C. elegans, by motoneuron photostimulation and muscular RCaMP Ca2+ imaging. We verified our approach on mutants affecting synaptic transmission. Mutation of genes affecting SV recycling  showed a distinct ‘signature’ of muscle Ca2+ dynamics, induced by cholinergic motoneuron photostimulation, i.e. faster rise, and earlier decrease of the signal, reflecting increased synaptic fatigue during ongoing photostimulation. To facilitate high throughput, we measured (3–5 times) ~1000 nematodes for each gene. We explored if this method enables RNAi screening for SV recycling genes. Previous screens for synaptic function genes, based on behavioral or pharmacological assays, allowed no distinction of the stage of the SV cycle in which a protein might act. We generated a strain enabling RNAi specifically only in cholinergic neurons, thus resulting in healthier animals and avoiding lethal phenotypes resulting from knockdown elsewhere. RNAi of control genes resulted in Ca2+ measurements that were consistent with results obtained in the respective genomic mutants, albeit to a weaker extent in most cases, and could further be confirmed by opto-electrophysiological measurements for mutants of some of the genes, including synaptojanin. We screened 95 genes that were previously implicated in cholinergic transmission, and several controls. We identified genes that clustered together with known SV recycling genes, exhibiting a similar signature of their Ca2+ dynamics. Five of these genes  were further assessed in respective genomic mutants; however, while all showed electrophysiological phenotypes indicative of reduced cholinergic transmission, no obvious SV recycling phenotypes could be uncovered for these genes.Synaptic vesicles (SVs) undergo a cycle of biogenesis and membrane fusion to release transmitter, followed by recycling. How exocytosis and endocytosis are coupled is intensively investigated. We describe an all-optical method for identification of neurotransmission genes that can directly distinguish SV recycling factors in  This SV protein interacts with the SNARE complex as well as the active zone membrane to trigger the actual fusion event ,zxIs6,unc-47(e307); zxIs3,unc-49(e407); zxIs6,unc-26(s1710); zxIs6,unc-47(e307); zxIs6,snt-1(n2665); zxIs3,ZX1489: +]; zxIs52[pmyo-3::RCaMP1h],unc-47(e307); zxIs6; zxIs52[pmyo-3::RCaMP1h],unc-49(e407); zxIs6; zxIs52[pmyo-3::RCaMP1h],snb-1(md247); zxIs6; zxIs52[pmyo-3::RCaMP1h],unc-47(e307); zxIs3; zxIs52[pmyo-3::RCaMP1h],snt-1(md290); zxIs3; zxIs52[pmyo-3::RCaMP1h],zxIs3,ZX1513:rde-1(ne219); zxIs59,ZX1514:rde-1(ne219); zxIs58; zxIs59,ZX1600:+],inx-10(ok2714); zxIs6,ZX1603:+],C27B7.7(ok2978); zxIs6,spp-10(gk349); zxIs6,unc-2(ra612); zxIs6,unc-17(e113); zxIs6,ZX1610:unc-2(ra612); zxIs58,ZX1611:inx-10(ok2714); zxIs58,ZX1613:erp-1(ok462); zxIs58,ZX1616:spp-10(gk349); zxIs58,ZX1617:inx-8(gk42); zxIs58,ZX1631: unc-26(s1710); zxIs58,ZX1632:unc-57(e406); zxIs58,ZX1633:snt-1(md290); zxIs58,ZX1634:unc-38(x20); zxIs58,ZX1635:unc-13(e1091); zxIs58,ZX1636:zxIs58,ZX1655:unc-25 (n2569); zxIs3[punc-47::ChR2(H134R)::YFP]; zxIs52[pmyo-3::RCaMP1h],ZX1659:+]; zxIs52[pmyo-3::RCaMP1h],zxIs6; zxIs52 [pmyo-3::RCaMP1h],zxIs3,ZX1796unc-41(e1199); zxIs58,ZX1797ehs-1::YFP],ZX1799itsn-1(ok268); zxIs58,ZX1800:rde-1(ne219); zxIs59; zxEx847[punc-119::YFP],ZX1971:+]inx-8(gk42); zxIs6[punc-17::ChR2(H134R)::YFP; lin-15.rde-1 cDNA. Following double digest using PspOMI and NheI, rde-1 was retrieved and subcloned into vector pSH122, containing the unc-17 promoter [To express SID-1 pan-neuronally, we used plasmid punc-119::sid-1  : ornai13 (5’-TCTCGCCATGTCCTGTTTCG-3’), ornai14 (5’-TGTGCTCCAAGAGCCAAAG-3’); inx-8 (gk42): ornai 23 (5’-GACAGATGGCAAGGGTTC-3’), ornai52 (5’-CACCGGGTAATTCTACTACTCG-3’); inx-10(ok2714): ornai31 (5’-GCTTCTCCATTAAATCTTGTGTTG-3’), ornai32 (5’-AAATCCAGCGATGCAACA AT-3’); erp-1(ok462): ornai43 (5’-TGATCACTTTGGCTTGCTTG-3’), ornai44 (5’-CCAGTAATTTCGTCCGTCG T-3’); itsn-1(ok268): ornai54 (5’-GAATTGTGTCACCGACATGC-3’) ornai56 (5’-GCACAACGTCAGCAACG AG-3’).2 blue light, unless otherwise stated. Image acquisition was performed using μManager [2+ imaging of single animals, they were immobilized on 10% M9 agar pads with polystyrene beads  [Fluorescence measurements were carried out on an inverted fluorescence microscope  equipped with two high-power light emitting diodes  coupled via a beam splitter to obtain simultaneous dual-wavelength illumination. Excitation light was passed through a double band pass excitation filter (479 and 585 nm), combined with a 605 nm beam splitter and a 647 nm emission filter . Blue light illumination protocols  were programmed on, and generated by, a Lambda SC Smart shutter controller unit , using its TTL output to drive the LED power supply. ChR2 stimulation was performed using 1.4 mW/mmμManager . For Ca2es, USA) .S1 Fig).M9 buffer was used to dissolve 10% (w/v) agar by boiling in a microwave oven. Microscope slides were prepared according to . The agaAnimals were washed off the culture dish with 1 ml of M9 buffer, and collected in a 1.5 ml eppendorf tube. Animals were allowed to settle for 5–10 minutes. 60 μl of the worm “sediment” at the bottom of the tube were transferred to a tube containing 1 ml of fresh M9 buffer, then animals were centrifuged at 2800 rpm for 2 min. Micro-wells were filled with 2x 3.5μl worm pellet.trans retinal , and 10 adult animals from the respective first culture dish were transferred onto the new culture dish and their progeny cultivated for 4  days.RNAi clones were picked from the Ahringer bacterial RNAi feeding library  (or in f0 = (Fi-F0)/F0, where Fi represents the intensity at this time point and F0 represents the average of the first 20 time points during blue light stimulation. For bulk measurements videos of the whole field of view were acquired. Analysis was performed by taking the whole micro-well, filled with animals, as one ROI. Mean fluorescence values were corrected for the intensity increase during blue light stimulation. To this end, the difference between the average of the last 30 frames before, and the first 20 frames during blue light stimulation was subtracted from data points during blue light stimulation. Traces were normalized by ΔF/F0 = (Fi-F0)/F0, where Fi represents the intensity at that time point and F0 the baseline as average from the first 30 frames before blue light stimulation. To take into account that peak fluorescence was not reached precisely at the same time for biological replicates, the traces were peak-normalized, then averaged, and again peak normalized, such that difference traces could be calculated between RNAi animals and the respective animals treated with empty RNAi bacteria (see ). Data analysis was carried out in either Excel  or Prism software . To distinguish significantly different behavior in RNAi animals compared to controls, we used 2-way ANOVA, with Bonferroni correction, across the entire time course, for the 3–5 replicates of the experiments for each gene, and the respective controls analyzed on the same day. An R script to generate color-coded graphs was kindly provided by C. Schultheis. Hierarchical clustering was performed using the Excel add-in collection XLSTAT . Clustering was done using agglomerative hierarchical clustering (AHC), with dissimilarity determined as Manhattan distances, with complete linkage, and defining 6 classes.Image analysis was performed in ImageJ (NIH). Analysis of immobilized single animals was done using a region of interest (ROI) placed around the animal and a second ROI for background fluorescence. Mean intensity values for each video frame were obtained and background fluorescence was subtracted from the fluorescence values derived from RCaMP expressed in body wall muscle cells (BWMs). Subtracted data was normalized to ΔF/FTo quantify YFP expression we imaged animals fed with “empty” RNAi feeding vector, L4440, versus those fed with the respective anti-GFP RNAi dsRNA producing bacteria (likewise targeting YFP), using identical microscope settings. We took the background-corrected absolute fluorescence values over the whole ventral nerve cord, and averaged this for several animals. To image and assign individual ventral cord neurons (i.e. GABAergic and cholinergic motoneurons), we imaged the animals under a spinning disk confocal microscope (Zeiss Cell Observer SD) and produced maximum projection z-stacks, again using identical microscope settings for control strain and GFP-RNAi animals.C. elegans Ringer’s , 340mOsm) and washed with CRG. Cells were clamped to a holding potential of -60mV using an EPC10 amplifier with head stage and Patchmaster software . The bath solution was CRG, the pipette solution was 115 mM K-gluconate, 25 mM KCl, 0.1 mM CaCl2, 5 mM MgCl2, 1 mM BAPTA, 10 mM HEPES, 5 mM Na2ATP, 0.5 mM Na2GTP, 0.5 mM cAMP, 0.5 mM cGMP, pH 7.2, with ∼320 mOsm KOH. Light activation  was performed using an LED lamp at a wavelength of 470nm  and controlled by Patchmaster software . For data analysis MiniAnalysis  and Origin  software were used.Electrophysiological recordings from dissected BWMs were essentially performed as described previously . After dFig 1A), enabling simultaneous ChR2 induced neuronal hyperstimulation and Ca2+ imaging [Fig 1B). As shown previously, photostimulation of cholinergic motoneurons in different mutant backgrounds results in specific contraction profiles over time [unc-26 synaptojanin or unc-57 endophilin) show a progressively decreasing contraction, as SVs become depleted . Mutants affecting GABA signaling (like the post-synaptic GABAA receptor unc-49) similarly show stronger contractions. We verified that expression of RCaMP did not alter BWM physiology, as contractions caused by ChR2 stimulation of cholinergic motoneurons were normal . We next performed Ca2+ imaging experiments in animals in which cholinergic neurons were stimulated for 60s in wild type or mutant backgrounds lacking GABAergic inhibition (unc-49(e407) GABAAR and unc-47(e307) pre-synaptic vesicular GABA transporter (vGAT); Fig 1E). Muscle Ca2+ signals reached a maximum (~20% ΔF/F0) within 7 s, then declined within the next 20 s ; in control animals, cultivated without the ChR2 chromophore all-trans retinal (ATR), no obvious change in the Ca2+ signal occurred. To obtain more robust data, particularly during an RNAi screen, we used small wells in an agarose matrix , enabling simultaneous imaging of ~1000 tightly packed animals, which can be imaged essentially in the same focal plane, using a low magnification (10x) objective . When cholinergic neurons were photostimulated in such mass analyses for 120 s, muscle Ca2+ signals reached a ~10% maximum ΔF/F0 within 20 s, and declined during the next 100 s ; in animals cultivated without ATR, no obvious Ca2+ signals were seen. When stimulating GABAergic motoneurons, Ca2+ signals dropped, both in single animal or mass measurements . Consequently, in unc-47(e307) vGAT mutants, or in unc-49(e407) GABAAR mutants, higher Ca2+ increases, or smaller Ca2+ decreases were obtained upon cholinergic or GABAergic motoneuron stimulation, respectively . This is consistent with more pronounced contraction upon cholinergic neuron stimulation . In mutants lacking all GABA (unc-25(n2569), encoding glutamic acid decarboxylase—GAD), no obvious reduction in muscle Ca2+ signal was observed upon 120 s GABA neuron stimulation . In snt-1(md290) mutants of synaptotagmin, required for SV exocytosis and recycling [2+ decrease was seen upon GABAergic stimulation , in agreement with our previous electrophysiological analysis [RCaMP-mediated Optogenetic Investigation of Neurotransmission).To monitor synaptic transmission in an all-optical manner, we expressed RCaMP in body wall muscle cells (BWMs) combined with ChR2 in cholinergic or GABAergic motoneurons . We wanted to compare observed Ca2+ responses and our previous behavioral and electrophysiological characterizations [S4 Fig; compare to Fig 1C). Next we compared Ca2+ traces of several mutants in their response to cholinergic motoneuron stimulation with the wild type . Fluorescence was analyzed as ΔF/F0 after correcting for the baseline shift induced by the ChR2 stimulation blue-light , averaging fluorescence from the whole micro-well (S1 Video). This allowed comparing the extent of signaling from neuron to muscle, and possibly also reflected muscle excitability. In addition, to allow a better comparison of Ca2+ dynamics, we normalized the data of mutant and wild type traces to the peak values . The corresponding peak-normalized Ca2+ traces of mutant and wild type were compared by 2-way ANOVA with Bonferroni correction, to identify significantly different Ca2+ dynamics; all genes analyzed in Fig 2B–2G met this criterion. Impairments in SV loading (unc-17(e113); vesicular acetylcholine transporter, vAChT [unc-13(e1091) [2+ increases, while peak-normalized traces showed an earlier fatigue . Impairment of pre-synaptic Ca2+ signaling (unc-2(ra612); voltage-gated Ca2+ channel, VGCC [2+ response, with otherwise normal Ca2+ dynamics . Defective transmitter release (snt-1(md290); synaptotagmin [unc-38(x20); nicotinic acetylcholine receptor subunit, nAChR [2+ response . Endocytosis defects, impairing SV recycling (unc-57(e406) endophilin, unc-26(s1710) synaptojanin [2+ signals during long-term stimulation compared to wild type animals . This was accompanied by a faster and earlier (> 20 s) appearing fatigue, as compared to other pre- or post-synaptic mutations, apparent also in contraction assays . We also analyzed these mutants in electrophysiological assays. Cholinergic neurons were photostimulated at 0.5 Hz, and post-synaptic currents were recorded . This showed largely reduced or essentially abolished post-synaptic currents in unc-2(ra612) or unc-17(e113) mutants, respectively. For unc-26(s1710) synaptojanin mutants, currents were progressively getting smaller, demonstrating the SV recycling deficit in these animals.To evaluate whether our all-optical system for analyzing synaptic transmission defects will enable assessing the likely nature of the defect  in bulk Caizations . As we iizations . The perr, vAChT ), or in 3(e1091) –52) did el, VGCC ), causedtotagmin , 55), ast, nAChR , 57) ledptojanin , 17, 58)2+ is not clear. Previously we showed that in snb-1 and unc-13 mutants, which release very little ACh (based on postsynaptic patch clamp measurements of evoked release), muscle cells exhibit a strongly increased excitability, probably as a compensatory effect [2+ signals, represents a distinctive feature that may well serve to identify such mutants. For example, consistent with its additional role in endocytosis, faster onset and earlier fatigue were also observed in the synaptotagmin mutant .Why some pre-synaptically compromised mutants even show a more pronounced and/or faster rise in post-synaptic Cay effect . ImportaC. elegans by feeding E. coli expressing double-stranded RNA homologous to the mRNA of interest [rde-1(ne219) mutants that are defective in RNAi [Fig 4A). To verify that our RNAi strain allowed cell-type specific RNAi, we expressed YFP pan-neuronally, and fed RNAi bacteria specific for GFP . Compared to transgenic control animals, YFP expression in the nerve cord was significantly reduced by 66% . This reduction could be attributed to cholinergic motoneurons, and their processes, which are representing ~75% of the cell bodies in the ventral nerve cord (56 cholinergic vs. 19 GABAergic motoneurons). To assess whether RNAi treatment decreased YFP expression specifically in cholinergic motoneurons, we used confocal imaging . Almost no cholinergic cell bodies, but all GABAergic cell bodies in the nerve cord could be detected, while in control animals, YFP expression was strong in all nerve cord neurons, including the numerous cholinergic cell bodies and neuron processes.RNAi can be conveniently achieved in interest , 60. Howinterest , 61, 62.interest . To thisinterest . We used in RNAi , and res2+ traces increase faster than wild type (as for example in unc-26 synaptojanin SV-recycling mutants), and becomes negative (shades of blue) when mutant Ca2+ levels drop below wild type controls . We compared RNAi knockdown to respective mutants for the following genes : unc-2 , unc-26 synaptojanin , unc-57 endophilin , unc-41 stonin , snt-1 synaptotagmin , snb-1 synaptobrevin (SNARE protein required for fusion), and unc-18 . While unc-2(ra612) ) showed inconclusive Ca2+ difference traces, and the period of positive Ca2+ signals was longer than 20 s, endocytosis/SV recycling factors unc-26(s1710), unc-57(e406), snt-1(md290) and itsn-1(ok268) exhibited a fast rise (0–20 s) and fast decay (> 20 s) of Ca2+ signals, reflected by the color-coded difference graph . This was comparable in RNAi animals for unc-26, snt-1 and itsn-1 , although the extent of the effects was most robust for unc-26 RNAi. RNAi, but not mutation of the stonin unc-41(e1199) showed a very weak SV recycling signature, compared to unc-26, unc-57, itsn-1 and snt-1, while the priming factor unc-18(e234) exhibited no such signature. Overall, mutant phenotypes and RNAi phenotypes matched relatively well, while the extent of the effects was mostly different . We also analyzed the ehs-1(ok146) mutant, encoding an Eps15 homolog (involved in SV recycling together with ITSN-1), and dyn-1 dynamin RNAi animals, that also exhibited this signature .We next compared several mutants affecting synaptic transmission, and particularly, in endocytosis and SV recycling, in our all-optical assay, to the equivalent RNAi knockdown animals using the cholinergic neuron RNAi-sensitized strain. In order to be able to quickly assess the data, particularly for high-throughput screening, we devised a color-coded representation. To this end we subtracted the peak-normalized traces of mutant / knockdown animals from the respective wild type / control animals. The resulting difference trace is positive (shades of red) when mutant Ca and SVs ), and itecycling ). In addunc-17(e113) mutants, affecting the vesicular ACh transporter, showed Ca2+ dynamics that were similar to the SV recycling signature, i.e. a positive Ca2+ difference trace at early time points (5–25 s), and a decay below wild type at > 20–25 s (unc-17 mutant and RNAi differed slightly). As the SV cycle is a circular process, it is not obvious at which stage a bottleneck, leading to progressive SV depletion, is situated. vAChT is responsible for SV filling with ACh, thus reduction of its function would likewise lead to more and more empty vesicles upon excessive synaptic activity, with the same (post-synaptic) consequence as a SV recycling defect. In contrast, a reduced or blocked activity of UNC-18, which prime or fuse SVs, would not alter the amount of  SVs available, as less SVs are fused, but also less SVs need to be recycled. So no progressively exacerbating phenotype is expected for such mutants, as seen in our assays . In a reverse genetic screen, we expect to find both mutants affecting SV endocytosis and recycling, as well as filling and priming, and our assays may suffice for an initial distinction, if the recycling phenotype is strong. The progressive decay of transmitter release must then be further assessed by electrophysiological recording .Interestingly, S1 Table): 11 were random picked genes with no known role in synaptic transmission. Among the other 95 genes, we included five known SV recycling factors  as well as four genes known or expected to be involved in endocytosis  while for the remaining 86 genes, though they were previously implicated in cholinergic synaptic transmission, based on pharmacological  assays and systemic RNAi [rab-5). We reasoned that our approach of restricting RNAi to cholinergic neurons may avoid lethality and/or uncover functions specifically in cholinergic synaptic recycling. We included two genes that were shown to generate aldicarb hypersensitivity when depleted, acting in GABAergic transmission (goa-1 Gαo and unc-43 CaMKII). Last, one postsynaptic aldicarb resistance gene , and one general trafficking gene, the kinesin unc-104, were assessed.We used our approach to perform a pilot RNAi screen in our cholinergic neuron sensitized strain. We chose 106 genes for this screen , and the data for the positive control SV-recycling mutants we included is shown in Fig 6A, compared to the respective RNAi animals. We used hierarchical clustering to sort the genes according to observed phenotypes . The mutants and respective RNAi strains of the known SV recycling genes  essentially clustered in two classes, where genomic mutants and RNAi animals were separated, apart from unc-26 (synaptojanin) RNAi, which was very similar to the unc-26(s1710) mutant. unc-57(e406) endophilin was sorted between the two clusters. The RNAi knockdowns  were clustered into 6 groups. The largest group (66 genes), class #1 (S1 Table), contained all the known SV recycling genes that we included , as well as other endocytosis genes like adapter protein complex 2 components apa-2 [aps-2 (σ2 subunit) [erp-1) and dynamin dyn-1. Based on the clustering algorithm used, 57 additional genes in class #1 exhibited a Ca2+ dynamics signature that resembled the ‘SV recycling signature’, i.e. earlier peak Ca2+ signals and earlier onset of fatigue.The data obtained for all genes was first analyzed for significant changes compared to the respective ‘empty’ RNAi feeding vector control. Of the 106 genes, 10 did not meet significance (2-way ANOVA with Bonferroni correction), as noted in ts apa-2  and aps-subunit) , endophivps-26  SNARE, snn-1 , unc-10 (RIM), egl-8 , sad-1 . In addition, numerous kinases and phosphatatses, and proteins involved in ubiquitination were found in this class, whose possible role in SV recycling  is not presently clear. Another group of proteins whose knockdown caused unc-26-like Ca2+ traces were three innexin gap junction subunits [inx-8, inx-10 [eat-5; the possible role of innexins in the SV cycle is not clear at present.This included genes whose known or inferred function conceivably may contribute in the context of SV recycling, like  complex ), rack-1modeling ), snb-1  priming , 72), unustering ), unc-2 subunits , inx-8, , inx-10  and eat-unc-26 cluster (#1), which may be involved in SV recycling. Thus, we wanted to analyze  these genes also in genomic mutants. This should provide an indication if following up on the remaining genes from class #1 will be worthwhile in a future endeavor. Interestingly, three innexin (invertebrate gap junction) subunits were among this group, indicating that this class of proteins may be involved in synaptic recycling in a more general manner. We thus further analyzed this gene class in genomic mutants. We chose inx-8(gk42) and inx-10(ok2714), as these genes are expressed in neurons [erp-1(ok462), which encodes endophilin B, but for which no clear involvement in C. elegans SV recycling has been demonstrated previously. Last, we also included two additional genes, i.e. the prosaposin homologue spp-10(gk349) -lipids), as well as C27B7.7(ok2978), encoding a titin-like protein, as their Ca2+ signatures resembled that of unc-26 synaptojanin. R-OptIoN data for the RNAi experiments is shown again in Fig 7A, emphasizing that for all genes, a (mild) ‘SV recycling signature’ could be detected. The mutant genes were crossed into our Ca2+ imaging reporter strain and analyzed for their Ca2+ dynamics upon photostimulation . Furthermore, we performed electrophysiological analyses following repeated photostimulation, using the zxIs6 transgene . Based on Ca2+ imaging, only the inx-8(gk42) mutant had a strong SV-recycling signature, while the other mutants showed, if at all, only weak hints of an involvement in SV recycling . In electrophysiological experiments, a mixed outcome was observed. Based on the absolute photo-evoked postsynaptic currents, following repeated stimulation at 0.5 Hz, all mutants apart from spp-10 had significantly lower currents, based on 2-way ANOVA, and inx-10, inx-8 as well as erp-1 mutants also showed significantly lower currents for single time points. When looking at the currents after normalization to the first evoked peak current, to better follow progressive reduction of the evoked currents, C27B7.7, inx-10 and spp-10 mutants showed significantly reduced currents. However none of the mutants showed a progressive exacerbation, as was observed for unc-26(s1710) mutants . Thus, none of the five genes we analyzed in more detail exhibited an obvious SV recycling phenotype based on the electrophysiological assays, despite a clear SV recycling signature in Ca2+ imaging observed for inx-8(gk42) mutants.Based on our RNAi screen, we found several previously unstudied genes in the  neurons . FurtherC. elegans. We aimed to quickly detect genes required for SV recycling among factors that were previously shown to affect aldicarb sensitivity in cholinergic neurons [2+ imaging based on RCaMP in muscle cells, combined with photostimulation of cholinergic neurons using ChR2, allows analyzing how synaptic ACh release and the respective muscle response develop in a time-dependent manner. This method is equivalent to our previously used behavioral readout, i.e. following muscle contraction by video microscopy [Here we explored a new strategy to investigate synaptic transmission in  neurons . Ca2+ imcroscopy , 28. Yetcroscopy .2+ transients for mutants affecting SV biogenesis by endocytic recycling , or for generation of functional SVs, e.g. filling of SVs with ACh (vAChT unc-17). This signature allowed distinguishing genes among the 96 genes involved in synaptic transmission that we tested, as they showed a similar signature, based on hierarchical clustering of the data. All of the known SV recycling or endocytosis genes were among these genes in cluster #1. This could provide a first indication that the respective proteins may affect SV recycling or another rate-limiting step in their biogenesis, or could be involved in exocytosis-endocytosis coupling. However, when comparing mutant phenotypes to RNAi induced phenotypes, only unc-26 synaptojanin RNAi was able to induce a similarly strong recycling signature as the genomic mutant. Additionally, among the genes from cluster #1 which we then further analyzed in genomic mutants, only the innexin inx-8 had a strong recycling signature. Unfortunately, further analysis by electrophysiology could not confirm a SV recycling phenotype for this gene.Analyses of characterized genes affecting synaptic transmission allowed defining a ‘signature’ of the developing Ca2+ imaging ‘SV recycling signature’? Based on analyses of the post-synaptic Ca2+ dynamics for established, ‘strong’ SV recycling mutants, like unc-26, our approach is robust. Thus, it could, in principle, allow identifying genes with strong recycling defects even in a genome-wide RNAi screen, while it will likely not be able to detect genes causing subtle SV recycling defects. Therefore, stringent criteria for inclusion in secondary screening have to be used. Here we tested the approach on genes that were previously shown to have aldicarb sensitivity defects. The genes as identified by Sieburth et al. [unc-26), however, makes it questionable if a genome-wide screen is really feasible.In sum, the results from RNAi-induced depletion of the respective mRNA in cholinergic neurons, and the phenotypes observed in genomic mutants, did not always match, and RNAi phenotypes were in most cases weaker than the mutant phenotypes. Thus, how robust is the Cah et al.  were isoh et al.  and 96-w2+ signaling in unc-2(ra612) mutants caused an overall increased Ca2+ response in muscle, with otherwise normal Ca2+ dynamics. Defective transmitter release (snt-1(md290) synaptotagmin), or post-synaptic transmitter sensing (unc-38(x20) nAChR subunit) led to an overall weaker Ca2+ response. Mutants defective for synaptic vesicle recycling  had the unique characteristic of beginning with a stronger activation, followed by a characteristic appearance of fatigue. This fatigue was also seen in mutants impairing vesicle loading (unc-17(e113) vAChT), or synaptotagmin, which acts as a clathrin adaptor in SV recycling, in addition to its role in release [Comparing cholinergic neuron specific RNAi experiments and genomic mutants might have resulted in different phenotypes because a mutant will affect the gene in other tissues as well, such that masking phenotypes may add to the cholinergic neuron specific phenotype. A recent approach to use recombinase-based transgene rescue in specific tissues, in the mutant background, may allow to look at phenotypes of a genomic mutant in cholinergic neurons . Alterna release . Thus, tS1 FigAgar pads of the thickness of one microscope slide were poured. A pre-heated LED cooling element was used to stamp wells into the agar pad.(TIF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 FigSingle representative images from the indicated time points from the video stream are shown in a color look-up table. Bottom: Each bar represents the mean intensity of the representative images (whole field of view), beginning at the first frame during stimulation, until 33s during stimulation.(TIF)Click here for additional data file.S4 Figunc-26(s1710)  (n = 7–36).To mimic experimental conditions during RCaMP imaging, this experiment was performed under additional, constant 590 nm illumination (orange bar). Shown are mean normalized body length (± SEM) for wild type (black trace), no-ATR control (grey trace), and (TIF)Click here for additional data file.S5 FigA) Original records of inward currents following repeated photostimulation (0.5 Hz), mutant strains as indicated. B) Baseline, mean (±SEM) miniature post synaptic current events (mPSCs per second) from the indicated number of animals (genetic background as labeled), during a period before photostimulation. C) Mean mPSC amplitudes of the same strains as in B. Statistically significant differences to wild type (one-way ANOVA) are indicated .(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S1 Tableunc-26 synaptojanin and other SV recycling positive controls (yellow shading). Color shading is explained in the legend. Genes from the Sieburth et al. (2005) RNAi screen are shown in white, if they were only shown to induce aldicarb resistance following systemic RNAi. Light grey indicates genes that were also verified in genomic mutants by aldicarb assays. Orange shading represents random picked ‘negative’ controls. Blue, green and pink shading includes additional genes inducing aldicarb phenotypes, or genes that were lethal upon systemic RNAi. Genes that were analyzed by RNAi, but did not show significantly different Ca2+ traces compared to controls (based on 2-way ANOVA with Bonferroni correction), are indicated on the lower right.Class 1 contains genes that cluster with (PDF)Click here for additional data file.S1 VideoFirst, a jump in RCaMP fluorescence is seen when the ChR2 stimulation light is turned on, followed by a further, slower increase in fluorescence while muscles are stimulated by ongoing cholinergic neuron activity.(AVI)Click here for additional data file.S1 DataVideos were obtained at 20 fps, reflected by the ~2400 data points obtained for each trace during each ~130 s experiment. Furthermore, the peak normalizations are calculated in the data tables, as well as the 2-way ANOVA comparisons.(RAR)Click here for additional data file.S2 DataVideos were obtained at 20 fps, reflected by the ~2400 data points obtained for each trace during each ~130 s experiment. Furthermore, the peak normalizations are calculated in the data tables.(RAR)Click here for additional data file.S3 DataVideos were obtained at 20 fps, reflected by the ~2400 data points obtained for each trace during each ~130 s experiment. Furthermore, the peak normalizations are calculated in the data tables.(RAR)Click here for additional data file.


The genomes of RNA viruses are relatively small. To overcome the small-size limitation, RNA viruses assign distinct functions to the processed viral proteins and their precursors. This is exemplified by poliovirus 3CD protein. 3C protein is a protease and RNA-binding protein. 3D protein is an RNA-dependent RNA polymerase (RdRp). 3CD exhibits unique protease and RNA-binding activities relative to 3C and is devoid of RdRp activity. The origin of these differences is unclear, since crystal structure of 3CD revealed “beads-on-a-string” structure with no significant structural differences compared to the fully processed proteins. We performed molecular dynamics (MD) simulations on 3CD to investigate its conformational dynamics. A compact conformation of 3CD was observed that was substantially different from that shown crystallographically. This new conformation explained the unique properties of 3CD relative to the individual proteins. Interestingly, simulations of mutant 3CD showed altered interface. Additionally, accelerated MD simulations uncovered a conformational ensemble of 3CD. When we elucidated the 3CD conformations in solution using small-angle X-ray scattering (SAXS) experiments a range of conformations from extended to compact was revealed, validating the MD simulations. The existence of conformational ensemble of 3CD could be viewed as a way to expand the poliovirus proteome, an observation that may extend to other viruses. Establishment of a bacterial or viral infection requires that the pathogen be able to evade intrinsic and innate immune defenses of the host cell . PathogeOne well known strategy of RNA viruses is the use of a virus-encoded protease(s) to inactivate host defense proteins, for example pathogen recognition receptors, their adaptors and/or signaling molecules that lead to expression of interferon . These sPoliovirus (PV) and other picornaviruses, single-stranded RNA viruses with genome size 7–9 kb , use a pcre) of the viral RNA, forming important interactions required for genome replication; however, 3CD exhibits enhanced ability to form these interactions compared to 3C . H. H51]. HIn terms of the missing polymerase activity, it was clear going into this study that the amino terminus penetrates the fingers sub-domain of the polymerase and contributes to the organization of conserved structural motif A, which, in turn, contributes to the organization of conserved structural motif C . AdditioWe suggest that picornaviruses have evolved 3CD to be devoid of polymerase activity. First, the orthologous protein in the Calicivirus family, Pro-Pol, actually exhibits robust polymerase activity and is thought to be the active form of the enzyme in cells ,60. In tWe speculate that the observation made here for PV 3CD extends to all viral polyprotein precursor proteins. Structures of other precursor or multi-domain viral proteins have been solved  62,63,6,663,66. Our laboratory has been quite intrigued by the concept that RNA viruses need to create mechanisms to expand their functional proteome . This noThe use of a polyprotein for gene expression has always been considered a strategy to encode more functions into the limited coding capacity of a virus. Here we suggest that conformational sampling of interdomain interactions in polyprotein processing intermediates may further increase the viral proteome. The impact of mutation at the interdomain interfaces can be transformative to the conformational ensemble and hence the proteome, providing a possible explanation for the requirement of genetic diversity of an RNA virus for optimal fitness.


High-resolution melt analysis (HRMA) is a cheap and reliable post-polymerase chain reaction (PCR) cancer mutation screening technique, which is fast gaining clinical relevance. The HRMA capabilities of the LightScanner (Idaho Technology) have been severally studied. However, the ABI 7500 HRM has not been tested against the purpose-built HRM instrument such as the LightScanner.DNA from formalin-fixed, paraffin-embedded gastric cancer, colorectal cancer, and normal tissue as well as from colorectal cancer cell lines were amplified at exons 2, 3, and 4 of KRAS, and at exons 11 and 15 of BRAF in the ABI 7500 fast real-time PCR machine and subjected to melting both on the ABI and on the LightScanner. HRMA data were analysed with the ABI HRM software v2.0.1 and the LightScanner Call-IT 2.5. We tested the ABI 7500 HRM for internal precision, accuracy, sensitivity, and specificity at mutation screening relative to the LightScanner, using crude percentage concordance, kappa statistics, and the area under the receiver operator characteristics (AUROC) curve on SPSS version 19.The results show that the ABI 7500 HRMA has a high internal precision, and excellent concordance, sensitivity, and specificity at mutation screening compared with the LightScanner. However, in contrast to the LightScanner HRM software analysis, the ABI HRM software v.2.0.1, cannot distinguish real from certain pseudovariations in PCR amplicons that are sometimes brought about by the artefacts of the melting process.In conclusion, the ABI HRM has a comparable performance level with the LightScanner, although in certain respects mentioned previously, the LightScanner has an edge over the ABI. High-resolution melt analysis is a highly reliable PCR-based technique which has found use in genotyping and mutation scanning and is fast gaining clinical relevance , 2.There are two classes of instruments utilized for HRMA, namely real-time PCR instruments with HRM modules and HRM instruments without PCR capabilities , 3. In tA few studies have compared the performance of HRM across different platforms. Generally, the HRM instruments have a higher discriminating power than the real-time PCR instruments which incorporate HRM modules , 3, 6. IThe aims of this study are to determine the degree of concordance between the ABI 7500 real-time PCR and the LightScanner in mutation screening and to compare the sensitivity and specificity of the ABI 7500 fast real-time PCR HRMA relative to that of the LightScanner. Our hypotheses are that there is a high rate of concordance between the HRMA results of the ABI 7500 real-time PCR and the LightScanner, and the ABI fast real-time instrument has an excellent sensitivity and specificity relative to the LightScanner. To test these hypotheses, the HRM results obtained with these instruments were analysed with the appropriate statistical tests of agreement. Furthermore, the sensitivity and specificity of the ABI instrument were compared using the area under the receiver operator characteristics (AUROC) curve and manually calculated from the results of HRMA. The results are presented in this article.This study was carried out at the Division of Pathology, University of Nottingham, Queen’s Medical Centre Campus, Nottingham, United Kingdom.We tested intra-assay precision or reproducibility of each of the HRM modules, and then, the inter-assay agreements among the modules.DNA from clinical gastric cancer, colorectal cancer and normal  tissues, and colorectal cancer cell lines  were included in this study.Different genomic regions were amplified using the recently described two-stage PCR protocol (manuscript submitted) in the ABI 7500 fast real-time instrument. PCR was carried out in a 10 μL volume made up of 5 μL of Diamond Hotshot master mix, 1 μL of LC Green Plus dye, 0.5% of Tween, 300 nm of primers, and 2 μL of amplicon-enriched DNA template.The samples were amplified in singles (for inter-assay testing) and duplicates (for intra-assay testing), and PCR was followed by melting in the ABI 7500 and then in the LightScanner. The primer sequences, cycling and melting parameters used in this study are shown in The melting data were analysed with the HRM software v.2.0.1 (ABI 7500) and the LightScanner software Call-IT 2.5. The LightScanner data were analysed with the Amplicon Scanning (LSAS) and the Amplicon Genotyping (LSAG) programmes of the software. In some instances, the sensitivity levels of the LSAS were adjusted until the curves of all the wild-type samples , and other samples tightly clustering with them were identified as a single variant.Intra-assay and inter-assay agreements were tested for each HRM operation using the crude percentage concordance and kappa statistics in the SPSS version 19. The sensitivity and specificity of the ABI HRMA in detecting mutations relative to the LightScanner were derived from the coordinates of the area under the receiver operating characteristic (ROC) curve and confirmed by manual calculations from the cross tabulations of the HRM results.DNA samples from cancer and normal tissue were amplified in five gene regions: exons 15 and 11 of BRAF, and exons 2, 3, and 4 of KRAS. For the purpose of comparison of assays, each amplified gene region was treated as a sample (a gene region sample), melted with ABI and then, the LightScanner, and analysed with the ABI HRM software, LSAS and LSAG. For example, when a single DNA sample is experimentally amplified at BRAF 15, BRAF 11, KRAS 2, and KRAS 3, it is regarded as four (gene region) samples and statistically analysed as such. Different experiments were performed for the intra-assay testing than for the inter-assay tests. For the intra-assay agreement, DNA samples were amplified in duplicates at KRAS 2 and KRAS 4 up to a total of 53 gene region samples and melted on the ABI and LightScanner. The degrees of agreements between the duplicates were compared for ABI, LSAS, and LSAG using the statistical tests mentioned earlier. For the inter-assay agreement, DNA samples were experimentally amplified in singles at BRAF 15, BRAF 11, KRAS 2, and KRAS 3 up to a total of 292 gene region samples. The degrees of agreement among the ABI, LSA, and LSAG were also compared using the same statistical tests mentioned.К = 0.811 [P < 0.001]; LSAS: 96.2%, К = 0.920 [P < 0.001]; LSAG: 94.3%, К = 0.884 [P < 0.001]), the LSAS and LSAG had better intra-assay precision or reproducibility.Exons 2 and 4 of KRAS were amplified in some of the above-mentioned samples to a total of 53 duplicate gene regions and subsequently melted on both instruments. Up to eight different amplicon variants were identified by each assay per gene region amplified. For each gene region sample, the duplicate HRMA data were input into SPSS as two different variables  for each assay. Statistical analyses with crude percentage concordance and kappa statistics were performed to determine the precision (reproducibility) of each of the assays. The results showed that while each of the assays had excellent intra-assay agreement   .The area under the receiver operating characteristics (AUROC) was derived for ABI (relative to LSAS and LSAG) and LSAG (relative to LSAS). The above results were confirmed by manual calculations of sensitivity and specificity from the cross-tabulations of the results from the three HRMA assays  and 5.Although the intra-assay agreement for all three assays were outstanding, the crude percentage concordance, and kappa values show that the LightScanner assays have more internal consistency than the ABI 7500 HRM assay. This better internal consistency of the LightScanner is in agreement with a previous study which showed that HRM instruments have a better precision than non-HRM instruments , 3.In this study, we have used the LightScanner as the standard to compare the inter-assay reproducibility and performance of the ABI because the LightScanner has been severally shown to have similar performance levels for mutation detection as the Sequencing methods –10. The The sensitivity of 83.3% of the ABI HRM module at mutation detection found in this study, although excellent, is lower than the 92–100% sensitivity obtained by ABI HRM relative to sequencing in the detection of micro-organisms . HoweverThe 80% sensitivity obtained with the LSAG relative to the LSAS analysis in mutation scanning was expectedly low, considering that LSAG is designed for genotyping, not scanning . We haveAccession numbers of DNA sequences shown inFigure 2BRAF exon 11 [NCBI Reference Sequence NC_018918.2]BRAF exon 15 [NCBI Reference Sequence NC_018918.2]KRAS exon 2 [NCBI Reference Sequence NC_018923.2]KRAS exon 3 [NCBI Reference Sequence NC_018923.2]KRAS exon 4 [NCBI Reference Sequence NC_018923.2]Our study did not include any sequencing methods as the aim is to show the extent to which the ABI HRMA replicates the LightScanner HRMA at mutation screening. This is more so as HRMA has severally been shown to have similar sensitivity and specificity as sequencing at mutation detection –10. We hTm, during amplicon melting. These variations are worse with the qPCR instruments incorporating HRM (including some of those manufactured by ABI) than the purpose-built HRM instruments. Variations in Tm can result in false variant calls by the instruments [Finally, we observed that the LightScanner software analysis is superior to that of the ABI 7500 HRMA in two respects. The first is that the variant calls by the LightScanner software are ‘stable’. That is, they are not affected by the addition or subtraction of a sample with a deviant melting pattern to a set of samples. In contrast, analysis by the ABI HRM software is more ‘delicate’ and its variant calls are significantly affected by the addition or subtraction of one or more samples with different melting patterns . The sectruments . While tThe ABI 7500 HRMA shows a high internal precision, and excellent concordance, sensitivity, and specificity at mutation screening compared with the LightScanner. In addition, the LightScanner HRM software analysis, but not the ABI HRM software v.2.0.1, can nullify certain pseudovariations in PCR amplicons brought about by the artefacts of the melting processes.HRMAHigh-resolution melt analysisLSASLightScanner amplicon scanning programmeLSAGLightScanner amplicon genotyping programmeThe authors declare no conflict of interest.HOE: Experiment development, execution and analysis, manuscript drafting, editing and preparation of the final manuscript version. MI: Conception, experimental analysis, manuscript editing, and preparation of final version for publication.


Massive, parallel sequencing is a potent tool for dissecting the regulation of biological processes by revealing the dynamics of the cellular RNA profile under different conditions. Similarly, massive, parallel sequencing can be used to reveal the complexity of viral quasispecies that are often found in the RNA virus infected host. However, the production of cDNA libraries for next-generation sequencing (NGS) necessitates the reverse transcription of RNA into cDNA and the amplification of the cDNA template using PCR, which may introduce artefact in the form of phantom nucleic acids species that can bias the composition and interpretation of original RNA profiles.Using HIV as a model we have characterised the major sources of error during the conversion of viral RNA to cDNA, namely excess RNA template and the RNaseH activity of the polymerase enzyme, reverse transcriptase. In addition we have analysed the effect of PCR cycle on detection of recombinants and assessed the contribution of transfection of highly similar plasmid DNA to the formation of recombinant species during the production of our control viruses.We have identified RNA template concentrations, RNaseH activity of reverse transcriptase, and PCR conditions as key parameters that must be carefully optimised to minimise chimeric artefacts.Using our optimised RT-PCR conditions, in combination with our modified PCR amplification procedure, we have developed a reliable technique for accurate determination of RNA species using NGS technology. The massive capacity of next generation sequencing (NGS) technologies is revolutionising transcriptome analysis and can be used to assess the complexity of viral diversity in highly mutable, genomes of RNA viruses that cause disease in humans, such as human immunodeficiency virus-1 (HIV-1). Accurate detection of clinically relevant, drug-resistant mutations is important for adapting patient drug regimes. In addition, deep sequencing is used to investigate host cell and viral factors that impact on the genetic diversity of HIV-1.The production of cDNA libraries for NGS involves laboratory procedures that include RNA extraction, reverse transcription PCR (RT-PCR) to generate cDNA followed by PCR amplification. Importantly, the amplification of each cDNA species must remain clonal, especially when studying the diversity of RNA species. The laboratory manipulations necessary for library generation are recognised as potential sources of artefactual recombination. Several papers have addressed the issue of minimising PCR artefacts -3 and thThus, in both the clinical and experimental setting there is a recognised need to identify sources of laboratory induced error and to minimise these to obtain a robust technique for generating DNA libraries for NGS that faithfully reflect the underlying genetic diversity of the virus. In the current study there were three aspects of sample processing that we were particularly interested in assessing and optimising: RNA concentration during first strand synthesis; effect of RNase H activity and PCR cycling conditions. To assess the impact of these on the introduction of recombinant artefact we used a mix of authentic wild-type (WT) HIV-1 and marker virus containing silent mutations that areUsing our viral system we have produced populations of genetically distinct, but functionally identical, homozygous HIV-1 particles (containing either WT or marker RNA) and also heterozygous HIV-1 (containing a strand of WT and marker RNA) as sources of viral RNA species for analysis of laboratory sources of recombination. We have characterised the important sources of error in RT-PCR that contribute to artificial chimera formation and, in combination with our modified PCR amplification procedure , have deCA) of homozygous WT and MK viruses were mixed together and RNA extracted  increased significantly as RNA concentration increased for RNA extracted from the mix of WT and MK virus Table a. In addIt has been shown that PCR conditions have a significant impact on the detection of genomic recombinants . Smyth eThe HIV-1 genome is comprised of 2 identical  strands of RNA, that are used as template during reverse transcription to produce a cDNA molecule for integration into the host genome during infection. Template switching during reverse transcription is acknowledged as an efficient mediator of viral diversity, generating recombinant HIV RNA species that are a mixture of the two parental RNA strands. Template switching is thought to be facilitated through the action of the RNase H activity of the HIV-1 RT whereby a dynamic balance exists between the polymerase activity of RT and the endonuclease activity of RNase H that cleaves the RNA from the nascent cDNA polymer ,13. Accoin vitro effect of RNase H activity on the formation of artificial recombinants viral RNA was reverse transcribed using either the high fidelity SSIII enzyme, engineered to have reduced RNase H activity, or AMV RT with full RNase H activity. We compared the recombination rates detected for 160 ng and 1600 ng of RNA transcribed with SSIII with the rate for 2ug RNA transcribed using AMV-RT, as recommended by the manufacturer. Surprisingly, the RNase H activity of AMV had little impact on the recombination rate when compared to 1600 ng of RNA transcribed with SSIII, however both of these were 10-fold higher than the recombination rate at 160 ng input RNA using SSIII  and resulting cDNA was diluted so that approximately 2,500 copies of HIV-1 cDNA were used as template and amplified using our optimised PCR protocols. The mixture of homozygous RNA species provides a baseline measure of artefactual recombination attributable to downstream laboratory manipulations, as any recombination between these homozygous viruses could only have occurred during RT-PCR, PCR or 454 sequencing. Thus, comparison of the rate of recombination between the mix of homozygous viruses  with that of the truly heterozygous viral RNA provides a novel and accurate estimate of the rate of transfection-induced recombination.Table in vivo viral species from laboratory induced artefacts.Any analysis of viral diversity through experimentation raises the possibility that recombinant quasi-species could arise as a result of laboratory manipulations, including virus production (transfection), infection of primary cells or cell lines, RNA extraction and conversion of RNA to cDNA (RT-PCR) and cDNA amplification. Mutations in the form of insertions, deletions or substitutions could occur during any of these procedures and deep sequencing. Further, with the vast improvements in treatment for HIV-1 infection that have occurred over the last 30 years, clinicians are now able to investigate the emergence of viral quasi-species in individual patients and to tailor drug regimes to counter the emergence of deleterious, drug-resistant mutants. Experimental programs to identify viral and host cell factors that affect recombination and clinical assessments of drug-resistant mutants require sensitive and validated methods to discern ‘true’ We produced genetically distinct, authentic HIV-1 viruses to investigate the most obvious sources of laboratory induced error, namely: transfection, RT-PCR and PCR conditions. Using our system we have been able to compare recombination rates between a mix of homozygous viruses (where recombination could only be due to laboratory manipulations) and heterozygous virus (where recombination could be due to laboratory manipulations or to the transfection process). Our data show that the transfection of HEK293T cells with plasmid DNA is an insignificant source of recombination and affirms the appropriateness of using transfection-derived viruses as model systems to identify viral and host cell factors that affect recombination. We stress the importance of using high quality plasmid DNA for the production of virus to minimise the risk of homologous recombination within the culture system. This is consistent with previous studies that have shown that nicked, non-circular plasmid DNA enhances the occurrence of homologous recombination between plasmid and homologous chromosomal regions ,10.By comparison considerable attention must be paid to the conditions of RT-PCR and PCR to minimise the occurrence of artefactual chimeras. We postulated that increasing the concentration of RNA during first strand synthesis would decrease the proximal distance of strands of RNA and enhance strand transfer events, thus resulting in increased recombination rates. Our data confirm that RNA concentration in RT-PCR is a critical parameter. Surprisingly, even acceptable ‘mid-range’ concentrations of RNA template  at the RT-PCR step can result in detection of false chimeras. Thus we show that even when using a high fidelity enzyme with low RNase H activity, RNA concentration is a critical factor and can have a marked effect on estimates of recombination rate. We recommend that input RNA be kept to a minimum 100-200 ng) which, in this study, is at least 10-fold lower than that recommended by the manufacturer. In accord with Di Giallonardo et al. [00 ng whiThe PCR amplification of DNA is highly susceptible to artefact. Previous studies have shown that input copy number ,2, anneagag, as previously described [The wild-type (WT) HIV-1 plasmid used was pDRNL(AD8)  that encescribed ,21 and described ,21. It iescribed ,20.FigurCA Antigen Capture Assay .Homozygous virus was produced by transfection of HEK293T cells with either WT or MK plasmid and heterozygous virus by co-transfection of equimolar amounts of WT and MK plasmids using polyethyleneimine . Based on Mendelian genetics, the heterozygous virus will be composed of 3 distinct populations: 25% of virus particles will contain 2 strands of WT RNA; 25% will contain 2 strands of MK RNA and 50% will be truly heterozygous, containing a strand of WT and MK RNA. Sixteen to twenty hours after transfection cell cultures were gently washed with PBS and replenished with fresh media. At 48 hr post-transfection viral supernatants were harvested, clarified by centrifugation, layered over a 20% sucrose cushion and centrifuged for 1 hour at 25,500 g, 4oC. Concentrated virus was then further refined by layering onto a sucrose gradient (consisting of 9 sucrose layers ranging from 50% sucrose to 32% sucrose in 2.5% decrements) and centrifuged for 16 h, 25,500 g, 4°C to reduce plasmid contamination. Concentrated virus was resuspended in RPMI (Invitrogen), aliquoted and stored at −80°C. Quantitation of virus was done with an ELISA assay to detect viral capsid protein using the HIV-1 p24gag1 amplicon. In all cases there was a minimum 10 cycle threshold differences between samples processed with the RT and those without, indicating very low levels of plasmid contamination.Viral RNA was isolated using TRI-reagent (Qiagen) according to the manufacturer’s recommendations. RNA was reverse transcribed using gene-specific primer, gag4(4195)Rv (5′ ACATTTCCAACAGCCCTTTTTCCTAG 3′), and either SuperScript III reverse transcriptase (RT) (Invitrogen) engineered to have minimal RNaseH activity or AMV RT (with RNAse H activity) (Promega). Variable amounts of input RNA template were used in optimal and ‘stress’ conditions, as described in the results section. To gauge plasmid DNA contamination, RNA samples were processed without reverse transcriptase (RT) and then analysed by qPCR using primers for gag region of HIV-1 and designated gag1, gag2, gag3 and gag4. Primers were designed with unique barcodes at the 5′ end (Table Barcoded PCR primers were designed so that marker points were amplified as 4 overlapping amplicons (~350 bp) covering the Modified PCR cycling conditions were used as described previously  to reducgag1 amplicon, ranging from 102-106 copies of DNA per microlitre. Aliquots of each amplicon (gag1-gag4) for each sample were pooled to construct sequencing libraries using the 454 library preparation kit (Roche). Emulsion PCR and sequencing were performed using standard XLR70 chemistry at the Institute for Immunology and Infectious Diseases, Perth, Australia.PCR replicates were pooled and purified using the Wizard SV gel and PCR Clean-Up System (Promega) following the recommended protocol and quantitated against a plasmid standard curve, generated with gag gene from WT and MK genomes into a single chimeric genome.Sequencing analysis was performed using software custom written in BioRuby. Chimera formation, expressed as recombination rate per 1000 nucleotides (REPN), and statistical comparisons performed as previously described . Recombi


Eukaryotic cells have evolved stringent proofreading mechanisms to ensure that intron-containing mRNAs do not leave the nucleus. However, all retroviruses must bypass this checkpoint for replication. Indeed, their primary polycistronic transcript (Full-Length) must reach the cytoplasm to be either translated or packaged as genomic RNA in progeny viruses.cis-elements have been identified in the FL RNA that regulate its cytoplasmic accumulation. However, their connection with an export mechanism is yet unknown. Our goal was to identify the cellular pathway used by MLV to export its RNAs into the cytoplasm of the host cells.Murine leukemia virus (MLV) is a prototype of simple retroviruses with only two well-regulated splicing events that directly influence viral leukemogenic properties in mice. Several Since other retroviruses use the CRM1 and/or the Tap/NXF1 pathways to export their unspliced RNA from the nucleus, we investigated the role of these two pathways in MLV replication by using specific inhibitors. The effects of export inhibition on MLV protein synthesis, RNA levels and RNA localization were studied by Western blotting, RT-qPCR, fluorescence microscopy and ribonucleoprotein immunoprecipitation assays. Taken together, our results show for the first time that MLV requires the Tap/NXF1-mediated export pathway, and not the CRM1 pathway, for the expression of its spliced and unspliced RNAs and for FL RNA nuclear export.By contrast to HIV-1, MLV recruits the same pathway for the cytoplasmic expression of its spliced and unspliced RNAs. Thus, MLV RNA expression depends upon coordinated splicing/export processes. In addition, FL RNA translation relies on Tap/NXF1-dependent export, raising the critical question of whether the pool of FL RNA to be packaged is also exported by Tap/NXF1. The quality of gene expression is assured by proofreading mechanisms that eliminate unprocessed or irregular pre-mRNAs,2. Retroe FL RNA.cis-elements, such as the Psi motifs and R region sequences in the 5' UTR of FL RNA, have been reported to promote the cytoplasmic accumulation of FL RNA[cis-acting elements also modulate RNA splicing efficiency, RNA stability and virus assembly has made it difficult to elucidate the nuclear export pathway that they use (reviewed in[The murine leukemia virus (MLV) was among the first retroviruses to be studied and constitutes the prototype for simple retroviruses. Moloney-MLV, in particular, has been key in our understanding of basic cellular processes such as the discovery of oncogenes, eukaryof FL RNA-13. Howeiewed in).In this study, we have investigated the nuclear export of MLV RNAs. We show that inhibition of the Tap-pathway dramatically decreases viral protein production and simultaneously decreases the levels of spliced and unspliced MLV RNAs. A sensitive and specific fluorescence detection method was used to study the export of unspliced viral RNA. RNA imaging and ribonucleoprotein (RNP) immunoprecipitation assays (RIP) provided strong evidence for the recruitment of the Tap-pathway by MLV to export its RNAs to the cytoplasm.Gag) and GagPol (Pr190Gag/Pol) precursors; ii) a partially-spliced 4.4 kb RNA (SD' or SD'p50) encoding for the p50 protein whose function remains unknown[Env) encoding for the envelope (Pr85Env). How these spliced and unspliced MLV RNAs exit the nucleus to be translated in the cytoplasm is unknown. Since other retroviruses use the CRM1 and/or Tap pathways to export their unspliced RNA, we investigated these two pathways. First, murine NIH3T3 cells transfected with the Moloney-MLV molecular clone (pMov9.1) were treated with the CRM1 inhibitor leptomycin B (LMB) and MLV expression was monitored by Western blot analysis of Pr85Env and Pr65Gag proteins translated from spliced and unspliced RNAs, respectively. LMB treatment impaired neither spliced or unspliced MLV RNA expression in NIH3T3 cells while it reduced HIV FL RNA expression in 293 T cells as expected[Gag and Pr85Env protein levels respectively, while the Tap siRNA reduced both protein levels to a similar extent (60%). Remarkably, MLV expression was abolished by the 4-CTE competitor  the unknown, and iiiexpected  oveexpected and iii)GagPol Pr0Gag/Pol GagPol Pr90Gag/PolGagPol Pr90Gag/Polenv-deleted MLV in order to prevent re-infection events. Total cellular RNAs were extracted at 12, 24 and 48 h post-transfection (p.t) and MLV RNAs were specifically quantitated by RT-qPCR, as previously described[P50 and SDEnv remained at undetectable levels, probably due to incomplete splicing [trans. In this viral context, the reporter RNA localized mainly to the plasma membrane, with reduced nuclear localization. There were also numerous fluorescent puncta in the extracellular space that are probably associated with released viral particles. As in the NIH3T3 context, TapΔC induced a 20% increase of nuclear RNA retention. Taken together, these results establish that TapΔC blocked the nuclear export of the MLV reporter RNA, regardless of whether MLV proteins were present, and validates the requirement for the Tap-pathway to export MLV RNA from the nucleus.To investigate the requirement of Tap for MLV RNA export, we used a fluorescence h (FISH) combinedh (FISH) and can h (FISH),22. To ah (FISH). First, h (FISH). RNA imaEnv) RNA . MLV RNAs retained by TapΔC on beads were amplified by RT-PCR specific to FL or spliced (SDcis with siRNA or excess of 4-CTE RNA competitor and in trans with a dominant-negative Tap mutant (TapΔC). We have demonstrated for the first time that Tap is required for MLV expression and that it interacts with both spliced and unspliced MLV RNAs. When interacting with TapΔC, the unspliced RNA was restricted to the nucleus, indicating that MLV RNA export requires the Tap-dependent pathway. Our results support the notion that MLV recruits the same pathway to export its spliced and unspliced RNAs. In contrast to HIV, which uses different export pathways to transport its fully-spliced and unspliced RNAs, MLV regulates the expression of its FL RNA through a highly coordinated splicing/export process. Furthermore, the Tap-pathway is a prerequisite to the translation of the two MLV RNA species, since Gag and Env protein levels were sensitive to TapΔC. Unlike HIV-1, MLV has two distinct pools of FL RNA with two different destinies: translation and packaging into new particles[In this report, different strategies were used to block the Tap-pathway, in articles. In thisarticles). It musThe authors declare that they have no competing interests.SL and MM designed and analyzed the research; LPV, SL, and MFA performed research, collected data, and helped in finalizing the manuscript. MM wrote the manuscript. All authors read and approved the final manuscript.The following oligonucleotides were used for the RT-PCR assays. The name refers to the RNA target.Click here for file


Protein–protein interactions are difficult therapeutic targets, and inhibiting pathologically relevant interactions without disrupting other essential ones presents an additional challenge. Herein we report how this might be achieved for the potential anticancer target, the TPX2–importin-α interaction. Importin-α is a nuclear transport protein that regulates the spindle assembly protein TPX2. It has two binding sites—major and minor—to which partners bind. Most nuclear transport cargoes use the major site, whereas TPX2 binds principally to the minor site. Fragment-based approaches were used to identify small molecules that bind importin-α, and crystallographic studies identified a lead series that was observed to bind specifically to the minor site, representing the first ligands specific for this site. Structure-guided synthesis informed the elaboration of these fragments to explore the source of ligand selectivity between the minor and major sites. These ligands are starting points for the development of inhibitors of this protein–protein interaction. Mr<300 Da) are identified through biophysical screens and elaborated into more potent molecules using structure-based ligand design.DMSO 96-well stock plates.Protein expression and purification: The protein construct used in this study is a truncated form of Mus musculus importin-α1  covering residues 70–529, lacking the N-terminal IBB domain: ΔIBB-importin-α.DMSO stock plates, giving a final DMSO concentration of 2 %. Binding was determined on observation of a change in fragment signals in the presence of 20 μm importin-α, relative to a control sample containing only buffer and no protein. If found to bind importin-α, a displacer sample was made by addition of 40 μm TPX2 (IIKPFNLSKGKKRTFDEAAS) peptide (Designer Bioscience) direct to the protein sample and displacement noted if the fragment signals showed a return to those seen in the control sample.Isothermal titration calorimetry: All experiments were performed on a Microcal ITC200 instrument  at 25 °C. All ITCs were performed at pH 6.0 using ITC buffer . Fragment ITCs were performed using the competitive ITC technique following the procedure and formula described by Zhang et al.[m 20-amino acid TPX2 to 25 μm importin-α 10 % DMSO at pH 6.0 (average Kd=1.0 μm) was compared directly with the same titration in the presence of the fragment at 5 or 10 mm. Direct ITCs were performed for elaborated compounds at pH 6.0 in ITC buffer titrating 10 mm compound into 25 μm protein. Compounds that showed double binding in crystal structures  had their ITCs fitted using a one-site binding model, as this gave the best curve fitting, suggesting the second binder remains relatively weak. Experimental parameters are described fully in the Supporting Information.Crystallisation and crystallographic methods: Crystals of unliganded ΔIBB-importin-α were grown using hanging-drop vapour diffusion in 24-well Linbro plates (Hampton Research) with 4 μL drops of 100 μm ΔIBB-importin-α1 at 1:1 protein/precipitant volume ratio  and streak-seeding from an ΔIBB-importin-α seed crystal plate 18 h after sealing the wells. Crystals reached their maximum size after 1–2 weeks, when they were soaked in solutions of fragment (100 mm or saturating concentration) in crystallisation buffer supplemented with 10 % DMSO for between 30 min and 5 h. Crystals were then briefly exposed to crystallisation buffer  as a cryoprotectant and flash cooled at 100 K in liquid nitrogen. X-ray data were collected at the Diamond Light Source or European Synchrotron Radiation Facility. All datasets were processed and reduced using XDS[AIMLESS.[IBB-importin-α1 in the Xenopus–mouse TPX2–importin-α structure;[PHENIX,[CCP4,[COOT.[COOT, with restraints generated in PHENIX. The resulting models were further refined with CCP4 or PHENIX, as well as adding waters and ions from the crystallisation conditions. The stereochemistry of the structure was finally assessed using MolProbity.[using XDS and AIMLtructure; PDB ID 3;[PHENIX, CCP4,[26P4,[COOT. ElectronlProbity. MoleculaCompound docking: All compounds were docked into an unliganded structure of mouse ΔIBB-importin-α1. The protein was prepared in Discovery Studio Visualizer  by removal of crystallographic waters and addition of hydrogens before selecting the coordinates of the key minor site residue Glu396. Compounds to be docked were loaded as .mol files into Discovery Studio Visualizer where hydrogens and relevant charges were added before the structures were minimised to relax bond lengths and fix bond angles. Ligands were docked into the protein in a radius of 13 Å around Glu396 using GOLD 5.1[ GOLD 5.1 using deSynthetic chemistry: General directions for the synthesis of the compounds described as well as their spectroscopic analyses are supplied in the Supporting Information. The purity of all compounds tested for binding to importin-α was assessed by LCMS or HPLC and is >95 % unless otherwise stated.Accession numbers: The coordinates and structure factors for the mouse–mouse TPX2–importin-α structure used to inform compound synthesis, as well as importin-α compound structures 1, 11, 12, 13, 14, 15, 16, and 17 have been deposited in the RCSB Protein Data Bank (http://www.pdb.org) under the PDB ID codes: 4U54, 4U5L, 4U5N, 4U5S, 4U58, 4U5O, 4U5U, and 4U5V respectively.


GSE67305. Here we provide additional information on the experimental setup and on important optimization steps pertaining to the ribosome profiling technique in mouse liver and to data analysis.Mammalian physiology and behavior follow daily rhythms that are orchestrated by endogenous timekeepers known as circadian clocks. Rhythms in transcription are considered the main mechanism to engender rhythmic gene expression, but important roles for posttranscriptional mechanisms have recently emerged as well (reviewed in Lim and Allada (2013)  For all experiments, mice were entrained to 12-h-light/12-h-dark cycles for 2 weeks with water and normal chow available ad libitum. Prior to organ collection, mice were anesthetized with isoflurane and sacrificed by decapitation. Mice were sacrificed at the indicated Zeitgeber times (ZT), with ZT00 corresponding to “lights on” and ZT12 to “lights off” in the animal housing facility. Livers were rapidly excised and immediately processed to lysate.2.32, 5 mM DTT, 100 μg/ml cycloheximide, 1% Triton X-100, and 0.5% sodium deoxycholate) supplemented with complete EDTA-free protease inhibitors (Roche) and 40 U/ml RNasin plus (Promega). Of note, RNasin plus inhibits RNase A, B and other RNases present in liver extracts, but not RNase I, which will be used at a later stage of the protocol to generate ribosome protected mRNA fragments (RPFs). The liver homogenates were transferred to microcentrifuge tubes and incubated for 10 min on ice. Cellular debris was pelleted by centrifugation at 1000 × g for 3 min at 4 °C. The supernatant was removed, aliquoted, and snap-frozen and stored under liquid nitrogen until further processing. For absorbance measurements at 260 nm, lysates were gently thawed on ice, diluted 1:10 and 1:20 in water, the absorbance determined by Nanodrop and the average value from the two dilutions was determined. In general, the lysates ranged between 100 and 200 OD260 per 1 ml lysate. Equal amounts of lysate (OD260) from 2 mice, collected at the same time point, were pooled and diluted with lysis buffer to a final concentration of 15 OD260/100 μl. Lysates were processed separately for RPF-seq and RNA-seq  RNA, 100 μl pooled lysate was mixed with 1 ml Trizol and incubated for 5 min at room temperature. RNA was isolated using the miRNeasy kit (Qiagen) according to the manufacturer's protocol and the concentration determined by Nanodrop. Prior to library preparation, a total of 5 μg RNA was subjected to ribosomal RNA depletion  and subsequently purified using a RNA purification kit . RNA-seq libraries were generated following the instructions for total RNA library preparation of the ARTseq ribosome profiling kit (Epicenter).2.5In preparation to processing the samples from the large-scale time series, we optimized the conditions for nuclease digest in order to ensure efficient and reproducible generation of RPFs of ≈ 30 nucleotides in length. To this end, liver lysates were incubated with different amounts of RNase I ranging from 0 to 1000 units (Ambion). The digested mRNA fragments were purified using Trizol extraction and analyzed by northern blot as described previously  g. 1 ml of Trizol was added to the flow-through and RNA was extracted using the miRNeasy kit (Qiagen) according to the instructions of the manufacturer. The concentration of the RNA was determined by Nanodrop and RNA was stored at − 80 °C. Before proceeding to library preparation, the quality of the extracted RPFs was verified for all samples of the time course experiment by northern blot analysis  were added to inactivate the RNase I enzyme. In the meantime, size exclusion spin columns , that would subsequently serve to purify the nuclease-generated monosomes, were prepared. To this end, spin columns were washed 3 times with 700 μl lysate buffer containing 20 U/ml Superasin in a microcentrifuge at 600 × g for 1 min. Between each washing step the matrix of the spin column was gently resuspended by vortexing. After the washing steps, lysates were applied to the matrix and the spin columns were centrifuged for 2 min at 600 ×analysis .2.6Library preparation of RPFs was performed according to the ARTseq ribosome profiling kit (Epicenter) with the modification that the steps of ribosomal RNA depletion (Ribo-zero) and polyacrylamide gel electrophoresis (PAGE) purification were inverted. The original protocol uses 5 μg of RPF RNA as starting material, which is the maximum amount of RNA recommended in a Ribo-zero reaction. However, using this protocol we were occasionally unable to obtain sufficiently concentrated libraries for sequencing. The inversion of the 2 steps allowed us to increase the starting material up to 25 μg RPF RNA, without noticing a negative effect on the performance of the Ribo-zero depletion. In our case, the RNA was first separated on a 15% urea-polyacrylamide gel and stained with SYBR-Gold (Invitrogen). Gel pieces between 26 and 34 nucleotides were excised, the RNA extracted, purified and only then used for ribosomal RNA depletion. After the Ribo-zero reaction, the RNA was purified using a RNA purification kit  and immediately subjected to end-repair and 3′ adaptor ligation according to the instructions of the ARTseq protocol. Reverse transcription, cDNA purification and circularization were done as described in the ARTseq protocol. During the last step of library preparation, i.e. the PCR amplification, 5 μl out of the 20 μl circularized cDNA product was used as template in the PCR reaction. The quality of the final library was assessed by analyzing 5 μl of the PCR reaction on an 8% native PAGE, stained with SYBR Gold. For some libraries, only a faint band was visible, and we then performed up to 3 additional PCR amplifications as described above in order to have sufficient material. In a final step, the identical PCR reactions were pooled and loaded on an 8% native PAGE. The library running at ≈ 150 bp was gel-purified, precipitated with ammonium acetate and resuspended in water. The concentration and the quality of both RPF-seq and RNA-seq libraries were determined by Qubit (Thermo Fisher) and BioAnalyzer (Agilent). Up to 6 libraries were multiplexed and subjected to 100 cycles of single-end sequencing on an Illumina HiSeq2500 (Illumina).2.7Here, we briefly outline the first steps of data analysis. More detailed information on data processing and analysis can be found in the supplementary information of the original publication In a first step, sequencing reads were de-multiplexed, adapter-trimmed and size-filtered (lengths of 26–35 nucleotides for RPF-seq and 21–60 nucleotides for RNA-seq). Next, we removed from the filtered reads sequentially the mouse and human ribosomal rRNA, mouse mt-tRNA, mouse tRNA, and then finally aligned the reads to mouse cDNA (Ensembl release 75) and genomic sequences (GRCm38.p2), using bowtie version 2.2.1 and Tophat v2.0.11, respectively. In parallel, a database of expressed transcripts was generated from RNA-seq reads (cufflinks v2.2.1) and used for subsequent analyses. Read quantification was done per gene for each annotation feature . Read counts were normalized with the upper quantile method of R package edgeR v3.4.2 and RPKM values were calculated as the number of counted reads per 1000 mapped and counted bases per geometric mean of normalized read counts per million (RPKM). Translation efficiencies were calculated as the ratio of RPF-RPKM/mRNA RPKM. The Babel framework was used to assess significant changes in translational regulation 3We describe here two temporal data sets in mouse liver composed of transcriptome (RNA-seq) and translatome profiling (RPF-seq) with 2-h resolution around the 24-h daily cycle. Rhythmic RNA abundance and rhythmic footprints affected a similar proportion (17%) of the total 10′800 genes detected in both RNA-seq and RPF-seq datasets. The majority of these rhythmic events (≈ 1200 genes) oscillated both at the mRNA abundance and the translation level. However, we also identified ≈ 150 genes that showed no daily changes in mRNA abundance but rhythms in translation. These genes are involved in ribosome biogenesis, translation regulation, iron homeostasis and other pathways. Future studies will aim at uncovering the precise mechanisms that engender rhythmicity at the translational level, thus adding a new level of understanding to posttranscriptional control of rhythmic gene expression (Lim and Allada (2013) The authors declare no conflicts of interests.


Sam68 and T-STAR are members of the STAR family of proteins that directly link signal transduction with post-transcriptional gene regulation. Sam68 controls the alternative splicing of many oncogenic proteins. T-STAR is a tissue-specific paralogue that regulates the alternative splicing of neuronal pre-mRNAs. STAR proteins differ from most splicing factors, in that they contain a single RNA-binding domain. Their specificity of RNA recognition is thought to arise from their property to homodimerize, but how dimerization influences their function remains unknown. Here, we establish at atomic resolution how T-STAR and Sam68 bind to RNA, revealing an unexpected mode of dimerization different from other members of the STAR family. We further demonstrate that this unique dimerization interface is crucial for their biological activity in splicing regulation, and suggest that the increased RNA affinity through dimer formation is a crucial parameter enabling these proteins to select their functional targets within the transcriptome. Sam68 and T-STAR are members of the STAR family of proteins, which regulate various aspects of RNA metabolism. Here, the authors reveal structural features required for alternative splicing regulation by these proteins. Sam68 (Src-associated protein in mitosis of 68 kDa)131911126mTORNeurexin AS4 exons2434CD44, Tra2β, Tau, VGEF and Neurexin pre-mRNAs2627Sam68 has been shown to have oncogenic properties1517STAR proteins are defined by the presence of a highly conserved RNA-binding domain, the STAR domain, also responsible for homodimerization3334363839in vivo. We speculate that homodimer formation may also contribute to splicing control of some pre-mRNAs through enabling looping out of regions of target RNAs.To gain mechanistic functional insights, we have deciphered the structural basis of dimerization and RNA recognition by Sam68 and T-STAR. We show that the dimerization of both T-STAR and Sam68 synergizes their binding affinity to target RNAs, and is essential for their function in splicing regulation We have shown previously using NMR spectroscopy that the isolated KH domains of Sam68 and T-STAR are sufficient for binding A/U-rich RNAsThe structures of the T-STAR QUA1-KH and STAR domains in complex with RNA show that the QUA1 and the KH domains form compact dimers, with each KH domain binding one RNA molecule, while the QUA2 domain does not adopt a fixed orientation . The QUA38392 per monomer, almost twice as large as the QUA1 dimerization interface, and involves mainly the C-terminal α-helix 3 of the KH domain and the C-terminal half of the QUA1-KH linker. The KH interface is stabilized by a network of hydrophobic interactions involving residues A138, Y141, M144, G145 and L148, and an intermolecular hydrogen bond between Y141 in α-helix 3 and Q58 in β-strand 1 of the KH  experiments of Sam68 QUA1-KH and STAR domains show that the QUA1 and KH domains and the C-terminal part of the linker adopt a rigid conformation , while the N-terminal half of the linker and the QUA2 region are flexible AA motif as high-affinity binding site for Sam68 and T-STAR41in vivo, we performed a genome-wide high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) experiment for T-STAR in adult mouse testis. In agreement with previous SELEX data, the CLIP tags are strongly enriched in adenine and uracil . In agrin2 ref. . In contin2 ref. , 39, 40.>15-(A/U)AA RNA sequence bound by Sam68 and T-STAR.The orientation of Sam68 and T-STAR KH dimers positions two (A/U)AA RNA motifs in an anti-parallel manner on opposite sides of the protein dimer with a distance >50 Å between the 3′ end of one RNA and the 5′ end of the other . This suCD44, Neurexin2 or Neurexin3 minigenes. Sam68 and T-STAR have previously been shown to induce the inclusion of CD44 exon v5  or repressing (Neurexin2 and Neurexin3) exon inclusion. To also investigate the importance of the length of the RNA target site for efficient splicing, we used a mutated version of the Neurexin2 minigene whose alternative splicing did not respond to Sam68 (ref. x4 or a (UAAA)x8 sequence downstream of exon AS4. Consistent with a requirement for a bipartite sequence for functional activity as suggested by our structural data, the insertion of a long (UAAA)x8 sequence produced skipping of exon AS4 in response to transfection with Sam68, while insertion of the shorter (UAAA)x4 did not  motif  motif , and thaA) motif . This sed uracil , the derd uracil . Accordiin vivo genome-wide CLIP experiments did not identify any propensity for secondary structure formation surrounding the (A/U)AA motifs. Similarly, previous analysis of SELEX sequences bound by T-STAR did not identify any secondary structuresbona fide ssRNA-binding domain.It has previously been suggested that Sam68 binds preferentially UAAA motifs in loop regions of structured RNAs, and that the structural context of the RNA influences Sam68-RNA binding>15-(A/U)AA RNA sequence. Interestingly, our data also indicate that the mutations in Sam68-Y241E and T-STAR-Y141E not only impair their dimerization and RNA-binding properties but also affect protein localization in the nucleus  and the KH domains bind specifically only four to five nucleotides and therefore, most splicing factors contain multiple RNA-binding domains (RRM or KH) to increase both affinity and specificity to their pre-mRNA targets. The STAR family is rather unique, in that it only contains a single KH domain, and specificity and affinity is thought to arise from their ability to dimerize. Our structural data explain clearly how the unique dimerization interface of Sam68 and T-STAR contribute to both specificity and affinity to the RNA by recognizing the bipartite (A/U)AA-N nucleus . Althoug nucleus . Notably nucleus , and mut nucleus . The subThe mechanisms by which Sam68 and T-STAR regulate alternative splicing remain poorly understood. Since the RNA sequence recognized by Sam68 could be found in numerous pre-mRNAs, how does Sam68 specifically affect only a subset of splicing events? Pre-mRNA molecules do not exist free in cells but interact with numerous RNA-binding proteins. Therefore, the consequence of Sam68-RNA interaction on splicing outcomes depends on the position of the bipartite RNA sequence relative to the splice sites, the competition for RNA binding by other splicing factors that compete for overlapping RNA sequences, the structure of the RNA or even post-translational modifications that are well known to affect Sam68 functions in alternative splicing. In some cases, it was proposed that Sam68 binding near splice sites can synergize or compete with the recruitment of other splicing factors, such as U2AF, hnRNP A1 or U1-70K142053CD44 and Neurexin3 alternative splicing  using the pLEICS-01 vector  for 16 h at 20 °C. Proteins were purified by affinity chromatography using Ni-NTA agarose (Qiagen) followed by tobacco etch virus (TEV) cleavage during overnight dialysis in phosphate buffer (20 mM sodium phosphate (pH 7), 100 mM sodium chloride and 10 mM β-mercaptoethanol) at 4 °C. Because short ssRNA oligonucleotides are easily prone to degradation, 5 μl SUPERaseIN RNase inhibitor (Invitrogen) was added to the protein sample and further purified by size-exclusion chromatography on a Superdex 75 10/300  into the desired buffer.Sam68 STAR (amino acids 97–283), KH-QUA2 (150–283) and KH (150–260) domains, and T-STAR STAR (1–183), KH-QUA2 (50–183) and KH (50–160) domains were cloned by the University of Leicester Cloning service , 1 vector . All plaSite-directed mutagenesis was carried out using overlap extension PCR with primers that contained the site of mutation centrally . Two PCR−1 and a protein/RNA molar ratio of 1:2. The T-STAR STAR domain in complex with AUUAAA RNA crystallized in 0.2 M NaCl, 0.1 M Na-HEPES (pH 7.5) and 24% PEG 4000 at a protein concentration of 15–20 mg ml−1 and a protein/RNA molar ratio of 1:2. The T-STAR KH-QUA2 domain in complex with AAUAAU RNA crystallized in 0.1 M imidazole (pH 8.0) and 8% PEG 8000 at a protein concentration of 10 mg ml−1 (protein/RNA molar ratio of 1:2).All the proteins constructs were dialyzed against 10 mM Tris (pH 7.0), 50 mM NaCl and all crystallization trials were performed using the sitting drop vapour diffusion method at 4 °C. The free KH domain and the KH-AAAUAA RNA crystallized as described previouslyCrystals were flash-frozen in mother liquor containing either 15% glycerol (QUA1-KH and STAR) or 15% 2-Methyl-2,4-pentanediol (MPD) (KH-QUA2).11 with four proteins per asymmetric unit. The phase of the KH free domain of T-STAR was solved using AutoSol1 with six proteins and one RNA per asymmetric unit. The phase was solved by molecular replacement using the structure of the SeMet KH domain as a template and the program PHASER12121 with two proteins and one RNA per asymmetric unit. The phase was solved by molecular replacement using the structure of the SeMet KH domain as a template and the program PHASER11 with two proteins and two RNAs per asymmetric unit. A model of the QUA1 domain of T-STAR was built using the NMR structure of Sam68 QUA1 domain11 with two proteins and two RNAs per asymmetric unit. The phase was solved by molecular replacement using the structure of the QUA1-KH domain as template and the program PHASERAll data sets were collected at the Diamond Light Source and processed using X-ray Detector Software (XDS)2PO4 (pH 6.2) and 50 mM NaCl for T-STAR constructs. Almost complete backbone resonance assignment of T-STAR KH and Sam68 STAR was achieved by using two-dimensional (15N–1H)-heteronuclear single quantum coherence spectroscopy (HSQC), three-dimensional (3D) HNCA, 3D HNCACB, 3D CBCACONH and 3D (15N–1H)-nuclear Overhauser effect spectroscopy (NOESY) spectra recorded at 303 K. All spectra were analysed with Sparky . Backbone chemical shifts of Sam68 STAR and T-STAR KH have been deposited to the BioMagResBank with accession numbers 26700 and 26701, respectively.NMR samples contained proteins at concentrations between 200 μM and 1 mM in 10 mM Tris (pH 7), 100 mM NaCl and 0.1% β-mercaptoethanol for Sam68 constructs, and 20 mM NaHHomology modelling of Sam68 QUA1-KH was carried out using the software Modeller−1 in the same buffers as those used for NMR. Protein–RNA complexes were measured at a concentration of 10 mg ml−1 protein and a protein/RNA molar ratio of 1:1. Circular averaging and background subtraction was done with the Rigaku SAXSLab software v 3.0.1r1. Molecular weights were calculated from the Porod volumes as described previouslyDmax, Porod volumes and distance distribution were calculated with GNOM, all part of the ATSAS package V 2.5.0-2 , 100 mM NaCl and 0.1% β-mercaptoethanol. Sam68 and T-STAR domains were serial diluted across the plate from 200 to 0 μM. Fluorescein-labelled RNA was then added at 0.2 μM final concentration. Plates were analysed using a PerkinElmer Victor X5 plate reader at excitation wavelength of 531 nm and emission at 595 nm.−2 and a wavelength of 254 nm using the Stratagene Stratalinker. The lysate was treated with DNase and RNase, followed by immunoprecipitation with 80 μl T-STAR antibody, and 3′ linker ligation. RNA bound to T-STAR was separated by SDS–polyacrylamide gel electrophoresis and a thin band at the size of 70 kDa (T-STAR migrates at ∼55 kDa and the molecular weight of 50 nt RNA is about 15 kDa) was cut out, RNA was recovered, ligated with 5′ linker and reverse transcribed into cDNA, which were then sequenced on a Roche 454 GS-FLX platform. Reads were processed to remove sequencing linkers and barcodes, filtered to remove PCR duplicates and mapped to the mouse genome (Mm9) using BowtieP value <0.05 for enrichment in T-STAR CLIP tags versus controls. The WebLogo was derived from tags containing the top 15 enriched k-mers using the online program WebLogo (http://weblogo.berkeley.edu/logo.cgi).HITS-CLIP was performed using a non-commercial affinity purified antibody raised against T-STARMinigene splicing experiments were carried out in HEK293 cells transfected using lipofectamine 2000 (Invitrogen). RNA was extracted with Trizol (Invitrogen), and analysed using a one-step RT–PCR (PCR with reverse transcription) kit from Qiagen, both using the standard protocol. RT–PCR experiments used 100 ng of RNA in a 5-μl reaction using primers within the β-globin exons of pXJ41; PXJRTF (5′-GCTCCGGATCGATCCTGAGAACT-3′) and PXJB (5′-GCTGCAATAAACAAGTTCTGCT-3′). Reactions were analysed by agarose gel electrophoresis and quantified by capillary gel electrophoresis. For localization assays, HEK293 cells were fixed after 24 h using paraformaldehyde, mounted in VECTASHIELD with 4,6-diamidino-2-phenylindole (DAPI) and then directly visualized for green fluorescence protein (GFP) expression using fluorescence microscopy.How to cite this article: Feracci, M. et al. Structural basis of RNA recognition and dimerization by the STAR proteins T-STAR and Sam68. Nat. Commun. 7:10355 doi: 10.1038/ncomms10355 (2016).Supplementary Figures 1-9 and Supplementary Tables 1-4.