P< 0.0001) being superior to the ‘indirect’ method (P = 0.0006). Cox regression analysis demonstrated that even after adjustment for stage, HPA positivity is an independent predictor for metastasis. The results of the present study indicate that N -acetyl-galactosamine/-glucosamine residues, recognized by HPA, are linked to metastasis in malignant melanoma. In contrast, β1-6 branched oligosaccharides or sialic acid residues, both of which were correlated with metastasis in other malignancies, are of no functional importance for metastasis formation in malignant melanoma. Thus, HPA proved to be a useful and independent prognostic marker for the metastatic phenotype of melanoma. © 2001 Cancer Research Campaign http://www.bjcancer.comChanges in protein glycosylation of tumour cells, as detected by lectin histochemistry, have been associated with metastasis formation in several human malignancies. This study analysed the association between lectin binding and metastasis in cutaneous malignant melanoma. In a 10-year retrospective study, sections of 100 primary cutaneous malignant melanomas were histochemically stained for the following 5 lectins: HPA, SNA-I, MAA, WGA and PHA-L, differing in their carbohydrate specificity. Since differences in the results of HPA binding depending on methodology have been reported, an indirect and a biotinylated method were employed for HPA. Kaplan–Meier analysis of time to first metastasis revealed a positive correlation between HPA binding and metastasis for both methods, with the biotinylated HPA method (


The zinc-finger antiviral protein (ZAP) specifically inhibits the replication of certain viruses, including murine leukemia virus (MLV), by preventing the accumulation of viral mRNA in the cytoplasm. ZAP directly binds to the viral mRNA through the zinc-finger motifs and recruits the RNA exosome to degrade the target RNA. RNA helicase p72 is required for the optimal function of ZAP. In an attempt to understand the structure-function relationship of ZAP, we performed alanine scanning analysis.A series of ZAP mutants was generated, in which three consecutive amino acids were replaced with three alanines. The mutants were analyzed for their antiviral activities against pseudotyped MLV vector. Out of the nineteen mutants analyzed, seven displayed significantly lower antiviral activities. Two mutations were in the very N-terminal domain, and five mutations were within or around the first and second zinc-finger motifs. These mutants were further analyzed for their abilities to bind to the target RNA, the exosome, and the RNA helicase p72. Mutants Nm3 and Nm63 lost the ability to bind to RNA. Mutants Nm 63 and Nm93 displayed compromised interaction with p72, while the binding of Nm133 to p72 was very modest. The interactions of all the mutants with the exosome were comparable to wild type ZAP.The integrity of the very N-terminal domain and the first and second zinc-finger motifs appear to be required for ZAP's antiviral activity. Analyses of the mutants for their abilities to interact with the target RNA and RNA helicase p72 confirmed our previous results. The mutants that bind normally to the target RNA, the exosome, and the RNA helicase p72 may be useful tools for further understanding the mechanism underlying ZAP's antiviral activity. Host restriction factors inhibit retrovirus infection at different steps in the retroviral life cycle by various mechanisms -3. The zAnalysis of the step at which ZAP inhibits MLV infection revealed that the formation and nuclear entry of the viral DNA were normal, but the viral mRNA level was significantly reduced in the cytoplasm of ZAP-expressing cells. The half-lives of the viral mRNA in the cytoplasm were about 2.5 h and 0.5 h in the control and ZAP-expressing cells, respectively, indicating that ZAP promotes the degradation of viral mRNA in the cytoplasm ,7.ZAP directly binds to the target RNA and recruits the RNA processing exosome, a 3'-5' exoribonucleases complex consisting of at least nine components ,8, to deIn the N-terminal domain of ZAP, there are four CCCH-type zinc-finger motifs. Disruption of the second or fourth finger abolished the antiviral activity of ZAP, while disruption of the first or third finger had little effect . When thAs a step to further understanding how ZAP organizes the RNA degradation machinery to degrade viral RNA, we used the alanine scanning method to explore the structure-function relationship of the N-terminal domain of ZAP.A series of NZAP-Zeo mutants, in which three consecutive amino-acids were substituted with three alanines, was constructed and packaged into MLV vector to transduce Rat2 cells. The transduced cells were selected in zeocin-containing medium and pooled for further analyses. Out of the 25 mutants constructed, 19 mutants rendered cells resistant to zeocin selection. However, the remaining 6 mutants failed to do so. To rule out the possibility that the mutations affected the packaging into MLV vector, these 6 constructs were also stably transfected into Rat2 cells, but none of the cells survived the selection. Why these mutants failed to render the cells resistant to zeocin remains elusive. One possibility is that the mutations interfered with the function of the zeocin resistance gene. Another possibility is that the mutations interfered with the folding of the protein, resulting in very low levels of expression.The expression levels of the zeocin resistant mutants were measured by Western blotting. The mutants were expressed at comparable levels except for NZAP-Zeo mutants 63, 83 and 93, which were expressed at lower levels than the rest Fig. . Five ofOut of the eight mutants that displayed significantly reduced antiviral activity, seven  were further pursued. The reason that mutant Nm83 was not included was that it was expressed at a relatively low level but displayed much higher activity than Nm 63 and Nm 93, which were expressed at comparable levels. To assess whether the mutations specifically affected the antiviral activity of ZAP against MLV, the mutants with reduced activity against MLV were also assayed for their activity to inhibit the propagation of SINV. As expected, the inhibitory effect against SINV of the seven mutants was significantly impaired Fig. . In contin vitro binding assay. The ZRE-containing RNA Na, which has been reported to bind to ZAP [It has been previously reported that ZAP directly binds to ZRE-containing RNA . To unded to ZAP , was used to ZAP , was useThe RNA processing exosome is an evolutionarily highly conserved 3'-5' exoribonucleases complex existing in both the nucleus and the cytoplasm -13. The The p72 RNA helicase is a member of the DEAD box family of RNA helicases, which are characterized by a conserved motif including Asp-Glu-Ala-Asp (DEAD) and are involved in various biological processes ,19. It hZAP specifically inhibits MLV replication by promoting the degradation of the viral mRNA in the cytoplasm . ZAP dirOut of the nineteen mutants tested, seven displayed significantly reduced antiviral activity to both MLV-luc vector and SINV Fig.  and 1C. The RNA binding activity of Nm3 and Nm 63 was almost depleted, while that of Nm103 was compromised . To generate pcDNA4/TO/myc-CZAP429, a ZAP fragment was amplified by using forward primer CZAP429SP bearing a CZAP429SP: CTGGATCCATGGCACAGGATCTGCAGACCACACZAP429AP: ACTCGAGCGGCCGCCCTCTGGACCTCTTCAll the cells were maintained in DMEM supplemented with10% FBS. Transfection was performed using Fugene 6 (Roche Diagnostics) according to the manufacturer's instruction. Rat2-HA-Zeo and Rat2-NZAP-Zeo cells have been described previously . The pBaMLV-luc has been previously reported . To eval5 in six-well dishes the day prior to infection. The next day, the cells were infected with the Toto1101 virus (MOI of 1) for 1 h. The titer of the stock was determined on BHK21 cells. After infection, the cells were washed twice with medium, and 2 ml of fresh medium was added. At 48 h post infection, the supernatants were collected and titrated in duplicate wells using permissive BHK21 cells.The methods for SINV infection and titration have been previously described . Briefly293TRex and 293TRex-ZAP cell lines have been described previously . To geneThe method has been described previously .Cells were lysed in lysis buffer B  on ice for 10 minutes, and the lysates were clarified by centrifugation at 4°C for 10 minutes at 13000 rpm. The supernatant was mixed with proteinG plus-agarose (Santa Cruz Biotechnology) and the antibody, and incubated at 4°C for 2 h. The resins were then washed 3 times with lysis buffer B, and the bound proteins were detected by Western blotting.GST fusion proteins were immobilized on glutathione Sepharose 4B and then incubated with the lysate of the cells expressing the NZAP-Zeo-myc mutants in the presence of RNase A (100 μg/ml) for 2 h at 4°C. The resin was washed three times with PBS, and then analyzed by SDS-PAGE and Western blotting.The authors declare that they have no competing interests.Author contributions: GG, FL and XW designed research; XW and FL performed research; XW, FL and GG analyzed data; and GG drafted the manuscript. All authors read and approved the final manuscript.ZAP mutants 23, 53 and 153 interacted with the target RNA, the exosome and the p72 RNA helicase similarly as the wild-type ZAP. Nm 23, 53 and 153 were assayed for their interaction with the target RNA (A), the exosome (B) and the RNA helicase p72 (C) as described in the legends to Figure Click here for file


SplitSeek can be used to detect novel splicing events in SOLiD RNA-seq data without the need for a pre-defined library. de novo prediction of splice junctions in short-read RNA-seq data, suitable for detection of novel splicing events and chimeric transcripts. When tested on mouse RNA-seq data, >31,000 splice events were predicted, of which 88% bridged between two regions separated by ≤100 kb, and 74% connected two exons of the same RefSeq gene. Our method also reports genomic rearrangements such as insertions and deletions.We have developed a new strategy for  To address this problem, the size of the junction library must be reduced dramatically, and consequently, most methods consider only the candidates involving known exons within the same gene. A severe limitation with this approach is that splicing events involving previously unknown exons cannot be identified. Also, this type of analysis is restricted to the relatively small number of species in which coordinates of genes and exons have been found.High-throughput sequencing of mRNA opens unprecedented opportunities to identify the spectrum of splice events in a sample on a global scale. The typical approach for detecting splicing in RNA-seq experiments has been to map the reads to a junction library consisting of predefined exon-exon boundaries -6. Althode novo identification of exon boundaries from raw RNA-seq data, which in itself is a computationally challenging task, especially for transcripts expressed at lower levels.To overcome some of these limitations, the splice-junction library can instead be created directly from the RNA-seq data without relying on any genome annotations. This approach is taken by the two packages G-Mo.R-Se  and TopHAn important application of deep RNA sequencing is the discovery of fusion transcripts in cancer, and two consecutive methods have been proposed by Maher and colleagues . Initialde novo without any preassumed set of allowed exon boundaries. This implies that all types of splicing events in the RNA sample can be detected in a completely unbiased way, including previously unknown splice junctions and fusion transcripts. Also, we rely entirely on short reads (~50 bp) from fragment libraries, which is the type of RNA-seq data normally generated by using the Illumina or SOLiD platforms. By applying our method to available RNA-seq data from mouse cells [Here we present an alternative approach to identify splice junctions. The junctions are predicted se cells , we showse cells . The potse cells  and usedse cells , which eOur strategy consists of a combination of a split-read alignment and the novel SplitSeek program  of 50 of the junction reads have this property. With a length of 75 bp and still splitting into 2 × 22 bp, this proportion would increase to 32 (43%) of 75, and this would likely increase the number of detected splicing events significantly. Another benefit of longer reads is that they could allow longer anchor lengths in the alignment, which might be necessary to discover junctions that are not uniquely mappable with shorter reads. However, it also is possible to increase the throughput by simply performing a deeper sequencing by using more of the 50-bp reads, and it is not obvious which is the optimal approach for this application. Although several benefits exist of using longer reads, some drawbacks might also occur, such as lower-quality base calls at the ends of the reads and difficulties in identifying splicing between very short exons.Because of the recent improvements in throughput of the next-generation sequencing platforms, we believe that this strategy will make it feasible to investigate the entire spectrum of splicing events or gene fusions in an RNA sample in a completely unbiased way. We also want to emphasize the possibility of finding insertions, deletions, and other types of genetic rearrangements with the SplitSeek approach. This moves beyond the scope of RNA-seq data analysis, because it can equally well be used for DNA samples sequenced with high coverage.de novo detection of splice junctions in RNA-seq data. The exon-exon boundaries are identified almost at nucleotide resolution and with a low false-positive rate, <1 in 10,000 for junctions within 100 kb. Our method makes it possible to study splice junctions and fusion genes while also quantifying the gene expression, all from the same RNA-seq data. In addition, our method reports insertions and deletions in coding and noncoding parts of transcripts. We expect this to be an important application in a wide range of RNA-seq projects.We have developed a strategy for The raw RNA-seq data on mouse oocytes were downloaded from Gene Expression Omnibus , with acSplice junctions were predicted from the alignment output files by using the SplitSeek software, which consists of two programs that are executed sequentially. In the first step, all candidate junction reads are identified and written to an intermediate BEDPE file. BEDPE is a file format that was recently introduced to give a concise description of paired-end sequence alignments . This inSplitSeek finds exon-exon boundaries that are supported by several split reads. In this case, we required each junction to be covered by at least two reads with unique starting points. Other parameters that may be specified by the user include the total number of reads required to cover a predicted junction, and the maximum allowed distance between two candidate junction reads that belong to the same predicted splice junction. SplitSeek groups candidate junction reads by traversing them in the order of their genomic coordinates and joining those where the two exon boundaries are both within the allowed distance. All groups in which the number of reads is greater than the user-defined threshold are then reported in the SplitSeek output. In some cases, SplitSeek may require an additional "chrmap" input file to ensure that the chromosome names of SplitSeek predictions agree with those in the genome databases. The user is allowed to specify an upper limit on the distance between the junctions , so that longer splicing events are not reported.The SplitSeek results are presented in two different formats, as a BED file and a BEDPE file. The BED file can be uploaded and viewed in the UCSC genome browser, whereas the BEDPE file can be used as input to BEDTools  or other6 bases. Because the mouse reference sequence (mm9) used in the alignment consists of about 2.7 × 109 bases, the probability that two randomly placed splicing boundaries are located within 1 Mb is ~2 × 106/2.7 × 109 ≈ 7.4 × 10-4. Under the null hypothesis, the number of expected splicing events within 1 Mb can therefore be estimated by N × 7.4 × 10-4, where N is the total number of predicted junctions. The FDR is then calculated as the ratio between expected/observed events. In the same way, we calculated the FDR for results within 100 kb. The results are presented in Table To make an estimate of the false discovery rate (FDR) in our results, we assume a null hypothesis in which the two parts of a splice event are uniformly distributed over the genome sequence. We then estimated an FDR for all splicing events within 1 Mb by comparing the observed values with the expected. To calculate the number of expected events, we assume that the first anchor has already been randomly mapped to the genome. In that case, the second anchor must be mapped within a ± 1-Mb window surrounding the first anchor for the criteria to be fulfilled. The size of this window is 2 × 10Version 1.01 of the RNA-MATE program was downloaded from the SOLiD software-development web page , along wEST: expressed sequence tag; FDR: false discovery rate; RNA-seq: high-throughput sequencing of RNA; 3' UTR: three prime untranslated region.AA and UG designed the research; AA implemented the software and conducted the analysis; and AA, AW, LF, and UG interpreted the results and wrote the manuscript.SplitSeek. The SplitSeek program code, released as free software under version 3 of the GNU General Public License [ License .Click here for file


Mathematical modeling is important to provide insight in the complicated pathway of RNA silencing. RNA silencing is an RNA based mechanism that is widely used by eukaryotes to fight viruses, and to control gene expression.We here present the first mathematical model that combines viral growth with RNA silencing. The model involves a plus-strand RNA virus that replicates through a double-strand RNA intermediate. The model of the RNA silencing pathway consists of cleavage of viral RNA into siRNA by Dicer, target cleavage of viral RNA via the RISC complex, and a secondary response. We found that, depending on the strength of the silencing response, different viral growth patterns can occur. Silencing can decrease viral growth, cause oscillations, or clear the virus completely. Our model can explain various observed phenomena, even when they seem contradictory at first: the diverse responses to the removal of RNA dependent RNA polymerase; different viral growth curves; and the great diversity in observed siRNA ratios.The model presented here is an important step in the understanding of the natural functioning of RNA silencing in viral infections. RNA silencing is an evolutionary conserved regulation system and has an antiviral role in plants and some animals -3. The kIn the primary silencing response siRNA is cleaved directly from viral RNA. In addition, in plants there can be a secondary response in which host encoded RNA dependent RNA polymerase (RDR) creates dsRNA that can be cleaved into one or more siRNAs.We here present the first model study that combines viral growth with RNA silencing. Previous models focused either on virus dynamics or on RNA silencing separately, or on direct siRNA delivery for clinical applications of RNA silencing -16.Previously we modeled the RNA silencing pathway and investigated the ability of RNA silencing to silence endogenous genes, transposons and dsRNA, and the role of the primary and secondary response in these cases . AntivirWe study virus induced RNA silencing and its efficacy to reduce viral infections in a single compartment system. We find that RNA silencing can alter viral growth in five qualitatively different ways, and we compare the behavior in these regions to experimentally observed growth curves. We investigate the effect of different Dicer cleavage modes, and the impact of the secondary response. Lastly, we vary Dicer single- and double-strand cleavage rates and find that our model provides an explanation for the wide range of observed siRNA ratios.In short, the model consists of the following processes: The virus replicates itself through dsRNA, that is produced via virus encoded RNA dependent RNA polymerase (RdRP). Viral double- or single-strand RNA is degraded by host encoded Dicer into siRNAs, that have a plus- or minus-strand polarity. Via RISC the siRNAs cause degradation of either viral plus- or minus-strand RNA. In addition, siRNAs can be synthesized through the secondary pathway that involves synthesis of dsRNA by host encoded RDR. The model of the primary pathway can apply to both plants and animals, the model with secondary pathways applies to plants only .We build up the mathematical model in a stepwise manner, starting with a model of viral replication. We then expand the model with the primary and finally the secondary silencing pathway. Each equation of the full model will consist of viral replication :kr. Semi-conservative synthesis of multiple plus-strands from a single minus-strand template is incorporated in the model. RdRP can associate with Dm (dsRNA complexes formed from the minus strand) with maximum rate od. In the case of Dp a single RdRP is present on the complex, and the entire complex dissociates with rate h into RdRP and a plus- and minus-strand. Multiple RdRPs are present on Dm, and each RdRP produces one product strand and then dissociates with rate h. However, the complex still exists after dissociation of one RdRP. The Dm complex disappears when the last RdRP dissociates. The chance that only one RdRP is present is Dm is with saturation constant v and a Michaelis Menten constant kv. d and dr are the decay rates of viral ssRNA and RdRP respectively.The virus produces virions that consist of plus-strand RNA and coat proteins. We simplify here by using the number of plus-stranded RNA instead of modeling a separate coat protein. The virion production has a maximum rate of virion production The viral replication model is extended to include viral induction of the RNA silencing pathway. The scheme is shown in Figure Sip, Sim, Rf, Rp and Rm represent siRNA cleaved from plus-strands, siRNA from minus-strands, free RISC, RISC loaded with Sip, and RISC loaded with Sim, respectively. We do not show the equations for Sim and Rm since they have the same form as the equations for Sip and Rp. The equation for the virions is unaltered (eq. 4).Variables Viral RNA is cleaved into siRNAs by Dicer. We simplify here by using only a single type of Dicer. Di is the number of Dicer molecules present in the host. Dicer can cleave siRNAs from dsRNA with maximum rate cd, and from ssRNA with rate cs. When Dicer cleaves both single- and double-strand RNA, we use the following function:cd + 2cs.that is saturated for all possible Dicer targets. When Dicer cleaves dsRNA a 1-1 ratio of siRNAs targeting the plus- and minus-strand is produced. When studying the effects of Dicer cleavage rate, we always use the total rate, that is, b1 with RISC to form siRISC: the active RISC complex that will cause the breakdown of viral RNA. One strand of the siRNA is kept in siRISC, and since that strand consists of a short stretch of either plus- or minus-strand viral RNA, it will match to the complementary strand. The target of the active RISC is the RNA strand that matches the incorporated siRNA. siRISC cleaves the target RNA with maximum rate b2. kri is the saturation constant of the siRISC cleavage function. dsi and dr are the siRNA and RISC decay rates.siRNAs associate with rate In addition to the primary response, the silencing pathway can include a secondary response. Host-encoded RDR synthesizes dsRNA from single-strand substrates, that are cleaved into secondary siRNAs. In vitro RDR has two modes of action: primed and unprimed amplification ,21. In tDe). This dsRNA is degraded into secondary siRNAs with a plus- or minus-strand polarity; Sisp and Sism respectively. Since Dicer now cleaves De in addition to Dp and Dm, the Dicer cleavage functions De:Where De, Sisp, Sism, Rsp and Rsm representing dsRNA produced via amplification, secondary siRNA with plus strand polarity, secondary siRNA with minus strand polarity, RISC loaded with Sisp and RISC loaded with Sism, respectively. Again we do not show Sim, Sism and Rm since they have the same form as Sip, Sisp and Rp respectively. The full model can be found in the Appendix.With Where possible, parameters were taken from literature Table . We haveWe first study the growth of a plus-strand RNA virus in a silencing defective system. The viral replication cycle is shown in Figure C. elegans [In the default setting our model results in a sigmoid growth of viral plus-strands Figure . Sigmoid elegans . In our o, od, h and r causes faster initial growth of the virus. A decrease in kr and kt has the same effect. A sigmoid curve with a higher equilibrium can be obtained by increasing o, od and r, and by decreasing h. Changing v does not have a large effect on viral growth, except when the timing of virion production is too early (when kv is low).Depending on the initial dose and growth parameters, the virus can expand to the equilibrium as shown in Figure f, the preference that RDR has for minus-strands. When increasing f the plus-to-minus ratio becomes increasingly biased towards the plus strand , the RISC cleavage rate (b2), the number of Dicers (Di), the influx of free RISC (i), and the siRNA production rate (cd and cs). All these parameters determine the rate at which RNA silencing degrades viral RNA. We refer to this effect as the silencing strength. We will use one parameter as an example to study the effect of silencing strength.The important silencing parameters are the RISC activation rate  post infection. Maximum and minimum values are monitored from 10 hours onwards. When silencing strength increases, we observe four possible effects of silencing. The four regions of different behavior are shown in the bifurcation diagram in Figure To investigate the effect that RNA silencing has on viral growth we vary the silencing strength. We do this by varying any of the silencing parameters according to the ranges in Table For a low silencing strength, in region I, virus levels are slightly decreased. A timeseries of this behavior is shown in Figure A further increase in silencing strength leads to the behavior in region III, where oscillations in viral RNA levels occur , there is a clear effect  plants, that are not capable of a secondary response, were only hypersusceptible to some of the tested viruses, while the response to other viruses was not affected [We conclude that enough dsRNA cleavage is necessary to observe an effect of the secondary pathway. Not all virus infections seem to be affected by the secondary response. RDR defective Tobacco . This ratio may be affected by viral properties as RNA folding and accessibility of single- and double-strand RNA. We keep total Dicer cleavage rate constant and plot the minimum and maximum siRNA ratio observed between 24 and 100 hours post infection  to avoid non-existent siRNA ratio's in region III, IIIa or IV.When only dsRNA is cleaved, the siRNA ratio will be 0.5, due to the fact that there is always an 0.5 chance that either siRNA strand is selected. The addition of primed amplification can raise this ratio: more minus-strand siRNAs are used for amplification because the plus strand is present in higher amounts. When only ssRNA is cleaved, the ratio follows from the plus-to-minus ratio produced by the virus. We find that when Dicer cleavage rates are intermediate between these two extreme cases, different siRNA ratios can occur for different viruses. In fact, the whole range between 0.5 and 1 is possible, and the experimentally observed ratios can be reached without implementing an extra mechanism or Dicer preference for the plus-strand. When the virus ssRNA has many hairpins and mainly ssRNA is cleaved, we predict a high siRNA ratio. When mainly dsRNA is cleaved we expect a low ratio Figure .The siRNA ratios are shown in ranges between the maximum and minimum because the siRNA ratio changes over time. The trend is that initial siRNA ratio's are close to 1 , followed by a decline in siRNA ratio, after which a stable ratio is reached Figure .Concluding, when Dicer is capable of both single- and double-strand RNA cleavage, the experimentally observed ratios can be reached without implementing a Dicer preference for the plus-strand.The RNA silencing pathway functions as an immune system in plants and several animals. We here presented the first model study that combines viral growth and RNA silencing.In contrast to the previously reported necessity of a nonlinear feedback in amplification to silencing transgenes , we showC. elegans with silencing able and silencing deficient hosts. They show that without silencing the virus grows according to a sigmoid curve to 1 · 106, with silencing this curve is flattened and the virus accumulates to 5 · 104. This behavior is in accordance with our results: in region I and II the virus equilibrium is decreased to similar extent. Dzianott and Bujarski [Brome mosaic virus growth curve in A. thaliana. They observed an initial decline in RNA, then a peak of viral growth, after which the concentrations decline toward zero again. We can assume the curve found by Dzianott and Bujarski [RNA silencing can alter the sigmoid growth pattern of the virus substantially. Wilkins et al.  studied Bujarski  obtainedBujarski  represenWe studied three cases of Dicer activity modes: Dicer can cleave dsRNA, ssRNA or both. We show that a combined degradation of single- and double-strand RNA by Dicer is more efficient than each case separately.Sufficient dsRNA cleavage is necessary to observe an effect of the secondary silencing response. Unprimed amplification is able to strongly increase the efficacy of RNA silencing, clearing the virus for much lower silencing strength. Virion production is then not possible, because virus growth is completely silenced. Primed and guided amplification can cause major oscillations that also lead to clearance of the virus, however, the virus is still able to produce virions during the initial growth peak. Moreover, primed amplification can only be beneficial when the siRNA gain through amplification is sufficiently high.Experiments have shown that viruses accumulate to higher levels in hosts defective in the secondary response -34. HoweIn antiviral silencing a wide range of siRNA ratios has been observed ,11,35. OOur work provides an important framework to study natural antiviral silencing. We have shown that various experimentally observed behaviors can be explained, even when they seem contradictory at first.MG and PH conceived and designed the models, and wrote the paper. MG performed the numerical computations.The full model:


Carcharhinus amblyrhynchos) and fidelity to individual reef platforms has gone largely unstudied. Their wide distribution implies that some individuals have dispersed throughout tropical waters of the Indo-Pacific, but data on large-scale movements do not exist. We present data from nine C. amblyrhynchos monitored within the Great Barrier Reef and Coral Sea off the coast of Australia. Shark presence and movements were monitored via an array of acoustic receivers for a period of six months in 2008. During the course of this monitoring few individuals showed fidelity to an individual reef suggesting that current protective areas have limited utility for this species. One individual undertook a large-scale movement (134 km) between the Coral Sea and Great Barrier Reef, providing the first evidence of direct linkage of C. amblyrhynchos populations between these two regions. Results indicate limited reef fidelity and evidence of large-scale movements within northern Australian waters.Despite an Indo-Pacific wide distribution, the movement patterns of grey reef sharks ( Conservation concerns about the status of coral reef associated shark populations in various locations around the world Carcharhinus amblyrhynchos from the Great Barrier Reef, Australia. The aims of this study were to: 1) determine the level of fidelity to individual reef platforms and marine protected areas, 2) examine the extent of movement within a series of closely associated reef platforms, and 3) determine if there are ontogenetic differences in fidelity and movement patterns.Defining movement patterns within reef shark populations is vital to interpreting results of sampling such as catch data and underwater visual surveys that have been used to infer reductions in reef shark populations. Recent studies have revealed higher relative abundances of reef sharks in areas closed to fishing and public entry C. amblyrhynchos ranging from 84–152 cm total length (TL) were fitted with acoustic transmitters in the Ribbon Reefs  were juveniles and some of the smallest individuals in the sample. These two individuals were recorded over long periods and showed significant reef fidelity. One of these individuals was released at Hicks Reef (zoned HP), recorded there on 98 of 150 days and was still present at the time of receiver removal. The second individual released at Yonge Reef (zoned SR and CP) covered a straight line distance of at least 5 km and was present at Day Reef (SR zone) from 6 Feb to 10 Mar before leaving the monitoring area . The remThe remaining three sharks moved between reefs and protection zones. One individual moved between different protection zones up to 23 times, crossing a 1.5 km channel between reefs repeatedly with at least 15 movements from one reef to another . This inOne additional individual, a 122 cm TL male fitted with a transmitter at Osprey Reef in the Coral Sea  was detected at the Ribbon Reef site. This individual was present at Osprey Reef from 27 Mar until 25 June 2008 and was next recorded on receivers at Day and Hicks Reefs starting 47.8 hours after the last detection at Osprey Reef. This is evidence that this individual travelled approximately 134 km across the open ocean from the Coral Sea to the Ribbon Reefs . This shC. amblyrhynchos monitored in the Ribbon Reefs showed variability in movement patterns. Smaller individuals appeared to be more site attached, while larger individuals were more likely to move beyond a single reef. This is similar to telemetry observations of Negaprion brevirostris and C. perezi in reef areas where juveniles showed high site fidelity to a small region Individual C. amblyrhynchos do show site fidelity to individual reefs, especially as juveniles. However, the lower level of site fidelity for larger individuals suggests that fishing may not be the only potential driver for differences in abundance. While the current study was not able to identify these drivers, potential mechanisms include differences in carrying capacity between fished and unfished reefs due to the ecosystem effects of fishing (e.g. reduce prey base on fished reefs) or behavioral differences between management zones that result in biased survey resultsPrevious research in the GBR has revealed sharks are in higher abundance in areas closed to fishing et al. C. perezi over 50 km off the coast of Belize and the current study has demonstrated movement of 134 km for C. amblyrhynchos. A movement of 134 km in less than 48 hours required this individual to have swum at a rate of 0.6–0.7 body lengths per second, a rate of movement within those calculated for other shark species C. amblyrhynchos populations on Coral Sea Reefs and those of the Great Barrier Reef. Individuals do move large distances and these movements may be more common than previously thought.Research is beginning to reveal that as Randall Evidence of large-scale movements lends support to the hypothesis that undetected individuals in the Ribbon Reefs may have moved beyond the monitored region. Individuals showing fidelity over significant periods were juveniles, with adults using broader areas and moving out of detection range more quickly. Individuals could follow the chain of Ribbon Reefs north into the Torres Strait or south into the central Great Barrier Reef. None of the individuals fitted with transmitters in the Ribbon Reefs have been detected on receivers at Osprey Reef, but movement between these sites and of this magnitude can no longer be ruled out.C. limbatus) in Florida have revealed detailed habitat use patterns and provided survival data useful to stock assessments and management decisions Based on this study it is apparent further research into the presence and movements of reef sharks is needed. Previous long-term studies of shark movement have been highly beneficial to understanding the ecology of those species and providing guidance for management. For example, studies of blacktip sharks  in north Queensland, Australia, provide near continuous habitat with individual coral reefs separated by channels of up to 40 m depth and typically 1–1.5 km wide. The study region included six reefs representing six different management zones: Habitat Protection Zone , Conservation Park Zone , Scientific Research Zone , Marine National Park Zone , Preservation Zone (P – no entry except for emergency anchoring and limited research access) and Buffer Zone . Thirty-one VR2 acoustic receivers (Vemco Ltd.) were deployed to passively track movements of uly 2008 . ReceiveData from acoustic receivers was processed to define the length of time an individual was monitored (release date to date of last detection), the number of days an individual was present during the monitoring period, and when detections were recorded (day vs night). Data from each reef was examined to define the number of reefs and marine park zones an individual visited and the amount of time spent within each. Significant differences in the proportion of detections of individual sharks between day and night were determined using Chi-squared tests.


Caenorhabditis elegans, a complex containing the enzymes Dicer and the Argonaute RDE-1 process dsRNA. Dicer is responsible for cleaving dsRNA into short interfering RNAs (siRNAs) while RDE-1 acts as the siRNA acceptor. RDE-1 then guides a multi-protein complex to homologous targets to trigger mRNA destabilization. However, endogenous role(s) for RDE-1, if any, have remained unexplored. We here show that RDE-1 functions as a scavenger protein, taking up small RNA molecules from many different sources, including the microRNA (miRNA) pathway. This is in striking contrast to Argonaute proteins functioning directly in the miRNA pathway, ALG-1 and ALG-2: these proteins exclusively bind miRNAs. While playing no significant role in the biogenesis of the main pool of miRNAs, RDE-1 binds endogenous miRNAs and triggers RdRP activity on at least one perfectly matching, endogenous miRNA target. The resulting secondary siRNAs are taken up by a set of Argonaute proteins known to act as siRNA acceptors in exogenous RNAi, resulting in strong mRNA destabilization. Our results show that RDE-1 in an endogenous setting is actively screening the transcriptome using many different small RNAs, including miRNAs, as a guide, with implications for the evolution of transcripts with a potential to be recognized by Dicer.RNA interference (RNAi) is a post-transcriptional silencing process, triggered by double-stranded RNA (dsRNA), leading to the destabilization of homologous mRNAs. A distinction has been made between endogenous RNAi–related pathways and the exogenous RNAi pathway, the latter being essential for the experimental use of RNAi. Previous studies have shown that, in  rde-1 gene from Caenorhabditis elegans was one of the first genes found in association with this mechanism and encodes the only Argonaute protein in worms, which is by itself essential for the classical RNAi pathway triggered by exogenously introduced dsRNA. However, little is known about endogenous functions of RDE-1. Here we show that RDE-1 binds to many classes of small RNAs, including microRNAs. We show that miR-243 is efficiently bound by RDE-1 and triggers regular RNAi on an endogenous target, implying that many RNA species, including miRNAs, are constantly being screened against the transcriptome using the canonical exogenous RNAi pathway.Due to its intrinsic characteristics, RNA interference (RNAi) has become one of the most widely used tools in cell biology and has revolutionized approaches to elucidate gene function. The process, also known as RNA silencing, is triggered by dsRNA molecules that are cleaved by Dicer proteins into small interfering RNAs (siRNAs). The  RNA silencing is a conserved mechanism for controlling gene expression. In this process, long dsRNAs or hairpin-like transcripts are diced into small RNAs ranging from 21 to 26 nucleotides Caenorhabditis elegans can be schematically divided in two classes: endogenous, comprising microRNAs, 21U- RNAs, transposon repression and other chromatin-related processes, and exogenous, required for processing artificially introduced double-stranded RNA molecules (RNAi). C. elegans microRNAs are processed from endogenously expressed transcripts containing hairpin structures and are preferentially bound by the Argonaute proteins ALG-1 and ALG-2 C. elegans, RDE-1 is the only one required for processing long exogenous triggers. Although the PIWI domain of RDE-1 is catalytically active, we showed that its activity is only required for the maturation of the small RNA duplex and not for target RNA silencing The proliferation and diversification of silencing-related genes during evolution allowed the specialization of small RNA-directed pathways in controlling different biological fates C. elegans, EGO-1 and RRF-1–3. EGO-1 and RRF-1 are key players in exo-RNAi pathways in germline and somatic tissues, respectively C. elegans are only of antisense polarity relative to the target, have tri-phosphate groups at their 5′ ends C. elegans have led to the suggestion they are direct products of RdRPs, instead of being Dicer products as observed in plants and fungi C. elegans-specific Argonaute proteins that will mediate further silencing. Indeed, knocking out multiple of these so-called secondary Argonaute proteins simultaneously leads to RNAi resistance In nematodes, plants and fungi, Argonaute proteins, together with RNA-dependent RNA polymerases (RdRP), are also involved in siRNA amplification C. elegans, and that RDE-1 is responsible for recruiting the amplification machinery in that scenario. But so far, no endogenous function has been attributed to RDE-1. Loading of small RNAs into RDE-1 depends largely on the structure of the duplex precursor. Fully matching precursor stems are preferentially loaded in RDE-1, but stems with 1-, 2- or 3-nucleotide mismatches are recognized as microRNAs and loaded into ALG-1 or ALG-2 in vivo, or whether RDE-1 is able to interact with other endogenous Dicer products as well.Thus, it is clear that exo-RNAi occurs sequentially in C. elegans transcriptome for homology to any Dicer product, with implications for the evolution of any RNA molecule that may trigger Dicer activity.We show that RDE-1 is loaded with a wide variety of Dicer products, and that miRNAs constitute a major fraction of the RDE-1-bound RNAs. The miRNA-RDE-1 complexes are functional and relevant, as we show that the gene Y47H10A.5 is silenced by miR-243 in an RDE-1- and RRF-1-dependent manner. Effectively, this makes RDE-1 a scavenger that surveys the complete rde-1 mutant population, rescued with an HA-tagged RDE-1 construct C. elegans, were also cloned from mixed cultures of previously established HA-tagged lines , repeat RNA, known microRNA, 21U-RNA, scRNA , snRNA , snoRNA , non-hairpin region, tRNA, rRNA, sense RNA and “other”. “Other” includes RNA species not falling into any of the 11 categories and contains sequences derived from non-genic, non-annotated regions.RDE-1, ALG-1 and ALG-2 small RNAs were predominantly 22 nt in length (data not shown). The small RNA reads were mapped to the C. elegans.As expected, ALG-1 and ALG-2 specifically bind miRNAs . Other cIn sharp contrast to ALG-1 and ALG-2, RDE-1 associates with significant numbers of reads derived from many different classes . When corde-1 mutant worms were cloned and deep-sequenced using an Illumina platform. To allow detection of indirect effects on secondary siRNAs carrying 5′-tri-phosphate groups, rde-1 mutant RNA was treated with Tobacco Acid Pyrophosphatase (TAP). For comparison, we sequenced two wild-type libraries: one with TAP treatment and one without , with both loci producing significantly less siRNAs in the rde-1 mutant.When the wild-type and observed . Therefoobserved . Two proC. elegans, W06 siRNAs depend strongly on TAP treatment for efficient cloning, indicating that they are predominantly secondary siRNAs . From those, 48.7% were upregulated and 51.3% were downregulated  that are likely responsible for the observed Y47 mRNA destabilization triggered by miR-243.Despite the many different short RNAs represented in RDE-1 immunoprecipitates, we found that not many loci are affected by loss of oduction . Only twC. elegans miR-243 is also able to trigger the generation of siRNAs reminiscent of plant tasiRNAs  pathway. In that system, miRNA-guided cleavage of non-coding precursor transcripts (TAS transcripts) triggers the production of dsRNAs by RDR6, a plant RdRP. The resulting TAS-dsRNAs are subsequently cleaved by DICER-LIKE -4 into phased 21 nt-size tasiRNAs tasiRNAs . As in ptasiRNAs . InsteadtasiRNAs , demonstC. briggsae, while many microRNA genes have well conserved homologs in C. briggsae and some even up to mammals. Also, miR-243 does not have a typical bulged miRNA precursor structure Two mechanisms have been proposed for the birth of miRNAs: inverted duplication of genic sequences C. elegans, and in any other animal system, do not have perfectly matching target mRNAs. Apparently, miRNAs that match perfectly to their targets are not tolerated well in animals. RDE-1 may provide a way to quickly recognize such perfect matches, followed by a silencing response that is much stronger than that typically triggered by a miRNA, ensuring that harmful interactions will be selected against firmly.The vast majority of miRNAs in While this work was under review, Gu et al alg-1(gk214), rde-1(pk3301), rde-1(ne300) rescued with rde-1::HAalg-1::HA(pkIs2250)mir-243(n4759); mir-1(gk276); rrf-1(pk1417); rrf-2(pk2040); rrf-3(pk1426). The MAGO(WM126) strain has the following composition: wago-8(tm1195); wago-6(tm0894); C04F12.1(tm1637); wago-4(tm1019); wago-7(tm0914). Note that wago-6 is also known as sago-2, wago-7 as ppw-1, wago-8 as sago-1 and wago-4 as F58G1.1 Nematodes were cultured according to standard procedures and the Bristol strain N2 was used as the standard wild-type strain. The alleles used in this study were Nematode extracts were obtained by freezing about 2 ml of nematodes in IP buffer (10 mM Tris-HCl (pH 7.5), 100 mM KCl, 2 mM MgCl2, 0.05% (v/v) Tween-20, 15% (v/v) glycerol, 5 mM DTT and 1 tablet of complete mini–EDTA-free protease inhibitor cocktail (Roche) per 10 ml buffer) in liquid nitrogen, followed by grinding with mortar and pestle and homogenizing with 20 strokes in a tight fitting dounce. Debris were spun down twice five minutes in a tabletop centrifuge at 10,000 g at 4°C.For RNA immunoprecipitations, HA::ALG-1, HA::ALG-2 and HA::RDE-1 were immunoprecipitated from nematode extract by incubation with anti-HA 3F10 affinity matrix (Roche) for 2 h at 4°C. Protein G–agarose (Roche) was used as the ‘empty-beads’ control. After five washes with IP buffer, 1% of the immunoprecipitate was used to detect HA–RDE-1, HA-ALG-2 and HA–ALG-1 by western blotting according to standard procedures using anti-HA 3F10 (Roche).32P-5′-labeled using T4 poly-kinase (Promega). The remaining RNA was used for library construction or northern blot analysis.RNA from nematode extracts and RNA-immunoprecipitates were isolated using Trizol LS (Invitrogen) according to the manufacturer's protocol. To assess the quality of the immunoprecipitated RNA, 1% of the RNA was treated with shrimp alkaline phosphatase (Promega) and For IP libraries, the small-RNA cDNA library was prepared by Vertis Biotechnology AG  to be suitable for massively parallel sequencing using 454 technology as described previously For mutant libraries, worms were staged as young adults, lysed by Protease K treatment and RNA was isolated using Trizol (Invitrogen). The RNAs were, or were not treated with Tobacco Acid Pyrophosphatase and subsequently poly(A)-tailed using poly(A) polymerase followed by ligation of a RNA adaptor to the 5′-phosphate of the small RNAs. First-strand cDNA synthesis was performed using an oligo(dT)-linker primer and M-MLV-RNase H- reverse transcriptase. The cDNA was PCR-amplified for 16 cycles according to the instructions of Illumina/Solexa. Equal amounts of bar-coded cDNA were mixed. The 125–140 bp fraction of the cDNA pool was obtained by fractionation of the cDNA on a preparative 6% polyacrylamide (PAA) gel. The eluted cDNA was finally purified using the Macherey & Nagel NucleoSpin Extract II kit and was sent for sequencing on an Illumina/Solexa platform.All sRNA sequences obtained in this work has been deposited in the GEO database with the accession number GSE20649.C. elegans genome (ce4) using the megablast program Computational analysis of small RNA reads was performed as described previously 32P]ATP by using T4 polynucleotide kinase (Promega). Probes used in this study were: miR-243 – 5′ ATATCCCGCCGCGATCGTACCG 3′; miR-58 – 5′ TTGCCGTCTGCGTCTC 3′; Y47H10A.5 siRNAs: 5′ GTTTCAGTTCTGGGGAATTTGGTCTAAAAAACTAT 3′ and 5′ TCACTATTTGGCCAGTTAATCTTATATTTCCCGG 3′;For detection of small RNAs, total RNA fraction extracted from young-adult worms was enriched for small RNAs using Mirvana kit (Ambion) and 10 µg were fractionated on 15% polyacrylamide gels and transferred to Hybond-N membrane (Roche). Pre-hybridization/hybridization and washes were done at 32°C for siRNAs and 37°C for microRNAs in ULTRAhyb-oligo hybridization buffer (Ambion). For detection of miRNAs, oligonucleotides corresponding to the antisense sequences of the small RNAs were synthesized and radioactively end-labeled with [α-Cdc-42, eIF-3, Pmp-3 and Tba-1, four housekeeping genes known to be stable in C. elegans−ΔCt method. Results presented are the average values obtained from three biological replicates. Primers used were: Y47 Forward (5′ TCGGGATAGTGAAATGAAAGC 3′), Y47 Reverse (5′ GGTTGTTCGTCTTGTAGGCAA 3′), Cdc-42 forward (5′ ATGTCCGAGAAAAATGGGTG 3′), Cdc-42 Reverse (5′ ATCCGTTGACACTGGTTTCTG 3′), eIF-3 Forward (5′ GCTGAGACTGTTAAGGGAATGG 3′), eIF-3 Reverse (5′ GAGCGAAACAGTGGCATAAAC 3′), Pmp-3 Forward (5′ GGAATTGTTTCACGGAATGC 3′), Pmp-3 Reverse (5′ TGGAGGACGATCAGTTTCAA 3′), Tba-1 Forward (5′ GTACACTCCACTGATCTCTGCTGACAAG 3′) and Tba-1 Reverse (5′ CTCTGTACAAGAGGCAAACAGCCATG 3′).For RT reactions, 5 µg of total DNase-treated RNAs were reverse-transcribed with M-MLV (Promega) and oligo dT primers. Quantitative RT-PCR was carried out using the MyiQ Single-Color Real-Time PCR Detection System from Bio-Rad. Each reaction contained: 10 µl of the iQ SYBR Green qPCR SuperMix (Biorad), 0.2 µM of forward and reverse primers and 5 µl of cDNA (1∶25 RNA dilution) in a total volume of 20 µl. PCR cycles were as follows: one cycle of 95°C for 3 min; 40 cycles of 95°C for 15 sec; 60°C for 30 sec and 72°C for 45 sec. Results were normalized against mir-243 young-adult worms were isolated and reverse-transcribed with random primers. Each cDNA sample was split and labeled with both Cy3 and Cy5. Samples were hybridized to Agilent C. elegans whole genome arrays at 65°C overnight. Signals were analyzed with the Agilent Array assist Software, utilizing background subtraction, LOWESS normalization, and dyeswap analysis. RNAs that changed at least 2-fold with a probability of p<0.05 in three biological replicates were considered differentially regulated between wild-type and mir-243.RNA samples from wild-type and http://babelomics.bioinfo.cipf.es/). FatiGO software provides different levels of GO analysis. Low levels consider only the general function of the genes. The higher the level, the more specific it becomes. Misregulated genes were analyzed in all available levels, including all three GO classifications . But only results for level 4 (p≤0.01) are shown.Gene ontology analysis was carried out by the online software FatiGO .Phylogenetic analysis of the Y47H10A.5 sequence and its paralogs. (A) Phylogenetic tree showing the relatedness of Y47H10A.5 with its paralogs. The predicted amino acid sequences were aligned with Multalign and the tree was constructed by the neighbor-joining method. Bootstrap values are indicated at each node. (B) Percentage identity between the amino acid sequences of Y47H10A.5 and its related sequences. (C) Multiple sequence alignments of the deduced amino acid sequences. Black boxes represent residues that are present in all sequences in the alignment. Columns in the alignment with less than 100% conservation but more than 60% are shaded in grey. Shading was performed by GeneDoc program ((1.33 MB TIF)Click here for additional data file.Figure S2Expression pattern of Y47H10A.5. An approximately 1kb region upstream of the Y47H10A.5 sequence was cloned behind GFP and injected into wild-type worms. Expression is confined to intestine cells.(2.56 MB TIF)Click here for additional data file.Figure S3in trans. Level of Y47H10A.3 transcript was compared between wild type and mir-243 worms by real-time PCR. The relative expression ratios are the average of three biological replicates, using three different genes as controls .Y47 siRNAs do not act (0.15 MB TIF)Click here for additional data file.Table S1Overview of small RNAs found in the immunoprecipitate libraries of ALG-1, ALG-2, and RDE-1compared to those found in the library made of total small RNAs Click here for additional data file.Table S2Cloning frequencies of microRNAs found in the libraries made from ALG-1, ALG-2, and RDE-1 immunoprecipitates and in the library from total small RNAs Click here for additional data file.Table S3rde-1 mutant animals.Overview of small RNAs found in the libraries of wild-type (with or without TAP treatment) and (0.04 MB DOC)Click here for additional data file.Table S4mir-243 worms.List of genes misregulated in (0.67 MB XLS)Click here for additional data file.


The results implied possible role of IRF2 in controlling the intricate balance of cellular gene expression under stress conditions in general. Here we have investigated the secondary structure of the Internal Ribosome Entry Site of IRF2 RNA and demonstrated the role of PTB protein in ribosome assembly to facilitate internal initiation.Earlier we have reported translational control of interferon regulatory factor 2 (IRF2) by internal initiation . Deletion of 25 nts from the 3′terminus of the 5′untranslated region resulted in reduced binding with PTB protein and also showed significant decrease in IRES activity compared to the wild type. We have also demonstrated putative contact points of PTB on the IRF2–5′UTR using primer extension inhibition assay. Majority of the PTB toe-prints were found to be restricted to the 3′end of the IRES. Additionally, Circular Dichroism (CD) spectra analysis suggested change in the conformation of the RNA upon PTB binding. Further, binding studies using S10 extract from HeLa cells, partially silenced for PTB gene expression, resulted in reduced binding by other trans-acting factors. Finally, we have demonstrated that addition of recombinant PTB enhances ribosome assembly on IRF2 IRES suggesting possible role of PTB in mediating internal initiation of translation of IRF2 RNA.We have probed the putative secondary structure of the IRF2 5′UTR RNA using various enzymatic and chemical modification agents to constrain the secondary structure predicted from RNA folding algorithm Mfold. The IRES activity was found to be influenced by the interaction of trans-acting factors to mediate internal initiation of translation.It appears that PTB binding to multiple sites within IRF2 5′UTR leads to a conformational change in the RNA that facilitate binding of other  IRF1 function as an activator of IFN and IFN-inducible genes, whereas IRF2 act as repressor of IRF1 action trans-acting factors. Ribosome binding analysis also indicated that supplementation of purified PTB enhanced the formation of translation initiation complex. This led us to hypothesize that PTB interaction with the IRF2 IRES might trigger a change in the conformation that helps in the recruitment of other hitherto unknown trans acting factors and ribosomes, thus facilitating translation initiation.We have partially mapped the secondary structure of the IRF2 5′UTR using various enzymatic and chemical modification probes. The data validates the predicted MFOLD structure of the 5′UTR RNA. To map the putative contact points of the protein on the IRF2 5′ UTR we have performed primer extension inhibition assay. PTB was found to have multiple contact points on the IRF2 RNA, but mostly at the 3′end of the 5′UTR. Since many contact points were found on the 3′ end of the RNA, a deletion mutant was generated, where 25 nt from 3′end was deleted. UV cross-linking and competition experiments showed a reduced binding of the purified PTB on the mutant RNA as compared to the wild type RNA. The above data was supported by Circular Dichroism (CD) spectra analysis of the RNA, which also suggested a change in the conformation of IRF2 5′ UTR in presence of PTB binding. Proteins from whole cell extracts showed that full length IRF2 IRES interacted predominantly with a 57 kDa (PTB) protein, compared to the mutant IRF2. Further PTB silencing experiments showed reduced PTB binding along with significant reduction in binding of other cellular Earlier we have shown that the putative secondary structure of IRF2 5′UTR RNA (predicted by using the MFOLD program) IRF2 monocistronic RNA was generated from the corresponding DNA construct . The RNAin vitro transcribed IRF2 UTR RNA was incubated with RNase T1 followed by extension using AMV-RT (Promega). The products were analyzed on 8% polyacrylamide-8M urea denaturing gel. For precise mapping of the contact points, a DNA sequencing reaction with the same end labeled primer was run alongside . Since IRF2 5′UTR folds into a fairly stable secondary structure, only few specific RT pauses were observed at G8, G44, G59, G69, G83 and G131 , the pauses corresponding to nuclease (TI and VI) cleavage sites and the toe prints corresponding to PTB binding sites were mapped to MFOLD predicted structure for clarity . The res32P labeled wild type IRF2 5′UTR RNA was incubated with 0.87 nM of purified PTB protein in absence and presence of increasing concentrations of the competitor RNAs. The toe-printing data showed that the contact points of PTB are predominantly at the 3′ end of the IRF2 5′UTR RNA. To investigate this further, 25 nucleotides were deleted at the 3′end from the IRF2 5′ UTR to generate mIRF2 . To compSince 3′ deletion mutant showed reduced PTB binding, we hypothesized that this might also affect the IRF2-IRES activity. To investigate it, the deletion mutant was cloned in the bicistronic plasmid construct . Both wiTo further verify the possible conformational change in the RNA upon protein binding CD spectroscopic studies were performed. CD spectra of IRF2 5′UTR RNA was analyzed in absence and presence of purified recombinant PTB protein. CD spectra were obtained in 240 to 320 nm range at 20°C in 0.5 ml RNA binding buffer. The results showed distinct change in the wavelengths at which the peak of ellipticity value is reached for RNA incubated with PTB (260 nm) compared to RNA alone (256 nm). Also, at this particular wavelength there was significant increase in the ellipticity value suggesting a change in the conformation of the IRF2 5′UTR RNA in presence of PTB . Interes32P labeled Wt and mIRF2 UTR RNAs were incubated with the extracted total proteins, UV-crosslinked and analysed on SDS-PAGE. The results indicated that wtIRF2 5′UTR interacted strongly with 57 kDa protein (PTB), whereas with mIRF2 5′UTR the intensity of the band corresponding to 57 kDa protein was relatively less. Interestingly, the mIRF2 showed binding with additional proteins, some of those could be the cleavage products of PTB (p25), which might negatively influence IRES activity trans acting factors to enhance translation, PTB depleted HeLa S10 was used in UV cross linking study. PTB was partially silenced in HeLa cells by using increasing concentration of siPTB. 36 hours post transfection S10 extracts were prepared. A significant decrease of PTB protein level was observed at 60 nm & 80 nm concentration of siPTB. UV-crosslinking experiment was performed using wt IRF2 RNA probes and S10 extracts from control or siPTB treated cells. Interactions of several cellular proteins were found to be significantly reduced  has been implicated as an important ITAF for a number of viral as well as cellular IRESs. It is believed that PTB has a chaperone like activity that can bring about a change in the conformation of the IRES structure, which might facilitate the interaction of the ribosomes with the RNA leading to efficiently initiate translation.The mechanism of IRES mediated translation in cellular RNA is still not completely understood. Various IRES In this paper, we have investigated the interaction of PTB with the IRF2-IRES RNA and studied its importance on its translation initiation. Multiple contact points were mapped on the IRF2 IRES RNA. A significant number of those contact points were mapped to the 3′ end of the IRES element. In fact, Apaf-1 IRES is also known to have two potential PTB binding sites at the 3′ end region However recent report suggests that the IRES activity might not completely depend on the overall structure but on different sequence modules that play important role in the ITAF recruitment trans acting factors near the vicinity of the translation start site that would facilitate the recruitment of the ribosomes to the RNA and thus facilitating translation initiation. To further consolidate the observation, S10 extract isolated from HeLa cells, partially silenced for PTB expression was used for binding using Wt IRF2 probe. Several cellular tran-acting factors were unable to bind Wt IRF2 in reduced presence of PTB. Interestingly, we found that supplementing the in vitro translation mix with purified PTB marginally enhanced the formation of the 48S ribosomal initiation complex.Nuclease mapping and chemical modifications partly revealed the secondary structure of the IRF2 5′UTR, which largely supports the MFOLD prediction. DMS modification interference assay indicated perturbation of the RNA structure in presence of PTB. The presence of PTB masked the RNA, rendering it inaccessible to DMS modifications at certain places. Also, a few new DMS modification sites were found under such condition, suggesting changes in local structure due to protein binding. CD spectroscopic analysis reinforces the idea of change in RNA conformation upon protein binding. In fact when CD experiment was performed with the mutant IRF2 IRES RNA and the PTB protein, change in molar ellipticity was found to be less than that obtained with the wild type RNA. PTB has been shown to have chaperone like activity, thus it would be interesting to study how its interaction with the IRF2 5′ UTR RNA and consequent change in the RNA conformation helps in ribosome assembly during internal initiation. Also it is possible that such a change in the conformation of the RNA might recruit certain other trans-acting factors that could facilitate IRES mode of translation initiation in the IRF2 mRNA. However, at this stage it is not clear how PTB or other IRES trans-acting factors (ITAFs) interaction helps in switching on the IRES activity of the cellular IRES elements. It could be a complex interplay of PTB and several other ITAFs. Future experiments would be directed to understand how the ITAFs binding directs the ribosome to land preferentially to the IRES site and translate by internal initiation under stress conditions.Thus we hypothesize that PTB serves as an ITAF which recruits other possible No, an ethics statement is not required for this work.The bicistronic constructs containing respective 5′UTR sequences of full length IRF2 (NCBI accession number NM_002199) and 3′ deletion IRF2  were cloned downstream of the landscape of structure derived form the inactive part of ΔEMCV IRES sequence between Renilla luciferase (RLuc) and Firefly luciferase (FLuc) genes, in HindIII and EcoRI sites. The construct pRΔEnullF HeLa S3 cells were maintained in DMEM (Invitrogen) with 10% fetal bovine serum . Cells were transfected with various bicistronic plasmids and pSV40β-gal using Tfx 20 reagent (Promega) and luciferase assay was performed using Dual luciferase assay reagent (Promega). Transfection of siRNA was performed in HeLa S3 cells growing in monolayer using Lipofectamine-2000 transfection reagent and optiMEM-I prepared without addition of antibiotic (Invitrogen). Cells were seeded onto 100 mm dishes in duplicates one day prior to transfection in similar manner. Transfections were performed with 40 nm, 60 nm and 80 nm of siPTB (Dharmacon) or 80 nm of nonspecific si (Dharmacon) diluted with optiMEM-I to a final volume of 100 µl followed by incubation at room temperature for 20 minutes. Subsequently, 4.9 ml of optiMEM-I was added to the transfection mixture, which was then layered onto cells. 4 hours later the medium was replaced with 9 ml of DMEM (with antibiotic) and 10% FBS. 36 hours post transfection the cells were washed with PBS, and were trypsinized followed by HeLa S10 extract preparation. S10 extract was prepared from HeLa cells as described before (22).32P labeled RNA probes corresponding to the 5′UTRs of IRF2 and deletion mutant IRF2 were made from their respective plasmid DNAs after linearizing with EcoRI and transcribed with T7 RNA polymerase and 10 µCi/µl of alpha 32P UTP (NEN) as per manufacturer's guidelines.The IRF2 5′UTR and mIRF2 RNA probes were made from IRF2Fluc and mIRF2Luc DNA plasmids respectively linearized with Eco RI and was transcribed by T7 RNA polymerase. Similarly, the E.coli (BL21 DE3) cells transformed with the expression vector. His-tagged protein was purified using Ni2+-nitrilotriacetic acid-agarose (Qiagen) under non-denaturing conditions and eluted with 250 mM imidazole.The expression of recombinant PTB (NCBI accession number NM_031990) from PET28a-PTB (a generous gift from Dr. J.G. Patton) was induced by 0.6 mM IPTG in in vitro transcribed IRF2 bicistronic RNAs were denatured at 65°C for 10 minutes and then cooled slowly to room temperature. The RNAs were then digested with 0.5 unit of RNase T1 (SIGMA) for 15 minutes at 37°C. After incubation the reaction mixture was treated with proteinase K followed by phenol:chloroform extraction and alcohol precipitation. For RNase V1 (Ambion) digestion, the RNA was incubated with 0.01 units of RNase V1 for 10 minutes at 30°C. After the incubation the reaction mixture was extracted with phenol: chloroform and alcohol precipitated. T1 digestions were carried out in the buffer containing 10 mM Tris.Cl (pH 7.5), 10 mM MgCl2, and 100 mM KCl. The DMS modification was carried out in the buffer containing 50 mM sodium cacodylate (pH 7.5), 5 mM MgCl2, 100 mM KCl at 30°C for 10 minutes using 1 µl of DMS diluted 1∶8 in absolute ethanol. The modified RNAs were precipitated with ethanol. The digested and the modified RNAs were reverse transcribed using AMV RT (Promega) with an end labeled primer annealing to 1–20 at the 5′ end of the firefly luciferase gene. The cDNAs were precipitated with 0.3 M sodium acetate and absolute ethanol and then resolved in a 8M urea-8% Acrylamide gel electrophoresis along with a reference sequencing reaction  using the same end-labeled primer. Similarly, purified PTB bound RNA in buffer was modified with 1 µl of DMS diluted 1∶8 in absolute ethanol at 30°C for 10 minutes The modified RNAs were precipitated with ethanol the modified RNAs were reverse transcribed using AMV RT (Promega) with an end labeled primer annealing to 1–20 at the 5′ end of the firefly luciferase gene and was analyzed as mentioned before.10 µg of in vitro transcribed RNA corresponding to the IRF2 bicistronic RNA (derived from the construct pRIRF2F) and binding reaction was performed in a final volume of 20 µl at 30°C for 20 minutes. Reaction where PTB was not added serve as a negative control. To the reactions, [32P]-end labeled primer complimentary to 20 nucleotides of the 5′ end of the Firefly luciferase was added and allowed to extend using 3 units of AMV-Reverse transcriptase (Promega) at 30°C for one hour. The cDNAs were alcohol precipitated, resuspended and compared with the dideoxynucleotide sequence ladders (obtained using same end-labeled primer) by electrophoresis on a 6% polyacrylamide/8M urea denaturing gel.Increasing concentration of purified his-tagged PTB protein (500 and 800 ng) was incubated with 5 pmoles of 2, 3.8% glycerol, 2 mM DTT, 0.1 mM EDTA). CD spectra were obtained in 240 to 320 nm range at 20°C with IRF2 5′UTR (400 ng) and 800 ng of PTB or bovine serum albumin (BSA).Measurements of CD spectra were performed with a Jasco J-715 spectropolarimeter. Spectra were obtained in 0.5 ml RNA-binding buffer . Briefly, [α-Protein concentration of the S10 extract prepared from HeLa cells were assayed by Bradford (Bio-Rad). Equal amounts of cell extracts were loaded on SDS-10% polyacrylamide gel. The resolved proteins were electro-transferred to nitrocellulose membranes. Samples were then analysed by mouse monoclonal anti-PTB antibody , followed by secondary antibody . Rabbit polyclonal anti-actin (Sigma) was used as control for equal loading of total cell extracts. Antibody complexes were detected using the enhanced chemiluminescence (ECL) detection kit (Amersham Antibodies).32P UTP and the 25 µl reactions containing 17.5 µl RRL (Promega), 1.5 µl of amino acid mix (Promega) and PTB was supplemented as indicated in the figure legends. Labeled RNA 100,000 cpm was used per reaction. The reactions were incubated at 30°C for 20 min. and the volume was made upto 150 µl with the sucrose density gradient buffer . The reactions were overlaid on 5–30% linear sucrose density gradients and centrifuged for 3 hrs at 30,000 rpm using SW41 rotor in Beckman ultracentrifuge. 200 µl fractions were collected from top of the radioactive tube. Counts of each fraction were measured and %cpm was plotted against the fraction number.IRF2 UTR RNA was labeled with We gratefully acknowledge members of our laboratory for their help and suggestions.


Coronaviruses: Molecular and Cellular Biology Coronaviruses are a group of single-stranded RNA viruses that mainly cause enteric and respiratory diseases in infected hosts. Before 2002, coronaviruses were known as important veterinary pathogens, as well as a cause of the common cold in humans. In 2002–2003, with the advent of the outbreak of severe acute respiratory syndrome (SARS), this picture changed. SARS was quickly shown to be caused by a novel coronavirus, and the ensuing explosion of research on coronaviruses is reflected in this new book.This multi-authored book contains 16 chapters and is organized into 2 sections. The first section of 7 chapters covers most aspects of coronavirus replication, from virus binding and entry into the cell to genome packaging. When appropriate, these chapters also draw on recent work with the closely related arteriviruses. Each chapter generally offers excellent and balanced reviews of the coronavirus literature through 2006, with a few references from 2007. The second section of 9 chapters discusses various aspects of the host-pathogen interface of several coronaviruses; the major focus is the SARS coronavirus, although the human coronavirus NL63 and murine, feline, and avian coronaviruses are also covered.This book provides a one-stop entry into current thinking in the field. For those unfamiliar with coronaviruses, the first section offers a current view of how these viruses replicate. Two areas that are not as well represented in this section are effects of coronavirus infection on cellular processes, such as the cell cycle, apoptosis, and other signaling pathways, and protein trafficking, virus assembly, and release. Separate chapters on these areas would have strengthened the book. In some ways, the second section of the book is not as satisfying. The 3 chapters on SARS coronavirus and the chapter on human coronavirus vaccine development have introductory sections that are somewhat repetitive. Including chapters on transmissible gastroenteritis virus and porcine respiratory coronavirus would also have been beneficial. That said, the chapters on SARS and the avian, murine, and feline coronaviruses are excellent. I heartily recommend that this book be placed in the library of every laboratory that is working on this fascinating group of viruses. It will be particularly valuable to newcomers to the field by providing a single entry point to recent thinking about these agents.


The development of protocols for RNA extraction from paraffin-embedded samples facilitates gene expression studies on archival samples with known clinical outcome. Older samples are particularly valuable because they are associated with longer clinical follow up. RNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue is problematic due to chemical modifications and continued degradation over time. We compared quantity and quality of RNA extracted by four different protocols from 14 ten year old and 14 recently archived (three to ten months old) FFPE breast cancer tissues. Using three spin column purification-based protocols and one magnetic bead-based protocol, total RNA was extracted in triplicate, generating 336 RNA extraction experiments. RNA fragment size was assayed by reverse transcription-polymerase chain reaction (RT-PCR) for the housekeeping gene glucose-6-phosphate dehydrogenase (G6PD), testing primer sets designed to target RNA fragment sizes of 67 bp, 151 bp, and 242 bp.Biologically useful RNA  was extracted in at least one of three attempts of each protocol in 86–100% of older and 100% of recently archived ("months old") samples. Short RNA fragments up to 151 bp were assayable by RT-PCR for G6PD in all ten year old and months old tissues tested, but none of the ten year old and only 43% of months old samples showed amplification if the targeted fragment was 242 bp.All protocols extracted RNA from ten year old FFPE samples with a minimum RIN of 1.4. Gene expression of G6PD could be measured in all samples, old and recent, using RT-PCR primers designed for RNA fragments up to 151 bp. RNA quality from ten year old FFPE samples was similar to that extracted from months old samples, but quantity and success rate were generally higher for the months old group. We preferred the magnetic bead-based protocol because of its speed and higher quantity of extracted RNA, although it produced similar quality RNA to other protocols. If a chosen protocol fails to extract biologically useful RNA from a given sample in a first attempt, another attempt and then another protocol should be tried before excluding the case from molecular analysis. For decades, human tissue samples obtained from surgical procedures have been routinely fixed in formalin and embedded in paraffin for long-term storage. Consequently, most institutions have large paraffin-block archives that allow long-term follow up for all types of neoplasms, including rare tumors. These archives represent a valuable source for molecular studies. A major limitation for the use of such samples to study gene expression is three-fold: RNA can degrade prior to formalin fixation; formalin fixation produces significant chemical modification of RNA; and RNA continues to fragment and degrade over time, even after dehydration and paraffin-embedding.Immediate freezing of fresh tissue samples preserves good quality RNA for gene expression studies; however, this procedure is not routinely performed in most hospitals and there are few institutions worldwide that have large frozen-tissue banks associated with long term clinical followup. Moreover, tumor samples accrued into a frozen tissue bank are inherently biased in their collection: such tumors must be sufficiently large and palpable in order for tissue to be excised and frozen for the bank .2OH); methylene bridging then occurs between neighboring bases (N-CH2-N), formed by condensation of amino bases and N-methylols [Formalin-fixed paraffin-embedded (FFPE) samples are universally available and, with Institutional Review Board/Ethics Committee approval, cancer samples can be linked to clinical and/or follow up information, often available through an institution's tumor registry. Extracting RNA from such samples has been a promising but problematic challenge. In addition to RNA degradation concerns, formalin fixation creates cross-linking between nucleic acids and proteins and adds mono-methylol to amino groups for all four RNA bases N-CHOH; methyRupp and Locker described the first successful RNA extraction from FFPE samples in 1988 . Since tMagnetic beads can also be utilized to isolate RNA. In these protocols, nucleic acids are bonded to paramagnetic beads and isolated by a magnetic field. RNA is isolated using an optimized buffer solution and later a DNAse step. Magnetic micro-beads can be prepared in a number of ways, but usually magnetically susceptible particles (e.g. iron oxide) are coated with synthetic or biological polymers with high affinity for nucleic acid. A magnet is applied to the side of the tube containing the magnetically-labeled sample mixture and the magnetically bound nucleic acid aggregates near the wall of the tube, allowing the unlabeled materials to be pipetted off and discarded. In addition to quickly separating magnetically-bound nucleic acid, this method does not create the shear forces generated by spin centrifugation that may lead to nucleic acid degradation .Breast cancer tissue RNA archived for one year is less degraded and has larger average molecular weight than RNA archived for six and 17 years, suggesting that fragmentation of FFPE tissue continues even after specimens are dehydrated and embedded in paraffin . Many moTable In the set of ten year old samples Tables  and 5, pFor the set of recently archived months old samples Tables  and 6, pRT-PCR for the housekeeping gene glucose-6-phosphate dehydrogenase (6GPD) was performed using primers that targeted different fragment sizes of extracted RNA. All samples from both one and ten year old sets successfully amplified 67 bp and 151 bp fragments of G6PD mRNA. However, when primers targeting 242 bp fragments were tested, only six of 14 (43%) months old FFPE samples and none of the ten year old samples demonstrated G6PD gene expression , but easy to use. We personally appreciated the speed and quantity of RNA extracted using Protocol 4.In conclusion, although the magnetic bead-based protocol extracted more RNA than spin column-based protocols, all protocols were able to extract RNA with a minimally acceptable quality from ten year old archived FFPE samples. Although the quality of RNA extracted from ten year old FFPE was similar to the RNA extracted from recently archived months old samples, the quantity, consistency and success rate was higher in the months old group. The RNA extracted from FFPE is suitable for RT-PCR analysis if the final product of amplification is up to 151 bp, with a success rate of 100% for both ten year old one and months old samples. If a chosen protocol fails to extract RNA from a given case in a first attempt, another extraction and then an alternative protocol should be attempted before excluding this case from further molecular analysis.The study conformed to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ribeirão Preto local Ethics Committee, Brazil, and Stanford University. Twenty-eight paraffin blocks containing breast cancers diagnosed in 1997  and 2007  were retrieved from the archives of the Pathology Service of the General Hospital of Ribeirão Preto Medical School, University of São Paulo, Brazil. Each block contained one piece of breast cancer tissue measuring at least 1.5 × 1.5 cm in area. Using a conventional microtome (Leica RM2125), histological sections 10 microns in thickness were cut from each block according to protocol specifications  [All protocols were performed according to Manufacturer's instructions using their specified input of FFPE tissue sections Table . Protocolla, CA) . Briefly® "FormaPure™ Kit"  [®) paramagnetic bead-based technology to isolate RNA from a maximum input of 10 mg of FFPE tissue . Similar to other protocols, a reagent (lysis buffer provided by the kit) is added to melt the paraffin and de-crosslink nucleic acids, and Proteinase K is added to complete tissue digestion and inactivate nucleases (60 minutes incubation time at 55°C). Contrary to the other three protocols, binding buffer is added to facilitate immobilization of the nucleic acids to the surface of paramagnetic beads and separation is magnetically-performed. This protocol does not require centrifugation.Protocol 4 utilized the Agencourtrly, MA)  followedThe RNA extraction from each of the 28 cases was done in triplicate: 84 extractions per protocol for each of the four protocols, for a total of 336 RNA extraction procedures.The RNA extracted in triplicate from the 28 breast cancer samples using the four protocols was analyzed (n = 336) for quantity and quality. To rapidly quantify RNA, the Agilent 2100 Bioanalyzer , a chip-based nucleic acid separation system, was used. The Bioanalyzer utilizes a combination of micro-fluidics, capillary electrophoresis, and fluorimetry to determine RNA length, distribution and concentration ,23. The et al.[To determine fragment sizes of RNA extracted from archival FFPE specimens, we targeted the housekeeping gene G6PD with different mRNA primer sets and performed RT-PCR as described by Liu et al.. From eaAll primers were designed by Liu et al. One sense primer (5'-GGC AAC AGA TAC AAG AAC GTG AA) and three antisense primers were used such that combinations of these primers would generate PCR amplicons of 67 bp (5'-CGC AGA AGA CGT CCA GGA T), 151 bp (5'-CCA GCT CAA TCT GGT GCA G), and 242 bp (5'-CCC TCA TAC TGG AAA CCC ACT), respectively. The sense primer was cleverly designed by Liu et al. to span two exons so that it would not anneal to or amplify genomic DNA.Multiplex RT-PCR was carried out using Superscript™III One-Step RT-PCR with Platinum Tag system  and optimized using Universal Human Reference RNA  prior to testing samples. The template consisted of 0.2–2 μg of RNA from the months old samples, depending on RNA quantity extracted, or 100 pg of RNA from 10 year old samples. Each reaction contained 250 pmol of sense primer and 100 pmol of each antisense primer. The first reverse transcription step was performed at 50°C for 30 min. The following PCR steps was carried out using a ''hot-start and touch-down'' program of 94°C for 2 minutes, followed by 1 cycle of denaturing at 94°C for 30 seconds, annealing at 66°C (one degree down per cycle until 59°C is reached) for 30 seconds, and extension at 68°C for 45 seconds, and then 30 cycles of 94°C for 30 seconds, 58°C for 30 seconds, and 68°C for 45 seconds. A final extension was performed at 68°C for 10 minutes. PCR products were analyzed by electrophoresis on 2% agarose gels and visualized using ethidium bromide staining. Fragments that were not visible on the gel by multiplex RT-PCR were reassessed by PCR with single sets of primers using the first RT-PCR product as template.FFPE = formalin-fixed paraffin-embedded; G6PD = glucose-6-phosphate dehydrogenase; RIN = RNA integrity number; RT-PCR = reverse transcription-polymerase chain reactionARS and SSJ conceived the study. ARS obtained the FFPE samples, performed the RNA extraction, and evaluated the quantity and quality of the extracted RNA. HZ optimized and performed the RT-PCR procedures. ARS and SSJ analyzed the data. ARS, HZ, and SSJ wrote the manuscript and approved the final manuscript.


Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters.We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane) showed the accuracy of 82%.The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters. Membrane proteins perform a diverse variety of functions, including the transport of ions and molecules across the membrane, bind to small molecules at the extra cellular space, recognize the immune system and energy transducers. The functional annotation of membrane proteins in genomic sequences is an important problem in bioinformatics and computational biology. Membrane transporters are a large group of proteins that span the cell membrane and form an intricate system of pumps and channels through which they deliver essential nutrients, eject waste products and assist the cell to sense environmental conditions. Transporters represent a large and diverse group of proteins that differ in membrane topology, energy coupling mechanism and substrate specificities . They plSeveral methods have been proposed to discriminate membrane proteins from amino acid sequence information. These methods include statistical analysis -5, hiddeIn this work, we have analyzed the characteristic features of amino acid residues in major transporters, such as, channels/pores, electrochemical potential-driven transporters and primary active transporters. We have utilized different machine learning techniques for discriminating these classes of proteins and achieved the 5-fold cross-validation accuracy of 68%. The sensitivity of correctly identifying channels/pores, electrochemical and active transporters are, 55%, 70% and 76% respectively, in a set of 510, 502 and 706 proteins. The classification of channels and pores has been carried out, which showed the accuracy of 92%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins, and from all other proteins (globular and membrane) to the accuracy of 85% and 82%, respectively. Further, the influence of chain length for discrimination will be discussed.We have constructed datasets for channels/pores, electrochemical transporters and active transporters from the information available in Transport Classification Database, TCDB . The TCDThe amino acid composition for the set of transporters has been computed using the number of amino acids of each type and the total number of residues. It is defined as:i is the number of residues of each type and N is the total number of residues. The summation is through all the residues in all the considered proteins. The same procedure was repeated for all the three groups of transporters for obtaining their amino acid composition. The total number of residues in the datasets of channels/pores, electrochemical and active transporters are respectively, 259,143, 252,585 and 289,109.where i stands for the 20 amino acid residues, nThe amino acid occurrence is the actual number of amino acid residues of each type present in a protein without normalizing with chain length.We have performed a 5-fold cross-validation test for assessing the validity of the present work. In this method, the data set is divided into five groups, four of them are used for training and the rest is used for testing the method. The same procedure is repeated for five times and the average is computed for obtaining the accuracy of the method.In jack-knife test, n-1 data are used for training and the prediction is made on the left-out protein. This procedure is repeated for n times and the average is computed for obtaining the accuracy.We have used different measures, such as specificity, precision, F-measure and accuracy to assess the performance of discriminating channels/pores, electrochemical and active transporters. The term sensitivity shows the correct prediction of specific transporters and accuracy indicates the overall assessment. F-measure is the balance between sensitivity and precision, 1/F = [(1/Sensitivity) + (1/Precision)]/2. These terms are defined as follows:Sensitivity = TP/(TP+FN)Precision = TP/(TP+FP)F-measure = (2 × Sensitivity × Precision)/(Sensitivity + Precision)= 2TP/(2TP+FP+FN)Accuracy = (TP+TN)/(TP+TN+FP+FN),where, TP, FP, TN and FN refer to the number of true positives, false positives, true negatives and false negatives, respectively.We have analyzed several machine learning techniques implemented in WEKA program  for disc12; CN-Cbl) binding pocket [The amino acid composition for the 20 amino acid residues in channels/pores, electrochemical and active transporters have been computed using Eqn. 1 and the results are presented in Table g pocket ,16, whicg pocket . Glu is g pocket . The comThe residues Phe and Leu are dominant in electrochemical transporters. In addition, the composition of Ala, Ile, Val and Trp are higher in this class of proteins compared with other two transporters. Interestingly, in glycerol-3-phosphate transporter the space between helices 1 and 7 is filled by nine aromatic side chains and the occurrence of bulky aromatic residues helps to close the pore completely . In lact12 binding protein [In active transporters none of the residue has the highest or lowest occurrence. All the residues have the composition, which lies between the compositions of channels/pores and electrochemical transporters. However, Glu, Gln, Phe, Arg and Lys are close to channels/pores whereas Ala, Asn, Thr and Tyr are close to electrochemical transporters. The structural analysis on high-potential iron-sulfur protein shows that the electron transfer is mainly achieved by hydrophobic interactions . In addi protein .We have analyzed the three-dimensional structures of transporters deposited in TCDB and derived the propensity of the 20 amino acid residues to be in the membrane part. This has been computed by the ratio between the occurrence of each amino acid residue in the membrane part and the respective residue in the whole protein. The results obtained for channels/pores, electrochemical and active transporters are presented in Table We have analyzed the performance of different machine learning methods for discriminating channels/pores, electrochemical and active transporters and the results obtained with amino acid composition are presented in Table Further, this analysis showed a moderate difference in the performance of different machine learning methods (the accuracy varies from 60% to 66% in most of the methods). The main cause of obtaining different prediction results might be due to the usage of different adjustable parameters in these methods.The performance of different machine learning methods for discriminating channels/pores, electrochemical and active transporters with amino acid occurrence as features has been analyzed and the results are presented in Table The comparison of results presented in Tables When compared the performance of different machine learning methods, unlike amino acid composition, several methods showed poor sensitivity for channels/pores with occurrence. For example, Naïve Bayes showed the sensitivity of 0.20 and 0.76, respectively for channels/pores and electrochemical transporters. However, several methods  showed good performances with similar sensitivity in all three classes of transporters.We have analyzed the capability of BLAST to discriminate the three different types of transporters based on homology search. For each protein we have computed the sequence identity with all proteins in the three transporters and assigned the group, which has the highest sequence identity or best e-value. The calculations have been repeated for all the 1708 proteins and computed the overall accuracy. This method showed an accuracy of 51.6% in discriminating channels/pores, electrochemical and active transporters. Our method showed the accuracy of 75%, which is superior to simple BLAST search and the analysis revealed the better performance of the present method.The amino acid composition of active transporters is in the range between that of channels/pores and active transporters Table . Hence, Proteins in the category of channels/pores have transmembrane channels, which consists of α-helical and β-strand spanning segments . Hence, We have developed a dataset of 3336 membrane proteins with less than 20% sequence identity that includes receptors and all other types of α-helical and β-barrel membrane proteins except transporters from SWISS-PROT database. Using a dataset of 3336 non-transporters and 1718 transporters we have analyzed the performance of different machine learning algorithms and the k-nearest neighbor could discriminate the transporters with the 5-fold cross-validation accuracy of 79.1%. The sensitivity and specificity are 69.2% and 84.2%, respectively. Further, we have repeated the computations with equal number of transporters and non-transporters and obtained the accuracy of 85.0%. The jack-knife test also showed similar results that we obtained with 5-fold cross-validation method.In addition, we have set up a dataset for 5048 proteins, which include membrane transport proteins and other membrane and globular proteins. We obtained a 5-fold cross-validation accuracy of 78.7% in discriminating transporters and non-transporters. Further, we have used the same number of proteins in transporters and non-transporters and repeated the calculations. We obtained the accuracy of 81.5% in distinguishing them, and both jack-knife test and 5-fold cross-validation method showed similar performance on discrimination.We have developed web servers for (i) discriminating membrane transport proteins from all other membrane and globular proteins  and (ii)The following procedure may be used to detect the type of a new protein. First the new sequence can be identified as a transporter or non-transporter using the discrimination method to classify them (previous section). It has been shown that the transporters and non-transporters are discriminated with the highest accuracy of 82%. For a transporter, it can be further identified into channels/pores, electrochemical and active transporters with an accuracy of 68%. Alternatively, several methods have been reported in the literature for discriminating globular proteins from α-helical ,28-30 orWe have systematically analyzed the amino acid compositions of channels/pores, electrochemical and active transporters and revealed the similarities and differences among them. Different machine learning algorithms have been tested to discriminate these transporters and we achieved the highest accuracy of 68% using neural network with amino acid occurrence. Further, we have examined the discrimination performance between two classes of transporters, which showed the highest accuracy of 87% between channels/pores and electrochemical transporters. In addition, the channels and porins are discriminated with the accuracy of 92%. On the other hand, the transporters and other membrane proteins/all other globular and membrane proteins are discriminated with the accuracy of 85% and 82%, respectively. We suggest that this method could be effectively used to discriminate transporters and different classes of transporters in genomic sequences.Project name: Functional discrimination of membrane proteinsProject home page: Operating system(s): Platform independentProgramming language: JavaLicence: No restrictionAny restriction to use by non-academics: No restrictionMMG conceived the project, carried out the computations and analysis, and wrote the manuscript. YY prepared the datasets and took part in computations. All authors read and approved the final manuscript.