The PDCD5 transfected cells showed higher sensitivity to cisplatin treatment than the HepG2-Neo cells, with a higher p53 protein expression level. PDCD5 overexpression can attenuate tumor invasion, EMT and the level of IGF-1 protein induced by TGF-β treatment. In conclusion, stable transfection of the PDCD5 gene can inhibit growth and induce cell cycle arrest in HepG2 cells, and its also notably improves the apoptosis-inducing effects of cisplatin, and reverses invasion and EMT induced by TGF-β. The use of PDCD5 is a novel strategy for improving the chemotherapeutic effects on HCC.Low expression levels of the programmed cell death 5 (PDCD5) gene have been reported in numerous human cancers, however, PDCD5 expression has not been investigated in hepatic cancer. The present study aims to investigate the biological behavior of PDCD5 overexpression in hepatocellular carcinoma (HCC) cells. The PDCD5 gene was stably transfected into the HepG2 HCC cell line (HepG2-PDCD5), and the expression levels of PDCD5 were examined by quantitative polymerase chain reaction and western blotting. An MTT assay was used to assess the cellular proliferating ability, and propidium iodide (PI) staining was used to evaluate the cell cycle by flow cytometry. The cells were incubated with 2 ng/ml transforming growth factor (TGF)-β for 7 days in order to induce invasion and epithelial-mesenchymal transition (EMT). Apoptosis was measured by Annexin V-fluorescein isothiocyanate and PI double labeling. A Boyden chamber invasion assay was carried out to detect tumor invasion. Western blotting was performed to detect the protein expression levels of PDCD5, insulin-like growth factor (IGF)-1 and the EMT marker, Snail. The results showed that the HepG2-PDCD5 cells exhibited slower proliferation rates and high G A number of studies have demonstrated that apoptosis is closely associated with the initiation, progression and recurrence of cancer –3. ThereThe decreased expression of PDCD5 has been reported in various human tumors, including prostate , lung 77 and ovain vitro by the stable transfection of the PDCD5 gene, and the effects on apoptosis induced by cisplatin and invasion by transforming growth factor (TGF)-β were investigated.Cisplatin is a common drug for cancer chemotherapy, however, with repeated exposure, tumor cells often become resistant to its effects. Hepatocellular carcinoma (HCC) is known to be resistant to various chemotherapeutics, including cisplatin. Studies have shown that this resistance is likely to be attributable to the cisplatin-induced upregulation of hTERT and the PI3K-dependent survivin pathway ,15. Ther2.The human HCC cell line, HepG2, was purchased from the Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences . The cells were incubated in complete Dulbecco’s modified Eagle’s medium  supplemented with 10% heat-inactivated fetal bovine serum , 100 U/ml penicillin and 100 μg/ml streptomycin, in a humidified incubator at 37°C with 5% COhttp://www.ncbi.nlm.nih.gov/genbank/; accession number, NM_004708.3). Total RNA was extracted using oligo (dT) from the human HCC HepG2 cells and was reverse transcribed as a template for reverse transcription polymerase chain reaction (RT-PCR). The primer sequences were as the follows: Sense, 5′-CGC GGA TCC CCG AGG GGC TGC GAG AGT GA-3′ and antisense, 5′-CGC GAA TTC CCT AGA CTT GTT CCG TTA AG-3′. PCR conditions of 40 cycles of 94°C for 30 sec, 60°C for 45 sec and 72°C for 30 sec followed by a final elongation step at 72°C for 10 min, were used. The PCR products of full-length PDCD5 cDNA were then ligated into the BamHI/EcoRI sites of the eukaryotic expression vector, pcDNA3.1/Neo(+) (Invitrogen) using T4 DNA ligase at 16°C overnight, followed by transformation of competent Escherichia coli DH5α. DNA sequencing was used to identify a recombinant plasmid clone with the correct sequence, and this bacterial clone was amplified and purified in for eukaryote transfection. The HepG2 cells were transfected with pcDNA3.1-PDCD5 plasmid or pcDNA3.1-Neo plasmid (empty vector) [pcDNA3.1(+)] using Lipofectamine™ 2000  according to the manufacturer’s instructions. RT-PCR and RT-quantitative (q)PCR were performed to detect PDCD5 mRNA expression 48 h after transfection. SuccessfulLY transfected HepG2 cells were then grown in complete medium for further G418 screening . After four weeks, colonies were isolated and expanded into cell clones. The subclone cells expressing only Neo or Neo and PDCD5 genes were termed HepG2-Neo and HepG2-PDCD5, respectively.A PDCD5 full length cDNA sequence was obtained from GenBank (18). The forward and reverse primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd., , and the sequences and expected sizes of the PCR products were as follows: PDCD5 forward, 5′-ACA GAT GGC AAG ATA TGG ACA-3′ and reverse, 5′-TCC TAG ACT TGT TCC GTT AAG-3′ (210bp); and β-actin forward, 5-CGG GAA ATC GTG CGT GAC ATT-3′ and reverse, 5′-CTA GAA GCA TTT GCG GTG GAC-3′ (510bp). The thermal procedure of PCR for PDCD5 and β-actin mRNA was performed at 94°C for 4 min for 1 cycle, then 94°C for 45 sec, 52°C for 45 sec and 72°C for 1 min for 30 cycles, and 72°C for 7 min for 1 cycle. PCR products were subjected to electrophoresis on 1.5% agarose gels containing ethidium bromide and then visualized under ultraviolet light.The levels of PDCD5 mRNA were first examined by RT-PCR and β-actin was used as an internal reference. Total RNA (5 μg) was isolated from the HepG2 cells 48 h after transfection and RT was performed to synthesize cDNA using random primers with Easyscript First-Strand cDNA Synthesis SuperMix  primed with oligo with SYBR Green . The following primers were used: Sense, 5′-ACA GAT GGC AAG ATA TGG ACA-3′ and anti-sense, 5′-TCC TAG ACT TGT TCC GTT AAG-3′ (199 bp) for PDCD5 and; sense, 5′-TTA GTT GCG TTA CAC CCT TTC-3′ and anti-sense, 5′-ACC TTC ACC GTT CCA GTT T-3′ (150 bp) for β-actin. Firstly, RNA was extracted and reverse transcribed to cDNA using Easyscript First-Strand cDNA Synthesis SuperMix , then 1 μl cDNA was added in a 20-μl reaction mixture containing 0.5X SYBR Green, 1X TransStart Green qPCR Supermix (Transgen Biotech) and 0.5 μmol/l primer sets. The cycling conditions were as follows: 95°C for 5 min for 1 cycle, followed by 95°C for 45 sec, 57°C for 20 sec and 72°C for 20 sec for 40 cycles. The expression levels of PDCD5 were internally normalized to β-actin. The relative expression level of PDCD5 mRNA was calculated by the 24/ml density into 96-well culture plates. MTT solution  was added into each well and incubated at 37°C for 4 h. Following centrifugation at 1,409 × g for 10 min, the supernatant was discarded and 100 μl DMSO was added. When the remaining formazan pellet was dissolved completely, the absorbance values at a 570 nm wavelength were read on an ELISA plate reader . The total procedure was repeated three times.The cell growth rate was determined by MTT assay (Sigma-Aldrich). Briefly, cells (100 μl) at the logarithmic growth phase were seeded at a 1×10HepG2 cells at the logarithmic growth phase were seeded in 6-well plates. After reaching 50% confluence, the adherent cells were cultured in serum-free medium for 24 h and then were cultured in DMEM supplemented with 10% FBS. After 48 h, the cells were digested and harvested with 250 μl trypsin. The cell pellet was obtained following centrifugation for 3 min at 4°C and 978 × g, and was re-suspended with 300 μl ice-cold PBS on ice, followed by resuspension in 70% ethanol at 4°C for 30 min. Finally, 1 ml propidium iodide (PI) staining solution  was added to the samples, and then the associated data were analyzed on a FACScan . Results were acquired from 10,000 cells.5 cells in each well were harvested. Subsequent to being washed with PBS buffer, the cell pellet was incubated with 2.5 μl Annexin V and 5 μl PI  in 100 μl 1X binding buffer for 15 min in the dark. Apoptosis was determined by flow cytometry and analyzed using CellQuest and Modfit software (Becton-Dickinson). At least 10,000 events were analyzed for each sample.Next, an Annexin V-fluorescein isothiocyanate (FITC) apoptosis detection kit  was used to identify the translocation of phosphatidylserine. The HepG2 cells were cultured with 5 μg/ml cisplatin. After 24 h, 2×10in vitro migration of the HepG2-Neo and HepG2-PDCD5 cells in a 24-well tissue culture plate with a Transwell filter membrane. The lower side of the filters was coated with type I collagen (0.5 mg/ml). The cells were seeded in the upper part of the Transwell plate at a density of 5×105/ml, with 100 μl cell suspension in each well. After 24 h, the cells on the upper surface of the filter were removed, and the remaining cells were fixed with methanol and stained with hematoxylin and eosin (Sigma-Aldrich). Cell counting was performed under light microscopy (x200 magnification) and the cells that had migrated to the lower chamber were regarded as migrated cells. Each sample was assayed in triplicate and repeated twiceThe Boyden chamber invasion assay was performed to evaluate the Proteins from the HepG2 cells were extracted and their concentrations were determined by bicinchoninic acid protein concentration assay kit . The cell lysates (50 μg) were resolved on 15% SDS-polyacrylamide gels, electrophoretically transferred to polyvinylidene difluoride membranes and then incubated with primary monoclonal mouse antibodies against PDCD5, phospho-p53, Snail or insulin-like growth factor (IGF)-1 . The horseradish peroxidase-conjugated rabbit anti-mouse secondary antibody was used at 1:1,000 dilutions for 2 h at room temperature. Blots were visualized using the chemiluminescence method. β-actin was used as an internal control.All quantitative data are expressed as the mean ± standard deviation. The statistical analysis was performed by commercially available SPSS 14.0 software . Student’s t-test  was performed to compare the means between two groups. The means of the different groups were compared using a one-way analysis of variance. P<0.05 was used to indicate a statistically significant difference.Following the DNA sequencing analysis for the validation of recombinant pcDNA3.1/Neo(+)-PDCD5 (data not shown), G418 screening was performed to select for cells with successful transfection. All untransfected HepG2 cells were dead following G418 (400 μg/ml) selection. The pcDNA3.1/Neo(+)-PDCD5 transfected cells were cultivated with G418 for four weeks, until viable clones could be observed. The clones were selected for further amplification. The RT-PCR, RT-qPCR and western blot analyses were performed to measure the mRNA and protein expression levels of PDCD5 in the HepG2, HepG2-Neo and HepG2-PDCD5 cells. The mRNA and protein levels of PDCD5 in the HepG2-PDCD5 cells were significantly higher than those in the HepG2 and HepG2-Neo cells (P<0.05). No significant difference was found in PDCD5 expression between the HepG2 and HepG2-Neo cells (P>0.05) .2/M phase was significantly higher in the HepG2-PDCD5 cells compared with the HepG2 and HepG2-Neo cells (P<0.05)  . This inThe HepG2-Neo and HepG2-PDCD5 cells were treated with varying concentrations of cisplatin and the chemotherapeutic sensitivity was assessed by Annexin V-FITC and PI double staining. Following treatment with 2.5, 5 and 10 μg/ml cisplatin for 24 h, the number of HepG2-Neo and HepG2-PDCD5 apoptotic cells were increased in a dose-dependent manner . In the PDCD5 interacts with p53 proteins in a variety of cancer cells. To assess the effect of PDCD5 on p53 protein, the level of phospho-p53 protein was measured by western blot analysis. Phospho-p53 protein expression was increased following 24 h of treatment with cisplatin in the HepG2-Neo and HepG2-PDCD5 cells. Moreover, the HepG2-PDCD5 cells showed higher phospho-p53 protein levels compared with the HepG2-Neo cells following cisplatin treatment . No diffThe HepG2-Neo and HepG2-PDCD5 cells were incubated with TGF-β (2 ng/ml) for 24 h to induce invasion and EMT. The Boyden chamber invasion assay showed that PDCD5 transfection exhibited no effect on the invasion index in the cells without TGF-β treatment. However, in the TGF-β-treated HepG2 cells, PDCD5 transfection significantly decreased the invasion index compared with the cells transfected with the control plasmid (P<0.05) .The expression of the EMT marker, Snail, was determined by western blotting. In the cells transfected with the HepG2-Neo control plasmid, Snail protein was significantly increased by TGF-β treatment. However, PDCD5 transfection significantly decreased Snail protein expression in the HepG2 cells treated with TGF-β (P<0.05) .IGF-1 protein expression was also measured in the HepG2 cells by western blotting. TGF-β treatment significantly increased the IGF-1 protein expression level in the HepG2-Neo cells, which was attenuated in the HepG2-PDCD5 cells . This in2/M phase compared with the HepG2 and HepG2-Neo cells. The PDCD5-transfected cells showed higher sensitivity to cisplatin treatment compared with the HepG2-Neo cells, with higher p53 protein expression. PDCD5 overexpression can attenuate tumor invasion, EMT and IGF-1 protein induced by TGF-β treatment.In the present study, the PDCD5 gene was stably transfected into a human HCC cell line to induce its overexpression. It was demonstrated that the transfection of PDCD5 into HepG2 cells could change the biological behaviors of tumors, such as the cellular proliferation, cell cycle progression, cisplatin sensitivity, tumor invasion and EMT. The growth of the HepG2-PDCD5 cells was slower than that of the HepG2 and HepG2-Neo cells. A higher percentage of HepG2-PDCD5 cells were in the GIn the present study, the HepG2-PDCD5 cells had decreased levels of proliferation compared with the HepG2 and HepG2-Neo cells, as demonstrated by the presence of less viable cells. This indicated that PDCD5 may participate in the pathogenesis of tumors, and will be associated with various clinicopathological factors in HCC patients. The decreased expression level of PDCD5 has been observed in various human tumors, and is correlated with high-grade astrocytic gliomas , a highe2/M phase compared with the HepG2 and HepG2-Neo cells. This suggests that the decreased number of viable HepG2-PDCD5 cells is partly caused by the inhibition of cell cycle progression. G2/M is an important cell cycle checkpoint prior to cells entering the mitotic phase. In the present study, G2/M arrest following PDCD5 transfection depended on functional p53, since in cells with inactive p53, G2/M arrest did not occur (in vitro.The present study found that the stable transfection of PDCD5 could also induce cell cycle arrest, as demonstrated by the higher percentage of HepG2-PDCD5 cells in the Got occur ,17. Thisot occur . Therefo2/M phase cell cycle arrest in HepG2 cells, and indicates functional p53 protein within the cells. Therefore, the study investigated whether p53 is able to participate in the enhanced sensitivity to cisplatin caused by PDCD5. The results showed that higher phospho-p53 protein levels were observed in the HepG2-PDCD5 cells compared with the HepG2-Neo cells following cisplatin treatment, and suggests that elevated phospho-p53 protein levels may mediate enhanced apoptosis by PDCD5 transfection following cisplatin treatment. In fact, PDCD5 can directly bind with p53 protein (Cisplatin is a second-generation platinum-based chemotherapeutic drug for the clinical treatment of a variety of tumors. Cisplatin functions through restraining DNA replication, leading to cell cycle arrest and apoptosis. The long-term use of cisplatin results the development of drug resistance in numerous patients with HCC, leading to disease recurrence . Therefo protein , and co- protein . The pre protein . This inThe present study also found that PDCD5 overexpression could reduce invasion and EMT induced by TGF-β. Tumor invasion is a complex and multi-step process that involves alteration of the cell adhesion to extracellular matrix proteins. TGF-β has been shown to promote vascular invasion in HCC . The preEMT is one vital step in epithelial cells, characterized by loss of cell adhesion and acquisition of malignant phenotype, including capabilities of cell motility, migration, invasion and metastasis to a new location . The preThe present study found that TGF-β treatment significantly increased IGF-1 protein expression in the HepG2-Neo cells, which was attenuated in the HepG2-PDCD5 cells, indicating negative regulation on IGF-1 by PDCD5. IGF-1 is mainly secreted by the liver as a result of stimulation by growth hormone. IGF-1 plays roles in the promotion of cell proliferation and the inhibition of apoptosis. In human prostate cancer cells, IGF-1 upregulates ZEB1 and drives EMT . The pre2/M phase in HepG2 cells. PDCD5 transfection can also enhance the sensitivity to cisplatin and p53 phosphorylation, and reverse invasion and EMT induced by TGF-β. PDCD5 represents a novel drug target and therapeutic strategy for the improved chemotherapeutic treatment of HCC.In conclusion, stable transfection of the PDCD5 gene can inhibit the growth and induce cell cycle arrest in the G


A 0.27 meV-bandwidth monochromator for 21.5 keV synchrotron radiation demonstrates exceptional stability using cryogenic stabilization and active feedback control. 151Eu. The first-of-its-kind, fully cryogenic design achieves an energy-alignment stability of 0.017 meV r.m.s. per day, or a 100-fold improvement over other meV-monochromators, and can tolerate higher X-ray power loads than room-temperature designs of comparable resolution. This offers the potential for significantly more accurate measurements of lattice excitation energies using nuclear resonant vibrational spectroscopy if combined with accurate energy calibration using, for example, high-speed Doppler shifting. The design of the monochromator along with its performance and impact on transmitted beam properties are presented.A high-resolution silicon monochromator suitable for 21.541 keV synchrotron radiation is presented that produces a bandwidth of 0.27 meV. The operating energy corresponds to a nuclear transition in  One technique is incoherent inelastic nuclear resonant scattering also known as nuclear resonant vibrational spectroscopy (NRVS) and is also used to probe lattice excitations, but is sensitive to their local influence at the resonant isotope only . One is inelastic X-ray scattering (IXS), which is used to measure lattice dynamical excitations and how they disperse by detecting very small energy and momentum transfers when X-rays scatter off a crystal  with usable spectral efficiency , the instabilities are typically small enough compared with the bandwidth for adequate periods of time that their impact can be managed. As bandwidths are reduced, however, the instabilities can become a significant contribution to the effective energy resolution.et al., 2006Improving bandwidth and stability along with efficiency can be achieved with a combination of crystal configuration and cryogenic stabilization, which involves operating the diffracting crystals at a temperature where the coefficient of thermal expansion vanishes. This stabilizes the lattice parameter and thus the diffracted wavelength against small to moderate thermal influences, and, because of the lower temperatures, also leads to increased Debye–Waller factors that improve reflectivity profiles and thus optic efficiency. The reduced thermal expansion coefficient along with the greater thermal conductivity of single crystals at cryogenic temperatures also contributes to a greater tolerance to X-ray power loading from stronger sources. For X-ray energies above 20 keV, cryogenic stabilization has demonstrated improved efficiency of meV-bandwidth X-ray optics  while still obtaining very high energy resolution. It does this by integrating cryogenic stabilization with active feedback control on both temperature and crystal angles. The monochromator produces the highest resolution using crystal optics ever achieved to date for nuclear resonant scattering measurements at the 21.541 keV level in After presenting the design and the measured performance, we discuss the results along with additional effects on the transmitted synchrotron radiation beam that originate from multiple asymmetrically cut crystal configurations and have important consequences for applications.2.The design involves a four-reflection silicon-crystal design that is cooled to the temperature at which the coefficient of thermal expansion for silicon vanishes (123 K). It utilizes a specially designed cryogenic platform that houses the HRM and positions it into the X-ray beam. The monochromator itself incorporates active feedback control of crystal angles to achieve unprecedented energy alignment stability. We first present the design of the cryo-platform, and then present that of the HRM itself.2.1.via a two-stage heat exchanger. The primary stage consists of copper coils immersed in a liquid-nitrogen bath at atmospheric pressure. The secondary stage uses the cold gas returning from the monochromator chamber to pre-cool the supply of room-temperature helium gas before it enters the primary heat exchanger. This improves the overall efficiency of the heat exchanger.A specially designed cryostat with a copper chamber (40 cm × 20 cm × 20 cm) houses the entire HRM including mechanics, position and temperature sensors, piezo actuators, ion-chambers and a PIN photodiode. The chamber is installed inside a vacuum vessel for thermal isolation. Cold helium gas flows through channels in five of the six walls of the chamber to effect the cooling. Helium gas is cooled A pump at room temperature recirculates the helium gas creating a closed cycle. Pulsation dampeners on both the inlet and the outlet sides of the pump mitigate a major source of vibrations that would otherwise significantly deteriorate the performance of the HRM.−1. The liquid-nitrogen bath loses approximately 39 L day−1 to evaporation.The temperature of the cryostat is actively controlled using a mass-flow controller that varies the He-gas flow rate to maintain a target temperature as measured by platinum resistance thermometers (Pt-111) that are placed in the gas stream. The mass-flow controller operates at room temperature and is located between the pump and the heat exchanger. After a cool-down phase that takes approximately 24 h, the mass-flow controller maintains the cryostat temperature within 2 mK of its target temperature with a helium-gas flow-rate of approximately 77 L minvia highly flexible bellows around each of three mounting spheres. The mounting platform allows the height and overall pitch of the HRM to be controlled from a driving structure that is outside the chamber, while also diminishing the impact of chamber vibrations on the alignment and energy stability of the HRM. The copper chamber contains nitrogen gas at 150 mbar (absolute) to facilitate thermal transport between the HRM and the chamber walls. The gas also acts as an ionizing medium for three ion chambers that allow for in situ flux monitoring of the diffracted beam from the first three crystals. A drawing of the cryo-platform is shown in Fig. 1The HRM is placed inside the copper chamber on its own kinematic mounting platform that is partially decoupled from the chamber 2.2.et al., 2001versus vertical angle and X-ray energy of incident beam is shown in Fig. 3The HRM employs four silicon crystals aligned to the (12 12 8) lattice reflection in a  arrangement as shown in Fig. 2via a combination of piezoelectric actuators and stepper motors located outside the cold environment.The mechanical structure for supporting the crystals and controlling their angles is based on piezoelectric-driven weak-link flexures fabricated from grade 7075 aluminium with capacitive sensors for active feedback control. Crystals #1 and #2 are mounted on a single monolithic flexural plate with a pair of capacitive sensors to monitor their pitch (Bragg) angle relative to each other. Piezoelectric actuation on the pitch of crystal #2 allows the first two crystals to be aligned relative to each other, while the pair of capacitive sensors are used as part of an active feedback system that controls and maintains any target angle. This forms a two-crystal subassembly. Similarly, crystals #3 and #4 are mounted on a separate monolithic flexural plate and form a second two-crystal subassembly with active feedback control that adjusts the pitch of crystal #4 to maintain its alignment relative to crystal #3. These two flexure subassemblies are mounted on a third, more complicated, monolithic flexural plate shown in Fig. 4Flux monitoring is integrated into the design to allow the crystals to be aligned initially to their Bragg reflections during cryogenic operation, while the capacitive sensors are used for active feedback control to maintain the crystal angles. A PIN photodiode positioned downstream of crystal #1, but inline with the incident beam, is used for monitoring the vertical position of the HRM relative to the X-ray beam. Platinum resistance thermometers (Pt-111) are placed in close proximity to each crystal for monitoring temperatures. The complete monochromator assembly with integrated flux monitors is shown in Fig. 5et al., 1999et al., 2000The HRM has an angular acceptance of 2.9 µrad and a vertical spatial acceptance of 0.2 mm. Acceptances in the horizontal are approximately 100 times larger. To compensate for the small vertical acceptances, a beryllium compound refractive lens (CRL) consisting of 12 one-dimensional circular (radius = 0.53 mm) cylindrical lenses  was positioned in the beam 34 m from the source, while the HRM was positioned 64 m from the source  from 13 photons s−1 within a bandwidth of 1.6 eV and a beam size of approximately 0.65 mm (V) × 2.0 mm (H) FWHM, but this was reduced to 6 × 1012 photons s−1 with a 0.2 mm vertical aperture to correspond to the spatial acceptance of the HRM. With this aperture, but without the CRL, the transmitted flux was 3.5 × 107 photons s−1. After insertion of the CRL upstream, the transmitted flux increased to 5 × 107 photons s−1. The measured spectral efficiency, if defined as the ratio of spectral flux after the CRL-HRM to that before without apertures, was 1.6%.The incident flux was 1.8 × 10151Eu. Despite the narrowness of both the nuclear resonance and the resolution function, the HRM maintained its alignment to the nuclear resonance for an indefinitely long time (at least a day). Energy alignment was also unaffected by changes in X-ray power load, e.g. by temporarily removing the incident X-ray beam (20 mW). In addition to the long-term stability, Fig. 7The HRM exhibited excellent energy-alignment, or wavelength stability, and this was evident upon aligning the HRM to the nuclear resonance in 4.4.1.cf. Fig. 6−9 RMS, or 0.05–0.1 meV FWHM at 21.5 keV, based on previous room-temperature monochromators that have achieved energy resolutions greater than 108 , if mitigated, would have resulted in a spectral efficiency of 6.5%, which is the theoretically expected result.en toto). A third contributor is the expected on-axis transmission (43%) that results from combining the reflectivities of four, asymmetrically cut, high-Q crystal reflections (factor of 2.3 loss).It is important to understand all the contributions to the low spectral efficiency in order to consider ways to improve it. The main contributor to the low efficiency is the mismatch between the spatial and angular acceptance of the HRM and the size and divergence of the X-ray beam . A secondary contributor is the unexpected (factor of 2.4 loss) and expected (factor of 1.5 loss) broadened bandwidth  adjusted to maintain a preset angle position as measured using the difference of two capacitive sensors. The second involves excellent temperature control that maintains the entire monochromator to within a few mK of a preset temperature. This affords excellent mechanical stability in the absence of a changing X-ray load. The third involves choosing the operating temperature to coincide with silicon’s zero-thermal-expansion temperature of 123 K. This requires the additional complexity of cryogenics, but stabilizes the crystal lattice additionally against moderate changes in X-ray load.−1) Doppler shifting of a nuclear resonant material, e.g. in the form of a spinning disk made from a high-strength material that contains or supports the nuclear resonant material. By observing elastic nuclear resonant scattering from a fast-rotating material, the energy position of the HRM can be verified with very high accuracy from a measurement of the rotational frequency (ω) and the tangential distance between the beam and the axis of rotation (r), using Owing to the exceptional stability, the use of backlash-free mechanics and the real-time energy-position sensing, performing energy scans on the fly should be possible. In addition to removing lost time that is inherent in step scans, on-the-fly scans would limit the impact of incident beam fluctuations that occur on a time period that is large compared with the sweep duration. This would result in more accurate measurements that would improve NRVS. Further improvements to NRVS measurements can be obtained by exploiting the energy alignment stability to produce a more reliable energy scale, but this requires relative energy-alignment calibration (relative to the nuclear transition energy) with an absolute uncertainty that is small compared with the HRM bandwidth. This can be achieved with high-speed , the net temporal shear is given byc is the speed of light, and e.g. a channel-cut) results in no pulse shearing. The HRM produces a very large temporal shear of approximately 740 ps, which is significantly larger than either the temporal stretch or the incident pulse length. In the configuration employed for the HRM  that affects the transmitted beam divergence. Like longitudinal stretching, this is also proportional to the gradient in the optical path length introduced by asymmetrically cut crystals. A general expression for the dispersion contribution to the angular divergence from N flat, asymmetrically cut, crystals with all lattice vectors and diffracting surface normals being coplanar is given byet al., 2012The use of asymmetric crystals also introduces dispersion into the beam  than the very narrow sub-µeV-bandwidth beam associated with the nuclear resonant radiation.et al., 2009Consequently, additional filtering of the narrow-bandwidth nuclear resonant radiation can be obtained either with the use of an angular slit in the form of a crystal reflection or, when combined with focusing optics, with a spatial slit positioned at, or near, the focal spot of the resonant radiation (Kohn


Motivation: RNA binding proteins (RBPs) play important roles in post-transcriptional control of gene expression, including splicing, transport, polyadenylation and RNA stability. To model protein–RNA interactions by considering all available sources of information, it is necessary to integrate the rapidly growing RBP experimental data with the latest genome annotation, gene function, RNA sequence and structure. Such integration is possible by matrix factorization, where current approaches have an undesired tendency to identify only a small number of the strongest patterns with overlapping features. Because protein–RNA interactions are orchestrated by multiple factors, methods that identify discriminative patterns of varying strengths are needed.Results: We have developed an integrative orthogonality-regularized nonnegative matrix factorization (iONMF) to integrate multiple data sources and discover non-overlapping, class-specific RNA binding patterns of varying strengths. The orthogonality constraint halves the effective size of the factor model and outperforms other NMF models in predicting RBP interaction sites on RNA. We have integrated the largest data compendium to date, which includes 31 CLIP experiments on 19 RBPs involved in splicing  and processing of 3’UTR . We show that the integration of multiple data sources improves the predictive accuracy of retrieval of RNA binding sites. In our study the key predictive factors of protein–RNA interactions were the position of RNA structure and sequence motifs, RBP co-binding and gene region type. We report on a number of protein-specific patterns, many of which are consistent with experimentally determined properties of RBPs.Availability and implementation: The iONMF implementation and example datasets are available at https://github.com/mstrazar/ionmf.Contact: tomaz.curk@fri.uni-lj.siSupplementary information:Supplementary data are available at Bioinformatics online. RNA-binding proteins (RBPs) play a major role in the control of gene expression. Misregulation of RBPs is associated with diseases such as fragile X syndrome, neurologic disorders and cancer . Our undCurrent approaches to model protein–RNA interactions focus on individual data sources and require precise structural knowledge of the involved proteins (Nonnegative matrix factorization (NMF) methods have been extensively applied in machine learning for clustering, community detection, classification, etc. . The method finds modular projections of data matrices, where data instances are assigned to modules described by non-overlapping features. In a supervised setting, orthogonality regularization prevents multicollinearity  and DoRiNA . Negative examples of protein–RNA interaction sites were sites within genes that were not detected as interacting in any experiment . Among them we sampled at least 40 000 positions and used them as negative examples of crosslinking nucleotides. In total, the training set included 50 000 positions , we assured that replicate information was not used in evaluation.RG: Region typeX, RNA: RNA secondary structureX, software , resultiKMER: RNA k-mersX, k-mers, with k = 4 in all experiments. The presence of a k-mer at a relative position was indicated with a binary value.GO: Gene annotationX. Genomic positions within known genes were annotated with Gene Ontology , RNA k-mers (HKMER), surrounding region types (HRG), RNA secondary structure (HRNA) and Gene Ontology terms (HGO) (A th iONMF . The resms (HGO) .Y column  in the target Y column . The tesThreefold cross-validation was used to estimate the predictive accuracy. Internal cross-validation  is assigned to one or more of the I is the identity matrix. The first term in the sum represents approximation error and second term the orthogonality of column vectors in α. The problem is non-convex and can be solved by (projected) gradient descent, alternating-least squares , which employs the scalarization approach for orthogonality regularization, optimizing the trade-off between orthogonality and approximation error. The iONMF model is learned by solving the following optimization problem. Given multiple data matrices  squares  or seconAlgorithm 1.iONMF on multiple data matrices.Input: data matrices Y, approximation rank r, orthogonality-approximation trade-off αOutput: coefficient matrix W, basis matrices 1: for each i: 2: 3: until convergence:4: 5: for each i: 6: 7: Running matrix factorization on large datasets requires a trade-off between the number of samples considered and the computational time. A common assumption when applying NMF for prediction is that all objects in the domain, including the test samples, are used in learning  to specific modules (in columns); see W are determined based on all The obtained coefficient matrix et al.  vectors of matrices Since we are interested in modules describing the positive data samples (crosslinked sites) for a particular protein in question, we sorted the modules on descending value of ding see .Supplementary Section S7.6 and Supplementary Algorithm 2.To extract complex RNA motifs of arbitrary length from the k-mer frequency and positional information encoded in the learned factor model , L1 regularization . Hyperparameters were sampled from range P < 0.05) of the observed differences in ranks of classifiers over multiple datasets, confirming the feasibility of orthogonality as a way to induce discriminative and parsimonious factor models.We used cross-validation on the training set of 30 000 positions to choose hyperparameters: orthogonality regularization  diagram  shown inet al. . We then calculated the average AUC and standard error obtained for each data source subset across all selected RBP experiments, shown in Supplementary Table S6. To ensure fair comparison, the factorization rank r was selected such that the total number of model parameters was approximately equal for each subset of data sources (Supplementary Table S6).To estimate the importance of data sources, we measured AUC as stated above, for each possible subset of data sources and each selected RBP experiment (Supplementary Table S6). This agrees with previous observations about the importance of particular RNA structure interaction interfaces (Supplementary Table S6). This agrees with combinatorial protein–RNA interactions that compete or cooperate for RNAs binding  and type of genomic region (T) with average AUC = 0.860 ± 0.017 . These features describe the genomic organization and sequence content biases of functional subunits, e.g. exon, intron, UTR and exon-intron boundaries.The most informative pair of data sources are RNA XGO alone  is likely due to sparse and incomplete gene function annotation, which is in great contrast to other data sources that are two orders of magnitude denser  does not change the predictive accuracy significantly .The poor performance when using XGO, combining two or more data sources resulted in better accuracy than in models obtained on individual data sources, supporting the benefit of data integration. A more detailed, Spearman correlation-based comparison of all data source combinations confirms several binding preferences supported by the literature .The average AUC correlates with the total number of included data sources. The best accuracy was achieved on r modules. The identified modules of crosslinked sites with common features were visualized and used to predict functionally relevant protein–RNA interactions. Visualization of a complete set of RBP experiments and the three most relevant feature vectors are shown in Supplementary Section S8.Factor models were used to identify features associated with each discovered module. As explained in Section 2.5 and shown in Supplementary Table S9. The most informative data subset is In the following paragraphs we present the results and provide an explanation for U2AF2 [30], a known splicing factor, where the most informative single data sources are RNA secondary structure. In agreement with U2AF2 being a single-strand RNA binding protein, the probability of double stranded RNA decreases around its crosslinked sites. Features in HRNA are shown in Supplementary Figures S8, S9 and Supplementary Section S8.3.RBP co-binding and k-mer composition. Examining features in Supplementary Section S8.1). The relationship is further confirmed by recognition of U-rich motifs, appearing in the corresponding module in Supplementary Fig. S4). The NMF method discovers both U-rich motif and known tandem UG repeats in a single module (column vector in HKMER), while iONMF successfully distinguishes the two. Assigning the data samples to corresponding modules (Section 2.5), 41.6% of positive samples are related to UG-rich component, while 80.3% are related to U-tracts (note that the two sets are overlapping). The similarity of proteins based on k-mer composition and co-binding is shown in Supplementary Figures S6, S7, S10 and Supplementary Sections S8.1, S8.4.Orthogonality regularization provides an advantage in interpretation over NMF. iCLIP and CLIP based methods are subject to a U-rich sequence preference due to UV-C cross-linking. As reported previously  between motifs derived with the procedure from Supplementary Section S7.6. Ten out of twelve motifs match their reported counterparts with Supplementary Figure S15 for results and visual rendering of the comparison. Moreover, the discovered motif agree in large part to GraphProt . Using k-means clustering (k = 20), we reduced the set to 20 most common complex motifs. For each experiment and for each of the 20 selected motifs, we calculated the log odds ratio of observed versus expected occurrence in positive and negative positions. These values were then used in hierarchical clustering of proteins and motifs; see k = 50, see Supplementary Figure S13.To identify groups of proteins with similar interaction properties, we performed k-means clustering on binding motif preference. We obtained 10 candidate motifs for each RBP . Hence, iONMF can detect common neighboring motifs even if these are not part of the primary binding site.Four groups of proteins and three groups of motifs can be seen. We found that hnRNP proteins that bind to introns to regulate splicing bind to U-rich motifs , whereas those binding to exons to regulate splicing (SR), spliced mRNA (eIF3E3), or 3 UTR  mRNA are GC-rich, in agreement with the fact that introns are U-rich, and exons are GC-rich . Importantly, overlap is only seen between a subset of RBPs, but we find no evidence that some sites or features are generally shared across all RBPs. While contribution of non-specific background should be considered, we find it most likely that co-binding profiles result from biologically relevant features. For example, many RBPs bind to similar RNA sequences or structures .An interesting finding of our study is that in addition to RNA structure and sequence, the position relative to genomic features  and CLIP data of other RBPs is informative for predicting binding sites of a specific RBP. Genomic regions are informative as many proteins bind at specific positions relative to these features, e.g. U2AF2 generally binds upstream of exons . We showSeveral of the examined RBPs are known to bind similar motifs, such as the U-rich motifs bound by ELAVL, TIA, hnRNPC and U2AF2, which are also detected in our analyses . Moreovein vitro study and identified a number of promising candidates for further investigation. Together, our experimental findings establish iONMF as the data integration technique of choice where sparse, modular models are desired.Data integration in iONMF yields improvements in accuracy when compared to state-of-the-art approaches. Orthogonality regularization favors non-overlapping and sparse solutions, which are desired by domain experts, providing class-specific descriptions and model interpretation. The resulting predictions are in strong accordance with a published


Despite the considerable role of heredity in explaining individual differences in deceptive behavior, few studies have investigated which specific genes contribute to the heterogeneity of lying behavior across individuals. Also, little is known concerning which specific neurotransmitter pathways underlie deception. Toward addressing these two key questions, we implemented a neurogenetic strategy and modeled deception by an incentivized die-under-cup task in a laboratory setting. The results of this exploratory study provide provisional evidence that SNP variants across the  Men are liars. We’ll lie about lying if we have to. I’m an algebra liar. I figure two good lies make a positive.Tim Allen‘Lying,’ as a facet of human nature, has been a focus of research across a broad range of disciplines including psychology, evolutionary biology, and experimental economics. Due to its immoral nature, lying is widely condemned across cultures. However, in addition to its dark side, lying is ubiquitous and also appears essential for frictionless social interactions .Lying is generally considered as unethical and immoral behavior and most individuals regard themselves as honest. Nevertheless, it is clearly tempting to deceive when the pay off is sufficiently attractive. Toward understanding how individuals resolve the conflict between self-interest and maintenance of a positive sense of one’s own worth, a growing number of studies implement laboratory-controlled experiments. Notably, the integrity of cognitive function seems to be vital for individuals to refrain for lying. Following a task that requires the exertion of mental self-control, subjects are more likely to deceive suggesting that the depletion of one’s cognitive resources leads to lowering of our moral guard. This explanation is strengthened by studies showing that subjects experiencing ego-depletion due to the wear and tear of daily experiences  or sleepSimilar to most human traits , individDespite the considerable heritability of lying behavior, few if any studies have examined the role of specific polymorphisms in contributing to lying and deception. The current investigation addresses two neglected issues in understanding the biological roots of lying in humans. We use a neurogenetic strategy to identify a neurotransmitter system that mediates lying and deception, and pinpoint specific polymorphisms contributing to individual differences in dishonesty. In modeling the lying phenotype, we focus on a single facet of lying, personal advantage . We model material gain in the laboratory using the die-under-cup paradigm introduced by TPH2). As the rate-limiting enzyme for the synthesis of central 5-HT, TPH2 plays a key role in the modulation of 5-HT neurotransmission. Numerous association studies have linked TPH2 genetic variants to a wide spectrum of endophenotypes, behavioral traits and neuropsychiatric diseases  were recruited from National University of Singapore (NUS) using Online Recruitment System for Economic Experiments . They were randomly selected from samples of an ongoing project of economic decision-making in Singapore and China (B2ESS2). Blood samples from 1127 ethinically Han Chinese students from NUS in Singapore from the first wave and saliva samples from 936 Han Chinese students for the second wave have been collected in advance. This study was approved by Institutional Review Board of National University of Singapore and written informed consent forms were obtained from all attending subjects according to the Declaration of Helsinki. A subsample of subjects (N = 205) participated in the die-under-cup paradigm at a later date – about 2 years after the initial recruitment and collection of DNA and genotyping. This group solely consisted of Singaporean Han Chinese due to logistic considerations.Two hundred and five undergraduates aged between 19 and 30 years  with gender and age as covariates. The dependent variable was the reported number of the rolled die. Although, it is impossible for us to tell who actually told a lie, we could determine lying on the group level by comparing the observed fraction of reported die-roll outcome with the expected 1/6 probability from a fair die. Lying degree was measured by the discrepant reported mean die-roll outcome at the group level. It is assumed that the higher the mean die-roll outcome reported, the higher the tendency that the examined group cheated and vice versa.This study was a between-subjects design. The independent variables were the Subjects arrived at the lab in groups varying from 8 to 19 in number. As the die-under-cup task was relatively short and in order to make it immune to potential confounds from other experimental tasks, it was carried out as the first task in a three-experiment session. To prevent the subjects from guessing the true purpose of the experiment, they were informed that the task was added to determine an additional payoff as a token of appreciation for their participation in the other two main experiments. Subjects were spaced such that there was a vacant space on either side of each subject; they could not see the dice outcomes reported by others. This is to prevent the infectiousness of cheating behavior mentioned by The procedures of the die-under-cup paradigm were closely adapted from DNA was extracted either from blood samples using QIAamp DNA Blood Midi Kit (QIAGEN), or from saliva samples collected with Oragene DNA OG-500 tubes . All subjects’ DNA samples were genotyped with Human Omni Express 12 v1.0 DNA Analysis Kit  at the Genome Institute of Singapore.To test whether subjects were lying, on average, a non-parametric chi-square test was carried out, comparing the observed distribution to the theoretical uniform distribution expected from a fair die. Based on this, a binomial test was conducted to test the deviation of the frequency of each die outcome from the equal probability predicted. Potential gender differences of lying were also examined using the independent chi-square test.TPH2 SNPs and deceptive behavior, a linear regression analysis was conducted, using sex and age as covariates. In order to avoid multiple comparisons, we corrected the p-value using the False Discovery Rate (FDR) test (3.To investigate the relationship between DR) test . LinkageTPH2 gene in lying behavior. We then carried out the regression analysis using this eigenvalue as the dependent variable with the reported die roll outcome, similar to the analysis for individual SNPs. Finally, we carried out haplotype analysis in PLINK over those individually significant SNPs of TPH2 in the previous linear regression at p threshold of 0.05.To test the robustness of our results, we further conducted principal components analysis (PCA) and haplotype analysis respectively. We ran PCA over the whole available 29 TPH2 SNPs using an additive model. PCA is regarded as a useful approach to identify the most informative SNPs in genetic analyses for association studies testing multiple SNPs or in correcting for stratification in disease studies . The firFigure 1, the die-roll outcome reported was not equally distributed with average reported number of 4.28 (SD = 1.64). A chi-square test of goodness-of-fit confirmed that the reported number was significantly skewed to larger die numbers , which indicates that some of the subjects were lying. Using the binomial test, we tested whether the frequency reported for each die outcome was significantly different from theoretical 16.7% of fair die. Die outcomes below or equal to 3  were significantly under reported as compared to the expected true value of 16.7%, whereas the frequency of “5” and “6” reports were prominently higher than 1/6  on explaining the individual heterogeneity of the reported dice roll. The regression analysis revealed that 16 out of 29 SNPs were significant at p < 0.05 after controlling for all demographic information including age, sex, IQ, and SES.We first analyzed the correlation between each one of the 29 SNPs and the die-roll outcome using linear regression analysis. For deceptive behavior, 18 of 29 SNPs were significant at Figure 2, except for four SNPs , the remaining 25 SNPs were in strong LD with each other and comprised six haplotype blocks. We further examine the robustness of the single SNP analysis using two independent strategies: haplotype analysis and PCA.As shown in TPH2 SNPs had a value of 13.27 and explains approximately 45% of the overall variance .Polymerase chain reaction analysis revealed that the first eigenvector extracted from all 29 p = 0.008, β = 0.505) and second most common  TPH2 haplotypes (15 SNPs) in opposite directions (Table 1). Furthermore, these two haplotypes (type 2 and type 4) have no overlapping alleles at each and every SNP site, which is consistent with a Yin Yang configuration as reported for a number of other human genes  reporting “1” (truly honest report) was more than twofold greater for carriers of GG genotype (6.2%). Notably, the TT carriers, who reported die number 1, 2, or 3 were not significantly less than 16.7% , strongly suggesting that this genotype group honestly reported the real outcome. In contrast, for each die-outcome (1–6) the GG/TG carriers reported significantly higher (die numbers 5–6) or lower (die numbers 1–3) than 16.7% . A two-sample Wilcoxon rank-sum (Mann–Whitney) test was administered and a significant difference was observed between TT versus GT/GG genotypes . Given our sample size, we further run a permutation test to confirm the robustness of our results and observe a p-value of 0.0009. In general, subjects who carry G (TG or GG genotype) allele were inclined to report higher number than those who are AA carriers.We further examined SNP rs4570625 (−703 G/T SNP) in greater detail since several studies of  variant  which isTPH2 can modulate individuals’ inclination to deceive. First, and consistent with previous studies (TPH2 and the reported die-roll by single SNP analysis, PCA as well as haplotype analysis. To the best of our knowledge, this is the first report of a common polymorphism associated with lying behavior for a small monetary gain carried out in a laboratory setting following the stringent guidelines of behavioral economics.Lying is ubiquitous in daily life from the banking industry  to indiv studies , our behSubjects’ deceive but do not entirely and in these Han Chinese undergraduates the distribution of the die-roll outcome is remarkably similar to that observed in Caucasians . This crThe results with SNP rs4570625 G/T are especially informative. Subjects with the G allele reported relatively higher number of die-roll, viz., more lying. Interestingly, the G allele is a risk allele in a number of psychiatric disorders. The G allele has been associated with post-stroke anxiety in Han Chinese , as wellConsiderable evidence suggests that behavioral traits such as impulsivity result in part from a deficit in serotonergic transmission . 5-HT apTPH2 polymorphism. In the paradigm implemented in the current report, it is likely that the widespread cheating behavior observed in this task indicates that the subjects see no harm done as a result of their anonymous actions. Additionally, as a task without component of social interactions, fairness plays little role for the judgment to cheat or not to cheat in the die-under-cup paradigm. Altogether, we suggest the effect of the TPH2 variants we have studied are related to the impulsivity facet of serotonin’s actions (Notably, Crockett and her collaborators have pioneered the use of serotonergic agents on moral judgment in human . Overall actions  viz., snTPH2 contribute to individual differences in honest behavior. Notably, this hypothesis makes eminent biological sense. The importance of the study is its implementation of a neurogenetic strategy to identify which neurotransmitter pathways are contributing to one facet of moral decision-making, viz., to cheat or not to cheat for small monetary reward. Although, any one common genetic polymorphism contributes only incrementally to complex behavior and are therefore not especially helpful in prediction, we believe the perhaps greater value of genetic analysis for psychological traits is to focus attention on which biological pathways underlie these behaviors. The current study succeeds in this aim and identifies serotonin, and the rate-limiting enzyme in its biosynthesis, as a salient mechanism contributing to lying behavior. Finally, we note that as for all candidate gene studies replication is essential to confirm the robustness of the current findings.In general, our study is driven by a strongly motivated candidate gene hypothesis that variants in QS, MT, EW, and RE conceived the project. EW, SC, and RE supervise the project. QS, MT, EW, EH, SC, and RE designed the experiments. QS and MT carried out the experiments. QS, MT, and EH analyzed the data. QS, MT, EW, EH, SC, and RE wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In addition, the packaged reverse transcriptase enzyme was fully active when extracted from virions. As the RNA and enzyme components for reverse transcription are properly present in virions produced in the presence of BI-D, the inhibition of reverse transcription is likely to reflect the mislocalization of the components in the aberrant virus particle.The viral integrase (IN) is an essential protein for HIV-1 replication. IN inserts the viral dsDNA into the host chromosome, thereby aided by the cellular co-factor LEDGF/p75. Recently a new class of integrase inhibitors was described: allosteric IN inhibitors (ALLINIs). Although designed to interfere with the IN-LEDGF/p75 interaction to block HIV DNA integration during the early phase of HIV-1 replication, the major impact was surprisingly found on the process of virus maturation during the late phase, causing a reverse transcription defect upon infection of target cells. Virus particles produced in the presence of an ALLINI are misformed with the ribonucleoprotein located outside the virus core. Virus assembly and maturation are highly orchestrated and regulated processes in which several viral proteins and RNA molecules closely interact. It is therefore of interest to study whether ALLINIs have unpredicted pleiotropic effects on these RNA-related processes. We confirm that the ALLINI BI-D inhibits virus replication and that the produced virus is non-infectious. Furthermore, we show that the wild-type level of HIV-1 genomic RNA is packaged in virions and these genomes are in a dimeric state. The tRNA Current therapy for HIV-1 infected individuals consists of a combination of antiretroviral drugs that target essential steps of the virus replication cycle: virus entry into the host cell and the subsequent processes executed by the viral enzymes reverse transcriptase (RT), integrase (IN) and protease (PR). The most recently approved drugs Raltegravir The HIV-1 pre-integration complex is tethered to the host chromosome via the cellular co-factor lens epithelium-derived growth factor (LEDGF/p75) During virus maturation the virion morphology changes from a core, in which the ribonucleoprotein (RNP) is located in a ring-shape at the virus membrane, to a virus particle in which the RNP is condensed into a conical core formed by the capsid protein. Virions produced in the presence of ALLINIs are non-infectious and contain aberrant cores as shown by electron microscopy lys3 primer for reverse transcription Virus assembly and maturation are highly orchestrated and regulated processes in which several protein and RNA partners come together to create an infectious virion particle that is able to execute the complex process of reverse transcription of the RNA genome upon infection of a new cell. The Gag and Gag-Pol polyproteins are selectively packaged into nascent virions together with the dimeric RNA genome and the tRNAThe different RNA steps are interwoven with protein events during virion maturation. Several examples will be presented. The Gag precursor packages a labile genomic RNA dimer through interaction of the nucleocapsid (NC) domain with the structured Ψ signal in the 5 leader region of the HIV-1 RNA lys3 primer that is selectively packaged in newly assembled virions by the aminoacyl tRNA synthetases LysRS  293T cells were grown in DMEM (Gibco) supplemented with 10% (v/v) heat-inactivated FBS (Gibco) and 1x minimum essential medium non-essential amino acids  at 37°C and 5% CO2.SupT1 T cells were cultured in advanced RPMI 1640 medium (Gibco) supplemented with 1% (v/v) heat-inactivated fetal bovine serum , 2 mM L-glutamine (Gibco), 15 µg/ml streptomycin and 15 units/ml penicillin at 37°C and 5% CO50) when indicated. The equivalent volume of DMSO was added to control cultures .Integrase-inhibitor BI-D was prepared as described in 6 cells in 5 ml) were infected with the HIV-1 LAI virus stocks . When indicated, the culture was split and BI-D or DMSO was added. Viral spread was monitored by measuring the CA-p24 level in the virus culture medium every 1–2 days.293T cells were seeded in T75 culture flasks, cultured to 50–70% confluency and transfected with 20 µg pLAI DNA plasmid that encodes the wt HIV-1 LAI isolate Virus produced by 293T cells with or without BI-D was pelleted by ultracentrifugation over a 20% sucrose cushion in phosphate buffered saline at 32,000 rpm  for 2 h at 4°C in a Beckman SW32 Ti rotor. The pellet was resuspended in 400 µl lysis buffer  and a sample was taken for CA-p24 measurement. Virions were lysed at 37°C for 30 min by addition of proteinase K . Viral RNA was extracted twice with phenol-chloroform-isoamylalcohol (25:24:1) at 4°C. The sample was split in two parts, ethanol-precipitated and washed with 70% ethanol. RNA for primer extension was resuspended in 10 µl TE buffer  and stored at –80°C. RNA for northern blotting was resuspended in TN buffer  and treated with DNase (Ambion) for 60 min at 37°C. After incubation, the RNA was extracted once with phenol-chloroform-isoamylalcohol (25:24:1). The RNA was ethanol-precipitated with GlycoBlue (Ambion) as carrier and washed with 70% ethanol. The RNA pellet was resuspended in 40 µl TENS buffer , aliquotted and stored at –80°C.32P by random-primed labeling  using α32P-CTP . The probe was added to the prehybridized membrane, followed by hybridization for 16 h at 55°C, after which the membrane was extensively washed. Quantification was performed using a phosphorimager (Amersham Biosciences) and the ImageQuant software package. To determine the thermal stability of the HIV-1 RNA dimer, viral RNA  in 10 µl TENS buffer was incubated at increasing temperatures (40–60°C) for 10 min before the RNA was mixed with 5 µl sample buffer (30% glycerol with 0.25% bromophenol blue dye) and analyzed on a non-denaturing northern blot. The Tm was calculated as the temperature at which 50% of the RNA dimer was melted into faster migrating RNA forms.Non-denaturing and denaturing northern blot analysis was performed on viral RNA isolated from equal amounts of virions . For the non-denaturing northern blot, RNA was mixed with non-denaturing sample buffer  and analyzed by electrophoresis on a 0.9% agarose gel in 1x TBE buffer at 72 V, 4°C for 6 h. For the denaturing northern blot, viral RNA was mixed with denaturing loading dye  and electrophoresed on a 0.9% agarose gel in MOPS buffer  with 7% formaldehyde at 100 V for 4 h. The gel for non-denaturing northern blotting was soaked in 10% formaldehyde at 65°C for 30 min before blotting. For both northern blots, the RNA was transferred overnight by capillary force onto a positively charged nylon membrane (Roche) using 20x SSC . An UV crosslinker (Stratagene) was used to cross-link the RNA to the membrane. The membrane was incubated for 1 h in ULTRAhyb (Ambion) at 55°C. The probe, consisting of a 1014-bp DNA fragment covering the Nef, U3 and R regions of the pLAI plasmid , was labeled with lys3 extension or was mixed with primer CN1 , heated at 85°C for 2 min, at 65°C for 10 min, followed by slow-cooling to room temperature over 1 h to allow primer annealing. 6 µl 3x RT buffer . The cDNA was analyzed on a denaturing 6% polyacylamide-urea sequencing gel and bands were quantified using a phosphorimager (Amersham Biosciences) and ImageQuant software.Viral RNA  in 12 µl buffer  was either used directly for tRNA2, 0.0035% Triton X-100, 0.2 mM dNTPs, 2 mM DTT, 36 nM 3 primer A [GCCTTAGCAGTGCCCTGTCT], 8 units RNAsin [Roche] and 120 ng MS2 RNA [Roche]). AMV-RT (New England Biolabs) diluted in RT dilution buffer B was used to generate a standard curve. The amount of MS2 cDNA formed at 37°C for 4 h was quantitated in a TaqMan-PCR . 10 µl cDNA was mixed with 40 µl PCR-mix . The following PCR-scheme was used: 15 min at 37°C, 10 min at 95°C and 50 cycles of 15 sec 95°C, 15 sec at 56°C and 45 sec at 60°C. In each PCR-cycle the amount of DNA formed was measured.To measure RT activity, we used a real-time qPCR-based RT assay 50). Viral spread was monitored by measuring the CA-p24 level in the culture supernatant. Whereas efficient virus replication resulting in a rapid increase in CA-p24 level was scored in the control culture, HIV-1 LAI was efficiently blocked by BI-D  using a MS2-specific probe. After correction for the virus input based on CA-p24, we measured a similar RT activity in the extracts of viruses generated with or without BI-D . This relys3 primer on the viral RNA, which is the essential first step of reverse transcription. To visualize the tRNAlys3 primer bound to the viral RNA, tRNAlys3 can be extended in vitro by the incubation of the virion-extracted RNA with dNTPs and exogenous RT enzyme . The resulting 257-nt tRNAlys3-cDNA product was visualized on a denaturing polyacrylamide gel and quantified with a phosphor imager. A similar level of this product was observed with the RNA isolated from untreated or BI-D treated virions. This result shows that the primer is present and that it can be extended efficiently, irrespective of the presence of BI-D during virus production  is not influenced by BI-D.The BI-D impact on reverse transcription could also be caused by improper placement of the host tRNAT enzyme  [56]. Fooduction . Extensioduction . Becauseout BI-D . The rel by BI-D . Very silys3 placement on the viral RNA and activity of the RT enzyme. This excludes a further expansion of the BI-D inhibitory potential to the RNA processes during HIV-1 virion maturation.Allosteric IN inhibitors that disrupt the IN-LEDGF/p75 interaction do not only affect the ‘early’ process of HIV-1 integration but, unexpectedly, also the ‘late’ process of maturation. Because of the intricate link between virus maturation and several RNA-mediated processes, we investigated the effect of ALLINI BI-D, the first compound for which an altered virion morphology was reported, on RNA processes during virion assembly. The combinatorial effect of ALLINIs on early and late processes and thus possibly on RNA mechanisms could pose a combination therapy in a single drug. We confirm that BI-D, when present during virus production, renders the progeny virus non-infectious. However, we did not observe any effect on HIV-1 genomic RNA packaging and dimerization, tRNAUsing two different methods, denaturing northern blot  and primlys3 primer is correctly placed on the genomic RNA for cDNA synthesis. Thus, all basic factors required for reverse transcription are functionally present in BI-D treated virions, which nevertheless are severely defective in reverse transcription. Multiple studies showed that the first step of reverse transcription (initiation and production of strong-stop cDNA) is already inhibited Cell entry is not affected for virus produced in the presence of several ALLINIs, but early reverse transcription products were severely reduced with compounds BI-D, CX05045 and GS-B Current antiretroviral therapies use drugs that target viral enzymes  or virus entry into the target cell. None of the current drugs exert an effect at the HIV-1 RNA level. With the unexpected late effect of ALLINIs on virus maturation, besides its inhibiting effect on integration, this class of drugs is remarkably pleiotropic, but BI-D does not interfere with the viral RNA processes.


Extracellular vesicles are selectively enriched in RNA that has potential as disease biomarkers. To systemically characterize circulating extracellular RNA (exRNA) profiles, we performed RNA sequencing analysis on plasma extracellular vesicles derived from 50 healthy individuals and 142 cancer patients. Of ~12.6 million raw reads for each individual, the number of mappable reads aligned to RNA references was ~5.4 million including miRNAs (~40.4%), piwiRNAs (~40.0%), pseudo-genes (~3.7%), lncRNAs (~2.4%), tRNAs (~2.1%), and mRNAs (~2.1%). By expression stability testing, we identified a set of miRNAs showing relatively consistent expression, which may serve as reference control for exRNA quantification. By performing multivariate analysis of covariance, we identified significant associations of these exRNAs with age, sex and different types of cancers. In particular, down-regulation of miR-125a-5p and miR-1343-3p showed an association with all cancer types tested . We developed multivariate statistical models to predict cancer status with an area under the curve from 0.68 to 0.92 depending cancer type and staging. This is the largest RNA-seq study to date for profiling exRNA species, which has not only provided a baseline reference profile for circulating exRNA, but also revealed a set of RNA candidates for reference controls and disease biomarkers. Extracellular vesicles such as exosomes and microvesicles are present in all types of biological fluids (e.g. blood)246Circulating extracellular vesicles in blood have been described as treasure chests for cancer biomarkers. It has been reported that extracellular vesicles contains a variety of RNA species, the majority being small non-coding RNAs. Because of their relative stability within vesicles, these extracellular RNAs (exRNAs) have been examined as potential biomarkers for various cancers including lung cancer10Currently, biomarker studies using extracellular vesicles are faced with at least two great challenges. The first is a lack of systematic evaluation of the technical effect of RNA-seq library preparation on RNA abundance and detectability. The second is a lack of large scale RNA-seq data in a variety of populations including both healthy individuals and those with diseases to generate exRNA expression profiles as a baseline reference. Previously, we have examined three plasma samples by RNA-seq, evaluated technical variations among different RNA-seq library protocols and presented plasma exRNA composition16GSE71008). On average, we achieved 12.5 million raw reads (ranging from 4 to 16 million)  . Of thesmillion) . The twomillion) . The nummillion) .To test if technical factors had any effect on distribution of detectable RNAs, we performed principal component analysis and observed significant bias of RNA extraction and gel size selection dates . To examth most abundant RNA transcript with average log2 expression value being 11.89 (range from 11.12 to 12.79). To examine the diversity of exRNA species, we applied an iterative strategy by mapping each of the RNA reference databases in sequential order. This analysis showed that miRNA and piwiRNA were the most abundant RNA species . Of thosLike mRNA transcripts, miRNAs also demonstrate variant transcripts (isoforms), characterized by slightly different sizes and nucleic acid positions. To evaluate miRNA isoform distribution, we categorized each mapped miRNA based on its length and position. We found isoforms in all commonly detected miRNAs. For example, the top 32 abundant miRNAs demonstrated a wide variety of isoforms . Some mith among the 60 selected transcripts.To date, there have been no well-established RNAs to serve as a reference baseline for quantitative analysis of target exRNAs. To identify such reference RNAs, we first selected 60 RNAs with the smallest coefficient of variance (CV). Among those selected, 48 were from miRNAs. We applied RefFinder to identify the most stably expressed RNAs. This analysis revealed various expression stabilities among 60 selected transcripts across the 192 samples . BecauseTo estimate age and sex effect on exRNA abundance, we first excluded all cancer patients from this analysis due to potential influence of disease status. We then performed analysis of covariance (ANCOVA) in 50 healthy controls by adjusting experimental factors (RNA isolation and gel size selection dates) and biological factors (age or sex). This analysis revealed 20 exRNA transcripts to be significantly associated with sex and 15 RNA transcripts with age (FDR < 0.05) . Among tCDHR1 and PAQR5 were the most significantly differential transcripts in prostate cancer and pancreatic cancer patients, respectively.To identify an exRNA signature for colon cancer, we applied ANCOVA by including disease status, age, sex, RNA isolation and gel size selection to examine expression differences between 100 colon cancer patients and 50 healthy controls. We compared each stage  to the controls separately. This analysis identified 1, 47, 120, and 167 unique RNA transcripts showing significant differences (FDR < 0.05) in stage I, II, III, and IV, respectively. Among these, small ncRNAs (mature miRNAs and piwiRNAs) were the most common RNA species, accounting for 0, 25, 55, and 85 individual RNAs for stages I–IV . ClearlyTo evaluate if the significant small ncRNAs were able to differentiate cancer patients from healthy controls, we first performed 10 fold cross-validation analyses on miR-125a-5p and miR-1343-3p, two most commonly down-regulated miRNAs in the dataset, for their ability of cancer classification. We found that miR-1343-3p alone was able to generate an area under the curve (AUC) of 0.59, 0.72, 0.73, 0.82 for colon cancer stages I, II, III and IV, 0.75 and 0.87 for HSPC and CRPC, respectively. miR-125a-5p alone was able to generate an AUC of 0.62, 0.76, 0.74, 0.77 for colon cancer stages I, II, III and IV, 0.77 and 0.86 for HSPC and CRPC, respectively. We then performed stepwise selection using 60 small ncRNAs (colon cancer) and 46 small ncRNAs (prostate cancer) with FDR < 0.05 based on . We idenIn this study, we applied RNA-seq to examine plasma exRNA profiles from 192 individuals and evaluated a variety of RNA species for their abundance, stability and age/gender correlation as well as disease association. Studies have shown that rRNAs are the most common species when preparing RNA-seq libraries with 15–70 nt insertsCaenorhabditis elegans miR-39/54/238 barely correct for variations of RNA extraction efficiency and do not have the capacity of normalizing variations under different biological and pathological conditions. The use of miR-16-5p as an internal control has been questioned because red blood cells are an important source of miR-16-5p22By far, qRT-PCR is the most commonly used approach for gene expression quantification. However, to quantify candidate RNA abundances, it is essential to normalize their expression levels to well established reference controls. Unfortunately these controls have not yet been established for exRNAs21http://pirnabank.ibab.ac.in/stats.html), there are a total of 32194 unique piwiRNAs, which is over 10 fold more than annotated miRNAs in human. It has been reported that the biogenesis of piwiRNAs is independent of Dicer and requires other nucleasesC. elegans, Drosophila, zebrafish, mice and ratsIt is well known that miRNAs are the most abundant circulating extracellular small RNAs in both healthy controls and cancer patients. However, our extracellular RNA-seq data show that another small RNA species, piwiRNA, is almost equally as abundant as miRNA in plasma extracellular vesicles. piwiRNAs are 25–33nt in length and lack sequence conservation26C15orf52 with an important paralog being CCDC9. The second most common mRNA is ST8SIA1, which encodes a type II membrane protein that catalyzes the transfer of sialic acid from CMP-sialic acid to GM3 to produce gangliosides GD3 and GT3. This protein may be found in the Golgi apparatus and is a member of glycosyltransferase family 29. Ganglioside GD3 is known to be important for cell adhesion and growth of cultured malignant cellsMTRNR2L5, a Humanin-like protein that has shown strong cytoprotective actions against various stress and disease modelsIn addition to the small ncRNAs (miRNAs and piwiRNA), we also detected other types of RNAs and nonhuman miRNAs. The most common mRNA transcript is a protein coding gene CSF2RA, DLD, and RRP1B). CSF2RA is the alpha subunit of the heterodimeric receptor for colony stimulating factor, a cytokine that controls the production, differentiation, and function of granulocytes and macrophages. DLD is a component of the glycine cleavage system and the alpha-ketoacid dehydrogenase complexes. This gene is involved in the hyperactivation of spermatazoa during capacitation and in the spermatazoal acrosome reaction. RRP1B is a nucleolar protein that regulates E2F1-induced apoptosis3536Our study shows that both sex and age are significant contributors to variations observed in abundance of some exRNA levels. The most significant association with age was found in three protein coding genes  were constantly downregulated in colon, prostate and pancreatic cancers including early stage colon cancer. Although regulatory mechanism is not clear, lower expression in tumor tissues than normal control tissues in previous studies38394038404238394041In conclusion, we examined exRNA profiles in plasma samples derived from 192 individuals. This is so far the largest study to profile RNA contents of these circulating vesicles by RNA-seq in healthy and diseased individuals. Our data show that RNA-seq library preparation procedures can introduce significant technical bias in the detection of different RNA species and abundance of individual RNAs. This result highlights the importance of establishing standardized techniques, protocols, and workflows for extracellular vesicle isolation and RNA sequencing library preparation. We also identified a set of RNAs  with relatively stable expression which may serve as reference candidates for exRNA quantification. Additionally, we identified a panel of RNA transcripts in plasma extracellular vesicles showing association with age, sex, and cancers. Although further study is needed to validate our findings, this study has clearly expanded our knowledge of extracellular vesicle biology and exRNAs.g for 10 min, leaving >1 ml supernatant and cell debris intact in the original tubes. All plasma samples were stored at −80 °C until use. To avoid batch effect, we randomized the 192 subjects during RNA extraction, sequencing library preparation, gel size selection and sequencing pooling. Informed consent was obtained from all study participants prior to blood draw. This study was approved by Mayo Clinic and the Medical College of Wisconsin Institutional Review Boards. The patient recruitment and informed consent were carried out in accordance with the approved guidelines from both institutions.Peripheral blood samples were collected from a total of 192 subjects including 50 healthy controls with a median age of 54 (ranging from 25 to 79), 100 colon cancer patients with a median age of 55 (ranging from 15 to 90) (N = 25 for each of stages I–IV), 36 prostate cancer patients with a median age of 69 (ranging from 49 to 87) including 21 castration-resistant and 15 hormone-sensitive patients, and 6 pancreatic cancer patients with median age of 69 (ranging from 59 to 80) . For theg for 10 min to remove possible residual cell debris after thawing the stored samples. The supernatants were incubated with pre-warmed thromboplastin D  for 15 min and mixed with ExoQuick Exosome Precipitation Solution . RNase A  was then added to a final concentration of 10 μg/ml and incubated at 4°C overnight to remove free RNAs in plasma. 150 units/ml of murine RNase inhibitor  was added followed by precipitating the extracellular vesicles by centrifugation at 1,500 × g for 30 min. The vesicle pellets were dissolved in 25μL of PBS and RNA was extracted immediately. RNA was isolated with miRNeasy Micro Kit  following the standard manufacturer protocol. To eliminate potential co-precipitated DNA, the column-bound RNA was treated with 30 units of DNase I for 15 min at room temperature. The RNA was then eluted with 14μl of DNase- and RNase-free water. RNA quality and quantity were estimated by Agilent Bioanalyzer 2100 using a Small RNA Chip .The vesicle isolation and RNA extraction have been published in our previous studySmall RNA libraries were constructed following manufacturer instructions using the NEBNext Multiplex Small RNA Library Prep Set for Illumina (NEB) with slight modifications. 2-10ng of RNA per sample were reversed transcribed into cDNA after ligation of the multiplex 3′ SR Adaptor, hybridization of the reverse transcription primer, and ligation of the multiplex 5′ SR Adaptor. RNA libraries were amplified by 10 PCR cycles using Illumina compatible index primers. 12 sequencing libraries were pooled into a single sequencing lane. The amplified libraries were resolved on a native 5% polyacrylamide gel . DNA fragments corresponding to 140–160bp  were recovered in 12 μl of Elution Buffer (QIAGEN). Libraries were quantified by real time qPCR using KAPA Library Quantification Kits  and subjected to sequencing using an Illumina HiSeq2000 analyzer.http://www.mirbase.org, Release 21), piwiRNABank (http://piwiRNAbank.ibab.ac.in), siRNDdb (http://siRNA.cgb.ki.se), and FLJ Human cDNA Database . The other human genome references were downloaded from NCBI . The aligner Bowtie (version 1.1.1) was integrated into eRNA, where the parameters for sequencing alignment were −l 18, −v 1, −m 2, and –norc –best –strata. To make the sequencing profiles comparable, we scaled  RNA profiles as read count of a target RNA per million mapped reads (RPM).The RNA-seq analytical pipeline eRNA (v1.2)For each miRNA, aligned sequences were grouped by nucleotide sequence length and position. Only sequences with more than 1920 combined read counts (i.e. 10 read counts/sample) across all individuals were analyzed and annotated with a numeric suffix to identify the isoform. For example, the most common nucleotide sequence aligning to hsa-let-7d was designated hsa-let-7d.1, the second most common as hsa-let-7d.2, followed by hsa-let-7d.3, and so on. Nucleotide sequences not meeting the 1920 read criterion were all grouped together for each miRNA and were annotated by the “pool” isoform suffix (e.g. hsa-let-7d.pool).http://www.leonxie.com/referencegene.php?type=reference). RefFinder was developed for evaluating and screening reference genes from experimental datasets. It integrates the currently available major computational programs 454647We performed RNA stability testing using Ref Finder to determine the most likely reference candidates for normalization  by their mean and standard deviation within the study groups and used analysis of covariance (ANCOVA) approaches to compare the abundance level differences between study groups for each exRNA while adjusting for experimental variables (RNA isolation and gel size selection) and biological variables  . Because 493 exRNAs were included in the analysis, we employed a false discovery rate (FDR) approach and computed a q-valueTo build multivariate models for differentiation between cancer patients and healthy controls, we first selected exRNA candidates that showed differential expression between cancer stages and controls (FDR < 0.05). We then performed multivariate feature selection with optimal feature number from 3 to 10 exRNA candidates. 10 fold cross-validation was included during the feature selection process. The classification methods were k-nearest neighbor, discriminant analysis, support vector machine and logistic regression. For each model, the AUC value along with sensitivity, specificity, positive predictive value, and negative predictive value was automatically reported (Partek Genomics Suite). This AUC value, often referred to as the c-statistic, examines all possible case control pairs and measures the proportion of the time the statistical model predicts higher risk for the caseHow to cite this article: Yuan, T. et al. Plasma extracellular RNA profiles in healthy and cancer patients. Sci. Rep.6, 19413; doi: 10.1038/srep19413 (2016).


After the discovery of small interference RNA (siRNA), nanostructured siRNA delivery systems have been introduced to achieve an efficient regulation of the target gene expression. Here we report a new siRNA-generating two dimensional nanostructure in a formation of nanosized sheet. Inspired by tunable mechanical and functional properties of the previously reported RNA membrane, siRNA nanosized sheets (siRNA-NS) with multiple Dicer cleavage sites were prepared. The siRNA-NS has two dimensional structure, providing a large surface area for Dicer to cleave the siRNA-NS for the generation of functional siRNAs. Furthermore, downregulation of the cellular target gene expression was achieved by delivery of siRNA-NS without chemical modification of RNA strands or conjugation to other substances. Attention towards ribonucleic acid (RNA) has naturally grown due to its myriad of biological potentials. In addition to messenger RNA (mRNA) carrying genetic information within organisms, non-coding RNAs such as transfer RNA (tRNA), ribosomal RNA (rRNA), short-interfering RNA (siRNA) and small nuclear RNA (snRNA) can also serve particular roles in biological system2367In particular, after the development of our self-assembled RNAi-inducing microsponges bearing multiple hairpin structures as siRNA precursorsInspired by membrane’s structural property, here we report the preparation of siRNA nanosized sheet (siRNA-NS) with lateral dimensions of <500 nm. To boost therapeutic potential of two-dimensional RNA structure with fully exploiting its material properties, such as large surface area and tunable biological functions, our RNA membrane was embedded with siRNA strands and fractured into nanosheets via ultrasonication to induce RNAi in cytoplasm . By contTo synthesize siRNA-NS for mediating RNAi, two types of circular DNAs with rationally designed sequences were first generated using the method reported elsewhere14To closely investigate the tearing process, each step of the process was observed by scanning electron microscope (SEM) including the image of intact RNA membrane . When inin vitro generation of siRNA duplexes was analysed by polyacrylamide gel electrophoresis  were treated with anti-GFP siRNA-NS. Decrease of green fluorescence intensities was confirmed at 24 h after the treatment of anti-GFP siRNA-NS, showing maximum silencing efficiency with 500 pM . The celIn conclusion, nanosized RNA sheets were synthesized successfully with potential siRNA strands. For producing siRNA-NS, partially complementary RNA membrane which has 46 base-pairings out of 92 bases was chosen, so that one turn of T7 RNA polymerase around the circular DNA can result in two potential siRNA regions. Through repetitive polymerization on the template DNAs, long RNA strands can be generated, which results in multiple Dicer cleavage sites. In addition, this RNA membrane could be easily torn into nanosized sheets by ultrasonication because the membrane has flexible mechanical property. We have also demonstrated efficient generation of siRNAs from siRNA-NS in presence of Dicer enzyme and fast gene silencing effect in cells, which suggests siRNA-NS can be utilized as a new platform for efficient siRNA delivery. Therefore, over the advantage of using spherical structures, two dimensional nanosized RNA sheet could bolster therapeutic efficacy of RNA-based materials.DNA oligonucleotides were purchased from Integrated DNA Technologies (IDT). T4 DNA ligase (Cat. No. M1804) was purchased from Promega. T7 RNA polymerase (Cat. No. M0251L), 10X RNA polymerase reaction buffer (Cat. No. B9012S) and ribonucleotide solution mix (Cat. No. N0466S) were purchased from New England BioLabs. GelRed (Cat. No. 41003) was purchased from Biotium. Dulbecco’s Modified Eagle’s Medium  and fetal bovine serum  were purchased from Welgene. 100 X Antibiotic-Antimycotic (Cat. No. 15240-062), trypsin-EDTA (Cat. No. R-001-100) and Dulbecco’s phosphate-buffered saline  were purchased from Gibco. Transfection reagent  was purchased from Mirus.−1 of T4 DNA ligase and ligase buffer (30 mM Tris-HCl (pH 7.8), 10 mM MgCl2, 10 mM DTT and 1 mM ATP).Phosphorylated 92 base-long linear DNA and 22 base-long primer DNA at the final concentration of 10 μM were mixed in nuclease-free water. For denaturation and annealing, the mixture was heated at 95 °C for 2 min and slowly cooled to 25 °C for 1 h using thermal cycler (Bio-Rad). To ligate the nick in the circularized DNA, the solution was incubated overnight with 0.03 U μl2, 3 mM spermidine and 1.5 mM dithiothreitol) and 5 U μl−1 of T7 RNA polymerase. The reaction solution was incubated for 20 h at 37 °C, then evaporation-induced self-assembly was carried out overnightFor complementary rolling circle transcription process, circularized DNA  and complementary circular DNA  were mixed with 15 mM of ribonucleotide solution mix, reaction buffer  field emission scanning electron microscope (FE-SEM) was used to obtain high resolution images of siRNA-NS, and FE-SEM based energy dispersion X-ray (EDX) was used to analyse chemical compositions of siRNA-NS. The size and surface charge of siRNA-NS were measured using Malvern Zetasizer Nano-ZS90 and analysed with Zetasizer software . Each sample was prepared immediately before use and diluted with nuclease-free water. All measurements were carried out at 25 °C, and three measurements with at least 10 sub-runs were performed for each sample.−1 of recombinant human Dicer enzyme and reaction buffer  at 37 °C for 24 h or 48 h. The cleaved products were examined by 20% non-denaturing PAGE in 0.5X Tris-borate-EDTA (TBE) buffer carried out at 120 V for 60 min. Then, the gels were stained with 1X GelRed in 0.5X TBE and analysed under UV with Image Lab software (Bio-Rad).For siRNA generation from siRNA-NS, siRNA-NSs were incubated with 0.1 U μl−1 of penicillin, 100 μg ml−1 of streptomycin and 1% Antibiotic-Antimycotic at 37 °C in a humidified atmosphere supplemented with 5% CO2. The cells were passaged routinely to maintain exponential growth. One day prior to transfection (~90% confluence), the cells were trypsinized, diluted with fresh medium and transferred to 96-well plates (7000 cells per well). The siRNA-NSs were covered with the transfection reagent prior to transfection according to the manufacturer’s instruction, then the cells were treated with the covered siRNA-NS for 24 or 48 h. For cytometry analysis, HeLa-GFP cells were seeded at 24-well plates at the density of 50000 cells per well. The cells were treated with 500 pM of the covered siRNA-NS for 12 h or 24 h. The cells were first stained with Hoechst33342 and propidium iodide, then analysed with NucleoCounter NC-3000 (ChemoMetec).HeLa-GFP cells were grown in DMEM supplemented with 10% FBS, 100 U mlHow to cite this article: Kim, H. et al. Generation of siRNA Nanosheets for Efficient RNA Interference. Sci. Rep. 6, 25146; doi: 10.1038/srep25146 (2016).