Advances in mRNA synthesis and lipid nanoparticles technologies have helped make mRNA therapeutics and vaccines a reality. The 5′ cap structure is a crucial modification required to functionalize synthetic mRNA for efficient protein translation in vivo and evasion of cellular innate immune responses. The extent of 5′ cap incorporation is one of the critical quality attributes in mRNA manufacturing. RNA cap analysis involves multiple steps: generation of predefined short fragments from the 5′ end of the kilobase-long synthetic mRNA molecules using RNase H, a ribozyme or a DNAzyme, enrichment of the 5′ cleavage products, and LC-MS intact mass analysis. In this paper, we describe (1) a framework to design site-specific RNA cleavage using RNase H; (2) a method to fluorescently label the RNase H cleavage fragments for more accessible readout methods such as gel electrophoresis or high-throughput capillary electrophoresis; (3) a simplified method for post-RNase H purification using desthiobiotinylated oligonucleotides and streptavidin magnetic beads followed by elution using water. By providing a design framework for RNase H-based RNA 5′ cap analysis using less resource-intensive analytical methods, we hope to make RNA cap analysis more accessible to the scientific community. The relatively short development and manufacturing time have been the main attributes propelling the rapid deployment of effective mRNA vaccines in a global health emergency such as COVID-19.In eukaryotic cells, the 5′ end of messenger RNA (mRNA) is characterized by a cap structure that plays key functional roles in many biological processes . Most reN7-methylated guanosine linked to the 5′ end of RNA through a 5′ to 5′ triphosphate group. In metazoans, the m7GpppN cap (Cap-0) is further modified by a cap-specific 2′-O-methyltransferase (MTase) to the m7GpppNm structure (Cap-1) (The 5′ cap consists of an  (Cap-1) .Currently, the cap structure can be incorporated into an in vitro transcript by two means: (1) incorporation of a chemically synthesized cap structure such as the anti-reverse cap analog (ARCA) or capped dinucleotides  during tO-MTase) from capping intermediates, such as unmethylated G-cap and 5′-diphosphate RNA, and unreacted 5′-triphosphate RNA molecules , unreacted RNA 5′-triphosphate, and small amounts of 5′-diphosphate byproduct. For enzymatic capping, the nature of the catalytic pathway  requiresolecules .The addition of a cap structure to a mRNA molecule amounts to a <600 Da mass change over potentially hundreds of kilodaltons in mass. Analytical methods such as gel electrophoresis and mass spectrometry may lack the resolution or detection range to confidently distinguish between Cap-1 or Cap-0 capped RNA and unreacted or intermediate capping products on full-length synthetic mRNA molecules. To overcome this problem, methods that cleave a predefined fragment from the 5′ end of the mRNA molecule using custom designed DNAzyme , ribozymEscherichia coli RNase H can be constrained to cleaving ssRNA at specific sites in vitro using a DNA–RNA chimera. However, E. coli RNase H may also cleave one or more nucleotides away from the 5′ or 3′ of the target site, giving rise to multiple cleavage products that differ by 1 nt  is an endonuclease that removes the RNA primers from the Okazaki fragments of the replicating DNA and processes R-loops to modulate R-loop-mediated biological processes, such as gene expression, DNA replication, and DNA and histone modifications . It has  by 1 nt . For thePreviously, it has been shown that by using a biotinylated DNA–RNA chimera oligo, the 5′ RNase H cleavage fragments could be readily isolated for qualitative and quantitative analyses using LC-MS . HoweverEscherichia coli RNase H has been shown to cleave ssRNA at predefined sites in vitro by hybridizing a DNA–RNA chimera to the target synthetic RNA, generating an RNA/DNA duplex akin to its physiological substrate. Two major cleavage sites, the adjacent phosphodiester bonds 5′ and 3′ to the ribonucleotide hybridized to the 5′ deoxynucleotide of the DNA–RNA chimera have been reported (reported .E. coli and from Thermus thermophilus) for their efficiency and specificity in cleavage on a synthetic RNA oligonucleotide containing the 5′ sequence of a firefly luciferase FLuc transcript (synFLuc-AC). To maximize the availability of cleavage sites, we designed the DNA–RNA chimera  to direct RNase H to cleave within a loop region of the predicted secondary structure . The substrate synFLuc-AC contains a 5′ FAM group so that the cleavage products can be analyzed using urea-PAGE electrophoresis and quantified using a flatbed laser scanner.To try to understand whether RNase H can be restrained to make more uniform cuts, we first compared two commercially available RNase H enzymes (from E. coli and T. thermophilus (Tth) RNase H achieved similar levels of cleavage . However, Tth RNase H generated more 24 nt cleavage product than the E. coli enzyme . Hence, Tth RNase H was used in the following study.As shown in FLuc-AC as a surrogate, we next sampled several potential cleavage sites using different TOs. Cleavage reactions were done in triplicate and cleavage events were evaluated using urea PAGE and LC-MS intact mass analysis , and <1% at the −3 position (U|A) (FLucTO-24), the majority of the cleavage events still took place at the A|C site at a lower frequency (60%), even though it was at the +1 site relative to the 5′ of FLucTO-24. The remaining cleavage events took place at the −1 (A|A) site (11%) and at the −2 (U|A) site (29%). When the TO was extended by 1 nt (FLucTO-26), most cleavage events took place at the A|C site. The A|C site, now at −2 position, was cleaved 66% of the time, with no detectible cleavage at the −1 site (C|U). Upon extending the TO to 2 nt (FLucTO-27), most cleavage events took place at the −1 U|U site (87%) with minor cleavage taking place at −2 (C|U), −3 (A|C), and −4 sites (A|A). Further extending the TO by 3 nt (FLucTO-28), the major cleavage site remained at the U|U site now at −2 position (98%). The −1 (U|U) site was cleaved at a low frequency (1%).Using the 5′ FAM-labeled synthetic RNA oligonucleotide synon (U|A) B. When tFLucTO-25 (TO-1) to guide Tth RNase H to cleave the FLuc in vitro transcripts (1.7 kb). FLucTO-27 and FLucTO-28 that generated 87% to 98% of a specific cleavage product were not chosen because of the presence of uridine at the cleavage sites (see below for the effect of pseudouridine substitution in RNase H cleavage). After cleavage by Tth RNase H, the 5′ cleavage product was purified using the water elution method described below and analyzed by LC-MS intact mass analysis. Consistent with the findings with the RNA oligonucleotide surrogate, the median cleavage frequency at the −1 (A|C) site was 91%, with 8% at the −2 (A|A) site, and 2% at the +1 (C|U) site (We next used a 3′ desthiobiotinylated version of |U) site B, from e|U) site . TherefoFLuc) in vitro transcript as a test case, the long 3′ RNase H cleavage product and the uncleaved full-length transcript were first separated from the smaller 5′ cleavage products and TO . For simplicity, a low salt wash buffer and elution with water was chosen to enrich desthiobiotin-tagged TO-RNase H cleavage product duplexes in subsequent experiments.It has been reported recently that ribozyme-cleaved 5′ cleavage fragments of in vitro transcript could be enriched for LC-MS analysis using silica-based spin columns. The spin column format, however, requires 20–60 µg RNA input . The useTO TO-1;  by size TO TO-1;  was addeTO TO-1; , which cTO TO-1; . The RNATO TO-1;  and LC-MUpon further investigation, we found that although a small amount of higher molecular weight RNA was present when the size-selection step was not performed, the data quality of the LC-MS analysis was not affected (data not shown). Hence, the size-selection step can be considered optional.CLuc or FLuc transcripts. The deconvoluted mass spectrums of the enriched 5′ cleavage fragments are shown in CLuc, or 1.7 kb FLuc in vitro transcript (2.9 µg) was sufficient to generate high quality LC-MS data for quantitative analysis.We used the single step post-RNase H affinity enrichment method to process enzymatically capped Cap-1 FLucTO-25 (and its 3′ desthiobiotinylated derivative TO-1) produced a 3′ recessive end   .7G cap  from unmethylated G cap (Gppp-). Rather, 5′ triphosphate and 5′ diphosphate co-migrate as uncapped RNA, while m7G cap and unmethylated G cap co-migrate as capped RNA. An affinity-based denaturing PAGE method that can resolve m7G cap (Cap-0) from unmethylated G cap (Gppp-) and uncapped (ppp- and pp-) RNA has been described . Capillary electrophoresis of the processed samples allowed quantification of 5′ ppp-, pp-, Gppp-, and m7Gppp-  from 5′ diphosphate (pp-), or mescribed . Capilla m7Gppp- C.Capillary electrophoresis can be routinely done in a 96-well format using an Applied Biosystems Genetic Analyzer  The high-throughput capability and resolution of enzymatic capping intermediates is of great interest for method development and quality control in platforms that utilize enzymatic capping for mRNA production.FLuc preparation was subjected to the RNase H/Klenow fill-in processing and analyzed by urea-PAGE, capillary electrophoresis, and LC-MS  and uncapped (pp- and ppp-) agreed well with the capillary electrophoresis and LC-MS results.To further validate the Klenow fill-in method, a partially capped nd LC-MS D. We fouUridine modifications  have been shown to help reduce cellular innate immune response and improve protein translation of synthetic mRNA . ModifieCypridina luciferase (CLuc) transcript (1.8 kb) was transcribed in vitro in the presence of either UTP or ΨTP. Targeting oligo CLucTO-26 was used such that the major RNase H cleavage sites were centered around a uridine residue . Upon Tth RNase H cleavage, the 5′ cleavage product of the uridine and the Ψ-substituted CLuc transcripts were subjected to the enrichment and analysis as described above. Two major cleavage events were observed with the unsubstituted CLuc transcript: 73% of the products resulted from cleavage 5′ of the uridine (C|UC) with a length of 25 nt, while 27% resulted from cleavage 3′ of the uridine (CU|C) with a length of 26 nt (To investigate the effect of pseudouridine (Ψ) on RNase H cleavage site preferences, a of 26 nt . When urMessenger RNA, as a single-stranded nucleic acid molecule, can adopt multiple stable conformations depending on formulation and reaction conditions. These stable conformers can affect RNase H, ribozyme or DNAzyme cleavage efficiency and specificity through factors such as substrate annealing and substrate-enzyme interactions. While these factors are still poorly understood, we showed that highly uniform RNase H cleavage can be achieved by systematic screening of Targeting Oligos (DNA–RNA chimera). The sequence complementarity-based method to fluorescently label the 3′ end of the 5′ RNase H cleavage fragments using the Klenow fragment further constrains the size of cleavage fragments for gel- or capillary electrophoresis-based fluorescence detection and quantitation. In addition, our simplified one-step affinity-based post-RNase H purification method allows for lower RNA input compared to the silica-based purification method .FLuc transcript  and one unrelated transcript (data not shown). Sufficient level of cleavage and product recovery could be obtained using TOs ranging from 14 to 37 nt (data not shown). The fact that pseudouridine substitution could affect RNase H cleavage specificity showed that it is important to include modified nucleotides in the surrogate substrate to ensure the TO-screening results are applicable to transcripts that contain modifications. Finally, we believe that our empirical TO-screening framework and the downstream affinity enrichment method is a generalized approach to develop a highly effective RNA cap analysis method.Using the TO selection framework that screens for RNase H specificity empirically, we have achieved ≥90% cleavage specificity in at least one out of four or five TOs on a anscript , 5, a CLOur methods present additional tools for RNA cap analysis for the rapidly expanding applications of synthetic mRNA. Ultimately, the availability of multiple approaches to evaluate synthetic mRNA cap incorporation could help democratize synthetic mRNA research, accelerate technology advancement, and benefit basic research.FLuc) and Cypridina luciferase (CLuc) transcripts containing artificial 5′ UTRs were performed using PCR-amplified DNA templates and the HiScribe T7 High Yield RNA Synthesis Kit (New England Biolabs), according to manufacturer's instructions. The RNA transcripts were purified using the Monarch RNA Cleanup Kit (New England Biolabs). RNA concentrations were determined using a Qubit RNA BR Assay Kit (Thermo Fisher Scientific).In vitro transcription of firefly luciferase  according to manufacturer's instructions. In some cases, a lower concentration of vaccinia RNA capping enzyme was used to generate partially capped RNA to demonstrate the resolution of reaction intermediates by the analytical methods.2, 10 mM DTT). The mixtures were heated at 80°C for 30 sec and cooled down to 25°C at a rate of 0.1°C/sec. The mixtures were then incubated with E. coli RNase H (New England Biolabs) or T. thermophilus RNase H  at a final concentration of 5 U/μL at 37°C for 1 h. Reactions were quenched by addition of EDTA to a final concentration of 10 mM. The quenched RNase H reactions were then subjected to 15% urea-PAGE followed by fluorescent imaging using the Amersham Typhoon RGB laser scanner (Cytiva). Alternatively, quenched reactions were analyzed by LC-MS directly.DNA–RNA chimeras (targeting oligo or TO) composed of 5′ deoxynucleotides and 3′ ribonucleotides with or without a 3′ TEG-desthiobiotin group were designed as described in the main text and synthesized chemically . For the investigation of RNase H cleavage specificity, 0.5 μM of synthetic RNA oligonucleotides containing a 5′ FAM label were combined with 2.5 μM of the corresponding TOs in a 10 μL reaction containing 1× RNase H reaction buffer . After cooling down to 25°C at a rate of 0.1°C/sec, the reactions were subjected to RNase H cleavage by incubation with Thermostable RNase H (New England Biolabs) at a final concentration of 0.5 U/µL at 37°C for 1 h.For cap analysis of in vitro transcripts, RNA samples (0.5 μM) were heated at 80°C for 30 sec in the presence of 2.5 µM of appropriate targeting oligos in a 10 μL reaction containing 1× RNase H reaction buffer or 1× RNA capping buffer . The mixtures were then analyzed by electrophoresis through a urea-15% polyacrylamide gel . To acquire the fluorescent signals, the urea gels were scanned directly using the Amersham Typhoon RGB scanner (Cytiva) with the Cy2 channel. To acquire total RNA stain, the gels were stained using SYBR Gold (Thermo Fisher Scientific) and scanned using the Amersham Typhoon RGB scanner using the same settings. Data were analyzed using ImageQuant (Cytiva).Supplemental Figure 3.Capillary electrophoresis of FAM-labeled RNA was carried out using an Applied Biosystems 3730xl Genetic Analyzer (96 capillary array) using POP-7 polymer and GeneScan 120 LIZ dye Size Standard (Applied Biosystems) . Peak deAfter RNase H cleavage and the optional Klenow fill-in, the 5′ cleavage fragment/TO duplex was purified by size selection followed by affinity-purification . BrieflyN,N-diisopropylethylamine (DIEA) aqueous buffer and methanol. UV detection was performed at 260 nm. Intact mass analysis was performed under full scan mode at a resolution of 70,000 (FWHM) at m/z 200. ESI-MS raw data were deconvoluted using Promass HR . The relative abundance of each deconvoluted mass peak was used to calculate the percentage of the substrate (ppp-), intermediates  and final products (m7Gppp- or m7GpppNm-) of enzymatic RNA capping. Methods and results for validation of deconvoluted mass peak intensities for RNA quantitation can be found in Supplemental Figure 4.Intact oligonucleotide mass analyses were done using in-house facilities or by external contractor Novatia LLC. For in-house analyses, intact oligonucleotide mass analyses were performed by liquid chromatography-mass spectrometry (LC-MS) on a Vanquish Horizon UHPLC system equipped with a diode array detector (Thermo Scientific) and a Q-Exactive Plus Orbitrap Mass Spectrometer operating under negative electrospray ionization mode (–ESI) (Thermo Scientific). UHPLC was performed using a DNAPac RP Column  at 70°C and 0.3 mL/min flow rate with a gradient mobile phase consisting of a hexafluoroisopropanol (HFIP) and Additional data are available upon request.Supplemental material is available for this article.S.H.C., J.M.W., N.D., G.T., I.R.C. Jr., and G.B.R. are current employees of New England Biolabs that markets molecular biology reagents. The affiliation does not affect the authors’ impartiality, adherence to journal standards and policies, or availability of data.


Numerous purines and their metabolic derivatives must be monitored for proper control of relevant metabolic pathways. In certain bacteria, some metabolic steps related to purine production or degradation are catalyzed by proteins whose production is under direct regulatory control by purine-sensing riboswitches. Four riboswitch classes selective for guanine, adenine, and 2′-deoxyguanosine (two classes) reported previously exploit a common architecture involving a three-stem junction. Here, we describe three additional classes based on this same scaffold that sense xanthine, guanine, or 2′-deoxyguanosine. Thus, some riboswitches can diversify their ligand-sensing and gene-control functions without the need to evolve entirely novel structures, which highlights a capability that could have also been exploited by ancient forms of life during the RNA World. The aptamer portions of previously reported riboswitch classes that sense guanine, adenine, or 2′-deoxyguanosine are formed by a highly similar three-stem junction with distinct nucleotide sequences in the regions joining the stems. The nucleotides in these joining regions form the major features of the selective ligand-binding pocket for each aptamer. Previously, we reported the existence of additional, rare variants of the predominant guanine-sensing riboswitch class that carry nucleotide differences in the ligand-binding pocket, suggesting that these RNAs have further diversified their structures and functions. Herein, we report the discovery and analysis of three naturally occurring variants of guanine riboswitches that are narrowly distributed across Firmicutes. These RNAs were identified using comparative sequence analysis methods, which also revealed that some of the gene associations for these variants are atypical for guanine riboswitches or their previously known natural variants. Binding assays demonstrate that the newfound variant riboswitch representatives recognize xanthine, guanine, or 2′-deoxyguanosine, with the guanine class exhibiting greater discrimination against related purines than the more common guanine riboswitch class reported previously. These three additional variant classes, together with the four previously discovered riboswitch classes that employ the same three-stem junction architecture, reveal how a simple structural framework can be diversified to expand the range of purine-based ligands sensed by RNA. Riboswitches are structured noncoding RNA domains most commonly found in the 5′-untranslated regions (UTRs) of mRNAs in bacteria and archaea –3. Each 4SI Appendix.Even with these restrictions, metabolite-binding riboswitches demonstrate a remarkable ability to recognize a wide range of biological ligands, such as signaling molecules, elemental ions, coenzymes, amino acids, and nucleotide derivatives . To date9+)  , 18, the+) , nucleos+) , the pur+) , and pos+) . Such RN+) , 23, 24.The need to form precise binding pockets for cognate ligands that rarely change through evolution makes riboswitch aptamers among the most highly conserved biopolymer sequences and structures . Thus, w30The apparent enormous potential for riboswitch aptamer variation and ligand specificity changes helps rationalize two somewhat contentious hypotheses. First, the relative ease with which evolution diversifies aptamer-binding pockets helps support the view that RNA World organisms could have evolved to become sophisticated entities without the help of protein factors to carry out ligand-sensing tasks . Second,Computational methods that identify conserved RNA sequence and structural features have been used to uncover the majority of riboswitch classes reported to date . G. G44). GPaenibacillus bacterial species as well as from Propionispira and unnamed Clostridium species (Upper). Some notable sequence differences reside at positions known to directly interact with the ligand in guanine riboswitches reported previously. In addition, the genes associated with some of these variant RNAs are not typical of those regulated by guanine riboswitches, suggesting that the variants might have altered their ligand specificity (Lower).To search for novel guanine riboswitch variants, we used a comparative sequence analysis strategy . Specifi species , Upper. cificity , Lower.Lower) frequently associates with genes annotated as coding for dioxygenase, allantoinase, and xanthine dehydrogenase enzymes, which are not commonly associated with guanine riboswitches. This variant RNA collection is also distinct because they carry nucleotide changes in the junction linking stems P2 with P3 (J2-3) and the junction linking stems P3 and P1 (J3-1)  , 47. In 1 (J3-1) , 46, 47.Lower), we speculated that these variants could potentially recognize oxidized purine products. To test this hypothesis, we designed and prepared a 92-nucleotide RNA construct called 92 allB  from Paenibacillus sp. DMB5. The RNA was subjected to in-line probing, which is a method that exploits the natural instability of RNA phosphodiester linkages to report on folding changes brought about by ligand binding  of ∼36.5 µM . Presumably, the altered nucleotides in the joining regions of the three-stem junction form a novel and highly discriminatory binding pocket that efficiently excludes xanthine analogs. Given the considerable number of changes in the aptamer core and its strong discrimination against various purine analogs, we anticipate very little similarity between these other aptamer classes and the newly found xanthine aptamer. However, biophysical studies will likely be needed to reveal details regarding how the binding pocket differs from guanine riboswitches and the previously reported variant classes.Importantly, the structure of 92 allB construct is a representative of a second riboswitch aptamer class that senses xanthine. In some examples, we can identify potential terminator stems that partially overlap the aptamer, which suggests that these RNA aptamers function as the sensory components of riboswitches. The architectures of these RNAs are consistent with genetic “ON” switches, where ligand binding activates gene expression. Given the gene associations, it appears that these xanthine riboswitches participate in regulating the degradation or salvage of various purine compounds.The existing bioinformatic and biochemical data, however, already strongly support the conclusion that the 92 NMT1 motif RNAs , that are more representative of guanine riboswitches (Lower) riboswitches.We also uncovered another collection of variant RNAs that are remarkably similar to the xanthine-II riboswitch aptamers described above B. Howeveswitches  than of switches  and xantswitches A, Lower PRT gene of Paenibacillus sp. FSL and called 92 PRT , although the full binding curve could not be established with the in-line probing reaction conditions used. This affinity compares favorably with that determined for a representative of the guanine riboswitch aptamer class originally reported . Furthermore, the analyses reveal that the KD value for guanine is more than 100-fold better than the values determined for guanosine, 2′-deoxyguanosine, and hypoxanthine . In these species, guanine-I riboswitches are associated with genes annotated as xanthine PRT (XPRTase). In contrast, guanine-II RNAs are found upstream of genes that encode PRT-type I family enzymes that include either hypoxanthine-guanine-xanthine PRT or xanthine-guanine PRT, among others. In addition, the directionalities of gene control upon ligand binding are predicted to be opposite for the guanine-I (OFF) and guanine-II (ON) riboswitches in Paenibacillus species.Notably, some species of It is currently not clear why some bacterial species use different guanine riboswitch variants to regulate PRT gene expression with opposite regulatory directions. One possibility is that abundant guanine triggers the guanine-II (ON) riboswitch to activate expression of a PRT gene whose product can directly utilize guanine for GMP formation . In contrast, when guanine concentrations are too low, the guanine-I (OFF) riboswitch permits expression of a PRT gene whose XPRTase product converts other available purines such as xanthine into XMP, a metabolic intermediate that can subsequently be converted into GMP. Because it is more efficient to produce GMP by adding a 5-phosphoribose moiety to guanine compared to adding 5-phosphoribose to other nucleobases that subsequently need to be converted into GMP, guanine-sensing riboswitches with opposing regulatory directions likely enable cells to most efficiently produce GMP.Bacillus sp. VT712 , while ignoring free guanine, xanthine, and hypoxanthine.In-line probing analyses also revealed that the RNA binds guanine more poorly than aptamers from either the guanine-I and guanine-II C classesSI Appendix, Fig. S5). These observations indicate that the ligand is a nucleoside whose accumulation activates production of a nucleoside hydrolase. Thus, the genetic “ON” riboswitch likely detects excess guanine-containing nucleosides that need to be degraded, rather than activating a gene involved in producing more guanine when this compound is already in excess.Two observations support the conclusion that this variant class naturally responds to G-containing nucleosides. First, the gene exclusively associated with these RNAs codes for purine nucleoside hydrolase, which uses nucleosides as substrates and produces free nucleobases as products. Second, the aptamer region of these riboswitches precedes a predicted intrinsic terminator stem, wherein ligand binding is predicted to turn on expression of the downstream coding region  Therefore, we recommend naming these additional variants 2′-dG-III riboswitches.We speculate that the binding pocket for this variant class has distinct features compared to the binding pockets formed by 2′-dG-I G and 2′-The identification and experimental validation of three additional aptamer types based on variants of the guanine-I riboswitch class adds to the tremendous diversity of riboswitches that are known to sense purines, purine precursors, or their derivatives . Each ofAlthough available crystal structures of the previously discovered variants  provide Paenibacillus and a few other organisms, these particular variant examples most likely have emerged more recently through the acquisition of mutations by guanine-I riboswitch aptamers. Regardless, this demonstrated potential for ligand-sensing diversification by natural RNA aptamers could have readily been exploited by RNA World organisms  was purchased from PerkinElmer.All candidate ligands and synthetic oligonucleotides were purchased from Sigma-Aldrich. , 1 mM EDTA), and the RNAs were precipitated using ethanol. Next, 60 pmoles of the RNA transcripts were dephosphorylated using rAPid alkaline phosphatase (Roche Life Sciences) following the manufacturer’s protocol, and 5 pmoles of the resulting RNAs were 5′ 32P-radiolabeled using T4 polynucleotide kinase (New England Biolabs). Radiolabeled RNAs were purified using denaturing 10% PAGE gel, further prepared as described above, and resuspended in autoclaved dH2O for storage at −20 °C until use.To prepare RNA constructs, synthetic DNA templates base-paired to a T7 RNA polymerase promoter oligonucleotide were used in in vitro transcription reactions with T7 RNA polymerase following the protocol described previously . The res32P-labeled RNAs were subjected to in-line probing reactions with the desired ligands in a 10-µL reaction mixture containing 100 mM Tris⋅HCl (pH 8.3 at 20 °C), 100 mM KCl, and 20 mM MgCl2 and incubated at room temperature for ∼40 h. Spontaneously cleaved RNA fragments were resolved using 10% PAGE and visualized using Typhoon FLA 9500 . ImageQuant 5.1 was used to quantify the cleavage patterns and GraphPad Prism 9 was used for graphical analyses.Stock solutions of ligands were prepared by dissolving in 50 mM aqueous NaOH and then the desired ligand concentrations were made by serially diluting in 25 mM aqueous NaOH. Following the protocol described previously , 5′ 32P-Supplementary File


Eukaryotic genomes often encode multiple transporters for the same nutrient. For example, budding yeast has 17 hexose transporters (HXTs), all of which potentially transport glucose. Using mathematical modelling, we show that transporters that use either facilitated diffusion or symport can have a rate-affinity tradeoff, where an increase in the maximal rate of transport decreases the transporter’s apparent affinity. These changes affect the import flux non-monotonically, and for a given concentration of extracellular nutrient there is one transporter, characterised by its affinity, that has a higher import flux than any other. Through encoding multiple transporters, cells can therefore mitigate the tradeoff by expressing those transporters with higher affinities in lower concentrations of nutrients. We verify our predictions using fluorescent tagging of seven HXT genes in budding yeast and follow their expression over time in batch culture. Using the known affinities of the corresponding transporters, we show that their regulation in glucose is broadly consistent with a rate-affinity tradeoff: as glucose falls, the levels of the different transporters peak in an order that mostly follows their affinity for glucose. More generally, evolution is constrained by tradeoffs. Our findings indicate that one such tradeoff often occurs in the cellular transport of nutrients. From yeast to humans, cells often express multiple different types of transporters for the same nutrient, and it is puzzling why a single high-affinity transporter is not expressed instead. Here we initially use mathematical modelling to demonstrate that transporters facilitating diffusion and those powered by the proton motive force can both exhibit a rate-affinity tradeoff, for quite general conditions. A transporter with a higher affinity necessarily has a lower rate, and vice versa. The tradeoff implies that there is a range of nutrient concentrations for which a transporter, characterised by its affinity, has a higher import flux than any other transporter with a different affinity. To mitigate the tradeoff, genomes may therefore encode multiple different transporters, and cells that express each transporter in the concentrations where it imports best will uptake nutrients at higher rates. Consistently, we show that as cells of budding yeast consume glucose, they express five types of hexose transporters in an order that follows the transporters’ affinities. Saccharomyces cerevisaie, for example, multiple transporters may be the norm rather than the exception, particularly for essential nutrients—there are two transporters for sulphate . It. It13]. ri = re = r , the order in which the different transporters become optimal as Se changes remains the same.The flux tends to zero as Kd, be and fe. Flux increases monotonically with the other rate constants, fi and r, which we might assume have values close to the maxima that selection allows.To summarise, we find that transporters using facilitated diffusion always exhibit a rate-affinity tradeoff if their rate of transitioning back and forth across the membrane is symmetric and unchanged when bound by substrate. This tradeoff affects flux only if the maximal rate and affinity are changed by varying the rate constants that determine the extracellular Many transporters work not by facilitated diffusion but are powered by the proton motive force across the plasma membrane. For example, in budding yeast, most phosphate  and aminm protons and n substrates and assuming that the intermediate states with only some of the protons and substrates bound are short-lived, then the steady-state flux of imported substrate becomes similar to r′ and b in r determines a refractory period, where the symporter is temporarily unable to transport.Symporters can be modelled as facilitative transporters  Materia. By replkcat and KM to describe the transport. Writing S for a substrate molecule, we can rearrange the expression for the antiporter’s steady-state flux to have the formSsym isψ denotes the plasma membrane potential, R is the ideal gas constant, T is temperature, F is Faraday’s constant, and a substrate molecule has charge zS.As before, we define an apparent kcat and KM areThe apparent  ≤ λ ≤ 1 . By calc+(1+eu)CandKM=(+(1+eu)Cwritingr or fi, there is such a tradeoff when fe changes and also when be changes if fe ≥ fi. This inequality favours import and so is likely to be obeyed by most nutrient symporters. Even if substrate binding disfavours import, there is still a tradeoff when be changes if u is sufficiently large and negative such that eu ≪ 1. Because Δψ is typically negative [m > −nzS. In all these cases, the derivative of the flux may be non-monotonic, implying that such a symporter, like a facilitative transporter, has particular extracellular conditions where its flux is maximal . Notebooks are available at be < 109 s−1, 103 < fe, fi < 109 M−1 s−1, and 0.1 < r < 107 s−1. bi.To generate n protons and m substrates at the extracellular space, and G ofCells maintain an electrical potential difference across their plasma membranes , and beczS so that m + nzS is the total charge transported.The substrate has charge ψ and any differences in concentration, this transport step should be able to reach equilibrium. Then the reaction’s ΔG is zero implyingu is defined in Once we include the effects of both ΔThe reaction should also obey detailed balanceψ  supplemented with 2% pyruvate for pre-culture. We used low fluorescence SC medium, which is the same as SC medium except riboflavin and folic acid have been removed from the yeast nitrogen base, supplemented with 2% glucose for growth in plate readers.We used 2% pyruvate for pre-culture to avoid any glucose-dependent effects because cells are then respiring and performing gluconeogenesis. We incubated such pyruvate cultures for 48 hours, then diluted and grew cells in fresh medium for another 24 hours, and then, again, diluting and growing in fresh medium for 4 hours to reactivate growth.μl of cell culture using a Tecan M200 plate reader.We measured optical density and fluorescence in 96 well microplates (Thermo-Fisher) with 200 omniplate Python module (available from https://swainlab.bio.ed.ac.uk/software/omniplate and https://pypi.org).We corrected the OD for its non-linear dependence on the number of cells  and fluoCandida albicans SC5314, Cyberlindnera jadinii NRRL Y-1542 (Phaffomycetaceae), Hanseniaspora valbyensis NRRL Y-1626 (Saccharomycodaceae), Lachancea thermotolerans CBS 6340, Eremothecium gossypii ATCC 10895, Kluyveromyces lactis CBS 2359, Torulaspora delbrueckii CBS 1146, Zygosaccharomyces rouxii CBS 732, and Saccharomyces cerevisiae S288C.We created the species tree  using a Candida albicans and Saccharomyces cerevisiae [The concatenated sequence was generated using the following proteins, given with the AYbRAH ortholog group in parentheses : Acc1 (Frevisiae .We used AYbRAH  and the S1 Notebook(NB)Click here for additional data file.S2 Notebook(NB)Click here for additional data file.


Sulfolobus solfataricus model organism. We confirm the association of aIF5A with several RNA molecules in vivo and demonstrate that the protein is endowed with a ribonuclease activity which is specific for long and structured RNA. By means of biochemical and structural approaches we show that aIF5A can exist in both monomeric and dimeric conformations and the monomer formation is favored by the association with RNA. Finally, modelling of the three-dimensional structure of S. solfataricus aIF5A shows an extended positively charged surface which may explain its strong tendency to associate to RNA in vivo.The translation factor IF5A is a highly conserved protein playing a well-recognized and well-characterized role in protein synthesis; nevertheless, some of its features as well as its abundance in the cell suggest that it may perform additional functions related to RNA metabolism. Here, we have undertaken a structural and functional characterization of aIF5A from the crenarchaeal  S. acidocaldarius, S. solfataricus, H. cutirubrum, T. acidophilum) contain hypusine, some anaerobic species undergo only the first reaction, so they contain deoxyhypusine, while some other contain both variants of the protein . W. WS. sollignment  with thend E120) . TherefophaFold2  to predinfidence , with annfidence . We havenfidence . The suprganisms . To furtr (APBS) . The hypIF5A EPS B,C, in aataricus . Furtherl domain C. Becausnd K131) ,54.S. solfataricus. The functions and properties of this protein have been studied in Eukarya and in Bacteria but remain somewhat elusive in the archaeal kingdom. In the hyperthermophilic model S. solfataricus, we show that this protein is always expressed during growth and that the bulk of aIF5A was found in the free form and was not ribosome associated [S. solfataricus.The present work reports a structural and functional characterization of one of the most abundant and conserved translation factors, the aIF5A from sociated , suggestS. solfataricus aIF5A is an RNA-binding protein in vivo, showing by RIP experiments, that it is associated with different types of RNA including two mRNAs (2184 and 0910) and one ncRNA (ncRNA98).First, we demonstrate that in In addition, aIF5A is endowed with an endonuclease activity. We performed several in vitro degradation assays and showed that aIF5A can cleave the two mRNAs previously identified (2184 and 0910) as being aIF5A-associated in vivo, as well as rRNA 16S and 23S isolated from 30S and 50S ribosomal subunits. On the contrary, the ncRNA98 as well as a mixture of small RNAs, mainly containing tRNAs, are resistant to aIF5A degradation activity.Our results are in agreement with previous findings, where we have hypothesized that cleavage was more likely to occur in single-stranded areas or bulges. Here, we show for the first time a clear preference of aIF5A for long RNA molecules such as rRNAs or mRNAs, that fold in more complex secondary structures, thus exposing more single-strand regions in loops as compared to shorter RNA, as tRNAs or ncRNAs, structurally more compact.In all cases, hypusine seems to be irrelevant for the RNase activity, even though on one of the mRNAs analyzed, the hypusinated protein seems to be slightly more efficient in the cleaving activity. This may indicate that different RNAs may interact in different ways with the protein, and therefore, in some complexes, the presence of hypusine may favor the enzymatic activity.Halobacterium aIF5A is dependent on its oligomeric form and it probably forms dimers [M. jannashii shows that it exists as a dimer in certain crystals [S. solfataricus protein in vivo, investigating the influence of the RNA molecules might have on its conformation . To this end, we fractionated a control cell lysate and a cell lysate incubated with RNase A on glycerol gradients, and we explored the distribution of the native protein in the two samples. The results show that in the control lysate, aIF5A appears to migrate as a monomer, but in a lysate treated with RNase A, aIF5A shifts its position migrating in higher molecular weight fractions (around 34–40 kDa). This result indicates that in the absence of RNA, the protein may form either dimers or higher molecular weight complexes associating with other proteins. Therefore, the protein is a monomer in vivo most likely by its association with RNA molecules, and these RNAs can either be its binding partners or fragments deriving from its RNA-degrading activity. If RNAs are completely removed, the protein tends to aggregate, forming dimers or associating with other proteins.Previous findings in yeast proposed that eIF5A occurs in solution as a dimer, and that dimerization is RNA-dependent ,31. Addis dimers , while ccrystals . Based oE. coli is also associated in a non-specific manner to bacterial RNAs (data not shown) [SAXS experiments were performed to gain more information on the solution structure of aIF5A and on its tendency to dimerize. The results have shown, in addition to a strong stability of the protein, which is not influenced by variations of the different parameters analyzed , that the main conformation adopted in solution by N-His-aIF5A is monomeric, with a slight tendency to form oligomers. This can be explained by the fact that the recombinant protein purified from t shown) ,31. In aHalobacterium and S. solfataricus suggests a possible similar catalytic mechanism. To better understand the interaction mechanism of the S. solfataricus aIF5A with RNA, the electrostatic potential surface (EPS) was calculated for several IF5A structures. The protein from S. solfataricus was the only one having a prominent positive potential in the C-terminal region , or through stabilization of the phosphate moieties on the nucleic acid backbone (basics) A. Concerl region B,C, and S. solfataricus. In addition, information on mechanisms by which RNA species reach their mature forms or are degraded are still fragmentary in Archaea. Several endonucleases have been identified from the information gathered from Bacteria and Eukarya, as the orthologue of RNase P, the splicing endonuclease End A, aRNase Z, aPelota, members of the ß-CASP ribonuclease family , aNob1 and CRISP Cas6 [S. solfataricus.Overall, the results seem to indicate that in the cell, a fraction of aIF5A is bound to translate ribosomes, while the rest is in the cytoplasm, most of it associated with RNA molecules. Some of these molecules  are binding partners, and it remains to be clarified whether the association with aIF5A has a functional meaning, and whether other RNA (mRNAs) are substrates for aIF5A degradation activity. Further studies are necessary to clarify in more detail the mechanism of cleavage of Sso aIF5A and to investigate the role of the protein in RNA-processing pathways in ISP Cas6 . In thisIn conclusion, we have shown that the protein exists mainly as a monomer associated with RNA molecules and probably remains RNA bound even when it acts as a ribonuclease. Indeed, being an endonuclease with preference for single strand loops, it is conceivable to assume that the products of the enzymatic activity are RNA fragments which may remain bound to the protein, helping to maintain its monomeric conformation.The different functions of aIF5A  are interconnected, and this “constitutive” association with RNA could be functional in providing a constant pool of monomeric protein ready to associate, when needed, with stalling ribosomes.


Drosophila have been based on a few RNAs in different tissues, and a comprehensive mechanistic analysis of RNA localization in a single tissue is lacking. Here, by subcellular spatial transcriptomics we identify RNAs localized in the apical and basal domains of the columnar follicular epithelium (FE) and we analyze the mechanisms mediating their localization. Whereas the dynein/BicD/Egl machinery controls apical RNA localization, basally-targeted RNAs require kinesin-1 to overcome a default dynein-mediated transport. Moreover, a non-canonical, translation- and dynein-dependent mechanism mediates apical localization of a subgroup of dynein-activating adaptor-encoding RNAs . Altogether, our study identifies at least three mechanisms underlying RNA localization in the FE, and suggests a possible link between RNA localization and dynein/dynactin/adaptor complex formation in vivo.Intracellular RNA localization is a widespread and dynamic phenomenon that compartmentalizes gene expression and contributes to the functional polarization of cells. Thus far, mechanisms of RNA localization identified in  Drosophila follicular epithelium by spatial transcriptomics and through genetic analyses determine canonical and translation-based mechanisms underlying basal and apical RNA localization.In this study the authors identify localized RNAs in the  Three main mechanisms have been described to account for RNA localization: (1) active transport on cytoskeletal tracks, (2) localized protection from degradation, or (3) facilitated diffusion and entrapment6. Recently, several novel mechanisms have been reported to mediate RNA localization, such as hitch-hiking on other RNAs or organelles and co-translational RNA transport15. Active transport is the best-characterized mode of RNA localization and consists of the transport of ribonucleoprotein particles by motor proteins on cytoskeletal tracks. Localizing RNAs are typically transported in a translationally silent state and contain cis-acting localization elements (LEs) that are recognized and bound by trans-acting RNA-binding proteins (RBPs) mediating motor recruitment16.RNA localization allows the precise compartmentalization of gene expression in space and time, and is a widespread phenomenon in many different cell types and organismsoskar (osk) RNA localization to the posterior pole of the Drosophila oocyte18. Whereas Tropomyosin-1 isoform I/C  regulates osk posterior localization by directly stabilizing Khc interaction with the RNA21, the Exon Junction Complex (EJC) deposited upon splicing is thought to activate kinesin-1 transport of the RNA20. Little is known about MT plus end-directed RNA transport in other tissues. Interestingly, aTm1 is also important for coracle RNA localization at Drosophila neuromuscular junctions22 and the EJC has been shown to mediate NIN RNA localization in human RPE1 cells23.Kinesin motor proteins mostly mediate microtubule (MT) plus end-directed transport. Kinesin-1 (Khc) has been shown to mediate Drosophila, dynein-mediated RNA transport is accomplished by the dynein-activating adaptor Bicaudal-D (BicD) and the RNA binding protein Egalitarian (Egl)26. The dynein/BicD/Egl complex is thought to mediate nurse cell-to-oocyte transport of maternal RNAs, and was shown to direct apical RNA localization in the early embryo, neuroblasts, and polar cells31. The dynein/dynactin/BicD (DDB) motor complex is highly conserved and participates in the transport of different cargoes, with BicD  linking the dynein motor to specific cargoes. While proteins binding to the BicD C-terminal domain (CTD), such as Egl or Rab6, impart cargo specificity35, the BicD N-terminal domain  binds to dynein/dynactin36 and activates dynein processivity39.Cytoplasmic dynein and its accessory complex dynactin direct trafficking of cargoes towards MT minus ends. In Drosophila germline, several examples of localizing RNAs have been also reported in the follicular epithelium (FE) that envelops the germline cyst44. The FE is composed of highly polarized secretory follicle cells (FCs) belonging to the somatic lineage, with minus ends of non-centrosomal microtubules (ncMTs) anchored at the apical cell cortex facing the oocyte45. The FE is an easily manipulatable and powerful genetic system that, through the generation of mosaics, allows the dissection of the effect of mutations without disrupting developmental processes. Several lines of evidence indicate that the dynein/BicD/Egl RNA transport complex active in nurse cell-to-oocyte transport is also responsible for the apical localization of a handful of RNAs in the FE48. However, a comprehensive overview of RNA localization in the FE and its underlying mechanisms are lacking.Although much of what is known about RNA localization comes from studies of maternally inherited RNAs in the Here, we apply subcellular spatial transcriptomics to first identify the landscape of apically- and basally-localizing RNAs in the columnar FE. By screening a subset of apical and basal RNAs identified in this way, we find that the dynein/BicD/Egl machinery acts by default in directing apical RNA localization, and that an additional kinesin-1-dependent layer of regulation must be applied to direct basal RNA localization. Moreover, we identify a third, translation- and dynein-dependent mechanism that underlies the apical localization of transcripts encoding dynein-activating adaptors, providing a possible link between RNA localization and dynein/dynactin/adaptor complex formation in vivo.Drosophila FE transcriptome-wide, we applied laser-capture microdissection (LCM) to isolate fragments of tissue that consisted of either the apical half  or basal half  of adjacent columnar follicle cells  of basal genes with log2FC < −3 were annotated as being expressed or having a function in muscle tissues (FlyBase) and their mapped reads were often absent or in very low number in the apical fragments  as being enriched in circular muscles with little or no expression in the FE  and atypical Tropomyosin-1 (aTm1) in the FE and analyzed the localization pattern of 4 validated basal RNAs     in the same mutant backgrounds. In contrast to basal RNAs, none of the apical RNAs analyzed was affected by disruption of kinesin-1-mediated RNA transport  Fig. . In all ls) Fig.  or aTm1 21) Fig. , basal R21) Fig. . Then, wTm1 Fig. . To checaTm1, nuclear events such as splicing and deposition of the Exon Junction Complex (EJC) play a role in the localization of oskar RNA at MT plus ends49. To test whether the EJC is involved in basal RNA localization, we disrupted the complex by overexpressing ΔC-Pym51. ΔC-Pym overexpression in FC clones impaired basal RNA localization  or Khc (Khc RNAi), or both Egl and Khc [(egl + Khc) RNAi] and evaluated changes in the RNA localization of zip, one of the most striking examples of the apical mislocalization phenomenon  RNAi caused zip to assume a ubiquitous localization that would be consistent with a failure of both kinesin-1-and dynein-mediated transport  RNAi cells (KD/wt DoA = 1.61) compared to Khc RNAi cells (KD/wt DoA = 2.49)  Fig. . Therefocrumbs (crb)46. To test in an unbiased way the degree of involvement of the dynein/BicD/Egl machinery in the localization of apical RNAs in the FE, we generated FC mutant clones in which either cytoplasmic dynein  or Egalitarian (egl) were knocked-down by RNAi. We then analyzed the localization pattern of 5 validated apical RNAs  by smFISH, along with the quantification of RNA localization by measuring the KD/wt DoA. The localization of all apical RNAs analyzed was completely abolished when Dhc was knocked down by RNAi, with the RNAs becoming ubiquitously distributed , BicD RNA was still apically localized, whereas localization of CG33129 RNA, previously found to be Egl-dependent  and cycloheximide (CHX) and analyzed the distribution of BicD RNA under these two conditions compared to control ovaries incubated in Schneider’s medium only  does, indicates that an intact translation machinery and the presence of a nascent peptide may be required for BicD RNA localization in FCs.Localization of nly Fig. . To asseols Fig. , Puro tr FE Fig. . The disent Fig. . As a prion Fig. . The facBicD depends on translation of its own RNA (in cis) or of other factors (in trans), we designed a series of transgenic constructs consisting of a BicD-GFP cassette inserted downstream of an 18-bp linker in which we could introduce the desired frameshift mutations without disrupting any unknown RNA localization element in the BicD CDS  as BicD-GFP constructs failed to localize when expressed in the germline or in the FE  showed a strong apical localization in FCs , verified by the absence of GFP signal in CD8-mCherry+ cells, was sufficient to impair apical RNA localization  was impaired in Puro-treated ovaries, whereas CHX had no effect , without significantly affecting nurse cell-to-oocyte transport, a process that is also dynein-dependent , namely hook (HOOK1-3), Bsg25D (NIN/NINL), Nuf (RAB11FIP3), and Milton (TRAK1-2), were significantly enriched apically in our list of localizing transcripts (Supplementary Data Spindly (SPDL1) which was below the detection threshold. By hypothesizing that the same dynein-dependent co-translational process that drives BicD RNA localization would also be responsible for the apical localization of adaptor-encoding RNAs, we tested whether the localization of adaptor-encoding RNAs was affected by either Dhc or egl RNAi. Interestingly, the apical localization of Bsg25D and hook was significantly disrupted in Dhc RNAi cells , subapical (the remaining 2/3), and basal  in Control, Puro, and CHX conditions. This analysis revealed that, similar to BicD RNA, the localization of hook and Bsg25D RNAs was significantly affected by Puro treatment, whereas CHX had no effect , reflecting MT plus end enrichment45. Khc, aTm1, and the EJC appear to be core components of a general basal RNA localization machinery. These results are in line with previous findings on osk RNA indicating that Khc/aTm1 bind to the 3’UTR20 and the EJC activates kinesin-1 transport through association with the coding sequence63.Only few examples of localizing RNAs in the FE have been described to date, with little mechanistic insight FE Fig. . In our 23 found that the EJC specifically localizes to the basal body of the primary cilium in mono-ciliated cells, where it controls the centrosomal localization of NIN RNA towards MT minus ends. In contrast, our data suggest that in columnar follicle cells, which are characterized by non-centrosomal MTOCs66, the EJC may play a role in MT plus end-directed  RNA transport by acting synergistically with kinesin-1 and aTm1. Strikingly, the localization of osk RNA to the posterior pole of the oocyte also relies on the presence of MTs generated from non-centrosomal MTOCs65.Therefore, the mammalian EJC might have acquired a specific role in the localization of NIN RNA at basal bodies of mono-ciliated cells, while the Drosophila EJC appears to contribute to the MT plus end-directed localization of several RNAs through a centrosome-independent mechanism both in the somatic follicular epithelium  and in the germline (osk RNA).According to our analysis, deposition of the EJC is necessary but not sufficient to determine RNA localization, as we found that the EJC is deposited on both apically- and basally-directed RNAs. Interestingly, Kwon et al.67. Alternatively, the dynein complex could be kept in an inhibited state and activated upon disruption of kinesin-1 and its regulators. If the tug-of-war scenario were correct, we would have expected a change in zip RNA localization in all RNAi conditions including egl RNAi alone, namely a shift to a more basal localization due to the enhanced Khc-dependent motility. However, since we did not see a significant change in zip localization when only Egl was knocked down, the tug-of-war hypothesis appears to be less likely than the inhibition hypothesis. In addition, this phenomenon recalls osk RNA mislocalization to the oocyte anterior upon disruption of kinesin-1, aTm1 or EJC components72 which was hypothesized to occur due to a failure to inactivate dynein-mediated RNA transport18.Interestingly, when either component of the kinesin-1 transport complex was lacking, basal RNAs were mislocalized to the apical domain in a dynein-dependent process. Therefore, dynein-mediated apical localization represents a default mechanism that must be overcome by kinesin-1 to drive basal RNA localization. Two possible scenarios could explain dynein-mediated apical mislocalization upon kinesin inhibition. Dynein and kinesin-1 could be engaged in a tug-of-war, pulling the RNAs in opposing directions, a phenomenon observed in the transport of vesicles and lipid droplets29. Our data suggest that the majority of apically localizing RNAs may belong to this class, as the localization of most of our randomly chosen apical RNAs was affected in both Dhc RNAi and egl RNAi conditions. This hypothesis is consistent with previous studies that identified several apical RNAs as BicD/Egl cargoes, in a variety of Drosophila tissues48. The BicD/Egl machinery has been hypothesized to be part of a larger RNP complex that ensures a tight translational control of the transported RNA73. Our finding that basal RNAs are on average more translated than apical RNAs suggests that RNAs transported apically in the FE by the dynein/BicD/Egl transport complex might indeed be kept in a translationally silent state until they have reached their final destination.Apical RNA localization, on the other hand, can be divided into two mechanistically distinct categories, both based on dynein-mediated transport. The first category includes those RNAs that are transported apically by the dynein/BicD/Egl machinery, a well characterized RNA transport complex that directs RNAs towards MT minus ends in a variety of tissuesBicD, hook, and Bsg25D . Common features of their apical RNA localization include sensitivity to puromycin and partial co-localization with cortical dynein foci containing also Dhc RNA. Moreover, both Bsg25D74 and BicD (this study) RNA constructs containing the CDS alone are sufficient for the accumulation of their encoded protein at MT minus ends. Puromycin causes the disassembly of the translational machinery and the release of the N-terminal peptides emerging from ribosomes. As the N-terminal portion of these adaptors binds dynein or dynactin subunits78, we propose that the apical localization of BicD, hook, and Bsg25D depends on the co-translational association between dynein components and nascent adaptors at cortical dynein foci  tethered to the cell cortex86. Therefore, the establishment of ncMTs could be at the basis of the mechanistic switch from translation-independent to co-translational BicD RNA localization in these compartments. A recent report has shown that NIN RNA  localizes at ncMTs and its expression is essential for apico-basal MT formation and columnar epithelial shape87. Therefore, it is possible that the co-translational transport of adaptor-encoding RNAs may be important for correct ncMT nucleation at the apical cortex of the follicular epithelium.In vitro studies have shown that full-length BicD/BICD2 adopts an autoinhibitory conformation resulting from CC1/2 folding onto the CTD-containing CC3w1118 virgin females were kept with males for 24 h at 25 °C on yeast-supplemented cornmeal food.Ovaries were dissected in PBS, transferred to a cryomold and snap-frozen in cold 2-Methylbutane after removal of excess PBS. Frozen ovaries were immediately covered with OCT cryoembedding compound (Sakura) and snap-frozen again. Before cryostat sectioning, each block was equilibrated at −20 °C for 1 h. 10 μm cryosections of OCT-embedded ovaries were carefully placed on a MembraneSlide NF 1.0 PEN (Zeiss), briefly thawed at RT and immediately fixed in 75% RNase-free (RF) ethanol for 30 s. Excess OCT was removed with ddH2O RF, and slides were stained in 100 μl Histogene staining solution (Arcturus) according to the manufacturer’s instructions. Finally, sections were dehydrated in increasing ethanol concentrations , and briefly air-dried before LCM.2/replicate. LCM samples were processed according to Chen et al.88 to produce high-quality Illumina sequencing libraries. Samples were multiplexed and simultaneously sequenced in a single lane using the NextSeq500 system according to the manufacturer’s instructions.LCM was performed with a Zeiss PALM MicroBeam and visualized under a 63X objective. Sectioned mid-oogenesis egg chambers were staged according to morphological criteria. Once stage 9–10 egg chambers had been identified, either the apical half  or the basal half  of 5-10 contiguous columnar follicle cells was microdissected and collected into the cap of an AdhesiveCap tube (Zeiss). 10 fragments of either apical or basal sample type from different egg chambers were pooled for each replicate, with a total microdissected area of ~3000–4000 μmD. melanogaster Release 6 (dm6) reference genome. To control for RNA degradation that might have occurred during LCM, the normalized transcript coverage of the uniquely mapping reads was calculated with CollectRNAseqMetrics . Uniquely mapped read counts were normalized with DESeq289. Differential gene expression analysis was performed with DESeq2 by comparing the mean read counts of the Apical  and Basal  samples. Replicates A5 and B5 were excluded from further analysis due to their high degree of dissimilarity with replicates of the same sample type as shown by PCA and Euclidean distance analysis, probably due to a high degree of contamination from neighboring tissues. Statistical significance was set to an FDR-adjusted p value <0.1 (Benjamini-Hochberg correction for multiple testing). The R package ComplexHeatmap90 was used to generate the heatmap in Fig. Pre-processing of demultiplexed raw reads was performed on EMBL’s instance of Galaxy platform. Raw reads were trimmed to remove low-quality bases, filtered from rRNA reads, and mapped against 91 (release FB2020_6) and their read distribution among apical and basal replicates analyzed through Integrative Genomics Viewer (IGV)92.Identification of contaminant RNAs was performed with R Studio. Among the RNAs that were significantly enriched in either the apical (log2FC > 0) or the basal (log2FC < 0) domain, were considered contaminants those RNAs displaying high absolute log2FoldChange (|log2FC | ), indicating that they were probably originating from neighboring tissues. A threshold of log2FC > 3 and log2FC < −3 was arbitrarily set to identify putative apical and basal contaminants, respectively. The functional annotation of each contaminant candidate was retrieved on FlyBasew1118 males at 25 °C on cornmeal food supplemented with yeast. Female offspring of the desired genotype were incubated with w1118 males on a yeast-supplemented medium for 24 h at 25 °C to stimulate the development of vitellogenic stage egg-chambers before ovary dissection.All fly stocks were maintained at 18 °C on standard fly food. For crosses, virgin females were mated with w1118 , DhcRNAi (#36698), eglRNAi (#28969), KhcRNAi (#35409), UAS-NLS-mCherry (#38425), osk-Gal4 (#44242), VK33 (#9750). Other stocks used were: HsFLP; arm > f + >Gal4; UAS-CD8-mCherry and tj-Gal4/CyO (gifts of Juan Manuel Gomez Elliff), Tm1eg1/TM3Sb,Ser and Tm1eg9/TM3Sb,Ser21, GFP-Mago93, Dhc64C-GFP58, vasa-Gal4/TM3Sb (gift of Jean Rene Huynh), UAS-ΔC-Pym-GFP51, UAS-Egl94, eglWU50/SM1 and eglPR29/SM6A24. Transgenic flies carrying UAS-GFP, UAS-0BicD-GFP, UAS-(+1)BicD-GFP, and UAS-(−1)BicD-GFP were generated in this study by phiC31 integrase-mediated recombination using the VK33 line, which carries an attP site on the third chromosome.The following stocks were obtained from the Bloomington Drosophila Stock Center (BDSC): eglNULLFC flies, eglWU50/CyO; osk-Gal4/TM3Ser were crossed with eglPR29/CyO; UAS-Egl/TM3Ser to generate eglWU50/eglPR29; osk-Gal4/UAS-Egl, expressing Egl only in the germline lineage to rescue the formation of rudimentary ovaries. tj-Gal4 and vasa-Gal4 drivers were used to express UAS-containing transgenes in the whole follicular epithelium and in the germline, respectively.For the generation of hsFlp; arm > f + >Gal4; UAS-CD8-mCherry virgins, and F1 females were subjected to heat-shock as described below.To generate flies for FC mutant clone induction, male flies carrying a UAS-containing transgene were crossed with HsFLP; arm > f + >Gal4/CyO; KhcRNAi/TM6B,Tb flies were crossed with + ; UAS-NLS-mCherry/CyO; eglRNAi/TM3Ser. F1 Female flies the desired genotypes  were collected and subjected to heat-shock as described below.To generate flies for induction of FC mutant clones in the experiment illustrated in Fig. 96. Freshly eclosed females resulting from each cross were collected and mated with w1118 males for 24 h at 25 °C on food supplemented with yeast. Flies were heat-shocked for 1 h in a water bath heated at 37 °C. According to Gonzalez-Reyes & St Johnston97, heat-shocked females were kept for 39 h at 25 °C with males on yeast before dissection, thus allowing follicle cells that induced the expression of the transgene at stage ~5 to develop into stage 10 follicle cells.The UAS-Gal4 “flip-out” system was used to generate marked mutant clones in a wild-type backgroundw1118 female flies were incubated with males for 24 h at 25 °C on fly food supplemented with yeast. Ovaries were dissected in PBS and immediately incubated in Schneider’s medium (Gibco) supplemented with 15% FBS (Gibco), 0.6X penicillin/streptomycin (Invitrogen), 200 μg/ml insulin (Sigma). For translation inhibitor treatment, either 200 μg/ml puromycin (Gibco) or 200 μg/ml cycloheximide (Sigma) or no compound (control) was added fresh to the medium and ovaries were incubated for 30 min at RT before fixation.Young w + cassette, a TLS-deficient version of the K10 3’UTR, and attB sites for phiC31 integrase-mediated recombination into the VK33 line were generated as follows.AttB-pUASp-BicD-GFP-K10 or AttB-pUASp-GFP-K10 plasmids carrying a 0BicD-GFP, (-1)BicD-GFP, (+1)BicD-GFP), BicD and GFP CDS were amplified by PCR and the two fragments were combined into AttB-pUASp-K10 vector by InFusion cloning (Clontech) according to the manufacturer’s instructions. pBS-BicD  plasmid (a kind gift from Jean-Baptiste Coutelis) was used as template to generate BicD CDS PCR amplicons. The Fw primer used to amplify BicD CDS was designed in order to include, in addition to a 20 nt-homology with AttB-pUASp-K10 vector, the Drosophila Kozak sequence98 in frame with a linker sequence where frameshift mutations could be generated, and a region annealing to nt 4-29 of BicD CDS. To generate 0BicD-GFP construct, the 18-bp linker containing the ATG (5’- ATGATCCTAGGCGCGCGG- 3’) was inserted in frame with nt 4-2346 of BicD-RA. To generate (+1)BicD-GFP construct, a C was inserted at position 4 in the N-terminal 18-bp linker (5’- ATGCATCCTAGGCGCGCGG- 3’). To generate (−1)BicD-GFP construct, a G was deleted at position 10 in the N-terminal 18-bp linker (5’- ATGATCCTA_GCGCGCGG- 3’). 0BicD-GFP, (−1)BicD-GFP, and (+1)BicD-GFP full insert sequences with the respective predicted translated ORF are listed in Supplementary Data To generate plasmid vectors carrying the BicD-GFP gene cassettes  diluted 1:1000 in blocking buffer o/n at 4 °C. Alexa fluor 647 goat anti Rabbit (Jackson Immuno Research) secondary antibody was added at 1:750 dilution in blocking buffer for 2 h at RT. Samples were washed 3 × 10 min with 1X casein/PBSTX(0.1%), 1 × 10 min with PBSTX(0.1%) + 1:15,000 DAPI and kept o/n in 100 μl of 80% TDE/PBS before mounting on microscope slides.5–10 pairs of ovaries were dissected in PBS and immediately fixed in 2% PFA in PBSTX(0.1%) (PBS + 0.1% Triton-X100) on a Nutator for 20 min at RT, followed by two washes of 15 min each with PBSTX(0.1%) shaking at RT. Ovaries were then blocked in 1X casein/PBSTX(0.1%)  for 30 min and incubated with rabbit anti-Egl primary antibody99 to generate oligonucleotides labelled at their 3’ and with ATTO-633-NHS ester (ATTO-TEC). When dual-color smFISH experiments were performed, each probe set was labelled with either ATTO-633 or ATTO-565. The degree of labelling  and concentration of the labelled probe sets was measured according to the published algorithm.smFISH antisense oligonucleotides (listed in Supplementary Data Dissected ovaries were immediately fixed in 2% PFA/PBSTX(0.1%) gently shaking for 20 min at RT. In case of ex vivo ovary incubation, dissected ovaries were incubated in Schneider’s medium supplemented with the respective pharmacological treatment before proceeding with fixation, as described above. Fixed ovaries were rinsed and washed twice with PBSTX(0.1%) for 10 min before dehydrating them by replacing PBSTX(0.1%) with increasing concentrations of ethanol/PBSTX(0.1%). Fixed and dehydrated ovaries were kept in 100% ethanol at −20 °C for up to 10 days until the day of the experiment.100 was followed with minor modifications. All steps were performed at RT unless specified otherwise. Dehydrated ovaries were first rinsed with PBSTX(0.1%), followed by 2 × 15 min washes with PBSTX(0.1%), and incubated in Pre-hybridization Buffer  gently shaking for 30 min. The Pre-hybridization Buffer was replaced with 250 μl of Hybridization Buffer , 100 μg/mL salmon sperm DNA (Invitrogen), 10% dextran sulfate, 20 μg/mL BSA) pre-warmed at 37 °C in which smFISH probes were added to a final concentration of 1 nM/probe. Ovaries were kept hybridizing in the dark for 16-17 h on a heat block set at 37 °C shaking at 1000 rpm. To remove the excess probes, ovaries where washed 3 × 10 min at 37 °C with Washing Buffer . 1:15,000 DAPI was added to the second wash. Finally, samples were rinsed 4x in PBST(0.1%) (PBS + 0.1% Tween20) and kept in in 100 μl of 80% TDE/PBS for at least 1 h before mounting on microscope slides.An optimized version of the smFISH protocol described in Hampoelz et al.Z-stacks of images were acquired on a Leica TCS SP8 confocal microscope with 405 nm, 488 nm, 552 nm and 640 nm fixed excitation laser lines using a 63 × 1.3 NA glycerol immersion objective. A suitable range for spectral detection was carefully chosen for each channel to avoid cross-talk of fluorescence emission. Images were automatically restored by deconvolution with the Lightning module.101. In mosaic FE, for each wild-type  and mutant (mCherry-marked) group of cells within the same Z-stack, a region of interest (ROI) was drawn encompassing the apical and the basal cytoplasm of 5-10 adjacent follicle cells (with the exclusion of nuclei); in addition, a ROI was drawn in an area of the image were no signal was present . The mean fluorescence intensity (m.f.i.) was measured for each ROI.To quantify smFISH fluorescence of localizing RNAs, average Z-projections of deconvolved confocal image stacks were analyzed with Fijit) (wild-type or mutant) and each experimental condition c, was measured as follows:c, the DoA measured in mutant (KD) cells was divided by the DoA measured in neighboring wild-type (wt) cells within the same Z-stack:Tm1NULL condition, due to the impossibility to obtain a mosaic tissue, the DoA of a given RNA in each cell type (t) (wild-type or Tm1NULL), was measured as follows:Tm1NULL egg chambers was divided by the average DoA measured in n wild-type egg chambers (wt):The degree of apicality (DoA) of a given RNA in each cell type . The p-value was estimated by double-sided Wilcoxon rank sum test.To analyze EJC enrichment on apical and basal RNAs, we annotated differentially EJC-enriched genes from Obrdlik et al.55 and control RNAi ovaries54. Translation efficiency was calculated as RFP[TPM]/RNA-seq [TPM] for apical and basal RNAs identified by our study. The p-value was estimated by double-sided Wilcoxon rank sum test.To calculate translation efficiency of apical and basal RNAs, ribosome profiling (RFP) TPM values as well as RNA-seq TPM values were extracted from published ribo-seq datasets of 0-2 h embryosImmunostaining and/or smFISH experiments were performed on ovaries from at least 3 flies (hundreds of egg chambers) and repeated at least twice at different times.H0: KD/wt(DoA) = 1, corresponding to no change in RNA localization bias following KD treatment [DoA(KD)=DoA(wt)]. One-sample two-sided Student’s t-test was used to compare means to a reference value of mu = 1 in each experimental condition. In Supplementary Figure 2c-d, we calculated the total smFISH signal intensity as the sum of apical and basal signals in mutant and wild-type cells, computed the KD/wt total signal intensity and tested against a null hypothesis of H0: KD/wt=1, corresponding to no change in total signal intensity in KD cells. One-sample one-sided Student’s t-test  was used to compare means to a reference value of mu = 1 in each experimental condition. In Supplementary Fig. 4d, GFP-Mago fluorescence intensity was measured in apical and basal domains. The A/B ratio of GFP intensity was tested against a null hypothesis of H0: A/B=1, corresponding to an evenly distributed signal long the A-B axis. One-sample two-sided Student’s t-test was used to compare mean GFP-Mago fluorescence to a reference value of mu = 1.In Figs. t-test was used to compare mean DoA(wt) and DoA(RNAi) values in each condition. In Fig. In Fig. Fluorescence intensity along lines was measured with Fiji on average Z-projections of confocal images and plotted with R Studio. Intensity values from each channel were normalized to 0-1 range.BicD or GFP mean fluorescence intensity along the A-B axis of the epithelium was measured in groups of 5–10 adjacent follicle cells as line plots. At least 3 line plots were generated for each RNA measured in each condition. The value corresponding to 50% of the cumulative area under the curve (a.u.c.) of each plot was considered as the variation of the respective RNA localization along the A-B axis of the epithelium. Welch two sample t-test was used to compare mean values of the 50% of the a.u.c with respect to untreated controls  or In-frame BicD-GFP (Frameshift vs. In-frame variation).Bsg25D and, to a lesser extent, hook, smFISH signal threshold was first manually adjusted. Then, the integrated density (IntDen) of background-subtracted signal was measured in the apical-cortical, subapical, and basal domains of adjacent FCs. To minimize sample-to-sample variability due to differences in threshold adjustment, the percentage of signal present in each subdomain within single egg chambers was measured, and average percentages were plotted for each RNA in each condition. Statistical testing was performed by independent two-sided Student’s t-test .smFISH signal in Control, CHX, and Puro conditions was quantified using Fiji. Due to low signal-to-noise ratio of Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Movie 1Reporting Summary


SARS-CoV-2 is a positive-sense, single-stranded RNA virus responsible for the COVID-19 pandemic. It remains unclear whether and to what extent the virus in human host cells undergoes RNA editing, a major RNA modification mechanism. Here we perform a robust bioinformatic analysis of metatranscriptomic data from multiple bronchoalveolar lavage fluid samples of COVID-19 patients, revealing an appreciable number of A-to-I RNA editing candidate sites in SARS-CoV-2. We confirm the enrichment of A-to-I RNA editing signals at these candidate sites through evaluating four characteristics specific to RNA editing: the inferred RNA editing sites exhibit (i) stronger ADAR1 binding affinity predicted by a deep-learning model built from ADAR1 CLIP-seq data, (ii) decreased editing levels in ADAR1-inhibited human lung cells, (iii) local clustering patterns, and (iv) higher RNA secondary structure propensity. Our results have critical implications in understanding the evolution of SARS-CoV-2 as well as in COVID-19 research, such as phylogenetic analysis and vaccine development. The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus. In the cells of COVID-19 patients, SARS-CoV-2 interacts with human proteins and is potentially subjected to their enzymatic activities. Here we investigated whether human protein enzymes can change the nucleotide sequence of SARS-CoV-2, thereby leaving a unique molecular footprint. We developed a robust computational algorithm to analyze the sequence data of SARS-CoV-2 obtained from lung fluid samples of COVID-19 patients and found that the virus contains new nucleotide changes that are likely induced by ADAR1, a powerful human protein that can modify specific nucleotide positions in many human transcripts. We further confirmed that the characteristics of the nucleotide changes detected in SARS-CoV-2 are similar to those observed in the human genes. Thus, these ADAR1-induced nucleotide changes may represent an under-appreciated force that can affect the evolution of SARS-CoV-2. Our study helps researchers better understand the evolutionary trajectory of SARS-CoV-2. The rapid spread of coronavirus disease 2019 (COVID-19) across the world represents an urgent healthcare emergency. By January 2022, the virus had infected >352 million people and caused >5.6 million deaths globally, and these numbers continue to increase. COVID-19 is caused by a novel coronavirus designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [Fig 1A shows the example of A-to-I RNA editing), the nucleotide changes thus induced could become a direct source of genetic variations inherited from generation to generation. Second, in sharp contrast to the human genome, the vast majority of the SARS-CoV-2 genome is protein-coding, and thus, RNA editing events would have a much higher probability of causing amino acid changes, thereby modifying protein products. Although identifying RNA editing events from RNA-sequencing data has been well described in many species, including humans, such an analysis for an RNA virus is not trivial. This is because, without the DNA sequence for comparison, it is almost impossible to distinguish single nucleotide variants (SNVs) caused by spontaneous mutation processes from those due to RNA editing, solely based on alignment-based sequence analysis. In this study, our strategy was to first identify a high-confidence nucleotide variant candidate pool from metatranscriptomic sequencing reads of COVID-19 patient samples using a robust bioinformatics pipeline and then test whether real RNA editing signals were enriched in the candidate pool. To do so, we evaluated multiple RNA editing-specific characteristics of the candidate sites in comparison to other A/T sites in the SARS-CoV-2 genome, including (i) ADAR1 binding affinity predicted by a deep-learning model based on ADAR1 CLIP-seq data; (ii) cause-effect relationship between ADAR1 expression and the global RNA editing level based on a drug-treated human cell line perturbation experiment, (iii) local clustering patterns of candidate sites from a distance-based analysis, and (iv) RNA secondary structure propensity. The results from these analyses strongly suggest that an appreciable proportion of the RNA variants we identified result from the ADAR1-mediated A-to-I RNA editing process.RNA editing is a widespread nucleotide modification mechanism through which specific nucleotides are modified by RNA editing enzymes at the RNA level without altering template genomic DNA . AdenosiS1 Table). We developed a rigorous bioinformatics pipeline to detect SNVs, which includes (i) removing low-quality reads, (ii) identifying viral reads using Fastv [Fig 1B). For 19 samples investigated, one sample had no detectable SNVs; and among the remaining samples, we observed a consistent pattern of A>G and T>C substitutions showing the highest abundance, followed by C>T and G>A substitutions in 17 samples . The dominance of the two SNV types, A>G and T>C, corresponding to potential A-to-I RNA editing events , was consistent at different VAF cutoffs across the 17 samples . It should be emphasized that several sources may contribute to these observed SNVs, including sequencing errors, single nucleotide polymorphisms , de novo mutations, and acquired RNA editing events in human cells. To distinguish high-confidence A-to-I RNA editing events from other types of variations, we applied a series of filters to the A>G/T>C variants in the 17 samples. First, given (i) the Illumina sequencing error rate is known to be ~0.1% [−6 substitutions per site per cell infection [de novo mutations as well as very weak RNA editing sites. Second, given the prevalence of SARS-CoV-2 SNPs has been estimated to be 9.6 nucleotides between any two viral sequences [Fig 1E and S2 Table). We further examined the flanking sequences of these candidate editing sites and observed a preference for G depletion and enrichment at the nucleotides 5’ and 3’ to the editing sites (-1 and +1 position), respectively, which is consistent with the context signal previously reported in human transcripts  [Fig 2B), most of which are in ORF1ab, followed by the spike protein . Fig 2D shows their position distribution along the viral RNA genome.To study the potential effects of A-to-I RNA editing in SARS-CoV-2, we first performed a systematic analysis of metatranscriptomic sequencing reads of bronchoalveolar lavage fluid samples of COVID-19 patients obtained from four independent studies  tbe ~0.1%  and (ii)nfection , we filtequences , we also –16. In tde novo mutations. To address this challenge, we sought to test whether our candidate pool was enriched for genomic and functional features that are known to be specific to A-to-I RNA editing. ADAR1 is the major enzyme responsible for most A-to-I RNA editing signals observed in humans [Fig 3A). We achieved extremely high performance with this model in cross-validation . We further validated the model performance using 10,000 independent human A-to-I RNA editing sites [Fig 3C). Notably, because our model was trained based on human sequences, which inevitably caused the model to learn features specific to both ADAR1 binding and the human genomic context, predicted ADAR1 binding affinity scores cannot be compared across different species directly. Instead, it is more appropriate to compare different sites for their relative ADAR1 binding affinity within the same species because they share the same genomic context. Confirming our hypothesis, the RNA editing sites detected in SARS-CoV-2 showed a significant shift towards higher ADAR1 binding scores . We also found that the enrichment ratio increased with the score cutoff value . This result indicates that many of these RNA editing candidate sites indeed tend to bind to ADAR1.Although we followed the best common practice in the RNA-editing field to identify a set of high-confidence A>G/T>C mismatch positions that served as an A-to-I RNA editing candidate pool, as discussed above, it is impossible to exclude the potential contributions of other sources, e.g., n humans ,18. Becan humans . Thus, wn humans , we builn humans , which ing sites  and obseFig 4A) [−4,  the inhibitory effect was more striking for p110 mRNA isoform, S3 Fig). Consistently, we observed much lower average RNA editing levels across the candidate sites . In addition to the sample-wise comparison, we analyzed the editing-level change per site and found that 63 out of the 84 (75%) editing sites with sufficient coverage showed a decreased editing level, significantly higher than random expectation . This result demonstrated a direct effect of host ADAR1 on the dynamics of viral A-to-I RNA editing. Second, RNA editing sites are known to form local clusters. Indeed, the RNA editing candidate sites showed a much shorter distance to neighboring RNA editing candidate sites than randomly sampled, same-size A/T control sets . Third, A-to-I RNA editing is known to be specific to double-stranded RNA structures. Using a computational RNA structure prediction algorithm, CROSS [Fig 4E). Indeed, the proportion of RNA editing sites was significantly higher than that of non-edited sites in secondary structure regions using different propensity-score cutoffs . These multiple lines of evidence strongly suggest that a considerable proportion of our inferred RNA editing candidate sites result from ADAR1-mediated A-to-I RNA editing.We further evaluated other RNA-editing specific features of the candidate pool in multiple aspects. First, to test the causal relationship between the expression of ADAR1 and the global RNA editing level, we obtained the RNA-seq data generated from a human lung cell line model following SARS-CoV-2 infection  . In the m, CROSS , we asseFig 5A) or considering the edited alleles at these sites  and found distinct tree topologies. Second, epitope-based vaccines have been under intensive investigation for COVID-19 prevention. We recently reported that RNA editing contributes to peptide diversity, and editing-derived epitopes can elicit immune responses in cancer cells [S3 Table).Finally, we examined the potential impact of A-to-I RNA editing events on two aspects of COVID-19 research. First, the phylogenetic analysis of SARS-CoV-2 plays a key role in studying the virus origin and evolutionary patterns. Although the vast majority of the RNA editing events have a low editing level, several cases can reach a very high level , thereby likely being identified as major alleles in the genome assembly. Thus, RNA editing signals may confound the phylogenetic inference. To demonstrate this point, we compared phylogenetic trees for seven samples from two studies (SRP142226 and SRP248092) after either excluding the 10 heavily edited sites  the A>G/T>C mismatches are more enriched among SNVs with an extremely low VAF , but we As an additional source of genetic variations, A-to-I RNA editing induced by human host cells would accelerate the overall evolution of SARS-CoV-2. Similar to spontaneous mutations, the fate of an RNA editing event depends on the fitness effect it causes: it can be subjected to purifying selection if it is deleterious or positive selection if it is advantageous. Given the very low editing levels, the fixation probability of the vast majority of A-to-I RNA editing events would probably be low. However, quantitative assessment of the fixation and evolutionary fate of such RNA editing events is challenging due to several reasons. First, it is hard to estimate the real RNA editing rate per generation from the observed VAF in bulk RNA-seq data, as the RNA editing level can be a result of multiple generations . Second, our knowledge about the fitness landscape of RNA editing events in SARS-CoV-2 is very limited (if any). Third, it remains unclear which model the virus evolution follows in host cells . Interestingly, we also observed C>T/G>A peaks in the SNV spectrum, which might reflect C-to-U RNA editing. These two types of RNA editing processes may cancel each other’s effects on GC content in the viral genome to some extent. Further efforts are required to investigate the functional consequences of A-to-I editing events and assess whether C-to-U RNA editing also exists.We note that two recent studies reported similar host-dependent RNA editing activities of SARS-CoV-2 in human cells ,28. Howehttps://github.com/OpenGene/fastv) to extract viral reads.All the sequencing data were generated as metatranscriptomic reads from bronchoalveolar lavage fluid of COVID-19 patients. We employed Fastp  to obtaihttps://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2/). We extracted the flanking sequences centered on each editing site to assess the preferred sequence contexts.Viral reads were aligned against the reference genome of SARS-CoV-2  with BWA MEM . We firsFig 2A). In light of a 40-round hyper-parameter random calibration, we ended up with a model with a CNN layer of 32 filters, a bi-LSTM layer of hidden size 100, an Adagrad optimizer, a Xavier initializer, a learning rate of 0.046, a dropout ratio of 0.3, and the number of learning steps as 5,000.We employed a state-of-the-art deep neural network architecture as detailed previously  to buildTo rigorously validate the ability of our prediction model to identify true A-to-I RNA editing sites, we assessed whether it would robustly distinguish the proximal flanking sequences of known RNA editing sites from the distal ones. We first randomly selected 10,000 RNA A-to-I editing sites from a pool of RNA events in a lymphoblastoid cell line annotated in the RADAR database . Then, whttps://github.com/OpenGene/fastv) to extract viral reads. Viral reads were aligned against the SARS-CoV-2 reference genome (NC_045512.2) with BWA MEM [To validate whether the identified RNA editing sites are directly modulated by ADAR1 activity, we analyzed a public RNA-seq dataset in which ADAR1 was inhibited . In brief, the SARS-CoV-2 receptor ACE2 was over-expressed in a lung adenocarcinoma cell line, A549. The cells were then treated with ruxolitinib (a JAK1 and 2 kinase inhibitor) or control, denoted as SARS-CoV-2_Rux and SARS-CoV-2, respectively, and infected with SARS-CoV-2. The expression level of ADAR1 and its isoforms was calculated by Cufflinks, and a two-tailed Student’s t-test was employed to evaluate the statistical significance between the two groups. To quantify RNA editing level across the six samples, we downloaded fastq files from SRA (Accession No. SRP253951). We employed Fastp  to obtai BWA MEM . For eacFor each A-to-I editing site, we calculated the shortest distance (nt) between this site and its two immediate neighbor editing sites, and we obtained the median value across all the sites. We performed the same analysis for 1,000 control sets, each consisting of the same numbers of A and T, randomly sampled from the SARS-CoV-2 genome. We compared the median values of the true RNA editing set against those control sets to assess the statistical significance.The secondary structure propensity score of the SARS-CoV-2 sequence was based on the SHAPE-MaP profiling data . To consTo reconstruct phylogenetic trees, we first inferred the genome sequences of the seven samples by replacing the reference nucleotides with SNVs with a VAF of ≥ 50%. We reconstructed the phylogenetic trees using Unweighted Pair Group Method with Arithmetic mean algorithm (UPGMA) from MEGA-X  under twTo evaluate the possibility of epitopes introduced by RNA editing, we extracted both wild-type and edited peptide sequences around the missense, high-confidence A-to-I RNA editing events. We performed eluted ligand likelihood prediction using the netMHCpan (v4.0) webserver . We onlyS1 Fig(TIFF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 TableSheet 1: Annotation of 144 high-confidence RNA editing sites; Sheet 2: The numbers of the high-confidence editing sites and related edited reads in each sample; Sheet 3: Details of all potential A-to-I RNA editing (A>G/T>C) calls in each sample; and Sheet 4: Details of all SNVs types (including A>G/T>C) in each sample.(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.