In vitro replication and recombination assays confirm the direct role of the ATPase function of Ded1p in suppression of viral recombination. We also present data supporting a role for Ded1 in facilitating the switch from minus- to plus-strand synthesis. Interestingly, another co-opted cellular helicase, the eIF4AIII-like AtRH2, enhances TBSV recombination in the absence of Ded1/RH20, suggesting that the coordinated actions of these helicases control viral RNA recombination events. Altogether, these helicases are the first co-opted cellular factors in the viral replicase complex that directly affect viral RNA recombination. Ded1 helicase seems to be a key factor maintaining viral genome integrity by promoting the replication of viral RNAs with correct termini, but inhibiting the replication of defective RNAs lacking correct 5’ end sequences. Altogether, a co-opted cellular DEAD-box helicase facilitates the maintenance of full-length viral genome and suppresses viral recombination, thus limiting the appearance of defective viral RNAs during replication.The intricate interactions between viruses and hosts include an evolutionary arms race and adaptation that is facilitated by the ability of RNA viruses to evolve rapidly due to high frequency mutations and genetic RNA recombination. In this paper, we show evidence that the co-opted cellular DDX3-like Ded1 DEAD-box helicase suppresses tombusviral RNA recombination in yeast model host, and the orthologous RH20 helicase functions in a similar way in plants.  in vitro, that co-opted cellular helicases by TBSV affect viral recombination through suppressing template-switching and replication of the new recombinant viral RNAs. Based on the presented data, a new concept emerges on the roles of co-opted cellular helicases in maintaining viral genome integrity. Altogether, the hijacked cellular DEAD-box helicases are involved in maintenance of full-length viral RNA genome and suppression of viral RNA recombination, thus blocking the appearance of defective or recombinant viral RNAs during replication.A major force in virus evolution is the ability of viruses to recombine and change their genomes rapidly. Similar to viral replication that greatly depends on subverted cellular proteins, viral genetic recombination is also affected by host factors based on genome-wide screens with tomato bushy stunt virus (TBSV) in yeast model host. However, the roles of host factors in the viral genomic RNA recombination process remain elusive. In this paper, we show evidence, in yeast, plants and  RNA viruses replicate inside cells and they require many cellular factors to complete their infection cycle. The intricate interactions between viruses and hosts include evolutionary arms race and adaptation that is facilitated by the ability of RNA viruses to evolve rapidly due to high frequency mutations and genetic RNA recombination as well as reassortment of genomic components –3. InterTomato bushy stunt virus (TBSV), a tombusvirus infecting plants, using yeast (Saccharomyces cerevisiae) model host. TBSV is an outstanding model for both replication and recombination studies . Th. Thin vi)repRNAs , lane 2,in vitro , lane 3.in vitro assay with a soluble form of p92, called p92-Δ167N, which can specifically use TBSV-derived (+)RNA template for RNA synthesis in vitro in the presence of biotynylated UTP and other ribonucleotides as shown schematically in Based on known features of DEAD-box helicases in remodeling protein-RNA complexes ,64, we r32P-labeled RI(+) RNA as a probe. Both MBP-p92-Δ167N and GST-Ded1p bind to the probe when applied alone RNA and the eIF4AIII-like Fal1p/AtRH2 helicases that bind to a 5’ proximal enhancer element in the (-)RNA  49,54],,54,49,54ng AtRH2 , which is yeasts . Thus, dTo test if AtRH2 has direct function in TBSV recombination, we used the CFE-based TBSV replication assay prepared from yeast with depleted Ded1p . InteresNicotiana benthamiana plants also expressing DI-AU-FP repRNA in the presence of Cucumber necrosis virus (CNV), a closely related tombusvirus that serves as a helper virus for the TBSV repRNA. The helper tombusvirus provides the p33 and p92 replication proteins in trans for the replication of repRNA and the de novo generated recRNAs in this system. We found that the Ded1p ortholog AtRH20 suppressed TBSV recRNA accumulation by ~2-fold, while AtRH2 increased recRNAs by ~2-fold  RNA synthesis is completed on the (+)RNA template  49,50,5,550,54. in vitro when Ded1p mutant is present, while the (+)repRNA is more abundant than (+)recRNAs or (+)degRNAs -strand synthesis.However, this work also reveals a new role of Ded1p in inhibition of (-)-strand synthesis, especially with those RNA templates that lack authentic 5’ sequences, such as degRNAs and recRNAs Figs. –3. InterAs Figs. –3. In caAs Figs. . Thus, oDed1p-driven suppression of replication of degRNAs might be critical in cells loaded with cytosolic ribonucleases that likely generate many truncated viral RNAs. These defective RNAs could likely compete with the full-length viral RNAs for viral- and host factors, thus leading to reduced viral replication. However, the co-opted cellular Ded1p helicase facilitates proper replication of TBSV RNAs and protects TBSV from competition by defective viral genomes. Since Ded1p inhibits the replication of recRNAs or degRNAs lacking the authentic 5’ end sequence through blocking the (-)-strand synthesis on these RNA templates, lesser amount of defective viral dsRNAs could accumulate. The reduced amount of dsRNA is an advantage for the virus, because dsRNAs could efficiently trigger antiviral responses, such as RNAi (or RNA silencing in plants) –74.Another surprising finding in this study is the stimulatory effect of a second group of co-opted cellular DEAD-box helicases on TBSV RNA recombination. Accordingly, over-expression of the eIF4AIII-like AtRH2 in yeast or plant cells led to increased level of recRNA accumulation Figs. –8.The AtRH2 helicase binds to the 5’ proximal region of the viral (-)RNA, which harbors the RIII(-) REN, resulting in localized unwinding of the dsRNA replication intermediate ,54. Althcis-acting elements in the (-)RNA portion of dsRNA, followed by (+)-strand synthesis via strand-displacement mechanism as shown before , and this condition then facilitates template-switching-based RNA recombination . In addiOverall, the novel function of the DDX3-like Ded1p/RH20 helicases is the down-regulation/inhibition of (-)RNA synthesis by promoting the efficient switch from (-)RNA to (+)RNA synthesis. Interestingly, this feature requires the authentic viral 3’ end sequences on the (-)RNA, suggesting similarities between telomeres and viral RNA synthesis in protection of the ends of linear nucleic acids ,76. ThosSaccharomyces cerevisiae) strain BY4741 (MATa his3(1 leu2(0 met15Δ0 ura3(0), R1158 and TET::DED1 (yTHC library) were obtained from Open Biosystems. The temperature-sensitive (ts) yeast strains ded1–95ts and ded1–199ts were of generous gift from C. Boone (U. Toronto).The yeast , and HpHisGBK-His33/DI-AU-FP , HpHisGBK-HFHis33/DI-72 , UpGBK-His33/DI-AU-FP  have been previously described [EcoRI and SacI and ligated into the plasmid HpGBK-His33/DI-72 to replace the full-length DI-72 fragment.The yeast expression plasmids LpGAD-His92  and #3957 (CCAGGAATTCATGGCTGAACTGAGCGAACAAG). The PCR products were cloned into pMalc-2x vector at EcoRI and PstI sites. For GST-Ded1p expression, pMAL-Ded1 was used as a template in PCR with primers #4308 (TGGAACTTGGAATTGTTTACACCTTAGTCTGTTGACTTAA) and #4309 (CCAGCTCGAGTCACCACCAAGAAGAGTTG). The PCR products were cloned into pGEX-his-RE vector at SpeI and XhoI site.The eviously ,54. To pBamHI and PstI sites.The plant expression plasmids pGD-RH2, pGD-RH20, pGD-CNV and pGD-DI-AU-FP were described previously ,65. To ots, ded1–199ts, R1158 and TET::DED1, yeast strains were co-transformed with LpGAD-His92 and HpGBK-His33/DI-AU-FP, HpGBK-His33/DI-RIIΔ70 or HpHisGBK-HFHis33/DI-72. The transformed BY4741, ded1–95ts, and ded1–199ts strains were pre-grown at 23°C overnight in SC-LH- (synthetic complete media without histidine and leucine) media with 2% galactose. Then, 50 μM CuSO4 was added to the yeast cultures to launch virus replication and recombination. Yeast was grown at either 23°C or 29°C for 24 h before sample collection for analysis. The transformed R1158 and TET::DED1 strains were pre-grown at 29°C overnight in SC-ULH-  media with 2% galactose containing 10 μg/ml doxycycline. Then, 50 μM CuSO4 was added to the yeast cultures to launch virus replication and recombination at 23°C or 29°C for 24 h.Yeast strains were co-transformed with plasmids by using the lithium acetate/ssDNA/polyethylene glycol method, and transformants were selected by complementation of auxotrophic markers . For TBSts strains were co-transformed with LpGAD-His92, UpGBK-His33/DI-AU-FP and the indicated plasmids (HpGBK-HisRH20 or HpGBK-HisRH2) expressing one of the host helicases. The transformed yeast strains were pre-grown at 23°C overnight in SC-ULH- media with 2% galactose, followed by the addition of 50 μM CuSO4 and culturing at 23°C or 29°C for 24 h.In the complementation study, BY4741 and ded1–199ts, and ded1–199ts strains were transformed with UpYC-DI-RIIΔ70 [- media with 2% galactose. After 24 h, the cultures were re-suspended in SC-U- media with 2% glucose and grown at 23°C or 29°C. The samples were collected at given time points mentioned in figure legend.For viral RNA stability assay, BY4741 ded1–95I-RIIΔ70 . The trats yeast strains, they were co-transformed with HpGBK-His33, LpGAD-His92 and pYC2-DI-/ #1165 (AGCGAGTAAGACAGACTCTTCA) for (+)RNA detection; and primers #18 (GTAATACGACTCACTATAGGAGAAAGCGAGTAAGACAG) / #1190 (GGGCTGCATTTCTGCAATG) for (-)RNA detection.TBSV RNA recombination was analyzed using total RNA extracted from yeast and plants. Standard RNA extraction and Northern blot analysis was performed as described in previous publication . To deteTyphoon FLA 9500 system (GE) and ImageQuant TL software were used to detect and quantify the bands in the gels. The repRNA and degRNA bands were identified based on molecular markers, while the recRNAs were identified based on previously characterized recRNAs ,16,58,65E coli and purified as published before [E. coli strain BL21 (DE3) CodonPlus. Protein expression was induced by isopropyl-β-D-thiogalactopyranoside (IPTG) at 16°C for 8 h. After collection of the cultures by centrifugation at 4000 xg for 5 min, the cells were re-suspended and broken in reduced-salt column buffer . The lysate was centrifuged at 14,000 rpm for 10 min to remove cell debris. Then, the supernatant was incubated with amylose resin (NEB) at 4°C for 1 h. After washing the resin with 50 ml reduced-salt column buffer (without β-mercaptoethanol), the recombinant proteins were eluted in maltose buffer (column buffer containing 0.18% (W/V) maltose).Recombinant MBP-tagged helicase proteins and MBP-tagged TBSV p33 and p92 replication proteins or MBP-p92Δ167N were expressed in d before . Brieflyin vivo-assembled replicase complexes as previously described [6-tagged p33 and comparable amounts of replicase (based on p33) from each preparation were used in the subsequent in vitro replicase assay. The replicase assay was performed as described [in vitro assay (50 μl) contained 10 μl of the normalized MEF preparations, 10 mM DTT, 50 mM Tris-Cl pH 8.0, 10 mM MgCl2, 0.1 U RNase inhibitor, 1 mM ATP, 1 mM CTP, 1 mM GTP and 0.1 μl of α32P-UTP (3000 Ci/mmol). Reaction mixtures were incubated at 25°C for 3h, followed by phenol/chloroform extraction and isopropanol/ammonium acetate (10:1) precipitation. 32P-labeled RNA products were analyzed in 5% acrylamide/8 M urea gels. To detect the membrane associated RNA, membrane preparations that contained comparable amounts of replicase were used to extract the viral RNA by standard phenol/chloroform extraction and isopropanol/ammonium acetate (10:1) precipitation. Then, the RNAs were analyzed by Northern blotting with (+) or (-) RNA specific probes.The membrane-enriched fraction (MEF) was obtained as published previously ,78. Brieescribed ,78. Brie32P-labeled RNA products were analyzed in 5% acrylamide/8 M urea gels [CFEs from BY4741 and TET::DED1 treated with 10 μg/ml doxycycline were prepared as described earlier ,62 and a32P-labeled full-length DI-72 (-)RNA and the RI(+) RNA were generated as described [32P-labeled DI-72(-) RNA probe in a binding buffer  at 25°C for 15 min. After the binding, the samples were analyzed by 5% nondenaturing PAGE performed at 200 V for 1 h in a cold room. To test the template release activity, briefly, 32P-labeled RI(+)RNA probe was incubated with p92-Δ167N at 25°C for 15 min, followed by adding affinity-purified GST-Ded1p to the reaction with or without 1 mM ATP, then the reaction was incubated at 25°C for 30 min. In addition, probe was also incubated with proteins in a different order mentioned in figure legend.The escribed . Ded1p ain vitro RdRp reaction was performed in 20 μl total volume containing 1 μl of adjusted CFE (soluble fraction only), 0.5 μg DI-mini (+)RNA transcript [in vitro reactions in the subsequent experiment. After incubation, the free, unincorporated biotin-UTP was removed by Sepharose G-25 column. Then, 200 μl of in vitro RdRp reaction mixture were incubated with Strepavidin-beads  at 25°C for 10 min to capture the biotin-labeled RNA and the RNA-bound p92-Δ167N RdRp as well. Then, we washed the beads once with 0.1% SSC buffer, followed by incubation of the beads with GST-Ded1p or GST (as a control) in RdRp buffer  with 1 mM ATP at 25°C for 10 min to elute (release) the p92-Δ167N RdRp from the streptavidin-bound RNA. Then, we collected and precipitated the eluted proteins with 10% TCA. The precipitated proteins  or pGD-RH20 (OD600 = 0.3) together with pGD-CNV (OD600 = 0.3) and pGD-DI-AU-FP (OD600 = 0.3) to launch tombusvirus replication and induce RNA recombination. Leaf infiltration with A. tumefaciens carrying “empty” pGD plasmid was used as a control. We also performed agroinfiltration with pGD-p33 + pGD-p92+ pGD-DI-ΔRI at a final concentration of 0.3 (OD600). Three and four days after agro-infiltration, samples from the agro-infiltrated leaves were collected from the agroinfiltrated leaves. Total RNA was extracted and Northern blot analysis was performed as previously described [Cultures of and RH20 ,61. N. bescribed .


As a large family of RNA-binding proteins, pentatricopeptide repeat (PPR) proteins mediate multiple aspects of RNA metabolism in eukaryotes. Binding to their target single-stranded RNAs (ssRNAs) in a modular and base-specific fashion, PPR proteins can serve as designable modules for gene manipulation. However, the structural basis for nucleotide-specific recognition by designer PPR (dPPR) proteins remains to be elucidated. Here, we report four crystal structures of dPPR proteins in complex with their respective ssRNA targets. The dPPR repeats are assembled into a right-handed superhelical spiral shell that embraces the ssRNA. Interactions between different PPR codes and RNA bases are observed at the atomic level, revealing the molecular basis for the modular and specific recognition patterns of the RNA bases U, C, A and G. These structures not only provide insights into the functional study of PPR proteins but also open a path towards the potential design of synthetic sequence-specific RNA-binding proteins. Pentatricopeptide repeat (PPR) proteins bind RNA and are involved in the regulation of RNA metabolism in eukaryotes. Here, the authors examine the capability of these proteins as modules for gene manipulation using structural biology methods. The ability to design proteins to manipulate specified target DNA/RNA sequences has been a long-sought but elusive goal46911131415Arabidopsis thaliana and of human mitochondrial RNA polymerase1921231525PSAJ–PPR10 complex corroborates this binary code model25262122282915A typical PPR repeat, also referred to as a PPR motifIn the past decade, many PPR genes have been identified and extensively studied15A. thalianaZea mays onto the amino and carboxyl termini. Engineered designer (dPPR) proteins can specifically select their predicted RNA targets according to PPR codes in vitro. Artificial manipulation of the PPR code amino acids, rather than the PPR repeat scaffolds, leads to specific RNA recognition. Similar results and crystal structures of artificially engineered PPR proteins free of target RNA have also been reported by other groups29in vitro. Despite these advances, the lack of a structure of a dPPR–RNA complex has hindered the elucidation of RNA recognition by dPPR proteins and, more importantly, has restricted the development of more efficient RNA manipulation tools.Previously, our group has successfully designed 35-amino-acid PPR repeat scaffolds, determined via comprehensive computational homology analysis of P-type PPR proteins from To determine how dPPR proteins specifically accommodate and recognize their single-stranded RNA (ssRNA) targets, we designed and purified a set of homogeneous dPPR proteins with high-target recognition specificity and solved the crystal structures of four different dPPR proteins in complex with their respective target ssRNAs. A typical RNA-bound dPPR protein adopts a right-handed superhelical spiral structure, with its target ssRNA molecule sitting in the interior cavity and interacting with corresponding PPR repeats in a modular fashion. These structures also reveal atomic-level interaction patterns among all four RNA bases  with different PPR codes. On the basis of our structural discoveries, models of RNA recognition by some additional PPR codes were verified. Together, our findings not only provide detailed modular and specific binding patterns of dPPR repeat, but also establish an important framework for gene-manipulation applications.Z. mays were fused onto the amino and carboxyl termini of a series of tandem dPPR repeats as amino-terminal domain (NTD) and carboxyl-terminal domain (CTD), to enhance the solubility of the engineered protein (8N2 (in which N indicates any nucleotide) comprising 10 dPPR repeats with different 5th and 6th repeats with different PPR codes were constructed and purified to homogeneity. Each of the four dPPR-U8N2 proteins specifically bound to its respective target ssRNA with a dissociation constant of ∼20 –75 nM, as estimated on the basis of the results of electrophoretic mobility shift assay (EMSA) (8N2 binding (On the basis of previous investigation protein . To veriy (EMSA) . The sub binding . For insFurthermore, we were able to target a specific ssRNA sequence by assembling dPPR proteins with a combination of four types of PPR codes. For example, dPPR-4, which comprises eight dPPR repeats with all four types of dPPR code, bound to its predicted target RNA with high specificity as expected. The dissociation constant was ∼25 nM . In summ8N2 in complex with its respective target ssRNA (5′-UUUUNNUUUU-3′), in space group P212121 (Methods). These four structures were determined by molecular replacement (MR) using the atomic coordinates of the consensus PPR10, dPPR-U8C2, dPPR-U8A2 and dPPR-U8G2, respectively , which are capped by NTD and CTD helices 8C2 structure, each helix b stacks against the helix a of the following repeat through extensive van der Waals interactions, forming an inter-repeat structure similar to a three-helix bundle  and dPPR-U8C2 all exhibit superhelical spiral shapes, they are distinct from one another in their configurational details. Although it has a similar diameter to RNA-free cPPR-polyC and synthPPR3.5, RNA-bound dPPR-U8C2 exhibits a more compact conformation with a helical period length of ∼70 Å, which is shorter than that of cPPR proteins  are almost identical indicates that RNA binding may change the interaction between PPR hairpin-shaped motifs and induce conformational changes. Compared with RNA-bound PPR10 (repeats 6–15), RNA-bound dPPR-U8C2 also exhibits in a tighter form, and there is a 20-Å difference between their diameters  have revealed atypical modular and dimeric RNA-targeting modes22ATPH-PPR10 is monomericAs a larger family of sequence-specific RNA-binding proteins, PPRs play various important roles in all aspects of organelles' RNA metabolism39212226Our data reveal that a dPPR protein recognizes its specific ssRNA target via hydrogen-bond-mediated interaction between the dPPR repeats and their coordinating nucleobases . The mos252615Furthermore, our high-resolution structures provide precise information about RNA coordination by PPR repeats. Several additional important amino acids in dPPR repeats, such as Val2 and Lys13 , also coin silico424546Together, our structural analyses should help to improve the mechanistic perception of the PPR protein and facilitate the optimal design of useful tools for RNA manipulation with enhanced specificity and affinity. Furthermore, our work may serve as a model to explore the α-helical repeat protein universe E. coli BL21(DE3). One litre lysogeny broth medium supplemented with 100 μg ml−1 ampicillin was inoculated with a transformed bacterial pre-culture and shaken at 37 °C until the optical density at 600 nm reached 1. The culture was cooled to 16 °C and induced with 0.2 mM isopropyl-β-D-thiogalactoside. After growing for 16 h at 16 °C, the bacterial pellet was collected and homogenized in buffer A . After sonication and centrifugation at 23,000g at 4 °C, the supernatant was loaded onto a column equipped with Ni2+affinity resin , washed with buffer B , and eluted with buffer C  followed by ion exchange . Each protein was then subjected to gel filtration chromatography . The buffer for gel filtration contained 25 mM Tris–HCl, pH 8.0, 100 mM NaCl, 5 mM MgCl2 and 5 mM 1,4-dithiothreitolDTT  and then subcloned into the pET21b vector (Novagen), resulting in recombinant dPPR proteins fused with a 6 × His tag at the C-termin. The plasmids were transformed into eitolDTT . The pea10 boundaries and corresponding RNA oligonucleotides (Takara). Finally, dPPR-U10 (residues 123–572) and 18-nt RNA 5′-ggggUUUUUUUUUUcccc-3′ were crystallized in the reservoir solution 11–13% (w/v) polyethylene glycol 3,350, 100 mM Bis-Tris propane, pH 6.5, 150 mM MgCl2. However, the crystals exhibited poor diffraction, diffracting only to 8 Å. To generate dPPR-U10 crystals with good X-ray diffraction, two rounds of additive screening were performed. The first additive screen revealed that ethyl acetate improved the diffraction to 3.5–4 Å. In this context, a second additive screen was then performed. Finally, the best crystals were obtained under the following conditions: 11–13% (w/v) polyethylene glycol 3,350, Bis-Tris propane, pH 6.5, 150 mM MgCl2, 1.5% ethyl acetate and 3% (w/v) D-(+)-glucose monohydrate. The crystals were flash frozen in liquid nitrogen using a 2 × mother solution as the cryoprotective buffer and diffracted beyond 2.3 Å at Shanghai Synchrotron Radiation Facility (SSRF) beamline BL19U.To obtain crystals of dPPR–RNA complexes, we first examined various combinations of dPPR-U8C2, dPPR-U8A2 and dPPR-U8G2; residues 123–572) and their corresponding 18-ntRNAs with sequences ofThe other three proteins , catalysed by T4 polynucleotide kinase (Takara). For EMSA, dPPR proteins were incubated with ∼2 nM 32P-labelled probe in final binding reactions containing 25 mM Tris–HCl, pH 8.0, 5 mM MgCl2, 5 mM 1,4-dithiothreitol, 0.1 mg ml−1 bovine serum albumin, 50 ng ml−1 heparin and 10% glycerol for 20 min on ice. The reactions were then resolved on 8% native acrylamide gels (37.5: 1 acrylamide: bis-acrylamide) in 0.5 × Tris-glycine buffer under an electric field of 15 V cm−1 for 40 min. Gels were visualized on a phosphor screen (Amersham Biosciences) using a Typhoon Trio Imager (Amersham Biosciences). All presented images are representative of results from at least three independent experiments.The ssRNA oligonucleotides were radiolabelled at their 5′ ends with [γ-Accession codes: The atomic coordinates and structure factors for the four structures in complex with RNA have been deposited in the Protein Data Bank (PDB) with the accession codes 5I9F (poly-U), 5I9G (poly-UC), 5I9D (poly-UA) and 5I9H (poly-UG).How to cite this article: Shen, C. et al. Structural basis for specific single-stranded RNA recognition by designer pentatricopeptide repeat proteins. Nat. Commun. 7:11285 doi: 10.1038/ncomms11285 (2016).Supplementary Figures 1-9, Supplementary Table 1 and Supplementary References.


Experimental designs constitute a vital component of all Stated Choice (aka discrete choice experiment) studies. However, there exists limited empirical evaluation of the statistical benefits of Stated Choice (SC) experimental designs that employ non-zero prior estimates in constructing non-orthogonal constrained designs. This paper statistically compares the performance of contrasting SC experimental designs. In so doing, the effect of respondent literacy on patterns of Attribute non-Attendance (ANA) across fractional factorial orthogonal and efficient designs is also evaluated. The study uses a ‘real’ SC design to model consumer choice of primary health care providers in rural north India. A total of 623 respondents were sampled across four villages in Uttar Pradesh, India.Comparison of orthogonal and efficient SC experimental designs is based on several measures. Appropriate comparison of each design’s respective efficiency measure is made using D-error results. Standardised Akaike Information Criteria are compared between designs and across recall periods. Comparisons control for stated and inferred ANA. Coefficient and standard error estimates are also compared.The added complexity of the efficient SC design, theorised elsewhere, is reflected in higher estimated amounts of ANA among illiterate respondents. However, controlling for ANA using stated and inferred methods consistently shows that the efficient design performs statistically better. Modelling SC data from the orthogonal and efficient design shows that model-fit of the efficient design outperform the orthogonal design when using a 14-day recall period. The performance of the orthogonal design, with respect to standardised AIC model-fit, is better when longer recall periods of 30-days, 6-months and 12-months are used.The effect of the efficient design’s cognitive demand is apparent among literate and illiterate respondents, although, more pronounced among illiterate respondents.This study empirically confirms that relaxing the orthogonality constraint of SC experimental designs increases the information collected in choice tasks, subject to the accuracy of the non-zero priors in the design and the correct specification of a ‘real’ SC recall period. The use of Stated Choice (SC) methods within health economics is widespread. The research focuses of SC studies in this literature are diverse covering a range of perspectives. These include: patient preferences for non-market medical interventions, health professional preferences towards prescribing medicines and treatments, health care priority setting and consumer preferences towards health insurance schemes –3]. A l. A l3]. Experimental designs determine the purposeful mixing of choice alternatives’ attributes and their levels. Different statistical properties and constraints governing the mixing of attribute levels are used in many SC studies across the broad field of applied economics ,8]. Ort. Ort8]. Despite the established use of efficient designs in several applied economic fields, the health economic literature is firmly centred on applying orthogonal designs . Recent In all SC studies, the analyst must select the experimental design prior to going into the field. Whilst in theory efficient designs should perform better, there is little (and mixed) supporting empirical evidence. The work of Louviere et al.  indicateDespite the above being known, what has not been studied to date are other effects of using different designs. There exists SC literature on design features, which states that designs may influence the outcome or process used in answering the questions shown ,13]. At. At13]. This paper statistically compares the effect of respondent literacy on patterns of ANA across fractional factorial orthogonal and efficient designs. Literate and illiterate sub-samples of respondents provide a natural context to compare the cognitive burden of experimental designs and the resulting modelled output ,20]. Th. Th20]. The current study is based on consumers’ choice of a ‘real’ market good – choice of health care provider to treat fever symptoms in rural north India. Although many SC studies measure preferences for non-market goods, another set of SC studies - termed ‘real’ SC surveys – model choice for market goods –23]. Re. Re23]. orthogonal and efficient are used to refer to fractional factorial orthogonal and efficient designs respectively. Efficient designs relax the orthogonality constraint and allow for some correlation across levels and the use of non-zero priors. The term ‘efficient’ follows the same use by Scarpa et al. . Tw. Tw27]. a health care providers in the north Indian state of Uttar Pradesh (UP). This demand is based on the counter-fractural assumption that government rural Bachelor of Medicine and Bachelor of Surgery (MBBS) doctors are always available at their assigned rural Primary or Community Health Centre ..a healthSurvey respondents for the purposes of the design comparison come from two UP districts covering two of the four economic regions of the state. One district is from the Bundelkhand (southern region) and the other is from the Eastern region. These districts approximately represent the interquartile range of mean per capita income across UP . Three djhola chhaap)b, ii) private MBBS, iii) government MBBS doctors and iv) other category. The attributes of price, recommendations, distance and medicine were selected to construct the design following the collection and analysis of qualitative interview data [Ngene software [Consumers’ preferences for outpatient health care services for fever treatment are estimated with data collected through a SC survey. The survey, using two experimental designs, has four alternatives: i) unqualified private sector providers  and Information Criterion, to assess the performance of alternative experimental designs may misrepresent the value of any given design in estimating the preferences of respondents. Table The presence of dominant alternatives in choice tasks, while lowering the log-likelihood measures of model fit, limits the amount of information collected from any given choice task. The reduced information on the trade-offs of levels across choice task alternatives increases the risk of biased parameter estimates. Moreover, reliance on log-likelihood based goodness-of-fit measures, such as Rural blocks and their corresponding villages were selected in a stratified quasi-random sampling frame. District administrative blocks were randomly selected and from selected blocks, gram panchayats  were then randomly selected. Relationships with elected village leaders in each of the sample villages were developed during several preliminary visits associated with collecting qualitative data. Village households were randomly selected by enumerators with either the personal or delegated assistance of village leaders. As per ethics approval, no incentives were given to respondents and all respondents were verbally informed as to their right to end their involvement in the survey without penalty. Respondents provided verbal consent before commencing any surveys.A total of 623 respondents were sampled across four villages in September 2012. A total of 5607 choice tasks were completed. The Bundelkhand sample (district 1) answered 3285 choice tasks from each design and from the Eastern region (district 2) the sample was 2322. Each respondent answered choice tasks from one randomly assigned design. On average the survey was completed in 25 minutes. The majority of this time was spent introducing the survey in reduced form . Respondents were then progressively stepped through larger choice tasks until the enumerator was satisfied the respondent understood the concept of the survey.A select set of socio-economic characteristics of the sample answering orthogonal and efficient choice tasks in districts 1 and 2 is presented in Table The recall periods of the most recent episode of fever are also consistent across respondents in the two experimental designs. Table Nlogit (version 5) was used for all modelling. The probability of making a choice is estimated with the following MNL formA multinomial logit (MNL) model is used to identify the determinants of consumer choice of health providers in rural north India. The use of a MNL model follows the empirical design comparison of Bliemer and Rose . Nlogit j is the number of alternatives, xi is a vector of consumer (i.e. decision-maker) characteristics and i represents an individual consumer. This model assumes that each choice made is independent from all others (IID assumption).where Distance , ii) Recommendations (private MBBS), and iii) positive Recommendation (government MBBS) differ. The coefficient signs in the efficient design for i) and ii) are as expected. The third is not.The parameter estimates of designs, assuming full attribute trade-offs for the samples in districts 1 and 2, are presented in Table ρ2 of 0.36 translates into a standard linear regression-based coefficient of determination measure of approximately 0.7 [ρ2 is 0.318. The ρ2 measure continued to show that the orthogonal design/data is a better fit, however, this measure is dataset specific and so should not be the basis for comparison.The model fit statistics indicate that the orthogonal design fits the data better than the corresponding efficient design and data. The Akaike Information Criteria (AIC) for the orthogonal design and data are also lower. This is also true for the standardised AIC. A tely 0.7 . The effThe parameter t-ratios from the orthogonal design are also consistently higher than those from the efficient design. Twelve t-ratios from the orthogonal design are larger than their corresponding efficient design t-ratios. Of these, nine are statistically significant at the five per cent level.Distance , ii) positive Recommendation , and iii) positive Recommendation (government MBBS) differ between the two designs. Those associated with the efficient design are as expected.A subset of the sample data from each design, based on those respondents who reported having at least a mild fever within the previous 14-days, in Table The standardised AIC scores show that the efficient design and data provide a better fit to the MNL model. The efficient design has a standardised AIC of 1.50 compared to the orthogonal result of 1.60.Continued modelling using progressively longer recall periods and four alternatives shows that the standardised AIC measure of the two designs converged and then the orthogonal design consistently has lower scores. Figure Following on from the more consistent performance of the full trade-off MNL model of 14-day or less recall period (see Table Controlling for stated ANA helps provide more consistent coefficients. Only one set of coefficients have differing signs in the results summarised in Table Ec)A Latent Class (LC) model allows for parameter heterogeneity across individual respondents with the use of discrete latent classes. Individuals are allocated to a class according to a non-parametric marginal probability. Within each class, choice probabilities are generated using a MNL model. Equation  outlinet denotes individual choice task completed by a given respondent and c denotes class. Expanding the expected value over all nominated classes equation  full trade-offs are assumed, ii) stated ANA is incorporated into MNL models and iii) inferred ANA is modelled using a LC model (results not shown in paper). The evidence of this pattern under differing attribute trade-off assumptions suggests that the benefits of greater information collected through efficient designs outweighs the potential noise created by inconsistent respondent choices due to cognitively more complex efficient designs.Controlling for design induced alternative dominance indicates that the estimated results from choice tasks that contain fewer dominant alternatives provide more consistently paired coefficients and standard errors. Among the ‘no dominance’ group of choice tasks the efficient design results continue to provide higher coefficients and lower standard errors. The opposite is true of choice tasks in the ‘weakly dominant’ group. Of the nine choice task from each design defined as at least ‘weakly dominant’, three orthogonal designs induced estimated probabilities for the dominant alternative at ≥ 0.95, while the corresponding number of efficient design choice tasks is five. The lower number of dominant choice task, defined by design and the data, is thought to help produce higher coefficients and lower standard errors.Distance parameter for the unqualified – jhola chhaap - provider remained negative for the efficient design and positive for the orthogonal. The increase in distance travelled to consult a health care provider is expected to reduce the likelihood of consulting that provider, all other things being equal. The positive Distance coefficient in the orthogonal design maybe a result of uncontrolled heuristics.However, the repeated opposing coefficient signs between the two designs, across several parameters and when controlling for ANA and recall bias, is unexpected. Controlling for non-trading across choice task attributes through stated ANA reduced the number of opposing coefficient signs, however, the The higher estimated probabilities in the LC model among the orthogonal design, associated with respondents trading across all attributes, indicates that respondents are less likely to employ choice task heuristics. These higher probabilities, relative to efficient design choice tasks in Tables The use of a MNL model as the basis for model fit design comparisons is a limiting factor of this analysis. While MNL output is generally robust against significant biases, the IID assumption is strong and may have an unaccounted affect on model fit. Moreover, the effects of choice task blocking is also not controlled in the study.The cognitive demands of efficient designs have a real impact on the likelihood of respondents’ employing choice task heuristics. The effect of the perceived cognitive demand of the efficient design is apparent among literate and illiterate respondents, however, it is more pronounced among illiterate respondents. Accounting for ANA when modelling choice data further enhanced the comparative statistical performance of the efficient design.The use of an appropriate D-error measure provides an important insight into the performance of different experimental designs. However, as speculated in the literature, the role of alternative dominant choice tasks, either by design and/or ANA, also affects commonly used goodness-of-fit measures. As such care should be taken in the comparative evaluation of alternative experimental designs.This study empirically confirms that relaxing the orthogonality constraint of SC experimental designs increases the reliable information collected in choice tasks, subject to the correct specification of a ‘real’ SC recall period. As model parameter estimates diverge from the non-zero priors used in the efficient design construction, the relative statistical performance of the orthogonal design improves and outperforms the efficient design. Although not presented in this study, the importance of convergence between non-zero priors and model parameter estimates suggests that SC Bayesian experimental designs would better manage potential non-zero prior uncertainty.aAllopathic health care in India is based primarily on the use of pharmaceutical goods to treat symptoms. This is in contrast to traditional Indian systems of medicine.bA range of terms are used to define unqualified allopathic health care providers in India, however, the term jhola chhap is widely used among rural north Indian settings and is also acknowledged in legal settings (see: [gs (see: ).The authors declare that they have no competing interests.RI conceived of the study, participated in the experimental design, managed the collection of data, carried out data manipulation and statistical analysis and drafted the manuscript. JR participated in the experimental design and assisted in framing the experimental design comparison. Both authors read and approved the final manuscript.Appendix A (presentation of SC choice task in English).Click here for file


Pseudomonas aeruginosa which was grown in glucose-supplemented (control) and polyethylene-supplemented (growth-limiting condition) minimal medium. All three extraction methods were coupled with an in-house DNase I treatment before the yield, integrity and size distribution of the purified RNA were assessed. RNA samples extracted with the best extraction kit were then sequenced using the Illumina HiSeq 2000 platform.Next-generation transcriptome sequencing (RNA-Seq) has become the standard practice for studying gene splicing, mutations and changes in gene expression to obtain valuable, accurate biological conclusions. However, obtaining good sequencing coverage and depth to study these is impeded by the difficulties of obtaining high quality total RNA with minimal genomic DNA contamination. With this in mind, we evaluated the performance of Phenol-free total RNA purification kit (Amresco) in comparison with TRI Reagent (MRC) and RNeasy Mini (Qiagen) for the extraction of total RNA of TRI Reagent gave the lowest yield enriched with small RNAs (sRNAs), while RNeasy gave moderate yield of good quality RNA with trace amounts of sRNAs. The Phenol-free kit, on the other hand, gave the highest yield and the best quality RNA  with good amounts of sRNAs. Subsequent bioinformatic analysis of the sequencing data revealed that 5435 coding genes, 452 sRNAs and 7 potential novel intergenic sRNAs were detected, indicating excellent sequencing coverage across RNA size ranges. In addition, detection of low abundance transcripts and consistency of their expression profiles across replicates from the same conditions demonstrated the reproducibility of the RNA extraction technique.Amresco’s Phenol-free Total RNA purification kit coupled with DNase I treatment yielded the highest quality RNAs containing good ratios of high and low molecular weight transcripts with minimal genomic DNA. These RNA extracts gave excellent non-biased sequencing coverage useful for comprehensive total transcriptome sequencing and analysis. Furthermore, our findings would be useful for those interested in studying both coding and non-coding RNAs from precious bacterial samples cultivated in growth-limiting condition, in a single sequencing run.The online version of this article (doi:10.1186/s13104-015-1726-3) contains supplementary material, which is available to authorized users. Bacteria play major roles in our everyday lives in more ways than one can imagine. Depending on the environment, bacteria can be detrimental by being causative agents for various diseases , 2 or beObtaining these valuable biological and molecular insights into the transcriptome of bacterial cells is now possible with the introduction of next-generation sequencing (NGS) platforms that perform massive parallel sequencing. NGS for transcriptomics often referred to as RNA-Seq has tremendously increased transcriptome coverage, which in turn has enabled the discovery of novel non-coding RNAs (ncRNA), untranslated regions (UTRs) and rare transcript variants –7. In faHowever, obtaining good sequencing coverage for an accurate representation of the transcriptome is impeded by the difficulties of isolating total RNA with good yield, high integrity and minimal genomic DNA contamination. Owing to the short half lives and sensitive nature of bacterial RNAs, much care has to be taken to extract high quality RNA with minimal degradation that are suitable for sequencing –13. In rAside from these, till date, no study has identified the best kit to obtain total bacterial RNA comprising high and low molecular weight transcripts with minimal genomic DNA contamination that is compatible with RNA-Seq. While Fromm et al.  had showPseudomonas aeruginosa (AIMST H2) was able to degrade polyethylene (PE) under laboratory conditions [P. aeruginosa, the model organism used in this study. In addition, the performance of Phenol-free kit was evaluated in comparison with other total RNA extraction kits/reagents widely used in previous studies for RNA-Seq, TRI Reagent  and RNeasy Mini kit  [Furthermore, we had previously shown using Fourier Transform Infrared coupled Attenuated Total Reflectance (FTIR-ATR) spectroscopy that a strain of nditions . We wereen, USA) , 19, 25.P. aeruginosa AIMST H2 was inoculated into a Erlenmeyer flask containing 100 ml minimal medium supplemented with 0.2 % (w/v) glucose (control) or 0.25 g PE powder as the sole carbon source. Once inoculated, the flasks were placed in a 37 °C shaking incubator and left to agitate at 180 rpm until the growth reached mid-logarithmic phase. The bacteria titer in each flask was adjusted to 1 × 109 cells to standardize the number of cells subjected to RNA extraction. The cells were harvested by centrifugation at 10,000 rpm for 10 min and the supernatant was discarded. The resulting cell pellet was maintained on ice and processed immediately to minimize RNA degradation.Ten ml of Luria–Bertani (LB) culture of 9 cells from three independent biological replicates of each condition using three different kits/reagent: TRI Reagent, RNeasy Mini kit and Phenol-free total RNA purification kit.RNA extraction was done with cell pellets containing 1 × 10Total RNA extraction was performed according to the manufacturer’s protocol with slight modification. One tenth volume of 3 M sodium acetate (pH 5.2) and three volume of absolute ethanol were used instead of isopropanol for precipitating RNA. This reaction mixture was incubated at −80 °C for 2 h to allow efficient precipitation of RNA. After washing the RNA pellet with 75 % ice cold ethanol, it was reconstituted with 50 µl of nuclease-free water. The RNA elutes were stored at −80 °C till further use.g for 10 min. The supernatant was discarded and the cell pellet was subjected to total RNA extraction and on-column DNase I treatment according to the manufacturers’ protocol.The cell pellet was reconstituted with 400 µl of sterile minimal media. Then, 800 µl RNAprotect Bacteria Reagent  was added and the contents in the tube were vortexed prior to a 5 min incubation at room temperature (RT). The tubes were centrifuged at 5000×4)2 SO4, 0.1 % Tween 20; 2.5 mM MgCl2; 0.16 mM dNTP mix; 20 pmol of Bak11-W and Bak-R primers and 0.75 U Taq DNA polymerase . Amplification was performed with an initial denaturation at 95 °C for 3 min, followed by 30 cycles of denaturation at 95 °C for 30 s, annealing at 52 °C for 30 s and an extension at 72 °C for 30 s. A final extension step was also included at 72 °C for 5 min. Based on the PCR analysis, additional DNase I treatment was performed on the RNA extracts with contaminating genomic DNA to remove the residual DNA. One hundred µl reaction consisting of 50 µl RNA elutes, 10 U DNase I , 1× DNase I buffer , 80 U recombinant RNasin ribonuclease inhibitor  and RNase-free water was incubated at 37 °C for an hour. After digestion, the RNA was recovered from the DNase I reaction mixture using phenol:chloroform, low pH  extraction followed by ethanol precipitation. The RNA pellet was reconstituted with 50 µl of nuclease-free water before 100 ng of the RNA wassubjected to PCR analysis again to determine the presence of genomic DNA. The additional DNase I treatment was repeated until no residual DNA was detected via PCR in the RNA samples. Purity of the RNA extracts was also determined before and after the DNase I treatment using spectrophotometric analysis.Total RNA obtained from replicates of each extraction method was subjected to PCR using bacterial 16S rDNA primers, Bak11-W (5′-AGTTTGATCMTGGCTCAG-3′) and Bak-R (5′-GGACTACHAGGGTATCTAAT-3′), to determine the presence of contaminating genomic DNA in the extracts . PCR reaThe RNA concentration and quality was determined using the RNA Nano 6000 LabChip kit . The LabChips were run in an Agilent 2100 Bioanalyzer following the manufacturer’s instructions. Aside from quantifying, this method determines the RNA Integrity Number (RIN) of an RNA sample, which indicates the overall integrity with a score of 1 indicating degradation of RNA and a score of 10 indicating intact RNA .Four purified RNA extracts (2 from cells grown in glucose supplemented medium and another 2 from cells grown in PE supplemented medium) with the best RIN values were selected for sequencing. First, ribosomal depletion was performed using Ribo-Zero Magnetic Kit . Then cDNAs were synthesized using TruSeq RNA Sample Preparation Kit  and SuperScript II Reverse Transcriptase . A minimum of 20 ng cDNA was fragmented using Covaris S220  to a targeted size of <500 bp. The fragmented cDNA were then end-repaired, ligated to Illumina TruSeq Adapters and PCR-enriched using TruSeq RNA Sample Preparation Kit . The final sequencing libraries were quantified using KAPA kit  on a Stratagene Mx-3005P qPCR system . Library sizes were confirmed using Agilent Bioanalyzer High Sensitivity DNA Chip . The resulting libraries were subjected to cluster generation and sequenced using an Illumina flow cell, 202 cycles (101 bp paired-end reads) on the Illumina HiSeq 2000 system . All steps were performed according to the manufacturers’ protocol, unless otherwise stated.P. aeruginosa PAO1 strain (GenBank ID: AE004091) was used as the reference genome for the alignment. HTSeq-count was performed on each alignment file to obtain the count table for each sample. The count table features the number of paired reads that map to each gene as specified in the generic feature format (gff) file of the reference genome. Finally, differential gene expression analysis was performed using DESeq with the count table generated from all four samples.The sequences that correspond to the Illumina sequencing adapters and low-quality fastq reads were trimmed and filtered using Trimmomatic v0.32 . The proGenomic DNA is a concern especially for bacterial RNA sequencing as the cDNAs corresponding to the contaminating genomic DNA will result in inaccurate representation of the expressed transcripts . Since DThe aforementioned observations also indicated that the protocols recommended by the manufacturers including the on-column DNase I treatments applied for the RNeasy and Phenol-free kit extracts did not yield DNA-free RNA and the in-house DNase I treatment was necessary to remove the contaminating genomic DNA. Our findings coincided with that of Schwochow et al. , who alsp < 0.05) as compared to the other two kits. Apart from that, it was observed that the average RNA yield was consistently lower in extracts obtained from PE-supplemented cells compared to those from glucose-supplemented cells. This could have been due to the lower number of genes being transcribed in cells grown under stressful/growth-limiting condition as a result of 6S RNA gene up-regulation . Bacterial 6S RNA inhibits transcription of genes when the cell is undergoing stress by specifically binding to the RNA polymerase holoenzyme containing sigma70 that controls the expression of most genes under the normal growth conditions. This form of regulation helps redirect the bacterial cells to an alternative survival strategy when grown under growth-limiting/stressful conditions [Following the in-house DNase I treatment, total RNA concentrations and integrity of all RNA extracts were determined using RNA Nano 6000 LabChip kit. The yield and RIN values of RNA extracts from the respective extraction method are shown in Table nditions , 31.Fig.It is also important to note that the overall yields obtained for the RNeasy and Phenol-free kits were lower than that expected (according to manufacturer). The reduced yield could be accounted for by the competitive binding of the contaminating genomic DNA that may have reduced the amount of RNA capable of binding to the silica membrane. This was evident as the initial RNA extracts prior to the in-house DNase I treatment had detectable genomic DNA contamination. The reduced yield in TRI Reagent extracts, on the other hand, could have been due to inefficient bacterial cell lysis as the extraction method completely relied on guanidium thiocyanate, unlike both the kits which utilized lysozyme aside from the cell lysis buffer provided. However, the reduced yield is not a major issue as far as RNA-Seq is concerned as the sample preparation procedure only requires 0.1–4 µg of RNA as starting material.Salmonella cells. On the contrary, RNA samples extracted using TRI Reagent failed to generate RIN values due to the overwhelming amount of small RNAs (sRNAs) as shown by the sharp peak between 25 and 200 bases . In addition, the low RNA yield obtained using TRI Reagent can be improved by up-scaling the culture volume as this technique has no limitations in terms of nucleic acid binding capacity posed by spin-column techniques. RNeasy kit, on the other hand, proved to be suitable for researchers interested in studying mRNAs as the extracts contained good quality high molecular weight transcripts. Since our group’s interest was to study both mRNAs and ncRNAs expressed in the bacteria in a single sequencing run, the RNA extracts obtained using Phenol-free kit were the most suitable as they had good ratio of low and high molecular weight transcripts, with high yield and integrity.Sequencing was performed on four samples (duplicates for each condition) extracted using Phenol-Free kit coupled with in-house DNase I treatment. A summary of RNA yield, purity and RIN values of the samples is shown in Table Each RNA sample which were converted to cDNAs and sequenced yielded approximately 16–22 million paired end reads of raw data. Upon pre-processing the data to remove low quality bases using Trimmomatic, approximately 9–12 million paired end reads were retained. The average PHRED quality scores for all four samples increased from 15 to 25, which made them suitable for analysis as typically, PHRED quality scores of 20 and above are preferred .P. aeruginosa PAO1 genome as Ref. [P. aeruginosa AIMST H2 transcriptome data. The expression of 28 out of 30 sRNAs previously documented in the P. aeruginosa PAO1 genome were also detected.Reference-based alignment and differential gene expression analysis were then performed using Bowtie 2 and DESeq, respectively. Based on the output of reference-based alignment, the overall sequencing coverage of the samples were excellent. Using the  as Ref. , we wereP. aeruginosa PAO1 grown in LB broth [P. aeruginosa AIMST H2 genome or were present, but not transcriptionally active under the experimental growth conditions. Furthermore, a small number of these sRNAs which were not detected were antisense RNAs which overlapped with coding genes. Unfortunately, the expression of these antisense sRNAs could not be confirmed as we were not able to distinguish the expression of the coding genes from that of the antisense sRNAs due to the nature of the non-strand-specific sequencing performed. Therefore, repeating transcriptome sequencing with a directional library prepared using the same RNA extracts would solve this problem and enhance the discovery of overlapping anti-sense transcripts. An illustration of the overall transcriptome sequencing coverage with reference to P. aeruginosa PAO1 genome [P. aeruginosa PAO1 sRNA-Seq [In addition, visual screening of the reference-based alignment output via Artemis Genome browser revealed expression ‘peaks’ in many intergenic regions which lack annotation in the genome. Upon extended analysis, we found that 452 of these peaks in the intergenic regions coincided with the sRNAs discovered by Gómez-Lozano et al.  who perfLB broth . These 4LB broth . The rem1 genome  and P. asRNA-Seq  is shownP. aeruginosa transcriptome which have not been categorized as sRNAs in previous studies. All 7 regions have transcription start sites (TSS) and rho-independent terminators which were determined using Dötsch et al. [Interestingly, we also observed expression “peaks” at seven other intergenic regions in the h et al.  and TranP. aeruginosa. The MA plot obtained from the preliminary analysis (p < 0.05) showed that a majority of the expressed genes had a mean read count between 100 and 10,000 with log2 fold change between −2.5 and 2.5  when aligned against P. aeruginosa PAO1 strain as the reference genome. An example of the observed SNPs is illustrated in Fig. Further analysis of the The excellent transcriptome coverage and depth as well as observation of genome-wide SNPs are evidence that high quality RNA with minimal DNA contamination results in good quality sequencing output, providing valuable insights into bacterial transcriptomes. One can expect equally good quality RNA extracts and transcriptome coverage with other Gram-negative as well as Gram-positive bacteria provided the cells are treated with the RNAprotect Bacteria Reagent and the cell lysis step is efficient. Incorporation of the RNAprotect Bacteria Reagent treatment is crucial to stabilize the RNA and prevent degradation as bacterial transcripts have short half lives. Once stabilized with the Reagent, bacterial gene expression will not undergo any changes and the downstream analysis will reflect the true gene expression in the cells. Cell lysis, on the other hand, can be enhanced by increasing the lysozyme treatment time as recommended by the manufacturer or by increasing the concentration of lysozyme.P. aeruginosa grown in minimal media supplemented with PE as the sole carbon source, our findings will also be useful for RNA extraction from bacteria grown in growth-limiting or stressful environmental conditions which limits cell growth.The primary findings of this study (i.e. the determination of the best extraction method) is useful not only to facilitate high-throughput total bacterial transcriptome sequencing, but also to perform other RNomics based experiments like RT-qPCR and microarray analysis. Since the total RNA extraction method demonstrated was also tested on P. aeruginosa. Bioinformatic analysis of the transcriptome data obtained via sequencing of the Phenol-free RNA extracts revealed that the coverage and depth was good as a high percentage of the coding genes (97.5 %), sRNAs (81.4 %), seven potential novel intergenic sRNAs and more than 500 low abundance transcripts were successfully detected. Genome-wide SNPs were also observed in the P. aeruginosa AIMST H2 strain using the PAO1 strain as a reference. The sequencing coverage and depth demonstrated via the bioinformatic analysis clearly proved that the extraction method is suitable for researchers interested in studying both bacterial mRNAs and sRNAs in a single sequencing run. This method will also benefit those dealing with precious bacterial samples grown in growth-limiting conditions. Lastly, the findings of this study also suggest that good quality RNA is the major contributing factor to transcriptome data with excellent coverage and depth as the sequencing technology is known to be sensitive. A simple illustration in Fig. Based on the parameters assessed in this study, Amresco’s Phenol-free total RNA purification kit coupled with an in-house DNase I treatment yielded the best quality RNA extracts comprising low and high molecular weight transcripts with minimal DNA contamination from


Rational modification of a natural RNA-binding peptide with a lanthanide EDTA chelator, and a phenanthroline ligand yields a highly selective luminescent sensor. Rational modification of a natural RNA-binding peptide with a lanthanide EDTA chelator, and a phenanthroline ligand yields a highly selective luminescent sensor. The sensing mechanism relies on the RNA-triggered folding of the peptide into a β-hairpin, which promotes the coordination of the phenanthroline sensitizer, and the efficient sensitization of complexed lanthanide ions. Besides, the folding of α-helices represents only one particular case of structural rearrangements coupled to biomolecular recognition processes, and a more general strategy applicable to the study of other conformational changes would be highly desirable.Fluorescence spectroscopy has transformed the study of biological systems by allowing the straightforward visualization of molecular events with extraordinary selectivity and sensitivity.Herein, we report a new sensing strategy based on the folding of a random coil peptide into a β-hairpin, which allows the introduction of the sensitizing antenna and the lanthanide ion at distant positions in the sequence, thus ensuring low intrinsic emission in absence of the target;TAR), a secondary RNA structure that is recognized with high affinity and high specificity by a 14-amino acid arginine-rich fragment from the Tat transcriptional activator.12Tat is a sequence-specific adaptor protein that directs the cellular transcription machinery to the viral RNA, thus promoting transcription elongation.Tat is closely related to its human immunodeficiency virus (HIV) counterpart,The viability of this strategy is demonstrated with the detection of the bovine immunodeficiency virus (BIV) RNA transactivation response element  with a Trp residue, and introducing a DOTA[Tb] complex at the C-terminus should result in a metallopeptide probe that, upon binding to its target TAR RNA, would fold into a β-hairpin, placing both the DOTA[Tb] complex and the sensitizing indole ring of the Trp close to each other.TAR RNA did not induce any increase in its luminescence, likely because the excited state of the Trp is rapidly quenched by the RNA bases (most likely G11 and G19 close to the Trp in the bound state) before the sensitization takes place (see details in the ESIEDTA[Tb]-Tat-Lys(φ), featuring an EDTA chelator at its N-terminus ,81 (20Based on the solution structure of the peptide DOTA),81 , top.20EDTA-Tat-Lys(φ) was assembled following standard Fmoc/tBu solid-phase peptide synthesis procedures.68) was acylated with EDTA dianhydride  complex. As expected, the EDTA[Tb]-Tat-Lys(φ) metallopeptide, formed in situ by incubating the peptide EDTA[Tb]-Tat-Lys(φ) with 1 eq. of TbCl3, does not show significant emission from the Tb(iii) ion upon irradiation of the phenanthroline antenna at 300 nm (Φ[Tb] ≈ 0.010).TAR RNA hairpin gives rise to a large increase in the luminescent emission bands of the Tb(iii) ion .Tat peptide core into a hairpin structure, and chelation of the terbium ion by the phenanthroline antenna upon binding to the RNA (5D4 → 7F5 transition of the Tb(iii) ion,KD ≈ 57 nM (Tat peptide for this hairpin RNA (KD[Tat] in the range of 50–100 nM).TAR RNA hairpin, and does not increase its emission in the presence of other non-target RNAs or DNAs; specific TAR RNA recognition by the EDTA[Tb]-Tat-Lys(φ) peptide is also demonstrated by EMSA and CD experiments (see details in the ESIiii) ions, and thus the analogous EDTA[Eu]-Tat-Lys(φ) probe also responds to the addition of the target TAR RNA with a large (30-fold) increase in the 5D0 → 7F2 emission band of Eu(iii) at c.a. 615 nm (EDTA[Eu]-Tat-Lys(φ) displays higher emission intensity than the bound Tb(iii) probe .iii) might arise from the small energy gap between the triplet state of the phenanthroline antenna and the emitting 5D4 level in the metal ion, which favors efficient sensitization, but also allows significant energy back-transfer to the chromophore,Having at hand the desired peptide probe, we studied the effect of the . 615 nm , right. EDTA[Tb]-Tat-Lys(φ) probe in D2O and H2O allowed us to calculate the number of inner-sphere water molecules bound to the metal center (q),q ≈ 1 for the probe in absence of its target RNA, and q ≈ 0 at saturating concentrations of TAR RNA. These values are in agreement with the reported number of water molecules coordinating the EDTA[Tb] complex, and support the RNA-promoted chelation of the ion upon folding of the peptide chain.Luminescence lifetime experiments with the EDTA[Tb]-Tat-Lys(φ) probe specifically detects intracellular TAR RNA, displaying a large increase in its luminescence when added to cell lysates obtained from TAR RNA transfected HeLa cells , for multiplex RNA sensing in combination with W[Tb]P22-N, a previously described probe targeting the boxB RNA hairpin.W[Tb]P22-N, and EDTA[Eu]-Tat-Lys(φ), were capable of independently signaling the presence of their target hairpin RNAs, boxB and TAR, respectively. Thus, incubation of a 50 nM mixture of both sensors with boxB results in a large increase of the Tb(iii) emission at 545 nm, resulting from the α-helical folding of the W[Tb]P22-N probe (TAR RNA produced a large and selective increase of the EDTA[Eu]-Tat-Lys(φ) emission at 655 nm  results in sensors that display both excellent dissociation constant and detection limit, with demonstrated bioanalytical applications. Finally, the modularity of this approach should allow its straightforward application for the development of sensors for monitoring other processes involving related folding events.Supplementary informationClick here for additional data file.


Antheraea mylitta cytoplasmic polyhedrosis virus (AmCPV), a cypovirus of Reoviridae family, infects non mulberry Indian silk worm, Antheraea mylitta, and contains eleven segmented double stranded RNA in its genome (S1-S11). Some of its genome segments  have been previously characterized but genome segment encoding the viral guanylyltransferase which helps in RNA capping has not been characterized.E. coli as 65 kDa his tagged fusion protein, purified through Ni-NTA chromatography and polyclonal antibody was raised. Immunoblot analysis of virion particles with the purified antibody showed specific immunoreactive band and suggests p65 as a viral structural protein. Functional analysis showed that recombinant p65 possesses guanylyltransferase activity, and transfers GMP moiety to the 5' diphosphate (A/G) ended viral RNA after the formation of p65-GMP complex for capping. Kinetic analysis showed Km of this enzyme for GTP and RNA was 34.24 uM and 98.35 nM, respectively. Site directed mutagenesis at K21A in KLRS motif, and H93A or H105A in HxnH motif completely abolished the autoguanylylation activity and indicates importance of these residues at these sites. Thermodynamic analysis showed p65-GTP interaction was primarily driven by enthalpy (ΔH = -399.1 ± 4.1 kJ/mol) whereas the p65-RNA interaction by favorable entropy (0.043 ± 0.0049 kJ/ mol).In this study genome segment 5 (S5) of AmCPV was converted to cDNA, cloned and sequenced. S5 consisted of 2180 nucleotides, with one long ORF of 1818 nucleotides and could encode a protein of 606 amino acids with molecular mass of ~65 kDa (p65). Bioinformatics analysis showed presence of KLRS and HxnH motifs as observed in some other reoviral guanylyltransferase and suggests that S5 may encodes viral guanylyltransferase. The ORF of S5 was expressed in Viral capping enzymes play a critical role in the post transcriptional or post replication modification in case of RNA virus. Our results of cloning, sequencing and functional analysis of AmCPV S5 indicates that S5 encoded p65 through its guanylyltransferase activity can transfer guanine residue to the 5' end of viral RNA for capping. Further studies will help to understand complete capping process of cypoviral RNA during viral replication within the viral capsid. Reoviridae  GTP at 25°C in presence of Mg2+ and the transfer of label from [α-32P] GTP to p65 was determined by analysing the product on SDS–10% PAGE followed by autoradiography. A single stable p65-GMP complex was detected in gel  to remove the terminal γ phosphate from the 5′ end. Incubation of these transcripts with purified p65 or virion in the presence of [α-32P]GTP and analysis of product by denaturing 10% PAGE followed by autoradiography showed generation of 32P labelled RNA in samples containing p65  was performed using di phosphate ended AmCPV RNA . Initialcription  and trea5 Figure A, lane 25 Figure A, lane 35 Figure A, lane 432P] GTP in presence of p65. Analysis of reaction products in 10% denaturing polyacrylamide gel followed by autoradiography showed the transfer of label to the both RNA ends in almost equal efficiency  and transguanylylation (i.e. transfer of GMP moiety to RNA) reactions during capping of 5′ end of RNA, the bi-substrate reaction kinetics was assayed by varying the concentration of GTP and RNA . The prod value for the p65-GTP or p65-RNA complex was determined by measuring tryptophan fluorescence of the protein after exciting at 295 nm where the emission spectra would arise almost exclusively from tryptophan. Therefore, despite the fact that p65 has 32 tyrosine residues and 8 tryptophan residues (single tryptophan near the active site), the emission spectra is dominated by indole fluorophores. This dominance is due, in part, to the higher molar absorption coefficient of tryptophan and resonance energy transfer from tyrosine to tryptophan.Thermodynamic parameter of ligand binding  to p65 was studied using fluorescence spectroscopy. Binding of GTP to p65 showed a significant modification in intensity of intrinsic fluorescence of the protein. In order to better characterize the nucleotide binding to the protein, the Kd value for GTP analogue and RNA was calculated as 3.224 × 10-6 and 4.6 × 10-6, respectively, indicating a strong affinity for ligand.Fixed concentration of p65 protein was titrated with increasing concentration of guanosine 5′-[γ-thio] triphosphate  or RNA and the change of fluorescence was recorded. The fluorescence intensity was plotted against the GTP analogue or RNA concentrations to get the saturation binding data  and 1/T over the temperature range tested (20°C to 35°C). Though the free energy of binding gives the overall description of a reaction, yet the enthalpy and entropic contribution provides the complete understanding of the driving forces that helps in enzyme-GTP or enzyme-RNA association. Enthalpic and entropic contribution to p65 were calculated from the observed changes in equilibrium constant (KA) with temperature. Specifically, estimation of enthalpy (∆H) or entropy (ΔS) associated with p65 were made using the slope and y-intercept, respectively, as described in the Van’t Hoff equation, ln(KA) = -(∆H/R) (1/T) + (ΔS/R), where KA is the inverse of Kd. Changes in the Gibb’s free energy was calculated for each ligand using the equation ∆G = -RT ln (KA) at 25°C. The Gibbs energy (∆G) for GTP analogue and RNA were calculated as -3.49 kJ/mol and -6.7 kJ/mol, respectively. The GTP binding step was exothermic at 25°C with a high enthalpy association, (∆H) = -399.1 ± 4.1 kJ/mol with a unfavorable entropic contribution (ΔS = -1.2 ± 0.137) as obtained from Van’t Hoff plot analysis , with a minor contribution from a favorable enthalpy change (ΔH = 0.043 ± .0049 kJ/mol)  with M13 forward and reverse primers as well as internal primers designed from deduced sequences.Purification of AmCPV polyhedra from virus infected larvae was done by following the method of Hayashi and Bird  with somhttp://www.expasy.ch/tools/protparam.html). Secondary structure was predicted using GOR4 program  GTP in a buffer containing 50 mM Tris -HCl (pH 7.5), 5 mM DTT and 5 mM MgCl2 for 30 min at 30°C  GTP at 37°C for 30 min. Parallel reactions using no RNA template or p65 were performed as controls. Similarly, experiments were also performed with triphosphate ended RNA transcripts (without recombinant RNA triphosphatase treatment). The reaction products were analyzed on 8 M urea containing 10% polyacrylamide gel and autoradiographed with a phosphoImager .Both 5′ diphosphate ended RNA transcripts i.e. ppA-RNA and ppG-RNA (1 μg) were incubated in a buffer containing 50 mM Tris–HCl at pH 7.5, 5 mM MgCl1  enzyme at 37 °C for 1 hr. Nuclease P1 was removed by phenol-chloroform (1:1) extraction and nuclease P1-resistant molecules were precipitated with ethanol and analyzed by HPLC together with of unlabelled GMP, GDP, GTP, GpppG marker.After the transfer of the labeled GMP moiety to the ppRNA (as described before), the formation of exact cap structure was determined through HPLC followed by scintillation counting . In brie2PO4 (pH 5.5) at a flow rate of 1 ml/min. Fractions were collected every minute and the amount of radioactivity was measured in a liquid scintillation counter (Perkin –Elmer).For HPLC, the reaction mixture was applied to a HPLC anion exchange column (ZORBAX SAX 5 μ from Agilent) and products were eluted with a salt gradient of 0.04 M to 0.5 M KHd values were determined through scatchard plot analysis from saturation binding isotherm. Additional analysis of the equilibrium binding constant in the various temperature (20 to 30°C) were conducted to determine the thermodynamic parameters for Gibb’s free energy, enthalpy and entropy using the Van’t Hoff plot. This thermodynamic relationship is described by the equation belowInitially, the background-corrected maximum emission wavelength of purified p65 [in 50 mM Tris–HCl (pH 7.5) and 50 mM potassium acetate] was determined by exciting the p65 at 295 nm followed by scanning from 310 to 440 nm . After o-1. M-1), G is Gibbs free energy, ∆H and ∆ S are the changes in enthalpy and entropy, respectively and T is the absolute temperature, KA is the association binding constant of the ligand with the enzyme (i.e. 1/Kd).R is the gas constant  from pyrophosphate (PPi), a bi-product of the capping reaction, using pyrophosphatase enzyme (Fermentas). Then the released Pi was measured in spectrophotometer at λ t 630 nm .2. The PPi, bi –product of the reaction was cleaved into Pi by one unit of inorganic pyrophophatase (NEB) at 37°C for 1 hr and the amount of Pi released was calculated from prepared standard curve of Pi generated from di sodium hydrogen phosphate by the same procedure. Kinetic parameters like apparent Km, apparent Vmax were determined by direct fit of rate versus substrate concentration data to Michaelis-Menten equation (using Graph pad Prism 4.0 software) followed by the Lineweaver burk plot for each of RNA concentration. The exact Km and Vmax were determined by replotting the apparent Km and apparent Vmax values.In brief, varying concentration of GT (0 to 120 μM) and diphosphate ended RNA  were incubated with constant amount of p65 (0.5 μg ) in a buffer containing 50 mM Tris–HCl (pH 7.5), 5 mM DTT and 5 mM MgClThe nucleotide sequence of AmCPV S5 has been deposited in the Genbank database under Accession no: JX853836.The author declares that they have no competing interests.PB designed the research study, performed the experiments, analysed the data and contributed to the writing of the manuscript. AK helped in bioinformatics analysis of sequence data. AKG supervised the whole work and contributed to the writing of the manuscript. All authors read and approved the final version of the manuscript.


Since the discovery of the first catalytic RNA in 1981, the field of ribozyme research has developed from the discovery of catalytic RNA motifs in nature and the elucidation of their structures and catalytic mechanisms, into a field of engineering and design towards application in diagnostics, molecular biology and medicine. Owing to the development of powerful protocols for selection of nucleic acid catalysts with a desired functionality from random libraries, the spectrum of nucleic acid supported reactions has greatly enlarged, and importantly, ribozymes have been accompanied by DNAzymes. Current areas of research are the engineering of allosteric ribozymes for artificial regulation of gene expression, the design of ribozymes and DNAzymes for medicinal and environmental diagnostics, and the demonstration of RNA world relevant ribozyme activities. In addition, new catalytic motifs or novel genomic locations of known motifs continue to be discovered in all branches of life by the help of high-throughput bioinformatic approaches. Understanding the biological role of the catalytic RNA motifs widely distributed in diverse genetic contexts belongs to the big challenges of future RNA research. Over the years, an enormous amount of data were obtained on high-resolution structures and the mechanisms of ribozymes6. All of this contributed to an understanding of ribozyme catalysis to an extent that has allowed engineering of ribozymes and DNAzymes with pre-determined functionality. Thus, the past decade has seen impressive developments based on the usage of known catalytic motifs in ribozyme-based switches for therapeutic and environmental diagnostics7 and more recently for control of gene expression8. In parallel, the ability of RNA to catalyse a wide variety of chemical reactions has revitalised the RNA world hypothesis, a postulated period in the origin of life in which RNA was the main player, for one as carrier of genetic information and for the other as catalyst9. Early life may have started with self-replicating RNA, and a great deal of effort has been invested in developing ribozymes capable of self-replication10 or, even more challenging, of catalysing RNA polymerisation12. The interest in RNA-world-relevant ribozyme activities continues, and one may well expect that there will be more to come.Nowadays, the term 'ribozyme' to designate an RNA catalyst is used with the same implicitness as the term ‘enzyme’ has always been used for proteinaceous biocatalysts. The fact that RNA can cleave and ligate itself, that cleavage of the 5′-trailer of tRNA in tRNA processing is mediated by the RNA subunit of RNase P, that introns may undergo self-splicing, and that the spliceosome and, even more impressively, the ribosome are actually ribozymes meanwhile has found entry into the textbooks. The exciting field of research into RNA catalysis started more than 30 years ago and over the first two decades was dominated by the discovery and identification of several classes of ribozymes occurring in nature and the elucidation of their catalytic structures and mechanisms. Apart from the ribosome that catalyses the formation of the peptide bond, all ribozymes discovered so far in nature support cleavage or ligation of a phosphodiester bond or both. However, the powerful method of SELEX , originally developed for the selection of high-affinity RNA binders (aptamers) from a random library16, and current research addresses the question of their biological role.In addition to ribozyme-based applications and RNA world scenarios as central topics of current research in the field, the frequency of ribozymes in nature and their function are of ongoing interest. With the help of high-throughput bioinformatic approaches, new ribozymes or novel genomic locations of known catalytic RNA motifs in highly diverse genetic contexts have been discovered in all branches of lifeThe field of ribozyme research has changed the focus from discovery and mechanistic/structural characterisation of ribozymes towards functional engineering into application. Nevertheless, the excitement of the first days of ribozyme discovery has carried over throughout the years; the search for new ribozymes or just ribozyme locations continues in all kingdoms of life—in particular, in the human genome. Moreover, as mentioned above, the search for RNA-world-relevant ribozyme activities continues with unchanged curiosity. A number of excellent review articles have summarised the achievements in nucleic acid catalysis  of specific mRNAs have gained much attention25. Ligand binding would support one of the two states, dependent on the specific design. As a consequence of ligand binding, translation is switched ON or OFF , physical signals (light or temperature) can be used to control ribozyme activity in such devices33. Beyond regulation of bacterial or mammalian genes, the potential of ribozyme-based genetic switches for regulation of DNA and RNA viruses has been demonstrated34. In particular, genome replication, infectious particle production and cytotoxicity of adenoviruses, and (in the case of a measles virus) progeny infectivity and virus spread were reduced by aptazyme-mediated control of gene expression, paving the way for future applications in medicine and virology.Allosteric regulation of ribozyme activity has been used in a variety of contexts in the life sciences. Here, significant effort has been made in artificially modulating gene expression by a chemical signal. A ribozyme-based device positioned in the 5′- or 3′-UTR of a transcript and acting as a regulatory unit is partitioned between two functional conformations: one representing a ribozyme active state, the other an inactive state or OFF . The adv35. Therefore, it is all the more important that powerful protocols forin vivo selection and screening and for high-throughput cellular RNA device engineering have been developed36. In general ribozyme-based switches allow for the regulation of gene expression by up to 30-fold27. However, it can be anticipated that, based on novel protocols for RNA device engineering and on the ever-growing understanding of the underlying structure-function relationships, novel designs will outperform those currently available.Important challenges in the engineering of ribozyme-based switches by modular composition are the link between ribozyme (actuator) and ligand-responsive aptamer (sensor) and the relatively slow kinetics of secondary structure changes induced by ligand binding, thus limiting the regulatory potential of ribozyme-based switchesin vitro selection of nucleic acid catalysts from random libraries have paved the way for the development of artificial RNAzymes and DNAzymes. One of the most proficient DNAzymes, the so-called 10–23 motif, was selected back in 199737 and was fully characterised in 199838 and since then has been used as a scaffold in a large number of re-selections and rational designs. In addition, novel DNAzymes were selected from fully randomised libraries. The chemical repertoire of DNAzymes is surprisingly broad, ranging from cleavage of phosphodiester, ester, and amide bonds over supporting C-C bond-forming reactions up to the repair of thymine dimers, peptide modifications, and others  for polymerisation54. Four different XNAs , were selected from random libraries in a method termed ‘cross-chemistry selective enrichment by exponential amplification’ (X-SELEX)nt XNAs  were use9. Thus, a number ofin vitro selections aimed at the identification of RNA catalysts supporting reactions that might have been used by RNA world organisms were carried out. The synthesis of RNA certainly would have been a core activity, and ribozymes for reaction steps involved in RNA synthesis have been generated55. Recent success has been made in ribozyme-mediated triphosphorylation of RNA-5′-hydroxyl groups using cyclic trimethaphosphate as the energy source57, in ribozyme-mediated self-replication58, and in polymerisation of activated nucleotides59. In addition, other recently demonstrated activities, such as ribozyme-mediated RNA processing61, recombination63, nucleotide addition64, and self-alkylation65 (some of them illustrated inThe discovery of ribozymes has led to a renaissance of the RNA world theory, and ever since much effort has been put into the identification of ribozymes with useful activities in a time period when life was based on RNA functioning as both genome and genome-encoded catalyst15. In keeping with the tradition of giving ribozymes names related to their secondary structure, the new motif was called twister because of its small yet complex consensus structure composed of three stems conjoined by internal and terminal loops and a two-pseudoknot tertiary fold (68. With anin vivo cleavage rate of 1000 per minute, the twister ribozyme is one of the fastest self-cleaving ribozymes, and based on biochemical experiments in conjunction with molecular dynamics simulation, a mechanism involving general acid-base catalysis by a conserved active site adenine residue has been proposed69. This is in general agreement with the mechanisms of other self-cleaving ribozymes like the hairpin or the hepatitis delta virus ribozyme, which also require an adenine residue in the active site5. However, apparently there is a striking difference: whereas in the hairpin and hepatitis delta virus ribozyme, N1 of adenine is involved in catalysis, N3 of adenine was suggested as a strong candidate to act as general base in twister ribozyme-mediated self-cleavage69. This is particularly interesting because, if indeed N3 takes this role, it would expand the mechanistic repertoire of the small endonucleolytic ribozymes.Until recently, 10 classes of ribozymes existing among contemporary organisms were known, the hammerhead and hairpin ribozyme probably being the most prominent examples. The years after the discovery of these ribozymes were filled with investigations into their structures and catalytic mechanisms, and it took a rather long time until the question for additional naturally occurring ribozymes was addressed. The first of the recently discovered self-cleaving RNAs constituting the eleventh class of ribozymes is a small catalytic RNA motif, present in many species of bacteria and eukaryotesry fold 66–68. 70, which uponin vitro characterisation were shown to indeed be ribozymes72. All of these new ribozymes support a transesterification reaction yielding a 5′-hydroxyl group and a 2′,3′-cyclic phosphate at the cleavage site. A recent review of the chemistry and biology of self-cleaving ribozymes referring also to the four new ribozyme classes can be found inHigh-throughput bioinformatics assisted the identification of additional self-cleaving candidates named twister sister, pistol, and hatchet ribozyme73. Ribozymes have been identified in intronic regions and mobile genetic elements, suggesting a role in pre-RNA and transcript processing75. Understanding this additional level of genetic control and regulation is one of the major challenges of current and future research in this area. The ongoing development of high-throughput bioinformatic approaches will further facilitate the identification of conserved structures and the evaluation of their genetic distribution. In addition to novel genetic locations of known ribozymes, new catalytic RNA motifs may be expected to be discovered, as shown recently for the twister, twister sister, pistol, and hatchet ribozymes70. In the area of ribozyme engineering by rational design andin vitro/in vivo evolution, exciting results regarding new approaches for the artificial control of gene expression by allosteric ribozymes placed in non-translated regions of transcripts may be anticipated. Also, the search for ribozymes with RNA world relevant activities can be expected to continue with unbroken excitement. In this regard, the catalytic repertoire of XNAzymes53 will certainly be further explored.Over the years, ribozyme research and nucleic acid catalysis have remained a very exciting field with unchanged potential for new discoveries. A strong focus of current research is the uncovering and understanding of the role that ribozymes play in biological systems. The first results on the influence of self-cleaving RNA structures on genetic control are just emerging. For example, the hammerhead, the hepatitis delta virus-like, and the twister ribozyme are widespread in nature and appear in rather diverse genetic contextsThirty-five years after the discovery of the first catalytic RNA, ribozyme research has not lost the intriguing and highly motivating flair of the first days. There are still many questions to be addressed and much is waiting to be discovered.FANA, 2′-fluoroarabino nucleic acid; SELEX, Systematic evolution of ligands by exponential enrichment; UTR, untranslated region; XNA, xeno nucleic acid.


A high-resolution structure reveals how the ribonucleoprotein particle called U1 snRNP engages with 5′ splice sites. Related research article Kondo Y,Oubridge C, van Roon AM, Nagai K. 2015. Crystal structure of human U1 snRNP, a small nuclear ribonucleoprotein particle, reveals the mechanism of 5′ splice site recognition. eLife4:e04986. doi: 10.7554/eLife.04986Image The U1 snRNP comprises a 164-base long RNA molecule bound to 10 proteinsGene expression is a carefully regulated process. Within the nucleus of a eukaryotic cell, multiple molecules work in concert to control whether or not a gene is transcribed to produce a molecule of pre-messenger RNA. Other molecules then direct how this molecule is processed to form a messenger RNA, and still more molecules determine if the messenger RNA is, in turn, translated to form a protein.Molecular complexes containing short RNA molecules and proteins also play several essential roles in regulating gene expression in eukaryotes. The RNA molecules in these so-called small nuclear ribonucleoprotein particles (or snRNPs) are rich in uridine bases, so they are often known as ‘U snRNPs’. Five of these particles are required for a process called pre-messenger RNA splicing: this involves the removal of introns—regions of RNA that do not code for proteins—from the pre-messenger RNA. Because the vast majority of genes in higher eukaryotes contain introns, this process must take place for almost all messenger RNAs.Splicing is carried out by a large ribonucleoprotein complex known as the spliceosome. Unlike ribosomes, the particles that translate messenger RNA, spliceosomes are not pre-formed but are assembled anew on each intron. Thirty-five years ago it was proposed that U1 snRNP recognizes the start, or 5′ end, of an intron ; this waeLife, Kiyoshi Nagai and colleagues at the MRC Laboratory of Molecular Biology—including Yasushi Kondo and Chris Oubridge as joint first authors—report a high-resolution crystallographic analysis of the structure of U1 snRNP. In doing so, they finally reveal in detail how this ribonucleoprotein particle engages 5′ splice sites  made of seven Sm proteins, and three more U1 snRNP-specific proteins . When viewed in two dimensions, most of the RNA molecule resembles a cloverleaf (because it folds back on itself to form three loops). The first loop is the binding site for the U1-70k protein, the second is the binding site for the U1-A protein, and the third makes extensive contacts with the Sm ring. The U1 RNA molecule also contains a fourth stem loop, but this is far removed from the business end of the snRNP.Nagai and colleagues had previously determined the structure of U1 snRNP using X-ray crystallography to a moderate resolution of 5.5 Å . AttemptAs expected a section near the beginning of the U1 RNA molecule bound, via base pairing, to a complementary sequence in a short RNA molecule that had been designed to mimic a 5′ splice site. Of more interest were contacts made between this double-stranded RNA structure (or duplex) and the U1-C protein. It had previously been reported that U1 snRNP lacking its starting sequence, and thus unable to base pair with the 5′ splice site, still selected 5′ splice site sequences from a pool of RNA molecules of random sequence . This reNevertheless, in the high-resolution crystal structure, U1-C does not make any contacts with the bases of either the U1 RNA molecule or the 5′ splice site RNA. Instead, it makes multiple contacts with the sugar phosphate backbones of both RNA strands . These oIn closing, recent studies have revealed three other functions for the U1 snRNP beyond splice site recognition. First, it prevents the poly(A) tail—which marks the end of a mature messenger RNA—from being added too early or at the wrong sites in a new pre-messenger RNA . This ac