Thus, our findings suggest an unanticipated RNA chaperoning role for Npl3 during spliceosome active site formation.The conserved SR-like protein Npl3 promotes splicing of diverse pre-mRNAs. However, the RNA sequence(s) recognized by the RNA Recognition Motifs (RRM1 & RRM2) of Npl3 during the splicing reaction remain elusive. Here, we developed a split-iCRAC approach in yeast to uncover the consensus sequence bound to each RRM. High-resolution NMR structures show that RRM2 recognizes a 5´-GNGG-3´ motif leading to an unusual mille-feuille topology. These structures also reveal how RRM1 preferentially interacts with a CC-dinucleotide upstream of this motif, and how the inter-RRM linker and the region C-terminal to RRM2 contribute to cooperative RNA-binding. Structure-guided functional studies show that Npl3 genetically interacts with U2 snRNP specific factors and we provide evidence that Npl3 melts U2 snRNA stem-loop I, a prerequisite for U2/U6 duplex formation within the catalytic center of the B Here the authors identify the sequence bound by Npl3 and solve the structure of the complex using NMR. Npl3 binds directly to the U2 snRNA and melt the stem-loop I, suggesting a chaperoning role during spliceosome active site formation. SR proteins typically contain one or two N-terminal RNA-recognition motifs (RRM) followed by a C-terminal arginine-serine-rich (RS) domain3. In humans, 12 proteins belong to the SR protein family named SRSF1 to SRSF123. They are found in all metazoans in which they play a role in constitutive and alternative splicing regulation of most genes4. In contrast, only around 4% of the genes of the budding yeast Saccharomyces cerevisiae contain introns and a few among them are alternatively spliced6. Consequently, only three SR-like proteins were identified in budding yeast 8. Of the three proteins, only Npl3 can promote splicing of intron-containing genes9. Npl3 was proposed to facilitate the splicing reaction by promoting the co-transcriptional recruitment of the spliceosome on chromatin through interactions via U1 and possibly U2 snRNPs9 and with the Rad6 complex that adds a mono-ubiquitin to the histone H2B10. Recently, Npl3 was also shown to be involved in the late steps of yeast spliceosome assembly by stimulating Prp28 helicase activity when Npl3 is phosphorylated. It was proposed that Npl3 may be the functional counterpart of the metazoan Prp28 N-terminal region that is absent in the yeast counterpart11. Finally, Npl3 was also shown to be required for the proper execution of the meiotic cell cycle by promoting splicing of introns containing non-consensus splice sites12. Npl3 has been implicated to function in multiple processes of gene expression including mRNA transcription elongation and termination17, mRNA export under stress19 and translation21. Npl3 was also reported to maintain genome chromatin stability by preventing R-loops formation22, contributing to telomere maintenance23 and promoting double-strand DNA break repair24. Npl3 shares many functions with other metazoan SR proteins, and therefore serves as an ideal model to understand the evolution of SR proteins.Serine and Arginine-rich (SR) proteins belong to a family of proteins best known for their function in pre-mRNA splicing regulation, as well as multiple steps of gene expression from transcription to translation26. The first canonical RRM is followed by a second pseudo-RRM28. Although Npl3 binding to RNA is important for its functions, its mode of RNA-recognition remains elusive. The structures of the two RRMs of Npl3 were previously determined in their free form and showed that both RRMs do not interact30. Npl3 was shown to bind preferentially to UG-rich RNA sequences using primarily its pseudo-RRM (RRM2)29, and a structural model of both RRMs bound to RNA indicates that the RRM1 could bind to a CA motif31.Npl3 is composed of two consecutive RRMs separated by a flexible eight amino acids linker that are followed by a C-terminal RS domain containing an Arg-Gly-Gly (RGG) repeat16 and iCLIP technologies32, to identify the RNA sequences bound by yeast Npl3 in vivo. Using NMR spectroscopy, we determine the structures of both RRMs bound to a representative RNA consensus sequence obtained with the split-iCRAC approach. Our analyses reveal that RRM1 binds preferentially upstream of the RRM2 binding site. Both domains recognize a distinct RNA motif: 5’-NCCN-3’ and 5’-GNGGN-3’, respectively  with the interdomain linker contributing to the RNA binding. Structure-guided studies reveal that mutations within RRM1, but not RRM2, negatively impact Npl3 function. However, Npl3 RRM2 has a specific effect on the splicing reaction, that is mediated through an unanticipated interaction of the protein with the U2 snRNA. We show that this interaction destabilizes the U2 snRNA stem-loop I, thus suggesting an RNA chaperoning role for Npl3 during the formation of the spliceosome active site.Here, we develop split-iCRAC, a combination of CRAC29 and in vivo16. However, the precise RNA motif(s) recognized by the two RRMs has remained elusive. To uncover the recognition motif of Npl3 in vivo, we performed a Crosslinking and Analysis of cDNA (CRAC) experiment with two key modifications16. First, we introduced an HRV-3C protease cleavage site directly after the sequence of RRM2 to distinguish RNAs that interact with the RRMs from those that are bound to the RGG/RS domain  strategy to prepare the cDNA library and obtain single nucleotide resolution of the crosslinking sites32. We termed this approach split-iCRAC. After HRV-3C cleavage, most of the RNA bound by Npl3 was detected with the RRMs  of 0.5 µM was determined with ITC for this complex  as the consensus sequence interacting with RRM1/2 and the full-length Npl3 Fig. . To valilex Fig. . The idelex Fig. , which hRMs Fig. . MoreoveRMs Fig.  were verlex Fig. . Taken t39 with ssDNA containing CX or XC motif  flanked by degenerated sequences  was significantly higher than each isolated RRM   Figs.  suggesti38. In order to more precisely position this base, we used in our structure calculations the same restraints for G9 H1 and residues of Npl3 RRM2 as for the structure determination of SRSF1 RRM2 bound to RNA38. Those restraints did not induce any distance violations indicating that they were in perfect agreement with all other experimentally derived restraints.Next, we investigated the mode of RNA recognition of both Npl3 RRMs. Although many intermolecular NOEs between Npl3 RRM1/2 and 5´-AUCCAGUGGAA-3´ could be observed, the quality of the NMR data was always better in the complexes with isolated RRMs. However, the similarity of the chemical shift perturbations observed upon RNA binding for the isolated RRMs and the RRM1/2 complex . These contacts also explain the chemical shift changes seen for Ile 279 and Arg280 upon RNA binding  derived restraints  adopting a “mille-feuille” topology, which certainly contributes to the higher RNA affinity of RRM2 compared to RRM1.Although no inter-NOE could be observed between the Arg199 and the base, the structure suggests that this side chain may interact with Gion Fig. . In goodd of 0.5 µM to 10.7 and 12.8 µM, respectively . Mutations that affect the recognition of the GG dinucleotide by RRM2 (Q214A and K217A) also showed a moderate decrease in binding affinity with Kd values increasing to 1.7 and 7.5 µM, respectively . The importance of this interaction was further corroborated by the drop in binding affinity (Kd of 2.2 µM) observed between WT RRM1/2 and a G6A RNA variant . Surprisingly, shortening the RNA by removing A5 did not affect RRM1/2 binding affinity. We can explain this effect by the presence of a very short inter-RRM linker (only 7 residues), which forces the two spacing nucleotides to adopt a loop to compact the RNA backbone  decreased the binding affinity strongly from a Kone Fig. . As a coone Fig. . Neverthone Fig. . This inone Fig. : mutatioone Fig.  indicatinpl3 gene (npl3∆) were transformed with plasmids expressing these mutants under the control of the natural Npl3 promoter. We investigated whether they could rescue the slow growth of the npl3∆ strain9. Interestingly, the complementation with Npl3 having single or double substitutions in RRM1 failed to completely rescue the slow growth defects  or RRM2  9 or chromatin remodeling (ex. rad6 and bre1)10. We investigated the respective involvement of both Npl3 RRMs in these two functions by testing whether the RRM1 and RRM2 mutants of Npl3 would lead to the same genetic interaction. In agreement with the predominant importance of the RRM1 RNA binding interface, we observed genetic interactions of RRM1 mutated Npl3 with the four tested genes  and GG (RRM2) sequences  including the two parts involved in the duplex formation with the U6 snRNA (underlined sequences). Using NMR spectroscopy, we confirmed that this RNA adopted the expected secondary structure based on previous NMR assignments obtained with this stem-loop41. In addition, the titration of this stem-loop with Npl3 RRM1/2 showed that the protein could interact with the U2 SL I sequence and destabilized the stem , the position of the two cytosines on the β-sheet surface and their recognition by the RRM are quite similar  is required to allow the two RRMs to lie side-by-side (β2-β4 type) and form an extended β-sheet RNA binding surface48. Recently, two structures (Dnd150 and Npl3 in this work) revealed new ways for tandem RRMs to bind RNA cooperatively with RRM1 binding to the 5’-end despite having a short interdomain linker . In such cases, the canonical β-sheet surface of the RRM is not used but rather both sides of the domain. In Dnd1, the α2−β4 edge of the RRM is used while in Npl3, this is the α1−β2 edge nes Fig. . However52. In yeast, the use of a npl3 Δ strain revealed a general decrease of pre-mRNA splicing suggesting a role in constitutive splicing. Npl3 was reported to facilitate co-transcriptional splicing by recruiting the U1 snRNP on RNA pol II9. In addition, the protein was recently shown to interact with U1 snRNP through protein-protein interaction using its RGG/RS domain53. However, we could not detect in our iCRAC data any specific enrichment of Npl3 binding around spliced introns nor specific enrichment in ribosomal protein genes. In good agreement with this observation, it was previously proposed that the recruitment of Npl3 at these sites might be driven through interactions with other proteins and chromatin modifications10. Our split-iCRAC data show a specific binding of Npl3 to the Stem-loop I of the U2 snRNA. Moreover, RNA mutations that prevent the binding of Npl3 without affecting the stability of the Stem-loop I resulted in a slow growth phenotype in combination with the deletion of lea1, as observed with Npl3 mutants preventing its binding to RNA  steps. The proteins were dialyzed in RRM1 NMR buffer , RRM2 NMR buffer , or RRM1/2 NMR buffer . The concentration of recombinant proteins was carried out using 10-kDa molecular mass cut-off Centricons (Vivascience®). The absence of RNases was confirmed using the RNase Alert Lab Kit (Ambion®).Escherichia coli BL21 (DE3) codon plus cells transformed with pET28a::Npl3 RRM1 (residues 114–201), pET28a::Npl3 RRM2 (residues 193–282) or pET28a::Npl3 RRM1/2 (residues 114–282) were grown at 37 °C in M9 minimal medium supplemented with 50 µg/ml kanamycin, 34 µg/ml chloramphenicol, 1 g/l All RNA oligonucleotides were purchased from Dharmacon®, de-protected according to manufacturer’s instructions, lyophilized and resuspended in the corresponding NMR buffer. NMR titrations were carried at a protein concentration of 0.2 mM. The Npl3 RRM–RNA complexes used for structure calculations were prepared in their corresponding NMR buffer at a protein:RNA stoichiometric ratio of 1:1 and a final concentration of 0.9 mM. The U2 RNA stem-loop (5’-GAGCGAAUCUCUUUGCCUUUUGGCUUAGAUC-3’) was transcribed in vitro and purified by HPLC on an anion exchange column at 85°C and in denaturing conditions (6 M urea). The fraction containing the RNA was precipitated using butanol and dissolved in water. The RNA was renaturated 30 sec at 95 °C followed by a slow cooling step to room temperature.ITC experiments were performed on a VP-ITC instrument , calibrated according to the manufacturer’s instructions. Protein and RNA samples were dialyzed against the NMR buffer. Concentrations of proteins and RNAs were determined using optical-density absorbance at 280 and 260 nm, respectively. 10 µM of each RNAs were titrated with 200–600 µM of protein by 40 injections of 6 µl every 5 min at 40 °C. Raw data were integrated, normalized for the molar concentration and analyzed using the Origin 7.0 software according to a single site model. A correction of the heats of dilution was only done for the complex formed with Npl3 RRM2 as the effect observed with control experiments was negligeable in the context of the RRM1 and RRM12. All measurements were performed in duplicate.http://www.cgl.ucsf.edu/home/sparky/) for data analysis.All the NMR spectra were recorded at 313 K using Bruker AVIII-500 MHz, 600 MHz, 700 MHz, AVIIIHD-600 MHz, 900 MHz equipped with a cryoprobe, and AVIII-750 MHz spectrometers. Topspin 3.6.2 (Bruker®) was used for data processing and Sparky 3.133 . The Pf1 phages were then added to the sample at a concentration of 10 mg/ml and the formation of a crystalline medium was monitored by measuring the splitting of the deuterium atoms from D61 was used for peak picking 3D NOESY (15 N- and 13 C-edited) spectra. Preliminary structures and a list of automatically assigned NOE distance constraints were generated through 7 cycles using CYANA noeassign61. Additionally, intra-protein hydrogen bond constraints were added based on hydrogen–deuterium exchange experiments on the amide protons. For these hydrogen bonds, the oxygen acceptors were identified based on preliminary structures calculated without hydrogen bond constraints. Intra- molecular RNA and RNA–protein intermolecular distance restraints were manually assigned and added to the calculation with 62 RDCs restraints in the case of Npl3 RRM1/2. Calculations with the RNA were done using CYANA 3.98.4 in which seven iterations were performed, and 500 independent preliminary structures were calculated at each iteration step. These 50 structures were refined with the SANDER module of AMBER 14.062 by simulated annealing in implicit water using the rna.ff12SB force field63. The 10 best structures based on energy and NOE violations were analyzed with PROCHECK67. Figures were generated with MOLMOL 2 K68 and Pymol 4.6.0. The Ramachandran plot of the Npl3 RRM1 in complex with RNA indicates that 86.9% of the residues are in the most favored regions, 12.9% in the additional allowed regions, 0.1% in the generously allowed regions and 0% in the disallowed regions. The Ramachandran plot of the Npl3 RRM1/2 in complex with RNA indicates that 71.2% of the residues are in the most favored regions, 25.4% in the additional allowed regions, 3.3% in the generously allowed regions and 0.1% in the disallowed regions.AtnosCandid 2.1 software39. Briefly, 1H–15N HSQC NMR titrations were done with 0.2 mM Npl3 RRM1 protein in the RRM1/2 buffer at 40 °C with successive addition of ssDNA . The chemical shift perturbations observed were calculated for the 1:1 ratio with the formula (Δδ = [(δHN)2 + (δN/6.51)2]1/2). The values calculated for non-overlapping peaks were summed.The method was adapted from Beuth et al.The BY4741 (MATa ura3 his3 leu2 met15 TRP1) was used as a parental yeast strain in which the promoter of Npl3 was replaced with an inducible gal promoter by homologs recombination. The strain was complemented with pRS315::Npl3±500kbp::HRV-3C::CterHTP plasmid. In this plasmid, the expression of Npl3 is driven by its endogenous promoter. A HRV-C3 protease cleavage site was inserted between amino acids S282 and N283 using PCR. A His-Trypsin-Protein A (HTP) tandem tag was placed at the C-terminus of the protein by PCR.69. Briefly, the recombinant yeast strains were grown in SD-leu medium to drive Npl3 expression only from the transformed plasmid. 2 L of yeast culture were harvested at an OD600 of ~2. The cells were resuspended in 1 v/w SD-Trp medium and UV-irradiated (1.6 J/cm2) in Petri dishes in a Stratalinker 1600 (Stratagene). Half the cells were not subjected to UV treatment and were kept as the UV minus control. Cells were pelleted and resuspended in 25 ml of lysis buffer  with addition of 1.3 mM PMSF, 1 mM DDT, complete protease inhibitor cocktail (Roche®)). The cells were lysed using 25 ml glass beads in Planetary mill for 20 min at 750 × g. 5 ml of lysis buffer was added, and the lysate was cleared by centrifugation . Cleared lysate was incubated with 300 of IgG bead suspension (1:1) for 2 h at 4 °C with rotation. Beads were collected and washed 3× with 10 ml wash buffer  followed by 3× with 10 ml lysis buffer with added 0.5 mM DDT. Beads were resuspended in 5 ml of lysis buffer and rotated with 40 μg of homemade TEV for 18 h at 4 °C. The eluates were concentrated to a volume of 500 μl in 30 kDa cutoff centricons (Millipore®). No RNase treatment was performed in the final experiments for library preparation. 0.4 g of Guanidine-HCl were dissolved in the eluate to yield a final concentration of 6 M. NaCl and imidazole were added to a final concentration of 300 and 10 mM, respectively. 100 μl of pre-equilibrated Ni-beads were added to the samples and incubated for 2 h at 4 °C. Beads were washed 3× with wash buffer , 300 mM NaCl, 0.1% NP-40, 40 mM imidazole, and 1 mM DDT) followed by 3× with PNK buffer (50 mM Tris-HCl (pH 7.8), 40 mM MgCl2, 0.1% NP-40, and 1 mM DDT). The beads were then incubated in 50 μl of PNK buffer (pH 6.5) in the presence of 10 units of PNK (NEB®) and 10 units of CIP (NEB®) and 20 units of SUPERase.In (Ambion®) for 30 min at 37 °C. Beads were washed 3× with wash buffer followed by 2× with PNK buffer (pH 7.8) and incubated with 50 pmoles of L3 adapter (rAppAGATCGGAAGAGCGGRRCAG/ddC/) in 50 μl of ligation mixture (1× PNK buffer (pH 7.8) supplemented with 12.5 units of T4 RNA ligase 1 (NEB®), 250 units of T4 RNA ligase 2 truncated K227Q (NEB®), 40 units of SUPERase.In (Ambion®) and 10% PEG 4000). The reaction is incubated for 18 h with mild shaking at 16 °C. Beads are then washed with 3× wash buffer followed by 3× PNK buffer. For the PreScission cleaved version, the beads are then incubated with 1× PNK buffer (pH 7.8) supplemented with 20 units of SUPERase.In (Ambion®) and 10 units of PreScission protease  for 18 h at 4 °C with mild shaking. The mixture is then supplemented with 10 units of PNK and 0.5 μl of γ32P-ATP and incubated for 1 h at 37 °C. 20 μl of 4× LDS is added to the beads, boiled for 10 min and resolved on a 4–12% Bis-Tris NuPage gel (Invitrogen®). Subsequent steps of RNA isolation and library preparation were done as described in Huppertz et al. 2014 Methods32. The negative control sample was generated following the same procedure but starting with WT yeast strain that does not express any tagged protein.The split-iCRAC was based on the original CRAC protocol described by Granneman et al., 2009 with some modificationsUV melting experiments were recorded on a CARY 100 Bio UV spectrophotometer (Varian) equipped with a temperature-controlled heating unit. The heating rate was 5 °C/min from 15 to 85 °C. Data from control experiments  were subtracted from the data presented in the Supplementary Fig. 70. At least 25 million reads were generated (up to 50 million) for each sample. After barcode removal and quality trimming, the reads were mapped against the S. cerevisiae reference genome S288C_R64-1-171 using STAR72. Approximately 30% of the reads of each sample were uniquely mapped to the genome. Reads mapping to the same genomic location and with the same Unique Molecular Identifier (UMI) were assumed to arise from PCR duplication and were therefore merged using UMI-tools73. To increase the reliability of identifying significant crosslinking sites, the deduplicated reads from the replicate samples were merged and subsequently used for peak calling using iCount74. A False Discovery Rate (FDR) cut-off of 0.05 was used to identify significant crosslinking sites. Identified crosslinking sites that were less than three nucleotides apart were merged into one cluster. Clusters that overlapped with ones identified in the negative control sample were not included in subsequent analysis steps. HOMER software34 was used for de novo motif discovery using the identified clusters flanked by five nucleotides on each side because of the expected short motif. Motif predictions were made for sizes ranging from 2 up to 10 nucleotides. The HOMER motifs were validated by plotting the density of the top motifs in the different samples and the negative control in a window of ±50 nucleotides around the crosslink cluster centers.Four replicates of the full-length protein and RRM1/2 domain, three replicates of the RGG/RS and one negative control sample were Illumina sequenced on a single lane of the NextSeq500 High Output (single-end 75 bp reads) according to manufacturer’s protocol. The reads corresponding to each sample were demultiplexed using the FLEXBAR tool67. Equal amounts of streaked yeast cells were resuspended in 90 μl H2O and subsequently diluted 10× in a series of 5 steps. 10 μl of the four lowest dilutions were spotted on SD plates. Plates were incubated up to one week at appropriate temperatures and pictures were taken daily using a Coolpix P310 digital camera (Nikon®).Genetically modified yeast strains were prepared by homologs recombination according to standard protocolsFurther information on research design is available in the Supplementary InformationReporting SummarySource Data


A fundamental step in the influenza A virus (IAV) replication cycle is the coordinated packaging of eight distinct genomic RNA segments (i.e. vRNAs) into a viral particle. Although this process is thought to be controlled by specific vRNA–vRNA interactions between the genome segments, few functional interactions have been validated. Recently, a large number of potentially functional vRNA–vRNA interactions have been detected in purified virions using the RNA interactome capture method SPLASH. However, their functional significance in coordinated genome packaging remains largely unclear. Here, we show by systematic mutational analysis that mutant A/SC35M (H7N7) viruses lacking several prominent SPLASH-identified vRNA–vRNA interactions involving the HA segment package the eight genome segments as efficiently as the wild-type virus. We therefore propose that the vRNA–vRNA interactions identified by SPLASH in IAV particles are not necessarily critical for the genome packaging process, leaving the underlying molecular mechanism elusive.  Zoonotic influenza A viruses (IAVs) from avian and mammalian species can cause severe disease in humans. Typically, such spillover events are rare and limited to a few infected individuals due to the poor adaptation of zoonotic IAVs to humans . OccasioAll eight viral RNAs (vRNAs) are organized into a central open reading frame (ORF) flanked by short non-coding regions (NCRs) required for segment replication and transcription . The vRNMany studies have postulated the existence of a vRNA–vRNA interaction network that controls the assembly of a supramolecular complex consisting of eight different vRNPs ,34,37–41et al. demonstrated the existence of complex and redundant vRNA–vRNA interaction networks in purified virions of several IAV strains  supplemented with 10% fetal calf serum  and 1% penicillin–streptomycin .MDCK-II cells  and HEK 293T cells  were grown at 37°C and 5% COTPS  TPCK-treated trypsin  and then plaque-purified. Mutations in the viral genome were confirmed by Sanger sequencing. Briefly, 200 μl virus supernatant was mixed with 600 μl Trizol reagent  and purified using the Direct-zol RNA Miniprep Kit . 5 μl of RNA was reverse-transcribed and amplified using segment-specific primers (Recombinant SC35M and chimeric PR8 viruses were generated using an eight-plasmid reverse-genetics system  Supplem. Subconf primers  and the Confluent MDCK-II cells in 6-well plates were washed with PBS and infected with wild-type or mutant SC35M virus at a multiplicity of infection (MOI) of 0.001 plaque-forming units (PFU) per cell in DMEM containing 0.2% BSA and 1% pen/strep. For chimeric PR8 viruses, the infection medium contained 1 μl per ml of TPCK-treated trypsin. Supernatants were collected at 24 h post infection (hpi) and PFU titers were determined by plaque assay on MDCK-II cells.2 HAU to PFU ratio of the mutant (mut) compared to the wild-type (WT) virus was calculated as follows:Confluent MDCK-II cells in 6-well plates were washed with PBS and infected with wild-type or mutant SC35M virus at an MOI of 0.001 PFU per cell in DMEM containing 0.2% BSA and 1% pen/strep. Supernatants were harvested at 24 or 36 hpi. PFU titers were determined by plaque assay on MDCK-II cells. Hemagglutination titers were determined by HA assay as described previously . BrieflyConfluent MDCK-II cells in 6-well plates were washed with PBS and infected with wild-type and mutant SC35M viruses at an MOI of 0.001 PFU per cell in DMEM containing 0.2% BSA and 1% pen/strep. Supernatants were collected at 24 or 36 hpi. For RNA isolation, 200 μl of virus supernatant was mixed with 600 μl Trizol and purified using the Direct-zol RNA Miniprep kit. 4 μl of RNA was reverse transcribed using random hexamer primers and the RevertAid First Strand cDNA Synthesis Kit  according to the manufacturer's protocol. 1:100 dilutions of the cDNA products and 400 nM of segment-specific primers  were use2, 1 mM DTT, 0.1% Tween-20). The beads were washed twice with cold RnlT buffer and incubated for 5 min at 4°C on a rotating wheel. The beads were resuspended in 100 μl ligation mix , 1 μl 10% Tween-20, 77.2 μl H2O) and shaken for 16 h at 16°C. The beads were washed twice with wash buffer and the RNA was eluted by resuspending the beads in 400 μl Trizol. The RNA was purified with the RNA Clean & Concentrator-5 Kit and reverse cross-linked with UV light at 254 nm for 5 min on ice. The RNA was concentrated with the RNA Clean & Concentrator-5 Kit and subjected to library preparation using the SMARTer smRNA-Seq Kit  according to manufacturer's protocol. RNA size selection was performed by binding to Ampure XP beads . Final libraries were pooled and sequenced on an Illumina NextSeq 550 instrument (1 × 150–160 cycles) using the NextSeq 500/550 High Output Kit v2.5 .SPLASH was performed as previously described ,45,46 wiVibrio cholera sialidase  in NTC buffer  at 37°C for 1.5 h. Released virions were cleared of debris by centrifugation  and concentrated by ultracentrifugation  through a 30% (w/v) sucrose cushion. To study the vRNA interactome in released virus particles, cell-attached virions were first released by sialidase treatment, followed by RNA–RNA cross-linking with 200 μM of psoralen-TEG-azide. To study the vRNA interactome in purified virions, RNA–RNA cross-linking with 200 μM of psoralen-TEG-azide was performed after sialidase treatment and ultracentrifugation. Purified virions were lysed in DNA/RNA Shield  and digested with 0.4 mg per ml of proteinase K for 60 min at room temperature. Viral RNA was purified using the RNA Clean & Concentrator-5 Kit and further processed as described in the ’SPLASH’ section with the following modifications: Briefly, the fragmented RNA was biotinylated overnight with 50 μM sDIBO-biotin alkyne  in PBS at room temperature. The biotinylated RNA was then enriched using Dynabeads MyOne Streptavidin C1 .Confluent MDCK-II cells in 15-cm dishes were washed with PBS and inoculated on ice with SC35M virus at an MOI of 3 PFU per cell in DMEM containing 0.2% BSA and 1% pen/strep. After 45 min on ice, the cells were incubated at 37°C for another 45 min. The viral supernatant was removed and the cells were washed five times with pre-warmed PBS. Infected cells were further cultured in the presence of 100 μM zanamivir  for 13 h at 37°C. To study the RNA interactome in newly formed cell-attached virus particles, infected cells were washed with warm NT buffer  and treated with 720 μM psoralen-TEG-azide  dissolved in warm NT buffer for 10 min at 37°C. Cells were cooled on ice for 5 min, followed by RNA–RNA cross-linking with UV light at 365 nm for 10 min. Virions were released from the cells by treatment with 25 milliunits per ml of https://github.com/gabriellovate/RNAswarm/releases/tag/v0.1.0). We first pre-processed the raw Illumina SPLASH data by trimming adapters and filtering for quality using fastp (https://osf.io/berj7/). To detect chimeric reads resulting from cross-linking of intra- and intersegmental RNA–RNA interactions, we mapped the pre-processed sequencing data to all eight segments of the corresponding viral reference genomes  into low- and high-frequency contacts, we defined cutoff points using a previously published analytical method . Cutoff https://github.com/desiro/Jakob2023_structures. MFE differences (ΔMFE) between wild-type and mutant interactions were calculated as follows: MFEmut − MFEWT. MFE and ΔMFE values are provided in To predict RNA structures and minimum free energy (MFE) values of the 39-by-39 nucleotide interaction regions (described in the previous section), we used RNAcofold from the Vienna RNA package  (versionSynonymous mutations aimed at disrupting SPLASH-identified vRNA–vRNA interactions were predicted using the SilentMutations (SIM) tool . ParametTo sequence viral stocks, RNA was extracted from cell culture supernatants using the Quick-RNA Viral Kit . Ribosomal RNA was depleted with RiboMinus Eukaryote Kit v2 Kit . Paired-end libraries were then prepared using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina NEB, E7760). A total of 8 pM library was sequenced on an Illumina MiSeq instrument . The de-multiplexed raw reads were subjected to a custom Galaxy pipeline. Briefly, the raw reads were pre-processed using fastp  using BW. A totalP values were corrected by the Bonferroni-Holm method using StatistikGuru , <0.01 (**), and < 0.001 (***) were considered significant. Pearson correlations between the top 30 interactions or the 15 HA segment interactions found in cell-attached, released, and ultracentrifuged virions were performed using GraphPad Prism 9.4.1 with the assumption that the log2-transformed (RPM + 1) values were normally distributed.Statistical analyses of PFU titers, relative HAU-to-PFU ratios, and relative vRNA levels were performed using GraphPad Prism 9.4.1, unless otherwise noted. An unpaired t-test was used to compare viral titers. Statistical analysis of relative HAU to PFU ratios and relative vRNA levels was performed using a one-sample t-test. Two-tailed stikGuru .Two-tailet al. . These nucleotide substitutions are critical for forming a vRNA–vRNA interaction with the Wyoming PB1 segment, which is detected by SPLASH and promotes co-packaging of both genome segments  and identified more than 1500 vRNA–vRNA interactions that varied in frequency over three orders of magnitude . Ranking4x. SPLASH and RNAswarm analysis revealed an overall similar interaction network compared to rWT  in the NA segment that caused an asparagine-to-serine exchange at position 196 (N196S) in the neuraminidase (NA) protein. rHA4x + 4x also contained a mutation (T614C) in the NP segment that resulted in a valine-to-alanine exchange at position 190 (V190A) in NP protein. We did not investigate these mutations further because the NA protein is not known to be involved in IAV genome packaging, and the residue 190 in NP is not exposed on the protein surface, unlike other NP protein residues known to be involved in genome packaging , is critical for coordinated genome packaging. We confirmed that viral replication . We confirmed the loss of the targeted HA segment interaction in rMmut by SPLASH and RNAswarm analysis  of the targeted interaction to the HA 5′-TPS from −28.5 to −9.5 kcal per mol. However, rMmut + PB1TPS+mut did not exhibit a more pronounced growth deficit than rPB1TPS , an experimental approach that allows RNA–RNA cross-linking in specific preparations of either cell-attached, released or ultracentrifuged viral particles Figure . CAPTIVETo compare vRNA–vRNA interactions between cell-attached, released and ultracentrifuged virions, we performed CAPTIVE coupled to SPLASH on wild-type SC35M virus. The resulting networks were very similar with the top 30 interactions Figure  and the The prevailing mechanistic model proposes that the eight IAV genome segments are selectively co-packaged into virions by a network of specific intersegmental RNA–RNA interactions. Recently, extensive and strain-specific vRNA–vRNA interaction networks have been detected in purified viral particles by SPLASH . HoweverSince SPLASH was previously used to identify a high-frequency vRNA–vRNA interaction mediating co-packaging of the PB1 and NA segments in H3N2 viruses, our results may seem surprising at first glance. However, it should be noted that the loci involved in this interaction were already suggested by previous mutational mappings , which m4x and rHA4x + 4x viruses, the remaining vRNA–vRNA interactions might be sufficient to maintain structural integrity of the network.Alternatively, demonstrating the actual importance of particular vRNA–vRNA interactions for coordinated genome packaging may be complicated by functionally redundant interactions in the network. If two mutually exclusive vRNA–vRNA interactions were able to mediate efficient HA segment packaging, it is possible that disruption of one would be compensated for by the other, resulting in no detectable packaging defect. Thus, despite tremendous interaction losses in our rHAAlthough the abundance of detected vRNA–vRNA interactions might indeed reflect to some degree a functional network redundancy, it could also point to systematic limitations in the SPLASH workflow that lead to false-positive interactions. RNA–RNA cross-linking by psoralen is a two-step reaction with a psoralen-RNA monoadduct as an intermediate . Like crFinally, it is possible that intersegmental RNA–RNA interactions are not fundamental to IAV genome packaging and are therefore rare and difficult to detect. Indeed, only two functional vRNA–vRNA interactions involved in genome packaging have been identified to date, and these are strain-specific ,40,43. Tde novo discovery of functional vRNA–vRNA interactions that coordinate IAV genome packaging. We propose that the vRNA–vRNA interaction networks identified by SPLASH are insufficient to explain coordinated vRNP packaging and call for expanded strategies to reveal the ‘true’ genome packaging machinery.In conclusion, our study questions the utility of the SPLASH workflow alone for the https://www.ncbi.nlm.nih.gov/sra, and can be accessed with the BioProject accession number PRJNA939935.The data underlying this article are available in the Sequence Read Archive (SRA) at gkad442_Supplemental_FilesClick here for additional data file.


These cell-permeable inhibitors were validated in cellulo to alter the regulation of alternative splicing events regulated by PTBP1. Our study demonstrates transient secondary structures of a protein can be mimicked by stapled peptides to inhibit allosteric mechanisms.The diverse role of the splicing factor PTBP1 in human cells has been widely studied and was found to be a driver for several diseases. PTBP1 binds RNA through its RNA-recognition motifs which lack obvious pockets for inhibition. A unique transient helix has been described to be part of its first RNA-recognition motif and to be important for RNA binding. In this study, we further confirmed the role of this helix and envisioned its dynamic nature as a unique opportunity to develop stapled peptide inhibitors of PTBP1. The peptides were found to be able to inhibit RNA binding  The dynamic role of a helix connecting the first two RNA-recognition motifs of PTBP1 was investigated for the design of an inhibitor. The developed stapled peptide interferes with RNA binding and was found to modulate an alternative splicing event regulated by PTBP1. One of such splicing factors is polypyrimidine tract-binding protein 1 (PTBP1) which regulates a distinct set of splicing events by binding to polypyrimidine rich sequences found in introns.11–13 It is part of the hnRNP family which typically have a repressive effect on splicing in the proximity of the sites they bind.11,14,15 Overexpression of PTBP1 is observed in various cancers, but it also plays a role in cardiovascular disease, viral infection, and neuronal development making it an attractive therapeutic target.16–20 PTBP1 binds RNA through four RNA-recognition motifs (RRMs), that together recognize the polypyrimidine sequence for high affinity binding.13,21–23 A canonical RRM is a small domain of approximately 90 amino acids and has a fold involving four β-strands and two α-helices in a β1α1β2β3α2β4 configuration.23,24 In the case of PTBP1 there are long flexible linkers in between RRM1 and 2 as well as RRM2 and 3 while RRM3 and 4 have a very short linker and are fixed in their position relative to one-another.22 A unique α3-helix is found in the linker between RRM1 and 2 , the extra C-terminal α-helix on RRM3 of La, the extra α-helices both N- and C-terminal of the oRRM4 of Prp24, or the extra α-helix on the N-terminus of the RRM of Saccharomyces cerevisiae Snu17p.29–32 Besides α-helices other structural elements are also observed such as an αββ-extension on the N-terminus of RRM1 on Syncrip, the 310-helix N-terminal of RRM2 in HuR, and the 310-helix on the C-terminus of RRM2 of the Drosophila melanogaster Sex-lethal protein.33–35 We hypothesized that exploiting these unique structural features might provide an opportunity towards the design of inhibitors of RRM containing proteins in spite of the lack of pockets and maybe even provide a method to achieve selectivity.Many RNA-binding proteins use one or more RRM domains for high affinity RNA-binding.Here, we first confirmed a role for the α3-helix in PTBP1–RNA-binding and exploited its dynamic nature for development of an inhibitor derived from this helix. By using a hydrocarbon peptide stapling approach, the helix could be mimicked to provide a peptide which can occupy its binding site and prevent PTBP1 from properly interacting with RNA. We demonstrate that such peptides bind to RRM1 and can indeed interfere with RNA-binding. After we confirmed them to be cell-permeable and have reasonable stability against cellular proteases we demonstrated they can modulate PTBP1 regulated RNA splicing events. We expect that this approach can become a general method for the design of RNA interaction inhibitors for RRMs and might also be applicable to other types of RNA-binding domains.25 The first set of proteins contained either the single RRM1, RRM1 lacking the α3-helix (RRM1Δα3) or RRM1–L151G  with a single PTBP1 binding site (UCUU) which can accommodate a single RRM (To confirm the role of the α3-helix described by the Allain group we performed fluorescence polarization (FP) experiments with various PTBP1 protein constructs and two RNA sequences.M1–L151G . The L15ngle RRM . The meangle RRM  and S1† 36 Since it has two poly(U) motifs, it is able to accommodate two RRMs and more accurately represents polypyrimidine tracts in mRNA. The affinities of all constructs improved for RNA-2 indicating an avidity effect. The overall trends stayed the same, where the affinity of RRM1 is better than RRM2 and is diminished when the helix is mutated or absent. For this RNA the affinity of RRM1–L151G was 2.4-fold lower than RRM1 which is identical to the reduction in affinity as observed by the Allain group. The double RRM constructs had a high affinity for RNA-2 in comparison to RNA-1 and the L151G mutation again reduced the affinity 2.5-fold. All used protein variants were analyzed by CD spectroscopy to verify folding and demonstrated identical spectral characteristics -pentenyl alanines (S5) were introduced in positions with three other amino acids in between. We picked three different amino acid pairs to replace with the S5 amino acids based on their orientation as observed in the NMR structures . As the staple is expected to stabilize the α-helical conformation we used circular dichroism (CD) spectroscopy to evaluate the helicity of the peptides. As expected, the most active peptide P-2 also demonstrated the highest helicity , as well as the less commonly used i, i + 4, i + 7 linkage in a so-called stitched peptide linking residues 145, 149 and 153 (P-6).44 Since we did not observe the formation of E/Z isomers during the ring closing metathesis reaction for these peptides we avoided reduction of the double bonds to simplify the synthesis and improve yields. The new peptides were tested for activity in the competition assay and P-5 and P-6 demonstrated good activities of 24.9 μM and 9.3 μM respectively with higher helicities than P-2. We selected P-6 as our candidate for further studies and synthesized the scrambled control variant P-6S. When tested in the competitive FP assay, P-6S was not able to inhibit the interaction between RRM12 and RNA-2 . Although an accurate KD could not be determined for RRM12 due to the absence of saturation, the curve is shifted slightly indicating the affinity is only somewhat elevated. To confirm binding we used P-6F in a microscale thermophoresis experiment  as well as a splicing factor from the SR-protein class (SRSF1).1 We evaluated P-6 in competitive fluorescence polarization assays using previously described RNAs recognized by these proteins.59 In both cases, no inhibition was observed up until 1 mM peptide concentrations  and -unbound state (PDB 1SJQ) with RMSD-values of 1.14–1.56 and 1.48–1.73 Å respectively, after aligning all 16 protein chains  in space group via rational design  and used them in the NanoClick assay.60 In this assay cells are transfected to express a NanoLuc–HaloTag fusion protein followed by treatment with a dibenzoazacyclooctyne reagent modified with a chloroalkane (DIBAC–CA) that covalently modifies the HaloTag protein. When an azide modified NanoBRET acceptor (NB618-Az) is added, it will undergo strain promoted azide–alkyne cycloaddition (SPAAC) with the DIBAC–CA placing the acceptor in the proximity of the NanoLuc protein leading to an observable BRET signal. When the cells are first treated with an azide containing peptide, it can occupy the DIBAC position and inhibit the BRET signal. The SPAAC reaction only happens if the peptide is able to reach the cytosol and the assay therefore provides a read-out of cell-permeability. The cells were incubated with the peptides for 20 hours and as controls, we used peptides described in the report on the development of the assay which are azido-octa-arginine as positive control and azido-ONEG as negative control.60,61 After background correction  and a >100-fold difference also in line with the original report.60 The results show that P-6-Az has very good cell permeability with an EC50 value of 35 nM significantly surpassing that of the positive control peptide  RNA is increased by the extra α3-helix and speculated that it needs to be formed to orient both RRMs properly for high affinity RNA-binding. Our findings are in line with recent structural studies from the Allain group indicating the formation of the transient helix after RNA-binding of RRM1 by integrative structural biology approaches.25,26 We hypothesized that occupying the binding site of the transient helix would be a suitable strategy for inhibiting the interaction between PTBP1 and RNA  or RRM2 (Raver1).63,64 The described inhibitors of PTBP1 are first-in-class and act through an unprecedented mode of action for RNA-binding inhibition. Although further studies on selectivity are necessary, the lack of activity on two alternative dual RRM proteins is promising. By demonstrating that intramolecular interactions can be disrupted to inhibit RNA binding we provide a novel way to target RNA-binding proteins that are otherwise devoid of well-defined pockets and could be considered “undruggable”.28In this study we confirmed a previously proposed role of a transient helix interacting with PTBP1 RRM1 during RNA-binding. and RNA . To this8BWF and can be obtained from https://www.rcsb.org/structure/8BWF.Crystallographic data for the PTBP1 RRM1Δα3:P-6 complex has been deposited at the Protein Data Bank under accession number PtH conceived the project. SS and KB performed biophysical experiments with PTBP1 constructs. GA, JYC, JO, and SP synthesized stapled peptides. SS performed direct binding FP, competitive FP, and MST experiments with PTBP1 constructs. GA performed competitive FP experiments with hnRNP A2/B1 and SRSF1 constructs. SS and RG performed crystallographic analysis of the RRM1Δα3:P-6 complex. SS and LP performed NanoClick experiments. GA performed cell lysate stability experiments. SS and KB performed PTBP1 knockdown and splicing experiments. PtH supervised the experiments and acquired funding for the project. PtH and SS performed data analysis and wrote the manuscript. All authors have given approval to the final version of the manuscript.There are no conflicts to declare.SC-014-D3SC00985H-s001


Three prime Repair Exonuclease 1) leads to accumulation of endogenous single-stranded DNA (ssDNA), double-stranded DNA (dsDNA) and DNA/RNA hybrids in the cytoplasm and triggers immune activation through the cGAS–STING pathway. Although inhibition of TREX1 could be a useful strategy for cancer immunotherapy, profiling cellular functions in terms of its potential substrates is a key step. Particularly important is the functionality of processing DNA/RNA hybrids and RNA substrates. The exonuclease activity measurements conducted here establish that TREX1 can digest both ssRNA and DNA/RNA hybrids but not dsRNA. The newly solved structures of TREX1–RNA product and TREX1–nucleotide complexes show that 2′-OH does not impose steric hindrance or specific interactions for the recognition of RNA. Through all-atom molecular dynamics simulations, we illustrate that the 2′-OH-mediated intra-chain hydrogen bonding in RNA would affect the binding with TREX1 and thereby reduce the exonuclease activity. This notion of higher conformational rigidity in RNA leading TREX1 to exhibit weaker catalytic cleavage is further validated by the binding affinity measurements with various synthetic DNA–RNA junctions. The results of this work thus provide new insights into the mechanism by which TREX1 processes RNA and DNA/RNA hybrids and contribute to the molecular-level understanding of the complex cellular functions of TREX1 as an exonuclease.In various autoimmune diseases, dysfunctional TREX1 (  Three prime repair exonuclease 1 (TREX1) is a crucial enzyme in mammalian cells, consisting of an N-terminal nuclease domain and a C-terminal transmembrane domain. TREX1 acts as a 3′-to-5′ exonuclease in the cytoplasm and the nucleus, and has multiple roles in cells . Under na)pyrene exposure. In the presence of such stress, TREX1 is overexpressed and translocated to the nucleus, where it participates in various DNA repair pathways by regulating poly(ADP-ribose) polymerase 1 (PARP-1)   or by di(PARP-1) ,12–15. T(PARP-1) . However(PARP-1) ,17,18, a(PARP-1) . Until nEscherichia coli homolog of TREX1, RNase T, plays important roles in DNA repair as well as in RNA maturation , the accumulation of HIV-1 DNA/RNA hybrids and IFN production were similarly observed  production and immune system activation . Dysfuncobserved , suggestA hybrid . These fIn this study, we investigate the activity of TREX1 against various types of nucleic acids, including DNA, RNA, DNA/RNA hybrids and specially synthesized DNA–RNA junctions. The binding affinity of TREX1 for these substrates is measured using quantitative methods. Furthermore, we determine the first structure of a TREX1–RNA product complex and uncover new structures of TREX1 in complexing ribonucleotides as well as deoxyribonucleotides. Together, the study reveals previously unavailable structural information regarding the effect of 2′-OH on exonuclease cleavage. Our results show that RNA and DNA/RNA hybrids are substrates of TREX1, although the activity of digestion is lower compared with that of processing ssDNA. A combination of the structural analysis with molecular dynamics (MD) simulation reveals that the 2′-OH in RNA modulates the conformational rigidity through intra-chain hydrogen bonding, leading TREX1 to exhibit distinctive catalytic properties compared with the processing of DNA. Our results also indicate that the rigidity of RNA through 2′-OH-mediated intra-chain hydrogen bonding may be a key property in the catalysis of other DEDDh exonucleases, such as RNase T, to distinguish DNA and RNA substrates, and could be useful in understanding the functionalities of other nucleic acid-binding proteins. Our establishment of TREX1 digesting RNA without sequence preference is in contrast to the behavior of RNase T. The cellular cooperation of TREX1 with HMGB-2 or RNase H2 in processing various substrates is also discussed. These findings provide new insights into the mechanism of TREX1 in processing RNA and DNA/RNA hybrids and lay the foundation for a better understanding of the complex cellular functions of TREX1 as an exonuclease.trex1 genes of Mus musculus (UniProt:Q91XB0) were inserted into the NdeI/XhoI or BamHI/XhoI site of the pET28a vector. The full-length and truncated mTREX1 were employed in biochemical assays, while the truncated (amino acids 1–242) and the N-terminal flexible region-removed mTREX1 (amino acids 11–242) were used for crystallization. The E. strain BL21-CodonPlus (DE3)-RIPL  transformed with the expression plasmids were incubated in Luria–Bertani (LB) medium with 50 μg/ml kanamycin, 35 μg/ml chloramphenicol and 25 μg/ml streptomycin. When the OD600 of the cell cultures reached ∼0.6–0.7, 1 mM isopropyl-β-d-thiogalactopyranoside (IPTG) was added to induce protein expression at 18°C for 20 h. The harvested cells were disrupted by a high-pressure cell homogenizer  in 50 mM Tris–HCl pH 8.0 containing 300 mM NaCl. The crude protein was centrifuged at 4°C, 13 000 rpm for 30 min to separate the supernatant. TREX1 was further purified from the supernatant sequentially by a HiTrap TALON crude affinity column (Cytiva), a HiTrap Heparin HP column (Cytiva) and a HiLoad 16/60 Superdex 200 prep grade column (Cytiva). The purified TREX1 in 50 mM Tris–HCl, pH 7.0, and 300 mM NaCl was concentrated to ∼28 mg/ml and stored at –20°C. Three recombinant mTREX1 proteins were purified by the same procedures. The TREX1 mutants (H195A and L24A) were generated by QuickChange site-directed mutagenesis kits (Stratagene) and purified by the same procedures as for wild-type mTREX1.Full-length (encoding amino acids 1–314) and truncated  2. The sequences of substrates are listed in The mTREX1 proteins were mixed with various 5′-FAM-labeled nucleic acids (0.5 μM) at 37°C for 30 min in 120 mM NaCl, 20 mM Tris pH 7.0 and 2 mM MgCl2. The reaction was allowed to proceed at room temperature for 10 min. For the samples of guanosine or its derivatives, the solution contained 10% Dimethyl sulfoxide (DMSO). All samples were excited at 270 nm. The emission spectrum was measured with 1 nm bandwidth resolution at 290 and 500 nm wavelengths by FluoroMax Plus (Horiba Instruments Inc.) with a 1 ml quartz cuvette. Three measurements were taken for each sample and averaged. The fluorescence intensity collected at 350 ± 3 nm was used for analysis. To verify that the aromatic rings of nucleotides would not interfere with ITF signals, a concentration of 4096 μM of nucleotides was tested under identical experimental conditions without protein (Kd) was derived from data by the one-site binding (hyperbola) model: Y = Bmax × X/(Kd + X), with X being the ligand concentration and Bmax being the maximum number of binding sites.A 30 μl aiquot of 40 μM protein was mixed into a 270 μl solution containing ligand, 120 mM NaCl and 20 mM Tris–HCl at pH 7.0 with or without 2 mM MgCl protein . The speHis-tagged truncated mTREX1 (amino acids 1–242 and 11–242) was concentrated at 24–36 mg/ml for crystallization. Protein and input DNA, RNA or nucleotide were mixed for 10 min before crystallization by the vapor diffusion method. The nucleic acid sequence and crystallization conditions are listed in et al. GROMACS 2023 Manual. 2023; https://doi.org/10.5281/zenodo.7588711.) was used to conduct MD simulations. Both TREX1–DNA and TREX1–RNA systems were solvated in a dodecahedron box of TIP3P water with at least 1.0 nm between any protein atom and the periodic boundary, and counter ions at 1.4 mM ionic strength. The cut-off of van der Waals (VDW) and short-range electrostatic interactions was 1.2 nm with a switching function effective at 1.0 nm, and the long-range electrostatics were calculated by Fast smooth Particle-Mesh Ewald with a grid spacing of 0.1 nm. During the all-atom MD simulations, all covalent bonds associated with a hydrogen atom were constrained at the equilibrium distance. After 4 ns of heating and equilibration, the production run was conducted at 310 K and 1.103 bar for 2 μs. The sampled configurations were saved every 10 ps for analysis. To determine the statistical uncertainties of hydrogen bonding strengths, the trajectory was equally divided into four independent blocks by using a longer duration between the snapshots.The all-atom models of TREX1 bound with ssDNA and ssRNA were constructed based on the X-ray structure of the TREX1–DNA complex (PDB code: 5YWS) with the positions of missing atoms patched using the CHARMM software . The lasr, was calculated as r = (IVVIHH)/(IVHIHV + 2 IVHIH), with I being the fluorescence signal intensity of FAM and subscripts H and V indicating the horizontal and vertical orientation of the excitation and emission polarizers, respectively. Each fluorescence signal of FAM was the average over 5 s with 494 nm excitation (1 nm slit) and 520 nm emission (5 nm slit). All three independent repeat data were analyzed using the GraphPad Prism 8 software. The fluorescence anisotropy was plotted as a function of the mTREX1 concentration. These binding curves were fitted into the software built-in non-linear regression fitting mode, Y = Bmax × X/(Kd + X) + Background × Kd/(Kd + X), to attain the dissociation constant Kd values. Here, Bmax is the maximum fluorescence anisotropy signal of the saturation binding curve and Background is the basic fluorescence anisotropy signal of free nucleic acids.The serial 2-fold dilutions of mTREX1 (amino acids 1–242) were separately mixed with FAM-labeled nucleic acids  into 300 μl aliquots. These mixtures containing 5 nM nucleic acid and different concentrations of mTREX1 were equilibrated at room temperature for 30 min in 120 mM NaCl, 20 mM Tris pH 7.0 and 20 mM EDTA. The fluorescence signals were measured by a fluorescence spectrometer, FluoroMax Plus (Horiba Instruments Inc.), equipped with a linear polarizer . The fluorescence anisotropy, E. coli were purified to homogeneity through chromatographic methods, as confirmed by sodium dodecylsulfate (SDS) electrophoresis  is expressed and purified for biochemical and structural analysis. The length and sequence of mTREX1 closely resemble the those of human TREX1 isoform b more than isoforms a and c , and thephoresis . The exophoresis , D.Truncated mTREX1 displays a higher activity in digesting ssRNA than cutting the RNA strand in DNA/RNA hybrids, and no activity is observed in processing dsRNA Figure , D. ThisIn targeting DNA/RNA hybrids, mTREX1 displays a higher activity in digesting the DNA strand than in degrading the RNA strand Figure . To bettThe most notable difference between the DNase and RNase activity of mTREX1 is that even at 2 μM mTREX1, i.e. 25 times the necessary concentration for digesting ssRNA, dsRNA remains intact Figure . On the in vitro experiments indicate that the RNase activity levels of these three mouse nucleases are within a similar range.To better assess the RNase activity of mTREX1 in comparison with other RNases, such as RNase H1 and RNase H2, mouse RNase H1 and H2 (mRNase H1 and H2) are expressed and purified into homogeneous states . The reso–Fc omit maps for the various nucleotides in these structures reported in To reveal the previously unavailable structural information on the mechanism by which the 2′-OH affects RNA processing, the crystal structures of mTREX1 in complexation with DNA or RNA products were determined. With the various RNA or DNA substrates digested by mTREX1 during crystallization, only a single nucleotide is left in the active site. Two structures of mTREX1 complexed with the DNA or RNA product are obtained at 2.0 Å resolution. The AMP and dGMP in our structures of the TREX1–RNA product complex and the TREX1–DNA product complex align well with the 3′-ended deoxyribonucleotides observed in the previously solved structures of TREX1–DNA substrate complexes [including ssDNA (PDB code: 2OA8)  and dsDNThe structure of the mTREX1–RNA product complex (AMP) showcases a traditional dimeric conformation of mTREX1, with two magnesium ions and AMP filling the active site. The base region of AMP is stacked by Leu24 and Ile84 Figure , B. To vTo understand how substrate binding depends on the base structure, the ribonucleotides in the mTREX1–RNA product (AMP) and mTREX1–ribonucleotide (CMP and UMP) structures as well as the deoxyribonucleotides in the mTREX1–DNA product (dGMP and dCMP) and mTREX1–deoxyribonucleotide (dAMP) structures were superposed. Our analysis reveals that AMP, CMP and UMP all align well, with the scissile phosphate and ribose in identical positions Figure . SimilarPrevious studies showed that TREX1 and its homolog TREX2 function as non-processive exonucleases by excising one nucleotide at a time from the 3′ end of a DNA substrate . WithoutKd) of mTREX1 with AMP, dAMP, CMP, dCMP, GMP and dGMP falls between 130 and 210 μM, with no specific difference between deoxyribonucleotides and ribonucleotides. Despite the two-metal ion catalysis  is employed to measure the binding affinity of mTREX1 for different nucleotides. The aromatic ring of nucleotides is shown not to interfere with the ITF signals . The resatalysis ,20, simid Figure . This fiKd of mTREX1 with various nucleosides and deoxynucleosides is measured using ITF. The results presented in Figure The structure of the mTREX1–uridine complex is determined for further elucidation of the role of 2′-OH, and the α-atom RMSD (root-mean-square difference) values over the trajectory, indicating robustness in the conformation. The 124–140 segment containing the helix of Asp130 and the substrate contacting Tyr129  for mTREX1 than does ssRNA. The Kd of ssDNA was measured to be 77.7 ± 6.0 nM, but the TREX1–ssRNA binding does not reach saturation, with an estimated Kd of 58 973.0 ± 11 302.0 nM. To further investigate the impact of 2′-OH of a single ribonucleotide on DNA, a 20 nt long DNA–RNA junction substrate is synthesized (ss19D1R) to have 19 nt long ssDNA and a 3′-end ribonucleotide. The binding affinity of ss19D1R for mTREX1 is reduced by ∼40% compared with the ssDNA 20 mer, indicating that the single 2′-OH at the 3′-ended ribonucleotide is a contributing factor to mTREX1 binding, although the impact is lower compared with that of ssRNA. However, when another 20 nt long DNA–RNA junction substrate is used, which consists of 17 mer ssDNA plus three continuous ribonucleotides at the 3′ end (ss17D3R), the Kd in the presence of more intra-chain hydrogen bonding decreases dramatically by ∼500-fold compared with the 20 mer ssDNA and is close to the value of binding ssRNA   Figure  that the) Figure . NotablyKd values of RNase T in binding with AMP and dAMP that do not have intra-chain hydrogen bonding, on the other hand, are similar, which is also consistent with the case of TREX1. This result suggests that intra-chain hydrogen bonding is also an important effector for the substrate binding of RNase T and potentially other exonucleases in the DEDDh family.To examine whether the aforementioned mechanism of TREX1 in distinguishing DNA and RNA substrates could be observed in other DEDDh exonucleases, RNase T was purified in a standard protocol , and theE. coli homolog RNase T, on the other hand, showed a different behavior of solely excluding cytosine (C), and the specific structural features of RNase T can be used to understand the molecular mechanism  over cytosine (C) and uracil (U), as indicated in previous studies . The E. echanism ,29. Howeechanism ,41,42, iechanism . Even atechanism . These fBased on previous structural analysis, RNase T prevents the removal of the 3′-end C by two features ,29, withSubstrate binding affinity and product release rate are critical factors for the different DNase and RNase activities of TREX1. As a non-processive exonuclease, TREX1 distinguishes DNA and RNA substrates primarily with distinct binding strengths and exhibits similar product release rates. Structural analysis and critical affinity measurements show that the extra 2′-OH does not impair the release rate Figures  for variAccording to the structural analysis conducted in this work, the 2′-OH at the 3′-end nucleotide of a substrate interacts with TREX1 through several hydrogen bonds and does not lead to steric hindrance Figure , indicatFor the clear inability of TREX1 to process dsRNA, the A-form structure of dsRNA  involvesWhile ssDNA and dsDNA are both TREX1 substrates, the double-stranded structure of dsRNA blocks the RNase activity even when the TREX1 concentration is raised to 25-fold the necessary concentration for digesting ssRNA or when HMGB-2 is added to enhance the activity for digesting double-stranded substrates Figure . Similar−/− MEFs, the viral-induced immune activation is turned on, suggesting that the HIV DNA/RNA hybrids are also non-productive HIV reverse transcripts and that TREX1 can play the role of processing the unwanted genetic material (TREX1 mutations were shown to lead to AGS disease and the accumulation of DNA/RNA hybrids in cells . On the material . In addimaterial ,13. ThesAnother interesting question is whether TREX1 and another AGS-related nuclease, RNase H2, work together in processing DNA/RNA hybrids. Mutations in TREX1 and RNase H2 were shown to lead to very similar autoimmune diseases, suggesting that they function in the same pathway and share common DNA/RNA hybrid substrates derived from endogenous retroelements . The exogkad910_Supplemental_FileClick here for additional data file.


Mycobacterium marinum in murine RAW264.7 macrophages. We found that, shortly after phagocytosis, DRAM1 localised in a punctate pattern to mycobacteria, which gradually progressed to full DRAM1 envelopment of the bacteria. Within the same time frame, DRAM1-positive mycobacteria colocalised with the LC3 marker for autophagosomes and LysoTracker and LAMP1 markers for (endo)lysosomes. Knockdown analysis revealed that DRAM1 is required for the recruitment of LC3 and for the acidification of mycobacteria-containing vesicles. A reduction in the presence of LAMP1 further suggested reduced fusion of lysosomes with mycobacteria-containing vesicles. Finally, we show that DRAM1 knockdown impairs the ability of macrophages to defend against mycobacterial infection. Together, these results support that DRAM1 promotes the trafficking of mycobacteria through the degradative (auto)phagolysosomal pathway. Considering its prominent effect on host resistance to intracellular infection, DRAM1 is a promising target for therapeutic modulation of the microbicidal capacity of macrophages.Damage-Regulated Autophagy Modulator 1 (DRAM1) is an infection-inducible membrane protein, whose function in the immune response is incompletely understood. Based on previous results in a zebrafish infection model, we have proposed that DRAM1 is a host resistance factor against intracellular mycobacterial infection. To gain insight into the cellular processes underlying DRAM1-mediated host defence, here we studied the interaction of DRAM1 with  Innate immune cells, including macrophages, are the gatekeepers of the immune system; they ingest microbes into internal compartments called phagosomes, they mount a range of cell-autonomous defence responses, and they alert other components of the immune system. A key cell-autonomous defence response is the phagolysosomal pathway, which delivers microbes through a phagosome maturation process to lysosomes. Upon lysosomal fusion, microbes are exposed to an acidic environment, antimicrobial peptides, and degradative enzymes . HoweverMycobacterium comprises several human pathogens that can subvert both the phagolysosomal and autolysosomal pathways, in order to facilitate their intracellular survival in macrophages [Mycobacterium tuberculosis (Mtb), which causes 10 million cases of tuberculosis (TB) and close to 1.5 million deaths every year [Mtb to a large collection of nontuberculous mycobacteria (NTM). For example, Mycobacterium avium lung infections are associated with poor clinical outcomes, and are notably on the rise [Mycobacterium marinum (Mm), known for outbreaks of a TB-like infection in fish in aquacultures, as well as for skin infections in humans [Mm is closely related to Mtb, sharing 3000 orthologous proteins with an average amino acid identity of 85% [Mm and Mtb, the bacteria require the ESX-1 system to evade phagolysosomal degradation and invade the cytosol [Mm or Mtb are targeted by xenophagy [Mtb has been shown to inhibit the autophagy-related LAP pathway [The genus rophages ,9,10,11.ery year . Howeverthe rise ,14. Anotn humans . Mm is cy of 85% . This siy of 85% . In both cytosol ). As a cenophagy ,20,21. Henophagy . Likewis pathway .Mm and Mtb infection [Mm infection, we showed that knockdown or mutation of the zebrafish ortholog of DRAM1 causes a hyper-susceptibility to infection, while its overexpression increases host resistance against Mm [Mm with LC3 and increases the lysosomal acidification of Mm-containing compartments [DRAM1, standing for damage-regulated autophagy modulator 1, is the founding member of a family of five stress-inducible autophagy regulators ,25. DRAMnfection ,24. In anfection ,27,28,29nfection . Using aainst Mm ,30. We aartments ,30. HoweMtb autophagy studies [Mm infection of this cell line leads to rapid permeabilisation of phagosomes and subsequent ubiquitination of bacteria, marking them as targets for xenophagy [Mm over the course of infection, and study this in relation to LC3, LysoTracker and LAMP1 patterns, as markers for autophagosomes and (endo)lysosomes. In addition, we generated DRAM1 knockdown macrophage cell lines to show that DRAM1 knockdown reduces the trafficking of LC3 to Mm, as well as reduces the acidification of Mm-containing vesicles. Furthermore, upon DRAM1 knockdown, the Mm infection rate increased. These results support the central role of DRAM1 in host resistance to intracellular infection, by promoting the trafficking of mycobacteria in the (auto)phagolysosomal pathway.To study DRAM1 localisation and function during mycobacterial infection in a relevant mammalian cell type, we used the mouse RAW264.7 macrophage cell line, which has been frequently employed for  studies ,32,33. Menophagy . Here, w2 atmosphere. The day before Mm infection, RAW 264.7 cells were seeded on sterile coverslips inserted in 12-well plates (2.5 × 105 cells/well for the 0–150 mpi Mm infection experiments or 4 × 105 cells/well for the Mm infection rate experiment) and incubated overnight at 37 °C with 5% CO2.The RAW 264.7 macrophage cell line was maintained in Dulbecco’s Modified Eagle’s Medium (DMEM) with high glucose , with 10% fetal calf serum (FCS)  at 37 °C in a 5% COMm M-strain, fluorescently labelled with mWasabi [Mm was washed twice with PBS, and optical density (OD) was measured at 600 nm. An OD 600 nm value of 1 is equal to 108Mm/mL [Mm, while DRAM1 knockdown and scramble control cell lines were used for the functional analysis of DRAM1. Cells were then infected with a multiplicity of infection (MOI) of 10, immediately centrifuged at 500× g for 10 min to synchronise infection, as described in [2. After 30 min, cells were washed twice with PBS to remove extracellular Mm and then incubated with LysoTracker-enriched medium for up to 150 min at 32 °C to obtain samples for immunofluorescence at 30 min intervals. At each 30 min interval, cells were fixed with Pierce™ 4% formaldehyde (PFA)  for 20 min at room temperature (RT). To analyse infection rates, cells were infected at a MOI of 10 without centrifugation and incubated at 32 °C. After 1 h, cells were either fixed with PFA or washed with PBS twice, in order to remove extracellular bacteria, and were then incubated with fresh medium for 6 h.The day before cell infection,  mWasabi , was cul08Mm/mL . Wild-tyribed in , and incMm  in PBS for 15 min, before blocking with 1% bovine serum albumin (BSA)  in PBS for 1 h at RT. Next, cells were incubated with the appropriate primary antibody, specifically DRAM1 (1:500) , LC3 (1:500) , or LAMP1 (1:1000)  for 1 h at RT. All primary antibodies were tested for a lack of cross-reaction with in vitro-cultured Mm . For sinAcidic vesicles were visualised by incubating RAW 264.7 cells in medium that was enriched with LysoTracker™ Red DND-99 (1:2500)  for at least 1 h prior to fixation at 37 °C . For non6 RAW 264.7 cells were seeded per T25 flask in DMEM-high glucose with 10% FCS and incubated overnight at 37 °C with 5% CO2. Then, 24 h later, cells were transduced at an MOI of 4 or 8, supplemented with 8 µg/mL polybrene , and incubated at 37 °C with 5% CO2. The medium was refreshed 24 h after transduction. After 48 h of transduction, 3 µg/mL puromycin  was added. Every 2–3 days, the medium was replaced until cells were 80–90% confluent. To isolate single clones with successful DRAM1 knockdown, cells from each condition were diluted in DMEM-high glucose with 10% FCS and 3 µg/mL puromycin to achieve 1 cell/well in a 96 well plate. The following day, wells containing 1 cell were marked. Once marked wells reached 80–90% confluency, cells were transferred to 12-well plates and subsequently to T25 flasks. Antibiotic pressure was removed from the medium to confirm the stability of DRAM1 shRNA integration into cells.To knockdown DRAM1, three short hairpin RNAs (shRNAs) against DRAM1 (NM_027878) from the Mission library (Sigma-Aldrich) were used, with scrambled shRNA as a control. pLKO.1-puro shRNA constructs were transduced into RAW 264.7 cells. The day before transduction, 1 × 106 cells were dissolved in TRIzol  and then chloroform . After centrifuging at 12,000× g for 15 min at 4 °C, the aqueous phase containing the RNA was transferred to a new tube. One volume of 70% ethanol was added and then transferred to a column from the RNeasy mini kit . RNA isolation was performed according to the manufacturer’s protocol, which included on-column DNAse digestion. A total of 500 ng of each RNA sample, measured with the Nanodrop (Thermofisher), was converted to cDNA with the C1000 Touch Thermal Cycler, using the iScript cDNA Synthesis Kit according to the manufacturer’s protocol , with the following modifications: 1 µL iScript Reverse Transcriptase was modified to 0.5 µL. Samples were then subjected to quantitative PCR (qPCR) using the CFX96 Real-Time System  with the iTaq™ Universal SYBR® Green Supermix . The program was set up as follows: initial denaturation at 95 °C for 3 min, then 40 cycles of 95 °C for 15 s (denaturation), and 60 °C for 30 s . A melting curve was included to test for PCR product purity: 55–95 °C in 0.5 °C increments. Dram1 primers (Sigma-Aldrich) used are as follows: forward: 5′-CCAGCTTCTTGGTCCGACG-3′; reverse: ‘5-GGGAGAAAGGGGTTGACGTG-3’. Gapdh was used as the housekeeping gene: forward: 5′- ATGGTGAAGGTCGGTGTGAA-3′; reverse: ‘5-CTGGAACATGTAGACCATGT-3’.Cell pellets containing 1 × 10g/min. Western blotting was performed using 15% polyacrylamide gel for LC3 and 10% for polyacrylamide gels for DRAM1 and LAMP1, followed by protein transfer to commercial PVDF membranes . Membranes were blocked with 3% BSA in 1× Tris-buffered saline (TBS) solution, with 0.1% Tween-20 (TBST), before incubating with primary and secondary antibodies: polyclonal anti-rabbit DRAM1 (1:1000) , GAPDH (1:1000)(D16H11), LC3 (1:1000) , and LAMP1 (1:1000) , as well as anti-rabbit IgG, and HRP-linked antibody (1:1000) . Digital images were acquired using the Bio-Rad Universal Hood II imaging system (720BR/01565 UAS). Band intensities were quantified with ImageJ, and values were normalised to GAPDH as a loading control.Cells were harvested, lysed in RIPA buffer  containing a protein inhibitor cocktail , and centrifuged at 4 °C for 10 min at 12,000× Mm colocalisation involved the characterisation into four categories , based on visual stack-by-stack inspection of the confocal Z-stack images. ‘None’: no colocalisation between DRAM1 and Mm. ‘Membrane’: DRAM1 staining surrounds Mm in a ring. ‘Punctate’: DRAM1 colocalises with Mm, but not along Mm’s entire length. ‘Luminal’: DRAM1 completely colocalises with Mm inside the lumen of a Mm-containing vesicle. The same definitions were used to quantify LC3–Mm and LAMP1–Mm colocalisations, where we note that the membrane pattern was not observed for LC3–Mm. Mm clusters fully colocalising with LysoTracker were also quantified. For quantification we imaged different regions of interest (ROIs) of the cells that were grown on coverslips in well plates, as described by Green et al. [RAW 264.7 cells stained by immunofluorescence and/or LysoTracker dye were imaged with a TCS SP8 confocal microscope (Leica) using a 63× oil immersion objective (NA: 1.40). Image processing and the analysis of fluorescent intensity and particles were performed using ImageJ software. Quantification of DRAM1–n et al. . ROIs weMm-infected cells were serially diluted with 5 steps in 7H9 broth, and 10 µL droplets were spotted onto Middlebrook 7H10 agar plates. The plates were incubated at 32 °C until single colonies were clearly seen, and bacterial colonies were quantified.At 7 h post infection, cells were lysed in water containing 0.05% SDS for 10 min. Lysates of At 7 h post infection, SYTOX™ Green Nucleic Acid Stain  was used at a final concentration of 5 μM for 10 min, in order to quantify cell death in different cell lines. Cells were then washed 3 × 5 min before fixation.In colocalisation studies, the mean probability of colocalisation per experimental condition was estimated, using a generalised linear regression model from the glmmTMB package in R . A beta-Mm infection in RAW264.7 macrophages, we performed immunofluorescence staining. We first determined the localisation pattern of DRAM1 in non-infected conditions. We observed that DRAM1 concentrates at certain areas in the vicinity of the plasma membrane. In these highly concentrated regions, DRAM1-positive circular structures of various sizes were occasionally observed  was always LysoTracker-negative  counts from DRAM1 knockdown cells were higher than in the control group phagolysosomal pathway [Mm first resides in a DRAM1-negative non-acidic phagosome, possibly recruiting LC3 through LAP. Subsequently DRAM1 may be recruited to the phagosomal membrane. Lysosomes containing DRAM1 within the membrane may then fuse with the Mm-containing vesicle, leading to its acidification. Alternatively, Mm escapes from the phagosome into the cytoplasm and is subsequently trapped in an autophagosome. This scenario is supported by the observation that Mm in RAW264.7 macrophages is ubiquitinated, making it a substrate for ubiquitin receptor-mediated xenophagy. The continued recruitment of DRAM1 to Mm-containing vesicles, of either a phagosomal or autophagosomal nature, would result in an increase in partial DRAM1–mycobacteria colocalisation. Subsequently, we hypothesise that DRAM1 becomes luminal following the fusion of phagosomes or autophagosomes with lysosomes, resulting in full DRAM1–mycobacteria colocalisation in the acidic and degradative environment of autolysosomes and endolysosomes. Another potential explanation for the full colocalisation pattern is that it is derived from the invagination of the membrane enclosing Mm, resulting in the formation of multi-vesicular bodies (MVBs) that contain intraluminal vesicles with DRAM1 in the membrane. This would imply that lysosomes do not fuse until after complete DRAM1–mycobacteria colocalisation, as MVBs are formed at a late stage of vesicle maturation, before lysosome fusion [In the present work we focused on the role of DRAM1 in intracellular host defence. During  pathway ,30. Basee fusion .Mm-containing vesicles, suggesting that DRAM1 mediates autophagic targeting and acidic vesicle trafficking to Mm. This reflects results seen in zebrafish, where DRAM1 knockdown or mutations resulted in reduced GFP–LC3-Mm colocalisation and reduced LysoTracker–Mm colocalisation [Mm-containing compartments showing partial or no colocalisation with the remaining DRAM1 protein in the knockdown lines. In contrast, despite DRAM1 knockdown, Mm-containing vesicles that showed full colocalisation with DRAM1 remained acidic. This suggests that DRAM1 affects the trafficking of acidic vesicles to Mm-containing vesicles, primarily at the early stages of vesicle maturation. In agreement, the effect of DRAM1 knockdown on LysoTracker–Mm colocalisation was larger than the effect on LAMP1–Mm colocalisation, suggesting that DRAM1 knockdown affects not only the fusion of lysosomes with Mm-containing vesicles, but also the acidification of these vesicles, due to fusion with late endosomes at an earlier step in the maturation process. The proposed role of DRAM1 in promoting fusion between acidic vesicles and Mm-containing compartments is supported by results observed in zebrafish overexpressing DRAM1, where large vesicles containing membrane remnants were observed in transmission electron micrographs, suggesting that DRAM1 mediates multiple vesicle fusion events [Mm infection burden in RAW 264.7 macrophages.Previously, DRAM1 was shown to regulate autophagic flux through the lysosomal v-ATPase in human A549 cells, under conditions of mitochondrial stress . To detelisation ,30. Exten events . The stiMm in RAW 264.7 macrophages, support the role of DRAM1 as a host resistance factor that is conserved across zebrafish and mammals. Therefore, DRAM1 represents a putative target for host-directed anti-mycobacterial therapy that could help overcome current challenges posed by anti-microbial resistance. Therapeutic strategies targeting DRAM1 might be more broadly applicable against other intracellular pathogens, considering our recent results that DRAM1 also protects against infections with Salmonella enterica serovar Typhimurium and Aspergillus fumigatus [The results of this study, which show the requirement of DRAM1 for (auto)phagolysosomal delivery of umigatus ,48. Furt


Understanding how the RNA-binding domains of a protein regulator are used to recognize its RNA targets is a key problem in RNA biology, but RNA-binding domains with very low affinity do not perform well in the methods currently available to characterize protein-RNA interactions. Here, we propose to use conservative mutations that enhance the affinity of RNA-binding domains to overcome this limitation. As a proof of principle, we have designed and validated an affinity-enhanced K-homology (KH) domain mutant of the fragile X syndrome protein FMRP, a key regulator of neuronal development, and used this mutant to determine the domain’s sequence preference and to explain FMRP recognition of specific RNA motifs in the cell. Our results validate our concept and our nuclear magnetic resonance (NMR)-based workflow. While effective mutant design requires an understanding of the underlying principles of RNA recognition by the relevant domain type, we expect the method will be used effectively in many RNA-binding domains.  •Specificity and function of low-affinity RNA-binding domains are often unclear•We propose a strategy to increase domain affinity but maintain specificity•We use it to reveal how a domain of the FRX protein recognizes RNA targets RNA-binding domains represent the building blocks of RNA regulation, and their sophisticated nucleic acid recognition builds into the selectivity and functional variation of complex post-transcriptional regulatory networks. The RNA recognition properties and the function of some domains are well characterized. However, as current methods to dissect RNA recognition require the interaction to be relatively stable, the low affinity of many other domains prevents the characterization of their RNA recognition properties and the understanding of the role they play in protein function. To overcome this limitation, we propose to use protein design to enhance a domain’s affinity of RNA binding without altering nucleobase recognition and specificity. We use these affinity-enhanced domains to reveal their RNA sequence specificity and their role in target selection in the cell and protein function. Low-affinity domains are common in RNA-binding proteins, but their sequence specificity and function are poorly understood. Chaves-Arquero et al. propose enhancing the domains’ affinity to better define their specificity. An NMR-based strategy is applied to the FXR protein, revealing a role for a low-affinity RNA-binding domain in RNA target selectivity. Here, we use the KH1 domain of the fragile X syndrome protein FMRP as a paradigm for a class of low-affinity RNA-binding domains whose contribution to RNA recognition is unclear. We have designed a structure-based, localized mutation that increases KH1 RNA-binding affinity without affecting its RNA-binding mode. Then, we have shown how this mutation can be used to define the domain’s sequence specificity and to rationalize FMRP strategy A. It alsin vitro. These studies have linked FMRP function to RNA regulation at the molecular level, but our understanding of the process of RNA target selection is incomplete. FMRP contains multiple RNA-binding domains and recognizes both structured motifs, such as G-quartets, and single-stranded (ss) RNA elements.,,in vitro.in vitro.FMRP is a multi-domain RNA-binding protein essential for the correct development and function of the brain. FMRP misexpression, or a dysfunctional mutant protein, is the causal factor of fragile X syndrome, the most common inherited form of cognitive impairment.,Notably, FMRP KH1 has been reported to bind ssRNA with low affinity.15N-correlation NMR experiments  mutanteriments D and S2.eriments D.D values in the sub-millimolar range. Briefly, NMR spectra are recorded on the domain free and when bound to quasi-degenerate RNA oligos with all but one randomized position. Comparison of the changes in the protein spectra when in complex with different oligos with either A, C, G, or U in a given sequence position reports on the nucleobase preference of the domain in that position. In practice, changes are measured as the chemical shift perturbations (CSPs) of backbone amide peaks that are in fast exchange on a chemical shift timescale. Normalization and averaging are then performed to obtain the final SIA scoresThen, we examined whether the mutation could help characterize the specificity of the domain using SIA as a step in our NMR workflow. SIA is an NMR-based method that allows defining the nucleobase preference of a domain in each of the positions of the bound RNA15N-correlation NMR spectra against the protein/RNA ratio , which was first identified in a PAR-CLIP (PhotoActivatable Ribonucleoside-enhanced CrossLinking and ImmunoPrecipitation) analysisOur understanding of RNA recognition by common RNA-binding domains has increased thanks to high-resolution structures of protein-RNA complexes and to bioinformatic studies, and we now have detailed information on how domains such as KH, RRM, and many other common RNA-binding domains interact with the cognate RNAs. This information helps the design of AE mutants, extending the concept and NMR workflow we discuss here to RNA-binding domains from a range of RNA-binding proteins, and we expect that this will help us understand how these domains contribute to target recognition in the cell. For example, KH domains have a common RNA-binding mode, and in the free protein, the GxxG loop is exposed in solution.in vivo.In order to design AE mutation(s), an understanding of the RNA-binding mode of each domain is required, and it is possible that a number of mutants need to be tested, depending on the domain to be examined. For KH domains, we expect that it will be generally possible to use the GxxG to GKKG mutation in the investigation as (1) KH domains have a common RNA-binding mode and (2) the GxxG loop is surface exposed and can be mutated without affecting the domain’s fold or stability. For other domains, where one or more structures in complex with RNA are available, we expect it will be possible to identify amino acids that are positioned in proximity of nucleic acid backbone phosphates that could be mutated to positively charged residues in homologs to optimize affinity without affecting nucleobase recognition. We use the well-studied RMM domain to exemplify this design. However, if no structural information is available, for example for newly identified RNA-binding domains, then designing AE mutants is likely to be quite difficult. It is also important to point out that while the mutants are valuable tools to understand target recognition and protein function, mutant design and testing is time demanding. Therefore, rather than high throughput, the concept we propose is to focus the experimental workflow on a specific protein of interest, which can be then studied 15N labeling of the protein domain. While straightforward with proteins expressed recombinantly in Escherichia coli, this is more complex in other expression systems. Additionally, there is a requirement for the protein to be stable at micromolar concentration for a period of days. This is typically not a problem for proteins that have been previously studied with biochemical or biophysical methods, and a range of buffer and experimental parameters can be used to help with this. Finally, as NMR is a size-sensitive method, experiments will typically provide better data for smaller domains or proteins. While in a majority of cases RNA-binding domains are typically of a size amenable to NMR studies (8–15 kDa), in isolation or as di- or even tri-domains, size should be considered.From a more technical stance, the SIA experiments require a.ramos@ucl.ac.uk).Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Andres Ramos  cells were used as the source organism to obtain the recombinant proteins studied in this work. The cells were stored at −80°C, and freshly transformed with the plasmids containing FMRP KH12, WT and RNA-AE coding sequences. Cell cultures and protein induction are detailed in the method details section.Commercial E. coli expression, was purchased from Eurofins. Primers were designed using the Crystallization Construct Designer on-line tool (https://ccd.rhpc.nki.nl)A gene encoding FMRP with the Δ331-396 deletion,E. coli cells, which were used to inoculate 1000 mL of M9 minimal media containing 15NH4 and 13C-glucose as the only nitrogen and carbon sources respectively, as previously described.d-1-thiogalactopyranoside at a final concentration of 0.5 mM. Cells were grown for a further 4 h at 37°C after induction, harvested by centrifugation, and cell pellets stored at −80°C.The plasmid containing the FMRP KH12, WT and RNA-AE coding sequences was transformed in BL21(DE3) Frozen cells were resuspended in equilibration buffer  and 200 μg/mL lysozyme (Sigma)), sonicated on ice and centrifuged at 17000 rpm for 1 h at 4°C. The recombinant protein was purified by immobilized metal ion affinity chromatography (IMAC), using Protino Ni-NTA Agarose resin (Macherey-Nagel) in a gravity-driven column. The resin was then washed with 10 CV of wash buffer  and eluted with 5 CV of elution buffer . HRV 3C protease was used to cleave the 6xHis-tag by incubation overnight at 4°C. The sample was dialyzed in equilibration buffer and the cleavage tag was separated from the protein by reverse IMAC. The protein-containing fractions were concentrated and purified further by size exclusion chromatography using a Hi-Load 16/600 Superdex 75 pg column . Peak fractions were concentrated and assessed for their purity (>95%) using SDS-PAGE.The RNA oligonucleotides  were purchased from Horizon Discovery and deprotected as advised by the manufacturer. Before use, the samples were lyophilised and resolubilized in 10 mM phosphate pH 6.9, 40 mM NaCl and 0.5 mM TCEP. RNA concentration was determined from the 260 nm absorbance of the sample.13C15N-labelled samples were prepared in a 90% H2O/10% D2O solvent ratio at a final concentration of 200 μM. NMR experiments were recorded at 25°C and 37°C on Bruker Avance and Varian Inova NMR spectrometers operating at 600, 700 and 800 MHz. 13C15N samples were used to acquire TROSY HNCA, 15N-NOESY-HSQC, HNCA, TROSY1H-15N SOFAST-HMQC spectra1H and δ15N are the chemical shift differences of the 1H and 15N dimensions respectively. For each of the four pools, CSP values for each peak were normalized with respect to the highest shift observed for that pool. For each pool, the average normalized values across the subset of peaks are taken to provide a comparative score of binding preference, which is defined as the SIA score.NMR-SIA was performed on FMRP KH1WT/KH2DD (WT) and FMRP KH1KK/KH2KK (RNA-AE) mutants. 50 μM stock protein was prepared in 40 mM NaCl, 10 mM phosphate pH 6.5, 0.5 TCEP, 0.002% sodium azide and RNasin Plus (Promega). RNA pools were added where required at a protein to RNA ratio of 1–4. Samples were transferred to 3 mm SampleJet NMR tubes (Sigma-Aldrich) and loaded into a Bruker Avance NMR spectrometer at 700 MHz using a Bruker Sample Jet loader. 15N-labelled protein samples in 10 mM phosphate pH 6.9, 40 mM NaCl, and 0.5 mM TCEP, and titrated with unlabelled RNA oligonucleotides  at protein-to-RNA molar ratios of 0, 0.5, 1, 2, 4, 6, 8, 10 and 12. Spectra were processed using Topspin 3.7 (Bruker) and a value for the 1H and 15N chemical shift changes was calculated for each residue by applying the equation:NMR titration experiments were performed using 50 μM of D values obtained were calculated using CcpNMR Analysis using the A(B + x-sqrt((B + x)ˆ2-4x) equation. The KD value calculated per NMR binding assays corresponds to the average of the KD’s individual residues.The KThermal unfolding of FMRP KH12, FMRP KH1/KH2 (K299D/N300D) and FMRP KH1(T236K/H237K)/KH2(K299D/N300D) was monitored by CD, as previously described.H. sapiens proteome were obtained in InterPro,Primary sequences of RRM and KH containing proteins from the whole Analysis explanation of the experiments can be found in the figure legends as well as in each subsection of the