Catalytically inactive CRISPR‐Cas13 (dCas13)‐based base editors can achieve the conversion of adenine‐to‐inosine (A‐to‐I) or cytidine‐to‐uridine (C‐to‐U) at the RNA level, however, the large size of dCas13 protein limits its in vivo applications. Here, a compact and efficient RNA base editor (ceRBE) is reported with high in vivo editing efficiency. The larger dCas13 protein is replaced with a 199‐amino acid EcCas6e protein, derived from the Class 1 CRISPR family involved in pre‐crRNA processing, and conducted optimization for toxicity and editing efficiency. The ceRBE efficiently achieves both A‐to‐I and C‐to‐U base editing with low transcriptome off‐target in HEK293T cells. The efficient repair of the DMD Q1392X mutation (68.3±10.1%) is also demonstrated in a humanized mouse model of Duchenne muscular dystrophy (DMD) after AAV delivery, achieving restoration of expression for gene products. The study supports that the compact and efficient ceRBE has great potential for treating genetic diseases. For all CRISPR/Cas systems, Cas6 is the smallest crRNA‐binding protein with only 199 amino acids. Similar to Cas13 protein, Cas6 can also be developed into an efficient and high‐fidelity RNA base editor. Through AAV delivery, Cas6 base editor, ceRBE, can successfully treat humanized mouse model of Duchenne muscular dystrophy (DMD). However, the large size and low editing efficiency of dCas13‐based RNA base editors still limit its application in vivo therapy. Effectively delivering the RNA base editors to the specific tissues is crucial for its use as therapeutic drugs. Adeno‐associated virus (AAVs) is the most promising vehicles of gene therapy due to their simplicity, low genotoxicity, and long‐term gene expression. However, the size of most base editors, consisting of dCas13 protein binding to RNA deaminase, makes it difficult to package into AAV for efficient in vivo delivery. Therefore, a smaller RNA base editor with higher editing efficiency in vivo is needed.RNA editing can modify gene products without causing permanent changes in the genome, and has great potential in gene therapy research. Among the numerous RNA base editing technologies, the base editor composed of catalytically inactive RNA‐targeting CRISPR‐Cas13 (dCas13) protein and a specific RNA deaminase has great advantages in efficiency and editing types.2, 3 Among all Cas13 proteins, Cas13X.1 is the smallest protein with 775 amino acids which is more suitable for AAV delivery. The HEPN‐inactive Cas13s have been engineered as programmable RNA‐binding modules for RNA base editing.The Cas13 protein is a crRNA‐mediated CRISPR nuclease targeting single‐stranded RNA for cleavage. Unlike Cas9, Cas13 processes its own pre‐crRNA into mature crRNAs without tracrRNA and RNase III. All Cas13 proteins carry a pre‐crRNA processing active site and a target RNA cleavage active site formed by two HEPN domains.6, 7 In type I CRISPR‐Cas systems, the Cas6 is also a key component of Cascade complex. Cas6f (Csy4) was reported to have high‐affinity for its pre‐crRNA and mature crRNA with an equilibrium dissociation constant of 50 pM. By taking advantage of the hairpin specificity of the Cas6 proteins, Csy4 (Cas6f) and Cse3 (Cas6e) have been used for multiplexed crRNA release and RNA tracing. Considering the small size of Cas6, we wonder whether Cas6 can be applied to RNA editing like Cas13.The Cas6, Cas5d and Csf5 proteins are small endoribonucleases with around 200 amino acids that process pre‐crRNAs for Class 1 CRISPR‐Cas systems.9 In tHere, we describe a smaller RNA base editor with higher editing efficiency in vivo than the existing dCas13‐mediated RNA base editors – ceRBE. We replace the existing dCas13 protein with ten small pre‐crRNA processing proteins, and successfully achieve RNA base editing. The EcCas6e protein, with low off‐target and high editing efficiency, is selected to optimize for toxicity and editing efficiency. Compared with the RESCUE‐S editor with the same deaminase, the optimized ceRBE shows a higher A‐to‐I and C‐to‐U editing ratio in HEK293T cells  with lower transcriptome off‐target. Further, to determine the therapeutic potential of the editor, we package the editor into a single AAV and explore in vivo treatment of the DMD Q1392X mutation in the humanized mouse model of DMD. The proportion of dystrophin fibers recovers to 68.1±9.4% at three weeks after intramuscular injection. Overall, ceRBE, as a small and efficient RNA base editor, exhibits strong therapeutic potential for the genetic diseases.22.1 MmCas6, BhCas5d, SpCas5d, SsCas6, EcCas6e, PaCas6f, MtCas6, PfCas6, and PaCsf5 . We further added a nuclear localization signal (NLS) to both ends of the fusion proteins and cloned it into a GFP expression vector. Our initial assays adopted an mCherry reporter system. Briefly, we introduced stop codons (G‐to‐A mutation) in the mCherry coding sequence , only when a fusion protein achieves an A‐to‐I conversion of the mutated position of the substrate reporter mRNA, the red fluorescence signal (RFP) will be evident .2 We ft Figure . We trang Figure . Among tg Figure . Taking 2.2Figure we examined the variant editor bearing this mutation and detected obviously reduced cytotoxicity  showed the highest red fluorescence ratio  or one HIV Rev nuclear export sequence (NES) or a vector without any localization signal. We tested guide RNA targeting the mCherry reporter gene or endogenous genes , respectively, and found that editor fused to the NES showed comparable or highest efficiencies  mutation, which we identified in the DMD gene on chromosome X of a patient with progressive myasthenia, results in the loss of dystrophin in multiple muscle tissues. To explore the therapeutic effect of ceRBE at this disease site, we fused the human exon 30 coding sequence (CDS) containing the Q1392X mutation with mCherry via T2A (self‐cleaving peptide) sequence to overexpress DMDQ1392X RNA in HEK293T cells  is the second most common hereditary muscular disease, because of the deficiency of dystrophin (DMD), affecting an estimated 1 in 3500–5000 male newborns.24 TheE488Q protein and gRNA with the tenth mismatch nucleotide were packaged into single AAV9 particle. The right tibialis anterior (TA) of 8‐week‐old male DMDQ1392X mice was injected with 5 × 1011 vg of AAV9 viral vehicles, while the left TA of the same mice were injected with saline as a control . In vitro, EGFP or BFP fluorescence was also co‐expressed with the editing system to indicate successful transfection and expression of the vector in host cells. We synthesized different spacers as oligos and cloned them downstream of the U6 promoter to express different gRNA configurations in cells.Coding sequence of different small Cas proteins or EcCas6e H20 mutants were human‐codon‐optimized and flanked with SV40 NLS (CCTAAGAAGAAGCGGAAGGTG) or HIV NES (CTGCCTCCACTTGAAAGAC TGACACTG). And then it was fused to the ADAR protein, the deaminase in the RESCUE‐S editor, or hADAR2ddFor fluorescent reporter system, in addition to plasmid of the base editing system mentioned above, an mCherry  reporter system containing an early stop codon TAG mutated from TGG codon (W) at W63 or W98 or W148 in its mCherry coding sequence also need to be co‐transformed.Q1392X were explored in vitro, reporter vectors were constructed using mCherry and ATG‐deleted human exon 30 sequences carrying the Q1392X (c.4174C>T) mutation. mCherry fluorescence indicated successful transfection and expression of the reporter vector in host cells.When DMDAll primers for PCR, sequence of proteins and gRNAs used in this study are provided in Tables HEK293T, a mammalian cell line, was used in the study. It was incubated at 37°C under 5% CO2 in a humidified incubator. Medium consisted of DMEM containing 1% penicillin/streptomycin, 10% fetal bovine serum, and 1% non‐essential amino acids. For fluorescence detection, HEK293T was passaged at a ratio of 1:3 to 12‐well plates. After 16 h, 1 µg plasmid expressing base editor and 1 µg fluorescent reporter plasmid were co‐transfected with polyethylenimine (PEI) using the standard protocol. 48 h after transfection, cells were analyzed by Beckman cytoFLEX. FlowJo X (v.10.0.7) were used for analyze Flow cytometry results.For endogenous sites, HEK293T was passaged at a ratio of 1:3 to 6‐well plates. After 16 h, 3 µg plasmid expressing base editor was transfected into cells with polyethylenimine (PEI) using the standard protocol. Cells were sorted by BD FACSAria III at 48 h after transfection.Q1392X, HEK293T was passaged at a ratio of 1:3 to 6‐well plates. After 16 h, 1.5 µg CRISPR targeting plasmids and 1.5 µg reporter were co‐transfected with polyethylenimine (PEI) using the standard protocol. Cells were sorted by BD FACSAria III at 48 h after transfection.For gRNA screening of DMDH20A and EcCas6eH20L were plated on a 96‐well plate at 5000 cells per well and were treated with or without Doxorubicin (Dox) (1 µg ml−1) for 0, 24, 48, 72, 96, or 120 h. Then, 10 µL of freshly prepared MTT  was added to each well. After 3 h incubated with MTT, 100 µL of dissolved formazan liquid  was added into 96‐well plate for 4 h at 37°C. Absorbance was measured at 570 nm by a microplate reader (Bio TeK cytation).Briefly, single‐cell clones with mCherry, EcCas6e, EcCas6e to quantify base conversion rate. Deep sequencing libraries were sequenced with 150 paired‐end reads on an Illumina Hiseq instrument. FASTQ format data were analyzed using the Cutadapt (v.2.8) according to assigned barcode sequences.To analyze base conversion rate of different base editors, transfected positive cells were sorted 48 h after transfection for RNA extraction at. According to the manufacturer protocol, total RNA of sorted cells or isolated tissues were isolated and converted to cDNA using the reverse transcription kit . Targeted editing sites were amplified using Phanta Max Super‐Fidelity DNA Polymerase  for Sanger sequencing or deep sequencing. Sanger sequencing results were analyzed using EditR 1.0.1027 to All primers for PCR used in this study are provided in Table  For HEK293T, SNPs filtering was done using the database downloaded from NCBI, 1000 Genomes Project  and the University of Washington Exome Sequencing Project (https://evs.gs.washington.edu/EVS/). For in vivo, the mouse mm10 genome and dbSNP of ensemble version 104 (https://www.ensembl.org/) were used to calculate and filter SNVs respectively.RNA‐seq reads were trimmed and edit sites were identified as described previously28 ForQ1392X mice were generated using the CRISPR‐Cas9 system as in reference. Mouse Dmd exon 30 was deleted by CRISPR‐Cas9 guided by two sgRNAs flanking exon 30  muscle was injected with 50 µL of AAV9 (5 × 1011 vg) viral vehicles, while the left TA of the same mice were injected with same volume saline solution as a control , and applied iodixanol density gradient centrifugation for purification. For intramuscular injection, 8‐week‐old male DMDl Figure .Isolated tissues were homogenized with RIPA buffer supplemented with protease inhibitor cocktail. Adjust lysate supernatants to an identical concentration using H2O, after quantifying it with Pierce BCA protein assay kit .Q1392X mice, equal amounts of samples were mixed with in NuPAGE LDS sample buffer  and 10% β‐mercaptoethanol and then were boiled at 70°C for 10 min. 10 µg total protein per lane was loaded into 3 to 8% tris‐acetate gel  and electrophoresed for 1 h at 200 V. Protein was transferred to a PVDF membrane under wet condition at 350 mA for 3.5 h. The PVDF membrane was incubated with primary antibody labeling specific protein after blocking in 5% non‐fat milk in TBST buffer. The membrane was further incubated with HRP conjugated secondary antibody specific to the IgG of the species of primary antibody against dystrophin  and vinculin , after washing three times with TBST. The target proteins were visualized with Chemiluminescent substrates . The gray values were quantified by using ImageJ.For DMD All images were visualized under Nikon C2. The amount of dystrophin positive muscle fibers is represented as a percentage of total spectrin positive muscle fibers.The mice were anesthetized and perfused with PBS solution and subsequent 4% paraformaldehyde (PFA) solution. The TA muscles of the mice were harvested and fixed in 4% PFA. After 8 h, the tissues were washed and dehydrated with PBS and 30% sucrose, respectively. Subsequent cryosection and staining of TA muscle tissue were performed as in reference.29 Allp > 0.05), * (p < 0.05), ** (p<0.01), *** (p<0.001) and **** (p<0.0001), compared with control. GraphPad Prism v8.0 software was used for statistical analysis.All data were shown as means ± standard deviation (SD). Unless otherwise mentioned, n = 3 independent experiments for in vitro and in vivo experiments. Tukey's multiple comparisons test and two‐tailed paired Student's t‐test were used to calculate significance levels. The significance levels are ns (Y.Z., H.Y., X.W., and R.Z. disclosed a patent applications related to this work. H.Y. is the founder of HuidaGene Therapeutics Co., Ltd. The remaining authors declare no competing interests.Q1392X exploration. Z.F. and H.D. assisted with plasmids construction and cell experiments. J.L. and XQ.W. assisted with in vivo exploration. Y.Z. and Y.L. conducted bioinformatics analysis. Z.W. and L.S. assisted in experimental discussion. X.W. and R.Z. analyzed the data and organized figures. X.W., D.Y., R.Z., and Y.Z. wrote the manuscript with help from by all authors.X.W., R.Z., H.Y., and Y.Z. jointly conceived the project. H.Y. and Y.Z. supervised the whole project. X.W., R.Z., D.Y., and G.L. designed and conducted experiments. X.W. and R.Z. designed vectors, performing in vitro experiments. G.L. designed and completed DMDSupporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.


EIF2AK2, APOL6, and miR-4477b seed regions. These biomarkers may alter the miRNA regulation of 133 PD-related genes. All these analyses reveal the potential mechanisms and regulations of RNA editing in PD pathogenesis.Parkinson’s disease (PD) is characterized by dopaminergic neurodegeneration and an abnormal accumulation of α-synuclein aggregates. A number of genetic factors have been shown to increase the risk of PD. Exploring the underlying molecular mechanisms that mediate PD’s transcriptomic diversity can help us understand neurodegenerative pathogenesis. In this study, we identified 9897 A-to-I RNA editing events associated with 6286 genes across 372 PD patients. Of them, 72 RNA editing events altered miRNA binding sites and this may directly affect miRNA regulations of their host genes. However, RNA editing effects on the miRNA regulation of genes are more complex. They can (1) abolish existing miRNA binding sites, which allows miRNAs to regulate other genes; (2) create new miRNA binding sites that may sequester miRNAs from regulating other genes; or (3) occur in the miRNA seed regions and change their targets. The first two processes are also referred to as miRNA competitive binding. In our study, we found 8 RNA editing events that may alter the expression of 1146 other genes via miRNA competition. We also found one RNA editing event that modified a miRNA seed region, which was predicted to disturb the regulation of four genes. Considering the PD-related functions of the affected genes, 25 A-to-I RNA editing biomarkers for PD are proposed, including the 3 editing events in the  AGO2), is abnormally expressed in PD patients [EIF2AK2) regulates α-synuclein by directly phosphorylating the Ser129 residue, linking it to neurodegenerative disorders such as PD [Parkinson’s disease (PD) is the second most common neurodegenerative disorder ,2. It ispatients . The infch as PD ,14.EEF1A in the PD-affected brain [MCL1 [AIMP2 [Aside from α-synuclein pathology, the selective degeneration of dopaminergic neurons also modulates PD. A recent study has reported a decline of ed brain . This gein [MCL1 ,17 and A1 [AIMP2 , both ofmiR-10a-5p, miR-153, and mR-409-3p, can be detected in the bloodstream and can serve as diagnostic biomarkers of PD [There is increasing evidence of blood biomarkers in PD, including circulating the serum neurofilament light chain , small nrs of PD . Alteratrs of PD ,26 for tADAR) [GluA2 is correlated with synapse loss, neurodegeneration, and behavior impairments in Alzheimer’s disease [A-to-I RNA editing is an important transcriptional modification carried out by adenosine deaminases acting on RNA (ADAR) . This foADAR) . Previou disease . In brai disease . Given t disease ,31,32 an disease ,34, it iHere, we developed a bioinformatics pipeline to identify A-to-I RNA editing biomarkers and uncover their potential mechanisms and transcriptomic impact in PD. The pipeline is outlined in To study the effects of RNA editing on gene expression, whole-blood RNAseq data of 372 PD patients and 169 healthy controls were downloaded from the PPMI cohort ,26. Corrn < 3) or low editing frequencies (<0.1) were filtered out. On average, there were 15,104 editing events per individual. The number of editing events was not associated with the disease state (p > 0.05). Furthermore, informative A-to-I RNA editing events that were found in more than 50 PD patients and had a standard deviation of higher than 0.05 were kept in our analysis. Their distributions across different genes, regions, and repeats were analyzed by ANNOVAR (Version: 2020-06-07) [The sequencing reads from RNAseq data were first aligned to hg38 reference genome (GENCODE v36) by STAR (v2.7.9a) . Then, R0-06-07) .Using the aligned reads as described in 2.2, gene expression was quantified  by the RSEM software (Version: 1.3.1) . Low-abup < 0.05). Age and sex were considered as covariates in the QTL analysis, which improves the identification sensitivity and reduces non-genetic phenotypic variance. For these gene-associated RNA editing events, their locations in genomic regions were analyzed. In total, 1203 RNA editing events were located in the 3′-UTRs of pre-mRNAs or lncRNAs and one RNA editing event was in the miRNA seed region. These events may alter miRNA binding and regulation of genes, especially for PD-related genes.To study the associations between A-to-I RNA editing events and genes, two different analysis methods were used: quantitative traits locus (QTL) with MatrixeQTL    and miRaAs previously mentioned, RNA editing events in miRNA-binding regions may not only affect the edited genes but also indirectly alter other genes due to miRNA competition. To investigate this, TargetScan and miRanda were also used to detect miRNA-binding regions in genes competing with the edited genes. To clarify, a competing gene is a gene that shares miRNA binding sites with the ones altered in the RNA-edited gene. This includes both lost (abolished) and gained (acquired) binding sites from the A-to-I editing. Similarly, the functional roles of the competing gene-associated RNA editing events were annotated using starBase and pathway enrichment analysis.Last but not least, RNA editing events can also be located in the seed regions of miRNAs (2–8 nt). The edited seed region can bind to and regulate a different set of genes than the intended genes. Similar procedures were applied to study the RNA editing events in miRNA seed regions, including the identification of downstream RNAs regulated by the edited miRNA and the analysis of their enriched pathways.p = 5.92 × 10−3), which is consistent with the decreased editing levels found in the brains of PD patients [Our RNA editing detection pipeline identifies 25,799 informative RNA editing events . Most ofpatients . These ap < 0.05) were performed. In total, there are 9897 RNA editing events associated with 6286 genes  and Pearson correlation , as shown in miR-3622a-3p and miR-3622b-3p, which may increase the degradation of this gene and result in the observed decrease in gene expression . The associated EIF2AK2 gene is known for its function in promoting PD progression via the phosphorylation of α-synuclein protein [p = 0.01) and in more severe PD samples (p = 0.03). The Chr2:37104057 RNA editing event is significantly less frequent in PD samples compared to healthy controls (p = 0.02) and is negatively associated with tau protein levels . Thus, this RNA editing event may be the reason for the observed downregulation of EIF2AK2 and may be considered a potential biomarker for PD.Interestingly, there is a noteworthy RNA editing event in the 3′-UTR of pression C. In fac protein . It is aEIF2AK2 encodes for a kinase that binds to dsRNA (RNA binding protein) and plays a major role in the regulation of gene transcription [EIF2AK2–RNA interactions from StarBase [EIF2AK2 targets and 4129 potential non-EIF2AK2 targets. All these genes are sufficiently expressed in blood with mean expressions of more than one TPM. Of 2158 potential EIF2AK2 targets, 31.37% have associations with both this editing event and EIF2AK2 . This suggests that EIF2AK2 editing may regulate these genes via its RNA binding functions. Taking a closer look at the experimentally validated EIF2AK2–RNA interactions from starBase, there are 16 protein-coding RNAs significantly correlated to the editing event and EIF2AK2  and in more severe PD patients (p = 0.02)  and its negative correlations with the editing event  further support their relationships. Therefore, the decrease of the RNA editing event (Chr2:37104057) may upregulate EIF2AK2 [Among the 16 affected genes, at least 4 genes  are kno = 0.02) F. Its co EIF2AK2 , which tRNA editing events in one gene may indirectly affect other genes. Editing events that create new miRNA binding sites may sequester miRNAs from regulating other RNAs. Similarly, editing events that abolish miRNA binding sites may release the miRNAs to regulate other RNAs. The process is also known as editing-mediated miRNA competition. In our study, eight RNA editing events that can alter miRNA competitions between their host genes and 1146 other genes were identified . These aAPOL6. It is located in the 3′-UTR and results in the loss of miR-19 and miR-4659 binding sites, as shown in APOL6 . This releases the two miRNAs from APOL6, allowing them to regulate other genes and potentially decrease the transcription of 47 genes, including EEF1A1 . One PD-related gene competing with the edited gene is EEF1A1. It is known for its pro-survival function in the protection of dopaminergic neurons [EEF1A1 translation factor are responsible for the synthesis of proteins, especially PD-related peptides. The dysregulation of these PD-related genes suggests that this editing event at Chr22:35661178 is a potential pathogenic biomarker for PD (p = 0.04) and tau protein levels . The analyses in this section provide one explanation for the trans-associations of A-to-I RNA editing events and genes.The editing event of most interest is the one in the Chr22:35661178 position of  process ,68 and i neurons . The eigr for PD F. It is miR-4477b (Chr9:63819627). This change may dysregulate four genes  can dramatically alter the targeted genes of the miRNAs. In total, we discovered one RNA editing event in the seed region of ur genes , includies . In addition, RNA editing in miR-4477b is positively correlated with the levels of amyloid β-protein  and α-synuclein . This suggests that the RNA editing event at Chr9:63819627 leads to the loss of miRNA regulation on AGO2 related to PD.This RNA editing event alters the nucleotide from A to I in the fourth position of the miRNA seed region and results in the loss of binding on three sites in AGO2 B. The loynuclein . The RNAAGO2 interacts with 168 protein-coding RNAs, according to starBase. Of them, 46 RNAs are significantly associated with the editing frequency of miR-4477b and the expression of AGO2 , also known as cis-regulatory effects. They can also regulate the expression of distant genes (dist > 1 × 106), which are considered trans-regulatory effects. Most of the associations were found to be trans-regulatory ones, in which the RNA editing event was significantly associated with a distal gene  ,73. In tp < 0.05). Of them, 620,616 editing–gene associations were still significantly correlated after Benjamini–Hochberg corrections (p.adjust < 0.05). To understand the mechanisms underlying these associations, two widely used miRNA-binding prediction tools, TargetScan and miRanda, were applied to identify the effects of RNA editing on the alterations of miRNA binding. The altered miRNA–RNA interactions were only kept when they were identified by both tools. All these criteria ensured the accuracy of the editing–gene associations and the miRNA–RNA interactions.To increase the reliability of our study, both QTL and Pearson correlation tests were used to identify the associations between A-to-I RNA editing events and genes. The associations were only determined when they all passed the statistical significance thresholds from the two tests. Among the 627,064 significant pairs identified by QTL analysis, 620,840 also passed Pearson correlation tests (ADAR) and genetic variants [ADAR activities, A-to-I RNA editing events, miRNA regulations, and gene expressions can explain the regulatory processes in neurodegenerative pathogenesis.Our study identified potential RNA editing biomarkers for PD and elucidated their effects on downstream genes and pathways. We presented three editing events associated with dysregulated PD-related genes. These A-to-I RNA editing events may also be affected by other factors, such as the main editing enzyme (variants  (Figure Additional research can be conducted to further understand RNA editing effects on PD pathogenesis. For example, multiple RNA editing events can affect multiple miRNA–RNA regulations and produce complex outcomes on PD-related genes . A netwoEIF2AK2, APOL6, and miR-4477b seed regions were discussed in detail. Their effects on the downstream genes and pathways related to PD were revealed. Our work helps researchers understand the mechanisms of the abnormal expressions of PD-related genes and the impact of A-to-I editing in neurodegeneration.In sum, we systematically analyzed the effect of A-to-I RNA editing events on the miRNA regulations of PD-related genes. In total, we discovered 25 A-to-I RNA editing biomarkers for PD. These biomarkers may alter the miRNA regulation of 133 PD-related genes. Three RNA editing events in the


Insects harbor diverse assemblages of bacterial and fungal symbionts, which play crucial roles in host life history. Insects and their various symbionts represent a good model for studying host–microbe interactions. Phylosymbiosis is used to describe an eco-evolutionary pattern, providing a new cross-system trend in the research of host-associated microbiota. The phylosymbiosis pattern is characterized by a significant positive correlation between the host phylogeny and microbial community dissimilarities. Although host–symbiont interactions have been demonstrated in many insect groups, our knowledge of the prevalence and mechanisms of phylosymbiosis in insects is still limited. Here, we provide an order-by-order summary of the phylosymbiosis patterns in insects, including Blattodea, Coleoptera, Diptera, Hemiptera, Hymenoptera, and Lepidoptera. Then, we highlight the potential contributions of stochastic effects, evolutionary processes, and ecological filtering in shaping phylosymbiotic microbiota. Phylosymbiosis in insects can arise from a combination of stochastic and deterministic mechanisms, such as the dispersal limitations of microbes, codiversification between symbionts and hosts, and the filtering of phylogenetically conserved host traits . Host–microbe symbioses play a crucial role in the ecological and evolutionary history of animals ,2. RecenPhylosymbiosis is defined as “microbial community relationship parallels the host phylogeny”, in which “phylo” refers to host lineage and “symbiosis” refers to the coexistence of hosts and microbes  6,7]. I,7. I6,7]Nasonia under rearing conditions . . 101]. DEcological drift leads to random variation in the relative abundance of species within the microbial community over time . MicrobeBuchnera aphidicola has highly coadapted to and evolved with aphids for millions of years [Ishikawaella capsulate in plataspid stinkbugs [Rosenkranzia clausaccus in acanthosomatid stinkbugs [Phylosymbiosis can arise from long-term and stable associations between microbes and hosts, such as coevolution and cospeciation. Here, we use “coevolution” in the narrow sense, which emphasizes the reciprocity and simultaneity of evolutionary changes in interacting species . Cospeciof years ,117,118.tinkbugs  and Rosetinkbugs .Lactobacillus Firm-5 and the host bees was observed, which suggested host–microbe codiversification [Codiversification represents another evolutionary process that underlies phylosymbiosis B. It occfication . Other afication  and sharfication , can alsBuchnera is located in specialized bacteriocytes and maintained within aphid generations via direct maternal transmission [Nephotettix cincticeps, the facultative symbiont Rickettsia is vertically transmitted to offspring paternally via an intrasperm passage as well as maternally via an ovarial passage [Acromyrmex leaf-cutting ants [Apis mellifera [Considering the low probability of the entirety of a microbial community being transmitted from mother to offspring with high fidelity, it seems unlikely that all microbiota members are involved in the aforementioned evolutionary processes driving phylosymbiosis. Early-arriving species can affect the ability of late-arriving species to establish themselves during community assembly, which is referred to as priority effects . The impsmission . In the  passage . Additio passage . For socing ants  and the ellifera , social Moran and Sloan  proposedNumerous studies have highlighted the importance of the host immune system in regulating microbial community composition ,141,142.Gilliamella in honey bees induced higher prostaglandin (PG) production than the native strain, which increased the expression of genes in the IMD and Toll immune pathways [Gilliamella.An insect’s innate immune system not only defends against pathogens but also plays an important role in maintaining host–microbe symbiosis ,152,153.pathways . These iThere is increasing evidence that diet plays a pivotal role in shaping the microbiota structures of animals ,158,159.Host plants are one of the major ecological factors shaping the bacterial communities of insect herbivores ,162,163.Another candidate ecological filter underlying host species-specific microbiota is the host’s physiological structure, such as the gut  and provThe selective filtering of microbes in the gut environment can explain major variations in phylosymbiotic gut microbial communities in humans . CompareWhile host–symbiont interactions have been documented across many insect groups, we still have a poor understanding of the prevalence of phylosymbiosis in insects. Phylosymbiotic investigations should be performed on a greater variety of insects to sufficiently disentangle the mechanisms underlying this pattern. In addition to bacterial and fungal communities, phylosymbiosis studies at the insect–virome level ,171 willTo date, most studies have focused on the impact of evolutionary processes on driving phylosymbiotic microbiota. Quantifying the contribution of ecological filtering factors in phylosymbiosis will greatly improve our understanding of the mechanisms behind these patterns. Host-specific biological characteristics and environmental factors should be identified and evaluated quantitatively in the future. It is more likely that a combination of multiple mechanisms rather than a single evolutionary or ecological process is involved in the development of phylosymbiosis; therefore, candidate mechanisms, including stochastic effects, evolutionary processes, and ecological filtering, need to be tested in a diversity of symbiosis systems in both evolutionary and ecological contexts.


Genome-wide measurements of RNA structure can be obtained using reagents that react with unpaired bases, leading to adducts that can be identified by mutational profiling on next-generation sequencing machines. One drawback of these experiments is that short sequencing reads can rarely be mapped to specific transcript isoforms. Consequently, information is acquired as a population average in regions that are shared between transcripts, thus blurring the underlying structural landscape. Here, we present nanopore dimethylsulfate mutational profiling (Nano-DMS-MaP)—a method that exploits long-read sequencing to provide isoform-resolved structural information of highly similar RNA molecules. We demonstrate the value of Nano-DMS-MaP by resolving the complex structural landscape of human immunodeficiency virus-1 transcripts in infected cells. We show that unspliced and spliced transcripts have distinct structures at the packaging site within the common 5′ untranslated region, likely explaining why spliced viral RNAs are excluded from viral particles. Thus, Nano-DMS-MaP is a straightforward method to resolve biologically important transcript-specific RNA structures that were previously hidden in short-read ensemble analyses. Nano-DMS-MaP combines the power of DMS mutational profiling and long-read nanopore sequencing to resolve structural differences among RNA isoforms, revealing the structural landscape of HIV-1 transcripts in cells. Among the methods for interrogating RNA folding, chemical probing stands out for its ease of use and ability to determine RNA structure in situ5. During chemical probing, RNA is treated with reagents that react preferentially with single-stranded regions of RNA. One such reagent, dimethylsulfate (DMS), methylates the N3 position of cytosines and the N1 position of adenines at the Watson–Crick face of unpaired residues, giving rise to information that can be used to perform high-accuracy RNA structure predictions10. This small cell permeable chemical is used widely for the in situ or in vitro structural analysis of RNA or RNA–protein complexes14. In classical experiments, the modified nucleotides, 1-methyladenosine (m1A) and 3-methylcytosine (m3C), stall reverse transcription causing reverse transcriptase (RT) drop off to form truncated complementary DNAs (cDNAs) that can be analyzed by gel or capillary electrophoresis5. In DMS sequencing (DMS-seq), truncated cDNAs are subjected to next-generation sequencing to perform genome-wide measurements of RNA structure16. Alternatively, DMS mutational profiling sequencing (DMS-MaP) uses modified buffer conditions to perform error-prone reverse transcription of DMS-modified nucleotides18. DMS-MaP therefore allows for straightforward measurements of RNA structure by counting mutations.RNA structure is a main determinant of RNA function17 but also has its drawbacks. Most importantly, typical RT conditions produce short cDNA molecules ideal for sequencing on Illumina sequencing machines20. The resulting reads, however, rarely span whole transcript isoforms like those generated by alternative transcription start and termination sites, or by alternative splicing. Therefore, DMS-MaP is not well suited to identify structural differences in transcript isoforms  Fig. . We used24. Signal-to-noise ratio is therefore limited by the inherent error rate of the sequencing platform and by RT and polymerase chain reaction (PCR) errors. DMS-MaP experiments are commonly designed to induce mutation frequencies of 1–2% at A and C residues. Such mutational signatures can be detected by short-read Illumina sequencing where most nucleotides have a Phred quality score (Q-score) above 30 (Q30), which is equivalent to 99.9% accuracy. While nanopore sequencing devices can perform long-read sequencing, they have a magnitude higher error rate than Illumina sequencing machines, with a substantial proportion of reads exhibiting low accuracies25. Recent improvements to Nanopore sequencing chemistry and basecalling algorithms, however, have raised modal accuracy to Q20 (99% accuracy)26.Sequencing accuracy is critical for DMS-MaP experiments because this method relies on the reverse transcription of DMS adducts into mutations that must be distinguished from site-specific errors by normalization with an unmodified control samplegag gene, and folds into a series of stem-loop structures that regulate the HIV-1 life cycle27. For reverse transcription, we used MarathonRT because it was reported to generate long cDNAs in the presence of RNA modifications29. Still, we found an inverse relationship between DMS concentration and the amount and length of cDNAs recovered  portion of the unspliced (US) HIV-1 RNA from infected cells. This region comprises the highly structured 5′ UTR and the beginning of the viral We next tested whether nanopore sequencing has a sufficient accuracy to enable high quality structure determination, especially at lower DMS concentrations that are expected to have reduced signal-to-noise ratio. We performed a nanopore sequencing run using Kit 12 chemistry and evaluated platform- and DMS-induced mutation rates on the US HIV-1 RNA . The seq14. For this comparison, we used the receiver operator characteristic area under the curve (ROC-AUC) score—a summary statistic to evaluate the correlation of DMS reactivity with strandedness . A score of 0.5 signifies a random association of the two variables, whereas 1 indicates a perfect match. At the 8 mM DMS concentration, ROC-AUC scores reached 0.6, indicating the presence of low-quality structural information. Increasing the concentration of DMS improved the ROC-AUC scores, reaching 0.9 at 85 mM DMS concentration, indicating excellent agreement with the reference structure. By subsampling reads, we observed that ROC-AUC scores saturated at approximately 4,000 reads, indicating that the low signal could not be overcome by increasing read depths  when counting mutations, as well as median per read Q-score filters and per position Q-score filters  and DMS concentrations  , we performed amplification of the genome in two PCR reactions, each spanning 4 kb Fig. . NotablyA comparison of the DMS reactivities across the entire HIV-1 genome showed a slight but consistent trend for increased DMS accessibility in the virions Fig. . The mol35. All viral RNAs share the first 289 nt of the 5′ UTR, including a major packaging signal, known as stem-loop 1 (SL1). SL1 contains a palindromic dimerization initiation sequence (DIS) within its apical loop, and is the primary binding site for the viral structural protein Pr55Gag   and fully spliced (FS) Fig. . During Gag Fig. 36,37. SLL2) Fig. . Neverthgag open reading frame (ORF). For the PS RNAs we used an RT primer complementary to a region in the D4–A7 intron  across two independent experiments . In the presence of DMS, we observed a progressive decrease in the proportion of reads mapping to longer transcripts with increasing DMS concentration. In particular, the 1.4 kb Vif2 and 897 bp Vpr3 transcripts in the PS sample were decreased compared with the shorter Env-expressing transcripts   of chemically modified transcripts53. An important caveat is that we used lower DMS concentrations than typically used in short-read DMS-MaP experiments. Although the accuracy of Nano-DMS-MaP structural information was similar at low and high DMS concentrations, higher read depths are generally required for longer molecules  stem-loop and sequences in gag59. The U5–AUG62 and polyA63 structure have both been implicated in 5′ UTR structural switching and the selective packaging of the US RNA63. We also observed increased DMS reactivity changes at position C58 that is linked to transcription start site variation that alters 5′ UTR structure to regulate genome packaging and translation of the US RNA65. We also cannot exclude that the unfolding of SL1 is due to the preferential translation of the spliced viral RNAs themselves. Testing whether SL1 unfolding drives RNA packaging selectivity in cells, and the role of transcription start site variation on 5′ UTR folding and translation are key topics for future studies.By applying our method to the complex splicing landscape of HIV-1 we identified strong and consistent increases in DMS reactivity in the SL1 stem of spliced viral RNAs, which is a structure involved in Pr5566 and 36 µl of 1 mg ml–1 transfection grade linear polyethylenimine , following the manufacturer’s recommendations.HEK 293T cells were obtained from the American Type Culture Collection and maintained in high glucose Dulbecco’s modified Eagle’s medium with GlutaMAX  supplemented with 10% (v/v) iron supplemented calf serum (Sigma-Aldrich). Cellular and viral RNA was produced by reverse transfection of 10 million cells with 3 µg of pDRNL43Δenvg and subsequently passed through 0.45 µm filter to remove cellular debris. Purified virus was concentrated by ultracentrifugation at 100,000g through a 20% sucrose cushion (w/v) in Tris-HCl 50 mM pH 7.4, NaCl 100 mM, EDTA 0.5 mM). After centrifugation, the viral pellet was gently resuspended in virus resuspension buffer . Samples were probed by adding a one-tenth volume of DMS diluted to the correct concentration in ethanol directly to cells or viruses. DMS treated samples were incubated for 6 min at 37 °C and quenched with one-tenth volume of β-mercaptoethanol (Sigma-Aldrich). For each sample, equivalent control reactions were performed incubating samples for 6 min at 37 °C in the presence of one-tenth volume ethanol instead of DMS. Probed and control RNA samples were purified by extraction with Tri reagent LS (Sigma-Aldrich), according to the manufacturer’s instructions with the addition of 1 µl of glycoblue (ThermoFisher Scientific) during isopropanol precipitation to enhance recovery of low abundance RNA from the viral samples. Purified RNA was resuspended in RNase-free H2O. Then, 16 µg of cellular RNA and the totality of the viral RNA was treated with 3 µl Turbo DNase (ThermoFisher Scientific), 12 U of RNasin and 5 µl of 10× Turbo DNase buffer in a 50 µl volume for 30 min at 37 °C. Following DNase treatment, RNA was column-purified using NTC buffer and the NucleoSpin Gel and PCR Clean-up kit (Macherey-Nagel), according to the manufacturer’s instructions.At 24 h posttransfection, DMS probing of viral RNA was carried out under native conditions from cells and viruses. Viral particles were collected as 15 ml viral supernatants, which were then clarified by centrifugation for 10 min at 5,00067, hc16 ligase, tetrahymena riboswitch and Vibrio cholerae glycine riboswitch30 were generated by assembly from DNA oligos (IDT) according to the primerize scheme68. The HCV IRES was subcloned from a reporter plasmid kindly provided by N. Caliskan. Fully assembled products were cloned into pJet-1.2 vector (ThermoFisher Scientific) for propagation and confirmed by Sanger sequencing. DNA was then amplified from plasmids with primer T7_fw (AAAGAATTCTAATACGACTCACTATAGG) and the M13_pA_re (TTTTTTTTTTGATTATCATACTCTGATAATCCAGGAAACAGCTATGACCATG) with the exception of HCV IRES, for which primer T7_HCV_fw (AAAGAAGACTTGGGGTAATACGACTCACTATAGGCCAGCCCCCGATTG) was used. DNA amplicons were then purified with 1.2× SPRI bead purification with Mag-Bind TotalPure NGS beads (Omega Biotek). Briefly, the DNA-bead mixture was incubated for 5 min under light agitation and beads were pelleted on a magnetic rack (Invitrogen DYNAL), followed by removal of supernatant and two washes with 100 µl freshly prepared 70% ethanol. Finally, beads were air-dried for 3–5 min (until appearance changed from glossy to rough) and DNA was eluted by addition of 15 µl H2O, followed by 5 min incubation at room temperature.DNA templates of the bacterial RNase P type A2, 10 mM DDT, 1 mM spermidine, 5 mM NTPs, 40 U RNasin (Molox) and homemade T7 RNA polymerase for 3 h at 37 °C, followed by DNase I treatment for 30 min at 37 C and 1.6× SPRI bead purification.For in vitro transcription 500 fmol of DNA were prepared in 40 mM Tris pH 7.5, 18 mM MgCl2  was added before incubation at 37 °C for 30 min. To probe the RNA, 1 µl DMS diluted in ethanol was added at the indicated final concentrations before incubation at 37 °C for 7 min. The reaction was quenched with four volumes of 30% β-mercaptoethanol. RNAs probed at the same concentration were pooled, 0.1 volume of 3 M NaOAc and 3 volumes EtOH were added, and RNA was precipitated at –20 °C overnight. RNA was then pelleted by centrifugation at 16,000g for 30 min, washed twice with 70 % EtOH before resuspension in H2O and normalization to 100 ng µl–1.For probing, 300 ng of the RNA was prepared in an 8 µl reaction mix in 0.5 mM EDTA, 30 mM HEPES pH 7.5, 300 mM NaCl and heated to 95 °C for 1 min, followed by placing on ice. To facilitate folding of the RNA 1 µl of 50 mM MgCl29. pET-6×His-SUMO-MarathonRT encoding MarathonRT was a gift from A. Pyle , and the enzyme was purified according to Zhao et al.29. US HIV-1 RNA was reverse transcribed using primer RT-US (GATGGTTGTAGCTGTCCCAGTATTTGTC), PS RNA using primer RT-PS (CTCCTTCACTCTCATTGCCACTGTC) and FS using primer RT-FS (CTCGGGGTTGGGAGGTGGGTTGC). The full-length genome was reverse transcribed with RT-FL (GAAGCACTCAAGGCAAGC). Human 18S rRNA was reverse transcribed with primer RT-h18S (TAATGATCCTTCCGCAGGTTCACCTAC), and the in vitro transcribed RNAs were reverse transcribed with primer M13_pA_re.Reverse transcription was performed on 1 µg of cellular RNA, the totality of viral RNA or 300 ng of purified in vitro transcribed RNA using MarathonRT2O and denatured for 5 min at 65 °C. Samples were placed on ice for 2 min and reverse transcription was initiated by adding 40 U of MarathonRT in 50 mM Tris-HCl pH 8.3, 200 mM KCl, 20% glycerol (v/v), 0.4 mM MnCl2, 4 U of RNasin in 20 µl total volume. Samples were incubated for 4–8 h at 55 °C for primer RT-US or 42 °C for primers RT-PS, RT-FS and full-length. No reverse transcriptase controls were carried out as above, with the omission of the MarathonRT enzyme.RNA was first mixed with 0.5 mM dNTPs, 50 nM of primer brought to 9 µl with RNase-free H2O. Viral RNA species were differentially amplified using primer pairs PCR-HIV_Fw (GGTCTCTCTGGTTAGACCAGATCTGAG) and PCR-US_Rv (GATGGTTGTAGCTGTCCCAGTATTTGTC) for US RNA, PCR-HIV_Fw and PCR-S_Rv (TTCGTCGCTGTCTCCGCTTC) for PS and FS RNA. PCR-HIV_Fw and PCR-A_Rv (CCCTGTCTCTGCTGGAATTACTTC) or PCR-B Fw (GAAGTAATTCCAGCAGAGACAGGG) and PCR-B-Rv (GAAGCACTCAAGGCAAGCTTTATTG) for the full-length genome. For h18S amplification primers h18S_fw (TACCTGGTTGATCCTGCCAGTAGCATATG) and h18S_re (TAATGATCCTTCCGCAGGTTCACCTAC) were used, whereas for the in vitro transcribed RNAs RNA-specific forward primers . Amplicon quality was checked on 1 % agarose gel poststained in EtBr.RT reactions were diluted one to eight to a total volume of 160 µl with nuclease free H2O, 1 µl end-repaired DNA, 1 µl barcode and 3 µl NEB Blunt/TA Ligase Master Mix for 20 min at room temperature. Ligation was terminated by addition of 1 µl EDTA (SQK-NBD112-96), samples were pooled and purified with 0.4× Ampure XP beads (SQK-NBD112-96), and washed twice with short fragment buffer . After elution of the pooled barcoded DNA in 35 µl H2O, the motor protein was ligated in a 50 µl reaction containing 30 µl barcoded DNA, 10 µl NEBNext Quick Ligation Reaction Buffer (NEB B6058S), 5 µl AMII H (Oxford Nanopore Technologies SQK-NBD112-96) and 5 µl NEB T4 DNA ligase high concentration (NEB T2020M). Following a 20-min incubation at room temperature, the sample was purified with 0.4× Ampure XP beads and washed twice with SFB, taking care to not let the beads dry out between washes or before elution. The library was then sequenced on a R10.4 flow cell  on a Minion Mk1B sequencer (Oxford Nanopore Technologies) using MinKnow acquisition software (Oxford Nanopore Technologies) v.21.11.8.DNA amplicons were purified via SPRI bead purification by addition of 0.7× volumes of beads for US, PS, FS, full-length or 1.2× volumes for IVT and h18S samples as described above. Next, 25–80 ng of DNA of each sample in volume of 5 µl underwent simultaneous dA-tailing and 5′-phosphorylation by addition of 0.7 µl NEBNext End-Repair Buffer and 0.3 µl NEBNext End-Repair enzymes followed by an incubation at room temperature for 5 min and 65 °C for 5 min. Barcodes of kit SQK-NBD112-96 (Oxford Nanopore Technologies) were then ligated in a 6 µl reaction containing 1 µl HData was basecalled with guppy v.6.1.3 with the following parameters: ‘–do_read_splitting –c dna_r10.4._e8.1_sup.cfg –min_qscore 10 –barcode_kits SQK-NBD112-96 –trim_strategy dna –trim_barcodes –trim_adapters’. Virtual gels were generated with a custom python script using the numpy library, with intensity scaled by read length .39), using a general feature file (GFF) generated from previously published data  or custom python scripts. Mutation counting was performed with rfcount (‘-mf mask_primers.csv –count-mutations –eq 10 –q 22 –mm –nd -ni’) followed by reactivity normalization with rf-norm . The signal-to-noise ratio was calculated per position as the mutation rate in DMS-probed sample divided by the mutation rate in the control as reported in the rfcount output files.Mutational Profiling analysis was performed for each isoform separately using RNAFramework v.2.7.2 . The command to perform DMS-guided secondary structure prediction was ‘eternafold predict {bp2seq_file} –evidence –numdatasources 1 –params EternaFold/parameters/EternaFoldParams_PLUS_POTENTIALS.v1’. Structures were then plotted using VARNA v.3-93 (ref. 70).De novo folding of isoform structures with coverage of at least 4,000 reads was performed by converting the reactivities on A and C residues to bp2seq files for input in EternaFold v.1.3.1 (ref. The amplicons from the US RNA sequenced previously by nanopore were prepared for Illumina sequencing as follows: The addition of the transposon sequence HF in 5′ and HR in 3′ of the amplicons was performed by five cycles of amplification using the primers PCR-HIV-HF_Fw (TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGggtctctctggttagacc) and PCR-US-HR_Rv (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGgatggttgtagctgtcccag) using the Q5 DNA Polymerase (NEB). DNA amplicons were purified via SPRI bead as described above using one volume of beads. Purified products (25 ng) were used in the final sequencing library preparation with Nextera DNA Flex Library Prep (Illumina) and Nextera DNA CD Indexes , according to the manufacturer’s instructions. Paired-end PE150 sequencing was carried out on an Illumina Novaseq instrument (Novogene). Fastq files were preprocessed with cutadapt v.4.1 with the following parameters ‘-a CTGTCTCTTATA -A CTGTCTCTTATA–nextseq-trim 25–minimum-length 25–max-n 0.’ The trimmed files were then aligned using bowtie v.2 with parameters ‘-D 20 -R 3 -N 1 -L 15 -i S,1,0.50,’ followed by the same analytical pipeline used for the nanopore data.DMS reactivity data shown are the mean of two independent biological replicates of Nano-DMS-MaP experiments on A and C residues unless stated otherwise. RT-PCRs optimization experiments were performed at least twice.Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41592-023-01862-7.Supplementary InformationSupplementary Figs. 1–5.Reporting SummaryPeer Review FileSupplementary TableTable 1. Mean mutation rate for different rfcount filter settings. Table 2. Signal-to-noise ratios with different rfcount setting. Table 3. Additional primer sequences for in vitro transcribed samples. Table 4. HIV-1 RNA isoform information.Supplementary Data 1DMS reactivities as csv files for all experiments and isoforms. –1 represents no information at position.Supplementary Data 2Eternafold de novo RNA structure predictions guided by Nano-DMS-MaP reactivities on A and C or A, C and U residues.


ACTB, GAPDH), ribosomal genes , and long non-coding RNAs . Our results show that RINs from diseased vascular tissue are low (2–4). If the isolation of primary cells is intended, as in our SVB, a cryoprotective solution is a better option for tissue preservation than RNAlater. Because RNA degradation proceeds randomly, controls with similar RINs are recommended. Otherwise, the data might convey differences in RNA degradation rather than the expressions of the corresponding genes. Moreover, since the 18S and 28S genes in the diseased vascular samples were degraded and corresponded with the low RINs, we believe that DV200, which represents the total RNA’s disintegration state, is a better decision-making aid in choosing samples for omics analyses.Proper biobanking is essential for obtaining reliable data, particularly for next-generation sequencing approaches. Diseased vascular tissues, having extended atherosclerotic pathologies, represent a particular challenge due to low RNA quality. In order to address this issue, we isolated RNA from vascular samples collected in our Swiss Vascular Biobank (SVB); these included abdominal aortic aneurysm (AAA), peripheral arterial disease (PAD), healthy aorta (HA), and muscle samples. We used different methods, investigated various admission solutions, determined RNA integrity numbers (RINs), and performed expression analyses of housekeeping genes ( Human tissue biobanks constitute an important source for clinical and translational research which seeks to understand the pathophysiological mechanisms behind particular diseases in order to be able to discover suitable biomarkers and optimal therapeutic strategies ,2. The cCardiovascular disorders (CVDs) are the leading cause of death worldwide . In the The most frequently used method to assess the quality of RNA currently acknowledged is the determination of the RIN (RNA integrity number). Typically, an RIN score of 6–7 or higher is recommended for sequencing analyses to achieve reliable data ,13. HoweIn order to address these important issues, we selected various vascular tissue samples from our Swiss Vascular Biobank (SVB), isolated the RNA using different methods, determined the RNA quality, and performed real-time polymerase chain reaction (RT-PCR) analyses involving various genes ). In addition, we compared the effects of different preserving solutions on the RNA integrity, incubating the tissue at 4 °C or room temperature (RT) for up to 7 days prior to extracting the RNA.n = 50), tissue affected by peripheral arterial disease , muscle tissue from the sartorius muscle obtained from PAD patients following open surgical repair , and non-aneurysmal healthy infrarenal aortic samples  obtained during kidney transplantation and provided by the Department of Visceral Surgery (USZ/UZH). All tissue samples were stored at −80 °C within five minutes of excision and kept frozen until the RNA extraction. All patients whose vascular tissue samples were collected in the SVB gave appropriate written informed consent. In emergency cases, the tissue samples were collected temporarily and the written consent was obtained after the surgical intervention. In cases of rejection, the tissue was disposed of. The local ethics committee  approved the tissue sample collection and analysis procedure. In addition, as a positive control for RNA quality, human endothelial cells  were used.Vascular tissue samples were obtained from patients who underwent open surgical interventions in our Department of Vascular Surgery (USZ/UZH). Samples are continuously collected in our Swiss Vascular Biobank (SVB). The following tissues were included in our study: infrarenal abdominal aortic aneurysm tissue  phase containing the RNA was carefully transferred into a new tube, 500 µL isopropanol was added, and the contents were mixed by inverting the tube several times to precipitate the RNA. Following incubation on ice and further centrifugation, the supernatant was discarded and the RNA was resuspended in 75% ethanol to improve RNA solubility. It was then centrifuged and the supernatant was again discarded. The RNA pellet was air-dried, resuspended in 50 µL RNase-free water, and stored at −80 °C until further use. The RNA concentration was determined using a NanoDrop Lite Plus Spectrophotometer . Because the TRIZOL solution and a motorised homogeniser provided the highest RNA concentration and quality  was used. The RNA integrity numbers (RINs) and DV200 index values (percentage of fragments of >200 nucleotides) of each specimen were determined using a standard Agilent RNA ScreenTape Assay or Agilent High Sensitivity RNA ScreenTape Assay, depending on the RNA concentration and in accordance with the manufacturer’s protocols. All measurements were performed in duplicates, and the experiments were repeated in cases of high variability or discrepancy.In order to compare the stability and quality of the RNA under different conditions, three protective solutions were used: (1) an optimised cryoprotective solution (CpS) composed of cell culture medium , 1.8 M dimethyl sulfoxide (DMSO), 0.1 M glucose , 20 mM 2-(4-(2-Hydroxyethyl)-1-piperazinyl)-ethane sulfonic acid (HEPES), and, optionally, 1% fetal bovine serum (FBS) (Thermo Fisher Scientific) ,17,18,19In order to identify the interrelationships between RNA quality, the various protective solutions, and gene expression at the mRNA level, quantitative real-time PCR (qRT-PCR) analyses were performed. First, cDNA was synthesised using 1 µg RNA and a RevertAid First Strand cDNA Synthesis Kit . Random Hexamer primers were used in order to encompass non-coding RNAs and degraded RNA fragments independent of the state of the poly(A) tail.ACTB) and Glycerinaldehyd-3-phosphat-Dehydrogenase (GAPDH). Furthermore, to evaluate the stability of the ribosomal genes 18S and 28S over time, which is used to calculate the RIN (Agilent), the expression of these genes was also analysed. All primers for the SYBR Green expression analysis were purchased from Qiagen. In addition, the expression of two long non-coding RNAs (lncRNAs), MALAT1 and H19, which play an important role in vascular disorders [PowerUp SYBR Green Master Mix (Thermo Fisher Scientific) was used to determine the expression of the housekeeping genes Beta-actin GAPDH: Hs_GAPDH_1_SG, amplicon length 95 bp (exons 6/7)18S: Hs_RPS18_1_SG, amplicon length 61 bpribosomal Gene 28S: Hs_RPS28_1_SG, amplicon length 77 bpribosomal Gene MALAT1: Hs00273907_s1, amplicon length 117 bpH19: Hs00399294_g1, amplicon length 62 bp (exons 2/3)The following primers were used:t-test and a Levene-test of equality of variances. Regarding the analysis of the RNA quality and expression at the mRNA level over time . In ver time , these wFirst, we compared different homogenisation tools (homogeniser vs. mortar) and isolation methods (Rneasy Kit vs. TRIZOL) for their suitability to obtain RNA of the highest quality and quantity from our vascular tissue samples . In contrast, when using mortar for homogenisation, extending the proteinase K incubation time did not improve the RNA quality .The highest RIN values were obtained using homogeniser and either TRIZOL or the RNease Kit (3.1 ± 0.4 or 2.7 ± 0.6) . When usOverall, the DV200 index values ranged between 40% and 80%, and there were no significant differences between the individual methods used ; these were higher than the values obtained using the Rneasy Kit (19.4 ± 9.1 ng/µL)  as well as in the human endothelial cell line (EA.hy926) .n = 20; AAA: 3.0 ± 0.5, n = 50; PAD 3.1 ± 0.5, n = 40). A similar pattern was observed in the DV200 index values. The endothelial cell samples had the highest DV200 values (93.6 ± 2.1%), followed by the muscle samples (90.2 ± 3.8%). The DV200 values of the diseased vascular tissue samples ranged between 36 and 76 .The RNA from the endothelial cell and the muscle samples had the highest RIN and DV200 values. They differed significantly from the healthy aorta (HA) and diseased vascular tissue samples  . The endTaken together, in contrast to the healthy muscle tissue, which had RINs of 7.5 ± 0.9 and DV200 index values of 90.2 ± 3.8%, the quality of the diseased vascular tissue samples was significantly reduced, with RINs of 3.0 ± 0.5 and DV200 index values of 56.8 ± 13.2%.In our experimental approach, outlined below, the extent of RNA degradation in the study samples —all of which were incubated at 4 °C—was analysed in different protective solutions  at different time points .p = 0.001).The RINs of the muscle samples at time point 0 were 7.7 ± 0.6 A. The bep = 0.037).In contrast to the muscle tissue samples, the RINs of the HA samples (3.2 ± 0.4) were significantly lower at time point 0 B. The RIp < 0.001). For the HA samples, the DV200 index values started at 58.4 ± 4.3% at time point 0 and remained stable in the RNAlater solution and the CpS for up to 7 days. In PBS, the DV200 values decreased slightly but continuously, with significant differences after 2, 3, and 7 days   B. RNA isd 0.008) C,D.p < 0.001). These changes were even more conspicuous in the PBS solution, where the RIN values significantly dropped after just 8 h to 4.63 ± 0.46 (p < 0.001) and were further reduced to 2.4 ± 1.0 (p < 0.001) after one day. Even the DV200 values were significantly more affected at room temperature compared with 4 °C (p = 0.014). Again, the most substantial drop was observed for the PBS solution: significant changes after just 8 h and a further reduction in the DV200 index values to 44.2 ± 9.0% (p = 0.007) after 2 days , ribosomal , and lncRNAs   .28S. In the muscle and HA tissue samples, the expression of the 18S gene was stable for up to 7 days. In the AAA and PAD samples, the expression dropped down significantly at days 3 and 7 in the RNAlater solution  (MALAT1 and H19) were stable for up to 7 days  C,D. For o 7 days .ACTB did not significantly change in any of the tested samples for up to 3 days . In the diseased AAA and PAD samples, significant reductions were observed as early as day 3 , reaching up to a 7-fold reduction in expression at day 7 (18S in the diseased vascular tissue samples was less stable than that of the housekeeping genes (Concerning our cryoprotective solution (CpS), the expression of the housekeeping gene o 3 days A–D. The at day 7 E–H. The ng genes C,D. A si28S gene was stable for up to 3 days . Interestingly, the DV200 index values did not correlate with time or RIN, except in the case of CpS , and this suggests that DV200 is more robust than RIN in determining RNA degradability. Regarding the diseased tissue samples (AAA and PAD), in which the RNA was already partially degraded at time point 0, the RNAlater solution exhibited the best protective properties for RNA, showing no correlation between time, RIN, and DV200. For the other protective solutions, the CpS and PBS, the RIN values significantly diminished over time  diminished over time, independent of the protective solution used. The stability of the RNA was highest in the RNAlater solution and lowest in the PBS . In contrast, the expressions of the housekeeping genes ACTB and GAPDH were stable over time. Similar results were observed for the healthy aorta samples . The CpS contains various components which are intended to maintain cellular viability ,17,18,19ACTB and GAPDH, their expression was unaffected for up to 2–3 days, regardless of the protective solutions in which the tissue samples were stored at 4 °C. Furthermore, ACTB mRNA seemed to be more stable than that of GAPDH. It is worth noting that the expression level strongly depended on the selected primers, the size of the amplicon, and the cDNA area, where the primers bind [18S seemed to be less stable than 28S. This observation is in line with those of Julian et al. [18S was the least stable gene among those tested. In contrast, ACTB and GAPDH were stable and thus also suitable as reference genes in aged and diseased ischemic tissue [18S and 28S gene stability in comparison to that of ACTB and GAPDH in glioblastoma-derived cells. Both ribosomal genes showed lower stability than the housekeeping genes. Thus, even if ribosomal genes are stable and can be used for the calculation of RNA quality , they may not be suitable for diseased vascular tissue in which the RNA is already degraded at the time of extraction.Regarding the analysis of the expressions of various genes included in our study, the housekeeping genes were mainly independent of the corresponding RINs. For both genes, ers bind ,30. Our n et al. , who comc tissue ,33. Furtc tissue  investigMALAT1 and H19 was observed after just 2 days’ incubation at 4 °C. MALAT1 in particular seemed to degrade rapidly. Furthermore, in contrast to the other tested genes, whose expression levels declined slowly with about a two-fold reduction after 2–3 days, the expression level of the lncRNAs dropped rapidly, and more than ten-fold. Again, the highest gene expression stability was observed in the RNAlater solution, and good results were also achieved using the CpS. The expression of MALAT1 and H19 is significantly increased in atherosclerotic lesions and aneurysm tissues [MALAT1 is an important lncRNA that regulates the proliferation of ECs and VSMCs and promotes autophagy [H19 plays a crucial role in metabolic disorders by suppressing lipid metabolism and increasing their accumulation, contributing to the progression of atherosclerosis [H19 is also involved in inflammatory responses involving NF-kB, TNF-α, IL-1β, and IL-6. Generally, lncRNAs, including MALAT1 and H19, are involved in many epigenetic regulatory processes, affecting their activity and time of action [Our experimental setup demonstrated that lncRNAs were the least stable genes. Depending on the heterogeneity of the point zero expression, a significant reduction in the expression of the lncRNAs  tissues ,20. MALAutophagy ,35. H19 clerosis . H19 is f action . In addif action . All of 18S and 28S) and can more reliably aid decisions concerning further analyses.The correlation analysis confirmed the results of the expression experiments. RNAlater demonstrated the highest protective capability against RNA degradation over time. The cryoprotective solution (CpS) used to preserve tissue samples collected in our SVB also showed a high protective capacity for RNA. Furthermore, the DV200 index demonstrated higher robustness and was not as strongly affected by time as the RIN. Focusing on RNA from non-diseased muscle tissue in PBS without any special protective properties, the expression of all the genes tested in our study significantly correlated with the RINs, as expected. These data show the importance of the RIN as a measure of RNA quality for reliable expression analyses, including transcriptomics and single-cell RNA sequencing. Interestingly, however, in the atherosclerotic and aneurysmal tissue samples, only the expression levels of lncRNAs were related to the RIN. These data suggest that when the RIN is low, as it often is in diseased vascular tissue, the RIN might not be the best indicator of whether the tissue sample is suitable for further expression analyses. In such cases, we would recommend using the DV200 index, which represents global RNA degradation , the quality of the RNA (RIN) was rather low (ranging between 2 and 4). We have assumed that in cases in which other research groups have found higher RIN values, this was probably because their vascular tissue samples were not as heavily affected by atherosclerotic and other cardiovascular pathologies. Regarding the protective solutions tested in our study, a cryoprotective solution, as suggested in the current work, might be a better option than RNAlater. Furthermore, because the RNA degradation in the atherosclerotic tissue proceeds randomly and globally, we recommend using proper corresponding controls with RINs in a comparable range. Otherwise, the transcriptomics data might convey differences in gene expression based on differences in RNA degradation rather than changes at the expression level of the corresponding genes. Concerning the expression analyses, the lncRNAs tested in our study were the least stable in our experimental approach. Finally, in the atherosclerotic samples, both ribosomal genes 00 > 30% . Based o


Ustilago maydis.Fungal pathogens execute well-defined infection programs that are intensively regulated at the posttranscriptional level. RNA biology determines the precise timing and subcellular expression of the encoded proteins. This temporal coordination is especially vital for membrane trafficking in order to synchronize the intracellular organelle network. This includes vacuole maturation, intra- and extracellular vesicle (EV) transport, protein entry into mitochondria, peroxisomes, and the ER. Here, we explore the intimate link between membrane trafficking, organelle function, and the RNA world during fungal plant pathogenesis, with a specific emphasis on the corn smut Candida albicans and U. maydis, respectively [septins: Cdc3, Cdc10, Cdc11, and Cdc12 [Many fungal pathogens require regulation of hyphal morphology for host invasion. These highly polarized hyphae rely on active transport along the cytoskeleton to deliver proteins to distinct subcellular regions. A fundamental mechanism is the transport of mRNAs, providing precise spatial and temporal control of protein synthesis. RNA-binding proteins (RBPs) play central roles in dictating the fate of mRNA from synthesis to degradation. Key RNA-binding proteins, for example, She3 and Rrm4, mediate actin- and microtubule-dependent mRNA transport in ectively ,2. ImporA transcriptome-wide iCLIP analysis revealed that Rrm4 interacts with hundreds of mRNAs, primarily through their 3′ UTR . InteresU. maydis, the scaffold protein Upa2 interacts with the poly(A)-binding protein, Pab1, to stabilize endosomal mRNA transport complexes [Sordaria macrospora [Aspergillus fumigatus, may also utilize this mRNA transport process for hyphal development.An outstanding question is how mRNAs are linked to transport endosomes. In plants, endosomal transport RBPs directly interact with the small GTPase Rab5, while in animal cells, the FERRY complex and annexin have been implicated in this process [omplexes . Furtheromplexes . SpecifiCryptococcus neoformans and C. albicans as well as plant pathogens such as U. maydis regulate RBP-mediated mRNA stability to control their virulence [U. maydis, the multi-KH domain RBP Khd4 is crucial for morphology and pathogenicity [Human pathogens such as irulence ,10. In Ugenicity . A transcib1 mRNA occurs on the cytoplasmic surface of ER membranes and is mediated by the transmembrane kinase/RNAse Ire1 in response to ER stress  mediating ER homeostasis during secretion. Unconventional splicing of R stress . The matDuring the pathogenic program, the UPR is specifically activated after plant invasion. This correlates with increased expression of more than 200 effectors many of which follow the classical ER-dependent secretory pathway . During pit1, pit2, pep1) [C. neoformans. Here, binding of the pumilio-type RNA-binding Puf4 to the mRNA encoding the Cib1-like protein Hxl1 supports unconventional splicing during UPR activation and mRNA degradation during recovery from ER stress [Excessive ER stress is suppressed by the negative feedback of the UPR on the signaling network, which controls the expression of the vast majority of effector genes . Importa2, pep1) . InteresR stress . In esseU. maydis, several glycolytic enzymes such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and 3-phosphoglycerate kinase (PGK-1) are targeted to peroxisomes through alternative splicing and translational readthrough, respectively. In both cases, the C-terminus gains a functional peroxisomal targeting sequence  are emerging as a novel class of effectors that can modulate host gene expression. The phenomenon of bidirectional cross-kingdom RNAi (ckRNAi) has been particularly well documented in plant–pathogen interactions, whereby both partners secrete small RNAs (sRNAs) that silence genes in one another . The fired genes . ckRNAi ed genes .A. thaliana sRNAs targeting B. cinerea transcripts were found associated with EVs, and DEAD-box RNA helicases and annexins have been implicated in their secretion [The routes of secretion and uptake of RNA during host–pathogen interaction are contentious, due to several possible mechanisms and a large variability between the systems. Extracellular vesicles (EVs) are one of the ubiquitous means of RNA secretion. In plant–pathogen interactions, ecretion . As for ecretion .Paracoccidiodes brasiliensis are translation-competent, yielding protein products in vitro. A comprehensive analysis of mRNAs associated with EVs from U. maydis cultures, designed to mimic infectious hyphae, has identified several candidate mRNA effectors that meet the following criteria: relatively enriched in EVs compared to the cells and up-regulated during infection [U. maydis to reprogram the host metabolism [Besides canonical sRNAs and mRNAs, tRNAs and tRNA fragments, circular RNAs, and even rRNAs can be secreted . As EVs nfection . As expetabolism . The bioU. maydis as a model pathogen reveals an intricate interplay between RNA biology and membrane trafficking. The regulation of RNA processes like splicing, localization, translation, and stability, precisely governs the exact translation levels of virulence factors. This investigation unveils a novel connection involving small GTPase regulation, septins, UPR, peroxisomal function, and the pathogen RNA trafficking to host cells.Studying Magnoporthe oryzae tRNA modification and codon usage regulate unconventional secretion of protein effectors [Understanding RNA biology is essential for studying the fundamental biology of fungal pathogens. A recent demonstration showcased that in ffectors . Advance