Our results establish how peptides of limited length, homogeneity and charge density facilitate the compartmentalization of active ribozymes into non-gelating, magnesium-rich coacervates, a scenario that could be applicable to cellular precursors with peptide-dependent functional phenotypes.It has long been proposed that phase-separated compartments can provide a basis for the formation of cellular precursors in prebiotic environments. However, we know very little about the properties of coacervates formed from simple peptides, their compatibility with ribozymes or their functional significance. Here we assess the conditions under which functional ribozymes form coacervates with simple peptides. We find coacervation to be most robust when transitioning from long homopeptides to shorter, more pre-biologically plausible heteropeptides. We mechanistically show that these RNA–peptide coacervates display peptide-dependent material properties and cofactor concentrations. We find that the interspacing of cationic and neutral amino acids increases RNA mobility, and we use isothermal calorimetry to reveal sequence-dependent Mg Phase-separated compartments have long been proposed as precursors to cellular life. Now, it has been shown that RNA–peptide protocells are more robust when formed using shorter (rather than longer) peptides, and that peptide sequence determines the functional materials properties of these compartments. Plausible pathways leading to complex polypeptides2 and ribozymes capable of the catalysis of elementary reactions such as RNA copying3, autocatalytic or cross-catalytic ligation4 and recombination6 are increasingly well understood. Beyond its chemical fingerprint, however, life is characterized by cellular organization. Therefore, an intriguing question is how molecular life could have transitioned into compartmentalized precursors of cellular life. In line with the classic view of biological cells as membrane-bound compartments, fatty acid vesicles have long been proposed as early cellular systems compatible with RNA encapsulation and activity7. More recently, however, it has become increasingly clear that liquid–liquid phase separation allows the formation of cellular compartments. Consequently, distinct biochemical environments with unique and dynamic properties and cellular functions can also be generated without the requirement for membranes9. Nevertheless, it remains unclear whether or how phase separation could have supported the transition from a molecular to a cellular world.The emergence of life on Earth has long been studied as a question of molecular reactions generating the building blocks of life such as peptides, lipids and nucleic acids10. In particular, coacervate systems have the potential to achieve RNA compartmentalization via simple and widespread interaction of oppositely charged polyelectrolytes14. With the advent of phase separation in biology19, these systems have raised interesting possibilities for research into the origins of life24 and synthetic biology25. A number of studies have observed the formation of RNA-containing compartments from simple components26. Examples of complex coacervates include combining nucleic acids or nucleotides with positively charged polymers, such as spermine or spermidine13 and oligo- or polylysine27. Coacervates formed from long complementary RNA and polycationic peptides such as proline–arginine and proline–lysine repeats have been found to exhibit complex materials properties26. Here an apparently fluid peptide phase coexists with a static RNA gel, a phenomenon that has been described as the essentially decoupled dynamics of molecular components26. Furthermore, RNA biochemical reactions have been shown to proceed within liquid–liquid phase-separated compartments29, ribozymes in complex polyamine coacervates were found to allow RNA base pairing and template-directed polymerization22, and enhanced the activity of ribozyme cleavage reactions was found in artificial polydiallyldimethyl–ammonium/rA11 coacervates22. In a cellular context, condensates often include proteins and RNA30, as is the case for stress granules31, the nucleolus32 and germ granules33. Analysis of biological condensates suggests a molecular grammar based on protein sequence which could determine compartment function and properties34. In particular, reconstitution experiments with FUS protein revealed that different amino acids lead to different behaviour in RNA-free protein condensates. While arginine and tyrosine have been suggested to be important drivers of protein phase separation, the material properties of condensates are also determined by serine, glutamine and glycine residues34, the latter preventing ageing and solidification of protein droplets34. Finally, transitions in the material state of the cytoplasm and subcellular compartment have been suggested to control enzymatic activity, metabolic turnover and cell-cycle-dependent functionality37. For these versatile properties and potential functions of compartmentalization to extend origin-of-life scenarios, however, they would need to be compatible with peptides of plausible length and compositional purity, rather than highly evolved proteins or artificially long homopeptides.Complex coacervation has long been suggested as a plausible physicochemical process to explain pre-biological compartmentalization2+ (an important cofactor of ribozyme reactions) without the need for a membrane. Our results establish how simple peptides can modulate the activity of ribozymes in plausible and evolutionarily attractive protocellular compartments, and emphasize opportunities to understand how biochemistry is regulated by the physicochemical properties of condensates in modern cells.In this article we study how phase-separated compartments could have formed during the origin of life. We find that the robustness of coacervation increases when transitioning from longer to shorter homopeptides. Weakening the constraints of peptide sequence further enables tuning of physiochemical properties and melting of RNA gels. Furthermore, we show that ribozyme function is modulated in a sequence-dependent manner, with peptide charge density as the major determinant of enzymatic activity. Mechanistic analysis reveals that coacervates form a distinct chemical environment in which peptide sequence determines concentrations of Mg39. To analyse the potential role of RNA–peptide coacervates in origin-of-life scenarios, we assessed the effect of charge and length of peptides on their formation   Fig. , we foun9, K9 and (RGG)4 by electrophoretic mobility shift assays (EMSAs) using non-denaturing agarose gels  caused only a mildly reduced electrophoretic mobility of RNA towards the anode with clear co-migration behaviour of the peptide. At peptide concentrations marking the onset of turbidity (a.a./nt ratio ≥1), RNA was unable to enter the gel matrix, suggesting a complete neutralization of the polyphosphate backbone. RNA mobility was ultimately reversed at a.a./nt ratios ≥2. A very similar trend was observed for K9. Intriguingly, for (RGG)4 both peptide and RNA mobility remained unaffected over the whole range of a.a./nt ratios and charge-neutral RNA–peptide complexes remaining inside the gel wells were not observed at any stoichiometry. This finding strongly suggests that RNA and (RGG)4 interact only weakly and their interaction is efficiently disrupted under EMSA conditions (1× Tris/Borate/EDTA buffer (TBE), T = 22 °C).Next, we set out to better understand the mechanisms and sequence dependencies that govern RNA–peptide coacervate formation. To this end, we characterized complex formation of the R3C ligase system with the peptides Rels Fig. . In the To extend our characterization of coacervate formation beyond turbidity assays, we employed transmission electron microscopy (TEM). We were particularly interested in observing whether there were soluble precursor complexes or free RNA molecules that coexisted with coacervates at the onset of turbidity. Furthermore, we wanted to check if the loss of solution turbidity was accompanied by dissolution of the coacervates. The TEM micrographs strengthened our previous model /rA11 (ref. 22) systems that sequestered variants of the Hammerhead ribozyme. Here we wanted to test whether coacervates formed from simple peptides, RNA enzymes and their substrates at standard reaction concentrations can sustain enzymatic activity. To this end, we quantified fluorescently labelled RNA ligation products retrieved from coacervation assays at different a.a./nt ratios by gel electrophoresis. To quantify the amount of enzyme in the coacervates irrespective of their sizes, turbidity plots were complemented by sequestration measurements after separating spun-down coacervates and supernatant. All reactions contained 5 µM E, 6 µM S2 and 0.1 µM Cy5-S1  appeared to be correlated with a strong inhibition of the ligation reaction 4 peptide at up to 20-fold a.a./nt excess 43. Coacervates were prepared at excess peptide, which is readily achieved at an a.a./nt ratio of 10 for R9 and K9, and an a.a./nt ratio of 70 for (RGG)4. When labelling R9 with fluorescein isothiocyanate (FITC), we observed rapid recovery of the fluorescence signal on a time scale of minutes, yet there was almost no mobility of Cy5-labelled-product RNA (labelling density <1% in both cases) es) Fig. . In agre26. In our case, RNA gelation was generally observed starting from R18 down to R7. Deviating from previous descriptions26, we observed this decoupling of molecular dynamics to break down when moving away from long and highly charged peptides, towards shorter, charge-interspaced peptides. The first indication for this was observed for coacervates made from RNA and R5, where some FRAP recovery of the RNA phase was noticeable after minutes 4-based peptides n droplets did not maintain subdomains , despite their 58-nt length difference, as they are part of the complexes E–P or E–S2 . Our data show that the apparent diffusion coefficients for the two RNA strands (P and S2) are very similar for Kn and (RGG)n coacervates n coacervates and differences in ribozyme activity therefore cannot be explained by impaired RNA–RNA interactions.Our data bring up the interesting question of which factors beyond the mechanical properties of the RNA phase may determine differential ribozyme activity in lysine-rich and RGG-based coacervates. One possibility is that RNA base pairing is disrupted inside coacervates, which could explain the absence of ribozyme activity in the fluid K–S2 Fig. . However2+ both for faithfully maintaining secondary RNA structure and as an essential cofactor for catalysis. Therefore, a differential presence of Mg2+ in coacervates could explain different levels of ribozyme activity, especially when comparing K9 and (RGG)4 coacervates. To specifically test the effect of peptide choice on the presence of magnesium in our coacervates, we used two complementary techniques: inductively coupled plasma mass spectrometry (ICP-MS) for determination of magnesium in the coacervate phase 4 compartments 4 coacervates required drastically increased a.a./nt ratios of >70 for full Mg2+ release.Apart from molecular mobility and base pairing, ribozyme activity requires sufficient amounts of Mg2+ binding to the RNA is an exothermic process45 with a total heat release 2+, the total enthalpic difference ∆∆H should equal ∆HMg if Mg2+ is completely released from the RNA  and to RNA preincubated (∆HPep+Mg) with 5 mM MgCl2 . We observed that Mgal) Fig. . We reasRNA Fig. . In otheCl2 Fig. . In agre9 and K9 titration in the absence and presence of Mg2+, we found that the ∆∆H of peptide binding to the RNA had an enthalpic cost precisely equal to the heat release of Mg2+ binding to R9 and K9 . Furthermore, we observed a highly differential response for (RGG)4 binding to RNA with Mg2+ incubation. In particular, we observed a highly reduced heat release when the negatively charged RNA was already neutralized by Mg2+ counter-ions, in which case the ∆∆H even exceeded the penalty of Mg2+ replacement 4 to RNA in the presence of magnesium. This lasting presence of RNA-bound Mg2+ in (RGG)4-based coacervates probably explains the maintenance of ribozyme activity.When comparing the heat release upon R K9 Fig. . This inent Fig. . Over a 2+ is able to efficiently compete with (RGG)4 for RNA binding, thus effectively changing the equilibrium constant of the process. In general, the efficiency of such competition depends on the affinity of the peptides for the RNA. Hence, we predict that if the equilibrium of cationic ion binding to RNA is shifted from peptides to Mg2+ in a sequence-dependent manner, we should see differential effects of Mg2+ presence on the coacervation process, for example, when replacing R9/K9 with (RGG)4. We therefore proceeded to investigate the effect of 5 mM MgCl2 on the coacervation process to address the effect of Mg2+ on the formation of (RGG)4 coacervates.To understand this result, it is necessary to consider that Mg2. As expected from the ITC data, MgCl2 promotes coacervation with R9 and K9, seen as a left shift of the turbidity curves 4 peptide were required to form coacervates, seen as a right shift of the turbidity curve 7 4, although coacervation here requires high peptide levels due the RNA-shielding capacity of the Mg2+ ions.Interestingly, the width of the transition regime , an excess of cationic peptide competitively depletes Mg2+ from coacervates, which accounts for a loss of ribozyme activity.Our systematic analysis reveals that the phenomenologically determined regimes in turbidity plots correspond to three functionally distinct regimes in which ribozyme activity is linked to the physicochemical properties of coacervates Fig. . In the 2+ ions and that weaker interactions should lead to higher Mg2+ concentrations in the coacervate phase. We therefore reasoned that RNA–peptide affinity can be tuned by the use of different MgCl2 concentrations in the system. Thus, we hypothesized that, if our observations hold true, reducing the RNA peptide affinity in (RGG)5 coacervates by increasing MgCl2 concentration from 5 mM to 20 mM would lead to a recovery of enzymatic activity. As expected, under these conditions, RNA enzymatic activity was maintained even after close to total enzyme RNA sequestration in the coacervate phase 9, we observed both a 120-fold acceleration in droplet fusion times . Of particular interest for origin-of-life scenarios, we find that charge-interspaced heteropeptides, which are statistically and chemically more plausible, have the highest potential to maintain the activity of ribozymes compared with arginine and lysine homopeptides.46. Notably, we observed similar behaviour for charge-interspaced lysine peptides, stressing the universality of these findings. Thus, considering stability and plausibility arguments, we propose charge-interspaced peptides as an evolutionarily relevant motif for the transition from molecular to coacervate precursors of life.In the absence of a genetic code to determine peptide sequence, charge interspacing by glycine has two distinct implications for plausibility. (1) Moving away from artificial homopolymers towards heteropolymer boosts the combinatorial plausibility of a pre-biological scenario in which long homopolymers were likely to be scarce. As an example, the combinatorial likelihood of generating a 12-a.a. heteropeptide containing 66% glycine , would have been more than 10,000 times (= 12 × 11 × 10 × 9) that of an equally long homopeptide, and adding only three more residues would have increased this factor to >360,000. Importantly, these probabilities increase exponentially with the numbers of peptide molecules required to form a coacervate. (2) Additionally, the much simpler glycine further boosts the chemical plausibly of interspaced and only weakly charged peptides because cationic peptides, including arginine and even the non-canonical but simpler ornithine, were likely to have a lower abundance among pre-biological amino acidsn towards RNA causes a substantial widening of the transition regime (region II), which drastically extends the range of peptide concentration in which ribozymes maintain their activity. Mechanistically, the reduced charge density promotes magnesium partitioning and compartment fluidity, both described here as prerequisites for ribozyme activity inside coacervate compartments. More specifically, (1) our ITC data systematically show that peptide composition, a primitive constraint on sequence, is itself sufficient to generate locally distinct physicochemical conditions that modulate ribozyme function via differential metal ion concentrations without the need for a membrane47. (2) In addition to chemical identity, the physical conditions are highly sequence dependent. In particular, RNA base pairing has recently been described to lead to RNA gelation in coacervates and can still be observed for oligo-arginine below 10 residues. Interestingly, this absence of RNA mobility can be prevented by the charge interspacing of short peptides, which melt the RNA gel and promote ribozyme activity. Our results therefore establish how self-assembly drives the formation of protocellular compartments in which peptide sequence controls nucleic acid activity via the emergent physicochemical phenotypes. These findings represent a functional link between two important classes of molecules and provide a cellular basis upon which future selection processes could act.While we can only speculate how cells evolved, it is clear that at some stage RNA and peptides, two chemical classes of central importance for cellular life, must have found themselves together in small compartments. When combining peptides within reach of pre-biological synthesis and model ribozymes, we find that coacervates, a long-standing suggestion for protocellular life, emerge. These not only show increased stability when increasing chemical and combinatorial plausibility, but we find emergent properties to be tunable in a peptide-dependent manner. Functionally, the reduced charge density of short heteropeptides influences the coacervate phase in several ways. The lower affinity of peptides such as (RGG)37, the earliest cellular metabolic processes  could have been tuned via the material properties of the compartment. In more evolved protocells, coexisting coacervate phases26 could have served different purposes, similar to spatial and temporal variations in the functional material properties of modern cells37. While gel-like droplets such as Rn–RNA structures could function as RNA storage units that increased RNA stability, (RGG)n–RNA-like compartments could have formed with active RNA enzymes. Notably, RGG/RG motifs are also highly enriched in RNA-binding proteins in eukaryotes48 and mediate protein–RNA interactions51. Several proteins with RGG domains have been observed to phase separate in the presence of RNA, including LAF-152, FUS54, PGL333 and FIB116. Our results suggest that the previously proposed fluidization of these condensates by glycine incorporation in mammalian proteins34 might also have relevance for other molecular species. This may include RNA mobility, and could even impact concentrations of co-factors such as small ions, which determine the biochemical identity of compartments. Given the low complexity of the molecular constituents required, charge interspacing might be an ancient evolutionary mechanism to locally modulate function in a sequence-dependent manner. The minimal models described here may further help to understand how amino acid changes alone suffice to modulate the material properties of RNA–protein biological condensates, while excluding the possibility of non-specific side effects that may result from amino-acid substitution in in vivo proteins.Interestingly, our results suggest that, as in bacteria and eukaryotic cellsTo summarize, our results provide a mechanistic explanation for how simple heteropeptides maintain ribozyme activity in coacervates and provide a compelling proposition for the origin of cellular organization with rich and sequence-dependent functional phenotypes.2, 2 mM spermidine, 40 mM Tris–HCl pH 7.8, 3.75 mM nucleoside triphosphates (each nucleotide), 0.5 μM double-stranded DNA, 10 mM dithiothreitol, 0.09 μg μl−1 T7 RNA polymerase and 5 units ml−1 inorganic pyrophosphatase. The reaction was incubated for 1 h at 37 °C. After transcription, reactions were concentrated and buffer exchanged with water using Amicon 10 kDa molecular weight cut-off (MWCO) filters. Concentrated samples were then mixed with 2× loading buffer  and heated to 80 °C for 2 min. E and S2 RNAs were run on 12.5% or 20% denaturing polyacrylamide gels , respectively, at a constant 30 V cm−1. RNA bands were visualized by ultraviolet shadowing using a fluorescent thin-layer chromatography plate and exciting with 254 nm light. Bands of interest were excised from the gel and electroeluted for 30 min using Bio-Rad model 422 with 10 kDa MWCO filters. After electroelution, samples were recovered, filtered with Costar 0.22 μm cellulose acetate filters and buffer exchanged four times with RNase-free water (Ambion) using Amicon 10 kDa MWCO filters. Final RNA concentration was measured using a NanoDrop 2000 spectrophotometer (ThermoFisher) at 260 and 280 nm wavelengths and the respective molar extinction coefficient (ε) for each RNA strand .E and S2 RNA strands were synthesized by in vitro transcription using a template DNA containing the T7 promoter in the 3′ region. The template DNA was hybridized with a 22-base complementary DNA strand containing the T7 promoter. Hybridization was carried out by mixing equimolar concentrations of template DNA and the T7 promoter complementary sequence. The hybridization mix was incubated in a water bath at ∼80 °C and left to cool to room temperature. This partially double-stranded DNA was then used for in vitro transcription. The in vitro transcription reaction contained the following: 20 mM MgCl2. Samples were prepared by addition of a master mix containing the RNA and buffer to a peptide solution. The final sample volume was 5 μl. After addition of RNA, samples were mixed for 20 s and incubated for a further 40 s. Then, 1.5 μL of sample was analysed using a NanoDrop 2000 with ultraviolet–visible settings. We measured absorbance at 500, 260 and 280 nm. Absorbance at 500 nm was then converted to turbidity using the following equation:Samples contained 5 μM E, 6 μM S2, 10 mM Tris pH 7.5 and 5 mM MgCln peptides, fitted with a function of a convolution of a Gaussian with an exponential curve:A1 is a scaling factor, σ is the width of the Gaussian, x0 is the inflection point in the sigmoidal part of the turbidity curve and τ is the exponential decay constant.Turbidity curves against the a.a./nt ratio were fitted to the following equation to capture the sigmoidal increase in turbidity and the exponential decrease in turbidity for the KCoacervates were prepared by mixing a solution containing buffer, E, 6 μM S2 and 0.1 μM of the fluorescent RNA or 3 μM in monomer units of FAM-labelled peptide. When product diffusion was measured, the solution was incubated at room temperature for 30 min to allow ligation of S2 and Cy5-S1 by the enzyme. After mixing with the peptide solution, samples were incubated at room temperature for 1 min. After incubation, 5 μl of Pico-Surf was added to form a water–oil emulsion. Samples were then loaded in flow chambers prepared for imaging. Imaging was carried out using a Plan-Apochromat 63×/1.4 oil DIC objective and a Zeiss LSM 880 Airy inverted confocal microscope. Images were taken every 200 ms for a total time of 3 min.The mean intensity of four regions of interest—bleaching region, whole droplet, reference droplet and background—was collected for every frame. After image acquisition, videos were analysed using a custom-made MATLAB application with droplet tracking.C was assumed to be 0. The fitted fluorescence recovery time constant (τ) was then used to calculate the diffusion coefficient D using the following experimental equation:r is the radius of the bleaching region. To calculate a final diffusion coefficient for each coacervate condition, individual diffusion coefficients were averaged. This mean diffusion is reported with a 95% confidence interval.Images were normalized by first subtracting the background from the bleaching region, the whole droplet and the reference droplet. The fluorescence for the bleaching region and the whole droplet was then corrected for photobleaching by dividing by the reference droplet and normalized to the mean of the frames before bleaching (20 frames). The bleaching region intensity for every frame was then divided by the intensity of the whole droplet. This final curve was then fitted to an exponential equation:55 of ε = 8.9 × 10−3 μM−1 cm−1.Torula yeast RNA was purified by first dissolving the RNA in MilliQ water. An equal volume of phenol:chloroform:isoamyl alcohol (25:24:1) was added to the RNA solution. The two-phase solution was vortexed to generate an emulsion and later centrifuged at 15,000 r.c.f. for 15 min. The aqueous phase was recovered and the process was repeated several times until no precipitate was observed between the aqueous and the organic phases. The final aqueous phase was taken and 3 M sodium acetate solution, preadjusted to pH 5.5, was added to a final concentration of 10% (v/v) To this solution, the same volume of isopropanol was added to precipitate the RNA. The pellet was finally washed twice with 70% ethanol. The washed pellet was then dissolved in MilliQ water. The final concentration of RNA was calculated using a NanoDrop 2000 and an average extinction coefficient for the nucleotides−1 for 20 min in 1× TBE buffer . After electrophoresis, 6-FAM fluorescence was collected using a Typhoon 9900 scanner. Gels were then incubated for 30 min in 0.05% SDS and stained for 30 min with SyproRed in 10% acetic acid. The gel was finally washed with 10% acetic acid for 5 min and then imaged to collect the SyproRed signal.Samples contained 5 μM E, 6 μM S2 and 0.1 μM 6-FAM-E and were prepared in the same way as for the turbidity assays. After 1 min of incubation, 1.25 μl of 5× loading buffer  was added to the samples. A 5 μl portion of each sample was then loaded in a 4% agarose gel. The gel was run at 6 V cmCarbon-coated grids  were prepared by depositing a thin carbon layer over the grids. The layer was obtained by carbon evaporation  onto muscovite . Grids were arranged on a mask and then placed on a homemade cuvette filled with distilled water. The carbon-coated muscovite was submerged in water to peel off the carbon layer and deposited on the grids by decreasing the water level of the cuvette. Grids were dried overnight and glow discharged before use . Samples for negative staining were prepared as for turbidity assays. After 1 min incubation, 5 μl was loaded on the grid. After 30 s, liquid was removed from the samples using Whatmann filter paper and samples were then immediately overlaid with 2% uranyl formate solution for another 30 s. After removing the uranyl formate, the grids were allowed to dry at room temperature. Imaging was performed using a Tecnai F30 transmission electron microscope.2 and peptide. Final sample volume was 5 μl. After mixing the RNA with the peptide, samples were centrifuged for 10 min at 20,000 r.c.f. After centrifugation, all the supernatant phase was transferred to a new tube. We then added 5 μl of 1× buffer to the tubes containing the coacervate phase. A 40 μl portion of 5 M NaCl was added to both the supernatant and coacervate. Finally, 12 μl was loaded in a 384-well plate with a flat plastic bottom, and each sample was measured in triplicate. The well plate was read on a TECAN Spark 20 M spectrophotometer using λexc = 492 nm and λem = 523 nm with a bandwidth of 10 nm at 25 °C.Samples contained 5 μM E, 6 μM S2, 0.1 μM of FAM-labelled RNA to be tested, 10 mM Tris 7.5, 5 mM MgCl4 and (RGG)5 and to exclude contamination by other shorter sequences produced during RNA chemical synthesis by the supplier, we prepared coacervates as stated before but centrifuged them for 2 min and analysed them by gel electrophoresis using 0.1 µM of FITC-labelled E RNA.To measure the partitioning of E for (RGG)Fmax is the maximum fluorescence intensity in the coacervates phase, Fmin is the minimum fluorescence intensity , Fhalf is the peptide concentration at which half of the fluorescent RNA is retained in the coacervate phase and n is the Hill coefficient. For Fig. Fmin constrained to 0.After data collection, we took the average fluorescence intensity of the triplicates and subtracted a reference background (containing buffer and NaCl). The intensity of the coacervate fraction was divided by the supernatant intensity. Data were then fitted to a Hill equation:2 to yield final concentrations of 5 µM E, 6 µM S2, 0.1 µM Cy5-S1, 10 mM Tris 7.5, 5 mM MgCl2 and the respective concentrations of peptide depending on the a.a./nt ratio tested. The final volume was adjusted to 5 µl. Reactions were incubated for 1 h at 30 °C. Then, incubation reactions were stopped and coacervates dissolved by adding 4 µl of loading buffer  per 1 µl of sample. Samples were loaded on a 12.5% polyacrylamide gel (19:1) with 8 M urea and 1× TBE. Gels were ran at 10 V cm−1 for 40 min and imaged in a Typhoon 9900 scanner to visualize Cy5 fluorescence. After imaging, gels were analysed with a custom-made MATLAB script to subtract the background and calculate the fraction of Cy5-S1 ligated into product P.Reactions were prepared by mixing a solution of E, S1, Cy5-S2 and Tris 7.5 with a solution of peptide and MgCl2. Droplets were prepared at an a.a./nt ratio of 10 for R9 and K9 coacervates, 40 for (RGG)5 and 70 for (RGG)4. Samples had a final volume of 5 µl. After coacervate preparation, 5 µl of Pico-Surf was added to encapsulate coacervates in a water–oil emulsion. Coacervates were imaged using a 60× UPLSAPO/1.2 water objective with W-IR coating (Olympus) mounted on a spinning disc confocal microscope. Cy5 was excited at λ = 633 nm with a Cy5 filter set. The microscope was equipped with a FLUCS setup56 that was used to bring droplets closer to each other.Droplet fusion experiments were performed in samples containing 5 µM E, 6 µM S2, 0.1 µM Cy5-S1 in 10 mM Tris 7.5 and 5 mM MgClτ) for every fusion event against the geometric radius of the fusing droplets  that uses the following equation:3 was added to the coacervate phase and samples were sonicated for 15 min at room temperature. After sonication, samples were further diluted with 4.5 ml of 1% (v/v) HNO3 and analysed using a quadrupole ICP-MS NexION 350x (Perkin Elmer). The system was calibrated for magnesium with an ICP element standard solution VI (Merck). ICP curves were fitted to:Samples were prepared as for the turbidity assays and then centrifuged for 30 min at 20,000 r.c.f. After centrifugation, the coacervate phase was separated from the supernatant for acidification. Then, 500 μl of high-purity 1% (v/v) HNO−1. ITC was first performed on Mg2+ binding to torula yeast RNA. For this purpose, torula yeast RNA in 10 mM Tris 7.5 was loaded at different concentrations in the measuring cell. Several torula yeast concentrations in nucleotide units were used: 10, 7.5, 5 and 2.5 mM. A solution containing 20 mM MgCl2 and 10 mM Tris 7.5 was titrated into the cell. The first injection introduced 0.2 μl and was discarded, as specified in the manufacturer’s instructions. The subsequent 39 injections had a volume of 1 μl with 200 s between injections. If the curve was not completed after 40 injections, the syringe was refilled and a new experiment was started without changing the material in the cell. This increases the final molar ratio attained. The curves of Mg2+ titration to pure buffer were subtracted from the curve derived from a Mg2+ binding to RNA. The total heat for the interaction was calculated as the sum of the heats released per injection and then normalized by the moles of RNA in the cell.ITC was performed using a microcalorimeter . The reference power of the cell was adjusted to 5 μcal s2+, the ITC cell was filled with torula yeast RNA in 10 mM Tris 7.5 with or without 5 mM MgCl2. We then titrated a solution of 10 mM R9, 10 mM K9 or 100 mM (RGG)4 in 10 mM Tris 7.5 with or without MgCl2 to the cell containing the torula yeast RNA. Torula yeast was present at different concentrations from 0.4 mM to 0.9 mM. The first injection introduced 0.2 μl and was discarded. The subsequent 39 injections had a volume of 1 μl with 200 s between injections for R9 and K9 and 300 s for (RGG)4. The heat released in the presence of MgCl2 was subtracted from the heat released in the absence of MgCl2 for every peptide. This difference was then compared to the heat released upon Mg2+ binding to RNA.To measure heat release upon peptide binding in the presence or absence of Mg5 and 17.5 mM (RGG)5 (in monomer units) in 10 mM Tris 7.5 and 20 mM MgCl2. A master mix containing all the RNA strands, MgCl2 and Tris was prepared before mixing the RNA with the peptide to ensure that all Cy5-S1 reacted to form Cy5-P (the product of the ligation). After mixing with the peptide solution, samples were incubated at room temperature for 1 min. After incubation, 5 μl of Pico-Surf was added to form a water–oil emulsion. The samples were imaged using a Plan-Apochromat 40×/1.2 water objective mounted on a Zeiss LSM 880 Airy inverted confocal microscope. Images were taken every 30 s for a total time of 63 min. Droplets were bleached using a 355 nm laser after the fifth frame. The Cy5 and FITC channels were imaged simultaneously.(RGG)5 coacervates were prepared at a 40 a.a./nt ratio. The final mix contained 5 µM E, 6 µM S2, 0.1 µM Cy5-S1, 0.2 µM FITC-(RGG)For the analysis the droplets were segmented using the FITC–peptide channel, which recovered immediately after exposure to the 355 nm laser. The generated mask was then used to monitor Cy5 fluorescence in the droplets over time.Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41557-022-00890-8.Supplementary InformationSupplementary Figs. 1–17, in–out diffusion of RNA from coacervates, references, complete gels.


Small nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions.We used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues . We identify 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level, and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. Fifty-nine percent of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, compared to only 16% of the correlated non-coding host gene/snoRNA pairs.Our results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.The online version contains supplementary material available at 10.1186/s13059-021-02391-2. Small nucleolar RNAs (snoRNAs) are a conserved family of mid-size non-coding RNA best characterized as guides for the chemical modification of nascent ribosomal RNA (rRNA) –3. Functtrans as in the case of rRNA modification guides or through cis base pairing that modifies the local structure surrounding the snoRNA, a mechanism that may be involved in snoRNA biogenesis [A growing number of orphan snoRNAs as well as snoRNAs with rRNA or snRNA targets are being assigned alternative functions in the regulation of gene expression including at the level of chromatin remodeling, pre-mRNA stability, alternative splicing, and polyadenylation .ogenesis . It can ogenesis , 15. Theogenesis –19). Theogenesis , 12. ThiIn human, with the exception of the few snoRNAs required for rRNA processing, the majority of snoRNAs are expressed from the introns of either protein-coding or non-coding host genes (HGs) . Each tissue was sourced from 3 different individuals and sequenced using TGIRT-Seq methodology, which was shown to reliably quantify the abundance of different types of RNA in a same sample , 29. IndTo evaluate the relative contribution of snoRNAs to the transcriptome of the different human tissues, we compared their abundance to other RNA biotypes detected in each of the tissues examined. Overall, the highest percentage of expressed non-rRNA transcripts was detected within tRNAs where 84% of the annotated genes are expressed at least in one tissue, followed by the protein-coding genes and snoRNA genes  are uniformly expressed across tissues, whereas 85 snoRNAs are enriched in specific tissues . These differences in abundance and snoRNA type appear to reflect a degree of functional specialization of the snoRNA abundance classes. Indeed, examining the type of RNA targeted by the snoRNA classes, we notice clear differences in the groups’ target preferences. In general, most targets of the UE class are in rRNA or snRNA, while most TE snoRNAs have no known canonical targets   Fig. C.Fig. 3p < 2 × 10−10)     Fig. D. The pr11) Fig. E. TE snop < 0.05 and p < 0.0005, respectively)         . Healthy breast, ovary, and prostate tissue samples were obtained from the FRSQ tissue bank (Université de Sherbrooke). Each 30 mg tissue sample was homogenized in 1 mL of TRIzol Reagent (Ambion) using a Polytron tissue homogenizer and kept at − 80 °C until RNA extraction. Characteristics of the samples are available in Additional file Since RNA was directly purchased for the skeletal muscle, liver, testis, and brain tissues, only total RNA extractions from breast, ovary, and prostate tissues were performed using RNeasy Mini Kit (Qiagen) as recommended by the manufacturer including on column DNase digestion with RNase-Free DNase Set (Qiagen). However, 1.5 volume of ethanol 100% was used instead of the recommended 1 volume of ethanol 70% in order to retain smaller RNA. RNA integrity of each sample was assessed with a 2100 Bioanalyzer (Agilent). These values are available from Additional file RNA-Seq libraries were built as previously described . BrieflycDNAs were synthesized via TGIRT template-switching with 1 μM TGIRT-III reverse transcriptase  for 15 min at 60 °C, during which a DNA oligonucleotide containing the complement of an Illumina Read 2 sequencing primer-binding site became seamlessly linked to the 5′ cDNA end. After reaction cleanup, a 5′ adenylated DNA oligonucleotide containing the complement of an Illumina Read 1 sequencing primer-binding site was then ligated to the 3′ cDNA end with Thermostable 5′ AppDNA / RNA Ligase (New England Biolabs). Properly ligated cDNAs were amplified by PCR (12 cycles) to synthesize the second strand and add Illumina flowcell capture and index sequences. Libraries were purified with 2 rounds of Ampure XP beads (Beckman-Coulter) and evaluated on a 2100 Bioanalyzer (Agilent). Libraries were then pooled and sequenced on a NextSeq 500 platform (Illumina) (2 × 75 bp) using a NextSeq 500/550 High Output Kit v2.5 (150 cycles) (Illumina). Three distinct sequencing runs were performed to sequence all tissue samples: the first pool was composed of the Breast_1, Breast_2, Ovary_1, Ovary_2, Ovary_3, Prostate_1, Prostate_2, and Prostate_3 RNA samples; the second pool was composed of the Brain_1, Brain_2, Brain_3, Liver_1, Liver_2, Liver_3, Testis_1, and Testis_2 RNA samples; the third pool was composed of the Breast_3, Skeletal_muscle_1, Skeletal_muscle_2, Skeletal_muscle_3, and Testis_3 RNA samples.https://github.com/etiennefc/TGIRT_Seq_pipeline.git [https://zenodo.org/record/3981426/files/human_ensembl_87_wo_dup_v2.BB_v3.correct_annotation.gtf) described in [All RNA abundance datasets were generated using a succession of bioinformatics tools regrouped in a reproducible Snakemake workflow . All detline.git , but areline.git  and the line.git ). In sholine.git   was calculated for each snoRNA. This method was also applied to other RNA biotypes . In short, the CV was calculated as the standard deviation of the abundance of that snoRNA across the tissues divided by the average abundance of that snoRNA across the tissues, all of that multiplied by 100. These CVs were represented in a kernel density estimate plot and the resulting bimodal curve was divided in two by tracing the tangent at the point where the derivative of the bimodal curve function was the most negative. The point at which the tangent crossed the x-axis was defined as the threshold for the two snoRNA abundance classes. Above that threshold of CV = 125, snoRNAs were dubbed “Tissue-enriched” or “TE”, whereas snoRNAs with a CV below that threshold were dubbed “Uniformly expressed” or “UE”. To classify in which tissue TE snoRNAs were predominantly expressed, the tissue where the snoRNA abundance (in TPM) was the highest was established as the enrichment tissue. This was the case for all TE snoRNAs except for 4 snoRNAs  that were highly abundant in both breast and ovary and had a difference of abundance (in TPM) of at most 2 times the abundance seen in the other tissue (either breast or ovary).p < 0.05, **p < 0.01, and ***p < 0.001. Graphs were generated using either the pandas v1.0.1, Matplotlib v3.1.1 or Seaborn v0.9.0 libraries.All statistical analyses and graphs were realized using Python-based packages. Pearson correlation coefficients (Pearson’s r) and their associated p values, Fisher’s exact test p values, and Mann-Whitney U test p values were generated using the Stats module from Scipy v1.4.1. SnoRNAs with a correlation of abundance with their HG (Pearson’s r) inferior to − 0.25 were considered “anticorrelated” whereas those with a Pearson’s r greater than 0.25 were considered “positively correlated”; snoRNAs with a Pearson’s r comprised inclusively between − 0.25 and 0.25 were considered “non-correlated”. P value correction for false-discovery rate (FDR) using the Benjamini-Hochberg correction (for the correlation of abundance between snoRNAs and their HG) was performed using the Multitest module from Statsmodels v0.11.0. Throughout this study, all results were considered significant at *Additional file 1. Supplementary figures (S1-S11) and tables (S1-S4) describe the modulation of the human snoRNome.Additional file 2. Supplementary table S5 describes the abundance across tissues and characteristics of all expressed snoRNAs and their host gene.Additional file 3. Peer review history.


Cryo-electron microscopy (cryo-EM) has emerged as an unprecedented tool to resolve protein structures at atomic resolution. Structural insights of biological samples not accessible by conventional X-ray crystallography and NMR can be explored with cryo-EM because measurements are carried out under near-native crystal-free conditions, and large protein complexes with conformational and compositional heterogeneity are readily resolved. RNA has remained underexplored in cryo-EM, despite its essential role in various biological processes. This review highlights current challenges and recent progress in using cryo-EM single-particle analysis to determine protein-free RNA structures, enabled by improvement in sample preparation and integration of multiple structural and biochemical methods. Whereas the above features make SPA particularly useful to determine structures of larger proteins and protein complexes (>200 kDa), additional technical advances, especially the development of Volta phase plate (VPP),12 have pushed the limit of protein molecular weight to as low as 52 kDa for structure determination by SPA.13 Readers interested in technical developments and current challenges in SPA are directed to a number of comprehensive reviews for further details.16The recent resolution revolution triggered by the development of direct electron detectors and other technical advances has allowed cryo-EM to break the previous resolution barrier(s) and led to exponential growth of near-atomic cryo-EM structures.19 It is estimated that about 85% of the human genome is transcribed into RNA,20 with more than 80% of the genome estimated to be biologically and functionally relevant,21 however, only 1.5 percent of the genome encodes proteins.22 In the Protein Data Bank (wwPDB), there are currently 183980 depositions of protein complexes, which has facilitated the development of accurate protein structure prediction algorithms.23 In contrast to our apparently better understanding of protein structures and functions, our knowledge of RNA structures remains scarce. There are currently 1569 protein-free RNA and 9790 protein-nucleic acid complex structures deposited in the PDB that accounts for only about 6% of the entire PDB deposition . To date, there are only three protein-free RNA cryo-EM structures determined at 4 Å or better resolution  structure in order to perform functions such as catalysis and gene regulation.ion Fig. . The lacon Table .Fig. 1St29 All RNA structures reviewed herein are cryo-EM structures of protein-free RNAs.The scarcity of protein-free RNA cryo-EM structures may be attributed to the following reasons: (1) Effective approaches and/or pipelines are missing for obtaining properly folded RNAs with stable tertiary structures; (2) the majority of isolated functional RNAs are simply too small for facile visualization and reconstruction in standard SPA pipelines; (3) intrinsic heterogeneity in most RNA molecules greatly limits the attainable resolution by SPA. This review summarizes recent efforts that overcome these challenges and enrich the protein-free RNA cryo-EM structure repertoire, including new approaches to obtain stable RNA structures for cryo-EM SPA and integration of multiple techniques to facilitate structural analysis when resolution is moderate. Cryo-EM structures of RNAs in RNPs such as ribosome, spliceosome, telomerase, and CRISPR complexes will not be discussed, as they are reviewed elsewhere.31 Group II introns are ribozymes with endogenous protein partners that stabilize the dynamic RNA structures and facilitate RNA catalysis.33 The analogous approach has been reported by Qu et al. in the cryo-EM structure of the Lactococcus lactis LtrB group II intron in complex with its intron-encoded protein LtrA at 3.8 Å  indicates that TLS undergoes drastic conformational changes to resemble “tRNA-like” shape in order to bind to TyrRS. This is a great example illustrating the importance of studying protein-free RNAs to provide insights of required conformational rearrangement upon protein binding.Bonilla and colleagues used cryo-EM SPA to solve the viral tRNA-like structure (TLS) of bromo mosaic virus (BMV) at 4.3 Å resolution.37 Self-assembly is achieved by insertions of kissing-loop sequence in the functionally non-essential peripheral stem loops, which makes the assembled RNA two- to three-times larger than the monomeric RNA ”, to obtain homomeric self-assembled dimers and trimers of protein-free RNAs for SPA at near-atomic to subnanometer resolutions.RNA Fig. . While t38 In this workflow, native gel analysis enables quick identification of optimal RNA refolding conditions. RNAs that form sharp bands in native gels are subjected to M2-seq experiments,39 in which secondary structures are determined to both assess the homogeneity of folded RNA structures and to assist RNA modeling. Cryo-EM SPA allowed the rapid determination of 11 previously unknown RNA structures at resolution ranging from 4.7 to 10 Å, which revealed explicit RNA features of major and minor grooves. Seven structures were determined with VPP for contrast enhancement. Finally, auto-DRRAFTER was developed based on the previous DRRAFTER40 to utilize secondary structures determined by M2-seq to build 3D RNA models guided by cryo-EM density, because de novo RNA modeling can be very challenging under such resolution. The estimated coordinate root mean square deviation (RMSD) accuracy was between 3.3 and 6.3 Å as predicted by modeling convergence, which is sufficient for revealing RNA overall fold. This workflow enables accelerated RNA cryo-EM structure determinations by introducing methods to examine RNA folding and structural homogeneity, which can be used both to assist RNA modeling and to guide additional cryo-EM data collection for improved resolution.Kappel et al. recently developed an accelerated RNA structure determination workflow, named “Ribosolve” Fig. , that in41 was initially resolved to 7 Å resolution using cryo-EM SPA with VPP. Zhang et al. continued to collect additional cryo-EM data and achieved 3.7 Å resolution for the apo state and 4.1 Å for the SAM-bound state allowing unambiguous ligand recognition.42 The final data sets that generated cryo-EM structures of both states at near-atomic resolution were collected without VPP. This is likely because the stronger electron scattering of phosphate backbones has provided sufficient contrast for visualization of this small RNA. At 3.7 Å resolution, only a portion of the base pairs is resolved, indicating that higher resolution is required to allow de novo modeling. Nonetheless, this study has demonstrated the capability of cryo-EM SPA to facilitate structure determination at near-atomic resolution for RNA that is beyond the current molecular weight limit of 52 kDa for protein.13A few applications of the “Ribosolve” workflow have been reported. SAM-IV riboswitch, a 40 kDa RNA that recognizes S-adenosylmethionine (SAM),Tetrahymena ribozyme in both apo and substrate-bound states at 3.1 Å resolution.43 Group I self-splicing intron of Tetrahymena thermophila was discovered as the first ribozyme and has since become an unprecedented model system to study RNA catalysis and structure-function relationship. However, the full-length Tetrahymena ribozyme structure remains unknown for 40 years. After a 6.8 Å cryo-EM map of the apo L-21 Tetrahymena ribozyme map was obtained by “Ribosolve”, more data was collected to achieve a 3.1 Å cryo-EM structure, in which the complete peripheral region was explicitly resolved and two previously unforeseen tertiary interactions that allosterically regulate catalysis were identified. The substrate-bound state revealed catalytic mechanism, conformational changes of the internal guide sequence, and local shifts of phosphate, nucleobase, and metal ions upon substrate binding. This study provided a complete structural view of the Tetrahymena ribozyme and a great example of dissecting the RNA structure-function relationship by cryo-EM.Recently, Su and colleagues solved the cryo-EM structures of full-length 44 Using “Ribosolve”, Zhang et al. resolved the 6.9 Å cryo-EM structure of the frameshifting stimulus elements (FSE), a highly conserved 88 nt RNA that is essential for the balanced expression of important viral proteins in the SARS-CoV-2 genome.45 It is also a potential candidate target for antiviral drugs such as small molecules and antisense oligonucleotides (ASO). Under the guidance of cryo-EM map, the RNA model was built with an estimated RMSD accuracy of 5.9 Å predicted by RNA modeling convergence following the “Ribosolve” pipeline.38 Subsequently, ASOs targeting FSE were designed and their antiviral activities were verified in vitro and at cellular level. This study features the smallest 28 kDa protein-free RNA studied by cryo-EM and resolving the tertiary structure of this key RNA element of SARS-CoV-2 potentially speeds up the development of new therapies for COVID-19.During the SARS-CoV-2 pandemic, cryo-EM SPA has played essential roles in unveiling the structural basis of viral infection, replication, and other stages in the virus life cycle.46 Molecular dynamics (MD) simulations of multiple time points on simulated cryo-EM data of DIS suggest that the intrinsic RNA structural heterogeneity limits cryo-EM SPA from achieving higher resolution for the DIS RNA.Zhang et al. used cryo-EM SPA to resolve a 30 kDa HIV-1 dimer initiation site RNA (DIS) at 9 Å resolution. The cryo-EM map helps restraining NMR model refinement to derive atomic ensembles of this RNA duplex to identify a flipped-out nucleotide at both ends of the duplex.Gly complex.47 Although the central tRNAGly is better resolved to 4.1 Å, featured by separated density of some phosphate and ribose groups, the outer T-box is only resolved to 6 Å. This moderate resolution poses great challenge for RNA modeling, especially in the newly identified 66 nt 3′-discriminator region with previously unknown structural features. They tackled this problem by determining a co-crystal structure of tRNAGly in complex with the 3′-discriminator from another bacterial species at 2.7 Å resolution. The final model of the full length T-box-tRNAGly complex was generated by combining the 3′-discriminator RNA model with the previously known crystal structure of tRNAGly and 5′-Stem I complex and refined into the cryo-EM density.49 Cryo-EM 3D classification indicated that structural heterogeneity of the T-box 5′-Stem I and 3′-discriminator regions may have limited the overall resolution.Li et al. resolved a 4.9 Å cryo-EM structure of the full-length T-box-tRNA50 The cryo-EM structures show an overall similar architecture compared to a previous high-resolution crystal structure except for an ~23° curvature at the end of one ENE, indicating that crystal packing may not reveal minor structural dynamics in solution. Small angle X-ray scattering (SAXS) reveals a global shape that is consistent with both cryo-EM and crystal structures.In another study, Torabi et al. resolved cryo-EM maps of a double element for nuclear expression (dENE) before and after poly(A) binding at subnanometer resolution.In conclusion, these examples illustrate the combinations of different high-resolution structural biology techniques, such as X-ray crystallography and NMR, to facilitate the analysis of cryo-EM RNA structures at moderate resolution Fig. . Accordide novo model building. In contrast, RNA cryo-EM structures at near-atomic resolution are rare. The recent progress in RNA cryo-EM SPA has generated most RNA structures at a moderate resolution ranging from 4 to 10 Å, which are challenging for de novo modeling. Multiple strategies have been used synergistically to assist structural analysis of these RNA cryo-EM structures, including hybrid approaches combining RNA modeling, NMR, and X-ray crystallography. In order to facilitate structural analysis based on cryo-EM structures, it is critical to identify and overcome the major factors that limit cryo-EM SPA to attain RNA structures at near-atomic resolution.Cryo-EM SPA can readily attain near-atomic resolution (between 2 and 4 Å) for proteins and protein complexes on a regular basis, which is sufficient to enable B-factor, derived from the correlation between the number of particles used for reconstruction and the achieved resolution, is used to evaluate the quality of the cryo-EM data .51 The B-factor values calculated for RNAs between 40 and 125 kDa are all greater than 200 Å2 , which will deteriorate the accuracy of particle alignment in SPA.B-factor, such as ice thickness, beam-induced motion (BIM), and intrinsic heterogeneity of the RNA molecules. To eliminate ice thickness variations, in which thicker ice will lead to decreased image contrast and SNR, novel sample preparation instruments have been developed and are currently optimized to reproducibly generate thin ice. For example, “Spotiton” can deliver as little as a few nanoliters of samples onto the grid while it plunges.58 The reduced time window between spotting and plunging also attenuates the air-water interface problem,59 which causes other issues in SPA such as preferred orientation and sample denaturation (reviewed elsewhere60).A number of other factors may have an impact on the 61 In particular, the amorphous nickel-titanium alloy (ANTA) film has been developed to reduce BIM.62 More recently, BIM has been minimized utilizing ultrastable gold foils on gold grids with specific hole diameter that ameliorate stress in the vitrified ice, named HexAuFoil.64 The drastic translational and rotational motions discovered in the first few frames that carry the highest resolution information can also be ameliorated by finer intervals (i.e. more frames) to improve motion correction accuracy. The resulting lower contrast and SNR of each frame can be potentially compensated by VPP or weighted denoising algorithms that should theoretically enhance SNR at low spatial frequencies.66BIM has been previously shown to be drastically reduced by the implementation of various supporting films and foils.B-factor than protein due to its intrinsic heterogeneity and dynamics. Structural study is primarily facilitated by the identification of RNAs with conformational homogeneity and stable 3D structures, as demonstrated by native gel analysis and M2-seq in the “Ribosolve” workflow.37 Additional information from computational analysis, such as phylogenetic analysis and predictions of long-range tertiary interactions  will further enable the identification of conformational homogeneous RNAs with stable 3D structures.67 It is noteworthy that cryo-EM provides the unique opportunity of resolving conformational heterogeneity. Recent advance in automated data collection strategies that uses beam-shift instead of mechanical stage movement for each exposure,68 combined with image processing algorithm that compensates the aberrations caused by beam-shift,69 enable significantly increased throughput of data collection. As more particles are collected within the same time frame, classification of multiple conformations become realistic using existing algorithms such as Relion multibody refinement,70 cryoSPARC 3D variability analysis,71 and the emerging neural network-based 3D heterogeneity analysis,72 to eventually resolve RNA structures and their intrinsic heterogeneity and dynamics.RNA may naturally adopt higher 76 However, these algorithms rely heavily on the plentifulness of experimental data. Although a recent study has reported a scoring system trained by very few existing RNA structures using machine learning algorithm to improve RNA structure prediction accuracy,77 the lack of experimental RNA structures remains to be the major barrier for precise RNA structure prediction. Recent progress in the field of RNA cryo-EM demonstrates how cryo-EM SPA complements X-ray crystallography and NMR to provide insightful structural information. Continued advances in technical and experimental developments of cryo-EM will allow accelerated structural findings previously not accessible by X-ray crystallography and NMR, and generate RNA structures at near-atomic resolution on a more regular basis. This will provide structural insights to deepen our understanding of RNA structure-function relationships as well as facilitating precise RNA structure predictions in the near future.We are in an exciting era for structural biology, in which the emerging deep learning structure prediction algorithms have enabled reliable structure predictions of proteins and protein complexes in eukaryotes including human.


Here we describe how modifications found in tRNAs anticodon-loop, rRNA, and mRNA can affect translation fidelity, and how approaches based on direct manipulations of the level of RNA modification could potentially be used to modulate translation for the treatment of human genetic diseases.RNA modifications play an essential role in determining RNA fate. Recent studies have revealed the effects of such modifications on all steps of RNA metabolism. These modifications range from the addition of simple groups, such as methyl groups, to the addition of highly complex structures, such as sugars. Their consequences for translation fidelity are not always well documented. Unlike the well-known m All types of RNA are subject to post-transcriptional modification. Since the discovery of RNA modifications in 1951, more than 150 RNA modifications have been found in coding and non-coding RNAs ranging from the addition of simple groups to the addition of highly complex structures  1,2,3].,3.2,3].Their biological consequences are largely unknown, but the discovery that RNAs undergo dynamic, reversible chemical modifications marked the birth of the era of epi-transcriptomics. All aspects of RNA metabolism can be affected by RNA modifications , either Translation is not perfectly accurate, as it has a median error rate of 0.01% in humans ,26. TherIn this review we will describe modifications affecting two abundant types of non-coding RNAs—tRNAs and rRNAs—and will consider how such modifications fine-tune translational accuracy. We will also discuss the importance of certain mRNA modifications affecting ribosome fidelity. There is a striking difference in the mode of action of modifications between coding and non-coding RNAs, in that modifications to rRNAs and tRNAs act directly on the folding and activity of the molecule, whereas most of the modifications to mRNAs act via reader proteins. This simplified presentation needs to be modulated because some tRNA modifications are required for the proper action of aminoacyl-tRNA synthetases (aaRS) .The type of RNA most frequently modified in cells is tRNA, in which about 17% of nucleotides are modified . ModificALKBH1 can remove the methyl group from m1A58 in tRNAs Sec [6A37 is proposed to enhance A:U stacking by stabilizing the Watson-Crick base pair but the chemical reasons are not yet clear [N6-isopentenyladenosine (i[Ser]Sec . The laset clear .6A37 on translation fidelity was assessed in a S. cerevisiae model (Blanchet 2017). Mod5p enzyme synthetizes the i6A37 in the Tyr and Cys tRNAs. The ability of Tyr and Cys tRNAs to readthrough respectively UAA/UAG and UGA stop codons has been assessed in a ΔMod5p strain by mass spectrometry. In this strain, both tRNAs are less efficient at being mis-incorporated, revealing that i6A37 modification acts as an enhancer of translation plasticity in S. cerevisiae. In another study in S. pombe, the role of i6A37 has been assessed using a β-galactosidase codon-swap reporter [6A37 increases the incorporation of tRNATyr at a near-cognate codon. Moreover, it shows that the modification enhances the incorporation of tRNACys at a cognate codon. Altogether, these data suggest that i6A37 promotes decoding activity generally. The role of ireporter . This co6A37 in translation fidelity. However, it is clear that TRIT1 mutation is associated with severe diseases. Indeed, it has been defined as a tumor suppressor [To date, no study has been made in humans about the role of ippressor . The mutppressor . 35, Ψ38 and Ψ39 on translation fidelity probably stems from their ability to improve the stacking of double-stranded RNA over that achieved with the uridine isomer [35) or next to (Ψ38-Ψ39) the anticodon enhances the stability and structure of pairing. Pseudouridine (Ψ) is an isomer of uridine in which uracil binds the ribose via a C1′-C5 rather than a C1′-N1 bond . The psee isomer . More pre isomer . Thanks S. cerevisiae) have shown that the deletion of PUS3 triggers an increase in misincorporation events relative to the WT strain [38 and Ψ39, at the end of the anticodon loop increase miscoding frequency. We have also studied the contribution of Ψ35 to the ability of tRNATyr to act as a near-cognate tRNA for stop-codon readthrough in a ΔPUS7 strain [PUS7 gene. This finding highlights the importance of Ψ35 for the ability of tRNATyr to read through UAA and UAG codons. Together, these studies demonstrate that Ψ modifications to the anticodon loop of tRNAs have a major effect on translation fidelity. The tRNA pseudo-uridine synthases PUS3 and PUS7 have both been implicated in human health problems; they cause different diseases, and notably intellectual disability [Studies in yeast , is stimulated by prior C to U editing at position 32 [It is interesting to mention that some modifications away from the anticodon loop seems to play a role in translation. For example, absence of ac4Cf m22G26 . Since tand Gm34 ,85,86; tof m3C32 ; m5C38 iormation ; and I34ition 32 . Future 38 of tRNAAsp [, protects tRNA from the degradation [ALKBH3 activity results in removal of m1A and m3C modifications, leading to a sensitivity to angiogenin cleavage [It is also possible that tRNA modifications act through other processes such as RNA sequestration, or the generation of tRNA-derived fragments (tRFs/tiRFs)  obtained tRNAAsp , protectradation . It has cleavage .Ribosomal RNA is the most abundant non-coding RNA in the cytoplasm. It is the main constituent of the ribosome. In total, 200 modification sites have been mapped on the human ribosome, in which about 2% of the nucleotides are modified ,94,95,962′-O-methylation (Nm) is a modification in which a sugar is added to the 2′C hydroxyl group of the nucleotide. The chemical impact of Nm on RNA has been investigated by several studies. It has been reported that Nm biases the sugar pucker equilibrium in favor of the C3′-endo conformation of pyrimidines . Intra-rIn human cells, Nm is mediated by the ribonucleoprotein complex consisting of the methylase fibrillarin (FBL) and the guide RNA (C/D box snoRNA) specific to the methylation site . FBL is 1639 was identified as the most important of the Nm sites tested. The abolition of Nm at this P-site triggers a slight increase in UAG readthrough. This work revealed a role for Nm-C1639 in the maintenance of ribosome fidelity during termination. There is now a need to reproduce such systematic analyses of Nm sites in humans.The role of Nm in miscoding has been explored in human cancer cells . FBL ove398 or Gm3745 in the 28S rRNA or of Am163 in the 18S rRNA is embryo-lethal in zebrafish [The role of rRNA’s Nm extends beyond miscoding events. The downregulation of FBL has been shown to alter IRES-dependent initiation and frameshifting. A single deletion of Amebrafish . Moreoveebrafish ,107,108.PUS7, the formation of Ψs in rRNA is catalyzed by a ribonucleoprotein complex composed of the pseudo-uridine synthase DKC1 associated with H/ACA box snoRNAs [With the exception of position 50 in the 5S rRNA that is catalyzed by the enzyme  snoRNAs ,110. In  snoRNAs ,113,114.609 and Ψ863 on the 18S rRNA, has been downregulated in HCC cells [609 and Ψ863 relative to wild-type ribosomes, depending on the tRNA entering the ribosome. It has also been shown that lower levels of SNORA24 expression increase amino-acid misincorporation by 10%–20% and readthrough by 15% at UGA, but not at UAG codons.The role of Ψs in miscoding has been investigated in human cells . SNORA24CC cells . An analThe way in which Ψs in rRNAs decrease the accuracy of translation seems to depend on their abundance in the peptidyl transferase and decoding centers of the ribosome . Ψs are Many studies over the last decade have revealed the importance of mRNA modifications. These modifications are highly dynamic, with eraser proteins able to eradicate the modifications from the mRNA. The dynamic aspect of the modifications allows integration in a very efficient manner of the RNA metabolism and translation to the physiological state of the cell, considering the appearance of possible stresses.The formation of inosine on mRNAs is catalyzed by the adenosine deaminases ADAR1 and 2 . The ino2+ ions [FLNB mRNA and hypo-editing of the COPA mRNA [One of the best known examples of the importance of A-to-I editing in mRNA is the modification of the glutamate receptor subunit B (GluRB) precursor messenger RNA: CAG (Gln) → CIG (Arg) in exon 11. This site is modified by ADAR2 and is essential to ensure the impermeability of the glutamate receptor to Ca2+ ions . A defec2+ ions . The dys2+ ions . PatientOPA mRNA . FinallyA. Thaliana mitochondria [Inosine in mRNAs is known to modulate alternative splicing and stability, but it clearly also plays an essential role as an enhancer of near-cognate tRNA incorporation, ensuring the activity of some proteins . On the chondria . The conUnlike the Ψs found in rRNA, the reaction generating those found in mRNA is catalyzed by pseudo-uridine synthases, which are RNA-independent proteins ,125,126,In prokaryotes, several studies have described the ability of Ψ to alter base-pairing and induce misincorporation ,133,134.Given the high frequency of Ψ in mRNA and its role in near-cognate tRNA recognition, Ψ modifications probably make a major contribution to translation fidelity. A closer look at codon/anticodon base-pairing in the case of the misincorporation of Cys at a Tyr codon reveals a central mismatch between an A and a C. This unfavorable interaction is probably compensated for by the strong ability of Ψ to stabilize the codon/anticodon structure by stacking interactions. Indeed, Ψ is known to enhance RNA structure stability. Despite its ability to form a supplementary N1-hydrogen bond, Ψ has the same Watson-Crick base-pairing properties as U . 6A) modification involves the addition of a methyl group to the N atom linked to the C6 of adenosine. Chemical predictions of the impact of m6A on RNA–RNA base-pairing suggest a disruption of this interaction due to the methyl group [The N6-methyladenosine  is responsible for adding the methyl group. Once modified, the site can be recognized by reader proteins, most of which belong to the YTH-domain protein family (YTHDC and YTHDF), or eraser proteins, which are demethylases (such as FTO and ALKBH5). In humans, more than 12000 m00 mRNAs ,137. Abog region . m6A is  readers ,140. A h6A at the first or second position of the codon has been measured by quench flow techniques [6A at the middle position of the codon has a lesser effect on pairing for near-cognate than for cognate tRNAs [6A at the middle position. However, contrary to these findings for prokaryotic systems, mass spectrometry assays in eukaryotes (wheat germ and HEK293T) identified no miscoding effect of the m6A modification [6A on miscoding events.The impact of mchniques . This mote tRNAs . This dification ,144. Thefication . In the 6A is one of the most commonly studied RNA modifications because of its broad influence on RNA maturation and degradation, RNA-protein interactions and translation efficiency, implicating this modification in a number of different biological processes [6A levels have been implicated in the regulation of the expression of genes relating to cancer pathogenesis and development [mrocesses ,148,149.elopment .5C) is a cytosine with an additional methyl group on C5. Like m6A, m5C is a dynamic modification, with writer, reader and eraser proteins. NSUN2 and the Aly/REF export factor are the principal m5C mRNA writer and reader proteins, respectively [5C has been mapped on several transcriptomes in humans [NSUN2 and NSUN6 are well-known tRNA-modification enzymes, they also appear to modify mRNA. The number of m5C sites in mRNA has been estimated at about a thousand by bisulfite RNA sequencing [5C modifications, suggesting that it could play a role in the discrimination of endogenous and exogenous RNAs.5-methylcytosine  paves the way for the development of such therapeutic approaches [As discussed above, it is possible to target mRNA with an H/ACA snoRNA for the incorporation of a Ψ at a specific position. This approach could be used in genetic diseases caused by the presence of a premature termination codon (PTC). Proof-of-concept has been obtained through the demonstration that replacing the U of the stop codon with Ψ converts the stop codon into a sense codon . Indeed,proaches . We are With so many unanswered questions both in terms of molecular mechanisms and physiological consequences, the field of RNA modifications gains more and more interest. One of the current limitations is the difficulty to identify and quantify RNA modifications, especially in highly structured molecules such as tRNAs or rRNAs. Mass spectrometry approaches are extremely accurate, but require highly purified molecules and are hardly quantitative on a large scale. Deep-sequencing (NGS) approaches require either chemical modification of the RNA or immunoprecipitation with a specific antibody, with the associated problems of specificity . Direct


This complex is widely distributed on the membrane of various subcellular organelles, such as endosomes and lysosomes, and plays a critical role in cellular processes ranging from autophagy to protein trafficking and endocytosis. Variants in ATP6V0A1, the brain-enriched isoform in the V0 domain, have been recently associated with developmental delay and epilepsy in four individuals. Here, we identified 17 individuals from 14 unrelated families with both with new and previously characterized variants in this gene, representing the largest cohort to date. Five affected subjects with biallelic variants in this gene presented with a phenotype of early-onset progressive myoclonus epilepsy with ataxia, while 12 individuals carried de novo missense variants and showed severe developmental and epileptic encephalopathy. The R740Q mutation, which alone accounts for almost 50% of the mutations identified among our cases, leads to failure of lysosomal hydrolysis by directly impairing acidification of the endolysosomal compartment, causing autophagic dysfunction and severe developmental defect in Caenorhabditis elegans. Altogether, our findings further expand the neurological phenotype associated with variants in this gene and provide a direct link with endolysosomal acidification in the pathophysiology of ATP6V0A1-related conditions.The vacuolar H  de novo and biallelic variants in ATP6V0A1 gene affect the ability of the V-ATPase complex to translocate protons and acidify the endolysosomal compartment in neurons, causing a severe neurological phenotype ranging from developmental and epileptic encephalopathy to progressive myoclonus epilepsy.Bott et al. here reports that  ATP6V0A1 presenting with a phenotype of early-onset progressive myoclonus epilepsy (PME) and ataxia and 12 cases with de novo missense variants in the same gene, with severe developmental and epileptic encephalopathy (DEE), resulting from direct impairment of endolysosome acidification and failure of lysosomal functions.Here, we report 5 individuals from 2 unrelated families with compound heterozygous variants in Ethical approval was obtained from the ethics committee of the following institutes: University of Federico II , University of L'Aquila , G. Gaslini Institute , University of Exeter (UK), Nottingham University Hospital (UK), Salpêtrière Hospital (France), University of Toronto (Canada), University of Ottawa (Canada), St. Luke's Children's Hospital (USA), Floating Hospital for Children at Tufts Medical Center (USA), Gillette Children's Specialty Healthcare Children's Hospital (USA), Children’s Hospital of Philadelphia (USA), Peking University First Hospital, Beijing (China). Written consent for the study was obtained from patients or legal representatives according to the Declaration of Helsinki. When individuals were not contacted directly, de-identified phenotypic and genomic data were used. Patient or guardian consent was given for the publication of the patient's data and clinical information. Patient II.1 was enrolled in a research study aimed at finding the genetic cause of progressive myoclonus epilepsy; Patient III.1, VII.1-X.1 and XIV.1 were referred to GeneDx for clinical whole-exome sequencing for diagnosis of suspected Mendelian disorders as previously describedBlood samples were collected and DNA was extracted using standard methods from peripheral blood lymphocytes from the indicated individuals in http://broadinstitute.github.io/picard/ Accessed 21 October 2021). Data analysis was based on the autosomal recessive mode of inheritance. Variant calling and quality score recalibration were performed using GATK (http://www.broadinstitute.org/gatk/ Accessed 21 October 2021). Variants remaining after exome data analysis containing missing data were Sanger sequenced using the BigDye Terminator version 3.1 chemistry (Applied Biosystems), run on an ABI 3730xl analyzer and analysed using Sequencher software version 4.2 (Gene Codes Corporation). Fam. II-XIV: Details on sequencing, alignment, variant calling (inherited and de novo) and variant annotation have been described previously.Fam. I: Exome sequencing was performed as previously described.Bos TaurusHomology models of the subunit a  and c  belonging to the V0 domain of the human V-ATPase has been built by Robetta server,ATP6V0A1 cDNA was kindly provided by Michael Forgac. Point mutations corresponding to the gene variants identified in the present study were introduced using a QuikChange II site-directed mutagenesis kit (Agilent Technologies) according to the manufacturer’s instructions, and subsequently the constructs were cloned into the PiggyBac (PB) Transposon vector clone . For stable transfection, PB Transposon vector and PB Transposase vector  were transfected at a ratio of 9:1 into Neuro2a cells plated on 24-well plates (∼50 000 cells per well). One day after transfection, the cells were trypsinized and transferred as serial dilution to fresh tissue culture plates. Drug selection using 10 µg/ml puromycin started on day 3 and was continued for 2–3 weeks until the visible colonies appeared. In order to induce the transgene expression, 1 µg/ml doxycycline was added to the media starting 1 day before transfection.Human After fixation with 4% paraformaldehyde, slides were placed in blocking solution [10% normal goat serum and 0.3% Triton X-100 in phosphate-buffered saline (PBS)] for 45 min at room temperature. Primary antibody staining was done at 4°C overnight in PBS with 5% normal goat serum and 0.1% Triton X-100 , using LysoTracker fluorescent dye  and Cathepsin D antibody . The slides were then washed 3 times with PBS (0.1% Triton X-100 in PBS), incubated with secondary antibody  for 1 h at room temperature in the dark, and then washed 3 times before drying and adding Vectashield/4′,6-diamidino-2-phenylinodole stain (Vector Laboratories). Coverslips were mounted with Permount (Fisher Scientific). The cells were imaged and acquired using the PANNORAMIC 250 fluorescent microscope scanner (3DHISTECH). An average of 100 cells from 3 independent experiments per each condition were analysed by a blinded investigator.2 (50 000 cells). The cells were then washed 3× in DMEM and the samples were read in a CLARIOstar Plus spectrophotometer (BMG Labtech) with dual-excitation and dual-emission spectral peaks at 324/441 and 381/541 nm. The ratio of emission was then calculated for each sample as indicated.Quantification of lysosomal pH was determined using Dextran conjugated Lysosensor Yellow/Blue DND-160 . Wild-Type and R740 mutant Neruo2a cells were grown in serum starved conditions (DMEM with antibiotics) with 1 µg/ml doxycycline to ∼80% confluence. Cells were then trypsinized, harvested and aliquoted at 100 µl into a black 96-well microplate with 5 µM Lysosensor probe for 15 min at 37°C with 5% COWhole cell lysates were collected as previously described.Caenorhabditiselegans were maintained on solid nematode growth medium seeded with E. coli OP50 at 20°C using standard methods.unc-32(ox683[unc-32::gfp +loxP]) III].mcherry at the 5′ end of endogenous lgg-1, and the introduction of a missense mutation corresponding to the substitution of the essential arginine by a glutamine in UNC-32::GFP at position 804 (numbered according to the isoform UNC-32A) into the EG9591 strain, were performed using CRISPR/Cas9 genome editing and resulted in strains AM1219 lgg-1(rm17[lgg-1::mcherry]) II and AM1233 unc-32(rm20[unc-32(R804Q)::gfp +loxP]) III/hT2[bli-4(e937) let-?(q782) qIs48] .The insertion of dpy-10 to generate cn64 rollers as phenotypic marker. Successful edits were identified by PCR screening and verified by Sanger sequencing.Genome editing was performed as previously described.mcherry at the endogenous lgg-1 locus, we targeted the 5′ end of the first exon with the guide sequence 5′-CCTTCGAATCAAAATGAAGT-3′. The repair template was synthesized by PCR to generate a double-stranded DNA fragment consisting of mCherry amplified from pAP582 (Addgene) and homology overhangs for insertion at the ATG start site using primers 5′-TAACCTTCTCTTCACACTAACCTTCGAATCAAAATGGTCTCAAAGGGTGAAGAAGATAAC-3′ and 5′-CTTCTCAAAGTTGTTCTCCTCCTTGTAAGCCCACTTCTTATACAATTCATCCATGCC-3′. The lgg-1(rm17) allele was isolated in a dpy-10(+) background and the resulting strain was back-crossed three times to N2.For inserting unc-32(ox683) allele using the guide sequence 5′-CTGCTTCATACCTTCGTCTT-3′ and a single-stranded oligonucleotide containing the CGT > CAG change, a silent T > G mutation resulting in the PvuII restriction site for genotyping, and homology arms flanking the edit as repair template 5′-TCTTGGATGTGTGTCACATACTGCTTCATACCTTCagCTgTGGGCTCTTTCATTGGCTCATGCTCGTAAGTAAAG-3′. The resulting unc-32(rm20) allele was confirmed by sequencing and kept on the hT2 balancer for strain maintenance.For generating the R804Q substitution in UNC-32::GFP, we edited the lgg-1 was performed by feeding animals with E. coli strain HT115(DE3) containing the appropriate RNAi vectors obtained from the Ahringer library and using L4440 as the empty vector control.vha-4, vha-16 and vha-17), the animals were initially grown on L4440 and transferred to RNAi plates at L4 stage.RNAi-mediated knock-down of V-ATPase genes or Animals were immobilized in 50 mM sodium azide on 3% agarose pads and imaged using a Zeiss LSM800 confocal microscope with 10× or 20× objective and Zen imaging software. For quantification of LGG-1::mCherry fluorescence levels, maximum intensity projections were generated from Z stack images and fluorescence intensity was quantified by tracing either the nerve ring for UNC-32::GFP or whole animals for LGG-1::mCherry using ImageJ software (NIH).cdc-42. The primers used are listed in Age-synchronized populations of at least 100 gravid adults were collected and snap frozen in liquid nitrogen. RNA was extracted using TRIzol (Invitrogen) and purified with QIAGEN RNeasy MinElute columns as per manufacturers’ instructions.www.graphpad.com), using the tests indicated in the figure legends. A standard confidence interval of 95% was applied in all analyses. Displayed in the figure are the mean values of all technical replicates for each of the independent experiments (displayed as single data points). Error bars represent the standard error of the mean. P-values <0.05 were considered statistically significant.Statistical analysis was performed with Graph Pad Prism version 8 for Windows , that co-segregate with the clinical phenotype  with ataxia and mental retardation, of unknown origin.henotype . From anhenotype , Table 1n = 110)n = 13 462)de novo variants c.1652G>A (p.G551E) (Fam. IV.1) and c.2219G>A (p.R740Q) (Fam. V/VI.1) heterozygous variants in ATP6V0A1  enrolled in the Italian Undiagnosed Rare Diseases Network (IURDN)  (de novo mutations (DNMs) , with frequent seizures, which were refractory to treatment, and severe mental retardation after a period of apparently normal development, with delay or loss of psychomotor milestones  , Table 1lestones , Table 1lestones . Brain blestones  and 2B, ATP6V0A1 variants, we analysed the recently published predicted damaging DNMs (n = 45 221) from the largest cohort to date of exome sequence data from individuals with severe DD (n = 31 058).ATP6V0A1, c.2219G>A recurring in 7 patients (6 of which are included in the present study), and concluded that ATP6V0A1 variants are the most common DNMs among all known lysosomal disease (LD) and LSD-associated genes in this database (To provide an estimate of the frequency of database .Saccharomyces cerevisiae V-ATPase (ScV-ATPase)ATP6V0A1, is essential for proton transport into organelles.de novo mutations overall affect organelle acidification by hindering glutamate deprotonation (p.R740Q and p. R804H), deforming the architecture of the protein region devoted to protons exchange (p.G551E), or altering the conformation of the loop that contours the exit of the luminal channel (p.S477P)  .ATP6V0A1, we generated Neuro2a cell lines stably expressing wild type or c.2219G>A (p.R740Q) mutant human ATP6V0A1 and assessed acidification of the endolysosomal compartment using the LysoSensor radiometric probe, which undergoes a pH-dependent emission shift to longer wavelengths in acidic environments. Compared to wild-type, we observed a decrease in red-shifted fluorescence signal in mutant ATP6V0A1-expressing cells, indicative of impaired protonation  fused to mCherry red fluorescent protein using CRISPR/Cas9. Consistent with a role of the V-ATPase complex in the autophagic pathway, RNA interference (RNAi) targeting unc-32 or other V0 subunits  increased LGG-1::mCherry fluorescence levels relative to control    allele show developmental arrest at early larval stages   and lyso, imp-2) , and inc  was first identified by trio-based WES as a variant of uncertain significance in one proband with gait abnormalities, stereotypic hand movements and partial loss of hand skills.de novo variant (corresponding to NM_001130021.3: p. R740Q) and two with the following biallelic mutations: a p. A512P missense variant (corresponding to NM_001130021.3: p. A505P) in compound heterozygosity with a 50-kb deletion, and a p. N534D missense variant (corresponding to NM_001130021.3: p. N527D) in compound heterozygosity with a disruption of a splice donor site. All the de novo cases reported so far displayed a phenotype of developmental and epileptic encephalopathy (DEE), with developmental delay in the first months of life and drug-resistant focal and generalized tonic-clonic seizures. Head circumference 2 standard deviation below the average was present in 50% of the children with the p. R740Q variant and one individual with the p. R804H variant, suggesting an association between microcephaly and ATP6V0A1-related diseases. With 58 DNMs  in genes of the V-ATPase complex identified in exome sequence data from over 30 000 individuals with severe DD,ATP6V0A1 and ATP6V1A) out of 281, we propose that a V-ATPase-related disease should be considered in individuals presenting with mild-to-profound developmental delays and epilepsy, with or without microcephaly. Five individuals from 2 unrelated pedigrees in our cohort carry the biallelic E149Kfs*18 frameshift and R495W substitution and manifest an early onset, progressive myoclonus epilepsy (PME) and ataxia, therefore, expanding the neurological phenotypes associated with ATP6V0A1 variants beyond the more severe developmental and epileptic encephalopathy observed in the de novo cases. Myoclonic epilepsy was also a feature in one of the biallelic cases recently reported.de novo.Here, we report 17 subjects from 14 unrelated families carrying ATP6V0A1 gene encodes the a1 isoform of the membrane-bound V0 components of the V-ATPAse complex, which of the four a-subunits is the most neuronal enriched,The de novo variants identified here cluster on the transmembrane domains of the a1 subunit and are predicted by homology modelling studies to hinder glutamate deprotonation (p.R740Q and p. R804H), deform the architecture of the protein region devoted to protons exchange (p.G551E), or alter the conformation of the luminal channel (p.S477P), suggesting that perturbation of proton translocation is fundamental to the disease  and reduced expression of Notch target genes. These findings corroborate previous reports in Drosophila indicating that the V-ATPase-mediated acidification of the endolysosomal compartment is required for the activation of Notch in endosomesWe next proceeded to study the mechanism of pathogenicity of the R740Q substitution, which accounts for over 70% of all ATP6V0A1 ortholog in C. elegans and observed reduced protein clearance in lysosomes and altered regulation of several components of the autophagic machinery in neurons, expression of global autophagy failure. Homozygote nematodes carrying the corresponding R740Q mutation showed severe developmental arrest at early larval stage, with widespread accumulation of undigested proteins in the nerve ring. In accordance with recent findings of lysosomal dysfunction and increased neuronal cell death observed in brains of ATP6V0A1 mutant mice carrying the homozygote A512P change,de novo variants.To further establish a role of this isoform in lysosomal function, we knocked down the de novo and biallelic variants in ATP6V0A1 in patients affected by DEE and PME and link the mechanism of pathogenesis to disruption of the canonical protonation function of the V-ATPase complex. Considering the increasing identification of disease-causing variants in V-ATPase genes and the critical relevance of vacuolar pump-mediated regulation of intracellular pH in cellular homeostasis in health and disease,In conclusion, here we identified Brain Communications online.fcab245_Supplementary_DataClick here for additional data file.


During mRNA transcription, diverse RNA-binding proteins (RBPs) are recruited to RNA polymerase II (RNAP II) transcription machinery. These RBPs bind to distinct sites of nascent RNA to co-transcriptionally operate mRNA processing. Recent studies have revealed a close relationship between transcription and co-transcriptional RNA processing, where one affects the other’s activity, indicating an essential role of protein–RNA interactions for the fine-tuning of mRNA production. Owing to their limited amount in cells, the detection of protein–RNA interactions specifically assembled on the transcribing RNAP II machinery still remains challenging. Currently, cross-linking and immunoprecipitation (CLIP) has become a standard method to detect in vivo protein–RNA interactions, although it requires a large amount of input materials. Several improved methods, such as infrared-CLIP (irCLIP), enhanced CLIP (eCLIP), and target RNA immunoprecipitation (tRIP), have shown remarkable enhancements in the detection efficiency. Furthermore, the utilization of an RNA editing mechanism or proximity labeling strategy has achieved the detection of faint protein–RNA interactions in cells without depending on crosslinking. This review aims to explore various methods being developed to detect endogenous protein–RNA interaction sites and discusses how they may be applied to the analysis of co-transcriptional RNA processing. Following transcription by RNA polymerase II (RNAP II), nascent RNA undergoes processing events of a 7-methyl guanosine cap at the 5′ end (5′ capping), splicing of exons, and formation of the 3′ end by cleavage and polyadenylation, to produce mature mRNA . The speA recent study detected more than 1000 proteins, which are directly associated with RNA in human cells . HundredAs the characterization of physiological protein–RNA interactions is essential to understand how mRNA is transcribed and processed in cells, various methods have been developed to detect such transient and faint interactions, which has been reviewed in several articles ,14,15. TIt had long been difficult to obtain a transcriptome-wide map of direct protein–RNA interaction sites before the development of high-throughput sequencing technologies. Instead, in vitro identified binding motifs of RBPs were searched in a specific RNA sequence to presume protein–RNA interaction sites. The consensus binding motifs of RBPs were derived using several methods such as SELEX , RNAcompThe RNA immunoprecipitation (RIP) method and its variations have been developed to detect physiological protein–RNA interactions. In the primary RIP method, an RBP is immunoprecipitated from the cell lysates using a specific antibody, preserving the protein–RNA complexes formed in cells as much as possible ,22. ThenTo specifically detect the in vivo direct protein–RNA interaction sites, the chemical crosslinking of the interactions was combined with the RIP method. The crosslinking of protein–RNA interactions enables the elimination of non-specifically remaining RNA and proteins from the immunoprecipitants by stringent washing of protein–RNA complexes with high-salt buffer and ionic detergents, as well as by gel purification. UV irradiation , formaldCurrently, UV irradiation of living cells is widely used to identify protein–RNA interactions, and it is referred to as the crosslinking and immunoprecipitation (CLIP) method . Owing tThe initial CLIP method employed cDNA cloning followed by Sanger sequencing to determine the identity of each isolated RNA . AlthougCurrently, the datasets of hundreds of CLIP-seq and its variations are available in public databases, including enhanced CLIPs (eCLIPs) of 150 RBPs in the Encyclopedia of DNA Elements (ENCODE) project . These aThe application of CLIP technology is not limited to the detection of RBP-binding sites in RNA. CLIP has been adopted to detect methyl adenosine 6 (m6A) modification sites ,49 as weDespite the advances in CLIP technology, the identification of protein–RNA interaction sites specifically assembled on transcribing RNAP II is still challenging, which is mainly because of the limited amount of nascent RNA associated with transcribing RNAP II machinery. The CLIP methodology requires a large amount of input materials, typically millions of cells, due to the loss of materials during multiple purification steps . InfrareWe recently reported the target RNA immunoprecipitation (tRIP) method , in whicThe high sensitivity of tRIP-seq enabled the identification of protein–RNA interaction sites assembled on RNAP II by serial IP of RNAP II–RNA–protein complexes  56]. Fo. Fo56]. Recently, a pulsed femtosecond UV to CLIP methodology  has been reported . CompareIn addition to the CLIP technology, other strategies that do not rely on crosslinking have been explored for the detection of protein–RNA interactions in vivo.A novel technique known as TRIBE (targets of RNA-binding proteins identified by editing) utilizes an RNA-editing mechanism to identify protein–RNA interactions in a small number of specific cells . This meQuite recently, a new method, STAMP (Surveying Targets by APOBEC Mediated Profiling), has been developed . For theProximity labeling (PL) is an efficient tool for elucidating the protein–protein interactome within a specific subcellular fraction. The genetic fusion of the PL enzymes, such as APEX , BioID , or TurbIn addition to the analysis of protein–protein networks, PL has been used to profile protein–RNA interactions. The combination of PL with crosslinking of protein–RNA interactions by UV (Proximity-CLIP)  or formaProtein–RNA interactions are essential for a wide range of cellular processes, and various approaches have been developed to identify the RBP binding sites in RNA. Among these, CLIP remains a standard method owing to its accuracy in detecting the genuine interaction sites in vivo. However, CLIP requires a large amount of input materials, making it difficult to analyze the protein–RNA interactions specific to co-transcriptional RNA processing. Several improved and specialized versions, including irCLIP, eCLIP, tRIP, and KIN-CLIP, have greatly enhanced the detection sensitivity of CLIP. tRIP has enabled the identification of the protein–RNA interactions specifically assembled on transcribing RNAP II by meta-gene analysis, although the distribution of the detected interaction sites was sparse at the individual gene level. Recently, other strategies that utilize RNA editing or PL mechanisms have been developed for the detection of protein–RNA interactions. These methods have their distinct advantages and disadvantages compared with CLIP . PL is a