DNA and RNA deformations play crucial roles in biological processes, such as DNA packaging and nucleic acid recognition by proteins. The relevant understanding is limited due to the challenge in the precise measurement of nucleic acid deformations and the complexity of nucleic acid interactions. We solve these two issues using experiments, simulations, and theory. Magnetic tweezers experiments provide an excellent opportunity to precisely measure DNA and RNA twist changes induced by salt, temperature change, and stretching. Surprisingly, our simulations and theory find that common deformation pathways drive DNA and RNA deformations induced by different stimuli. Furthermore, the common deformation pathways appear to be utilized by protein binding to reduce the energy cost of DNA and RNA deformations. Nucleic acid deformations play important roles in many biological processes. The physical understanding of nucleic acid deformation by environmental stimuli is limited due to the challenge in the precise measurement of RNA and DNA deformations and the complexity of interactions in RNA and DNA. Magnetic tweezers experiments provide an excellent opportunity to precisely measure DNA and RNA twist changes induced by environmental stimuli. In this work, we applied magnetic tweezers to measure double-stranded RNA twist changes induced by salt and temperature changes. We observed RNA unwinds when lowering salt concentration, or increasing temperature. Our molecular dynamics simulations revealed the mechanism: lowering salt concentration or increasing temperature enlarges RNA major groove width, which causes twist decrease through twist-groove coupling. Combining these results with previous results, we found some universality in RNA and DNA deformations induced by three different stimuli: salt change, temperature, and stretching force. For RNA, these stimuli first modify the major groove width, which is transduced into twist change through twist-groove coupling. For DNA, these stimuli first modify diameter, which is transduced into twist change through twist-diameter coupling. Twist-groove coupling and twist-diameter coupling appear to be utilized by protein binding to reduce DNA and RNA deformation energy cost upon protein binding. Double-stranded (ds) DNA and dsRNA deformations play crucial roles in many biological processes, such as DNA packaging –6, nucle7111423Nucleic acid deformations strongly affect nucleic acid–protein binding affinity because proteins often recognize nucleic acids through shape readout –36. UponAn intriguing property of nucleic acid deformations is that many structural parameters of nucleic acids are correlated, which means that the variation of one structural parameter causes the variation of another one. For instance, stretching DNA leads to overtwisting , 37, whi38While nucleic acid deformations are biologically important, the relevant understanding is limited because nucleic acid deformations are usually on very short lengths and the precise measurement of deformations is challenging. Some researchers used the DNA structures in the Protein Data Bank (PDB) to analyze DNA deformations induced by protein binding, while these DNA structures were precisely resolved by X-ray diffraction . HoweverIn this work, we employed magnetic tweezers (MT) experiments to precisely measure RNA twist changes induced by salt and temperature changes. MT experiments provide an excellent opportunity to precisely measure DNA or RNA twist changes because even small twist changes can accumulate along a long DNA or RNA molecule and cause a large rotation of the DNA or RNA end A, which 2239Our work aims to reveal the common deformation pathways in eight different phenomena: RNA and DNA deformations induced by salt, temperature change, stretching force, and protein binding. Among these eight phenomena, RNA deformations induced by salt and temperature changes are interesting results from our experiments and simulations. DNA and RNA deformations induced by protein binding are analyses of existing structures of protein–RNA/DNA complexes. RNA deformations by stretching force , 25, 38 csalt /Nbp, where Nbp = 13.6 × 103 is the number of base pairs. For convenience, we treated 1 M as the reference salt concentration, i.e., the RNA twist change Δωexp = 0 at csalt = 1 M.We used MT experiments to measure the RNA twist changes with the salt concentration, csalt A 16). A. Acsalt n curves B. We detnt again C and D. csalt slightly modifies the refractive index of the buffer, which slightly affects the measurement of RNA extension. As described above, determining salt-induced twist changes needs just the peak locations of the curves in SI Appendix, section S2).In the above measurement, the change in csalt at the temperature of T = 295 K. With the decreasing of csalt, Δωexp decreases steadily for all five monovalent ions. The salt-induced RNA twist changes are similar for all five ions, suggesting that the twist changes may be mainly caused by electrostatic screening.In  cations . They poΔω to zero at 1 M for all ions in order to observe the common trend. In addition, we shifted Δω because we did not measure the absolute RNA twist but measured the twist change in an RNA molecule when varying csalt. To obtain the RNA twist change induced by switching the ion type, we carried out a set of additional experiments where we measured the twist change in an RNA molecule when switching the ion type at a fixed csalt. We find that for a given csalt between 0.05 M and 1 M, RNA twist roughly increases as SI Appendix, section S3).In SPSDOUBLEDOLLAR > csalt curves . We did not observe a clear trend when varying the GC content. The sequence effect may be caused by different nucleic acid mechanical properties at different types of base pairs or base-pair steps .We also measured salt-induced RNA twist changes for two additional RNA sequences. In total, three RNA sequences were used and have GC contents of 36%, 43%, and 57%, respectively, while the data in ir steps . For exair steps . A similT = 295 K. The sequence is CGACU CUACG GAAGG GCAUC UGCGC, which contains nine dinucleotide steps  simulations of 25-bp RNA at different concentrations of NaCl, KCl, and RbCl at de steps . For eacsoftware  with OL3software . The trasoftware . Only thSI Appendix, section S14). We hope such an attempt of reparameterization can help future refinement of the relevant force fields.As shown by the solid lines in z et al. , we manucsalt strengthens electrostatic repulsion between phosphate groups and hence widens the major grooves, which is transduced to the twist decrease through the twist-groove coupling.Semiquantitative reproduction of salt-induced RNA twist changes by MD simulations suggests that our simulations should capture the key features during RNA deformations. Then, we analyzed the structural changes of RNA in MD simulations and eventually deciphered the mechanism of the twist changes: The decrease of ω and the major groove width, G:In the following parts, we first elaborate the twist-groove coupling in RNA and then derive the salt-induced RNA twist changes using this coupling. The twist-groove coupling can be extracted from a two-dimensional potential of mean force (PMF) over the twist, kB is the Boltzmann constant, T is the temperature, and Ω is the relative density of RNA conformations at a given ω and G.where ω0 = 32.15o and G0 = 0.52 nm. SI Appendix, section S6 for the details of the calculation of Ω. From the PMF, a negative coupling between ω and G is ascertained by the blue valley in Left Top to the Right Bottom. The twist-groove coupling constant equation , 25, 40:whereas here G, the PMF can be approximated by a harmonic potential, and the location of the potential minimum shifts toward a smaller ω with the increase of G. The 2, in agreement with experimental and simulation results . Meanwhile, SI Appendix, Table S3 in section S7). We find that all three coefficients are insensitive to the salt concentration or species .The fitting quality can be seen in  results , 38  electrostatic repulsion and is estimated using the Debye screening formula:After obtaining the twist-groove coupling constant, we move to derive the twist changes based on this coupling constant. The derivation is based on the idea that the decrease in r is the P–P distance, e = 1.6 × 10−19 C is the unit charge, ϵ0 is the vacuum permittivity, ϵr ≈ 78.4 is the dielectric constant of water, and r. For simplicity, we set r = 0.6 nm.where fG is transduced to Δω, we add a term in Eq. To derive how ΔfGsalt ≈ fGsalt − fGsalt(1M). ΔfGsalt is the change in fGsalt when csalt deviates from 1 M. Minimizing P with respect to Δω and ΔG yieldsHere, α is added to ΔfGsalt:As shown in α = 1.8 yields an excellent agreement between Eq. r = 0.6 nm in the above calculation. Using other values of r also leads to good agreements with simulation results of Δω after adjusting the rescale factor . We note that in Eq. r should depend on csalt, but considering such dependence dramatically complicates the calculation. Furthermore, rigorous calculations of fGsalt needs to consider much more pairs of P–P repulsions . The above theoretical model does not consider different ion distributions (different screening abilities) for different ion types , which is an important topic for future studies.In this subsection, we present a simple theoretical model based on the mechanism that salt-induced RNA twist change is mediated by the variation of major groove width. This mechanism is supported by ion distribution around RNA: Cations strongly prefer to accommodate in RNA major grooves, as observed by a recent simulation study by Cruz-León and Schwierz . The strΔfGsalt by ΔfGT, the force of enlarging major groove width induced by temperature change. The calculation of fGT is based on the following idea. The equilibrium major groove width, G, results from the competition of conformational entropy S(G), which tends to increase G, and the sum of interaction energies U(G), which tends to decrease G. The dependence of conformational entropy on G can be extracted from the PMFs of our MD simulations at different temperatures. The PMF can be expressed as F(G)=U(G)−T × S(G). After obtaining multiple sets of F(G) at different temperatures from simulations, we can solve U(G) and S(G) based on the approximation that U(G) and S(G) are insensitive to T. See the calculation details in SI Appendix, section S15. S(G) calculated using this method. From this result, we extract a coefficient, kSG, for the dependence of entropy on G:We also measured RNA twist change with temperature A. We revkSG indicates that the conformational entropy increases with G, which supports our argument above: The conformational entropy tends to increase G. With the coefficient kSG, we obtain the force of enlarging major groove width induced by temperature change:The positive value of Substituting the above equation into Eq. The above coefficient agrees with our experimental result, −0.014 ° /(°C ⋅ bp), as shown in It is interesting to find out the molecular mechanism for the twist-groove coupling. To establish a relationship between the major groove width and the twist, we make the following approximation. As shown in h is the vertical distance between two adjacent base pairs , D = 1.95 nm is RNA diameter, θ = 15.5 ∼ 17.5° is the angle between the base-pair plane and the horizontal plane (or the inclination angle), β ≈ 140° is the azimuthal angle between two strands in RNA and ω is the twist angle per base-pair step. Eq. ω to G. The prediction of Eq. where Inspired by the above results as well as the results in previous studies , 38, 40,A natural question arises from the above results is that why RNA deformations are mediated by major groove width variation and twist-groove coupling, but DNA deformations are mediated by diameter variation and twist-diameter coupling. A simple answer is that RNA and DNA choose the deformation pathways with the lowest energy cost for themselves , 38. Thekω = 0.18 ± 0.02 kBT/deg2, kD = 263 ± 39 kBT/nm2, kωD = 4.5 ± 0.8 kBT/(deg ⋅ nm), which were obtained from our previous study  (H. sapiens TRBP (PDB: 3adl)  ADAR2 dsRBD2 (PDB: 2l2k) , ii) ADAB: 2nue) , v) H. sB: 3adl) , and vi)B: 3adl) . The strΔD and Δω are along the direction of twist-diameter coupling. For these three complexes, proteins wrap around DNA. In addition, ΔD is negative, and Δω is positive. Accordingly, we speculate that protein binding may compress DNA diameter, which is transduced into twist increase through twist-diameter coupling.We carried out similar analysis for six DNA–protein complexes as shown in In summary, we precisely measured RNA twist changes with salt and temperature by leveraging the accumulation of small twist change along an RNA chain. The precise experimental results of RNA twist changes (precision ∼ 0.01 ° /bp) provide a unique window to probe nucleic acid deformation pathways. Combining the experiments with simulations and theoretical analysis, we revealed and quantified RNA twist-groove coupling in RNA, which is the common driving force for salt, temperature, and stretch-induced RNA twist changes. Similarly, DNA twist-diameter coupling is the common driving force for salt, temperature, and stretch-induced DNA twist changes. Very intriguingly, we find that RNA twist-groove coupling and DNA twist-diameter coupling appear to take effect in nucleic acid–protein binding—that is, nucleic acid deformations induced by protein binding are along the direction of RNA twist-groove coupling or DNA twist-diameter coupling. Identifying the common deformation pathway, i.e., RNA twist-groove coupling or DNA twist-diameter coupling, should provide a simplified and quantitative view of nucleic acid deformations on many occasions.While this work focuses on the commonality of RNA and DNA deformations induced by different stimuli, the specificity, such as ion-type effect and sequence effect, also plays crucial roles in RNA and DNA deformations, which are important topics for further investigation. The ion-type effect on RNA twist is strongly linked to the ion binding and distribution. Accordingly, the experimental measurement of salt-induced RNA twist, combined with MD simulations, provides a unique window to probe ion distribution around RNA and to refine MD force fields, just as what has been done for DNA by Schwierz and coworkers recently . The seqSI Appendix, section S1). We attached the digoxigenin end of RNA/DNA to the inner bottom surface of the flow cell which was coated with antidigoxigenin (Roche). We attached the biotin end of RNA/DNA to a superparamagnetic microbead (DynabeadsTM MyOneTM Streptavidin C1). We used a pair of separated NdFeB magnets to apply constant forces to the magnetic bead and stretch the RNA/DNA. We rotated the RNA/DNA by rotating the magnets using a rotation motor . We used a high-brightness collimated LED  to illuminate the flow cell through the gap between the magnets. We captured the images with a CCD camera  and analyzed the 3-D position of the beads based on the diffraction pattern of the beads. We used an objective heater (Bioptechs) to wrap around the oil objective to control the temperature in the flow cell.We built the magnetic tweezers on an inverted microscope  equipped with a n groups , 56 Click here for additional data file.


The development of RNA-targeting CRISPR-Cas systems represents a major step forward in the field of gene editing and regulation. RNA editing presents a viable alternative to genome editing in certain scenarios as it offers a reversible and manageable approach, reducing the likelihood of runaway mutant variants. One of the most promising applications is in the treatment of genetic disorders caused by mutations in RNA molecules. In this study, we investigate a previously undescribed Cas12g nuclease which was found in metagenomes from promising thermophilic microbial communities during the expedition to the Republic of North Ossetia—Alania in 2020. The method outlined in this study can be applied to other Cas orthologs and variants, leading to a better understanding of the CRISPR-Cas system and its enzymatic activities. The cis-cleavage activity of the new type V-G Cas effector was indicated by in vitro RNA cleavage experiments. While CRISPR-Cas systems are known for their high specificity, there is still a risk of unintended cleavage of nontargeted RNA molecules. Ultimately, the search for new genome editing tools and the study of their properties will remove barriers to research in this area. With continued research and development, we may be able to unlock their full potential. The CRISPR array is composed of direct repeats separated by spacers, which are fragments of non-native viral or plasmid DNA. This enables cells to effectively identify and eliminate previously encountered pathogens [The CRISPR-Cas system is a defense mechanism of the adaptive immune system, which is widespread among archaea and bacteria that protect them against viruses and other foreign genetic material. It uses Cas proteins to identify and cut specific nucleic acid sequences that match the guide RNA ,2,3,4,5.athogens . Genome The CRISPR-Cas system is a widely utilized tool in various scientific fields, including molecular biology, medicine, and biotechnology. Its impact on these industries is profound, as it enables precise genome editing and has numerous applications in both experimental and applied research . CRISPR-The CRISPR-Cas RNA-targeting systems enable specific targeting of nucleic acid fragments, including RNA molecules, and can cleave RNA upon target detection. One of the most promising applications of RNA-targeting CRISPR-Cas systems is in the treatment of genetic disorders caused by mutations in RNA molecules. For example, Huntington’s disease is caused by the accumulation of a mutant form of the huntingtin protein, which is encoded by an RNA molecule . MoreoveDespite the vast knowledge of nucleases, there is still much to discover about their diversity and functions. Metagenomics has emerged as a powerful tool to explore microbial diversity and uncover new genes and enzymes. In particular, metagenomics has been used to identify novel nucleases from diverse habitats. The search for new nucleases in metagenomics data is important for several reasons. First, it can lead to the discovery of enzymes with unique properties, such as higher specificity or activity under extreme conditions. Second, the discovery of new nucleases can contribute to the development of new strategies for combating infectious diseases and antibiotic resistance.Scientists all over the world are primarily focused on the research and development of genome editing, particularly with the utilization of CRISPR-Cas tools. The study of novel nucleases continues to be a major pursuit in molecular biology, as a single tool that can be applied in all areas has not yet been discovered. One such area of focus is the identification and examination of new subtypes of class 2 systems, specifically type V systems, in order to expand the CRISPR-Cas toolbox. In this study, we investigate a previously undescribed Cas12g nuclease, which was found in metagenomes from promising thermophilic microbial communities during the expedition to the Republic of North Ossetia—Alania in 2020. The method outlined in this study can be applied to other Cas orthologs and variants, leading to a better understanding of the CRISPR Cas system and its activities.The sequence analysis showed that the Cas12g protein belongs to the CRISPR-Cas type V superfamily of enzymes that contain a RuvC nuclease domain that is responsible for RNA-guided cleavage. This recently discovered endonuclease displays collateral RNase and single-strand DNase activities upon activation by target molecular RNA, similar to Cas12a and Cas13 nucleases. Its bilobed architecture consists of a recognition lobe (REC) and a nuclease lobe (NUC) ,26,27,28Terriglobia; phylogenetic analysis shows that the evolutionary nearest homologs belong to members of Terriglobia, Planctomycetota, and several candidate divisions  with one of the ten repeats containing 1 bp mutation -tag. Protein purification was carried out by metal chelate chromatography and gel filtration  is a rapid and sensitive method to detect protein–nucleic acid interactions ,35,36. MPrevious studies have shown that Cas12g is capable of cis-cleavage (on-target cleavage of target molecule) and trans-cleavage  activities ,22,29. TTo confirm that Cas12g is also active on single-stranded DNA, three replicates were carried out in the presence of a DNA probe labeled with a fluorophore and a quencher at its 5′ and 3′ ends, respectively . The rap® Ultra™ II DNA Library Prep Kit  according to the manufacturer’s instructions. DNA libraries were sequenced on NovaSeq 6000  using the NovaSeq 6000 S2 Reagent Kit (300 cycles) . The quality of sequencing reads was assessed with FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (accessed on 19 June 2023)). Low-quality regions (trimq = 18), adapter sequences, and poly-G regions of reads were trimmed off using BBDuk ver. 38.90 (https://sourceforge.net/projects/bbmap/ (accessed on 19 June 2023)). Reads were assembled into contigs using SPAdes [−³. The secondary RNA structure of the found regions was predicted using the RNAfold web server [−6. The search for homological spacers and DR was conducted using NCBI blastn [The search of the gene coding for Cas protein was performed in metagenome assemblies of thermophilic microbial communities from Karmadon gorge hot springs, North Ossetia (Russia). Sediments and microbial mats were collected into plastic tubes filled with RNAlater  and kept at 4 °C. DNA was extracted using the Qiagen PowerLyzer PowerSoil kit  according to the manufacturer’s instructions without any modifications, as was reported previously . DNA seqg SPAdes  ver. 3.1g SPAdes  ver. 1.2g SPAdes . Regionsg SPAdes  in blastb server . Metagenb server  with defb server . When cob server  with an I blastn  with an I blastn  with defThe prediction of the 3D structure of Cas12g was performed using AlphaFold ,47. The The Cas12g homolog was discovered using NCBI BLAST  with defE. coli Top10. For protein expression, E. coli Rosetta (DE3) was used. The E. coli strains were routinely cultured at 37 °C and 220 rpm in Luria Bertani medium (LB). Plasmids were maintained with kanamycin (50 mg/mL) and/or chloramphenicol (35 mg/mL), as needed. Liquid media were supplemented with IPTG as specified.The bacterial strain used for the cloning and propagation of plasmids in the current study is ® Plasmid Miniprep Kit (NEB). DNA gel extraction and purification were performed with the QIAquick Gel Extraction Kit . Sequencing of the resulting DNA constructs was performed by the Sanger method . All the sequences are shown in the All oligonucleotides were designed in SnapGene software and ordered from Lumiprobe (Russia). All enzymes were purchased from (NEB) and used according to the manufacturer’s protocols, unless otherwise specified. The isolation of plasmids was performed with the MonarchE. coli cells were transformed with a ligase mix and incubated on LB agar plates supplemented with kanamycin. The constructed plasmid was extracted with the Monarch® Plasmid Miniprep Kit according to protocol and confirmed by Sanger sequencing.The Cas12g encoding gene was PCR-amplified using Q5 High-Fidelity 2X Master Mix and primers containing NotI and NdeI restriction sites from 4135 specimens of the extracted environmental DNA . The ampThe 8N randomized PAM plasmid library was constructed by analogy with the one we previously described in . BrieflyThe plasmid encoding the template for gRNA synthesis was obtained by sequentially incorporating fragments into the pUC119 scaffold. Initially, two oligonucleotides containing the tracrRNA and T7 RNAP promoter sequences were annealed, and PCR was extended to produce a blunt-ended product for further ligation into HincII-digested pUC119. Then, a BbsI/EcoRI-annealed fragment containing a direct repeat sequence and a spacer was inserted into the resulting construct. The sequence of the resulting plasmid was confirmed by Sanger sequencing.6-tagged Cas12g protein (the sequence is shown in E. coli Rosetta (DE3) cells transformed with appropriate plasmids. A total of 0.4 L of LB supplemented with 34 μg/mL and 100 μg/mL kanamycin was inoculated with cells from freshly transformed cells. The E. coli cells were grown at 37 °C until the OD600 reached 0.7. The protein expression was then induced by the addition of 0.3 mM IPTG. The cells were further cultured for 20 h at 18 °C. Cells were harvested by centrifugation and resuspended in buffer A ) and then disrupted by sonication Branson Ultra. Cleared lysates were obtained by centrifugation at 28,000× g for 30 min at 4 °C in order to clarify the lysate and applied onto a 1 mL chelating Ni-NTA HisTrap HP  equilibrated with buffer B . The column was washed with 10 mL buffer B, and the protein was eluted with buffer E . Protein fractions were pooled and transferred to the final buffer . Protein fractions during protein isolation were run on 12% denaturing PAGE, followed by Coomassie G-250 staining. The protein concentration was determined by the Qubit protein assay  and stored at −80 °C until use.The C-terminally HisMseI digestion leaves a 5′-overhanging end suitable for in vitro transcription. Guide RNA synthesis was obtained with the HiScribe T7 High Yield RNA Synthesis Kit. The reaction mix consisted of 1x reaction buffer, 1 μg of DNA template, rNTP mix with a final concentration of 10 mM each, T7 RNA Polymerase Mix, and 1 μL of RNasine and nuclease-free water to a final volume of 40 μL. The reaction was incubated at 37 °C overnight. To remove template DNA, the resulting mixture was incubated with DNase I in 1xDNaseI buffer for 30 min at 37 °C. RNA extraction was performed with the TRIZOL-chloroform method and ethanol precipitation. Finally, the gRNA pellet was dissolved in RNase-free water. The obtained RNAs were confirmed by 8% UREA-TBE (8M urea) polyacrylamide gel electrophoresis stained with EtBr. The RNA concentration was measured on Qubit 3.0 using a Qubit RNA HS Assay Kit .The DNA template for sgRNA transcription containing a T7 RNAP promoter was obtained by PCR amplification with M13 primers. The PCR fragment was run on agarose gel and then gel-purified. The resulting PCR fragment was cut with the MseI restriction enzyme and purified prior to transcription. 2, 50 mM NaCl, 1 mM DTT, pH 7.5). Reaction products were run on 1% agarose gel for 4 h to check the combining efficiency, and electrophoresis was performed in a 1 × TBE buffer. Gels were imaged with the Gel Doc EZ System . Bands were quantified using ImageLab software on the assumption of the percentage of bend intensity.Binding assays were performed by incubating 0, 0.2, 0.5, 1.0, 2.0, 3.0, and 4.0 µg fresh working stock dilutions of Cas12g with 1 µg of gRNA for 30 min  at 37 °C in an equilibration reaction buffer  at 37 °C for 15 min. The pre-assembled Cas12g–crRNA complex was mixed with the target RNA (at 1:3:30 target/Cas12g/gRNA ratio) and then incubated at 37 °C for 60 min in 1xNebuffer 2. The reaction was stopped by the addition of Proteinase K (40 ng). The reaction products were incubated at 95 °C for 5 min with RNA loading dye buffer for denaturing and then fractionated by electrophoresis using 10% TBE-Urea-PAGE gel and analyzed on the Gel Doc EZ System (Bio-Rad). In vitro cleavage experiments were performed at least three times.The ssDNA target labeled at the 5’ end with the ROX fluorophore was used to determine the collateral activity of the nuclease of nontarget ssDNA. The pre-assembled Cas12g–sgRNA complex (1:2 molar ratio) was mixed with the target RNA. The final concentration of labeled substrate was 100nM. Target cleavage assays were set up in the optimized cleavage buffer  at 37 °C for 30 min. Reactions were first treated with an RNase cocktail with incubation at 37 °C for 15 min. Next, they were treated with Proteinase K and incubated at 37 °C for 15 min. To detect ssDNA cleavage products, the reactions were analyzed with a Varioskan LUX multimode microplate reader (ThermoFisher). Excitation filter: 575 nm; emission filter: 602 nm.The development of RNA-targeting CRISPR-Cas systems has opened up a promising avenue for advancing research and therapeutic applications. With the ability to target RNA, researchers can now manipulate gene expression at the post-transcriptional level, allowing for greater precision in gene editing and regulation . Cas12g,Although CRISPR-Cas12g systems are currently under extensive research, with Cryo-EM structures already obtained and the substrate cleavage mechanism elucidated, along with potential methods for repurposing Cas12g, there are still some challenges to overcome before RNA-targeting CRISPR-Cas systems can be widely adopted. One of the main challenges is off-target activity. While CRISPR-Cas systems are known for their high specificity, there is still a risk of unintended cleavage of nontargeted RNA molecules. This can lead to unwanted side effects and potentially harmful consequences. Researchers are currently working on improving the specificity of RNA-targeting CRISPR-Cas systems by optimizing the guide RNA design and delivery methods.Delivery is another issue that needs to be addressed. RNA-targeting CRISPR-Cas systems require the delivery of both the Cas protein and the guide RNA into the target cells, so the same is true for all Cas systems. This can be challenging, especially for certain cell types or tissues. Researchers are exploring different delivery methods, such as viral vectors or lipid nanoparticles, to improve the efficiency and specificity of RNA-targeting CRISPR-Cas systems. Despite these challenges, the potential clinical applications of RNA-targeting CRISPR-Cas systems are vast.The multifaceted nature of Cas12g, which possesses both collateral RNase and single-stranded DNase activities, makes it an ideal tool for advancing biotechnology and biomedical research. The methods outlined in this study can be applied to other Cas orthologs and variants, leading to a better understanding of the CRISPR-Cas system and its enzymatic activities. Continued development in this field will undoubtedly lead to advancements in both research and therapeutic applications. Ultimately, the search for new genome editing tools and the study of their properties will remove barriers to research in this field, leading to new discoveries and innovations in biotechnology and medicine. RNA-targeting CRISPR-Cas systems have the potential to revolutionize the way we treat genetic disorders and infectious diseases, and with continued research and development, we may be able to unlock their full potential.


The total amount of RNA in a cell is 5 to 10 times greater than that of DNA. As elucidated by the “Central Dogma” principle, RNA serves as a bridge to facilitate the important translation process of converting genetic information from DNA into protein. Apart from messenger RNAs that encode proteins, non-coding RNAs constitute 90% of RNA molecules in cells, exerting crucial regulatory roles in the modulation of gene expression and participating significantly in diverse biological processes . OngoingThe Special Issue of the International Journal of Molecular Sciences entitled “Exploring the Possibility of RNA in Diverse Biological Processes” contains original articles and two comprehensive reviews. These publications under this issue encompass various aspects of RNA biology including gene transcription , RNA proIn women with preeclampsia, neutrophils infiltrate extensively into the maternal blood vessels, which triggers a sterile inflammatory response different from wound infection. Researchers have discovered that pregnancy neutrophils uniquely express protease-activated receptor 1 (PAR-1) ,10. ThisDrosophila melanogaster development. Specifically, Rok1 was found to be essential for the precise cellular localization of Rrp5 in the nucleolus. In the absence of Rok1 and Rrp5, the nucleolus underwent enlargement, resulting in significant disruptions to rRNA processing. The findings shed light on the vital functions of Rok1 and Rrp5 and provide insights into their implications for ribosome processing in multicellular eukaryotes [During the biogenesis of ribosomes in eukaryotes, numerous assembly factors (AFs) and ribosomal proteins come together with pre-ribosomal RNA (pre-rRNA) to form early ribosomal particles. These particles are subsequently transported from the nucleolus to the cytoplasm to form functional 80S ribosomes, which are responsible for protein synthesis . StudiesIn eukaryotes, the maturation of mRNA usually requires the addition of poly (A) tails to its 3′-end. A notable phenomenon observed in most eukaryotic genes is the presence of multiple potential poly (A) sites, leading to the generation of diverse transcript isoforms . This phRNA helicases are a vibrant group of RNA-binding proteins (RBPs) present in eukaryotes. They play crucial roles in various aspects of RNA metabolism, including RNA splicing, RNA export, and RNA turnover . Among tSarcoptes scabiei), an arthropod that infests the human epidermis, is responsible for skin diseases. While a few studies have examined certain RNAs and proteins of S. scabiei, no investigations have thus far compared the transcriptome characteristics across distinct developmental stages of this species or explored the associated regulatory molecular processes. Korhonen et al. conducted an initial transcriptomic sequencing of early and late-stage embryonic eggs, as well as adult females, of S. scabiei. Their investigation revealed a strong negative correlation between miRNAs and genes exhibiting decreased mRNA transcription, while a positive correlation was observed between miRNAs and genes displaying increased mRNA transcription during the developmental stages. These findings provide evidence for post-transcriptional regulation mediated by miRNAs during S. scabiei development. They also list six key sets of miRNAs, proposed to be essential regulators of differentiation and development, with potential roles in stress responses and environmental adaptation. These analyses can guide forthcoming laboratory examinations pertaining to the regulation of miRNAs (microRNAs) across all developmental phases of the scabies mite [The scabies mite (ies mite .Single-cell RNA sequencing (scRNA-Seq) has emerged as a prominent sequencing technology in recent years, offering new possibilities for investigating various facets of life science. By facilitating high-throughput and multidimensional analysis of individual cells, scRNA-Seq enables more accurate classification of cell subpopulations and in-depth exploration of cellular heterogeneity. This technology has proven invaluable in unraveling the complexity of biological systems and has found widespread application in diverse areas of research. In this review, Wang et al. provided a detailed account of the developmental trajectory and specific workflow of single-cell sequencing. The authors meticulously elucidate the intricate steps involved in this cutting-edge technology. Furthermore, they emphasize the wide-ranging applications of scRNA-Seq in recent research, with particular emphasis on its utility in investigating the tumor microenvironment. In addition, the article specifically highlights the pioneering applications and potential advancements of scRNA-Seq in the realm of traditional Chinese medicine (TCM) research. It delves into areas such as TCM syndrome differentiation studies, uncovering the mechanisms of action and efficacy of TCM, and elucidating the toxicological mechanisms associated with TCM usage. The authors also addressed crucial considerations for refining scRNA-Seq methodologies and techniques to effectively address existing challenges .The articles published within this Special Issue provide remarkable insights into diverse facets of RNA research. However, it is important to acknowledge that there exist numerous intriguing and noteworthy aspects of RNA research that have not been covered within our special issue. Currently, we would like to highlight several areas within the field of RNA research that merit attention and further exploration.Firstly, the advent of high-throughput sequencing technologies has led to the identification of a plethora of regulatory RNAs, such as HARRs  and circSecondly, noteworthy advancements have been made in the development of novel technologies that hold immense potential for advancing our understanding of RNA biology and unveiling new principles of RNA regulation. These include third-generation sequencing technologies ,18, spatThirdly, the remarkable achievement of developing mRNA vaccines in response to the COVID-19 pandemic has reinvigorated interest in RNA therapeutics . Moreove


As coral reef ecosystems experience unprecedented change, effective monitoring of reef features supports management, conservation, and intervention efforts. Omic techniques show promise in quantifying key components of reef ecosystems including dissolved metabolites and microorganisms that may serve as invisible sensors for reef ecosystem dynamics. Dissolved metabolites are released by reef organisms and transferred among microorganisms, acting as chemical currencies and contributing to nutrient cycling and signaling on reefs. Here, we applied four omic techniques  to waters overlying Florida's Coral Reef, as well as microbiome profiling on individual coral colonies from these reefs to understand how microbes and dissolved metabolites reflect biogeographical, benthic, and nutrient properties of this 500-km barrier reef. We show that the microbial and metabolite omic approaches each differentiated reef habitats based on geographic zone. Further, seawater microbiome profiling and targeted metabolomics were significantly related to more reef habitat characteristics, such as amount of hard and soft coral, compared to metagenomic sequencing and untargeted metabolomics. Across five coral species, microbiomes were also significantly related to reef zone, followed by species and disease status, suggesting that the geographic water circulation patterns in Florida also impact the microbiomes of reef builders. A combination of differential abundance and indicator species analyses revealed metabolite and microbial signatures of specific reef zones, which demonstrates the utility of these techniques to provide new insights into reef microbial and metabolite features that reflect broader ecosystem processes. Microorganisms and the dissolved metabolites they process are central to the functioning of ocean ecosystems. These “invisible” ocean features are poorly understood in biodiverse and productive coral reef ecosystems, where they contribute to nutrient cycling and signaling cues among reef organisms. This study demonstrates that reef water microbes and metabolites successfully distinguish reef habitats, including geographical, reef compositional, and environmental features, and together they provide novel insights into reef ecosystem characteristics. Microbes and dissolved metabolites offer a new means to examine reef features and have applications for conservation, monitoring, and restoration efforts in these changing ecosystems.Coral reefs, one of the most biodiverse and economically valuable ocean ecosystems, are dynamic habitats that are impacted worldwide by climate change and other human pressures. Coral reef ecosystems have responded positively and negatively to disturbances through time . In the Central to the success of reef ecosystems are the invisible microbial and chemical dynamics that play a major role in reef processes, such as settlement  and coraReef microorganisms and dissolved chemicals, or metabolites, are well-poised to serve as sensors of reef ecosystem dynamics , 18. TheDendrogyra cylindrus, in Florida . We also conducted microbiome profiling via amplicon sequencing of near-coral seawater and coral hosts. Our results demonstrate that microbes and metabolites successfully distinguish between individual reefs according to biogeochemical zones and that their combined use provides novel insights into reef ecosystem parameters that may benefit monitoring, conservation, and restoration activities in these important ecosystems.To better understand the metabolite and microbial landscape of FCR and the potential utility of these invisible sensors to reef ecosystem dynamics, we leveraged a cruise of opportunity on OceanX's M/V Prochlorococcus, Synechococcus, picoeukaryotes, and heterotrophic microbes [unpigmented bacteria and archaea]), from reef depth waters  from within 0.5 m of the reef benthos for both targeted and untargeted metabolome analyses  approach yielded 43,118 ± 6,834 sequences per sample and 468 total amplicon sequence variants , with 1Analysis of seawater omic data sets  via ordinations revealed significant clustering of all data types according to biogeographic reef zone . TOC, heterotrophic microbes, and Synechococcus explained changes in the microbiome as well as in the targeted and negative mode untargeted metabolome, with heterotrophic microbial abundances explaining the most variation   was distinctly clustered from zone 1 to zone 7 in seawater taxonomic and functional microbiomes  and taxonomic microbiomes  Fig. . Unlike P < 0.00192; Fig. Prochlorococcus had a parabolic distribution, while Synechococcus and picoeukaryote abundances were higher in Dry Tortugas and then increased from the Marquesas zone 7 to zone 1   metabolites. Two of the 39 targeted metabolites in reef seawater changed across reef zones: 5′-methylthioadenosine (MTA) and taurocholic acid . Some of these genes were involved in biosynthetic pathways unique to zone 8, including arginine, cysteine, folate, glutamine, isoprenoid, serine, and ubiquinone biosynthesis. Additionally, genes from two types of ATP synthases (FoF1 and A/V) and 66 genes with unknown pathways were zone 8 indicators  that were either apparently healthy or showing active SCTLD lesions, and this resulted in 116,942 ± 59,302 sequences per sample and a total of 3,020 ASVs after filtering . We collected samples from five coral species  significantly increased northeast along FCR, suggesting the northern region may be more heterotrophic, or the types of autotrophs could be shifting to different phytoplankton groups. Additionally, high TOC concentrations and heterotrophic microbial abundances have been previously documented on Floridian reefs . Th. ThProchan reefs  and was an reefs . Interesan reefs . At the l growth  and nutrTOC significantly changed across FCR, but TOC is a single value that does not capture the complex dynamics of thousands of low-molecular-weight dissolved and particulate compounds. After using both targeted and untargeted approaches, we found that dissolved targeted metabolites related well to the benthic and biogeochemical habitats, while the dissolved untargeted metabolome (in both positive and negative ion modes) significantly related to a few measured biogeochemical parameters. Within the untargeted metabolome (positive and negative ion modes), 56 total metabolites shifted across reef zones, in patterns that varied broadly from the concentration of TOC. Two metabolites from the targeted metabolomic analysis, taurocholic acid and MTA, changed significantly across the zones in FCR. Taurocholic acid is a bile salt, which is released and used as an olfactory cue by fishes, and the varied concentrations may reflect differences in fish communities , though Paramoritella  is more cost-effective compared to shotgun metagenomic sequencing and is even adaptable to in-the-field use, though at the loss of potentially useful functional information , 75. RegIn conclusion, this novel omic data set of reef microorganisms and metabolites enhances our understanding of the chemical and microbial habitat within FCR. Further, it provides insights into specific compounds (e.g. MTA and taurocholic acid) and microbial indicators for focus in follow-up experimental studies to better understand the dynamics of these indicators within the reef habitat. Outside of experimental work, continued investigations of reef microorganisms and metabolites are needed. In particular, those in a time-series context that link microbial and metabolite patterns to habitat characteristics or external stressors will help elucidate the mechanisms behind patterns we observed and how these features may contribute to reef decline or growth. For example, currently (summer 2023) FCR is experiencing unprecedented levels of seawater warming and coral bleaching. Follow-up omic studies could identify the nonvisible, ecological impacts of the predicted coral reef ecosystem mortality. While metabolomics and microbial analyses probe the smallest components of a reef, they also reflect larger habitat patterns in reef environments, warranting further inclusion of these techniques in studying Earth's most biodiverse ocean ecosystem.Alucia between 2019 June 5 and 2019 June 19 . Inorganic nutrient samples were frozen after 1.4 mL subsamples were removed and fixed with paraformaldehyde  to quantify cell abundances. Organic carbon and TN samples were acidified and kept at room temperature or 4°C until analysis.We sampled coral reef benthic environments during a research cruise aboard the M/V  19 Fig. . We targ 19 Fig. , 53, 76  19 Fig. . At 85 rAt 13 reefs, we collected triplicate 1.7 L seawater samples for metabolomic analysis (targeted and untargeted) via SCUBA. The seawater was prefiltered (0.1 µm) to remove microbial biomass and acidified before low-molecular-weight organic metabolites were concentrated using solid-phase extraction (SPE) cartridges. At 27 reefs (including the 13 sampled for metabolomics), we collected two 4 L benthic seawater samples. We filtered 2 L at a time using a 0.2 µm filter  or GF/F filter . Filters and SPE cartridges were frozen at −80°C for analysis at the Woods Hole Oceanographic Institution (WHOI).Colpophyllia natans, Dichocoenia stokesii, Montastraea cavernosa, Orbicella faveolata, and Pseudodiploria strigosa. The seawater was hand-filtered (0.2 µm), and all samples  were frozen at −80°C until analysis at WHOI. Further details are included in the On 11 reefs with active SCTLD, we collected coral tissue with 10-mL Luer Slip syringes and near-coral seawater with 60-mL Luer Lok syringes from separate apparently healthy and SCTLD-afflicted coral colonies. We targeted the following coral species: Photomosaics at 45 reefs were analyzed for benthic composition as described in Fox et al. . The numSPE cartridges were processed following the methods in Weber et al. . For untWe extracted DNA from 0.2 µm filters used for 1.7 L seawater collections and four control blank filters using PowerBiofilm kits  following manufacturer protocols. The resulting DNA was used as the template for both 16S rRNA gene sequencing of bacteria and archaea as well as shotgun sequencing. For 16S rRNA gene sequencing for the taxonomic microbiome, we followed methods previously reported  and sequTo expedite the turnaround time between sample collection and taxonomic microbiome results for disease diagnostics, we performed on-ship processing and 2 × 150 bp sequencing on the Illumina iSeq100 system for near-coral seawater samples from five reefs from 2019 June 9 to 2019 June 10. All remaining coral and near-coral seawater samples were processed at WHOI. On-ship and at-WHOI methods followed in-the-field microbiome preparation protocols described previously  and are Sequence reads from the Illumina MiSeq and iSeq runs were separately run through the DADA2 pipeline to generate ASVs (v1.18.0) . We remoShotgun sequencing on the Illumina NextSeq yielded 13,592,782 ± 3,357,010 paired-end sequence reads per reef seawater microbial community sample. Due to sequencing errors, six reefs were singulars, while all others had duplicate sequence samples. We quality filtered the sequence reads and coassembled them with MegaHit (v1.2.9) , as thisP-value to account for multiple comparisons   or 85 reefs  in FCR across eight zones. We used a Kruskal–Wallis test in R (v4.0.3) to compare changes across zones with a Bonferroni-corrected ons Fig. . We follustment) . To examustment) .Prochlorococcus, Synechococcus, picoeukaryotes, hard coral cover, algae cover, soft coral cover, sponge cover, and hard coral species richness) explained changes in metabolomes and microbiomes. dbRDAs were calculated for each data set with either gower (targeted metabolomes) or Bray–Curtis (other omic data sets) dissimilarities. Significance of individual environmental variables within the analysis was evaluated with an ANOVA using the parameter by = “terms”.A dbRDA was calculated to evaluate how geography (zone) and environmental conditions , followed by pairwise Wilcoxon rank sum tests between zones (FDR-adjusted P < 0.05). The 56 untargeted features were z-score standardized for visualization. Model II ordinary least squares linear regressions were used to relate average relative abundance of MTA source and sink genes in seawater metagenomes to dissolved concentration of MTA.To test for metabolites that changed across zones, sites in zones 2 and 3 as well as zones 5 and 6 were grouped to ensure each zone had more than one reef. Kruskal–Wallis or ANOVA tests were used to evaluate significantly changing metabolites across zones (Bonferroni-corrected A) over 0.6 and sensitivity (B) over 0.6 and had a P < 0.05. Indicator ASVs and functional genes were visualized with heat maps and summarized in To identify seawater taxa and functional microbiome indicators of FCR, we used the multilevel pattern analysis, multipatt function in the R package indicspecies (v1.7.12). Indicators were reported if they had a positive predictor value (Coral and near-coral seawater taxonomic microbiome beta diversity was calculated with Bray–Curtis dissimilarity and visualized with principal coordinates analysis. A PERMANOVA test was used to identify the influence of zone, disease, and coral species on microbiome composition. Apparently healthy coral microbiomes were subset from the larger data set for differential abundance analysis to test which ASVs significantly changed by zone and controlling for the effect of species using corncob . All stapgad287_Supplementary_DataClick here for additional data file.


The multimolecular assembly of three-dimensionally structured proteins forms their quaternary structures, some of which have high geometric symmetry. The size and complexity of protein quaternary structures often increase in a hierarchical manner, with simpler, smaller structures serving as units for larger quaternary structures. In this study, we exploited oligomerization of a ribozyme cyclic trimer to achieve larger ribozyme-based RNA assembly. By installing kissing loop (KL) interacting units to one-, two-, or three-unit RNA molecules in the ribozyme trimer, we constructed dimers, open-chain oligomers, and branched oligomers of ribozyme trimer units. One type of open-chain oligomer preferentially formed a closed tetramer containing 12 component RNAs to provide 12 ribozyme units. We also observed large assembly of ribozyme trimers, which reached 1000 nm in size. Hierarchical folding and assembly are characteristic features of biomacromolecules required to exhibit their functions in living systems. The defined tertiary structures of single polypeptide proteins are usually composed of smaller and simpler structural elements, such as α-helices and β-sheets. Secondary structural elements are then assembled into globular tertiary structures, which are required for biological functions. Some structured proteins further assemble to yield their quaternary structures, which enable sophisticated and complex functions impossible for their monomer subunits without assembly.Rifitia pachyptila is assembled from 24 globin subunits, which can be dissected into a pair of globin dodecamers . Th. ThTetra L RNAs) . Through L RNAs)  and alsoThis study was performed to develop ribozyme assemblies larger than the above trimer and tetramer in a stepwise manner. By mimicking the development of giant hemoglobin, we regarded the ribozyme trimers (L3/L7/L8 and L1/L1/L1) as unit oligomers corresponding to the globin tetramer unit in giant hemoglobin. To oligomerize the unit trimers, we introduced kissing loop (KL) interaction motifs  as oligoWe first designed a dimeric form of a closed L RNA trimer by introducing a KL interaction to one of three L RNA units in each trimer . The ste2+, homodimerization of Y3h RNA was experimentally confirmed by an electrophoretic mobility shift assay (EMSA)  B, lane 5y (EMSA) B, lane 6 RNA  interaction, we performed AFM measurement of samples containing Y3h, L7, and L8 RNAs C. In the2+, each RNA component  was nearly inactive , distinct catalytic activity was observed with a reaction rate of 0.030 min−1 (−1) was similar to that with L3/L7/L8 (0.030 min−1)  D, suggesBased on the observation that the introduction of a single homo-KL motif element for homo-KL (h:h) interaction to the L3/L7/L8 ribozyme trimer (Y3h/L7/L8) resulted in its homodimerization, we then introduced the homo-KL (h) motif element into two of three component L RNAs. We prepared Y7h RNA to form a unit trimer (Y3h/Y7h/L8) bearing two homo-KL elements in the unit A. The Y3−1), however, was 1.36-fold lower than that of the parent L3/L7/L8 trimer (0.030 min−1).In EMSA, RNA samples containing a set of RNAs  were stuck in the sample wells D. VariouIntroduction of two KL (h) motif elements to the L3/L7/L8 trimer produced oligomers, and the oligomerization of the resulting trimer (Y3h/Y7h/L8) was supported by the homo-KL (h:h) interaction C,D. Whil2+, electrophoretic mobilities of Y3α RNA and Y3α′ RNA were similar to that of L3 RNA  and 8.3 mM MgM images . While EM images A. In AFMM images B, lane 6M images B. In theM images B. Oligom−1) was slightly lower than that of the parent sets (0.029–0.03 min−1). The activity of L3/Y7α/Y8α′ set (0.024 min−1) was similar to that of the Y3h/Y7h/L8 set (0.022 min−1) (−1) as the parent trimer  even without L3 RNA  with the parent sets (L/L/L-type and Y/L/L-type) C. The ac2 min−1) E, oligomt L3 RNA C.2+ because the L3/L24/L25 trimer with three ∆P5/P5abc interfaces was less stable than the L3/L7/L8 trimer and the stability of ∆P5/P5abc interfaces was shown to be improved by increasing Mg2+ concentration [−1) (−1) (−1)  C was low−1) (−1) E. Instal−1) (−1) C. With t−1) (−1) D. We als−1) (−1) B, lane 8−1) (−1) E.We designed and constructed ribozyme-assembly nanostructures using L3/L7/L8 and L3/L24/L25 heterotrimers D as unit2+, Y1h RNA cleaved the substrate RNA (−1) was 3.3-fold lower than that of L1 RNA (0.053 min−1). We then performed EMSA to confirm oligomerization of Y1h RNA. Y1h RNA did not migrate on nondenaturing polyacrylamide gel electrophoresis (PAGE), indicating the formation of Y1h RNA oligomers  to expand the size and complexity of their oligomeric states. We added a stem-loop element for the KL interaction to the P6b element of L RNAs to yield a series of engineered L RNAs (termed Y RNAs). The ribozyme trimers with KL-mediated assembly ability formed dimeric states (Y/L/L-type unit trimers), linear oligomers (Y/Y/L-type unit trimers), and higher-order oligomers with branched oligomerization (Y/Y/Y-type unit trimers) depending on the number of Y RNA elements in the unit trimers. The assembly properties of the Y/Y/L-type unit trimers can be altered by changing the homo-KL (h:h) interaction to hetero-KL (α:α′) interaction. Linear oligomers of Y/Y/L-type unit trimers preferentially underwent ring-closing tetramerization to form cyclic tetramers when they had a hetero-L/L/L (L3/L7/L8 or L3/L24/L25) trimer core and a hetero-KL (α:α′ or β:β′) interaction. The resulting cyclic homotetramer of the cyclic heterotrimer consisted of eight Y RNAs and four L RNAs. Such ribozyme dodecamers cannot be analyzed by nondenaturing PAGE because they were too large to enter and migrate into the gel. The RNA remained stuck in the sample well, suggesting the formation of assemblies containing nine or more L/Y RNA components [In this study, we introduced oligomerization elements into cyclic trimers of the engineered mponents ,29. DireThe substrate cleavage activities of oligomers of the ribozyme trimers suggested that there was no functional advantage with regard to the enzymatic activity of the unit trimer upon oligomerization. In the case of oligomerization mediated by homo-KL interaction, the resulting oligomers (Y3h/Y7h/L8 and Y1h/Y1h/Y1h) had distinctly lower enzymatic activities than the parent L/L/L trimers (L3/L7/L8 and L1/L1/L1). The trimers formed using KL (h:h)-dependent oligomerization, which induced efficient but poorly controlled assembly of the ribozyme trimers and/or their components, showed reduced catalytic activity. Ribozyme trimer units in the KL (h:h)-mediated oligomeric states may have structural defects and/or be subject to structural strain. In contrast to ribozyme oligomers formed by homo-KL interactions, oligomerization mediated by hetero-KL (α:α′ or β:β′) interactions showed no significant negative effects on catalytic activity. This observation suggested that hetero-KL-mediated assembly may cause structural restrictions, which may be minimized by cyclic tetramerization in the Y/Y/L systems.The ribozyme dodecamers identified in this study can be compared with the hemoglobin dodecamer and may be utilized as core modules to generate larger ribozyme complexes corresponding to giant hemoglobin formed through assembly of the hemoglobin dodecamer ,6. Y RNAWhile the design and investigation of self-assembly of functional RNAs are important for their application in biotechnology and synthetic biology as RNA tools ,14,15, sTetrahymena group I ribozyme (PDB ID: 6WLS) and the crystal structures of coaxially stacked KL interactions of HIV-1 RNA (PDB ID: 1K9W and 2B8R) were used for construction of 3D models of L and Y RNAs and their oligomers . Molecular modeling was performed using Discovery Studio .A model 3D structure of the full-length 2+ and 1 mM of each nucleotide triphosphate. The solution was treated with DNase I for 30 min to digest the DNA template. The transcribed RNA was then purified by 6% denaturing PAGE. Labeling of RNA 3′-ends with BODIPY (boron-dipyrromethene)-fluorophore was performed according to the published procedure [The plasmid DNAs newly constructed in this study were made by PCR-based mutagenesis from plasmids reported previously ,17. Plasrocedure .2 or 80 mM Tris-acetate, pH 7.5, and 17.5 mM Mg(OAc)2). The resulting mixtures were then incubated at 37 °C for 30 min for preparation of most of the RNA structures. An extended incubation period at 37 °C (1 h) was applied for formation of the homodimer of the Y3h/L7/L8 or L3/Y7h/L8 trimer. To prepare the heterodimer of the two trimers (Y3α/L7/L8 and Y3α′/L7/L8), each trimer was assembled separately and then mixed. The resulting solution was subsequently incubated at 37 °C for an additional 1 h. Each sample solution was kept at 4 °C for 30 min and then mixed with 6× loading buffer containing 0.1% xylene cyanol and 50% glycerol. Samples were electrophoresed on 5% polyacrylamide gels (acrylamide:bisacrylamide = 39:1) containing 70 mM Tris-borate (pH 8.3) or 80 mM Tris-acetate (pH 7.5) and a given concentration of Mg(OAc)2. The running buffer and the loading solution containing dye also possess the same concentration of Mg(OAc)2. Electrophoresis was performed at 4 °C, 200 V for the first 5 min and then 75 V for 12 h. To visualize nonlabeled RNA samples, the gels were treated with SYBR Green and then analyzed using a Pharos-FX fluoroimager  or treated with ethidium bromide and visualized using a gel-documentation system . BODIPY-labeled RNA samples were visualized using a Pharos-FX fluoroimager (Bio-Rad). It should be noted that we initially performed EMSA using various concentrations of RNA and Mg2+. By analyzing the gel bands corresponding to the anticipated nanostructures, residual monomer units, and undesired oligomers, we established the optimal conditions for EMSA for each set of individual RNAs.For assembly of each RNA structure, an aqueous solution of the appropriate set of RNAs was heated at 80 °C for 2.5 min. Subsequently, the incubation temperature was changed to 37 °C by adjusting the temperature setting on the block incubator. To this solution was added 10× concentrated folding buffer at 37 °C 2) and 2 mM guanosine triphosphate  were added to the RNA solutions and incubated at 37 °C for 30 min. Ribozyme reactions were initiated by introducing fluorophore-labeled substrate-a into the reaction mixture at a final concentration of 0.9 μM, and the reaction was allowed to continue at 37 °C. At specific time points, aliquots were taken and mixed with 1.5 volumes of stop solution containing 0.1% xylene cyanol, 100 mM EDTA, and 75% formamide to effectively halt the reaction. The resulting mixtures were electrophoresed on 15% polyacrylamide gels containing 7 M urea. Reactions of FAM- and TAMRA-labeled substrate RNAs were visualized using a Pharos-FX fluoroimager (Bio-Rad) and a gel-documentation system , respectively. Quantification of visualized gel bands was carried out using Quantity One software version 4.5 . In the preliminary activity assay with L1 RNA homotrimer to compare FAM (Carboxyfluorescein)- and TAMRA (Carboxytetramethylrhodamine)-labeled RNA substrates, the two substrate RNAs provided nearly identical results  were heated separately at 80 °C for 5 min. Subsequently, the incubation temperature was changed to 37 °C by adjusting the temperature setting on the block incubator. The RNA components were then mixed at 37 °C. The 10× concentrated reaction buffer 2) was performed according to the protocol for EMSA. Total concentrations of RNAs in the solution were then adjusted to ~80 nM by addition of sample loading buffer 2 or 80 mM Tris-acetate, pH 7.5, and 17.5 mM Mg(OAc)2). The sample solution (2 μL) was deposited onto a mica surface coated with 0.1% (3-aminopropyl)triethoxysilane and incubated for 5 min. The mica surface was then washed gently with sample loading buffer. The samples in the loading buffer solution were imaged at ambient temperature. A cantilever for High Speed AFM  with a spring constant of 0.1–0.2 N/m and a resonant frequency of 400–1000 kHz was employed. AFM imaging was performed at a scan rate of 0.2 fps.AFM was carried out with a high-speed instrument . Assembly of RNA components in buffer Tetrahymena ribozyme that formed cyclic trimers. These cyclic ribozyme trimers can serve as unit structures to develop larger and more complex assemblies. Oligomerization of the cyclic ribozyme trimers in this study preferentially yielded cyclic tetramers. Although further improvements of assembly efficiency and selectivity are needed, the resulting ribozyme dodecamer represents a promising platform for the development of larger ribozyme nanostructures that may correspond to giant hemoglobin consisting of 144 globin subunits and can be dissected into dodecamers of dodecamers. We also produced large and poorly ordered assemblies of ribozyme trimers, which reached 1000 nm in size. Such large ribozyme oligomers may represent possible protocellular nanostructures that may have emerged in the RNA world.We previously constructed and characterized engineered derivatives of the


Ribosomal RNAs are decorated by numerous post-transcriptional modifications whose exact roles in ribosome biogenesis, function, and human pathophysiology remain largely unknown. Here, we report a targeted direct rRNA sequencing approach involving a substrate selection step and demonstrate its suitability to identify differential modification sites in combination with the JACUSA2 software. We compared JACUSA2 to other tools designed for RNA modification detection and show that JACUSA2 outperforms other software with regard to detection of base modifications such as methylation, acetylation and aminocarboxypropylation. To illustrate its widespread usability, we applied our method to a collection of CRISPR-Cas9 engineered colon carcinoma cells lacking specific enzymatic activities responsible for particular rRNA modifications and systematically compared them to isogenic wild-type RNAs. Besides the numerous 2′-O methylated riboses and pseudouridylated residues, our approach was suitable to reliably identify differential base methylation and acetylation events. Importantly, our method does not require any prior knowledge of modification sites or the need to train complex models. We further report for the first time detection of human rRNA modifications by direct RNA-sequencing on Flongle flow cells, the smallest-scale nanopore flow cell available to date. The use of these smaller flow cells reduces RNA input requirements, making our workflow suitable for the analysis of samples with limited availability and clinical work. Ribosomes are evolutionary-conserved sophisticated nanomachines responsible for protein production in all three kingdoms of life. They are composed of a small and a large subunit, termed 40S and 60S in eukaryotes. Mammalian ribosomes are composed of four ribosomal RNAs (rRNAs), the 5S, 5.8S, 18S, and 28S rRNAs and of 80 ribosomal proteins , which aAn important step of ribosome biogenesis is the modification of rRNAs ,7. Some DKC1 (dyskerin) cause X-linked dyskeratosis congenita, which is associated with bone marrow failure, skin and mucosa alterations, and increased cancer susceptibility [DKC1 also lead to defective telomerase maintenance [DKC1 depletion [The importance of correct ribosome assembly for cell homoeostasis is evidenced by an emerging class of syndromes designated as ribosomopathies. Ribosomopathies are ribosome biogenesis dysfunction diseases caused by ribosomal protein or ribosome assembly factor mutations . Althougtibility . Mutationtenance , and it ntenance . Furtherepletion ,19.In the past, the analysis of mutations in ribosomal proteins and ribosome assembly factors was made possible by the use of diverse perturbation techniques. However, it was less feasible to systematically elucidate the effect of mutations in rRNA (due to the high complexity and repetitive nature of genomic rDNA loci ), or to 6A [6A modifications on mRNA and the detection of modified uridine residues (mainly pseudouridine) on rRNA [With the advent of long-read sequencing techniques, especially the direct RNA sequencing method (direct RNA-seq) introduced by Oxford Nanopore Technologies (ONT), it has become possible to directly sequence full-length RNA molecules . Using d6A ,26,28–316A . Nanopor6A ,30, yeas6A ,33, and 6A  with dif6A . Furtherde novo identification of differential modification sites with no need for training data or prior knowledge of the position and chemical nature of the modification. First, we established nanopore targeted direct RNA-seq of human 18S rRNA with a specific adapter . In a benchmark of JACUSA2 against other published tools, we find that JACUSA2 Mis is especially useful to identify base modifications as methylation and acetylation. Moreover, JACUSA2 is faster and computationally less demanding than most other tools. To validate the detection of these RNA modifications, we employed a collection of CRISPR-Cas9-engineered human colon carcinoma cells (HCT116) lacking specific modifications on the 18S rRNA. To detect modification signatures in nanopore direct rRNA-seq data, each analysed modification was systematically compared in mutant (MUT)/knock out (KO) and isogenic wild type (WT) control cells. Using this approach, we validated, in addition to the abundant 2′-O-ribose methylated and pseudouridylated residues, several 18S rRNA base modifications . Employing JACUSA2 call-2, we show that all analysed rRNA modifications are detectable as differential sites in nanopore direct rRNA-seq data. Importantly, we provide experimental and computational evidence that our approach can estimate relative levels of modification based on calibration curves. Lastly, to expand the repertoire of biological samples that are accessible to nanopore direct rRNA-seq, the targeted rRNA-seq method was transferred to the small-scale Flongle flow cells. We demonstrate that downscaled nanopore direct rRNA-seq on these small devices equipped with only 126 pores allows for detection of rRNA modifications as efficiently as with MinION flow cell sequencing.In this work, we show that JACUSA2 affords the  m6A1832 , the DIM 26A1851 ,39, the  [7G1639 ,41, and In summary, we show that nanopore direct rRNA-seq in combination with JACUSA2 is a fast and simple approach to identify changes in rRNA modification pattern, irrespective of the chemical nature of the analysed modifications or prior knowledge on the modification sites. Furthermore, our miniature Flongle-based sequencing approach makes the method amenable to precious low-input samples of biological and clinical relevance.−/− cell line has been described previously [All human cell lines were generated in p53-positive diploid HCT116 cells  by genome editing. The recipient cell line was diagnosed by ATCC by short tandem repeat (STR) analysis prior to use. The HCT116 METTL5eviously . Here, tY131G/Y131G, WBSCR22D82K/D82K, and SNORD13 KO cell lines, the selected point mutations or deletion of SNORD13 were introduced by CRISPR-Cas9 genome editing on both alleles, as follows: an in vitro reconstituted Cas9 RNP complex  consisting of specific crRNA guides (see Table S2), a universal tracrRNA , and the Streptococcus pyogenes Cas9 , was electroporated in cells freshly resuspended in nucleofector solution V  together with a single-strand donor DNA  in case of the point mutations. Cells were electroporated with an enhancer  in a nucleofector device . Cells were incubated for 24 h to allow them to recover and then detached and cloned by serial dilution. Individual clones were selected and diagnosed by PCR amplification of the modified area , followed by differential restriction digest for DIMT1LY131G/Y131G clones  and WBSCR22D82K/D82K clones  as well as by DNA sequencing of the modified area.To generate the HCT116 DIMT1L2.HCT116 cells were cultured in McCoy’s 5A medium  supplemented with 10% foetal bovine serum , 100 U/ml penicillin, and 100 µg/ml streptomycin  in a New Brunswick Galaxy 170 R incubator at 37°C and under 5% COTotal RNA from HCT116 cells was extracted in TriReagent solution (Thermo Fisher) according to the manufacturer’s instructions.Genomic DNA was isolated from five Mio HeLa cells using the NucleoSpin tissue kit (Macherey-Nagel) according to the manufacturer’s protocol.in vitro transcription (IVT). The following protocol was used for touchdown PCR: 30 sec initial denaturation at 98°C, 20 cycles of touchdown ; 5 min, 72°C), followed by 15 cycles standard PCR at 62°C annealing temperature and final elongation . The primer sequences are listed in Table S1.The complete 18S rRNA sequence was amplified from genomic DNA by touchdown PCR with Q5 DNA polymerase (New England Biolabs) using a forward primer that introduces the T7 promoter sequence for The 18S IVT was generated using the T7 Megascript kit (Thermo Fisher Scientific) according to the manufacturer’s protocol. RNA integrity was analysed on a 1% agarose gel. The IVT product was purified using RNA Clean and Concentrator kit (Zymo Research).One-microgram 18S IVT was polyadenylated with an E-PAP based Poly(A) Tailing Kit (Thermo Fisher Scientific) according to the manufacturer’s instructions and purified using RNA Clean and Concentrator kit (Zymo Research).Direct RNA-seq libraries were generated using the SQK-RNA002 kit (Oxford Nanopore Technologies) following the sequence-specific protocol. Universal oligo A and sequence-specific oligo B (Table S1) were annealed at a concentration of 1.4 µM each in 10 mM Tris, pH 7.5, 50 mM NaCl . Briefly, 500 ng total RNA in a volume of 9 µl was ligated to 1 µl custom adapter using 1.5 µl T4 DNA ligase (New England Biolabs) in NEB next Quick ligation buffer  in the presence of 0.5 µl RNA CS (Oxford Nanopore Technologies) for 10 min at room temperature. Reverse transcription to stabilize the RNA strand was performed using Superscript IV reverse transcriptase ). Reactions were cleaned up using Agencourt RNAClean XP beads (Beckman Coulter). The RMX RNA adapter was ligated as described above, followed by Agencourt RNAClean XP purification and elution in 21 µl elution buffer. The concentration of the library was determined using Qubit DNA HS assay (Thermo Fisher Scientific). Libraries were sequenced on a GridION X5 device equipped with MinION R9.4.1 flow cells for 48 h and basecalled with Guppy 5.0.11 in fast-basecalling mode.2O and the following steps carried out in a smaller volume: 10 µl RNA were ligated to 2 µl RMX with 1 µl T4 DNA Ligase in a total volume of 20 µl and purified with an equal volume of Agencourt RNAClean XP beads. Libraries were eluted in 9 µl ELB. Flongle flow cells were loaded by a community protocol to allow loading similar to the FLO-MIN106D flow cells (https://community.nanoporetech.com/posts/a-very-gentle-relatively). Flongle flow cells were primed with 117 µl FLB +3 µl FLT. Eight-microlitre library was diluted with 7 µl H2O and loaded with 15 µl RRB. Flongle libraries were sequenced on a GridION X5 device equipped with Flongle adapters and Flongle flow cells for 24 h and basecalled with Guppy 5.0.11  and d) Mismatch, Insertion, and Deletion score of the 5-mer context ((MDI)Con). We either use these JACUSA2 scores and feature sets directly or employ them as input to the Local Outlier Factor (LOF) [post hoc based on the analysis by [The JACUSA2 software  calculator (LOF)  method. lysis by .The rRNA benchmark has been implemented as a snakemake (v7.25.3) workflow to measure the performance of different software solutions in identifying RNA modifications. All employed tools perform pairwise comparisons where WT and KO/IVT conditions are contrasted. Performance has been measured against a set of known 18S rRNA modifications. The influence of basecalling, and the number of replicates has been investigated by running tools on data sets processed with different combinations of the aforementioned factors. Calculations have been carried out on the same node in a slurm cluster (see Supplementary Text for details). The area under the precision recall curve has been used to compare the performance of the tools . The running times of the tools were determined in triplicates .To evaluate the effect of read coverage on the analysis, BAM files were downsampled to different amounts of reads . We employ various seed values for the downsampling procedure. The generated down-samplings were subjected to the JACUSA2 call-2 analysis. To compare results across the different levels of read coverage, we calculated the distance between modification sites and the median in terms of two basic scores: the JACUSA2 Mismatch scores and the score assigned to each site by the LOF method. To avoid bias caused by the different scales of LOF scores across analyses, the normalized distance was considered so that the difference between the score of the modification site and the median is divided by the maximum LOF value.in silico samples with different averages of modification rates  were designed by combining WT and KO/MUT samples of 1,000 reads. Then, differential analysis of the generated mixtures and the MUT/IVT samples was performed using JACUSA2 call-2. For the experimental mixing analysis, WT and KO/MUT RNA were mixed with the indicated ratios and libraries were prepared for sequencing on Flongle flow cells as described above. The JACUSA2 Mismatch score was compared across different mixture ratios.To evaluate the ability to detect rRNA modifications with low stoichiometry, https://doi.org/10.5281/zenodo.8268171).Preprocessing, down-sampling, and mixing were performed using Samtools version 1.9. A Snakemake pipeline for the analysis workflow was developed and is available on Zenodo . 200 pg reduced RNA or non-treated control (not shown) was reverse transcribed with a primer targeting the H45 of the 18S rRNA (18S H45 rev) and TGIRT-III reverse transcriptase. RNA was mixed in a total volume of 17 µl with 4 µl 1 µM RT primer and 4 µl 5 × TGIRT buffer  and incubated 3 min at 75°C, followed by 3 min on ice. Then, 1 µl 100 mM DTT and 0.5 µl TGIRT-III (Ingex) were added. Reactions were incubated for 20 min at room temperature. After addition of 1 µl dNTP mix with reduced dGTP , reactions were incubated 60 min at 57°C. PCR reactions were composed of 2 µl cDNA, 2.5 µl 10 µM 18S H45 forward and reverse primer, respectively, 10 µl 5 × HF buffer, 1 µl 10 mM dNTPs, 1 µl Phusion Hot Start Flex DNA Polymerase (New England Biolabs) and 31 µl water. Reactions were cycled with the following programme: 30 sec initial denaturation at 98°C; 35 cycles  and final elongation . PCR products were analysed on 2% agarose gels stained with GelRed (Biotium) and cleaned up with NucleoSpin Gel and PCR Clean-up Kit (Macherey-Nagel). PCR products were analysed by Sanger sequencing (LGC Genomics) with the 18S H45 forward primer. Primer sequences used in the Misincorporation assay are listed in Table S3. Chromatograms were analysed with Chromas 2.6.6 (Technelysium Pty Ltd).Acetylation of 18S rRNA Cescribed . Brieflyin vitro polyadenylation, we established a custom adapter  platform developed by Oxford Nanopore Technologies (ONT). Here, we established a protocol with minimal pre-processing to enable the analysis of low-input samples . To prevogous to ) for thein vitro transcribed (IVT) 18S rRNA. A ten nucleotides long adapter was sufficient to efficiently capture the 18S rRNA . Furthermore, this analysis revealed sequencing of incomplete (missing 3′ end) and reverse strand RNA molecules with the standard RTA. This problem was not observed with the sequence-specific adapter . This adapter was then used for direct rRNA-seq of rRNA from human HCT116 cells and compared to the sequencing of a full-length 18S IVT  adapter (RTA) employing an  18S IVT . The cel 18S IVT , which ilgorithm .To elucidate whether JACUSA2 is indeed suitable to identify well-defined rRNA modifications , we analThe performance of these JACUSA2 feature sets was benchmarked against other tools designed for the identification of RNA modifications by direct RNA-seq, namely xPore , Nanocom4C, m1acp3psU, m6A and m7G in nanopore direct RNA-seq data. JACUSA2 Mis scores on HAC basecalled data  and for the other JACUSA2 feature sets  are provided in the Supplementary Material.The JACUSA2 Mis scores for the WT – IVT comparison were further stratified for every modification type , revealiIn conclusion, Nanopore direct rRNA-seq coupled to JACUSA2 analysis is suitable for the detection of diverse RNA modifications in human rRNAs and may be especially useful for detecting base modifications as methylation and acetylation.Modification sites on rRNAs, including human rRNAs, have been characterized extensively by a range of techniques, including classical RNA biochemistry (such as primer extension), HPLC, mass spectrometry, short-read deep sequencing-based methods (see Introduction), and more recently, by CryoEM. For most of these modifications, the responsible enzymes and, when relevant, the antisense snoRNA guides have been identified and characterized. We made use of this knowledge to analyse specific rRNA base methylations of the 18S rRNA in human cells lacking individual modifications by targeted nanopore direct RNA-seq as a proof-of-concept.6A modification at position 1832 of the human 18S rRNA [7G modification at position 1639 of the 18S rRNA [EcoRV site as monitored by differential restriction digest  genetically engineered by CRISPR-Cas9 genome editing to harbour either a knock-out (KO) or a catalytic-dead variant (MUT) of selected methyltransferases . The cell lines and affected modifications are listed in 18S rRNA . In addi18S rRNA ,39, wher18S rRNA ,41. The n digest . As expeon assay  followinreatment . In caseion site . A primehylation , a resulinterest .Figure 7G1639 affected basecalling not only at the actual modified position but also strongly at the neighbouring residues (−3 to +3), providing a powerful signature .Current input requirements may preclude the use of nanopore direct RNA-seq for samples with limited availability. Furthermore, multiplexing of samples with barcoding is currently not officially supported for direct RNA-seq by ONT, increasing the cost for direct RNA-seq experiments. To overcome these problems, we aimed to transfer the targeted direct rRNA-seq approach described above from the standard MinION flow cells (512 channels with 4 pores each) to the recently introduced smaller Flongle flow cells (126 pores), which require less RNA input. The overall results of the JACUSA2 analysis were highly comparable for MinION and Flongle flow cell-derived data . For the DIMT1L target sites, the identification is mostly independent of the number of analysed reads . In summary, 1,000 reads are sufficient to detect the analysed modifications. In most cases, more reads are not beneficial and less reads are sufficient.To exclude the impact of coverage on our analysis, we used 1,000 reads throughout this work to analyse differential RNA modifications . To elucin silico by mixing either RNA or sequencing reads from WT and KO/MUT at various ratios. We first sampled in silico a total of 1,000 reads from all samples. For the reference ‘Mix’ sample, different ratios of WT and KO/MUT reads were bioinformatically mixed as indicated  or catalytically dead variant (MUT) of an enzyme is compared to a wild-type cell line . The loss of C1842 acetylation in this cell line was validated by a primer extension assay  and direct rRNA-seq – JACUSA2 analysis that identified ac4C1842 as a bona fide outlier  to install the acetylation of 18S at position C1842 ,50,51, w outlier .Figure 1842 acetylation. On the other hand, the C-to-T misincorporation assay could not discriminate between 100% WT and 90% WT/10% SNORD13 KO, revealing an inherent limitation of this approach . Our targeted approach ensures that only properly processed rRNAs with defined 3′ ends are sequenced , and no findings ,32, we set al. [post hoc evaluation of our results. As for every nanopore error-profile-based approach, the chemical nature of de novo identified RNA modification sites needs to be determined by other methods.It is important to emphasize that our prediction of modification sites with JACUSA2 does not rely on any prior knowledge, as we only use modification maps  for pos7G1639, m6A1832, and the double dimethylation m1850 m1851. These base modifications cause distinct basecalling errors that are reflected by the Mismatch scores calculated by JACUSA2 , can be fitted automatically by sklearn.neighbours.LocalOutlierFactor, as described [6A modification, more reads did not improve results.Employing a collection of genetically engineered HCT116 cell lines lacking individual modifications , we demo JACUSA2 . Importa JACUSA2 , enablinescribed . We do nin silico  analysis.6A or pseudouridine [In this work, we applied JACUSA2 call-2 in pairwise comparisons to identify differences in rRNA modification. A number of other computational pipelines are already available in the literature to analyse rRNA modifications in nanopore direct RNA-seq data and were compared here to JACUSA2 , including Nanocompore , EpiNanoouridine ,32. The post hoc validation of our findings. In contrast to some other workflows, JACUSA2 supports the handling of replicate samples as well as pairwise comparison [Importantly, JACUSA2 does not depend on prior knowledge or on training of complex models to identify modification sites. However, in this work, we took advantage of the accurate mapping of rRNA modification sites by mass spectrometry for mparison , enablinIn conclusion, we established a targeted nanopore direct RNA-seq strategy for human rRNA and detection of modifications by JACUSA2. The down scaling to Flongle flow cells enables the study of samples with limited availability. Future work will focus on the identification of differential modification sites in samples of biological interest and clinical relevance and to understand the biological consequences of altered modification patterns.Click here for additional data file.


From splicing to localization to degradation, RNA-binding proteins (RBPs) influence the destiny of an RNA and provide an important layer of posttranscriptional regulation. Historically, RBPs were identified by crosslinking (or bonding together) RNA and interacting proteins and isolating the RNA-protein complexes using oligo(dT)-containing beads . UnfortuTo overcome this shortcoming, protocols to capture more diverse RNA-protein complexes were developed . Phase sDespite the promise of phase separation–based strategies, they have yielded mediocre results when applied to plant tissue. A trial of orthogonal organic phase separation using Arabidopsis tissue had low overlap to previous RBP datasets and even identified a non-RBP, histone H4, as an RBP candidate . Is planYong Zhang and colleagues  of Arabidopsis root or leaf tissue, with or without exposure to high-salt conditions. PPE could identify salt-responsive RBPs, the majority of which were tissue specific. One example of a salt-responsive RBP was ACTIN DEPOLYMERIZING FACTOR2, which had reduced RNA binding in the leaf but increased binding in the root when salt levels were high, demonstrating tissue-specific stress response.A huge benefit of PPE is that it can collect RBPs associated with nonpolyadenylated RNA. By categorizing RBPs found by both PPE and previous oligo(dT)-based approaches as the “poly(A) RBPome,” the authors could separate out the RBPs found solely by PPE as the “non-poly(A) RBPome.” Nearly one-half of the RBPs found by PPE were not identified in previous oligo(dT)-based studies, affording a glance into RBPs that may associate with nonpolyadenylated RNA. Interestingly, RBPs from the non-poly(A) RBPome had differently enriched domains than RBPs from the poly(A) RBPome, highlighting the uniqueness of these 2 populations.Finally, to verify the RNA binding of RBPs identified by PPE, the authors developed an RNA pull-down assay that used polyadenylated Arabidopsis RNA on oligo(dT) beads as bait to capture an input RBP. If the RBP binds to RNA and is pulled down on the beads, it can be visualized via immunoblotting. Using this technique, the binding capacity of several RBPs was confirmed.PPE marks a great improvement in methodology to identify RBPs in plant tissue by phase separation. Although PPE was not able to identify all RBPs previously discovered by competing approaches, it still identified comparatively more RBPs than other methods. Additionally, a majority of these RBPs overlapped with other RNA-binding proteomes. Further exploring the RNA partners of some of the identified RBPs will provide deeper insight into their potential roles.