RNA modifications, containing m6A, m1A, alternative polyadenylation and adenosine-to-inosine RNA editing, involve in critical cancerous immunity and cancerous processes. However, the functional roles of RNA modification writers in bladder cancer (BLCA) are largely unknown.In this study, unsupervised clustering was used to identify novel RNA modification writers -mediated molecular subtypes in BLCA. A corresponding quantitative indicator called WriterScore was developed using univariate Cox and Least absolute shrinkage and selection operator (LASSO) analysis. Then, we systematically analyzed the correlation between RNA modification writer-related clusters (WriterScore) and immunological characteristics, classical molecular subtypes, clinicopathologic features and treatment options in BLCA. Finally, we validated the WriterScore in multiple other external BLCA datasets, clinical sample dataset in Shengjing Hospital and pancancer.Two RNA modification writer-related clusters and three DEGclusters were obtained. These RNA modification writer-related clusters (WriterScore) were strongly associated with immunological characteristics, classical molecular subtypes, clinicopathologic features of BLCA. Moreover, WriterScore can properly predict the clinical outcomes and immunotherapy of BLCA patients.Our study systematically investigated the role of RNA modification writers and developed a significant WriterScore to guide several treatment options in BLCA, which might bring some potential benefits for BLCA patients. Bladder cancer (BLCA) is the second most prevalent malignancies in the urinary system , with anEpigenetic alterations modulating heritable changes play important role in the malignant process of human cancer . RNA modIn the past decade, immunotherapies have been conducted great progress and shown tremendous assistant to advanced solid tumors. In 2016, immune checkpoint inhibitors (ICIs) have been formally applied in BLCA patients , and havFour types of adenine modifications, including m6A, m1A, APA and A-to-I RNA editing, are the most impactful RNA modifications. In this study, we comprehensively evaluated the correlation of four types of adenine-related RNA modification writers with immunological characteristics, classical molecular subtypes, therapeutic opportunities, clinicopathological features for BLCA. Next, we developed two RNA modification writer-related clusters and three DEGclusters based on unsupervised clustering. Finally, we established and verified a WriterScore to quantify the efficacy of RNA modifications patterns in individual BLCA patients and evaluate its application value in predicting immunotherapy benefits.Sixty BLCA samples and twenty normal samples were obtained from Tissue specimen Bank of Shengjing Hospital from 2015 to 2022. None of the patients in this study received preoperative radiotherapy or chemotherapy. The baseline information of the BLCA samples were presented in Total RNA of the BLCA samples was extracted by TRIzol . The purity and concentration of the RNA samples were measured by NanoDropND-1000 . Subsequently, we removed rRNA from total RNA and obtained mRNA. Each sample was amplified and transcribed into a fluorescent cRNA using a random primer method. The sample RNA was first generated into cDNA by reverse transcription, and then purified and labeled. Finally, Agilent Gene Expression Hybridization Kit was used to hybridize the labeled probe and chip under standard conditions. We obtained the chip map and read the values to get the original data using Agilent Feature Extraction software. Then, GeneSpring GX v12.1 software (Agilent Technologies) was used to process the original data.Total RNA from normal samples and BLCA samples was extracted by TRIzol  and reverse-transcribed to cDNA. Real time quantitative polymerase chain reaction (RT-qPCR) was performed based on SYBR Premix Exaq . GAPDH was used as an internal reference to calculate the relative expression levels of 26 RNA modification writers according to the 2-ΔΔCt method. http://xena.ucsc.edu/). As a training dataset in this study, TCGA- BLCA dataset included 400 BLCA samples and 19 normal samples after filtering the patients without prognostic information. Then, the FPKM values of the RNA sequencing data were transformed into transcripts per kilobase million (TPM) value. The “maftools”R package was used to plot the “oncoplot” based on the somatic mutation data. Tumor mutation burden (TMB) of pan-cancers was calculated using VarScan2 based on the mutation data. The microsatellite instability (MSI) data and the stemness indices of pan-cancers were respectively downloaded from the supplementary files of Bonneville’s study  data and clinical data of TCGA- BLCA and pan-cancers were downloaded from the UCSC Xena Public Hub . We then combined and normalized the two datasets into a meta-GEO dataset using the “sva” R package and the “gcrma” R package. The RNA sequencing data and clinical data of E-MTAB-4321 dataset was downloaded from http://E-MTAB-4321<ArrayExpress<BioStudies<EMBL-EBI. Subsequently, nine immunotherapy cohorts including IMvigor210 , GSE135222 , GSE78220 , GSE100797 , Gide2019 , Nathanson2017_ Post and _Pre , Riaz2017_ Naïve and Prog  were obtained. Finally, a public BLCA single-cell data set (GSE145137) was downloaded from GEO dataset to explore the expression profiles of RNA modification writers on the cell clusters and cell types using “Seurat” R package. The microarray datasets from GEO were directly downloaded the present log scale matrix files. The baseline information about all of these datasets is collected in GSE48075 and GSE32894 from the same microarray platform (GPL6947 Illumina HumanHT-12 V3.0 expression beadchip) were downloaded from Gene Expression Omnibus , 4 m1A enzymes , 7 m6A enzymes  and 12 APA enzymes   and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore the functions of DEGs in BLCA using the “clusterProfiler” R package. Univariate Cox regression was conducted to select the DEGs with prognostic value for further analysis. Unsupervised clustering was performed to classify TCGA- BLCA patients into different geneclusters based on the expression level of the prognostic-related DEGs to verify the stability of the RNA modification writers related phenotypes. Next, the LASSO regression analysis was performed to establish the Writer-score scoring system to quantify all individuals with BLCA based on the following formula: Writer-Score = ∑(Coefi * Expri); here, i means the genes in LASSO model, Coefi respects the coefficient of each gene and Expri indicates the expression level of each gene. The patients were classified into high-and low- Writer-Score groups using the “survminer” R package. The robustness of Writer-score scoring system was verified using meta-GEO dataset, E-MTAB-4321 dataset and clinical sample dataset.The information of several classical molecular subtypes including CIT, MDA, Lund, TCGA, UNC, Baylor and Consensus subtypes was collected from predecessors’ research –33. TwelImmunological characteristics involved in BLCA were composed of 122 immunomodulators, tumor-infiltrating immune cells (TIICs), 36 effector genes of TIICs, cancer immunity cycles, several stromal signatures, T cell inflamed score (TIS) and 22 inhibitory immune checkpoints  35, 36), 3635, 3Several gene signatures correlated with the clinical response to an anti-PD-L1 agent (atezolizumab) in BLCA were summarized from Mariathasan’s study . A set ohttps://www.gsea-msigdb.org/gsea/msigdb). False discovery rate (FDR) was corrected by Benjamini and Hochberg (BH) method and FDR < 0.05 was considered as signatures.GSVA enrichment analysis was conducted using “GSVA” R package to explore the differential biological function between distinct RNA modification writer-related clusters (WriterScore) . We downAll statistical data analyses were conducted using R software (version 4.1.2). The level of significance was set at P < 0.05, and all statistical tests were two-sided. Correlation analysis was applied using Pearson or Spearman coefficients. T-test or the Mann-Whitney U test was performed to the comparison among groups. Chi-square and Fisher’s exact tests were used to ensure exact test. Kaplan-Meier (K-M) survival curves was plotted to assess prognostic value and the statistical significance was evaluated by log-rank test.26 RNA modification writers were collected in the current study based on the recent studies , 50. In The patients in TCGA- BLCA dataset were divided into several clusters based on the expression of 26 RNA modification writers using unsupervised clustering. We found that the clustering algorithm achieve optimal result when the patients were classified into two clusters, including clusterA (n = 122) and clusterB (n = 284), and the patients in the two clusters have different prognosis Table S3Among the two clusters, we subsequently identified 1525 RNA modification-related DEGs . In our The relationships among Cluster, geneCluster, Writer-Score and seven classical molecular subtypes were displayed in A majority of immunomodulators and effector genes of several anticancer TIICs were overexpressed in Cluster A , acute myeloid leukemia (LAML), Mesothelioma (MESO), ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), skin cutaneous melanoma (SKCM) and thyroid carcinoma (THCA) , 47. HerWe validated the predictive performance of Writer-Score to the immunotherapy in multiple immunotherapy datasets collected from GEO or TIDE database. We found that the Writer-Score was negatively related to inhibitory immune checkpoints in these immunotherapy datasets S15. ConIncreasing evidence indicate that RNA modification writers play a critical role in tumor immunity. For example, Zhao J et al.  revealedHere, we first systematically assessed the RNA expression profile and somatic mutant profile of 26 RNA modification writers in TCGA-BLCA patients and found that 121 out of 412 patients experienced mutations and that 19 RNA modification writers were abnormal expression in TCGA- BLCA patients. The frequency of mutations ranged from 4% to 1%, and PCF11, METTL3, ZC3H13 had the highest mutations of mutations among the 26 RNA modification writers. The CNV alteration of the 26 RNA modification writers could contribute to their dysregulation expression, and many writers have a significant prognostic value in BLCA. The above results suggested that RNA modification writers play an indispensable role in diagnosis and prognosis of BLCA. We then identified two distinct RNA modification and named them as Cluster A and Cluster B, respectively. Compared with Cluster B, Cluster A was positively corrected with immunological characteristics, such as many immunomodulators, cancer immunity cycles, inhibitory immune checkpoints, many anticancer TIICs and their effector genes. As expect, Cluster B had the poor prognosis in BLCA patients due to the suppression of tumor immunity. In addition, GSVA enrichment analysis indicated that Cluster B was highly enriched in proliferation and apoptosis pathways, such as cell cycle, nucleotide excision repair, and mismatch repair pathways, which explains its poor prognosis.Furthermore, 1525 differentially expressed mRNA were selected between the two distinct RNA modification patterns. Among them, 355 genes with significant prognostic value were selected to develop a Writer-Score scoring system to quantify the RNA modification patterns of individual BLCA patients. Subsequently, two Writer-Score groups (high- and low writer-score groups) exhibited distinct immunological characteristics. That is, low Writer-Score group appeared to have positively correction with immunological characteristics. K-M analysis revealed that patients in a high Writer-Score group had poor clinical outcome compared with patients in low Writer-Score group. These findings suggested that the Writer-Score was a reliable scoring system for comprehensive clinical assessment of RNA modification patterns in individual BLCA patients, and the low Writer-Score group may be an inflamed phenotype and be more sensitive to ICB. Finally, we reconfirmed these results in multiple immunotherapy datasets and pan-cancer dataset.More importantly, the low Writer-Score group indicated the luminal subtype, while high Writer-Score group represented the basal subtype. The RNA modification patterns (Writer-Score) also can be used to predict the sensitive to several therapeutic strategies, such as neoadjuvant chemotherapy, EGFR targeted therapy and radiotherapy, chemotherapies targeting immune-inhibited oncogenic pathways. The mutation rate of RB1 was significantly higher in the high Writer-Score group, suggested that the patients in high Writer-Score group (Cluster B) may achieve more benefits from neoadjuvant chemotherapy. In addition, we found that the high Writer-Score group (Cluster B) with hypoxia, cell_cycle, DNA_replication and EGFR_ligands enriched was more sensitive to EGFR targeted therapy and radiotherapy. However, the low Writer-Score group (Cluster A) with several immune-inhibited oncogenic pathways enriched, suggested that targeting these pathways may have advantages for patients in the low Writer-Score group. In summary, the widespread application of the Writer-Score may promote the development of precision medicine in BLCA.Our discovery comprehensively analyzed four types of RNA modification writers and develop a reliable Writer-Score scoring model, revealing a novel regulatory mechanism by which they bring some potential implications for identifying molecular subtypes, and guiding therapeutic strategies for BLCA.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/This study was approved by the Ethics Committee of Shengjing Hospital of the China Medical University, and informed consent was obtained from all patients. In addition, all methods were performed in accordance with relevant guidelines and regulations. The patients/participants provided their written informed consent to participate in this study.YC, YZ, and WW conceived and designed the study. YC, YZ, and WW developed the methodology. YC, YZ, and WW analyzed and interpreted the data. YC, YZ, and WW wrote, reviewed, and/or revised the manuscript. All authors contributed to the article and approved the submitted version.


Firstly, to find out whether the RNA of interest to a user contacts with chromatin, and if so, with which genes or DNA loci? Secondly, to find out which RNAs are in contact with the DNA locus of interest to a user (and probably participate in its regulation), and if there are such, what is the nature of their interaction? For a more detailed study of contact maps and their comparison with other data, the web interface allows a user to view them in the UCSC Genome Browser.Every year there is more and more evidence that non-coding RNAs play an important role in biological processes affecting various levels of organization of living systems: from the cellular  to cell populations and even organismal ones . The development and creation of mutually complementary databases that will aggregate, unify and structure different types of data can help to reach the system level of studying non-coding RNAs. Here we present the RNA-Chrom manually curated analytical database, which contains the coordinates of billions of contacts of thousands of human and mouse RNAs with chromatin. Through the user-friendly web interface (Database URLhttps://rnachrom2.bioinf.fbb.msu.ru/ Key PointsNon-coding RNAs, while performing their function in the nucleus, play an important role in biological processes.The RNA-Chrom database currently stores all available genome-wide RNA–chromatin interactions data: 62 human and 125 mice experiments from 66 articles, totaling more than 5 billion RNA–DNA contacts.RNA-Chrom database contains not only the data processed with standardized protocol but also the comprehensive experiments metadata.RNA-Chrom provides a user-friendly web interface. Two types of the data analysis (‘from RNA’ and ‘from DNA’) can be performed.RNA-Chrom can be an important resource that will allow researchers to reach a more systematic level of work with the RNA–chromatin interactome and will promote to expand the understanding of the biological role of non-coding RNAs in a variety of processes.Back in the 1960s, it was found that a large amount of different RNAs are associated with chromatin . HoweverDrosophila. There are also a number of regulatory RNAs  that affect gene expression by attracting chromatin modifiers such as TrxG and PRC1/PRC2 to certain loci. Another example is MALAT1 and NEAT1, which are associated with such nuclear structures as speckles and paraspeckles and regulate gene expression. Moreover, Firre can serve as a local organizing factor to ensure a topological proximity of trans-sites and its genomic locus; lnc-NR2F1 is involved in neurogenesis; Bloodlinc is involved in erythropoiesis; and DACOR1 interacts with maintaining DNA methyltransferase 1 and is expressed at a higher level in normal cells of the healthy colon and at a lower level in colon cancer cell clones. Many more biological examples of the interaction of RNA with chromatin can be cited  that contains all available genome-wide RNA–DNA interactions data. Since there is no standard protocol for processing these data, it is difficult to conduct a comparative analysis of RNA–chromatin contacts. Here we have standardized the data processing protocol and implemented it starting with raw reads. The RNA-Chrom database allows a user not only to download data processed by a single protocol but also to perform various methods of data analysis and comparison in real time. It is also possible to view contact maps in the UCSC Genome Browser  (an asynchronous event-driven JavaScript runtime), ‘React.js’ (https://reactjs.org/) and ‘Redux’ (https://github.com/reduxjs/redux) libraries and implemented as a ‘Single Page Application’. The ‘Material-UI V4’ (https://mui.com) library was taken as the basis for the web interface elements, and the ‘Plotly JavaScript Open Source Graphing Library’ (https://plot.ly/javascript/) was taken to create interactive plots. ‘Back-end’ was implemented using the Python web microframework ‘Quart’ (https://pgjones.gitlab.io/quart/) as it supports asynchronous database requests. The database itself, which stores RNA–chromatin contacts, was created on the basis of ‘ClickHouse’ (https://clickhouse.com/) (the Open Source OLAP database management system), due to which a user’s waiting time for any of their analytical requests was reduced to seconds.‘Front-end’ was developed using ‘Node.js’ (http://www.ncbi.nlm.nih.gov/geo/) using the keywords ‘RAP-seq’, ‘CHART-seq’, ‘ChIRP-seq’, ‘dChIRP-seq’, ‘ChOP-seq’ and ‘CHIRT-seq’ and taking into account only human and mouse data sets. Then we went as far as possible through articles that referred to the main one-to-all methods . Surpriods . Possible polymerase chain reaction duplicates were removed via FastUniq . In mice, 18 all-to-all data sets and 291 one-to-all data sets for 31 RNAs were collected  . Since nWith RNA-Chrom, a user can perform two types of analysis of the RNA–chromatin interactions data in real time that can transition into each other. We called the first type of analysis ‘from RNA’, since the first step is to select the RNA of interest. This analysis allows a user to answer the question ‘Where does the selected RNA contact chromatin?’. While the second type of analysis, ‘from DNA’, begins with the selection of the genomic locus of interest, and a user will receive an answer to the question ‘What RNAs contact with the selected target locus?’. These types of analysis include the following:tables of RNAs contacting the entire genome  or the selected gene or locus , with the corresponding characteristics of their contactability ;tables of genes with which the selected RNA contacts directly or in the vicinity of 50 000 nucleotides ;three types of analytical plots :contacts density distribution on target locus or on the whole genome  and 6D;change in contact density depending on the distance between the RNA source gene and chromatin target loci   anddistribution of RNA-parts of contacts across their source gene body  andthe ability to view contact maps in the UCSC Genome Browser .In addition, the RNA-Chrom database allows a user to download all pre-processed RNA–chromatin interactions data for a user’s own research or downstream analysis  and select one from it for further analysis.Homo sapiens), they should enter the RNA name in the ‘Select RNA’ field, select the needed RNA in the drop-down list and then click on the ‘GRAPHICAL SUMMARY’ button .A user may click on the ‘BROWSE ALL RNAS’ button. At the ‘Complete table of RNAs’ different filters can be used, such as ‘Search by RNA name’, ‘Select RNA names’, ‘Select RNA types’, ‘Genomic loci’, etc. . As an eThe ‘Graphical Summary’ page  consistsIn the ‘Contacts Summary’ table a user can choose, as an example, ‘Exp.ID: 14’  and then click on one of the four buttons, for example, ‘ALL TARGET GENES’. The ‘All target genes’ page will open in a new tab.From the ‘All target genes’ page  a user cThis type of analysis allows a user to find all RNAs that contact with the selected gene or locus. To perform ‘from DNA’ analysis, the following steps should be taken :A user should choose ‘from DNA’ analysis on the start page . The pagA user should click on the ‘CHOOSE A DNA LOCUS’ button located on the right side of the page .Mus musculus’, enter the approximate coordinates of the HoxA cluster (chr6:52 015 389-52 270 886) and click on the ‘APPLY’ button. Another way is to select a locus by a gene name ’ and sort the table by the column ‘max n-reads’ .To go to the ‘Graphical Summary’ page, one should click on the RNA name they are interested in .The ‘Graphical Summary’ page  consistsIn the ‘Contacts Summary’ table one can choose, for example, ‘Exp.ID: 102’ .A user may choose normalization ‘Norm. & in peaks ’ and click on the ‘VIEW IN GENOME BROWSER’ button. UCSC Genome Browser will open in a new tab .If one clicks on the ‘ALL CONTACTS’ button, the ‘Graphical Summary’ page  correspoA user can click on the ‘ALL TARGET GENES’ button, choose normalization ‘Norm. & in peaks ’ and fill the filter ‘Search by target gene’ with the value ‘hox’ . Then thThe ‘Content’ page is a table with complete meta-information for all experiments from the RNA-Chrom database . Here a The ‘Metadata’ page contains all the metadata for a particular experiment, summary statistics on data processing, ‘Shares of different RNA types in the total number of contacts’ and ‘Distribution of the number of RNAs according to the number of contacts with the genome’ plots. A user can open the ‘Metadata’ page by clicking on the experiment ID everywhere the experiment ID appears, such as on the ‘Graphical Summary’, ‘All target genes’ and other pages.The ‘Overview’ page describes the contents of the RNA-Chrom database and its functionality in detail, specifically what functions are available to a user, what formulas were used to preprocess data for plots and tables, and what information we can extract from those plots and tables.The ‘Tutorial’ page contains ‘Basic’ and ‘Advanced’ examples of both ‘from RNA’ and ‘from DNA’ assays.In order to go to the ‘Content’, ‘Overview’ or ‘Tutorial’ pages, a user should click on the corresponding buttons in the header of the website.RNA-Chrom is the first manually curated database that contains a comprehensive collection of genome-wide human and mouse RNA–chromatin interactions data: 16 all-to-all experiments and 171 one-to-all experiments, totaling more than 5 billion RNA–chromatin contacts. We paid special attention to the outstanding procedure of data processing, and a user has the opportunity to evaluate the data quality. RNA-Chrom also provides a user-friendly web interface and two types of data analysis (‘from RNA’ and ‘from DNA’), which can be used for research. Throughout the analysis, a user has the opportunity to apply different filters, such as the type of normalization, the number of contacts of RNA with the whole genome or with the target locus, CPKM, the RNA type, the length of RNA source gene and others.In order to determine the functional role of RNA in the corresponding DNA locus, additional genome-wide data and annotations are needed, for example, on the structure of chromatin, gene expression or the localization of DNA-binding and chromatin-modifying proteins. RNA-Chrom provides a variety of information about the interaction of RNA with chromatin, which can be used in a comparative analysis with other data or as a target for experimental refinements .In the future, we plan to develop the database by adding new experiments and expanding the list of organisms, as well as to realize several additional normalization procedures that will take into account dependence of contact density on distance between the RNA source gene and chromatin target loci , RNA expression level, etc. In addition to this, we are developing a special peak caller for RNA—DNA interactions data, which will be able to determine areas of statistically significant enrichment of the true signal compared to the background. As we can see, a significant fraction of reads was filtered out due to multiple mapping. We are going to develop approaches to the multiple mapping problem in these data. It is expected that the RNA-Chrom database will allow researchers to reach a more systematic level of work with the RNA–chromatin interactome, which will help to expand the understanding of the biological role of non-coding RNAs in a variety of processes.baad025_SuppClick here for additional data file.


Overall, these results reveal some unique features in sqADARs that may contribute to the high-level RNA recoding observed in cephalopods.The coleoid cephalopods display unusually extensive mRNA recoding by adenosine deamination, yet the underlying mechanisms are not well understood. Because the adenosine deaminases that act on RNA (ADAR) enzymes catalyze this form of RNA editing, the structure and function of the cephalopod orthologs may provide clues. Recent genome sequencing projects have provided blueprints for the full complement of coleoid cephalopod ADARs. Previous results from our laboratory have shown that squid express an ADAR2 homolog, with two splice variants named sqADAR2a and sqADAR2b and that these messages are extensively edited. Based on octopus and squid genomes, transcriptomes, and cDNA cloning, we discovered that two additional ADAR homologs are expressed in coleoids. The first is orthologous to vertebrate ADAR1. Unlike other ADAR1s, however, it contains a novel N-terminal domain of 641 aa that is predicted to be disordered, contains 67 phosphorylation motifs, and has an amino acid composition that is unusually high in serines and basic amino acids. mRNAs encoding sqADAR1 are themselves extensively edited. A third ADAR-like enzyme, sqADAR/D-like, which is not orthologous to any of the vertebrate isoforms, is also present. Messages encoding sqADAR/D-like are not edited. Studies using recombinant sqADARs suggest that only sqADAR1 and sqADAR2 are active adenosine deaminases The conversion of adenosines to inosines in RNAs is the most frequent form of RNA editing. Because ribosomes read inosine as guanosines, these events can recode mRNAs . HistoriDrosophila, recoding is a bit more abundant, with ∼1,000 sites conserved across the taxon  at their N-terminus followed by a catalytic deaminase domain (DD) at their C-terminus  supplemented with 10% fetal bovine serum, 1% penicillin-streptomycin solution, 1 mM sodium pyruvate, and 2 mM glutamine. Cells were seeded in culture dishes and 2 days later were transfected. For transfection, the Effectene Transfection Reagent kit  was used according to protocol.Doryteuthis pealeii brain transcriptome that was previously reported , incubated for 10 min end-over-end at 4°C, and centrifuged at 2,000 × g for 20 min at 4°C. sqADAR1 protein was then purified with the Ni2+-Nitriloacetic acid column  as described previously  total RNA  and amplified using primers with the T7 promoter sequence. Recombinant sqADAR proteins (10 nM) were incubated with the radiolabelled dsRNA substrate (0.5p.m.) for 2 h at 35°C in Q140  supplemented with 5 mM DTT, 0.5 mM PMSF, 0.5 μg/μl tRNA, and 1X Halt Protease Inhibitor cocktail . For the sqADAR/D-like co-incubation editing assay, the protein concentration was either 10 or 50nM; n = 5.Radiolabelled dsRNA substrate synthesis and non-specific editing assays were performed and analyzed as described previously . In shorIn vitro editing assays with the squid potassium channel (sqKv1.1) have been described previously (v1.1A mRNA (1 nM) in Q140 Buffer as described above. sqKv1.1 mRNA was synthesized using the T7 mScript™ Standard mRNA Production System . cDNA was then synthesized , followed by amplification using Phusion DNA polymerase  and sent to Genewiz Inc. for direct sequencing. Only the first 300 nt of the sqKv1.1A channel were sequenced, and quantification was done based on C/T dual peak heights. For clarity, sequences shown in the Figures have been reverse complemented and editing shown as A/G dual peak height in electropherograms. Assays were performed in triplicates.eviously . In shorD. pealeii. Total RNA was immediately extracted from the fresh tissues using the Trizol reagent . 500 ng of total RNA from each sample was then converted into cDNA using Protoscript II Reverse Transcriptase and Oligo dT primers .Three nervous tissues  and one non-nervous tissue (Gills) were dissected from 4 adult male specimens of cDNA from 15 ng total RNA was then quantified using hydrolysis probe-based qPCR with primers specific for sqADAR1, sqADAR2 and sqADAR/D-like . PrimersPrimeTime Gene Expression Master Mix  was used for qPCR with 250 nM forward and reverse primers and 150 nM hydrolysis probe. qPCR was performed in triplicates using a BioRad CFX Opus 96 cycler with initial denaturation at 95°C for 3 min, followed by 40 cycles of 5 s at 95°C and 30 s at 60°C.10 and 102 molecules per reaction. Standard curves were constructed by linear regression and absolute numbers of molecules in the samples were interpolated from the curves.For absolute quantification, known amounts of gBlocks Gene Fragments (Integrated DNA Technologies) corresponding to the target amplicons were used to prepare a standard curve consisting of 10-fold dilutions between 10p < 0.05. These tests were used for the data presented in One-way ANOVA and the Tukey’s test were used for mean comparisons using The IUPred2A program was used to predict the disordered portions of sqADAR1 using the default (long) setting .Taking advantage of published genomes and transcriptomes from squid and octopus , we searDrosophila ADAR2 has the same domain architecture  residue. Three of these codons  are edited at all three positions, leading to outcomes K, E, R or G. These changes may lead to a possible charge reversal (K > E), a side-chain erasure (K > G) or a minimal change (K > R). There are 2 sites in the single dsRBM, 4 in the linker between the dsRBM and the DD, and 12 in the DD, 9 of which recode. Due to their locations, some editing events are worth highlighting : N110 is important for Z-DNA binding  cDNA as a template. Sanger sequencing revealed 30 editing sites . These s binding ; K833, w binding ; and K10in folds . As previn folds , sqADAR2P. pastoris and showed that both forms are active (P. pastoris but were unsuccessful (ADAR1s are notoriously difficult to purify from heterologous systems). Small amounts of sqADAR1, however, could be purified from transiently transfected HEK293T cells . As a positive control, sqADAR2a and sqADAR2b gave robust catalytic activity converting 48% ± 2% and 53% ± 3% of the A’s→I’s, respectively  and one non-neural (gill) tissues. This was accomplished using qPCR. Specific primer pairs were designed for each ADAR  and testThe high-level recoding by RNA editing in the coleoid cephalopods appears unique, yet the underlying mechanisms are not well understood. Data presented in this study provide a catalogue of candidate features that may contribute to extensive editing. We also provide a complete list of the complement of functional sqADARs based on transcriptomics, genomics, functional assays, and expression patterns. As vertebrates, squid express two active ADARs and a catalytically inactive one, and the two active ones are orthologous between the clades. Despite these similarities, the two active squid ADARs possess unique domains. Particularly striking are the SRD of sqADAR1, the extra dsRBM of sqADAR2 and the fact that the mRNAs encoding both are themselves extensively edited.Of the two active sqADARs, sqADAR1 is the more divergent from the vertebrate orthologs. First of all, it is missing the Z-β domain and two of the three dsRBMs. On top of this, the SRD is a truly unique feature for an ADAR and draws one to speculate about its purpose. The SRD is very positively charged at pH 7, which could promote non-specific binding to the negatively charged RNA backbone. This RNA binding could be further regulated via phosphorylation. In the SRD there are 67 potential phosphorylation sites, and the addition of these negative charges would serve to reduce RNA binding, perhaps in a graded manner. Another level of control could be by editing adenosine residues within the sqADAR1 mRNA itself. In the serine-rich region there are a total of 11 editing sites within 5 lysine codons, recoding the position to an E, R or G. These changes would lower the pKa and thus affect RNA binding. Finally, the SRD is predicted to be intrinsically disordered; thus it may serve to promote phase partitioning, or promote sqADAR1’s association with partitioned RNA in granules. The relationship between edited RNA and RNA phase separation/RNA granules is unexplored.6 binding (There are many editing sites in the sqADAR1 messages, with many in areas outside of the SRD, and some have the obvious potential to regulate activity. For example, codon N110 can be edited to D, S or G and this residue has been shown to be important for Z-DNA binding . In addi binding  thus thiin vitro editing results on sqKv1 messages, however, do not agree with this idea.The expression pattern of sqADARs across tissues might provide clues on their activities. qPCR analysis revealed that sqADAR1 is the most highly expressed isoform in the nervous system and sqADAR2 is the predominant ADAR in the gill. Message recoding is many times higher in the nervous system than in other tissues, however stochastic editing in non-coding regions is spread uniformly across tissues . Accordiin vivo (in vivo are not edited by either sqADAR in our in vitro assay. The inability to reproduce all naturally occurring editing sites in vitro could be due to the fact that the entire structure required for editing is not encoded in this substrate. For instance, the sqKv1.1 pre-mRNA contains a very large intron at the beginning of the pre-mRNA coding sequence and none of the intronic sequence is included in our substrate. Another possibility is that there are other accessory proteins or RNAs in squid that influence editing site selection.sqADAR2 edits 4 of the 9 sites in our substrate that are known to be edited in vivo  while sqin vivo . At the Drosophila, whose genome encodes a single ADAR, a fully-active ADAR2 ortholog (in vitro. In vertebrates, hADAR3 has also been shown to inhibit ADAR2 activity (Interestingly, both cephalopods and vertebrates appear to require a catalytically inactive ADAR-like protein, at least in terms of adenosine deamination. The same cannot be said for ortholog . sqADAR/ortholog . These iortholog . Residueortholog  are alsoactivity . sqADAR/activity . ADADs aactivity . The funIn summary, the molecular underpinnings of squid ADARs are complex. The gene complement is remarkably similar to that of vertebrates: an ADAR1 ortholog, an ADAR2 ortholog and a third protein that may play a similar role as ADAR3, ADAD1 or ADAD2, or perhaps a wholly different role. Many of the features within these genes, however, appear to be unique for cephalopods. Of particular interest are the SRD of sqADAR1, the extra dsRBM of sqADAR2, and the extensive self-editing of the transcripts for both. Recent advances on the use of CRISPR-Cas9 mediated gene knockouts in cephalopods will enable us to explore these features more thoroughly with the goal of better understanding the mechanisms underlying high-level RNA recoding in the coleoid cephalopods.


Howbeit, the mechanism underlying the m5C modification in carcinogenesis remains to be fully addressed.The precise temporal and spatial regulation of N5C levels were determined by mRNA isolation and anti‐m5C dot blot in both retinoblastoma (RB) cells and clinical samples. Orthotopic intraocular xenografts were established to examine the oncogenic behaviours of RB. Genome‐wide multiomics analyses were performed to identify the functional target of NSUN2, including proteomic analysis, transcriptome screening and m5C‐methylated RNA immunoprecipitation sequencing (m5C‐meRIP‐seq). Organoid‐based single‐cell analysis and gene‐correlation analysis were performed to verify the NSUN2/ALYREF/m5C‐PFAS oncogenic cascade.Global and mRNA m5C RNA methylation fuels purine biosynthesis during the oncogenic progression of RB. First, we discovered that global and mRNA m5C levels were significantly enriched in RBs compared to normal retinas. In addition, tumour‐specific NSUN2 expression was noted in RB samples and cell lines. Therapeutically, targeted correction of NSUN2 exhibited efficient therapeutic efficacy in RB both in vitro and in vivo. Through multiomics analyses, we subsequently identified phosphoribosylformylglycinamidine synthase (PFAS), a vital enzyme in purine biosynthesis, as a downstream candidate target of NSUN2. The reintroduction of PFAS largely reversed the inhibitory phenotypes in NSUN2‐deficient RB cells, indicating that PFAS was a functional downstream target of NSUN2. Mechanistically, we found that the m5C reader protein ALYREF was responsible for the recognition of the m5C modification of PFAS, increasing its expression by enhancing its RNA stability.Herein, we report that NSUN2‐mediated m5C function during tumour progression. As the NSUN2/ALYREF/m5C‐PFAS oncogenic cascade is an important RB trigger, our study suggests that a targeted m5C reprogramming therapeutic strategy may be a novel and efficient anti‐tumour therapy approach.Conclusively, we initially demonstrated that NSUN2 is necessary for oncogenic gene activation in RB, expanding the current understanding of dynamic m NSUN2‐mediated m5C modification accelerates retinoblastoma progression.NSUN2 is necessary for PFAS activation in vitro and in vivo.m5C modification is important for purine synthesis in retinoblastoma. In this study, we found that enhanced NSUN2 leads to an elevated level of m5C modification, which supported cell growth both in vitro and in vivo. Using genome‐wide proteomic analysis, transcriptome screening, m5C‐meRIP‐seq and organoid‐based single‐cell analysis, we found that NSUN2 enhances the expression of phosphoribosylformylglycinamidine synthase (PFAS), which is a vital enzyme in purine biosynthesis, serving as a functional downstream target of NSUN2. Mechanistically, we found that the m5C reader protein ALYREF was responsible for the recognition of the m5C modification of PFAS, increasing its expression by enhancing its RNA stability. Overall, we revealed that m5C modification on mRNA is important for purine synthesis, which bridges the current understanding of RNA modification and metabolic reprogramming. Since the NSUN2/ALYREF/m5C‐PFAS oncogenic cascade is an important trigger of RB, our study provides a novel targeted m5C reprogramming therapeutic strategy, which may potentially be an efficient anti‐tumour therapy approach.Thus, we aimed to identify the oncogenic function of m22.12. The cells were authenticated by STR profiling.The RB cell line Y79 was acquired from American Type Culture Collection. The RB cell line WERI‐Rb1 and the adult retinal pigment epithelium cell line ARPE‐19 were purchased from Cell Bank . The cells were cultured in RPMI 1640 medium  supplemented with 10% foetal bovine serum  and 1% penicillin/streptomycin. The cultures were cultured in a humidified atmosphere at 37°C with 5% CO2.2RB tumour tissues and adjacent normal retinas were collected in the Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. We detached the tissues from the vitreous cavity of the eyeball. After snap‐frozen in moderate liquid nitrogen, fresh tissue samples were placed at −80°C for long‐term storage. Prior to surgery, patient consent documents from the Institutional Research Ethics Committee were obtained. The clinicopathological information for these tissue specimens is described in Table 2.3Immunofluorescence was performed as described previously.2.45C antibody  at 4°C overnight. After three washes with TBST , the membranes were incubated with HRP‐conjugated anti‐rabbit IgG  for 1.5 h at RT and then visualized using an enhanced chemiluminescence kit  and a detection instrument .Total RNA was extracted using TRIzol reagent (Invitrogen) according to the standard manufacturer's protocol and then quantified and diluted in 10 mM Tris‐EDTA buffer. The indicated amounts of RNA samples were loaded onto Hybond‐N + membranes . The membrane was crosslinked at 254 nm UV for 60 s after a short drying process, blocked with 5% milk for 1.5 h at RT and incubated with an anti‐m2.5Western blotting was performed as described previously.2.6Total RNA was extracted using TRIzol reagent as above described. cDNA was then synthesized using a PrimeScript RT Reagent Kit (Takara). qRT‒PCR was executed on a Roche LightCycler 480 system . The primers used in this study are listed in Table 2.6.1According to the manufacturer guideline and previous studies,2.6.2According to the manufacturer guideline, the Cytoplasmic and Nuclear RNA Purification Kit  was used. Briefly, the culture was dissolved with 200 μL lysis buffer. After a short vortex and centrifugation, the cytoplasmic RNA was transferred into another tube. A moderate buffer solution was added into the cytoplasmic and nuclear RNA. The mixture was centrifuged for 1 min at 3500 g. Then, column wash and RNA elution were performed again to separate cytoplasmic and nuclear RNA. The RNA was placed at −80°C for long‐term storage.2.6.37 cells were harvested and treated with 500 μL .4 mol/L perchloric acid solution. After ultrasonic treatment, the protein concentration was detected through a BCA assay. Hundred microliters supernate was mixed with 100 μL .4 mol/L potassium hydroxide solution, centrifuged for 10 min at 12 000 rpm at 4°C. The supernate was analysed using waters 2695 high‐performance liquid chromatograph . After normalization by protein concentration, inosinemonphosphate (IMP) concentration was analysed and calculated.According to the published method,2.7A combination of Lipofectamine 3000 reagent (Invitrogen) and Opti‐MEM I Reduced Serum Medium (Gibco) was employed to transfect 293 cells with 3 μg of plasmid and 6 μg of PsPax plasmid and 3 μg of pMD2.D plasmid. After 4 h, the medium was replaced with 12 mL of fresh medium. The medium was gathered at 72 h. Prior to transduction, the cell medium was replaced with a virus‐containing medium containing 3 ng/mL polybrene . The medium was refreshed after transduction. The selection was performed with 3 μg/mL puromycin for 2 weeks and 1 μg/mL puromycin  for a long time.2.8ALYREF siRNA was purchased from Genomeditech . The sequences of the selected siRNAs are listed in Table 2.9In total, 3000−5000 RB cells were seeded into per well of 96‐well plates. Then, 10 μL of Cell Counting Kit‐8  reagent was added to each well at the indicated time. After incubation for 3 h, the absorbance of 450 nm was detected with a microplate reader .2.104 RB cells were mixed .75 mL complete medium and .75 mL .4% agar and seeded. Every 3 days, 150 μL of complete medium was added to keep the soft agar wet. The 6‐well plates were cultured for a month. After that, the soft agar was washed three times and then stained with a .1% crystal violet solution for 3 h. Images were captured, and the number of colonies was counted using ImageJ software (7.0).A soft agar assay was performed as described previously.2.114 Y79 cells from each group were injected into the eyeball with a sharp 30‐gauge injection needle. The infected eyes were protected with ophthalmic bacitracin ointment. Four weeks after tumour cell injection, the nude mice were sacrificed, and the eyeballs were excised, weighed and photographed. The tumours were embedded in paraffin and then sliced into 2 μm thick sections. Next, the slides were incubated with the specific primary antibody at 4°C overnight, then incubated with biotinylated goat anti‐rabbit serum streptavidin–peroxidase conjugate at RT for .5 h. Finally, after sections were developed with diaminobenzidine and counterstained with haematoxylin, images were captured.Animal ethics were approved by the Institutional Animal Care and Use Committee of the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. Eighteen 5‐week‐old BALB/c nude mice were obtained from the Model Animal Research Center of Shanghai Jiao Tong University School of Medicine. After a week of environmental adaptation, approximately 5−10 × 102.12Briefly, total RNA was isolated from the cultured cells using a TRIzol reagent (Sigma‒Aldrich). Then, we confirmed the RNA integrity using a 2100 Bioanalyzer  and detected the RNA concentration using a Qubit 2.0 fluorometer with a Qubit RNA assay kit . Then, sequencing libraries were generated using an Illumina TruSeq RNA Sample Prep Kit . Finally, the libraries were sequenced on the Illumina HiSeq 3000 platform (Illumina).2.13The control and NSUN2‐deficient Y79 cells were lysed with SDT buffer . Protein supernatants were subjected to protein digestion, tandem mass tag labelling, fractionation, LC‒MS/MS analysis, protein identification and protein quantitation.2.145C antibody was conjugated to protein A/G beads at RT for 1 h. The RNA fragments were incubated with the beads at 4°C overnight. Then, the captured RNA was eluted from the beads and extracted with TRIzol reagent. Both the input sample and the m5C IP sample were subjected to library generation. Libraries were qualified using an Agilent 2100 bioanalyzer  and sequenced on a NovaSeq 6000 platform (Illumina). After quality control and removal of low‐quality reads, the clean reads of all libraries were aligned to the reference genome (HG19) using HISAT2 software (v2.0.4) 36. Methylated sites on RNAs (peaks) were identified and differentially methylated sites were identified using diffReps. Moreover, GO and pathway enrichment analyses were performed using the differentially methylated protein‐coding genes.In brief, RNA was randomly fragmented to approximately 200 nt using RNA Fragmentation Reagents, and m2.157 cells were lysed to obtain 250 μL of RIP lysate, of which 20 μL was kept as an input control and 200 μL was enriched with antibody‐ or rabbit IgG‐conjugated Protein A/G Magnetic Beads in IP buffer supplemented with RNase inhibitor at 4°C overnight. The immunoprecipitated RNA was digested and purified with the beads. The purified RNA and the input control were further analysed via qPCR. The following primary antibodies were used in the study: anti‐ALYREF , anti‐YBX1  and anti‐MTR4 .A Magana RIP Quad kit  was used to examine RNA‐binding proteins on specific genes according to the manufacturer's protocol. Briefly, a total of 3.0 × 102.16According to the manufacturer's protocol , a standard curve was generated. Then, sample solutions were prepared through multigelation and added to the detection plates. The reaction system was incubated at 37°C for 1 h with 100 μL HRP conjugated antibody in each well. After five washes with wash buffer, 100 μL of chromogen solution was added to each well. The mixture was gently mixed and incubated for 15 min at 37°C. Finally, within 15 min, the absorbance of each well was measured at 450 nm using a microtiter plate reader.2.17A total of 500−1000 Y79 cells were seeded into 6‐well plates for 24 h. Cells were treated with 5 μg/mL actinomycin D (Sigma‒Aldrich) and collected at the indicated time points. RNA isolation and qRT‒PCR were performed further as described above.2.18t‐test. Differences were considered significant at p value < .05, and asterisks denote statistical significance .Prism 7.0 software  was used for statistical analyses. Quantification data are presented as the mean ± SD, and differences between the two groups were compared with an unpaired Student's 33.15C modification during the pathogenesis of RB, we first compared the m5C modification levels between RB samples and normal retinas. As demonstrated by anti‐m5C dot blot assay results, RB samples presented with elevated global m5C levels   Figure . Notablys Figure  and cells Figure . ImportaA Figure  levels.R = .62, p < .001), differentiation , inflammation  and metastasis . Conclusively, these observations indicate that NSUN2 overexpression potentially serves as an “oncogenic trigger” in the pathogenesis of RB.Interestingly, according to single‐cell analyses in RB organoids,3.2NSUN2 expression in RB cell lines was noted after transfection with the two shRNAs, as demonstrated by qRT‒PCR  to identify m5C‐methylated transcripts in both RB cells and normal control cells . Among these genes, we found that phosphoribosylformylglycinamidine synthase  between NSUN2 and PFAS expression in a cohort of 76 RB samples  and metastasis  scores  group , metastasis  and stemness  scores (Figure R = .494, p = 5.80e‐06, Figure We then explored the detailed mechanism underlying the mp Figure . Taken ts Figure . Most imPFAS were markedly decreased after ALYREF silencing, followed by a significant reduction in RNA stability (Figure 5C reader to recognize and facilitate RNA transportation of m5C modified mRNA.5C‐dependent manner. Taken together, these results support the idea that ALYREF serves as an important recognition regulator of the m5C‐methylated PFAS transcript.To verify the importance of the regulation of PFAS by ALYREF, we subsequently silenced ALYREF using two individual siRNAs and assessed the expression levels of PFAS. Intriguingly, the mRNA Figure  and proty Figure . In addiy Figure  and attey Figure  in RB cey Figure . Since A45C RNA modification plays essential roles in the determination of RNA fate, controlling RNA stability and thereby regulating its expression.5C RNA modification and RB remains enigmatic. In this study, we demonstrated that NSUN2‐mediated m5C RNA methylation was tumour‐specifically elevated, which fuels purine biosynthesis during the oncogenic progression of RB. Mechanistically, NSUN2 methylated the PFAS transcript and promoted its RNA stability in an ALYREF‐dependent manner. Conclusively, this study initially demonstrated that NSUN2 is necessary for oncogenic gene activation in RB, expanding the current understanding of dynamic m5C function during tumour progression. Since NSUN2‐mediated m5C RNA modification is an important trigger of purine synthesis, our study bridges the current knowledge of m5C modification and metabolic reprogramming in cancer (Figure Dynamic and reversible regulation of mr Figure .5C modification promotes the pathogenesis of bladder cancer by enhancing the binding of YBX1 to HDGF and thereby promotes its expression.5C‐dependent manner.5C function during tumour progression. These studies indicated that NSUN2‐mediated m5C modification regulates cancer cell fate through the metabolism of mRNA. Moreover, recent studies have demonstrated that m5C RNA modifications of rRNA and tRNA participate in diversified biological functions. For instance, NSUN1‐mediated m5C regulates ribosome biogenesis via regulating pre‐rRNA processing.5C modification regulates tRNA function and the brain proteome to cognition and complex behaviours.5C modification could also regulate metabolic reprogramming through tRNA methylation, the role of m5C‐mediated tRNA methylation in RB tumorigenesis awaits successive investigations.Notably, NSUN2, a 5‐methylcytosine RNA methyltransferase, has been reported to function as an indicative regulator of the cell proliferation and metastasis observed in diverse cancer types. For example, NSUN2‐mediated mde novo synthesis of purines, playing an important role in RIG‐I activation during viral infection, autophagic regulation and carcinogenesis.Notably, PFAS is an essential enzyme in the 55C function during tumour progression. Notably, we revealed that m5C modification on RNA is important for purine synthesis, which bridges the current understanding of RNA modification and metabolic reprogramming. Since the NSUN2/ALYREF/m5C‐PFAS oncogenic cascade is an important trigger of RB, our study provides a novel therapeutic strategy, namely, a ‘targeted m5C reprogramming strategy’, that may potentially be an efficient anti‐tumour therapy.In this study, we initially demonstrated that NSUN2 is necessary for PFAS activation by enhancing its RNA stability in RB, which expands the current understanding of dynamic mThe authors declare that they have no conflict of interest.Supporting InformationClick here for additional data file.


Using aqueous precursors, we report successfully fabricating thin-solid films of two nucleic acids, ribonucleic acid (RNA) and deoxyribonucleic acid (DNA). We investigated the potential of these films deposited on a fiber optic platform as all-fiber integrated saturable absorbers (SAs) for ultrafast nonlinear optics. RNA-SA performances were comparable to those of DNA-SA in terms of its nonlinear transmission, modulation depth, and saturation intensity. Upon insertion of these devices into an Erbium-doped fiber ring-laser cavity, both RNA and DNA SAs enabled efficient passive Q-switching operation. RNA-SA application further facilitated robust mode-locking and generated a transform-limited soliton pulse, exhibiting a pulse duration of 633 femtoseconds. A detailed analysis of these pulsed laser characteristics compared RNA and DNA fiber optic SAs with other nonlinear optic materials. The findings of this research establish the feasibility of utilizing RNA as a saturable absorber in ultrafast laser systems with an equal or higher potential as DNA, which presents novel possibilities for the nonlinear photonic applications of nucleic acid thin solid films. One of the advantages of utilizing these fundamental biological constituents is their unparalleled abundance in nature12. Nucleic acids and nucleobases are found in virtually all living organisms14, making them an abundant and sustainable source. Furthermore, they possess inherent bio-compatibility, making them ideal for biomedical applications and a well-proven capability to integrate biochemical functionalities16. The authors' group has experimentally demonstrated short pulse generation using a thin solid film (TSF) of DNA8 and nucleobases9, providing compelling evidence for their high potential in nonlinear optic applications.In recent years, researchers have been exploring the use of novel biomaterials19 that have not been fully explored in the field of nonlinear optics thus far. In contrast to DNA20, RNA has a short single-strand structure, which makes it an ideal low-viscosity aqueous precursor in the thin-solid-film (TSF) fabrication process. RNA dissolved in water could make a more efficient and reliable precursor option than DNA for TSF formation due to its unique low viscosity even at a high doping rate. RNA also has higher UV radiation resilience23 and chemical stability25 making it a more promising candidate for practical thin solid film applications. In our prior report26, we experimentally confirmed that additional heat should be supplied to make RNA aqueous solutions which strongly implies that RNA can sustain a higher temperature than DNA. An appropriate viscosity of the liquid precursor is essential in TSF processes to provide uniformity in the film thickness. RNA aqueous solution showed a viscosity26much less than DNA solution for the same concentrations. Therefore, conventional spin-coating processes are expected to obtain RNA TSFs more repeatably than DNA TSFs. Despite these high potentials of RNA TSFs, most studies on RNA have been strictly confined to aqueous solutions28, which has restricted their solid-state device explorations in contrast to vast demonstrations by DNA-TSFs40. The authors' group has made an initial report on making RNA TSF26 on silica and silicon substrates with a high uniformity using a spin-coating process. The article reported large third-order optical coefficients in RNA-TSF through femtosecond laser z-scan experiments, confirming the high potential in nonlinear optic applications.Ribonucleic acid (RNA) is another critical constituent with unique and novel optical characteristics42 on a side polished fiber (SPOF), making it an efficient saturable absorber (SA). We thoroughly investigated the nonlinear transmission of RNA-TSF on SPOF using a femtosecond laser, analyzing the modulation depth, saturation intensity, and nonsaturable loss, which were then compared with those of DNA-TSFs already estimated by the authors' group5. To demonstrate the practical application as an efficient fiber optic SA, we embedded RNA-TSF and DNA-TSF on SPOF into an erbium-doped fiber ring laser (EDFRL) cavity to generate pulses passively. We systematically analyzed the pulsed laser characteristics in the wavelength-spectral, radio-frequency, and temporal domains. To the authors' best knowledge, we successfully Q-switched EDFRL passively, using RNA and DNA SAs, the first experimental demonstration. Furthermore, we succeeded in the first mode-locking of EDFRL using RNA SA.This study presents an integration of RNA TSFs on a proven fiber optic platform technology opening new possibilities for their implementation in arbitrary fiber laser cavities as efficient nonlinear optic devices. Furthermore, we experimentally compared it with DNA TSFs' nonlinear optic performances in detail. We achieved this goal by optimizing the TSF fabrication process using an aqueous precursor composed of pure RNA dissolved in deionized water. The resulting device demonstrated a unique low-loss evanescent wave coupling between light guided by the optical fiber with RNA and DNA-TSFsFigure 46. In comparison to DNA, RNA has a significantly different water solubility43, and we developed an optimal process to prepare an RNA aqueous precursor making it suitable for conventional TSF fabrication processes. This study used a V-type Ribonucleic acid (tRNA) transferred from wheat germs . RNA powder of ~ 0.10 g was poured into deionized (DI) water of 2 mL in a vial. It was heated at ~ 40 °C and stirred magnetically for two hours to obtain five wt% aqueous precursor solutions. Note that an optimal heating process was necessary for RNA solution preparation, which differed from the DNA solution made at room temperature. Another important characteristic of the prepared RNA aqueous solution was its low viscosity, which was similar to pure water even at a high RNA concentration of ~ five wt%. This high concentration level was not possible in DNA aqueous solutions, and only a few wt% of DNA made the solution too viscous to be used in the TSF fabrication processes. In contrast to long double-strand DNAs, the short single-strand structure of RNA was attributed to these differences in the viscosity of the aqueous solutions compared.DNAs are highly soluble in water at room temperature. DNA-TSFs have been successfully fabricated on silica substrates using a spin-coating and drop-casting process with DNA aqueous solution precursors23.To deposit RNA-TSFs, we used quartz substrates washed with acetone and isopropanol for 10 min, and then the surface was treated with an oxygen plasma to make it hydrophilic. Detailed film deposition process parameters for spin-coating are similar to those reported in47. The absorption coefficient was obtained by UV–VIS-IR spectrometer . Table 51, we analyzed third-order nonlinearities RNA-TSF by axially translating the sample across the focused laser beam. We used a Ti:Saphire laser at λ = 795 nm with a pulse duration of 90 fs and a pulse repetition rate of 80 MHz. From the best fittings to the Z-scan measurements, we could estimate the nonlinear refractive index (n2) and nonlinear absorption coefficient (β)48, from which the real and imaginary part of χ(3) for RNA-TSF are obtained using the following Eqs.52:The Wollam ellipsometry system was used to estimate the linear refractive index and film thickness based on Cauchy modeln0 is the linear refractive index, n, in Table Here, 5 and nucleobase TSF9 showed n2 ~ 10–12 cm2/W, and β of 10–9 ~ 10–8 m/W in the similar spectral range. RNA-TSFs showed nearly the same n2 but less β, resulting in a magnitude of χ(3) ~ 10-10esu. The magnitude of χ(3) was comparable or larger than those of DNA (~ 10–11)5 and nucleobase TSFs9. When compared with other organic nonlinear optic materials54 RNA TSF showed significantly higher χ(3), and we pursued its applications in short pulse lasers as explained in the following sections.DNA-TSF3 with an insertion loss of < 0.5 dB. The top surface of SPOF was oxygen-plasma treated, and RNA was deposited on it by drop-casting processes56, which ensured a sufficiently thick film thickness for the evanescent wave coupling with the light guided by the optical fiber. The optimal thickness of RNA TSF on SPOF at the evanescent wave coupling region61 was empirically found to be ~ 300 nm to make the device an efficient all-fiber saturable absorber (SA). The prepared samples were then slowly heated in a vacuum desiccator at 30 ºC for 24 h to drive out air bubbles reducing the scattering sites62.We prepared one wt% RNA aqueous solution using the process described in the previous section. We used side-polished optical fibers (SPOFs) purchased from KS Photonics with the standard quartz block 5 × 10 × 27mm63:T is the nonlinear transmission, a0 modulation depth, and ans nonsaturable loss. I and Isat are the incident light intensity and the saturation intensity, respectively. The transmission did not reach the full saturation level due to the limited laser power in the experiments. Still, we were able to estimate a0 > 1.2%, Isat = 1.8 MW/cm2, and ans < 97% by fitting experimental results with Eq. (68. Note that the modulation depth of RNA was larger than DNA (a0 ~ 0.4%) and nucleobases (a0 ~ 0.4 ~ 0.9 wt%)9. Figure We measured the transmission of RNA-TSF on SPOF using a femtosecond laser at the wavelength of λ = 1550 nm, and the experimental setup is schematically shown in Fig. 2 ~ –22.3 ps2/km, attenuation at λ = 1530 nm ~ 0.08 dB/km) was used as a gain medium. The EDF was pumped by a laser diode (LD) at λ = 980 nm via a 980/1550 nm wavelength division multiplexer (WDM). A polarization controller (PC) was used to adjust the polarization state of the laser inside the cavity, and an optical isolator was used to remove the unwanted back-reflection. A fiber coupler with a 90:10 optical power ratio at λ = 1550 nm was used as an output coupler of the laser cavity. The laser outputs were analyzed by using an electrical spectrum analyzer  in the frequency domain, an oscilloscope  in the temporal domain, and an optical spectrum analyzer  in the wavelength domain. Here we used a photodetector with a maximum bandwidth of 1.2 GHz to fully characterize the laser pulses.After confirming the nonlinear transmission of RNA-TSFs on SPOF, we implemented both RNA-SA and DNA-SA devices separately into an erbium-doped fiber ring laser (EDFRL) cavity to generate pulse trains. Figure 2. We successfully obtained Q-switching using a nucleic acid TSF on SPOF as a fiber optic SA for the first time.In Q-switching experiments, we used EDF of 1.5 m, and the overall cavity length was about six meters. corresponding net dispersion was estimated to be about -0.16 ps69. Other than the pumping power differences, the quality of the interface between the nucleic acid TSF and the polished fiber surface at SPOF could be an important attribute, which can incur additional cavity loss and the evanescent wave interaction length41. We found noticeable variations among the prepared TSF on SPOFs, and the decisive parameters to determine the lasing wavelength was not clearly understood. These results suggest that variables beyond the magnitude of pump power considerably influenced the determination of the central wavelength. The particular molecular configuration and the manufacturing process employed for the RNA and DNA TSFs could also be responsible for the observed variation in central wavelengths. Even subtle changes in these factors could potentially affect the nonlinearity of these materials70, subsequently impacting the central wavelength of the Q-switched lasers. Here we report the most stable Q-switching results for RNA and DNA TSF-SAs.For RNA-TSF SA, stable pulse trains were obtained at the central wavelength of λ = 1566 nm for the pump power of 458 mW. The laser pulse width was ~ 3.2 µs, and the pulse repetition rate was 39 kHz. In the case of DNA-TSF SA, the central wavelength of the laser was at λ = 1600 nm for the pump power of 415 mW. The laser pulse width was ~ 4.8 µs, and the pulse repetition rate was 34 kHz. Comparison of the Q-switched lasers for RNA-TSF SA and DNA-TSF SA are summarized in Fig. 71 of the gain medium and the interaction with the saturable absorber can influence the temporal characteristics of the Q-switched pulses73. We believe that the interface between the nucleic acid TSF and the SPOF variations, as stated above, could eventually affect the laser wavelength in the spectral domain and the temporal characteristics. Further identification of the main attributes is being pursued by the authors.In the time domain, the traces of the oscilloscope measurements are shown in Fig. 74. The pulse repetition rate of RNA and DNA Q-switching increased from 25 to 39 kHz and 19.1 kHz to 34.4 kHz, respectively. The maximum available pulse energy and peak power were 3nJ and 0.9 mW, respectively for RNA Q-switching. In DNA Q-switching showed a maximum pulse energy of ~ 140 nJ and peak power of ~ 27 mW. See Fig. 79. DNA Q-switching was comparable to other inorganic SAs, but RNA Q-switching showed less output energy and peak power.Figure 81 as compared to their DNA counterparts when subjected to electric or magnetic fields. In the TSF deposition process, RNA molecules are directly influenced by the surface of the SPOF, which exerts a certain electric field and the nanoscopic grooves can also align RNA to a certain direction similar to the DNA case82 Well-defined surface treatment of the substrate for RNA TSF deposition could be a critical factor to control its net nonlinear optic effects85 in pulse generation applications.RNA molecules are known to exhibit a significantly higher dipole moment2. The cavity length equilibrates the nonlinearity and dispersion inside the fiber laser cavity. Note that in Q-switching the overall loss of the cavity was higher by 1–2 dB than in mode-locking. Here we used RNA-TSF SA optimal for the mode-locking, which was chosen empirically.We further investigated passive mode-locking using our RNA-TSF SA in an anomalous dispersion regime by adjusting the polarization state and optimizing the length of the cavity, which was set at approximately 9.5 m. We employed an EDF with a length of 0.9 m and achieved a net dispersion value of -0.19 ps88 in the initial pulse generation. However, recent works on passive SA revealed90 that the saturable absorption in the nonlinear optic material plays the dominant role in pulse generation processes. Our experimental observation for RNA/DNA agreed well with their interpretation of the role of SAs.We did experiments with a similar side polished optical fiber block without any RNA/DNA film deposited. In this case, the role of DNA/RNA can be excluded entirely. There were sporadic pulses but their duration/repletion rate was not controllable by rotating PC. In contrast, only after RNA/DNA films were deposited, both Q-switching and mode-locking were obtained in a very stable manner, which were maintained over hours. The fiber optic SA did show polarization dependence of 20 dB and there could be a contribution from nonlinear polarization rotation (NPR)64. A stable and self-starting mode locking was observed in a pump power range of 107 to ~ 370 mW. The typical shape of soliton pulses with Kelly sidebands91 was observed in the wavelength spectral domain as in Fig. 94. Figure 2 pulse shape, indicating that the pulse is chirped slightly. In Fig. 5 and nucleobase9, indicating stable and robust mode-locking using RNA-TSF SA.The output characteristics of the mode-locked laser are summarized in Fig. 99. Here we compared various nonlinear optic SAs deposited on SPOF.Some of the recent passively mode-locked EDFRLs using nonlinear fiber-optic SAs are summarized in Table 4103, which can be incorporated into a mode-locked laser cavity to enable further hypersensitive photonic sensing.The proposed RNA-TSF SA showed comparable laser characteristics in the pulse duration, SNR, and average output power. See Table We experimentally demonstrated the application of nucleic acid (RNA and DNA) thin solid film (TSF) as a saturable absorber (SA) by employing it in an erbium-doped fiber ring laser (EDFRL) cavity for short pulse generation. Nucleic acid-TSF was deposited on a side polished optical fiber (SPOF) to provide an efficient evanescent wave coupling. Q-switching by both RNA and DNA SAs was successfully achieved for the first time. RNA-TSF on SPOF provided a nonlinear transmission with a modulation depth of over 1.2%. Using the RNA-TSF SA in an EDFRL cavity, we obtained stable Q-switching. Both RNA Q-switching was achieved at λ = 1566 nm, and it showed a pulse width of 3.2 µs, pulse-repetition rate of ~ 39 kHz, pulse energy of 3nJ, and peak power of ~ 0.9mW. DNA Q-switching was achieved at λ = 1600 nm with a pulse width of 4.8 µs, repetition rate of ~ 34 kHz, pulse energy of ~ 140 nJ, and peak power of 27 mW. RNA-TSF on SPOF showed variation in nonlinear optic properties and finer control of the substrate surface morphology and deposition process parameters are being pursued by the authors to improve the energy and power of Q-switched pulses. We also demonstrated robust mode-locked soliton pulse trains at λ = 1551.3 nm with a pulse duration of 633 femtoseconds, repetition rate ~ 20 MHz, peak power 0.6 kW, and a high signal-to-noise ratio (SNR) of 71 dB. RNA-TSF showed nonlinear optic characteristics equivalent to DNA and two-dimensional materials. UV radiation resilience and high-temperature durability of RNA could enhance the long-term stability of Q-switching and mode-locking, which could be a practical advantage of RNA compared with other biomaterials. We believe that RNA-TSF can open a practical avenue for ultrafast biphotonic technologies and nonlinear optics.


Rhodobacter sphaeroides. Rhodobacter is a facultative phototroph that can perform aerobic and anaerobic respiration, fermentation, and anoxygenic photosynthesis. Oxygen concentration and light conditions decide the pathway for ATP production. Here, we show that CcaF1 promotes the formation of photosynthetic complexes by increasing levels of mRNAs for pigment synthesis and for some pigment-binding proteins. Levels of mRNAs for transcriptional regulators of photosynthesis genes are not affected by CcaF1. RIP-Seq analysis compares the binding of CcaF1 to RNAs during microaerobic and photosynthetic growth. The stability of the pufBA mRNA for proteins of the light-harvesting I complex is increased by CcaF1 during phototrophic growth but decreased during microaerobic growth. This research underlines the importance of RNA-binding proteins in adaptation to different environments and demonstrates that an RNA-binding protein can differentially affect its binding partners in dependence upon growth conditions.In natural habitats, bacteria frequently need to adapt to changing environmental conditions. Regulation of transcription plays an important role in this process. However, riboregulation also contributes substantially to adaptation. Riboregulation often acts at the level of mRNA stability, which is determined by sRNAs, RNases, and RNA-binding proteins. We previously identified the small RNA-binding protein CcaF1, which is involved in sRNA maturation and RNA turnover in  Rhodobacter are characterized by high metabolic versatility, which allows them to adapt to changing environmental conditions. While aerobic respiration takes place in the presence of oxygen, anoxygenic photosynthesis (in the presence of light), anaerobic respiration, or fermentation (both in the absence of light) can generate ATP under anoxic conditions. Many studies have addressed the adaptation of Rhodobacter capsulatus and Rhodobacter sphaeroides (now renamed Cereibacter -ATP  by a T4 polynucleotide kinase end-labeling reaction .For the detection of small RNAs, 8 µg total RNA were separated on a 10% polyacrylamide gel containing 7 M urea and transferred to a nylon membrane  by semi-dry electroblotting . For detw/v) formaldehyde gel and transferred to a nylon membrane  by vacuum blotting [32P]-CTP  by using the Prime-a-Gene Labeling System . For the detection of mRNA transcripts, 10 µg total RNA were separated on a 1% agarose . To analyze the intensities of the phosphorimaging signals the 1D-Quantity One software version 4.6.8 Basic  was used.The membranes were hybridized overnight using the Church and Gilbert buffer system , washed R. sphaeroides WT pRKccaF1FLAG_NT and R. sphaeroides pRKccaF1 as an untagged control [660 0.2 and incubated under phototrophic growth conditions for 8 h . The cells (from 100 mL culture) were harvested by centrifugation at 10,000 rpm at 4 °C. The CoIP was performed as described in Grützner et al. and Pfeiffer et al. [For CoIP, microaerobic precultures of  control  were dilr et al. ,43. The ® Green qPCR Master Mix Kit  was used as described in the manufacturer’s manual. The 10 µL reaction mixtures contained 5 µL Master Mix (supplied), 0.1 µL DTT , 0.5 µL RiboBlock solution (supplied), 0.4 µL water, 1 µL of each primer (10 pmol/L), and 2 µL DNA-free RNA (20 ng/µL). The reactions were performed in a spectrofluorometric thermal cycler , and the resulting data were visualized using the Bio-Rad CFX Manager 3.0 software. All real-time RT-PCR experiments were performed in technical duplicates with samples originating from biological triplicates. For all primers, a no-template control was included, to confirm the absence of DNA contamination. RNA abundances were normalized to rpoZ. Fold changes were calculated according to Pfaffl [For quantitative real-time RT-PCR, the Brilliant III Ultra-Fast SYBRo Pfaffl .R. sphaeroides  was performed using the READemption pipeline v.1.0.5 [The RNA-Seq data processing was performed as described in Börner et al. . The ali v.1.0.5 . Process v.1.0.5 .


We report on the effects of ethanol (EtOH) and Poly (ADP-ribose) polymerase (PARP) inhibition on RNA ribosomal engagement, as a proxy for protein translation, in prefrontal cortical (PFC) pyramidal neurons. We hypothesized that EtOH induces a shift in RNA ribosomal-engagement (RE) in PFC pyramidal neurons, and that many of these changes can be reversed using a PARP inhibitor. We utilized the translating ribosome affinity purification (TRAP) technique to isolate cell type-specific RNA. Transgenic mice with EGFP-tagged Rpl10a ribosomal protein expressed only in CaMKIIα-expressing pyramidal cells were administered EtOH or normal saline (CTL) i.p. twice a day, for four consecutive days. On the fourth day, a sub-group of mice that received EtOH in the previous three days received a combination of EtOH and the PARP inhibitor ABT-888 (EtOH + ABT-888). PFC tissue was processed to isolate both, CaMKIIα pyramidal cell-type specific ribosomal-engaged RNA (TRAP-RNA), as well as genomically expressed total-RNA from whole tissue, which were submitted for RNA-seq. We observed EtOH effects on RE transcripts in pyramidal cells and furthermore treatment with a PARP inhibitor “reversed” these effects. The PARP inhibitor ABT-888 reversed 82% of the EtOH-induced changes in RE (TRAP-RNA), and similarly 83% in the total-RNA transcripts. We identified Insulin Receptor Signaling as highly enriched in the ethanol-regulated and PARP-reverted RE pool and validated five participating genes from this pathway. To our knowledge, this is the first description of the effects of EtOH on excitatory neuron RE transcripts from total-RNA and provides insights into PARP-mediated regulation of EtOH effects. Alcohol use disorder (AUD) affects about 10% of adults in the United States . The prefrontal cortex (PFC) is a brain region thought to play an important role in alcohol seeking behavior . Prior sPoly-ADP Ribose Polymerase-1 (PARP1) is an enzyme that affects gene expression through histone modification and DNA methylation, among other molecular mechanisms . In C57BOur primary objective was to examine the effects of EtOH and of the co-administration of EtOH and ABT-888 on the distribution of RNA transcripts, specifically the subset that are captured by ribosomes for protein translation  from the total-RNA pool in excitatory PFC neurons. The addictive process is the result of a complex interplay among the various neural cell-types, including excitatory and inhibitory neurons, as well as glial cells. We hypothesized that EtOH induces a shift in RE in the PFC pyramidal neurons, and that many of these changes can be reversed using a PARP inhibitor.The cell-type specificity of the study derives from the use of a transgenic mouse model that expresses a GFP-Rpl10a ribosomal protein under the control of the promoter for CaMKIIα, an enzyme expressed predominantly in excitatory pyramidal neurons . RibosomTo obtain RNA for TRAP, we used a mouse strain in a C57BL/6J background that expresses a fluorescently tagged ribosomal protein (EGFP-Rpl10a) in the presence of tetracycline-controlled transactivator (tTA). TRAP mice for our study were derived by crossing C57BL/6J-Tg(tetO-EGFP/Rpl10a)5aReij/J with B6.Cg-Tg(CaMKIIα-tTA)1Mmay/DboJ(CaMKIIα-tTA) mice. Both mouse lines were purchased from Jackson Laboratories. The resulting offspring have ribosomes tagged with EGFP expressed only in CaMKIIα expressing cells . Genotypad libitum access to food and water. Male transgenic mice 8-12 weeks old were randomly assigned to three treatment groups: control, ethanol (EtOH), and ethanol + ABT-888 (EtOH + ABT-888). The animals were administered i.p. twice a day with normal saline (CTL) or ethanol  for four consecutive days (2 h between the first and second injection of the day). The dosing strategy was the same as the involuntary ethanol administration protocol reported earlier , EtOH group  and EtOH + ABT-888 group .An enzymatic assay calibrated against a standard curve of ethanol known concentrations was utilized to determine BECs . BrieflyThe technology was developed in the Heintz lab at Rockefeller University . BrieflyRNA samples were quantified using the Quantus fluorimeter (Promega) with dual RNA/DNA quantification. Levels of remaining DNA did not exceed 10% of the total amount of Nucleic Acid. RNA Integrity Numbers (RIN) were assessed using Agilent 4200 TapeStation (Agilent) . The samples were subjected to rRNA depletion and sequencing libraries prepared for Illumina sequencing . Final amplified libraries were purified, quantified and average fragment sizes confirmed to be 254 –323 and then subjected to test sequencing on a MiniSeq instrument in order to check sequencing efficiencies. Sequencing was carried out on NovaSeq 6000 (Illumina), SP flowcell, 2 × 50 bp PE reads.The resulting FASTQ files were checked for adapters and following QC, raw reads were aligned to the reference genome, mm10, in a splice-aware manner using the STAR aligner . The genn = 3); EtOH_TRAP (n = 4); EtOH + ABT-888_TRAP (n = 4); Control_total-RNA (n = 3); EtOH_total-RNA (n = 4); EtOH + ABT-888_total-RNA (n = 4). We further performed the following comparisons indexed in ®; QIAGEN).Six experimental samples were obtained from the three experimental conditions: Control_TRAP  for the canonical pathways indicate the probability of association of molecules from our dataset with the canonical pathway by random chance alone. IPA assigns the negative −log p-value to pathways based on a Fisher’s exact test of the probability of the number of molecules from the user-created dataset included in the given pathways vs. being included based on chance alone. Z-scores measure the inclusion/exclusion of genes within networks according to experimental conditions and indicate the activation/inhibition states of the molecule. Gene lists were uploaded to IPA with Ensemble ID, Log2 FC and FDR values and the resulting Canonical Pathway information along with –log p-values obtained.IPA Pathway lists were prioritized by computing −log ® SYBR Green/ROX qPCR Master Mix . To confirm amplification specificity, the PCR products were subject to a melting curve analysis, in which only one peak was observed. Crossing point values were measured with the PikoReal analysis software. Primers  and Maxima Primers  were despost-hoc Bonferroni or Tukey tests or with Student’s t-test as appropriate. All statistical analyses were performed using GraphPad Prism for Windows 1 or SPSS .Statistical significance was determined using one-way analysis of variance (ANOVA) followed by Egfp, CamKIIα, S100b, and Ef101557 expression in TRAP samples. We expected isolated ribosomes to have high green-fluorescent protein mRNA expression (Egfp) and CamKIIα expression and low expression of the astrocyte specific-S100b and microglial-specific Ef101557 transcripts. In support of the ability of the TRAP technique to isolate CaMKIIα-expressing cells we found Egfp  and CamKIIα  to be highly elevated in the TRAP samples compared to total-RNA, while astrocyte marker S100b  and microglial marker Ef101557  were reduced.In preliminary TRAP experiments we measured several markers that would confirm the successful isolation of RNA from CaMKIIα-expressing cells. Specifically, we measured p < 0.05) and performed pathway analyses and have included that information in In this study, total-RNA is not cell-type specific (multiple cell-types), as is TRAP-RNA, but can still provide valuable context of overall transcriptional activity in this PFC region. Because, both total-RNA and TRAP-RNA are extracted from the same sample, we can contextualize the background from which the ribosome captures RNA. We examined the distribution of RNA transcripts between the ribosomal fraction in CaMKIIα-positive excitatory neurons  and total-RNA. The first three rows of RE is dependent upon neural cell-type, the rate of genomic expression, mRNA stability, the presence of ribosome-binding motifs and their electrostatic properties, and cellular location . Given these considerations, we next restricted our analysis to only TRAP samples. Administration of EtOH caused the differential distribution of 1,365 ribosomal transcripts  across the pool of RE transcripts; 718 transcripts had a higher probability of RE, and 647 had lower RE . EnricheFollowing a similar analysis method as described in section “3.1.2. RE ratio,” we examined the EtOH total-RNA samples compared to Control total-RNA samples. EtOH induced 3,015 genes to be differentially expressed compared to control (1517 higher and 1498 lower)  and total-RNA (transcribed) to detect RNA transcripts that are significantly enriched or reduced in both ribosomes and the total-RNA pool. We identified 785 transcripts significantly altered (FDR < 0.05) in both the RE and total-RNA pools, suggesting coordinated changes in both transcription and translation regardless of cell type. These changes were in the same direction in all but three instances. Expression of Fbln5 was increased with EtOH in the total-RNA pool and decreased in the RE pool, while expression of Pltp6 and Ptpn6 was decreased with EtOH in the total-RNA pool and increased in the RE pool. We next used IPA to identify enriched canonical pathways in this data set of 785 transcripts. The top 20 pathways ranked according to their negative log p-value are shown in We wanted to identify the number of transcripts whose EtOH-induced expression changes were nullified or “reversed” by the addition of ABT-888. We identified 1115 1365-250) transcripts or 82% (1115/1365) of all EtOH affected genes to be “reversed” by ABT-888 co-administration , and Mapk11  were chosen based on the differences in logFC between the EtOH_TRAP/Control_TRAP and the EtOH + ABT-888_TRAP/Control_TRAP comparisons. Genes showing a ΔlogFC value higher than 0.50 were selected for qRT-PCR validations  within excitatory pyramidal cells from the PFC in mice exposed to EtOH. Using the TRAP method, we isolated ribosome bound RNA from these cells. We demonstrated, firstly, that this fraction of RE transcripts  is enriched for CAMKIIα expression. Further, we demonstrated the impact of EtOH exposure on the transcript distribution in both the RE and total-RNA pools. Finally, in a direct test of the PARP hypothesis from our lab , we demoPrevious studies indicate that ABT-888 reduces consumption in the binge-like drinking-in-the-dark (DID) binge-like alcohol drinking model and PARP1 overexpression in the PFC increases DID alcohol drinking behavior . We hypop-value score of this network . Given that PARP proteins are involved in DNA repair and chromatin remodeling, increased CREB signaling after administration of ABT could provide an alternate mechanism for a controlled and targeted shift in the translatome. Another interesting pathway was “Sirtuin Signaling Pathway,” which showed a decreased IPA generated –log p-value score, following administration of ABT-888. Sirtuins are described as NAD (nicotinamide adenine dinucleotide)-dependent protein deacetylases with myriad metabolic roles and interact with PARP to regulate concentrations of cellular NAD. PARP enzymes can be activated (acetylated) by p300/CBP and deactivated (deacetylated) by SIRT1. Our observation of a suppressed sirtuin pathway following ABT-888 demonstrates the intricate connection of the sirtuin family of enzymes and PARP activity. Thus, members of the Sirtuin and CREB signaling pathways could be exerting a shift in the translatome through nucleosomal DNA in a NAD-dependent manner.Pathway analyses by IPA showed an overrepresentation of many interesting pathways and we utilized IPA generated –log p-value scores to visually compare the representation of these pathways across treatment conditions . Many inWe focused on the Insulin Receptor Pathway  given thPoly (ADP-ribose) polymerase enzymes target numerous epigenetic proteins  as well as transcription factors  . One patAlthough we could not profile coordinate changes in protein manufacture, TRAP-seq correlates highly with fold changes in large protein datasets in cell studies  . FurtherThis study found that the addition of ABT-888 reversed a significant portion of the changes in transcript levels induced by ethanol, suggesting that PARP inhibitors may be able to target the molecular mechanisms underlying the development of alcohol addiction. We and others have previously reported on the role of PARP enzymes in drug-induced phenotypes. Both Cocaine and Ethanol significantly increase PARP1 expression and enzymatic activity in the nucleus accumbens and PFC respectively, and regulation of PARP inhibition modifies both cocaine and alcohol related behaviors . Of partGSE227947.The data presented in this study are deposited in the GEO repository, accession number The animal study was reviewed and approved by VA Innovation and Research Review System (VAIRRS) Subcommittee on Research Safety and Security (SRSS) Animal Component of Research Protocol (ACORP).HK contributed to the data analysis, bioinformatics interpretation, pathway analysis, and manuscript preparation. GV conducted the experimental procedures and the early phase of data analysis. HG contributed to the editing, verification, and formatting. MG contributed to conceptualization and feasibility analysis. HR contributed to the pathway analysis, bioinformatics, and manuscript preparation. DG was responsible for the conceptualization, funding, and contributed toward data analysis and manuscript preparation. RS coordinated the interpretation, data analysis, and manuscript preparation and submission. All authors contributed to the article and approved the submitted version.


Interferon induced with helicase C domain-containing protein 1 (IFIH1) gene encodes a cytoplasmic RNA helicase otherwise known as melanoma differentiation-associated 5 (MDA5), a RIG-1-like RNA helicase that recognizes viral RNA and is involved in innate immunity through recognition of viral RNA. Upon binding to double-stranded (ds) RNA, MDA5 forms a filamentous assembly along the length of dsRNA and utilizes molecular signatures to discriminate self, versus non-self on the basis of dsRNA length and methylation. Its missense variant rs35667974 is protective for type 1 diabetes, psoriasis, and psoriatic arthritis, but is also found to be associated with an increased risk for ankylosing spondylitis, Crohn’s disease, and ulcerative colitis. To gain insight into the complex role of this variant we performed a structural analysis of MDA5 in complex with dsRNA using molecular dynamics simulations. Our data suggest that while the Ile923Val mutation of the rs35667974 variant does not affect binding to native dsRNA significantly, it displays a destabilizing effect in the presence of 2′-O uridine methylation. Thus, the presence of 2′-O-methylation at the dsRNA introduces a sensing signature that leads to selective reduction of the overall MDA catalytic activity. This study represents an evaluation of the role of the shared rs35667974 variant of autoimmune locus IFIH1, reported to lead to selectively reduced catalytic activity of the modified MDA5 phenotype and, as a consequence, reduced negative feedback on cytokine and chemokine signaling and selectively protection against autoimmunity.The online version contains supplementary material available at 10.1007/s00239-022-10090-0. Genes and mechanisms involved in autoimmune diseases, which affect approximately 5% of the population, remain still elusive but accumulating data strongly suggest that different autoimmune diseases can share a common genetic background, thus pointing out the existence of variants that are shared by different autoimmune diseases , transfer RNA (tRNA), ribosomal RNA (rRNA), microRNA (miRNA), and long noncoding RNA (lncRNA). RNA molecules contain numerous (more than 150) chemical modifications  plays an important role in evasion of cellular innate immune responses in the host cells  gene encodes a cytoplasmic RNA helicase also known as MDA5 (Melanoma differentiation-associated protein 5), and it is a RIG-I-like receptor (RLR) that performs antiviral function in innate immunity by detecting viral RNAs. MDA5 recognizes 0.5–1 kb RNA duplex stem structure that is usually formed during picornaviral replication and mediates an immune response on viral infection . This rs35667974 IFIH1 single-nucleotide polymorphism (SNP), where a conserved isoleucine (codon [ATT]) at position #923 changes to valine (codon [GTT]), is a rare variant as the minor allele frequency (MAF) is C = 0.010031  based on TOPMED  based on ALFA  was retrieved from the UNIPROT database  provides a measure of selective pressure at the amino acid level. The magnitude of the value of dN/dS (ω) represents the types of selection: ω < 1 for negative selection, ω = 1 for neutral selection, and ω > 1 for positive selection .The cryoelectron microscopy (cryo-EM) structure of hMDA5–dsRNA filament in the presence of ATP (PDB ID: 6GKM)  the native MDA5–dsRNA, (ii) MDA5(V923)–dsRNA, (iii) MDA5–dsRNA(2′OMe), and (iv) MDA5(V923)–dsRNA(2′OMe). All systems were solvated in truncated octahedral solvent boxes of pre-equilibrated TIP3P water molecules, with a minimum buffer of 10 Å around the complex and then the required number of counter ions was added to obtain charge neutralization of the systems. MD simulations were performed with the GPU-accelerated version of PMEMD  throughout 1 ns, followed by 9 ns of unrestraint equilibration under constant pressure. After these initial 10 ns of equilibration , 100 ns of production simulations in the NPT ensemble were performed for each system at 300 K and 1 atm, while storing snapshots of the system every 5.0 ps for analysis using the CPPTRAJ module of AMBER 18  in the RD/CTD domain, indicating structural/functional importance. The polymorphism rs35667974 in exon 14 of the human gene causes a conserved amino acid mutation at position 923 from Ile to Val in hMDA5. However, there are another sixteen distant species that have the same position occupied by a valine  . Also, for the branch-site model C for the 39 ortholog MDA5 genes (Suppl. Table 4), 33% of the sites are evolving at category ω0 = 0. 027. On the other hand, 41% of the sites are evolving under category ω2. Yet, these have ω values that are conditional on the branch type (ω20 = 0.25 and ω21 = 15.32).In particular, for the branch-site model C for the CTD domain (Suppl. Table 3), 33% of the sites are evolving at category The conducted evolutionary analysis demonstrates that the Ile923Val substitution is not a unique variant in the human species, since Val exists in the MDA5 sequence position in other species too. MDA5 is a viral double-stranded RNA (dsRNA) receptor that plays a key role in antiviral immunity through its distinct specificity for viral RNA  of each protein residue and the hydrogen-bonding distance of H927 with U12 Below is the link to the electronic supplementary material.