Catalytic RNAs, or ribozymes, catalyze diverse chemical reactions that could have sustained primordial life in the hypothetical RNA world. Many natural ribozymes and laboratory evolved ribozymes exhibit efficient catalysis mediated by elaborate catalytic cores within complex tertiary structures. However, such complex RNA structures and sequences are unlikely to have emerged by chance during the earliest phase of chemical evolution. Here, we explored simple and small ribozyme motifs capable of ligating two RNA fragments in a template-directed fashion (ligase ribozymes). One-round selection of small ligase ribozymes followed by deep sequencing revealed a ligase ribozyme motif comprising a three-nucleotide loop opposite to the ligation junction. The observed ligation was magnesium(II) dependent and appears to form a 2′–5′ phosphodiester linkage. The fact that such a small RNA motif can function as a catalyst supports a scenario in which RNA or other primordial nucleic acids played a central role in chemical evolution of life. Extant RNA catalysts, or ribozymes, such as group I introns5, self-cleaving ribozymes9, and the functional RNA core of the ribosome machinery10, are viewed as evidence that RNAs are capable of catalyzing important biological reactions. Furthermore, in vitro selection experiments of ribozymes from random RNA sequences have yielded artificial ribozymes that can catalyze diverse chemical reactions with impressive efficiency12. However, most of these natural and synthetic ribozymes contain a complex catalytic core within a large structure. Long RNA sequences necessary to encode such ribozymes are not likely to have emerged by chance during the early phase of chemical evolution. It is likely that simpler and smaller, perhaps less efficient, ribozymes played crucial roles in primordial life before the evolution of complex and more efficient ribozymes.The RNA world hypothesis proposes that at an early phase of prebiotic evolution, RNA played the role of both a carrier of genetic information and catalysts of various reactions that are needed to sustain primordial lifeIn this work, we explored such simple ribozymes that can catalyze template-directed ligation of RNA fragments. Specifically, we selected ribozymes that can catalyze the formation of a phosphodiester linkage between a free 3′ terminus of an RNA fragment and a 5′-triphosphorylated RNA fragment from a small RNA library with 7 or 8 randomized nucleotides. We discovered a small catalytic core comprising a three-nucleotide motif located opposite to the ligation junction. The ligation yielded a 2′–5′ phosphodiester linkage. Our results suggest that the potential roles of simple RNA motifs with catalytic activity in the origin of life deserve further investigations.13, we systematically minimized an RNA ligase F1* originally discovered by the Joyce group14 through multiple rounds of ribozyme sequence design and high-throughput assay. F1* contained a 35-nt catalytic core which we minimized to 18-nt  distinct sequences. The library was allowed to react for 4 h at 42 °C in EPPS pH 8.5 buffer supplemented with 25 mM MgCl2 with the substrate fragment T7Psub. T7Psub was designed to hybridize with the substrate-binding region of the ribozyme library to place its 3′-terminus in proximity to the 5′ end of the ribozyme. The ligated products were isolated by polyacrylamide gel electrophoresis (PAGE).Lib-N7/8 contains 81,920  in the presence of T7Psub using NUPACKsub Fig. a. Sequen2, ~ 18% of FAM-T7Psub reacted after 8 h in a linear fashion (kobs = 2.3 × 10−2 h−1)  and 50 mM (kobs = 0.10 h−1) .We confirmed the ribozyme activity of N8-1 by conventional polyacrylamide gel electrophoresis (PAGE). Fluorescently-labeled T7Psub (FAM-T7Psub) was reacted with an excess unlabeled N8-1 to approximate a first-order reaction. The reaction products were sampled at different time points and analyzed by PAGE. Intensities of bands corresponding to the unreacted FAM-T7Psub and the ligated FAM-T7Psub were measured to calculate the fraction of FAM-T7Psub that was ligated (FL: fraction ligated). With 10 mM MgCl17. As a positive control, we synthesized a native 3′–5′ ligation product of FAM-T7Psub and N8-1 using T4 RNA ligase. Treatment of the N8-1-catalyzed ligation product with Dz8-17-N8-1 yielded no detectable cleavage product while the T4 RNA ligase-catalyzed ligation product was clearly targeted by the DNAzyme  8–17. DNAzyme 8–17  to assess the sequence requirements in the vicinity of the ligation junction Fig. a. The fi23. Similarly, laboratory evolution experiments of artificial ribozymes have mostly focused on optimizing catalytic activity, thus generally resulted in rather complex sequences and structures. Less attention has been paid to smaller and less efficient ribozyme sequences, as such sequences are quickly lost in laboratory evolution experiments. A notable exception is a 5-nucleotide trans-aminoacylating ribozyme discovered by the Yarus group. A remarkably small catalytic core comprising 3 nucleotides was shown to catalyze acylation of the 2′-hydroxyl group of a tetranucleotide substrate24.Natural ribozymes such as group I intron have highly evolved and complex structures with high catalytic efficiencies18. While this motif looks intriguingly similar to N8-1, the observed ligation rate was markedly lower (kobs = 5.4 × 10−5 h−1) albeit at different conditions 18. More recently, Mutschler et al., discovered a tetranucleotide loop motif 5′ GAAA 3′ that catalyzes ligation between a fragment containing a 2′,3′ cyclic phosphate terminus with another fragment with a 5′-hydroxyl terminus in a template directed fashion yielding a 2′–5′ ligation linkage25. Interestingly, the catalytic motif (J4) and the ligation junction appear somewhat similar to that of N8-1  was found to catalyze 2′-5′ ligation Fig. c18. WhilWe identified a new motif comprising only three nucleotides that significantly accelerates templated-directed RNA ligation. Combined with few other examples of similarly small catalytic motifs, it is reasonable to expect other simple RNA motifs exist that can catalyze additional reactions. While these small ribozymes exhibit modest catalytic efficiencies compared to the larger, more extensively engineered counterparts, they could have played important roles in primordial living systems before the emergence of complex machinery that can accurately replicate long RNAs.The oligo DNAs and RNAs were purchased from Sigma-Genosys or Eurofins with cartridge purification. The sequences are provided in Table Libraries with 7 degenerate bases (N7) and 8 degenerate bases (N8) were prepared separately, and they were mixed in 1:4 ratio so that each variant was represented equally in the final library (Lib-N7/8). To prepare the DNA templates for in vitro transcription, 2 μM each of the forward (LibT7P-f) and the reverse (LibT7P-N7-rt3-r or Libt7P-N8-rt3-r) oligos were annealed and extended by OneTaq 2X Master Mix with Standard Buffer (New England Biolabs) in 200 μL volume. The reaction solutions were first denatured at 94 °C for 5 min followed by two cycles of 94 °C for 30 s, 56 °C for 30 s, and 68 °C for 8 s. Afterwards, the solutions were kept at 68 °C for 3 min to ensure complete extension. The DNA templates were purified by DNA Clean & Concentrator-5 kit (Zymo Research).2O) was added and kept at 37 °C for 10 min to digest the DNA template. The transcribed RNA libraries were purified using RNA Clean & Concentrator-5 kit (Zymo Research). The RNA libraries were stored at -80 °C until use.The library DNA templates were transcribed into RNA libraries using ScriptMax Thermo T7 RNA Polymerase Kit (Toyobo) according to the manufacturer’s instructions. Specifically, the reactions were performed in 10 μL volume using 200 ng of the DNA template. In vitro transcription reactions were performed at 50 °C for 1 h. Subsequently, 10 μL of DNase solution (2 μL Recombinant DNase I (New England Biolabs), 2 μL 10 × DNase I buffer, 6 μL H2, 10% RNase Inhibitor, Murine (New England Biolabs) was added to the RNA solution to initiate the ligation reaction for 4 h at 42 °C. The reaction was stopped by addition of 36 μL stop solution (1:2.6 mix of 0.5 M EDTA and 2X RNA Loading Dye from New England Biolabs) and was stored at − 80 °C until gel purification.Eight microliters of the Lib-N7/8 (1.5 μM) RNA was mixed with 4 μL of the substrate T7Psub (24 μM). The mixture was incubated at 70 °C for 3 min and then placed on ice. Four microliters of the 4 × reaction buffer  was added to the crushed gel to extract the RNA at 4 °C while shaking at 600 rpm for 4 h . The extracted RNA was isolated from the gel by a spin column , and the RNA was ethanol precipitated using Quick Precip Plus Solution (EdgeBio). The RNA pellet was washed with 70% ethanol and suspended in 10 μL of nuclease free water.2O  was incubated at 65 °C for 5 min followed by incubation on ice. Then, a mixture of 2 μL 5 × buffer, 0.25 μL RNase inhibitor, and 0.5 μL reverse transcriptase were added . The reaction was performed at 65 °C for 30 min followed by heat inactivation at 85 °C for 5 min. The resulting cDNA (0.5 μL) was PCR amplified using OneTaq 2X Master Mix with Standard Buffer (New England Biolabs) in a total volume of 20 μL with 0.2 μM primers (R2-T7P-f and R1-bc2-T7P-rt3-r). The reaction solutions were first denatured at 94 °C for 1 min followed by 12 cycles of 94 °C for 30 s, 52 °C for 30 s, and 68 °C for 8 s, followed by a 3 min incubation at 68 °C. The PCR product was diluted 25-fold with water. This diluted product (15 μL) was further amplified using Q5 High-Fidelity 2X Master Mix in a 100 μL reaction with 0.5 μM primers (TruSeq-i7-UDI0003 and TruSeq-i5-UDI0003). The reaction solutions were first denatured at 98 °C for 30 s followed by 20 cycles of 98 °C for 10 s, 69 °C for 30 s, and 72 °C for 10 s, followed by a 2 min incubation at 72 °C. The PCR product was purified using 3% agarose gel and was submitted for sequencing analysis using MiSeq (Illumina).The purified RNA was reverse-transcribed using Maxima H Minus Reverse Transcriptase (Thermo Fischer Scientific) according to the manufacturer’s protocol. Briefly, a mixture of RNA (2.5 μL), 10 μM primer rt3-r (1 μL), 10 mM dNTP mix (0.5 μL), and 3.25 μL HThe sequencing library was analyzed using MiSeq Reagent Kit v3 (Illumina). Single reads for 130 bases were acquired. Raw sequencing data (fastq file) were analyzed by a custom Python script. The reads that contained the expected constant sequences were used to extract the randomized 7 or 8 bases. Only those sequences that yielded quality score of 20 or greater in all randomized positions were retained and counted for analysis. In total, 100,392 reads were obtained.2, 5% RNase inhibitor) were prepared. The RNA mixture and the 4 × reaction buffers were separately incubated at 42 °C for 3 min before mixing to initiate the ligation reaction . The reaction was carried out at 42 °C. At appropriate time points , 4 μL from the reaction solution was collected and mixed with 9 μL stop solution on ice. The samples were stored at -80 °C until PAGE analysis.DNA template for in vitro transcription was prepared as described above using oligo DNAs T7p-N8-1-f and N8-1-rt3-r. The DNA template was used to generate N8-1 ligase RNA by in vitro transcription as described above. An RNA mixture containing 12 μL of 8.2 μM N8-1 ligase RNA and 6 μL of 2.4 μM FAM-T7Psub was incubated at 70 °C for 3 min and then placed on ice. Separately, 6 μL of 4 × reaction buffers . The ligated and unligated susbtrates were imaged and quantified using a Typhoon FLA9500 imager . Band intensities were measured by ImageJ to calculate the percentage of the substrates that were ligated at each time point.In vitro transcribed N8-1 RNA was treated with Quick CIP (New England Biolabs) to remove the 5′ triphosphate, and then monophosphorylated by T4 polynucleotide kinase (Takara) according to the respective manufacturer’s instructions. The phopsphorylated N8-1 RNA was ligated to FAM-T7Psub by T4 RNA Ligase 1 (New England Biolabs) following the manufacturer’s protocol, and the ligated product was purified by PAGE as described above. This RNA was used as the 3′–5′ linkage control product. Similarly, ribozyme catalyzed products were purified from the reaction between N8-1 and FAM-T7Psub using PAGE.2, 250 mM EPPS, pH 8.5), 0.665 μL RNase Inhibitor, and 0.665 μL of 20 mM spermidine , and the mixture was incubated at 37 °C for 1.5 h. TURBO DNase (Thermo Fisher Scientific) and its reaction buffer were added to the final concentration of 0.2 U/μL  and incubated at 37 °C for 30 min to digest the DNAzyme. Finally, 13.3 μL RNA Loading Dye (2X) was added and analyzed by PAGE as described above.The (enzyme or ribozyme) ligated RNA (125 fmol) was mixed with 100 pmol DNAzyme (Dz8-17b-N8.2) in a 4 μL solution containing 100 mM KCl, 50 mM Tris–HCl pH 7.5, and 0.25 mM EDTA. The mixture was heated to 95 °C for 1 min, then cooled to 37 °C (0.1 °C/s), kept at 37 °C for 10 min, and finally cooled to 4 °C. DNAzyme catalyzed RNA digestion was initiated by adding 1.33 μL 5 × buffer  at 42 °C for 4 h. The reaction was stopped by adding 36 μL of the stop solution on ice. The ligated RNA was recovered and processed for sequencing as described above. Two independent experiments (ligation reaction) were performed.Lib-N5 was prepared as described above for Lib-N7/8 except for using oligo DNAs LibT7P-f and LibT7P-N5 for DNA template production. Lib-N5 RNA (0.75 μM) was ligated to T7Psub (6 μM) in a total volume of 16 μL in the reaction buffer . After reverse transcription using rt3-r as the primer, the first PCR was performed with primers R2-T7P-f and R1-bc#-T7P-rt3-r (after ligation) or R2-lig-f and R1-bc#-T7P-rt3-r (before ligation). “bc#” denotes the barcode sequence that identifies “before” or “after” ligation and the two replicate experiments. The second PCR was performed as described above.The reads were sorted by the barcode and checked for the complete constant sequences. Sequences with all randomized positions yielding quality score of 30 or greater were retained and counted. The total number of reads for the four groups of experiments  ranged from 195,928 to 696,654.2 concentration of 25 mM at 42 °C. The samples were quenched at 4 h and analyzed by PAGE as described above.DNA templates for in vitro transcription was prepared as described above using oligo DNAs analogous to T7p-N8-1-f with appropriate mutations at the second and third nucleotides of the transcribed ribozyme and N8-1-rt3-r. The DNA templates were used to generate N8-1 variants by in vitro transcription as described above. Ligation reactions were performed as described above, with the final MgClSupplementary Information 1.Supplementary Information 2.


RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA’s conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I–III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base–base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications. RNA plays major roles in various biological processes, including virus replication, gene transcription, and protein synthesis ,2,3,4,5.There are some experimental methods to determine the RNA structure. Unfortunately, X-ray crystallography only determines static structures, and RNA structures’ flexibility often prevents the formation of RNA crystals . AlthougAt present, many algorithms have been developed for predicting and identifying RNA pockets. For example, 3 V, MSPocket, PocketFinder, and CHUNNEL are used to identify static pockets given a single RNA conformation ,21,22,23In this work, we provide a computational approach, RPflex, to calculate the conformational flexibility of RNA pockets. The 3154 pockets from 160 NMR RNA-related structures are first divided into 297 groups by similarity using a coarse-grained lattice model. Then, we introduce the flexibility score to quantify the pockets’ topological flexibility. The flexibility scores show a strong correlation with RMSF calculations (Pearson correlation coefficient of 0.53–0.76 in Testing Sets I–IV). The network calculations provide a mechanism for pocket flexibility by network interaction changes. We further analyzed 178 ligand- and 284 protein-binding pockets to reveal the recognition mechanism and interaction characteristics. Our results suggest that most ligand-binding pockets are relatively rigid, and some protein-binding pockets are relatively flexible. We believe RPflex could help the understanding of pocket flexibility to accelerate RNA-related drug design.We divided 160 RNA-related structures of the RNA dataset into thirteen categories based on their functions: rRNA (13), mRNA (10), tRNA (2), viral RNA 32), telomerase RNA (10), snoRNA (2), 7sk RNA (2), dsRNA (4), IRES (9), ribozyme (12), riboswitch (6), aptamer (12), and others (46) . Figure , telomerTo compare the pocket flexibility and structural flexibility, we calculated the RMSFs of the pockets and the corresponding structural models. Larger RMSF values indicate higher flexibility, while smaller RMSF values indicate more rigidity. For example, the snoRNA (PDB code: 6HYK) is the U14 snoRNA K-turn motif (kt-U14) determined by NMR. Chagot et al. demonstrated that the structure of kt-U14 is stabilized upon Snu13p binding to control the assembly of many cellular RNPs and their downstream processes . Here, wAnother example is the structure (PDB code: 1NYB) consisting of an amino-terminal bacteriophage φ21 N protein in complex with a boxB RNA. Cilley et al. discovered the φ21 boxB RNA adopts a stem-loop structure with a lack of stable hydrogen bonds . Here, wAs mentioned above, the conformational changes in pockets can reflect structural flexibility. Although RMSF can describe pocket flexibility at the atomic level, it ignores the topological features that are essential for pocket-like geometric structures. Therefore, there is an urgent need for a theoretical approach to measuring pocket flexibility in terms of topological characteristics.Through RPflex, we calculated the flexibility score (Q) to quantify pocket flexibility by the coarse-grained lattice model. Compared to measuring flexibility by RMSF, the flexibility score considers the topological features of pockets, including volume, surface area, and sphericity. A larger value of Q indicates higher flexibility. Then, we divided the pocket dataset into three classes based on the flexibility score: rigidity, 130 pocket groups (0 < Q < 0.30); intermediate flexibility, 119 pocket groups (0.30 ≤ Q < 0.60); and flexibility, 48 pocket groups (0.60 ≤ Q) .3 [To validate the correlation between RMSFs and Qs, we divided the 297 pocket groups into Testing Sets I–III based on the overlapping volume: small ( groups) . In Tabloups)  consists of an amino-terminal bacteriophage φ21 N protein in complex with a boxB RNA . CompariThe structural elements have been successfully applied to RNA complex structure prediction. However, understanding the higher level of pocket flexibility is still limited. To test if the higher level of pocket flexibility can identify native-like RNA complex structures, we ran the popular RNA structure prediction program (RLDOCK) on complex structures (PDB code: 1ARJ and 1F7I) to build sampling structures and evaluate the prediction accuracy. For topological principles of the recognition mechanism, the rigidity pockets with a volume of 527~1338  classes . Figure To construct a diverse RNA dataset, we extracted the RNA-related structures from the Protein Data Bank (20 October 2021) with the search options “RNA” and “NMR”. We extracted the RNA-related structures with a single RNA chain that binds to ligands or a single-stranded protein. There are three types of NMR structures: RNA (358 entries), RNA–ligand (54 entries), and RNA–protein (41 entries). Then, we removed the short (less than 20 nucleotides) and highly complex (more than 120 nucleotides) RNA structures. To acquire the non-redundant dataset, we used the CD-hit to remove the redundant RNAs with RNA sequence identities >80% ,47. ThenTo construct the pocket dataset, the pockets of an NMR structure with multiple structural models were recognized by the 3V server using the rolling probe method ,48,49. THere, we focus on exploring the conformational flexibility of RNA pockets, using the flexibility score to quantitatively describe topological changes globally. The flexibility score is calculated by the geometric topology of pockets using the coarse-grained lattice model. The coarse-grained lattice model scales the box for the pocket size and divides the box space into 3D grids of small cubes . The first step is to calculate the pocket similarity using the coarse-grained lattice model A. For q Then, we figured out The second step is to divide milarity B. Here, The third step is to calculate the flexibility score to quantify the conformational flexibility of each pocket group C. For 𝓂 Larger Q values indicate higher flexibility, while lower Q values indicate more rigidity.We constructed structure networks to capture the effect of interactions between nucleotides on pocket flexibility. The fragment of RNA tertiary structure forming a pocket is transformed into a network in which nucleotides are nodes, and non-covalent interactions with each other are edges. Previous work has shown that 8  studies . If two lization .To characterize the network characteristics, we calculated the average degree  verified the pocket flexibility by using GROMACS. Here, we used overlapping nucleotides to measure flexibility. We define the overlapping nucleotides as a nucleotide that occurs more than 50% in a pocket group. The overlapping nucleotides forming the first pocket in each pocket group were used as the reference positions. For a pocket group, the nucleotide-averaged RMSF is calculated byFor a pocket group, We utilize the atom-level model for interaction calculation. First, we consider the nucleotides as six chemical groups: phosphate, ribose, adenine, cytosine, guanine, and uracil . For proa server .In this work, we developed the RPflex to analyze the flexibility of RNA pockets. This new approach considers the topological properties and three-dimensional conformation of pockets. RPflex uses a coarse-grained network model to quantify flexibility by pocket features. Combining the network interactions, our method provides local and long-range interaction information and better characterizes pocket flexibility. The result shows that the ligand-binding pockets prefer to be more rigid compared to protein-binding pockets. The base–base hydrogen bonds stabilize the RNA structure, and ribose–ribose van der Waals contacts optimize the structure. In addition, we constructed a pocket dataset that provides information on topology properties and flexibility characteristics. We hope that the analysis of pocket flexibility will facilitate the discovery of druggable pockets and contribute to future drug design.


Bacillus altitudinis. The linear forms promote B. altitudinis tolerance to H2O2 stress, partly through increased translation of a stress-responsive gene, htrA. The 3′ end sequences of the linear forms are crucial for RNA circularization, and formation of circular forms can decrease the levels of the regulatory linear cognates. Bioinformatic analysis of available RNA-seq datasets from 30 bacterial species revealed multiple circular RNA candidates, distinct from DucS, for all the examined species. Experiments testing for the presence of selected circular RNA candidates in four species successfully validated 7 out of 9 candidates from B. altitudinis and 4 out of 5 candidates from Bacillus paralicheniformis; However, none of the candidates tested for Bacillus subtilis and Escherichia coli were detected. Our work identifies a dual-conformation regulatory RNA in B. altitutidinis, and indicates that circular RNAs exist in diverse bacteria. However, circularization of specific RNAs does not seem to be conserved across species, and the circularization mechanisms and biological functionality of the circular forms remain unclear.Circular RNAs have been extensively studied in eukaryotes, but their presence and/or biological functionality in bacteria are unclear. Here, we show that a regulatory noncoding RNA (DucS) exists in both linear and circular conformation in  Bacillus altitutidinis, and provide evidence for the existence of other circular RNAs in diverse bacterial species.The presence and/or biological functionality of circular RNAs in bacteria are unclear. Here, the authors identify a dual-conformation (linear and circular) noncoding RNA that promotes tolerance to oxidative stress in  The major working mode of these sRNAs is roughly analogous to that of eukaryotic microRNAs, mediated by short base pairing to regulate multiple target mRNAs, which can be as many as ~1% of all mRNAs for a single sRNA2. This base pairing alters mRNA stability or translation, thus resulting in the inhibition or activation of target gene expression. Nonetheless, some sRNAs act through direct interactions with regulatory proteins, e.g., the RNA component of the ubiquitous signal recognition particle (SRP) and sRNA CsrB/CsrC which sequester the small protein CsrA5. To date, all bacterial noncoding RNAs have been reported to function in linear forms.In the last 20 years, bacterial small RNAs (sRNAs) have gone from biological curiosity to being recognized as a major class of posttranscriptional regulators7. Circular RNAs have been shown to not only be involved in a variety of human diseases but also participate in plant stress responses8. Circular RNAs are also discovered in archaea, whose gene expression are more similar to eukaryotes. In archaea, circular RNAs can be formed from excised tRNA-introns and rRNA processing intermediates, as well as a few functional noncoding RNAs, including box C/D RNA, RNase P, and SRP RNA12. In bacteria, the identified circular RNAs are all from the autocatalytic Group I and II introns, a class of self-cleaving ribozymes14, except for a predicted circular tmRNA, whose presence was supported only by bioinformatic analysis15.Circular RNAs, a class of noncoding RNAs first found in eukaryotes more than 40 years ago, have recently been shown to exert biological functions by acting as decoys, transporters, scaffolds, templates for translation, etc.Bacillus strains are important industrial enzyme producers16, and many commercial enzymes, including proteases, amylases, xylanases, and lipases, have been characterized and purified from different Bacillus species20. To explore posttranscriptional regulation in Bacillus strains, we previously identified a set of sRNAs in Bacillus altitudinis SCU11 , a productive strain of extracellular alkaline protease, through an RNA-seq-based approach and subsequent validation by northern blotting22. We noticed that one actively transcribed novel sRNA gave rise to multiple transcripts, some with abnormal sizes. In this work, we report that this sRNA is a dual-conformation small noncoding RNA (DucS) that is found as linear and circular forms simultaneously, and confirm that DucS plays a positive regulatory role in the oxidative stress tolerance of B. altitudinis. Circular RNAs may represent a new area of bacterial noncoding RNA research.B. altitudinis SCU11 with a predicted size of 225 nucleotides (nt) according to transcriptome analysis and northern blotting verification22. DucS is encoded by the intergenic region of the B. altitudinis chromosome that exists only in several closely related species, including B. pumilus, B. cellulasensis, B. safensis, and B. xiamenensis  was constructed through the CRISPR‒Cas9 system, and the complementation strain was established by introducing plasmid-borne DucS into the ΔducS strain. Northern blotting assays revealed that both the wild-type (WT) and complementation strains produced multiple unexpected bands on denaturing urea-polyacrylamide gel electrophoresis  and transcriptional terminator site (TTS) of DucS. The sequencing results showed that the TSS of DucS was uniquely mapped to G946314 of the B. altitudinis SCU11 genome, whereas the TTS was variable. The most prevalent TTS and the longest TTS were mapped to A946512 (named TTS1st) and T946545 (named TTS2nd), respectively , was evaluated in the ΔducS strain  should be initiated at the same TSS. Then, we investigated whether they were generated by terminating at variable sites, such as through read-through. To test this hypothesis, oligonucleotide probes corresponding to downstream regions of TSS and two TTSs, denoted olig1, 2, and 3, were used for northern blotting analysis  to degrade processed transcripts but spare primary transcripts harboring 5′ triphosphates. Then, the treated RNA was used as a template for the cRACE assay (an improved 5′ and 3′ rapid amplification of cDNA ends from circularized RNA)ely Fig. . Based osis Fig. . As a posis Fig. , we spec946513, the next nucleotide after TTS1st A946512, whereas the 5′ termini were variable. Most 5′ termini of the junctions corresponded to TSS G946314 (named the S1 junction), and a small fraction was located in the region approximately 26–35 nt downstream of the TSS (named the S2 junction)  Fig. . Accompaon) Fig. . In view28. While the convergent primers amplified PCR products of the expected size, the divergent primers also generated clear products with RNase R-treated samples; meanwhile, a linear reference mRNA could not be amplified in this system  PCR was first applied to validate the circular form of DucS by using two sets of primers. The divergent primers were used to amplify the circular RNA only, while the convergent primers were used as positive controls to amplify both linear and circular forms Fig. , left. Rtem Fig. , right. ons Fig. , which wely Fig. , left. Tely Fig. . Collectely Fig. .32. No classical Group II intron structure was found in the DucS sequence through conserved Group II intron prediction . The in vitro self-splicing assay suggested that DucS could not perform self-splicing and give rise to circular RNA in vitro , A (DucSMA), and G (DucSMG)  Fig. . To our MG) Fig. . Furtherion Fig. . DucSΔ10ion Fig. . Altoget33, in combination with GLASSgo34, was applied to target prediction, and the top 5 candidates  as a reporter. The assay was based on the co-expression of a translational fusion of the 5′ region of htrA mRNA and sfgfp (htrA::sfgfp) controlled by a constitutive promoter with or without DucS under its native promoter in the ΔducS strain. The yerD::sfgfp fusion was used as a negative control since no interaction was detected between yerD and DucS in the EMSA. While the expression of DucS did not affect yerD fusion  to test whether DucS affected the level of HtrA protein. Western blotting revealed that more HtrA protein appeared in the presence of DucS  to increase translation  to investigate their interactions with htrA. As the results showed, although mutations at M1 and M4 did not alter the regulation of DucS, mutations at two G-rich regions (M2 and M3) attenuated the activation of the htrA::sfgfp fusion, and the M2/M3 double mutant abolished the regulation , and conversely, the circular RNA deficiency mutant possessed very stable linear RNAs, independent of the two growth phases  and two strains from natural habitats  were used for experimental validation of circular RNA candidates with high abundance. As described above, RNase R-treated total RNA from four strains was used for RT‒PCR assays using convergent and divergent primers simultaneously. Finally, 7 out of 9 candidates from B. altitudinis SCU11 and 4 out of 5 candidates from B. paralicheniformis were identified by divergent primers  or in E. coli K-12 MG1655 (0/8). To provide further evidence, five candidates from B. altitudinis, including the well-studied SRP RNA, were detected by northern blotting 45 and ATP-dependent RNA ligase (Rnl)46, have been shown to be involved in RNA circularization in archaea. Direct experimental evidence is required to elucidate circular RNA biogenesis in bacteria, this may also be helpful to reveal the mechanism in eukaryotic organelles.The biogenesis of nuclear circular RNAs in eukaryotes is tightly controlled by pre-mRNA splicing machinery. However, circular RNA generation in organelles is fairly elusive, even though mitochondrial and chloroplast genome-encoded circular RNAs have been identified and proven to play important rolesE. coli and B. subtilis failed to be detected by RT‒PCR. Finally, eleven circular RNA candidates from B. altitudinis or B. paralicheniformis were found by both methods, and the most interesting candidate was the well-known noncoding SRP RNA, which was detected in both strains. The signal recognition particle (SRP) is a ribonucleoprotein complex conserved in all three domains of life, playing an essential role in the co-translational targeting of secretory and membrane proteins. SRP RNA is pivotal for the structure and function of all SRPs, and the structures of SRP RNA of bacteria, archaea, and eukaryotes show a high degree of similarity to each other47. The canonical SRP RNAs exist as linear and structured RNAs whose 5′ and 3′ regions are clamped together. The circular SRP RNA in B. altitudinis shows an increased abundance with growth, even though it is significantly lower than that of the linear forms. Do the circular forms of SRP RNA possess functional potential in bacteria, or are they just transcription noise since they are absent in B. subtilis? Considering its increasing tendency with the growth of B. altitudinis and the few species of the archaeal genus Thermoproteus containing only circular SRP RNAs to function12, it is worthwhile to explore the contribution of the circular form in the future.Advances in high-throughput sequencing and associated bioinformatics tools have facilitated the discovery of circular RNAs, such as studies in eukaryotes, archaea, and bacteria. However, it is well known that the reverse transcription step in RNA-seq library preparation can generate artifactual sequences. Therefore, experimental approaches are required to validate the presence of circular RNAs prior to subsequent functional exploration. In regard to the circular RNA candidates predicted from 30 bacteria in this study, two commonly used methods, divergent RT‒PCR and northern blotting in combination with RNase R digestion, are applied for experimental identification. Among the four tested strains, candidates from 48, it is reasonable to assume that circular RNAs in bacteria, at least those with high abundance, may have yet unidentified biological roles. Several recent reports describe that sRNAs contained in bacterial outer membrane vesicles can be transferred to hosts, such as human airway cells, acting as pathogen-host interkingdom communication tools, as they can modulate host gene expression49. Because circular RNAs are very stable and resistant to most RNA-degrading machinery, they may possess special advantages in regulating gene expression intracellularly and extracellularly.The functional significance of circular RNAs has only been explored preliminarily, even in eukaryotes, which is at least in part due to limitations of the tools used to study them. Similarly, functional characterization of bacterial circular RNAs will be a case-by-case scenario and a huge challenge, and new methods need to be developed for bacteria. Considering that the formation of circular DucS RNAs inevitably leads to a reduction in linear RNA (L1) level, we can speculate that circular RNAs play an indirect regulatory role by antagonizing the level of functional linear RNAs. Given that eukaryotic circular RNAs were initially considered byproducts of RNA splicing and that processing byproducts of bacterial RNAs can function as regulatory sRNAs or RNA spongesB. altitudinis SCU1121 was obtained by combined mutagenesis from the parent strain BA06 (accession number CGMCCC 0518). This strain was previously classified as B. pumilus and recently re-classified to B. altitudinis based on genome phylogeny50. The plasmids were transferred into B. altitudinis by electroporation. Liquid Luria-Bertani  medium or solid medium containing 1.5% (w/v) agar served as routine cultivation media. Unless indicated otherwise, the liquid cultures were cultivated as follows: the overnight culture was adjusted to OD600nm of 1 and transferred to fresh LB medium at a ratio of 1%, then grown at 37 °C with shaking at 200 × g until indicated period. For the oxidative stress experiments, liquid cultures were grown to OD600nm of 1 and then divided into two aliquots. Equal volume fresh LB was added, and cells were challenged with or without 1.5 mM H2O2. Where appropriate, antibiotics were supplemented at the following concentrations: 100 μg/ml ampicillin for E. coli and 20 μg/ml kanamycin for B. altitudinis SCU11.The bacterial strains used in this study are listed in Supplementary Data 51 was used for the stable expression of sRNA or gene in B. altitudinis. Plasmid pJOE899952 carrying CRISPR-Cas9 system was used for Bacillus gene editing. For deletion of the sRNA or gene chromosomal region, DNA fragments upstream and downstream of the target sequence were amplified respectively from B. altitudinis SCU11 chromosomal DNA by PCR. Two fragments were fused to a single fragment by overlapping PCR. The fusion fragment with flanking BsaI sites and chemically synthesized sgRNA spacer sequence (designed by http://crispr.dfci.harvard.edu/SSC/) were inserted into plasmid vector pJOE8999. To construct the sRNA expression plasmid, the chromosomal fragment including DucS and its upstream and downstream regions (0–300 bp) was amplified by PCR. The fragments with flanking XbaI/EcoRI sites were cloned into plasmid pSU03. Site-directed mutagenesis of DucS in pSU03 was carried out according to the QuikChange® protocol (Stratagene). The deletion mutations of DucS in pSU03 were generated by amplifying respective parental plasmids using the corresponding divergent primers with homologous sequences. Positive clones were selected on plates with 100 μg/ml ampicillin, and confirmed by sequencing.Plasmids and primers are detailed in Supplementary Data htrA mRNA was constructed as described previously53. Briefly, the 5′ UTR and the first 27 codons of htrA mRNA was amplified from B. altitudinis SCU11 chromosomal DNA. The superfolder green fluorescent protein segment (sfgfp) was amplified from plasmid pCN33-egfp. Two segments were recombined to form htrA::sfgfp fusion by overlapping PCR. The fusion fragment was inserted into Acc651 and EcoRI sites of plasmid pSU03 with or without (control) DucS expression cassette, resulting pHtrA::sfGFP and pDucS-HtrA::sfGFP.The interaction system between DucS and target htrA, DNA fragments upstream and downstream of the termination codon of htrA gene were amplified from B. altitudinis SCU11 chromosomal DNA by PCR. The fragments and chemically synthesized 3×FLAG sequence were fused to form htrA::3xFLAG by overlapping PCR. The fusion fragment was inserted into the Acc651 and EcoRI sites of pSU03 with or without (control) DucS expression cassette, resulting pHtrA::3xFLAG and pDucS-HtrA::3xFLAG.For construction of 3xFLAG-tagged g for 1 min at 4 °C and the pellets were stored at −80 °C. Cell pellets were resuspended in 120 μl of lysozyme (5 mg/ml), and incubated at 37 °C for 10 min. Total RNA was extracted by TRIzol reagent. The purified total RNA was quantified with a NanoDrop ND-2000 spectrophotometer. For the northern blotting assay, 1–5 µg of total RNA was separated by electrophoresis on an 8% polyacrylamide 1×TBE-urea (7 M) gel. Electrophoresis was conducted at 120 V for 1 h 40 min and then transferred onto a positively charged nylon membrane . RNA was cross-linked to the membrane with 1200 mJ of UV. Digoxigenin-labeled RNA probes were prepared by in vitro transcription with a DIG Northern Starter Kit22 . The procedure of hybridization was performed as described previously54. Briefly, the membranes were prehybridized for 30 min at 65 °C in DIG Easy Hyb Granules hybridization buffer, then probed with 10 pmol of DIG-labeled probe for 12–16 h. After high-stringency (2×SSC) and low-stringency (0.1×SSC) washes, membranes were blocked and hybridized using blocking solution and Anti-digoxigenin-AP, respectively. Detection was accomplished with a ChemoCam Imager . The 16S rRNA was used as the loading control. For RT-PCR assay, the total RNA treated with or without RNase R was reverse-transcribed by random hexamers as primers using the PrimeScript™ RT reagent kit with gDNA Eraser . The primers for amplification of selected sequences are listed in Supplementary Data Bacterial cells were harvested by centrifugation at 10, 000 × 55. RNase R digestion reaction was carried out at 37 °C for 30 min in 10 μl with 1× reaction buffer , total RNA (2–10 μg), and RNase R (6–30 U). For control reaction, RNase R was substituted with DEPC-treated water. The reactions were stopped by adding 2 × RNA loading dye . The treated RNA samples were used directly for northern blotting or purified for RT-PCR.RNase R  was used to degrade linear RNA. Briefly, the total RNA after heating at 95 °C for 5 min and cooling on ice for 2 min was split into two aliquots: one for RNase R digestion and the other for control without digestion23. Briefly, Total RNA was firstly incubated with Terminator™ 5′-PhosphateDependent Exonuclease  at 30 °C for 1 h to remove 5′ monophosphate RNA and heated at 70 °C for 5 min to stop reaction. Then RNA was treated with RNA 5′ pyrophosphohydrolase  to convert 5′ triphosphate RNA into 5′ monophosphate RNA and purified by phenol/chloroform extraction. The resulted RNA was then circularized in 50 μl reactions containing 2 μl of T4 RNA ligase I , ATP and buffer according to the manufacturer’s recommendations. Reactions were allowed to proceed for overnight at 16 °C and purified with phenol/chloroform. The circularized RNA was then subjected to reverse transcription by random primer, PCR amplification with specific primers, PCR products cloning, and sequencing. 5′ and 3′ end fusions were analyzed by mapping DNA sequence of DucS using SnapGene (Version 3.3.1).cRACE was used to determine 5′ and 3′ extremities of DucS transcripts by RT-PCR across the ligation site of circularized RNA as template as described previouslyhttp://rna.informatik.uni-freiburg.de/IntaRNA/Input.jsp). For in vitro transcription assay, template DNA was generated by PCR using gene-specific oligonucleotides with a T7 promoter sequence at the 5′ end of the forward primer. The primers used to amplify DucS sRNA, the 5′ UTR of targets and its nearby sequence are listed in Supplementary Data g, 4 °C. This was then transferred to an equal volume of a 24:1 solution of chloroform/isoamyl alcohol and centrifuged for 5 min at 13,000 × g, 4 °C. RNA was precipitated from the aqueous phase by adding 2 volumes of ethanol and 0.1 volume of 3 M of NaOAc (pH 5.2) solution. RNA precipitation was dissolved in RNase-free water.Interaction regions between DucS and target genes were predicted using online tool IntaRNA . The reaction mixtures without EMSA binding buffer were incubated for 2 min at 95 °C and placed on ice for 2 min. Then REMSA binding buffer was added and incubated at 37 °C for 30 min. RNA was separated by 8% Native PAGE (0.5× TBE) which was pre-run for 30 min at 100 V and 4 °C. The separation was conducted for 40 min at 100 V and 4 °C, stained with SYBR Gold nucleic acid gel stain  for 10 min, and visualized under UV light.An RNA-RNA EMSA assay was performed to verify the interaction of RNAs, as previously described59. Briefly, precursor RNA was heated to 70 °C for 5 min and immediately placed on ice for 3 min, then incubated in 50 mM Tris-HCl (pH 7.5), 10 mM MgCl2, 10 mM DTT, with (for group I intron) or without (for group II intron) 2 mM GTP at 55 °C (for group I intron) or 45 °C (for group II intron) for 15 min. Then, the products were fractionated on a 4% polyacrylamide gel under denaturing conditions. The separation was conducted for 60 min at 150 V, stained with SYBR Gold nucleic acid gel stain  for 10 min, and visualized under UV light.The assays are used to evaluate whether DucS circular RNAs are formed through group II or group I intron processing mechanism. In vitro transcribed RNAs were used for self-splicing assay, performed as previously describedB. altitudinis strains (adjusted to OD600nm of 1) were transferred to fresh LB medium at a ratio of 2%, then grown at 37 °C for 3 h and 6 h with shaking at 200 × g. Rifampicin (inhibitor of transcription initiation) was dissolved in dimethylsulfoxide (250 mg/ml) and added to bacterial cultures at a final concentration of 500 µg/ml. Samples were collected after 0, 8, 16, 24, and 32 min and mixed immediately with 0.2 volumes of stop-buffer . RNA was extracted for northern blotting analysis. Transcript half-lives (t1/2) of DucS L1 and L2 were calculated by pixel counting (ImageJ software) from three biological replicates.The overnight cultures of 600nm of 1) were transferred to fresh LB medium at a ratio of 2%, then grown for 10 h at 37 °C with shaking at 200 × g. Supernatant and cell pellets were harvested from 1 ml culture by centrifugation at 12,000 × g for 10 min at 4 °C. The equal amount of intracellular protein extracted from pellets was separated via SDS-PAGE (12%) gels as loading control. The supernatants representing extracellular proteins were separated via SDS-PAGE (12%) gels and subsequently transferred onto PVDF membrane . The membrane was incubated in blocking solution (2.5 g powdered milk in 50 ml 1× TBS containing 0.1% Tween 20 (TBS-T)) for 1 h. After 2 × washing for 10 min in TBS-T, the membrane was incubated at 4 °C for overnight with the anti-FLAG mAb , which was diluted 1:2500 in 1× TBS-T milk. After 2 × washing for 10 min in TBS-T, anti-mouse antibody (1/5000) coupled with Alexa Fluor® 680 Conjugate was incubated at room temperature for 1 h. Azure biosystems C500 was used to detect the signals.The overnight cultures . The overnight cultures (adjusted to OD600nm of 1) of each strain were transferred to fresh LB medium at a ratio of 2%, then grown at 37 °C with shaking at 200 × g. To compare expression levels, the fluorescence intensity (FI) and OD600nm of cultures at indicated time after inoculation were measured by microplate reader . Control samples not expressing fluorescent proteins were used to subtract background fluorescence. Normalized fluorescence (FI/OD600nm)60 was used for comparison. The specific excitation and emission wavelengths for detection of the sfGFP reporter were 448 and 507 nm, respectively.B. altitudinis SCU11 were downloaded from NCBI. Based on the sequence of DucS in length of 232 nt, every 30 nt sequence of DucS were aligned to all raw reads, then the high quality matched raw reads (mapped by 30 nt DucS sequence with up to two mismatches) were extracted and mapped to B. altitudinis SCU11 genome visualizing by Kblamm software.RNA-seq BAM file (Accession number SRR8892267) and reference genome (NZ_CP038517.1) of 61. Then, all the unmapped reads were used to identify circular RNAs by CIRCexplorer262. We used a cut-off for circular RNA candidate’s statistics when at least five junction reads were detected, and junctions were aligned uniquely to the genome within 1000 nt.The paired-end RNA-seq BAM files of 30 bacteria were downloaded from NCBI . 33 parameters by extract mRNA regions of 300 nt (from 200 nt upstream to 100 nt downstream of the start codon), from 23 homologous strains searched by GLASSgo34. Interactions between targets and DucS were predicted by IntaRNA63. Promoter and terminator region were predicted by BPROM (http://www.softberry.com/berry.phtml?topic=bprom&group=programs&subgroup=gfindb) or FindTerm (http://www.softberry.com/berry.phtml?topic=findterm&group=programs&subgroup=gfindb).30 transcriptomes and genomes of bacteria downloaded from GenBank were used to circular RNA analysis. Targets prediction by CopraRNA in the Supplementary Data Further information on research design is available in the Supplementary informationPeer Review FileDescription of Additional Supplementary FilesSupplemenrary Data 1Supplemenrary Data 2Supplemenrary Data 3Supplemenrary Data 4Supplemenrary Data 5Supplemenrary Data 6Supplemenrary Data 7Reporting SummarySource Data


Small RNA sequencing has been widely used for characterizing the landscape of small non-coding RNAs—the most abundant cargo in extracellular vesicles (EVs). Here, we performed a systematic assessment of the quality, technical, and potential biological biases introduced by different EV isolation methods and the enrichment of specific, small RNA biotypes in EVs. The findings in this study guide the quality control of EV small RNA-seq and the selection of EV isolation techniques and enhance the interpretation of small RNA contents and the preferential loading of specific RNA biotypes into EVs.Motivation: Extracellular vesicles (EVs) are produced and released by most cells and are now recognized to play a role in intercellular communication through the delivery of molecular cargo, including proteins, lipids, and RNA. Small RNA sequencing  has been widely used to characterize the small RNA content in EVs. However, there is a lack of a systematic assessment of the quality, technical biases, RNA composition, and RNA biotypes enrichment for small RNA profiling of EVs across cell types, biofluids, and conditions. Methods: We collected and reanalyzed small RNA-seq datasets for 2756 samples from 83 studies involving 55 with EVs only and 28 with both EVs and matched donor cells. We assessed their quality by the total number of reads after adapter trimming, the overall alignment rate to the host and non-host genomes, and the proportional abundance of total small RNA and specific biotypes, such as miRNA, tRNA, rRNA, and Y RNA. Results: We found that EV extraction methods varied in their reproducibility in isolating small RNAs, with effects on small RNA composition. Comparing proportional abundances of RNA biotypes between EVs and matched donor cells, we discovered that rRNA and tRNA fragments were relatively enriched, but miRNAs and snoRNA were depleted in EVs. Except for the export of eight miRNAs being context-independent, the selective release of most miRNAs into EVs was study-specific. Conclusion: This work guides quality control and the selection of EV isolation methods and enhances the interpretation of small RNA contents and preferential loading in EVs. Extracellular vesicles (EVs) are lipid-bound particles that are secreted from cells into the extracellular environment. Although EVs were initially considered to be part of a waste-removal mechanism to discard unwanted cellular materials , increasAmong the variety of molecular cargo in EVs, small non-coding RNAs are the most abundant, including miRNAs, rRNA fragments, tRNA fragments, Y RNAs, snRNAs, and snoRNAs ,17. AmonSmall RNA sequencing has been widely used for characterizing small RNA landscapes in EVs ,41,42,43We used the terms “(exosome OR exosomes OR ectosomes OR microvesicles OR microvesicles OR “EV” OR “extracellular RNA” OR (extracellular AND vesicle) OR (extracellular AND vesicles)) AND “Homo sapiens”[porgn] AND “gse”[Filter]) NOT “exosome complex” NOT “nuclear exosome” NOT “RNA exosome” AND “high throughput sequencing”[PTYP]“ to search the Gene Expression Omnibus (GEO) and the Sequence Read Archive (SRA). In addition, we reviewed all datasets deposited in the ERCC and publications listed on vendor websites selling exosome extraction kits. We downloaded and manually checked all publicly available datasets from the GEO, SRA, and ERCC. We only kept small RNA-seq datasets from human EVs and removed those from non-vesicles, non-small RNA-seq, or other organisms. To ensure EVs are enriched, we only kept studies where EVs were isolated using either commercial exosome extraction kits, such as Exo-Quick, ExoEasy, qEV, and total exosome isolation kit , or differential ultracentrifugation, which have been proven to isolate high-yield and high-purity EVs ,50,51,52https://github.com/chc-code/findadapt, accessed on 23 October 2022). The adapter patterns identified by FindAdapt, including adapter sequences and random bases at 5′ and 3′ ends, were provided to our standard small RNA-seq analysis pipeline, TIGER, for adapter trimming, reads mapping to host and non-host genomes, and quantification and differential expression of a variety of small RNA biotypes [www.bioinformatics.babraham.ac.uk/projects/fastqc (accessed on 23 October 2022)). After trimming, reads were first mapped to a customized database built from the host genome (GENCODE GRCh37.p13) and from known sequences of host mature transcripts curated in specific library databases (such as for miRNAs in miRbase and tRNAs in GtRNAdb2) by Bowtie1 (v1.3.0) [We processed and analyzed all the raw sequencing data uniformly. Since a variety of commercial and customized small RNA library preparation kits were used, different adapter patterns were included in raw reads because adaptor sequences are not always available. To streamline the analysis, we developed a Python package, FindAdapt, for fast, accurate, and automatic detection of adapter patterns without any prior information (biotypes . Brieflybiotypes  was used(v1.3.0) , allowinThe proportion of total mapped reads and host genome reads was calculated by the number of total mapped reads and host genome reads divided by the total number of reads after trimming. Small RNA abundance was determined by the number of small RNA reads divided by the number of host genome reads. The abundance of each type of small RNA was determined by the number of reads that mapped to that type of small RNA relative to the total number of small RNA reads. To reduce the potential bias from characteristic compositions of different EV isolation methods, three-way ANOVA with the EV isolation method as a confounding variable was used to estimate the significance of enrichment or depletion of RNA biotypes in EV compared to cells. The expression of miRNAs was normalized to the median value across all samples to identify highly expressed miRNAs in both EVs and cells, as well as EV-specific miRNAs. For each study with matched cell and EV samples, DESeq2  was usedAfter excluding 513 samples from the donor cells, we assessed the quality of 2243 EV datasets using the total number of reads after adapter trimming, the overall mapping rates to both the host and non-host genomes, the total number of reads and the mapping rates to the host genome only, and the proportion of small RNA and miRNA reads . After at-test: p = 2.37 × 10−5/0.02). EVs from urine obtained a larger IQR in small RNA proportions than EVs from other biofluids (t-test: p = 0.003).We further explored the median and the interquartile range (IQR) of small RNA proportions within each study. The IQR is a measure of variability, and a high IQR suggests high variability in the study. Most studies obtained high median values (>0.9) and small IQRs (<0.06), indicating high abundances and low variability in small RNA content . Severalt-test: p = 0.006/0.002/0.03/0.008/0.26, differential ultracentrifugation compared to Exo-Quick kit, ExoEasy, ExoRNeasy, qEV, and total exosome isolation kit, respectively). To reduce the potential bias introduced by different experimental conditions and small RNA extraction methods, we focused on studies of plasma only and further narrowed down to those using miRNeasy kits for RNA purification. Comparing the variability after restricting to these studies resulted in the same conclusion: that differential ultracentrifugation purification consistently showed higher variability and lower replicability in small RNA proportions within each study , and differential ultracentrifugation. Sorting studies by EV extraction methods, we found that differential ultracentrifugation generally resulted in significantly larger IQRs in small RNA proportions than other methods, except total exosome isolation kit , indicating that their high abundance was not likely to be biased by different EV isolation methods. Among the nine miRNAs, mir-451a and miR-144 have been previously reported to show higher levels in human EVs compared to cellular levels [Focusing on specific miRNAs, we found that 15 miRNAs were abundant in both EVs and donor cells A, includr levels .We calculated the differential expression of miRNAs between EVs and matched cellular levels. Eight miRNAs were found to be preferentially exported into EVs in a context-independent way  found that parental cells expressed abundant levels of small RNA, while the small RNA content in EVs was modest and highly variable across samples . If the Despite the challenges above, we sought to determine global enrichment for each small RNA biotype. We found that miRNAs and snoRNA fragments are generally more likely to be retained in cells rather than exported into EVs, while rRNA fragments and tRNA fragments are more likely to be released into EVs. This finding may provide a clue toward understanding the selective sorting of small RNAs into EVs. miRNAs are typically associated with Ago2 within RISC complexes, but eukaryotic cells express multiple Ago proteins. Differential association with Ago proteins, as is observed in plants ,106, couWe analyzed the overall quality of all the publicly available small RNA-seq data on EVs. We found that small RNA reads in EVs were mainly derived from miRNAs, Y RNAs, and fragments of rRNA and tRNA. We further evaluated the technical and potential biological biases introduced by different EV isolation techniques in terms of small RNA proportions. The analysis presents a global picture of quality in EV small RNA-seq experiments and guides future quality control and selection of EV isolation methods.We further studied the preferential enrichment of small RNA biotypes in EVs compared to their cellular levels. We revealed that miRNAs and snoRNA fragments are more likely to be retained in cells, while rRNA fragments and tRNA fragments are more likely to be transported into EVs. Although several miRNAs showed an overall preference to be either loaded into EVs or retained in cells, selective sorting of miRNAs into EVs was mostly study-specific. Together, our findings shed light on the preferential loading of specific RNA biotypes into EVs.


Escherichia coli, though the details of how ProQ binds these RNAs remain unclear. In this study, we used a combination of in vivo and in vitro binding assays to confirm key structural features of E. coli ProQ’s FinO domain and explore its mechanism of RNA interactions. Using a bacterial three-hybrid assay, we performed forward genetic screens to confirm the importance of the concave face of ProQ in RNA binding. Using gel shift assays, we directly probed the contributions of ten amino acids on ProQ binding to seven RNA targets. Certain residues  were found to be essential for binding of all seven RNAs, while substitutions of other residues (K54 and R62) caused more moderate binding defects. Interestingly, substitutions of two amino acids , which are evolutionarily variable but adjacent to conserved residues, showed varied effects on the binding of different RNAs; these may arise from the differing sequence context around each RNA’s terminator hairpin. Together, this work confirms many of the essential RNA-binding residues in ProQ initially identified in vivo and supports a model in which residues on the conserved concave face of the FinO domain such as R58, Y70, and R80 form the main RNA-binding site of E. coli ProQ, while additional contacts contribute to the binding of certain RNAs.RNA-binding proteins play important roles in bacterial gene regulation through interactions with both coding and noncoding RNAs. ProQ is a FinO-domain protein that binds a large set of RNAs in  Escherichia coli and Salmonella enterica, which bind distinct, but partly overlapping RNA pools  participate in the regulation of gene expression in bacteria, contributing to the maintenance of cellular homeostasis and adaptation to environmental changes . Hfq andNA pools . ProQ bienterica , and conenterica , 2017, aenterica , motilitenterica , carbon enterica , adaptatenterica , and virenterica . While HSupplemental Figs. S1, S2; E. coli and S. enterica ProQ, the FinO amino-terminal domain (NTD) is connected via a long, positively charged linker to the carboxy-terminal Tudor domain (CTD)  FinO protein (in (CTD) . The Finin (CTD) .E. coli ProQ FinO domain that are protected by the binding of two RNAs, cspE and SraB, have been mapped using hydrogen–deuterium exchange experiments   assay  to detec of ProQ . The NMRoli ProQ  suggesteoli ProQ . Intriguoli ProQ  to fall Lpp1663) , as welloli ProQ . The latE. coli ProQ were quite distant from one another; (ii) will the effects of mutations observed for the few RNAs examined so far hold true for a more diverse set of RNAs bound by ProQ; and (iii) whether all of the critical residues for in vivo interactions are directly involved in RNA binding, rather than mediating indirect cellular effects?At the end of our previous work, three primary questions remained unanswered: (i) how do we explain that the amino acid residues found to be required for RNA binding on the FinO domain of E. coli ProQ, using our B3H assay and a compensatory mutagenesis screen to shed light on the location of the conserved R80 residue. The results of this unbiased screen support a structural model in which the side chain of R80 points through to the concave face of the FinO domain, close to other RNA-binding residues and to the position of this side chain in structural homologs. Building on this structural insight, we have conducted the first in vitro site-directed mutagenesis experiments with E. coli ProQ to probe the contributions of both conserved and more variable amino acids on RNA binding. Gel shift and quantitative analysis of 12 ProQ mutants revealed that certain amino acids have differential contributions to binding across seven natural RNA ligands, suggesting that ProQ may utilize distinct contacts with different RNA ligands. Further, we explored the properties of RNA structure that contributed to differential interactions with ProQ’s FinO domain and demonstrated the importance of single-stranded regions both upstream and downstream from terminator hairpins. Overall, this work advances a model in which the concave face of the FinO domain serves as the main RNA-binding site of E. coli ProQ, and residues on the periphery of this surface tune interactions with different RNA ligands.In this work, we have used both in vivo and in vitro binding experiments to resolve these unanswered questions about ProQ–RNA interactions. We have probed the in vivo structure of the FinO domain of cspE-3′, SibB, and malM-3′. Surprisingly, even the very conservative substitution of arginine to lysine at position 80 eliminated RNA binding to a similar extent as an alanine for all RNAs tested .We previously used an in vivo B3H assay to examine the effects of mutations on ProQ–RNA interactions , but no other substitutions at either position were found to support detectable binding in vivo. This confirms that both Y70 and R80 are uniquely required for RNA interaction. Indeed, these residues are both highly conserved across FinO-domain sequences and are located near one another in a concave pocket in most solved structures of FinO domains .The inability of lysine to substitute for arginine at residue 80 is analogous to the strongly deleterious effect we previously observed of a conservative Y70F substitution on RNA binding in vivo . We wondE. coli ProQ’s interaction with RNA, it was important to clarify if these residues are indeed located on opposite faces of the protein as previously suggested  or in other FinO domain proteins . We then used a saturation mutagenesis strategy  to create a library of all possible single point-mutations at each of these amino acid positions on the pPrey-ProQR80K plasmid.Given that both Y70 and R80 were important for uggested , especiaR80K, saturation mutagenesis libraries were transformed into B3H reporter cells containing pAdapter and pBait-malM plasmids. Transformants were plated on X-gal-indicator plates, and plasmids were purified and sequenced from colonies that were more blue than a pPrey-empty control. Mutations that partially rescued ProQR80K-malM binding were identified from each of the three mutagenesis libraries constructed . The strongest of these substitutions also resulted in statistically significant but modest rescue of ProQR80K binding to malM-3′ in liquid β-gal assays  and to cspE-3′ and SibB RNAs in plate-based assays . The fact that compensatory effects of substitutions on RNA binding were more evident in plate-based assays with malM-3′ than in liquid β-gal assays or interactions with other RNA ligands is not surprising since they were identified in a plate-based screen with malM-3′ RNA and the conditions of the plate-based assay can be tuned to highlight small differences in β-gal levels . Finally, when V74K and L91V substitutions are modeled into the respective structures as lowest-energy rotamers, the terminal atoms are 9–14Å away from that of a convex-facing R80K . The model also explains why a V74K substitution would rescue a lysine at position 80, as it provides a second amine in hydrogen-bonding distance of R80K in an otherwise hydrophobic environment . In this model, the concave face of the FinO domain looks quite like other structural homologs, with the highly conserved Y70 and R80 residues positioned near one another in a concave pocket.Together, these results lend experimental validation to the AlphaFold model of E. coli ProQNTD in mind, we wished to further explore how specific FinO-domain residues contribute to RNA binding. In particular, we wanted to test whether conclusions from B3H studies with cspE-3′ and SibB RNAs about the importance of specific residues on RNA binding , gapA-3′, SibA and SibB, all of which are specific ligands of ProQ in vivo, and RybB, which is bound by both ProQ and Hfq in vivo. With the exceptions of SibB and RybB, the binding of all these RNAs had already been studied with purified ProQNTD ; only gapA-3′ and RybB bound weaker with Kd values of 14 nM and 26 nM, respectively . Overall, the seven RNAs bound WT ProQNTD with a relatively narrow range of affinities.For binding studies, we used a 130-aa long version of ProQ’s NTD, the RNA-binding properties of which had been previously studied . We firscspE-3′, malM 3′, and SibB (NTD (1 µM) for cspE-3′, cspE81-3′, and malM-3′ RNAs, and no binding detected at all for gapA-3′, RybB, SibA, and SibB RNAs . Because this and subsequent mutations affected the maximum fraction of RNA bound to ProQ, Kd values for experiments where the fraction bound reached at least 40%. Substitutions at R80 were even more deleterious than those at Y70: no binding was detected for any of the seven RNAs to either R80A or R80K mutants , consistent with the strong effect of both mutants in vivo . However, we did not observe improvement in binding compared to the single R80K mutant . This suggests that despite an observable effect in the in vivo B3H assay, the compensatory role of the L91V substitution is too subtle to be detected using a gel shift assay. The lack of an effect could reflect that the complex is not sufficiently stable during the time required for electrophoretic separation. Alternatively, it is possible that the double mutant ProQ might be stabilized inside the cell by interactions with cellular RNAs or an additional factor that could support its function in the three-hybrid assay.To test if the compensatory effects of double mutations observed in the B3H assay can also be observed with an in vitro binding assay, we constructed and purified the R80K-L91V double mutant, which showed restoration of binding to Supplemental Fig. S1). Despite these factors, the T65A mutation had rather small effects on RNA binding by ProQNTD, ranging from no effect on the binding of gapA-3′ and RybB, to twofold weaker binding than WT ProQNTD for cspE81-3′, malM-3′, and SibA, and fourfold weaker binding for cspE-3′ and SibB . In keeping with the modest effects on Kd, the T65A mutant did not alter the maximum fraction bound of any RNA compared to WT ProQNTD. These data suggest that T65 makes only small contributions to RNA binding despite its partial conservation and positioning adjacent to the essential Y70 residue.Next, we analyzed the role of threonine 65, which is close to Y70 on the concave face of the FinO domain A. While Ec ProQ is the only one that contains arginine in this position in the concave-face pocket . While arginine is present in homologous positions of ProQs from related enterobacteria . The mutant protein’s interaction with cspE-3′ was the strongest of all the RNAs with a Kd value only fourfold weaker than WT ProQNTD, although with a fraction bound just above 40% at the highest concentration tested of R62A ProQNTD , demonstrating an essential role of R58 in RNA binding by the ProQ FinO domain. On the other hand, the effects of a K54A mutation were more moderate: the maximum fraction bound only reached about 60% for cspE-3′, 30% for malM-3′, and cspE81-3′, and <20% for gapA-3′ and RybB, while no binding was detected for SibA and SibB . These effects are comparable to those of the R62A mutation described above. Together, these data show that residues K54 and R58 on helix H3 of the FinO domain play important roles in RNA binding.We next turned our attention to two basic residues that were found to be important for in vivo ProQ–RNA interactions and were hypothesized to interact with the double-helical portion of a terminator hairpin . These rcspE, which suggests that K35 could contribute differentially to the binding of distinct RNAs  or threefold  to more than fivefold in the strongest cases (SibA and SibB) . Interestingly, the binding of all seven RNAs to the D41A mutant reached the same maximum fraction bound as with WT ProQNTD . In vitro binding data showed that an R32A mutation does not affect the Kd value of ProQ binding to gapA-3′ and malM-3′ and has only modest two- to threefold detrimental effects on the binding of cspE-3′, cspE81-3′, RybB, and SibA . The only RNA that was markedly affected by this mutation was SibB; while its Kd value was only weakened approximately threefold by the R32A mutation, its maximum fraction bound was reduced to just above 40% . In vitro binding data showed that an R69A substitution had a three- to fivefold detrimental effect on the binding of malM-3′ and cspE-3′, and an eight- to 10-fold effect on interactions with SibA and gapA-3′ . The R69A mutation had an even stronger detrimental effect on the binding of other RNAs: the maximum fraction bound reached by RybB was below 40%, while the binding of SibB was not detected. The large range of effects of the R69A mutation was reminiscent of the effects of K35A, though perhaps qualitatively slightly stronger for each RNA. It is interesting to note that the rank-order of effects caused by K35A and R69A mutations on the maximum fraction bound reached by each RNA were similar, with cspE-3′ being the least affected by either mutation and SibB being the most affected  replaced the two terminal cytidines with uridines . We next introduced additional mutations to make the double-stranded base of the SibB terminator hairpin more like that of cspE-3′. This SibB–cspE chimera now had four A–U base pairs at the base of the terminator and an extended 8-uridine 3′ tail to match that of cspE-3′ . These are considerable improvements from the original SibB RNA, which showed no detectable binding to the R69A mutant, though they do not represent as strong of a binding as seen with cspE-3′ RNA, which reached a maximum fraction bound of 88% to the R69A mutant with a Kd of 20 nM.The results above indicated that several residues, especially K35 and R69, made differential contributions to the binding of the seven RNAs we tested. To explore the basis for these differences, we focused on  in vivo , and bec ligands , we focurom SibB . We intruridines A,B, resu cspE-3′ C,D. WhilNTD to distinct RNAs could result either from disruptions of direct contacts formed by K35 and R69 with specific RNAs or from indirect effects on alterations of contacts with other amino acids. Because R69 and K35 are located outside of the central concave-face pocket that has been proposed to interact with dsRNA . First, we constructed a model RNA (cspE-mini) by removing the minimally structured 17-nt sequence from its 5′ end and introducing guanosines in three locations within this model construct to enable efficient in vitro transcription of further 5′ truncated constructs—at the 5′ end, the base of the terminator hairpin, and above the A–U base pairs at the base of the hairpin , suggesting that loss of a longer 5′ single-stranded tail makes RNA binding more dependent on the K35 side chain. While there were only modest effects of removing the first 17 5′ nt, removal of the remaining single-stranded sequence on the 5′ side . To explore if releasing the 3′-oligoU tail of cspE-3′ would compensate for the contacts to ProQNTD lost on the 5′ of the hairpin, we further removed four adenosines opposite the 3′-oligoU tail (cspE-mini-5′-truncated) . Despite its longer single-stranded oligoU tail, no binding of this construct was detected even for WT ProQNTD. Together, these data show that single-stranded nucleotides 5′-adjacent to the terminator hairpin are essential for the RNA binding by ProQNTD, while nucleotides further upstream of the terminator hairpin do not markedly affect RNA binding to WT ProQ but may make additional contacts to the protein that help compensate for the loss of K35. Importantly, these data are not consistent with either R69 or K35 directly contacting the 5′ single-stranded RNA, since substitution of either residue led to additional loss of interaction of 5′-truncated RNA.We hypothesized that the differential effects of R69A and K35A on the binding of ProQth dsRNA , we wond hairpin A,B. The  cspE-3′ ; Fig. 6BcspE-mini-3′-6U), the 3′ tail of which was shortened from eight to six Us, only two of which are predicted to be single-stranded  was further weakened to this RNA construct, with strong effects seen on the maximum fraction bound for R69A and K35A proteins , the result that a 4-uridine truncation is detrimental for RNA binding is consistent across both constructs.We next examined the effects of a more extensive 3′ truncation, removing an additional two terminal uridines to create ni-3′-4U F. Bindinproteins . The facuncation . While tIn summary, these mutational studies suggest that R69 and K35 both likely contribute to contacts to the core terminator hairpin of the RNA rather than the adjacent 5′ or 3′ sequences. This is consistent with the above observation that the heightened susceptibility of SibB to R69A and K35A mutations is explained by the properties of its terminator hairpin ; Fig. 5.E. coli ProQ. Data collected from both biochemical and genetic experiments support a model in which all residues of the FinO domain of ProQ involved in RNA binding are located on the concave face of this domain. This includes basic and aromatic side chains poised in the concave-face pocket to interact with intrinsic terminators at the 3′ end of many of ProQ's RNA ligands. Our data suggest that additional residues on the periphery of the concave face—and even pointing toward the opposing convex face of the FinO domain—make smaller contributions to RNA binding that are more varied across RNA ligands. Together, these findings strengthen and extend our prior results, showing that nearly all the ProQ residues implicated previously in RNA binding through in vivo methods indeed impact RNA binding directly in vitro, and allowing for nuanced comparisons to be drawn across a variety of RNA ligands.In this study, we set out to refine our model of molecular recognition of RNA ligands by the FinO domain of Ec ProQ) that is critical for RNA binding  as well as in the AlphaFold model for Ec ProQ. For this reason, we used the structure of E. coli ProQ predicted by AlphaFold for downstream structural modeling in this work , substitution with lysine could impact RNA binding either directly by moving the residue's charged terminus away from the RNA, or indirectly by destabilizing the hydrophobic core of the protein. Several of the validated compensatory substitutions could subtly alter the hydrophobic environment surrounding R80 to create space for, or help to reposition, lysine's primary amine. Importantly, even the strongest of the identified compensatory substitutions (L91V and V74K) lead to only modest recovery of RNA binding by the R80K ProQ mutant. This underscores the key role that R80 plays in FinO-domain structures, consistent with its universal conservation.The AlphaFold model provides an explanation for why the seemingly conservative R80K substitution is so strongly deleterious to RNA binding in vivo and in vitro B,C, 3. WE. coli ProQ shares many structural features with the other four FinO-domain homologs with solved structures . The fact that the shape of the concave pocket is almost identical between Lp RocC and Ec ProQ suggests that Ec ProQ may also bind the 3′ terminal two nucleotides in this pocket in the vicinity of Y70, R80, and G37 . Interestingly, a G37A substitution was previously identified as deleterious to Ec ProQ binding in an in vivo forward genetic screen . The fact that similar conclusions were reached for this larger set of RNAs suggests that many of the RNA ligands of Ec ProQ share a similar mode of binding as was seen in the prior genetic study . In addition, two independent genetic screens looking for mutations abrogating the role of ProQ in gene expression regulation in S. enterica isolated substitutions of R80 to histidine, serine or glycine , each of which makes moderate or strong contributions to RNA binding in vitro .The double-stranded stem of the RNA terminator hairpin is contacted in the O domain . Alignmeld model A places in vitro , 7B,C. Oin vitro ; Fig. 3,in vitro . Additio of RocR , while t of RocR , suggest3H assay . Additio hairpin . On the  hairpin . AlthougSupplemental Figs. S7–S13). K35 and R69 are positioned on the concave face and the edge of the convex face, respectively, and occupy evolutionarily variable positions within stretches of highly conserved sequence . The differential contribution of Ec K35 to interaction with cspE-3′ and SibB has been previously observed in the B3H assay . A previous study showed that the optimal binding of malM-3′ and cspE-3′ requires a terminal hairpin stem with a single-stranded tail of at least four uridines . For instance, replacing the two terminal cytidines of SibB with uridines markedly improved the binding of the resulting RNA molecule . However, the analysis of either mutant protein binding to minimal cspE-3′ RNAs was not consistent with K35 or R69 directly contacting RNA on either side of the terminator hairpin, since substitutions at these residues led to additional binding defects beyond those caused by RNA truncations in these regions , listed with the following abbreviations: AmpR (ampicillin and carbenicillin), CmR (chloramphenicol), KanR (kanamycin), StrR (streptomycin), and TetR (tetracycline). All strains were stored as glycerol stocks at −80°C.CP, tethers (ii) a Bait RNA construct upstream of a test promoter such that it is available for interaction with (iii) an RNAP-tethered prey protein  leads to a boost in β-gal levels relative to basal levels indicated by three negative controls in which half of each hybrid component is left out  a DNA–RNA adapter protein, CI-MS2 protein A. Reportleft out B; the stleft out .CP fusion protein, while pCDF-pBAD constructs express the MS2hp fusion RNA and pBR-α expresses the α-ProQ fusion protein. For each transformation, there were three negative controls, one where each of these core plasmids was replaced with an “empty” construct. Single colonies from each transformation were inoculated into 1 mL of LB broth supplemented with 0.2% arabinose and antibiotics: carbenicillin (100 µg/mL), chloramphenicol (25 µg/mL), kanamycin (50 µg/mL), and spectinomycin (100 µg/mL) in a 2 mL 96 well deep-well block (VWR) sealed with breathable film (VWR) and shaken at 900 rpm and 37°C overnight. Overnight cultures were back-diluted (1:40) into 200 µL LB supplemented with the same antibiotics and arabinose as outlined above, as well as 0 µM, 5 µM, or 50 µM IPTG  into optically clear 200 µL flat-bottom 96-well plates covered with plastic lids (Olympus). Mid-log cells (OD600 0.3–0.6) were transferred into a new 96-well plate with rLysozyme and PopCulture reagent (EMD Millipore) and allowed to lyse for 0.5–4 h. Lysate was transferred into a fresh optically clear 96 well plate (Olympus) with Z-buffer, ONPG , and β-mercaptoethanol. β-gal activity was measured by taking OD420 values every minute at 28°C for 1 h using a microplate spectrophotometer (Molecular Devices SpectraMax). OD420 readings were normalized using the OD600 values from directly before lysis to give β-gal activity in Miller units (Liquid assays were performed with the use of the B3H system. Reporter cells (KB473) were cotransformed with pAC-, pBR-, and pCDF-derived plasmids. pAC constructs express the CI-MS2er units . β-gal aSupplemental Figure S4, was calculated by dividing the intensity in the blue channel by the intensity in the red channel (Blue/Red), representing the skew toward blue relative to pure white. Two-tailed, unpaired Student’s t-tests were conducted to assess whether values for each mutant were significantly different from those of R80K.For qualitative plate-based assays, 3.2 µL of mid-log cells from above were pipetted from the 96-well plate onto a large LB agar plate supplemented with inducers (0.2% arabinose and 1.5 µM IPTG), antibiotics  and indicators . Plates were incubated at 37°C overnight, moved to 4°C for at least 1 d, and then photographed with oblique lighting on a black velvet background . Images Cell lysates from β-gal assays were normalized based on OD600 with LB plus PopCulture Reagent. Lysates were mixed with 6× Laemmli loading dye, boiled for 10 min at 95°C and electrophoresed on 10%–20% Tris–glycine gels (Thermo Fisher) in 1× NuPAGE MES Running Buffer (Thermo Fisher). Proteins were transferred to PVDF membranes (Bio-Rad) using a semidry transfer system (Bio-Rad Trans-blot Semidry and Turbo Transfer System) according to the manufacturer’s instructions. Membranes were probed with 1:10,000 primary antibody anti-ProQ overnight at 4°C and then a horseradish peroxidase (HRP)-conjugated secondary antibody . Chemiluminescent signal was detected using ECL Plus Western blot detection reagents (Bio-Rad) and a c600 imaging system (Azure) according to the manufacturer’s instructions.Supplemental Table S4). Otherwise, the primers were complementary to the backbone sequence. For multisite saturation mutagenesis of the R80K vector, multiple forward primers were designed to mutagenize one codon position at a time with a degenerate NNN codon . For each of the three libraries targeting a different 6–7aa region of ProQ, 6–7 forward primers were used in a pooled polymerase chain reaction (PCR) with a single reverse primer. Primers were used in a PCR with 2× Phusion Master Mix (New England Biolabs) and the appropriate parent plasmid: pKB955 (pBrα-ProQΔCTD) for Y70X and R80X libraries and pSP144 (pBrα-ProQΔCTD-R80K) for the R80K multisite compensatory libraries. For Y70X and R80X libraries, PCR products were Kinase–Ligase–DpnI (KLD) treated in 10 µL reactions containing 1 µL PCR Product, 1 µL T4 DNA Ligase (New England Biolabs), 1 µL T4 DNA Ligase buffer (New England Biolabs), 1 µL T4 polynucleotide kinase , 1 µL DpnI (New England Biolabs), and 5 µL MilliQ water. For the multisite-ProQ-R80K libraries, a commercial KLD mixture was used according to the manufacturer’s instructions (New England Biolabs). KLD products for each library were transformed into NEB5α cells. Cells were serially diluted and spread on LB-carbenicillin and incubated at 37°C overnight to provide a near-lawn for library preparation and to allow for estimates of colony numbers . Plasmid for each library was directly miniprepped from a cell slurry harvested from the overnight plates and stored at −20°C for further use.Single-site mutagenesis was performed using Q5 site-directed mutagenesis. Mutagenic forward and reverse primers were designed using NEBaseChanger. For the Y70X and R80X library plasmids, a region of the primer representing the single codon of interest was replaced by a mixture of 25% of each nucleobase in each of the three sites, written as “NNN” in the primer sequence  and pCW17 (pAdapter). Cells were heat-shocked and plated on LB agar supplemented with inducers (0.2% arabinose and 1.5 µM IPTG), antibiotics  and indicators . Plates were incubated at 37°C overnight. Each time that a transformation was performed, positive and negative controls were transformed alongside the experimental conditions to allow for comparison of blue/white levels . The plates were transferred from the 37°C incubator to 4°C once colonies had grown to sufficient size, ∼18 h. Plates were stored at 4°C for a minimum of ∼5 h and a maximum of ∼3 d before being examined for the presence of blue colonies. Colonies that showed any blue color above that of pPrey-empty negative-control colonies were restruck on indicator plates to ensure single blue colonies. Plasmid from these colonies were miniprepped and sent for sequencing. Sequences were aligned to the sequence of wild-type E. coli ProQ to identify mutations at the codon of interest.Screens of these library plasmids were performed with the use of the B3H assay. The plasmid libraries were transformed into KB473 reporter cells pretransformed pKB1210  of ProQ were cloned into pET15b vector (Novagen), as described (6-tag and TEV protease recognition sequence (ENLYFQ↓S), so an additional serine residue remains after the cleavage of the amino-terminal His6-tag. The mutated variants of NTD of ProQ were obtained by site-directed mutagenesis, where the substitutions were introduced by specifically designed primers  to change a single amino acid in the protein sequence. All constructs were overexpressed in BL21 Δhfq strain , and purified as described . RNA molecules were transcribed with T7 RNA polymerase and purified using denaturing gel electrophoresis, as described (32P labeled using T4 polynucleotide kinase (Thermo Scientific), followed by phenol–chloroform extraction, purification on denaturing gel and precipitation with ethanol.The DNA templates used for in vitro transcription were obtained by Taq polymerase extension of chemically synthesized overlapping oligodeoxyribonucleotides , and incubated for 30 min at RT in low-protein binding microplates pretreated with a solution containing 0.0025% bovine serum albumin (BSA). After this time, reactions were loaded onto a 6% polyacrylamide gel (19:1) running in 0.5× TBE buffer at 4°C. After the electrophoresis, gels were vacuum-dried and exposed to phosphor screens overnight. The signal was quantified using a phosphorimager and MultiGauge software (Fuji FLA-5000), data were fitted to a quadratic equation using GraphPad Prism software, and the equilibrium dissociation constant (Kd) values were calculated as described . In each binding reaction, 1 nM escribed . The aveSupplemental material is available for this article.