When the two groups (lung metastasis and liver metastasis) were compared, the liver metastasis group had more bone metastasis than the lung metastasis group , but the lung metastasis group had more brain metastasis (8.9% vs. 11.5%) (p = 0.023). In a study of overall survival (OS) in the ICI era for mRCC, we found that lung metastasis was significantly associated with improved survival compared to liver metastasis (p < 0.001: 7 months vs. 4 months). This survival advantage restricted in lung metastasis group of mRCC after adjusting age, sex, race, marital status, histological type, metastasis to bone, and brain, origin, radiotherapy record chemotherapy record, surgery on multivariable using Cox proportional hazard model . The overall survival difference between the variables of the lung metastasis and liver metastasis was noted among most of the variables, with survival benefits restricted to patients in lung metastasis in the ICI era. Patients who had undergone chemotherapy and surgery were strongly positive predictors for better OS  , and ,  in lung metastasis group and liver metastasis group. The c-index of the prognostic nomogram for OS prediction was 0.74 and 0.73. This study found that patients with lung metastasis who received ICI had better survival than those with liver metastasis. Chemotherapy and surgery enhanced survival in kidney cancer patients, whereas radiation had little impact. We developed a complete and realistic nomogram for mRCC patients based on distant metastases to the lung and liver.Patients with metastatic renal cell cancer (mRCC) for whom surgery is ineffective may experience a poor prognosis. The different sites where cancer has spread, and the different ways to treat it in the immune checkpoint inhibitors era could help clinical decision-making. In this study, individuals with mRCC were selected from the SEER database between 2015 and 2016 based on the Food and Drug Administration (FDA) approval of ICIs. A total of 4011 mRCC patients were studied (2239 with lung metastasis vs. 797 with liver metastasis in the immune checkpoint inhibitors period). The age  RCC is one of the most common urinary system tumors, with clear cell carcinoma histology accounting for 60%–85% of all renal carcinomas. The global prevalence of kidney cancer has increased from around 200,000 new cases in 1990 to 393,000 in 2017, with almost 400,000 new cases found in 2018. At the current time, 20%–40% of people with a new diagnosis of RCC have metastatic disease . The greThe treatment plans for patients with advanced-stage RCC have been difficult to implement. However, since 2011, FDA has approved several immunotherapeutic drugs for cancer, indicating that treatment options for patients with metastatic RCC have rapidly expanded over the last decade, with targeted ICI emerging as the new cornerstone treatment modality. Clinical studies are exploring many innovative ICI to examine if they might improve anti-tumor immune responses . The ICIThe ethics statement permitted us to read the SEER research data files retrieved using the reference number 10237-Nov2018. The SEER database does not require informed patient consent for information distribution. SEER* Stat software was used to identify individuals with additional treatment data from SEER 18 registries in 2018. (version 8.3.9). As part of its mission, the National Cancer Institute’s (NCIs) SEER program collects and reports cancer incidence and survival data from a variety of sources. These figures are from central cancer registries in the United States, which cover roughly 30% of the population. SEER data includes patient demographics, initial tumor location, morphology, diagnosis stage, an initial course of cancer therapy, and vital status follow-up. We collected by selecting the primary site labeled of kidney site with years (2015−2016) which according to the FDA are treated with ICI and with only stage IV adult patients this data period is ICI era. The incidence statistics were combined with additional treatment fields to create this report. Only patients who had active follow-up during and after therapy were included in the study to reduce the missing data.The following variables were chosen for analysis: tumor subtype , histo-behavior , metastatic sites , laterality (left or right), age (20 years or more), sex , race  taking part in radiation therapy, chemotherapy treatment, or surgical procedures, marital [yes or no  ] and insurance statuses (yes or others). A detailed description is summarized in p-value less than 0.05.The baseline demographic characteristics of patients were compared using the two-tailed test by the chi square for categorical variables with a p-value less than 0.05.Kaplan-Meire analysis (K.M) to calculate the OS and log-rank tests were used to compare groups. The influence of a prognostic variable on OS was determined using univariate and multivariable Cox proportional hazards models with a http://www.r-project.org/).The nomogram was created as a predictor of survival for variables resulting from multivariable analysis. Finally, the parameters from the final model were utilized to create a nomogram and risk categorization system. Concordance index (c-index) is used to evaluate the nomogram model. C-index, a value range between 0 and 1, is to assess performance of the model. The receiver operating characteristic (ROC) curves are used to evaluate the nomogram’s ability to estimate patient mortality to that of the scoring criteria in lung metastasis and liver metastasis, respectively. All statistical analyses were done by SPSS version 26. Whereas nomogram and ROC were analyzed using the R program version 4.2.0 (p = 0.001), while metastasis to the brain was significantly lower in the liver metastasis group than in the lung metastasis group (8.9% vs. 11.5%) (p = 0.023). All characteristics are summarized in full in The majority of those diagnosed with mRCC were of the male gender in both lung and liver metastasis groups, respectively (68.6% vs. 65%). Metastatic to bone was significantly higher in the liver metastasis group than in the lung metastasis group (41.8% vs. 34.1%) (p < 0.001), as results our study comprehensively focused on the lung and liver metastasis groups. The SEER database has 4011 cases of mRCC with 2239 lung metastasis, 797 liver metastasis, 1588 bone metastasis, and 393 brain metastasis in the ICI era p < 0.001). p < 0.001). p < 0.001) respectively During the ICI era, we noticed that mRCC patients with lung metastasis had a much longer median survival time than those with liver metastasis , , and ,  in both groups (lung metastasis and liver metastasis) The survival effect of several factors within the lung metastasis and liver metastasis groups demonstrated improved survival in treatment methods (chemotherapy and surgery). Surprisingly, there was no difference in survival in the liver metastasis group between those who received radiation and those who did not Finally, a nomogram model was built based on the prognostic factors that were significantly positive predictors of survival multivariable cox regression of mRCC of the two groups (lung metastasis and liver metastasis) separately. Each prognostic parameter was assigned a score based on its prognostic value, and the sum total of the scores was used to predict 1-3 and 5-year survival. The sum of the scores for all factors was turned into an estimate of the likelihood of death in the experiment. In the lung metastasis group, the c-index of the prognostic nomogram for OS prediction was 0.74. The prediction model revealed that the most critical factor influencing prognosis was surgery, followed by chemotherapy. To evaluate the nomogram’s performance, 1-, 3-, and 5-year receiver operating characteristic (ROC) curves were created. The assessment revealed significantly improved prediction accuracy. AUC values of 0.87, 0.82, and 0.80 were obtained for the 1-, 3-, and 5-year survival nomograms, respectively Globally, the prevalence of mRCC is increasing. Although most cases are detected early enough for surgical excision to be curative, up to one-third of individuals have recurrence of tumors . AdditioAccording to the findings of this study, mRCC individuals with lung metastasis those received ICI had higher survival than those with liver metastasis. Chemotherapy and surgery improved OS in patients with metastatic stage kidney cancer. Radiation, on the other hand, had minimal effect. Considering that distant metastasis to the lung and liver has such a significant impact on prognosis in the ICI era, the goal of this study was to develop a comprehensive and practical nomogram for predicting the chance of survival in RCC patients based on distant metastasis to the lung and liver. Extensive study and large cohort data are necessary in order to better identify the OS difference across metastatic locations and establish possible treatment targets.


Camellia sinensis, respectively. Analysis of the base preference around the RNA editing sites showed that in the −1 position of the edited C had more frequent occurrences of T whereas rare occurrences of G. Three conserved motifs were identified at 25 bases upstream of the RNA editing site. Structural analyses indicated that the RNA secondary structure of 32 genes, protein secondary structure of 37 genes and the three-dimensional structure of 5 proteins were altered due to RNA editing. The editing level analysis of matK and ndhD in six tea cultivars indicated that matK-701 might be involved in the color change of tea leaves. Furthermore, 218 PLS-CsPPR proteins were predicted to interact with the identified RNA editing sites. In conclusion, this study provides comprehensive insight into RNA editing events, which will facilitate further study of the RNA editing phenomenon of the tea plant.RNA editing is a post-transcriptional modification process that alters the RNA sequence relative to the genomic blueprint. In plant organelles , the most common type is C-to-U, and the absence of C-to-U RNA editing results in abnormal plant development, such as etiolation and albino leaves, aborted embryonic development and retarded seedling growth. Here, through PREP, RES-Scanner, PCR and RT-PCR analyses, 38 and 139 RNA editing sites were identified from the chloroplast and mitochondrial genomes of  RNA editing is a post-transcriptional process that modifies the nucleotide sequence of RNA . During Arabidopsis thaliana [Triticum monococcum [Zea mays [Salvia miltiorrhiza [RNA editing of C-to-U was first reported in the mitochondria of flowering plants ,8,9, folthaliana , Triticunococcum , Zea mayZea mays  and Salviorrhiza . HoweverRNA editing of C-to-U is a deamination reaction . A numbeC. sinensis were predicted and partially validated. The base preference and potential motifs of sequences surrounding the editing sites were investigated. RNA and the protein secondary structure, protein transmembrane structure domain and protein three-dimensional (3-D) structure were predicted from the sequences of RNA or protein before and after RNA editing. The editing level of matK and ndhD in six tea cultivars were analyzed. In addition, the interaction between PLS-CsPPR proteins and RNA editing sites was analyzed. Our results are helpful to further study of the RNA editing in the tea plant, as well as provide a theoretical and experimental basis for the breeding of albino and etiolation tea varieties.In China, many albino and etiolation tea cultivars, such as ‘Baiye 1’, ‘Huangjinya’, ‘Huabai 1’ and ’Baijiguan’ ,33,34, ahttp://prep.unl.edu (accessed on 11 November 2021)) [To study RNA editing events in tea plants, potential editing sites for tea chloroplast and mitochondrial genes were predicted using PREP software (r 2021)) . Overallr 2021)) , these eatp6, position 223 of atp9 and position 1309 of ccmFc were edited to introduce a stop codon, which resulted in a premature termination of the protein translation. These RNA editing sites were mapped to positions 22,491 to 649,557 of the mitochondrial genome  of the RNA editing sites were at the second base, while the remaining 34.42% (116/337) were at the first base B. Of thel genome B.https://github.com/ZhangLabSZ/RES-Scanner (accessed on 1 October 2021)) [https://bedtools.readthedocs.io/en/latest/, accessed on 1 October 2021). Except for two editing sites in tRNA, the other 80 editing sites were annotated in protein-coding regions. A total of 35 editing sites had two types of editing, while the remaining 45 sites had only one type of editing. In mitochondria, 352 RNA editing sites were identified ) . A totalentified , among wndhB, five sites in ndhD, three sites in matK, and two sites in atpA, rps2 and rpoC2, while the remaining 16 chloroplast genes had only one editing site (ccmB contained the most editing sites (n = 34), followed by nad5 (n = 17), cob (n = 15), cox2 (n = 15), atp4 (n = 11), atp1 (n = 6), rpl5 (n = 6), matR (n = 4), rpl10 (n = 4) and rps12 (n = 4).To confirm the RNA editing events, regions covering the editing sites were PCR-amplified using the gDNA and cDNA of LJ43 as templates. Through sequencing, 38 RNA editing sites from 22 chloroplast genes were identified and confirmed, all of which were of the C-to-U type. Among them, eight sites occurred in ing site . For miting site  were detndhK, position 87 of ccmB, position 450 of rpl5 and position 1722 of matR) occurred at the third position. Because of the above RNA editing sites, 6 and 12 types of amino acid transitions happened in chloroplasts and mitochondria, respectively  located at the first position of the codon, 116 (85 in mitochondria and 31 in chloroplast) occurred at the second position and 4  and all mitochondrial genes except rps7. By contrast, neither the RNA nor protein secondary structures of psbF, atpF, rps8, ndhK and psaI were affected by RNA editing. In addition, 3-D models of six proteins with at least eight editing sites—ndhB, nad5, atp4, cox2, cob and ccmB—were constructed using the SWISS-MODEL. Although eight RNA editing events occurred in ndhB , matK-701, ndhD-674 and ndhD-1310 sites in different cultivars  were analyzed. As shown in matK-445 was over 90% in SC1 and HB1, around 65% in BY1 and slightly more than 50% in LJ43, HJYA and ZH3. The editing extent of matK-701 was approximately 30% in the albino cultivars BY1 and HB1, and about 30% and 45% in etiolation cultivars HJYA and ZH3, respectively, whereas it exceeded 95% in green varieties LJ43 and SC1. In LJ43, SC1 and HB1, more than 80% of ndhD-674 was edited, whereas about half C was edited in ZH3 and around 30% in BY1 and HJYA. The extent of editing of ndhD-1310 was completely edited in LJ43, ~80% in SC1 and HB1, ~50% in ZH3, ~40% in HJYA and <10% in BY1. These results indicated that the levels of RNA editing might have some physiological connection with the color change of tea leaves.Previous reports found that RNA editing events were associated with leaf color changes in plants ,30. To eNumerous studies indicate that PLS-PPR proteins are important RNA editing factors ,3, and 2RNA editing seemed to be a challenge to the central dogma of molecular biology at the transcriptional level, and has received increasing attention ,3. In rehttps://github.com/ZhangLabSZ/RES-Scanner (accessed on 1 October 2021)) identified 125 and 300 sites, respectively. One reason for the different numbers of editing sites was that PREP could only predict RNA editing sites in the protein-coding regions of 35 chloroplast genes and 43 mitochondrial genes; another was that RES-Scanner could cause read mismatches, resulting in false-positive editing sites. Therefore, PCR amplification with gDNA and cDNA templates was performed to verify the combined predicted results. In total, 38 and 139 C-to-U RNA editing events were found in the protein-coding regions of chloroplast and mitochondrial genes, respectively. Similar to previous studies [In this study, we used two software packages to investigate RNA editing sites. PREP predicted 52 and 337 RNA editing sites in the tea plant chloroplast and mitochondrial genomes, respectively , while R studies .Sweet Sorghum [A. thaliana. Generally, 20–25 nucleotides upstream of the RNA editing site are involved in the binding of editing factors [S. miltiorrhiza [http://meme-suite.org/tools/meme (accessed on 19 March 2022)) found three conserved motifs  in tea plants , whereas it was about 30% in albino varieties (BY1 and HB1) and no more than 50% in etiolation varieties (HJYA and ZH3). A previous study found that OTP81 (QED1) plays a very important role in the editing of matK-706 [To date, a total of five types of RNA editing factors were discovered, among which the PLS-PPR protein is considered to be the most important and has been extensively studied ,3. The sd atgun1 ,13,30,52d atgun1 , such asmatK-706 , and it matK-706 . PerhapsC. sinensis cv. ‘Longjing 43’, LJ43; C. sinensis cv. ‘Shaancha 1’, SC1; C. sinensis cv. ‘Huangjinya’, HJYA; C. sinensis cv. ‘Zhonghuang 3’, ZH3; C. sinensis cv. ‘Huabai 1’, HB1; C. sinensis cv. ‘Baiye 1’, BY1) used in this study were planted in the greenhouse of Northwest A&F University  under natural light, 20 °C to 25 °C ambient temperature and 60% ± 10% relative humidity. The normal green leaves of LJ43 and SC1, etiolation leaves of HJYA and ZH3, albino leaves of HB1 and BY1 were collected on 5 July 2021, respectively. The fresh leaf samples were immediately snap-frozen in liquid nitrogen and stored in a −80 °C freezer for DNA and RNA extraction.All tea tree cuttings (http://eplant.njau.edu.cn/tea/index.html (accessed on 1 October 2021)). The annotation information for the chloroplast genome of C. sinensis was downloaded from The Rocap Lab (https://rocaplab.ocean.washington.edu/tools/cpbase/ (accessed on 1 October 2021)) and then integrated with the GFF file to generate a new complete chloroplast genome annotation file of LJ43. The mitochondria genome and GFF of C. sinensis var Assamica were downloaded from TPGD (http://eplant.njau.edu.cn/tea/index.html (accessed on 1 October 2021)). The DNA-seq  and RNA-seq  data of LJ43 [https://www.ncbi.nlm.nih.gov/ (accessed on 15 October 2021)) and European Bioinformatics Institute (https://www.ebi.ac.uk/ena/browser/home (accessed on 15 October 2021)), respectively.The chloroplast genome and General Feature Format (GFF) of LJ43 were downloaded from the Tea Plant Genome Database ) [https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (accessed on 1 October 2021)) was used to check the quality of the reads. Finally, the RES-Scanner [C. sinensis var. Assamica as reference sequences. After that, RNA editing sites were annotated using bedtools [The RNA editing sites were identified using the Predictive RNA Editor for Plants suite ) . DNA-seqr 2021))  was used-Scanner  was usedbedtools  accordinThe tea leaves were divided into two parts along the main vein of the leaves. Half of them were used to extract gDNA (RNA free) using a Plant Genomic DNA Isolation Kit . The total RNA was extracted from the other half of the samples using a Plant Total RNA Isolation Kit . A total of 1% agarose gel electrophoresis was used to check the integrity of total RNA. The concentration of total RNA was measured with a NanoDrop ND 1000 spectrophotometer . A total of 1–2 μg of the total RNA was used to synthesize the first-strand complementary DNA (cDNA) with HiScript Q RT SuperMix for qPCR (+gDNA wiper) . Specific primers were used to amplify genes containing RNA editing sites using the gDNA and cDNA as templates, respectively .http://meme-suite.org/tools/meme (accessed on 19 March 2022)).To study the upstream and downstream bases’ preference of RNA editing sites, 10 bases (except position 0) from the position −5 to +5 of the editing site were extracted. In addition, the upstream 25 bases of the RNA editing site were used to discover potential binding motifs for RNA editing factors using Multiple Em for Motif Elicitation  ) web server was employed to predict changes in the RNA secondary structure with or without RNA editing using default parameters. Effects of RNA editing events on the transmembrane domain and the secondary structure of the protein were investigated using the TMHMM tool [https://services.healthtech.dtu.dk/service.php?TMHMM-2.0 (accessed on 19 February 2022)) and PSIPRED [http://bioinf.cs.ucl.ac.uk/psipred/ (accessed on 21 February 2022)), respectively. The three-dimensional structural model of the protein was constructed using the SWISS-MODEL [https://swissmodel.expasy.org/interactive (accessed on 21 February 2022)).The RNAfold  (http://HMM tool  (https:/ PSIPRED  (http://SS-MODEL  (https:/https://meme-suite.org/meme/tools/fimo (accessed on 13 April 2022)) program in the MEME suite software (https://meme-suite.org/meme (accessed on 13 April 2022)) in the MEME suite.Interaction analysis between the PLS-CsPPR protein and their target sequence was performed according to the method of Kobayashi et al.  with minmatK-445, matK-701, ndhD-674 and ndhD-1310) in 6 cultivars  indicated that matK-701 might be involved in the color change of tea leaves. Furthermore, the interaction between 159 target sequences and 218 PLS-PPR proteins were predicted through PPR-RNA code. These data provide new insights into of RNA editing phenomenon of the tea plant, which will facilitate further study of albino and etiolation in tea leaves.RNA editing is an important post-transcriptional process, which alters the nucleotide sequences of RNA, such that the genetic information and phenotype of plants are changed. PPR proteins widely exist in plants and are dominantly localized in plastids and mitochondria, which play essential roles in organellar RNA metabolism. This study systematically analyzed RNA editing events in tea chloroplast and mitochondria genomes; 38 and 139 RNA editing events were validated by PCR and sequence analysis. Analysis of the base preference around the RNA editing sites showed that in the −1 position, C to T were more frequent occurrences. Structural analyses indicated that RNA the secondary structure of 32 genes, protein secondary structure of 37 genes and the 3-D structure of 5 proteins were altered due to RNA editing. The editing level analysis of 4 RNA editing sites (


By comparing the RNA and protein behavior for sequences with six different damage profiles, our results highlight an allosteric mechanism, allowing a stronger binding of the oxidized guanine at position 9 only if another 8-oxoG lesion is present at position 15, in full agreement with experiments. We assess the role of lysine K23 and the additional ketone group of the oxidized guanine, thanks to computational site-directed mutagenesis.Oxidatively generated lesions such as 8-oxo-7, 8-dihydroguanine (8-oxoG) on RNA strands constitute a hallmark marker of the oxidative stress in the cell. Poly-C binding protein 1 (PCBP1) is able to specifically recognize severely damaged RNA strands containing two 8-oxoG lesions separated by five nucleobases, which trigger a signaling pathway leading to cell apoptosis. We apply an  Guanine (G) is one of the four constitutive nucleobases of RNA, which pairs up with cytosine. It singles out by the existence of stable G-quadruplexes (G4) and its relatively easy oxidation as it features the lowest ionization amongst the canonical RNA/DNA nucleobases. Oxidation of guanine mainly results in 8-oxo-7,8-dihydroguanine (8-oxoguanine or 8-oxoG or °G), which is prone to pair not only with cytosine but also with adenine, conferring to this ubiquitous oxidatively induced nucleobase a potentially deleterious nature. Moreover, the presence of an additional ketone on the purine ring can modify the conformation of the DNA backbone . Then, 8Single strand RNA is much more flexible than DNA, and the recognition of the damages does not involve the same proteins and the same mechanism as the well-shaped double DNA strand. It is also less crucial to repair RNA than DNA with regard to the replication of the genetic information, although mRNA oxidation can impact translation processes  and be aIndeed, it has been experimentally suggested that PCBP1 binding to oxidized RNA  consistsin silico all-atom molecular dynamics (MD) simulations. Recently, our simulation and analysis protocol has successfully revealed the changes in the interaction network between a glycosylase and a DNA strand containing an 8-oxoG or a tandem lesion  of the protein and 9 to 15 RNA sequences   and backbone dihedral angles are reported in ) around 4 Å , regardless of the damage position or the previously described RNA structural parameters. As the two oxygen atoms cannot have a direct attractive interaction due to their chemical nature, this conformational constraint must involve another polar molecule. The radial distribution function of the water oxygen atoms around O8 , while the loop itself is relatively close to the positions 9 to 12 and to K23.We use an unsupervised machine learning approach based on principal component analysis (PCA) to discriminate the importance of the different protein residues with respect to the binding conformation . Focusinβ-sheet , while the yellow node contains 8-oxoG15 and residues 48 to 51. These two nodes are strongly and directly connected. However, the second part of the loop (residues 52–55) belongs to its own independent node, connected to the β-sheet residues.The comparative analysis of the dynamic cross correlations of the PCBP1–RNA system confirms the existence of different interaction patterns between the control and the °GCCCUG°G sequences see . In bothIn order to assess the role of some protein residues in RNA binding, we perform MD simulations of different mutated PCBP1 KH 1 domains with the targeted sequence °GCCCUG°G. Our previous results suggest that K23 can play a strong role in the preference of PCBP1 for the oxidized RNA sequence. Two mutants are considered: K23Q, which keeps a polar characteristic associated with a relatively long chain, and K23M, where the polar properties are lost, but a relative linear long side chain is kept. In addition, the double mutants K31D and K32D experimentally show a decrease in RNA binding, supporting the idea of a role of these two residues in the protein–RNA interaction . In our We first investigate the RNA strand behavior. Apart from K23M, the mutations do not impact the inter base or backbone parameters see . The lysThe MMPBSA binding energy  suggestsLooking at the PCA profiles , we can β-sheet. However, the machine-learning principal component analysis reveals the importance of the 49–55 loop, standing between β-sheet strands and relatively close to K23. During the simulation in the presence of the °GCCCUG°G sequence, this loop moves from a close to an open conformation, which is concomitant with the formation of the K23–RNA interaction. Then, the loop retrieves its close conformation, but K23 still interacts with the RNA backbone. Our results suggest an allosteric mechanism, involving the transient fixation site of 8-oxoG15 and the motion of K23 close to 8-oxoG9, with a communication through the β-sheet and the 49–55 loop. The strong dynamic cross correlation between the different parts of RNA and the β-sheet present for the damaged sequence but absent in the control simulation, especially around G15, tends to confirm this hypothesis. To assess the role played by K23, we have computationally mutated K23 to glutamine and methionine. In the first case, the amine group is able to replace the ammonium group and thus conserve the interaction with the RNA backbone and the 8-oxoG9 O8 atom. In the second case, the interaction is lost as methionine has no polar group, and the binding free energy decreases by about 20 kcal/mol. We have also tested the K31D mutation, inspired by the experiment. Combined to the K32D mutation, it experimentally impedes the severely damaged sequence specific recognition by PCBP1. In our simulation, this mutation induces the loss of the electrostatic interaction between lysine and the RNA backbone but does not impact the 8-oxoG9 binding. As this interaction is not specific to the oxidized RNA sequence, our results are consistent with a participation of K31 to the upstream recognition mechanism and not to the specific stabilization of the oxidized RNA–PCBP1 interaction. This work also illustrates the current performance of GPU-accelerated molecular dynamics simulations to capture fine sequence effects for RNA or DNA repair  or a polar residue such as lysine. This interaction also impacts the rigidity of the RNA strand. Nevertheless, this K23–RNA interaction is not observed when no other 8-oxoG is present or if it is too close (at position 13). This different behavior suggests that 8-oxoG in position 15 is required to trigger this interaction, whereas this damaged guanine does not seem to have a specific interaction with the protein. Indeed, only few hydrogen bonds have been observed between the purine nitrogen atoms and some threonines located in the PCBP1


Combining tRNA and mRNA response to stress we reveal a mechanism of stress-induced down-regulation in translational elongation. We also find that native tRNA molecules lacking several modifications are biased reservoirs for the biogenesis of tRNA fragments. Our results demonstrate the importance of simultaneous investigation of small RNAs and their modifications in response to varying biological conditions.Small RNAs include tRNA, snRNA, micro-RNA, tRNA fragments and others that constitute > 90% of RNA copy numbers in a human cell and perform many essential functions. Popular small RNA-seq strategies limit the insights into coordinated small RNA response to cellular stress. Small RNA-seq also lacks multiplexing capabilities. Here, we report a multiplex small RNA-seq library preparation method (MSR-seq) to investigate cellular small RNA and mRNA response to heat shock, hydrogen peroxide, and arsenite stress. Comparing stress-induced changes of total cellular RNA and polysome-associated RNA, we identify a coordinated tRNA response that involves polysome-specific tRNA abundance and synergistic N3-methylcytosine (m This paper develops a multiplex RNA-seq method that reports tRNA abundance, modification, charging, and fragmentation. Results show stress-induced regulation in translational elongation and association of modification and tRNA fragment biogenesis. The role of tRNA in translational regulation depends on the expression and aminoacylation (charging) levels of different tRNA species, as well as many modifications that fine-tune tRNA activity4. Therefore, comprehensive and high-throughput characterization of tRNA is essential for a deeper understanding of the biological function of small RNAs.High-throughput RNA sequencing has provided transformative insights into cellular homeostasis, dynamic response to stress and environmental change, and RNA modifications. However, significant challenges associated with the characterization of small RNAs remain. Small RNAs are less than 200 nucleotides in length and include transfer RNAs (tRNA), microRNAs, small nucleolar RNAs, tRNA fragments, and many others that play important roles in cellular pathways and physiology. Altogether, small RNAs constitute more than 90% of cellular RNAs in copy numbers; among these, tRNA is the most abundant11. Cozen et al. (ARM-seq)6 and Zheng et al. (DM-tRNA-seq)5 both used E. coli AlkB demethylases to remove the abundant Watson–Crick face methylations in tRNA before the reverse transcriptase (RT) reaction. Pinkard et al (QuantM-tRNA-seq)7 used 3′CCA specific adapter ligation that specifically tagged tRNA for improved library construction. DM-tRNA-seq also used a thermostable RT (TGIRT) to facilitate a read-through of tRNA modifications and secondary structure. Behrens et al. (mim-tRNA-seq)8 found a TGIRT reaction condition that significantly improved the yield of cDNA synthesis of full-length tRNA. Gogakos et al. (Hydro-tRNA-seq)10 carried out partial alkaline hydrolysis first which reduced the structural context of tRNA to improve the efficiency of tRNA library construction. Hu et al. (AQRNA-seq)11 used a one-pot reaction in library construction including the removal of excess adapter oligos by a nuclease. A common drawback of these approaches involves size selection steps or sequence context requirements which limit the investigation of RNAs to a certain size range or to specific families and uncouples the coordinated expression and response of small RNA families, e.g., tRNA with tRNA fragments. Finally, small RNA-seq procedures also lack the level of multiplexing enjoyed by mRNA sequencing12. Therefore, new small RNA-seq methods are still needed to better characterize tRNA properties, incorporate tRNA results with other small RNA families, and increase multiplexing capability.Most commonly used RNA-seq methods are incompatible with the comprehensive study of small RNAs. Many small RNA-seq techniques ligate adapter oligonucleotides to the target RNAs, followed by cDNA synthesis. Products of incomplete reverse transcription, often induced by RNA modification or structure, are not amplified and not included in downstream analysis. tRNA is the RNA family most limited by these methods, due to rigid secondary structure and extensive modification. Several recent approaches have profoundly advanced our ability for efficient and quantitative tRNA sequencingmultiplex small RNA sequencing (MSR-seq), a platform for RNA-seq library construction that provides multiplexing to greatly increase throughput. The key feature of MSR-seq is the design of a biotinylated oligonucleotide that is used for barcode adapter ligation, immobilization, on-bead reverse transcription, second adapter ligation, and PCR. This unification of multiple steps in RNA-seq library construction enables multiplexing of many samples in the same reaction which increases sample handling throughput and reduces input amount. Our method also allows for the inclusion of enzymatic and chemical treatment of RNA on-bead, thus accommodating the investigation of RNA modifications and other applications. For biological application, we investigated the stress response of tRNA abundance, charging, and modification, as well as other small RNA families upon heat shock, exposure to hydrogen peroxide, and to arsenite which are known to strongly affect translation15. Using MSR-seq measurements of tRNA in total RNA and in the polysome, we identify specific tRNA responses. Together with mRNA measurements, the tRNA response is consistent with stress- and tRNA-dependent translational downregulation during translational elongation. We also find native tRNA molecules lacking several modifications as altered reservoirs for tRNA fragment biogenesis.Here, we describe The basic steps of small RNA-seq library construction include first adapter ligation, reverse transcription, second adapter ligation, and PCR amplification. Additions can include enzymatic or chemical treatments of the RNA to profile RNA modifications or map RNA structures. Our goal is to immobilize and barcode RNA samples at the earliest step possible, thereby enabling all subsequent reactions, including optional enzymatic/chemical reactions to proceed on a solid support, which increases multiplexing potential and minimizes sample handling Fig. . First, 16 (iii) a barcode sequence for sample pooling and multiplexing; (iv) a biotin moiety for immobilization; (v) a primer binding site embedded in the hairpin for reverse transcription and PCR; (vi) a 3′ ribonucleotide to prevent second adapter ligation to free CHO: this ribonucleotide enables periodate oxidation of the unligated CHO which converts its 2′,3′ hydroxyls to 2, 3′ aldehydes at the 3′ end. Only 2′,3′ hydroxyls allow for the ligation of the second adapter. (vii) a 3′ phosphate to prevent self-ligation of the excess CHO.We designed a capture hairpin oligonucleotide (CHO) that contains several features to make all steps compatible with streptavidin beads Fig. . The sal17. To examine the bias of the 3′ end nucleotide identity of the sample RNA in the first ligation, we measured the ligation efficiency of four RNA oligonucleotides of 5′ N10X  as the input samples. The ligation generated stoichiometric amounts of products for all four RNA oligos under our reaction condition  as the input samples. The on-bead ligation generated high levels of product with little bias for the 3′ deoxynucleotide identity  of reverse transcriptases5, it results in duplication of library preparation for the same sample, rendering it less practical for high volume tRNA-seq experiments. Similar to mim-tRNA-seq8, we found an SSIV RT reaction condition  ethylcarbodiimide (CMC) reaction for pseudouridine (Ψ) modification20 to test the compatibility of MSR-seq on-bead protocol with harsh chemical treatment conditions /tRNASer/tRNAThr (m3C32 in tRNA nomenclature) and in the loop of the variable arm stem-loop of tRNALeu(CAG)/tRNASer (m3C47d or m3Ce2 in tRNA nomenclature)24. The mutation fraction of m3C47d in tRNASer, but not in tRNALeu(CAG) showed a marked decrease under heat and arsenite stress, and an increase under hydrogen peroxide stress , tRNAIle(TAT), and tRNALys(TTT) showed a 3–4-fold increase  under stress by Northern blot , tRNAIle(TAT), and tRNALys(TTT) abundance in the arsenite stress. All three tRNAs read A/T-rich codons and may associate with ribosome stalling that contributes to the reduction of global translation (see below).The tRNA abundance change at the isoacceptor level on the polysome is the largest for the arsenite stress Fig. . Specifiase Fig. , while tlot Fig. . In addiess Fig. , similarRNA Fig. . The oveSer m3C modifications were associated with the polysome. In unstressed controls, polysome-associated tRNASer showed an increase in m3C47d and m3C32 levels compared to bulk tRNA . First, we observed that codon usage was related to transcript abundance, for example, abundant transcripts encode more lysine using both AAA and AAG codons  that read these codons.The polysome mRNA and tRNA results can be explained by a tRNA-dependent downregulation of translational elongation during stress. Even though mRNAs on the ribosome are enriched for C/G-ending codons, tRNAs on the ribosome are enriched for those that read A/T-ending codons. This is consistent with increased ribosome stalling at A/T-ending codons corresponding to slowed elongation exacerbated by stress. Potential ribosome stalling may be particularly pronounced at the Ile-AAT, Ile-ATA, and Lys-AAA codons under arsenite stress which may explain the high level of on-polysome accumulation of tRNA33. tRF sequencing commonly uses size-selected RNAs of 20–60 nucleotides. Although this approach obtains a high coverage of tRF and other small RNAs, potential direct connections between tRF and full-length tRNA are diminished by sequencing them separately. To simultaneously analyze tRNA and tRF in MSR-seq, we used a simplistic approach by binning reads by the 3′ ends of their mapped tRNA  are a family of small RNAs that regulate many aspects of gene expressionlot Fig. .Fig. 6An5C, Q, and m1G protect tRNA from cleavage37. However, it is unclear whether naturally occurring tRNA lacking a specific modification enhances or hinders tRF biogenesis. We addressed this question by simultaneously comparing the mutation fractions of the tRF and its cognate full-length tRNA of the same sequence. The m3C47d level was much lower in tRF compared to their cognate full-length tRNA   Fig. . In contTrp Fig. . These rHere we developed an RNA-seq method that enables multiplexed sequencing library preparation, on-bead enzymatic and chemical treatment, one-pot tRNA abundance, charging, and modification measurements, and simultaneous analysis of tRNA, tRNA fragment, and other small RNA families. We applied our method to human cell stress response and found additional insights into translational regulation through tRNA response to stress and in tRNA fragment biogenesis.43. We found that the RNA libraries on streptavidin beads could withstand harsh chemical treatments such as the CMC reaction, which involves two steps at pH 8–10 and hours of incubation at 30–37 °C. Chemical and enzymatic treatments are useful in profiling RNA modifications such as Ψ, m5C, m1A, or m7G45 and for RNA structural mapping.Advantages of carrying out sequencing library construction on solid support include the rapid exchange of buffers and reagents, thorough removal of contaminants, and elimination of size selection steps or adapter/primer removal. The solid support platform also allows for on-bead treatment of RNA with chemicals and enzymes, which has become widely used in studies of RNA modifications and other applications18 in the RT reaction is the single issue that remains to be solved. We found that the amount of TdT was highly variable depending on the input sample and reaction conditions. Currently, we remove the TdT products by size selecting the final PCR products. Possible future solutions include screening other RTs, further optimization of reaction conditions, and finding new enzymes that can selectively remove the added deoxynucleotides.The key feature of our method is the design of the capture hairpin oligonucleotide (CHO). Our innovation is the inclusion of a 3′ ribonucleotide and 3′ phosphate which blocks the second ligation to the excess CHO upon periodate oxidation after the RT reaction so that only CHOs with cDNA product are amplified in the final PCR step. The presence of a substantial amount of the terminal transferase product (TdT)47, and our work here reveals additional insights regarding tRNA abundance and modification. This was achieved by not only measuring the response of total tRNA, but also tRNA on the polysome under stress. Previous tRNA profiling from density gradients analyzed tRNAs in the ribo-seq 80 S peak48. Our tRNA profiling includes the fractions of disomes and larger which measures tRNAs only in the elongating ribosomes. Most previous stress response studies deal with the regulation of global translation and translational initiation. By measuring tRNAs on elongating ribosomes, we were able to illuminate tRNA-based stress response in translational elongation.Translational regulation in stress response has been extensively studiedIle(AAT) reads ATT, tRNAIle(TAT) reads ATA, and tRNALys(TTT) reads AAA codons. These results are consistent with increased ribosome stalling at A/T-ending codons under stress; furthermore, ATT, ATA, and AAA codons may be hotspots of such stalling under arsenite stress. Stress-induced, codon-dependent tRNA response in translational elongation may also be driven in part by the post-translational modification of the eEF2 protein49.For tRNA abundance, the most striking result is the enrichment of tRNAs that read A-ending over G-ending codons on the polysome under stress. At the same time, mRNAs from the same polysome samples show enrichment of C/G-ending over A/T-ending codons. Among the 3 tRNAs that are enriched at the highest level on the polysome, tRNA3C, which can be studied by MSR-seq at high sensitivity. m3C32 is present in the anticodon loop of tRNASer, tRNAThr, and tRNAArg(yCT) and enhances translation28. m3C47d is in the variable loop of tRNASer and tRNALeu(CAG), which is located at the 40S–60S interface in the 80 S ribosome. Our striking result is the coordinated response of m3C32 and m3C47d under stress. Without stress, tRNAs with higher m3C32 and m3C47d levels are loaded on the polysome. Heat and arsenite stresses reduce the m3C47d level in total RNA, possibly through the action of a tRNA eraser such as ALKBH3;26 this results in a corresponding reduction of m3C47d level in polysome-associated tRNASer. However, the same stresses also increase m3C32 levels in tRNASer to reach nearly stoichiometric levels in total RNA and in polysome. These results are consistent with both m3C modifications working together to fine-tune decoding under stress. At this time, however, the m3C47d installation enzyme is not known50, so we were unable to thoroughly investigate the function of this modification on codon-dependent protein synthesis. Once the m3C47d writer is identified, knock-down or knock-out of this enzyme separately or in combination with the m3C32 writer could reveal how these modifications coordinate in translation regulation.For tRNA modification, we focused on m3C or m1G levels compared to their cognate full-length tRNA, indicating that naturally occurring hypomodified tRNAs can indeed be preferred reservoirs for tRF biogenesis. Second, tRFs can have higher m22G levels compared to their cognate tRNA, indicating that naturally occurring tRNA modifications can also enhance tRF biogenesis.We also revealed an underappreciated relationship between tRNA modification and tRNA fragment biogenesis in native tRNA. tRFs are involved in many aspects of gene expression, developmental biology, and human diseases. It is well known that tRNA modifications strongly influence tRF biogenesis, with a consensus that tRNA modification generally hinders tRF generation. We present two insights here through simultaneous full-length tRNA and tRF analysis in the same data. First, certain tRFs have lower mIn summary, MSR-seq provides a platform for small RNA-seq with the emphasis on RNA components in translation and translational regulation and simultaneous analysis of multiple RNA families.4, 10 mM NaOAc pH 4.8. Periodate oxidation proceeded for 30 min at room temperature. Oxidation was quenched with the addition of 1 µL of 0.6 M ribose to 60 mM final concentration and incubated for 5 min. Next 5 µL of freshly prepared 100 mM sodium tetraborate, pH 9.5 was added for a final concentration of 33 mM. This mixture was incubated for 30 min at 45 °C. To stop β-elimination and perform 3′ end-repair, 5 µL of T4 PNK mix  was added to the reaction and incubated at 37 °C for 20 min. T4 PNK was heat-inactivated by incubating at 65 °C for 10 min. This 20 µL reaction mixture can be used directly in the first barcode ligation by adding 30 µL of a ligation master mix described below.Up to 500 ng of total RNA in 7 µL was used for optional one-pot beta-elimination prior to library construction. To start, 1 µL of 90 mM sodium acetate buffer, pH 4.8 was added to 7 µL input RNA. Next, 1 µL of freshly prepared 150 mM sodium periodate solution was added for a reaction condition of 16 mM NaIOTotal RNA was prepared for library construction by the first deacylating in a solution of 100 mM Tris-HCl, pH 9.0 at 37 °C for 30 min, then neutralized by addition of sodium acetate, pH 4.8 to a final concentration of 180 mM. Deacylated RNA was then ethanol precipitated and resuspended in water, or desalted using a Zymo Research Oligo Clean-and-Concentrator spin column.Depending on the nature of the experiment described in the main text, input RNA or total nucleic acid samples were either deacylated or had undergone one-pot deacylation and β-elimination as described above. Up to 1 µg of total RNA input was used in a ligation reaction of 50 µL with the following components: 1 U/µL T4 RNA ligase I (NEB), 1x NEB T4 RNA ligase I buffer, 15% PEG 8000, 50 µM ATP, 1 mM hexamine cobalt chloride, and 5% DMSO. After adding the ligation mix to the sample, the capture hairpin oligo  were added to each sample in a 1.2:1 excess over CHO . The bead-sample mixture was incubated at room temperature for 15 min. After binding, supernatants were removed, and the beads were washed once with high salt wash buffer  and once with low salt wash buffer . After washing, multiple individually barcoded samples can be combined for downstream steps. At this stage, enzymatic or chemical treatments can be incorporated into the library preparation protocol such as AlkB demethylase reaction or CMC treatments (see below).2, 0.5 mM ZnCl2, 20 mM HEPES, pH 7.3. The sample was incubated at 37 °C for 30 min. The sample was then washed once with high salt wash buffer and once with low salt wash buffer, then resuspended in 20 µL water.A 50 µL dephosphorylation mix containing the following was added to the multiplexed sample on bead: 0.04 U/µL calf-intestine phosphatase (Roche), 10 mM MgClFive microliters of SuperScript IV VILO 5x master mix (Thermo Fisher) were added to the dephosphorylated sample  and then incubated at 55 °C for 10 min. The sample was then washed once with high salt wash buffer and once with low salt wash buffer. Identical results were obtained upon extending the reaction time to 60 min. For overnight reverse transcription, after the initial 10 min incubation at 55 °C, the samples were further incubated at 35 °C overnight.Beads were then resuspended into 50 µL of RNase H master mix containing 0.4 U/uL RNase H (NEB) and 1x NEB RNase H buffer and incubated at 37 °C for 15 min. The sample was then washed once with high salt wash buffer and once with low salt wash buffer. The sample was then resuspended in 40 µL water.Ten microliters of 250 mM freshly prepared sodium periodate, 0.5 M sodium acetate, pH 5 were added to the RNase H digested sample and incubated at room temperature for 30 min. Afterward, ribose was added to a final concentration of 167 mM to quench excess periodate at room temperature for 5 min. The sample was then washed once with high salt wash buffer and once with low salt wash buffer.Beads were resuspended into 50 µL of a ligation master mix with the following components: 2 U/µL T4 RNA ligase I (NEB), 1x NEB T4 RNA ligase I buffer, 2 µM second ligation oligo (Supplementary Data A 50 µL PCR reaction was run using 5–10% of the bead slurry products from the second ligation reaction using Q5 DNA polymerase (NEB) and following the manufacturer’s instructions: 0.02 U/µL Q5 DNA polymerase, 1x Q5 reaction buffer, 0.2 mM dNTPs, 0.5 µM Illumina index primer . The gel fragments were extracted overnight and then ethanol precipitated.10X, where X = rA, rC, rG, rU) were made at an approximate molar ratio of 2 CHO: 1 RNA oligo. Four microliters of each mixture were added to individual tubes (n = 3 for each RNA oligo). To each tube, 21 µL of first ligation mixture  chloride, and 2 U/µL NEB T4 RNA ligase I) were added  and the samples were incubated at 16 °C overnight.Four separate mixtures containing final 0.8 µM CHO and four 11-mer RNA oligonucleotides  were added to each sample to degrade the ligase. The samples were then incubated at 37 °C for 25 min and subsequently boiled at 92 °C for 3 min.The samples were loaded onto a Bio-Rad pre-cast 15% TBE-Urea PAGE gel and electrophoresed until the bromophenol blue was near the bottom of the gel. The gel was then stained with a 10,000x dilution of SYBR Gold and imaged on a Chemi-Doc imager and quantified with Quantity One software (Bio-Rad).10X, where X = dA, dC, dG, T) were made at an approximate molar ratio of 10 s ligation oligo: 1 DNA oligo. Four microliters of each mixture were added to individual tubes (n = 3 for each biotin-DNA oligo). Three microliters of 10 mg/mL Thermo Fisher streptavidin-coated MyOne C1 Dynabeads were then added to each sample and allowed to capture the biotinylated DNA oligos for 10 min.Four separate mixtures containing the final 2 µM second ligation oligo and four 26-mer 5′ biotinylated DNA oligonucleotides  chloride, and 4 U/µL NEB T4 RNA ligase I) was added  and the samples were incubated at room temperature (~20 °C) overnight.After overnight incubation, 2.5 µL of 18 mg/mL Roche PCR-grade Proteinase K and 15 µL of 2x RNA loading dye  were added to each sample to release the products from the beads and to degrade the ligase. The samples were then incubated at 37 °C for 25 min and subsequently boiled at 92 °C for 3 min.The samples were loaded onto a Bio-Rad pre-cast 15% TBE-Urea PAGE gel and electrophoresed until the bromophenol blue was near the bottom of the gel. The gel was then stained with a 10,000x dilution of SYBR Gold and imaged on a Chemi-Doc imager quantified with Quantity One software (Bio-Rad).A first ligation mixture was made containing the following: 15% PEG 8000, 1x NEB T4 RNA ligase I buffer, 50 µM ATP, 1 mM hexaammine cobalt (III) chloride, 0.8 µM CHO, 25 ng/µL HEK total RNA, and 1.67 U/µL NEB T4 RNA ligase I . This was incubated at 16 °C overnight.After overnight ligation, 75 µL  were pipetted into a separate tube (henceforth known as “- CIP” tube) and mixed with 75 µL of 100 mM EDTA to quench the ligation reaction. The remaining ligation mixture was ethanol precipitated.2, 1 mM ZnCl2, and 40 mM HEPES, pH 7.5) and 8 µL of 5 U/µL NEB Quick CIP. The “+ CIP” tube was then incubated at 37 °C for 30 min. After the 37 °C incubation, the “+CIP” tube was incubated at 65 °C for 10 min to inactivate the phosphatase. The “+ CIP” sample was then ethanol precipitated.The ethanol-precipitated ligation mixture (henceforth known as “+CIP” tube) was resuspended in 92 µL of water and mixed with 100 µL of 2x dephosphorylation buffer . To three of these tubes, 8 µL of 10 mg/mL Thermo Fisher streptavidin-coated MyOne C1 Dynabeads were added. To the “−CIP” tube, 24 µL of beads were added. The beads were incubated with the samples for 10 min to allow them to bind the biotinylated oligos. (The “−CIP” tube was then split into three separate tubes.) After incubation, the beads were then magnetized, the supernatant was removed, and the beads were washed once with 50 µL of high salt Neonate wash buffer  and then washed once with low salt wash buffer .After washing, the samples were resuspended in 8 µL of autoclaved water. To all nine tubes, 2 µL of Thermo Fisher 5x SuperScript IV VILO mix were added and the samples were then incubated at 55 °C for 10 min. After incubation, the off-bead samples were then mixed with 8 µL of beads. All samples were then washed as before.RNase H digestion section.From this point on, the MSR-seq protocol was followed, beginning at the See Supplementary Data 32P dGTP [Perkin Elmer]. The samples were incubated at 37 °C for 30 min; and then mixed with 10 μL of 2x urea loading dye  and incubated at 93 °C for 2 min before loading on a 15% denaturing polyacrylamide gels. The primer sequence for tRNASer(GCT) was 5′-TGGCGACGAGGATGGGATTCGAACCCACGCGT.About 100 ng of total RNA sample was added to a tube containing 20 pmol  of RT primer and 2 μL of 5x annealing buffer ; water was added for a total volume of 5 μL. Samples were heated to 93 °C for 2 min and then directly placed on ice. Five microliters of a Post-annealing mix, containing the following components, was added to each sample tube : 2x AMV Buffer; 2 U/μL AMV RT [New England Biolabs]; 2x poisoned dHTP mix ; and 2 μCi/μL α-5. Briefly, NEB T7 Expression cells were grown in LB media at 37 °C, in the presence of 50 µM kanamycin, to an A600 of 0.6–0.8. Once the cells reached the desired density, IPTG and iron sulfate were added to final concentrations of 1 mM and 5 µM, respectively. After induction, the cells were incubated overnight at 30 °C. Cells were collected, pelleted and then resuspended in lysis buffer  plus 300 mM NaCl. The cells were lysed by sonication and then centrifuged at 17,400 rcf for 20 min. The soluble proteins were first purified using a Ni-NTA superflow cartridge (Qiagen) with buffers A (lysis buffer plus 1 M NaCl for washing) and B (lysis buffer plus 1 M NaCl and 500 mM imidazole for elution) and then further purified by ion-exchange  with buffers A (lysis buffer plus 100 mM NaCl) for column loading and B (lysis buffer plus 1.5 M NaCl) for elution.These were adapted from the previously described protocols for DM-tRNA-seq51. Three stock solutions are made fresh immediately before reaction: l-ascorbic acid 200 mM, 2-ketoglutarate 3 mM, and ammonium iron sulfate 5 mM. The final reaction mixture contained 2 mM l-ascorbic acid, 1 mM 2-ketoglutarate, 0.3 mM ammonium iron sulfate, 100 mM KCl, 50 mM MES pH 6, 50 ng/µL BSA, 4 µM wild-type AlkB, and 4 µM AlkB-D135S. About 50 µL of the reaction mixture was added to 5–20 µL of decanted streptavidin bead slurry after ligation, immobilization, and washing. The reaction continued for 30 min at 37 °C. Following the reaction, beads were washed once with high salt wash buffer  and once with low salt wash buffer .Demethylase buffer conditions were modified from Li et al.HEK293T cells  were cultured with complete DMEM medium under standard conditions according to ATCC. Briefly, HEK293T cells were grown in Hyclone DMEM medium  with 10% FBS and 1% Pen–Strep (Penicillin–Streptomycin) to 80% confluency and passaged. Cells were collected and total RNA was extracted using TRIzol  by following the manufacturer’s protocol when cells reached 80–90% confluency.6 cells each) were seeded three days before collection. On the day of polysome profiling, six plates of cells (two plates for one sample) were treated with different stress conditions: (1) unstressed control; (2) 42 °C heat shock, 1 h; (3) 0.6 mM H2O2, 2 h; (4) 300 µM NaAsO2, 2 h. Polysome profiling was immediately performed after stress treatment.HEK293T cells were cultured in DMEM medium  with 10% FBS and 1% Pen–Strep (Penicillin–Streptomycin). Twenty-four 15-cm plates of HEK293T cells  in DMEM for 7 min right after stress treatments. DMEM medium was removed. Cells were then collected using 10 ml ice-cold PBS with 100 µg/ml CHX and cell lifter. Cells were pelleted by centrifugation at 3000 RPM for 5 min. The cell pellet was washed twice with 5 ml ice-cold PBS with 100 µg/ml CHX. Cells from two plates were combined for one sample. Cells were resuspended in 1 ml ice-cold PBS and transferred to microcentrifuge tubes. About 200 µl cell suspension from each sample was saved as input. Cells were pelleted by centrifugation at 3000 RPM for 5 min. For input cells samples, 500 µl TRIzol reagent was added to extract the total RNA. For polysome cells samples, the cell pellet was resuspended by 4 volumes of lysis buffer , 40 U/µl RNase inhibitor ). Cells were rotated and lysed at 4 °C cold room for 30 min. Lysed samples were centrifuged at 16,000×g for 15 min to collect the clear lysate (~600–700 µl). About 4 ul Turbo DNase was added to each lysate and the samples were incubated at room temperature for 15 min. The samples were centrifuged again at 16,000×g for 15 min to get clear lysate. Absorbance at 260 nm of each sample was measured. Samples were adjusted to the same absorbance using lysis buffer. 5–50% sucrose gradient  was prepared using a Biocomp gradient station. About 600 µl gradient buffer was removed from the top of the balanced sucrose gradient. About 600 µl lysate was loaded onto the top of the gradient slowly while gently rotating the tube. The samples were centrifuged at 28,000 RPM for 3 h at 4 °C using a Beckman SW28.1 rotor. After centrifugation, fractions were collected and measured using the Biocomp gradient station . Fractions were flash-frozen and stored at –80 °C before RNA extraction and library construction. For polysome RNA extraction, fractions from disome and higher were combined and 2 volumes of TRIzol reagent were added to extract the RNA. PolyA+ RNA was extracted from the input and polysome RNA using a polyA+ RNA extraction kit from Promega (Z5310) or NEB (E7490S), respectively.Polysome profiling procedures were adapted from ref. Poly(A)-selection was done with NEBNext Poly(A) mRNA Magnetic Isolation Module  according to the manufacturer’s instructions.2O. The fragmented RNA was purified using Zymo RNA clean and concentrator columns and eluted in 16 µl sterile H2O. Two microliters of T4 PNK buffer and 2 µl T4 PNK were added to the tubes and the tubes were incubated at 37 °C for 30 min to repair the ends of the fragmented RNA. MSR-seq method was then used to build sequencing libraries with the fragmented RNA. Slight modifications were made to the MSR-Seq protocol. After the first ligation step, the ligation reaction was quenched by adding 50 mM EDTA. Samples were combined and ligation products over 200 nt long was purified using Zymo RNA clean and concentrator columns twice. Target cDNA products were purified using AMPure XP beads with a 1:1 ratio after PCR.One microgram of input polyA+ RNA samples and 100 ng polysome polyA+ RNA samples were used to build sequencing libraries. The RNA fragmentation and end-repair steps are the same as the CMC sequencing libraries construction. Briefly, polyA+ RNA in 18 µl were added to PCR tubes and 2 µl Magnesium RNA fragmentation buffer  was added to each tube. The tubes were incubated at 94 °C in a thermocycler for 5 min to fragment the RNA to ~200 nt. The tubes were transferred to ice and a 2 µl RNA fragmentation stop solution was then added to each tube to stop the fragmentation. Samples were spun down and diluted to 50 µl using sterile H53 (https://deeptools.readthedocs.io/en/develop/) with bin size as 1 to get the bigwig sequencing depth coverage files. The bigwig coverage files were visualized using IGV and coverage track images were obtained.Raw 100 bp paired-end sequencing reads were obtained from the Illumina Nova-Seq platform. Reads processing and trimming was the same as CMC sequencing libraries. The reads were mapped to the human transcriptome (hg38) obtained from Ensembl. The mapped “bam” files were then analyzed using bamCoverage tool of the “deeptools”54 using 32P radiolabeled probes. About 500 ng of each polysome RNA sample were diluted to 9 µl in microcentrifuge tubes. About 1 µl 1 M Tris-HCl, pH 9 was added to each tube and mixed well. The samples were incubated at 37 °C for 30 min to deacylate the tRNAs. About 10 µl 2× RNA loading buffer ) were added. All RNA samples were loaded onto a 10% pre-run denaturing PAGE gel. The gel was stopped when the Xylene cyanol band passed the middle of the gel. RNA was transferred to Hybond-XL Membrane  at 80 °C for 4 h using a gel dryer (Bio-Rad). The membrane was soaked in deionized water with the membrane side on the top to separate the gel and the membrane. The gel was stained with SYBR gold  and scanned using a Chemi-Doc imaging system (Bio-Rad). The membrane was UV-crosslinked twice (254 nm for 1200 mJ). The membrane was then prehybridized for 30 min twice with hybridization buffer . About 40 pmol of the tRNA probes were radiolabeled by T4 PNK with γ-32P-ATP in a 10 µl reaction. The labeling mixture were diluted to 50 µl and cleaned by Illustra MicroSpin G-25 Columns . The membrane was incubated with 15 µl 32P radiolabeled probes for 16 h at 60 °C in the UVP Hybridizer Oven . The membrane was washed twice using 50 ml washing buffer  for 30 min each. The membrane was wrapped in plastic wrap and exposed to a phosphorimager screen for 1–2 days depending on the signal strength. The screen was then scanned using a personal molecular imager (Bio-Rad). The image was analyzed using ImageLab software.The northern blot method was adapted from ref. Northern blot probes were from Integrated DNA Technologies (IDT) and gel purified. Sequences of the probes were :Gly: 5′-TGCATTGGCCRGGAATYGAACCCGGGYCTCCCRCGTGGWAGGCGAGAATTCTACCACTGMACCACCMAYGC-3′Ile-AAT: 5′-TGGCCMGTACGGGGATCGAACCCGCGACCTTGGCGTTATTAGCACCACGCTCTAACCAACTGAGCTAACCRGCC-3′55 (http://geneontology.org/).Gene ontology analysis was performed using the default setting in ref. All samples were incubated at 95 °C for 10 min, separated on a 4–12% polyacrylamide Bis-Tris protein gel , and transferred to polyvinylidene fluoride membranes . The membranes were blocked in 10% w/v milk . The blots were probed with 1/1000 v/v EIF2S1 antibody  or 1/500 v/v Phospho-EIF2S1 (Ser51) antibody , followed by 1/10000 v/v sheep anti-mouse IgG  or 1/10000 v/v donkey anti-rabbit IgG conjugated to horseradish peroxidase . The blots were visualized with ECL Prime Western Blotting Detection Reagents  using a Bio-Rad Chemi-Doc MP.MCF7 cells  were cultured in EMEM medium  with 10% FBS , 0.01 mg/ml bovine insulin , and 10 nM β-estradiol  to 80% confluency and passaged at ratios of 1:3. Total RNA were extracted using TRIzol.2O in a microcentrifuge tube. The RNA was transferred to PCR tubes and 2 μl Magnesium RNA fragmentation buffer  was added to each tube and the tubes were incubated at 94 °C in a thermocycler for 5 min to fragment the RNA to ~200 nt. Two microliters of RNA fragmentation stop solution were then added to each tube. The samples were diluted to 50 μl with H2O and Zymo Research spin columns were used to purify the fragmented RNA; the RNA were eluted in 16 μl sterile H2O in a microcentrifuge tube. For 3′ end-repair of the RNA fragments, 2 μl 10x T4 PNK buffer and 2 μl T4 PNK at 10 U/μl  were added and the mixture was incubated at 37 °C for 30 min. The fragmented, end-repaired RNA was used to build sequencing libraries using the msRNA-seq protocol described above with the following modifications. The fragmented RNA was ligated to barcoded capture hairpin oligonucleotides and bound to streptavidin beads. The samples were then pooled, mixed, and split into two parts for ±CMC (N-cyclohexyl-N′-(2-morpholinoethyl)carbodiimide) treatment (+CMC:-CMC = 1.5: 1 ratio). About 12 μl sterile H2O and 24 µl TEU buffer (50 mM Tris-HCl (pH 8.3), 4 mM EDTA, 7 M urea) were first added to each tube, then 4 µl freshly prepared 1 M CMC in TEU buffer was added to +CMC samples and 4 µl sterile H2O was added -CMC samples. The samples were incubated at 30 °C for 16 h at 1400 rpm on an Eppendorf ThermoMixer. The samples were washed twice with high salt buffer and once with low salt buffer. The samples were then resuspended with 40 µl of 50 mM sodium carbonate and 2 mM EDTA (pH 10.4) buffer and incubated at 37 °C for 6 h at 1400 rpm. The beads were washed twice with high salt buffer and once with low salt buffer and then proceeded to the msRNA-seq steps such as phosphatase treatment and reverse transcription.MCF7 total RNA sequencing libraries were constructed as follows. Small RNA (<200 nt) was first removed from 1 μg MCF7 total RNA using spin columns  and the large RNA (>200 nt) was eluted with 18 μl sterile H56. BM and LEN options were adjusted for samples with a 3 nt barcode instead of 4, and for samples where the barcode is located in read 2. Barcode sequences are listed in Supplementary Data 57, https://github.com/pysam-developers/pysam) to sum all reads that mapped to each gene. Related custom scripts were used to divide reads based on which 10 nt window the 3′ end mapped to for each tRNA; this is for fragment analysis. Data were visualized with custom R scripts. All custom scripts are available on GitHub (https://github.com/ckatanski/CHRIS-seq).Libraries were sequenced on Illumina Hi-Seq or NEXT-seq platforms. First, paired-end reads were split by barcode sequence using Je demultiplex with options BPOS = BOTH BM = READ_1 LEN = 4:6 FORCE = true C = false2O2, and AsO2) for one replicate. This gave a set of ~1500 genes, with small fluctuations in detection in other replicates. TE calculations were confirmed to be roughly log-normally distributed. A Z-score was calculated for each sample based on log10 (TE) value. The mean Z-score from the control replicates was used as a reference for stress-dependent change.For each gene, read counts mapping to all transcript variants were summed together. Read counts were normalized for total detection in each sample  among mRNA-detection reads . After normalization, genes were filtered to have more than 100 counts. Next translational efficiency (TE) was calculated as the normalized gene counts in the polysome fraction divided by the input fraction for each replicate and each stress. Next, analysis was limited to a set of well-detected genes: this set of genes was defined as genes where TE could be calculated in all four treatments . Percentile ranks were used to calculate statistical differences between gene groups for each sample and each codon; tests were calculated via the two-sided Wilcox test. Codon usage frequency is not normally distributed, so a non-parametric hypothesis test is appropriate.Z-score from the mean of control replicates: decreased TE, no change in TE, and increased TE. Percentile group thresholds were again 33rd and 66th. Percentile ranking in codon usage was again used for hypothesis testing between groups for each sample and each codon with a two-sided Wilcox test as above.Next, for each sample, genes were again divided into three groups, but based on the percentile of change in http://hannonlab.cshl.edu/fastx_toolkit/). For read1 reads, the random six nucleotides' unique molecular identifier (UMI) sequence at the start of the reads and the barcoded adapter sequence at the end of the reads were removed using Trimmomatic58 using single-end mode with a 15 nt cutoff. For read2 reads, the 7 nt barcode sequence at the start of the reads and the UMI and adapter sequence at the end of the reads were removed by Trimmomatic using paired-end mode with a 15 nt cutoff. The reads were then mapped to human rRNA transcripts using bowtie2. The output sam files were converted to bam files and then sorted and indexed using samtools. A command-line version of “igvtools count”  were used to count nucleotide composition, insertions, and deletions at single-base resolution. “Bedtools genomecov”  was used to count the start and end of all reads at each position. All the output files and reference sequence were combined into a single file for each sample, and the mutation rate and the stop rate were computed by custom python scripts. The output files were analyzed to identify target pseudouridine sites.Raw 100 bp paired-end sequencing reads were obtained from the Illumina Hi-Seq platform. Read1 reads were separated by barcodes with the barcodes sequence on paired read2 reads using custom python scripts. Read2 reads were separated by barcodes using fastx_barcode_splitter (fastx_toolkit, Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Reporting Summary


DDX58 mRNA, along with A-to-I RNA editing sites, we encountered putative U-to-C editing. These U-to-C edits were present in several cell lines and appeared regulated in response to specific environmental stimuli. The same findings were also observed for the human long intergenic non-coding RNA p21 (hLincRNA-p21). A more in-depth analysis revealed that putative U-to-C edits result from A-to-I editing on overlapping antisense RNAs that are transcribed from the same loci. Such editing events, occurring on overlapping genes transcribed in opposite directions, have recently been demonstrated to be immunogenic and have been linked with autoimmune and immune-related diseases. Our findings, also confirmed by deep transcriptome data, demonstrate that such loci can be recognized simply through the presence of A-to-I and U-to-C mismatches within the same locus, reflective A-to-I editing both in the sense-oriented transcript and in the cis-natural antisense transcript (cis-NAT), implying that such clusters could be a mark of functionally relevant ADAR1 editing events.Despite hundreds of RNA modifications described to date, only RNA editing results in a change in the nucleotide sequence of RNA molecules compared to the genome. In mammals, two kinds of RNA editing have been described so far, adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. Recent improvements in RNA sequencing technologies have led to the discovery of a continuously growing number of editing sites. These methods are powerful but not error-free, making routine validation of newly-described editing sites necessary. During one of these validations on  Recent years have seen an exponential increase in RNA sequencing (RNA-seq) technologies providing scientists with an incredible amount of transcriptomic data. Once compared to genomic data (DNA-seq), RNA-seq reveals information about several post-transcriptional processes that RNA molecules can undergo. For example, RNA editing is a mechanism that alters the RNA sequence itself. In mammals, two distinct kinds of RNA editing have been described so far, adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U). These edits are the result of the deamination activity by proteins belonging to the adenosine deaminase acting on RNA (ADAR)  and the via PCR. This method has some variations; for example, cDNA can be produced from oligo-dT, random hexamers, or specific primers for a particular transcript. In this latter case, and when a Hot Start DNA Polymerase is used, the reverse transcription and PCR amplification of a specific target take place one after the other in the same tube, in a so-called one-step RT-PCR reaction. This method allows a fast and easy RT-PCR setup, optimal for RNA editing detection validation. Additionally, one-step RT-PCRs exclusively generate cDNA from the transcript of interest leading to higher sensitivity in RNA editing detection when the transcript of interest is poorly expressed or edited  data to detect RNA editing sites , leadingr edited .DDX58) and a long intergenic non-coding RNA (hLincRNA-p21) nearby A-to-I editing sites. In both cases, U-to-C editing appeared to be regulated upon specific stimulations a feature characteristic of RNA modifications. After looking for an RNA modification that could lead to this base change, we realized that U-to-C edits result from A-to-I editing on overlapping antisense RNAs that had not been previously described. We have also confirmed this finding by the analysis of known sense–antisense transcripts through deep transcriptome data from human tissues.In this study, we report the observation of a putative U-to-C RNA editing while validating some A-to-I ADAR1 editing sites. U-to-C edits were observed on an mRNA , supplemented with 15% fetal bovine serum  and 1% of Penicillin/Streptomycin . A549 cells  were cultured at 37°C, 5% CO2 in high-glucose DMEM  supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin . HEK293T cells  were cultured at 37°C, 5% CO2 in high-glucose DMEM  supplemented with 5% FBS  and 1% penicillin/streptomycin . Cell lines were authenticated using Multiplex Cell Authentication by Multiplexion  as described recently  and U2932  were cultured at 37°C, 5% COrecently . Additiorecently . No Myco5 HEK293T cells were seeded in 12-well plates in a total volume of 1 ml media containing 200 U/ml of IFN-α . After 16 h, cells were collected, and RNA was extracted using a Qiagen RNeasy Plus kit .For interferon-alpha (IFNα) stimulation, 2.5 × 105 HEK293T cells were seeded in 24-well plates to have around 30%–50% confluency the day after. The following day the cells were transfected with pcDNA3-hLincRNAp21-MS2  tagged with 24 copies of MS2 RNA hairpins, as previously described   . DNA olie_52961) . pCMVDR8https://n2t.net/addgene:48138; RRID:Addgene_48138) (pSpCas9(BB)-2A-GFP (PX458) was a gift from Feng Zhang  . DNA olie_48138)  and an ae_48138) .Ribo-depleted RNA-seq experiments from seven human tissues  were selCircular heatmaps were generated using the R package circlize  and the https://github.com/BioinfoUNIBA/antisenseEditing.The entire pipeline and scripts are available at ® High-Fidelity DNA Polymerase . RNA was extracted using the RNeasy Plus Mini kit  and treated with DNase . Following RNA extraction, RT-PCRs were performed with gene-specific primers (https://inp.univ-amu.fr/en/amplifx-manage-test-and-design-your-primers-for-pcr) or ApE . The chromosomal locations of all the editing sites analyzed in this study are listed in For editing site validation, PCRs were performed on genomic DNA (gDNA) and RNA. gDNA was extracted using the High Pure PCR Template Preparation kit  following manufacturer instructions. PCR amplification was performed using Q5 primers  and a On primers . Alterna primers , AmplifXDDX58 or hLincRNA-p21, respectively. Two microliters of a 1:2 diluted cDNA were used to set up a 10 µl qPCR reaction using SsoAdvanced Universal SYBR Green Supermix . Finally, fold change expression was calculated using the comparative CT method (ΔΔCT) . Before qPCR, RNA was additionally treated with DNase . cDNA synthesis was then performed using ProtoScript M-MuLV First-Strand Synthesis Kit  using 1 µg of RNA DNAse digested. cDNA was synthesized using oligo-dT or random primers to detect d (ΔΔCT) . SupplemAB_2722520) following IFN-α stimulation using β-Actin as a loading control . Lenti-NT control cells were kept polyclonal. After screening, clones three and four were shown to completely abolish ADAR1 (p110 and p150) expression . After 48–72 h, cell-free supernatant was collected and used for transduction of HEK293T cells. The transduced cells were selected with puromycin (1 μg/ml). As soon as non-transduced cells died (∼2 days), ADAR1 knockout cells were seeded in 96-well plates in a limiting dilution (0.5 cells/well). Upon expansion of single clones, ADAR1 KO clones were validated by Western blot -2A-GFP carrying the sgRNAs for DTWD1, DTWD2 or TSR3 were transfected into HEK293T cells using Lipofectamine 2000  following manufacturer instructions. 48 h after transfection, GFP-positive cells were sorted and plated (one cell per well) in 96-well plates. The clonality was validated by visual inspection with a microscope, and positive clones were screened by Sanger sequencing.p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, ns: not significant.Data were analyzed and plotted using GraphPad Prism (version 9.3.1). Specific information about data presentation is provided in each figure caption throughout the manuscript. Statistical significance was calculated by unpaired, two-tailed Student’s t-test: *via PCR amplification of a specific region containing the editing sites to be validated from either DNA or cDNA (the latter represents the RNA). In a recent work from our lab, we identified RNA editing sites comparing RNA- and DNA-seq data in a cohort of Diffuse large B cell lymphoma (DLBCL) patients  of the 3′ untranslated region (3′UTR) of DDX58 we could detect 11 A-to-I sites and 11 U-to-C sites , validating them as real RNA editing sites , lower. DDX58 would change after specific stimulation, we decided to treat HEK293T cells with interferon-alpha (IFN⍺). IFN⍺ treatment has two relevant consequences for this experiment: first, it induces ADAR1 p150 expression  itself  itself . HEK293Tmulation . Followimulation . Not surmulation  which ismulation , 2006. Hmulation . These dDDX58 mRNA, we asked if this editing was also present in other RNA species, such as long non-coding RNAs (lncRNAs). LincRNA-p21 is a crucial molecule during the response to cellular stress driven by p53 . Recent work has shown that hLincRNA-p21 contains inverted-repeat Alu elements, which can fold as independent domains  itself leads to low levels of U-to-C transitions after reverse transcription , and thiquencing . Unfortuquencing . It thusquencing . This moquencing . Additioquencing . This m1quencing . Therefoquencing . We succg ; alternatively, naturally poor editing on some transcripts might be reported as “no editing” (depending on cut-offs). Both of these are limitations to our approach. These limitations could be cell type-specific or disease-specific. Overall though, our work suggests that clusters of A-to-I (and U-to-C) editing might specify dually edited, convergently transcribed regions, offering a potentially simple way to identify loci that may be of disease relevance .DDX58 mRNA and the lncRNA hLincRNA-p21. U-to-C edits show typical features of a bona fide RNA modification. Indeed, they can be identified in multiple cell systems and respond to environmental stimulation differently from other co-existing modifications. However, careful evaluation demonstrated that putative U-to-C corresponds to A-to-I editing introduced by ADAR on overlapping antisense transcripts , the antisense editing was catalyzed by ADAR1  antisense transcripts and matching them with reported editing events. Like others before us, we find that such events are rare overall. However, when convergent transcription overlaps with editing, at least a quarter  of such transcripts are edited in the antisense orientation (thus generating apparent “U-to-C” RNA modification events). Around half of these are edited in both orientations, suggesting that these events, though rare, are not insignificant. It is important to note that antisense transcripts are frequently degraded by the nuclear RNA exosome limiting their detection in RNA-seq data. Using alternative NGS methods such as chromatin RNA-seq may improve the detection of antisense transcripts and, therefore, antisense editing. Finally, our analysis was limited to known antisense transcripts. Defining the antisense signal directly from the RNA-seq, despite being more challenging, may lead to the discovery of non-annotated antisense transcript and, thus, more antisense RNA editing.Whether the antisense editing is derived from intra- or intermolecular interactions of RNAs, the fact that ADAR1 edits overlapping sense and antisense RNAs may suggest those transcripts as particularly relevant in activating MDA5 and, therefore, could be highly immunogenic. In such a scenario, the identification of clusters of apparent U-to-C and A-to-I modifications could simplify the prediction of potentially strongly immunogenic self-dsRNAs [which are thought to be functionally relevant ].DDX58 upon IFN treatment is probably due to the ∼20-fold increase in expression of its sense-transcript together with a 2-fold increase in ADAR1 expression  but not in others . Indeed, A549 shows abundant A-to-I but no U-to-C editing indicating the absence of antisense transcription .


Due to the complexity of the mechanisms involved in epileptogenesis, the available antiseizure drugs (ASDs) do not meet clinical needs; hence, both the discovery of new ASDs and the elucidation of novel molecular mechanisms are very important.BALB/c mice were utilized to establish an epilepsy model induced by pentylenetetrazol (PTZ) administration. The peptide HsTx2 was administered for treatment. Primary astrocyte culture, immunofluorescence staining, RNA sequencing, identification and quantification of mouse circRNAs, cell transfection, bioinformatics and luciferase reporter analyses, enzyme-linked immunosorbent assay, RNA extraction and reverse transcription–quantitative PCR, Western blot and cell viability assays were used to explore the potential mechanism of HsTx2 via the circ_0001293/miR-8114/TGF-β2 axis.The scorpion venom peptide HsTx2 showed an anti-epilepsy effect, reduced the inflammatory response, and improved the circular RNA circ_0001293 expression decrease caused by PTZ in the mouse brain. Mechanistically, in astrocytes, circ_0001293 acted as a sponge of endogenous microRNA-8114 (miR-8114), which targets transforming growth factor-beta 2 (TGF-β2). The knockdown of circ_0001293, overexpression of miR-8114, and downregulation of TGF-β2 all reversed the anti-inflammatory effects and the influence of HsTx2 on the MAPK and NF-κB signaling pathways in astrocytes. Moreover, both circ_0001293 knockdown and miR-8114 overexpression reversed the beneficial effects of HsTx2 on inflammation, epilepsy progression, and the MAPK and NF-κB signaling pathways in vivo.HsTx2 suppressed PTZ-induced epilepsy by ameliorating inflammation in astrocytes via the circ_0001293/miR-8114/TGF-β2 axis. Our results emphasized that the use of exogenous peptide molecular probes as a novel type of ASD, as well as to explore the novel endogenous noncoding RNA-mediated mechanisms of epilepsy, might be a promising research area. Epilepsy is a common, serious neurological condition causing recurrent unprovoked seizures. It is the fourth most common neurological disorder and affects ~ 65 million people worldwide . The curEpileptogenesis is associated with an increased, strong, and persistent inflammatory state in the microenvironment of neural tissue . NeuronaButhus martensi Karsch, inhibits the widespread seizures induced by pentylenetetrazol (PTZ) and pilocarpine-induced status epilepticus in rats [Parawixia bistriata spider venom, exerts promising neuroprotective and antiseizure effects [Polybia paulista, exerted a noticeable antiseizure effect on rats and mice [Heterometrus spinifer, was identified, and HsTx2 exerted obvious neuroprotective effects on rats with ischemic stroke via the MAPK signaling pathway [Since 2000, approximately 30 innovative peptide drugs have been approved and marketed, with several achieving great success, such as abaloparatide, semaglutide, and plecanatide , 17. In  in rats . Parawix effects . Ppnp7, and mice . These nand mice . In our  pathway . ConsideMicroRNAs are powerful modulators of post-transcriptional gene expression that are dysregulated during epileptogenesis . They arCircular RNAs (circRNAs) are a subclass of endogenous noncoding RNAs that form covalently closed loops without 5′ to 3′ polarity or polyadenylated tails , 26. RecIn this study, we first explored the anti-seizure effects of HsTx2 and the underlying mechanisms and found that peptide HsTx2 had no effect on potassium and calcium channels (data not shown); thus, the neuroprotective mechanism of HsTx2 was not clear. A cell membrane penetration experiment showed that the peptide HsTx2 may cross the membrane of astrocytes directly (data not shown). We also analyzed the expression profiles of circRNAs in hippocampal tissues from epileptic mice and identified a circular RNA termed circ_0001293. After detecting inflammatory factors in the brain tissue of PTZ model mice, knockdown of circ_0001293 and overexpression of miR-8114 in astrocytes, HsTx2 was finally considered to alter the inflammatory response in seizures by regulating the circ_0001293/miR-8114/TGF-β2 axis. According to our results, HsTx2 has the potential to serve as a new potential ASD.The peptide HsTx2 (purity > 95%) and the random scrambled peptide (AGERSRKILKREHGHICMVTRGAKK) (purity > 95%) were commercially synthesized and provided by Wuhan Bioyeargene Biotechnology Co., Ltd. (China).BALB/c mice  were purchased from Hunan SJA Laboratory Animal Co., Ltd.  and housed under laboratory conditions  at room temperature of 20–23 °C. All experimental protocols were approved by the Animal Experimental Ethical Inspection of Kunming Medical University (KMMU2020076). The epilepsy mouse model was induced by administering PTZ  . BrieflyThirty minutes after each behavioral observation experiment, the mice were anesthetized with 4% chloral hydrate solution and then intracardially perfused with phosphate-buffered saline for 3 min, and the hippocampal tissue was collected. Protein samples were used immediately for biochemical assays or stored in a − 80 °C freezer for total RNA extraction and western blot testing.Behavioral seizure scoring and electrophysiological (EEG) evaluations were performed at the last PTZ administration. Two unipolar scalp electrodes were placed on the bilateral temporal skin of the mice. Then, the mice were allowed to move freely in transparent cages. The baseline EEG was recorded for approximately 15 min before the injection of PTZ or saline, and then the EEG was recorded for at least 30 min using the numerical acquisition system . An electrophysiological seizure was defined as a seizure with a high frequency (> 5 Hz) and high amplitude (> 2 times the baseline) that lasted for more than 5 s. The seizure intensity was assessed based on the Racine scale: stage 0, no response; stage 1, mouth and facial movements; stage 2, head nodding; stage 3, forelimb clonus; stage 4, rearing; stage 5, rearing and falling; stage 6, death . The behPrimary astrocyte cultures were prepared from the hippocampal tissue of postnatal BALB/c mice on day 1 as previously described . Cell cuThe animals were anesthetized and transcardially perfused with 4% paraformaldehyde in phosphate buffer. Brains were removed and embedded in paraffin. Brain blocks were then sectioned into serial arrays of 3-μm-thick sections. The tissue sections were deparaffinized, rehydrated and subjected to antigen retrieval. Then, sections and cultured astrocytes were permeabilized with 0.4% Triton X-100 for 10 min and blocked with goat serum  for 1 h to eliminate nonspecific staining. Sections and cultured astrocytes were incubated with a mixture of a rabbit anti-TGF-β2 antibody  and rabbit anti-GFAP antibody  overnight at 4 °C. Alexa Fluor-conjugated secondary antibodies  were then incubated with the samples for 1 h at room temperature. The cell nucleus was stained with 0.1% Hoechst 33342  for 5 min at room temperature. TGF-β2 and GFAP staining was observed using a Nikon Eclipse 80i microscope (Nikon Corporation).P value < 0.05) using the R package edgeR.Total RNA was extracted from six hippocampal tissues from each group. The RNA concentration and purity in each sample were quantified using a NanoDrop ND-1000 spectrophotometer . RNA integrity was assessed using an Agilent 2100 instrument, with RIN > 7.0. Approximately 5 μg of total RNA was used to deplete ribosomal RNA according to the instructions of the Ribo-Zero™ rRNA Removal Kit , followed by cDNA library construction. Next, deep sequencing was performed with an Illumina HiSeq 4000 instrument  according to the vendor's recommended protocol. First, Cutadapt was used to remove the reads that contained adaptor contamination, low-quality bases and undetermined bases. Then, sequence quality was verified using FastQC. We used Bowtie2 and Hisat2 to map reads to the genome of the species. The remaining reads (unmapped reads) were still mapped to the genome using TopHat fusion. CIRCExplorer2 and CIRI were first used for the de novo assembly of the mapped reads to circular RNAs; then, back splicing reads were identified in unmapped reads using TopHat fusion. All samples generated unique circular RNAs. The differentially expressed circRNAs were selected with log2 (fold change) > 1 or log2 (fold change) < − 1 and with statistical significance (5), which were subcultured at a density of 80%, with Lipofectamine 2000 reagent  at 37 °C. Forty-eight hours after transfection, the transfection efficiency was detected using RT‒qPCR and Western blotting, and then subsequent experiments were performed.For this experiment, miR-8114 mimic, miR-NC mimic, miR-8114 inhibitor, miR-NC inhibitor, specific small interfering RNAs (siRNAs) targeting circ_0001293 (si-Circ) and TGF-β2 (si-TGF-β2), and siRNA-negative control (si-NC) were purchased from Shanghai GenePharma (China). The sequences of circ_0001293 were inserted into a pcDNA3.1 plasmid to obtain the circ_0001293 overexpression plasmid pcDNA3.1-circ_0001293 (oe-circ), and an empty pcDNA3.1 plasmid was used as the negative control (oe-NC). Plasmid DNA, siRNA, miR-mimic or miR-inhibitor was transfected into astrocytes (1 × 10https://cm.jefferson.edu/rna22/Interactive/) online software was used to predict target binding sites of miRNAs in circRNAs and mRNAs. PmirGLO-circ_0001293-wild (circ-WT)/-mutant (circ-MUT) type and PmirGLO-TGF-β2-WT/-MUT type reporter plasmids were provided by Shanghai GenePharma Co., Ltd. HEK293 cells (2 × 105/well) were cotransfected with the circ-WT/-MUT or TGF-β2-WT/-MUT plasmid and miR-NC mimic or miR-8114 mimic using Lipofectamine 2000 reagent  at 37 °C. At 48 h post-transfection, luciferase activity was determined using the dual-luciferase reporter assay system . Firefly luciferase activities were normalized to Renilla luciferase activities.RNA22 , IFN-γ , IL-6 , IL-1β , IL-10 , and TGF-β2  in the hippocampus were measured using corresponding ELISA kits according to the manufacturer’s instructions. Absorbance was determined using a microplate spectrophotometer .Total RNA was extracted from cells using TRIzol® reagent  according to the manufacturer's protocol. First-strand cDNAs were synthesized from total RNA using the PrimeScript™ RT reagent kit  according to the manufacturer’s instructions. RT–qPCR was subsequently performed using the SYBR-Green qPCR kit  according to the manufacturer’s protocols. The following primer sequences were used for RT‒qPCR: miR-8114, forward 5′-TCACCCATCTCCTCTCC-3′ and reverse 5′-TGTCGTGGAGTCGGC-3′; TGF-β2, forward 5′-CCAGGGGGAAGGAGGTCATA-3′ and reverse 5′-CTTCGGCAGACACGTGTTTG-3′; circ_0001293, forward 5′-AAATCCTCTGCAGCCCTTCC-3′ and reverse 5′-TTCATCTCTTGGTCGAGGCG-3′; U6, forward 5′-CTCGCTTCGGCAGCACA-3′ and reverse 5′-AACGCTTCACGAATTTGCGT-3′; and β-actin, forward 5′-CACTGTGCCCATCTACGAGG-3′ and reverse 5′-TAATGTCACGCACGATTTCC-3′. RT‒qPCR experiments were performed using an Applied Biosystems 7900HT Fast Real-time PCR system . The relative expression levels were calculated using the 2-ΔΔCq method  and normTissues and cells were isolated, total proteins were extracted using RIPA buffer, and protein concentrations were measured using a BCA Protein Determination kit . Equal quantities of protein samples were separated on 10% SDS–PAGE gels and transferred to polyvinylidene difluoride membranes, which were then washed and blocked. Specific primary antibodies against TGF-β2 , p-ERK , p-p38 , p-JNK , p–p65 , and β-actin  were incubated with membranes, followed by an incubation with an HRP-conjugated secondary antibody . Antibody binding was detected using enhanced chemiluminescence reagent . ImageJ  was used to analyze the gray value of each band on the membrane.Forty-eight hours after cells were seeded in 96-well plates at a density of 2500 cells per well, cell viability was assessed using a CCK-8 assay  according to the manufacturer’s instructions. Absorbance was measured using a microplate spectrophotometer .All experiments were performed in triplicate. Statistical analyses were performed using GraphPad Prism 7 . The results are presented as the means ± standard deviations (SD). Two groups were compared with Student’s t test, and three or more treatments or groups were compared with one-way ANOVA followed by the Tukey–Kramer post hoc test. A P value < 0.05 was defined as statistically significant.As shown in our previous study, HsTx2 ameliorates cerebral ischemic injury in rats by exerting neuroprotective effects , suggestUsing the bioinformatics database starBase to search for potential targets, a putative interaction between miR-8114 and circ_0001293/TGF-β2 was identified, and the target binding sequence is shown in Fig. Astrocytes were purified from hippocampal tissues to confirm the molecular mechanisms underlying the antiseizure effect of HsTx2. As shown in Fig. We constructed stable circ_0001293 knockdown cell lines using si-circ_0001293, and si-circ_0001293 significantly downregulated the expression of circ_0001293 Fig. a. The reWe next overexpressed miR-8114 in astrocytes and established cell lines stably overexpressing miR-8114 Fig. a. The RTWe constructed stable TGF-β2 knockdown cell lines using si-TGF-β2, and si-TGF-β2 significantly downregulated TGF-β2 expression Fig. a. As shoWe next examined the expression of circ_0001293 and its downstream genes miR-8114 and TGF-β2 to further validate whether HsTx2 exerts its function via the circ_0001293/miR-8114/TGF-β2 axis. As shown in Fig. We next assessed and confirmed whether the potential antiseizure activity of HsTx2 was mediated by the circ_0001293/miR-8114/TGF-β2 axis in vivo. Epileptic mice were injected with HsTx2, lenti-si-circ_0001293 or miR-8114 mimic, and the expression levels of these genes were analyzed. As shown in Fig. Thamnophis elegans) expresses high levels of mutant Na(+)/K(+)-ATPase mRNA in cardiac muscle [A large number of bioactive peptides have been identified in recent years –43. Peptc muscle . Scorpioc muscle –49. BaseNotably, circRNAs have been reported to play numerous roles in gene regulation and other cellular processes , 50. ImpPrevious studies have documented changes in miRNA levels in the hippocampus of patients with temporal lobe epilepsy and neural tissues from animal models of epilepsy , such asBinding of miRNAs to the 3′ UTR of mRNAs inhibits gene expression post-transcriptionally . We aimeThe effect of HsTx2 on ion channels was tested in previous experiments. Because direct effects of HsTx2 on ion channels were not found (data not shown), it is likely that anti-inflammatory effects are involved. Inflammatory responses are important in the development of epilepsy. Inflammatory cytokines are present in small amounts in the brain, but their levels increase after seizures , 63. TheIn summary, HsTx2 treatment significantly protects against the progression of epilepsy through a mechanism that mainly depends on anti-inflammatory activity by regulating the circ_0001293/miR-8114/TGF-β2 axis. These findings suggest that HsTx2 is an antiseizure peptide that should be further investigated for use in the treatment of epilepsy.