Mycobacterium smegmatis porin A (MspA) suggests a sensing mode called nanopore trapping/translocation, which clearly distinguishes between microRNA, small interfering RNA (siRNA), transfer RNA (tRNA) and 5 S ribosomal RNA (rRNA). To further profit from the acquired event characteristics, a custom machine learning algorithm is developed. Events from measurements with a mixture of RNA analytes can be automatically classified, reporting a general accuracy of ~93.4%. tRNAs, which possess a unique tertiary structure, report a highly distinguishable sensing feature, different from all other RNA types tested in this study. With this strategy, tRNAs from different sources are measured and a high structural conservation across different species is observed in single molecule.Folding of RNA can produce elaborate tertiary structures, corresponding to their diverse roles in the regulation of biological activities. Direct observation of RNA structures at high resolution in their native form however remains a challenge. The large vestibule and the narrow constriction of a  Nanopores have been used for direct observation of RNA structure in native environments but have limited RNA differentiation capabilities. Here, the authors report on the use of Mycobacterium smegmatis porin A nanopores for the trapping and translocation identification of microRNA, siRNA, tRNA and ribosomal RNA. Many unknown biological roles of RNA have been discovered4, leading to a growing demand for determination of RNA tertiary structures. Classical structural biology techniques including X-ray crystallography5 and NMR spectroscopy7 have contributed most to the RNA tertiary structure determination, preferentially those with small RNA architectures8. As a complement, cryo-electron microscopy (cryoEM) plays an increasingly important role in unveiling the structures of larger (>50 kDa) RNA molecules10. Emerging techniques such as single-molecule Förster Resonance Energy Transfer (smFRET)11 and single-molecule force spectroscopy12 have also been applied to probe RNA structure and interaction dynamics at the molecular level. However, high end equipment and laborious efforts in sample preparation are required and the risk of perturbing non-covalent interactions within the RNA structure is also present. As a consequence, direct interrogation of tertiary structures of RNA in its native state remains a challenge.The functional diversity of RNA stems in part from its ability to fold into elaborate tertiary structures that can specifically bind with ligands to regulate cellular activities17 and clinical applications such as the quantification of severe acute respiratory syndrome coronavirus 2 were as well demonstrated14. However, the thickness of a solid state nanopore prohibits it from producing refined sensing information, limiting its resolution to clearly resolve structurally similar RNA structures. Besides, the geometric reproducibility of a solid state nanopore remains a technical bottleneck, reducing the consistency of sensing when different batches of pores are used. Biological nanopores represent a growing family of channel proteins used for single-molecule sensing18. Emerging nanopores such as ferric hydroxamate uptake component A (FhuA) or aerolysin are capable of performing sensing of nucleic acids19, protein–protein interactions20 or amino acids21 with a high accuracy and consistency. Previous studies of transfer RNA (tRNA) using biological nanopores were carried out with wild type α-hemolysin (α-HL)22. However, chemical ligation with a leading strand is required and the acquired information reflects the difference of unfolding kinetics or the primary sequence rather than the overall tertiary structures of different tRNAs, largely due to a limited size of the pore constriction. To permit passage of large biomolecules, recent efforts have been made to develop biological nanopores with large constrictions. These pores include Cytolysin A (ClyA)23, Phi29 connector protein24, Fragaceatoxin C (FraC)25, FhuA20, and Pleurotolysin A (PlyA)/Pleurotolysin B(PlyB)26, with which dsDNA, proteins, or protein-small molecule complexes were thoroughly investigated. However, to the best of our knowledge studies of such complexes with RNA tertiary structures have not yet been carried out. These large pores are also associated with various issues such as short storage time23, non-uniform pore assembly27, or spontaneous gating when a large potential is applied27.RNA structures can be probed by solid state nanoporesMycobacterium smegmatis porin A (MspA) is a conically shaped biological nanopore composed of rigid β-barrel structures28. Previous reports indicate that the pore in an octameric form possesses an incredible stability and consistency against extreme conditions29. Its narrow constriction, measuring ~1.2 nm in diameter is advantageous in applications of nanopore sequencing30 or nanopore force spectroscopy31. On the other side, its large vestibule, which measures ~4.8 nm in diameter, would permit transient accommodation of a large analyte in its native form by nanopore trapping. Surprisingly, this geometric advantage has however been ignored since its original report.We here propose a sensing mode with MspA, termed nanopore trapping/translocation, with which direct discrimination between differently structured low molecular weight (LMW) RNAs such as miRNA, overhanged siRNA, blunt siRNA, tRNA, or 5 S rRNA is reported. The RNA structure is profiled in its folded form during trapping. Translocation is not strictly needed and no denaturant or sample ligation is required. Complementary to existing developments of large channel proteins, advantages such as the efficiency of pore preparation, the ease of spontaneous pore insertion, the high consistency of pore assembly, the long storage time, and a high spatial resolution are all gained  was placed in cis and a 1 M CaCl2 buffer  was placed in trans. According to the current–voltage characterization, the placement of a 1 M CaCl2 buffer instead of a 1.5 M KCl buffer in trans reduces the open pore current only slightly when a positive potential is applied 32 Fig. . If not ied Fig. .Fig. 1Re34, was custom synthesized and treated as a model miRNA to test the method /1.5 M KCl (trans), translocation events of hsa-miR-21 appeared as quite short-residing spikes as demonstrated in Fig. cis)/1 M CaCl2 (trans) while keeping all other conditions identical, the rate of event appearance was significantly increased. The event dwell time was dramatically extended and the blockage amplitude  and has been well investigated as multiple cancer biomarkersted Fig. . This di35. This duplex of siRNA is conformationally more confined than that of dsDNA and is primarily in the A form36. The duplex of siRNA has a cross-sectional diameter of ~2.4 nm37, larger than that of the MspA constriction, indicating that a direct translocation of siRNA through MspA is geometrically restricted , measuring 20–25 bp in length, appears as a RNA duplex with 2-nt 3′-overhangs or blunt ends and plays a central role in gene silencingted Fig. . To the 38  in n = 3) in n = 3) was obtained during the trapping stage.siFoxA1, which inhibits the expression of Forkhead protein FoxA1, is a 19-bp siRNA duplex with overhanging nucleotides on each end38 Fig. . After tion Fig. . This is39, a 21-bp duplex and an inefficient silencing structure40, was employed as a model blunt siRNA  is another intensively studied and well-known model in RNA structural biology. Its secondary structure is composed of four domains: the acceptor stem, the D-arm, the T-arm, and the anticodon loop /1.5 M KCl (trans), tRNAphe translocation results in events with non-uniform characteristics. Previously observed type 1 and type 2 events have completely disappeared , Brewer’s yeast tRNAics Fig. . When thphe were carried out with applied voltages varying between +125 and +225 mV. Both tRNA type 1 and type 2 events were still observed. In general, the residence times of all type 1 events were systematically extended when the applied voltage was increased , four loops (B–E), and one hinge (A), which form a Y-shaped tertiary structure46. The loop C, loop E, and helix I are located at the three ends of the “Y” shape46. The structure shows a higher complexity than that of tRNA and might generate different event characteristics when probed by MspA.5 S ribosomal RNA (5 S rRNA) is an integral component of the ribosome. Its small size (approximately 120 nt), conserved structure, and association with ribosomal proteins made it an ideal model RNA for studies of RNA structureE. coli  with many negative going spikes. The type 3 event demonstrates a two-step blockade and the mean blockage amplitude  type 1 events, 155 tRNA (tRNAphe) type 2 events, 133 5 S rRNA (E.coli 5 S rRNA) events and 134 “others” events were used. All these training events have known identities since they were generated during measurements involving a sole, known analyte. Here, events defined as “others” were abnormal nanopore events mainly caused by nanopore clogging or spontaneous gating  and translocation (type 2) of tRNA when probed by MspA  and with the tRNA translocating through the pore (Z < 0). As shown in Fig. The different analyte-pore interactions caused by different conformations of tRNA lead to distinctive ionic currents. To quantitatively compare the resulting ionic current for the different conformational states of the system, the external electric field was switched to 0.09 V/10 nm, which corresponds to a voltage bias of ~+150 mV as used in the experiments. Following a previous study58. With this knowledge in mind, the structure-induced nanopore events of brewer’s yeast tRNAphe might be generally applied to a much wider variety of tRNAs from different sources. To explore this speculation, we performed nanopore sensing of the total tRNAs from brewer’s yeast and from E.coli, both supplied by Sigma-Aldrich.Previous crystallographic studies indicate that with the exception of particular mammalian mitochondrial tRNAs, tRNAs of a widely divergent phylogenetic origin demonstrate a highly conserved L-shaped tertiary conformationE.coli total tRNAs contain noticeable contaminations, including 5 S rRNA and other higher molecular weight RNAs59 , yeast tRNA or purified phe Fig. . The proE.coli (BL21) DE3 was lysed. All low molecular weight (LMW) RNA ( < 200 nt) was extracted by the small RNA extraction reagent from Takara, named RNAiso for Small RNA. The extraction procedure is schematically illustrated in Fig. 65. Other than tRNA, the other RNAs may serve as interfering RNAs with which to test the robustness of the machine learning algorithm.To verify its feasibility, cultured 61, the band with a molecular weight equivalent to ~80 nt corresponds to the tRNAs65. Nanopore sensing of LMW RNA was performed with 40 ng/μL LMW RNA in cis. A representative trace of a 70 s duration is shown in Fig. Prior to nanopore measurements, the extracted sample was first characterized by 12% denaturing urea polyacrylamide gel electrophoresis (Urea-PAGE) analysis Fig. . AccordiE.coli (BL21) DE3 were extracted using MiniBEST Universal RNA Extraction Kit (Takara). This kit preferentially extracts all RNAs with a molecular weight >200 nucleotides (nt) according to the manufacturer’s protocol66. Detailed extraction procedures are described in Methods. Experimentally, from 1% agarose gel electrophoresis results, the sharp bands respectively correspond to the 23 S Ribosome RNA (rRNA) (2904 nt) and the 16 S rRNA (1542 nt) which is a good indication that the HMW RNA extraction was successful  RNAs (>200 nt) of A (rRNA) 04 nt andcis. A representative 10 min trace is shown in Supplementary Fig. Nanopore sensing of the HMW RNA extraction was performed with a 50 ng/μL final concentration of HMW RNA in 68 or reverse transcription70, it requires no prior chemical treatment or amplification and a single molecule resolution is achieved. It thus serves as an alternative method for fast estimation of the expression level of a particular RNA, and is suitable for assessment of RNA integrity, stress-induced tRNA differential expression71 or tRNA cleavage derived fragments72. Acknowledging an overall rigidity and conical geometry of the pore, trapping by MspA also reports highly consistent and distinguishable event characteristics. To cope automatically and quantitatively with sensing events, a custom machine learning algorithm has been developed , tRNAphe from brewer’s yeast, total tRNA from brewer’s yeast and total tRNA from E.coli were from Sigma-Aldrich. Dioxane-free isopropyl-β-D-thiogalactopyranoside (IPTG), kanamycin sulfate, imidazole, N,N,N′,N′-tetramethyl-ethylenediamine (TEMED) and tris (hydroxymethyl) aminomethane (Tris) were from Solarbio. DNA Marker DL2000, RNA Marker RL1000, RNA Marker RL6000, RNAiso for Small RNA, MiniBEST Universal RNA Extraction Kit and RNase-free water were from Takara. ZR small-RNA™ PAGE Recovery Kit was from ZYMO research. Low Range ssRNA Ladder was from New England Biolabs. SYBR gold nucleic acid gel stain was from Invitrogen. Potassium chloride (KCl) was from Aladdin. 4-(2-hydroxyethyl)−1-piperazineethanesulfonic acid (HEPES) was from Shanghai Yuanye Biotechnology. 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhPC) was from Avanti Polar Lipids. E. coli strain BL21 (DE3) was from Biomed. Luria-Bertani (LB) agar and LB broth were from Hopebio. Chloroform was from Labol. Isopropanol and urea were from GHTECH. 75% ethanol (prepared with DEPC treated water) was from KeyGeN. 40% Acrylamide/methylene diacrylamide solution was from Sangon. High-performance liquid chromatography–purified hsa-miR-21, siFoxA1 and luciferase siRNA were hybridized by Sangon and delivered as a double stranded form , Triton X-100, Genapol X-80, calcium chloride  were prepared and membrane-filtered  prior to use. RNA was dissolved in RNase-free water before use. The M1 MspA (D90N/D91N/D93N) and M2 MspA (D90N/D91N/D93N/D118R/D134R/E139K) were expressed with E. coli BL21 (DE3) and purified by nickel affinity chromatography as described previously77. The plasmid DNAs encoding M1 or M2 MspA were custom synthesized by Genescript (New Jersey) and have been shared via https://www.molecularcloud.org/s/shuo-huang. The access codes are MC_0101207 (M1 MspA) and MC_0101191 (M2 MspA). The majority of results were acquired with the M2 MspA. For simplicity, M2 MspA is referred to as MspA throughout the text, if not otherwise stated.1.5 M KCl buffer , and 1 M CaClcis chamber, while the opposing chamber was defined as the trans chamber. In total 100 µL pentane solution of DPhPC (5 mg/mL) was added to both chambers. A lipid bilayer was formed by pipetting the electrolyte buffer in either chamber up and down several times. Upon the successful formation of the lipid bilayer, the acquired current immediately drops to 0 pA, indicating that the aperture connecting both chambers has been completely sealed. MspA was added to the cis chamber to initiate spontaneous pore insertion. Upon a single nanopore insertion, the buffer in the cis chamber was manually exchanged to avoid further pore insertions.The measurement device is composed of two custom poly-formaldehyde chambers separated by a ~20 μm-thick Teflon film drilled with an aperture (~100 μm in diameter). Prior to the measurement, the aperture was first treated with 0.5% (v/v) hexadecane (dissolved in pentane) and set for pentane evaporation. Afterwards, 500 μL electrolyte buffers were respectively added to both chambers. A pair of custom Ag/AgCl electrodes, electrically connected to the patch clamp amplifier, were respectively placed in both chambers, in contact with the buffers. Conventionally, the chamber which is electrically grounded was defined as the To avoid external electromagnetic and vibration noises during the measurements, the device was shielded in a custom Faraday cage (34 cm by 23 cm by 15 cm) mounted on a floating optical table (Jiangxi Liansheng Technology). All electrophysiology measurements were performed with an Axonpatch 200B patch clamp amplifier paired with a Digidata 1550B digitizer (Molecular Devices). All single-channel recordings were sampled at 25 kHz and low-pass filtered with a 1 kHz cutoff frequency. The acquired traces were further digitally filtered with a 500 Hz low-pass Bessel filter (eight-pole) using Clampfit 10.7 (Molecular Devices).cis and a 1 M CaCl2 buffer  in trans and a + 150 mV potential was continuously applied.Unless otherwise stated, all nanopore measurements in this paper were performed with a 1.5 M KCl buffer  in RNA translocation events were recognized with the “single channel research” option in Clampfit 10.7. The machine learning algorithm was custom programmed by Python. Subsequent analyses including histogram plotting and curve fitting were performed in Origin 9.1 (Origin Lab).78 with the CHARMM36m force field79 and TIP3P water model80. The setup of the simulation system was prepared by using the CHARMM-GUI web server81. The atomic coordinates of MspA28 and tRNA82 were taken from the Protein Data Bank (PDB) with the entries 1UUN and 1EVV, respectively. Following the experimental setup, the mutations R96A, D93N, D91N, D90N, D118R, D134R, and E139K were introduced to simulate the composition of an M2 MspA. A 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) lipid bilayer with the size of 12 × 12 nm2 was added. The resulting system was then solvated in a rectangular water box with periodic boundary condition. To simplify the simulations, the system was established in a symmetric KCl buffer electrolyte system. K+ and Cl− ions were added at random positions to give a salt concentration of 1.5 M and to neutralize the simulation system. The final system consists of ~225,000 atoms. The long-range electrostatic interactions were calculated using the smooth particle-mesh Ewald method83. The cutoff distance for the calculations of the short-range part of the electrostatic interactions and the van der Waals interactions were set to 1.2 nm. The covalent bonds involving hydrogen atoms were restrained with the LINCS algorithm84.All molecular dynamics (MD) simulations were conducted by GROMACS 201985. The heated systems were further equilibrated under NPT ensemble at 298 K and 1 atm for another 1.75 ns, with the Berendsen semi-isotropic barostat85, leading to a box size of ~11.6 nm × 11.6 nm × 16.5 nm. The simulations of translocation were initiated from the final structures of the above equilibrating simulations with NVT ensemble. An external electric field of 2.0 V/10 nm was applied along the direction perpendicular to the membrane plane for 0.5 ns, then the external electric field was switched to 4.0 V/10 nm. The production simulations lasted for 100 ns with a time step of 2 fs. During the simulations, harmonic positional restraints were applied to the Cα atoms of MspA with a spring constant of 500 kJ/mol/nm2. Experimentally, translocation of tRNA typically lasts ~second, which is far beyond the accessible timescale of conventional all-atom MD simulations. In order to observe a full translocation process within a feasible simulation timescale, the external electric field of 4.0 V/10 nm used in the translocation simulations corresponds to a much higher voltage bias than that is applied in the experiment. As discussed in previously reported literatures87, high electric fields often result in the formation of electroporation of the lipid bilayer even in short MD simulations, which can lead to ion leakages. Consequently, different simulation strategies were used to avoid the formation of electroporation of the lipid bilayer, such as adding positional restraints88, using puling force with steered MD to drive the translocation89, or using more sophisticated Grid-steered MD90. Here we applied positional restraints to avoid the formation of electroporation, in which all the heavy atoms of the lipid molecules were restrained to the positions in the structures obtained from the minimization step by a harmonic potential with a spring constant of 1000 kJ/mol/nm2.To simulate tRNA translocation, each system was firstly minimized for 1000 steps and then equilibrated at 298 K for 0.25 ns under NVT ensemble using Berendsen weak-coupling thermostatTo characterize the simulated tRNA translocation process, we used three reaction coordinates, including the number of base-pair hydrogen bonds (H-bond), the root mean square deviation (RMSD) from the native structure, and the z-coordinate of the tRNA (Z). The H-bond represents the number of hydrogen bonds between the nucleotide pairs which form base pairs in the native structure. Therefore, decrease of the H-bond corresponds to the disruption of the tRNA base pairing. The RMSD characterizes the overall structure change of the tRNA, which is not only sensitive to the structural unfolding, but is also sensitive to the overall deformation of the molecules. Therefore, the H-bond and RMSD can be applied to describe different conformational properties of the tRNA during translocation. The reaction coordinate Z is defined by the z-coordinate of the leading nucleotide during the translocation . The initial structure of the system with the tRNA translocating through the pore was extracted from the above translocation simulations. The software PyMOL was used for the structural visualization91.To simulate the ionic current, starting from the equilibrated structures with the above-mentioned three different tRNA orientations, the systems were firstly relaxed for 20 ns under an external electric field of 1.0 V/10 nm, so that the tRNA makes sufficient contacts with the entrance of the MspA. The production simulations started from the relaxed structures under an external electric field of 0.09 V/10 nm, which corresponds to a voltage bias of ~+150 mV, similar to that used in the experiments. The production simulations lasted for 100 ns. We also repeated the simulations at higher electric fields, including 0.2 V/10 nm and 0.6 V/10 nm. As the lipid bilayer can keep stable under these electric fields within the simulation timescale, the positional restraints were applied only to the C2. The atomic coordinates of 5 S rRNA were taken from the PDB with the entry 1C2X. The final system for the translocation of the 5 S rRNA consists of ~270,000 atoms with a box size of ~12.5 nm × 12.5 nm × 17.0 nm.Similar simulations were performed for translocation of 5 S rRNA  was loaded into a 12% denaturing urea polyacrylamide gel. Gel electrophoresis was continuously run for 100 min with a + 180 V applied potential. The gel was illuminated with a portable UV lamp (254 nm). The gel fragments respectively containing 5 S rRNA or tRNA were excised for further recovery. RNA recovery was performed using ZR small-RNA™ PAGE Recovery Kit (ZYMO research). According to the manual, crushed RNA fragment was transferred into a Zymo-Spin™ IV Column. In total 400 μL RNA Recovery Buffer was added to the column and incubated at 65 °C for 15 min. The column was quickly frozen in a −80 °C freezer for 5 minutes and incubated at 65 °C for 5 min. The column was then centrifuged at 1500 × g for 30 s. The filtrate was transferred to a Zymo-Spin™ IIICG Column and centrifuged at 1500 × g for 30 s. The filtrate was added with 2 volumes of RNA MAX Buffer and thoroughly mixed. The mixture was then transferred to a Zymo-Spin™ IC Column and centrifuged at 12000 × g for 30 s and the supernatant was discarded. The column was added with 400 µL RNA Prep Buffer and centrifuged at 12,000 × g for 1 min and the filtrate was discarded. The column was added with 800 µL RNA Wash Buffer and centrifuged at 12,000 × g for 1 min then the filtrate was discarded. The column was added with 400 µL RNA Wash Buffer and centrifuged at 12,000 × g for 1 min and the filtrate was discarded. The column was centrifuged at 12,000 × g for 2 min to ensure complete removal of the wash buffer. The column was added with 30 µL RNase-free water. After standing for 1 min, the column was centrifuged at 10,000 × g for 1 min to elute the RNA. The eluted RNA concentration was determined by nanodrop  and the sample was further characterized using 12% denaturing urea polyacrylamide gel electrophoresis. Finally, the recovered RNA was stored at −80 °C for subsequent electrophysiology measurements. All tips and tubes used were RNase-free.In total 30 μg commercial E. coli strain BL21 (DE3) was cultured in LB broth and shaken overnight (230 × rpm) at 16 °C. The cells were pelleted by centrifugation at 12,000 × g for 20 min at 4 °C and washed with 1× PBS to remove residual LB broth. The deposition was collected and lysed in 1 mL RNAiso for Small RNA (Takara). After vigorous vortexing, the lysis solution was placed at room temperature (rt) for 5 min. To extract LMW RNA, the lysis solution was added with 200 μL chloroform and fully emulsified through vortexing. After standing for 5 min, the mixture was centrifuged at 12,000 × g for 15 min at 4 °C. When carefully removed from the centrifuge, the mixture was divided into three layers: the colorless supernatant containing LMW RNA, the white middle layer containing protein and the colored lower layer containing the organic solvent. The supernatant was transferred to a new centrifugal tube and added with 600 μL isopropanol. After thorough mixing, it was set for 10 min at 15–30 °C. The mixture was centrifuged at 12,000 × g for 10 min at 4 °C to collect the pellet. The pellet was washed with 1 mL 75% ethanol and centrifuged at 12,000 × g for 5 min at 4 °C and the supernatant was discarded. The pellet, which is the LMW RNA, was dried at room temperature for 30 min. A total of 25 μL of RNase-free water was then added to dissolve the LMW RNA. The concentration of the sample was determined by nanodrop. This LMW RNA sample was further characterized using 12% denaturing urea polyacrylamide gel electrophoresis. Finally, LMW RNA was stored at −80 °C for subsequent electrophysiology measurements. All tips and tubes used are RNase-free.E.coli (BL21) DE3 was extracted using MiniBEST Universal RNA Extraction Kit. E. coli strain BL21 (DE3) was cultured in LB broth and shaken overnight (230 rpm) at 16 °C. The cells were pelleted by centrifugation at 13,800 × g for 20 min at 4 °C and washed with 1× PBS water to remove residual LB broth. A total of 350 μL lysis Buffer RL was added to the collected cells. The lysate was transferred to a gDNA Eraser Spin Column and centrifuged at 13,800 × g for 1 min at 20 °C to remove the gDNA. The filtrate was added with isopycnic 70% ethanol and mixed thoroughly. The mixture was transferred to RNA Spin Column and centrifuged at 13800 × g for 1 min at 20 °C. The RNA Spin Column was added with 500 μL Buffer RWA and centrifuged at 13,800 × g for 30 s at 20 °C. The filtrate was discarded. The RNA Spin Column was added with 600 μL buffer RWB and centrifuged at 13800 × g for 3 min at 20 °C. The RNA Spin Column was placed onto 1.5 mL RNase Free Collection Tube and added with 30–200 μL RNase free water. After 5 min, HMW RNA was eluted by centrifugation at 13,800 × g for 2 min at 20 °C. The concentration was measurement using nanodrop and the desired fraction was determined using 1% agarose gel electrophoresis. Finally, HMW RNA was stored at −80 °C for subsequent electrophysiology measurements. Tips and tubes used were RNase-free.High molecular weight (HMW) RNA ( > 200 nt) of Further information on research design is available in the Supplementary InformationReporting SummaryDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4Supplementary Movie 5


N = 252) completed a choice task to assess valuation of monetary LLRs at bundle sizes of 1 (control), 3, and 9 rewards per choice . To control for the magnitude effect, the total reward amounts were held constant across conditions. Choice bundling significantly increased LLR preference (p < .001), with the largest effect observed at the largest bundle size. The descending bundle-size order produced significantly greater LLR preference than the ascending order (p < .05), although order did not significantly interact with bundle size. Difference scores between observed measures and those predicted by an additive model of hyperbolic discounting were small and not significantly different than zero, but were not equivalent to zero. Future research should investigate the clinical utility of choice bundling for reducing the maladaptive health behavior  with which delay discounting is associated.One method known to increase preference for larger, later rewards (LLRs) over smaller, sooner rewards (SSRs) is choice bundling, in which a single choice produces a series of repeating consequences over time. The present study examined whether effects of choice bundling on preference for LLRs: (1) increase with the number of rewards in the bundle ; (2) are independent of differences in reward magnitude between conditions; and (3) accord with predictions of an additive model of hyperbolic delay discounting, in which the value of a bundle of rewards can be expressed as the summed discounted value of all rewards in that bundle. Participants ( Rewards are devalued as a function of the delay until they are received—a process known as delay discounting , 2. In oV is the discounted value of the reward, A is its objective amount, D is its delay, and k is a free parameter that describes the degree of discounting. This model may be used to predict intertemporal choice, or preference between larger, later rewards (LLRs) and smaller, sooner rewards (SSRs). For example, in D1) or $500 immediately. The subjective value of the $1000 LLR is discounted proportional to the delay and the prevailing value of k ; however, the value of the immediate $500 SSR is undiscounted and equal to its objective, nominal value. In the choice in D1 falls below that of the undiscounted SSR; thus, When the subjective value of a reward is assessed across a range of delays, the nonlinear function that describes the data approximates the hyperbolic form :V=A1+kchoice bundling on preference for LLRs is predicted quantitatively by an extension of Vbundle) is equal to the summed discounted values of all rewards in the bundle  and three $500 SSRs . In the LLR option, the first reward is delivered after D1 (as in Panel A), and the second and third rewards are delivered after D2 and D3, respectively. In the SSR option, the first reward is delivered immediately (as in Panel A) and the second and third rewards are delivered after D1 and D2, respectively. Summing the discounted values of rewards in each bundle (according to k = 0.003) yields a summed value of LLR rewards ($477.33 + $313.48 + 233.37 = $1024.18) that exceeds the summed value of SSR rewards ($500 + $238.66 + 156.74 = $895.40). Thus, k) and the relative difference in objective amounts of these options have not changed. This shift in preference is due to the hyperbolic shape of the discounting curve in which the steepness of the curve  diminishes with increasing delay, which allows the discounted values of distal LLR rewards in the bundle to accumulate in Vbundle at a greater rate than those of bundled SSRs Next, participants completed the five-trial, adjusting-delay task  to assesall at once in lump sums. For example, you may see a question like this:You will now be presented with a series of choices between receiving different amounts of money at different points in time. In some questions, the amounts will be delivered Which would you rather receive?A. $500 noworB. $1000 in 3 weeksin installments over time. For example, you may see a question like this:In other questions, the total amounts of each choice option will be the same as those above ($500 and $1000), but these amounts will be delivered Which would you rather receive?A. $166.67 now, $166.66 in 3 weeks, and $166.67 in 6 weeksorB. $333.33 in 3 weeks, $333.34 in 6 weeks, and 333.33 in 9 weeks?These questions are hypothetical, but please choose your answer as if you will receive the money in the time frame(s) selected. Please pay close attention to the amount and time frame(s) of each option, and choose accordingly. There are no right or wrong answers in this task. Please take your time.D1) or $500 immediately. The position of these LLR and SSR options on the screen (left or right) was randomized on every question. The value of D1 started at three weeks and adjusted after each trial based on the previous choice until reaching an indifference delay , at which point the subjective values of the LLR and SSR choice options are approximately equal.D1, as described above, with additional rewards in the bundle delivered after D2, D3, etc. These additional delays were equal to D1 multiplied by the order of that delay in the series  was equal to D1. Likewise, any given SSR in a bundle was available D1 units sooner than its paired LLR.The bundle-size 3 and 9 conditions  were identical to the BS1 condition, with the following exceptions. Both the LLR and SSR choice options comprised either 3 (BS3) or 9 (BS9) rewards delivered over time. The delay to the first LLR in both conditions was D1 was adjusted across trials as described for the BS1 condition, with the values of additional delays in the bundle adjusted accordingly. In order to ensure that the total amounts available from the LLR and SSR choice options remained constant across bundle sizes, the monetary amounts of individual rewards in the bundle were equal to the amounts from the BS1 condition divided by the bundle size . Individual reward amounts were adjusted in $0.01 increments to correct for rounding errors, where needed  within- and between-subjects factors interaction in repeated-measures ANOVA, assuming an alpha value of .05, two groups, three repeated measures, and a correlation between repeated measures of .50.All analyses were performed in MINITAB statistical software version 20.1 . The approximate sample size was informed by a power analysis in which 260 participants provides 95% statistical power to detect at least a small , calculated as the adjusted value of D1 after the final trial of the five-trial adjusting-delay task. This is similar to measures of indifference delay used and validated previously with discrete rewards . Here, we note that the predictions of Such attempts to adapt choice bundling for clinical use, however, may first benefit from a more thorough understanding of its effects in more controlled laboratory studies, particularly in clinical samples . For example, as mentioned previously, identification of moderators of choice bundling effects may provide the ability to identify subpopulations likely to show optimal and suboptimal responses. Moreover, in order to be effective in clinical settings, choice bundling should be able to exert its effects across a wide range of choice contexts. Thus, examination of the effects of bundling on choice for monetary losses , health gains and losses, and other commodities may provide insight into the generality or specificity of observed effects We conclude that choice bundling parametrically increases willingness to wait for monetary LLRs over SSRs when controlling for differences in reward magnitude between conditions. Observed effects approximate, but are not equivalent to, those predicted by an additive model of hyperbolic delay discounting. Future research should be designed to identify predictors of heterogeneity in observed bundling effects, use more precise methods of measurement that may reduce heterogeneity, and evaluate the relative accuracy of alternative delay discounting models in predicting choice. Future research should also further explore the potential clinical utility of choice bundling, including examinations of its effects on intertemporal choice for health outcomes.S1 Figy axis to aid in interpretation.The left panel depicts ascending and descending order groups combined and the right panel depicts individual order groups (right panel). Gray and patterned bands represent 95% confidence intervals around model-predicted effects of bundle size, based on participants’ BS1 indifference delay values (control condition). Linear indifference delay values are scaled on the right (TIF)Click here for additional data file.S2 FigThe left panel depicts both order groups combined, the middle panel depicts the ascending order group, and the right panel depicts the descending order group. The horizontal gray band reflects the equivalence interval, defined as zero plus or minus 0.1 standard deviations of difference scores.(TIF)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


We found a substantial diagnostic correlation between SRH-based neuropathological diagnosis and H&E-stained frozen sections (κ = 0.8). The interpretability of intraoperative SRH imaging was demonstrated to be equivalent to the current standard method of H&E-stained frozen sections. Further research using this label-free innovative alternative vs. conventional staining is required to determine to which extent SRH-based intraoperative decision-making can be streamlined in order to facilitate the advancement of surgical neurooncology.Intraoperative histopathological examinations are routinely performed to provide neurosurgeons with information about the entity of tumor tissue. Here, we quantified the neuropathological interpretability of stimulated Raman histology (SRH) acquired using a Raman laser imaging system in a routine clinical setting without any specialized training or prior experience. Stimulated Raman scattering microscopy was performed on 117 samples of pathological tissue from 73 cases of brain and spine tumor surgeries. A board-certified neuropathologist — novice in the interpretation of SRH — assessed image quality by scoring subjective tumor infiltration and stated a diagnosis based on the SRH images. The diagnostic accuracy was determined by comparison to frozen hematoxylin–eosin (H&E)-stained sections and the ground truth defined as the definitive neuropathological diagnosis. The overall SRH imaging quality was rated high with the detection of tumor cells classified as inconclusive in only 4.2% of all images. The accuracy of neuropathological diagnosis based on SRH images was 87.7% and was non-inferior to the current standard of fast frozen H&E-stained sections (87.3 vs. 88.9%, The online version contains supplementary material available at 10.1007/s10143-021-01711-1. State-of-the-art intraoperative histopathological diagnosis in a neurosurgical setting is routinely performed using fast frozen section and H&E staining. This technique is limited by the amount of samples that can be processed in real-time in a routine clinical setting, as for a single sample there is a delay of 15–30 min from tissue removal to histopathological diagnosis. Therefore, an exhaustive histopathological sampling of tumor margins to assist neurosurgical decision-making in real-time is currently not available during routine tumor resections. Decisions on the extent of resection rather rely on subjective criteria such as visual and haptic impressions of the neurosurgeon, 5-aminolevulenic acid (5-ALA)-mediated fluorescence , intraopA technological breakthrough , 7 leadiCompared to conventional H&E staining, SRH has several advantages such as the ease of use, the time of data processing, and the digital nature of the obtained images. Digitalization allows remote consultations and image processing using automated classifiers and machine learning routines .At the core of the novel application of SRH is the fundamental understanding of the obtained SRH images. Despite obvious analogies between SRH images and H&E-stained sections, there are also differences. Firstly, tissue specimens used in SRH are squash preparations where characteristic cytoarchitectonic features of the tissue may be disrupted. Secondly, SRH images highlight cellular features — mainly tumoral and glia fibers — but also putative axons that are usually not evident on conventional H&E stains. The incorporation of intraoperative SRH imaging into clinical routine requires a close interdisciplinary exchange, whereby neurosurgeons and neuropathologists potentially with the support of expert vibrational spectroscopists become familiar with these new imaging modalities.Following the introduction of intraoperative SRH imaging at our institution, we have tested the applicability of this technique in a routine clinical setting . The aimn = 67) and stereotactic biopsies (n = 6). The usual surgical routine was neither disrupted nor influenced.Tissue samples were collected and imaged in accordance with the guidelines of the biobank at the Department of Neurosurgery, Medical Center University of Freiburg, with the approval of the local ethics committee of the University of Freiburg (protocol 5565/15) and with written informed patient consent. One hundred seventeen samples of putative pathological tissue from 73 consecutive surgical cases of brain, spine, and peripheral tumors (1.6 ± 0.9 range from 1 to 5 samples/case) were investigated using stimulated Raman scattering microscopy. Surgeries included tumor resections  and C-H3 bonds (primarily characteristic for proteins and DNA), respectively. The raw images were generated as sequential line scans of 1000 pixels in width at an imaging depth of 10 µm below the coverslip. The nominal pixel size was 467 nm. The images were automatically stitched and converted to SRH  images via subtraction and the use of a proprietary lookup table .Small (1–3 mm edge size) samples were compressed to a thickness of 230 µm on a sample holder designed for use in the Raman imaging system . SRH images were generated using a fiber-laser-based stimulated Raman scattering microscope . Briefly, the raw image data consisted of Raman shifts at wavenumbers 2845 cmsee ref. ), which n = 14) by a referee (D.H.H.).The SRH images were presented to a board-certified neuropathologist (D. E.), who had no prior experience in the interpretation of SRH. To evaluate SRH image quality, each image of putative pathological tissue was classified with respect to the assessability of tumor infiltration using a ranked score: (1) infiltration is certain or can be certainly excluded, (2) possible infiltration, and (3) inconclusive, where assessment of infiltration is not possible. Next, the medical information including age, tumor location, and an anonymized brief medical history otherwise identical to the information available at the time of the conventional neuropathological consultation was revealed. Then, based on all SRH images per case, the neuropathologist stated a diagnosis. As a guideline, the following categories were an optional diagnosis: high-grade glioma, low-grade glioma, metastatic brain or spinal tumor, meningioma, CNS lymphoma, pituitary adenoma, sub-/ependymoma, sarcoma, schwannoma, necrosis, reactive gliosis, ganglioglioma, hemangioblastoma, colloid cyst, epidermoid, unclear, or other tumors. The written SRH and H&E-based diagnosis were then classified into the final categories  were calculated using the F measurement function in the FlowSOM package in R (RStudio Version 1.4.1106). fficient  using thn = 63) with high-grade gliomas  and brain metastasis (n = 13) forming the largest groups , (2) recurrent disease (n = 16), and (3) primary metastatic disease with known potential origin outside the CNS (n = 18)  Fig. . While m18) Fig. . Example18) Fig. , 3b are n = 309) of putative pathological tissue, we established a ranked score based on the subjective confidence of a neuropathologist, who was novice in the interpretation of SRH images. The presence or absence of tumorous cells was assessed regardless of the underlying pathology. The score comprised 3 classes of tumor infiltration: class 1 certain infiltration (yes/no); class 2 possible infiltration; and class 3 inconclusive , fibrous tissue , white matter (n = 2) , and SRH images taken close to the sample border .To evaluate the interpretability of the obtained SRH images . Prior treatment such as radio- and/or chemotherapy decreased the interpretability of SRH images  vs. primary tumor cases  . Stratification of subjective interpretability of SRH into the six largest tumor categories  Fig. , the clacf. Fig.  revealedThe neuropathologist stated a diagnosis based on all available SRH images/case and the medical history. In 2 out of 73 cases , a diagnosis was not possible. Using the final neuropathological report as a ground truth, the overall accuracy of the diagnosis based on SRH imaging was 87.7% (64 of 73 cases) Fig. . The diap = 0.783, chi-squared), demonstrating that the diagnostic accuracy of SRH is en par with H&E-stained fast frozen sections, which was previously reported [p = 2.5E-10), with a diagnostic of correlation of κ = 0.84 . Similarly, the precision and recall for the diagnosis based on H&E-stained sections were 0.96 and 0.89 (p = 2.2E-16) with a diagnostic correlation of κ = 0.86 .A comparison of the SRH-based diagnosis to the current standard in neuropathological diagnosis based on fast frozen H&E-stained sections was performed in 63 cases Fig. . The accreported . The correported  and was p = 0.395, chi-squared test)  was compared to the groups of recurrent disease and metastatic tumors with a known primary disease outside the CNS (group 2 and 3) Fig. . The diast) Fig. .We report the first experience at our institution with the neuropathological interpretation of ex vivo SRH images, conducted in a routine clinical scenario without any specialized training. Compared to other novel tools for intraoperative histological examination in vivo such as fluorescein-assisted confocal laser endomicroscopy , 14 and In 67.6% of all images, we found a high confidence in the assessment of tumor infiltration by a neuropathologist, who was unfamiliar with the interpretation of SRH images. Post hoc analysis revealed that 6 samples contained cortex adjacent to the tumor; therefore, the class of “certain infiltration” also encompassed certain non-infiltrated  tissue Fig. . We obseNeuropathological diagnosis based on frozen sections of brain tumors in the case of re-operations was shown to have a significantly lower diagnostic accuracy compared to primary brain tumors  . As expeThe accuracy of the SRH-based neuropathological diagnosis from the first samples analyzed at our institution (including the very first) was 87.7% Fig. , which wThe SRH-based diagnosis was most accurate for solid primary tumors . Misclassifications occurred in cases of recurrent pre-treated tumors, reactive gliotic tissue, and HGGs which were also difficult to interpret in conventional H&E-stained tissues Fig. . SamplinAs previously reported in a prospective trial by Eichberg et al. where SRH and conventional histology had a similar diagnostic accuracy , we founWe anticipate that neurosurgeons, neuropathologists, and potentially neuroradiologists along with radiotherapists will in future become more familiar with the interpretation of SRH images, which will yield even more accurate interpretations. In addition, it is anticipated that appropriate deep learning/machine learning strategies  will augThe first positive results reported here together with promising results attesting the diagnostic accuracy of SRH-based imaging similar to the current standard , 17, 18 In a possible future surgical scenario of a brain tumor resection Fig. , after eSupplementary file1 (DOCX 3249 KB)Below is the link to the electronic supplementary material.


During HIV-1 maturation, Gag and Gag-Pol polyproteins are proteolytically cleaved and the capsid protein polymerizes to form the honeycomb capsid lattice. HIV-1 integrase (IN) binds the viral genomic RNA (gRNA) and impairment of IN-gRNA binding leads to mis-localization of the nucleocapsid protein (NC)-condensed viral ribonucleoprotein complex outside the capsid core. IN and NC were previously demonstrated to bind to the gRNA in an orthogonal manner in virio; however, the effect of IN binding alone or simultaneous binding of both proteins on gRNA structure is not yet well understood.Using crosslinking-coupled selective 2′-hydroxyl acylation analyzed by primer extension (XL-SHAPE), we characterized the interaction of IN and NC with the HIV-1 gRNA 5′-untranslated region (5′-UTR). NC preferentially bound to the packaging signal (Psi) and a UG-rich region in U5, irrespective of the presence of IN. IN alone also bound to Psi but pre-incubation with NC largely abolished this interaction. In contrast, IN specifically bound to and affected the nucleotide (nt) dynamics of the apical loop of the transactivation response element (TAR) and the polyA hairpin even in the presence of NC. SHAPE probing of the 5′-UTR RNA in virions produced from allosteric IN inhibitor (ALLINI)-treated cells revealed that while the global secondary structure of the 5′-UTR remained unaltered, the inhibitor treatment induced local reactivity differences, including changes in the apical loop of TAR that are consistent with the in vitro results.. This study, together with previous probing experiments, suggests that IN and NC binding in vitro and in virio lead to only local structural changes in the regions of the 5′-UTR probed here. Accordingly, disruption of IN-gRNA binding by ALLINI treatment results in local rather than global secondary structure changes of the 5′-UTR in eccentric virus particles.Overall, the binding interactions of NC and IN with the 5′-UTR are largely orthogonal in vitroThe online version contains supplementary material available at 10.1186/s12977-021-00582-0. Understogenesis .Allosteric IN inhibitors  are a promising class of anti-retroviral drugs –20. ALLIDisruption of proper CA core formation around the vRNP appears to be a particularly attractive drug target , 3. HoweWe applied crosslinking-coupled selective 2′-hydroxyl acylation analyzed by primer extension (XL-SHAPE), a single-nt resolution technique that allows the identification of both direct protein interaction sites and protein binding-induced RNA conformational changes . ChangesWe first used SHAPE to probe the 352-nt HIV-1 5′-UTR RNA in the absence of added protein factors to ensure the RNA is properly folded. To avoid conformational heterogeneity due to monomer-dimer equilibrium, a monomeric mutant 5′-UTR-ΔDIS construct was used for all in vitro probing experiments, wherein the palindromic dimerization initiation signal (DIS) loop (AAGCGCGCA) was mutated to a stable GAGA tetraloop . The seqWe present probing data for the following protein binding conditions: NC alone, IN/IBD alone and the two proteins together with different order of addition. IN/IBD refers to a complex between the IN-binding domain (IBD) of lens-epithelium-derived-growth-factor (LEDGF)/p75 and an F185H mutant form of HIV-1 IN. The IBD helps improve the solubility of IN and stabilizes the tetrameric form of IN that displays high binding affinity to RNAs , 47–49. A summary of the results for the 5′-UTR under each protein binding condition is presented in Figs. TAR plays a major role in stimulating viral transcription , whereasWhen NC was preincubated with the 5′-UTR before IN/IBD addition, the C39 crosslinking site observed for IN/IBD alone was lost Fig. . The preUpon binding of NC alone, numerous crosslinking sites were observed in the single-stranded region of U5 Fig. . This reLys,3, the HIV-1 reverse transcription primer, and is important for reverse transcription initiation [Lys,3 anticodon domain [Lys,3 primer anneals. NC binding also increased the SHAPE reactivity at these crosslinking sites, indicating that NC binding may make the PBS region more accessible to the tRNALys,3 primer. IN/IBD alone crosslinked to U166 near the TLE hairpin and C208, downstream from the PBS, resulting in mixed decreased and increased SHAPE reactivity  with impaired RNA binding  was test3A with iHIV-1 virions incorporate two copies of gRNA (~ 9.4 kilobases each), ~ 2500 copies of NC, and ~ 125 copies of IN , 65. TheNext, we performed in virio SHAPE probing of RNA extracted from virions to assess how inhibition of IN-RNA binding by ALLINI treatment affects global and local 5′-UTR structures. To abolish IN-RNA binding, viral producer cells were exposed to BI-D during HIV-1 egress . In the Upon BI-D treatment, some local SHAPE reactivity changes were, however, observed. Decreased SHAPE reactivity was detected throughout the 5′-UTR, with the most significant changes occurring in the TLE and TAR apical loops, as well as the PBS Fig. . The mosA previous CLIP-seq study of RNA extracted from HIV-1 virions suggested that U31 in the apical loop of TAR is a direct IN interaction site . In our 2+ from the NC zinc fingers, which results in defective NC-RNA binding, led to increased SHAPE reactivity changes in several single-stranded regions of Psi: two bulges in SL1  and the apical loop of SL2 [A previous in virio SHAPE study suggested that the ejection of Znp of SL2 . Our datp of SL2 , 66, 67,p of SL2 , 68, 69.p of SL2 .IN and NC were previously demonstrated to bind to the gRNA in an orthogonal manner in virio . Here, o2+ from NC zinc fingers did not change the overall structure of the 5′-UTR in virio [In virio SHAPE studies performed after treating producer cells with the ALLINI BI-D revealed that the lowest-energy secondary structure of the 5′-UTR was the same as the DMSO control Fig. : Fig. S9in virio . Therefoin virio  collectiin virio , 71. TheOur in vitro experiments suggested that NC specifically interacts with Psi, independent of the presence of IN. Treatment with ALLINIs was previously shown not to affect NC-RNA binding . ConsistDuring viral maturation, the stability of the HIV-1 RNA dimer increases in a stepwise manner, and this process largely depends on the HIV-1 protease , 73. TheOur detailed investigation of in vitro binding of NC and IN with the HIV-1 5′-UTR is consistent with the conclusion that binding is largely orthogonal. NC binds preferentially to the UG-rich region proximal to the U5:AUG stem and Psi, while IN binding impacts nt flexibility in the TAR/polyA domains. The global secondary structure of the 5′-UTR remained unaltered in native vs. eccentric virions produced in the presence of ALLINIs. Instead, inhibition of IN-RNA interactions by ALLINIs changed local RNA backbone flexibility at a few specific sites throughout the 5′-UTR, including the apical TAR loop.6-tagged IN(F185H) and His6-tagged IBD (residues 307–460) [Escherichia coli and the cells were grown at 37 °C in LB containing 120 µg/mL ampicillin for IN and 50 µg/mL kanamycin for IBD. The cells were grown to ~ 0.6–0.8 OD600, followed by 1 mM isopropyl β-d-1-thiogalactopyranoside induction for 4 h at 37 °C. Both IN and IBD cell pellets were lysed together in 50 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), pH 7.5, 1 M NaCl, 10% glycerol, 2 mM 2-mercaptoethanol (BME) and protease inhibitor. After sonication, the filtered supernatant was subjected to nickel-affinity and heparin column purification as previously described [6-tagged IBD alone. His6-tagged IN was purified as described [His307–460) , 75 were307–460)  was usedescribed . This waescribed .HIV-1 NC protein (BH10 strain) was purchased as a synthetic peptide from New England Peptide .6 M/cm.HIV-1 352-nt 5′-UTR-ΔDIS (NL4-3 strain) was prepared by in vitro transcription using FokI-linearized pUC19 plasmid templates and T7 RNA polymerase, as described . This RN2, followed by incubation at 37 °C for 30 min and incubation on ice for at least 30 min.Prior to all XL-SHAPE probing experiments, the HIV-1 5′-UTR-ΔDIS RNA (4 µM) was refolded in 50 mM HEPES, pH 7.5 by heating to 80 °C for 2 min, 60 °C for 2 min, addition of 1 mM MgCl2. Diluted RNA (90 µL) was mixed with either 10 µL of neat DMSO or 10 µL of N-methylisatoic anhydride  (8 mM in DMSO). The SHAPE reactions were incubated at 37 °C for 45 min and the RNAs were recovered by ethanol precipitation.An initial SHAPE probing experiment was performed to test whether the RNA was properly folded in the absence of bound protein. For this experiment, the folded RNA was diluted to 0.1 µM in 20 mM HEPES, pH 7.5 and 1 mM MgCl2 and 100 mM NaCl. The following protein concentrations were used: 1, 0.7, 0.3 and 0 µM for NC; 0.3, 0.2, 0.1 and 0 µM for IN/IBD, and 0.3, 0.1, 0 µM for IN. For XL-SHAPE probing experiments with BI-D-treated IN/IBD, 10-fold molar excess of BI-D (in DMSO) was added to each diluted IN/IBD complex, followed by incubation at room temperature for 1 h. For XL-SHAPE experiments with both NC and IN/IBD, the folded RNA was diluted to 0.125 µM and first incubated with 1.25 µM NC or 0.25 µM IN/IBD for 2 h on ice, in the same binding reaction buffers as described above. IN/IBD or NC was then added to NC+RNA complex or IN/IBD + RNA complex, respectively, and incubated for another 2 h on ice in the same binding reaction buffers. The following protein concentrations were used: 0.2, 0.15, 0.1 or 0 µM for IN/IBD; 4 , 1, 0.7, 0.3 or 0 µM for NC. The addition of the second protein also led to dilution of RNA to 0.1 µM, preincubated NC to 1 µM, and preincubated IN/IBD to 0.2 µM.For XL-SHAPE probing experiments with NC, IN/IBD, or IN, the folded RNAs were diluted to 0.1 µM and incubated with each protein for 2 h on ice, in a buffer containing 20 mM HEPES, pH 7.5, 1 mM MgCl2) on ice in a UVP UV crosslinker CL-1000 model . Two control XL experiments were also performed without proteins: an RNA-only reaction was exposed to UV light to assess UV damage and a second RNA-only reaction was incubated on ice in the absence of UV irradiation. After SHAPE reaction or UV crosslinking radiation, all the samples were treated with 10 µL of 5% SDS and 1 µL of Proteinase K , and incubated at 55 °C for 60 min. The RNAs were recovered by phenol–chloroform extraction and ethanol precipitation.After binding, half of the samples were used for SHAPE probing and half were used for UV crosslinking. For SHAPE probing, 10 µL NMIA (8 mM in DMSO) was added into 90 µL of each of the binding reactions. Control reactions without proteins contained either neat DMSO or NMIA (in DMSO). The SHAPE reactions were incubated at 37 °C for 45 min. For XL probing, each of the binding reactions (90 µL) was exposed to UV light , which was used to generate the secondary structure representation. The differences between the XL and SHAPE reactivity of the control and protein-bound samples were compared using an unpaired, two-tail student’s t-test. Absolute reactivity differences of ≥ 0.3 with a p value < 0.05 were considered to be statistically significant. Dose-dependent reactivity changes in the case of protein binding were an additional prerequisite for establishing significance. At least 3 independent trials were performed for all in vitro XL-SHAPE experiments. The raw data of all XL-SHAPE experiments can be found in Additional file The primer extension and capillary electrophoresis (CE) experiments were performed as described previously , 78. The2. Cell-free HIV-1NL4−3 viral particles were produced by transfecting HEK293T cells in 15-cm cell culture plates with 30 µg pNL4-3 plasmid DNA [HEK293T cells were propagated in humidified incubators at 37 °C in Dulbecco’s modified Eagles medium supplemented to contain 10% fetal bovine serum (FBS), 100 IU/mL penicillin, and 100 µg/mL streptomycin in the presence of 5% COsmid DNA  per platsmid DNA .Primer extension and CE analyses were performed with ~ 1.2 pmol of NMIA-modified or control RNA, as described above. The CE data were also analyzed as described above. Absolute SHAPE reactivity differences of ≥ 0.3 between BI-D-treated and DMSO-treated control samples were considered significant. Two independent trials were performed for in virio SHAPE experiments.Additional file 1: Figure S1. SHAPE reactivity-constrained lowest energy secondary structure of the 352-nt HIV-1 5′-UTR-ΔDIS RNA. The secondary structure model was generated by applying averaged normalized SHAPE reactivity from three independent trials as pseudo free-energy constraints. Nucleotides are colored in accordance to SHAPE reactivity as indicated in the key. Nucleotides that could not be analyzed are shown in grey. In this construct, the Psi DIS sequence (AAGCGCGCA) was replaced by a GAGA tetraloop (boxed). Nucleotide numbering is according to the WT HIV-1 5′-UTR sequence.Additional file 2: Figure S2. Results of in vitro XL-SHAPE analysis of 352-nt HIV-1 5′-UTR-ΔDIS RNA in TAR/polyA region, upon binding to (A) NC; (B) IN/IBD; (C) NC + IN/IBD (NC incubated first) and (D) IN/IBD + NC (IN/IBD incubated first). Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. Identified crosslinking sites are labeled with stars. All identified sites had reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with RNA alone control (A and B), RNA + NC (C), or RNA + IN/IBD (D). Results are based on the average of at least 3 independent experiments. Nucleotides that could not be analyzed are shown in grey.Additional file 3: Figure S3. Results of in vitro XL-SHAPE analysis of 352-nt HIV-1 5′-UTR-ΔDIS RNA near the U5:AUG region, upon binding to (A) NC; (B) IN/IBD; (C) NC + IN/IBD (NC incubated first) and (D) IN/IBD + NC (IN/IBD incubated first). Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. Identified crosslinking sites are labeled with stars. All identified sites had reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with RNA alone control (A and B), RNA + NC (C), or RNA + IN/IBD (D). Results are based on the average of at least 3 independent experiments. Nucleotides that could not be analyzed are shown in grey. Nucleotide numbering is according to the WT HIV-1 5′-UTR sequence.Additional file 4: Figure S4. Results of in vitro XL-SHAPE analysis of 352-nt HIV-1 5′-UTR-ΔDIS RNA in the PBS/TLE region, upon binding to (A) NC; (B) IN/IBD; (C) NC + IN/IBD (NC incubated first) and (D) IN/IBD + NC (IN/IBD incubated first). Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. Identified crosslinking sites are labeled with stars. All identified sites had reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with RNA alone control (A and B), RNA + NC (C), or RNA + IN/IBD (D). Results are based on the average of at least 3 independent experiments.Additional file 5: Figure S5. Results of in vitro XL-SHAPE analysis of 352-nt HIV-1 5′-UTR-ΔDIS RNA in the Psi region, upon binding to (A) NC; (B) IN/IBD; (C) NC + IN/IBD (NC incubated first) and (D) IN/IBD + NC (IN/IBD incubated first). Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. Identified crosslinking sites are labeled with stars. All identified sites had reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with RNA alone control (A and B), RNA + NC (C), or RNA + IN/IBD (D). Results are based on the average of at least 3 independent experiments. Nucleotides that could not be analyzed are shown in grey. The Psi DIS sequence (AAGCGCGCA) was replaced by a GAGA tetraloop (boxed). Nucleotide numbering is according to the WT HIV-1 5′-UTR sequence.Additional file 6: Figure S6. XL-SHAPE analysis of IBD binding to the 352-nt HIV-1 5′-UTR-ΔDIS RNA. Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. All identified sites have reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with the no protein control. Results are based on the average of at least 3 independent experiments. Other information is as noted in the legend to Fig. S1.Additional file 7: Figure S7. XL-SHAPE analysis of IN  binding to the 352-nt HIV-1 5′-UTR-ΔDIS RNA. Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. All identified sites have reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with the no protein control. Results are based on the average of at least 3 independent experiments. Other information is as noted in the legend to Fig. S1.Additional file 8: Figure S8. XL-SHAPE analysis of near-physiological stoichiometry of NC binding to the HIV-1 5′UTR-ΔDIS/IN/IBD complex. Sites with decreased and increased SHAPE reactivity upon protein binding are indicated by green and red arrowheads, respectively. Identified crosslinking sites are labeled with stars. All identified sites have reactivity changes of ≥ 0.3 and p < 0.05 based on unpaired, two-tailed Student’s t-tests, compared with the RNA + IN/IBD control. Results are based on the average of at least 2 independent experiments. Other information is as noted in the legend to Fig. S1.Additional file 9: Figure S9. In virio SHAPE reactivity-constrained lowest energy secondary structure of the HIV-1 5′-UTR after treatment of cells with DMSO. The secondary structure model was generated by applying averaged normalized SHAPE reactivity from two independent trials as pseudo free-energy constraints. Nucleotides are colored according to SHAPE reactivity as indicated in the key. Nucleotides that could not be analyzed are shown in grey. The tRNALys,3 annealing site is indicated by a black line.Additional file 10. Raw data files for all of the XL-SHAPE studies reported here.


RNA editing—primarily conversion of adenosine to inosine (A > I)—is a widespread posttranscriptional mechanism, mediated by Adenosine Deaminases acting on RNA (ADAR) enzymes to alter the RNA sequence of primary transcripts. Hence, in addition to somatic mutations and alternative RNA splicing, RNA editing can be a further source for recoding events. Although RNA editing has been detected in many solid cancers and normal tissue, RNA editing in chronic lymphocytic leukemia (CLL) has not been addressed so far. We determined global RNA editing and recurrent, recoding RNA editing events from matched RNA-sequencing and whole exome sequencing data in CLL samples from 45 untreated patients. RNA editing was verified in a validation cohort of 98 CLL patients and revealed substantially altered RNA editing profiles in CLL compared with normal B cells. We further found that RNA editing patterns were prognostically relevant. Finally, we showed that ADAR knockout decreased steady state viability of MEC1 cells and made them more susceptible to treatment with fludarabine and ibrutinib in vitro. We propose that RNA editing contributes to the pathophysiology of CLL and targeting the RNA editing machinery could be a future strategy to maximize treatment efficacy. Alu-sites. Alu elements are short, repetitive DNA stretches with more than one million copies distributed throughout the genome. Pairs of inverted copies of Alu elements are preferred targets for ADARs [Alu elements has been used as an indicator for global editing activity [Recent data from whole-exome and whole-genome sequencing approaches revealed a complex genomic landscape for many cancer entities –3. In ador ADARs . Consequactivity , 8. Howeactivity –13.Chronic lymphocytic leukemia (CLL) is a highly heterogeneous disease  and, acchttps://www.ncbi.nlm.nih.gov/sra. In addition, RNA sequencing and clinical data from CLL samples and normal B cells were downloaded from the European Genome-phenome Archive (EGAS00001000374) [Peripheral blood from chemo-naïve CLL patients participating in a previously reported clinical trial   with fir1000374) .We studied RNA editing in 45 previously untreated CLL patients prior to first line therapy with fludarabine/rituximab combined with escalating doses of lenalidomide  in CLL samples from RNA sequencing data as previously described [Alu regions, RNA editing in Alu sites reflects the overall A > I RNA editing activity of a particular sample. We measured all edited adenosine within Alu elements (unique Alu editing sites) as well as the averaged editing level across all Alu adenosines, weighted by their relative expression  [Alu editing sites and AEI did not correlate with ADAR p110 or p150 expression in the IGHV unmutated samples  . We deteles Fig. .Fig. 1A p < 0.05; supporting Table As we observed RNA editing activity to correlate with ADAR levels only in IGHV mutated CLL, we asked whether a set of recently identified editing cofactors  would beAlu repeats is a proxy for global RNA editing activity, but gives little information on recoding events, as those are mostly located outside Alu elements. In order to determine RNA editing in coding regions, we next screened for RNA-DNA single nucleotide differences (RDDs) from matched RNA-sequencing/whole-exome sequencing (WES) data from our 45 patients. Screening for differences in matched RNA/DNA pairs revealed a total of 80,150 RDDs in 45 samples. Similar to a previous report [Alu regions (6864 events) as determined by the UCSC repeat masker track, were mostly of the A > I type, consistent with the finding that A > I editing occurs predominantly in Alu regions , allowing comparison of CLL RNA editing with that from different normal B cell subsets. From these RNA-seq data, we extracted A/G variant frequencies at the 19 editing sites. While in most samples from the CLL cohort from Ferreira et al the coverage of the CDK13 gene was too low for assessing RNA editing - and we hence excluded the four CDK13 sites from all further analyses—we found that the remaining 15 out of these 19 sites were also robustly edited in the validation cohort. Moreover, depending on the IGHV mutation status, editing depths  from most of these sites were significantly different compared with normal B cell subsets, indicating aberrant RNA editing in CLL. While normal B cell subsets had distinctive RNA editing depths for each site, RNA editing in CLL cells was highly variable , underpinning increased variability in RNA editing activity in malignant cells. Conversely, expression of ADAR isoform p150 is significantly higher in CLL compared with normal B cells and corroboratively to the AGMT-REVLIRIT cohort, ADAR expression is slightly increased in IGHV unmutated samples  [p = 0.09; log rank test, Fig. To validate the results from the Ferreira cohort, we performed hierarchical clustering of editing sites from the AGMT-REVLIRIT cohort (n = 45) , which yp = 0.0005  was shown to frequently associate with poor clinical outcome in solid cancer [A to I RNA editing was recently shown to substantially contribute to transcript diversification in health and disease and an increased global editing activity (determined by d cancer . In contd cancer . This asd cancer , 27 wereAlu-elements prevents their binding to dsRNA sensors, which leads to a robust interferon response [RNA editing patterns were highly specific for normal naïve and memory B cells, corroborating recent results that ADAR mediated RNA editing is required for normal B cell development . For CLLresponse , 31. In response , 33. In response . Hence, Alu editing in MEC1 cells.So far, many cancer cell lines have shown increased vulnerability toward type-I interferon signaling upon ablation of ADAR . ResultsSummarizing, we showed that RNA editing substantially contributes to protein recoding in CLL. Our data on MEC1 cells further suggest that interference with ADAR function renders CLL cells more susceptible to distinct therapeutic regimens in vitro, which makes ADAR an interesting target for future combination-treatment strategies.supplemental methodssupplemental figure and table legendsFigure S1Figure S2Figure S3Figure S4Figure S5Figure S6Figure S7Figure S8Figure S9Figure S10Table S1Table S2Table S3Table S4Table S5Table S6Table S7Table S8Table S9Table S10Table S11Table S12


Ustilago maydis. For this initial survey, we examined EV-enriched fractions from axenic filamentous cultures that mimic infectious hyphae. EV-associated RNAs were resistant to degradation by RNases and the presence of intact mRNAs was evident. The set of mRNAs enriched inside EVs relative to the fungal cells are functionally distinct from those that are depleted from EVs. mRNAs encoding metabolic enzymes are particularly enriched. Intriguingly, mRNAs of some known effectors and other proteins linked to virulence were also found in EVs. Furthermore, several mRNAs enriched in EVs are also upregulated during infection, suggesting that EV-associated mRNAs may participate in plant-pathogen interactions.Extracellular vesicles (EVs) can transfer diverse RNA cargo for intercellular communication. EV-associated RNAs have been found in diverse fungi and were proposed to be relevant for pathogenesis in animal hosts. In plant-pathogen interactions, small RNAs are exchanged in a cross-kingdom RNAi warfare and EVs were considered to be a delivery mechanism. To extend the search for EV-associated molecules involved in plant-pathogen communication, we have characterised the repertoire of EV-associated mRNAs secreted by the maize smut pathogen,  Extracellular vesicles (EVs) are ubiquitously secreted from cells, carrying a diverse array of molecular cargos. The role of EVs in intercellular signalling and communication is particularly interesting, as they can facilitate mass delivery of otherwise intracellular molecules across the extracellular space. EV-associated molecules can induce physiological changes in the recipient cells . In pathCandida albicans is important for biofilm formation and antifungal resistance [Cryptococcus gattii effectuate long-distance coordination of virulence between fungal cells engulfed in different macrophages; EVs from a hypervirulent strain trigger rapid proliferation of less virulent strains in the phagosome [Investigations on fungal EVs have identified associated proteins , RNAs 66, lipidssistance . Furtherhagosome . While Ehagosome  and promhagosome ,13,14, mhagosome .Arabidopsis thaliana carry small RNAs (sRNAs) that silence virulence genes in the grey mould fungus Botrytis cinerea [Phytophthora capsici [A. thaliana EVs additionally contain “tiny RNAs” [Sclerotinia sclerotiorum [The role of EVs in plant-pathogen interaction is not yet well understood, although they have been frequently observed at various plant-fungal interfaces ,17,18 Bi cinerea  and the  capsici  during iny RNAs”  and variny RNAs” . In anotrotiorum .Zymoseptoria tritici [Fusarium oxysporum f. sp. vasinfectum  have beproducer . While sFungal EVs have been found to contain all types of RNA, the majority of the cargo being shorter sRNAs and tRNAs, but also mRNAs and rRNAs . sRNA efUstilago maydis is a biotrophic fungal pathogen of maize [U. maydis and maize cells during biotrophic infection [of maize , which cof maize . It is aof maize  and has of maize . This manfection , suggestnfection .U. maydis is the dikaryotic filament, formed by mating of compatible sporidia [U. maydis as an ideal system for an initial survey of EV cargo mRNAs in plant pathogens.In nature, the infectious form of sporidia . Filamensporidia ,36. Heresporidia . AB33 insporidia ,36. Henc600 1.0 ± 0.1 in complete medium [w/v) to induce filamentation as described previously [g) for 10 min. Cell pellets were snap-frozen and saved for RNA extraction. The supernatant was passed through 0.45 µm filter . The filtrate was ultracentrifuged with 45 Ti rotor (Beckman Coulter) at 36,000 rpm , 4 °C, for 1 h. Resulting pellet was resuspended in phosphate buffered saline  and treated with PBS (mock), 0.1 µg/µL RNase A (ThermoFisher), or RNase A with 0.1% (v/v) Triton X-100  at 4 °C for 10 min. Protease treatment was not included as incubation at the recommended temperature 37 °C alone compromised sample quality, while protease treatment itself did not produce a qualitative difference. The treated EVs were “washed” by adding PBS and repeating ultracentrifugation. The final pellets were resuspended in PBS and passed through qEVorginal/70 nm size exclusion chromatography columns . Fractions enriched in EVs were collected and concentrated with Vivaspin-500 MWCO 1000 kDa concentrator . EVs were snap-frozen and stored at −80 °C until required.Initial sporidial cultures of strain AB33 from Brachmann et al.  were groe medium , suppleme medium  with 2% eviously . Filamenv/v) in PBS, then 1% glutaraldehyde (v/v). Samples were contrasted with 4% uranyl acetate (w/v), 2% methylcellulose (w/v) and examined with an EM902 transmission electron microscope . EVs in PBS were stained with 8 µM FM4-64  and examined with a Zeiss Axio Imager M1, equipped with a Spot Pursuit CCD camera  and Plan Neofluar objective lens . FM4-64 was excited with an HXP metal halide lamp (LEj) in combination with filter set for mCherry . Microscope operation and image processing were conducted with MetaMorph . Differential interference contrast images of sporidia and filament cells were obtained with the same instrument with a 63× objective (NA 1.25).Grids with EV samples for transmission electron microscopy (TEM) were prepared as previously described with a few modifications . EVs in TM (ThermoFisher) was used for EV RNA samples for the first extraction and for all samples in the re-extraction. RNA quality was controlled with BioanalyzerTM RNA 6000 Nano  assay using the eukaryote setting. Libraries for sequencing were generated with NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina together with NEBNext® Poly(A) mRNA Magnetic Isolation Module according to the manufacturer’s instructions . Libraries were quality controlled with High Sensitivity DNA Kit on Bioanalyzer (Agilent) and quantified on Qubit 2.0 Fluorometer (ThermoFisher) with ds HS Assay Kit. Sequencing was performed in the Genomics Service Unit of LMU Biocenter, on Illumina MiSeq with v3 chemistry with 2 × 150 bp paired-end reads .RNA was extracted from EVs and filament samples using standard methods for TRI-reagen LS (Sigma) and TRI-reagent (Sigma), respectively, with a few modifications. Extracted RNA was treated with DNase I (ThermoFisher) as per manufacturer’s instructions and re-extracted with TRI-reagent LS. Coprecipitant GlycoBlueUstilago maydis genome  [Raw sequencing reads were quality checked with FastQC (November 2014) , adapterENSEMBL) ,42, usinENSEMBL)  with knoENSEMBL)  using thENSEMBL)  and thenENSEMBL) . To corrENSEMBL) . The DegENSEMBL) . Raw reaENSEMBL)    and the For comparison of 3′ untranslated regions (3′UTRs) of mRNAs enriched in EVs versus those depleted from EVs, UTRs were partially annotated based on the mapped RNA-seq reads. Reads with gaps larger than 10 kb were removed with BBMap (version 38.87 ). Reads ® High-Fidelity DNA Polymerase (NEB) with 35 cycles. Annealing temperature was 60 °C and extension time was 50 s for all reactions. For RT-qPCR, 100 ng of RNA was used as input for first-strand cDNA synthesis. The cDNA was diluted 16-fold and 2 µL was used per reaction in qPCR, following an otherwise standard Luna® Universal qPCR Master Mix (NEB) protocol in Stratagene Mx3000P (Agilent). Relative gene expression analysis was carried out using the 2^-ddCT method [RNA extracted from RNase-treated EVs and filament cells were cleaned, concentrated with RNA Clean & Concentrator-5 . 200 ng of cleaned RNA was used as template for first-strand cDNA synthesis with SuperScript™ IV First-Strand Synthesis System (ThermoFisher), with an inclusive RNase H treatment as according to the manufacturer’s instructions. The first-strand reaction was 8-fold diluted and 1 µL was used as template for PCR with 100 nM primers, following an otherwise standard protocol for PhusionU. maydis hyphae secrete EVs with appreciable RNA cargo, we have developed a robust protocol for EV isolation (or enrichment) from U. maydis cultures. EVs were isolated from filaments of strain AB33 [First, to check whether ain AB33 , inducedTM profiles of EV-associated RNAs were examined following RNase treatment of EVs prior to RNA extraction. While RNA extracted from EVs treated with RNase alone  peaks and a larger, broader peak of less than 200 nt (n = 4) in EV samples  value of 3.6 ± 1.7, compared to 9.8 ± 0.1 for filament cell RNA n = 4; d. This icell RNA ,63. The cell RNA ,63.U. maydis EVs, sequencing was carried out on poly(A)-enriched libraries of RNA from mock-treated EVs, RNase-treated EVs, and the corresponding hyphal filaments , of which 758 transcripts were ≥2-fold enriched within EVs and 1189 were depleted from EVs to the same extent , and 1.523 kb for those in neither category  in our RNA-seq experiment. Annotations of untranslated regions (UTRs) are not available for e in EVs d. Furthee in EVs d.For verification, four enriched mRNA candidates, that have previously been shown to be upregulated during infection , were chU. maydis seem to play a role in nutrient acquisition rather than having a direct virulence function [U. maydis [With the notion that mRNAs enriched inside EVs are more likely to be functionally important, we carried out GO term overrepresentation analysis on transcripts differentially associated with EVs. Indeed, mRNAs relatively enriched in EVs showed overrepresentation of different functional GO terms from those that are depleted . Transcrfunction . Overrepfunction , and sep. maydis ,68.−13). These results suggest that subcellular localisation of mRNAs may affect their loading into EVs: mRNAs associated with intracellular vesicles are more likely to be loaded into EVs, while those that require translation at the rough ER are relatively depleted from EVs.Transcripts that are relatively depleted from EVs  were involved in transmembrane transport, cell wall processes, signal transduction, and several ER-related process such as protein glycosylation, glycolipid metabolism, ER organisation, and the ER-associated protein degradation (ERAD) pathway a. Accordp = 1.3 × 10−19) and less cytosine (p = 1.1 × 10−7) and uridine (p = 9.6 × 10−3) compared to the depleted sequences. Accordingly, A-rich 4-mers were significantly increased in frequency among the enriched 3′UTR sequences compared to the depleted , with the assumption that these are more likely to have been loaded in EVs to serve a biological function (in planta (g:SCS padj = 1.43 × 10−4). In essence, we observe an enrichment of mRNAs in EVs that can be linked to filament induction and infection.We have examined the most highly enriched mRNAs . On theU. maydis filaments, used as a surrogate for infectious hyphae in planta  protocol and examined EVs produced in axenic cultures of n planta . Omics silaments ,35,36 Thbona fide effectors and several secreted proteins linked to virulence in AB33 filaments and their EVs  in multivesicular endosomes (MVEs) that are released upon fusion with the plasma membrane, while microvesicles are formed by direct budding from the plasma membrane . Hence, . maydis . DiscoveU. maydis EVs (U. maydis-maize interaction: (1) fungal mRNA fragments lead to silencing of maize genes or (2) full-length fungal mRNAs are translated into multiple effector proteins in maize cells.Since mRNAs enriched within EVs encode proteins with functions distinct from those that are depleted, we suspect a biological reason for preferentially exporting these mRNAs. Since several transcripts upregulated during infection are enriched in ydis EVs a, such mU. maydis has lost the conventional RNAi machinery [Bradyrhizobium japonicum participate in silencing of plant genes involved in root hair development to promote nodulation [Bidirectional, cross-kingdom RNA interference (RNAi) is a widespread mechanism of plant-pathogen interaction . Diverseachinery . Therefodulation .Paracoccidioides spp., mRNA cargos of EVs were found to be translation-competent in a heterologous, in vitro system [Effector delivery in the form of mRNA could be highly cost-effective for the pathogen, if they can be translated in the correct location at required amplitude in the host cell. In support of this hypothesis, proof of principle studies using elegant reporter systems have demonstrated that EV-associated mRNAs are transferred and translated de novo in the recipient cells ,89. A reo system . Given tU. maydis is accompanied by extensive reprogramming of metabolism, redox status, and hormone signalling in the infected plant tissues [U. maydis also harbours metabolic enzymes lacking signal peptides that can synthesise [Verticillium dahliae and Phytophthora sojae [U. maydis present an opportunity to discover novel RNA effectors in plant pathogenic fungi.It is interesting that the set of mRNAs enriched in EVs and upregulated during infection are overrepresented in metabolic enzymes and oxidoreductases . Biotrop tissues . The fun tissues  and sali tissues ), and in tissues . U. maydnthesise ,95, degrnthesise , or potenthesise . Intrigura sojae . SimilarU. maydis and identified mRNAs that are enriched within EVs compared to the cells. Many of the highly enriched mRNAs are also upregulated during infection and are likely to be full-length. The inventory of these mRNAs now forms the foundation for future research addressing the mechanism of mRNA loading into EVs and their function in a recipient cell.We have isolated EVs from the phytopathogenic fungus