A dual-localized PPR protein, OsPGL1, is required for simultaneous RNA editing in mitochondria and chloroplasts. OsPGL1 binds to two distinct target transcripts directly and cooperates with OsMORFs. OsPGL1 resulted in defects in both chloroplast RNA editing of ndhD-878 and mitochondrial RNA editing of ccmFc-543, both of which could be restored in transgenic complementation lines. Despite synonymous editing of ccmFc-543, the loss of editing of ndhD-878 caused a failed conversion of serine to leucine, leading to chloroplast dysfunction and defects in the photosynthetic complex; the results of additional experiments demonstrated that OsPGL1 directly binds to both transcripts. Interactions between three OsMORFs (OsMORF2/8/9) and OsPGL1 both in vitro and in vivo were confirmed, implying that OsPGL1 functions in RNA editing via an editosome. These findings also suggested that OsMORFs assist with and contribute to a flexible PPR–RNA recognition model during RNA editing. These results indicate that, in cooperation with PPRs, OsPGL1 is required for RNA editing. In addition, our study provides new insights into the relationship between RNA editing and plant development.In flowering plants, various RNA editing events occur in the mitochondria and chloroplasts as part of post-transcriptional processes. Although several pentatricopeptide repeat (PPR) proteins and multiple organellar RNA editing factors (MORFs) have been identified as RNA editing factors, the underlying mechanism of PPRs and the cooperation among these proteins are still obscure. Here, we identified a rice dual-localized PPR protein, OsPGL1. The loss of function of  RNA editing is broadly defined as a post-transcriptional process whereby the sequence of an RNA molecule is altered from that of its master DNA . RNA edipsbF-C77 and accD-C794 in Arabidopsis /multiple organellar RNA editing factors (MORFs), organelle RNA recognition motif (ORRM) proteins, organelle zinc-finger (OZ) proteins, and protoporphyrinogen oxidase 1 (PPO1), have been identified as components of the plant RNA apparatus  . Most PPOsPGL1 (Os12g06650), in rice; this gene is required for the RNA editing of two different cis elements. The loss of editing of ndhD-878 caused the failure of conversion of serine to leucine, while the loss of editing of ccmFc-543 did not cause a change in valine, both of which are extremely conserved amino acids in plants. The loss of function of OsPGL1 caused a pale green leaf phenotype, resulting from a defective photosynthetic complex during chloroplast development. Further investigation showed that OsPGL1 functions together with OsMORF2/8/9 and, via its 10 PPR motifs, directly binds to ndhD and ccmFc. These results confirmed that PPR proteins and OsMORFs are required for RNA editing and that both types of proteins function together via a complex editosome.Here, we studied a novel dual-localized PPR gene, Os12g06650, after which the specificity was analyzed by CAS-OFFinder (http://www.rgenome.net/cas-offinder) (Oryza sativa L. japonica Zhonghua 11 (ZH11) were used for Agrobacterium-mediated transformation. Wild-type (WT) and CRISPR/Cas9 knockout lines were grown in a paddy field and greenhouse in Wuhan, China, under appropriate management.Two target sites 20 bp upstream of the protospacer-adjacent motif sequence (PAM) in accordance with the recognition principle of the CRISPR/Cas9 system were designed for For SEM assays, samples were prepared as described previously . After being dehydrated in ethanol, the samples were embedded in acrylic resin. Ultrathin sections (50–70 nm) were double stained with 2% (w/v) uranyl acetate and 2.6% (w/v) lead citrate aqueous solution, after which the sections were examined with a transmission electron microscope at 200 kV .For TEM assays, the samples were fixed in 2.5% (w/v) paraformaldehyde and 0.25% glutaraldehyde in a 0.2 N sodium phosphate buffer for 2–4 h at 4 °C (pH 7.0), after which they were post-fixed in 1% OsOTotal RNA was extracted with 1 ml Trizol reagent (Invitrogen) according to the manufacturer’s instructions. After isopropanol precipitation, the RNA was resuspended in 30 μl RNase-free water and treated with RNase-free DNase I (New England Biolabs). For quantitative reverse transcription–PCR (qRT-PCR), first-strand cDNA was reverse transcribed using random primers  35S promoter to produce a construct encoding the 35S:OsPGL1:sGFP fusion protein. Protoplast preparation and transformation procedures were as previously described , 10 mM dithiothreitol, 2.5 mg ml–1 heparin, and 300 mM NaCl]. The mixture was incubated at 25 °C for 30 min followed by separation in 5% native PAGE in 0.5× TBE buffer; afterwards, the reactants were transferred to a nylon membrane (Roche). For the competitive REMSAs, gradually increasing concentrations of unlabeled probe were added to the reaction mixture in accordance with the procedure described above.The corresponding cDNA fragment of  primers  and clonOspgl1 mutants, a full-length (1815 bp) cDNA fragment was constructed into a pCAMBIA-2300 vector driven by the CaMV 35S promoter, after which the construct was transformed into an Ospgl1-1 mutant background by the Agrobacterium-mediated method. Independent transgenic lines were obtained and subsequently planted in Wuhan, China.For complementation of OsPGL1 (Os12g06650), WSP1 (Os04g51280), OsMORF1 (Os11g11020), OsMORF2 (Os06g02600), OsMORF3 (Os03g38490), OsMORF8 (Os09g33480), and OsMORF9 (Os08g04450) were cloned into the pGBKT7 and pGADT7 vectors. The constructs were subsequently co-transformed in pairs into yeast (strain AH109) in accordance with previously described methods  for 24 h and quantified using the bicinchoninic acid method. The recombinant GST-OsPGL1 protein was incubated with glutathione sepharose for 1 h on ice and then washed five times with five volumes of PBS. Trx-His, WSP1-His, and Trx-OsMORFs-His proteins were subsequently added to detect any interaction. The bound proteins were washed five times with five volumes of PBS, which were eluted with glutathione reductase and separated by 10% SDS-PAGE. The resulting products were transferred on to a polyvinylidene fluoride (PVDF) membrane (Bio-Rad) and investigated with antibodies to GST and His.The purified recombinant proteins  were dialyzed against PBS  in a pUC-SPYCE (C-terminus) vector. Similarly, OsMORF2, OsMORF8, and OsMORF9 were fused to the N-terminus fragment of YFP in a pUC-SPYNE (N-terminus) vector. The two vectors were co-transformed in pairs into rice protoplasts and observed by bright-field and fluorescence microscopy using a Leica microscope  (For the bimolecular fluorescence complementation (BiFC) analyses, the full-length cDNA of The total proteins from transgenic plants fused with FLAG (UBI:OsPGL1-FLAG) and GFP (35S:OsMORFs-GFP) were extracted with extraction buffer . Afterwards, the extracted proteins and 2 µg of anti-GFP antibodies were incubated together overnight at 4 °C; 100 µl of protein A-Sepharose beads was then added, after which the mixture was incubated for an additional 3–4 h. The immunoprecipitates were washed five times with co-immunoprecipitation buffer  and loaded into 6× SDS loading buffer by denaturing for 10 min. The proteins were separated via 10% SDS-PAGE and then were detected by immunoblotting with anti-FLAG and anti-GFP antibodies.Total proteins were extracted from young leaves and quantified with a bicinchoninic acid protein assay kit (Thermo Scientific). A 10 μg aliquot of total proteins was separated by SDS-PAGE and then transferred on to a PVDF membrane (Bio-Rad), after which the membrane and primary antibodies to NdhD , PsaA, PsbA, PetA, AtpA, Lhca2, and Lhcb2 (Agrisera) were incubated together. Actin served as a reference antibody. Detection was carried out by using ECL western blotting detection reagents (Bio-Rad).Ospgl1-1 mutant plants were treated and loaded on to a blue-native PAGE system as described previously , WSP1 (XP_015636466), NdhD (NP_039444), CcmFc (YP_002000589), OsMORF1 (XP_015615260), OsMORF2 (XP_015643218), OsMORF3 (XP_015628181), OsMORF8 (XP_015612485), and OsMORF9 (XP_015650748).Oryza sativa. L. japonica ZH11 and obtained two independent transgenic Os12g06650 knockout lines. Additional genomic DNA sequencing revealed a 41 bp deletion from position 288 to 328 and a 1 bp deletion at position 530 in this PPR gene  and defined the two mutant lines as Ospgl1-1 and Ospgl1-2. The chlorophyll content was drastically reduced in the Ospgl1 lines  and nuclear-encoded polymerase (NEP). The results showed that the expression levels of PEP-dependent genes  decreased in Ospgl1, which is consistent with their corresponding protein levels , RpoTp (encoding NEP core subunits), CAB1R and CAB2R (light-harvesting chlorophyll a/b-binding proteins of PSII), HEMA1 (encoding a glutamyl-tRNA reductase), rbcS , YGL1 (encoding a chlorophyll synthetase), and CAO1 (encoding chlorophyll a oxygenase 1). Our qRT–PCR analysis revealed that, compared with that in the WT plants, the expression level of these genes was lower in the Ospgl1 mutant plants  revealed that OsPGL1 contains 10 PPR motifs  , Sorghum bicolor (Sb08g003980), Arabidopsis thaliana , Theobroma cacao (XP_017974392), Glycine max (XP_003529581), and Brassica napus (BnaC07g33170D), respectively  . The C-tngement) . These dectively . REME2 iervation . These rOsPGL1 in WT plants, we performed RT–PCR and qRT–PCR on various tissues. The RT–PCR results showed that OsPGL1 was constitutively expressed in both vegetative and reproductive tissues, including roots, stems, leaves, and panicles  indicated that OsPGL1 is predicted to localize in the chloroplast and the mitochondrion, albeit with a low degree of confidence. To confirm the subcellular localization of OsPGL1, its full-length cDNA was fused with green fluorescent protein (sGFP) driven by the CaMV 35S promoter, after which the constructs were transiently expressed in rice protoplasts. The results showed that the GFP signals overlapped with the red autofluorescent signals of chlorophyll  were analyzed. The results showed that these two residues are extremely conserved among the five tested species, in both monocots and dicots, implying that the leucine of NdhD and the valine of CcmFc are important for plant development  was analyzed by western blot using anti-GST antibodies to confirm its high purity , was used as a negative control; this probe is a specific target of another rice PPR protein (to be reported separately)  . GST-OsPtogether , C. In ancreased , C. ThesPPR proteins bind target RNA via a modular recognition mechanism . To evalndhD-878  and ccmFc-543 (mitochondrion) were completely edited in WT plants, despite the editing of ccmFc-543 (mitochondrion) being synonymous. The loss of function of OsPGL1 reduced the editing efficiency to zero and resulted in a pale green leaf phenotype. Arabidopsis PPR CRR28 is required for editing at the chloroplast ndhD-878 site (PPR proteins are trans-acting factors with respect to organellar RNA and act as site-specific RNA-binding proteins (ndhD and ccmFc in monocots.The PPR motif consists of two antiparallel α-helices, and its binding specificity depends on the first α-helix , implyin3PPR could be sharply increased upon MORF9 binding, suggesting that interactions between PPR and MORF9 could be more important than those of other proteins (nad2-842 in Arabidopsis mitochondria (ndhD-878, suggesting that WSP1 and PGL1 might cooperate together for RNA editing of ndhD-878. Therefore, we tested the interaction between WSP1 and OsPGL1. The results of yeast two-hybrid assays and pull-down assays showed that OsPGL1 and WSP1 did not interact together in vitro (in vitro and in vivo. The interaction between OsPGL1 and OsMORF2 was seemingly weaker but significantly stronger than that between OsPGL1 and the other OsMORFs (Non-PPR editing factors and PPO1 are both components of the plant RNA editosome, which is required for RNA editing (in vitro . However OsMORFs , implyinOsPGL1. Both Ospgl1-1 and Ospgl1-2 mutants exhibited pale green leaves throughout the whole vegetative stage. Further investigation revealed that chloroplast development and photosynthesis were defective at the RNA and protein levels in the mutants. The up-regulation of NEP-dependent genes in the mutants implied that unknown retrograde signals from the chloroplasts were involved in compensatory effects during the development of chloroplasts. Complementation lines could rescue this aberrant phenotype, suggesting that the base deletion mutation in the OsPGL1 gene was responsible for the pale green leaf phenotype. OsPGL1 regulated chloroplast development by its organellar RNA editing of ndhD. The highly conserved leucine at NdhD-293 is important for the structure or function of NdhD. The results of protein immunoblotting showed that the amounts of the photosynthetic complex subunits dramatically decreased in the mutants. To date, there is not enough evidence to prove that the defect of RNA editing in ndhD transcripts and loss of the NDH complex can cause the pale green phenotype; thus, the pale green leaf phenotype of the Ospgl1 mutant might be caused by the absence of other functions of OsPGL1, which require further study. However, the results suggest that PPR genes play a vital role in regulating chloroplast development in plants.Leaves constitute an important plant tissue. In this study, we constructed CRISPR/Cas9 knockout mutants lacking JXB online.Supplementary data are available at Ospgl1-1 mutant in a paddy field.Fig. S1. Phenotype of the WT and the Ospgl1 RNAi line.Fig. S2. Phenotype of the WT and an Fig. S3. Schematic structural sequence of OsPGL1.OsPGL1 with its orthologs in various plants.Fig. S4. Sequence alignment of Fig. S5. Conservation of the amino acid at the 6 and 1ʹ positions of each PPR motif.46-604.Fig. S6. Expression and purification of GST-OsPGL1Fig. S7. Interaction of OsPGL1 with OsMORF2/OsMORF8/OsMORF9 detected by yeast two-hybrid assays.Fig. S8. Expression and purification of Trx-OsMORF2-His, Trx-OsMORF8-His, and Trx-OsMORF9-His.Fig. S9. Interaction of OsPGL1 with WSP1 detected by yeast two-hybrid assays and pull-down assays.Table S1. Design of target adaptor for CRISPR/Cas9 system.Table S2. Primers used for qRT–PCR, vector construction, and RNA editing.Supplementary MaterialsClick here for additional data file.Ospgl1-1 and Ospgl1-2 mutants and RNAi lines. HX and YX carried out most of the experiments, HX and QZ conducted SEM and TEM, FZ and CN performed expression and purification of recombinant proteins, and J Huang, WL, and LP contributed to field management. HX and J Hu wrote the manuscript with feedback from all authors.HX, J Hu, and YZ designed the study. HX and QZ contributed to the construction of the


Salmonella typhi, Listeria monocytogenes, and Campylobacter jejuni is thought to play a key role in transmission and persistence of these important zoonotic agents; however, little is known about the molecular mechanisms that allow for bacterial survival within this harsh environment. Recently, a highly virulent C. jejuni sheep abortion (SA) clone represented by the clinical isolate IA3902 has emerged as the dominant cause for sheep abortion in the United States. Previous studies have indicated that the C. jejuni clone SA can frequently be isolated from the gallbladders of otherwise healthy sheep, suggesting that the gallbladder may serve as an important reservoir for infection. To begin to understand the molecular mechanisms associated with survival in the host gallbladder, C. jejuni IA3902 was exposed for up to 24 h to both the natural ovine host in vivo gallbladder environment, as well as ovine bile in vitro. Following exposure, total RNA was isolated from the bile and high throughput deep sequencing of strand specific rRNA-depleted total RNA was used to characterize the transcriptome of IA3902 under these conditions. Our results demonstrated for the first time the complete transcriptome of C. jejuni IA3902 during exposure to an important host environment, the sheep gallbladder. Exposure to the host environment as compared to in vitro bile alone provided a more robust picture of the complexity of gene regulation required for survival in the host gallbladder. A subset of genes including a large number of protein coding genes as well as seven previously identified non-coding RNAs were confirmed to be differentially expressed within our data, suggesting that they may play a key role in adaptation upon exposure to these conditions. This research provides valuable insights into the molecular mechanisms that may be utilized by C. jejuni IA3902 to colonize and survive within the inhospitable gallbladder environment.Colonization of the gallbladder by enteric pathogens such as  Campylobacter jejuni is currently the leading cause of ovine campylobacteriosis in the United States  to assess the in vivo transcriptome of C. jejuni during colonization of the chick intestinal tract. Using this technology, the authors were able to demonstrate differential expression of both protein coding genes as well as identify numerous putative regulatory RNAs that were previously unknown , as well as ovine bile in vitro. We reasoned that assessing exposure to both bile in vitro and the sheep gallbladder in vivo would enable the most complete assessment of the complex gene expression and regulatory networks necessary for survival within the host gallbladder environment provided to date. Specifically, we hypothesized that by utilizing the in vivo host environment we would be able to identify an increased number of candidate genes required for survival in the gallbladder environment when compared to utilization of an in vitro model of bile alone. In addition, we hypothesized that the newly identified class of regulators, non-coding RNAs, could be identified utilizing this same approach and would be observed to display changes in expression under the conditions studied.The overall goal of this study was to utilize RNA sequencing technology to study the transcriptome of in vivo host environment following 24 h of exposure. In addition, 89 known and putative non-coding RNA genes were observed to be upregulated with 12 downregulated under the same conditions. The number of genes identified in the in vivo host environment was demonstrated to be almost twice the number identified at the same time points in vitro. This research provides for the first time valuable insights into gene expression patterns and potential regulatory mechanisms that may be employed by the highly virulent C. jejuni IA3902 to colonize and survive within the inhospitable gallbladder environment where it potentially serves as a chronic nidus of infection for spread of disease between animals and humans.By utilizing strand-specific total RNA sequencing on the Illumina HiSeq platform, we were able to identify 434 protein coding genes that were upregulated and 102 downregulated in the C. jejuni SA (sheep abortion) clone, IA3902, was used for the entirety of this study. This isolate was obtained from a sheep abortion outbreak in Iowa in 2006  broth or agar plates  at 42°C under microaerophilic conditions with the use of compressed gas .A clinical isolate of the For preparation of the IA3902 inoculums, cultures were grown on MH plates overnight for 16 h until lawn growth was achieved. Plates were then washed with 1 mL of MH broth and the wash fluid was collected into sterile 50 mL conical vials. The volume contained in each vial was then standardized and 500 μl of the collected culture was removed and processed immediately for RNA protection as described below. An additional 100 μl was also removed for standard plate counts to determine actual inoculum in CFU/mL. The remaining inoculum was then centrifuged at 3,000 × g for 5 min to pellet the cells and the inoculum was resuspended in a minimal amount of MH broth for inoculation. The prepared inoculums were then placed under microaerophilic conditions and used within 3 h of preparation.C. jejuni IA3902 (either in vivo or in vitro) were processed identically to determine if culturable bacteria were present prior to inoculation. For the in vivo study, 1 mL of bile was removed from the gallbladder of all animals prior to inoculation of C. jejuni IA3902 using a sterile 3 mL syringe and 20 gauge 1″ needle; this sample was stored at 4°C for less than 2 h until processed. For the bile to be used for in vitro studies, the entire volume of collected bile was collected into 50 mL conical vials and stored at 4°C for less than 2 h until processed. All samples were screened for bacterial growth at 37°C on blood agar  under aerobic and anaerobic conditions , as well microaerophilic growth on MH plates at 42°C. Of the in vivo inoculated animals, one animal did not have any appreciable bile in its gallbladder at the time of inoculation, therefore fecal culture on MH plates supplemented with Preston Campylobacter selective supplement  and Campylobacter growth supplement  according to the manufacturer's recommendations for isolation of Campylobacter from fecal sources was used instead to screen for intestinal carriage of C. jejuni as a proxy for gallbladder carriage.All samples of bile to be inoculated with C. jejuni utilizing a MALDI-TOF mass spectrometry biotyper  for identification. Screening of the feces from the single animal that did not have bile for collection pre-inoculation did not reveal the presence of C. jejuni.Of the 7 animals that had bile that could be harvested from the gallbladder pre-inoculation, only 1 animal displayed any growth under the conditions studied; the remaining cultures were free of any bacterial colonization as detectable by these methods. The single animal that exhibited bacterial growth displayed a pure growth of colonies on MH agar at 42°C microaerophilic that was confirmed to be in vivo and in vitro samples, 100 μL from each bile sample as well as 100 μl of mucosal scraping was set aside and used to determine the viable CFU/mL following exposure via serial dilution onto MH plates and incubation at 42°C microaerophilic using the drop-plate method as previously described  over the common bile duct were the only options to be successfully performed in a single animal each. Rapid excretion of bile into the duodenum from the gallbladder was noted in the animal without Hemoclip® placement which precluded collection of adequate total RNA at the end of study, therefore, all future inoculations were performed via full laparotomy with placement of a Hemoclip® over the common bile duct.All animal experiments were approved by the Iowa State University Institutional Animal Care and Use Committee (IACUC) prior to initiation and followed all appropriate animal care guidelines. Preliminary experiments utilizing one or two mixed breed female sheep obtained from local farms were performed to determine the best method to inoculate the gallbladder of sheep with C. jejuni related abortions. The sheep were randomly divided into two groups, either 2 or 24 h incubation, via a random number generator (http://www.random.org).For the primary study, eight adult female mixed breed sheep were obtained from two local farms with no known history of The animals were fasted for 12 h prior to anesthetic induction. A jugular catheter was placed and patency maintained for the remainder of the study using heparinized saline flushes every 8 h. General anesthesia was obtained using an intravenous triple drip solution consisting of 500 mL guaifenesin 5% + 500 mg ketamine + 50 mg xylazine. Anesthesia was induced in 5 to 10 min by the rapid administration of 0.5 to 2 mL/kg of this solution and maintained at a rate of 2 mL/kg/h until the end of the procedure. Once fully anesthetized, the animals were placed in left lateral recumbency and the right paracostal region was clipped and aseptically prepared for surgery.C. jejuni IA3902. Following removal of the pre-inoculation bile sample, 1.5 mL of MH broth containing approximately 1011 CFU of C. jejuni IA3902 inoculum was then injected into the lumen of the gallbladder using a separate 3 mL syringe and 20 gauge 1″ needle. The body wall incision was closed and the animals recovered uneventfully from surgery. Food and water were provided following recovery from anesthesia and animals were monitored for signs of pain or septicemia following the procedure.Entry into the abdomen was made via a right paracostal approach to allow for best visualization of and access to the gallbladder. Following visualization of the gallbladder, the common bile duct was located and a Hemoclip® was placed to prevent outflow of bile from the gallbladder following inoculation. Using a sterile 3 mL syringe and 20 gauge 1″ needle, 1 mL of bile was removed from the gallbladder of all animals prior to inoculation of C. jejuni (CFU/mL) following exposure to bile.At either 2 or 24 h post-inoculation as previously determined via random assignment, the sheep were humanely euthanized via intravenous injection of 1 mL/10 lb body weight pentobarbital . Immediately following euthanasia, a clean incision was made into the ventral midline of the abdomen to expose the liver and gallbladder. Using a 16 gauge 1″ sterile needle and a 60 mL syringe, the entire amount of bile retained in the gallbladder was removed via gentle aspiration. The collected bile was immediately processed for RNA protection and isolation as described below and 100 μL was used for a serial dilution in MH broth to determine viable counts of in vivo gallbladder environment to bile-only exposure in vitro, fresh bile was collected at necropsy from an additional group of eight sheep obtained from one of the same farms as above that were being used for an unrelated study. Again using a 16 gauge 1″ sterile needle and a 60 mL syringe, the entire amount of bile retained in the gallbladder was removed via gentle aspiration at the time of necropsy. Following collection, the bile was cultured as described above to determine if it was free of culturable bacteria. While awaiting culture results, the bile was stored at 4°C in sterile 50 mL conical tubes. Following confirmation of culture negative status, the entire collected amount of bile from four of the animals confirmed to be culture-negative (ranging in volume from 14 to 33 mL) was pre-warmed to ovine body temperature (39.5°C) in an incubator for 20 min and then inoculated with 1011C. jejuni IA3902 suspended in MH broth prepared as described above for the in vitro study. Following inoculation, the bile was then incubated under microaerophilic conditions at 39.5°C in a static incubator to best replicate in vivo host conditions. At 2 h, the bile was mixed via gentle shaking and half of the total amount was removed for RNA protection and isolation as described below. The remaining bile was then incubated until 24 h at which time it was also processed for RNA protection and isolation in an identical manner.To compare the in vivo and in vitro experiments were pooled in sets of two for processing . As all of the inoculums were grown and prepared in an otherwise identical fashion, these six RNA samples were considered to represent six biological replicates of RNA expression by C. jejuni immediately prior to exposure to the tested environments. The inoculum samples were centrifuged at 8,000 × g for 2 min immediately following collection to rapidly pellet the cells while minimizing the time elapsed between collection and introduction of an RNA protection solution. Following pelleting of the cells, the supernatant was decanted and 1 mL QIAzol Lysis Reagent  was added to the cultures to quench further RNA production and protect the RNA present from degradation. To resuspend the pellet, the mixture was pipetted up and down and vortexed at high speed for 1 min. Following vortexing, the QIAzol-culture mixture was incubated at room temperature for 5 min. QIAzol-protected cultures were then stored at −80°C for up to 2 months prior to proceeding with total RNA isolation.The bacterial inoculum samples that were set aside during preparation were processed immediately for RNA protection to maintain integrity of the RNA transcripts present. To minimize the number of replicates necessary for sequencing yet maintain a representation of all of the inoculums used, the inoculums for both the C. jejuni IA3902, immediately following collection from either the in vivo gallbladder or from the samples incubated in vitro, the bile was transferred into 15 mL conical tubes (FisherScientific) with no more than 7 mL bile per tube. The tubes were then centrifuged at 8,000 × g for 2 min to rapidly pellet the cells while minimizing the time elapsed between collection and introduction of an RNA protection solution. The bile supernatant was then decanted and QIAzol Lysis Reagent to add to the tube for RNA protection. For concentrated bile samples , 1 mL of QIAzol Lysis reagent was added to the cell pellet per 1.5 mL of the starting bile amount. For dilute bile samples , 1 mL QIAzol was added per 3 mL of the starting bile amount. To resuspend the pellet, the mixture was pipetted up and down and vortexed at high speed for 1 min. Following vortexing, the QIAzol-culture mixture was incubated at room temperature for 5 min. QIAzol-protected cultures were then stored at −80°C for up to 2 months prior to proceeding with total RNA isolation.For the bile samples inoculated with free kit  following RNA isolation to remove any residual DNA contamination. The total RNA was then purified using the RNeasy MinElute Cleanup kit (QIAGEN) with the following modifications as recommended by QIAGEN Technical Services to retain total RNA, including RNA < 200 nt in length: (1) no more than 50 μL of RNA sample was used to enter the RNeasy MinElute Cleanup protocol at a time; (2) to the RNA sample, 350 μL of Buffer RLT was added, followed by 600 μL of 100% ethanol. The RNA-RLT-ethanol mixture then proceeded with the standard bind/wash/elute steps of the protocol as provided by the manufacturer.Total RNA isolation was performed using the miRNeasy Mini Kit (QIAGEN) according to the manufacturer's instructions to isolate total RNA >18 nt. One column was used per 1 mL of QIAzol used for RNA stabilization. On-column DNase treatment was performed using the RNase-free DNase set (QIAGEN). Further treatment of 10 μg of extracted RNA was performed using the TURBO DNA-C. jejuni IA3902, using primers SA1356F, and SA1356R  and Qubit RNA BR Assay  and RNA quality was measured using the Agilent 2100 Bioanalyzer RNA 6000 Nano kit . Verification of complete removal of any contaminating DNA was performed via PCR amplification of a portion of the CjSA_1356 gene, which is part of the capsule locus and has previously been determined via comparative genomics to only be present in in vivo collected RNA samples via the Agilent Bioanalyzer suggested that some samples likely contained host (ovine) RNA along with bacterial RNA; therefore, an rRNA removal kit suited to removal of both eukaryotic and prokaryotic rRNA was chosen for preparation of the RNAseq library. A total of 2.5 μg of confirmed DNA-free total RNA was treated with the Ribo-Zero Magnetic Gold rRNA Removal Kit (Epidemiology) according to the manufacturer's instructions (Illumina). Following rRNA removal, the rRNA-depleted RNA was again purified using the RNeasy MinElute Cleanup kit using the same modifications as described above. Following clean-up, the RNA was eluted into 12 μL of sterile RNase-free water; quality, quantity, and rRNA removal efficiency was then analyzed via the Agilent 2100 Bioanalyzer RNA 6000 Pico kit (Agilent Technologies).Analysis of the Library preparation for sequencing on the Illumina HiSeq platform was completed using the TruSeq stranded mRNA HT library preparation kit (Illumina) with some modifications. As this kit was designed for use with eukaryotic RNA with poly-A tails, the initial poly-A RNA purification step was omitted. To enter the protocol, 5 μL of the rRNA-depleted RNA totaling approximately 200 ng was added to 13 μL of the “Fragment, Prime, Finish” mix. The remainder of the library preparation was carried out according to the manufacturer's instructions and all 24 samples were barcoded using the high-throughput (HT) 96-well RNA Adapter Plate (RAP) as supplied by the manufacturer. Following enrichment of the cDNA fragments, the quality of the cDNA was validated using the Agilent 2100 Bioanalyzer DNA 1000 kit (Agilent Technologies) and quantity was determined via the Qubit dsDNA BR Assay (ThermoFisher Scientific). Following library validation, the indexed cDNA samples were submitted to the Iowa State University DNA Facility where they were normalized and pooled according to the manufacturer's instructions. The pooled library was then sequenced on an Illumina HiSeq 2500 machine in high-output single read mode with 100 cycles.in vivo gallbladder, and in vitro bile exposed strains C. jejuni IA3902 at various time points, Rockhopper (http://cs.wellesley.edu/~btjaden/Rockhopper/), a freely available RNAseq analysis platform, was used as previously described using the standard settings of the program  was below 5% and a >1.5-fold change in expression levels was present. If in any condition being compared the expression level (RPKM) was “0,” it was changed to “1” to allow for statistical analysis to be performed. Any significant changes in 16S or 23S rRNA genes were ignored as these were determined to be due to differences in efficiency of rRNA removal by Ribo-Zero and not inherent differences between strains and conditions. Read count data was visually assessed using the Integrated Genome Viewer (IGV) (https://www.broadinstitute.org/igv/)     and pVir plasmid (13) demonstrated at least 2 consecutive genes differentially upregulated, with 21 of those exhibiting changes in all of the genes predicted in the operon. Conversely, 21 of the 363 predicted operons  were demonstrated to have at least 2 consecutive genes downregulated, with 9 of those exhibiting changes in all of the genes predicted in that operon. Supplementary Tables in vivo and in vitro conditions and time points. Supplementary Table in vivo timepoint also includes annotation to indicate which genes are part of predicted multi-gene operons.A summary of the differences in numbers of genes with increased and decreased expression identified via Rockhopper under either omosome 30 and pViC. jejuni IA3902 and the percentage of possible genes differentially expressed was then calculated for each category along with the hypergeometric probability to test for significance  enrichment in three of the four conditions. “Secondary metabolites biosynthesis, transport and catabolism” and “intracellular trafficking and secretion” were also highly upregulated on a percentage basis with statistically significant enrichment (p < 0.02) for both in the in vivo 24 h environment. “Cell wall/membrane biogenesis” was consistently noted to be the top category represented in all conditions and time points based on total number of genes upregulated rather than percentage but did not reach statistical significance. In contrast, the categories observed to have the highest percentage of genes exhibiting decreased expression in all comparisons and time points were “amino acid transport and metabolism,” which exhibited statistically significant enrichment (p < 0.02) in all four conditions, as well as “signal transduction mechanisms” which showed statistically significant enrichment (p < 0.01) in three of the four conditions studied.To estimate the functional categories of genes affected by each condition and time point, the COG function for each gene was mapped and the totals compiled for each condition and time point. These totals were then compared to the total number of possible genes within each category in in vivo or in vitro exposure  CjSA_0897. The CheA-CheY phosphor-relay pathway has previously been shown to act as the master switch to control taxis by altering the direction of flagellar rotation from a swimming phenotype (counter-clockwise rotation) to a tumbling phenotype (clockwise rotation) , is specifically designed for use with eukaryotic (human/mouse/rat) and prokaryotic (gram positive and negative bacteria) mixed samples as would be encountered during in vivo experiments. This kit was chosen due to visual evidence of potential eukaryotic RNA presence observed in the RNA samples post-isolation, however, the drawback to utilizing a mixed population epidemiology kit is that a decreased number of probes were likely present to target gram negative rRNA. As the majority of the rRNA still likely originated from gram negative bacteria in this case, it is likely that the binding capacity of those probes was exceeded and thus increased the amount of bacterial rRNA that remained in the sample despite the visual appearance of removal of all 16S and 23S rRNA via the Agilent Bioanalyzer. The overall percentage of reads that mapped to the C. jejuni genome was quite high, indicating that very little eukaryotic or other types of prokaryotic RNA were present in the samples. Only one sample failed to rRNA deplete, while an additional sample was observed to have a lower percentage of reads mapping to C. jejuni IA3902. Analysis of differential gene expression via Rockhopper with and without the inclusion of these samples yielded minimal alterations in results; therefore, it was elected to maintain the samples within the dataset. Despite the minor difficulties related to less than ideal rRNA depletion, the samples averaged over 3 million high quality mapped reads per sample. Previous studies undertaken to assess the necessary amount of reads per prokaryotic sample to generate statistically significant data indicate that when data from well-correlated biological replicates are included, 2–3 million reads per sample enables a significant number of genes differentially expressed to be identified with high statistical significance  that were validated to exist in the closely related C. jejuni 11168 and predicted to exist in IA3902 based on sequence homology  and were observed to be consistently increased to a greater degree in the in vivo host conditions, was CjNC130, which has been demonstrated to be a 6S RNA homolog. The 6S RNA has been shown in other model organisms to play an important role in regulating transcription on a global scale by competing with DNA promoters for binding to RNA polymerase  of less than 0.05 along with a fold change of greater than 1.5 was utilized to narrow the list of proposed differentially regulated genes to a robust, yet hopefully biologically relevant list. The fact that a large number of complete operons were observed to be differentially regulated in our data provides additional confidence that the results obtained are likely to be statistically sound and biologically relevant. In addition, analysis of the COG function of the differentially expressed genes was utilized to assess for enrichment of certain functional categories within the dataset. For all conditions and time points studied, the “cell motility” category demonstrated either the highest or second highest percentage of total genes upregulated and exhibited statistically significant enrichment in three of the four conditions. As motility has previously been demonstrated to be a requirement for in vivo colonization and virulence of C. jejuni , not within the gallbladder itself . As presented in Table Campylobacter, 2 of which are not present in strain IA3902. The efflux pumps cmeABC and cmeDEF are arguably the most important genes to have previously been shown to play an important role in resistance of Campylobacter to bile salts in vitro  have previously been show to induce expression of cmeABC in vitro in a time and dose dependent manner ranging from 6- to 16-fold increases in expression  has also been shown to be required for resistance to the effects of bile salts, as mutants lacking it are unable to grow under sub-inhibitory concentrations of sodium deoxycholate  has also been suggested to play a role in bile tolerance and has been demonstrated to be secreted upon co-cultivation of C. jejuni with intestinal cells and play a role in the ability of C. jejuni to invade host cells , and L-fucose (Allen and Griffiths, flaA was not shown to be statistically different under any of the conditions studied. This was an unexpected finding given the previous work done in vitro; however, as the in vitro work looked at very specific conditions and did not actually measure gene transcripts, only promoter activity, it is possible that exposure to a complex host environment renders a different response, or again, that the increased expression response was missed in the time points studied.The last gene of interest to be previously described as important in the response of Campylobacter to bile on a more global scale. Microarray analysis of RNA extracted from C. jejuni strain F3011 cultured with 0.1% deoxycholate for 12 h resulted in a total of 156 upregulated and 46 downregualted genes under these conditions (Malik-Kale et al., ciaB and cmeABC, they also identified increased expression of two additional virulence factors: dccR, which has been shown to be part of a two-component system regulatory system that may play a role in the in vivo colonization ability of C. jejuni (MacKichan et al., tlyA, a hemolysin that has been shown to be important for Helicobacter sp. in vivo colonization ability (Martino et al., tlyA were minimal to non-existent in all conditions examined in our work; this may be related to differences between strains of C. jejuni. Expression of dccR was observed to be increased 1.4-fold at 24 h under both in vivo and in vitro conditions; therefore, it is possible that during the time period between 2 and 24 h significantly increased expression may have occurred. In a separate study, Fox et al., in vitro, it is possible that differences between the simplified in vitro environment and the complex in vivo environment presented in our study allowed for differing results. In addition, altered translation efficiency in the absence of increased presence of the mRNAs of the respective proteins may also play a role and lead to difficulty in comparing protein expression to transcriptomic data.A few additional works have attempted to assess the response of in vivo and in vitro conditions as we have demonstrated here is the sheer amount of data that is generated. For the work presented here we have limited our analysis of the data to answering the original hypotheses of the study, however, many other comparisons and conclusions can likely be drawn from this data and will be the focus of future work.One of the biggest advantages, but also disadvantages, of generating RNAseq transcriptomic data under multiple C. jejuni IA3902 during exposure to an important and relevant natural host environment, the sheep gallbladder. We have demonstrated that the transcriptional “landscape” during direct interaction within the host, as displayed by utilizing in vivo inoculation of and RNA recovery from the sheep gallbladder environment, provides a more robust picture of the complexity of gene regulation required for survival when compared to in vitro exposure to ovine bile alone. A subset of genes were identified that are believed to play an important role in survival within bile, as well as survival in the host environment, including two highly expressed hypothetical proteins that warrant further study. In addition to the identification of important protein coding genes that are differentially expressed, seven previously identified non-coding RNAs were also confirmed to be differentially expressed within our data, suggesting that they may also play a key role in rapid regulation of gene expression upon exposure to bile and the host environment.In summary, this is the first report of the complete transcriptome of AK and PP were responsible for the design, execution and data analysis of all material presented in this article. JS was responsible for performing the surgical inoculation of the sheep gallbladders. MY was responsible for necropsy and sample collection from the sheep gallbladder. QZ assisted with design and data interpretation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Here, we compile folding information for every base pair of the genome that may be transcribed: coding, noncoding, and intergenic regions, as well as repetitive elements, telomeres, etc. This was done by fragmenting the GRCh38 reference genome into 154,414,320 overlapping sequence fragments and, for each fragment, calculating a set of metrics based on the sequence’s folding properties. These data will facilitate a wide array of investigations: e.g. discovery of structured regulatory elements in differential gene expression data or noncoding RNA discovery, as well as allow genome-scale analyses of RNA folding.RNA plays important roles in almost every aspect of biology, and every aspect of RNA biology is influenced by its folding. This is a particularly important consideration in the era of high-throughput sequencing, when the discovery of novel transcripts far outpaces our knowledge of their functions. To gain a comprehensive picture of biology requires a structural framework for making functional inferences on RNA. To this end we have developed the RNA Structurome Database ( RNA’s gene regulatory roles can occur in-cis, via sequence/structure elements embedded within messenger (m)RNAs: e.g. regulatory elements in untranslated regions (UTRs) and introns can affect translation7 alternative splicing8, and mRNA lifetime/abundance9 Additionally, RNA can regulate gene expression in-trans via intermolecular base pairing between mRNAs and noncoding (nc)RNAs such as micro (mi)RNAs11, as well as through interactions that mediate the epigenetic control of gene expression: e.g. the Xistlong (l)ncRNA that associates with one of two X chromosomes in mammalian females and leads to chromosomal condensation and inactivation. A great deal of work has gone into identifying, understanding, and archiving cis- and trans-regulatory sites on human mRNAs. For example, the regulatory (reg)RNA12 web server contains a large repository of data on various motifs, such as splicing regulatory motifs, polyadenylation signals, and mRNA degradation elements; drawing from additional databases of cis-regulatory elements: e.g. ERPIN13, fRNAdb14, and Rfam15. The RBPMap web tool allows users to deduce primary sequence binding motifs on RNAs for a wide array of regulatory proteins16.Once thought to be solely an intermediary between the genome and proteome, RNA is now known to be a key player in the biology of all living things . In addition to carrying the genetic information needed to generate proteins, RNA can also act as a catalystbase pairs (bp) long (Genome Reference Consortium). Approximately 90% of our genome is transcribed into RNA17 yet, only 1.5% encodes protein. This results in a staggering amount of potentially functional RNA to be characterized. Although some of this pervasively transcribed RNA may be “junk”, many of these sequences are differentially expressed (compiled within the NRED database18) in diseases such as cancer21, or under conditions of cellular stress22. Considerable effort is underway to identify and elucidate the functions of ncRNAs. A number of labs have been recording and annotating sequences recovered from high-throughput sequencing and more traditional molecular and cell biology approaches. Collections of ncRNA sequences are being built into databases such as Rfam23, lncRNAdb25, LNCipedia27, mirBASE32 and RNAcentral35. These important projects are compiling well-annotated and, in many cases, functionally validated ncRNAs alongside other valuable data. The RNA families (Rfam) database, for example, contains entries for families of ncRNAs linked by homology. Rfam entries contains information describing ncRNA biosynthesis, localization, phylogenetic distribution and functional roles, as well as evolutionary conservation of primary sequence and, importantly, secondary structure. Conservation of secondary structure is a defining feature of ncRNAs and is used in essentially all ncRNA prediction programs36.The list of new ncRNAs and novel functions of ncRNAs grows daily: however, this is likely only the “tip of the iceberg”. The current release of the human genome reference sequence (GRCh38.p10) is 3,088,269,832 40. This program is based on a support vector machine (SVM) that is trained on data from known ncRNAs contained within Rfam. Two primary training parameters are used for ncRNA classification: a structure conservation index (SCI), which measures conservation of secondary structure and a thermodynamic z-score, which measures the propensity of a particular sequence to form a defined and energetically stable structure. Typical ncRNAs have structures with high conservation and propensity to form structure. RNAz was previously used to scan through whole genome alignments comparing human vs. animal genomes (ranging in similarity down to zebrafish) to identify putative ncRNAs. This yielded >30,000 high-confidence predictions with ~1,000 that were conserved throughout all vertebrates41. The identification of so many deeply conserved structured RNAs highlights their likely ubiquity and importance.A powerful, and popular, program for genome-wide ncRNA prediction is RNAz42. This is the key principle behind the thermodynamic z-score implemented in RNAz: functional RNAs have a more stable folding energy than randomized sequences. Specific folds can be recognized by regulatory proteins43, occlude/present functional motifs44, or alter the distance between functional sites45.The impact of RNA structure on alternative splicing, for example, has been particularly well-studied47. Additionally, awareness of the importance of non-specific RNA structure (e.g. regions that do not form particular folds or adopt dynamic structures) is growing. For example, thermodynamically stable regions within open reading frames are proposed to modulate the speed of translation and thus affect protein folding49. RNA intramolecular thermodynamic stability is important in mediating its accessibility for intermolecular interactions: e.g. stable regions in UTRs are less accessible to miRNA binding, thus affecting miRNA-mediated gene silencing50. Dynamic RNA structure also has significance to disease: single nucleotide polymorphisms (SNPs) can affect RNA folding in ways that impede healthy function by disrupting specific motifs or altering conformational equilibria52.In both coding and noncoding RNAs, secondary structure plays key roles throughout their functions. The diversity of RNA functions and potential for physiological impact (much like with proteins) is made possible by the ability of RNA to fold into unique functional structures. Functional RNA structures form thermodynamically stable base pairs that have been selected for by evolutionin-vivo RNA structure probing techniques have been developed to acquire transcriptome-wide folding information53. Snapshots of the human “RNA structurome”  will become more common in the near future; informing our knowledge of human biology and advancing our understanding of pathogenesis. For this reason, and the reasons discussed above, it is critical to have a knowledge framework in place to understand the roles of RNA structure in human biology. This is the motivation for the creation of the RNAStructuromeDB. Here, we have compiled computed RNA folding information across the entire human genome, irrespective of whether or not it is known to be transcribed. The RNAStructuromeDB is a web-accessible (https://structurome.bb.iastate.edu) repository for investigators to obtain structural metrics for any RNA sequence originating from the human genome. To further aid investigators we have put the data into context by incorporating comprehensive Gencode annotations54 using the biological database schema Chado55. This allows the rapid comparison of differential gene expression data (e.g. to identify regulatory RNA structures) or transcriptome-wide RNA biochemical probing data against the RNAStructuromeDB facilitating these, and other types of studies.Advances in sequencing technology will continue to massively expand the list of interesting RNA sequences and, excitingly, also provide information on secondary structure. Several The RNAStructuromeDB holds the results of a genome-wide computational analysis in which we folded the entire human genome. The results of this analysis are comprised of folding metrics which indicate every region of the genome’s propensity to generate structured RNA molecules. Tools have been built by which users can quickly download these metrics or use them to search for novel RNA structural elements or to assess the global folding properties of a transcript. Here we present the metrics that will aid in the investigation of RNA structure/function, and the tools which have been developed to view these metrics effectively.58 as well as in specific lncRNAs59. Here we consider discrete, overlapping windows whose size was selected based on several considerations. Due to the kinetics of RNA folding, RNAs typically fold into structures composed of smaller motifs; for example, lncRNAs like HOTAIR  are comprised of locally folding domains (4 domains), each containing many local substructures (e.g. RNA hairpins60). Additionally, the majority of known RNA sequences/structures archived in Rfam are short (<200 nt long). Incidentally, a window size spanning 100 to 150 nt was shown to be most accurate at predicting base pairs in known cis-regulatory structures of large mRNA molecules 61. Finally, folding algorithms scale O(N3) in time and O(N2) in memory, where N is the sequence length62; thus, shorter sequences, in addition to yielding more accurate predictions, can be folded more quickly and efficiently. With these factors in mind, a window size of 120 nt was selected to maximize the chance of encapsulating structured elements, while also optimizing prediction accuracy and computational resources. A step size of 40 nt was selected to ensure the entire genome is canvassed with multiple frames, increasing the likelihood of capturing all structured elements. This window and step size resulted in the generation of 154,414,320 windows which were analyzed in both strand orientations.To analyze a genome as large as the human genome requires fragmenting the sequence data into smaller pieces that are both computationally tractable, as well as biologically meaningful. The fragmentation approach taken in the construction of the RNAStructuromeDB is similar to those that were successfully used for the analysis of RNA structure in the human and other genomes64 . The ΔG was calculated using the program RNAfold, which is a component of the ViennaRNA package63; predictions were made at 37 °C (human body temperature) and values are reported in kcal/mol. 2D structures associated with window MFE predictions were captured and archived in “dot-bracket" notation; here, paired nt are represented by matched brackets “” and single stranded nt by dots “.”. To determine if the MFE ΔG depends on the nt order or composition, we compared the native sequence ΔG vs. in silico randomized sequences with the same nt composition. In general, structured ncRNA molecules have lower (more stable) MFE values than random sequences of the same nucleotide composition65; a property which can be exploited for structured RNA motif discovery66. For each window, we report the thermodynamic z-score. The z-score is calculated by taking the difference between native MFE (ΔGnative) and the mean MFE of random sequences  pairing contacts that give the RNA thermodynamic stability. Positive z-scores are harder to interpret, however, they could suggest regions of RNAs that are evolved to be more accessible/unstructured59. The z-score can also be qualified using the p-value, which is calculated as the fraction of ΔGrandom values with more thermodynamic stability than ΔGnative. This provides a measure of the z-score quality, where p-values close to zero indicate higher prediction confidence: few or no randomized sequences are more stable than the native sequence; this also indicates if the randomization number is high enough to yield reliable z-scores.For each window, five folding metrics were calculated and archived. The Gibb’s minimum free energy (MFE) of folding (ΔG), which estimates the thermodynamic stability of the most stable 2D conformation of an RNA given Turner nearest neighbor energy parametersmentclass2pt{minimensemble diversity (ED) and the frequency of the MFE (fMFE) metrics. Structured RNAs have rough folding landscapes  and, in some cases, are capable of occupying several conformations. The probably of finding any of these structures within the Boltzmann ensemble is mathematically described by the partition function67, which was calculated using RNAfold63. From this partition the ED is calculated by taking the average base-pair “distance” between all structures in the ensemble, where distance is defined as the number of base pairs different between structures65. The ED then, is a metric to mathematically signify the variety of folding structures within the ensemble . The fMFE metric is the probability of finding the MFE within the Boltzmann distribution of structures, where a high probability suggests the MFE structure is more likely to be the dominant fold.Two values are recorded which measure statistical properties of the RNA 2D folding ensemble: the 69 or ncRNA prediction . A region can have a very stable ΔG, but mediocre (or positive) z-scores because the order is unimportant vs., for example, the GC content. The p-value estimates the quality of the z-score. If almost every randomized sequence is less stable than native, then the likelihood of the order being significant is higher. The ED and fMFE indicate the diversity of the RNA folding ensemble in a region and how well-represented the MFE prediction is in the 2D structural ensemble, respectively. These can suggest which regions have well-defined folds (e.g. with low ED and high fMFE) or where folding may be diverse . Taken together, these metrics can also suggest which regions may be harboring functional structures. Overlapping windows with interesting folding metrics can be concatenated to define larger regions of interest, which can then be used for comparative sequence/structure modelinggeneric feature format version three (GFF3) directly from the download page (https://structurome.bb.iastate.edu/downloads). GFF3 is a standardized file format developed by The Sequence Ontology70 for the sharing of genomic information in a unified manner and is compatible with several bioinformatics programs. This file contains each window’s sequence, coordinates, strand orientation (forward or reverse), MFE, z-score, p-value, ED, fMFE and dot-bracket 2D structure. This data format will allow interested end-users to parse out trends using their preferred methods or protocols; however, users may want to filter the metrics, downloading only information relevant to their needs/interests. Therefore, we have also created an interface where a user can filter and search for data based on any combination of genomic coordinates, Ensembl IDs, gene symbols, or folding metrics—facilitating varied inquiries. Investigators interested in multiple genes can quickly search for, populate, and download folding metrics coinciding with each gene as a single consolidated CSV  file. Conversely, a user may have discovered an RNA molecule lacking any established annotations; as long as coordinates are supplied, this user will find folding metrics for their novel transcript as well. This genome-wide analysis provides the freedom to obtain data from any known or novel transcript.There are three main methods for accessing the data: flat files, data tables, and via an interactive genome browser. Users can freely download raw data as flat files in The JBrowse genome browser provides significant insights into the structural landscape of each chromosome via a customizable visual interface. Within the JBrowse interface, folding metrics have been adapted to allow for rapid structural inferences to be made: they are displayed as bar graphs canvasing each chromosome sequence. Each folding metric  has been split into separate graphical tracks that can be displayed parallel to genomic annotations. A user interested in a specific transcript will be able to observe the folding metrics of its constitutive features , while at the same time be able to see the folding metrics of the entire gene within greater genomic context. The human eye is very good at identifying patterns (e.g. within the structure of the data represented in the JBrowse tracks) and visualizing the genome, transcriptome and predicted RNA structurome simultaneously can facilitate discovery. Examples are given below.73; however, most lncRNAs and their functions remain uncharacterized73. One aspect of lncRNA function that remains controversial, is the role played by RNA secondary structure. Many reports describe extensive local or global folding for lncRNAs74; yet, statistical evidence of structure conservation remains tenuous75. It is worth noting that, even in the absence of high structural conservation, RNA folding can play functional roles76. Analyzing lncRNA folding landscapes and building 2D structural models of these molecules will aid in understanding their mechanisms of action  and, possibly, in developing therapeutic strategies77 to modulate function. lncRNAs tend be modular in structure, consisting of multiple structured domains78. Sliding window approaches for RNA structure detection are able to roughly define the extent of these domains59. The RNAStructuromeDB suggests these domains for all potential human lncRNAs with the folding metrics and local structural models necessary to begin to decipher the structure and function of these transcripts.Currently, thousands of lncRNAs have been discovered in the human transcriptome and a growing list has been assigned functions and are implicated in diseases such as cancermetastasis-associated lung adenocarcinoma transcript 1) is a highly conserved  lncRNA, which is involved in numerous cellular processes  and implicated in disease states: such as cancer83 and diabetes84. Here, the RNAStructuromeDB data table interface is used to define the structured domains of MALAT1 . This resulted in seven domains  and ED scores RNA85. The terminal window in this domain contains the predicted model of the mascRNA . Links to all of these tools can be found on the RNAStructuromeDB website.For example, MALAT1 44. Within this mRNA, is a region of the 3′ UTR which can adopt two structural conformations, each of which leads to different translational levels of VEGFA. The adoption of either conformation is mediated by protein binding which occurs as a result of hypoxic signaling. When expressed in high abundance (under hypoxic conditions) the regulatory protein hnRNP L binds to the VEGFA riboswitch causing two sequences, known as the GAIT (gamma interferon inhibitor of translation) element and the stem stability sequence . Using VARNA, we annotated the 2D image with the key riboswitch elements  conformation that dominates under hypoxia, where the GAIT element and stem stability sequence are annealed to each other. The differences in the MFE model and the TP conformation described in the literature occur primarily at the hnRNP L binding site. The literature model is based on enzymatic probing of an in vitro generated construct that terminates 5 nt upstream of the hnRNP L interaction site. The MFE model, however, includes 13 additional upstream nt because of the window size used. These additional nt allow for the formation of a short hairpin stem that sequesters part of the hnRNP L binding site in a short hairpin loop  enzyme family: Adenosine to Inosine (A-to-I) deamination. These editing events are ubiquitous throughout the body90 and likely play a role in regulating gene expression91 and establishing disease states92. Inosine is recognized by most cellular machinery (as well as the enzymes used in RNA sequencing) as guanosine; indeed it is the A-to-G transitions observed as variants in sequencing reads that allows one to quantify the percent A-to-I editing at a nt93. Efforts towards creating an “inosinome Atlas” (by conducting whole genome and transcriptome sequencing of human cells to detect A-to-I editing events) resulted in the identification of ~3 million A-to-I editing sites90. Given their quantity, likely roles in regulating gene expression, and their implication in disease states it is important to gain insight into the structural features of A-to-I “hot-spots”.In addition to the most well-known RNA post-transcriptional modifications  RNA molecules can undergo endogenous enzyme-mediated chemical modifications; a process known as RNA editingdouble stranded (ds)RNA regions94. ADAR editing was first described in helical regions of very long hairpins found in 3′ UTRs96 Subsequently, many editing sites were found; for example, within regions containing Alu elements97 whose inverted repeat structure facilitates hairpin formation. This structure-preference for ADAR makes the folding metrics within the RNAStructuromeDB particularly useful for interpreting patterns of A-to-I editing data. We utilized the customizability of JBrowse to visualize A-to-I editing sites alongside folding metrics in order to examine the structural landscape corresponding to edited regions. We prepared tracks using data from a study which looked at RNA editing in human B cells91 where several transcripts were discovered to be hyperedited. For example, the formin binding protein 1 (FNBP1) transcript was found to have the most editing events (291) of any gene, and when viewed alongside folding metrics it was clear that predicted structured regions aligned well to editing sites  the information in the RNAStructuromeDB can also offer insights into the detailed structural contexts of A-to-I editing sites. The primary sequence context of these editing sites is being investigated, with insights being made into flanking nucleotide preferencesThe RNAStructuromeDB is a repository of useful RNA folding metrics and a powerful vehicle for exploring the human genome via RNA structure. It allows users to browse, access, and retrieve the data quickly and flexibly, which will facilitate a wide array of researches. We presented three examples of how this database can be used: to generate a map of RNA folding throughout the MALAT1 lncRNA, VEGFA gene, and FNBP1 transcript. In each example, global properties of folding (e.g. the enrichment for stable folding in intronic or UTR regions), as well as the identification of functional motifs (e.g. the identification and modeling of the VEGFA riboswitch and stable hairpin in FNBP1) could be quickly deduced. We anticipate that this tool will have many applications both in basic research and in the therapeutic targeting of disease-associated human RNAs.http://researchit.las.iastate.edu) running Postgres 9.2, with all computational and genomic data stored within the Chado schema. Folding metrics were calculated on Iowa State University’s High Powered Compute cluster using RNAfold (version 2.2.10) and Perl (version 5). The website pages were built using Iowa State University’s Luggage platform (http://luggagedocs.info/), which is constructed on an underlying Drupal 7 framework. Tripal100 (version 2.1) was used to upload all data into the Chado schema and populate page “views” by later pulling relevant data from the Chado schema. JBrowse API  was used to generate JBrowse tracks directly from the Chado schema. An overview of this procedure is indicated in Fig. Our database is housed on a Red Hat Enterprise Linux (RHEL7) server (provided by the Research IT group at Iowa State University 54 (release 26) were acquired from Gencode directly in the form of GFF3 files (ftp://ftp.sanger.ac.uk/pub/gencode/Gencode_human/release_26/gencode.v26.annotation.gff3.gz).This analytical approach utilizes FASTA chromosomal DNA sequence files as input. For the human genome, the standardized reference sequence is generated by the Human Genome Reference Consortium. The latest major release of this human genome reference sequence (GRCh38/hg38) was acquired from Ensembl FTP server (ftp://ftp.ensembl.org/pub/release-90/fasta/homo_sapiens/dna/) as 24 separate chromosomal FASTA files (consisting of unmasked DNA sequence). Regions of sequence ambiguity and/or difficult to sequence nucleotides are depicted as the character “N” and were not considered in any calculations, but remain as placeholders within corresponding windows. Comprehensive Gencode genome annotationset al.66 as illustrated in the following equation:Each chromosomal FASTA file supplied the underlying sequence for metric calculations, and was analyzed every 40 nt using 120 nt windows. Each window fragment is run through RNAfold to calculate its MFE  and partition function at 37 °C. To account for the reverse strand, each fragment is also converted to its reverse complement and run through the same process in a parallel script. Partition function calculations output an ensemble diversity score and an fMFE in the ensemble value for each window. Each “native” window sequence is then scrambled to produce 30 randomized versions which are run through RNAfold to calculate their MFE values as well. The MFE values of the native sequences are then compared to the MFE values of random sequences to generate a thermodynamic z-score, calculated with a method adapted from Clote 101. Folding metric windows and Gencode annotations were also prepared as feature tracks for the JBrowse genome browsing interface; each folding metric window is displayed as a feature with directionality and each gene was visualized as “processed transcripts” . Additionally, each folding metric  was extracted and prepared as separate bigWig tracks for both forward and reverse strands – with each folding metric window trimmed to span only its initial 40 nt, allowing for proper visualization of each metric as a bar graph. We have left JBrowse customizable: users are given the option to upload tracks  alongside RNAStructuromeDB metrics. Users are also able to download data from every track (whole sets or selected regions).Web-based interfaces were prepared to put folding metric output into genomic context. An example of the pipeline used to generate the RNAStructuromeDB is shown in Fig. https://structurome.bb.iastate.edu/folding-metric-feature-search by filtering using Ensembl ID (ENSG00000251562.7) and downloading via the CSV link in the webpage. Statistical analyses were performed and graphs/tables were generated in Excel.MALAT1 metrics were obtained from https://structurome.bb.iastate.edu/jbrowse/ by inputting its Ensembl ID (ENSG00000112715.21). All data was gathered from the JBrowse interface directly. All structures were generated using VARNA and annotated as described in Ray, et al.VEGFA was navigated to at 88 supplemental table five. Genomic coordinates were converted from human genome reference version hg18 to version hg38 using the UCSC reference conversion tool: https://genome.ucsc.edu/cgi-bin/hgLiftOver. Converted coordinates were then used to create bigWig tracks for each nucleotide site. These tracks were uploaded directly to JBrowse from the user interface for visualization along with folding metrics.A-to-I editing sites were obtained from ref.https://structurome.bb.iastate.edu/downloads or from corresponding author on reasonable request.The datasets generated during the current study are available in the RNAStructuromeDB downloads repository, Supplementary InformationSupplementary Table


Higher eukaryotes can further modify this minimal cap structure with the addition of a methyl group on the ribose 2'-O position of the first transcribed nucleotide (m7GpppNmpRNA) and sometimes on the adjoining nucleotide (m7GpppNmpNmpRNA). In higher eukaryotes, the DXO protein was previously shown to be responsible for both decapping and degradation of RNA transcripts harboring aberrant 5’ ends such as pRNA, pppRNA, GpppRNA, and surprisingly, m7GpppRNA. It was proposed that the interaction of the cap binding complex with the methylated cap would prevent degradation of m7GpppRNAs by DXO. However, the critical role of the 2’-O-methylation found in higher eukaryotic cap structures was not previously addressed. In the present study, we demonstrate that DXO possesses both decapping and exoribonuclease activities toward incompletely capped RNAs, only sparing RNAs with a 2’-O-methylated cap structure. Fluorescence spectroscopy assays also revealed that the presence of the 2’-O-methylation on the cap structure drastically reduces the affinity of DXO for RNA. Moreover, immunofluorescence and structure-function assays also revealed that a nuclear localisation signal is located in the amino-terminus region of DXO. Overall, these results are consistent with a quality control mechanism in which DXO degrades incompletely capped RNAs.The 5' RNA cap structure ( O position of the first transcribed nucleotide (cap1) and sometimes at the adjoining nucleotide (cap2) . Telf RNAs ,5. Indee as MDA5 ,7, indic as MDA5 ,9). SincThe first evidence of a specialized quality control mechanism for the mRNA cap structure was demonstrated in lower eukaryotes. The Rai1 protein possesses a pyrophosphohydrolase (PPH) activity toward 5’-triphosphorylated RNA (pppRNA → PPi + pRNA) and a decapping activity toward unmethylated capped RNA (GpppNpRNA → GpppN + pRNA) ,11. Intem7GpppRNA (cap0). The authors of the study suggested that this lack of specificity would most likely be thwarted in cells by the cap binding complex (CBC) which preferentially binds the methylated cap, thereby preventing degradation of cap0 RNAs by DXO  is the concentration of the protein, [DXO·ligand] is the concentration of complexed protein, and [ligand] is the concentration of unbound ligand in solution. The proportion of ligand-bound protein is related to the measured fluorescence emission intensity by Eq (2):max is the difference at infinite [ligand], and [DXO]tot is the total protein concentration. If the total ligand concentration, [ligand]tot, is in large molar excess relative to [DXO]tot, then it can be assumed that [ligand] is approximately equal to [ligand]tot. Eqs (1) and (2) can then be combined to give Eq (3):The binding can be described by Eq (1):d values were determined from a non-linear least-square regression analysis of titration data by using Eq (3).The K5’GUAGUUCGCCUGUGUGAGCUGACAAACUUA3’) harbouring a chemically modified 2’-O-methyl nucleotide at either the first or the 16th position from the 5’ end as well as a non-modified oligonucleotide were purchased from IDT. RNAs were labelled with [32P]pCp at their 3’ end by incubation with T4 ssRNA Ligase  for 1.5 hours at 37°C. RNA was precipitated with ethanol, resuspended in nanopure water and quantitated by spectrophotometry before being phosphorylated at the 5’ end by PNK kinase . RNA was purified by gel filtration using the Illustra Probe Quant G-50 micro columns . The exoribonuclease assay was performed by incubating 2μM of recombinant DXO with 100nM of RNA in IVDA-2.1 buffer  at 37°C for different time intervals. The reaction was stopped by the addition of EDTA to a final concentration of 100mM and reaction products were analyzed on a 20% polyacrylamide gel containing 8M urea. The radiolabeled RNA was visualized by autoradiography of the gel and was quantified with a phosphorimager (Amersham Biosciences).Two 30-mer RNA oligonucleotides  supplemented with 10% FBS  and 1mM sodium pyruvate . Cells were transfected with pcDNA3.1+/DXO-WT and pcDNA3.1+/DXO-K7A-R8A using Lipofectamine 2000 transfection reagent  for 48 hours. The culture medium was removed, and the cells were washed in PBS prior to being fixed with a PBS solution containing 4% paraformaldehyde and 4% sucrose for 20min at room temperature (RT). Cells were washed with PBS before being permeabilized with 0.15% Triton X-100 in PBS for 5min at RT. Afterwards, cells were washed twice with PBS and blocked in 10% normal goat serum  for 20 minutes at RT. DXO was stained with a rabbit polyclonal DXO antibody  diluted 1:100 in blocking solution (10% NGS) overnight at 4°C. Cells were washed three times with 10% NGS before being incubated in the dark for 1h at RT with an Alexa Fluor 488-labeled anti-rabbit secondary antibody  at a 1:1000 dilution in 10% NGS. All subsequent steps were carried out in the dark. Cells were washed three times with PBS at RT, and nuclei were stained with 1μg/ml Hoechst  for 15 min at RT. After a final wash in PBS, the coverslips were mounted on slides using a SlowFade mounting medium . Epifluorescence microscopy was conducted using a Nikon TE2000E microscope. The fluorescent images were acquired at a 60x magnification and images were processed using the HCImage software.The wild-type DXO gene as well as the K7A-R8A mutant was cloned into the pcDNA3.1+ mammalian expression vector. HeLa or HEK293T cells were seeded on coverslips  in a 24-well plate  24 hours before transfection and grown at 37°C and 5% COO-methylation but not the N7-methylation . However, since non-N7-methylated RNA is not naturally found in mammalian cells, and thus constitutes an unusual substrate for the 2’-O-methyltransferase, only 30% of the substrate was successfully 2’-O-methylated, and the GpppGm-RNA substrate used in the decapping assay contains a significant amount of GpppG-RNA.Since DXO has been identified as a key player in the mammalian mRNA cap quality control machinery , we decihylation . RNA subE. coli as described under 'Materials and methods' and purified by affinity chromatography on a Ni-NTA column. SDS-PAGE analysis showed that the 45.8-kDa DXO protein was the predominant polypeptide in the purified fraction (m7GpppN-RNA (cap0), to yield GpppN and m7GpppN, respectively. However, DXO displayed no activity towards the m7GpppNm-RNA substrate (cap1) (The human DXO protein was expressed in fraction . The abie (cap1) . We concO-methylations) were not, we tested the possibility that the sole presence of the 2’-O-methylation could prevent RNA degradation. RNAs were capped in vitro, and without the addition of a methylation at the N7 position, the substrates were subjected to 2’-O-methylation. Upon incubation with DXO, we observed that the enzyme was able to hydrolyze the capG substrate but failed to cleave the cap1 substrate (O-methylation is sufficient to prevent DXO decapping activity.Since RNAs harboring a cap0 structure (N7 methylation only) were decapped by DXO whereas RNAs with a cap1 structure . Moreover, a mutation D236A in mouse DXO has previously been shown to abrogate its catalytic activity [2+ ions in the active site . Residue D236 was targeted since it was previously shown to coordinate an Mgactivity ,15. Accoive site . These tive site . A D236Aive site . Only wiive site , S1 Fig.O-methylation, we investigated its affinity for both m7GpppGm-RNA (cap1-RNA) and m7GpppG-RNA (cap0-RNA) using fluorescence spectroscopy. In the absence of RNA, a maximal peak of tryptophan fluorescence emission was detected at 332nm  is approximately 30 times smaller than the Kd for cap1-RNA (25μM) indicating that the presence of the 2’-O-methylation on the cap structure drastically reduced the affinity of DXO for the RNA.Given that DXO does not hydrolyze cap structures that contain a 2’-at 332nm . We obseO-methylated RNA  which is typically defined as two basic clusters separated by a spacer region of any 10 amino acids. Residues K7 and R8 of human DXO constitute the first cluster of basic amino acids of the presumed NLS. We substituted these two residues by alanine residues and determined the impact on the cellular localization of the mutant by immunofluorescence. As expected, the wild-type DXO protein is present predominantly within the nucleus. However, the DXO K7A-R8A mutant is located in both the nucleus and in the cytoplasm  [O-methylation of the first transcribed nucleotide was never investigated in this context. In the present study, we demonstrate that DXO senses and spares fully capped (cap1) RNA transcripts while selectively degrading transcripts lacking 2’-O-methylation (such as cap0 and capG). These results are consistent with a quality control mechanism that degrades incompletely capped RNAs (capG and cap0) while sparing fully capped RNAs (cap1).In recent years, various studies have demonstrated the presence of aberrant cellular pre-mRNAs which are incompletely capped ,14. HoweA (cap0) . An hypom7Gppp-RNA, were decapped by DXO while m7GpppNm-RNA was resistant to its activity. In this context, the 2’-O-methylation appears to be the key element defining mRNA as fully capped and suitable for survival, export and translation. These results are further supported by the observation that DXO affinity for RNA is drastically reduced by the presence of 2’-O-methylation on the RNA substrate. Moreover, the DXO 5’-3’ exoribonuclease activity is blocked by the presence of a 2’-O-methylation on the RNA substrate. These findings suggest that DXO-mediated mRNA quality control is dependent on the 2’-O-methylation status of pre-mRNAs rather than on the competition of CBC and DXO for mRNA binding as proposed previously [The present study showed that RNAs bearing immature cap structures, such as Gppp-RNA and eviously .The human DXO protein appears as a key component of the mammalian RNA decapping pathway. Mounting evidence suggest that RNA decapping is a highly regulated process which involves both positive and negative regulators. In mammalian cells, Hedls was shown to be a positive effector of Dcp2 decapping . The eukO-methylated RNA transcripts. DXO is directly involved in the mRNA quality control mechanism by degrading mRNAs with abnormal cap structures Click here for additional data file.