNA oligonucleotide could specifically target the HCV NS5B protein in an Octet biosensor system.As illustrated in n. In −1 . As anotein NS5B . The OctIn 3.5.In 4.In summary, we demonstrated a RNA aptamer system that can effectively detect and monitor HCV viral protein using biotin-based RNA oligonucleotide on an Octet platform. The monitoring of HCV viral protein has been of considerable interest in developing simple and reliable methods for HCV detection in diagnostic medicine applications. Our main goal in this study is to demonstrate the proof-of-concept that viral protein can be detected and monitored with remarkable selectivity and specificity. For application, this designed platform for a novel inhibitor assay possesses significant potential as a target screening. As these results show, RNA-protein interactions may be of great utility in the identification of novel RNA binding proteins and in understanding how proteins recognize particular RNA sequences. An RNA oligonucleotide biosensor based on the streptavidin-biotin conjugation method has attracted significant attention and has become a promising method for the specific detection of oligonucleotide because of its high sensitivity, low cost, rapid response, and low labor-intensive requirements. The proposed method can be considered an efficient strategy and new promising platform for monitoring applications.


We consider all combinatorial possibilities using all possible tree inputs, both those that are RNA-like in structure and those that are not. The resulting data from each tree merge operation is represented by a vector. We use these vectors as input values for a neural network and train the network to recognize a tree as RNA-like or not, based on the merge data vector. The network estimates the probability of a tree being RNA-like.Determining the secondary structure of RNA from the primary structure is a challenging computational problem. A number of algorithms have been developed to predict the secondary structure from the primary structure. It is agreed that there is still room for improvement in each of these approaches. In this work we build a predictive model for secondary RNA structure using a graph-theoretic tree representation of secondary RNA structure. We model the bonding of two RNA secondary structures to form a larger secondary structure with a graph operation we callThe network correctly assigned a high probability of RNA-likeness to trees previously identified as RNA-like and a low probability of RNA-likeness to those classified as not RNA-like. We then used the neural network to predict the RNA-likeness of the unclassified trees.There are a number of secondary RNA structure prediction algorithms available online. These programs are based on finding the secondary structure with the lowest total free energy. In this work, we create a predictive tool for secondary RNA structures using graph-theoretic values as input for a neural network. The use of a graph operation to theoretically describe the bonding of secondary RNA is novel and is an entirely different approach to the prediction of secondary RNA structures. Our method correctly predicted trees to be RNA-like or not RNA-like for all known cases. In addition, our results convey a measure of likelihood that a tree is RNA-like or not RNA-like. Given that the majority of secondary RNA folding algorithms return more than one possible outcome, our method provides a means of determining the best or most likely structures among all of the possible outcomes. Our understanding of the role of RNA has changed and continues to be redefined. It was once believed that the sole purpose of RNA is to carry the information needed to construct a specific protein. This information is obtained from the protein’s gene and carried from the nucleus of the cell to the machinery outside the nucleus in the cell where the protein is then constructed. That is, RNA carried the protein’s code. It is now known that RNA is a major player in many gene regulatory networks and that there are numerous RNA structures whose function does not involve coding for a protein. Thus, we now refer to RNA as either coding or non-coding. Novel non-coding RNA structures are still being found and the number of non-coding RNA structures now exceeds the number of coding RNA . The rolA number of algorithms have been developed to predict the secondary structure from the primary structure. Most of these algorithms use the thermodynamic parameters based on the principle that the most likely secondary structure is one having the minimal free energy. But some suggest the actual RNA secondary structure may have local instead of a global minimum free energy  and thusRNAalifold  integratRNA structure is divided into three classes: primary, secondary and tertiary. The RNA sequence is the primary structure. The primary structure forms the secondary by folding back onto itself. When this folding occurs, it forms Watson-Crick base pairs with intervening unpaired regions. These regions occur in four types of structures known as hairpins, bulges, internal loops and junctions. Paired regions connecting these are usually referred to as stems. Secondary RNA structure can be represented by a two-dimensional drawing. Tertiary RNA, or the three dimensional RNA molecule, can be best described as being built from combinations of secondary structure. Thus, the study of the secondary structure of RNA has received and will continue to receive much attention.Since secondary RNA is represented by a two-dimensional schematic, graph theory nicely lends itself as a modeling tool for secondary RNA structure. The basic skeletal structure of secondary RNA is captured by representing the stems as edges of the graph and the regions with unpaired bases as vertices. The resulting graph is a graph known as tree graph, or simply a tree. The RNA trees used in this work were first developed by Le et al. in  and Moron). For example, for the set n = {2, 3, 4, 5, 6, 7, 8, 9}, there are a total of {1, 1, 2, 3, 6, 11, 23, 47} distinct trees, respectively , where for i  ∊ {1, 2},[〈deg(iv) is the degree of the identified vertex of iT, andy1 = 1 and y2 = 0 if the result tree is an RNA-like tree, and y1 = 0 and y2 = 1 if the result tree is not RNA-like.In their numerical form as data vectors, the vertex identification results are used to predict the RNA-like status of the 43 unclassified trees on 9 vertices. The data vectors from the 15 known (red) tree graphs on 7, 8 and 9 vertices along with the data vectors of the 11 non-candidate (black) tree graphs on 7 and 8 vertices make up the training data. To check the validity of our model, we then predicted the status of the 26 known tree classifications on 7, 8 and 9 vertices. Then, the model is used as a predictive tool for the 43 unclassified trees of order nine. This research parallels previous work by the authors in [ input later, contains four perceptrons corresponding to the data vector from one vertex identification of the complete merge between two trees. The last layer, or output layer, consists of two perceptrons with activations y1 and y2, where y1 = 1 and y2 = 0 if the result tree, which corresponds to the input data vector, is predicted to be an RNA tree and where y1 = 0 and y2 = 1 if the result tree is not RNA-like. The middle layer, or hidden layer, is comprised of 24 perceptrons. The weights between the input and hidden layers will be denoted by jkw  and the weights between the hidden and output layers will be denoted by ijα.Following the network created in , our appThe data vectors from the vertex identifications of the 26 trees on 7, 8 or 9 vertices that either are an RNA tree or not an RNA-like tree determine the training setiq = 〈1, 0〉 if the tree is known or predicted to be an RNA tree, and iq = 〈0, 1〉 of the tree is not RNA-like. The back-propagation algorithm is used to implement a gradient following minimization of the total squared errorWhere y(ip) = 〈y1(ip), y2(ip)〉 is the output due to an input of ip and the norm is generated by the corresponding dot product.where ip, iq) the weights jkα are adjusting usingThe weights are initially assigned random values close to 0. Then, for each pair . Once the network is trained, it is used to predict the classification of the data in the complement set. This is known as leave-v-out cross-validation. According to [The network was trained using the datarding to , cross-vIn order to most accurately utilize our data, each tree’s final classification was calculated as an average of a linear combination of prediction values from the vertex identifications. To do so, we began this procedure by using the MLP to predict the value for each vertex identification for a given tree. Then, this value was multiplied by a weight which refers to the total number of graph isomorphisms for the vertex identification. This weight was noted for each identification and can be referenced in the “Total Graphs” column of Additional file Once the MLP was fully trained, the network was used to predict the classification of the 26 red or black RAG trees on 7, 8 and 9 vertices. For these trees, the final MLP prediction values range from 1.0 to 0.0. As a result, the key in Table Using a tree representation of secondary RNA structure, we model the creation of a larger structure from the bonding of two smaller structures by considering all combinatorial possibilities. We model the bonding with a graph operation called (vertex) merge. Data from this process included information on the degrees of the vertices identified in the merge and the classification of substructures. We created data vectors and then utilized these data vectors from known RNA trees on 7, 8 and 9 vertices together with the data vectors from the non-candidate RNA trees on 7 and 8 vertices to create and train a neural network to recognize a tree as RNA-like or not-RNA-like in structure. We applied this predictive tool to categorize known RNA classifications and to predict unknown RNA trees.The results for the 15 red trees of orders seven, eight, and nine agree with the classifications from the RAG database and previous research in [We revealed that graphical operations from the field of mathematical graph theory can successfully model secondary RNA motifs. Further, we demonstrated that these numerical values from these operations can enable the training of an artificial neural network to recognize the difference between likely and unlikely RNA structures. These findings, along with those from previous predictive models, exhibit the power of mathematical graph theory as an effective modeling method. By representing bimolecular structures with graph theory, modern researchers enter an extensive and unexplored field of quantitative biology. Although trees have previously been used to model secondary RNA structure, the applications of techniques from graph theory have been limited. There are numerous binary operations on graphs, such as the Cartesian product and graph join. In this paper, we have introduced graph merge as a novel approach to the study of RNA binding.As a follow up to this study, future research could combine the data from ,15 and tThe authors declare that they have no competing interests.DRK produced the tree merge data, trained the neural network, and contributed to writing the paper. DJK conceived of the study, participated in its coordination and execution, and was involved in drafting the manuscript and revising it critically for important intellectual content. JK designed and helped train the neural network. TH participated in the coordination of the study, helped with the graph theory, and was involved in drafting the manuscript. All authors read and approved the final manuscript.Click here for file


Reoviridae family, is the primary etiological agent of severe diarrhea in young children worldwide. Previous studies demonstrated that rotavirus replication induces a MAVS-dependent type I IFN response that involves both RIG-I and MDA5, two cytoplasmic viral RNA sensors. This study reports the isolation and characterization of rotavirus RNAs that activate IFN signaling. Using an in vitro approach with purified rotavirus double-layer particles, nascent single-stranded RNA (ssRNA) transcripts (termed in vitro ssRNA) were found to be potent IFN inducers. In addition, large RNAs isolated from rotavirus-infected cells six hours post-infection (termed in vivo 6 hr large RNAs), also activated IFN signaling, whereas a comparable large RNA fraction isolated from cells infected for only one hour lacked this stimulatory activity. Experiments using knockout murine embryonic fibroblasts showed that RIG-I is required for and MDA5 partly contributes to innate immune signaling by both in vitro ssRNA and in vivo 6 hr large RNAs. Enzymatic studies demonstrated that in vitro ssRNA and in vivo 6 hr large RNA samples contain uncapped RNAs with exposed 5’ phosphate groups. RNAs lacking 2’-O-methylated 5’ cap structures were also detected in the in vivo 6 hr large RNA sample. Taken together, our data provide strong evidence that the rotavirus VP3 enzyme, which encodes both guanylyltransferase and methyltransferase activities, is not completely efficient at either 5’ capping or 2’-O-methylation of the 5’ cap structures of viral transcripts, and in this way produces RNA patterns that activate innate immune signaling through the RIG-I-like receptors. In mammalian cells, the first line of defense against viral pathogens is the innate immune response, which is characterized by induction of type I interferons (IFN) and other pro-inflammatory cytokines that establish an antiviral milieu both in infected cells and in neighboring uninfected cells. Rotavirus, a double-stranded RNA virus of the  Rotavirus (RV) is the primary etiological agent of severe dehydrating diarrhea in young children worldwide, and is responsible for almost half a million deaths annually ,2. In 20Reoviridae family of non-enveloped, segmented double-stranded RNA (dsRNA) viruses. The virus exhibits host-range restricted replication, such that viruses from one species (homologous host) are only infrequently isolated from another species (heterologous host) [RV is a member of the us host) ,5. The Rus host) .Upon infection of mammalian cells with bacterial or viral pathogens, an early line of defense, termed the innate immune response, is triggered. The innate immune response is initiated by host proteins called pattern recognition receptors (PRRs) that sense pathogen-associated molecular patterns (PAMPs) presented during the microbial infection. The innate immune response is characterized by the production of type I interferons (IFN-α/β) and many other pro-inflammatory cytokines . Bindingin vitro indicate that RV infection induces an early IFN response, but in most cases the virus rapidly suppresses IFN signaling through the actions of viral proteins such as NSP1 [The adaptive immune response to RV infection has been well characterized, and studies have demonstrated that CD8+ T cells play a critical role in the timely clearance of a primary infection while B cells are crucial for resistance to re-infection ,36. Much as NSP1 ,41,42,43 as NSP1 . Recentl as NSP1 . IFN ind as NSP1 . These r as NSP1 . A previ as NSP1 . Whetherin vitro and in vivo approaches to isolate and characterize RNAs generated during RV transcription. We demonstrate that RV ssRNA transcripts are a key activator of innate immune signaling. RIG-I is required for and MDA5 contributes to IFN production in response to RV transcripts. Enzymatic characterization studies indicate that RV transcription produces uncapped RNAs with exposed 5’ phosphate groups and RNAs with incompletely 2’-O-methylated 5’ cap structures. These two RNA signatures provide a molecular basis for how RV induces RLR-dependent innate immune signaling.In this study, we used a combination of in vitro-transcription (IVT) reactions carried out using highly purified RV double-layer particles (DLPs), and the second approach was to purify RNAs from RV-infected cells.In rotavirus (RV) infected cells, plus- and minus-strand RV RNAs are first detectable around 3 hours post-infection (hpi), and the level of transcription increases significantly until 9 to 12 hpi, when the concentration of plus-strand transcripts and dsRNA reaches a maximum . PrimaryS-adenosylmethionine, and magnesium ions [32P-GTP, and all four NTPs (complete conditions) or in the absence of ATP (incomplete conditions). As a negative control, we included a reaction lacking DLPs. After a 5-hour incubation at 42°C, reactions were treated with antarctic phosphatase to digest unincorporated NTPs into inorganic phosphate (Pi). RNA products from each reaction were analyzed on a denaturing 20% urea-acrylamide gel. As shown in DLPs contain the complete dsRNA genome, have a functional RNA-dependent RNA polymerase (RdRP), and can efficiently generate capped and methylated transcripts when supplemented with nucleotides (NTPs), ium ions . The fir32P-GTP. Total RNA was then purified from the reactions and applied to a denaturing urea-acrylamide gel, and UV shadowing was used to visualize the RNA. In the complete IVT reaction lane, a region of large molecular weight (MW) RNAs was visible beginning at the bottom of the well and extending to approximately 1 centimeter below the well. We did not visualize a region of large MW RNAs in the incomplete IVT reaction lane. The large MW RNAs seen in the complete IVT reaction are presumed to include both nascent transcripts as well as input genomic dsRNA released from the DLPs during the RNA extraction process. However, because the amount of nascent transcripts in the complete IVT sample greatly exceeds that of input genomic dsRNA, we believe that the large MW smear detected by UV shadowing was mostly, if not entirely, due to the nascent transcripts and not the input genomic dsRNA. The incomplete IVT reaction contained an equivalent amount of input genomic dsRNA, but because the actual amount of this dsRNA was low and UV shadowing has limited sensitivity, a large MW RNA smear was not visible in the incomplete IVT reaction lane. A small MW smear at the very bottom of the gel just below the bromophenol blue dye front (expected size of 8 nucleotides) was detected in both IVTs, and this smear likely contained both short oligos and unincorporated NTPs. No RNAs were detected in the middle of the gel in either lane, similar to the findings in To determine if any of the IVT RNA products had immunostimulatory potential, complete and incomplete IVT reactions were carried out under similar conditions but in the absence of α-To measure the immunostimulatory potentials of these gel-purified RNAs, we transfected the entire recovered large and small MW RNA eluates into Huh7 human hepatoma cells and measured stimulation of an IFN-beta firefly luciferase reporter. The large MW RNA fraction (containing both nascent transcripts as well as input genomic dsRNA) purified from the complete IVT reaction was a potent IFN activator whereas the small MW RNA fraction (containing unincorporated NTPs and short oligos) purified from the complete IVT reaction lacked IFN stimulatory potential . Equivalent amounts of the 1 hr large RNA fraction (containing input RV genomic dsRNA but little if any newly synthesized RV ssRNA transcripts or newly synthesized genomic dsRNA) and 6 hr large RNA fraction  were transfected into wild type murine embryonic fibroblasts (MEFs). Cell culture media was collected 21 hours post-transfection and the amount of secreted IFN-beta quantified using ELISA. As shown in in vivo requires RV transcription and/or replication.The data from the IVT reactions  in downstream innate immune signaling from the in vitro ssRNA and in vivo large RNA samples, matched RIG-I wild type (WT) and knock-out (KO), MDA5 WT and KO, and MAVS WT and KO MEFs were mock-transfected or transfected with equal amounts of in vitro ssRNA, in vivo 6 hr large RNAs, in vivo 1 hr large RNAs, or polyI:C. Cell culture media was collected 21 hours post-transfection and the amount of secreted IFN-beta quantified using ELISA. In all three sets of WT MEFs, the in vitro ssRNA and in vivo 6 hr large RNA samples were potent inducers of IFN-beta production, whereas the in vivo 1 hr large RNA sample was minimally stimulatory  found within the in vivo 6 hr large RNA sample with any of the three enzymes significantly diminished its IFN stimulatory potential  fractions from cells infected with RV for 1 or 6 hours and determined that the 6 but not the 1 hour RNA sample also induced IFN signaling. Taken together, these results strongly suggest that RV RNA transcripts generated both in vitro with purified RV DLPs and in vivo in RV-infected cells contain immunostimulatory PAMPs. We further found that RIG-I is required for and MDA5 contributes to downstream innate immune signaling from these RNA samples. The RLR mitochondrial adaptor protein MAVS was also shown to be necessary for this response. Our findings confirm a recent postulation by Holloway and Coulson that RV plus-sense RNA transcripts could be possible RIG-I and/or MDA5 ligands because they are localized to the cytoplasm during RV infection and could potentially contain motifs known to trigger RIG-I/MDA5 signaling [In this report we provide new insight into how RV infection activates innate immune signaling. Although it has long been known that RV induces IFN signaling, and also efficiently blocks this pathway, the molecular basis for how RV triggers an innate response has remained unclear. Using an ignaling .in vitro ssRNA and in vivo 6 hr large RNA samples indicate that some RV transcripts appear to be uncapped and contain exposed 5’ phosphate groups while other transcripts are capped but incompletely 2’-O-methylated. These data suggest that the VP3 component of the viral transcription machinery is not completely efficient at either adding a 5’ cap structure to nascent transcripts or adding a 2’-O-methyl group to capped transcripts, a proposition put forward in the literature [The results of enzymatic characterization assays carried out with the purified terature ,58. As aReoviridae viruses that has been shown to have immunostimulatory potential was genomic dsRNA [in vivo 6 hr large RNA sample and could have been a source of IFN stimulation in our experiments. However, it is important to note that during RV infection, the dsRNA genome is generated during assembly of subviral particles. This process takes place in protein-rich viroplasm structures, which have been shown to protect viral RNAs from RNAi degradation [Until now, the only nucleic acid associated with ic dsRNA . It is pradation . As suchin vitro ssRNA and in vivo 6 hr large RNA samples. However, in our experiments, we observed that RIG-I is indispensable for the IFN response to these RNA samples . In addition to enhancing mRNA stability and translational efficiency, the 5’ cap structure is one way that host cells discriminate self from non-self RNA. The ability of viruses to activate RIG-I signaling through the production of uncapped RNAs with exposed 5’ phosphate groups is well-described in the literature [In eukaryotes, newly transcribed RNAs initially contain a 5’ triphosphorylated end, but during subsequent processing of most cellular transcripts the exposed 5’ triphosphate ends are converted to a monophosphate or a guanine cap. The type I cap structure of many higher eukaryotic mRNAs is modified with a methyl group at the N7 position of the guanosine capping residue and the ribose-2’-O position of the 5’-penultimate residue  ,40,42,43in vivo studies in a mouse model of RV infection showed that age-dependent TLR3 expression within the intestinal epithelium may be implicated in susceptibility to RV infection [Our studies do not exclude the possibility that RV transcripts may contain other PAMPs that also activate IFN signaling through the RLRs. We carried out experiments with RNases that target base-paired regions of RNAs and our preliminary results indicate that RV transcripts contain structured regions (data not shown). This preliminary observation is supported by computer modeling and RNase mapping studies which suggest that RV plus-strand RNAs form panhandle structures through base-pairing between the 5’ and 3’ ends ,68,69. Snfection . Future Renilla luciferase) plasmid was obtained from Promega.MA104 African green monkey kidney cells were purchased from the American Type Culture Collection (ATCC) and were maintained in M199 media supplemented with 7.5% fetal calf serum (Invitrogen) and L-glutamine, penicillin, and streptomycin (complete M199). Huh7 and Huh7.5 human hepatoma cells ,72 were Viral particles were first concentrated from RRV-infected MA104 cell lysates by genetron extraction and pelleting over a sucrose cushion. DLPs were then generated by treating the particles with 10 mM EDTA to remove the outer VP4/VP7 layer, followed by cesium chloride density gradient centrifugation as described ,78. DLPsin vitro-transcription (IVT) reactions were carried out using 2.4 μg of purified DLPs, 5 mM ATP, 2.5 mM GTP, 2.5 mM CTP, 2.5 mM UTP, 0.5 mM S-adenosylmethionine (SAM), 0.5 U/µl RNasin, and 1 mM DTT in 1X TNM buffer . Incomplete IVT reactions lacked ATP. Reactions were incubated for 5-6 hours in a 42°C water bath. Total RNA (genomic dsRNA and nascent transcripts) was purified by extraction with an equal volume of phenol: chloroform: isoamyl alcohol  and precipitation with 0.3 M sodium acetate and ethanol. Total RNA was then sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. RNA concentration was determined by absorbance on a NanoDrop spectrophotometer (Thermo Scientific), and RNA samples were stored in aliquots at -80°C.Complete 32P-GTP, 0.5 mM S-adenosylmethionine (SAM), 0.5 U/µl RNasin, and 1 mM DTT in 1X TNM buffer. An incomplete reaction lacking ATP and a reaction lacking DLPs were also carried out under identical conditions except for the indicated lacking constituent. Reactions were incubated for 5 hours in a 42°C water bath. Unincorporated radiolabel was removed by treating the IVT reactions with antarctic phosphatase (New England Biolabs) for 1.5 hours in a 37°C water bath. IVT samples were denatured in urea loading dye for 5 minutes at 95°C, cooled on ice for 5 minutes, and analyzed on a 20% urea-acrylamide gel  in 1X TBE buffer run at 500-700 V for approximately 4 hours until the bromophenol blue dye front migrated 15.5 cm. The gel was dried on Whatman paper overnight at 80°C, exposed to a phosphorimager screen overnight, and the screen was scanned using a Storm phosphorimager (Molecular Dynamics).A complete IVT reaction was carried out using 0.6 μg of purified DLPs, 5 mM ATP, 2.5 mM GTP, 2.5 mM CTP, 2.5 mM UTP, 1 mM αTo isolate large and small molecular weight RNAs, IVTs were denatured with formamide for 5 min at 90°C and run on a denaturing 12% urea-acrylamide gel  in 1X tris borate EDTA (TBE) buffer  at constant 12 mA current for 4-6 hours until the bromophenol blue dye front was approximately 1 inch from the bottom of the gels. UV shadowing was used to visualize large and small molecular weight RNA bands, which were then excised from the gel and eluted in 0.5 M ammonium acetate, 10 mM magnesium acetate, 1 mM EDTA, and 0.1% SDS at 4°C overnight with nutation. RNA was separated from the gel material by centrifugation at full speed for 10 minutes, followed by extraction with an equal volume of P:C: IAA and precipitation with ethanol. RNA was then sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. RNA concentration was determined by absorbance on a NanoDrop spectrophotometer, and RNA samples were stored in aliquots at -80°C.Renilla luciferase, Promega) using Lipofectamine 2000 (Invitrogen). After 24 hours, cells were mock-transfected, transfected with the entire recovered RNA sample, or transfected with 500 ng per well of polyI:C (Sigma) in duplicate using Lipofectamine 2000 (Invitrogen). Approximately 21 hours after RNA transfection, cells were lysed in 100 µl of passive lysis buffer (Promega), and an aliquot was analyzed using the dual-luciferase reporter assay system (Promega).40,000 Huh7 human hepatoma cells were plated per well of a 24-well plate. After 24 hours, cells were transfected with 100 ng of pIFN-beta-luc (firefly luciferase) and 4 ng of pRL-TK (Isolation of the ssRNA fraction from the IVTs was carried out as described previously for bluetongue virus . BrieflyMA104 cells were seeded in 8-well chamber slides (Nunc) at 1.5 x 104 cells/well. After a 3-day incubation, cells were washed twice with M199 media supplemented with penicillin-streptomycin (incomplete M199) and either mock-infected, infected with RRV at an estimated MOI of 10, or transfected with 1 μg/well polyI:C (Sigma). After a one-hour incubation at 37°C, all the wells were aspirated, cells were washed once with incomplete M199, and incomplete M199 was added back to each well. After another 5 hours of incubation at 37°C, all wells were aspirated, cells were washed once with PBS, fixed for 10 minutes in 3% paraformaldehyde, washed once with PBS, and stored in PBS overnight at 4°C. J2 monoclonal antibody, which recognizes dsRNA with helix >40 basepairs, was purchased from English and Scientific Consulting, Hungary and used at a 1:500 dilution. Guinea pig anti-NSP5 polyclonal antibody was obtained from John Patton  and was used at a 1:1000 dilution. Goat anti-mouse secondary antibody conjugated to Alexa 594 (Invitrogen) was used at a 1:250 dilution. Donkey anti-guinea pig secondary antibody conjugated to DyLight 549 (Jackson ImmunoResearch) was used at a 1:400 dilution in the presence of 1% donkey serum. All antibodies were diluted in immunofluorescence (IFA) buffer . Primary antibody incubations were done at room temperature for approximately one hour and secondary antibody incubations were done at room temperature in the dark for approximately 45 minutes. After the primary antibody incubation, wells were washed three times with IFA buffer. After the secondary antibody incubation, wells were washed three times with IFA buffer and three times with PBS, chambers were removed from the slide, the slide was allowed to air-dry for a few minutes, coverslips were mounted with Vectashield mounting medium with 4',6-diamidino-2-phenylindole (DAPI) (Vector Laboratories), and the slides were sealed with nail polish and allowed to dry in the dark. Images were taken using a Zeiss LSM710 confocal microscope with the 40X objective and analyzed with Volocity 6.0.1 software (PerkinElmer).T175 flasks of MA104 cells were infected with RRV at an MOI of 5 for 1 hour or 6 hours. Cells were washed three times with cold PBS, scraped into PBS, and pelleted 5 minutes at 1000 rpm. Cell pellets were resuspended in 3 ml of hypotonic buffer ), supplemented with 1 mM DTT, and incubated on ice for approximately 10 minutes to allow the cells to swell. Cells were then transferred to a Dounce homogenizer and broken with approximately 30 strokes to generate a cytoplasmic extract. The cytoplasmic extract was supplemented with 0.1% Triton X, and cell debris and nuclei were sedimented by centrifuging for 5 minutes at 1500 x g. The supernatant was digested with 100 μg/ml proteinase K in 1X SDS buffer  for 20 minutes in a 42°C water bath. The total RNA sample was deproteinized by extraction with 2 volumes of P:C: IAA and 2 volumes of C: IAA and precipitated with 0.3 M sodium acetate and ethanol. Total RNA was sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. Total RNA was then digested with 2 U/µl DNase I (Ambion) for 30 minutes in 37°C water bath, supplemented with 1X SDS buffer and 0.3 M sodium acetate, extracted with 2 volumes of P:C: IAA and 2 volumes of C: IAA RNA, and precipitated with ethanol. Total RNA was then sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. RNA concentration was determined by absorbance on a NanoDrop spectrophotometer, and RNA samples were stored in aliquots at -80°C. To isolate large (>100 nt) RNAs from this total RNA fraction, total RNA was mixed with an equal volume of 5 M LiCl and incubated on ice for 30 minutes. The large RNA fraction was pelleted by centrifugation for 30 minutes at 14,000 rpm, resuspended in RNase-free water, and precipitated with 0.3 M sodium acetate and ethanol. Large RNAs were then sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. RNA concentration was determined by absorbance on a NanoDrop spectrophotometer, and RNA samples were stored in aliquots at -80°C.In vitro ssRNA and in vivo 6 hr large RNA samples were denatured for 10 minutes at 65°C then quick-cooled on ice. 2’-O-methyltransferase (New England Biolabs), antarctic phosphatase (New England Biolabs), and 5’ capping (CellScript) reactions were set up using 10 μg of each RNA sample and the appropriate enzymes according to the manufacturer’s instructions. Control reactions lacking enzyme were also set up for each RNA sample. Reactions were incubated for 1.5 hours at 37°C followed by extraction with one volume of P:C: IAA and precipitated with 0.3 M sodium acetate and ethanol. RNAs were sedimented by centrifugation, washed with 70% ethanol, dried briefly, and resuspended in RNase-free water. RNA concentration was determined by absorbance on a NanoDrop spectrophotometer (Thermo Scientific) and RNA samples were stored in aliquots at -80°C.ELISA. MEFs were seeded in 24-well plates at 4 x 104 cells per well or 48-well plates at 2 x 104 cells per well. When the wells reached 80-90% confluency, cells were mock-transfected or transfected with 500 ng per well (for 24-well plate) or 250 ng per well (for 48-well plate) of RNA or polyI:C (Sigma) using Lipofectamine 2000 (Invitrogen). After a 21-hour incubation, cell culture media was collected and the concentration of secreted IFN-beta protein in the cell media was measured using an enzyme-linked immunosorbent assay (ELISA) for mouse IFN-beta . The concentration of secreted IFN-beta was determined by comparison to a standard curve generated using a mouse IFN-beta standard according to the manufacturer’s instructions.