RNA-binding proteins (RBPs) are crucial regulators of gene expression, often composed of defined domains interspersed with flexible, intrinsically disordered regions. Determining the structure of ribonucleoprotein (RNP) complexes involving such RBPs necessitates integrative structural modeling due to their lack of a single stable state. In this study, we integrate magnetic resonance, mass spectrometry, and small-angle scattering data to determine the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) bound to an RNA fragment from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV). This binding, essential for enhancing the translation of viral RNA, leads to a complex structure that demonstrates RNA and protein compaction, while maintaining pronounced conformational flexibility. Acting as an RNA chaperone, PTBP1 orchestrates the IRES RNA into a few distinct conformations, exposing the RNA stems outward. This conformational diversity is likely common among RNP structures and functionally important. Our approach enables atomic-level characterization of heterogeneous RNP structures. An integrated structural biology approach is utilized to elucidate the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) complexed with an internal ribosome entry site (IRES) RNA fragment from encephalomyocarditis virus (EMCV). Typically, RBDs are flanked and linked by intrinsically disordered regions (IDR) of various lengths and sequences2. Recently, these flanking IDRs have been studied extensively in the context of liquid-liquid phase separation5. For example, the low complexity domain of the ALS-associated protein FUS has not only been connected to functional phase-separated states but is also associated with plaque formation that causes neurotoxicity7. The IDRs that link RBDs potentially have diverse biological functions and they unavoidably cause flexibility and heterogeneity of the overall protein conformation. However, cooperative binding of the RBDs to RNA-binding sites may lead to an increased conformational order of the protein. This raises questions about the extent to which a disorder-to-order transition is achieved, and whether both flexibility and rigidity are important for the biological function of the protein-RNA complex.Gene expression is critically regulated by protein-RNA interactions. RNA-binding proteins (RBPs) usually contain multiple RNA-binding domains (RBDs), among which the RNA recognition motif (RRM) is the most abundant domain type14). They generally represent well-defined, three-dimensional folds following the Anfinsen dogma15. However, the presence of structurally undefined flexible regions connecting these subunits and the associated conformational heterogeneity hinders the structure determination of full-length RBP and their complexes by using exclusively these classical techniques, as well as cryo-EM18. Thus, current access to ribonucleoprotein (RNP) structures is limited to protein-RNA machineries with stable intermediates such as ribosomes and spliceosomal particles or to protein-RNA complexes of mainly single and tandem RBDs bound to optimized RNA sequences21. Yet, the biological function of protein-RNA complexes may depend on the adoption of multiple conformations, which may be important for binding distinct targets22. Integrative structural biology approaches that combine multiple methods overcome the restrictions of classical techniques in the characterization of such heterogeneous structures18. However, integrating a variety of structural constraints with different levels of precision and length, as well as, the aforementioned features of the protein-RNA complexes, also necessitates a shift in the concept of structure determination during the modeling stage.A plethora of structures of isolated RBDs are available from nuclear magnetic resonance (NMR) and X-ray crystallography  trans-acting factor (ITAF)28. IRES elements allow non-canonical translation initiation in a 5’-cap independent manner. These large, highly structured RNA sequences are present in the 5’ untranslated regions (UTRs) of particular cellular mRNAs and of the genomes of positive-strand RNA viruses. IRES sequences enable translation during global repression of canonical translation due to cell stress. For instance, during viral infections, canonical translation is arrested and non-canonical translation activates the antiviral response and programmed cell death to prevent further viral spread. In this context, PTBP1 acts as an ITAF and favors the translation of important pro-apoptotic factors31. Similarly, RNA viruses have evolved PTBP1-responsive IRES elements in their 5’ UTRs to hijack the antiviral response and favor the translation of their viral proteins33. PTBP1 is among the most frequently found ITAFs and it is an extensively characterized enhancer of the IRES-mediated translation in picornaviruses, including poliovirus (PV), human rhino virus (HRV), hepatitis C virus (HCV), foot and mouth disease virus (FMDV) and several cardioviruses such Theiler’s murine encephalomyelitis virus (TMEV) and encephalomyocarditis virus (EMCV)34.The abundant 57 kDa RBP polypyrimidine tract protein 1  is a general regulator of cellular mRNA metabolism. In the context of splicing regulation, PTBP1 acts either as a splicing repressor, potentially by binding competition with other factors, or as a splicing activator in a position-specific manner36  suggested a protein-RNA binding ratio of 2:1 with binding of one molecule of PTBP1 to the IRES stem-loops (SLs) D-F , NMR, small-angle neutron and X-ray scattering (SANS/SAXS), and cross-linking of segmentally isotope-labeled RNA with tandem mass spectrometry (CLIR-MS/MS), to study the structure of the full-length PTBP1 in complex with an RNA derived from the IRES of EMCV . PTBP1 and EMCV-IRES-DtoF are highly dynamic molecules in their isolated states. Upon complex formation, they assemble into a compact and ordered structure while still sampling a fairly large conformational space. This conformational variety can only be described by a structural ensemble. As confirmed using EPR and bicistronic reporter assays, binding of RRM4 to the single-stranded RNA linker between SLE and SLF is crucial for a stable complex assembly as well as for IRES activity, consistent with an RNA chaperone role of PTBP1 in enhancing IRES-mediated translation.39 in the RNA (pyrimidine-tracts) are also conserved in cardioviruses  curves suggests an elongated shape for the full-length PTBP1, as already described earlier by others49. Interestingly, ensemble modeling of free PTBP1 using EOM50 resulted in 14 unique models that (1) were not all extended and (2) did not show any orientational preferences between the rigid bodies RRM1, RRM2 and RRM34. The Rg and Dmax are 46.20 Å and 168.20 Å  or IAP spin labeling and used the four-pulse double electron-electron resonance pulse (DEER) experiment for measuring electron spin-spin distance distributionsons Fig. . This imIn summary, the NMR, EPR and SANS/SAXS data show that the free forms of both the RNA and protein are best described by rigid, well-defined bodies (RRMs or SLs) connected by flexible linkers that allow fluctuating spatial arrangements.39, this implies that the RNA structure is also stabilized in a preferred conformation. Importantly, the local secondary structure of the RNA remains unchanged upon PTBP1 binding since the imino proton signals were identical compared to the free state  and EPR-based distance measurements on the full-length PTBP1 protein, we demonstrated that the EPR-based distance distributions within each isolated RRM are consistent with the NMR-based structures45. Importantly, the distance distributions between the labeled positions within each RRM of the full-length protein were identical to those measured on the isolated RRMs  to confirm the binding register  and to four nucleotides of the LinkEF (RRM4) as rigid bodies. The structural details of these sub-complexes have been determined previously using a hybrid approach of NMR, CLIR-MS/MS and available structural data64, resulting in a final ensemble of 25 conformers  compared to the main ensemble. Furthermore, a geometric average distance distribution overlap of 0.683 is achieved, slightly surpassing that of the main ensemble . After the fitting process, we eliminated conformers with less than 0.1% of the total population, resulting in an ensemble composed of 32 conformers. This approach involved fitting to background-corrected DEER traces rather than distance distributions and utilizing least-squares instead of minimizing In a third test, we maximized distance distribution overlap while ignoring the small-angle scattering curves. This DEER-only ensemble, visualized in Supplementary Fig. Comparison of the fit quality of all these ensembles with the raw ensemble .Finally, we tested how the fit quality and size of the reweighted ensemble depend on the size of the raw ensemble  between the 25 conformers of the PTBP1/EMCV-IRES-DtoF main ensemble varies from 2 to 30 Å over the entire complex  and RRM4 further downstream (LinkEF) using the interaction surface near the small helix of the linker. This is seen in both the major and minor forms of the complex. However, only in the minor form, the trans arrangement brings the intervening RNA near the RRM34 inter-domain linker enabling additional protein-RNA interactions   Fig. . In othe–7) Fig. , contact–7) Fig. . In a fo–7) Fig. . In a fi–7) Fig.  and in o–7) Fig. . In a fi–7) Fig. . This il74 (see “Discussion”).Overall, a key aspect of this PTBP1-IRES structural ensemble is that protein binding results in a compacted RNP structure with reduced (compared to the free protein and RNA), but still pronounced conformational flexibility. Importantly, the four RRMs lie in the interior of the structure and expose the three conserved RNA stems to the outside Fig. . This coThe RRM4-LinkEF interaction is central to the complex structure as it stabilizes the longest RNA linker (LinkEF) and thereby participates in the compaction of the complex. We therefore investigated the effect on the structural integrity of the complex by interfering with the RRM4-LinkEF interaction to test its functional importance Fig. . Replace75. In this assay, Renilla Luciferase is translated 5’-cap-dependent and Firefly Luciferase is translated under the control of the EMCV-IRES, both from the same transcript. Thus, the ratio of Firefly Luciferase activity to Renilla Luciferase activity is a direct measure of IRES activity76. We first compared the activity of the EMCV-IRES wild-type (WT)  Fig.  with a dely Fig. . Strikin74. The overall conformation that exposes the RNA stems and the remaining conformational dynamics may allow the RNP to present a subset of conformations that can be recognized by the translation machinery through conformational capture. In contrast, without PTBP1 binding, the inherent flexibility due to the lack of linker binding loosens the complex arrangement and therefore impedes translation initiation.Together these experiments revealed rather surprisingly that a flexible RNA linker, which connects two SLs, has an essential role in the biological activity of an RNA molecule. PTBP1 binds to the flexible RNA linker and remodels the overall RNA structure. The resulting structure and the ordering of the RNA structure upon PTBP1 binding are crucial for the IRES-mediated translation initiation, potentially by facilitating the recruitment of the ribosome or interaction with translation initiation factors43, and thus this data can be seen as an independent support for the structural conformers , and RRM2 interacts extensively with RRM1 and RRM4, while the inter-domain linker between RRM3 and RRM4 folds into two α-helices upon RNA binding. Therefore, PTBP1 and Prp24 use completely different modes of action, although both act as RNA chaperones. Importantly, while Prp24 has a single RNA-binding substrate, PTBP1 has thousands of RNA-binding targets being involved in almost all post-transcriptional gene regulatory processes85. Therefore, it may not be surprising that the complex formation of PTBP1 results in a discrete number of complex structures and not a single one. Moreover, it is likely that it would be energetically more favorable for an RNP complex to have a higher degree of flexibility and thereby maintain a higher conformational entropy compared to a rigid structure, especially considering the large entropic cost associated with the binding between two very flexible molecules. The preservation of conformational dynamics in the bound state may also facilitate the recruitment of additional binding partners and allow them to exert additional influence on the RNAs conformational landscape, required to attain functional conformations.The structural details presented here also provide general insights into how RBPs interact with RNAs. To our knowledge, the only other structure of a multi‐RRM containing protein with more than two RRMs in complex with a natural RNA is the crystal structure of the spliceosome-specific RNA chaperone Prp24 bound to U6 snRNA20. Our approach that combines short and long-range distance constraints from NMR, MS and SAS, as well as, distance distributions from EPR, allows us to determine a structural ensemble covering the full conformational space covered by such dynamic RNPs. Distance distributions from EPR experiments inform on the width of conformational distributions and thus represent a basis for integrative structure modeling of large systems, provided that three-dimensional models of the structurally well-defined building blocks already exist. The recent advances in AI-driven structure predictions will aid the availability of such building blocks86. Further work is required in perfecting integrative ensemble modeling and, in particular, in providing uncertainty estimates for broad ensembles. Integrating NMR and EPR data, protein-RNA cross-linking restraints, and SAS curves holds much promise as a strategy to determine ensembles of rigid-body arrangements and even protein-RNA condensates, to provide insights into the relationship between structure, dynamics and function of RBPs.We expect that the approach presented here will prove valuable for future structural characterizations of RNP complexes involving the numerous RBPs in the human genome that, similarly to PTBP1, are composed of multiple RBDs separated by flexible linkers. RNA binding may result in several, substantially different conformations and could be vital to their function. Many RNP machineries rely on major structural rearrangements, as seen in the different steps catalyzed by the spliceosome or the ribosome8 using the software package Multiscale Modeling of Macromolecular systems (MMM)87. For inter-domain EPR distance measurements, we chose amino acids in the RRMs that are predominantly located within the α-helices, with geometrical similarities and related chemical properties compared to cysteine. Positions in the peptide linker regions were selected close to the C-terminus of RRM1 and RRM2, close to the N-terminus of RRM3 or in the center of the linker. Site-directed mutagenesis was performed using quick-change PCR with specific primers listed in Supplementary Table Positions for site-directed spin labeling (SDSL) on the protein were chosen based on simulating the spin-label attachment to existing NMR solution structures of individual RRMs of PTBP145. For distance measurements >5.5–6 nm, expression was performed in 95–99% D2O using minimal M9 medium followed by the same purification protocol. Samples for NMR and SANS experiments were finally transferred to 10 mM NaPO4, pH 6.5, 20 mM NaCl buffer with 1–2 mM DTT by size-exclusion chromatography and dialysis.Protein expression and purification of PTBP1 and individual RRMs were performed as described previously45. For spin labeling of RNA, respective RNA segments were removed by RNase H cleavage and chemically synthesized (Dharmacon) thio-uridinated RNA segments were ligated after spin labeling similarly as described before88.In vitro transcription of EMCV-IRES-DtoF and of individual SLs was performed as described previously45. For SDSL of PTBP1, we used predominantly MTSSL  methanethiosulfonate, Toronto Research Chemicals) or IAP (3-(2-iodoacetamido)-proxyl, Sigma Aldrich). For RNA SDSL, different uridine positions in the loop or linker regions in EMCV-IRES-DtoF were selected and the respective short oligonucleotides containing 4-thiouridine were spin-labeled and ligated to the full-length RNA following earlier published protocols60.Spin labeling protocols used for all PTBP1 mutants have been described elsewhere39. In brief, EMCV-IRES-DtoF was diluted in all cases to approximately 4 µM in 5 mL low salt buffer . Concentrated doubly-labeled PTBP1 was mixed with the RNA in a molar ratio of 1:1.2 and the complex was then purified by size-exclusion chromatography using a Superdex 75 column (Cytiva). Complex samples were then buffer-exchanged into D2O and concentrated to approximately 50–100 µM. For DEER distance measurements, complex samples were diluted 1:1 (v/v) with d8-glycerol (Sigma Aldrich), and 30 µL sample solution was filled into 3 mm quartz tubes. Complex formation was ensured by native RNA polyacrylamide gels.Complex formation and purification were performed essentially as described before89. EMCV-IRES mutants were generated using standard site-directed mutagenesis procedures. HEK-293T cells were derived from a lab stock and maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% heat-inactivated fetal calf serum (GibcoBRL) and antibiotics. For IRES activity assays, a 24-well plate was seeded with 500 µL cell suspension . After 24 h growth, the medium was exchanged to medium without antibiotics. Then, cells were transfected with 500 ng plasmid/well and a final volume of Lipofectamin 2000 (Thermo Fisher) of 1 µL/well in a total volume of 100 µL OPTI-MEM (Gibco) medium/well. Cells were incubated for 24 h and lysed using the Dual-Luciferase Assay lysis buffer supplemented with Roche Complete Protease Inhibitor . Lysates were cleared by centrifugation . Then, 5 µL of lysate/well was pipetted into a 96-well ELISA plate and 25 µL of Firefly-Luciferase substrate solution was added and measured after 15 s shaking in the plate reader. Then, 25 µL of Stop-N-Go solution was added and samples were measured to assess the Renilla-Luciferase activity. All IRES assays were performed in technical triplicates of biological triplicates and measured on a Berthold MicrolumatPlus luminometer. IRES activity is determined by normalizing the Firefly-Luciferase activity to the Renilla-Luciferase activity, whereas the activity of the WT-plasmid is set to 100%.Bicistronic pRemcvF plasmids were a generous gift from Prof. Dr. A. Willis 39 was reanalyzed with an optimized parameter set containing more neutral loss products, to increase the number of identified protein-RNA cross-links. Mass spectrometry data files (Thermo Fisher RAW format) corresponding to the uniformly labeled EMCV-IRES RNA experiment were retrieved from ProteomeXchange via the PRIDE partner repository (PXD005566) and converted to mzXML using msconvert.exe (ProteoWizard msConvert v.3.0.9393c)90. The files were searched using RNxQuest91, an add-on to xQuest (both available for download from https://gitlab.ethz.ch/leitner_lab/)93, against a database containing only the target PTBP1 protein sequence, with expected light-heavy RNA adducts defined as mono-links. Adducts with lengths of 1–4 nucleotides were considered. In addition to the whole RNA adduct, the following neutral losses were considered: -H2O, -H4O, -HPO3, -H3PO3, -H2, -HPO3+H2O, -HPO2, -H4O2, -H5PO5. Further details about the expanded parameter set can be found elsewhere94. All amino acids were set as cross-linkable. Delta masses for each adduct were defined depending on the nucleotide sequence composition, as described previously39. Further parameters used for xQuest searching: delta mass tolerance: +/− 15 ppm, retention time tolerance: 60 s, enzyme = Trypsin, maximum missed cleavages = 2, MS1 mass tolerance = 10 ppm, MS2 mass tolerance = 0.2 Da. Identifications with an ld.Score > 20 (according to the scoring scheme described previously92) were considered. Further processing and visualization were performed using the scripts contained in the RNxQuest package. The reanalyzed mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium  via the PRIDE partner repository95 with the dataset identifier PXD034894.Mass spectrometry data from previous CLIR-MS/MS analysis of the PTBP1-IRES complex1H1H-NOESY spectra were recorded at 278 or 283 K. Imino-1H15N-TROSY spectra were recorded at 278 and 293 K. We processed spectra with Topspin 2.1 or Topspin 3.0 and analyzed in Sparky 3.096. 1H-1H imino assignments of the RNA were achieved by standard methods98. Imino resonances of SLE were assigned using conventional jump-return NOESY with 200 ms mixing time and facilitated with SMT experiments99 at 278 and 275 K. Non-exchangeable protons were assigned using sequential walk in NOESY spectra recorded at 298 K and in 100% D2O NMR buffer . Assignment of other hydrogens and heteronuclei was obtained using intra-nucleotide assignment experiments, including aromatic HSQC, CT HSQC of sugar resonances, TROSY HCCH COSY for adenine H2-H8 assignment, HCCH COSY for H5-H6 correlations of pyrimidines, and finally HCN and HCNCH experiments. Assignments of protein resonances were obtained using conventional triple resonance experiments, HCCH-TOCSY and 3D NOESY-HSQCs. Intermolecular NOEs were identified in 13C,F3-filtered HSQC-NOESY experiments using 100–150 ms NOE mixing time and L-PROSY NOESY recorded with 10 loops and 40 ms per loop101. Throughout the study, simple titration experiments were recorded using 0.2 mM protein/RNA samples, assignments experiments for molecules in the free state were performed with 1 mM samples, and the protein-RNA complexes were at approximately 0.7–0.8 mM of each molecule.All NMR experiments were recorded on Bruker Avance III 500, 600, 700 or 900 MHz spectrometers equipped with cryo-probes and on a Bruker Avance III 750 MHz spectrometer with a room temperature probe. NMR protein spectra (free proteins and protein-RNA complexes) were acquired at 313 and 323 K, imino Labeling efficiencies and spin-label tumbling regimes of spin-labeled protein and RNA samples were determined by CW-EPR spectroscopy at ambient temperature. Experiments were performed at X band (9.5 GHz) using a Bruker Elexsys E500 spectrometer with a Bruker super-high Q resonator ER4122SHQ and spectra were recorded with a field modulation of 100 kHz, a modulation amplitude of 1 G, a time constant of 10.24 ms, a conversion time of 40.96 ms and an attenuation of 25 dB of 200 mW incident microwave power. Samples were filled into glass capillaries (BLAUBRAND®) with a diameter of 1.5/0.9 mm (outer/inner). Labeling efficiencies were determined by digital double integration of the EPR spectra and comparing them to free nitroxide radical IAP of standard concentration. Changes in the spin-label mobility could be detected by amplitude reduction of the low- and high-field components of the nitroxide spectra, which indicated successful spin labeling.48 were performed at a home-built high-power Q-band spectrometer (35 GHz) with 200 W microwave power, a Bruker ElexSys acquisition system (E580) and a home-built TE001 pulse probe102. Temperature stabilization during all measurements was ensured by a He-flow cryostat  and a temperature control system . All free protein and complex measurements were carried out at 50 K because this temperature corresponds to the optimal conditions for nitroxide radicals with respect to their longitudinal and transverse relaxation. Pump pulses were always set to 12 ns and detection pulses to 16 ns. While a setup with all 12 ns pulses may provide better sensitivity, it requires a very good resonator mode and thus careful sample volume and sample position adjustment. In practice, we found it more convenient to slightly compromise the bandwidth of the detection pulses by increasing their length from 12 ns to 16 ns. The first inter-pulse delay τ1 was set to 400 ns, τ2 was set according to the expected distance and its required DEER trace length for suitable background correction. Time increment t was also adapted to the length of the τ2 as described earlier45. The pump pulse was always applied on the maximum field position of the nitroxide spectrum, whereas detection pulses were applied by an offset of approximately 100 MHz. Samples that were diluted 1:1 (v/v) with d8-glycerol (Sigma Aldrich) were shock-frozen with liquid nitrogen and measured in this state.To obtain EPR distance restraints, four-pulse DEER experiments103, version 2022, in automated mode. When an artifact arose from the overlap between the excitation bands of the pump and detection pulses104, up to 15% of the data was cut at the end. For background correction, we used a dimensionality of 3, corresponding to a homogeneous three-dimensional distribution of complexes in the sample as expected for soluble proteins. Automated comparative analysis computes distance distributions by neural network analysis with DeerNet105 and Tikhonov regularization106 with DeerLab in a single step with background correction107 and provides 95% confidence intervals for both distributions. Unless otherwise indicated, we report the mean of the two distributions and confidence intervals that include uncertainty due to model bias. The mean distances (〈r〉) and standard deviations (σ(r)) of the distance distributions were implemented as upper and lower limits in CYANA modeling (see below).For processing all DEER data we used the software package DeerAnalysis2O/H2O ratio of the buffer  were determined by contrast variation and extrapolation of I0 to be 66% D2O for RNA, and 42% or 112% for protonated or deuterated protein, respectively. Free protein and RNA were recorded at a wavelength of the neutron beam of 6 Å, a collimation of 6 m and a detector distance of 2 m and 6 m. SAS data collection parameters are summarized in Supplementary Table Small-angle neutron scattering experiments were recorded at the SANS-I and SANS-II facility, Swiss Spallation Neutron Source, SINQ, Paul Scherrer Institute, Switzerland. Scattering density matching points for RNA and protein with respect to the D39 and dialyzed for 24 h against suitable buffers. Each reference cuvette was filled with the corresponding dialysis buffer. Complexes were measured at SANS-I at a wavelength of 4.5 Å and either a collimation of 11 m and a detector distance of 11 m or a collimation of 3 m and a detector distance of 2 m. Scattered neutrons were detected using a two-dimensional 96 × 96 cm2 detector with a pixel size of 0.75 cm. The cross section of the collimator was 50 × 50 cm2 and the effective sample diameter was 0.8 × 1.5 cm2. At SANS-II, the selected wavelength was 4.9 Å and collimation and detector distance were 2 m and 1.2 m or 4 m and 4 m, respectively. The detector had a diameter of 64 cm with 128 × 128 pixels.For both, SANS and SAXS experiments, complexes were reconstituted as described previously108 and visualized using Primus QT109 from the ATSAS program110. Beamline-specific correction factors for data reduction are 1.338 and 1.284 for data recorded at a wavelength of 4.5 and 6 Å, respectively. SAXS experiments were performed on the liquid samples using a Rigaku MicroMax-002 microfocused beam . The Cu Kα radiation (λCuKα = 1.5418 Å) was collimated by three pinholes  collimators. The scattered X-ray intensity was detected by a two-dimensional Triton-200 X-ray detector  for SAXS. SAXS detectors cover an effective scattering vector range of 0.1 nm−1 < q < 4 nm−1, where q is the scattering wave vector defined as q = 4π sin θ/λCuKα, with a scattering angle of 2θ. The SAXS samples were measured in 2 mm quartz X-ray capillaries (purchased from Hilgenberg).Reduction and analysis of SANS data were performed with the program BerSansg, Dmax, Porod Volumes) was done using the ATSAS Suite, in particular Primus and functions therein111.Analysis of experimental data 35 were renumbered according to the PTBP1 amino acid sequence and used as rigid bodies, RRM34 (amino acids 324–531) was set as “fixed”. Sequence ranges 56–141, 177–284 and 324–531 were defined as rigid bodies, all other as “disordered”.The SANS curve measured for protonated PTBP1 at 0% D39. However, as CYANA does not allow to load protein-RNA complexes as input structures, protein and RNA were loaded separately. Based on the imino-1H1H-NOESY signals and structure prediction by McFold/McSym, we modeled RNA stems using standard A-form RNA-helix angles and Watson-Crick base-pair restraints. We merged the protein models (only the first state of the bundle) and RNA models in one PDB file  and used the regularized macro of CYANA to generate a similar  bundle of PTBP1 input structures (RMSD < 0.3 Å). Subsequently, the definition of rigid bodies in CYANA for protein domains was achieved using the command “angle fix”. To preserve the RNA secondary structure, Watson-Crick base-pair restraints were enforced in the stem, while RNA loops and bulges were kept flexible. These regularized rigid bodies were used as input for a CYANA calculation. The linkers between these rigid domains were generated with random starting conformations by CYANA. In these calculations, intermolecular restraints that were adapted from previous work39 were used to define protein-RNA contacts as observed in the individual sub-complexes.For the integrative structure modeling of PTBP1/EMCV-IRES-DtoF . A final set of 35 EPR distance restraints were implemented as upper and lower limits corresponding to the mean plus or minus one standard deviation of the distance distribution, respectively. Conformers are not penalized for their deviation from the mean distance as long as the distance is between the lower and upper limits.max determined by SAS experiments and, thus, does not artificially compact the RNA.As CYANA does not include electrostatics, we used artificial lower limits of 6 Å between RNA-phosphate groups with corresponding upper limits set to 200 Å. The latter distance is larger than DUsing these input rigid bodies (protein domains and RNA fragments) in combination with the short and long-range intermolecular restraints, we executed a simulated annealing protocol with 30,000 steps and calculated 20,000 models (20 × 1000 with different seeds). Out of these 20,000 models, the 10% energy best structures (lowest target function) were selected for further refinement. This filtering does not further bias the raw ensemble toward the EPR data.All pseudoatoms from the CYANA output were removed, it was split into two chains (protein and RNA) and the RNA was renumbered by a customized script. Afterward, models with flexible peptide linkers that are threaded through RNA or contain C4’-O4’ bond lengths in RNA sugars longer than 1.6 Å were discarded. These tests discard between 2 and 8 models per run (out of 100 models). The models, which passed both tests, were refined by YASARA version 21.8.27 calling YASARA Structure with the standard script used by the YASARA Minimization Server and included in the MMMx distribution on GitHub as minimization_server.mcr. The resulting structure remains close to the input structure while removing clashes, and fixing wrong bond lengths, wrong bond angles, and wrong torsion angles.The individual output models of YASARA have different protonation states of RNA, however, models in a PDB file must have the same number of atoms. Therefore, all protons that did not exist in all structures of the first run were removed to obtain consistent models with minimal protonation. Models with fewer protons than the first model, which usually indicates problems in RNA geometry, were discarded. Once again, models were checked for flexible peptide linkers threaded through RNA. This is necessary because some CYANA models were very strained, and their structures changed so strongly during refinement that such threading occurred even if it did not exist in the input model of the YASARA refinement. In the case of threading after YASARA refinement, models were discarded. Similarly, sugar bonds were checked again. When trying to remove strain, YASARA sometimes breaks a C4’-O4’ bond, because this is less costly in terms of energy than the alternatives. All models with altered sugar bonds were discarded. The set of all YASARA-refined CYANA models that passed these tests contained 766 conformers and furnished the raw ensemble for ensemble reweighting.2O, 1.2 and 4 m detector distance) were used for refinement. An additional ensemble was refined only with the EPR restraints. In these refinements, the whole distance distribution, including its shape, is fitted, rather than only the mean and standard deviation.Ensemble reweighting was performed with MMMx commit b330052. In total, 35 EPR (distance distribution) restraints, the SAXS curve and two SANS curves . Overlap for a single distance distribution restraint corresponds to the common area below the experimental and simulated distance distributions, whereas the total area of each distribution is normalized to 1. It ranges between 0 for completely distinct and 1 for identical distributions. Overlap deficiency for the set of all distance distribution restraints ranges between 0 and 1, with 1 meaning no overlap for at least one restraint and 0 meaning perfect overlap for all restraints. Second, the block was fit to only the three small-angle scattering (SAS) curves by minimizing the sum of the χ2 values for all SAS curves. This provides the best sum of χ2 values that can be achieved for the conformers in this block by assigning populations . Finally, the block was fit to EPR and SAS restraints simultaneously. In this fitting step, conformers of the block are selected, and populations are determined. Fit quality of EPR and SAS restraints are balanced. For each trial set of populations, the mean overlap deficiency (OD2) and the sum of χ2 values for the SAS curves (SCS2) are computed. Because this cannot be better than OD1 in this block, OD2 ≥ OD1. Likewise, it cannot be better than SCS1, i.e., SCS2 ≥ SCS1. Hence, (OD2/OD1 + SCS2/SCS1)/2 ≥ 1. The minimum of 1 can only occur if the same set of populations provides the best fit for EPR restraints as well as the best fit for SAS restraints. If the restraints are inconsistent or the set of input conformers is not good enough, the value will be substantially larger than 1. In order to get a transparent measure, we defined the loss of merit, (OD2/OD1 + SCS2/SCS1)/2 − 1. The loss of merit is zero, if both restraint sets are best fitted by the same set of conformers and their populations. If it is larger than one, the two figures of merit  have more than doubled. If this happens, the subsets of restraints are inconsistent or the set of conformers is very poor. Values for the loss of merit of 0.2 to 0.4 are quite normal112. The loss of merit for the PTBP1/EMCV-IRES-DtoF ensemble refined with both DEER and SAS data is 0.332 and thus indicates overall consistent restraint sets and supports the integrity of the CYANA raw ensemble.In each block, the following fitting steps were performed. First, the block was fit only to the EPR restraints. This provides the best overlap deficiencyχ2 of the small-angle scattering curve fits. In this work, we prefer the non-linear approach that balances between groups of restraints for the ensembles specified as the main ensemble. MMMx is freely available at https://github.com/gjeschke/MMMx.In a second approach to ensemble reweighting, we determined all conformer populations simultaneously by non-negative linear least squares (NNLLSQ). In this case, we fitted to small-angle scattering curves disregarding the dependence of noise on the scattering vector and to background-corrected DEER traces, which are output by automated comparative DEER analysis. The approach allows for an additional polynomial background correction, which we performed up to order 2. This approach was newly implemented into MMMx. It turned out that only a small fraction of the populations (48 out of 766) deviated significantly from zero . The command line tool online analysis was used to provide quality measures for the individual conformers. Quality measures for the ensemble, as reported in Supplementary Table https://github.com/gjeschke/MMMx.Radii of gyration for all ensembles (Supplementary Table Further information on research design is available in the Supplementary Information fileReporting SummarySource Data


Diachasmimorpha longicaudata, Fopius arisanus, and Spalangia endius. These wasps are parasitoids that can parasitel tephritid flies, one of the most important pest groups of fruits and vegetables. In D. longicaudata, the small RNAs derived from the viruses exhibited distinct peaks at 22 nt and were symmetrically distributed across the viral genome. These findings indicate that these viruses can activate the host’s RNAi immune response. PCR detection further revealed that DlNaLV efficiently infects female individuals of D. longicaudata with 100% efficiency, and ZcNLV is capable of infecting both D. longicaudata and its host, Zeugodacus cucurbitae. Our findings contribute to a better understanding of RNA viruses in parasitoid wasps and lay the foundation for future research on the triple-level trophic relationships between tephritid flies, parasitoid wasps, and RNA viruses.Parasitoid wasps are a diverse group of parasitoid insects that play a crucial role in biological control and integrated pest management programs due to their wide range of host species and complex behaviors. Previous studies have reported that select RNA viruses in parasitoid wasps can affect either the host-parasitoid wasp or the pest host parasitized by the wasps. Therefore, a study of the dynamics of RNA viruses in parasitoid wasps is essential for artificial breeding programs and improving their parasitic capabilities. In this study, we detected the presence of nine novel and three known RNA viruses with complete genomes in three parasitoid wasp species: Diachasmimorpha longicaudata. These findings have important implications for the development of sustainable pest management strategies and the enhancement of artificial rearing techniques for parasitoid wasps.Parasitoid wasp populations have developed persistent beneficial symbiotic relationships with several viruses through repeated evolution. However, there have been limited reports on RNA viruses in parasitoid wasps of tephritid flies, a significant pest group affecting fruits and vegetables. This study explores the diversity of RNA viruses in three parasitoid wasps of tephritid flies and highlights the potential biological significance of specific viruses in  Biological control, which is a green, environmentally friendly, safe, and sustainable approach, can effectively manage pest populations in agricultural ecosystems . This meDiachasmimorpha longicaudata entomopoxvirus (DlEPV) disrupts the regular functions of the host’s hemocytes, ensuring the normal growth and development of offspring of the parasitoid wasp D. longicaudata within its host  has been observed to extend the lifespan of its host, P. puparum, and significantly reduce the number of female progenies, thereby modulating the offspring sex ratio  for D. longicaudata. Additionally, RNA-seq libraries were downloaded for S. endius and F. arisanus. Following quality control, we obtained 44,117,406 paired clean reads from the RNA-seq library of D. longicaudata. Utilizing de novo assembly fragments, we searched non-redundant protein databases and identified potential viral sequences based on NR annotation results. Our analysis identified 12 potential viral sequences, with no cross-species phenomenon observed. Among these, nine showed less than 85% amino acid sequence identity with the known viral sequences, implying that they potentially represent novel viral sequences  and D. longicaudata narna-like virus (DlNaLV), respectively. The genome of DlTLV consisted of 2,024-nt and contained two partially overlapping open reading frames (ORFs). ORF1 (239 aa) encoded a hypothetical protein, while ORF2 (414 aa) encoded RNA-dependent RNA polymerase (RdRp) (We discovered seven positive-sense RNA virus sequences in three parasitoid wasps. In e (RdRp) . The RdRe (RdRp) . Phylogee (RdRp) . On the e (RdRp) . The RNAe (RdRp) . Phylogee (RdRp) .F. arisanus and given the names Fopius arisanus permutotetra-like virus (FaPLV), F. arisanus dicistrovirus (FaDV), F. arisanus Nora virus (FaNV), and F. arisanus narna-like virus (FaNaLV), respectively. The genome sequence of FaPLV is 4,953-nt and includes three forward ORFs and one reverse ORF. Forward ORF1  encodes the RdRp protein, forward ORF2 (391 aa) encodes the capsid protein, while forward ORF3 (196 aa) and reverse ORF (138 aa) encode unknown proteins  encoding Capsid, Hel, and RdRp , was discovered in and RdRp . Sequencand RdRp .D. longicaudata and S. endius, named D. longicaudata rhabdo-like virus (DlRLV) and Spalangia endius hurwu-like virus (SeHLV), respectively. The assembled genome of DlRLV was 11,938 nt, consisting of five forward ORFs and one reverse ORF. ORF1 (460 aa) encoded a Rhabdovirus nucleocapsid protein, ORF2 (449 aa) encoded a hypothetical protein, ORF3 (219 aa) encoded the Matrix protein, ORF4 (529 aa) encoded the Glycoprotein, and ORF5  encoded RdRP, RNA capping domain, and Viral methyltransferase. The reverse ORF encoded an unknown protein (Tenuivirus NS4 protein and one reverse ORF (175 aa) encoding the Tenuivirus NCP protein. Segment 3 consisted of one ORF (308 aa) encoding the Tenuivirus nucleocapsid protein . DlNaLV, DlTLV, and DlRLV exhibited robust small RNA signals, characterized by a prominent peak at 22-nt, and a symmetrical distribution of VsRNAs across both strands of the genome (Zeugodacus cucurbitae negev-like virus (ZcNLV) showed a robust small RNA signal on the positive strand of the genome, but it did not display a prominent peak at 22 nt. To gain further insight into the small RNA distribution of ZcNLV, we performed a reconstruction of the small RNA library (accession number: SRR25621799) and conducted a thorough analysis of ZcNLV’s small RNA data. The results showed that the VsRNAs derived from ZcNLV displayed a minor peak at 22 nt .In the context of RNAi antiviral immunity, viral double-stranded RNA structures can induce host RNAi responses and produce virus-derived small RNAs (VsRNAs). These VsRNAs then specifically silence viral gene expression by targeting the viral genome . To detee genome . In contD. longicaudata, we conducted RT-PCR analysis on 10-female and 10-male-adult specimens. The reference gene test results confirmed that the samples were of high quality and free from any quality issues. Overall, all four viruses were found to be present in the D. longicaudata populations  did not show any amplification .To assess the infectivity of ZcNLV in D. longicaudata. These findings indicate that the parasitoid wasps D. longicaudata, S. endius, and F. arisanus harbor a diverse range of RNA viruses, providing substantial evidence of their genuine in vivo infections.Meta-virome and high-throughput sequencing technologies are revolutionizing our understanding of the viral landscape, leading to the discovery and identification of an increasing number of viruses . FurtherD. longicaudata, potentially due to the virus-induced lethality in males. This phenomenon has been observed in Drosophila, where the male-killing partitivirus 1 encodes a protein, known as the partitivirus male-killing protein 1, that leads to the death of male Drosophila , suggesting a potential widespread infection of Hymenoptera insects by this virus. ZcDV, a member of the family Dicistroviridae, exhibits a high infection frequency within the population of Zeugodacus cucurbitae  in Guangxi Province, China, in 2021. These cultures were subsequently maintained in a constant temperature incubator at 25 ± 1°C and 65 ± 5% relative humidity, with a photoperiod of 14 h light: 10 h dark (L:D). After emergence, the adult wasps were provided with honey and sterile water. Mated adult females were used to parasitize larvae of a laboratory strain of B. dorsalis. The rearing of B. dorsalis and Zeugodacus cucurbitae followed the methods we previously reported . The quality of the extracted RNA was assessed using Agilent 2100  and Nanodrop  to ensure that the sample passed the quality control for the next-generation sequencing library. The Epicentre Ribo-ZeroTM Kit  was employed to remove host rRNA, and the Illumina TruSeq Total RNA Sample Prep Kit  was used for preparing RNA-seq libraries. Subsequently, RNA libraries were sequenced using paired-end sequencing (150 bp) on the NovaSeq 6000 platform . Additionally, a small RNA library was constructed using a small RNA Sample Prep Kit  and sequenced on the NovaSeq 6000 platform  with PE50,using the same total RNA sample.To characterize the RNA virome and VsRNAs in S. endius (SRR1038395) and F. arisanus , were retrieved from the National Center for Biotechnology Information.RNA-seq raw data for the other two parasitoid wasps, de novo assembly was performed using CLC Genomics Workbench . Subsequently, orkbench , Trinityorkbench , and Spaorkbench . Redundaorkbench . The remorkbench  using thFollowing quality control, the clean reads of small RNAs were aligned to the potential viral sequences using the Bowtie alignment software . The reshttp://linux1.softberry.com/berry.phtml?topic=virus0&group=programs&subgroup=gfindv). The conserved and functional domains of viral proteins were assigned using the SMART online tool  were predicted using the online software SoftBerry (ine tool .http://tree.bio.ed.ac.uk/software/figtree/).Phylogenetic trees were constructed based on the conserved domain  of RNA viruses. First, the MAFFT software was used to align the RdRp amino acid sequences of each virus. Then, IQ-TREE  was emplD. longicaudata, viral-specific primers targeting the RdRp region were designed using Primer3web (https://primer3.ut.ee/). Total RNA was extracted from 10 female and 10 male specimens following the previously described methods. Subsequently, cDNA was synthesized using TaKaRa’s PrimeScript 1st Strand cDNA Synthesis System  after DNaseI digestion (Invitrogen). To ensure sample quality, β-Actin was selected as the internal reference gene. A returned sample from transcriptome sequencing served as the positive control, while water was used as a negative control. Positive PCR products were validated through Sanger sequencing. For viral replication detection, the method of Nguyen et al. (CGTATGCCGTCTTCTGCTTG) and the virus-specific sequence, allowing for specific binding to the negative-strand RNA produced during positive-strand RNA virus replication. Finally, the reverse transcription product was used as a template for PCR amplification with NS1-F and NS1-R primers (Table S1).To investigate the prevalence of each virus in n et al.  was prim


Caulobacter crescentus has three DEAD-box RNA helicases, including RhlB, the main RNA helicase associated with the RNA degradosome. In this work, we evaluated the impact of RhlB on C. crescentus gene expression both at normal and low temperatures and its role in global RNA decay. The rhlB null mutant showed a freezing-sensitive phenotype after pre-incubation at low temperature, indicating a failure in assembling a proper cryotolerance response. A global transcriptomic profile of the wild-type and rhlB mutants was carried out at 30°C and 10°C and showed 73 and 477 differentially expressed genes, with the most affected gene categories being translation and posttranslational modifications. The rhlB mutant is more sensitive to streptonigrin, suggesting that the downregulation of iron-regulated genes may be due to a higher intracellular iron concentration. A high throughput screening for RhlB-binding RNAs identified 220 transcripts at 30°C, and global RNA decay analyses identified several mRNAs and sRNAs that displayed altered profiles of RNA decay rates. Analyses of the transcripts’ 5′-ends from the C. crescentus rhlB mutant and from Pseudomonas aeruginosa PAO1 rhlE1 and rhlE2 mutants confirm that in the absence of the DEAD-box RNA helicase associated with RNase E, there is an accumulation of RNA degradation intermediates.The RNA helicases from the DEAD-box family participate in several biochemical processes, with special relevance in the assembly of ribosome ribonucleoparticles and in RNA turnover as part of the multi-enzymatic RNA degradosome complex. Caulobacter crescentus causes important changes in gene expression and cell physiology. These are probably due, at least in part, to inefficient RNA processing by the RNA degradosome, particularly at low-temperature conditions.One of the most important control points in gene regulation is RNA stability, which determines the half-life of a transcript from its transcription until its degradation. Bacteria have evolved a sophisticated multi-enzymatic complex, the RNA degradosome, which is dedicated mostly to RNA turnover. The combined activity of RNase E and the other RNA degradosome enzymes provides an efficient pipeline for the complete degradation of RNAs. The DEAD-box RNA helicases are very often found in RNA degradosomes from phylogenetically distant bacteria, confirming their importance in unwinding structured RNA for subsequent degradation. This work showed that the absence of the RNA helicase RhlB in the free-living Alphaproteobacterium  RNA helicases are enzymes that act solely on RNAs, whether single-stranded, double-stranded and structured, or associated with other proteins, remodeling these molecules via an ATPase activity that is exclusively dependent on RNA , 2. TheyEscherichia coli, five of them  have been described  . Bacteriescribed , of whicescribed , 7. Lateescribed , 9. Alonescribed .E. coli and Bacillus subtilis, acting as an RNA processing machinery whose composition varies among species (E. coli degradosome is composed of an endoribonuclease (RNase E) associated with a phosphorolytic exoribonuclease (PNPase), a glycolytic enzyme (enolase), and a DEAD-box RNA helicase (RhlB)  . The inte (RhlB) , 14.The N-terminal region of RNase E encompasses the catalytic core of the enzyme, while the C-terminal portion serves as the anchoring point for the other components of the degradosome [reviewed in reference ]. AlthouCaulobacter is a free-living oligotrophic bacterium, spread across humid soils and aquatic environments, associated with the plant’s rhizosphere, and well-adapted to low-temperature conditions  of RNA processing, providing localized sites of RNA degradation in a membrane-less structure . The interaction of RhlB with specific RNAs was also evaluated by pulldown of a tagged RhlB followed by high throughput RNA sequencing, and the RNA decay rate between the two strains was determined. We have shown that RhlB has an impact on gene expression, mainly at 10°C, and is necessary for efficient and complete RNA decay by the RNA degradosome.This work has investigated the impact of the DEAD-box RNA helicase RhlB in C. crescentus .Each member of the degradosome plays a distinct role in the processing and turnover of RNAs. RhlB is the main DEAD-box RNA helicase associated with this complex in escentus  and may 2 fold change ≥1 (upregulated) or ≤1 (downregulated) . We have further analyzed the expression of selected differentially expressed genes (DEGs) by reverse transcription quantitative real-time PCR (RT-qPCR), and the results confirmed the expression pattern observed in the RNA sequencing (RNA-seq) experiments , validating the RNA-seq data. A categorization of the DEGs’ functions was carried out using the Clusters of Orthologous Groups (COG) . The categories overrepresented among the upregulated genes were : translation, and ribosomal structure and biogenesis (We found that 73 (25 upregulated and 48 downregulated) genes were differentially expressed, considering a logogenesis , posttrarhlB mutant is opposite to what was determined for these genes in response to iron availability  or also very stable . In addition, as the RNA-seq libraries were made by shearing the RNA to 50 nt fragments by base hydrolysis, these samples contain a mixture of fragments originating from full-length mRNAs as well as from partially degraded mRNAs. We could not determine a measurable difference between the two strains in bulk half-life, because the replicates of the RhlB mutant showed significant variation. The results showed that 24 transcripts were more stable in the mutant, while 110 mRNAs were less stable, as well as 25 sRNAs whose half-life was significantly altered between the strains . A transcript was considered RhlB-bound if it was enriched in the FLAG-RhlB library compared to the untagged RhlB pulldowns by peak-calling analysis. However, it must be noticed that as RhlB binds RNase E in the RNA degradosome, there is a possibility that RNA pulled down in the HITS-CLIP experiment is bound by the RhlB-RNase E complex. A total of 220 RNA targets were identified , five ofrhlB mutant strain shows a mild growth defect at 15°C, and this may be compensated by overexpressing the rhlE gene, suggesting that the phenotype is due to a lack of sufficient helicase activity , rhlB, and rhlE strains were grown either at 30°C or after 2 h at 15°C and were further transferred to a −20°C freezer and incubated for 24 h prior to plating for CFU counting. As shown in rhlE mutant viability is severely affected after 2 h at 15°C. The rhlB mutant shows slightly smaller colonies at 15°C, but no loss of viability. After 24 h freezing, no difference in viability was observed among the cultures previously grown at 30°C, all showing about a 10-fold reduction in viability. However, the rhlB and rhlE mutants showed a significant reduction in viable cell counts than the wt in cultures pre-incubated at 15°C for 2 h before freezing (2O2) . This indicates that the freezing protection generated by cold adaptation is inefficient in the absence of these RNA helicases and that the role of these enzymes is particularly important in response to this stress.The Δactivity . To testfreezing . These mrhlB gene is induced at low temperature  in the rhlB mutant. Six genes showed opposite expression profiles between temperatures .The perature  and the response . A largeresponse . FourteerhlB mutant increased about sixfold, belonging mainly to the COGs, the inorganic ion transport and metabolism; transcription; amino acid transport and metabolism; translation, ribosomal structure and biogenesis; and posttranslational modification, protein turnover, chaperones , with only two of them being upregulated in the rhlB strain  to assess their decay rate between the wt and rhlB mutant strains at both temperatures  to the cold stress transcriptome (478 genes), we observed a significant overlap of 74 transcripts  is clearly larger than the opposite : there are approximately 78% more genomic positions that have P = 1 relative to P = 0  generated almost identical results .Results from 10°C and 30°C vary markedly. The mutant strain clearly cannot eliminate cleaved RNAs as efficiently as the wt strain at low temperature. The effect practically disappears at 30°C since the excess of mutant-exclusive fragment signals is minimal: there is only a 16% increase of genomic positions that have P. aeruginosa RhlE mutants   causes an accumulation of 5′-ends when compared to the wt strain PAO1 , while the absence of rhlE1 does not (BER = 0.92). These results validate our analysis of the C. crescentus rhlB mutant and confirm that in the absence of the DEAD-box RNA helicase associated with RNase E, there is an accumulation of RNA degradation intermediates and that RNA processing is severely affected likely due to inefficient degradation of structured molecules either by RNAse E and/or PNPase.To evaluate if this increase of 5′-ends is related to the absence of a DEAD-box RNA helicase in the RNA degradosome complex, we used the same method to analyze previously published RNA-seq data from 1/rhlE2) . RhlE2 iC. crescentus, by comparing a null rhlB mutant strain to its isogenic wildtype. The absence of RhlB was previously shown not to affect the binding of the other RNA degradosome components, so the observed effect would be only due to the lack of RhlB activity , it binds to RNA and may affect its decay rates  complex medium (E. coli was grown in a lysogeny broth medium (Sigma-Aldrich). The strains harboring the pBV-MCS4 vector  was also added to the C. crescentus cultures when necessary to induce the expression of the rhlB gene from the pBV-MCS4 vector.The s NA1000  was usedx medium . E. coli4 vector  were grorhlB and rhlE::Tn5 strains were grown in PYE at 30°C overnight, cultures were diluted for optical density at 600 nm (OD600nm) = 0.1 and incubated until OD600nm= 0.3, when small differences among the samples were adjusted to give equal numbers of cells/mL. Aliquots from each culture were: (i) plated on PYE plates and incubated at 30°C or 15°C for the colony-forming unit (CFU) counting; (ii) transferred to a −20°C freezer for 24 h and plated on PYE plates at 30°C for CFU counting; (iii) incubated at 15°C for 2 h and then transferred to a −20°C freezer for 24 hr and on PYE plates at 30°C for CFU counting.The NA1000 and ΔrhlB, and Δfur strains. Cultures were incubated at 30°C in PYE for 16 h. The OD600nm of each culture was adjusted for 0.1 and incubated with either 0, 0.5, or 1.0 mg/mL Streptonigrin (Sigma-Aldrich S1014) for 24 h at 30°C. Aliquots were then plated and incubated for 48 hr at 30°C to determine CFU.The streptonigrin sensitivity test , 57 was 600nm = 0.5) grown in M2 medium in 50 mL Erlenmeyer flasks at 30°C to a shaker at 10°C and further incubating them with agitation at 250 rpm for 2 h. Aliquots from three independent biological replicates grown at 30°C or 10°C in the same batch of M2 medium were collected and maintained at −80°C until RNA extraction.Growth at low-temperature conditions was obtained by transferring cultures  and RNA concentration and integrity were verified with Agilent 2100 Bioanalyzer . rRNA depletion and cDNA libraries were prepared using the Illumina Stranded Total RNA Ligation with RiboZero Plus kit (Illumina), essentially as described in reference . The conFor the RT-qPCR assays, cultures were grown in M2, and total RNA was extracted from 1 mL aliquots with TRIzol RNA (Invitrogen Life Technologies), following the manufacturer’s instructions. RNA concentration after extraction was determined by OD 260/280 nm ratio and integrity was confirmed by electrophoresis.rho gene (Table S2). Synthesis of cDNA was performed using the SuperScript III first-strand synthesis kit (Invitrogen). RT-qPCR was performed using Power SYBR Green and PCR Master Mix (Applied Biosystems), using CCNA_02070 as the internal gene for reference control. Tested RNAs were amplified using primer pairs described in Table S2, and reactions were performed in the StepOnePlus Real-Time PCR System (ThermoFischer Scientific). Relative change in the normalized expression of each gene was calculated by the 2-ΔΔCt relative expression quantification method  the addition of rifampicin (200 µg/mL) and after 2 (t2), 4 (t4), and 6 (t6) min at both temperatures. Samples were centrifuged at 12,000 rpm for 1 min, and pellets were resuspended with TRIzol RNA (Invitrogen Life Technologies) and immediately frozen in dry ice with ethanol. RNA extraction and cDNA synthesis were performed as described above. RT-qPCR was performed using primer pairs to amplify each gene (Table S2). To determine the mRNA decay rate in each condition, the CT of the t0 time point was used as a reference to calculate the relative mRNA levels (ΔCT), from which we calculated the expression ratio (2-ΔΔCt) for each time point.rhlB gene in the pBV-MCS4 plasmid (E. coli S17-1 and subsequently was transferred to the rhlB mutant strain by conjugation.We used the QuikChange Lightning Site-Directed Mutagenesis kit (Agilent) to introduce the M2 (FLAG) coding sequence (primers FLAG-RhlB Fw and Rv) in a previous construction of the  plasmid . The corrhlB mutant strain carrying the pBV FLAG-RhlB plasmid as previously described (C. crescentus strains ΔrhlB pBV-FLAG-RhlB and ΔrhlB pBV-RhlB (without the epitope) were grown in 800 mL of M2 medium with gentamicin with agitation at 30°C until OD600nm= 0.3. Vanillate (0.5 mM) was added, and cultures were incubated for two more hours, reaching a final OD600nm of ~0.5. Formaldehyde was then added to a 0.5% concentration for crosslinking, and cultures were incubated at 30°C for 10 min. RNA extractions were performed using TRIzol RNA (Invitrogen Life Technologies), and the purified RNAs were resuspended with 16 µL diethyl pyrocarbonate (DEPC) water. Isolated RNAs were processed as reported in the RNA-seq section.RhlB RNA targets were identified via co-immunoprecipitation assays using the escribed , 60. BriRNA samples from two independent biological replicates from the pBV-RhlB control strain and three RNA independent biological replicates from the pBV FLAG-RhlB strain were submitted to high throughput sequencing. One microgram of RNA from each sample was used to prepare the cDNA libraries using the Illumina Stranded Total RNA Ligation with RiboZero Plus kit (Illumina), skipping the ribosomal RNA depletion step.Caulobacter crescentus NA1000 cells and delta rhlB cells were grown in an M2G medium overnight. The next day, after diluting the cultures, the mid-log-phase cultures (OD600nm = 0.3–0.5) at 30°C were treated with 10 mg/mL rifampicin resulting in a final concentration of 200 µg/mL in the culture. Just prior to rifampicin addition, 1 mL of culture (0 min) was removed and added to 2 mL of RNAprotect Bacteria Reagent (QIAGEN), vortexed, and incubated at room temperature for 5 min. This step was repeated at 1-, 3-, and 9-min post-rifampicin addition. The cells were pelleted at 20,000 × g for 1 min in 1.5 mL microtubes to prepare for RNA extraction.g for 10 min. The supernatant was transferred to siliconized tubes and 500 µL of chloroform was added, vortexed, and spun at 20,000 × g for 10 min. RNA samples were precipitated using 1× volume of isopropanol and 0.1× volume 5 M NaOAc pH 5.2 overnight at −80°C. The RNA samples were centrifuged at 20,000 × g for 1 h at 4°C. Pellets were washed with cold 80% ethanol and centrifuged for 10 min at 20,000 × g, air-dried, and resuspended in 10 mM Tris-HCl (pH 7.0).Pelleted cells were resuspended in 1 mL of pre-warmed (to 65˚C) TRizol Reagent (Ambion) and incubated for 10 min at 65°C. Two hundred microliter of chloroform wasadded to the samples and the tubes were gently inverted a few times. Then, the samples were incubated at room temperature for 5 min and spun at 20,000 × Caulobacter crescentus rRNAs from siTOOLs Biotech) and library construction was performed according to the protocol in reference  was added and then incubated for further 2 h. A C. crescentus strain containing a FLAG-RNE fusion  Bolt 1× sample buffer and boiled for 10 min before transferring to ice and centrifuged at 12,000 rpm for 3 min. Supernatants were applied to a denaturing Bolt 4%–12% Bis-Tris Plus (Invitrogen) gel in 2-(N-morpholino)ethanesulfonic acid (MES) buffer and submitted to electrophoresis (150 V for 30 min). Proteins were then transferred to a nitrocellulose membrane at 250 mA for 1 h and the immunoblot was conducted as the method described previously   –67, ani/frtc/)  and custs Viewer  was useds Viewer .HITS-CLIP data were analyzed using the peak-caller Piranha . First, R2 and unpaired R2 reads to account for the 5′ end of the sequenced fragments using SAMtools (Pi = mutanti/(mutanti + wti) for each i genomic position. For every position in the genome, P = 1 means zero counts in the wild-type strain, P = 0 means zero counts in the mutant strain, and P = 0.5 means both strains have the same number of counts. Since these counts are high, a continuous Gaussian model was imposed as an approximation with variance pooled from all P except our biologically relevant targets, P = 0 and P = 1, assuming them as the background noise informing the model. A Bayesian Decision Theory approach was used to compare the statistical significance of the difference between P = 0 and P = 1 counts (https://github.com/bpicinato/ccrescentus_fragmentation_drhlB.Fragmentation was indirectly inferred by the number of aligned reads representing all sorts of fragments. To avoid mathematical difficulties in normalizations, for this specific analysis, we used an undersampling approach setting artificially the sequencing depth to 90% of the number of uniquely aligned reads from the less sequenced library and randomly sampling this number of reads from all libraries equally. From the resampled BAM alignment files of paired-end RNA-seq experiments, we generated filtered files containing only paired SAMtools . Then, w1 counts . Namely,


Salmonella enterica across multiple stages of growth. We have identified the OmpD porin mRNA as a central regulatory hub that is targeted by a dozen sRNAs, including FadZ cleaved from the conserved 3’UTR of fadBA mRNA. Both ompD and FadZ are activated by CRP, constituting a type I incoherent feed-forward loop in the fatty acid metabolism pathway. Altogether, we have established an approach to profile RNA-RNA interactomes in live cells, highlighting the complexity of RNA regulatory hubs and RNA networks.Small noncoding RNAs (sRNAs) are crucial regulators of gene expression in bacteria. Acting in concert with major RNA chaperones such as Hfq or ProQ, sRNAs base-pair with multiple target mRNAs and form large RNA-RNA interaction networks. To systematically investigate the RNA-RNA interactome in living cells, we have developed a streamlined in vivo approach iRIL-seq (intracellular RIL-seq). This generic approach is highly robust, illustrating the dynamic sRNA interactomes in  Here the authors report a new approach to profile RNA-RNA interactions in live bacterial cells. The charted RNA interaction networks unveil a key mRNA regulatory hub targeted by twelve small RNAs, including a novel RNA involved in fatty acid metabolism. Bacterial sRNAs often act in concert with major RNA chaperones such as Hfq or ProQ4, and regulate the expression of target mRNAs via direct base-pairing interactions2. Most sRNAs regulate more than one mRNA using a conserved seed sequence that has partial complementarity to target mRNAs7. Vice versa, functionally important mRNAs  are targeted by several different sRNAs, which have been conceptualized as mRNA regulatory hubs8. These mRNAs and regulatory sRNAs thus constitute a large and intricate RNA-RNA interaction network involving hundreds of genes in bacteria10. The scale of this RNA-RNA network now begins to rival that of the protein-protein and protein-DNA interaction networks, and covers all aspects of bacterial physiology including central metabolism, cell shape, envelope integrity, quorum sensing, biofilm formation, antibiotic resistance, host infection, symbiosis and more18.Gene regulation at the post-transcriptional level is crucial for the rapid, global response to environmental changes and survival under stressful conditions. The largest class of post-transcriptional regulators in bacteria are small noncoding RNAs of 50–250 nt in length21, and also by profiling the RNA interactome using global approaches24. RIP-seq (RNA immunoprecipitation and sequencing) profiling of Hfq-bound transcripts have discovered a plethora of sRNAs that are derived from the 3’ region of mRNAs25. These sRNA are either transcribed from gene-internal promoters26, or processed from mRNAs by the major endoribonuclease RNase E30. The latter was first exemplified by the CpxQ sRNA, a 58-nt 3’UTR fragment cleaved from the mRNA of envelope-stress chaperone CpxP and represses the expression of multiple extracytoplasmic proteins involved with envelope stress response31. Despite the absence of a 5’PPP cap, these processed 3’UTR-sRNAs stably accumulate in vivo and function as missing regulatory arms in well-characterized pathways21. With hundreds of Salmonella mRNAs that have the potential to produce 3’UTR-derived sRNAs by RNase E cleavage25, the true number of such 3’UTR-sRNAs may be underestimated, leaving key regulatory nodes missing in the RNA interaction network and physiological pathways.The bacterial RNA interaction network has been rapidly expanding, driven by the discovery of novel sRNAs from unexpected genomic locations23), CLASH , and Hi-GRIL-seq . Both RIL-seq and CLASH rely on UV-crosslinking and in vitro RNA ligation using a purified T4 RNA ligase, which mediates proximity-ligation of sRNAs to their interacting partners crosslinked on an RNA-binding protein such as Hfq or ProQ. It has enabled systems-wide analyses of RNA-RNA interactomes in several Gram-negative bacterial pathogens including E. coli34, S. enterica35, Pseudomonas aeruginosa36, and Vibrio cholerae13. These global analyses identified new sRNAs acting as RNA sponges, advanced our understanding of sRNA-target interactions, and revealed fundamental regulatory networks. However, current approaches are complicated by the use of irreversible UV crosslinking and lengthy in vitro on-bead reactions including RNase trimming, RNA end repair, ligation, and protease digestion steps prior to cDNA library preparation37. These technically demanding and error-prone steps may introduce in vitro artefacts and biases, hindering the identification of physiologically important regulations in vivo and the elucidation of RNA interactomes in living cells. Hi-GRIL-seq is an alternative in vivo approach that enables RNA proximity-ligation by T4 RNA ligase expressed inside bacteria32, which however has noisy background and limited throughput for in-depth analysis of RNA interactome at the systems-wide level.To interrogate the bacterial RNA-RNA interactome, several global approaches have been developed to profile sRNA-mediated interactions, such as RIL-seq   from an inducible pBAD promoter  Fig. . By pulsflhD38 and CyaR-ompX39. As important controls, chimeras were not detected in the absence of T4 RNA ligase or in the control IP (untagged WT) samples. We also did not detect chimeras for non-target interactions , together indicating the high specificity and sensitivity of our in vivo ligation and capture strategy.To validate the feasibility of the approach, we have successfully detected in vivo ligation products using RT-PCR for several known sRNA-target pairs in Hfq-coIP samples  confirms that most sRNAs are ligated to the 5’UTR and CDS of mRNAs , and over 90% of sRNAs are located at the 3’ end (“RNA2”)  Fig. . This diSalmonella growth in LB medium. At EP , ESP (early stationary phase) and SP (stationary phase), we induced the expression of T4 RNA ligase in Salmonella for 30 min, and then pulled down Hfq and its bound RNAs , our iRIL-seq analysis identified a total of 436, 855 and 1705 statistically significant RNA–RNA interactions under three growth conditions, respectively  from RIL-seques Fig. . Strikinues Fig. 42,43. Th44 had the highest abundance among ArcZ S-chimeras in our dataset. We also captured the classical ChiX-chbBC sponge pairs45, as well as the OppX-MicF sponge complex that was recently recognized to adjust envelope porosity to transport capacity35.In addition to these sRNA-mRNA interactions, we also identified almost 100 sRNA-sRNA chimeras involving many potential RNA sponges , all of which were captured as S-chimeras in our dataset , but also showcase the reliability and robustness of iRIL-seq analysis.Among the most-targeted mRNAs are tes Fig. , among wRNA Fig. , whereasRNA Fig. . To valimpD Fig. , while sSalmonella using differential RNA-seq51 and proposed as a 3’UTR-derived sRNA52. It is located within the 196 nt-long 3’UTR of the fadBA mRNA, which encodes enzymes involved in fatty acid oxidation and metabolism  for detailed characterization. FadZ was initially described as a primary sRNA candidate in ism Fig. . Our iRInia Fig. , was pulnia Fig. . On nortoli Fig. . As experneTS)  in an RNase E temperature-sensitive strain (TS) Fig. , suggestTS) Fig. 25. MutatompD mRNA  at the post-transcriptional level , which may affect the transcriptome during induction. Besides Hfq, the iRIL-seq approach needs further validation for other RNA-binding proteins with varying affinity to sRNAs, such as ProQ and CsrA, where UV crosslinking might become necessary to stabilize RNA chimeras. Future addition of end-repairing steps in vivo  might improve ligation with primary sRNAs by iRIL-seq.59. Despite the growing interest in the class of processed sRNAs, there is a lack of specialized method to globally identify and differentiate them from degradation intermediates. The discovery of processed sRNAs has been previously aided by mapping the RNase E-cleavage fragments using TIER-seq, and by identification of Hfq-associated RNAs using RIP-seq in our earlier studies25. Building on Hfq RIP-seq20, the iRIL-seq approach here represents an effective method to differentiate processed, functional sRNA regulators from degradation intermediates. Our results show that iRIL-seq readily captures processed sRNAs and their abundant ligation products in chimeric reads , RpoS, CRP, Cfa, as well as Hfq itself, most of which play crucial functional or regulatory roles in bacteria. For the general stress factor RpoS, our data suggest it may interact with its downstream regulator SdsR64, as well as MgrR in the PhoPQ pathway67, in addition to the three known activating sRNAs . This suggests that the even well-studied hub genes such as RpoS may have additional novel sRNA regulators that remain to be discovered using RNA-RNA interactome approaches. Of note, we have not detected chimeras for the CsgD hub and its targeting sRNAs8, probably because this master regulator of biofilm formation is not expressed under the conditions used in this study. This indicates that many more key regulatory hubs may be waiting to be discovered in bacteria under different growth conditions.Apart from 68. Long-chain fatty acids are taken up by a high-affinity porin FadL, and metabolized by pairwise removal of carbon atoms through successive rounds of β-oxidation, releasing ATP and other molecules including acyl-CoA, acetyl-CoA, NADH, and FADH69. This makes fatty acid oxidation crucial for many other catabolic processes such as the TCA and glyoxylate cycles, as well as the synthesis of cell wall components. The fatty acid metabolism pathway is known to be regulated by the master transcription factor FadR54. Downstream of FadR, we have found FadZ as the missing cognate sRNA regulator in this pathway in enterobacteria. FadZ is processed by RNase E from the 3’UTR of fadBA mRNA, and represses major porins OmpD and OmpC . This type of regulatory loop is not uncommon for sRNAs in bacteria, for example PhoP-AmgR-mgtC in Salmonella72, PrrA-PcrZ-bchN in Rhodobacter73, and involving a 3’UTR-derived sRNA, NarL-NarS-nirC in Salmonella30. The results here add FadZ as another example of 3’UTR-derived sRNA mediated I1-FFL. In this case, the sRNA might function as a fine-tuning mechanism to minimize fluctuation in target mRNA levels in response to fatty acid oxidation.The biogenesis of FadZ is under multiple layers of control in lla Fig. . Its parSalmonella enterica serovar Typhimurium strain SL1344 was used as wild-type. Strains with deletions or chromosomally 3xFLAG epitope-tagging were constructed using the λ-Red recombinase method75. Bacteria were grown at 37°C with 220 rpm shaking in lennox broth (LB) or M9CA minimal medium (#A507025) supplemented with 0.1% carbon source: glucose (#A501991), octanoic acid (#A501844), oleic acid (#A502071) at pH 7.0. Brij 58 (#A606306) was added at a final concentration of 0.4% as vehicle to promote dissolution of fatty acids. For T4 RNA ligase pulse expression, bacteria were grown in LB at 37 °C to the indicated OD600, L-arabinose was then added to the final concentration of 0.2% for 30 min. For the rne-TS experiment, bacteria were grown in LB at 28 °C to an OD600 of 1.0, and then shifted to 28 °C or 44 °C for 30 min. For oleic acid exposure assays, overnight cultures were grown from a single colony in M9CA minimal medium supplemented in 0.1% glucose with 0.4% Brij-58, diluted 1:100 in fresh medium and grown to OD600 of 1.0. Cells were washed twice with PBS at room temperature and resuspended in M9CA minimal medium supplemented with 0.1% oleic acid and 0.4% Brij-58. Where appropriate, media were supplemented with antibiotics at the following concentrations: ampicillin (Amp), 100 μg/ml; kanamycin (Kan), 50 μg/ml; chloramphenicol (Cm), 20 μg/ml; and hygromycin (Hyg), 100 μg/ml. Unless stated otherwise, chemicals were purchased from Sangon Biotech, Shanghai. The plasmids were documented in Supplementary Data Bacterial strains used in the study can be found in the Supplementary Data Salmonella and hfq::3xFLAG tagged strains carrying the plasmid pYC582 were grown in LB medium at 37 °C with 220 rpm shaking. T4 RNA ligase was induced for 30 min by addition of 0.2% L-arabinose when the culture reached the indicated OD600 . The strains were grown to EP , ESP  and SP , respectively. A culture volume corresponding to 50 OD600  of bacterial cells were collected by centrifugation at 12,000 g for 5 min. The pellets were washed twice with 10 ml precooled PBS and stored at −80 °C until use. Hfq-coIP was performed using a published protocol in our previous reports20. The bacterial pellets were resuspended in 600 µl ice-cold lysis buffer , and lysed for 10 min with 500 µl glass beads using Cryolys Evolution at 4 °C. Cell lysates were collected by centrifugation for 30 min at 17,000 g at 4 °C, and transferred to new tubes. The lysates were incubated with anti-FLAG antibody  conjugated protein G magnetic beads  for 1 h at 4 °C with rotation. The beads were washed five times with 500 µl ice-cold lysis buffer and resuspended in 100 µl lysis buffer. The Hfq-bound RNA was purified using RNA clean & concentrator columns  and resuspended in nuclease-free water.Wild-type 37. Briefly, RNA was subjected to fragmentation and DNase I treatment, and purified with 2.5x Agencourt RNAclean XP beads  and 1.5x isopropanol. RNA was ligated to the 3’ barcoded adaptor and purified with 2.5x AMPure XP beads and 1.5x isopropanol. Ribosomal RNA was removed using Ribo-off rRNA depletion Kit . The rRNA depleted sample was purified with 2.5x RNAclean XP beads and 1.5x isopropanol. First strand cDNA was synthesized using HiScript II 1st Strand cDNA Synthesis Kit . RNA was degraded by 1 M NaOH. cDNA was purified with 2.5x AMPure XP beads and 1.5x isopropanol. The cDNA 3’ end was attached to a second adaptor and cleaned up twice with 2.5x RNAclean XP beads and 1.5x isopropanol. Libraries were PCR amplified with Illumina P5 and P7 primers using Q5 High-Fidelity DNA Polymerase , and purified with 1.5x RNAclean XP beads. The libraries were sequenced by 150 bp paired-end sequencing with an Illumina NovaSeq 6000 instrument.iRIL-seq libraries were constructed using the RNAtag-Seq protocol with a few modifications37. The raw sequencing reads of iRIL-seq in fastq files were processed by cutadapt to trim the adaptor sequence and remove low-quality ends. In order to detect chimeric fragments, the first 25 nucleotides of high-quality paired-end reads were taken and mapped to the genome of Salmonella strain SL1344 (NC_016810.1) using the BWA software with default parameters. The paired reads obtained from paired-end sequencing by Illumina NovaSeq are considered two mates. If two mates of 25 nt from both ends of a sequenced fragment were mapped to different genomic locations and the distance is greater than 1000 nt, the fragment was called as chimera. Otherwise, the fragment was defined as singleton when the mates mapped to the same transcript or within a distance of 1000 nt. Significant chimeras (S-chimera) were analyzed by comparing the detected pairwise interactions to the counts of random ligations using a Fisher’s exact test as previously reported37. Each Chimera was assigned a p-value and an Odds Ratio value by multiple hypotheses testing. Chimeras with a p-value ≤ 0.05 and an Odds Ratio ≥1 were defined as S-chimeras. Only S-chimeras with ≥10 sequenced fragments were presented and further investigated. For the genome annotation of RNA fragments, the genomic features were classified into eight major categories: housekeeping RNA , tRNA, rRNA, CDS, IGR (intergenic region), sRNA, 3’UTR, CDS, 5’UTR.The sequencing data were analyzed similar as previous RIL-seq methods76. The consensus motifs related to Supplementary Fig. 76. Only motifs that had an E-value ≤ 0.05 were considered.To analyze the sequence features of RNAs located in RNA2, all the sequences of RNA2s in Supplementary Data Bacterial samples were collected and resuspended in 1× protein loading buffer and incubated at 95 °C for 5 min to lyse the cells. For SDS-PAGE, 0.1 OD of total protein samples were loaded per lane. Gels were stained overnight with Coomassie blue and visualized using ChemiDocTM XRS+ (Bio-Rad). For Western blotting, 0.05 OD of proteins samples were loaded per lane and separated by SDS–PAGE. Proteins were transferred onto nitrocellulose membrane  and blocked with DifcoTM skim milk . Membranes were incubated with monoclonal α-FLAG , α-His  or α-GroEL  antibodies, and secondary α-mouse or α-rabbit HRP-linked antibodies . Chemiluminescence was developed using the Novex™ ECL Chemiluminescent Substrate Reagent Kit , and then visualized on ChemiDocTM XRS+ and quantified using ImageLabTM Software.Salmonella strains carrying GFP translational fusions were grown in LB media containing Amp and Cm to an OD600 of 0.5. 100 μl of the cultures were collected and washed 3 times with 1x PBS and fixed with 4% paraformaldehyde. GFP fluorescence intensity was quantified by a microwell plate reader or flow cytometry .2PO4, 10 mM KCl, 1 mM MgSO4, pH = 7.0 and supplemented with 2.7 ml of β-mercaptoethanol per liter). Mixtures were vortexed and incubated at 30 °C for 5 min and then added with 200 μL ONPG buffer  to start the reaction at 30 °C. When the reaction mix became yellow in the optimal range (OD420 0.2–1.0), 500 µl of 1 M Na2CO3 was added to stop the reaction. Reaction mixture was centrifugated and 200 μL supernatant was collected for OD measuring. OD420 and OD550 were read on a Bio-Rad benchmark plus microplate reader with the Z-buffer as blank. β-galactosidase activity was calculated in Miller units with the following formula: 1000 × (OD420 – 1.75 × OD550)/(OD600 × time[min] × 0.1 [ml]).100 μL bacterial culture was collected and mixed with 15 μL 0.1% SDS, 30 μL chloroform and 700 μL Z buffer .Bacterial total RNA was isolated using the hot phenol method. Briefly, Cells were resuspended in lysozyme, 10% SDS and 3 M sodium acetate (pH 5.2). The cleared lysate was mixed with saturated phenol (pH 4.5) and incubated at 64 °C for 6 min with shaking. After mixing with chloroform and centrifugation in a Phase Lock Gel tube , the aqueous phase was collected and mixed the with 30:1 ethanol: sodium acetate (pH 6.5) and precipitated at −80 °C overnight. RNA pellets were washed with 80% ethanol and dissolved in nuclease-free water. The RNA concentration was determined using NanoDrop 2000. 10 μg of total RNA was denatured at 95 °C for 2 min in RNA gel loading buffer II, and separated by gel electrophoresis on 6% polyacrylamide/7 M urea gels in 1x TBE buffer. RNA was transferred to Hybond-N+ membranes  by electroblotting. For agarose gels, 25 μg of total RNA was denatured at 65 °C for 5 min in RNA loading buffer and separated in 1.2% agarose gels containing 1% formaldehyde in 1x MOPS buffer. Gels were stained with ethidium bromide to visualize rRNA, then transferred onto Hybond-N+ membranes  using capillary blotting in 10x SSC buffer overnight. The membranes were cross-linked with UV light (120 mJ/cmfadBA) was hybridized at 68 °C overnight. Membranes were washed three times, for 15-min each, in 5× SSC/0.1% SDS, 1× SSC/0.1% SDS and 0.5x SSC/0.1% SDS buffers at 50 °C for the DNA probe or 68 °C for the RNA probe. After one wash in maleic acid wash buffer for 5 min at 37 °C, and then blocking solution  for 45 min at 37 °C, membranes were incubated with 75 mU/mL Anti-Digoxigenin-AP  in blocking solution for 45 min at 37 °C. Membranes were then washed in maleic acid wash buffer twice for 15 min each, and equilibrated with detection buffer. Signals were visualized with CDP-star  on a ChemiDocTM XRS+ station and quantified using ImageLabTM Software.Northern blot analysis was performed using the Roche DIG system. Briefly, membranes were prehybridized in DIG Easy Hyb  for 30 min. The Digoxin-labeled DNA probe  was hybridized at 50 °C overnight. The Digoxin-labeled RNA probe . 1 μg total RNA was treated with gDNA eraser and then reverse-transcribed to cDNA with random oligos and PrimeScript RT Enzyme Mix I. cDNA transcribed from 0.025 μg total RNA was used per PCR reaction with TB Green Premix Ex Taq II . PCR was performed using a Bio-Rad CFX96 Touch Real-Time PCR Detection System. Data were analyzed by the relative quantification (ΔΔCt) method, with the Further information on research design is available in the Supplementary InformationPeer Review FileReporting SummarySupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7


Each exerts its function by targeting different types of genetic material within cells.RNA therapy is defined as the prevention or treatment of disease using RNA-based molecules. In a previous review, I categorized RNA therapy based on the chemistry of various RNA molecules into the categories of antisense RNA, small-interfering RNA (siRNA), RNA aptamers, and messenger RNA (mRNA)2. RNA-based drugs, such as those that utilize antisense RNAs and siRNAs, inhibit protein production by targeting mRNA, an intermediate product of protein expression1. In addition, RNA aptamers can regulate proteins by binding to them directly. However, the products from non-coding RNA genes, which are more abundant than protein-coding genes in cells3, are similar to one another, except for in their sequences; thus, it is difficult to use conventional small-molecule- or antibody-based drugs to target them based on structural differences. In contrast, RNA-based drugs, including antisense RNAs and siRNAs, can bind to target RNAs in a sequence-specific manner, which means that these RNA drugs can suppress non-coding RNAs with similar structures but different sequences.A key advantage of RNA therapy is its ability to target a wide variety of substances in cells. As exemplified by recent drugs targeting cancer, small molecule- and antibody-based drugs are commonly used to treat diseases, and they mainly target proteins by recognizing the specific structure of a target protein4. These miRNAs act as important regulators of human disease progression; cancer was the first disease in which their importance was studied. In an early study to comprehensively profile normal and cancerous tissues using microarrays, the expression patterns of miRNAs were found to clearly distinguish cancerous tissues from normal tissues5. Moreover, another study showed that the origin of cancerous tissue can be accurately identified by measuring the expression of miRNAs6. Building on these preliminary studies and other important research, various miRNAs that control the oncogenes or tumor suppressor genes important in the progression of diverse cancer types have been identified.Diverse non-coding RNAs play important roles in disease progression, and controlling them is important for treating human disease. Regarding non-coding RNAs, the importance of small RNAs in particular has been emphasized in recent years. Specifically, small non-coding RNAs that regulate other molecules are important modulators of various cellular signaling pathways. One of the most intensely researched RNAs is microRNA (miRNA). MiRNAs are single-stranded, small regulatory RNAs of approximately 23 nucleotides that modulate mRNAs, mainly by targeting their 3'-untranslated regionsExperimental & Molecular Medicine, Kim & Croce summarize recent and ongoing miRNA clinical trials focusing on cancer diagnosis and therapy7.Since then, much research has been performed, and efforts continue to develop therapies that target key miRNAs. To inhibit disease-associated miRNAs, antisense RNA, which can bind directly to miRNAs, can be utilized. This binding prevents miRNA from regulating its target mRNAs. However, if increased expression of a miRNA is expected to inhibit the progression of a particular disease, the miRNA sequence can be synthesized and administered to patients. In this special issue of 8. Instead, a great amount of work has been conducted with the goal of silencing specific RNAs by introducing chemically synthesized siRNAs into cells. This technique, known as RNA interference, can be used to transiently induce the cleavage of target RNAs that are important in disease progression9. Based on this mechanism, many siRNA-based drugs have been developed, and some have already been approved to treat specific diseases1.SiRNAs are another important family of small regulatory RNAs that are mechanistically similar to and share core functional molecules with miRNAs. Although they are expressed endogenously in cells, their roles as regulators have been studied less often than those of miRNAs10. SiRNAs are being actively investigated as therapeutic agents for diverse metabolic diseases related to the liver, especially with the help of hepatocyte-targeting conjugates, such as N-acetylgalactosamine11. However, the siRNA targeting of the transcripts residing in other organs has been less well researched because it is challenging to deliver siRNAs to other organs. Therefore, developing siRNA-based drugs that can target various organs is the most important issue in this field, and is a challenge that Han and colleagues discuss in this issue of Experimental & Molecular Medicine12.However, to date, the siRNAs that have been approved or are being studied mainly target enzymes in liver cells. This is because when siRNA is injected into the body, a significant proportion of the molecules are primarily targeted to the liver via circulation13.There are many other types of small regulatory RNAs in cells. In particular, transfer RNAs (tRNAs), which were initially known only for their auxiliary roles in transferring amino acids during mRNA translation, have recently been recognized to play important roles as intracellular regulators. The cleavage products of tRNAs, called tRNA-derived small RNAs (tsRNAs), play important roles in the progression of cancer, and this topic is discussed by Kim and colleagues in this special issue1. Based on these strengths, various mRNA-based vaccines against a wide range of infectious diseases are currently being developed14. However, as seen in the case of the COVID-19 vaccine, many people who have received the vaccine have complained of side effects, which is a phenomenon requiring further study. In this special issue of Experimental & Molecular Medicine, Lee et al. describe immune responses and adverse effects triggered by mRNA vaccines and discuss the challenges in balancing these effects15.While RNA-based drugs to target these various small regulatory RNAs are in development, it is perhaps the mRNA vaccine for coronavirus disease 2019 (COVID-19) that has spurred major research interest in RNA therapy. It was possible to develop an mRNA-based vaccine to counter the COVID-19 pandemic because mRNA-based materials can be developed quickly. Moreover, once the chemistry of the material has been established and the synthesis platform is in place, RNA-based drugs can be easily adapted to the treatment of other types of diseases by changing their RNA sequencesAs shown by recent studies, the field of RNA therapy has made significant progress. In particular, the ability to target various genetic materials in the body and to develop drugs quickly are reasons to believe that more research efforts will be focused on the development of RNA-based therapeutics in the future. It is expected that by developing better drugs, it will become possible to overcome diseases that were previously difficult to treat and prevent.