Extracellular vesicles have been the focus of a large number of studies in the past five years. Exosomes, a subgroup of extracellular vesicles, are of particularly high interest because they partake in a wide number of biological pathways. Produced by a variety of cells, exosomes have an important role in both physiological and pathological conditions. Exosome cargo heavily defines the vesicles’ unique characteristics, and the cargo with the most intriguing prospects in its’ biomedical applications is the non-coding RNAs. Non-coding RNAs, and specifically microRNAs are implicated in the regulation of many biological processes and have been associated with numerous diseases. Exosomes containing such important cargo can be used as biomarkers, therapeutic biomaterials, or even drug carriers. The potential media use of exosomes seems promising. However, some obstacles should be overcome before their clinical application. Synthetic exosome-like biomolecules may be a solution, but their production is still in their beginning stages. This review provides concise information regarding the current trends in exosome studies. Extracellular Vesicles (EVs) are membrane-bound vesicles secreted by cells into the extracellular space and have the ability to transport various molecules, such as DNA, RNA, and proteins, between cells . EVs areCurrently, one of the most investigated classes of EVs is exosomes. Exosomes are single-membrane nano-sized vesicles with a diameter of ~30 to ~200nm with a topology similar to that of a cell . The reaAs mentioned above, EVs can carry different types of molecules between cells. One exosome cargo that has attracted much attention for its potential clinical applications is the non-coding RNA (ncRNA), predominantly microRNAs (miRNAs) . MiRNAs Exosomes are produced and released by various types of cells in the body, such as nervous system cells, such as Schwann cells , astrocyDue to the presence of exosomes in most cell types, they are involved in various procedures both in physiological and pathological conditions. One of the most important processes in which exosomes participate is the immune response. Immune cells secrete exosomes that are responsible for their inter-communication . From thAnother crucial role of exosomes is in the brain and nervous system functions. Here, exosomes participate in and assist the communication of neural cells with other types of cells, mainly between cells responsible for nerve axis integrity and myelination. Additionally, communication between neurons and oligodendrocytes, which are involved in the myelinating process, also depends on the secretion of exosomes. According to this mechanism, secretion of exosomes is signalled by glutamate, which as a neurotransmitter, leads to activation of glial ionotropic glutamate receptors. Through this process, exosomes are internalised by the neurons and release their cargo, which is now available for use. It has been reported that oligodendrocytic exosomes contain enzymes that resist oxidative stress, such as catalases and superoxide dismutase-1, thereby increasing neuronal tolerance to oxidative stress . Some stIn the cardiovascular system, exosomes have been observed to contain TNF-α in hypoxic conditions . CardiomThe role of exosomes is also important in pathological situations, where they are involved in the development and spread of diseases. Their role has been clarified mainly in neurodegenerative  and cardIn neurodegenerative diseases, such as Parkinson and Alzheimer, exosomes may be responsible for disease spread. In Alzheimer disease (AD), accumulation of amyloid β (Aβ) molecules takes place, resulting in plaque formation in the brain . In thisA similar function of exosomes also occurs in cases of heart failure, and a more specific example is peripartum cardiomyopathy (PPCM), which occurs in pregnant or postpartum women. In this particular condition, exosomes function as carriers of a specific miRNA, miRNA-146a, which is produced by a prolactin fragment. These exosomes are taken up by cardiomyocytes and release their content into these cells, causing a decrease in cell metabolic activity and alterations in gene expression, ultimately resulting in heart failure .At the heart of the research on exosomes is the study of their role in cancer. The exosomes secreted by cancer cells are transported to other cells of the same or other tissues, transferring both genetic material and proteins, that cause tumour proliferation and metastasis . ExampleAside from DNA, proteins and lipids, exosomes possess a substantial RNA content. RNA species, such as messenger RNA (mRNA), miRNA, and long ncRNA (lncRNA) were shown to be present in exosomes in multiple studies. More modern techniques have revealed the presence of additional RNA species within exosomes, such as small nuclear RNA (snRNA), piwi-interacting RNA (piRNA), vault RNA, transfer RNA (tRNA), small nucleolar RNA (snoRNA), Y-RNA, SRP-RNA, small conditional RNA (scRNA), 7SK-RNA, as well as fragmented RNAs . MoreoveRNAs transcribed in a cell and released into an exosome can be received by another cell, resulting in the transfer of the RNA to the recipient cell in its functional form. This process has been described by various studies over several years, while more recent evidence has shed light on the mechanisms of RNA loading into the exosome. More precisely, RNA-binding proteins appear to bind specific subsets of RNAs. An example of this mechanism is the function of Gag and Gag-like proteins. These proteins impact the RNA content of the exosome by binding genomic RNA and other RNAs and transferring them into exosomes . This exet al. reported that the exosomal lncRNA TUC339 from liver cancer cells could affect the microenvironment of the tumour, resulting in changes in adhesion and growth of tumour cells through the horizontal information transfer via exosomes  binding .et al. reported different levels of specific miRNA populations in exosomes derived from different cancer cell lines (Several subspecies of miRNAs with roles in exocytosis, hematopoiesis tumorigenesis, and angiogenesis have been documented in intercellular communication via exosomes . Oshima ll lines . Moreovell lines . Similarll lines  as well ll lines .Lastly, another study reported a close relationship between the expression of miR-134, a microRNA found in exosomes, and breast cancer, suggesting that this miRNA species can be used as a biomarker for diagnosis as well as a possible target for drug therapy .Interest in exosome research has escalated in the last decade because of their potential therapeutic applications . ExosomeBiomarkers are accurate and measurable indicators of health or pathological state . BiomarkFurthermore, pathogens like viruses can take advantage of exosomes to infect host cells . Thus, aNaturally occurring exosomes could also be used as therapeutic biomaterials  because Moreover, naturally occurring exosomes could be used as biomolecule carriers . There aWhile the clinical use of naturally occurring exosomes seems to be an up-and-coming field of study, it is important to be prescient in their utilisation as they take part in a large number of physiological pathways. Their multifaceted abilities might have adverse effects on a patient’s immune response, cancer progression, drug resistance and metabolism . FurtherExosomes are an intriguing field of study. Their cargo and unique abilities imply vast potential in their use as biomarkers, natural therapeutic vehicles and drug carriers. Before advancing in their clinical application, though, the mechanisms dictating their role in physiological and pathological conditions should be better elucidated.


We sequenced four severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Malaysia during the second wave of infection and found unique mutations which suggest local evolution. Circulating Malaysian strains represent introductions from different countries, particularly during the first wave of infection. Genome sequencing is important for understanding local epidemiology. We sequenced four severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Malaysia during the second wave of infection and found unique mutations which suggest local evolution. Circulating Malaysian strains represent introductions from different countries, particularly during the first wave of infection. Genome sequencing is important for understanding local epidemiology. Coronaviridae and the genus Betacoronavirus and has caused a pandemic of coronavirus disease (COVID-19). As of 31 March 2020, Malaysia had 2,766 confirmed cases with 43 deaths (Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the family se COVID-9. As of 3 deaths .Viral RNA was extracted from the samples using a QIAamp viral RNA minikit  and amplified according to the ARTIC nCoV-2019 protocol (MN908947) with the Geneious mapper. About 94% of the reads were mapped, except for strain 186197 (25.2%). The average depth of coverage for iSeq was 5,000×, except for strain 186197, which had only 1,000× coverage (www.gisaid.org), including six other previously deposited Malaysian strains .The iSeq raw FastQ files were analyzed using Geneious Prime 2020 . The average number of raw paired reads obtained from iSeq was 1.8 million . Paired coverage . Therefocoverage . Multiplcoverage . PhylogeThe four complete genome sequences reported here date from the main second wave of infections in Malaysia . Strain Our data showed that current circulating strains in Malaysia represent introductions from different countries and local evolution. More genomic data will clarify virus spread in Malaysia, particularly with respect to the role played by the mass gathering.MT372480 to MT372483), BioProject (PRJNA616147), BioSample , and SRA .These sequences have been deposited in the GISAID EpiCoV newly emerging coronavirus SARS-CoV-2 platform under identifiers EPI_ISL_417917 to EPI_ISL_417920. The sequences were also deposited in the following NCBI databases: GenBank (accession numbers


The gastrointestinal tract plays a crucial role in bioavailability determination of orally administered drugs, which may vary depending on, e.g., physicochemical characteristics of drug molecules  or specific drug formulation and function of the gastrointestinal tract, i.e., pH, water content, motility, drug metabolizing enzyme and drug transporters expression and activity as well as disease states.Drug transporters constitute one of the most important factors governing drug movements across intestinal wall, and constitute a part of its functional barrier . The transporters belong to transmembrane proteins that can be localized in both apical and basolateral membranes of enterocytes, and are engaged in cellular uptake or efflux processes of endogenous compounds , nutrients  and xenobiotic compounds. The membrane transporters are classified into two major superfamilies, ATP-binding cassette transporters  and solute carriers . Only few of the transporters, about 15–20, were characterized for their distinct role in drug transport Gly-Sar and ceftibuten, was studied by Shimizu et al. digoxin (P-gp substrate) accumulation in Caco-2 cell monolayers as compared with control cells. Changes in ABCB1 expression level under T3 treatment were also associated with acceleration of [3H]digoxin basal-to-apical transcellular transport glycylsarcosine (PEPT1 substrate) maximum uptake (Vmax) value but produced no effect on Km value [Studies on the Caco-2 cell line have demonstrated that thyroid hormone T3 decreased PEPT1 carrier activity via transcription inhibition and/or decreased stability of PEPT1 protein and mRNA. The thyroid gland hormone produced a significant decrease in the amount of Km value .14C]glycylsarcosine in hyperthyroid rats. Kinetic analysis showed that the [14C]glycylsarcosine uptake (Vmax) value was markedly reduced in hyperthyroid animals, whereas Km value was not affected. Thus, functional studies confirm quantitative Pept1 results, suggesting the transporter downregulation in hyperthyroidism  mice, measured via quantitative targeted absolute proteomics (QTAP) was evaluated by Pan et al. . A signiThe accumulated data suggest that both the gastrointestinal pathologies , systemic pathology states  affect the expression and function of the drug transporters in the gastrointestinal tract. The altered status the transporters provide compensatory activity in handling endogenous compounds, affect local drug actions in the gastrointestinal tract as well as impact drug bioavailability. P-gp, BCRP and MRPs belong to the best defined transporters. However, most of the available information about drug transporters and carriers in the gastrointestinal tract during pathology states are derived from in vitro and/or animal studies, and should be verified in further clinical observations.


Mechanistically, our research found that ZFAS1 could directly recruit DDX21 protein by harboring the specific motif (AAGA or CAGA). Finally, POLR1B was identified as the downstream target of DDX21 regulated by ZFAS1, which was also up-regulated in CRC cells and tissues and closely related to poor prognosis. The unrecognized ZFAS1/DDX21/POLR1B signaling regulation axis may provide new biomarkers and targets for CRC treatment and prognostic evaluation.Increasing evidence supports long non-coding RNA-ZFAS1 as master protein regulators involved in a variety of human cancers. However, the molecular mechanism is not fully understood in colorectal cancer (CRC) and remains to be elucidated. Here, we uncovered a previously unreported mechanism linking RNA helicase DDX21 regulated by lncRNA ZFAS1 in control of POLR1B expression in CRC initiation and progression. Specifically, ZFAS1 exerted its oncogenic functions and was significantly up-regulated accompanied by elevated DDX21, POLR1B expression in CRC cells and tissues, which further closely associated with poor clinical outcomes. Notably, ZFAS1 knockdown dramatically suppressed CRC cell proliferation, invasion, migration, and increased cell apoptosis, which were contrary to the effect caused by ZFAS1 up-regulation. We further revealed that the inhibitory effect caused by ZFAS1 knockdown could be reversed by DDX21 overexpression  RNA helicases exert their multiple functions as important modulators and drivers of mRNA metabolism and gene expression relying on ribonucleoprotein complexes forming, transcription factors recruitment, acting as decoys to sequester RNA binding proteins, or directly interacting with proteins by specific binding sites, etc –4. In huvia the resolution of aberrant R-loops formation in response to inflammatory stimulus  at 4 °C overnight. After washing with RIP buffer for three times, followed by protein isolation with 40μl 1×SDS protein lysis at 95°C for 10 min and 13000g centrifuged for 10 min. Input and co-immunoprecipitated proteins were analyzed by SDS-PAGE separation, and the expression level of DDX21 were measured with PARP1as internal control.shNC, shDDX21#1, followed with a treatment by actinomycin D  at a final concentration of 5 μg/mL for 0.5, 1, 2, 3, and 6 hours. Total RNA was extracted and analyzed by qRT-PCR. Then, the calculation of RNA turnover rate and half-life (t1/2) of POLR1B were determined according to the previous publications [dC/dt) is proportional to the constant of RNA decay (Kdecay) and RNA concentration (C) as shown in the following equation:SW620 cells were transfected with ications . Since adecayk was estimated by:Thus the RNA degradation rate 0C/C=1/2), the equation below can be used to calculate the RNA half-life (t1/2):When 50% of RNA is decayed  with a concentration of 200 μg/ml in the fresh cell medium. Thereafter, the cells were incubated with CHX based on the different time points . The zero hour represents the start time of treatment with CHX. The total protein was isolated according to the time courses. Finally, the expression levels of DDX21, POLR1B were measured with GAPDH as the internal control assayed by western blot method.6 SW620 stably cells were subcutaneously injected into the right armpit region. All protocols used followed the Regulations of Experimental Animal Administration issued by the Ministry of Science and Technology of the People's Republic of China. When the tumors were visible (the tumor size reached to 50 mm3), the mice were randomly divided into four groups (5 mice for each group). The mice weight and tumor size were measured every 5 days with vernier caliper. Simultaneously, the survival of mice was tracked and recorded. 37 days after injection, the mice in each group were sacrificed and the subcutaneous tumors were isolated and measured. Also, the tumor tissues were fixed in 10% formalin for further research.All mice were purchased from Shanghai Laboratory Animal Center . Before the experiments, the mice were acclimatized to the new environment for one week. 4-week-old BALB/c-nu mice were weighed. 5×10s.d.) or median (quartile). Student’s t test or Wilcoxon T test was performed to analyze the significance differences of the paired and unpaired continuous variables. Pearson χ2or Fisher’s exact test was conducted to analyze the expression or distribution differences of the variables. Kaplan-Meier method and multivariate Cox proportional hazard regression analysis was used to estimate the potential prognosis associated indicators. P-values were two sides, and P < 0.05 was considered statistically significant in all tests.All of the statistical analysis was employed using SPSS 19.0 software package , and GraphPad Prism 5 software . The data are presented as mean ± standard deviation (This study was approved by the Ethics Committee of China Medical University. All the animal experiments performed in this study were approved by the Institutional Animal Care and Use Committee of China Medical University.Supplementary FiguresSupplementary Tables


In winemaking, clarification and stabilization are the processes by which insoluble matter suspended in the wine  is removed before bottling. The light lees represent 2–4% of the total wine volume. Under certain circumstances, resuspension of lees may occur. The resuspension of lees has been attributed to temperature variations between the wine stored in tanks and the environment of the cellar. From in situ, laboratory-scale studies involving laser tomography techniques, it was shown that low (positive or negative) thermal gradients between a wine tank containing light lees and its external environment induce mass transfer by natural convection. To extrapolate these findings to full-scale tanks, an Eulerian-Eulerian multiphase CFD model was applied to simulate the two-phase flow behavior as a function of temperature variations on a 24–h cycle. Numerical temperature and time-dependent flow patterns of both wine and lees confirm that low thermal gradients induce sufficient fluid energy to resuspend the lees, thus showing that the laboratory results can be extrapolated to full-scale tanks. In winemaking, so-called lees are generated after the fermentation of grape must. They consist of a solid phase mainly composed of microorganisms (yeast and bacteria), insoluble carbohydrates, phenolic compounds, lignin, proteins, tartaric acid, a liquid phase rich in ethanol and organic acids, colloids and inorganic matter ,2,3. Leebâtonnage in French. This process of mechanical mixing is purely empirical and does not comply with any specifications. Bâtonnage favors the redistribution of the polysaccharides, amino acids, nucleic acids and esters contained in lees, well known for their strong flavors [In winemaking, the alcoholic fermentation process  is followed by a period of storage in contact with lees (known as storage on light lees). The lees used for aging wines correspond to only a small proportion of the total quantity produced during wine production. The light lees represent 2–4% of the total wine volume . During  flavors ,6. AlthoUnder certain circumstances, the resuspension of lees may also be carried out involuntarily, thus perturbing the winemaking process; this may be the case when the cause for resuspending the lees is not of mechanical (by the stirring action of wine) but of thermal origin. Such circumstances may occur as the wines are left in stainless steel tanks or wooden barrels in nonthermoregulated cellars, which is quite common in the wine world. For example, in November in the Champagne-Ardenne region in France (where the most renowned French sparkling wine is produced), cellars can usually be subjected to wide differences in temperatures, ranging from 4 °C in the morning to 20 °C in the afternoon. And in the near future, global warming will certainly bring about even bigger differences between the day- and night-time temperatures . Under sUnder a low thermal gradient, free convection in tanks or wooden vats is the result of differences in wine density in the close vicinity of the reservoir walls, due to the thermal gradients between the wine and the cellar environment ,10. Underoom > Twine or negative Troom < Twine) between the container and the outside of the container. If these low gradients induce a resuspension of the lees, then, by extension, higher gradients will contribute even more. In a second step, a numerical study was carried out to ascertain whether the laboratory results could be extrapolated to full-scale tanks. For this purpose, Computational Fluid Dynamics (CFD) calculations were performed using a calculation code based on the finite volume method and a two-phase flow model .The question that motivated this study is whether the free convection driven by the thermal gradient is sufficient to promote an effective stirring effect to resuspend the light lees within the wine bulk. Two distinct methods were applied to answer these questions. As a first step, a purely experimental study was established by creating a low thermal gradient of 3 °C . The wine was previously clarified by racking to remove heavy lees. Glass cylindrical laboratory receptacles with a capacity of 1 L and a diameter of 10 cm were used for this set of experiments.−3) which were likely to produce sufficient light scattering and subsequent facilitate efficient traceability of the flow.To investigate the natural convection flow patterns, a simple first experiment was conducted using a clear white wine sample at 12 °C, without the presence of lees. The wine sample was subjected to a low positive thermal gradient , and to a negative one . Due to the axisymmetric nature of the convective flow, a 2D investigation was sufficient to correctly reveal the dynamics of the overall 3D flow patterns. Natural convection flow can thus be highlighted through laser tomography (with a 2 W argon laser light sheet - INNOVA 70Ce2W), with the laser sheet crossing the plane of symmetry of the cylindrical receptacle ,12,13,14The flow analysis within the wine bulk resulting from the low thermal gradients between the wine and the external environment is displayed in While Does the gravitational settling rate of the light lees have an influence on their resuspension in the wine bulk, or is it negligible compared with the characteristic velocity field of the flow patterns driven by the low thermal gradients? To answer this question, a small amount of light lees was collected from the wine. Two micrographs of light lees, taken using a 15kV JEOL/JSM 6460LA scanning electron microscope, are displayed in −3 [g, The average density of wine lees is close to 1.25 g·cm−3  :The temperature dependence of the wine dynamic viscosity typically follows an Arrhenius-like equation. The following equation was derived by Liger-Belair et al.  for a st−1. By using a particle image velocimetry (PIV) measurement system, including a Litron Nd:YAG laser and a CCD video camera identical to that used in a previous study [−1  [For light lees with 5 µm in diameter and at a wine temperature of 12 °C, the settling velocity of lees was found to be of 0.0016 mm·sus study , the velocities) . It can bâtonnage, a low thermal gradient, i.e., ±3 °C, does not allow all the settled lees to be fully stirred, and therefore efficiently resuspended in the wine bulk. However, we can legitimately speculate that the greater the thermal amplitude, the more efficient the resuspension of the light lees.In order to visualize the resuspension of the lees in the receptacle (filled with 1 L of wine with lees) subjected to the low thermal gradients, the same laser tomography process was used. In a lees-free sample, tracers were added to the liquid phase to serve as wine markers in order to build the tomography-images of the wine flow structures  was used in the following tests. The calculation domain was meshed using the ANSYS Workbench Meshing® commercial code was used to calculate the anisothermal flow in the 2D calculation domain. Convective exchanges require the activation of the energy equation to take into account thermal transfer phenomena. Depending on the wine-growing region, not all wine cellars are thermo-regulated; the temperature of the ambient air in cellars can fluctuate daily [The ANSYS Fluent 19.3te daily . Such flThis subroutine is implemented in the calculation code and modulates the thermal boundary condition at the wall at each time-step of the simulation. In order to enable comparison between the laboratory-scale studies and the numerical simulation carried out on real size tanks, we used an identical temperature gradient of +/−3 °C  can be estimated as: Re being the Reynolds number defined as: 2·s−1).For the internal convective coefficient nditions , namely The Grashof number, being defined as the ratio of the buoyancy to viscous force acting on a fluid in the velocity boundary layer, is expressed hereafter for the wine stored in the tank: The thermo-physical characteristics of the materials used to determine the tank wall thermal boundary conditions are shown in For the internal free convection flow inside the tank, an analysis of the Rayleigh number . In order to quantify the proportion of light lees remaining in suspension after alcoholic fermentation, small scale alcoholic fermentation was carried out in a laboratory on a sample of uncleared wine. The quantity of light lees was estimated to be about 0.03% of the total volume. The numerical procedure consisted of injecting the appropriate quantity of lees into the bottom of the tank and then allowing it to settle by sedimentation. The unsteady calculation started when the fluid was perfectly inert and the lees were completely settled at the bottom of the tank. Moreover, both wine and lees were initialized at a temperature of ρ being the liquid density, The classical hydrodynamics in the liquid phase are described by the continuity and momentum conservation equations for laminar flows presented hereafter. The general form of the continuity equation can be written as:For a two-dimensional (2D) axisymmetric geometry, the continuity equation is given by: Conservation of momentum is described by: For 2D axisymmetric geometries, the axial and radial momentum conservation equations are given by: At the small scale of a 1 L vessel, laser tomography proved that low positive or negative thermal gradients between the wine (holding light lees) and its external environment could promote natural free convection and the subsequent resuspension of lees. To extrapolate these findings to full-scale tanks, a numerical study was carried out to simulate the two-phase flow behavior as a function of temperature variations over a 24 h cycle. −1) were observed at t = 18 h along the axis of symmetry of the tank. We can also note that the velocity profile for t = 6h merged with that of t = 24 h, transition time between positive and negative gradients.As shown in The question that motivated this study was whether a low thermal gradient between the wine and the outer part of the tank would be sufficient to resuspend the light lees. We have shown that a low thermal gradient allows a continuous and slow mixing of the wine. The postprocessing of the CFD calculations allowed each phase of the flow (wine and lees) to be followed independently.The time evolution of the volume fraction of lees in the tank, over a 12 h period, is displayed in −1, against 2.15 mm·s−1 for the wine. A key finding is that the average velocity of the wine was about 31% higher than that of the lees, which have a higher density. It should be noted, however, that the actual lees velocity was up to 250 times higher than the settling velocity previously determined using the Stokes equation (1). Moreover, it should be noted that the lees granulometry did not induce a sufficient sedimentation rate to oppose the vortex structures and the natural convection flow velocities involved. This implies that as long as the wine tank is not subjected to thermal equilibrium , the lees will not settle to the bottom of the tank. Finally, the numerical results confirmed that the laboratory results can be extrapolated to full-scale tanks, and that a small thermal gradient is sufficient to resuspend the light lees.An interesting matter is the velocity of the lees in relation to that of the wine. bâtonnage. This resuspension, if not desired, can have harmful effects on the clarification or filtration processes of wines. To ensure that our observations made at the laboratory scale  could be extended to the scale of real tanks, numerical simulations were performed using a CFD method. This study yielded three major findings. Firstly, it was shown that low thermomechanical energy is sufficient to set the liquid phase in vortex motion, regardless of the sign of the thermal gradient. Secondly, it was shown that the granulometry of the lees did not induce a sufficient sedimentation rate to oppose the vortex structures and the natural convection flow velocities involved. The higher the thermal gradient between the outside and inside of the container, the higher the quantity of lees that was resuspended. And thirdly, our numerical results evidenced that the average velocity of the wine is about 31% higher than that of the lees, which have a higher density. Simulations carried out on a real size cylindrical geometry tank for a positive and negative gradient confirmed the observations made during laboratory experiments. Finally, both methods evidenced that even under low thermal gradients, the resuspension of light lees occurs and follows the flow features.This study shows for the first time how the resuspension of light lees may occur in wine tanks when the two-phase flow mixing has a thermal origin rather than a mechanical one, such as This study was conducted in the Champagne region, where Chardonnay, Pinot noir and Pinot Meunier grape varieties are grown; however, it could easily be extended to the large variety of wines elaborated throughout the world, including those with different alcohol and sugar levels. The various proportions of ethanol and sugars will indeed modify both the density and viscosity of the wine matrix, and therefore, the subsequent flow patterns dynamics in the tank resulting from thermal gradients will vary. This may be examined in future work.


This technique is rapid, inexpensive and simple for genotyping and mutation screening in DNA sequence. The aim of this study was to evaluate the ability of HRM-PCR to analysis spa genes amongst MRSA isolates.Molecular typing methods are useful for rapid detection and control of a disease. Recently, the use of high-resolution melting (HRM) for mecA gene using PCR. We used HRM analysis and PCR-sequencing method for spa typing of MRSA isolates. In total, 15 different spa types were discriminate by HRM and sequencing method. The melting temperature of the 15 spa types, using HRM genotyping were between 82.16 and 85.66 °C. The rate of GC % content was 39.4–46.3. According to the results, spa typing of 50 clinical isolates via PCR-sequencing and HRM methods were 100% similar. Consequently, HRM method can easily identify and rapidly differentiate alleles of spa genes. This method is faster, less laborious and more suitable for high sample at lower cost and risk of contamination.A total of 50 MRSA isolates were collected from two teaching hospitals in Shiraz, Iran. The isolates were confirmed as MRSA by susceptibility to cefoxitin and detection of  Staphylococcus aureus, the mecA gene causes resistance to methicillin. This gene produces PBP2A (protein binding to penicillin) which inhibits beta-lactam antibiotics [S. aureus isolates; however, this method is time consuming process, expensive, complicated, and difficult to standardize [mec typing method is simple and cost effective with high discriminatory power to detect MRSA isolates associated with nosocomial infections [S. aureus has been performed by spa sequence typing [spa) gene has the polymorphic in X region, which determines by sequencing method [MRSA is one of the most common nosocomial pathogens worldwide, leading to severe morbidity and mortality. In ibiotics . Moleculndardize . Amongstfections . In recee typing –6. The Sg method , 6.spa typing hypervariable X region of the spa gene [spa genes amongst MRSA isolates.In recent years, high-resolution melting (HRM) analysis has been used to analyze genetic variations. This technique is rapid, inexpensive, simple and cost effective for genotyping and mutation screening in DNA sequence . HRM witspa gene –11. In tmecA gene, as it was described previously [In this study, from January 2017 to June 2018, a total of 50 MRSA isolates were collected from different patients. All isolates were identified as MRSA by standard biochemical tests, resistance to cefoxitin and detection of eviously .spa gene was amplified, using spa-1113f (5-TAA AGA CGA TCC TTC GGT GAG C-3) and spa-1514r (5-CAG CAG TAGTGC CGT TTG CTT-3) primers [http://www.spaserver.ridom.de).The X region of the The genomic DNA was extracted using Exgene Clinic SV  according to manufacturer’s guidelines and primer pair spa (spa-1113f and spa-1514r) were applied to the HRM method.The HRM analysis was performed by the Quant studio real-time PCR system . HRM was performed in 25 µL reaction containing 5 µL of 5 HOT FIREPol EvaGreen HRM Mix (ROX) , 1 µL of each primer (10 pM), 2 µL of DNA template (20 ng) and 16 µL of water . The PCR thermocycling condition was: 95 °C for 12 min, 40 cycles at 95 °C for 15 s, 63 °C for 20 s and 72 °C for 20 s. Then, 95 °C for 1 min and 40 °C for 1 min followed by HRM ramping from 75 to 90 °C with fluorescence data acquisition at 0.5 °C increments. The melting curves of all samples were analyzed by HRM Software v3.0 .In the present study, total of 50 MRSA isolates were analyzed. Overall, 26 and 24 MRSA isolates were collected from female and male patients. The study group age range was between 8–90 years. The MRSA isolates were obtained from patient’s skin , Blood , wound , Sputum , nasal , fluid , abases  and eye . Samples were isolated from different wards including Dermatology , Internal , Emergency , ICU  and outpatient .spa types, including spa types; t021, t018, t030, t037, t386, t081, t325, t345, t790, t314, t186, t304, t003, t1877, t1816. Spa type t030 was the major type in this study. These spa types were defined as the control for HRM analysis. The processing time for HRM analysis was around 2 h. The melting temperature of the 15 HRM genotypes was between 82.16 and 85.66° C. The rate of GC % lies between 39.4 and 46.3 (Table Using conventional PCR-sequencing analysis for the 50 clinical isolates of MRSA, showed 15 different spa typing and SCCmec typing [Spa typing method is based on short sequence repeats of hypervariable X region in the spa gene, but this method is still expensive. But then again this typing method is effective and easy technique to detect typing MRSA isolates [spa- types, and spa type t030 was the most common amongst MRSAs [spa genes [spa types. All of the isolates had significant difference in Tm and GC content. The G + C percentage and the length of the tandem repeats in the X region of spa gene might cause differences in melting temperature among the samples. Our spa typing results was completely similar to HRM results. This finding is in line with the findings of Hon-Kwan Chen et al. study in China [spa sequencing [Spa typing using with other typing methods, such as MLST and SCCmec can be distinguished better amongst MRSA clones in hospital [spa type. HRM method can be affected by testing conditions and type of real time machine as well as HRM software [spa type. Even though HRM method is simple, and more economical than the conventional method, it has several limitations. The HRM method cannot be replaced by sequencing and it requires the presence of positive controls for each polymorphism. In this technique it is essential to have a known control type; however, if there is a new spa type conventional PCR-sequencing is required. Also, isolates that have the same GC content with the same TM, their discrimination is difficult [MRSA can cause infections both in hospitals as well as communities , 14. Duec typing . Spa typisolates . In a prst MRSAs . HRM anapa genes . This mepa genes . In our in China . Howeverin China  and Stepin China , which squencing . Spa typhospital . Differesoftware , 11. In software . In our software , 9. Thesifficult . In HRM spa genes. This method can analysis faster is less laborious, more suitable for high quantity samples with lowers risk of contamination. Accordingly, this technique has the potential to show variation, but require control, and should be accompanied by the spa gene sequence, and it is not suitable for new strains.HRM method is simple, more economical than the conventional method. HRM method can easily and rapidly identify the different alleles of A limitation in this study was that we did not carry out HRM for MSSA isolates, due to financial constraints.


The extent of non-coding RNA alterations in patients with sepsis and their relationship to clinical characteristics, soluble mediators of the host response to infection, as well as an advocated in vivo model of acute systemic inflammation is unknown. Here we obtained whole blood from 156 patients with sepsis and 82 healthy subjects among whom eight were challenged with lipopolysaccharide in a clinically controlled setting (human endotoxemia). Via next-generation microarray analysis of leukocyte RNA we found that long non-coding RNA and, to a lesser extent, small non-coding RNA were significantly altered in sepsis relative to health. Long non-coding RNA expression, but not small non-coding RNA, was largely recapitulated in human endotoxemia. Integrating RNA profiles and plasma protein levels revealed known as well as previously unobserved pathways, including non-sensory olfactory receptor activity. We provide a benchmark dissection of the blood leukocyte ‘regulome’ that can facilitate prioritization of future functional studies. Sepsis is a multifaceted syndrome that develops as the consequence of an abnormal host response to infection leading to organ failure and high risk of death . It is eProtein-coding RNA expression profiling of blood leukocytes from sepsis patients has helped to broaden our understanding of sepsis immunopathology , for exaKnowledge of the non-coding RNA landscape in patients with sepsis is limited. Here we report a comprehensive screen of non-coding RNA expression patterns in blood leukocytes of patients with sepsis and their relation to clinical characteristics and soluble mediators of the host response. In addition, by using a guilt-by-association approach we positioned non-coding RNAs in network modules encompassing protein-coding RNA reflecting distinct cellular biological pathways.In order to build a comprehensive map of RNA expression in the context of sepsis, we evaluated protein-coding, long and small non-coding RNA expression in whole blood leukocytes from 156 sepsis patients and 82 healthy subjects (median age (Q1–Q3), 54 (42 – 60); 26% male). Patient characteristics are tabulated in Comparing sepsis patients to healthy subjects identified 15,097, 13,158, and 635 significantly altered  protein-coding, long non-coding, and small non-coding RNAs, respectively . IngenuiTXLNGY, LINC00278, and XIST had 98%, 97%, and 94% of variance explained by gender, respectively (MMP8), resistin (RETN), and lipocalin 2 (LCN2). Low expression protein-coding RNA included a Na+/Ca2+ exchanger (SLC8A1), membrane metalloendopeptidase (MME), and interleukin (IL-) six receptor (IL6R). Long non-coding RNA included lincRNA lung cancer-associated transcript 1  and antisense RNA   . No signression) . No sign2 was found for sepsis and 4 hr post-LPS (r2 = 0.51). Correlation analysis of small RNA fold expression during endotoxemia against fold expression in sepsis revealed indirect correlations (Previous studies have compared the protein-coding RNA response in patients with sepsis or trauma (non-septic) to the response after lipopolysaccharide (LPS) administration to healthy volunteers in a controlled clinical setting (human endotoxemia) . Here weelations .ATM), TNF alpha-induced protein 3 (TNFAIP3 or A20), histone deacetylase 2 (HDAC2), and mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) paracaspase , SNORD84 , HBII-276 (translation initiation module), hsa-miR-1275 , and hsa-miR-664b-3p (neutrophil degranulation/extracellular exosome module)   in sepsis patients only , a weighacaspase . Non-codo health , and miR module) . Of note(HEK293) .MMP8 and MMP9), neutrophil activation cluster of differentiation 177 (CD177), lipocalin 2 (LCN2), and arginase 1 (ARG1) , cell proliferation, and metastasis-associated antisense RNA of the titin gene (TTN-AS1) and an IL10 receptor beta subunit antisense RNA, IL10RB-AS1. Calculating intra-modular connectivities enabled us to define ‘hub’ transcripts, which are understood to represent cogs in the functional output of a network module  and LUCAT1 (Lung Cancer Associated Transcript 1) in the TLR-signaling (black) module, as module ‘hubs’. In line with their respective module eigengene correlations with inflammatory response markers, MYOSLID expression was directly correlated with levels of inflammatory response markers IL-6, IL-8, IL-10, and acute phase response protein CRP , protein ubiquitination (pink), and mitotic cell cycle (tan) modules correlated with soluble mediators of inflammation , endothelial responses (E-selectin and angiopoietin-2 [ANG2]), coagulation (D-Dimer), and clinical variables of disease severity . In cont1 (ARG1) . LincRNAk module , and idetein CRP . In cont for CRP .In this study we found that the transcriptional changes in critically ill patients with sepsis are not exclusive to protein-coding RNAs. Whole blood long non-coding RNAs, and to a lesser extent small non-coding RNAs, were significantly altered in sepsis patients relative to healthy subjects. The pattern of protein-coding and long non-coding RNA profiles in sepsis was mimicked by expression profiles in a human endotoxemia model, notably at a time point indicative of endotoxin tolerance. Small non-coding RNA profiles in sepsis patients were not recapitulated in human endotoxemia. In general, common clinical characteristics explained low proportions of variation in protein-coding and non-coding RNA profiles, suggesting that variation in leukocyte responses are largely not explained by clinical parameters. Leveraging on the concepts of network biology, protein-coding and non-coding RNA were clustered as functional biological units with RNA binding/RNA biosynthesis and cell death/olfactory receptor activity/cell-cycle G2-M DNA damage checkpoint and regulation modules central to network architecture.Advances in genomics, notably massively parallel cDNA sequencing, have shown that active transcription is not exclusive to protein-coding RNA regions . RegionsIn line with previous studies , we founA substantial proportion of variance in protein-coding and non-coding RNA expression in critically ill patients with sepsis remained unexplained. Other sources of variation, not assessed in this study, include patient genetics and time between the onset of sepsis and ICU admission . The forGABPB1-AS1  (This study was part of the Molecular Diagnosis and Risk Stratification of sepsis (MARS) project, a prospective observational study in the mixed ICUs of two tertiary teaching hospitals in the Netherlands  (1905033) . For the1905033) , accompa1905033) . Patient1905033)  and SOFA1905033) . Shock w1905033) . Blood wClinicaltrials.gov identifier NCT02328612); the subjects who received placebo were used in the current study . Whole blood was collected in PaxGene Blood tubes (Qiagen) before and 2, 4, 6, and 24 hr after LPS administration.PAXgene and EDTA tubes were also obtained from 82 healthy subjects. Eight male subjects were exposed to intravenous LPS in a Phase I, randomized, single-blind, parallel group, placebo controlled study , soluble E-selectin, and fractalkine were measured using FlexSet cytometric bead arrays  using a FACS Calibur . Neutrophil gelatinase-associated lipocalin (NGAL), ANG-1, ANG-2, protein C, antithrombin, matrix metalloproteinase (MMP)−8 , and D-dimer  were measured by Luminex multiplex assay using a BioPlex 200 . CRP was determined by an immunoturbidimetric assay (Roche diagnostics). Platelet counts were determined by hemocytometry, prothrombin time (PT), and activated partial thromboplastin time (aPTT) by using a photometric method with Dade Innovin Reagent or by Dade Actin FS Activated PTT Reagent, respectively . Normal biomarker values were obtained from 27 age- and sex-matched healthy subjects, except for CRP, platelet counts, PT, and aPTT .Total RNA was isolated by means of PaxGene blood miRNA isolation kit (Thermo-Fisher) as per manufacturer’s instructions. Quality RNA  was processed and hybridized to either the GeneChip Human Transcriptome Array (HTA) 2.0 (Thermo-Fisher) or the miRNA 4.1 96-array plate (Thermo-Fisher) following manufacturer’s instructions. Both arrays were done on all samples . Microarrays were scanned at the Cologne Center for Genomics, Cologne, Germany.2-transformation using the oligo method (version 1.44)  were processed in the R language and environment for statistical computing version 3.5.0 . Following robust multi-average (RMA) background-correction, quantile normalization, and logon 1.44)  data weron 1.44) . Probes on 1.44) , and lowon 1.44) . The miR package . Compari package  and sign package . IngenuiThe novelty of our study, that is, profiling non-coding RNA expression in leukocytes of patients with sepsis, precludes an adequate study power estimation. However, considering known co-regulation with protein-coding RNA expression, we provide study power estimates based on previous observations in typical gene expression studies . Considehttp://www.geneontology.org)  method (version 1.64) was used to build the leukocyte co-expression network as described previously . A pair-ogy.org) . Biofuncogy.org) . Human s2). Categorical data were analyzed by Fisher exact tests or chi-squared tests. Multiple comparison (Benjamini–Hochberg) adjusted p-values <0.05 defined significance. The proportion of variance in RNA expression explained by demographics and clinical characteristics was calculated using a multivariate approach implemented in the variancePartition method (version 1.10) . Comparison of continuous data between categories was done with the Wilcoxon rank sum test. Correlation analysis of continuous data was performed using Pearson’s method unless otherwise stated as well as the coefficient of determination (ron 1.10) . A multion 1.10) . Data is In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Sepsis is a serious clinical condition, in which an abnormal host response to infection leads to organ failure with a high risk of death. This study by Scicluna et al. assesses the role of non-coding RNA in patients with sepsis. Using advanced molecular analysis and bioinformatics the authors compare non-coding RNA patterns in sepsis patients and healthy subjects. In addition, the authors have treated healthy volunteers with bacterial endotoxin, which is considered an important factor in bacterial sepsis, to investigate the role non-coding RNAs. They have found that long non-coding RNAs, and to a lesser extent small non-coding RNAs, were significantly altered in sepsis patients as compared to healthy controls. Thereby, this paper significantly adds to the current concepts of the regulatory responses in sepsis.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, including Evangelos J Giamarellos-Bourboulis as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Jos van der Meer as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Michael Bauer (Reviewer #3).Thank you for submitting your article "The leukocyte non-coding RNA landscape in critically ill patients with sepsis" for consideration by The reviewers have discussed the reviews with one another and the Senior Editor has drafted this decision to help you prepare a revised submission.eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as Consensus review proposal:Non-coding RNA have been recently discovered as a new component of regulatory complexity of gene Expression in eukaryotic cells. The present study by Scicluna et al. is aimed to assess the role of non-coding RNA in sepsis patients. Using advanced molecular analysis and bioinformatics the authors compare non-coding RNA patterns in sepsis patients and healthy subjects. Additional, healthy volunteers have been treated with lipopolysaccharide to investigate effects of endotoxemia on non-coding RNAs. Resulting data are of novelty and significantly add to the current knowledge on sepsis related regulatory responses. The RNA preparation and analysis has been accomplished by up-to-date technology.The paper is descriptive, well-written, and with reasonable conclusions. It is a reasonable step forward in the field, but to some degree the paper suffers from a lack of context. Other authors have written on this topic and no attempt is made to discuss, reproduce, or bioinformatically include/compare to those studies.Essential revisions:1) The authors might consider PMID: 29657277 (data on GEO). A very small study is here: https://doi.org/10.1089/gtmb.2017.0061. They also might consider mining their own dataset GSE65682 as others have done recently: https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-020-02372-2. Many microarrays measure lncRNAs and the data are available, just not examined, online. Shouldn't the authors try to validate their findings externally?2) As a brief aside, much of the above is also true for endotoxin studies. There are also a huge number of studies looking at miRNAs in sepsis in a mechanistic fashion; nice review here: PMC6255943. All of this could be contextualized better.3) Why is the analysis of non-coding RNAs in this submission accompanied by an analysis of protein-coding regions? We understand that the authors try to investigate how the expression of coding regions is modulated by non-coding regions in terms of pathways analysis, but the way data are analysed does not support such conclusions.4) Although there is a positive association of coding-RNAs between sepsis patients and the LPS endotoxemia model, this is at the best marginal for the non-coding RNAs. This should be highlighted and the data of Figure 3—figure supplement 1 showing this should be moved in the core of the manuscript.5) For Figure 1C and the resulting pathways analysis, was an effect size threshold also used? Or just significance?6) Remarkable that the endotoxemia model had so few genes differently expressed from sepsis at 24 hours (just 43). Worth a comment on the model?7) Across which data was the functional inference done? Sepsis only? Sepsis and healthy?8) Figure 5 should be revised and demonstrate the correlation of biomarkers with non-coding RNAs.9) Figure 5B examines shock vs. non-shock; can Figure 1 add this subclassification?10) We welcome the authors to present Volcano plots and analysis of non-coding RNAs between survivors and non-survivors. Since data on 1-year survival are available, can the authors shifts in expression of non-coding RNAs between original after 28-days who become survivors and non-survivors after one year?11) Materials and methods: do any patients profiled here overlap with this group's prior microarray studies?12) Materials and methods: why were two different microarray types used, and how was this technical difference accounted for in the sepsis-vs.-endotoxemia analysis?13) As the results indicating correlation of non-coding RNA profiles in sepsis patients and expression profiles in the human endotoxemia model simultaneously with endotoxin tolerance is of extraordinary importance and interest, we suggest discussion of the  interplay of resistance and tolerance responses during endoxemia and sepsis. Essential revisions:1) The authors might consider PMID: 29657277 (data on GEO). A very small study is here: https://doi.org/10.1089/gtmb.2017.0061. They also might consider mining their own dataset GSE65682 as others have done recently: https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-020-02372-2. Many microarrays measure lncRNAs and the data are available, just not examined, online. Shouldn't the authors try to validate their findings externally?Absolutely, we have certainly searched the public domain for independent datasets to provide a level of robustness to the patterns we observed. The three studies noted by the reviewers were indeed shortlisted in our search for potential use as external validation cohorts. However, we found certain issues with the studies that precluded their use in validation of our findings. The study by da Silva Pellegrini, et al. (PMID: 29657277) was done on a granulocyte fraction after Ficoll-Paque density gradient centrifugation of whole blood, that is, only polymorphonuclear cells were assessed. This contrasts tremendously with our study on whole blood leukocytes. The data used in the study by Dai, et al. (PMID: 28872921) is not available in the public domain, and severely underpowered since the authors performed microarray analysis of 3 septic patients relative to 3 healthy controls. The study by Cheng, et al. (PMID: 32471511), which also included our own previous data (not on non-coding RNA expression), was done by inferring the potential interaction of long non-coding RNA with coding gene expression profiles, that is, not one long non-coding RNA mentioned was measured. Thus, while of high interest, these earlier studies unfortunately cannot be used to validate our findings.2) As a brief aside, much of the above is also true for endotoxin studies. There are also a huge number of studies looking at miRNAs in sepsis in a mechanistic fashion; nice review here: PMC6255943. All of this could be contextualized better.We concur with the reviewers that a body of work has identified specific microRNA as potential modulators of the immune response, particularly endotoxin tolerance, as kindly noted by the reviewers in the article by Vergadi and colleagues (PMC6255943). However, interpretation of our findings in the context of previous studies on microRNA is complicated by the fact that the majority of clinical studies focused on extracellular (circulating) microRNA, whereas more mechanistic studies employed predominantly mouse macrophages or a pro-monocytic cell line THP1 or human embryonic kidney cell lines. In order to accommodate the reviewer’s suggestion, we opted to specifically discuss those miRNA that were unmasked as potential co-expression network modulators. We found that hsa-miR-200c  was shown to modify the capacity of HEK293 cells for TLR-signaling in a MYD88-dependent fashion . We greatly appreciated the reviewers for raising this question as it has certainly helped in raising the confidence level of our network findings. The main text has been revised accordingly:“Of note, hsa-miR-200c-3p has been shown to modify TLR4 signaling efficiency dependent on MYD88-mediated pathways in an embryonic kidney cell line (HEK293).”3) Why is the analysis of non-coding RNAs in this submission accompanied by an analysis of protein-coding regions? We understand that the authors try to investigate how the expression of coding regions is modulated by non-coding regions in terms of pathways analysis, but the way data are analysed does not support such conclusions.We analyzed protein-coding and non-coding RNA in combination because we sought to mainly infer on the functional connotations of long non-coding RNA. Functional inference of long non-coding RNA is currently limited to a handful of transcripts, unlike those of protein-coding RNA. To address this problem, we reasoned that by identifying modules (or clusters) of tightly correlating protein-coding and non-coding RNA we can then infer on functional outputs of non-coding RNA by virtue of the pathways that associate with protein-coding RNA in each module. Using this “guilt-by-association” approach we were able to position a substantial proportion of non-coding RNA with otherwise no known functional annotation. We discuss this aspect of our analysis in the Discussion section, while avoiding the topic of protein-coding RNA modulation by non-coding RNA since, as the reviewers rightly pointed out, the analytical strategy we undertook would not support it. To clarify this issue in the revised manuscript we modified the following section:“To address this challenge, we undertook a guilt-by-association strategy that sought to position long non-coding RNA in co-expression modules of tightly correlating protein-coding RNA, thereby infer on functional outputs of long non-coding RNA by virtue of the pathways that associate with protein-coding RNA in each module.”4) Although there is a positive association of coding-RNAs between sepsis patients and the LPS endotoxemia model, this is at the best marginal for the non-coding RNAs. This should be highlighted and the data of Figure 3—figure supplement 1 showing this should be moved in the core of the manuscript.It is definitely remarkable that non-coding RNA expression in sepsis patients was marginally correlated to that in the human endotoxemia model. In particular, small non-coding RNA mainly showed indirect correlations. We agree with the reviewers to restructure Figure 3 by including data originally found in Figure 3—figure supplement 1. Specifically, we moved Figure 3—figure supplement 1E to Figure 3A, showing the extent of the correlation in protein-coding RNA expression between sepsis and endotoxemia.5) For Figure 1C and the resulting pathways analysis, was an effect size threshold also used? Or just significance?We used a fold change cutoff (≤ -1.2 or ≥ 1.2) and adjusted P-value ≤ 0.01. We included this information as a legend beneath volcano plots in Figure 1C. In addition, all other volcano plots throughout our manuscript were clarified by including legends for fold change cutoffs.6) Remarkable that the endotoxemia model had so few genes differently expressed from sepsis at 24 hours (just 43). Worth a comment on the model?Yes, definitely worth a comment and to accommodate the reviewer’s suggestion we have now expanded on the human endotoxemia model in the Discussion:“The human endotoxemia model is a highly relevant in vivo model of acute systemic inflammation in the context of a controlled clinical setting . In general, the model is characterized by a robust systemic response, including leukocyte transcriptional responses, exhibiting shared and unique temporal changes that resolve within 24 hours of bolus administration .”7) Across which data was the functional inference done? Sepsis only? Sepsis and healthy?Functional inference was done with sepsis patients only. We reasoned that in so doing we could test the co-expression modules against clinical characteristics, that is, without the confounding signal of the dramatic changes in sepsis relative to health. In order to clarify this point, we added the following to the main text:“On the basis of a bi-weight midcorrelation matrix of the most variable protein-coding and long non-coding RNA  in sepsis patients only, …”8) Figure 5 should be revised and demonstrate the correlation of biomarkers with non-coding RNAs.MYOSLID  expression (red module hub) and LUCAT1 (Lung Cancer Associated Transcript 1) expression (black module hub), respectively, against levels of inflammatory response markers IL-6, IL-8, IL-10, and acute phase response protein CRP. MYOSLID expression correlated directly with inflammatory markers, whereas in contrast LUCAT1 expression was indirectly correlated. We thank the reviewers for motivating this analysis as it has provided specificity to formulating testable hypotheses on the functions of non-coding RNA thereby strengthening our study. The Results section and figure legend have been revised as follows:To address this comment, we calculated the connectivity of each transcript (sum of transcript adjacencies with respect to other module transcripts) in the co-expression network as described in the Materials and methods and illustrated in Figure 4. By ranking the intra-module connectivities we identified non-coding RNA as module “hubs”. Correlation analysis of all “hub” non-coding RNA against soluble mediators showed strong correlations, particularly for markers of systemic inflammation. Of note, these patterns fully reflected the module eigengene correlations to soluble mediators shown in Figure 5A. To illustrate these findings, we focused our attention on modules that correlate substantially to levels of different soluble mediators, that is, neutrophil degranulation (red) and TLR signaling (black). Figure 5D and E now depict dot plots of MYOSLID , cell proliferation and metastasis associated antisense RNA of the titin gene (TTN-AS1) and a IL10 receptor beta subunit antisense RNA, IL10RB-AS1. […] In contrast, LUCAT1 expression was indirectly correlated to soluble mediators of inflammation, except for CRP .”“LincRNA and antisense RNA included an inducer of differentiation MYOSLID expression and (E) LUCAT1 expression against soluble mediators of inflammation IL-6, IL-8 and IL-10, as well as the acute phase response protein CRP. Rho, Spearman’s coefficient.”Figure 5D and E legend: “(D and E) Dot plots of (D) 9) Figure 5B examines shock vs. non-shock; can Figure 1 add this subclassification?Definitely, and since the question is related to a source of transcriptomic variation in sepsis patients, we would prefer including the analysis motivated by the reviewer in Figure 2. Figure 2 illustrates an analysis of variance in blood transcriptomes of sepsis patients against various demographic and clinical characteristics, including shock. Figure 2C and D now depict the global blood transcriptomic changes in septic shock patients relative to no shock. In the Results section we have included the following sentences to report the new findings:2+ exchanger (SLC8A1), membrane metalloendopeptidase (MME) and interleukin (IL-) 6 receptor (IL6R). Long non-coding RNA included lincRNA lung cancer associated transcript 1  and antisense RNA  . No significant alterations were identified in small non-coding RNA expression profiles.”“Septic shock explained low proportions of variation in RNA expression , and directly comparing patients with septic shock to patients without shock resulted in 837 and 80 significantly altered protein-coding and long non-coding RNA, respectively . […] Low expression protein-coding RNA included a Na+/CaThe legend of Figure 2 has also been revised to include the following details: “(C) Volcano plots depicting the changes in protein-coding and long non-coding RNA in patients discordant for septic shock on ICU admission. Horizontal (black) line denotes the adjusted p-value threshold for significance (adjusted p ≤ 0.01).”10) We welcome the authors to present Volcano plots and analysis of non-coding RNAs between survivors and non-survivors. Since data on 1-year survival are available, can the authors shifts in expression of non-coding RNAs between original after 28-days who become survivors and non-survivors after one year?Based on the reviewer’s comments, we firstly report results pertaining to long non-coding RNA expression in sepsis patients discordant for survival after 28 days of ICU admission. Secondly, considering only 28-day survivors we compared non-survivors to survivors after one year follow-up. We uncovered differences in protein-coding RNA profiles, albeit minimal, but no differences were observed for non-coding RNA profiles. This analysis suggests that non-coding RNA expression may not be a suitable source of signal for mortality prediction. No differences were found for 28-day survivors followed up to one year. Since our data showed no added value of RNA expression in discriminating sepsis survivors from non-survivors, we opted to only include a few sentences to report the results of the 28-day mortality analysis. However, if the reviewer would prefer us to incorporate the one year follow up analysis of 28-day survivors, we will gladly add them to the main text. The Results section was revised accordingly:“Evaluating RNA expression in patients discordant for survival after 28 days, identified 146 significantly altered protein-coding RNA . No significant differences were uncovered in non-coding RNA expression profiles, suggesting that non-coding RNA profiles obtained on ICU admission may not be suitable as mortality predictors.”Figure 2—figure supplement 1 legend: “(C) Volcano plot of significantly altered protein-coding RNA in non-survivors relative to survivors after 28 days since ICU admission. Horizontal (black) line denotes -log10 transformed adjusted p-value thresholds.”11) Materials and methods: do any patients profiled here overlap with this group's prior microarray studies?None of the patients profiled here overlap with our previous microarray studies.12) Materials and methods: why were two different microarray types used, and how was this technical difference accounted for in the sepsis-vs.-endotoxemia analysis?Two types of arrays were used in all samples (sepsis patients and human endotoxemia) based on their specificity for measuring the different types of non-coding RNA expression. The human transcriptome array (HTA) 2.0 was designed for exon-level protein-coding RNA and mainly long non-coding RNA expression studies. The miRNA 4.1 array was used to comprehensively assay small non-coding RNA including types of small RNA  that are not covered in the HTA 2.0 microarrays. To clarify this we added the following to the Materials and methods section:“Both arrays were done on all samples ”.13) As the results indicating correlation of non-coding RNA profiles in sepsis patients and expression profiles in the human endotoxemia model simultaneously with endotoxin tolerance is of extraordinary importance and interest, we suggest discussion of the  interplay of resistance and tolerance responses during endoxemia and sepsis.In accordance with the suggestion of the reviewer we added the following to the Discussion:“The host response during infection is characterized by a balance between resistance (seeking to limit the pathogen load) and tolerance (aiming to retain cell and organ functions). […] While our time-sequential data in healthy humans injected with LPS suggest that coding and long non-coding RNA profiles in blood leukocytes of sepsis patients particularly reflect a tolerant state, time course studies in patients are needed to increase the insight into the role of distinct RNA species in the interplay between resistance and tolerance”.


Nuclear factor-κB (NF-κB) plays a prominent role in promoting inflammation and resistance to DNA damaging therapy. We searched for proteins that modulate the NF-κB response as a prerequisite to identifying novel factors that affect sensitivity to DNA damaging chemotherapy.Using streptavidin-agarose pull-down, we identified the DExD/H-box RNA helicase, DDX39B, as a factor that differentially interacts with κB DNA probes. Subsequently, using both RNA interference and CRISPR/Cas9 technology, we demonstrated that DDX39B inhibits NF-κB activity by a general mechanism involving inhibition of p65 phosphorylation. Mechanistically, DDX39B mediates this effect by interacting with the pattern recognition receptor (PRR), LGP2, a pathway that required the cellular response to cytoplasmic double-stranded RNA (dsRNA). From a functional standpoint, loss of DDX39B promoted resistance to alkylating chemotherapy in glioblastoma cells. Further examination of DDX39B demonstrated that its protein abundance was regulated by site-specific sumoylation that promoted its poly-ubiquitination and degradation. These post-translational modifications required the presence of the SUMO E3 ligase, PIASx-β. Finally, genome-wide analysis demonstrated that despite the link to the PRR system, DDX39B did not generally inhibit interferon-stimulated gene expression, but rather acted to attenuate expression of factors associated with the extracellular matrix, cellular migration, and angiogenesis.These results identify DDX39B, a factor with known functions in mRNA splicing and nuclear export, as an RNA-binding protein that blocks a subset of the inflammatory response. While these findings identify a pathway by which DDX39B promotes sensitization to DNA damaging therapy, the data also reveal a mechanism by which this helicase may act to mitigate autoimmune disease. Nuclear factor-κB (NF-κB) is an inducible transcription factor that plays a prominent role in the cellular response to stress . In the DDX39B/BAT1 linked with reduced activity have also been associated with autoimmune disease  ATP using T4 polynucleotide kinase. Bacterially expressed DDX39B was used for electrophoretic mobility shift assay (EMSA). One hundred-fold molar excess of unlabeled NF-κB probe was included in competition assay. Complexes were separated by electrophoresis on non-denaturing 5% acrylamide gel and assayed by autoradiography. Experiments were performed at least twice.Oligonucleotide probes were obtained from IDT  or with RNA mini-prep kit (Zymo). For RNA fractionation experiments, fractionation was performed as described above with exception that buffers were supplemented with RNAseOut (Invitrogen) and DTT 1 mM. RNA concentration was determined using NanoDrop, and cDNA was generated using iScript (Biorad) or cDNA synthesis kit (Applied Biosystems). Quantitative real-time PCR (qPCR) was performed as described previously using EvaGreen SYBR Green (BullsEye) . For anaGBM44 cells were infected with lentiviral vectors expressing sh-DDX39B or sh-control, and triplicate biological samples cultured for 48 h before RNA isolation. Total RNA was extracted using TRIzol reagent followed by DNase treatment and purification. RNA integrity and quantity were assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies), and total RNA (1 μg) was processed for mRNA enrichment with Magnetic mRNA Isolation Kit (NEB). The isolated mRNA from each sample was used to prepare cDNA libraries using NEBNext Ultra RNA Library Prep Kit for Illumina (NEB), and all steps were completed according to the manufacturer’s manual. The cDNA libraries were single end sequenced (1 × 50 bp) on Illumina HiSeq 4000 platform at the University of Chicago genomics core facility. RNA-seq data were processed to generate pre-processed FATSQ files exhibiting the same indexes, followed by a merge-process using CASAVA Pipeline (Illumina). Data was deposited at the NCBI GEO repository (GSE129542). The FASTQ sequences were then aligned to a reference human genome annotation (GENCODE human v29). The alignment was performed using HISAT2 software (version 2.1.0) with default parameters. The aligned sequences were further sorted with Samtools (version 1.9). Expression quantification counting was performed using HTSeq-count (version 0.11.1) using a reference human genome annotation (GENCODE v29) at default union mode. The count matrix was then normalized, and differentially expressed genes identified with the DESeq2 package (version 1.22.2) in R/Bioconductor software (version 3.8). The GO analysis was performed with Gorilla online tool.RNA-Seq data (GSE94730) from HeLa cells expressing si-DDX39B were previously published . The rawCells were plated on chamber slides and fixed with paraformaldehyde for 10 min. After blocking with 5% BSA in 0.1% Triton, slides were incubated overnight at 4 °C with the following primary antibodies: rabbit anti-p50 (1:300) , rabbit anti-p65 (1:300) , or mouse anti-double-stranded RNA (1:50) . After washing with PBS, slides were incubated with Alexa Fluor 488 secondary antibody (Life Technologies) for 2 h at room temperature and then rinsed and cover-slipped with mounting medium containing DAPI (Fisher Scientific). For negative controls, primary antibody was replaced with appropriate serum.Fluorescence images were captured on a Zeiss Axiovert 200M microscope. DAPI and AlexaFluor 488 images were captured using sequential acquisition to give separate image files for each. At least three high power fields (20–40×) were selected by viewing DAPI staining. This approach provided data on at least 100 cells per field. Quantification was calculated from samples plated in triplicate by counting all positive cells in each field per run and averaging their total number in a blinded manner. The percentage of these among the total cells was then reported. Each experiment was repeated at least twice with similar results.t test with significance taken as P < 0.05.In vitro and other studies where indicated were analyzed by two-tailed Student’s Additional file 1:Figures S1- S5.Additional file 2:Table S1. Analysis of RNA-Seq data from GBM44 GSCs expressing sh-DDX39B or non-targeting sh-control.Additional file 3:Table S2. Analysis of RNA-Seq data from HeLa cells transfected with si-DDX39B or non-targeting control siRNA.Additional file 4:Table S3. Sequences of oligonucleotides used in the study.


Dear Editor,2, which raises a key unresolved issue about its transcriptomic and epitranscriptomic architectures. The complete viral genomic RNA sequence contains six major open-reading frames (ORFs), including two large polyproteins ORF1a and ORF1b that can form nonstructural proteins through proteolytically cleaving upon cell entry. Other subgenomic mRNAs (sgRNAs) encoding structural proteins including spike protein (S), envelope protein (E), membrane protein (M), nucleocapsid protein (N), and accessory proteins , generated through a mechanism termed discontinuous extension of minus strands.The worldwide pandemic of COVID-19 is caused by a novel β-coronavirus SARS-CoV-2, an enveloped RNA virus with a positive-sense, single-stranded RNA genome of ~30 kb3. Moreover, the formation of sgRNAs is based on the discontinuous transcription leading to the leader–body fusion controlled by the RNA-dependent RNA polymerase and transcription-regulatory sequences (TRSs). TRSs, located at the 3′ end of the leader sequence (TRS-L) and preceding each viral gene (TRS-B), contain a conserved 6–7 nt core sequence and variable 5′ and 3′ flanking sequences4.All the viral transcripts contain a 5′ cap, a common 5′ leader sequence of around 70 nt, a common 3′ untranslated region (3′UTR), and a 3′ poly(A) tailN6-methyladenosine (m6A) as the most abundant methylation type in mRNA has been shown to regulate the viral life cycles and the cellular response to viral infection6. Recently, dozens of RNA modification sites have been identified through nanopore direct RNA sequencing8, while the intrinsic nature and the detailed functions of the RNA modifications remain obscure. Here, we conducted m6A MeRIP-seq (methylated RNA immunoprecipitation sequencing) using RNAs from SARS-CoV-2-infected Vero cells, and identified 13 m6A-modified peaks on viral transcripts ). We found that m6A might regulate abundance of SARS-CoV-2 through a mechanism of 3′UTR with or without RRACH.RNA chemical modifications are involved in physiology and pathology processes through regulating RNA metabolism. 6A landscape along SARS-CoV-2 transcriptome. The results showed that more than 99.4% reads aligned to SARS-CoV-2 derived from positive-sense RNA and that only less than 0.6% from negative-sense RNA in both immunoprecipitated (IP) and input samples  algorithm was designed based on the analysis model reported in previous study9   and negative-sense RNA  to profile the m6A peaks along the viral positive-sense RNA  were located in the CDS segments of ORF1ab  contained less than 11 peaks with RRACH  as an internal artificial reference for normalization during library construction  were significantly decreased upon METTL3 knockdown, while others kept a similar level of enrichment after depleting METTL3   or without random inner junction (regular 3′UTR). In normal cells, viral sgRNAs with regular 3′UTR can be methylated by the host METTL3, which likely stimulates the cellular degradation program to clear away the viral RNA. On the other hand, to resist the m6A-dependent degradation, SARS-CoV-2 might acquire diverse 3′UTR by depleting m6A-modified RRACH motifs (Supplementary Fig. In summary, our work analyzed the mSupplementary InformationSupplementary Table S1Supplementary Table S2


This method is sequence-dependent on efficiency and is limited to products longer than ~12 nucleotides. Additionally, the native initiation sequence is required to achieve high yields, putting a strain on sequence variability. Deviations from this sequence can lead to side products, requiring laborious purification, further decreasing yield. We here present transcribing tandem repeats of the target RNA sequence followed by site-specific cleavage to obtain RNA in high purity and yield. This approach makes use of a plasmid DNA template and RNase H-directed cleavage of the transcript. The method is simpler and faster than previous protocols, as it can be performed as one pot synthesis and provides at the same time higher yields of RNA.There is an increasing demand for efficient and robust production of short RNA molecules in both pharmaceutics and research. A standard method is  Ribonucleic acid (RNA) is one of the main building blocks of life. It is not only accepted as being the first self-replicating precursor of all life, but still maintains an essential role in all living organisms. Apart from encoding protein sequence as messenger RNA, it also forms major regulatory pathways between the genome and the proteome through a vast number of RNA classes ,2, like Commercial RNA is often produced through solid-phase synthesis. This is limited to short sequences (~100 nucleotides (nt)) and is comparatively costly, but offers the possibility to incorporate chemical modifications, which can facilitate delivery and increase stability and activity in cells ,15. Whilin vitro transcription (IVT) using RNA polymerase from bacteriophage T7 (T7RNAP) [The method of choice for in-house production of non-modified RNA samples is (T7RNAP) ,18. Whil(T7RNAP) ,21,22,23(T7RNAP) ,25,26. I(T7RNAP) . A common method to increase T7RNAP processivity and termini homogeneity is an alteration of the DNA template. 5′-inhomogeneity can be reduced by addition of G-rich initiation-sequences directly after the T7 promotor. Furthermore, 2′-methoxylation of the final two 5′-nucleotides of the DNA template should suppress the addition of non-templated nucleotides on the 3′-end of the RNA product . Yield aAnother means of decreasing 5′- and 3′-inhomogeneity is the incorporation of cis-acting ribozymes that self-cleave after transcription, leaving well-defined 5′- and 3′-ends . HoweverEscherichia coli RNase H cleaves the RNA phosphodiester bond in an RNA-DNA hybrid duplex opposite the DNA’s 5′-end, leaving native 3′-OH and 5′-monophosphate termini [RNase H has been employed to replace ribozymes for the removal of initiation sites, or excise labelled fragments ,33. Esch termini ,35,36. Tin vitro production of miRNA that is based on promoter-free rolling circle transcription from a short, single-stranded, circular DNA to produce a tandem repeat transcript, which is successively cleaved by RNase H [Wang et al. presented a method for  RNase H . A simil RNase H . Herein we report a simple and cost-effective strategy for the enzymatic production of short, non-modified RNAs in high yield and purity. We use a plasmid encoding tandem repeats of the target RNA sequence. The resulting transcript is cleaved with RNase H guided by a chimeric cleavage splint to produce single repeat units of precise length. The resulting pool of cleaved RNAs is highly homogenous, simplifying downstream purification and improving subsequent yield .We here present a one-pot method that facilitates enzymatic RNA production by transcribing from a plasmid encoding a repetitive template and thereafter site-specifically separating the tandem repeats with RNase H cleavage guided by a short chimeric oligo to release single target RNAs . These sWe tested this method on six different constructs, one of 20 nt, four of 22 nt, and one of 75 nt length. None of them starts with a GG sequence, and are therefore, poor candidates for conventional IVT.For the transcription of tandem repeats, we generated a template consisting of a T7 promotor (5′ – TAA TAC GAC TCA CTA TA – 3′) followed by an optimal initiation sequence (5′ – GGG AGA – 3′) . These aWe chose plasmid DNA, as they are reliable templates, because a high number of repeats is possible, and maintenance is simple and well-established. We used a pUC19 vector as a plasmid backbone and purchased a 600 bp insert cloned into the vector (insert synthesis and subcloning performed by Genscript), which resulted in e.g. for construct 2: 26 repeats of a 22 nt target RNA after the T7 promoter (detailed information in SI). The cloning site was chosen so that a BamHI recognition site is within a few base pairs downstream of the insert for linearization. It can be problematic to verify the exact number of repeats in a construct by sequencing; however, the exact number of repeats is not strictly important for this approach, as it does not influence the result apart from the ratio of pure cleaved product to side-product.The transcription condition from the linearized plasmid of construct 2 has been optimized with published conditions as a starting point . Interes2+ concentrations above 40 mM inhibit the reaction for construct 2 and construct 3 (data not shown). The transcription reactions for all 6 constructs can be seen in As proof of principle, the IVT of construct 1 is shown in E.coli RNase H cleaves the RNA in an RNA-DNA duplex opposite the DNA’s 5′-end and shows improved specificity and efficiency if the DNA sequence is flanked by modified nucleotides with an enhanced binding affinity to RNA. For this purpose, 2′-OMe modifications are employed [employed  . This renders purification between T7 transcription and RNase H cleavage reactions obsolete and means, and they can be performed in the same vessel. Simultaneous and successive reactions showed no difference in yield and purity, but could shorten the overall time requirements.Preparative HPLC can struggle to separate nucleic acids of similar length, due to their small relative difference in size and charge. Our group recently developed a protocol to purify milligrams of short RNA to a single-nucleotide resolution with ion-exchange HPLC . Using tReaction yield was quantified with HPLC using an external standard of known amounts of construct 2. A standard curve of samples containing 149.8, 74.9, 37.4, 18.7 and 9.3 nmol of construct 2 was created, confirmed by UV spectroscopy, to allow quantification of HPLC analyte samples after normalization of molar extinction coefficients . Yields When scaling up, we usually found no correlation of yield to reaction scale. However, a difference in generation of inorganic pyrophosphate precipitates during transcription and cleavage efficiency between small scale (20–50 µL) and large scale (1–40 mL) reactions was observed. Precipitation during T7 transcription reactions is attributed to aggregation of pyrophosphate with magnesium ions and nucleic acids . While tThe protocol we present here aims at maximizing the yield of synthesized RNA and simplifying the purification of the product. In synthetic chemistry, the yield is defined as the ratio of obtained pure product to input of limiting reagent. In contrast to this, biochemical publications on RNA production often report on fold amplification compared to the input DNA template, often in units of mass . The DNACompared to state-of-the-art protocols , our metThe optimal initiation site (5′ – GGG AGA – 3′ ) increases the overall production of RNA through facilitating the binding and altering the processivity of the T7 RNA polymerase . AdditioThe increased starting purity of our samples simplifies purification and allows us to retain more of the original synthesized product in the final sample, therefore, increasing the yield. Typically, the purification of single copy transcripts was hampered by side products of similar length in high concentration, where their removal is a challenge in preparative chromatography or gel electrophoresis methods , Figure B,C. BecaE.coli, allowing for highly similar reaction conditions. Another factor for yield loss comes from the mere number of handling steps of the sample, such as buffer-exchange or change of vessel, where RNA is lost. This issue is especially present for the annealing step of large volumes, as the sample requires heating to ~95 °C. The annealing process in the presence of magnesium needs to be fast, as otherwise, high temperature leads to hydrolytic cleavage of the RNA chain . Therefoin vitro transcribed RNA is immunogenic, due to 5′-triphosphate moieties and double-stranded side products [It has been found that products . With ouproducts , which iproducts .In conclusion, our method proposed a new way of producing large amounts of single-stranded RNA at high yield. The obtained RNA sample is of high purity and has defined 5′-monophosphate and 3′-hydroxyl termini. Through the RNase H-catalyzed cleavage of a tandem transcript, the crude RNA product is of high purity which facilitates purification significantly.The template design is an essential step in the high yield of this protocol. Several different methods have been proposed, and advantages are discussed below. One of the methods described in the literature is rolling circle transcription to generate tandem repeats for RNase H cleavage in a few instances. The method described by Wang et al.  is analoOur strategy instead relies on well-established plasmid templates  that benWe explored the use of ssDNA template encoding a lower number of repeats (2–5), which could be purchased cheaper and faster than an entire plasmid. However, we found that ssDNA strands complementary to the RNA target can lead to the complete degradation of the RNA in the presence of RNase H. This issue does not arise when using dsDNA templates. E.coli NEB 5-alpha (NEB) and been purified using a Maxiprep purification kit (Machery-Nagel NucleoBond Xtra Maxi and QIAGEN Plasmid Maxi Kit). All plasmids have been linearized using BamHI (NEB) in the supplied reaction buffers at 37 °C for 1 h at a plasmid concentration of 20 ng/µL up to 500 µL total volume. To ensure complete linearization, reactions have been loaded on a 1% agarose gel in 0.5X TBE buffer .pUC19 plasmids have been purchased from GenScript with a solid-phase synthesized fragment inserted using PstI and SalI restriction site  and 8 M urea, acrylamide:bisacrylamide 19:1 . Sample preparation: Typically, 1 µL sample was denatured in 9 µL loading solution  and heated to 95 °C for 2 min. Gel specifics: 12 × 8 cm, Mini-Protean , run in 1X TBE buffer at 350 V for 1 h. Of the prepared loading solution of 10 µL, 1 µL was loaded. Small gels were post-stained with SYBR Gold (Invitrogen) and at 460 nm wavelength. Agarose gels have been prepared in 0.5X TBE and 1% agarose concentration and run in 0.5X TBE buffer for 150 V for 20 min. Transcription reactions of construct 2 have been optimized in a small scale of 50 µl before large scale reactions. The same final conditions used for all constructs are shown in Cleavage reactions from plasmid tandem transcription have been optimized for construct 2 in 20 µL volume, varying enzyme and cleavage guide concentration, as well as reaction time and temperature. The best conditions found have been used to cleave the large scale tandem transcription reaction in the same reaction tube. E.coli RNase H has been added : 100 units/mL final concentration), as well as inorganic pyrophosphatase (IPPase) to 0.1 mg/mL. The cleavage reaction has been checked for completion on a 20% denaturing PAGE. Reactions took typically between 3 and 6 h for completion at 37 °C. In case of incomplete cleavage reactions, microwave annealing was repeated, and more RNase H was added. A chimeric cleavage guide usually consists of 4 central DNA nucleotides flanked by 4 2′-OMe modified nucleotides on each side. The sequences for each cleavage guide used and further discussion can be found in the For simultaneous cleavage and transcription reactions, the reactions mixtures were prepared with the same volumes and concentrations as described above. Enzymes were added in the order: RNase H, IPPase, T7RNAP. Simultaneous large scale reactions were left for 16 h at 37 °C.The reaction was stopped by adding an excess of EDTA at 100 mM and pH 6.5  of 100 mM). Solutions were concentrated if necessary, and filtered before injection in HPLC with 22 µm PTFE or acetate cellulose syringe filters. TM PA200 column of 22 × 250 mm by Thermo Scientific has been used . Running buffers were A: 20 mM sodium acetate, 20 mM sodium perchlorate, 10% acetonitrile, pH 6.5; B: 20 mM sodium acetate 600 mM sodium perchlorate, 10% acetonitrile, pH 6.5. Buffers have been filtered and degassed using 0.2 µm bottle top filters. The sequence was run at 5.5 mL/min flow rate and 75 °C to provide denaturing conditions. Gradient settings were: 0–7 min: 0% B; 7–16 min: 0–20% B; 16–46 min: Elution, typically 20–30% B; 46–62 min: 100% B; 62–73 min: 0% B. Specific elution gradients for constructs can be found in construct specification in the For ion-exchange purification, a UltiMate 3000 UHPLC system (Thermo Scientific) with a DNAPACd is the path length and https://eu.idtdna.com/calc/analyzer/). RNA concentrations have been determined using an Evolution 260 Bio UV-Visible Spectrophotometer . The obtained absorbance value at 260 nm has been used to calculate the RNA concentration according to the Lambert-Beer lawThe yield As an example, construct 2 contains nine uridine residues, so the absolute UTP concentration was divided by 9. For the obtained product of 760 nmol from a 10 mL reaction, this givesRNA yields were quantified by comparison to an external HPLC standard curve with known amounts of construct 2. Standard curve samples of 1 mg, 0.5 mg, 0.25 mg, 0.125 mg and 0.062 mg  were prepared, and the concentration of the standard curve samples was determined with UV spectroscopy as described above.2 value of 0.9997 (All standard curve samples were brought to 1 mL with MilliQ-purified water and injected into HPLC as described in 4.5 with an elution gradient of buffer B of 20–30% over 30 min. The area under the curve (AUC) was calculated and used to create a standard curve which gave a slope of 30.8 nmol/mAU and an Rf 0.9997 . To extract the molar amount of an injected target analyte sample Short RNA molecules are increasingly important as tools in basic research for downregulation or gene manipulation and are increasingly researched in structural biology to understand regulatory RNA mechanism. Through CRISPR/Cas and RNA interference, also the pharmaceutical industry requires large amounts of short RNAs with defined sequence and length. The protocol that we present here can provide both large amounts and high purity of especially these short RNAs. This addresses the needs of both basic research and pharmaceutical application for non-modified RNAs.Described issues from 5′-triphosphate and double-stranded RNA side products are avoided as the RNA produced reliably carries a 5′-monophosphate and are single-stranded.We expect that our method can make short RNAs more accessible to the scientific community, due to cheaper and simpler production and their results and application more valuable, due to the high reliability of the sample integrity.A provisional patent application was filed at the UK patent office in March 2019. No decision has been taken to this point.