Setx gene, defective in ataxia oculomotor apraxia type 2 (AOA2) leads to the accumulation of DNA/RNA hybrids (R-loops), failure of meiotic recombination and infertility in mice. We report here the presence of R-loops in the testes from other autosomal recessive ataxia mouse models, which correlate with fertility in these disorders. R-loops were coincident in cells showing high basal levels of DNA double strand breaks and in those cells undergoing apoptosis. Depletion of Setx led to high basal levels of R-loops and these were enhanced further by DNA damage both in vitro and in vivo in tissues with proliferating cells. There was no evidence for accumulation of R-loops in the brains of mice where Setx, Atm, Tdp1 or Aptx genes were disrupted. These data provide further evidence for genome destabilization as a consequence of disrupted transcription in the presence of DNA double strand breaks arising during DNA replication or recombination. They also suggest that R-loop accumulation does not contribute to the neurodegenerative phenotype in these autosomal recessive ataxias.Disruption of the  Skourti-Stathaki et al 2011 demonstrated that senataxin resolves R-loops formed at transcriptional pause sites to enable transcription initiation and termination The autosomal recessive cerebellar ataxias (ARCAs) are a diverse group of disorders arising from defects in genes involved in the response to DNA damage; mitochondrial function and those controlling different levels of metabolic and other cellular processes −/−, Setx−/−, Aptx−/−, Tdp1−/−Atm) were screened for the presence of R-loops. Initial histological examination of testes sections revealed a severe disruption of the seminiferous tubules, vacuolation and absence of mature germ cells in both −/−Setx and −/−Atm testes . Immunofluorescent labelling with an antibody (S9.6) specific for R-loops revealed high levels of staining in the testes sections of both −/−Setx and −/−Atm mice  was performed. It was observed that most cells positive for R-loops were also undergoing apoptosis  assays for +/+Setx and −/−Setx testes, brain, and cerebella. In order to perform DRIP assays, we first searched for R-loop prediction using the R-loop forming sequence (RLFS) model to predict location of RLFSs on the mouse genome Pkd2l1gene located in the HS44.2 locus  in R-loop formation was observed in −/−Setx testes compared to wildtype supporting our immunofluorescence findings  in −/−Setx testes , a water-soluble analogue of CPT −/−Setx mice, coinciding R-loop and Ki67 signals were detected under untreated conditions −/−Setx mice failed to reveal evidence of R-loop formation . Following TPT treatment, the number of R-loops-containing cells in −/−Setx mice drastically increased in all three tissues by a 17.3-fold in the intestine, 10.5-fold in the spleen, and 1.5-fold in the testes which remained the tissue containing the highest number of R-loops-positive cells .Given that the loss of TDP1 leads to an age-dependant and progressive cerebellar atrophy, and that cerebellar neurons or primary astrocytes derived from Setx and Tdp1 in mice led to the accumulation of R-loops in proliferating cells consistent with collision between transcription and DNA replication forks when DNA lesions were not repaired Setx in mice caused persistence of DNA DSB, a defect in Rad51 disassembly, accumulation of R-loops and a failure of crossing-over in spermatocytes −/−Atm spermatocytes halt development largely at leptotene stage of meiotic prophase 1 and ovaries from females contain no primary oocytes or follicles −/−Atmspermatocytes consistent with a role for ATM in monitoring DNA DSB during meiotic recombination in early leptotene. ATM responds to the presence of excess breaks by inducing apoptosis. In this study we detected excess DNA DSB in testes sections from −/−Atmmice and these co-localised with R-loops suggesting that a combination of blocked transcription together with unrepaired DNA DSBs is responsible for the disrupted spermatogenesis. It is also evident that the majority of R-loop-containing spermatocytes are undergoing apoptosis. Mutations in TDP1 give rise to spinocerebellar ataxia with axonal neuropathy (SCAN1) −/−Tdp1mice are fertile and do not exhibit the same high level of R-loop accumulation and cell death in testes sections as −/−Setx and −/−Atm mice, we did detect levels of R-loops that were significantly higher than wildtype and there was concordance between these and apoptosis. This suggests that there is elevation in DNA breaks in −/−Tdp1mouse spermatocytes or increased DNA replication blockage that leads to R-loop accumulation. Mutations in the APTX gene lead to ataxia oculomotor apraxia type 1 (AOA1). APTX codes for aprataxin, which is an enzyme that catalyzes the removal of abortive DNA ligation intermediates and is important for DNA SSB repair −/−Aptx which also exhibits normal fertility, had elevated numbers of R-loops in the testes as compared to wildtype and similar to the −/−Tdp1mouse. However it was not to the same extent as that seen in the −/−Setx and −/−Atmmice. These data indicate that in the absence of proteins involved in recognition and/or repair of DNA damage, R-loops occur in proliferating cells due the presence of unrepaired DNA lesion that can stall the transcription machinery. In addition, the extent of R-loop accumulation can exacerbate genomic instability, trigger apoptosis and is indicative of the fertility status.Recent evidence suggests that senataxin plays a central role at the interface between transcription, DNA replication and genetic recombination in resolving R-loops to minimise the risk of genome instability −/−Tdp1mice, there is an accumulation of Topo1-linked breaks in astrocytes and an age-dependent reduction in cerebellar size −/−Atmmice also exhibit cerebellar pathology, neuronal cell death in vitro, reduced synchronization persistence in neural networks, vascular abnormalities and degeneration of the nigro-striated pathway per se. Vantaggiato et al. 2011 reported a role for senataxin in neuronal differentiation through fibroblast growth factor 8 (FGF8) signalling where they found that an overexpression of senataxin was sufficient to trigger neuronal differentiation in primary hippocampal neurons or in P19 cells treated with retinoic acid All four mutants studied here correspond to autosomal recessive ataxias characterised by cerebellar atrophy and loss of Purkinje cells Cellular viability depends on the well-orchestrated functions carried out by numerous protein-coding and non-coding RNAs, as well as RNA-binding proteins. Mutations or abnormalities that disrupt RNA or protein components of RNP complexes can be deleterious to cells and cause disease states. During the last decade, it has become increasingly evident that abnormalities in RNA processing represent a common feature among many neurodegenerative diseases. For instance, some neurodegenerative diseases result from mutated coding and non-coding RNAs, and misregulation of long non-coding RNA transcription All animal work and experiments have been approved by The QIMR Berghofer Medical Research Institute Animal Ethics Committee and all efforts were made to minimize suffering.Setx (C57Bl6/129Sv), Tdp1 (C57Bl6), Aptx (C57Bl6) and Atm (C57Bl6/129Sv) mouse strains were bred in house  and have previously been characterised and described +/−Setx and +/−Atm were crossed to generate homozygote knockouts since both knockouts animals are sterile. −/−Tdp1 and −/−Aptx were used for breeding since these animals are fertile. The mice were housed in a specific pathogen Free (SPF) PC2 facility in OptiMICE caging system (Opti-Polycarbonate cages) with artificial bedding material and subjected to a light/dark cycle of 12 h/12 h. Temperature of the animal facility was maintained constant (21°C–23°C) and the mice had permanent access to food and water (24 h/7days). Mice were housed with 2–5 companions per cage and had an enriched environment composed of shredded paper and toilet rolls. Welfare-related assessments were carried out prior to, during and after the experiment to ensure minimal suffering. The mice were ear clipped for identification at 10 days post-partum, genotyped, and weaned at 21 days post-partum. Genotyping was carried out by PCR on genomic DNA isolated from tail tips. Genotyping for the Setx, Tdp1, Aptx and Atm mice has been previously described 2 gas) as instructed by Animal welfare guidelines. Animal colonies were regularly screened every 3 months for health and immune status.The Testes from adult (1 month-old) male mice were collected and fixed in PBS buffered 10% formalin, embedded in paraffin block and sectioned at 4 µm. Sections were stained with Hematoxylin and Eosin (H&E). Slides were examined under light microscope and then scanned using Scanscope CS system . Images corresponding to ×10 and ×20 magnification were captured and assembled into Adobe Photoshop 7 .in situ Cell Death Detection Kit  following the manufacturer's instructions. TUNEL is a method for detecting DNA fragmentation by labelling the terminal end of nucleic acids and a common method for detecting DNA fragmentation that results from apoptotic signalling cascades. DNA was stained with DAPI  for 10 min at room temperature, and slides were mounted in Celvol 603 medium. Images were captured at room temperature using a digital camera  attached to a fluorescent microscope  and the AxioVision 4.8 software . The objectives employed were a Zeiss Plan Neofluar ×10/0.30 (mt10 magnification) or a 63× Zeiss Plan Apochromat 1,4 Oil DIC . Images were subsequently assembled in Adobe Photoshop 7 , and contrast and brightness were adjusted on the whole image panel at the same time. For double staining, TUNEL was carried out first followed by immunostaining as described below.Paraffin sections from testes, brain, cerebellum, spleen and intestines were dewaxed and rehydrated with Shandon Varistain Gemini ES . Apoptotic cells were detected by Terminal deoxynucleotidyl transferased UTP Nick End Labelling (TUNEL) assay using the Fluorescence −/−Setx testes sections with RNAse H   for 1 h at room temperature. Slides were incubated with anti-R-loop , anti-γH2AX  or anti-Ki67  antibodies overnight at 4°C in a humidified chamber. Slides were washed 5 times with 1× PBS containing 0.5% Triton X-100 for 5 min each at room temperature. Alexa-Dye488 or Alexa-Dye594-conjugated secondary antibody  was added for 1 h at 37°C in a humidified chamber. Subsequently, slides were washed 3 times as before and DAPI  was added for 10 min to staining nuclei. Slides were finally washed twice and glass coverslips were mounted in Celvol 603 medium for imaging. Imaging was performed as described above. Confirmation of R-loop specific staining was obtained by pre-treating bs, USA)  A.SETX (Invitrogen): SETX 1 (CCAUCUAACUCUGUACAACUUGCUU) and SETX 3 (CCAAUUGCUCCUUUCAGGUGUUUGA). Approximately 2.5–10×105 cells were transiently transfected in a six-well plate with control/SETX RNAi oligoribonucleotide (5 µl of a 20 µM stock) using Lipofectamine 2000 (Invitrogen) as described by the manufacturer. Knock-down efficiency of SETX was determined 48 h post-transfection by immunoblotting of whole cell extracts and immunostaining using and anti-senataxin  antibody SETX siRNA-tranfected cells were treated with 25 µM of camptothecin  for 2 hours at 37°C/5% CO2 to induced DNA damage and then fixed with 4% PFA and processed for immunostaining as previously described to detect R-loop formation SETX siRNA-transfected cells were also treated with actinomycin D  to transiently inhibit transcription prior to the addition of camptothecin to confirm the transcription-dependant formation of R-loops.HeLa cells (ATCC) were transfected with Stealth RNAi Negative Control LO GC (#12935200) (Invitrogen) and Stealth RNAi specific for the knock-down of In order to exacerbate the formation of R-loops and determine whether R-loop could form in post-mitotic tissues upon DNA damage accumulation, ARCA mouse models were treated with Topotecan (TPT) (Sigma-Aldrich), a water-soluble derivative of camptothecin for a period of 9 days. Topotecan was administered daily (approximately at 10:00 am) as an intraperitoneal injection following a brief anaesthesia using Isofluorane gas (2.5% at 3 L/min). Isofluorane is one of the safest methods recognised for rodents anaesthesia. For each genotype group, 3 mice were injected daily either with carrier solution  or TPT (2 mg/Kg/Day) and weight was monitored and recorded daily prior and 24 hours post injection. Animal weights were recorded prior, during, and after the treatment regimen. General health and behaviour of the mice was monitored daily until the end of the treatment when the animals were sacrificed to assess for R-loop formation, apoptosis levels and proliferation status.Pkd2l1gene located in the HS44.2 locus on chromosome 19 and the Foxo4 gene located on the X chromosome, were selected for DRIP analysis. Genomic DNA and RNA extraction from +/+Setx and −/−Setx mice testes, LCLs and HeLa cells were performed using the DNeasy Blood & Tissue Kit  following the manufacturers' instructions. Extracts were sonicated  for 3 min with 1 min incubation on ice within each min. 40 µl of Protein G beads (50∶50 slurry)  was added to the extracts and pre-cleared. In a separate tube, 15 µg of anti-R-loop antibody (S9.6) and 40 µl of Protein G beads (50∶50 slurry)  were added together and incubated at 4°C overnight on a rotating wheel to allow binding of antibody to beads. Mouse anti-IgG antibody and 40 µl of Protein G beads (50∶50 slurry)  were also added together to serve as a non-specific control for our experiment. The next day, the tubes were centrifuged at 5400× g for 2 min to pellet the beads. The supernatant was then divided equally into 3 tubes- 1 was left untreated, 1 was treated with 200 U of S1 Nuclease  and the other was treated with 10 U of RNAse H . Extracts were incubated at 37°C for 2 h, heat inactivated for 20 min at 65°C then added on to the antibody-bound Protein G beads and incubated at 4°C overnight on a rotating wheel to allow binding of R-loops fragments to antibody-bound beads. The next day, the beads were pelleted at 5400× g for 2 min and the supernatant was discarded. The beads were washed once with the IP Wash Buffer 1 , twice with the High Salt Wash Buffer , once with the IP Wash Buffer 2  and twice with TE Buffer . The immunoprecipitates were incubated at 4°C on a rocker for 3 min between each wash. The nucleic acids were then eluted twice with 100 µl of Elution Buffer . 3 µl of Proteinase K (20 mg/ml) was then added to each sample and incubated at 55°C. The samples were then diluted to 400 µl with TE Buffer and 3 µl of Glyogen (20 mg/ml)  was added. The nucleic acids were extracted using 400 µl of Phenol Chloroform (1∶1) and vortexed for 1 min. The samples were centrifuged at 16, 000× g for 5 min and the aqueous phase containing the nucleic acids were retained. These were extracted again using 400 µl of Chloroform under the same conditions. 2.5× of 100% EtOH was added to the samples and these were incubated at −80°C for 20 min. The samples were centrifuged at 16, 000× g for 20 min and the supernatant was decanted. The pellet was washed with 70% EtOH, centrifuged at 16, 000× g for 20 min and the supernatant was decanted. The pellet was air-dried and resuspended in EB Buffer .R-loop forming sequence (RLFS) model Primers for the predicted RLFS of mouse HS44.2 region were mHS44.2 1F and mHS44.2 1R. Primers for the predicted RLFS of mouse Foxo4 region were mFoxo4 F and mFoxo4 R. RLFS regions are detailed in Immunoprecipitation of senataxin protein was performed as previously described 2 , 20 µM dNTPs, 1 µM of each primer, and 5 µl of AmpliTaq Gold DNA Polymerase . The primer pairs used for gene expression analysis are described in Total RNA was isolated from 35-day-old wild type and knockout mice testes using the RNeasy mini kit  according to the manufacturer's protocol. RNA concentrations were determined by UV spectrophotometry using a Nanodrop ND-2000  and cDNA was made from 1 µg of purified RNA using Super Script III  according to the manufacturer's protocol. Gene expression analysis was performed by PCR in a 2720 Thermal Cycler . Reactions (25 µl) contained 14.5 µl of sterile water, 300 ng of cDNA template, 1× PCR Buffer II , 2.5 mM MgClFigure S1Lack of R-loops formation in −/−Atm, −/−Aptx and −/−Tpd1brain and cerebellar sections.A. Specificity of the R-loop (S9.6) antibody. Serial testes sections from −/−Setx animals were either pre-incubated with RNAse H (1 hour at 37°C) or left untreated and subsequently immunostained for R-loops. As expected a reduction of R-loop fluorescence intensity is visible in RNAse H-treated samples thus confirming the specificity of the R-loop antibody. B. Histological sections of brain and cerebellum were stained for R-loops (Red) and TUNEL (Green). DAPI stained nuclei. Scale bar, 100 µm.(TIFF)Click here for additional data file.Figure S2Knockdown of senataxin in HeLa cells using short interfering RNA (siRNA).A. Following transfection of Control (Ctrl siRNA) and SETX siRNA, HeLa cells were immunostained for senataxin (SETX) and also processed for immunoblotting. As shown in panel A, a reduction in senataxin fluorescence signal was observed after SETX siRNA treatment. B. These data demonstrated the effective knock down of senataxin in HeLa cells via immunoblotting. C. Graph is plotted to show knockdown efficiency of SETX.(TIFF)Click here for additional data file.Figure S3Primer pairs used for the genotyping of −/−Atm, −/−Setx, −/−Aptx, −/−Tdp1 mice, PCR analyses for HS44.2 and Foxo4 regions from DRIP assay as well as RT-PCR.(TIFF)Click here for additional data file.Figure S4Senataxin expression in mouse tissues.A. Senataxin immunoprecipitations from testes, brain, cerebellum, spleen and intestine were carried out to detect senataxin protein levels. A faint signal corresponding to senataxin protein was only detected in +/+Setx testes indicating lower levels of senataxin in the others tissues and/or weak sensitivity of the senataxin (Ab-1) antibody. B. RT-PCR analysis from testes, brain, cerebellum, spleen and intestine confirmed the lower levels of senataxin expression in brain, cerebellum, spleen and intestine compared to testes.(TIFF)Click here for additional data file.Figure S5R-loop prediction and candidate genes selection.A. An RLFS-containing region was found downstream of the Pkd2l1 gene located in the HS44.2 locus. The predicted RLFS was found at the position Chr19: 44,221,689–44,221,838. B. In chromosome X, the RLFS located in Foxo4 was found nearby a poly(A) signal. The predicted RLFS was found at the position ChrX: 98,456,266–98,456,499. For these genes, the predicted RLFS was located close to poly(A) signals (<500 bp) observed in mouse testes (by UCSC browser). Nucleotide sequence of the RLFS is in bold and primers are underlined.(TIFF)Click here for additional data file.


These sites contact both side chains, usually including the protonated imidazole of His, but bind-free l-His and l-Phe with much lower, sometimes undetectable, affinities. The most frequent His–Phe sites do not usually contain previously isolated sites for individual amino acids, and are only ≈35 % larger than previously known separate His and Phe sites. Nonetheless, His–Phe sites appear enriched in His anticodons, as previous l-His sites also were. Accordingly, these data add to existing experimental evidence for a stereochemical genetic code. In these peptide sites, bound amino acids approach each other to a proximity that allows a covalent peptide linkage. Isolation of several RNAs embracing two amino acids with a linking peptide bond supports the idea that a direct-RNA-template could encode primordial peptides, though crucial experiments remain.According to the RNA world hypothesis, coded peptide synthesis (translation) must have been first catalyzed by RNAs. Here, we show that small RNA sequences can simultaneously bind the dissimilar amino acids His and Phe in peptide linkage. We used in vitro counterselection/selection to isolate a pool of RNAs that bind the dipeptide NHThe online version of this article (doi:10.1007/s00239-012-9501-8) contains supplementary material, which is available to authorized users. Extant protein synthesis depends on the activity of proteins, but the initial encoded peptides must necessarily have been synthesized by non-protein agents. RNA is both capable of storing information and catalyzing reactions. Moreover, peptidyl transfer is today catalyzed by the RNA component of the ribosome  hypothesis supposes that this can be accomplished by aligning activated amino acids in RNA aptamer sites, whose proximity facilitates peptide bond formation Yarus .Multiple RNA aptamers that bind eight different individual amino acids have been isolated Yarus  using inNonetheless, it has been argued that peptide bond synthesis is impossible on a DRT, because two amino acids bound in adjacent RNA sites could not approach each other to the required bonding distance  was dehydrated in N,N-dimethylformamide (DMF). 33 μmol Fmoc-Phe-OPfp (Novabiochem) in DMF and 66 μmol N,N-diisopropylethylamine (DIPEA) were added, and the solution was mixed for 120 min. Sepharose was washed with DMF, and the column was acetylated with 3 mmol acetic anhydride + 3 mmol DIPEA for 60 min. Fmoc was then removed by the addition of 20 % piperidine in DMF. Fmoc-His-Fmoc-OPfp  and 800 μmol DIPEA were then added, and the column was mixed for 4 h. The column was again acetylated, and Fmoc was removed by addition of 20 % piperidine in DMF. Concentration of His–Phe was determined by measuring OD301 of piperidine/DMF fractions to calculate the Fmoc eluted from the column. Final His–Phe concentration was 1.6 mM. This matrix was washed and stored in water.To prepare His–Phe–Sepharose, EAH Sepharose 4B GCGTAGAGGAGGACAGCG-3′. 3′-Primer sequence, 3′ DIP: 5′-CGCTGTCCTCCTCTACGC-3′. 5′-Primer sequence, T7 DIP: 5′- Taq buffer (Promega), 0.41 mM dNTPs, 4.4 mM MgCl2, 4.5 μM each primer, 0.45 μM BR DNA, 0.046 units/μl Taq polymerase (Promega). Cycles: 94 °C for 5 min; *94 °C for 30 s, 50 °C for 30 s, 72 °C for 2 min; repeat from “*” 5 times; 72 °C for 7 min. Amplified DNA was ethanol-precipitated and resuspended in water.Single-stranded DNA BR was converted to double-stranded DNA using PCR. PCR conditions: 1×32P-GTP or CTP, 1–10 μM DNA, 1× T7 Flash enzyme (Epicentre). Incubation was at 37 °C overnight. Transcription was then treated with DNase I (Epicentre), gel purified, and ethanol-precipitated.RNA was transcribed from dsDNA as follows: 1× T7 Flash buffer (Epicentre), 7.5 mM NTPs, 10 mM DTT, 0.125–0.25 μM (1.5 mCi/ml) α-32P-labeled RNA was folded by heating at 65 °C for 3 min, adding 5× column buffer to a final concentration of 1× , and reheating for 30 s. Each cycle (except for Cycle 1) was preceded by a counter-selection against RNAs that nonspecifically bound to acetylated Sepharose. RNA (1 nmol for cycle 1) was then applied to His–Phe–Sepharose columns (equilibrated with 8 column volumes column buffer) and eluted with 1.5 mM His–Phe in column buffer (Cycle 1), or 1.5 mM His, 1.5 mM Phe, and then 1.5 mM His–Phe in column buffer (subsequent cycles). Columns were then washed with high salt buffer: 50 mM HEPES pH 7.0, 1 M NaCl, 2 mM EDTA. Desired fractions were pooled, precipitated, and reverse-transcribed into DNA using AMV reverse transcriptase . ssDNA was amplified by PCR (as for library amplification), and the cycles were repeated until a significant fraction of the RNA (by scintillation counts) was shown to elute from His–Phe columns upon addition of His–Phe. This RNA was cloned (Novagen PT7 Blue-3 Perfectly Blunt Cloning Kit) and sequenced by Sanger methods.Before column affinity chromatography, 2, 5 mM CaCl2). Modification of RNA by N-methylisatoic anhydride (NMIA) was carried out as in  exchanged with column buffer, and subjected to affinity chromatography through a His–Phe–Sepharose column. Unbound fractions followed by fractions eluted upon addition of 1.5 mM His–Phe were collected, ethanol-precipitated, and reverse-transcribed for PAGE analysis. PAGE used 8 % acrylamide/7 M urea in TBE, run at 1,600 V until xylene cyanol had migrated 16.5 cm.RNA was folded as previously but with the addition of 5.5× SHAPE folding buffer to 1×  was preceded by a counterselection which discarded RNAs eluted by free l-His and l-Phe. RNA eluted upon subsequent addition of 1.5 mM His–Phe peptide was pooled, reverse-transcribed, PCR-amplified, and transcribed back into RNA for re-selection. In the fifth cycle, 50 % of RNA was eluted by addition of peptide to the His–Phe–Sepharose  did not elute selected RNA  though all the eighteen bound His–Phe dipeptide Fig. . This doKD was determined by isocratic elution from His–Phe–Sepharose affinity columns as in Ciesiolka et al. . All the three RNAs showed an increased affinity for His–Phe, with 7.0 Fig. . FurtherN-methylisatoic anhydride (NMIA), which reacts with ribose 2′-OH of accessible nucleotides  as any selected nucleotide that is conserved in independent isolates, or implicated in binding by chemical criteria , or both conserved and chemically implicated. The sum of these “implicated nucleotides” therefore counts every nucleotide whose function is supported by recurrence, chemical experiment or both. The count of implicated nucleotides in His, Phe, and His–Phe sites is compared in Table A modular DRT, with independent amino acid sites brought together by a linking sequence, is not ruled out by our results, but Table KD have different sequences, and also have apparently different secondary structures and possible site motifs. Varying RNA affinities for the individual amino acids as well as related dipeptides indicate that His–Phe aptamers may bind different parts of the His–Phe dipeptide with high affinity, though none characterized here appears to concentrate on one amino acid exclusively. RNA 16, in particular, has measurable affinity for both the individual amino acids as well as for the dipeptide. It therefore meets the most elementary requirements of a DRT, which must bind and order activated, subsequently reacting, amino acid substrates  or possibly separated into two tracts  or the Phe moiety (RNAF–H). Such an equilibrium permits His plus Phe affinity without simultaneous binding, and would be thereby unusable for a DRT. However, present RNAs infrequently show reduced affinities for dipeptide in the presence of either His or Phe ½ in the presence of high concentrations of either amino acid; e.g., from 100 μM to 10 mM. Most tellingly, even for the one case where affinity for both His and Phe is detectable  and product (peptide) affinity have been demonstrated . RUG anticodons for His accordingly recur improbably frequently within His–Phe-binding sites. Because we have shown that the most prevalent His–Phe peptide-binding sites are not composed of the most prevalent amino acid sites, this apparent His anticodon excess occurs in a new class of RNA-amino acid interactions. These data therefore present a new level of evidence consistent with a DRT, and thereby, consistent with a stereochemical explanation of the genetic code for His Below is the link to the electronic supplementary material.


Methanopyrus kandleri grows near the upper temperature limit for life. Genome analyses revealed strategies to adapt to these harsh conditions and elucidated a unique transfer RNA (tRNA) C-to-U editing mechanism at base 8 for 30 different tRNA species. Here, RNA-Seq deep sequencing methodology was combined with computational analyses to characterize the small RNome of this hyperthermophilic organism and to obtain insights into the RNA metabolism at extreme temperatures. A large number of 132 small RNAs were identified that guide RNA modifications, which are expected to stabilize structured RNA molecules. The C/D box guide RNAs were shown to exist as circular RNA molecules. In addition, clustered regularly interspaced short palindromic repeats RNA processing and potential regulatory RNAs were identified. Finally, the identification of tRNA precursors before and after the unique C8-to-U8 editing activity enabled the determination of the order of tRNA processing events with termini truncation preceding intron removal. This order of tRNA maturation follows the compartmentalized tRNA processing order found in Eukaryotes and suggests its conservation during evolution.The methanogenic archaeon  Methanopyrus kandleri is a methanogenic archaeon that can survive extreme heat and pressure conditions. One of the earliest archaeal genome sequences was obtained for M. kandleri AV19  gene-based phylogenetic studies placed the M. kandleri branch deep at the root of the archaeal tree  set was characterized that highlights the importance of the modification of structured RNAs and the defence against viruses. Sequencing of tRNAs with and without C8 editing revealed tRNA processing intermediates and highlighted that termini truncation precedes intron removal.The extreme growth conditions of Methanopyrus kandleri cells were a kind gift of D. Söll. The organism was grown in the Archaeenzentrum Regensburg  in a 300 l fermenter as described  buffer (NEB) for 6 h at 36°C in a total volume of 50 µl with no additional treatment. Sample 2: 10 µg of M. kandleri sRNA was incubated in a buffer containing 50 mM sodium phosphate, 1 mM EDTA and 0.36% H2O2 at 20°C for 3 h to facilitate dethiolation of RNA. Sample 3: 10 µg of M. kandleri sRNA was incubated in a buffer containing 170 mM Tris–HCl (pH 8.8) at 37°C for 3 h to facilitate deacetylation of tRNA molecules. Samples 1–3 resulted in highly similar RNA-Seq sequencing output. Samples 4–6 were treated with T4 PNK to ensure proper termini for adapter ligation to RNA molecules that contain either 5′ OH termini or 3′ phosphate termini. Sample 4: 10 μg of small RNA was incubated at 37°C for 6 h with 20 U T4 PNK and in 1× T4 PNK buffer in a total volume of 50 μl. Subsequently, 2 mM adenosine triphosphate (ATP) and 10 U T4 PNK were added, and the reaction mixture was incubated for 1 h at 37°C to generate monophosphorylated 5′ termini. Sample 5: The protocol for Sample 4 was followed but the final addition of 2 mM ATP was omitted. Sample 6: The protocol for Sample 4 was followed, but 2 mM ATP was added from the beginning. Samples 4 to 6 resulted in highly similar RNA-Seq sequencing output. RNA libraries were prepared with an Illumina TruSeq RNA Sample Prep Kit (Ambion), and sequencing on an Illumina HiSeq2000 sequencer was performed at the Max-Planck Genomecentre, Cologne .Six different M. kandleri reference genome (GenBank: NC_003551) with CLC Genomics Workbench 5.5 . The following mapping parameters were used: mismatch cost, 2; insertion cost, 3; deletion cost, 3; length fraction, 0.5; similarity, 0.8. This program was also used to determine the coverage of individual RNA molecules. All predicted RNA molecules and their termini were manually verified, and all intergenic regions were checked for the presence of RNA molecules with coverage of >500 reads. Target prediction of identified C/D box sRNAs was performed with the PLEXY tool using the default parameters (Supplementary Table S1). The following algorithms were used for further computational analysis of the data: RNA folding [Mfold (Sequencing reads were trimmed by (i) removal of Illumina TruSeq linkers and poly-A tails and (ii) removal of sequences using a quality score limit of 0.05. A total of 83 338 855 reads with an average length of 61 nt were mapped to the rameters . Provideg [Mfold ], tRNA gg , small g [Mfold ], crRNA g [Mfold ], RNA alg [Mfold ] and RNAg [Mfold ]. Gene aM. kandleri sRNA preparation were treated with Superscript III reverse transcriptase (Invitrogen) and primers against C/D box sRNAs 5, 11, 16, 17, 27 to generate complementary DNA (cDNA) for the detection of circular sRNA molecules. The RNA was denatured at 100°C for 5 min and cooled on ice for 5 min to facilitate reverse transcription at 55°C for 30 min. Inactivation of the reverse transcriptase was carried out at 70°C for 15 min. Subsequently, the cDNA products were polymerase chain reaction (PCR) amplified with Platinum Taq DNA polymerase (Invitrogen) using forward and reverse primers. The following primers were used:In all, 10 ng of an C/D_5_For: 5′-GATCCCATCCTCATCCCAC-3′,C/D_5_Rev: 5′-GATCTGGGAGGCCGTTAC-3′,C/D_11_For: 5′-GCGTGGGGTAGCATCGTC-3′,C/D_11_Rev: 5′-ACCCCGATGAGGAGGAAC-3′,C/D_16_For: 5′-GTTCGTCGGCCTACCTCG-3′,C/D_16_Rev: 5′-GGGATGACGACCCCTGG-3′,C/D_17_For: 5′-CGATCCTGCGACCACTCC-3′,C/D_17_Rev: 5′-GCGGTTGTTCGCTTCTTCATC-3′,C/D_27_For: 5′-GCTCAATCTTCATCCACAGGATC-3′,C/D_27_Rev: 5′-AGCCCGGCACTGACTCG-3′.The PCR amplificates were cloned into a pCR2.1 TOPO vector (Invitrogen) and sequenced (Eurofins MWG Operon).The RNA-Seq data are available at NCBI’s Gene Expression Omnibus website as series GSE44979.M. kandleri. RNA molecules were isolated from M. kandleri cells, and small RNA molecules (<200 nt) were selectively enriched. The RNA preparation was split into six fractions and subjected to different RNA modification procedures  before adapter ligation. Three RNA samples were treated with T4 PNK to enable sequencing of RNAs with 5′ OH termini. Six independent library preparations were used for HiSeq2000 RNA-Seq sequencing. The obtained reads were mapped to the 1.69 bp long M. kandleri genome. In total, these mappings contain 83 338 855 reads with an average length of 61 nt. Clear differences for the obtained sRNome coverage were observed for the three RNA samples that were treated with T4 PNK in comparison with the three samples without this treatment. This allowed us to focus our small RNA analysis on two of these conditions and provided us with four further mappings that we used for the assessment of the reproducibility of our observations. The overview of the genome-wide RNA profile of M. kandleri reveals that most sequence reads were obtained for fragments of the 5S and 16S rRNAs as well as for small C/D box sRNAs  and tRNAAsp (23871 reads). Interestingly, in both cases, the majority of the reads represent tRNA precursors that still contain a 5′ leader sequence (5′-GAGGGGTGCGGGA-3′ for tRNATyr and 5′-GGAGGGATGAGA-3′ for tRNAAsp). These precursors most likely do not contain modifications that could block reverse transcription. The tRNATyr species is the only tRNA that is required to start with a C as the first base to ensure proper aminoacylation by the archaeal tyrosyl-tRNA synthetase . Three tRNA genes displayed problematic annotations. A tRNALeu isoacceptor lacked three 5′-terminal residues, and the two tRNAGlu isoacceptors display an unusual second intron in the tRNAs’ D-loop, which was previously predicted to be recognized by the splicing endonuclease . The occurrence of different tRNA maturation intermediates that did or did not contain features of other intermediates allowed for the generation of an order of tRNA processing events. Here, the C8–U8 editing serves as an ideal marker for one clearly distinguishable modification event. Ninety-nine percent of all tRNAs that contained the edited mature U8 base were identified by reads that started with the +1 base  that still contain the unusual intron in the D-loop of the tRNA. This indicates that, although CDAT8 requires a matured acceptor stem, it tolerates disruption and insertion of structured sequences in the D-loop and the anticodon-loop. This observation is in agreement with a model of CDAT8 interaction with the T-stem/loop and acceptor-stem portion of 30 different tRNA substrates (Reads that mapped to the regions of tRNA genes were used to distinguish between different stages of tRNA processing. The following different tRNA maturation intermediates were identified: (i) tRNAs with 5′-terminal leader sequences, (ii) tRNA with intronic sequences, (iii) tRNAs with C8 to U8 editing by CDAT8 and (iv) tRNA fragments (possibly caused by bulky modifications). The first three intermediates can be inferred from sequencing reads at single nucleotide resolution that were mapped to the tRNA genes in the reference genome or tRNA genes in a modified reference genome that contained the C8–T8 exchange. The different precursors were quantified . The abundance of individual C/D box sRNAs was found to be highly variable in the cell, despite conserved length, structure and functions. Some C/D box sRNAs were covered by few hundred reads, whereas others were among the most abundant sRNA molecules in the cell covered by hundred thousands of sequencing reads (Supplementary Table S1). We identified sequence coverage and manually annotated termini and potential C and D boxes for all detected C/D box sRNAs (Supplementary Table S1). Computational analyses using the algorithm ‘snoscan’ (Supplementary Table S1). These targets include not only rRNAs but also tRNAs and other non-coding RNAs. Interestingly, the target with the overall best score is the 5′ leader region of a newly identified H/ACA box sRNA , which suggests potential cooperative activity of guide RNAs required for different RNA modifications. We observed the highest number of sequence reads that map to a protein-coding gene for the gene MK0859 coding for GAR1, a member of the H/ACA small ribonucleoprotein complex. Analysis of the GAR1 mRNA sequence revealed a highly stable 3′-terminal hairpin structure with 10 consecutive G-C base pairs within the open reading frame that might influence mRNA stability .Most sequencing reads were obtained for C/D box sRNAs. These 55–97 nt small RNA molecules use a guide sequence located between the conserved C and D box RNA motifs to target RNA (most commonly rRNAs) for 2′-hylation . A diffesnoscan’  identifiSupplementary Table S1). Circular RNA molecules require internal cleavage to facilitate adapter ligation to the permuted RNA, which suggests that such circular molecules are likely underrepresented in RNA-Seq studies. To verify that circularization is not an artifact occurring during RNA library preparation, we performed inverse reverse transcriptase-polymerase chain reaction (RT-PCR) amplification with selected C/D box sRNA candidates. The amplification products were sequenced and confirmed the presence of the circularization sites  and are relics of viral infections. Our RNA-Seq analyses revealed that all five CRISPR clusters are active, i.e. they are transcribed and processed into small crRNAs that have the potential to mediate immunity against viruses that are recognized via base complementarity between viral DNA and crRNA spacer sequence. Based on the presence of different sets of CRISPR-associated (Cas) genes and different repeat sequences and structures, CRISPR/Cas subtypes have been classified . Most of the sequenced crRNAs harbor an 8 nt 5′ tag derived from cleavage within the repeat sequence, whereas the 3′ ends are gradually degraded and did not show a distinct cleavage site (Supplementary Table S1).The genome of assified . Methanoate ends . These tage site F. Our seage site . These cM. kandleri sRNome revealed a number of sRNAs that did not belong to any of these RNA families (Supplementary Table S1). These RNAs include intergenic sRNAs and cis-antisense RNAs, which could provide means to regulate gene expression. An Lsm protein (MK0220) to facilitate interaction of regulatory sRNAs with their mRNA targets is present in M. kandleri. Unfortunately, the lack of genetic tools for M. kandleri does not permit function analyses for these sRNA candidates.After identification of rRNAs, tRNAs, C/D box sRNAs, H/ACA box sRNAs, SRP RNA, RNase P RNA and crRNAs, the Methanopyrus kandleri grows near the upper temperature limit for life. These extreme conditions provide challenges for the production and stability of all cellular macromolecules. Proper folding and the stable maintenance of the folded structure have to be guaranteed for structured non-coding RNA molecules. One strategy is the use of G-C base pairing over A-T base pairing in RNA structure elements . Therefore, the observed circularization of C/D box sRNA might be used to stabilize these important guide RNAs at elevated temperatures.In addition, the stability of the guide RNAs that are involved in these RNA modifications needs to be guaranteed. C/D box sRNAs contain conserved RNA motifs (box C and box D sequences) that are required to form a kink-turn RNA secondary structure motif on binding of the L7Ae protein ,32. BaseCircular C/D box sRNAs have been found in three different archaeal organisms that all share a hyperthermophilic lifestyle , which sM. kandleri cells is cytidine deamination of tRNA at position 8, catalyzed by the orphan deaminase CDAT8. In all, 30 of 34 tRNA genes are transcribed as primary transcripts with a C at position 8 that is edited to U in the mature tRNA molecule. We took advantage of this unique editing marker to differentiate tRNA precursors in the RNA-Seq data and revealed that C-to-U editing occurs after termini truncation but before intron removal. This allows us to deduce the order of these processing events in a wild-type prokaryotic non-compartmentalized cell. In eukaryotic cells, compartmentalization can be used to order tRNA precursor maturation events. The tRNA genes are transcribed in the nucleus and tRNA termini are trimmed and matured. In yeast, these tRNAs are exported into the cytoplasm, where subsequently modifications are introduced and introns are spliced ; the Max-Planck Society. Funding for open access charge: Max-Planck Society.Conflict of interest statement. None declared.


Bone scanning (BS), liver ultrasonography (LUS), and chest radiography (CXR) are commonly recommended for baseline staging in patients with newly diagnosed breast cancer. The purpose of this study is to demonstrate whether these tests are indicated for specific patient subpopulation based on clinical staging and molecular subtype.A retrospective study on 5406 patients with newly diagnosed breast cancer was conducted to identify differences in occurrence of metastasis based on clinical staging and molecular subtypes. All patients had been evaluated by BS, LUS and CXR at diagnosis.P < 0.01); liver metastasis rate was 0%, 0.1%, and 1.0%, respectively (P < 0.01); lung metastasis rate was 0.1%, 0.1%, and 0.7%, respectively (P < 0.01). Complete information on molecular subtype was available in 3411 patients. For Luminal A, Luminal B (HER2-), Luminal BH (HER2+), HER2+ overexpression, and Basal-like, bone metastasis rate was 1.4%, 0.7%, 2.5%, 2.7%, and 0.9%, respectively (P < 0.05); liver metastasis rate was 0.1%, 0.1%, 1.0%, 1.1%, and 0.9%, respectively (P < 0.01); lung metastasis rate was 0.20%, 0%, 0%, 0.27%, and 0.9%, respectively (P < 0.05). cT (tumor size), cN (lymph node), PR (progesterone receptor), and HER2 status predicted bone metastasis (P < 0.05). cT, cN, ER (estrogen receptor), PR, and HER2 status predicted liver metastasis (P < 0.05). cT, cN, and PR status predicted lung metastasis (P < 0.05).Complete information on clinical staging was available in 5184 patients. For stage I, II, and III, bone metastasis rate was 0%, 0.6% and 2.7%, respectively (These data indicate that based on clinical staging and molecular subtypes, BS, LUS and CXR are necessary for patients with newly diagnosed breast cancer. Breast cancer is the most common malignancy in women in the world and patients are assigned a clinical stage at diagnosis for efficient local and systemic treatment. It has been shown that detectable metastatic disease is a low probability event increased with clinical staging in the newly diagnosed breast cancer ,2. Most + and/or PR+, HER2-, Ki67 < 14%; 2) Luminal B: ER+ and/or PR+, HER2-, Ki67 ≥ 14%; 3) Luminal BH: ER+ and/or PR+, any Ki67, HER2 overexpressed or amplified; 4) ERBB2/HER2 overexpression: ER-/PR-, HER2/neu overexpressed or amplified; [-/PR-/HER2-  [To better understand molecular pathogenesis of breast cancer, immunohistochemistry and cDNA microarray have been used to define major subtypes based on receptor status ,6. Basedplified; : ER-/PR-ke TNBC) . These mke TNBC) . Baselinke TNBC) -20. Howe5406 patients with newly diagnosed breast cancer from January 2000 to July 2010 at Harbin Medical University Cancer Hospital were included in the current study. The median age of the patients was 60 (ranging from 18 to 75). 102 patients with bone pain symptoms or elevated transaminase or alkaline phosphatase and 120 patients with inadequate information of clinical stage were excluded, leaving 5184 cases for further analysis. Among them 3411 cases had completed immunohistochemical data for subtype classification analysis. All patients were evaluated by physical examinations to determine their T (tumor) and N (lymph node) stages. Routine investigations with BS, LUS and CXR were then carried out to detect subclinical metastases. Clinical staging was defined by American Joint Committee on Cancer (AJCC) System , based oAll statistical analysis was conducted by SPSS software (version 15.0). Differences between categorical variables in metastatic events were evaluated by chi-square or Fisher’s exact tests. A p value of <0.05 was considered as statistically significant.P < 0.01); liver metastasis rate was 0%, 0.1%, 1.1%, respectively, (P < 0.01); lung metastasis rate was 0.1%, 0.1%, 0.7%, respectively (P < 0.01).Metastases were more frequent in bone, than liver and lung as shown in Table P < 0.01); live metastasis rate was 0.1%, 0.3%, 0.8%, 2.7%, respectively (P < 0.01); lung metastasis rate was 0.1%, 0.2%, 0.3%, 2.7%, respectively (P < 0.05).According to AJCC cT stage (tumor size), for patients with T1, T2, T3, and T4 disease, bone metastasis rate was 0.6%, 0.9%, 3.0%, 6.7% respectively (P < 0.01); lung metastasis rate was 0.1%, 0.1%, 0.9%, and 0.4%, respectively (P < 0.01).According to AJCC cN stage (lymph node involvement), for patients with N0, N1, N2, and N3 disease, bone metastasis rate was 0.2%, 1.2%, 2.1%, and 3.1%, respectively (P < 0.01); liver metastasis rate was 0%,0.2%, 1.0%, and 1.1%, respectively ; liver metastasis rate was 0.1%, 0.1%, 1.0%, 1.1%, and 0.9%, respectively (P < 0.01); lung metastasis rate was 0.2%, 0%, 0%, 0.3%, and 0.9%, respectively (P < 0.05).P < 0.05). Five factors  predicted liver metastasis (P < 0.05). Three factors  affected lung metastasis (P < 0.05).Four factors  evaluated in the univariate analysis had significant influences on bone metastasis , and share biological features and pathways with their preferred distant metastatic sites . PreviouIn summary, rates of bone, liver, and lung metastasis showed significant differences between different subtypes of newly diagnosed breast cancer patients. Baseline staging tests BS, LUS and CXR after a new diagnosis of asymptomatic breast cancer are necessary based on subtype classification to avoid over– and under-treatment.BS: Bone scanning; CT: Computed tomography; CXR: Chest radiography; ER: Estrogen receptor; HER2: Human epidermal growth factor receptor 2; LUS: Liver ultrasonography; MRI: Magnetic resonance imaging; PR: Progesterone receptor; TNBC: Triple negative breast cancer.There are no competing interests among the authors.CX, SL, CY, LY, ZT, LQ, MQ, PH, ZY collected clinical information. CX, CY, SL, LY, ZT, CL and DX participated in the design of the study and performed the statistical analysis. CL and DX drafted the manuscript. All authors read and approved the final manuscript.


Caenorhabditis elegans proteins NID-1/nidogen and PTP-3A/LAR-RPTP function to efficiently localize the presynaptic scaffold protein SYD-2/α-liprin at active zones. Loss of function in these molecules results in defects in the size, morphology and spacing of neuromuscular junctions.The conserved v2-like voltage-gated calcium channel (VGCC) proteins, UNC-2 and UNC-36, and the calmodulin kinase II (CaMKII), UNC-43, function to regulate the size and morphology of presynaptic domains in C. elegans. Loss of function in unc-2, unc-36 or unc-43 resulted in slightly larger GABAergic neuromuscular junctions (NMJs), but could suppress the synaptic morphology defects found in nid-1/nidogen or ptp-3/LAR mutants. A gain-of-function mutation in unc-43 caused defects similar to those found in nid-1 mutants. Mutations in egl-19, Cav1-like, or cca-1, Cav3-like, α1 subunits, or the second α2/δ subunit, tag-180, did not suppress nid-1, suggesting a specific interaction between unc-2 and the synaptic extracellular matrix (ECM) component nidogen. Using a synaptic vesicle marker in time-lapse microscopy studies, we observed GABAergic motor neurons adding NMJ-like structures during late larval development. The synaptic bouton addition appeared to form in at least two ways: (1) de novo formation, where a cluster of vesicles appeared to coalesce, or (2) when a single punctum became enlarged and then divided to form two discrete fluorescent puncta. In comparison to wild type animals, we found unc-2 mutants exhibited reduced NMJ dynamics, with fewer observed divisions during a similar stage of development.Here we show that the CaC. elegans synaptogenesis. UNC-2 has a modest role in synapse formation, but a broader role in regulating dynamic changes in the size and morphology of synapses that occur during organismal development. During the late 4th larval stage (L4), wild type animals exhibit synaptic morphologies that are similar to those found in animals lacking NID-1/PTP-3 adhesion, as well as those with constitutive activation of UNC-43. Genetic evidence indicates that the VGCCs and the NID-1/PTP-3 adhesion complex provide opposing functions in synaptic development, suggesting that modulation of synaptic adhesion may underlie synapse development in C. elegans.We identified UNC-2/UNC-36 VGCCs and UNC-43/CaMKII as regulators of  Cav1 channels localize more broadly and have been associated with events including gene regulation, local translation and dendritic growth . Transgenic animals were generated by germ line transformation as described . All images were collected on either a Zeiss Pascal confocal microscope or an Olympus FV1000 confocal microscope equipped with Fluoview software . Images were acquired using multi-track parameters when necessary (unc-36 and unc-43 rescue), with either a 63X or 60X Plan-apochromat objective, respectively. Animals were anesthetized using 0.5% phenoxy-propanol  in M9 and mounted on 2% agarose pads. Measurements of SNB-1::GFP were as described with minor modifications [t-test, while double and triple mutant combinations were compared within the group using a Kruskal-Wallis test with a Dunn’s Multiple Comparison post hoc test. Circularity is a measure of how close to a perfect circle an object is, where 0 is a line and 1 is a perfect circle. The test relates the area of the observed object to the area of a circle with the same radius:Synapse morphology of D type neurons was visualized by ications . All imaunc-36(e251) defect we generated a PCR product including the putative promoter and endogenous 3′UTR using the following primers (unc-36promF1: 5′-ccacgtacatagaattcggaatc-3′ and unc-36 3′UTR R1: 5′- caaggcagttggaaagtcgac-3′). The PCR product was TOPO cloned into pCRXLII  to generate pBA234. pBA234 was injected at 10 ng/μl into unc-36(e251);juIs1 animals along with pPD118.33 (Pmyo-2::gfp) as a co-injection marker, plus pBA186 (Punc-25::mCherry) to mark the GABAergic motor neurons containing the transgene.To rescue the unc-36 coding region was amplified using the following primers (unc-36promF1: 5′-ccacgtacatagaattcggaatc-3′ and unc-36 3′UTR R1: 5′- caaggcagttggaaagtcgac-3′). The PCR product was T/A cloned into the pCR8/GW/TOPO vector (Life Technologies), and then was recombined using L/R clonase (Life Technologies) into pBA153, creating pEVL404 (Punc-25::unc-36). pEVL404 was injected into unc-36(e251);juIs1 animals at 10 ng/μl along with pPD118.33 (Pmyo-2::gfp) as a co-injection marker. For unc-43, we isolated a full-length cDNA for UNC-43D isoform by RT-PCR from wild type RNA isolated by Trizol using the following primers (unc-43cDNA F1: 5′-atgatgaacgcaagcacca-3′ and unc-43cDNA R1: 5′- ctagaattcagatactgttgtatttgttg-3′). Using the InFusion  enzyme this product was recombined into pEVL387 (Punc-25::mCherry::unc-43 3′ UTR) to generate pEVL400 (Punc-25::mCherry::unc-43E::unc-43 3′UTR). The pEVL400 plasmid was injected into unc-43(e408);juIs1 at 5 ng/μl. Any additional information about sequences or cloning procedures is available upon request.A genomic fragment covering the L4 animals were immobilized on 10% agarose pads in the presence of 5% (w/v) polystyrene beads . Animals were imaged at 5-minute intervals for 1 hour. Animals that died during the acquisition process  were excluded from the analysis. Images were then exported to ImageJ. Z-stacks were produced for each time point, and then times 0 and 60 minutes were thresholded, converted to masks and overlaid as false colored, green and red respectively. This allowed simple determination of spots that were added or removed, grew or shrank or divided during the analysis period. The total number of puncta added/lost during the hour session was determined by comparing initial time and final time points for the appearance or disappearance of puncta.E. coli to achieve the final desired concentration. Using plates with an increasing dose of gabapentin, we found that animals reared throughout development on NGM plates containing 100 μM gabapentin phenotypically resembled unc-36, appearing thin, with poor movement (data not shown), thus we used this concentration for our experiments. Plates were permitted to dry overnight and then 20 L4 animals of each genotype were placed on the media. Animals were imaged 24 hours later (as young adults).Gabapentin  was resuspended in DMSO at 100 mM, and then diluted in 1:10 in PBS and added to standard NGM plates seeded with OP50 CaMKII: calmodulin kinase II; CNS: central nervous system; ECM: extracellular matrix; GABA: γ-amino butyric acid; GOF: gain of function; LOF: loss of function; L4: 4th larval stage; NMJ: neuromuscular junction; S.E.M.: standard error of the mean; Syd: synapse defective; Unc: uncoordinated movement; VGCC: voltage-gated calcium channel; wt: wild type.The authors declare that they have no competing interests.ju493. BDA drafted the manuscript. All authors have read and approved the final manuscript.RCC and BDA carried out the molecular, genetic and cell biological studies and collected and analyzed the data. YJ and BDA designed and conducted the genetic screen to isolate unc-2/unc-36 and nid-1. (A) The egl-19 LOF allele, n582, animals had normal appearing SNB-1::GFP puncta. (B) In egl-19(n582); nid-1(cg119) the puncta appear enlarged and disorganized. (C) A deletion in the Cav3-like channel, cca-1, had no obvious effect on SNB-1:GFP morphology. (D) Removing cca-1 from nid-1 mutants did not suppress the morphological changes, as puncta were observed to be elongated and disorganized. (E) Loss of the second α2/δ subunit, tag-180, had only a modest effect on SNB-1::GFP puncta, but did not suppress the defects found in nid-1 mutants (F). (G) A plot of the puncta area measured by genotype as mean (circle) with the 5 to 95% confidence interval (whiskers). All animals in these micrographs are young adults ). Specificity of interaction between Click here for file


We detected ferret coronaviruses in 44 (55.7%) of 79 pet ferrets tested in Japan and classified the viruses into 2 genotypes on the basis of genotype-specific PCR. Our results show that 2 ferret coronaviruses that cause feline infectious peritonitis–like disease and epizootic catarrhal enteritis are enzootic among ferrets in Japan. Mustelo putorius furo) in the United States in 2000   was first recognized in domestic ferrets , and reverse transcription PCR (RT-PCR) was performed by using the QIAGEN OneStep RT-PCR Kit (QIAGEN) using coronavirus consensus primers IN-6 and IN-7, which amplify the open reading frame (ORF) 1b region, encoding RNA-dependent RNA polymerase (RdRp). This primer pair can amplify nucleic acids from many coronaviruses in the subfamily avirinae . Nucleotavirinae . The corOn the basis of additional sequence data, a new primer pair was designed: forward FRCoV RdRp-F1 (5′-GTT GGT TGC TGC ACA CAT AG-3′) and reverse FRCoV RdRp-R1 (5′-GGA GAA GTG CTT ACG CAA ATA-3′). Results for RT-PCR using this new primer set showed that 44 (55.7%) of 79 samples were positive for coronavirus, which was a higher number than that obtained by using the published coronavirus consensus primers (55.7% vs. 41.8%) . Two samOn the basis of the partial sequences of the spike gene, Wise et al. . SamplesOur results indicate that both genotypes of coronavirus have been spreading within the ferret population in Japan for some time, and some ferrets have been coincidentally infected with both genotypes. Of note, most ferrets that were positive for genotype 1 ferret coronavirus in this study did not show FIP-like disease , indicatTo further investigate virus transmission routes, oral swab specimens were collected from 14 of the 79 ferrets and examined by RT-PCR using primers FRCoV RdRp-F1 and FRCoV RdRp-R1. Five (35.7%) specimens were positive (data not shown), providing a route leading to infection of susceptible animals. Coronaviruses are known to cause both respiratory and intestinal diseases in various animal species; therefore, ferret coronaviruses should be investigated in respiratory disease.We established a sensitive RT-PCR method using a new primer pair to detect coronavirus sequences and demonstrated that ferret coronaviruses are widespread among ferrets in Japan. We determined the partial nucleotide sequences of the spike gene of 23 strains and found they were clearly divided into 2 genotypes, 1 and 2 . The rep


Self-rated health (SRH) is a popular health measure determined by multiple factors. International literature is increasingly focusing on health-related behaviors such as smoking, dietary habits, physical activity, even religiosity. However, population-based studies taking into account multiple putative determinants of SRH in Greece are scarce. The aim of this study was to clarify possible determinants of SRH with an emphasis on the relationship between SRH and lifestyle variables in a large sample of urban citizens.In this one-year cross-sectional study, a stratified random sample of 3,601 urban citizens was selected. Data were collected using an interview-based questionnaire about various demographic, socioeconomic, disease- and lifestyle related factors such as smoking, physical activity, dietary habits, sleep quality and religiosity. Multivariate logistic regression was used separately in three age groups  in order to identify putative lifestyle and other determinants of SRH.Reporting of good SRH decreased with age . Overall, possible confounders of the lifestyle-SRH relationship among age groups were sex, education, hospitalization during the last year, daily physical symptoms and disease status. Poor SRH was associated with less physical activity in the 15-29 years old , with past or heavy smoking, along with no sleep satisfaction in the 30-49 years old  and with obesity and no sleep satisfaction in the 50+ years old individuals . Sleep dissatisfaction of the 50+ years old was the only variable associated with poor SRH at the 0.001 p level of significance . Subgroup analyses of the 15-19 years old individuals also revealed sleep dissatisfaction as the only significant variable correlated with SRH.Slight differences in lifestyle determinants of SRH were identified among age groups. Sleep quality emerged as an important determinant of SRH in the majority of participants. Self-rated health (SRH) is among the most widely used health measures in epidemiological and medical research that it is based on the individual's perception of his/her health status rated in a four or five-point scale . Self-asSeveral determinants of SRH have been recognized, such as demographic, socioeconomic, behavioral, psychosocial and disease-related factors -15. CurrA recent review of 56 studies states that "most investigations do not cover concomitantly the various aspects...of this multifaceted health measure" . In the This is a cross-sectional study carried out in the city of Athens during the period of January 2006 to December 2007. The study was ethically and methodologically approved by The Research Committee of the Technological and Educational Institute of Athens. Eligible participants were residents of Athens of both sexes and over 15 years old. Participants consisted of a stratified random sample, representative of the Athens population. In more detail, households were randomly selected by assigning random numbers at first into different municipalities of Athens and secondly at 30 of their streets by using geographical maps of the area. Subsequently, 10 streets where again randomly selected. An open letter was then posted, informing residents of the buildings of the selected streets with regards to the date of visit and the purposes of the study. Trained health professionals performed the visits at the specific dates. 47% responded negatively or were absent for two consecutive visits. When needed, a new (third) appointment was scheduled, in order to increase response rates. All participants had to give his/her informed consent for entering the study. Interviews and somatometric characteristic measurements were performed at home by trained health professional students. Written informed consent was obtained before any measurement. Data collection was based on a face to face interview questionnaire, filled only by the interviewers. Sample size was determined by the one-year period of recruitment.SRH was based on the following statement: "In general, you would describe your health as...". There were five possible answers: "excellent", "very good", "good", "moderate" and "poor". For the main analyses good SRH was defined by the first three positive answers and poor SRH by the last two. Secondary subgroup analyses for "good" vs. "very good"/"excellent" health also took place.Socio-demographic variables included age, gender and marital status. Age was divided into 3 equal groups: 15-29, 30-49 and 50+. Marital status was classified as married (or living with others) and unmarried .2) per person (range 1 to 9) was divided into two equal groups with a cutoff point of 25.5 square meters/person. To our knowledge there are no available meaningful cut-offs for this variable and since checking for different ones is beyond the scope of this study, we chose to take the median value of 25.5 sqm/person.Socioeconomic status included four variables, namely education years, occupational status, social security coverage and house surface measured in square meters/person. Education years were divided into 2 groups: below 12 and above 12 years representing higher education. Occupational status was classified as employed and unemployed. Students, household-keepers and pensioners were included into the employed category, due to our specific interest in the category of unemployed people. Concerning, social security we created two main categories one including the major social security organization i.e. IKA  and one with all the other smaller agencies. House surface size  during last year". Only two possible answers were given: "yes" or "no". Disease status was calculated with the following open question: "Do you currently suffer from a condition needing regular medical treatment?" Individuals were asked to list their health problems and two doctors independently classified their answers as valid or not. Classification was as following: healthy (or disease free), one disease needing regular medication and finally comorbidity was defined as the presence of two or more diseases needing regular medication. Daily physical symptoms were based on a similar open question: "Is there any physical symptom hindering your everyday functioning during last year?" The majority of the answers provided were about musculoskeletal, gastrointestinal, headache and fatigue symptoms. We decided to keep the analyses coding simple as "yes" or "no", because the question gave emphasis on everyday functional impairment rather than the type of the symptom.Lifestyle variables included smoking, dietary habits, sleeping patterns and religiosity.Smoking was classified as no smoker, past smoker, light smoker (≤ 20 cigarettes per day) and heavy smoker (> 20 cigarettes per day).Exercise was based on the question: "Do you work out more or less than 1 hour per week?" Answers were "more" or "less".Dietary habits were recorded by asking the respondents about the number of glasses of alcohol they drink per week, and the number of days per week that they consume meat, fruits, vegetables, legumes and fish. Cut-offs were derived by the weekly guidelines about the Mediterranean diet: 0-1 days meat, 7 days fruits and vegetables, at least 1 day legumes, at least 2 days fish and 1 glass of any alcoholic beverage per day .2), according to World Health Organization recommendations, and comprised of three categories for both men and women: normal (< 25 kg/m2), overweight (25-29.9 kg/m2) and obese (≥ 30 kg/m2).Each individual had his/her height and weight measured at the site of first encounter. All weighing machines were of the same brand name and model. Body mass index (BMI) was calculated as  "Do you pray at least once a week?" (2) "Do you attend church ceremonies at least once a week?" Crosstabs analyses came up with two main subcategories: (1) those who responded yes to both questions and (2) those who responded no to both questions.All analyses were conducted separately for the three age subgroups. Descriptive measures of the categorical variables are presented as percentage values. Missing values did not exceed 3% in any of the independent variables. In table The number of respondents in each age group was 1,360 for 15-29 years old, 1,122 for 30-49 years old and 1,112 for 50-96 years old. In the first age group there were 602 males and 758 females, in the second 473 males and 649 females and in the third 520 males and 599 females  by age groups were the following: 1) 15-29 years old: disease status 0.13 , 2) 30-49 years old: disease status 0.28 , smoking 0.07 , BMI 0.07  and 3) 50+ years old: smoking -0.05 , BMI 0.1 . The above values are in accordance with the chi-square results in table Table In the final multivariate models constructed by the forward stepwise method with 0.001 p level of significance, all adjustment variables remained significant for all age groups, while only sleep dissatisfaction was related with poor SRH in the 50+ years old individuals .Additionally, we have compared the subgroups reporting "good" versus "very good or excellent SRH" (data not presented in Table). These analyses revealed that the same pattern was pertained across each age group, although findings exhibited slightly lower strength of associations. In the first group (15-29 years), females , unmarried participants , who have used health services in the past year , who reported at least one chronic disease or comorbidity  and those sufferers physical symptoms ) reported worst (i.e. good in this case) SRH. Regarding lifestyle variables, individuals reporting no sleep satisfaction  and who consumed vegetables less than 7 times a week  also reported worst SRH.In the middle age group (30-49 years old), females , use of health care services in the past year , physical symptoms  and one chronic disease or comorbidity  were associated with poorer SRH, while higher education was significantly related to better SRH . Regarding lifestyle variables, lack of sleep satisfaction was the only variable associated with worse levels of SRH .In the oldest group, health care use in the past year , IKA insurance , one chronic disease , comorbidity , daily physical symptoms , and from lifestyle factors only sleep dissatisfaction  contributed in reporting lower levels of SRH.The objective of this cross-sectional study was to clarify putative determinants of SRH with an emphasis on the relationship between SRH and lifestyle factors in a large sample of urban citizens. As expected, female gender and more consistently disease status and healthcare use were associated with poor SRH, while significant variability of SRH putative determinants across age groups was monitored.In the younger group, individuals reporting exercise less than one hour per week have poorer SRH, implying a particular awareness of the role of exercise on health among young people.Concerning the middle age group, people with lower education level, past or heavy smokers and individuals dissatisfied with their sleep quality reported poorer SRH. Education was significant only in this age group, probably due to its higher correlation with putative socio-economic (and employment related) inequalities. Past and current heavy smokers seem to consider smoking habit more relevant to their health, possibly representing past reasons for quitting and worries of excessive smoking, respectively.In the 50+ years old group, daily physical symptoms, increased BMI score and low sleep satisfaction, were associated with poorer SRH. Interestingly, the role of gender was not significant in the elders while BMI emerged as a new SRH determinant. The most consistent correlation was that of sleep dissatisfaction and poor SRH, even in younger people when subgroup analyses (good vs very good/excellent SRH) was performed. Moreover, sleep dissatisfaction was the only lifestyle variable associated with poor SRH in elders, even when higher level of significance was applied (0.001).Overall, the explained variances of SRH from the youngest to the oldest age group were 12%, 28% and 30% respectively. The lower explained variance in the youngest group implies that other than the measured factors may determine SRH in younger people. We hypothesize that the lack of measured psychosocial factors, related mainly to interpersonal relationships or academic performance could account for this low percentage of explained variance. To test if such an assumption could be true, we repeated multivariate analyses separately for 15-19 years old and 20-29 years old people, considering that the younger group refers mainly to students of secondary education, while the second one represents students at university or labor force. For the first group, only sleep dissatisfaction correlated with poor health  and for the second one, variables were the same with the initial (e.g. 15-29 years old) group with little R square increase .In the literature, there are a vast number of similar studies that differ in respect of participants' characteristics and measurement issues, a fact that hinders a complete "face-to-face" comparison with our own. However, our main findings are quite similar with those of the most pertinent previous studies, albeit in different cross-cultural settings, that have shown, the significant relations of SRH with smoking ,18,20,22On the contrary, we did not found any relationship between dietary habits or alcohol intake and SRH supported by previous studies ,18,22. WIt is acknowledged that this study has a number of limitations. Firstly, cross-sectional analyses cannot infer causality among measured factors. Secondly, measurements are mainly based on self-report increasing the likelihood of information and recall bias. Seasonal variation in responses during the one year period of the study may contribute to information bias. Moreover, inter-interviewer variability and issues with regard to social communication  may more likely introduce measurement bias than simple questionnaire administration, but interviews have the advantage of minimizing missing values, which was the case in our study. Thirdly, low participation rate (53%) could introduce a selection bias and impair generalizability, although no cluster of low participation rate among regions was noted. Fourthly, dietary cut-offs were made according to the guidelines of Mediterranean diet without including information about the level of individuals' awareness to these directions. As written earlier in the introduction, SRH is subject to individual's perceptions and expectations, so a poor informative status about diet could deviate the association of this lifestyle matter with SRH. Finally, we did not include psychosocial variables which could be putative mediators or moderators of the lifestyle-SRH relationship.This is the first population-based survey in Greece include a plethora of lifestyle and other factors in respect to self rated health. Our study shows that - adjusted for other well known SRH related factors - lack of regular exercise, obesity, past or heavy smoking and mainly sleep dissatisfaction were related with poor SRH in a randomly selected urban population. Low explained variances of SRH, especially in the younger group, may underline the need for psychosocial measurements in future studies. The fact that lifestyle factors were associated with SRH, underlines the need to be incorporated in self-awareness and health-promotion context.SRH: self-rated health; OR; odds ratio; CI: confidence intervals.The authors declare that they have no competing interests.The conception and design of this study was made by CD. For data collection XT was responsible. Under the guidance of ECA, AKA performed the statistical analyses and wrote the first draft of the article. All authors contributed equally to the interpretation process. CD and ECA revised the manuscript. All authors read and approved the final manuscriptThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/619/prepub


We have developed a physicochemical framework, relying on base pair interaction energies, to design multi-state sRNA devices by solving an optimization problem with an objective function accounting for the stability of the transition and final intermolecular states. Contrary to the analysis of the reaction kinetics of an ensemble of sRNAs, we solve the inverse problem of finding sequences satisfying targeted reactions. We show here that our objective function correlates well with measured riboregulatory activity of a set of mutants. This has enabled the application of the methodology for an extended design of RNA devices with specified behavior, assuming different molecular interaction models based on Watson-Crick interaction. We designed several YES, NOT, AND, and OR logic gates, including the design of combinatorial riboregulators. In sum, our  in vivo RNA-RNA interactions and thermodynamics enough to perform the unsupervised computational design of fully synthetic sequences encoding functional RNAs in living cells? Recent work gave a positive answer for the challenging problem of designing activating riboregulators. This was done by integrating theory and computation to develop a physicochemical framework for the design of regulatory RNA systems, using Watson-Crick interactions and optimization algorithms. Still, the objective function was not directly validated, preventing using with confidence the methodology for other systems. We here validate experimentally an objective function relying on free energies of RNA complex activation and formation, which allows extending the framework to produce logic devices that can be implemented to program gene expression. We demonstrate that it is possible to design increasingly sophisticated and modular functions, pointing our results out that energy-based optimization methods can perform the large combinatorial search required for RNA design.Is our current knowledge of  To overcome this, we propose an evolutionary computation design strategy Small non-coding RNA (sRNA) has raised a big interest because of the predictability and modularity of its binding with a large variety of molecules and macromolecules In this work, we demonstrate a full design automation of RNA sequences that implement diverse riboregulatory mechanisms, able to produce several sRNA-based logic gates that are functional in living cells. We generalize our previous work in vitro annealing of small DNAs By generalizing the positive riboregulation paradigm, where an sRNA interacts through Watson-Crick pairing with a target mRNA to trigger a conformational change enabling ribosome docking, we can extend the methodology to design arbitrary logic gates, accounting for new regulatory mechanisms, such as anti-termination, and implementing constrained design strategies . For thaab initio objective function, which contrasts with other approaches In the following, we will start by formulating the RNA design problem as an inverse problem to program gene expression. This is based on an optimization method that minimizes an Riboregulation is based on conformational changes, after interaction, in the structures of RNA molecules, which allow controlling protein expression. To design such regulatory RNAs, we optimize the potential energy curve defined in the transition state theory Here, we consider the structures of all individual species as design specifications. To address the computational design, we firstly have to find sequences folding into predefined structures and, second, find sequences able to interact specifically among them to form complexes displaying the correct behavior. The structural constraints are exploited to considerably reduce the combinatorial space and accelerate the design of nucleic acid sequences. Our computational procedure optimizes at the same time all RNA sequences of the circuit. During the optimization, we do not impose constraints in nucleotide sequence, such as stems with high GC-content or loops with YUNR motifs, which have been found in natural systems But, is the proposed objective function predictive enough to allow the designability of multi-state RNA devices? To illustrate this question, we constructed here a library of mutants of one of our previously designed circuits  of protein TraJ Gkin and ΔGstr in section trans-repressing sRNAs. In our designs, we used the Shine-Dalgarno sequence AGGAGA.We first applied our design methodology to obtain sRNA-based repression and activation. Many known riboregulators impart a repressive action on their targets by promoting accelerated degradation through endoribonucleases, which initiate turnover of both RNAs E. coli consists in repression, an sRNA can also operate as an activator (YES logic function) trans-activates a cis-repressed gene by its 5′ UTR. After interaction, the conformational change in the 5′ UTR releases the Shine-Dalgarno sequence and allows translation , because this constrains the sequence space of possible solutions Gstr a new term for the stability . Finally, the convergence of the algorithm is highly reduced when evolving systems with multiple species, making necessary to reduce the sequence space by reusing functional modules to obtain more sophisticated systems.Our approach has, however, some limitations, which prospect further research in the field. One of them is the use of the secondary structure to model riboregulation. This type of regulation could involve pseudoknot interactions and even non-canonical base pairing, for which three-dimensional models could better capture the interaction features Gkin explained differences in experimental repression fold for a set of mutational variants of the IS10 antisense RNA system  to overcome the complexity in obtaining fully synthetic riboregulation, exploring the vast combinatorial space of sequences. The proposed objective function was shown predictive enough to allow the designability of multi-state RNA devices, as ΔA system  [4]. MorGkin and ΔGstr, for every possible conformational state (intra- or intermolecular) of a given genotype, results in an effective free energy that defines a fitness landscape. In case of riboregulation, the total search space can be about 1040 sequences 6–107 iterations. Indeed, the generalized problem of finding the nucleotide sequences of multi-species ensembles that will fold into specified conformations has an exponentially large number of solutions. It remains however a question how to distinguish several optimized sequences . For instance, differences in intracellular stability of the species will affect the ratio sRNA/mRNA, and then be key for the regulatory activity. Additionally, the kinetics of RNA folding, binding, and turnover will have significant impact on the performance of designed RNA circuits The combination of ΔOur present methodology is general and could be applied to obtain designs based on further mechanisms. In addition, instead of attempting full designs, it permits reusing complete known sequences  to constrain the design of new logic systems. This capacity enables the creation of a large variety of combinatorial sRNA systems, increasing sophistication at a reduced computational cost. Moreover, our approach can be used to analyze potential RNA sequences for a given functional circuit as a reverse engineering tool. The designed sRNA-based logic gates can be combined with transcription regulation to generate more complex functions Z) of the whole system. Using the reaction coordinate of the system (r), defined as the number of intermolecular Watson-Crick interactions  Z can be written asG(r) is the effective free energy of the state with reaction coordinate r (where G(0) represents the free energy of the no-interaction state, with G = 0 for the unfolded state), R the gas constant, and T the temperature. Here, we are interested in G(r) at the reaction coordinates for the transition, G(transr), and final intermolecular (hybridization) states, G(hybr), to define our functions ΔG, the free energy of formation, and ΔG‡, the free energy of activation, byWe considered riboregulation (RNA-RNA interaction) in terms of thermodynamics Z. In this work, we used the Mfold 3.0 RNA energy parameters T = 37°C .To compute the free energy and secondary structure of all species (single and complexes) of a system, we used the ViennaRNA A and B, an intermediate complex at the transition state ([A:B]‡) is formed mediated by the seed. Then, a fast reaction inducing a conformational change occurs. Denoting onk and offk the forward and reverse constants, respectively, to form [A:B]‡, and hybk the hybridization constant to form the final complex (A:B), the mass action kinetic model readsδ1 and δ2 are the degradation constants. Assuming that offk + hybk is much greater than δ1 /onk is the Michaelis constant. Hence, A:B  will be in steady state proportional to hybk/MK, assuming there is no saturation.In an RNA-RNA interaction between species onk can be obtained by fitting in vitro DNA hybridization data, where only the length of the seed (α), irrespective to the sequence, determines the kinetic constant following a Boltzmann factor hybk is determined by ΔG (the free energy of formation between A + B and A:B) also with a Boltzmann factor. This allows us to writepG is a fitted parameter to account for the average energetic contribution of one nucleotide. pG = −1.28 Kcal/mol G + pαG as the objective function to optimize RNA-RNA interactions. This formulation is in part equivalent to maximize Z, because from the Arrhenius equation G‡ and α should have a linear relationship.The constant Our evolutionary algorithm consists in a Monte Carlo Simulated Annealing useful mutations, e.g., mutations that are always guaranteed to contribute for an interaction among RNA species. We do this by taking a word  from one sequence, making its reverse complementary, and randomly inserting it into another sequence. Initially, the length of this word is three, and it is reduced to one  during the optimization process. Those mutations speed up the in silico evolution. If a nucleotide that has to be mutated belongs to a stem, its pair in the stem is also mutated with the corresponding nucleotide with the aim of preventing the disruption of the secondary structure and improving the convergence. We avoid sequences having consecutive repeats of four or more identical nucleotides.The design specifications comprise the secondary structures of all single RNAs, critical subsequences of nucleotides , the reaction free energies, and the structure of the output complex. The algorithm starts from pure random sequences satisfying the structural and subsequence constraints, although it can also be specified an initial sequence. If the subsequence constraints do not allow satisfying the structures, the algorithm stops. Eventually, we can introduce a relaxation in the structural constraints (through an harmonic constraint) allowing having species with dissimilar structures to their targets. Subsequently, an iterative process of mutation and selection is implemented  accounts for the reaction kinetics of the system. For that, we compute the ΔG and α of all possible reactions, having between species A and BGkin is a negative-valued variable. We will minimize or maximize ΔGkin if the reaction must occur or not (in order to obtain the specified behavior). Maximizing ΔGkin is equivalent to minimize −ΔGkin. During the optimization we exclude sequences forming homodimers. In addition, we considered ΔGsat = −15 Kcal/mol and αsat = 6 as arbitrary saturation levels . These values can be enlarged to get designs with lower ΔGkin, although at a cost of altering the convergence. The second term (ΔGstr) accounts for the structural change of the output RNA. For that, we use a Hamming distance (d) between the current and target structures, beingA (which can be single or complex) is evolved to display the target structure, or substructure, Str . pG is used to rescale the distance in terms of free energy. We note that ΔGstr is a positive-valued variable, which we will minimize.The objective function is a weighted sum of two terms to be minimized. The first term  and II  in a volume of 20 µL with 0.4 U of the high fidelity Phusion DNA polymerase (Thermo Fisher Scientific) in the presence of HF buffer (Thermo Fisher Scientific), 3% dimethyl sulfoxide, 0.2 mM each dNTP and 0.5 µM each primer. Reactions consisted of an initial denaturation of 30 s at 98°C followed by 30 cycles of 10 s at 98°C, 30 s at 55°C and 1∶15 min at 72°C, with a final incubation of 10 min at 72°C. After PCR, 10 U of DpnI (Thermo Fisher Scientific) were added to each sample to digest the template plasmid and incubated for 1 h at 37°C. Reaction products were electrophoresed in a 1% agarose gel in TAE buffer  and the gel stained with ethidium bromide. The 4460-bp long DNA product corresponding to the full-length plasmid was eluted from the gel, digested with BpiI for 1 h at 37°C (Thermo Fisher Scientific) and finally subjected to self-circularization with 5 U of T4 DNA ligase (Thermo Fisher Scientific) for 1 h at 22°C. Reaction products were purified by chromatography with silica gel spin columns  and electroporated in E. coli DH5α. Recombinant bacteria were selected in plates with 50 µg/mL ampicillin. Plasmids were purified from liquid cultures of selected clones  and analyzed by electrophoresis in 1% agarose gels in TAE buffer, followed by ethidium bromide staining. Forty-five plasmids whose electrophoretic mobility matched that of parental pRAJ11 were subjected to sequence analysis with primer III (5′-GAATTCGCGGCCGCTTCTAGAGC-3′) to find out the particular sequence in the randomized trinucleotide position introduced by primer I. Eleven mutant clones (see 100 ng of plasmid pRAJ11 coding for the riboregulatory device RAJ11 were subjected to 30 cycles of PCR amplification with divergent primers I (ones see  were selones see .600 about 0.5). Ampicillin was used as antibiotic at 50 µg/mL. Then, 500 µL of each culture were centrifuged for 2 min at 13,000 rpm, and resuspended in the same volume of water. Subsequently, we loaded the multiwell plate with 200 µL for each sample, which was assayed in a Victor X5 (Perkin Elmer) to measure absorbance (600 nm absorbance filter) and fluorescence . Background values of absorbance and fluorescence, which corresponded to water, were subtracted to correct the signals, and the normalized fluorescence was calculated as the ratio of fluorescence and absorbance (Cultures (2 mL) inoculated from single colonies  were grown overnight in LB medium at 37°C and 220 rpm. Cultures were then diluted 1∶100 (in 2 mL of LB), and were grown for 3 h in the same conditions Click here for additional data file.Figure S2Regulation of a natural gene. Design of a synthetic sRNA  able to interact with and release the RBS of the natural RpoS 5′ UTR. (A) Detail of the RpoS 5′ UTR, showing the RBS in blue and the start codon in green, together with the synthetic sRNA. (B) Detail of the intermolecular species.(TIFF)Click here for additional data file.Figure S3Scheme of the algorithm to design riboregulation.(TIFF)Click here for additional data file.Figure S4Characterization results of our library of devices. We present the fluorescence values for cells transformed with different plasmids: pRAJ11 and its derived mutants (mX), pRAJ11m, and pBS  as a control. Error bars represent SE (standard errors).(TIFF)Click here for additional data file.Figure S5Plasmid maps. They correspond to the native RAJ11 device, which was previously engineered (Addgene refs. 39244 and 39245) (TIFF)Click here for additional data file.Table S1RNA sequences for the designs shown in the Figures. On the 5′ UTRs, we highlight the RBS sequence (blue) and the start codon (red), and the poly(U) tail (yellow) when appropriate.(DOC)Click here for additional data file.Table S2Properties of experimental systems for independent validation. These RNA systems (selected from ref. E. coli. Reported repression folds (changes in percentage of protein expression in absence or presence of sRNA) were measured by fluorometry.(DOC)Click here for additional data file.Table S3RNA sequences of the library of devices constructed in this work. These are mutants of the system RAJ11 (from ref. (DOC)Click here for additional data file.Table S4Properties of our library of devices. These RNA systems are employed to validate the objective function used in this work.(DOC)Click here for additional data file.


Matrin 3 (MATR3) is a highly conserved, inner nuclear matrix protein with two zinc finger domains and two RNA recognition motifs (RRM), whose function is largely unknown. Recently we found MATR3 to be phosphorylated by the protein kinase ATM, which activates the cellular response to double strand breaks in the DNA. Here, we show that MATR3 interacts in an RNA-dependent manner with several proteins with established roles in RNA processing, and maintains its interaction with RNA via its RRM2 domain. Deep sequencing of the bound RNA (RIP-seq) identified several small noncoding RNA species. Using microarray analysis to explore MATR3′s role in transcription, we identified 77 transcripts whose amounts depended on the presence of MATR3. We validated this finding with nine transcripts which were also bound to the MATR3 complex. Finally, we demonstrated the importance of MATR3 for maintaining the stability of several of these mRNA species and conclude that it has a role in mRNA stabilization. The data suggest that the cellular level of MATR3, known to be highly regulated, modulates the stability of a group of gene transcripts. Matrin 3 (MATR3) is a highly conserved, inner nuclear matrix protein of 125 kDa MATR3 was reported to be phosphorylated by the protein kinase PKA following activation of the NMDA receptors, which led to its degradation Following our earlier observation of MATR3′s involvement in the DNA damage response In order to obtain clues to MATR3′s function we set to identify novel MATR3-interacting proteins. FLAG-tagged MATR3 was expressed in HEK293T cells and immunoprecipitated using anti-FLAG antibody, with an empty vector serving as control. The immune complexes were separated using SDS-PAGE, and the gels underwent silver staining . Bands tIndividual interactions with MATR3 were validated by co-immunoprecipitation. The proteins DHX9 and HNRNPK co-immunoprecipitated with ectopic and endogenous MATR3 . In viewMATR3 has two zinc finger domains that can potentially interact with DNA, and two RRMs that are known to interact with RNA . These dCo-immunoprecipitation of MATR3 with its interactors was RNA- and RRM2-domain-dependent, suggesting that MATR3 binds RNA molecules via its RRM2 domain, and this RNA is important for MATR3 interactions. We undertook to identify these RNA species. FLAG-MATR3 was immunoprecipitated from HEK293T cells, and RNA was extracted from the immune complexes and underwent RNA-seq using the Illumina/Solexa technology. We used total cellular RNA as background control. While an ideal control would have been RNA obtained from immune complexes of RRM2-deleted MATR3, the amount of RNA found in such immune complexes was minute and did not allow sequencing. We thus identified 4 RNA species in MATR3 immune complexes that were significantly over-represented in these complexes compared to their occurrence in total cellular RNA. All of these RNAs turned out to be small noncoding RNAs .S. Cerevisiae was added to this RNA as an exogenic control. The results confirmed that all 4 small noncoding RNAs co-immunoprecipitated with wild type MATR3  in cells proficient or deficient of MATR3, by monitoring the decay of these mRNAs after inhibition of de novo transcription using actinomycin D. Indeed, MATR3 depletion reduced the stability of the 3 mRNAs compared to GAPDH mRNA . This reMATR3′s activity and mode of action are unclear, but its domains predict a role in RNA metabolism. We identified DHX9 and HNRNPK as new interactors of MATR3. DHX9 is a DNA and RNA helicase with diverse physiological functions in transcription, RNA processing, transport In view of the involvement of MATR3′s RRM domains and its new interactors in RNA metabolism, we asked whether RNA is involved in these interactions and found them to be dependent on both RNA and the RRM2 domain of MATR3. Furthermore, we obtained a first demonstration that MATR3 is an RNA-binding protein. Deep sequencing of bound RNA identified several small noncoding RNAs, which were over-represented in MATR3 immunoprecipitates and whose binding depended on MATR3′s RRM2 domain. Interestingly, one of these RNAs was 7SK, which is known to bind HNRNPK While HNRNPK was shown to co-activate p53, our microarray analysis indicated that MATR3 is not involved in p53 activation . HoweverThe half-life of mRNA molecules is affected by specific sequences usually located in the 3′ UTR, and is regulated by RNA-binding proteins that bind to these sequences . An extensively documented example is the ARE sequence, a short sequence (AUUUA) found in the 3′ UTR of many mRNAs . RNA-binding proteins such as the Hu proteins bind to this sequence and enhance the stability of the corresponding mRNAs . The steady-state levels of the mRNAs thus depend on the balance between their own production and the levels and activity of proteins that stabilize them or enhance their degradation.The levels of cellular MATR3 are highly regulated 2 atmosphere.HEK293T (ATCC Number: CRL-11268) and U2OS (ATCC Number: HTB-96) cells were grown in DMEM supplemented with 10% fetal bovine serum, at 37°C and 5% COPolyclonal antibodies against MATR3, DHX9, and HNRNPK were obtained from Bethyl Laboratories . FLAG-conjugated beads were purchased from Sigma-Aldrich, RNase A from RBC , neocarzinostatin from KayaKU Chemicals  and actinomycin D from Sigma-Aldrich.A full-length cDNA clone of MATR3, KIAA0723, was obtained from the Kazusa DNA Research Institute  and cloned into pCMV:FLAG2B vector. Deletions in the cDNA were generated by Pfu polymerase amplification using the MATR3 construct as template and primers flanking the domain to be deleted.Immunoblotting and immunoprecipitation were carried out according to standard techniques. Briefly, cells were harvested and lysed in RIPA lysis buffer, and the lysates were run on 8% SDS PAGE and transferred onto a nitrocellulose membrane. For immunoprecipitation, cells were washed twice with ice-cold PBS, harvested, and lysed for 30 min on ice in 0.5% NP40, 150 Mm NaCl, 50 Mm Tris pH7.5, and 1 mM EDTA supplemented with a mixture of protease and phosphatase inhibitors. Supernatants were collected and the primary antibody was added for 2 hr at 4°C. Protein A and G sepharose beads were added for an additional 1 hr, after which the beads were washed 4 times. Beads were boiled in sample buffer and loaded onto the gel. In the RNA-IP experiment the RNA was extracted from the immune complexes after the above IP procedure. Mass spectrometric analysis was carried out as previously described AGACTTCCATGGACTCTTA) targeting human MATR3 mRNA were designed, and subsequently synthesized by Dharmacon  with the OnTarget Plus modifications. The above oligonucleotide was used for the microarray experiment and subsequent experiments were carried out using OnTarget Plus SMARTpool against MATR3, which was obtained from Dharmacon . U2OS cells were grown to 20%–50% confluency and transfected with siRNA using the DharmaFECT 1 reagent .RNA duplexes of 19 nucleotides (RNA was isolated from cells or immune complexes using the RNeasy plus mini kit (QIAGEN).Following protein immunoprecipitation, immune complexes bound to beads were washed twice with lysis buffer containing 0.5% NP-40 and suspended in the same buffer containing 0.1 mg/ml of RNase A for 15 min at room temperature.Libraries were prepared as described in Sultan et al. 2008 The SOAP program cDNA synthesis was carried out with the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). qPCR was performed with the Power SYBR Green RT-PCR Master Mix (Applied Biosystems) and the ABI PRISM 7900HT sequence detection system (Applied Biosystems). The comparative Ct method was employed to quantify transcripts, and delta Ct was measured in triplicate.S. Cerevisiae Phe-tRNA (Sigma-Aldrich), which was added to the samples after RNA extraction of the immune complexes. Primers used in the RT–PCR assays are provided in RIP-Sequencing results were normalized against U2OS cells were transfected with siGFP (irrelevant siRNA) or siRNA against MATR3, and 96 hr later the cells were treated with actinomycin D (2 µg/ml) for different time points, and harvested in Trizol reagent (Sigma-Aldrich). Total RNA was used for qPCR. For each time point, amounts of mRNAs were normalized against 18S rRNA and half-lives were calculated relative to untreated sample.Figure S1Expression profiles were recorded in U2OS cells knocked-down for MATR3 and in control cells transfected with siGFP, using the Affymetrix Human Gene 1.0 ST arrays. Profiles were measured at two time-points (3 and 6 hr) after treatment with the radiomimetic drug neocarzinostatin (NCS) and in time-matched untreated controls. Responding genes in the datasets (defined as those showing at least 1.7 fold-change in expression level following NCS treatment) were subjected to clustering analysis by the CLICK algorithm (EPS)Click here for additional data file.Table S177 genes whose expression levels were reduced in MATR3-depleted cells.(XLS)Click here for additional data file.Table S2Primers used for real-time PCR.(XLS)Click here for additional data file.