The assignment of specific patterns of gene expression to specific cells in a complex tissue facilitates the connection between genotype and phenotype. Single-cell sequencing of whole tissues produces single-cell transcript resolution but lacks the spatial information of the derivation of each cell, whereas techniques such as multiplex FISH localize transcripts to specific cells in a tissue but require a priori information of the target transcripts to examine. Laser dissection of tissues followed by transcriptome analysis is an efficient and cost-effective technique that provides both unbiased gene expression discovery together with spatial information. Here, we detail a laser dissection protocol for total RNA extraction from butterfly larval and pupal wing tissues, without the need of paraffin embedding or the use of a microtome, that could be useful to researchers interested in the transcriptome of specific areas of the wing during development. This protocol can bypass difficulties in extracting high quality RNA from thick fixed tissues for sequencing applications. Recent advances in spatial transcriptomics approaches have paved a new frontier in our understanding of tissue and organ development. The study of spatial transcriptomics using multiplex fluorescent in situ hybridization (multiplex-FISH) based techniques such as MERFISH , seqFISHLaser capture microdissection-mediated RNA sequencing (LCM-seq) is an alternative/complementary spatial transcriptomics method to the methods described above ,14,15,16The technique involves fixing biological tissues using a non-crosslinking fixative such as alcohol and/or acetone  on a memHere, we describe a laser-capture microdissection protocol for developing butterfly wing tissue. We show how to fix and stain the butterfly wing tissue, perform the laser microdissection, isolate the microsections using fine tweezers, extract RNA from the isolated tissue, and perform RNA quality analysis. The butterfly wings because of their thickness (above 40 µm) are difficult to capture using the upward force of UV lasers and hence we used fine tweezers to isolate the microtissues from the dissected samples. We successfully applied this technique for the isolation of RNAs from the intervein sectors of larval wing tissues, from the larval eyespot centers, and from the pupal eyespot rings with RIN (RNA integrity number) values above 8.0. This technique will be helpful to other researchers who are interested in similar microsections of their tissues, who are working on similar thick tissue types, and who have difficulty in the extraction of high-quality RNA from PEN membrane-bound and ethanol-/acetone-fixed tissues.The major steps involved in the microdissection and isolation of RNA from laser micro-dissected wing tissues include: (1) Tissue fixation using ethanol and acetone and transfer onto a PEN membrane slide; (2) Wing staining using a cell staining solution—this allows better visualization of transparent tissues; (3) Wing microdissections using a laser microbeam microscope; (4) Isolation of the micro-dissected samples using fine tweezers; and (5) Extraction of RNA from the microsections.Microcentrifuge tubes 1.5 mL PCR tubes 200 µL PEN membrane slides Fine straight tweezers Stainless steel beads, 0.5 mm Filter Pipette tips Ice bucket with closed lid Flat spatula Zirconium beads, 0.1 mm LCM Adhesive Cap 500 Histogene staining solution Ethanol (Sigma Aldrich (Merck), Burlington, MA, USA; Cat. No. E7023-1L)Acetone (Sigma Aldrich (Merck), Burlington, MA, USA; Cat. No. 179124-1L)RNaseZap RNase Decontamination Solution UltraPure DNase/RNase-Free Distilled Water Proteinase K Qiagen RNA isolation kit (RNeasy Plus Mini Kit (250); Qiagen, Hilden, Germany.; Cat. No. 74136)Agarose molecular grade Trizma base (Sigma-Aldrich (Merck), Burlington, MA, USA; Cat. No. T1503-500G)EDTA Sodium Dodecyl Sulfate , Burlington, MA, USA; Cat. No. 151-21-3)SYBRSafe DNA ladder RNA Gel Loading Dye Zeiss Stemi 305 stereo microscope Zeiss laser microdissection microscope Gel electrophoresis system Gel documentation system Nanodrop ND-1000 Spectrophotometer Homogenizer Dissect the butterfly larval and pupal wings based on the protocol described in  and tranDehydrate the wings by adding a gradual concentration of 50, 75, and 100% ice-chilled alcohol mixed with PBS. Alternatively, dissected wings can be transferred to a PEN membrane slide and dehydrated on the slide by adding a gradual concentration of 50, 75, and 100% ice-chilled alcohol.  PAUSE STEP Dehydrated wings can be stored at −80 °C for up to 6 months.3.After dehydration, move the wings to a PEN membrane slide. For the larval wings, use a 1000 µL pipette to transfer the wings and for the pupal wings use a flat spatula. The wings once dry will stick to the membrane of the slide.4.Fix the wings twice with 100% ice-chilled acetone using a 1000 µL pipette.  CRITICAL STEP Keep the PEN membrane slide in an ice box as much as possible to avoid RNA degradation.After wing fixation use Histogene staining solution to stain the wings. Gently add a few drops of the staining solution on top of the wings and leave for 10–40 s, until a purple color is seen on the wing.Wash the wings with 100% EtOH using a 1000 µl pipette three times and let the wings dry on the slide.Move the slide to a 50 mL falcon tube.  PAUSE STEP Wings can be stored inside the falcon tube for over 6 months in a −80 °C freezer.Move the slide inside an ice box (Coleman ice bucket with crushed ice) to the laser microdissection microscope room.Turn on the microscope, turn on the PALMRobo 4.8 pro software, and mount the slide for dissection A,B.To mount the slide and the adhesive cap (LCM Adhesive caps 500), click on the button indicated by the red and yellow arrow in PALMRobo 4.8 pro software indicated in Note: The adhesive caps are used only to allow the microscope to operate. The butterfly wing microsections are thick and hence very difficult to capture using the adhesive caps.Use the settings as mentioned in Use the tools highlighted inside the red box in After the microdissection, transfer the slides back to the ice box and bring back to lab for isolation of the microsections and extraction of RNA.  PAUSE STEP Wings can be stored at this stage at −80 °C for up to 6 months.1. Move the PEN membrane slide with the microdissected samples on an ice-filled Petri plate under a normal dissection microscope (Zeiss Stemi 305).2. Prepare 200 µL tubes with 20 µL of molecular grade water on ice for the transfer of the microsections.3. Using a fine tweezer carefully pick up the microsections and move them to the respective 200 µL tubes.4. After all the sections are collected, move to RNA isolation.  PAUSE STEP Wings can be stored at this stage at −80 °C for up to 6 months.Add 100 µL of LCM lysis buffer (1% SDS in Tris-EDTA) and 10 µL of proteinase K to the 200 µL tubes with the microsections.Incubate the tubes at 55 °C in a water bath, vortex every 3 min, for a total of 9 min. At this step the microsections will partly dissolve in the LCM lysis buffer.After this step, proceed to RNA extraction using a kit of choice.Transfer the 130 µL solution from the previous step to a 1.5 mL microcentrifuge tube.Add 350 µL of RLT plus buffer and a small amount of 0.1 mm zirconium beads.Place the tube in a homogenizer and homogenize for 3 min at the maximum rate.Remove the tubes and centrifuge at 14,000 rpm at 4 °C for 3 min.Transfer the supernatant to a gDNA eliminator spin column and centrifuge at 14,000 rpm for 30 s.Discard the column and to the flow-through add 350 µL 70% EtOH. Mix well and transfer to RNeasy spin column.Centrifuge at 14,000 rpm for 30 s and discard the flow-through.Add 700 µL of RW1 buffer to the column and centrifuge at 14,000 rpm for 30 s. Discard the flow-through.Add 500 µL of RPE buffer to the column and centrifuge at 14,000 rpm for 30 s. Discard the flow-through.Add 500 µL of RPE buffer to the column and centrifuge at 14,000 rpm for 2 min. Discard the flow-through and transfer the column to a 1.5 mL microcentrifuge tube.Add 20 µL molecular grade water to the column and let it sit for 3 min before centrifugation.Centrifuge at 14,000 rpm for 1 min. Discard the column and measure the concentration of the RNA in a nanodrop machine.Prepare a 2% agarose gel by mixing 1 gm of agarose to 50 mL 1X TAE buffer.Mix 3 µL of RNA loading dye and 3 µL of RNA sample and load it in one of the agarose gel wells. Add ladder in the adjacent well.Run the gel for 30 min at 120 V and 400 mA.Image the gel in a gel documentation system. The RNA should appear as a clear band in the gel.After Histogene dye staining, certain regions of the wing with denser cell populations will be visible. These include the eyespot centers, the intervein cells, and the wing margin A,D,G. ThAfter the RNA extraction, the RNA sample appears as a clear band in an agarose gel K and hasThe concentration of RNA from 30 larval wings is usually above 1000 ng for tissue from each wing sector  for producing thin slices of tissues which can then be used for capturing tissue sections using an LCM microscope ,34,39. TThe integration of LCM data with that from single cell, multiplex FISH, and spatial sequencing will help address the limitations of each technique, to produce more robust spatial transcriptomes.In a 50 mL sterile falcon tube add 0.5 mL of 1M Tris Hcl (pH 8.0) and 0.1 mL 0.5M EDTA (pH 8.0).2O in a beaker. Mix with gentle stirring.Prepare 10% SDS by mixing 10 g of SDS in 90 mL of dH2O to the falcon tube till 50 mL and mix properly by shaking.Add 5 mL of the 10% SDS and dHAdd 242 g of Trizma base and 18.61 g of EDTA in a 1-L bottle.2O and add 57.1 mL glacial acetic acid.Add 500 mL dHAdjust the volume to 1 L and autoclave.


Most pandemics of recent decades can be traced to RNA viruses, including HIV, SARS, influenza, dengue, Zika, and SARS-CoV-2. These RNA viruses impose considerable social and economic burdens on our society, resulting in a high number of deaths and high treatment costs. As these RNA viruses utilize an RNA genome, which is important for different stages of the viral life cycle, including replication, translation, and packaging, studying how the genome folds is important to understand virus function. In this review, we summarize recent advances in computational and high-throughput RNA structure-mapping approaches and their use in understanding structures within RNA virus genomes. In particular, we focus on the genome structures of the dengue, Zika, and SARS-CoV-2 viruses due to recent significant outbreaks of these viruses around the world. The recent COVID-19 pandemic once again highlights the social and economic impact of RNA viruses. RNA viruses contain an RNA genome that is translated into viral proteins and replicated to create more copies for packaging and growth. Important human RNA viruses include coronaviruses , flaviviruses ), influenza viruses, human immunodeficiency virus (HIV), enteroviruses, and alphaviruses. Collectively, these viruses are responsible for sizable annual healthcare expenditure, loss of productivity, and, most significantly, lowered quality of life and increased mortality . UnderstTraditionally, most therapeutics against RNA viruses target either the viral proteins or key host receptors/host interacting proteins inside cells ,5. TheseIn this review, we summarize recent efforts in understanding the structure and function of RNA viruses, with a focus on DENV/ZIKV and SARS-CoV-2, as these were involved in recent pandemics. DENV is responsible for approximately 390 million infections (of which 100 million are symptomatic) and 36,000 deaths per year, with approximately 70% of the disease burden residing in Asia . The aveAs the SARS-CoV-2 pandemic is still in progress, estimations of the total burden of SARS-CoV-2 are by necessity preliminary and subject to later revision. As of July 2022, there have been over 500 million documented SARS-CoV-2 infections resulting in over 6 million deaths . In addiHere, we describe advances in computational and experimental RNA structure-mapping methods that have greatly facilitated our ability to identify new, functionally important RNA structures along viral genomes. We also discuss potential gaps that need to be filled for viral RNA to be made into viable drug targets.While RNA structures have long been known to be functionally important in viral genomes, much of what we previously knew about RNA structures was serendipitous. Such functional structures include the internal ribosomal entry site (IRES) on hepatitis C virus (HCV), enteroviruses, and polioviruses ,14,15,16The difficulty of determining RNA structures experimentally prompted the widespread use of computational predictions using sequence information. These include thermodynamics-, simulation-, and AI-based approaches to predicting RNA structure . The moshttps://www.viprbrc.org) (accessed on 23 May 2022) [https://hivdb.stanford.edu/) (accessed on 23 May 2022), which contains >20,000 HIV genomes.When an RNA sequence contains many known homologs or shows strong structural conservation , informaay 2022)  is curreThe information from viral sequences can also be used to study mutation landscapes. When a mutation happens on a base that is paired and the pairing is functionally important, there will typically be evolutionary pressure to incur additional mutations that restore the base-pairing over time. The existence of such mutations is called covariation. Multiple sequence alignments are used to compute sequence covariation at a single-nucleotide resolution to identify these covaried and presumably functionally important structures. This multiple sequence alignment is used by algorithms such as R-scape to support the presence of conserved RNA secondary structure elements . In DENVThe difficulty in obtaining structural information for long RNA sequences was considerably reduced in 2009 when the entire HIV-1 genome was structurally mapped experimentally by SHAPE chemical probing . SecondaData from a high-throughput RNA structure-probing experiment using SHAPE or dimethyl sulphate (DMS) can be in the form of either the number of reverse transcriptase (RT) drop-offs or the frequency of mutation errors along each base of an RNA . CountinTo identify functional structures along viral genomes, regions that are highly structured (low SHAPE reactivity) and contain low Shannon entropy ,46 whic. Using aWith increased structural mapping of RNA viruses with SHAPE-MaP and DMS-MaPseq, single-molecule analysis of the mutational profile of each read along the virus genome has shown that viral RNA structures are more complex than previously thought and can take on alternative structures. Although alternative structures have been observed from proximity ligation sequencing experiments , as muchBox 1High-throughput experimental techniques such as SHAPE are able to profile the RNA at single-nucleotide resolution. However, they can only provide a reactivity that associates each nucleotide with the propensity to be in single- or double-stranded conformation. It has recently been shown that experimental data can be used as soft constraints inside thermodynamics-based algorithms ,54. AnotWhile hard constraints force the algorithms to work through rigidly-imposed structures, soft constraints guide the algorithms by providing more degrees of freedom during folding. Hard constraints assign a specific conformation to a nucleotide and thus reduce the degrees of freedom of the search. On the other hand, soft constraints work as guidelines, using the experiments as a continuous signal, where a weak signal allows more degrees of freedom to the algorithm without imposing a structure. Due to their flexibility, soft constraints are widely used and accepted by the majority of the algorithms. RNAstructure and RNAfold both accept DMS and SHAPE data as soft constraints ,53. EspeTo work as soft constraints, SHAPE reactivities are converted into pseudo-energy contributions . A commoThe integration of experimental profiles and predictive algorithms was successfully applied to almost every model of secondary structure for ssRNA viruses, including HIV, ZIKV, DENV, and SARS-CoV-2 ,35,49. MWhile the structures of RNA viruses have been studied in the past decade, the need to understand RNA virus structure and function has been recently heightened due to two pandemics . UnderstDengue/Zika viruses belong to the Flaviviridae family of viruses, which includes the West Nile, HCV, and yellow fever viruses, all of which are clinically important to our society. Prior to the 2015 Zika outbreak, most attention had been focused on DENV, its close relative. DENV infects >390 million people around the world each year, imposing a high social and economic burden . AlthougUsing a combination of high-throughput structure-probing strategies, the genome organizations of DENV and ZIKV in virions and inside infected cells were probed, and it was observed that many genome interactions are associated with virus growth . Using SThe COVID-19 pandemic has brought our attention back to the coronaviruses. Following the SARS outbreak in Hong Kong in 2002–2004, there has been a coronavirus outbreak about every decade. With a genome size of 26–32 kb, coronaviruses are some of the largest RNA viruses that exist . RNA strThese comprehensive structural analyses reveal different aspects of the SARS-CoV-2 genome and biology, including its ability to form many short- and long-range RNA interactions, higher-order RNA conformations, and alternative structures. The SARS-CoV-2 genome also interacts extensively with host RNA-binding proteins for infectivity ,68. AddiRecent advances in computational modeling and high-throughput experimental structure-probing have greatly increased our understanding of the diversity and prevalence of structures along RNA virus genomes. In combination with biochemical probing, high-throughput sequencing, and structural modeling, we can now map RNA structures along the viral genome, visualize what they potentially look like, and identify potential functional structures that are conserved through evolution. While much of the structural information exists as an aggregate across all copies of the detected RNA genomes, recent developments in single-molecule structure clustering have increased our resolution of RNA structures by identifying alternative structures along the genome. Used together with mutagenesis and functional assays, we can now identify RNA structures that play important roles during the virus lifecycle.While current technologies provide a snapshot of what the RNA virus genome looks like at a given point in time, viral genomes are constantly going through different stages of the viral lifecycle, such as replication, translation, and packaging. As such, structure mapping of viral genomes can only provide an aggregate picture of structures across all stages of its lifecycle. Further studies on viral genome conformations at different stages of the virus lifecycle will facilitate our understanding of RNA structures that are specific to viral replication, translation, and packaging. Additional information on the location of heterogenous RNA structures, such as in HIV-1 and SARS-CoV-2, and, in particular, the identification of the functional alternative structures, will greatly facilitate our understanding of RNA structure and function ,52,71.Through comprehensive structure probing of virus genomes, we can now identify potential functional structures for therapeutic targeting by small RNAs (including siRNAs and antisense oligos) which preferentially target single-stranded regions along the virus genomes. Additionally, recent developments in RNA drug targeting have demonstrated RNA structures to be effectively targeted by small molecules due to their ability to bind to compounds with high specificity and affinity . As such


Antiviral agents are needed for the treatment of SARS-CoV-2 infections and to control other coronavirus outbreaks that may occur in the future. Here we report the identification and characterization of RNA-binding compounds that inhibit SARS-CoV-2 replication. The compounds were detected by screening a small library of antiviral compounds previously shown to bind HIV-1 or HCV RNA elements with a live-virus cellular assay detecting inhibition of SARS-CoV-2 replication. These experiments allowed detection of eight compounds with promising anti-SARS-CoV-2 activity in the sub-micromolar to micromolar range and wide selectivity indexes. Examination of the mechanism of action of three selected hit compounds excluded action on the entry or egress stages of the virus replication cycle and confirmed recognition by two of the molecules of conserved RNA elements of the SARS-CoV-2 genome, including the highly conserved S2m hairpin located in the 3’-untranslated region of the virus. While further studies are needed to clarify the mechanism of action responsible for antiviral activity, these results facilitate the discovery of RNA-targeted antivirals and provide new chemical scaffolds for developing therapeutic agents against coronaviruses.  The current COVID-19 pandemic has shown the need to develop effective measures to prevent and treat infections by SARS-CoV-2 (SCoV2) and other coronavirus outbreaks that will likely occur in the future. Although effective vaccines have been developed against SCoV2, a large part of the world population remains unvaccinated, and the current antiviral treatments rely on small-molecule compounds targeting viral enzymes or monoclonal antibodies inhibiting virus entry [Among the possible mechanisms for blocking the replication cycle of RNA viruses, strategies based on targeting structured RNA elements have not been exploited to the same extent as other direct-action approaches, mainly due to the challenges associated with specific RNA recognition . HoweverIn the context of the ongoing pandemic, we carried out a phenotypic study to rapidly detect possible RNA-binding molecules with antiviral action . This waIn an attempt to identify new SCoV2 inhibitors with a mechanism of action based on RNA-binding, a small library of 32 compounds targeted towards human immunodeficiency virus type-1 (HIV-1) or hepatitis C virus (HCV) RNA structures was assembled . The HIV50 values below 10 μM  having anti-SCoV2 ECow 10 μM . Ignorin50 values below 10 μM in both cell lines together with a selectivity index  above 5 in at least 1 cellular type. These compounds comprised one drug-like molecule from the HCV IRES subset and seven molecules from the HIV-1 RRE subset, including three clinically used drugs and four drug-like molecules  exhibited EColecules .50 values, selectivity indexes, and repurposing potential, three compounds were selected for further examination: the FDA-approved HIV-1 RRE inhibitor clomiphene citrate, an additional trityl-imidazole RRE inhibitor (hereafter identified as trim), and a piperidinyl-quinazolinone HCV IRES ligand (qz2)  A. These 7 and 71 A. Infect7 and 71 B. No losIn order to narrow down the location of the block in viral replication caused by the selected compounds in the virus life cycle, we carried out cell infection assays adding the inhibitor at different times during the SCoV2 replication cycle C. In thiIn order to evaluate whether the selected compounds could have a mechanism of action based on RNA inhibition, we used NMR spectroscopy experiments to assess binding to a collection of six conserved structural elements of the SCoV2 RNA genome. The sequences included hairpins SL2 and SL3 of the 5’ untranslated region (UTR) (identified as 5_SL2+3), the programmed ribosomal frameshift full-length region (PRF) located between open reading frames ORF1a and ORF1b, a smaller PRF subdomain (ATTL), a segment of open reading frame 7b (ORF7b), and the SL1 and SL2 stem–loops (3_SL1+2) and S2m hairpin (3_S2m) of the 3’UTR . The 5_S1H NMR experiments to analyze the interaction of the selected compounds with each of the six RNA elements specified above, including one-dimensional, Carr–Purcell–Meiboom–Gill (CPMG) and waterLOGSY (wLOGSY) experiments. These assays detect changes in the 1H signals of the ligand upon RNA association , CPMG and wLOGSY perturbations induced by each RNA element . Conside signals . In contThe perturbation data also provided relevant information about the ligand components exhibiting enhanced RNA interactions. For example, of the two stereoisomers present in clomiphene citrate, the cis isomer bound RNA with stronger affinity than the trans form . In qz2,1H NMR experiments to examine the association of trim, clomiphene, and qz2 to the 5_SL2+3 and 3_S2m RNA elements, together with the attenuator hairpin of the PRF  of 12.5 μM. The 3_S2m Kd value doubled for clomiphene citrate, 33.2 μM, whereas qz2 exhibited lower affinity for this RNA element  or qz2 (>50 μM) in good agreement with the NMR analyses  but well above the EC50 in human 293T-ACE2 cells (0.33 μM). This means that association with the 3’UTR S2m stem–loop is not sufficient to explain the antiviral mechanism of this molecule. We have explored a limited fraction of the structural RNA elements present in the SCoV2 genome, but while it is possible that trim binds with enhanced affinity to other viral elements, we cannot presently discard other antiviral mechanisms. In this regard, the association of this molecule to the 5_SL2+3 double hairpin, essential for sgRNA synthesis [The K50 of this compound, 4.4 μM, was close to its HIV-1 RNA-binding Kd value (12.4 μM for RRE subdomain IIB), and RT-PCR assays supported an antiviral mechanism based on inhibition of Rev function in addition to transcriptional blockage [The SCoV2 inhibitory action of clomiphene citrate has been previously proposed to be related to sigma receptor association  or to anChemical optimization of the trityl-imidazole hit is currently in progress in our laboratories, with the aim of improving antiviral activity and selectivity index, as well as pharmacokinetic properties. In this regard, in vivo antiviral experiments will be important to validate the potential of these compounds as antiviral agents.2O at the same concentration. Compounds aimed for NMR analyses were dissolved in DMSO-d6  at 5 mM concentration.The source of the 32 HIV-1 and HCV RNA-binding compounds is specified in 2. Two hours before infection with SARS-CoV-2 USA-WA1/2020, the medium was replaced with 100 µL of viral growth medium (DMEM 2% FBS) containing the indicated compounds at a concentration fifty percent greater than those indicated, together with a DMSO control. Experiments were then transferred into the Biosafety Level 3 facility, and 100 PFU (MOI = 0.025) for VeroE6 infections and 1000 PFU (MOI = 0.25) for 293T-ACE2 infections were added in 50 µL of viral growth media, bringing the final compound concentrations to those indicated. Plates were incubated for two days at 37 °C. Supernatants were then removed, and cells were fixed with 4% formaldehyde for one day prior to being removed from the Biosafety Level 3 facility. The cells were then immunostained for the viral N protein with an in-house mAb 1C7 provided by Dr. Thomas Moran (Thomas.Moran@mssm.edu), with a DAPI counterstain [50 and EC90 for each experiment were determined using Prism software . Cytotoxicity was also measured using the MTT assay , according to the manufacturer’s instructions. Cytotoxicity experiments were performed in uninfected cells with identical compound dilutions and concurrently with the antiviral assay. Infectious SCoV2 in supernatants was measured using a TCID50 assay. Briefly, infectious supernatants were collected at 48 h post-infection in the absence and presence of two compound concentrations and frozen at −80 °C. Infectious titers were quantified by limiting dilution titration using Vero E6 cells as previously described [Two thousand Vero E6 or 293T-ACE2 cells were seeded into 96-well plates in cell growth media (DMEM 10% FBS) and incubated for one day at 37 °C and 5% COterstain . Infecteescribed . All assTwo thousand 293T-ACE2 cells were seeded in 96-well plates. One day later, cells were infected with SCoV2 USA-WA1/2020 at an MOI of 2. DMSO vehicle or indicated compounds were added at different time points relative to infection, according to the timeline and concentrations indicated in 2.The following sequences of the SCoV2 RNA genome were prepared by T7-polymerase in vitro transcription for NMR analyses: SL2 and SL3 hairpins of the 5’UTR , programmed ribosomal frameshift (PRF) region , attenuator and slippage region of the PRF region , attenuator hairpin of the PRF region , ORF7b segment , SL1 and SL2 hairpins of the 3’UTR , and S2m hairpin of the 3’UTR  . The DNAE. coli MRE 600 (identified as tRNAmix) used to evaluate specificity was obtained from Roche .The 3_S2m-23fl RNA oligonucleotide used in fluorescence intensity experiments was purchased HPLC-purified from Integrated DNA Technologies . This oligonucleotide contained a fluorescein probe linked to the apical loop nt U23 and was identical in sequence to the unlabeled 3_S2m molecule used in NMR experiments . The mixNMR spectra were acquired in Avance III 500 MHz and cryoprobe-equipped Avance II 600 MHz spectrometers , and analyzed using Topspin, version 3.6.1  and NMRFAM-Sparky, version 1.414   software1H experiments [2, and 10% D2O. RNA–ligand molar ratios of 1:50 and 1:100 were explored . Clomiphene citrate was studied at a 1:100 ratio to avoid precipitation observed in the 1:50 condition. In all cases, either N-methyl-valine  [One-dimensional, relaxation-edited Carr–Purcell–Meiboom–Gill (CPMG) and water-ligand observed by gradient spectroscopy (wLOGSY) eriments  were useMO, USA)  or the cMO, USA) . wLOGSY MO, USA) ,38. All All ligand signals were individually analyzed. For clomiphene citrate, the signals corresponding to cis and trans forms were identified by comparing the spectrum of clomiphene citrate with those of the individual stereoisomers. In CPMG experiments, the binding of the compounds to the different RNA sequences was quantified as 100 minus the percentage of ligand signal area in the +RNA CPMG spectrum relative to the corresponding signal area in the -RNA CPMG spectrum. In wLOGSY experiments, binding was quantified with the LOGSY factor, or % of ligand signal in the difference spectrum between the +RNA and –RNA wLOGSY spectra, relative to the corresponding signal in the one-dimensional -RNA reference spectrum . In one-2O. The 3_S2m titrations were duplicated at 25 °C using 120 μM RNA samples and additionally acquiring NOESY spectra (250 ms mixing time) at 1:0 and 1:4 ratios. For this system, the chemical shift perturbation analyses included 63 H1’, H2’, and aromatic 3_S2m resonances. The isolated 3_S2m hairpin was studied at two different temperatures (25 and 35 °C) using 120 and 500 μM RNA samples and similar TOCSY and NOESY (120 and 250 ms mixing times) experiments. The assignment of 3_S2m non-exchangeable 1H resonances was based on the analysis of these spectra, as well as on previously published assignments of 3_S2m exchangeable protons [The interactions of trim, clomiphene citrate, and qz2 with 3_S2m, 5_SL2+3, and ATTH RNA molecules were monitored with one- and two-dimensional  experiments at increasing RNA–ligand molar ratios of 1:0, 1:1, 1:2 and 1:4. The RNA samples were previously diafiltrated into an aqueous solution containing 25 mM potassium phosphate (pH 6.2), 50 mM KCl and 0.1 mM EDTA, and the titration experiments were carried out at 27 °C using 50 μM RNA samples in 100% D protons . The relmix. The equilibrium dissociation constants Kd were obtained by fitting the dose–response curves to a two-state binding model [These experiments measured the association of clomiphene citrate, trim, and qz2 with a 3_S2m-23fl RNA hairpin labeled with fluorescein at extrahelical loop nucleotide U23 B and werng model  with PriA three-dimensional model of a 3_S2m-trim complex was built starting from a 3_S2m FARFAR2 model structure previously generated  using seA patent application, PCT/EP2022/053938, partially resulted from the work reported in this manuscript.By screening a small library of HIV and HCV RNA-binding compounds with a dose–response live-SCoV2 assay, we have identified eight FDA-approved and drug-like molecules with significant antiviral activities and selectivity indexes. Three of the screening hits had substantial anti-SCoV2 activity and associated with functional SCoV2 RNA elements with different degrees of selectivity. While further studies will be needed to determine the antiviral mechanism of action of these compounds, these results open the door to the development of new anti-ScoV2 agents with a mode of action different from those used by typical direct-action agents.


Body fluids/tissue identification (BFID) is an essential procedure in forensic practice, and RNA profiling has become one of the most important methods. Small non-coding RNAs, being expressed in high copy numbers and resistant to degradation, have great potential in BFID but have not been comprehensively characterized in common forensic stains. In this study, the miRNA, piRNA, snoRNA, and snRNA were sequenced in 30 forensic relevant samples  using the BGI platform. Based on small RNA profiles, relative specific markers (RSM) and absolute specific markers (ASM) were defined, which can be used to identify a specific body fluid/tissue out of two or six, respectively. A total of 5204 small RNAs were discovered including 1394 miRNAs (including 236 novel miRNA), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs. RSMs for 15 pairwise body fluid/tissue groups were discovered by differential RNA analysis. In addition, 90 ASMs that were specifically expressed in a certain type of body fluid/tissue were screened, among them, snoRNAs were reported first in forensic genetics. In brief, our study deepened the understanding of small RNA profiles in forensic stains and offered potential BFID markers that can be applied in different forensic scenarios. Body fluids  and skin tissue are frequently encountered biological materials at a crime scene. Therefore, the identification of the origin of different body fluids/tissue is indispensable for reconstructing the offense scene and providing scientific clues or evidence. Usually, forensic body fluid identification (BFID) is an essential forensic step besides DNA-based individual identification . The traThe miRNA are small (~22 nt) non-coding single-stranded RNAs that have tissue-specific expression and are also present in various extracellular body fluids such as blood, saliva, urine, and breast milk . It exisThe wide use of massively parallel sequencing (MPS) has greatly advanced the discovery of small noncoding RNAs (sncRNAs). In addition to miRNA, the PIWI-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and small nuclear RNA (snRNA) also belong to sncRNA (<300 nt in length) , and havAlthough plenty of studies have been conducted to investigate sncRNAs for BFID, most were focused on miRNA and a comprehensive profile of the sncRNAs, which targets different types of sncRNAs such as piRNA, snoRNA, and snRNA, are rare. Nevertheless, a comprehensive characterization of the RNA profile is the first step in selecting markers for BFID. At present, sncRNAs markers discovered through different BFID studies have often been inconsistent ,26,27. HFirst, five kinds of forensically related fresh body fluids and skin tissue were collected from healthy individuals. Informed consent was obtained from all of the volunteers. Five people were sampled for each type of sample. Semen (SE) and saliva (SA) were collected in 5 mL sterile tubes and put in a −80 °C refrigerator quickly after liquid nitrogen freezing. Menstrual blood  and vaginal secretion (VS) were collected with a sterile flocking swab . The skin (SK) was collected by rubbing the left forearm with a sterile water-wetted flocking swab. All swabs were put in the preservation solution (Huachenyang) temporarily, and then in a −80 °C refrigerator as soon as possible. Venous blood (VB) was collected from elbow veins in a 5 mL EDTA anticoagulant tube. To decrease the influence of heme from red blood cells on subsequent sequencing, human lymphocyte separation liquid  was used to separate the leukocyte from venous blood, which was then stored in TRIzol reagent  and put in a −80 °C refrigerator. The information of all samples is shown in The total RNA was extracted from five body fluids and skin tissue using Trizol  according to the manufacturer’s instructions. RNA integrity number (RIN) and quantity were determined using Agilent RNA 6000 Pico Reagents with Agilent 2100 Bioanalyzer . The RIN value (1–10) is an index to determine the degradation degree of RNA, and the smaller the value, the more severe the degradation. Usually, the RIN of eight is recommended for MPS library construction. A NanoDrop (Thermo Fisher Scientific) was used to detect the inorganic ions or polycarbonate contamination.The RNA library was prepared with 200 ng~1 μg of input RNAs. To extract small RNAs, purification was performed using electrophoretic separation on a 15% denaturing urea polyacrylamide gel electrophoresis (PAGE) gel. The 18–30 nt gel bands that corresponded to small RNAs were purified. Then, we ligated the small RNAs to adenylated 3′ adapters annealed to unique molecular identifiers (UMI) , followed by the ligation of 5′adapters. After transcribing the adapter-ligated small RNAs into cDNA by SuperScript II Reverse Transcriptase (Invitrogen), we enriched the resulting fragments by PCR amplification with the PCR Primer Cocktail and PCR Mix . Finally, the targeted 110~130 nt PCR products were selected by agarose gel electrophoresis using a QIAquick Gel Extraction Kit . We quantified the purified libraries using real-time quantitative PCR  and qualified them by examining the distribution of the fragment sizes with an Agilent 2100 bioanalyzer. Sequencing was performed with the BGISEQ-500 platform  with the single-end (SE) mode.https://github.com/deweylab/RSEM, accessed on 23 April 2021), an accurate and user-friendly software tool for quantifying the transcript abundances from RNA-Seq data. The analysis of differential expression was performed using DEGseq2 [q-value < 0.05 and the absolute value of Log2 Ratio >1 (two folds). The reference genes were screened by ERgene using default parameters [Raw sequencing data, or raw reads, were processed with FastQC  to eliminate low-quality reads such as reads with 5′ primer contaminants or poly-A, reads without 3′ primer, and reads shorter than 18 nt. The clean reads were mapped to the reference genome (GCF_000001405.38_GRCh38.p12) and small RNA databases such as miRbase (miRNA) , piRNABa DEGseq2  with deframeters .2FC more than 1, and a q-value  less than 0.05 in the pairwise groups. Then, for the identification of ASMs, the criteria of log2FC of more than 1 when the expression was compared with any of the other five groups and a q-value less than 0.05 were applied.In our search, we defined two categories of body fluids/tissue-specific markers, the relative specific markers (RSM) and absolute specific markers (ASM). The RSM means that the markers are specific to some of the body fluids/tissue combinations. It could be used to pick out the interested body fluid/tissue within the assumed pairwise combinations and was not for the purpose of picking one fluid/tissue type out of six types of stains, while ASM is a marker that is specifically expressed in a certain type of body fluid/tissue, which is supposed to be able to help pick one fluid/tissue type out of common forensic stains (six types in this study). According to forensic practice, these two types of markers have different usage scenarios. For instance, to reconstruct the crime scene in a rape case that may involve a mixture of semen and vaginal secretion, RSM markers that could identify semen from a semen and vaginal secretion mixture rather than ASM markers that identify semen out of the six stains are enough to use. Based on the concepts, the RSMs were screened first. For the identification of RSMs, we set the criteria as the expression changes of 2-fold change (FC), in other words, logA summary of RNA concentration and RIN of the total RNA are listed in 6, which fluctuated up and down in most samples. However, some samples such as SK004, MB005, and VB001 exhibited relatively unbalanced sequencing depth among the different clean reads.After filtering, the total mean clean reads ranged from 21.11 M to 25.38 M , with anThen, all of the clean reads were aligned to the reference databases and the mapping percentages were calculated for all of the samples . As showThe accurate quantification of small RNA is important to characterize small RNA profiles. To obtain more real and accurate small RNA profiles, the adenylated 3′ adapters with UMI were ligated to the small RNAs before the reverse transcription. This is a key step to create a unique identification for each molecule, and some effects from PCR amplification bias, for example, uneven sampling of the starting template, were identified and corrected . CompareIn this study, after normalization and filtering, 1394 miRNAs (including 236 novel miRNAs), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs were detected, reaching a total of 5204 small RNAs (EXP > 0 was counted). The percentage of different RNA classes for each group is illustrated in In our study, the read count of small RNA was standardized to the EXP value for follow-up analysis. After standardization, the EXP value can be used to compare the different groups and samples directly. Based on this value, the heatmap  presenteTo further compare the expression level distribution, each RNA with an average expression of more than 1 EXP value was presented in In terms of expression level, the repeatability of the library construction and sequencing was studied by adding a technical duplication (VB006) of a blood sample (VB002). The Pearson correlation coefficient of these two samples was 0.9794. This indicates that their expression was extremely similar and they could be considered to be from the same sample. In other words, the quality of the library construction and sequencing were reliable. In all of the subsequent analyses of the VB group, VB006 was not included.The differential RNA analysis, which intuitively reflects the biological phenomenon behind it, is a common task in medicine. For forensic applications, differentially expressed RNAs are the ideal source of a specific marker for BFID in crime investigation, and the discovery of these kinds of markers are of great significance. In this study, 15 pairwise groups  were set for differential RNA analysis. The results were visualized in the volcano plots . GeneralFurthermore, 90 ASMs that were specifically expressed in a certain type of body fluid/tissue were screened and are shown in To verify the discriminating power of ASMs, we conducted hierarchical clustering analysis for all samples based on Euclidean distance. As shown in Up until now, many body fluids/tissue-specific small RNAs have been reported for the six stains, most of which are miRNA . Some poWe also noticed that most of the candidate miRNA markers for BFID did not coincide among the published studies. For instance, the miR-203, which was regarded as a SA-specific marker in previous studies ,25,52,632 FC: 1.30; q-value: 0.52) between VB and MB. Although piRNAs were abundant in the reproductive system, studies have also shown their expression in other body fluids or tissue such as menstrual blood, saliva, skin, venous blood, and vaginal secretions [Generally, piRNA is mainly expressed in semen. There were 11 new piRNA ASMs in the SE group . Surpriscretions ,66. In tIn this study, snoRNA ASMs were identified in four of the six body fluids/tissue. In particular, the number of snoRNA ASMs reached 14 and 10 for the VB and SK groups, respectively . This isThe selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression. Ideally, reference genes should be stable at the expression level in various tissues and under different developmental stages and external conditions. Thus, for forensic BFID, its stability of expression in different body fluids/tissue is fairly critical. In the present study, a total of 11 reference genes  includinIn recent years, many studies on miRNA have been conducted for body fluids and skin tissue identification, either based on RT-PCR or MPS. In our study, six types of forensically relevant biological samples were studied by performing small RNA massively parallel sequencing using the UMI library on the BGI platform. Compared with previous studies, we comprehensively characterized the small RNA profiles of menstrual blood, saliva, semen, skin, venous blood, and vaginal secretion based on the UMI quantitative method. The results showed that the influence on the sequencing quality by RIN value was limited. Hence, samples with low RIN are also recommended to conduct small RNA sequencing. After data cleaning and standardizing, a total of 5204 small RNAs were detected including 1394 miRNAs (including 236 novel miRNAs), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs. We focused on the characterization of their profiles including the small RNA class and expression level in each body fluid/tissue group. Subsequently, we defined two classes of body fluid/tissue-specific markers (RSMs and ASMs) for applications in different forensic scenarios. As a result, many RSMs and ASMs for the six types of body fluids/tissue were screened, among which some were new small RNA markers. Given the variation in the expression and specificity level of ASMs, they were set hierarchically to levels I to IV, which contributed to the selection of ideal BFID markers. Meanwhile, we also found some inconsistent markers between our results and other studies, a phenomenon that was reported in previous publications. Nonetheless, our study expanded the number of available candidate small RNA markers for conducting BFID in forensic studies and applications. In addition, a total of 11 reference genes were predicted based on MPS data, which could be used as potential markers to standardize gene expression. In the future, more samples should be investigated to explore and verify the RSMs, ASMs, and reference-gene markers.


DEAH/RHA helicases remodel RNP complexes in central processes of RNA metabolism such as transcription, splicing, or translation at the cost of adenosine triphosphate (ATP) hydrolysis. These enzymes require activation to function efficiently in their specific cellular context. We show that G-patch factors do not only recruit the DEAH/RHA helicase Prp43 to its cellular localization, but also interfere with its mechanism of motion along RNA substrates. Instead of dissociating from the substrate after a single round of catalysis, Prp43 bound to G-patch translocates continuously along the RNA, resolving stable RNA structures. Our research reveals the mechanism of RNA duplex unwinding by Prp43 and demonstrates how this process is regulated by its cellular cofactors. The DEAH/RHA helicase Prp43 remodels protein–RNA complexes during pre-messenger RNA (mRNA) splicing and ribosome biogenesis. The helicase activity and ATP turnover are intrinsically low and become activated by G-patch (gp) factors in the specific cellular context. The gp motif connects the helicase core to the flexible C-terminal domains, but it is unclear how this affects RecA domain movement during catalysis and the unwinding of RNA substrates. We developed single-molecule Förster Resonance Energy Transfer (smFRET) reporters to study RecA domain movements within Prp43 in real time. Without Pfa1(gp), the domains approach each other adopting predominantly a closed conformation. The addition of Pfa1(gp) induces an open state, which becomes even more prevalent during interaction with RNA. In the open state, Prp43 has reduced contacts with bound nucleotide and shows rapid adenosine diphosphate (ADP) release accelerating the transition from the weak (ADP) to the strong (apo) RNA binding state. Using smFRET labels on the RNA to probe substrate binding and unwinding, we demonstrate that Pfa1(gp) enables Prp43(ADP) to switch between RNA-bound and RNA-unbound states instead of dissociating from the RNA. ATP binding to the apo-enzyme induces the translocation along the RNA, generating the unwinding force required to melt proximal RNA structures. During ATP turnover, Pfa1(gp) stimulates alternating of the RecA domains between open and closed states. Consequently, the translocation becomes faster than dissociation from the substrate in the ADP state, allowing processive movement along the RNA. We provide a mechanistic model of DEAH/RHA helicase motility and reveal the principles of Prp43 regulation by G-patch proteins. RNA helicases of the DEAH/RHA family are involved in key steps of RNA metabolism and reorganize structured RNAs and RNA–protein complexes (RNPs) through ATP-dependent translocation in 3′ to 5′ direction along single strands . They sh27715Some specialized DEAH-box helicases target their substrates with high sequence specificity, such as DHX36, which binds RNA- and DNA- quadruplex structures with high affinity , 20. How21So far, eight of the more than 20 human G-patch factors are known to regulate DHX15 activity; however, the interaction partners of most remaining G-patch factors are still undiscovered . Besides32− with closed RecA domains  to monitor in real-time how the G-patch motif affects the conformational cycling of Prp43 RecA domains. Using smFRET labels on the RNA substrate, we follow RNA binding and unwinding by the Prp43-G-patch complex. We show that the G-patch motif induces the open state of RecA domains which is incompatible with nucleotide binding and facilitates nucleotide release. We confirm that the G-patch motif enhances RNA binding and demonstrate that ATP binding generates sufficient force to melt short RNA duplexes. During turnover, the G-patch accelerates transitions of the RecA domains between the open and closed state which couples ATP hydrolysis to processive motion along the RNA. Our results reveal the principal regulation mechanism of Prp43 by G-patch partners and lead to a mechanistic model of its motility cycle.Chaetomium thermophilum Prp43 (ctPrp43Cys) and a control mutant with labels at C187 in RecA1 and C303 in RecA2 (ctPrp43Cys2) .To analyze domain movements in Prp43 by smFRET, we generated fluorescence labeling sites at position C170 in RecA1 and C303 in RecA2 of SI Appendix, Fig. S1 B and C). We immobilized Prp43 on streptavidin-functionalized glass cover slips , corresponding to an estimated donor–acceptor distance of 4.3 nm. This value is comparable to the distance between the Cα atoms of the labeled residues in the crystal structure of ctPrp43–ADP where the RecA domains are close together . We denominate this conformation the closed (C) state. Next, we followed smFRET of the Prp43–Pfa1(gp) complex in order to test whether the G-patch alters the conformation of RecA domains in Prp43  indicating the opening of the RecA domains in Prp43 in response to Pfa1(gp) binding. We denominate this conformation the open (O) state. O and C states are nearly equally populated , and a small fraction of smFRET traces (7%) shows transitions between the states suggesting slow exchange between the populations . In the presence of ADP, Prp43 and the Prp43–Pfa1(gp) complex show similar FRET states compared to the apo-enzyme . However, for the G-patch complex, the C state is more prevalent in the presence of ADP, which agrees with the notion that contacts between RecA domains and the nucleotide stabilize the C conformation . The Prp43–Pfa1(gp)–RNA complex shows a second population with EFRET = 0.40 corresponding to the O state and the distribution of populations is comparable to Prp43Cys . Hence, the opening of the Prp43 RecA domains is principally possible through binding of the RNA substrate, similar as for other DEAH-box helicases such as DHX36 or Prp22  and ssRNA are similar to wild-type ctPrp43(wt) and to scPrp43 indicating that the catalytic activity is not impaired by the fluorescence tags . We used the structure of ctPrp43–ADP  and of DB: 5d0u ) as examSI Appendix, Table S2). Further analysis of the nucleotide binding site showed that the open RecA domain conformation is incompatible with ADP binding by Prp43 (N-methylanthraniloyl-ADP (mant-ADP) from Prp43 by a stopped-flow setup (off = 0.002 s−1. Mant-ADP release was accelerated by threefold in the presence of ssRNA and by 100-fold in the presence of Pfa1(gp) . The low affinity of Prp43 for mant-ADP under these conditions resulted in a very low signal amplitude . Previous studies have shown that Prp43 and Prp43-gp complexes in the nucleotide-free state target their RNA substrates with higher affinity than in the ADP state  B, indicaPfa1(gp) D and G. DP state . The lowSI Appendix, Fig. S5). Consistent with previous results . In the presence of ADP, however, the affinity decreases severely without Pfa1(gp), the KD was so high that a full titration was not feasible (KD > 100 µM). The Prp43-Pfa1(gp) complex showed moderate affinity in the presence of ADP (KD = 0.5 µM), confirming that the G-patch promotes the binding of the helicase to the substrate and that the choice of the nucleotide  regulates the switch between weak or strong binding states.To further investigate how Pfa1(gp) modulates Prp43 interaction with the RNA substrate, we determined the binding affinity in our system . After incubation with Prp43(apo), the majority of RNA molecules (76%) showed still stable signals with EFRET=0.79, similar to the free (F) RNA probe, and a smaller fraction (24%) displayed signals with EFRET = 0.51, corresponding to RNA bound (B) by the helicase . The addition of ADP shifted the distribution of FRET values entirely to the F state, which agrees with the very low binding affinities observed by fluorescence polarization . In the presence of AMPPNP, the distribution is shifted slightly toward the B state, which is also consistent with the fluorescence polarization data . Binding of the Prp43–Pfa1(gp) complex shifted the population toward the B state (88%), while high concentrations of Pfa1(gp) without Prp43 resulted only in the F state, confirming that the G-patch enhances Prp43 binding to the RNA . Upon the addition of ADP, the probe interconverted between F and B states indicating binding and dissociation of the Prp43–Pfa1(gp) complex . Traces with B to F transitions were used to estimate the dissociation rate of the complex in the low-affinity ADP state . This rate is one order of magnitude lower compared to the rate of ATP turnover . Hence, binding, hydrolysis, and release of ATP are much faster than dissociation of the complex from the RNA in the weak-affinity state, suggesting that Prp43-Pfa1(gp) can perform multiple rounds of ATP turnover while bound to the substrate.Next, we visualized time-resolved RNA binding by Prp43. We designed an RNA probe with a single-strand 3′-overhang allowing for Prp43 binding, followed by a stem loop, which is separated during Prp43 translocation B. The 3′FRET=0.35 . We assume that Prp43 binding straightens the RNA probe leading to the decrease in FRET in the B state. Hence, further reduction of FRET values most likely corresponds to the partial unwinding (PU) of the stem loop. In 20% of the duplex RNA molecules, the PU state is transiently sampled . However, the distribution of FRET states of the RNA probe, in particular the sampling of the PU state, was similar as in the experiments with ATP . The PU state was also sampled when we incubated the probe with a Prp43 variant (Prp43E216A) that hydrolyses ATP at very low rate, comparable to the AMPPNP hydrolysis rate by Prp43(wt)  (E216A-Pfa1(gp)–ATP , indicating that the binding and potentially hydrolysis of a single ATP are sufficient to induce partial unwinding of the RNA probe, i.e., the transition from the B to the PU state. A previously published translocation model derived from structural analysis of the DEAH-box helicase DHX37 suggested that the power stroke for translocation occurs during ATP binding, rather than during hydrolysis  in the presence of the physiological substrate ATP . At high sampled B. The an sampled B. A veryA and C) , 44. In drolysis . This modrolysis , 10, 19.drolysis , 46, whidrolysis . TherefoSI Appendix, Fig. S8A). To interpret the stopped-flow signals with respect to the unwinding of the RNA constructs, we therefore normalized the data by division by the fluorescence amplitude corresponding to the complete unwinding of the RNA duplexes . The Prp43–Pfa1(gp) complex separates the 10, 14, and 16 bp RNA constructs completely . This is presumably caused by a partial reannealing of separated strands that competes with the stem loop formation. Next, we manually dissected the lag phase preceding the actual strand separation, and analyzed the duration with respect to the duplex length . As the dequenching of the ATTO488 dye only occurs when the Prp43–Pfa1(gp) complex reaches the 5′ end of the bottom strand, the lag-phase correlates in first approximation with the translocation time. The Prp43–Pfa1(gp) complex requires significantly more time to arrive at the 5′-end of longer duplexes, which is a strong indicator for an unwinding process that involves multiple successive translocation steps on the same RNA . It appears that the longest duplex (20 bp) is close to the maximum range of unwinding by the Prp43–Pfa1(gp) complex. This range exceeds the size of the first unwinding step significantly . However, a small part of the population (13%) showed the O state, which was so far only observed in the presence of Pfa1(gp) or ssRNA . To examine the influence of Pfa1(gp) and ssRNA on the motility of the RecA domains, we first monitored smFRET of the Prp43–Pfa1(gp) complex in the absence of ssRNA. The complex showed increased levels of the O state (35%) and 27% of molecules toggled between C and O, which is a significant increase compared to unstimulated Prp43 and agrees with elevated rates of ATP turnover . The incubation of the Prp43–Pfa1(gp) complex with ssRNA further stimulated the rate of ATP hydrolysis . The conformational distribution and exchange rates were independent from the label positions as the control mutant Prp43Cys2 with a different label position in RecA1 showed similar transitions rates . The rate of ATP turnover determined in steady-state kinetic experiments is somewhat faster than the rate of conformational transitions observed by smFRET, presumably due to reduction of activity caused by the immobilization process. Still, kC→O is faster than the previously determined dissociation rate from the RNA , indicating that the helicases convert fast enough from the weak (ADP) to the strong (nt-free) RNA binding state to complete several conformational cycles before detachment.Knowing that continuous turnover is necessary for Prp43 to unwind more than the initial base pairs of an RNA duplex, we investigated the conformational dynamics of Cy3-/Cy5-labeled Prp43 at high ATP concentrations . In the or ssRNA D and F–Hor ssRNA  and domacat(scPrp43) = 5 s−1, SI Appendix, Fig. S12) corresponds to the rate of translocation (5 nt/s). The dissociation of the Prp43–Pfa1(gp) complex is much slower (koff(scPrp43) = 0.45 s−1), indicating that the helicase undergoes several catalytic cycles before dissociation from the RNA. Continuous turnover enables the Prp43–Pfa1(gp) complex to separate duplex strands of up to 20 bp. In our experiments, strand separation takes only place when Prp43 translocates across the entire duplex, which would require 20 processive translocation cycles.The DEAH/RHA helicase Prp43 samples both open and closed RecA domain conformations. In the absence of RNA and G-patch factor, RecA domains rarely enter the O state such that nucleotide release and ATP turnover are slow. Without G-patch, the affinity of Prp43 for RNA is low and the dissociation from the RNA occurs with higher probability than the translocation in 5′ direction. Overall, Prp43 is in a state where continuous unwinding of structured RNAs is hardly possible. Our data show that Pfa1(gp) promotes transitions between open and closed conformations of RecA domains during ATP turnover resulting in processive translocation and unwinding of duplex RNA . In the RNA unwinding by Prp43 relies on continuous conformational cycling of the RecA domains. Most likely, the transition to the closed state during ATP binding leads to the separation of proximal duplex strands. The underlying principle resembles the winching mechanism applied by the spliceosomal helicases Prp16, which remodels the spliceosomal C complex after the first splicing reaction to enable exon ligation, and Prp22, which subsequently releases the mature mRNA from the complex –51. BothRNA unwinding by Prp43 is clearly distinct from the mechanism employed by the structurally related DEAD-box helicases, which unwind structured RNAs by local strand displacement in a nonprocessive manner . Without5869Cofactors play a central role in the regulation of DEAH/RHA helicases, which have low intrinsic substrate specificity and therefore require activation in a specific cellular environment avoiding futile ATP hydrolysis and undesired RNA unwinding. Prp2/DHX16 is a further DEAH/RHA family member known to interact with a G-patch partner –77. In y78We demonstrate how conformational cycling of a DEAH/RHA helicase correlates with processive translocation along the RNA substrate. Remaining open questions concern how translocation is regulated in the cellular context, i.e., as part of spliceosome or in nascent ribosome complexes. In vivo, different G-patch factors compete for the interaction with Prp43  and mighSI Appendix, Materials and Methods.Detailed descriptions of the experimental procedures are provided in Escherichia coli Rosetta II and first purified by glutathione sepharose affinity chromatography using the N-terminal glutathione S-transferase (GST)-tag. Prp43 constructs were then subjected to affinity chromatography using their C-terminal His6- or Strep-tag. Finally, all Prp43 and Pfa1 constructs were purified to homogeneity by size exclusion chromatography.All Prp43 and Pfa1 constructs were expressed in Prp43 was fluorescently labeled with a mixture of Cy3-maleimeide and Cy5-maleimide using reactive cysteines at position C303 and K170C. The labeled protein was separated from excess dye by Ni-sepharose affinity chromatography.smFRET experiments were performed using a commercial TIRF microscopy setup  described in ref. ATP turnover by Prp43 was monitored using a coupled enzymatic assay following nicotinamide adenine dinucleotide absorption. The binding of Pfa1(gp) to Prp43 was monitored by isothermal titration calorimetry (ITC) with a MicroCal VP-ITC , and the RNA binding of Prp43 was measured by fluorescence polarization spectroscopy using a VICTOR Nivo Multimode Microplate Reader (PerkinElmer). ADP release from Prp43 was followed through FRET between Prp43’s tryptophan residues and mant-labeled ADP using a stopped-flow apparatus (Applied Photophysics). Using the same stopped-flow apparatus, unwinding of RNA duplex constructs was monitored by the dequenching of ATTO488 fluorescence upon distance increase to the Eclipse quencher attached the 5′- and 3′-ends of partner strands.Appendix 01 (PDF)Click here for additional data file.


Enhancers confer precise spatiotemporal patterns of gene expression in response to developmental and environmental stimuli. Over the last decade, the transcription of enhancer RNAs (eRNAs) – nascent RNAs transcribed from active enhancers – has emerged as a key factor regulating enhancer activity. eRNAs are relatively short-lived RNA species that are transcribed at very high rates but also quickly degraded. Nevertheless, eRNAs are deeply intertwined within enhancer regulatory networks and are implicated in a number of transcriptional control mechanisms. Enhancers show changes in function and sequence over evolutionary time, raising questions about the relationship between enhancer sequences and eRNA function. Moreover, the vast majority of single nucleotide polymorphisms associated with human complex diseases map to the non-coding genome, with causal disease variants enriched within enhancers. In this Primer, we survey the diverse roles played by eRNAs in enhancer-dependent gene expression, evaluating different models for eRNA function. We also explore questions surrounding the genetic conservation of enhancers and how this relates to eRNA function and dysfunction. Summary: This Primer evaluates the ideas that underpin developing models for eRNA function, exploring cases in which perturbed eRNA function contributes to disease. Simplistically, enhancer potential is determined by the binding of TFs to DNA and by the packaging of DNA into chromatin , bidirectionally transcribed transcripts that are 5′ m-spliced . Longer -spliced . For sho-spliced . It is u-spliced . The sen-spliced . This mad  – nascent RNA species pervasively transcribed from active enhancers – has emerged as a key factor that contributes to enhancer activity . The tracis-regulatory elements, particularly enhancers  and monomethylation of lysine 4 on histone H3 (H3K4me1) are the predominant histone modifications deposited at the nucleosomes flanking enhancer elements. H3K4me1 is globally associated with enhancers , indepenCga) gene converts H3K27 from an active acetylated state to a repressive methylated state at both the enhancer and the associated proximal promoter  and Fendrr  is a crucial repressive modification during development, ensuring genes that require silencing are packaged into heterochromatin. H3K27me3 is generated by polycomb repressive complex 2 (PRC2) . In embrpromoter . Moreoventiation , physicantiation , akin tod Fendrr .PRC2 preferentially binds RNA motifs composed of short repeats of consecutive guanine residues; the natural abundance of this RNA motif explains the promiscuous binding activity of PRC2. Further, PRC2-DNA binding sites are significantly enriched for sequences that code for PRC2-binding RNA motifs, potentially mediating site-specific RNA interactions. In line with its preference for guanine tracts, PRC2 binds to guanine quadruplex (G-quadruplex) structures in RNA with high affinity . This poTogether, these studies of H3K27ac and H3K27me3 highlight the potential of eRNAs to interact with enzyme complexes responsible for generating histone modifications – both activating and repressive – to generate a chromatin environment that is conducive to active transcription . At actiNanog-linked enhancers in ESCs  enhancer directly impacts tumorigenicity. Hypomethylation of the CEBPB enhancer induces eRNA synthesis and is correlated with poor prognosis in HCC patients , the methylation status of the CCAAT/enhancer-binding protein-β  pausing is a genome-wide regulatory mechanism by which the pausing and subsequent release of RNAPII into productive elongation acts as a key rate-limiting step for transcription. eRNAs can facilitate the release of paused RNAPII, thus promoting the transition into productive elongation, via interactions with complexes of negative elongation factor (NELF) and the positive elongation factor P-TEFb . P-TEFb Such interactions between eRNAs and NELF have been shown to be crucial for rapid induction of neuronal immediate early genes (IEGs) in neurons. In this context, eRNA binding to NELF facilitates the release of paused RNAPII in response to neuronal stimulation . Replaciin vivo , which functions as both a transcriptional activator and a repressor . eRNAs bin vivo . YY1 canin vivo . Howeverin vivo . Thus, eeRNAs can also bind to the transcriptional and epigenetic regulator BRD4, which plays a well-established role in cancer development . In humaAlthough multiple studies have demonstrated functional roles for eRNAs in transcriptional regulation, the role played by specific eRNA sequences and conserved eRNA structures is less well defined. Following the classification of ∼10,000 newly detected nascent RNAs, including 3257 classified as eRNAs, ∼10% were predicted to be structured . HoweverDRReRNA  is transcribed from the enhancer regions of the myogenic master regulator MyoD  forms multiple simultaneous allosteric contacts with several RNA binding sites on NELF. In the absence of sequence and structure dependency, the length of the eRNA, and therefore the degree of eRNA flexibility, is key, facilitating folding of the eRNA substrate into a structure that favours simultaneous binding to both the NELF-E and NELF-A subunits .AR-eRNA) shares a similar secondary structure with the 3′ end of the small nuclear RNA 7SK   , an estas RN7SK) . Competis P-TEFb . As AR-eeRNAs can also co-transcriptionally assemble into DNA/RNA hybrid structures, termed R-loops , in whicAR-eRNA, which is predicted to form a stem-loop structure, is key for AR-eRNA function, recruiting DNA methyltransferase 1 (DNMT1) to the associated enhancer to alter the DNA methylation levels of AR target loci -positive breast cancer cells, genome-wide annotation of 17β-estradiol (E2)-regulated eRNAs identified a ∼40 nucleotide functional motif predicted to form a hairpin loop structure, termed the FERM element. The FERM element in eRNAs transcribed from ERα-bound enhancers modulates the expression of the cognate target genes, pression . The FERpression , a coregpression . BCAS2 kferation .HPSE eRNAs interact with the RNA-binding protein heterogeneous nuclear ribonucleoprotein U (hnRNPU) via its arginine/glycine-rich RGG domain – a canonical RNA binding motif. This binding induces structural alterations in hnRNPU that favour its interactions with p300; the subsequent enrichment of hnRNPU and p300 at the enhancer promotes looping to the HPSE promoter and stimulates HPSE expression , a protein that is upregulated in various malignancies and bestows metastatic potential to cancer cells . HPSE eRpression . It shoupression . Howeverpression .Assembly of the transcriptional machinery into biomolecular condensates at enhancers is a tightly-regulated process that is dependent on both RNA sequence features, such as RNA identity, length and modifications, and RNA properties intrinsically encoded in their sequence, such as RNA structure . For exaC9orf72 gene in familial Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) (4C2) repeat expansion templates multivalent interactions, driving the formation of large gel-like aberrant foci via phase separation  . In thisparation . Interesruplexes . Such struplexes .Phase-separated transcriptional condensates have been shown to form at enhancers, generating high local concentrations of transcriptional regulators and promoting their synergistic function . The disA model is emerging in which the transition from transcriptional initiation into elongation is driven by the shuttling of RNAPII between distinct transient condensates at gene promoters and within gene bodies, whereby condensates function to concentrate factors required for initiation and elongation, respectively . Such seAlthough RNAs play a broad role in determining the formation of membraneless compartments, it has been suggested that they may be less significant for transcriptional condensate formation . Super-eThe deposition of chemical modifications on eRNAs, such as N6-methyladenosine (m6A), may affect transcriptional condensate assembly. Both the METTL3/METTL14/WTAP m6A methyltransferase complex (MTC) and the demethylase ALKBH5 associate with enhancers . ConsequMechanistically, m6A-modified eRNAs recruit nuclear m6A reader proteins such as hnRNPG (RBMX) and YTHDC1 to active enhancers, promoting productive enhancer transcription. The protective functions of m6A readers shield eRNAs from processing by the endonuclease subunit of the Integrator complex, INTS11, which would otherwise cleave nascent RNAs, resulting in premature transcriptional termination . In addim6A modification levels are largely hard-wired in nascent RNA sequences via the presence of ‘GGACT’ motifs, consistent with the canonical RRACH methylation motifs seen in mRNAs . With thIn contrast to the longstanding belief that sequence conservation implies functionality, many enhancers appear to maintain functions that are relatively independent of precise sequence conservation. This complex balance not only complicates their identification, but also raises questions regarding the mapping of disease-associated variants within enhancer elements. If enhancer sequence has little relevance to functionality, why do SNPs associated with human complex disease so frequently localise to enhancers ? To answOne barrier to better understanding eRNA function is the difficulty of manipulating eRNAs in the cellular environment; most studies have focused on a handful of eRNAs in isolation to characterise their function. Therefore, further studies are clearly required to examine the function of eRNAs in their native contexts. Although there is a lack of an overall conserved sequence motif for functional eRNAs, the diverse mechanisms covered in this Primer reveal a myriad of avenues by which eRNAs can exert their function in a more enhancer-specific manner. Therefore, determining whether eRNA sequence motifs and structures are fundamental in governing the functional complexity of eRNAs should be considered the focal point to unlock the roles of enhancers in gene control and disease.


Braveheart were widely reported to regulate the recruitments of PRC2 to their specific targets, a promiscuous RNA binding profile by PRC2 was also identified to play an essential role in cardiac cell fate decision. In this review, we focus on RNA-mediated PRC2 recruitment machinery in the process of cardiac cell fate decisions. The roles of individual lncRNAs which recruit PRC2, as well as promiscuous RNA binding by PRC2 in heart development are summarized. Since the binding priority of RNAs with different primary and secondary structures differs in its affinity to PRC2, the competitive relationship between individual lncRNAs binding and promiscuous RNA binding by PRC2 may be important for understanding the machinery by which biding of individual lncRNA and promiscuous RNA by PRC2 coordinately control the well-ordered dynamic cardiac cell lineage differentiation process.The epigenetic landscape determines cell fate during heart development. Polycomb repressive complex 2 (PRC2) mediates histone methyltransferase activity during cardiac cell differentiation. The PRC2 complex contains the proteins embryonic ectoderm development (EED), suppressor of zeste (SUZ12), the chromatin assembly factor 1 (CAF1) histone-binding proteins RBBP4 and RBBP7, and the histone methyltransferase called enhancer of zeste (EZH2 or EZH1), which incorporates the Su(var)3-9, Enhancer-of-zeste, Trithorax (SET) domain. Cardiac PRC2-deficient mice display lethal congenital heart malformations. The dynamic process of cardiac cell fate decisions is controlled by PRC2 and the PRC2-mediated epigenetic landscape. Although specific individual long noncoding RNAs (lncRNAs) including  Both genetics and epigenetics are focused on the study of genes and heredity. Genetics studies on how certain qualities or traits are passed on from parents to offspring as a result of changes in DNA sequence, while epigenetics is focused on the study of heritable phenotypic changes that do not involve alterations in DNA sequence . Epigene+ cardiovascular progenitors which give rise to the cardiomyocyte, smooth muscle and endothelial cell lineages at a relatively delayed time point  proteins, originally found in gulators . In mammgulators . The fungulators . The catgulators , 1.In this review, we summarize the role of the PRC2 complex in heart development and cardiac cell fate decisions, focusing on the roles of RNA in the PRC2-mediated epigenetic landscape during cardiac cell fate decision-making. An updated promiscuous PRC2 recruitment model is presented which reconsiders the relationship between specific individual RNA binding and promiscuous RNA binding by PRC2, and how both coordinately controls the well-ordered process of dynamic cardiac cell lineage differentiation.Jarid2 by cardiac cell lineage specific NK2 homeobox 5 (Nkx2.5)-Cre mice induced similar cardiac malformations as EZH2-null mice including ventricular septal defects, thin myocardium, hypertrabeculation, and neonatal lethality , SIX homeobox 1 (Six1), Isl1, paired box 6 (Pax6), myosin heavy chain 6 (Myh6) and hyperpolarization activated cyclic nucleotide gated potassium channel 4 (Hcn4), which are related to heart development , cardiac EZH2 deficiency significantly changed the expression of 511 genes in the ventricle apex including elopment . The direlopment . De-reprelopment . Endotheelopment . Thus, tH3K27me3, a direct product of PRC2, plays a key role in regulating heart development . Genome-In summary, PRC2 controls normal heart development by temporally and spatially regulating the expression of genome-wide cardiac-specific genes in an epigenetic manner during heart development .The first lineage choice in embryonic development separates trophectoderm from the inner cell mass , and naïin vitro ESC differentiation  was the first identified lncRNA, which is expressed in the early stages of embryonic heart development, contributing to the formation of beating cardiomyocytes (Bvht and PRC2 was observed to control cardiac cell fate decisions via mesoderm posterior 1 (MesP1), the master regulator of a common multipotent cardiovascular progenitor  structures but shows little binding to duplex RNAs  is dictated by the local chromatin context . Howeverin vitro differentiation  was recently reported to control genome-wide PRC2 occupancies during the process by which human ESCs direct differentiation into cardiomyocytes . By counKcnq1ot1), one imprinted lncRNA, was reported to recruit PRC2 on target genome and induce the spread of PRC-dependent chromatin modifications over multi-megabase domains. The spread of polycomb is controlled by genome architecture and CpG island DNA  is an lncRNA transcribed from telomeres, which contains UUAGGG repeats as a G4 noncoding RNA . The inttructure , 2. Sometructure . The pretructure . Thus, TIn summary, RNA with the G4 structure is essential for heart development and RNA with G4 structure may regulate the PRC2-mediated epigenetic landscape in ESCs and early embryonic development.The binding of individual lncRNAs and promiscuous RNA binding by PRC2 may both play key roles in controlling heart development. The relationship between binding of individual lncRNA and promiscuous RNA by PRC2 in heart development is therefore an interesting unknown question. In addition, whether individual lncRNAs regulate promiscuous RNA binding by PRC2 during heart development is still unknown. How do binding of individual lncRNA and promiscuous RNA by PRC2 coordinately construct the dynamic epigenetic landscape?Since the binding priority of RNA to PRC2 is different, a “competitive model” may be described to explain the relationship between binding of individual lncRNA and promiscuous RNA by PRC2 during heart development and early embryonic development . During PRC2- and H3K27me3-mediated epigenetic landscape regulate cardiac cell fate decisions. Both individual and promiscuous RNA binding by PRC2 is essential for cardiac cell fate decisions. RNA with the G4 structure is also important for heart development. The binding affinity between PRC2 and RNA is not dependent on a specific protein-binding motif in RNA but rather depend on the amount of guanine nucleotides and specific G4 secondary RNA structure. Thus the machinery by which promiscuous RNA binding by PRC2 controls the well-ordered cardiac cell lineage differentiation process becomes an interesting open question. A “competitive model” among PRC2-interatcting individual RNAs may explain the coordinate regulation of the well-ordered cardiac cell lineage differentiation process. Dynamic specific G4-enriched lncRNAs may act during heart development to change the promiscuous RNA binding by PRC2.Thus, systemic understanding of stage-specific promiscuous RNA binding profiles, the dynamic expression of specific G4-enriched lncRNAs, and specific G4-enriched lncRNA-induced changes in the RNA binding profile by PRC2 during heart development will be important for comprehension of the dynamic epigenetic landscape regulating heart development. Finally, this will be essential for understanding the pathogenesis of genetic and non-genetic factors-induced congenital heart disease.


We present evidence suggesting that the severe acute respiratory syndrome (SARS) coronavirus non-structural protein 13 (Nsp13) modulates the Z-RNA dependent regulated cell death pathways . We show that Z-prone sequences [called flipons] exist in coronavirus and provide a signature (Z-sig) that enables identification of the animal viruses from which the human pathogens arose. We also identify a potential RIP Homology Interaction Motif (RHIM) in the helicase Nsp13 that resembles those present in proteins that initiate Z-RNA-dependent cell death through interactions with the Z-RNA sensor protein ZBP1. These two observations allow us to suggest a model in which Nsp13 down regulates Z-RNA activated innate immunity by two distinct mechanisms. The first involves a novel ATP-independent Z-flipon helicase (flipase) activity in Nsp13 that differs from that of canonical A-RNA helicases. This flipase prevents formation of Z-RNAs that would otherwise activate cell death pathways. The second mechanism likely inhibits the interactions between ZBP1 and the Receptor Interacting Proteins Kinases RIPK1 and RIPK3 by targeting their RHIM domains. Together the described Nsp13 RHIM and flipase activities have the potential to alter the host response to coronaviruses and impact the design of drugs targeting the Nsp13 protein. The Z-sig and RHIM domains may provide a way of identifying previously uncharacterized viruses that are potentially pathogenic for humans. Nidovirales are known to infect humans (Seven human coronaviruses (hCoV) of the order t humans –3. Theset humans . A numbet humans ]. Host ft humans –8.CoV are long (~30Kb) positive strand, single-stranded RNA (ssRNA) viruses that replicate themselves within double membrane vesicles through a dsRNA intermediate , 9. The n, (CA)n and (UG)n. The propensity of flipons to adopt the ZNA conformation can be scored using the ZHUNT3 (ZH3) program (The left-handed Z-DNA and Z-RNA (ZNA) conformations form from their right-handed counterparts of B-DNA and A-RNA by flipping the bases over to produce the characteristic zig-zag backbone of these reverse-twisted, double-stranded nucleic acid conformers . The ene program . Much of program .via the adaptor protein FADD, inhibiting necroptosis  for each strain of virus is unique Figure 2Alu repeats  for arginine. Another highly conserved Z-prone sequence was found in the Nsp12 (RdRp) gene, within the region encoding the NiRAN domain. This domain catalyzes the NMPylation of the strongly conserved N terminus of Nsp9, a modification essential for CoV genomic replication , suggesting that there regions interact with RNA . Within  studies . The Z-s studies , potentiVGTNLPLQLGF), in argonaute proteins (YPHLPCLQVG), in RELB (AAIERKIQLGI) and UPF1 (RPMFFYVQLGQ) did not align well with known RHIM sequences, but warrant further investigation to test their functionality and their preferred interaction partner(s).In assessing the potential for Z-RNA dependent responses, we searched for viral proteins containing a RHIM that could modulate cell death pathways through interactions such as those illustrated in Both strategies of looking for Z-prone sequences and RHIMs focused our attention on the Nsp13 helicase and its potential novel role as a Z-flipon helicase (flipase). Nsp13 unwinds both DNA and RNA in the 5’->3’ direction. It is a member of the helicase superfamily 1B (SF1B) . Along wThe Nsp13 RHIM is present in the 1B domain, which bridges the RecA1 and RecA2 domains. Rather surprisingly, the peptide PARA encoded by the Z-prone sequence that is in the RecA1 domain interacts with the RHIM when the Nsp13 is in the ATP-free closed conformation . The cavThe Nsp13 cavity shown in Our analysis reveals a number of Z-RNA prone sequences (Z-sigs) in human CoV that can be used as fingerprints to identify closely related stains to trace their zoonotic origins. The approach is facile without the need for deep sequence analysis or alignment to confirm the relationship and is quite robust to errors in such procedures.The plots in Of note is that some hosts lack functional Z-RNA dependent inflammatory cell death pathways, so there is less constraint on the available sequence space they can exploit . HoweverOur structural analysis of the potential Nsp13 RHIM raised the possibility that protein has a non-canonical helicase activity that exploits the strand separation occurring during the transition of A-RNA to Z-RNA . By sequIt also appears from the structural analysis shown in via the bridging adaptor TRAM  is directly bound by the dsRNA sensor TLR3 but is indirectly recruited to lipopolysaccharide binding TLR4 tor TRAM . Mice lator TRAM . Anothertor TRAM . The vultor TRAM . EngaginIn summary, we propose that Nsp13 is able to prevent ZBP1 activation of cell death pathways in two different ways. First, the helicase prevents the Z-RNA formation required to engage ZBP1 and second, the RHIM domain inhibits activation of cell death pathways by ZBP1 4A. Potein vitro and in vivo models of SARS-CoV2 infection  and that the RHIM in Nsp13 regulates ZBP1, RIPK3, RIPK1, TRIF or SMG1 signaling, then we suggest that effects will depend on the stage of viral infection. At early stages, suppressing Z-RNA formation and cell death/NMD through the RHIM interactions would enable increased viral replication while diminishing severity of the initial infection. Here the recognition of Z-RNA prone sequences by Nsp13 flipase then blocks the viral polymerase until the two RNA strands are fully separated by the classical Nsp13 helicase activity. At later stages of infection, the dsRNA tangles formed as defective viral genomes accumulate may create Nsp13 clusters, leading to the formation of amyloid filaments, then inflammatory cell death as recently reported for nfection .From our analysis, it seems that the RHIM domain is a requirement for CoV for the successful jump the virus made from its natural host to humans, although not a sufficient one as other mutations that enable engagement of human cell surface receptors are required. The combination in Nsp13 of the RHIM domain with a Z-flipase so far appears unique among human viruses and may account for the extreme virulence of a subset of CoV. The presence of RHIMs in other viruses that are currently poorly characterized may identify them as potential pathogens before they become pandemic in humans, allowing implementation of pre-emptive measures to counter human infections.The susceptibility of humans to SARS and other novel viruses may also depend on each individual’s genome as there is a high frequency of gene variants that impact the necroptotic machinery . The losWhile Nsp13 inhibitors that target the ATP-binding site are likely to be effective early in CoV infection by inhibiting the classical helicase function of the enzyme, only those compounds that lock the enzyme in a conformational state unable to engage Z-RNA are likely to be effective against the Z-flipase activity.https://github.com/Ho-Lab-Colostate/zhunt) using the following command line “zhunt3nt 12 6 24” (th, 2022 at https://www.ebi.ac.uk/Tools/msa/clustalo/ and MAFFT V7 for Coronavirus sequence alignment, using the option to preserve gaps with the others left as the default and accessed online on March 24th, 2022at https://mafft.cbrc.jp/alignment/server/ (The Z-forming potential of the Coronavirus sequences were assessed using ZHUNT3 (12 6 24” . The str12 6 24” , 6XEZ (412 6 24”  and 7RDX12 6 24”  were vis12 6 24” . Amino a12 6 24”  using th12 6 24” , using t12 6 24”  CLUSTAL /server/  and moti/server/  and RNAf/server/ .AH is an international supervisor for the HSE Bioinformatics Laboratory run by MP. AH conceptualized and wrote the paper with suggestions and edits from MP and AH prepared the figures. All authors contributed to the article and approved the submitted version.Author AH is the founder of InsideOutBio, a company that works in the field of immuno-oncology.The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.