Long noncoding ribonucleic acids (lncRNAs) are a subclass of regulatory noncoding ribonucleic acids for which expression and function in human endothelial cells and angiogenic processes is not well studied.The authors discovered hypoxia-sensitive human lncRNAs via next-generation ribonucleic acid sequencing and microarray approaches. To address their functional importance in angiogenic processes, several endothelial lncRNAs were characterized for their angiogenic characteristics in vitro and ex vivo.Ribonucleic acid sequencing and microarray-derived data showed specific endothelial lncRNA expression changes after hypoxia. Validation experiments confirmed strong hypoxia-dependent activation of 2 intergenic lncRNAs: LINC00323 and MIR503HG.Silencing of these lncRNA transcripts led to angiogenic defects, including repression of growth factor signaling and/or the key endothelial transcription factor GATA2. Endothelial loss of these hypoxia-driven lncRNAs impaired cell-cycle control and inhibited capillary formation. The potential clinical importance of these endothelial lncRNAs to vascular structural integrity was demonstrated in an ex vivo model of human induced pluripotent stem cell–based engineered heart tissue.The authors report an expression atlas of human hypoxia-sensitive lncRNAs and identified 2 lncRNAs with important functions to sustain endothelial cell biology. LncRNAs hold great promise to serve as important future therapeutic targets of cardiovascular disease. The identification of the expression and function of cardiovascular noncoding ribonucleic acids (RNAs), such as microRNAs (miRNAs) , has opened a new avenue of genome-regulatory paradigms. Numerous reports have proved that single miRs have a master role in the regulation of cardiovascular pathophysiology and serve as interesting treatment targets The current annotation of lncRNAs within databases is a very dynamic process because of actively increasing knowledge in this field Very recently, endothelial lncRNA MIAT was found to be induced in diabetic conditions LncRNAs may also enter the circulation to form a basis for new diagnostic and prognostic strategic approaches to cardiovascular disease In this work, we globally studied whether lncRNAs are differentially regulated in human ECs through hypoxia using RNA-seq and microarray approaches and applied gain- and loss-of-function studies for selected novel endothelial lncRNAs in vitro and ex vivo to study their functional importance for endothelial biology. Thus, the aim of this study was to provide an overview of hypoxia-sensitive functional lncRNAs to discover new entry points for the development of lncRNA-based strategies to modulate tissue vascularization.We used 2 μg of total RNA from human umbilical vein ECs (HUVECs) cultured under normoxic or hypoxic conditions for 24 h and subjected to RNA-seq analysis (n = 3). After extracting the total RNA from the samples, ribosomal RNA was removed from the total RNA. By using the fragmentation buffer, the left RNA was fragmented into short fragments, then the first strand complementary deoxyribonucleic acid was synthesized by random hexamer-primer using the left RNA fragments as templates. Buffer, nucleotide triphosphates containing deoxyribose, ribonuclease H, and deoxyribonucleic acid polymerase I were added to synthesize the second strand. The double-strand complementary deoxyribonucleic acid was purified using the QiaQuick polymerase chain reaction extraction kit  and washed with elution buffer for end repair and poly(A) addition. Finally, sequencing adaptors were ligated to the fragments, which were purified by agarose gel electrophoresis and enriched by polymerase chain reaction amplification. The library products were sequenced using the HiSeq 2000 .A detailed methods section is available in the To identify hypoxia-sensitive endothelial lncRNAs, HUVECs were first subjected to 24 h of hypoxia. In preliminary experiments, we found this time point optimal for identifying regulations of a vast majority of lncRNAs (data not shown). Hypoxia-sensitive noncoding RNA expression was detected via 2 approaches, microarray- and RNA-seq-based techniques. We first focused on the microarray-derived noncoding RNA dataset to search for lncRNAs using the following criteria: minimal 4-fold deregulation and intergenic lncRNA localization. By this approach, we identified LINC00323 (lnc-DSCAM-1) to be the strongest (∼8-fold) up-regulated lincRNA after hypoxia (probe uc002yyv) .2-fold expression changes derived from the 2 different technologies were significantly correlated both for lncRNAs  and for protein-coding genes   significantly deregulated lncRNAs . The ana× 10−16) . RNA-seq× 10−16) .Figure 1In addition, from the RNA-seq data, we identified another hypoxia-sensitive lncRNA, MIR503HG (lnc-PLAC1-1), on the basis of the following criteria: 1) minimal 4-fold up-regulation; 2) base mean >1,000; and 3) intergenic annotation. On the basis of these stringent criteria, we identified lnc-MST1P9-2 and lnc-PLAC1-1 as high propriety candidates but omitted lnc-MST1P9-2 from further studies because of potential protein-coding properties. Subsequent validation experiments confirmed the hypoxia-dependent up-regulation of the previous 2 array- or RNA-seq-derived lincRNAs, LINC00323 and MIR503HG . High puLINC00323 is encoded on chromosome 21 and has 3 transcript isoforms cis-action of lnc-MIR503HG on neighboring miR-424. MiR-424 was previously described to be antiproliferative in lung arterial ECs; moreover, its overexpression triggers antiangiogenic effects in human ECs The RNA-seq-derived lincRNA MIR503HG is located at chromosome X, harbors a coding sequence of miR-503, and is adjacent to miR-424 . Indeed,To study the role of enhanced lincRNA expression in ECs, the hypoxia-sensitive lincRNAs LINC00323-003 and MIR503HG were both overexpressed by generation of stable green fluorescent protein (GFP)-expressing EC lines (Ea.Hy926) . TransgeTo investigate whether the in vitro findings could be validated in a 3-dimensional ex vivo model, we generated human induced pluripotent stem cell–derived engineered heart tissues (EHTs) enriched with GFP-overexpressing HUVECs for easy identification of ECs in such human ex vivo constructs. HUVECs showed 99% purity after blasticidine selection, as confirmed by flow cytometric analysis (data not shown) and GFP fluorescence microscopy . EHTs weHypoxia is a strong proangiogenic stimulus and induces VEGF-mediated signaling in ECs Key experiments for LINC00323-003 were also validated in arterial ECs, suggesting the importance on ECs in general. Of translational importance, lncRNA knockdown also resulted in impaired vascularization in an ex vivo induced pluripotent stem cell–based 3-dimensional engineered human heart tissue model. This model was used because of weak conservation at the sequence level in nonhuman species. However, a potential mouse homologue for MIR503HG, Gm28730, with about 70% sequence overlap, could be identified. The choice to investigate LINC00323-003 and MIR503HG was dependent on their high deregulation in either microarray or RNA-seq datasets. It is likely that many other thus far uncharacterized lncRNAs also have crucial functions in endothelial biology and should be investigated in future studies; the database of array- and RNA-seq-based lncRNA expression profiles reported here will be helpful in this context.Both lncRNAs LINC00323-003 and MIR503HG exerted an important functional relevance for EC biology, making them potential attractive molecular targets in vascular diseases. We have provided initial insight into their interaction partners, such as miRNAs and proteins, but we wish to point out that more in-depth mechanistic studies are needed in the future to fully understand the mode of action of the identified lncRNAs. In general, lncRNAs are less (sequence) conserved among species, thus hampering translational approaches in a relevant in vivo vascular disease setting in other species models. To circumvent this limitation, we applied a model of human induced pluripotent stem cell–based EHT to translate the importance of these 2 lncRNAs in endothelial biology in a more realistic translational scenario.PerspectivesCOMPETENCY IN MEDICAL KNOWLEDGE: Angiogenesis is a key mechanism by which organs maintain blood supply, and this has therapeutic implications for amelioration of ischemia in organs or inhibition of vessel-dependent cancers. LncRNAs are key regulators of endothelial proliferation and play a role in angiogenesis.TRANSLATIONAL OUTLOOK: Future research should examine the potential role of interventions that increase or normalize lncRNA expression and cell type–specific function to modulate angiogenesis in patients with myocardial infarction, peripheral arterial disease, or ischemic stroke.We have identified 2 novel hypoxia-sensitive endothelial lncRNAs, LINC00323-003 and MIR503HG, by the use of microarray and next-generation RNA-seq techniques. Functional characterization applying loss- and gain-of-function approaches in cultured ECs revealed an important role for both of these lncRNAs in endothelial biology. Our data enable the future development of novel lncRNA-therapeutic approaches to cardiovascular diseases. More general, our data identify novel strategies based on lncRNA modulation to alter tissue vascularization, with the aim of either enhancing  or blocking  vascularization.


Our findings show that the median window of opportunity interval length for TVU monitoring and HGSOC detection is approximately 1.76 years. This does not translate into reduced mortality levels or improved detection accuracy in an in silico cohort across multiple TVU monitoring frequencies or detection sensitivities. We demonstrate that even a semiannual, unimodal TVU monitoring protocol is expected to miss detectable HGSOC. Lastly, we find that circa 50% of the simulated HGSOC growth curves never reach the baseline detectability threshold, and that on average, 5–7 infrequent, rate-limiting stochastic changes in the growth parameters are associated with reaching HGSOC detectability and mortality thresholds respectively. Focusing on a malignancy poorly studied in the mathematical oncology community, our model captures the dynamic, temporal evolution of HGSOC progression. Our mathematical model is consistent with recent case reports and prospective TVU screening population studies, and provides support to the empirical recommendation against frequent HGSOC screening.High-grade serous ovarian cancer (HGSOC) represents the majority of ovarian cancers and accounts for the largest proportion of deaths from the disease. A timely detection of low volume HGSOC should be the goal of any screening studies. However, numerous transvaginal ultrasound (TVU) detection-based population studies aimed at detecting low-volume disease have not yielded reduced mortality rates. A quantitative invalidation of TVU as an effective HGSOC screening strategy is a necessary next step. Herein, we propose a mathematical model for a quantitative explanation on the reported failure of TVU-based screening to improve HGSOC low-volume detectability and overall survival.We develop a novel  Ovarian cancer is a relatively rare disease, representing 2.6% of all new cancer cases in US women . HoweverO2 species, making a departure from healthy homeostasis difficult to observe [in vivo or estimate in vitro.Focusing on HGSOC, clinical features of its progression prior to detection are difficult to observe. Only circa 15% of HGSOC are solely localized to the ovary or fallopian tubes at the time of diagnosis . Moreove observe . HGSOC cBRCA1 and BRCA2 mutation carriers, or women with a significant family history of breast or ovarian cancer.Existing early detection screening strategies for other cancer types, including prostate, colon, breast and cervical cancers, raise the question of whether HGSOC is amenable to similar screening strategies. Emerging insights into HGSOC’s disease progression suggest that early detection of low volume advanced stage, rather than large volume early stage HGSOC, may be a more clinically actionable goal of screening studies, since five-year relative survival rates for advanced stage cancers at diagnosis are significantly lower than for early stage cancers at diagnosis , 6, 8–10So far, evidence of a mortality benefit continues to elude HGSOC screening. Several studies have evaluated the efficacy of uni- or multi-modal TVU screening in general-risk populations and their impact on mortality benefit for several ovarian cancer histologies , 19, 20.in vitro temporary cessation of tumor growth, or provides a quantitative assessment of the feasibility of frequent TVU monitoring with respect to HGSOC low-volume detectability and overall survival. It is precisely this absence of inferences from mathematical modeling regarding HGSOC progression that motivated this study of TVU-based detection strategies.A wide variety of mathematical models on cancer and tumor growth exist, e.g. –29, howein silico mathematical model that provides a quantitative explanation behind the reported failure of TVU to improve HGSOC low-volume detectability and overall survival rates. We develop a mathematical assessment of the efficacy of a unimodal TVU monitoring regimen as a strategy aimed at detecting low-volume HGSOCs in cancer-positive cases, defined as cases in whom the inception of the first HGSOC malignant cell has already occurred. Our model captures the dynamic, temporal evolution of HGSOC growth and progression, and provides quantitative estimates of otherwise unknown clinical parameters such as the duration of HGSOC’s pre-diagnosis stage and the screening window of opportunity interval length.Herein, we propose a novel in silico mathematical framework modeling incipient HGSOC growth kinetics in an untreated scenario, subject to stochastic heterogeneous fluctuations. Herein, we refer to an untreated HGSOC as a radiographically detected, clinically asymptomatic, treatment-free malignancy in which no surgery and/or other systemic therapies has yet been performed/administered. Inspired by a stochastic numerical model of breast cancer growth [We develop an r growth , we foll3 for pre- and 10 cm3 for postmenopausal women [3) would represent a suspicious TVU finding, and subsequently be diagnosed as a radiographically detectable HGSOC case. The data points illustrated in To estimate a lower bound for the initial HGSOC growth rates, we identified the existing TVU-based screening study with the largest cohort of ovarian cancer patients . In thisal women . Menopaual women . We subs3 , as previously published [3 = 1 cc = 109 HGSOC cells [window of opportunity interval as the difference between the two thresholds based on the growth curves that reach both endpoints.HGSOC-growth curve time is measured from the inception of the first malignant cell until the time needed to reach the baseline TVU detection threshold, or until the baseline life-threatening tumor volume is reached. Herein, we assume that the minimum, baseline TVU detectability threshold for a cancer-positive case is 10 cmublished . The twoOC cells . The basin silico cancer-positive cohort, for which the former term is more appropriate.We use the incipient HGSOC growth kinetics model to study the timing of HGSOC initiation relative to reaching TVU detectability and the life-threatening untreated tumor volume sizes, as defined above, and its subsequent implications on TVU monitoring protocols. We choose to use the terminology ‘TVU monitoring’ in lieu of ‘TVU screening’, as the latter would be a more appropriate term for a detection strategy focused on a cohort of cancer-negative, general or high-risk otherwise asymptomatic healthy women , as oppoin silico HGSOC growth curves that would be missed even under frequent TVU monitoring. To this end, we developed a mathematical framework modeling incipient untreated HGSOC volume growth in order to satisfy two purposes: one, to simulate the natural history of the malignancy, and two, to quantify the relationship between TVU monitoring frequency and detection time of a non-life-threatening HGSOC volume.A main study end point for this model was HGSOC-specific mortality, specifically the number of 0 represents the initial, pre-diagnosis HGSOC cell count, set as 1 for computational convenience, and time t is measured since the inception of the first malignant cell. If we let kgrowth represent the initial HGSOC growth rate constant and kdecay describe the growth saturation rate, where both parameters have the dimension of inverse time , the Gompertz function modeling tumor growth can be expressed as∞ is assumed to be finite and nonzero. It follows that kdecay > 0, and that i(ti), we requireTo obtain a temporal estimate of the effective growth behavior of a simulated HGSOC growth curve, we let N(t) be the total HGSOC tumor volume, i.e. the number of HGSOC cells located in the primary tumor site , at time t. Nin vitro, with tumor dormancy in ovarian cancer spheroids [in vivo with tumor xenografts implanted in mice [decay, we assume that HGSOC growth slows down due to adverse environmental conditions . The irregular tumor growth kinetics illustrated in our model accounts for the observed heterogeneity in the progression of clinical HGSOCs [in vivo and in vitro.In this case, the tumor cell burden can outgrow its size at the inflection point by a factor of e. The inflection point represents a turning point in the dynamics when the observed growth trend starts decelerating. Nonetheless, while the Gompertz equation describes a density-dependent growth rate, it does not account for any stochastic irregularities, e.g. stepwise growth patterns, also see ; such tepheroids , 44, humpheroids , 46, or  in mice , and mayl HGSOCs  and highl HGSOCs ). The tudecay to be initial decay, in a two-step manner. First, we generate a number α ∼ ln N, that is log-normally distributed with mean = 10−2, variance = 25 x 10−2, and range = 0.0094 − 0.150 . Herein, α refers to the probability of random change in kdecay. In order to implement conservative estimates for the clinically occult random variable α, we choose an asymmetric, right-skewed probability distribution function. Second, we check whether α is less than a randomly generated number between 0 and 1. If that is the case, we then generate a second random number between 0 and 1 and compute the updated kdecay asdecay occurs again, which leads to another update.We assume the inception of the first HGSOC malignant cell occurs sometimes during premenopausal years, and thus we increment time in intervals of 28 days  for a tgrowth or kdecay makes little qualitative difference from a mathematical perspective; we can thus infer that modifying either parameter yields similar qualitative effects. From a molecular perspective, we chose to focus on changes in the initial HGSOC growth saturation rate, kdecay, as these infrequent, rate-limiting changes could be associated in part with the several (epi)genetic alterations in tumor suppressor genes and/or changes in genes involved in DNA damage repair pathways. Reducing the growth saturation rate, kdecay, of the HGSOC tumor cell burden the program increases the current HGSOC carrying capacity, kdecay occurs, cells proliferate according to the newly updated Gompertz-type growth law. Simulation time continues until the untreated HGSOC life-threatening tumor volume threshold is reached (e.g. corresponding to 1012 HGSOC cells), or until 38.5 years since the inception of the first HGSOC cell have elapsed. If the respective HGSOC growth curve reaches TVU detectability, we compute the time since the inception of the first HGSOC cell until clinical detection is reached. Similarly, we compute the time until clinical life-threatening HGSOC tumor volume is reached if the respective HGSOC growth curve reaches that stage. For an individual growth curve, the initial kgrowth is uniformly sampled from the values illustrated in n = 1000 simulated growth curves. A flowchart of the computational model is shown in Fig A in Given a fixed carrying capacity, varying either kgrowth = 0.0133 day-1 (range = 0.0014–0.0448). The data points illustrated in decay, we illustrate how a HGSOC volume grows in stepwise patterns and may not increase for relatively large amount of time , or the life-threatening threshold (succumbed) are also reported therein. Subsequent results reported below are based on the same computation that yielded the data generated in Table B in Based on the HGSOC clinical findings reported in  upon TVU of time , as oppodecay is around 7  does not yield substantially different median or range values for the estimated cdf’s.To produce estimates of the duration of HGSOC’s pre- and post-diagnosis phases, we report the generated value ranges , with median values of the times needed to reach baseline TVU detection threshold, baseline life-threatening tumor volume, and the window of opportunity interval length; we chose to report median values as the median was a more robust statistic compared to the mean throughout all sample model simulations, and thus constitutes a more accurate descriptor of the aggregate cancer-positive HGSOC population dynamics. The model-generated empirical cumulative distribution functions (cdf’s) for reaching the baseline detection threshold, the baseline life-threatening tumor volume and the window of opportunity length interval are reported in n = 1000 simulated HGSOC growth curves. Semiannual monitoring HGSOC progression via TVU performs the best genetic alterations in tumor suppressor genes and DNA damage repair pathways. We chose to focus on an unimodal, ultrasound-based HGSOC detection method (i.e. TVU), rather than on blood biomarker levels (i.e. CA-125 or HE4 levels), pelvic examinations or simultaneous TVU and CA-125 detection. Despite its well-recognized detection limitations in detecting localized or distant metastatic burden, TVU examinations are routinely performed when assessing ovarian volume, while the latter are either not recommended as low HGSOC volume detection unimodal prognostic markers [in silico cancer-positive population. Specifically, despite the fact that semiannual monitoring HGSOC progression via TVU performs, as expected, the best compared with annual or biannual monitoring , a nonzero percentage of succumbed cases is reported in all subsequent simulations of the HGSOC growth and progression model. Given that our TVU monitoring algorithm is assumed to have 100% specificity and 100% positive predictive value, the actual percentage of such succumbed HGSOC cases might be substantially higher. This invalidates the use of TVU as an effective HGSOC screening strategy aimed at lowering mortality rates in general-risk or high genetic-risk women. Our mathematical model thus represents a novel attempt to explain why multiple, large-scale TVU-based HGSOC detection screening studies have not proven significant mortality benefits, and focuses on a malignancy that has received very little attention by the mathematical oncology community.We develop a novel  markers , 15, 25  markers . Our resin silico cohort across multiple TVU monitoring frequencies or detection sensitivities. Our findings suggest that even a semiannual, unimodal TVU monitoring protocol is expected to miss detectable HGSOCs. We also find that circa 50% of the simulated HGSOC growth curves never reach the baseline detectability threshold, and that on average, 5–7 rate-limiting events are associated with reaching HGSOC detectability and life-threatening untreated HGSOC volumes respectively.We find that the median time until baseline TVU detection from the inception of the first HGSOC cell is 26.7 years. Given that an average patient’s age at diagnosis of ovarian cancer is 55–65 years , our finYachida et al. analyzed genomic sequencing data of metastatic tumors from 7 patients with metastatic pancreatic cancer and calculated that the first parental (non-metastatic) founder cancer cell may require 6.8 years to generate sub-clones with metastatic potential [Jones et al. also reported that a benign colorectal tumor might require 17 years to develop into an advanced carcinoma [Meza et al. reported that the average time from an initial premalignant mutation to the ultimate conversion of a detectable cancer in pancreatic and colorectal cancers may take up to 50 years [The predictions obtained with our HGSOC model are consistent with other published cancer progression chronologies reported for colorectal  or pancrotential . These sarcinoma . On a la50 years . While tkdecay are required to reach a baseline TVU detectable or life-threatening untreated HGSOC tumor volume. Additionally, we note the substantial heterogeneity in the number of such genomic aberrations predicted by our model, and observe that on average, one or two extra events are required in order for a detectable HGSOC tumor volume to become life-threatening. Our modeling findings align with the reported heterogeneity and number of the HGSOC-associated pathways altered in clinical HGSOC samples, as identified in [Our modeling results can also be correlated with published comprehensive genomic studies of clinically annotated HGSOC samples. For example, The Cancer Genome Atlas Research Network examined 489 HGSOC tumor samples, and provided the most comprehensive and integrated catalogue of (epi)genomic changes associated with HGSOC progression to date . An outcified in  , we chose conservative baseline TVU detection and life-threatening volume thresholds. Variation in the model parameters or baseline thresholds would only result in a faster or delayed HGSOC progression, but would not yield substantially different median or range values for the estimated cdf’s. A reasonable parameter set range would, however, enable us to obtain sharper estimates. Finally, it is possible that HGSOC rates of cellular division may vary within different subcellular populations belonging to the tumor volume. For simplicity, we do not distinguish between the various subpopulation growth rates, as such values are difficult to quantify empirically.Several limiting assumptions were made in our model. First, we do not distinctly address the underlying mechanism behind either HGSOC initiation or its progression, but it is well known that many factors may contribute to HGSOC carcinogenesis and progression A2 genes . Third, in silico a clinically occult pathological process, and obtain quantitative estimates of otherwise unknown statistics that are impossible to obtain even in large-scale prospective cohort screening studies . Our mathematical model provides a quantitative mathematical explanation that supports clinical findings such as the ones reported in [The HGSOC growth and progression model presented here represents an initial and novel attempt to model orted in  and resuorted in .S1 FileFig A. Workflow behind the HGSOC growth model. Table A. The baseline parameter values used in the model simulations. Table B. Cell-number-to-volume and tumor diameter conversion. Table C. Statistics generated from one sample simulation of the HGSOC growth and progression model illustrating the time needed to reach the baseline TVU detection threshold, the baseline life-threatening tumor volume (TLV), the window of opportunity interval length (WOP), and the number of HGSOC growth curves that never reach TVU baseline detectability (occult), or the life-threatening threshold (regressed) volumes, respectively, during the sample simulation. Table D. The data used to produce (DOCX)Click here for additional data file.


We use optical tweezers to control the folding and unfolding of individual DNA and RNA hairpins by force. Four hairpin molecules are studied in comparison: two DNA and two RNA ones. We observe that the conformational dynamics is slower for the RNA hairpins than for their DNA counterparts. Our results indicate that structures made of RNA are dynamically more stable. This difference might contribute to the fact that DNA and RNA play fundamentally different biological roles in spite of chemical similarity. There is no general relationship between these two quantities. In addition, the attempt frequency and the force loading rate are the key parameters in this case of non-equilibrium conditions.We performed single molecule force measurements with a dual-beam optical trapping setup on a series of molecular constructs containing a DNA or RNA hairpin. Pulling in a direction transverse to the stem, we can impose a mechanical constraint and follow the folding and unfolding of individual hairpins in time. In the main series of experiments, dynamic stretch and release cycles are applied. We used different pulling speeds (corresponding to force loading rates in the range 1-25 pN/s) and extracted kinetic and thermodynamic parameters of the hairpins by comparing the experimental data with a theoretical description based on non-equilibrium statistical physics. Analysing these results, it is crucial to keep in mind the distinction between the activation energy barrier and the equilibrium free energy difference between the two hairpin states . The laser beam is split in two beams of orthogonal polarisation. One of the two beams encounters only immobile optical compounds, while the second one is reflected by a mirror mounted on a piezoelectric stage. To avoid issues caused by residual interference between the polarized beams, the mobile beam is frequency shifted with an acousto-optic modulator . The polarisation corresponding to the mobile trap is rejected with a Glan polariser, and the displacement of a bead in the fixed trap is measured by back focal plane interferometry using a PSD detector . After calibration by analysis of the power spectral density of a captured bead, force is obtained with piconewton precision. More details on the setup have been presented elsewhere –11.We designed two hairpins with the same stem of 13 base pairs and a loop of 10 or 18 nucleotides, both as an RNA and a DNA molecule. The GC-content of the stem is close to 50 %. The resulting four hairpins are depicted in Figure Escherichia coli plasmid, which serves as a template for two polymerase chain reactions (PCRs). In addition to the part complementary to the template, one primer of each PCR includes one half of the sequence encoding the hairpin. The PCR products are then digested with Xba1, which generates cohesive ends in the middle of the hairpin sequence. After a ligation step, the complete hairpin sequence appears in the DNA. The resulting ≈4000 nucleotide double-stranded DNA is amplified by PCR. For the RNA hairpin constructs, an in vitro transcription of this DNA is performed.DNA oligonucleotides carrying the hairpin sequence of 36 or 44 bases have been inserted between two double-stranded handles of about 2000 base pairs each. The original DNA corresponds to a sequence coding for 23S ribosomal RNA in an To generate the handles, the DNA strands complementary to the sequence before and after the hairpin part are synthesized by PCR. A digoxigenin functionalized nucleotide is inserted at the 5′ end of one of the handles through the PCR primer. The other handle undergoes an enzymatic treatment  after PCR to add a biotin functionalized nucleotide at the 3′ end .To hybridise the handles with the hairpin containing strand, each double-stranded handle and the complete double-stranded DNA (resp. single-stranded RNA) are incubated for 30 s at 95°C, and the sample is cooled down to 4°C over 2 h. Carboxylated polystyrene (resp. silica) microspheres  of 2.19 μm diameter (resp. 1.01 μm) are functionalized  with biotin (resp. anti-digoxigenin) from Roche . Prior to each experiment, the beads are linked to the molecular constructs by incubation at room temperature   and put in a ≈100 μm deep chamber between two microscope cover slips . The chaHairpin folding and unfolding are complex dynamical processes. They depend on several characteristics of the molecular construct. The base sequence of the hairpin stem induces a complex energy landscape and the size of the loop and the elasticity of the DNA/RNA handles also are important. Moreover, the force measurement by itself influences the experimental result, via the trap stiffness and the externally imposed distance versus time protocol. The imposed distance between the centres of the optical traps is subject to position noise arising from piezo-control electronics, mechanical vibration and acoustic perturbations.keff. A free energy barrier of height E separates the folded (x = 0) and unfolded (x = L) states. The free energies of the two states differ by ΔG. In the absence of force, the folded to unfolded transition rate is k0 = k(F = 0) = ν0 exp ( − E/kBT) (it includes the barrier height E and the attempt frequency ν0). The reverse process is associated to a transition rate k1 = k0exp (ΔG/kBT) = ν0 exp ( − (E − ΔG)/kBT). Applying an external force F tilts this landscape. In the limit of high barrier (E ≫ kBT) and small applied force (F ≪ E/x→), the position of the transition state x→ does not vary significantly and the barrier for unfolding is reduced by an amount F x→. Increasing (resp. decreasing) the external force linearly with time within this model, the unfolding probability p→(F) (resp. folding probability p←(F)) can be derived analytically. More details about the model and a complete derivation of these probabilities are presented in Supplementary Section S1. Both probabilities explicitly depend on the pulling speed.We use an out-of-equilibrium statistical physics description that is closely related to earlier publications ,13–17 (uFunfold − Ffold). The obtained values are weighted according to the number of force cycles actually performed on the molecule, and normalized. More details about the building of the histograms are presented in Supplementary Section S3. We numerically calculate p→(F), p←(F) and their convolution, compare the theoretical result with the measured hysteresis distribution and fit the position of the transition state x→ and a characteristic transition rate k0. The fit is globally performed on the data of the four velocities in order to obtain a single set of parameters for each hairpin (see Supplementary Section S1). We analyse hysteresis values rather than separate unfolding and folding forces because the uncertainties of the hysteresis values are smaller in our measurements. This is explained by a simple estimation of the experimental errors, presented in Supplementary Section S2. All other parameters are measured, taken from the literature or estimated with the structure prediction program mfold  of ≈1.4, where the hairpin is always in the unfolded state. The movement is then inversed, so that the traps reapproach at the same speed and the hairpin can refold. This cycle is performed several times on the same molecule.In Figure When releasing the strain by inversing the direction of displacement and bringing the traps closer to each other, the hairpin can fold back into its initial structure. As no intermediate state is observed during the corresponding sudden upwards rise in force, this process also appears to be cooperative.The stretch and release curves are indistinguishable, except for the region where the unfolding (resp. folding) occurs. For a velocity of 50 nm/s and for all constructs except DNA10, a force hysteresis between unfolding and folding is observed. The hysteresis indicates that transitions occur out of thermal equilibrium. On the other hand, DNA10 shows several force flips between the folded and unfolded states during dynamic stretching and releasing of the construct Figure , inset. Experimental data presented in Table Measuring the successive unfolding (resp. folding) forces during stretch/release cycles on different molecules allowed us to build the hysteresis histograms for the four hairpins at the different displacement velocities. For DNA10 at 50 nm/s, when flips occur, only the first unfolding and first refolding forces are measured, according to the model used. Figure For all four hairpins, the force hysteresis increases with displacement velocity. Supplementary Figure S4 (Supplementary Section S7) presents histograms of the hysteresis recorded for RNA10 at 50, 150, 300 and 450 nm/s as an example. A clear increase of the mean hysteresis is visible, with its value going from 5 pN at 50 nm/s to 7.5 pN at 450 nm/s. The hysteresis values for the four hairpins are given in Supplementary Table S2. For each hairpin and pulling speed, variability in the unfolding and folding forces is seen, inducing a variability in the hysteresis. This behaviour is expected from the stochastic character of the unfolding and folding processes.Theoretical analysis of the hysteresis histograms enables us to extract thermodynamic and kinetic information about the hairpin structures. The experimental distributions were fitted to calculated probability distributions, as defined in Materials and Methods and supplementary information. For each hairpin, the fitting procedure is applied over the global data set, combining the four different speeds. The calculated force hysteresis distribution is presented by the solid line in Figure Ft (average of the mean opening force and the mean folding force at 50 nm/s) and transition lengths L, as well as theoretical free energy values that were obtained by simulation (see Supplementary Section S1 for details) are presented in Table x→ between folded state and transition state and the characteristic transition rate k0 were fitted to the experimental data and are presented in Table −3 for each fitted histogram  for definition) and allows us to univocally determine the two parameters.Measured mean transition forces x→ indicate a clear asymmetry in the energy landscape for both DNA and RNA hairpins . The DNA values of x→/L ≈ 0.3 are higher than the RNA values of x→/L ≈ 0.17. The transition rates k0 differ by a factor of about 10 between DNA18 and RNA18. The ratio is also about 10 between DNA10 and RNA10. These results confirm and quantify the faster dynamics of DNA as compared to RNA, already suggested by the appearance of force flips in the DNA10 curves at 50 nm/s.The results for The observation that the transition rates and hence the dynamics differ between the DNA and RNA hairpins is further confirmed by additional measurements performed with the four hairpins at constant extension. Here, the molecular construct is brought to a defined extension, which is then maintained constant during 10 s to 2 min. If the energy barrier is not too high, there are extension values where the hairpin can spontaneously flip between its folded and unfolded states ,20; the k0 values of RNA10 and DNA10, presented in Table Figure G values. This difference between RNA10 and RNA18 is consistent with the observation that the k0 value of RNA18 obtained from the varying extension data is an order of magnitude smaller than the one of RNA10.DNA10, DNA18 and RNA10 present spontaneous force flips at constant extension. For RNA18 however, no extension was observed where both spontaneous unfolding and folding occurs, although the two RNA hairpins are close in terms of the theoretically predicted ΔG an RNA duplex is more stable than the DNA duplex of equivalent sequence. Note however that there are three problems with this simplified view. First, the denaturation mechanisms under force and by thermal melting are different . As can be seen from Table We observe that the RNA hairpins unfold and fold at higher force than the DNA hairpins. This may be expected from the known fact that in terms of free energy difference Δifferent . WhereasF in the present case, this initiation requires a mechanical work of the order W = FL, where L denotes the length of the unfolded loop. For similar W (energy fluctuations of similar amplitude), the different L thus implies that folding of the small-loop hairpin occurs at higher F than folding of the large-loop one. Of note, it was found by fluorescence techniques that even without external force the rate of hairpin closing decreases with increasing loop size  exhibits smaller k0 and larger hysteresis than DNA 10 (resp. 18) at given velocity. For example, the transition length L corresponding to RNA10 unfolding (resp. folding) is ≈20 nm. Considering a typical equilibrium dwell time of 1 s for this hairpin  transition is thus highly unlikely. The unfolding transition (resp. folding) thus occurs out of equilibrium at this speed. On the contrary, the shorter dwell time of DNA10 (≈0.1 s) induces a displacement (≈5 nm) that is smaller than L (≈15 nm) and allows for flipping between the two states. In this case, the measurement can be considered as close to equilibrium  to build non Watson–Crick base pairs and we note that mfold does not fully take the corresponding free-energy contributions into account ,23. The We tentatively attribute the slower dynamics of the RNA hairpins to a stronger cooperativity. For strong cooperativity, barriers against folding and unfolding may be localized and high, since they can cumulate energy contributions of many structural elements. With weak cooperativity, on the other hand, the energy contributions of the structural elements distribute more equally over the reaction coordinate, high local barriers are less probable to occur and therefore passage of this landscape by a random walk that is biased by the external force is faster.Measurements on more complex RNA structures showed pronounced structures in the force versus extension curves (or length versus force curves for force-clamp measurements) and hysteresis occurred even at low pulling speed –27, in qk/Δx develop, where k is the stiffness of the molecular linker and Δx the relative displacement. This global picture suggests that the configuration studied in the present paper represents an elementary building block of complex three-dimensional structures formed by a single-stranded nucleic acid chain. Specifically, our result that the dynamics of folding and unfolding under mechanical load is slower in RNA hairpins than in the corresponding DNA hairpins translates itself into predicting that RNA structures are dynamically more stable. In other words, structures formed by single-stranded DNA rather than RNA exhibit significantly faster inter-conversion between alternative configurations. There are of course good reasons of evolutionary origin to explain why the domain of biologically-active three-dimensional nucleic acid structures is traditionally occupied by RNA. Our suggestion that RNA structures are dynamically more stable than DNA structures may be an interesting additional argument to understand why single-stranded DNA was not selected to become a molecule that assures its biological role by a complex internal structure.A typical RNA molecule has a complex three-dimensional shape stabilized by several duplexes. The individual duplexes are connected by single strands of varying length, which allows for propagation of conformational changes within the RNA structure. This propagation of strain and displacement is influenced by the elasticity of the connecting single strands. Forces of the order Two RNA hairpin structures of different loop size were compared with their DNA equivalents. Under the same experimental conditions, the forces needed to unfold the DNA hairpins are systematically lower. Hysteresis between unfolding and folding is more pronounced for RNA than for DNA. For all studied hairpin types, the hysteresis increases with the pulling speed. Imposing a constant distance, spontaneous force flips are observed for the large loop DNA hairpin, but are absent for the equivalent RNA structure. For small loop hairpins, flipping between the folded and unfolded states occurs with both DNA and RNA. Comparison of the experimental data with a theoretical description allowed us to estimate the position of the transition state and a characteristic transition rate. The latter is found to be smaller for RNA than DNA. From all these results emerges the picture that RNA exhibits a more pronounced out-of-equilibrium character than DNA. The force-induced conformational dynamics of hairpins is slower in RNA than in DNA. The results suggest that structures made of RNA are more stable against internal and external forces than structures made of single-stranded DNA and therefore the former are more apt to form complex structures that are required for an active biological function.Supplementary Data are available at NAR Online.


HTT) gene. Recent evidence suggests that HD is a consequence of multimodal, non-mutually exclusive mechanisms of pathogenesis that involve both HTT protein- and HTT RNA-triggered mechanisms. Here we provide further evidence for the role of expanded HTT (expHTT) RNA in HD by demonstrating that a fragment of expHTT is cytotoxic in the absence of any translation and that the extent of cytotoxicity is similar to the cytotoxicity of an expHTT protein fragment encoded by a transcript of similar length and with a similar repeat size. In addition, full-length (FL) expHTT is retained in the nucleus. Overexpression of the splicing factor muscleblind-like 1 (MBNL1) increases nuclear retention of expHTT and decreases the expression of expHTT protein in the cytosol. The splicing and nuclear export factor U2AF65 has the opposite effect, decreasing expHTT nuclear retention and increasing expression of expHTT protein. This suggests that MBNL1 and U2AF65 play a role in nuclear export of expHTT RNA.Huntington’s disease (HD) is caused by a CAG repeat expansion in the huntingtin ( HTT) gene3468expHTT RNA neurotoxicity have been proposed. First, RNA with sufficiently long stretches of CUG or CAG triplets forms hairpin structures79HTT (expHTT) RNA in patient-derived HD fibroblasts aggregates into foci that co-localize with MBNL1, with the predicted consequence that at least some transcripts under MBNL1 control are misspliced11HTT transcripts8Huntington’s disease (HD) is caused by CAG repeat expansions in the huntingtin . We hypothesize that nuclear retention of expHTT is likely to lead to increased neurotoxicity, and therefore that pathways leading to this phenomenon may provide valuable therapeutic targets.In the current study, we provide further evidence of the cytotoxicity of untranslated HTT exon 1 fragment encoding expHTT RNA with 80 CAG repeats is cytotoxic in SH-SY5Y cellsHTT transcripts with CAG repeats ranging in length from 23 triplets  to 128 triplets (extreme juvenile onset), and including a length of 45 triplets , we overexpressed truncated HTT RNA in the SH-SY5Y and SK-N-MC neuroblastoma cell lines. To obtain the non-translatable N63(CAG)nHTT construct, we modified a truncated N63QnHTT construct containing a sequence corresponding to the first 63 amino acids of HTT plus the repeat regionexpHTT by RAN translation in specific cell typesHTT RNA itself, we cloned untranslatable N63(CAG)nHTT sequences into a vector in which each sense-strand reading frame is tagged (N63(CAG)nHTT-RAN plasmidN63(CAG)150HTT RNA, which expresses a polyAla-containing RAN product, no evidence of RAN translation was observed in SH-SY5Y cells expressing expHTT  expressing both HTT RNA and protein. We used truncated HTT constructs for these experiments, as these constructs enabled us to control for levels of transcription and to measure cytotoxicity in an unbiased manner using chemical readouts. Although repeat lengths were not precisely matched between the constructs expressing translatable and non-translatable transcripts due to slight shifts in repeat lengths during plasmid preparation, similar levels of RNA were expressed from all HTT constructs and triggered comparable levels of cytotoxicity at each repeat length  with a 2′-O-methylated CUG riboprobe, we observed RNA foci in truncated N63HTT constructs expressed in SK-N-MC cells  also formed foci in a small percentage of cells, presumably as a consequence of overexpression. These results demonstrate that both truncated and FL expHTT RNA form structures that facilitate RNA aggregation into RNA foci, and hence that foci formation is not an artifact of a short transcript.Nuclear RNA foci, punctate aggregates of expanded RNA, are hallmarks of RNA-mediated toxicity1711MC cells  and in tMC cells . Next weRNA foci  similar reatment . Full-leDrosophila model of SCA3311RNA foci are thought to be one of the major sites of interaction between RNA with repeat expansions and RBPs, including the splicing factor MBNL1112011HTT RNA foci in neuronal-like cells, we co-transfected plasmids encoding FL-HTTQ82 and either GFP or GFP-MBNL1 . MBNL1 overexpression had no significant effect on the expression of any of these proteins 66HTT transcripts without an ATG codon produce non-ATG–translated polyAla-containing peptides in SK-N-MC cells expHTT. However, the degree to which MBNL1 binds to different CAG repeat–containing transcripts may be influenced by disease-specific sequences flanking the CAG repeats.HD is one of nine autosomal dominant neurodegenerative diseases caused by CAG repeat expansionsJPH3 causes HDL2, in part via RNA-mediated neurotoxicity7JPH3 results in transcript variants in which the CUG repeat resides in the 3′ UTR or within open reading frames translated into polyAla or polyleucineJPH3 construct in which the repeat is in-frame for translation into polyAla (JPH3Ala55)We next sought to determine if the effect of MBNL1 on translation is CAG repeat-specific. CUG repeat expansion in expHTT RNA and other transcripts with expanded repeats by interfering with nuclear export processes. The nuclear export of mRNA is mainly mediated by the nuclear export factor 1 (NXF1) receptor pathwayATXN3 RNA in a fly model of SCA3cardiac troponin T (cTNT) splicing siteexpHTT, we overexpressed U2AF65 with FL expHTT. In SK-N-MC cells, overexpression of U2AF65 increases the levels of expHTT protein , reproduces many of the features of HD, leading to the speculation that the interruptions in the repeat prevent the formation of abnormal RNA structures, hence eliminating a contribution of RNA toxicity. However, it is difficult to reconcile this conclusion with the increasingly compelling data, primarily from cell models (including human HD cells), that RNA is also important in disease pathogenesis. Part of the problem is that mouse models of repeat disease are inherently imperfect—each defers from other mouse models, from cell models, and from human disease in the degree to which they recapitulate the mechanistic complexity of repeat diseases, including variables such as repeat length and integrity, transcript and protein expression levels, localization and aggregation of protein and RNA, and the presence of RAN translation7910111213141532expHTT RNA. Finally, it is quite possible that longer repeats shift the relevant importance of RNA and protein toxicity, so that the long repeats used in most mouse models may obscure the role of RNA toxicity.Several HD mouse models have been used to demonstrate that alterations in protein sequence markedly suppress the phenotype of HD, including the YAC128 transgenic mice “short stop” (a mutation prevents expression of full length protein), the YAC128 line in which the caspase -6 cleavage site has been eliminated, and the BAC transgenic mice expressing full-length mutant huntingtin with serines 13 and 16 mutated to aspartate3738HTT RNA aggregates into RNA foci in neuronal-like cells and in neurons of an HD transgenic mouse model expHTT with antisense oligonucleotides or small molecules may therefore have substantial therapeutic benefits4849U2AF65, a splicing factor and a component of the NXF1 receptor export pathwaypHTT RNA , oppositf expHTT , furtherAnalysis of the effect of MBNL1 on the effect of expHTT toxicity is complicated by the finding that with or without the N-terminal zinc finger domain or NLS signal, MBNL1 itself increases cytotoxicity , and MBN2634515253555657expHTT transcripts contribute to the pathogenesis of HD and support an examination of nuclear export pathways as a source of novel therapeutic targets for HD.Taken together, our data provide mechanistic support for the hypothesis that Control siRNA (sc-37007) and human MBNL1 siRNA (sc-60988) were purchased from Santa Cruz Biotechnology . The antibodies used for immunoblotting were as follows: anti-huntingtin , anti-polyglutamine, 1C2 , anti-ATXN3  from EMD Millipore ; anti-ATXN2  from BD Transduction Laboratories ; anti-β-actin  from Abcam ; anti-GFP , anti-myc , anti-HA  from Life Technologies ; anti-MBNL1  from Dr. Charles A. Thornton ; anti-mRFP  from Chromotek ; anti-N-terminus of huntingtin  from Santa Cruz Biotechnology; anti-FLAG  from Origene .Neuroblastoma cell lines SK-N-MC  and SH-SY5Y  were cultured in Dulbecco’s Modified Eagle Medium with 4.5 g/L glucose and supplemented with 10% fetal bovine serum. Nine-month-old C57BL/6J wild type mice were from The Jackson Laboratory , and N586-82Q transgenic HD mice were previously describedet al. and Ratovitski et al., respectively59N63(CAG)nHTT inserts were PCR-amplified and cloned into the XhoI and XbaI sites of the A8(*KKQEXP)-3Tf1 vector to produce N63(CAG)nHTT-RAN plasmidsJPH3 transcript in the polyalanine frame and JPH3-(CTG)55 plasmid expressing a non-translatable JPH3 transcript were described by Seixas et al.et al.30Plasmids encoding truncated N-terminal HTT (N63QnHTT) and FL HTT (FL-HTTQn) were described by Cooper HTT transcripts and fixed in 4% paraformaldehyde 48 hours post-transfection. Frontal cortices from wild-type or N586-82Q HD mice were collected and frozen-sectioned. Fluorescence in situ hybridization (FISH) with or without DNase/RNase treatment was performed as previously describedSK-N-MC cells were transfected with plasmids expressing FL SK-N-MC cells were co-transfected with FL-HTT and GFP-MBNL1 plasmids, and 48 hours after transfection FISH analysis was performed. Twenty-five fields per treatment were randomly selected. In each view, the number of GFP-positive cells, number of RNA foci-containing GFP-positive cells and number of RNA foci in each cell were manually counted in a single-blind manner. The percentage of cells containing foci was calculated as [100*number of foci-containing GFP-positive cells/number of GFP-positive cells]. Average foci number was calculated as [number of RNA foci/number of foci-containing GFP-positive cells].2, 10 mM EDTA, pH 7.4) and lysed on ice in lysis buffer  for 5 minutes. After centrifugation at 12000 × g for 5 minutes, the supernatants containing the cytoplasmic fraction of RNA were collected. The remaining nuclear pellets were rinsed with lysis buffer twice and finally centrifuged as the nuclear fraction. Cytoplasmic and nuclear RNA were then extracted by TRIZOL reagent. One μg of RNA was used to synthesize cDNA by the SuperScript III First-Strand Synthesis System (Life Technologies). PCR reactions were performed using the following primers: N63HTT forward 5′-GGG CCC TTC GAA CAA AAA CTC-3′, reverse 5′-TAG AAG GCA CAG TCG AGG-3′; FL-HTT forward 5′-AAT ACG ACT CAC TAT AGG G-3′, reverse 5′-CTT TCT TTG GTC GGT GCA GCG-3′; U6 forward 5′-GTG CTC GCT TCG GCA GCA CAT ATA C-3′, reverse 5′-AAA AAT ATG GAA CGC TTC ACG AAT TTG-3′; tRNA forward 5′-AGC AGA GTG GCG CAG CGG-3′, reverse 5′-GAT CCA TCG ACC TCT GGG TTA-3′; ACTB forward 5′-ATG TGC AAG GCC GGC TTC GC-3′, reverse 5′-CCA CAC GCA GCT CAT TGT AG-3′; GFP-MBNL1 forward 5′-CAT GGT CCT GCT GGA GTT CGT G-3′, reverse 5′-TTG TGG CTA GTC AGA TGT TCG-3′; endogenous MBNL1 forward 5′-ATT ACA ACC CGT GCC AAT GT-3′, reverse 5′-TTG TGG CTA GTC AGA TGT TCG-3′.SK-N-MC cells were transfected with indicated plasmids and, 48 hours post-transfection, total RNA was extracted by TRIZOL reagent (Life Technologies). Nucleocytoplasmic fractionation of RNA was performed as previously describedSK-N-MC cells were plated in 6-well plates , transfected with 4 μg of plasmids and 4 μL of Lipofectamine 2000 (Life Technologies), and protein extracts were analyzed by immunoblotting 72 hours post-transfection. For knock-down of MBNL1, cells were first transfected with 200 pmol of siRNA. After 72 hours cells were further transfected with 100 pmol of siRNA plus 2 μg of plasmids and analyzed by immunoblotting 48 hours post-transfection. Cells were lysed with RIPA buffer , and the protein lysates were subjected to SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to nitrocellulose membranes. Membranes were blocked, probed with primary antibody at 4 °C overnight, washed, and incubated with HRP-conjugated secondary antibodies, and the proteins were then visualized using the ECL Prime Western Blotting System  and Hyperfilm ECL .SK-N-MC and SH-SY5Y cells were plated in 96-well plates  and transfected with 0.2 μg of plasmids and 0.2 μL of Lipofectamine 2000. Cytotoxicity was assessed at 72 hours post-transfection by measuring caspase-3/7 activities using the Caspase-Glo 3/7 Assay system .SK-N-MC cells were plated in 96-well plate  and transfected with 0.2 μg of plasmids and 0.2 μL of Lipofectamine 2000. Cell numbers before and after transfection were assessed 72 hours post-transfection using the Vybrant MTT Cell Proliferation Assay Kit (Life Technologies).At least three biological replicates of each experiment were performed. Data were presented as mean ± SD. The results were analyzed using Student’s t-test, one-way analysis of variance (ANOVA) followed by Dunnett’s or Bonferroni’s post-hoc test, or two-way ANOVA followed by Bonferroni’s post-hoc test. Statistical significance was set at P value < 0.05.How to cite this article: Sun, X. et al. Nuclear retention of full-length HTT RNA is mediated by splicing factors MBNL1 and U2AF65. Sci. Rep.5, 12521; doi: 10.1038/srep12521 (2015).


Thermoproteus species even though they contain SRP19 and SRP54 proteins. Here, we show that genome rearrangement events in Thermoproteus tenax created a permuted SRP RNA gene. The 5'- and 3'-termini of this SRP RNA are located close to a functionally important loop present in all known SRP RNAs. RNA-Seq analyses revealed that these termini are ligated together to generate circular SRP RNA molecules that can bind to SRP19 and SRP54. The circularization site is processed by the tRNA splicing endonuclease. This moonlighting activity of the tRNA splicing machinery permits the permutation of the SRP RNA and creates highly stable and functional circular RNA molecules.Signal recognition particles (SRPs) are universal ribonucleoprotein complexes found in all three domains of life that direct the cellular traffic and secretion of proteins. These complexes consist of SRP proteins and a single, highly structured SRP RNA. Canonical SRP RNA genes have not been identified for some DOI:http://dx.doi.org/10.7554/eLife.11623.001 Cells make many proteins that are eventually released outside the cell or inserted into the cell’s membrane. As these proteins are still being made, they are captured by a “signal recognition particle” (or SRP); this molecular machine then guides the newly forming protein to the cell’s membrane. SRPs are found in all living organisms on Earth and contain several different proteins and a short RNA molecule. However, a few species belonging to the archaeal domain of life did not seem to contain an identifiable gene for the RNA component of the SRP.Thermoproteus tenax, a single-celled microbe which grows in the absence of oxygen and at temperatures of up to 95°C.Now Plagens et al. have sought to solve the mystery of the “missing” component of this essential protein-targeting machine. This involved searching through the RNAs that are produced by an archaeon called Plagens et al. discovered that the “missing” SRP RNA gene had not yet been identified because rearrangements in this archaeon’s genome had swapped the left and right portions of the SRP RNA gene. Further experiments revealed that the correct sequence order is restored in mature SRP RNA molecules by the two ends of the molecule being linked to form a circle. These RNA circles are made by the cellular machinery that normally removes the unneeded sections from other RNA molecules .Circular RNA is much more stable at high temperatures and does not degrade easily, and Plagens et al. suggest that this particular arrangement is therefore especially advantageous for this species. Future work will now aim to work out which selective pressures favor the evolution of such fragmented RNAs.DOI:http://dx.doi.org/10.7554/eLife.11623.002 Thermoproteus (e.g. Thermoproteus tenax and Thermoproteus uzoniensis) do not contain canonical SRP RNAs and SRP RNA genes are not annotated  that bind to the ribosome and recognize signal peptides in secretory proteins . SRP binnnotated . Genes ennotated . Thus, wT. tenax cells and subjected them to Illumina Hiseq2000 RNA-Seq analysis. 13.45 million sequence reads were mapped to the reference genome to obtain insights into the RNome of T. tenax. Subsequently, we searched the sequence reads for minimal conserved SRP RNA features. SRP RNA molecules are highly structured and contain several conserved structural features but only few absolutely conserved sequence segments. These sequences include a conserved SRP54 binding motif in helix 8b and a GNAR tetraloop motif connecting helix 6. We identified these short motifs in an intergenic region between the genes TTX_0683 (pyruvate phosphate dikinase [ppdK]) and TTX_0684 (protein phosphatase [ppa]). The prediction of RNA folding for this intergenic sequence revealed a high potential for extended helical regions, which prompted us to analyze this region in more detail. We utilized the obtained RNA-Seq reads to identify the 5'- and 3'-termini of a 309 nt long highly structured RNA transcript. The alignment of this RNA molecule with other archaeal SRP RNA molecules that are annotated in the SRP database (Thermoproteus species with ‘missing’ SRP RNA genes contain permuted SRP RNA sequences in which the transcripts’ termini have been shifted by over 100 nucleotides and the order of sequence motifs has been rearranged. We identified a similar permuted SRP RNA gene in T. uzoniensis and noticed that nucleic acid sequence variations do not occur in conserved regions of the SRP RNA and in most cases do not disrupt the structure of the SRP RNA (i.e. G-C base pairs are replaced by G-U or A-U basepairs)  . Sequenc-termini . The obs-termini . A TATA RNA gene . Northert probes . Full-let probes .10.7554/Escherichia coli and variant S-domains of the SRP RNA were transcribed in vitro  motif . A simil SRP RNA . BHB ele SRP RNA . A BHB c SRP RNA . The pre46 tRNAs . These i46 tRNAs . This fa46 tRNAs . We prodThermoproteus species and believe that this observation correlates with the emergence of increased tRNA gene fragmentation  were a kind gift of R. Hensel (Essen) and grown heterotrophically in Thermoproteus medium  and small RNAs (<200 nt), 0.1 g pelleted cells were lysed by homogenization and the RNA was subsequently isolated using the mirVanaTM miRNA Isolation Kit  according to the manufacturer’s instructions. To generate the SRP S-domain RNA constructs , two forward and reverse complementary DNA oligonucleotides with 15 bases overhangs were synthesized , 1 mM spermidine, 4 mM of ATP, CTP, GTP and UTP, 20 U RNase inhibitor and 1 µg T7 RNA polymerase at 37°C for 4 hr. The BHB substrate for RNA cleavage assays was synthesized  to ensure proper adapter ligation of RNA termini. The cDNA libraries were prepared according to the TruSeq Small RNA Library Protocol (Illumina) and sequenced using HiSeq2000 technology (Illumina) at the Max-Planck Genome Centre (Cologne). Sequencing data processing and analyses were performed using CLC Genomics Workbench 8 . The sequences were trimmed by quality score , adapter trimming and filtered by length (15 nt cutoff). The trimmed sequences were mapped to the T. tenax reference genome (FN869859) using default settings (mismatch cost set to 4). The T. tenax RNA-Seq data is available at Gene Expression Omnibus .Preparations of T. tenax total RNA was performed by electrophoretic separation on 8% denaturing-polyacrylamide gels next to an RNA and DNA marker . Additionally, to verify the circularization of SRP RNA, 15 ng of full-length SRP RNA in vitro transcript and circularized SRP RNA served as a running control. To obtain a circular SRP RNA control, full length SRP RNA transcript was 5'-dephosphorylated for 6 hr at 37°C using alkaline phosphatase (NEB) and the reaction was stopped by heating for 10 min at 65°C. Then, the RNA was 5'-phosphorylated using T4 PNK (NEB) and ATP for 1 hr at 37°C and ligated using T4 RNA ligase 1 (NEB) for 1 hr at 37°C. The reaction was stopped by incubation at 95°C for 5 min in 2× formamide loading buffer .Fractionation of 1–4 µg 32P]-ATP ) that were complementary to different regions in the SRP S-domain  and bands were visualized via UV irradiation. The RNA was blotted by capillary transfer onto nylon membranes  and immobilized by UV crosslinking. Hybridization was performed at 42°C for 18 hr in ULTRAhyb-Oligo buffer (Ambion) with two 5'-labeled probes (the label was added using T4 PNK [NEB] and γ-[T. tenax genes srp19 (TTX_2083) and srp54 (TTX_0615) were cloned into pET20b creating a fusion with a C-terminal 6× His-tag. The plasmids were transformed into E. coli strain DH5α (Invitrogen) and protein production carried out in E. coli Rosetta2(DE3)pLysS cells (Stratagene). Cultures were grown in LB medium at 37°C, shaking at 200 rpm. For protein production, 1 mM IPTG was added to a growing culture (OD600: 0.6) which was incubated for 3 hr. SRP19-His expression cells were homogenized in buffer 1 , lysed by sonication and cleared by centrifugation . The protein was heat-precipitated  and centrifuged . The SRP19-His protein was further purified by Ni-NTA affinity chromatography  and eluted with a linear imidazole gradient (0–500 mM) at 400 mM imidazole using a FPLC Äkta system . SRP54-His was purified by cell lysis in buffer 2 , lysed by sonication and cleared by centrifugation . The protein was loaded onto a Ni-NTA affinity chromatography column and eluted with a 500 mM imidazole step. Protein fractions were dialysed in buffer 3  and purified over a HiTrap Heparin Sepharose HP column  eluting with a linear salt gradient (0–1 M) at 650 mM NaCl.The The formation of SRP RNA-protein complexes was tested using a DEAE-Sepharose assay as described earlier . 2 µM ofT. tenax genes TTX_1594  and TTX_1893  were cloned together into pETDuet-1 and the protein was purified as described earlier and gel-purified as described above. 1–1000 nM purified splicing endonuclease was incubated with 2 nM of 5'-labeled RNA in nuclease buffer  at 60°C for 20 min. The cleavage reaction was stopped by adding formamide loading buffer and incubating at 95°C for 5 min. The reaction was loaded onto a 20% denaturing polyacrylamide gel running in 1× TBE, 6 W for 4 hr next to a low molecular weight marker  and an alkaline hydrolysis ladder of the BHB substrate. The cleavage products were visualized by phosphorimaging.10 pmol of the BHB substrate for RNA cleavage assays was 5'-labeled with T4 PNK (Ambion) and γ-[ review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and two reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for submitting your work entitled "Circularization restores SRP RNA functionality" for consideration by The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.Thermoproteus tenax and Thermoproteus uzoniensis are encoded in a permuted fashion and that the RNA ends are ligated to form a circular molecule, possibly to confer added stability to the RNA. The authors also show that a tRNA splicing endonuclease generates the site of circularization, pointing to a moonlighting activity for this enzyme. The reviewers only have limited comments:In this short report, Plagens et al. show that the SRP RNAs of 1) The title is vague and should mention the archaeal focus of the study.2) 3) While the sequencing data and co-migration with ligated RNAs in  In this short report, Plagens et al. show that the SRP RNAs of Thermoproteus tenax and Thermoproteus uzoniensis are encoded in a permuted fashion and that the RNA ends are ligated to form a circular molecule, possibly to confer added stability to the RNA. The authors also show that a tRNA splicing endonuclease generates the site of circularization, pointing to a moonlighting activity for this enzyme. The reviewers only have limited comments:1) The title is vague and should mention the archaeal focus of the study.Thermoproteus” was added.We changed the title. SRP is spelt out in full and “…in 2) Thermoproteus species . We provide additional support with a new figure supplement  While the sequencing data and co-migration with ligated RNAs in We performed Northern blot assays with RNase R treated total RNA (1-20U RNase R/μg RNA) and saw no significant reduction of the signal. However, RNase R resistance might also be observed for the highly structured linear SRP RNA with its four nucleotide 3’ overhang as it was shown that “duplex RNAs with no overhang or with a 4-nucleotide overhang bind extremely poorly to RNase R and are inactive as substrates”. . We sequenced the termini ligation site in hundreds of unique reads in independent RNA-Seq datasets (available at GEO database GSE72127) and consider this to be conclusive evidence.


MicroRNAs (miRNAs) are critical post-transcriptional regulators of gene expression. Their precursors have a globally A-form helical geometry, which prevents most proteins from identifying their nucleotide sequence. This suggests the hypothesis that local structural features  play a central role in specific double-stranded RNA (dsRNA) selection from cellular RNA pools by dsRNA binding domain (dsRBD) containing proteins. Furthermore, the processing enzymes in the miRNA maturation pathway require tandem-dsRBD cofactor proteins for optimal function, suggesting that dsRBDs play a key role in the molecular mechanism for precise positioning of the RNA within these multi-protein complexes. Here, we focus on the tandem-dsRBDs of TRBP, which have been shown to bind dsRNA tightly.We present a combination of dsRNA binding assays demonstrating that TRBP binds dsRNA in an RNA-length dependent manner. Moreover, circular dichroism data shows that the number of dsRBD moieties bound to RNA at saturation is different for a tandem-dsRBD construct than for constructs with only one dsRBD per polypeptide, revealing another reason for the selective pressure to maintain multiple domains within a polypeptide chain. Finally, we show that helical defects in precursor miRNA alter the apparent dsRNA size, demonstrating that imperfections in RNA structure influence the strength of TRBP binding.We conclude that TRBP is responsible for recognizing structural imperfections in miRNA precursors, in the sense that TRBP is unable to bind imperfections efficiently and thus is positioned around them. We propose that once positioned around structural defects, TRBP assists Dicer and the rest of the RNA-induced silencing complex (RISC) in providing efficient and homogenous conversion of substrate precursor miRNA into mature miRNA downstream. Multicellular organisms employ complex gene regulatory programs that often include post-transcriptional controls in order to establish gene-appropriate expression levels. Among the most studied mechanisms relevant to higher eukaryotes is post-transcriptional gene silencing carried out in RNA interference (RNAi). MicroRNAs (miRNAs) and small interfering RNAs (siRNA) are single-stranded RNAs that bind to complementary sequences found in the 3′-untranslated region of mRNA and down-regulate protein expression.,2 Both mProcessing of nascent miRNAs to their final form involves two multi-macromolecule complexes : the ‘MiNearly all of the proteins named above contain one or more double-stranded RNA binding domains (dsRBDs) and routinely function in gene regulation. One striThis study aims to provide fundamental insights into the molecular mechanism of TRBP binding to RNA commonly encountered in the miRNA maturation pathway, which will lead to a better understanding of its role in delivering mature miRNA to RISC. The findings of this study are motivated through a systematic analysis of TRBP interactions with a model RNA library, monitored by electrophoretic mobility shift assays (EMSAs) and circular dichroism (CD). Our results demonstrate that TRBP is sensitive to imperfections in RNA structure and binds shorter miRNA-relevant length duplexes in a RNA-length dependent manner. One key finding is that the tandem dsRBD-construct of TRBP (TRBP-ΔC) binds dsRNA in a different mode than its isolated dsRBDs. We conclude our study with assays that compare TRBP-ΔC binding to the native pre-mir-16-1 and miR-16-1/miR-16-1* duplex, showing that TRBP is unable to bind to regions of RNA with helical imperfections efficiently and thus is positioned around them. We propose that once positioned by structural defects on the precursor miRNA, TRBP assists Dicer and the rest of RISC in providing efficient and homogenous conversion of substrate pre-miRNA into mature miRNA downstream.A synthetic TRBP2 (1–345) gene was purchased from Geneart, from which three TRBP constructs were PCR amplified: TRBP-dsRBD1 (9–85), TRBP-dsRBD2 (139–215), and TRBP-ΔC (9–215). The expression and purification of the protein was performed as previously described, with twoFour triple lysine-to-alanine amino acid mutations were made using a QuickChange Lightening kit (Agilent Technologies) and following the manufacturer’s suggested protocol. The four knockout mutants generated were as follows: TRBP-dsRBD1-Null , TRBP-dsRBD2-Null , TRBP-ΔC-RBD1-Null , and TRBP-ΔC-RBD2-Null . Mutations were verified through DNA sequencing. The expression, purification, and preparation of the mutant proteins were performed as described for the wild-type sequences.All RNA sequences can be found in in vitro transcription conditions reported by Wostenberg et al.-ATP. For the duplex RNAs, the radiolabeled top-strand RNA was mixed with a 20-fold molar excess of cold bottom strand and purified as a duplex from an 8% native gel; all self-complementary sequences, including pre-mir-16-1 and the various stem-loop model RNAs, were denatured at 95°C for 1.5 min. and renatured 4°C for 5 min. prior to mixing with protein. EMSAs were carried out as previously described, from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S3 Figblack dots) are averaged from the two independent experiments, with the black best-fit line produced from the determined Kd,app and nH values, reported in The radiograph images are presented, representing the increase of [TRBP-dsRBD2] from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S4 Figblack dots) are averaged from the two independent experiments, with the black best-fit line produced from the determined Kd,app and nH values, reported in The radiograph images are presented, representing the increase of [TRBP-ΔC] from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S5 Figblack dots) are averaged from the two independent experiments, with the black best-fit line produced from the determined Kd,app and nH values, reported in The radiograph images are presented, representing the increase of [TRBP-dsRBD1] from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S6 Figblack dots) are averaged from the two independent experiments, with the black best-fit line produced from the determined Kd,app and nH values, reported in The radiograph images are presented, representing the increase of [TRBP-dsRBD2] from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S7 Figblack dots) are averaged from the two independent experiments, with the black best-fit line produced from the determined Kd,app and nH values, reported in The radiograph images are presented, representing the increase of [TRBP-ΔC] from left to right. To the right of the gels are the Hill-style analyses of a set of two titrations. The experimental data ((TIF)Click here for additional data file.S8 FigThe radiograph images are presented, representing the increase of [TRBP-RBD1-Null] and [TRBP-RBD2-Null], respectively, from left to right. No binding is observed within the concentration window for these two constructs.(TIF)Click here for additional data file.