Previously, we have identified a novel human metastasis-inducing lncRNA (named SKAI1BC), that suppresses the KAI1/CD82 metastasis-suppressing gene and is upregulated in triple negative breast cancer and melanoma derived cell lines. Modeling of the SKAI1BC lncRNA secondary structure and its potential interaction with Inforna compounds, led us to identify several compounds that might bind the SKAI1BC lncRNA. We found that these compounds inhibit metastasis invasion and cell migration in culture, in all eight types of solid human cancers tested: several of which are the most lethal and/or frequent human malignancies. Moreover, in most cases, the mechanism of action of several of our compounds involves enhancement of KAI1/CD82 RNA level depending on the specific compound and the human tumor type. With the epigenetic inactivation of KAI1/CD82 in at least ten additional solid human cancers, this implies a very good chance to broaden the spectrum of human cancers affected by our compounds. This is the first time that modeling of a large lncRNA (> 700 bp) secondary structure followed by its potential interaction with Inforna like compounds database has led to the identification of potential biologically active small molecule drugs. Thus, the function of the vast majority of the lncRNAs has not been investigated yet.One of the most unexpected findings of the genomics area is the extensive transcription of RNA from non-protein coding regions of the genome. Large-scale sequencing of human cDNA libraries elucidated tens of thousands of noncoding RNAs (ncRNAs), prominent among which are long noncoding RNAs (lncRNAs), or noncoding RNAs longer than 200 bp. The FANTOM CAT database of human lncRNAs with accurate 5′ ends currently contains 27,919 lncRNAs, out of which 19,175 are potentially functional. In turn, the LNCIPEDIA database currently has 127,802 human lncRNAs encoded by 56,946 genes. At least 1555 human lncRNAs have experimental evidence to be functional3.Several authors have shown initially the potential of promoter-directed short hairpin RNAs (shRNAs) to activate gene expression of tumor/metastasis suppressor genes silenced by promoter spanning as-lncRNAs5. MALAT1, an abundant nuclear lncRNA, promotes cancer cell proliferation and metastasis in non-small cell lung carcinoma4.Two other prominent examples of breast cancer linked lncRNAs are HOTAIR (HOX antisense intergenic RNA) and MALAT1 (Metastasis-associated lung adenocarcinoma transcript 1). HOTAIR is a lncRNA that acts as a scaffold molecule by interacting with a chromatin modification complex that enables the HOXD gene silencing in trans. In primary and metastatic breast cancer cells, HOTAIR expression is up to hundreds-fold higher than in normal breast epithelia. This leads to transcriptional silencing of metastasis suppressor genes and results in tumor metastasis6. Likewise, at least 10 other human solid tumors are deficient in KAI1/CD82 metastasis suppressor gene expression: hepatocellular carcinoma, clear cell renal cell carcinoma, melanoma, osteosarcoma, pancreatic carcinoma, prostate cancer, ovarian cancer, bladder carcinoma, cervical carcinoma, and thyroid cancer9.A direct correlation of overall patients’ survival and KAI1 expression had been observed in at least the following five solid tumors: colorectal carcinoma, gastric carcinoma, non-small cell lung cancer (NSCLC), breast cancer, and laryngeal squamous cell carcinoma (LSCC), reviewed in7. At the transcriptional level KAI1 is upregulated by several transcription factors such as AP2, p53, JunB, and ΔNp63α7. Post transcriptionally, in liver HCC cells and gastric stomach cancer KAI1 is negatively regulated by miR-197 and miR-362-3p. Similarly, miR-338-5p negatively regulate KAI1 RNA in melanoma A375 cells while miR-217 suppresses KAI1 expression in NSCLC. Loss of heterozygosity (LOH) of KAI1 in human cancers is a rare event, and similarly no point mutations were found in the KAI1 gene in human malignancies7. Thus, KAI1 expression in human tumors is clearly being epigenetically silenced. The promotion of homotypic cell–cell adhesion is an important metastasis suppressive function of KAI1.Noteworthy, in at least three solid tumors  KAI1 affects also tumor proliferation7. In addition, the actin cytoskeleton organizing FAK-Lynp130CAS-CrkII pathway is attenuated by KAI1 mediated inhibition of the active p130CAS-CrkII complex formation.Recent reports propose a combination of altered KAI1-protein interactions and signaling pathways. It has been suggested that KAI1 interacts directly with the epidermal growth factor receptor (EGFR) and weakens migration signaling by rapid desensitization of EGF-induced signals10. For that purpose, total cellular RNA/nuclear RNA from three different TNBC cell lines,  were subject to RT-PCR with primers specific for potential upstream promoter-spanning antisense RNAs for ten of the most important human breast metastasis suppressors- and tumor suppressor- genes . Noteworthy, out of these 10 tested genes, only KAI1/CD82 had an antisense lncRNA spanning its promoter and suppressing it in the triple-negative breast cancer cell line MDA-MB-231 cell line. The existence of a KAI1 antisense lncRNA that is transcribed off the KAI1/CD82 promoter imply the latter is a bidirectional promoter, a finding that we previously reported11. We found that the KAI1 as-lncRNA is not polyadenylated, and is primarily present in the nucleus. Moreover, specific degradation of this lncRNA via RNAi (with either constitutive or inducible shRNAs expression) in breast cancer cells or melanoma cells led to a drop in this lncRNA and increase in KAI1 RNA and protein level in both breast cancer MDA-MB-231 and MDA-MB-435 melanoma cells. This leads to increase in cell adherence and consequently, inhibition of cancer cell invasiveness and cell migration11. Therefore, this lncRNA is a natural suppressor of KAI1 and consequently an enhancer of the metastasis process. Accordingly, we named it SKAI1BC-"Suppressor of KAI1 in Breast Cancer". Sequencing of this lncRNA showed that it is 792 bp long11. An identical sequence of a human long noncoding RNA of 792 bases (without a 3’ polyA tail) derived from a cDNA library of the GM12878 cell line, contig_343318, was then found in the UCSC database as UCSC Accession no. wgEncodeEH000148, one of the many thousands of transcripts derived off this cell line. However, no other information was reported about this RNA transcript.In order to try identifying new breast cancer affecting lncRNA(s), we established a primer-specific RT-PCR screening process for promoter-spanning lncRNAs of antisense orientation11. However, despite numerous attempts over the past 43 years (oligonucleotides), and 24 years (RNAi based technologies), the FDA approved only 4 ASOs and 11 siRNAs as drugs12. Therefore, we decided to try to ablate the oncogenic activity of SKAI1BC lncRNA, via RNA-binding small molecules13. Previously we developed a method to predict small compounds binding to RNAs15. We have used this approach to identify small molecules that target expanded repeating RNAs, which cause or contribute to neurological/neuromuscular diseases, as well as small compounds that target oncogenic pre-miRNAs and viral RNA18. Until 1/1/2021, the FDA has so far approved one compound  as a drug19. Therefore, there is an urgent need to provide effective compounds for inhibiting metastatic properties of cancer cells20.Previously we also disrupted SKAI1BC RNA activity by oligonucleotides (modified and non-modified) in the form of ASO or siRNA11, confronted us with the question of how to stimulate the epigenetically suppressed activity of KAI1 in metastatic cancer(s). This is a challenging problem because the KAI1/CD82 metastasis suppressor is known to be epigenetically silenced in at least 15 solid human tumors and possibly a few hematopoietic human malignancies. Importantly, the level of KAI1 expression is prognostic of overall survival or other clinical key features of the patients’ disease in at least 10 solid human cancers.One acute problem in cancer therapy is the scarcity of effective drugs against metastasis, resulting in 90% of cancer deaths. Another major difficulty emerging in cancer therapy is the recent realization that many of the ~ 30,000 unexplored human lncRNAs are functional and a good many are likely to be involved in malignancy. Our recent discovery of a novel human lncRNA, which we initially identified as a suppressor of the KAI1/CD82 in triple-negative breast cancer21. For each window, ScanFold-Scan calculates a thermodynamic z-score, an indication of unusual structural stability of an RNA, and the ensemble diversity (ED), a measure of diversity of structures in an ensemble. The average z-score for all windows is − 0.67 ± 1.16, indicating that the RNA can potentially fold into stable structures. Among the 673 windows, 119 have z-scores more than one standard deviation below the average z-score for all windows. The average ED for all windows is 25.62 ± 12.35, and 77 of the 119 lowest z-score windows have ED values more than one SD below average. ScanFold-Fold was then used to identify base pairs that generate low z-score windows.To assess the drugability of the 792 bp long KAI1 as-lncRNA, we used ScanFold 2.0 to identify regions of the RNA likely to form functional structures. First, the RNA was folded with ScanFold-Scan in 120 nt windows to find local structural motifs. The 120 nt window size was chosen on the basis that previous studies found a window size between 100 and 150 nt to be optimalavg) below − 1. Lowering the Zavg cutoff to − 2 further decreased the number of base pairs to 42. The folding landscape is dominated by structures with Zavg >  − 2, with structures with Zavg <  − 2 dispersed throughout the lncRNA. Zavg and ED correlate, as determined by a correlation coefficient of 0.75; base pairs with lower Zavg values also have lower ED values. However, there does not appear to be a positive trend between either of these metrics and ΔG37°. Constrained refolding of structures containing Zavg <  − 2 base pairs using RNAfold added 52 base pairs to the structures  with fitness scores of at least 70% for each region, the top hits among which are shown in Fig. These presumably targetable small structures were compared to the RNA motifs-small molecule interactions Inforna 2.0 database, which was generated experimentally primarily by one of us, M. DisneyWe sought for compounds that not only bind the SKAI1BC as-lncRNA, but also inhibit its activity as might be reflected in KAI1 stimulation. Compounds #1–#5 are imidazole derivatives., middle row). Interestingly, compound #5 inhibited cell invasion of all four TNBC cell lines, even though it did not boost KAI1 RNA level in MDA-MB-231, BT-549, HCC70 and Hs578T . In contrast, none of the five compounds inhibited the very modest invasion of the MCF10A derived cells (data not shown). These experiments were followed by inquiry of the compounds effect on cell migration, the second step of metastasis following cell invasion. As shown . In all three cell lines, there is no significant stimulation of KAI1 RNA level by each of the five compounds (#1–#5). The five compounds managed to inhibit cell invasion and cell migration in all three Breast cancer cell lines , ZR-75-30  and SkBr3 (HER2+) cell lines  derived cell lines tested in this work. In general, the NCI-H1975 and NCIH2030 cell lines responded better to the compounds than the other two cell lines in terms of KAI1 RNA stimulation , whereas in C3A compounds #1 and #3 stimulated KAI1 RNA by × 3.5 and × 2.7, respectively . Without being bound by the theory, the inventors assume that compounds binding to the particular SKAI1BC lncRNA prevent the lncRNA annealing to the complementary sense DNA strand (at the KAI1 promoter region), and thus enabling the KAI1 gene to be transcribed. Alternatively, the compounds may interfere with the SKAI1BC lncRNA binding of an essential KAI1 gene/s-specific transcription factor, and in this way enhance KAI1 RNA transcription.22. Obviously, such intervention is likely to be desirable in human tumors developing metastases early on after primary tumors’ formation. Ten additional solid cancers such as prostate, gastric, ovarian, colon, cervical, renal clear cell carcinoma, osteosarcoma, bladder, thyroid and LSCC cancers are known to be dependent on deficiency in KAI1/CD82 expression. Therefore, more tumors are likely to respond to these compound/s7. This also brings up the question whether SKAIBC lncRNA may serve as a biomarker for metastasis in a fraction of the solid human cancers. To the best of our knowledge, this is the first time that modeling of a large lncRNA (> 700 bp) secondary structure followed by its potential interaction with Inforna like compounds database, has led to identification of biologically active, potential small molecule drugs.The metastasis-specific activities of these compounds, coupled to their lack of cytotoxicity, may also enable their use to prevent formation of disseminated tumor cells (DTCs). This latter is related to the recent discovery of biomarkers for generation of DTCs27, the potential importance of these compounds (which have been recently named Migrastatics) is clear.In view of the fact that until now, there are very few effective anti-metastasis drugsThe following cell lines were obtained from ATCC: TNBC MDA-MB-231, BT-549,HCC70 and Hs578T; Melanoma SK-MEL-24, RPMI-7951 and MDA-MB-435;2 each in its recommended medium supplemented with 5–10% fetal bovine serum (FBS) , 10 units/ml of penicillin and 50 µg/ml streptomycin.Pancreatic cancer AsPC-1, BxPC-3 and CFPAC-1; NSCLC A-549, NCI-H1299, NCIH1975 and NCI-H2030; Liver hepatocarcinoma SK-HEP1 and C3A. They were routinely cultured according to ATCC “culture method” at 37 °C in 5% CO29. The transcript was folded in 120 nt windows, 1 nt increments (step size = 1), and 37 °C temperature. The Gibbs free energies of the structures (ΔG37°) were compared to the average free energy of 100 randomized sequences. Structures containing base pairs with Zavg values below − 2 were refolded with RNAfold in the ViennaRNA package30 using ScanFold-predicted base pairs as constraints to extend helices and remove isolated base pairs. The probabilities of secondary structural features were calculated using ProbScan in the RNA structure package31. Figures of RNA folding results were generated for publication using IGV-ScanFold32 and VARNA33. Inforna was queried with these structures to find compounds that bind to structural motifs with high fitness scores15. The following compounds were received from NCI and dissolved in DMSO to a final concentration of 0.05%.The SKAI1BC as-lncRNA (792 nt) was folded using ScanFold 2.0Compound #1: NSC no. 50460.Compound #2: NSC no. 50469.Compound #3: NSC no. 57161.Compound #4: NSC no. 63676.Compound #5: NSC no. 364277.Total RNA of the different cultures was extracted using Quick-RNA™ MiniPrep Kit  according to the manufacturer instructions. RNA concentration and RNA quality were determined by SpectraMax quick drop micro-volume spectrophotometer (Molecular Devices).Reverse transcription was carried out using RevertAid™ Premium kit (Thermo Fisher), using hexamer primers and according to the manufacturer instructions. Usually, 1 µg of RNA was reverse-transcribed in a 20 µl reaction volume. In order to identify promoter-spanning lncRNAs of antisense orientation (so it is not mixed with plausible upstream-initiating protein coding transcripts), total cellular RNA/nuclear RNA from the human tumor cell lines, were subject to primer-specific RT-PCR.CT method was used for quantification of the relative RNA expression applying HMBS as the normalizing housekeeping gene. Each sample was validated three times (n = 3).RNA level was assessed using the TaqMan Gene Expression Assay (Applied Biosystems) and a QuantStudio 1 RT-qPCR System (Thermo Fisher) following the manufacturer-recommended procedures. TaqMan® PCR took place in 96-well reaction plates holding a volume of 10 µL in each well. The mixture consisted of TaqMan® Gene Expression Assay 20 × (Thermo Fisher Scientific), TaqMan® Universal PCR Master Mix 2 × (Thermo Fisher Scientific), and 30 ng of desired cDNA. The 2ΔΔCells were treated with 5 µM of compounds #1–5 for 48 h and total RNA was extracted and reverse-transcribed to cDNA. Relative KAI1 mRNA expression, as well as SKAI1BC lncRNA, were quantified by Real-Time PCR with HMBS RNA as endogenous normalizing control.34, cells were treated with 5 µM of each of the compounds #1–#5) for 24 h. Then, ThinCert™ (Greiner Bio-One) cell culture inserts were placed in a multi well cell culture plate. Each insert contains a polyethylene terephthalate (PET) membrane at the bottom with a pore size of 8 µm that separates the upper from the lower compartment. Of the pre-treated cells, 100,000 serum-starved cells were seeded at the top of the insert in 200 µl serum free media, with or without 5 uM of the different particular compound. The lower compartment contains 10% FBS media as a chemo-attractant that may induce active migration of the seeded cells through the PET membrane. Adherent cells that migrate through the pores remain attached to the underside of the PET-membrane. After 24 h, the medium in the inserts and lower compartment was removed. To estimate the percentage of migrated cells, a Resazurin Cell Viability Assay was performed and compared to the mock control cells.To study cell migration35.Cells were treated with 5 µM of each of the compounds (#1–#5) for 24 h. Cells were then seeded in CytoSelect  transwell chambers for additional 24 h, while under starvation conditions, and in the presence of the compounds. Cells invasion from the upper chamber to the chemoattractant (10% serum) in the lower chamber were quantified using colorimetric assay and according to the manufacturer instructionsTNBC MDA-MB-231 cells were grown in six well plates and treated with either 0.05% DMSO as a mock, or 5 µM of either Compound #3 or Compound #5. Forty-eight hours later, RNA was extracted from a six well plate using 1 ml of Trireagant (T9424) according to manufacturer’s instructions. RNA concentration and purity were measured with Nano drop to verify QC 1.8–2.2 for 260/230 and 260/280. RNA integrity was examined on Tapestation 2200 (Agilent) using RNA Tape and Buffer  and confirmed to be > 9.5 for all samples.Poly (A) selection was performed with kit NEX Poly (A) beads 2.0 (48 rxn)-NOVA512992 (Perkin Elmer) using 1.2 µg according to manufacturer’s instructions and eluted in 14 ul. Enriched RNA was used for RNA library preparation NEXTFLEX Rapid XP DNA-seq Kit (96rxn)-514,903 (Perkin Elmer) according to manufacturer’s instructions using 15 min fragmentation and 10 cycle amplification. cDNA was quantified using DSDNA HIGH SENSITIVITY 1000 RXN-DSDNA-H2 and quality was assessed with Tapestation (D1000 SCREEN TAPE 5067–5582 and D1000 REAGENTS 5067–5583) to determine band specificity and size.Libraries were pooled and sequenced on a Hiseq (Illumina). Samples were demultiplexed using Bcl2FastQ and paired score quality was measured using fastqc and multiqc to be > 30 for > 87% of all samples.38.Samples were aligned to Hg38 genome using STAR with default parameters. Mapping quality was examined using SeqMonk and > 85% were found to map to exons, with no rRNA or mtDNA contamination. Samples were quantified using htseqcount and compared using Deseq2 with default parameters. Pathways analysis was performed using ClusterProfiler tool, using genes with a ≥ 1.5-fold change and significance of 0.1FDR to obtain enriched GO terms and KEGG pathwaysStatistical analysis of mock-treated and compound-treated cells was carried out using a one-tailed t-test. The null hypothesis in each case was that the compounds had no effect on cell migration, invasion, or proliferation or KAI1 mRNA levels.All data generated or analyzed during this study are included in this published article, and its “Supplementary Information.


The identification of special protein or RNA molecules via computational methods is of great importance in understanding their biological functions and developing new treatments for diseases. Computational methods can help identify proteins and RNA molecules by analyzing genomic and proteomic data, as well as using machine learning algorithms and other computational techniques to identify patterns and structures within the data. The identification of special proteins or RNA molecules can lead to the discovery of new therapeutic targets for the treatment of diseases, such as cancer or viral infections. By understanding the structures and functions of these molecules, researchers can design drugs that target them specifically, resulting in more effective treatments with fewer side effects. Furthermore, computational methods can also aid in the identification of biomarkers, which are molecules that indicate the presence of a disease. By identifying specific proteins or RNA molecules that are associated with a particular disease, researchers can develop diagnostic tests that can detect the disease at an early stage, leading to earlier treatment and improved patient outcomes. Non-coding RNAs (ncRNAs) are RNA molecules that do not encode proteins but have regulatory roles in gene expression. Proteins are essential macromolecules that carry out a variety of functions in a cell, including catalyzing biochemical reactions, transporting molecules, and regulating gene expression. Some good work has been published on the role of molecular dynamics simulations in understanding the functions of RNA-based systems ,2. In thThe interactions between ncRNAs and proteins are critical for many biological processes, including transcriptional and post-transcriptional regulation, RNA splicing, RNA editing, translation, and protein stability. Predicting interactions between ncRNAs and proteins is crucial to understanding the molecular mechanisms of these processes and identifying potential targets for drug development. Zhan et al. predicted ncRNA–protein interactions based on an innovative as well as practical deep learning model and improved sequence information, and they employed a stacked autoencoder network to extract hidden high-level features . Zhan’s Predicting disease-related microRNAs (miRNAs) is an important area of research with significant potential for improving our understanding of disease mechanisms and developing new therapies for a wide range of diseases. miRNAs are small non-coding RNA molecules that play important roles in regulating gene expression in a variety of biological processes. There are several methods for predicting disease-related miRNAs, including computational approaches that analyze gene expression data, sequence information, and other genomic features. In this Special Issue, Xuan et al. proposed a dual convolutional neural-network-based method to predict candidate disease-related miRNAs and captured the topology structures of the miRNA and disease networks . The metCircular RNAs (circRNAs) are a type of non-coding RNA that have been found to play important roles in various biological processes, including gene regulation, transcriptional and post-transcriptional control, and the development of certain diseases. As a result, the detection of circRNAs from RNA-seq data has become an important research topic in molecular biology. One of the main challenges in detecting circRNAs from RNA-seq data is their circular structures, which make them resistant to traditional RNA sequencing approaches; however, recent advances in RNA sequencing technology and bioinformatics tools have made it possible to detect circRNAs from RNA-seq data. Zhang et al. provided a novel computing method, CIRCPlus, that located circRNA candidates by identifying a set of back-spliced junction reads by comparing the local similar sequence of each pair of spanning junction reads . Zhang eProtein function prediction and identification are crucial for the development of new biotechnologies. For example, identifying proteins with specific functions can lead to the development of new enzymes for industrial processes. Seven papers focus on describing protein function prediction or protein identification, which include the prediction of signal peptides in proteins, protein hydroxylation site prediction, protein–protein interaction (PPI) prediction, and protein identification. To identify signal peptides in proteins from malaria parasites, Burdukiewicz et al. present a prediction method called signalHsmm . The proInternational Journal of Molecular Sciences Editorial Office.Overall, papers in this Special Issue have demonstrated that the identification of special proteins or RNA molecules via computational methods is a powerful tool that can help advance our understanding of biological processes and lead to the development of new therapies and diagnostic tools. We expect that such studies will receive great attention. Finally, we thank all of the efforts of the authors, reviewers, and staff at the


Trichomonas vaginalis is one of the most common sexually transmitted parasites in humans. This protozoan has high iron requirements for growth, metabolism, and virulence. However, iron concentrations also differentially modulate T. vaginalis gene expression as in the genes encoding cysteine proteinases TvCP4 and TvCP12. Our goal was to identify the regulatory mechanism mediating the upregulation of tvcp12 under iron-restricted (IR) conditions. Here, we showed by RT-PCR, Western blot, and immunocytochemistry assays that IR conditions increase mRNA stability and amount of TvCP12. RNA electrophoretic mobility shift assay (REMSA), UV cross-linking, and competition assays demonstrated that a non-canonical iron-responsive element (IRE)-like structure at the 3′-untranslated region of the tvcp12 transcript (IRE-tvcp12) specifically binds to human iron regulatory proteins (IRPs) and to atypical RNA-binding cytoplasmic proteins from IR trichomonads, such as HSP70 and α-Actinin 3. These data were confirmed by REMSA supershift and Northwestern blot assays. Thus, our findings show that a positive gene expression regulation under IR conditions occurs at the posttranscriptional level possibly through RNA-protein interactions between atypical RNA-binding proteins and non-canonical IRE-like structures at the 3′-UTR of the transcript by a parallel mechanism to the mammalian IRE/IRP system that can be applied to other iron-regulated genes of T. vaginalis. Iron is a cofactor in many biochemical activities. In several enzymes, iron is necessary to carry on cellular processes, including energy-producing redox reactions, oxygen transport, DNA synthesis, and cellular detoxification . Howevertrans-acting cytoplasmic iron regulatory proteins (IRP-1 and IRP-2) with cis-acting iron-responsive elements (IREs). IREs are stem-loop structures present within the 5′- or 3′-untranslated regions (UTRs) of some mRNAs  UTP  in the transcription reaction. The canonical IRE-fer transcript was used as the positive control [For in vitro transcription, we used DNA from the pSPT-fer plasmid (a generous gift of Dr. Lukas Kühn) that contains the human ferritin H-chain IRE (IRE-fer) region ,46. We a control ,39. The 32P-labeled RNAs (0.2 ng in 2 × 105 cpm) in 20 μL of reaction volume incubated for 10 min at 25 °C with the recombinant hIRP-1 (1 μg), with HeLa cells (20 μg), or with T. vaginalis (50 μg) cytoplasmic extracts in the presence of 5 μg heparin. The RPCs were resolved on a 6% non-denaturing polyacrylamide gel and visualized by autoradiography as before [RNA-protein complexes (RPCs) were first detected by REMSA as previously reported using s before ,39. The s before , as a noT. vaginalis (50 μg) cytoplasmic extracts with 32P-labeled RNA probes (5 × 105 cpm) for 20 min at 30 °C in 25 μL of a reaction mixture. After, it was irradiated using a UV lamp (240 nm) for 30 min on ice, and then incubated with RNase A (10 μg) and RNase T1 (20 u) for 30 min at 25 °C. Proteins bound to RNA were resolved by SDS-PAGE on 10% polyacrylamide gels, CBB-stained, and dried. The radioactive bands were visualized by autoradiography. For competition assays, a distinct molar excess of the unlabeled IRE-tvcp12, IRE-tvcp4 [Briefly, the UV-cross-linking assays were performed as previously reported, by incubating hIRP-1r (0.5–1.0 μg), HeLa cells (30 μg), or RE-tvcp4 , or IRE-RE-tvcp4 ,39.The modified Northwestern blot assay was performed as described previously  by combitvcp12 transcript increased in IR compared to in HI conditions [tvcp12, we first investigated whether iron regulates the amount of tvcp12 transcript by modulating mRNA stability. The tvcp12 mRNA was chased after a transcriptional blockage in actinomycin D-treated trichomonads grown under different iron conditions and measured at 0 to 24 h by semi-quantitative duplex RT-PCR assays using total RNA. We also amplified the β-tubulin mRNA as an internal control. tvcp12 mRNA in IR trichomonads remained stable even 24 h after the actinomycin D-treatment  19 nt IRE-like hairpin structure with a 6 nt loop UAAUUG  hairpin stem-loop RNA secondary structure was compared with the secondary structures of the human IRE-fer [tvcp4 mRNA [UAAUUG-3′ sequence, which does not correspond to the canonical sequence reported for eukaryotic IRE  and the heat-shock protein 70 (TvHSP70) that specifically interacted with the first non-canonical IRE described in trichomonads, the IRE-tvcp4 RNA structure [Interestingly, the protein bands crosslinked with IRE-tvcp12 have a similar size to those that interacted with trichomonad IRE-tvcp4, which were previously identified by mass spectrometry ,40 as α-tructure ,40. ThusTo test our hypothesis regarding the participation of TvACTN3 and TvHSP70 in RNA-protein interactions between IRE-tvcp12 and IR trichomonad cytoplasmic extracts, we performed supershift assays using the anti-TvACTN3r and anti-TvHSP70r antibodies in REMSA reactions between parasite IR cytoplasmic extracts and the radiolabeled IRE-tvcp12 RNA transcript. tvcp12 to TvACTN3 and TvHSP70, we conducted an NWB assay as another functional assay using purified TvACTN3r and TvHSP70r proteins to be tested and hIRP-1r and TvTIM2r as positive and negative control proteins, respectively  in the 3′-UTR mRNA that interacts with atypical cytoplasmic RNA-binding proteins present in the cytoplasmic extract from trichomonads grown under IR conditions, such as TvACTN3 and TvHSP70. Thus, it is likely that expression of TvCP12 is modulated by a posttranscriptional atypical iron regulatory mechanism mediated by specific RNA-protein interactions parallel to the IRE/IRP system, preventing mRNA degradation in IR conditions as in other organisms ,5,6. tvcp4 gene is upregulated by high iron at the posttranscriptional level due to the presence of a non-canonical iron-responsive element (IRE-tvcp4) at the 5′-region of the tvcp4 transcript, blocking its mRNA translation [tvcp12 transcript  with atypical cytoplasmic RNA-binding proteins under IR conditions  is similar to some of the IRE-fer mutants reported by Henderson et al. [Even if most mammalian IREs found in mRNA coding proteins involved in iron homeostasis are similar and follow a canonical stem-loop structure ,62, the n et al. ,46. Desptvcp4 [tvcp12 are not identical, the functional assays for the IRE-tvcp12 hairpin show that the RPCs formed with HeLa and trichomonad cytoplasmic extracts are specific  to IRE-tvcp12 hairpin have similar sizes to those bound to IRE-tvcp4  and can s genome , suggests genome ,39. By Rtvcp12 gene expression under IR conditions as a model. In the IR conditions  and stress response proteins (TvHSP70) instead of the typical IRP. Thus, our data suggest that the highly conserved mechanism of iron regulation mediated by the canonical IRE/IRP system might represent a specialization throughout the evolution for the maintenance of iron homeostasis [T. vaginalis. In T. vaginalis, this mechanism might regulate the expression of a wide variety of genes, including some encoding proteins involved in trichomonal metabolism and virulence, in addition to those related to iron homeostasis.The fact that this parasite could respond to the changing iron concentrations during vaginal infection by differentially regulating the expression of multiple genes at the same time supports the existence of a parallel IRE/IRP-like regulatory mechanism in l TvACTN- and streeostasis ,5,6,62 ttvcp12 expression is upregulated by the lack of iron due to a differential modulation of its mRNA stability by specific RNA-protein interactions under IR conditions mediated by the binding of a non-canonical IRE-tvcp12 hairpin stem-loop structure located at the 3′-UTR of the tvcp12 mRNA to TvACTN3 and TvHSP70 atypical cytoplasmic proteins. In conclusion, in this study, we have demonstrated that tvcp4 [tvcp12 gene expression regulation by iron, and controlling translational blockage or mRNA stability, the existence of a posttranscriptional mechanism through a parallel IRE/IRP-like system in T. vaginalis, an early branching protozoan, can be illustrated. This regulatory mechanism could explain the way some trichomonad genes are differentially expressed by the same iron concentration at the posttranscriptional level. This will pave the way to enhance our understanding of trichomonad gene expression regulation in response to iron variations during infection. We are currently working on identifying the presence of IRE-like structures at the 3′-UTR of mRNAs upregulated by iron-restricted conditions and their impact on their gene expression regulation at the posttranscriptional level.By combining the data from tvcp4 ,39,40 an


Alternative splicing is an important mechanism that enhances protein functional diversity. To date, our understanding of alternative splicing variants has been based on mRNA transcript data, but due to the difficulty in predicting protein structures, protein tertiary structures have been largely unexplored. However, with the release of AlphaFold, which predicts three-dimensional models of proteins, this challenge is rapidly being overcome. Here, we present a dataset of 315 predicted structures of abnormal isoforms in 18 uveal melanoma patients based on second- and third-generation transcriptome-sequencing data. This information comprises a high-quality set of structural data on recurrent aberrant isoforms that can be used in multiple types of studies, from those aimed at revealing potential therapeutic targets to those aimed at recognizing of cancer neoantigens at the atomic level. Therefore, it is not surprising that the gene isoforms play important roles in many biological processes, such as processes related to development, pluripotency and apoptosis5. Aberrant isoforms have been implicated in multiple human tumors, including uveal melanoma (UM), showing extensive changes via alternative splicing and the expression of critical gene isoforms8. Specific splicing isoforms are important for the initiation, metastasis and drug resistance of cancer, and some AS events have been shown to be significantly related to patient survival11. Although the role of a few splicing isoforms in cancer has been studied, 3D protein structure prediction on a scale that covers the transcriptome and can be used for evaluating biological functionality remains unexplored.Alternative splicing (AS) can influence transcriptome and proteome diversity, as evidence shows that approximately 95% of genes with multiple exons produce multiple isoforms12. Long-read mRNA sequencing (long-read RNA-seq) shows advantages over short-read RNA-seq in isoform detection because long reads directly cover the entire transcript without the need of reconstruction, which is needed for short reads15. However, because of the high sequencing error rate (~15%) of raw long-read RNA-seq data, it is still challenging to determine the precise splicing sites with only long-read RNA-seq data16. Hybrid sequencing, combining long-read RNA-seq reads with high quality short-read RNA-seq reads and taking advantage of both platforms, improves the identification of AS events and gene isoforms18. Although great efforts have been made to study the alternative splicing mechanisms and functions of different isoforms, our knowledge of the 3D structure of splicing isoforms is very limited20. This lack of information means that for a large majority of spliced isoforms, no documented structures have been deposited in the Protein Data Bank (PDB), causing a large knowledge gap; hence, accurate prediction of protein structure is one of the most challenging goals in biology22. As structures carry vital information about how different isoforms with a certain degree of sequence homology perform different functions, it is necessary to investigate the 3D structure of abnormal isoforms to explore their functions23. The most recent achievement in related technology, AlphaFold, a deep-learning-based approach, has been proven to be highly successful in predicting the 3D structures of proteins based on their amino acid sequences24. This is a significant advance that might have a profound impact on the study of protein dysfunction and the discovery of new polypeptides with potential medical applications25.The suitability of short-read mRNA sequencing (short-read RNA-seq) in the discovery of AS events is limited because of the mapping uncertainty of short read lengths or assembly problemsIn this study, we provide an information resource based on the predicted structures of 315 novel isoforms obtained by long-read RNA-seq and short-read RNA-seq of transcriptome data from 18 UM patients. To better understand the structural differences of abnormal isoforms and the potential effects, we compared the structural differences between 295 abnormal-gene-encoded isoforms and their normal gene-encoded protein counterparts. We also identified 13 potential AS-derived neoantigens in 10 abnormal isoforms with altered amino acid sequences. These data constitute particularly valuable information on aberrant isoform structures that intersects with that on abnormal isoforms in other datasets, which can be used for an investigation into the roles of these isoforms in multiple cancer types. This study also offers new insights into the structure-based prediction of neoantigens and potential drug targets.A total of 20 patients with primary UM who visited Shanghai Ninth People’s Hospital between 2018 and 2021 were selected for sampling. The detail information of the 20 UM patients is listed in Table Total RNA was isolated using Trizol Reagent (Invitrogen Life Technologies), then the concentration, quality and integrity of RNA were determined by NanoDrop spectrophotometer (Thermo Scientific). Three micrograms of RNA were used as input material for the RNA sample preparations. Sequencing libraries were generated which was then sequenced on Illumina NovaSeq. 6000 platform by Shanghai Personal Biotechnology Cp. Ltd.Total RNA was isolated using the Trizol Reagent (Invitrogen Life Technologies), and the concentration, quality and integrity were determined by NanoDrop spectrophotometer (Thermo Scientific). A total of 1ug RNA was prepared for cDNA libraries using the cDNA-PCR Sequencing Kit (SQK-PCS109) according to the instructions of Nanopore Technologies (ONT). Defined PCR adaptors were directly added to both ends of the first-strand cDNA by reverse transcriptase. After 14-cycle of PCR by LongAmp Tag (NEB), the PCR products were subjected to ONT adaptor ligation using T4 DNA ligase (NEB). Agencourt XP beads were used for DNA purification according to ONT protocol. The final cDNA libraries were added to FLO-MIN109 flow cells and were sequenced on the PromethION platform. GUPPY (version 3.2.6) was used for basecalling to convert the fast5 format data to fastq format.17. LoRDEC is a new and efficient hybrid correction algorithm based on De Bruijn Graphs (DBG) of short reads. Achieving a comparable accuracy, LoRDEC runs six times faster and requires 93% less memory than PacBioToCA and LSC. LoRDEC first reads the short reads, builds their DBG of order k and then corrects each long read one after the other independently.Hybrid error correction, a simple and cost-effective approach involved with high quality short-read RNA-seq data, was used to improve the quality of long reads Fig. . Here we26. Spliced_bam2gff was used to convert sorted BAM files with spliced alignments (from minimap2) into GFF2 format. With sorted GFF2 file as input, based on the median of exon boundaries from all transcripts in the cluster, cluster_gff clusters reads with similar exon/intron structures into a rough consensus set of clusters. Then, by mapping all reads to the median length of read within each cluster generated by cluster_gff, polish_clusters creates an error corrected read and polishes it using racon27. Finally, taking polished and consistent transcripts as input, collapse_partials filters transcripts which are likely caused by 5′ end degradation and collapses input transcripts into a polished and collapsed transcripts set of each UM case  after the cuffcompare process. Isoform labeled by “ = ” and “j” tags in the output “.tracking” file was considered as an annotated and unannotated (novel) isoform, respectively. We got a median of 8,989 annotated and a median of 9,150 novel isoform candidates based on pinfish pipeline (Table We filtered out transcripts supported by less than two FL reads. With the cuffcompare tool in the Cufflinks package30. The tool of ORFfinder (https://www.ncbi.nlm.nih.gov/orffinder/) was subsequently employed to search for open reading frames (ORFs)31. The 3D structure was predicted using AlphaFold-Multimer version 2.2.0 using Shanghai Jiao Tong University’s supercomputing resources  memory)24. The version and parameters of AlphaFold-Multimer databases used were outlined as below:For novel isoforms, we first extracted corresponding DNA sequences from the human reference genome (hg38) using “samtools faidx” based on the coordinates and orders of all their exons, as well as the strand“python run_alphafold.py--use_gpu_relax--data_dir = $DIR--uniref90_database_path = $DIR/uniref90/uniref90.fasta--mgnify_database_path = $DIR/mgnify/mgy_clusters_2018_12.fa--bfd_database_path = $DIR/bfd/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt--uniclust30_database_path = $DIR/uniclust30/uniclust30_2020_06/UniRef30_2020_06--pdb_seqres_database_path = $DIR/pdb_seqres/pdb_seqres.txt--template_mmcif_dir = $DIR/pdb_mmcif/mmcif_files--obsolete_pdbs_path = $DIR/pdb_mmcif/obsolete.dat--uniprot_database_path = $DIR/uniprot/uniprot.fasta--model_preset = multimer--max_template_date = 2022-1-1--db_preset = full_dbs--output_dir = output--fasta_paths = input.fasta”https://www.uniprot.org) according to the priority order of EM, NMR, X-ray and alphafold predicted sources of structures. We used TM-score (https://zhanggroup.org/TM-score) to compare the predictive results with typical structures32. Protein pairs with a TM-score > 0.5 are mostly in the same fold while those with a TM-score < 0.5 are mainly not in the same fold, and some of them with a TM-score < 0.17 just have random structural similarity33. We then check the distribution of comparison scores of novel isoforms based on the gene ontology enrichment results above , and define the peptide as a weak binder if the % Rank is above the threshold of the strong binders but below the specified threshold (2%)ens Fig. . Finally36. Our cohort includes a total of 20 cases, of which 20 cases have short-read RNA-seq data and 18 cases have long-read RNA-seq data. This study is based on the 18 cases with both short-read and long-read RNA-seq data. AlphaFold-Multimer predicted structures files are accessible at figshare37. Each folder, whose name consists of gene name and isoform ID, corresponds to each isoform structure files . Each folder contains multiple format text files which represent the predicted structures information. Among all predicted structures files, “ranked_0.pdb” file has the highest confidence.The datasets presented here have been stored at GEO under GSE206464https://github.com/nanoporetech/pychopper) was used to identify, orient and rescue FL cDNA reads. The number of total long reads ranged from 4,788,440 to 14,048,314 in which the FL reads were between 4,112,595 and 12,828,344 (Table Pychopper package (


Aedes japonicus is rapidly invading North America and Europe. Due to its potential to transmit multiple pathogenic arthropod–borne (arbo)viruses including Zika virus, West Nile virus, and chikungunya virus, it is important to understand the biology of this vector mosquito in more detail. In addition to arboviruses, mosquitoes can also carry insect-specific viruses that are receiving increasing attention due to their potential effects on host physiology and arbovirus transmission. In this study, we characterized the collection of viruses, referred to as the virome, circulating in Ae. japonicus populations in the Netherlands and France. Applying a small RNA-based metagenomic approach to Ae. japonicus, we uncovered a distinct group of viruses present in samples from both the Netherlands and France. These included one known virus, Ae. japonicus narnavirus 1 (AejapNV1), and three new virus species that we named Ae. japonicus totivirus 1 (AejapTV1), Ae. japonicus anphevirus 1 (AejapAV1) and Ae. japonicus bunyavirus 1 (AejapBV1). We also discovered sequences that were presumably derived from two additional novel viruses: Ae. japonicus bunyavirus 2 (AejapBV2) and Ae. japonicus rhabdovirus 1 (AejapRV1). All six viruses induced strong RNA interference responses, including the production of twenty-one nucleotide-sized small interfering RNAs, a signature of active replication in the host. Notably, AejapBV1 and AejapBV2 belong to different viral families; however, no RNA-dependent RNA polymerase sequence has been found for AejapBV2. Intriguingly, our small RNA-based approach identified an ∼1-kb long ambigrammatic RNA that is associated with AejapNV1 as a secondary segment but showed no similarity to any sequence in public databases. We confirmed the presence of AejapNV1 primary and secondary segments, AejapTV1, AejapAV1, and AejapBV1 by reverse transcriptase polymerase chain reaction (PCR) in wild-caught Ae. japonicus mosquitoes. AejapNV1 and AejapTV1 were found at high prevalence (87–100 per cent) in adult females, adult males, and larvae. Using a small RNA-based, sequence-independent metagenomic strategy, we uncovered a conserved and prevalent virome among Ae. japonicus mosquito populations. The high prevalence of AejapNV1 and AejapTV1 across all tested mosquito life stages suggests that these viruses are intimately associated with Ae. japonicus.The Asian bush mosquito  Aedes genus are responsible for mosquito-borne viral disease outbreaks worldwide. The tropical yellow fever mosquito Aedes aegypti and the invasive Asian tiger mosquito Aedes albopictus pose a large threat to human health by transmitting medically important arthropod-borne (arbo)viruses including Zika virus (ZIKV), chikungunya virus (CHIKV), dengue virus, and yellow fever virus . Although arboviruses are maintained in transmission cycles between arthropods and vertebrate animals or humans, ISVs do not replicate in vertebrates and only infect insects. ISVs can persistently infect mosquito populations and have recently received increasing attention due to their potential effects on host physiology and arbovirus transmission . ExploriA. aegypti and A. albopictus  was discovered in Ae. japonicus from the Netherlands  coding for the RNA-dependent RNA polymerase (RdRp) on the positive strand but also a very long ORF with unknown function on the (reverse complement) negative strand  replication intermediates are recognized and cleaved by Dicer-2, a key protein of the antiviral RNA interference (RNAi) machinery, which results in the production of twenty-one nucleotide (nt) small interfering RNAs (siRNAs) . The forAe. japonicus mosquitoes from populations in the Netherlands and France and identified AejapNV1 and three novel virus species. Interestingly, for AejapNV1, not only the primary genome segment (S1) encoding the RdRp was found, but we also discovered an ambigrammatic secondary genome segment (S2) with unknown function. S2 did not align to any known sequence in public databases. Still, it could be associated with the same virus on the basis of similar (di)nucleotide composition in S1 and S2 and by applying unsupervised clustering techniques using small RNA features generated by our small RNA metagenomic approach. Additionally, we found sequences derived from two putative, novel virus species, and together with the other four discovered viruses, we characterized their genome organisation and small RNA profiles. Finally, reverse transcriptase PCR (RT-PCR) was used to study the prevalence of these viruses in Ae. japonicus adults, larvae, and eggs.In the current study, we applied a small RNA-based metagenomic approach to analyse the virome of wild-caught Aedes japonicus adult female mosquitoes from Strasbourg, France, were collected using human landing catches (HLCs)  Short Read Archive (SRA) under BioProject PRJNA545039 (s (HLCs)  and furtNA545039 . LibrariNA545039 . Note thNA545039 .A. aegypti (AaeL5)  . Plots were generated in R using ggplot2 v3.3.5 package. For manual curation of putative viral contigs, top five BLAST and DIAMOND hits were analysed to rule out the similarity to other organisms; ORF organization and small RNA profiles (size distribution and coverage) were analysed to differentiate exogenous from endogenous viruses and check for inconsistencies. Contigs containing truncated ORFs and small RNA profiles without symmetric small RNA peaks at 21 nt were considered putative EVEs and removed from further analysis as described before (-aS) with 90 per cent of global identity (-c) to remove redundancy. Representative unique contigs from the CD-HIT clustering were used for co-occurrence analysis based on small RNA abundancy in each of the small RNA libraries. A dendogram was generated based on hierarchical clustering of each representative unique contig based on Reads Per Kilobase of transcript per Million reads (RPKM) values of 20 to 22 nt small RNAs aligned to the contigs in each of the four independent libraries. The dendogram was generated in R using Euclidean distance and average method. For small RNA profiles, Z-scores were calculated based on the frequency of each small RNA size from 15 to 35 nt mapped to representative contig considering each strand polarity separately using the library where the contig was originally assembled. Strand polarity for contig comparisons was adjusted based on the reads abundance per strand and coding ORFs direction of each contig. Heatmaps for RPKM and Z-score values were plotted using the package ComplexHeatmap in R  , A. albobopictus , and bacbopictus . Unmappebopictus  and Velvbopictus . More debopictus . Contigsg BLAST+  and againsitive) , consided before . Curatedd before  requirinmap in R . As an amap in R , contigsmap in R  with theZ-score. A–U enrichment for first and tenth positions of 24-29 nt long reads was observed by filtering these reads after alignment to viral sequences and plotting sequence logos using the ggseqlogo R package . Searches for potential homologous viral sequences were performed using Blastx against the nr database. Coding sequences were translated to amino acids, and multiple sequence alignments were performed using the software multiple alignment using fast Fourier transform  ratios of viral and unknown sequences were determined using the function Composition Scan within SSE version 1.4 .Narnavirus RNA sequences were aligned using MUSCLE version 3.8.1551 . NarnaviPrimary structure physical–chemical properties were determined using ProtParam software . Global Ae. japonicus mosquitoes were collected in Lelystad, the Netherlands using oviposition traps, water reservoirs in local rain barrels and HLCs as described (Culex pipiens (biotype pipiens) was used as negative control for the RT-PCR analyses. Culex pipiens mosquitoes collected in Wageningen, the Netherlands, during the summer of 2020, were used to establish a laboratory colony as previously described  in combination with 0.5 mm zirconium oxide beads  or 0.9–2.0 mm stainless steel beads  at maximum speed for 2 min. Afterwards, homogenates were centrifuged at maximum speed in an Eppendorf 5424 centrifuge for 1 min. Pellets were resuspended in 450 μl lysis buffer from the innuPREP DNA/RNA Mini Kit  and subsequently incubated for 20 min to lyse. RNA was isolated using the innuPREP DNA/RNA Mini Kit  according to the manufacturer’s instructions. RNA yields were measured using a NanoDrop ND-1000 spectrophotometer.Taq DNA polymerase (Invitrogen) according to the manufacturer’s protocol. In the case of a dsRNA virus, total RNA was subjected to a 5-min incubation step at 95°C prior to the RT-PCR reaction to denature the viral dsRNA. Mosquito total RNA (50 ng) was used as input for RT-PCR, and each virus was amplified using specific primers targeting the viral RdRp sequence  and SuperScript III One-Step RT-PCR System with Platinum sequence . For Aejsequence . To testsequence . The RT-Ae. japonicus, two new small RNA libraries of Ae. japonicus from France (FR_01 and FR_02) were sequenced and two published small RNA libraries of Ae. japonicus from the Netherlands (NL_01 and NL_02) (To assess the collection of viruses found in d NL_02)  were read NL_02) . Librarid NL_02) . Generalnt and nr), contigs were classified into 229 viral, 1,563 non-viral, and 1,477 unknown sequences  larger than 200 nt were assembled from the four individual libraries. A summary of the assembly results is shown in equences . ProportEVEs are often misperceived as viruses in metagenomic studies based on RNA sequencing , and this can overestimate the number of viruses in a given sample. To discriminate sequences derived from viruses and EVEs, we used a previously established analysis pipeline . BrieflyIn an effort to associate different segments that may belong to the same virus, we evaluated co-occurrence of the viral contigs based on small RNA counts in the four libraries as previously reported . In thisAedes anphevirus  . The secphevirus . Two othphevirus . Finallyphevirus . Other cNarnavirus, family Narnaviridae) that had been previously identified as a possible ISV  , Ae. japonicus anphevirus 1 (AejapAV1), and Ae. japonicus bunyavirus 1 (AejapBV1), respectively (Ae. japonicus bunyavirus 2 (AejapBV2) and Ae. japonicus rhabdovirus 1 (AejapRV1) based on the closest reference  . Phylogeectively . Based oectively ; Table 2eference .Phasmaviridae in contrast to AejapBV1 that belongs to the Phenuiviridae family  were very similar to those of the ∼3-kb long AejapNV1 genome sequence coding for the RdRp . TogetheAlphanarnavirus clade contains the prototypical narnaviruses such as Saccharomyces cerevisiae 20S RNA narnavirus (Scer20SNV) and the mosquito-associated narnaviruses containing an rORF. These viruses contain short, complementary runs of G and C nucleotides at their 5ʹ and 3ʹ termini, respectively, and have a conserved RNA stem-loop (SL) structure at their 3ʹ end (Culex narnavirus 1 (CxNV1)   also con (CxNV1) .Ochlerotatus-associated narna-like virus 2 (ONLV2), GenBank KF298284.2; Ochlerotatus-associated narna-like virus 1 (ONLV1), GenBank KF298275.1) and the yeast-infecting Scer20SNV (GenBank NC_004051.1). For all viruses and segments analysed, short runs of G and C nucleotides were present at the 5ʹ and 3ʹ termini , GenBank MW520409.1;  termini . Similar termini , have pr termini , ONLV1 a termini , and Sce termini  and were termini . The preTo the best of our knowledge, the sequence of CxNV1 S2 is the only publicly available second segment sequence of a narnavirus infecting mosquitoes. Despite the similar genomic termini and ambigrammatic coding strategy  Retalla, the S2 Totiviridae during translation of their RdRp  was observed for all three  or two  segmentsde novo assembled viruses were present in field-collected Ae. japonicus, RT-PCR assays were designed using primers targeting the RdRp coding region of AejapNV1, AejapTV1, AejapAV1, or AejapBV1. RT-PCRs with primers targeting S2 of AejapNV1 were also performed to confirm the presence of this putative segment. All four viruses were successfully detected in individual samples and pools of field-collected adult Ae. japonicus females, while they could not be detected in adult Cx. pipiens females that were tested in parallel . Both segments of AejapNV1 were present at very high prevalence (close to 100 per cent) in all tested mosquito samples and the different life stages , which we could confidently associate with the same virus. Small RNA abundancy and size distribution profiles were very similar for both segments, suggesting that they belong to the same virus. Further support comes from the similar CpG and GC content, conserved genomic termini, and unusual ambigrammatic nature of segments S1 and S2. Bisegmented narnaviruses have also been discovered in Plasmodium (Culex mosquito cells, whereas the primary segment could persist in cell culture without the presence of the secondary segment (Ae. japonicus mosquitoes, which is in accordance with previous findings for CxNV1 in wild-caught mosquitoes (Regarding our results on the identification of asmodium , in a trasmodium , and, veasmodium . For the segment . In our squitoes , thus suDespite some conserved features between AejapNV1 S2 and CxNV1 S2, such as the genomic termini and ambigrammatic ORF structure, these sequences are highly divergent at nucleotide and amino acid sequence levels. Such divergence raises questions about the origin and function of this secondary genome segment. Here we analysed the conservation between polypeptides encoded by AejapNV1 S2 and CxNV1 S2 at the structure levels. Conserved motifs at secondary and tertiary levels between proteins encoded by the fORFs were observed when comparing the presence and synteny of predicted α-helix regions and the core structure predicted by AlphaFold. Interestingly, the rORF of CxNV1 S2 may not encode a functional protein . NeverthAe. japonicus remains enigmatic. Despite the presence of an siRNA profile, we could not clearly associate twenty-one unknown contigs to any defined viral species in this study. Further studies will be necessary to determine if these unknown sequences with the siRNA profile are of viral origin. One possible explanation derives from the lack of a reference genome available for Ae. japonicus, implying that some of those unknown contigs could have originated from unknown repetitive elements in the genome and/or overlapping mRNA fragments that may produce endogenous siRNAs (Still, the origin of a substantial portion of the dark matter present in s siRNAs .Ae. japonicus. However, we could not identify a potential L segment encoding an RdRp for AejapBV2. Based on previous successful detection of segmented viruses from different families including bunyaviruses using our small RNA-based approach (Phenuiviridae and Phasmaviridae, respectively, which might render complementation or reassortment less likely. In addition, this hypothesis implies that AejapBV2 replication is dependent on the presence of the L segment of AejapBV1, but we could not detect AejapBV1 in our Ae. japonicus NL_02 small RNA library, while AejapBV2 was present (Ae. japonicus.Our small RNA-based approach also pointed to the presence of two distinct bunyaviruses in approach , it is uapproach . Given t present . Future Phasi Charoen–like virus, infecting A. aegypti, and the authors reasoned that the piRNA biogenesis could be linked to ovary tropism (Ae. japonicus. Interestingly, there is a striking difference in the profile of piRNAs produced from Segments M and S of AejapBV1 and AejapBV2, which suggests that these viruses infect different tissues in the mosquito (Remarkably, AejapBV1, AejapBV2, AejapAV1, and AejapRV1 produced abundant piRNAs with strong signals of a ping-pong mechanism. Notably, not all viruses induce the production of piRNAs during infection in mosquitoes . A simil tropism . It woulmosquito .Ae. japonicus from the Netherlands indicated a high prevalence of AejapNV1 and AejapTV1 across all tested mosquito life stages, suggesting efficient transmission of these viruses, possibly vertically. Such a phenomenon was described for narnaviruses discovered in fungi (Ae. japonicus mosquitoes harboured AejapNV1 (Screening of wild-caught in fungi  and nemain fungi , for whiAejapNV1 .Ae. japonicus mosquitoes from the Netherlands and France. This indicates a high stability of the virome across mosquito populations, which has also been observed for other mosquito species (Ae. japonicus despite active antiviral RNAi responses, hence suggesting that these viruses should be considered important constituents of the biology of Ae. japonicus mosquito populations.In our study, AejapNV1, AejapTV1, AejapAV1, AejapBV1, and AejapBV2 were all detected in  species , and mayAe. japonicus, a species that can transmit multiple arboviruses and has become increasingly prevalent in North America and Europe. We discovered a highly diverse virome in Ae. japonicus with viruses from at least five families: Narnaviridae, Totiviridae, Xinmoviridae, Phenuiviridae, and Phasmaviridae. We showed a collection of viruses not only diverse at the sequence level but also in RNAi responses generated by Ae. japonicus, providing the basis for future studies to elucidate the immune mechanisms involved in dealing with multiple viral infections. By discovering and characterizing AejapNV1 S2, we showed the strength of our small RNA-based approach to access the ‘viral dark matter’ of insect metagenomes. Beyond associating a highly divergent viral genomic segment with a single virus, we provided evidence that it replicates in the host by showing its siRNA signature. Our study establishes solid ground to explore whether these resident viruses could impact arbovirus transmission by Ae. japonicus. Infection with these likely ISVs might add yet another complex variable to the risk assessment of arbovirus outbreaks caused by Ae. japonicus, and future studies are needed to dissect the role of the virome in arbovirus transmission.This study uncovered the virome of the invasive Asian bush mosquito vead041_SuppClick here for additional data file.


To verify the healthy immigration effect on self-rated health (SRH) among Chinese internal migrants, identify the determinants of SRH, and provide recommendations for the Chinese government to formulate effective intervention strategies to improve population governance and health management in megacities.A sample comprising 1,147 white-and blue-collar migrant workers was randomly selected through an online survey conducted in Shanghai from August to December 2021. Multivariate logistic regression models were used to verify the healthy immigration effect as well as determinants of the effect among internal migrants in Shanghai.p < 0.001), whereas the odds ratio for those who had lived there for ≥10 years was not statistically significant. Additionally, marital status, a postgraduate or higher degree, income level, number of physical examinations in the past 12 months, and the number of critical diseases they were suffering from, were significant contributing factors for favorable SRH among the internal migrants. Furthermore, a cross-sectional analysis revealed that SRH demonstrated a healthy immigration effect among blue-collar internal migrants from the manufacturing industry but not among white-collar internal migrants.Among 1,024 eligible internal migrants, 864 (84.4%) were aged between 18 and 59 years, 545 (53.2%) were men, and 818 (79.9%) were married. When confounders in the logistic regression models were adjusted, the odds ratio of SRH for internal migrants who had lived in Shanghai for 5–10 years was 2.418 (A healthy immigration effect was observed among internal migrants in Shanghai. The migrant population that had lived in Shanghai for 5–10 years had more health advantages than the locals, whereas those who had lived there for ≥10 years did not. The Chinese government should understand this effect and enact measures accordingly, such as implementing physical examinations, improving acculturation, addressing individual characteristics, and improving socioeconomic conditions to improve the physical and mental health of internal migrants. Enacting such changes could facilitate the integration of migrants into the local culture of megacities. For example, according to statistics from the seventh national population census in 2021, the proportion of Shanghai’s population over the age of 60 years was 23.38%, and that over the age of 65 years was 16.28%. Therefore, Chinese cities, especially megacities, urgently require internal migrants to alleviate the so-called brain drain. Because of this need, the migrant population in megacities has gradually increased in recent years. In 2018, approximately 355 million internal migrants were recorded in the four first-tier megacities of Beijing, Shanghai, Guangzhou, and Shenzhen  theory, also known as the epidemiological paradox, migrants tend to have more health advantages than locals. Jasso et al.  evaluateTherefore, with respect to the Chinese population flow, verifying the presence of the HIE is essential. Related studies have focused primarily on HIE among international migrants between countries . Moreove2.2.1.A sample comprising 1,147 white-and blue-collar migrant workers was randomly selected from manufacturing enterprises in Shanghai through a questionnaire posted on the online survey platform “Star,” between August and December 2021. Considering the disadvantages of online surveys  we practiced the following four methods to ensure unbiased representation of the research population and quality of the data:Method 1: The questionnaire set the first filling threshold and the single IP restriction response method. For example, participants were asked whether they were internal migrants or not and whether they had lived in Shanghai for >6 months. Participants replying in the negative would finish the survey, and would be excluded from the study.Method 2: A respondent-driven sampling technique was applied to collect data. Respondent-driven sampling combines the snowball sampling method with the method of assigning weights to samples. This type of sampling incentivizes respondents  to recommend a specific number of peer groups, thereby reducing sampling bias through multiple recommendations of seeds.Method 3: To encourage participants to actively fill in the questionnaire, electronic WeChat red envelopes (a form of cash bonus) were issued immediately after survey completion, to improve the response rate and control the data quality simultaneously.Method 4: As the data collection progressed, a dynamic monitoring method was adopted to consistently identify groups that did not meet the conditions, or those whose proportion was too high even though they did meet the conditions, so that the questionnaire distribution channels could be adjusted timely and accordingly.The online questionnaire consisted of 47 questions that were required to be answered using a single IP address. Respondents were excluded if (i) they were under the age of 18 years, (ii) completed the survey in <200 s, (iii) provided duplicate answers or followed similar answer patterns, (iv) missed 5% or more values, or (v) provided answers with logical errors.Due to the possibility of information leaks, the respondents’ real names, contact details, and other private information was not sought. The questionnaire for this study was based on a literature review and contained variables such as (i) demographic and socioeconomic characteristics ; (ii) use of health-care options ; and (iii) health-related profile, including health status , and numbers of chronic diseases (disease І) or critical diseases (disease II) they are currently suffering from.This study was conducted in compliance with the Shanghai University of Medicine and Health Sciences Institutional Review Board for the Protection of Human Subjects . All participants provided written informed consent.2.2.Based on expert consultations and data derived from previous literature , the durHealth-care use was measured based on the frequency of physical examinations and physician visits in the past 12 months, and the preferred health-care institution. Frequencies were answered using a 4-point Likert scale ; higher the score, more frequently had the participant used health-care services. The preferred type of health-care institution was dichotomized into hospitals and primary care institutions.Health status was measured using a revised version of the 12-item Short Form Survey that was developed previously  and cons“Disease І” consisted of ten common chronic health conditions, namely asthma, back pain, hypertension, hyperlipidemia, diabetes, allergies, migraine, ulcers, bronchial inflammation, and arthritis . These c2.3.t-test and one-way analysis of variance (ANOVA) to identify statistically significant differences between the study groups. Additionally, Pearson’s correlation analysis was performed to test linear relationships between continuous variables. Statistically significant covariates from the one-way ANOVA and t-tests were retained for subsequent multivariate logistic regression analysis.The Kolmogorov–Smirnov (K–S) test was conducted to test the normality of the data and was followed by a descriptive analysis of the demographic and socioeconomic characteristics, health-care use, and disease types. We then conducted an independent sample To determine the HIE, we verified whether an internal migrant participating in the study had a more favorable SRH than a local resident. Because age , sex 1919, maritp-value and Akaike information criterion for subsequent comparisons. To identify the goodness of fit and predictability of the model, we used the receiver operating characteristic curve and area under the receiver operating characteristic curve (AUC) index. The results are presented as adjusted odds ratios (ORs).To assess whether a predictor had a confounding effect, a difference of 20% or more in the coefficients of number of years of residence was used as the cut-off point. Effect modifications were investigated by examining all possible two-way interactions for the main variable of interest, and including predictors and confounders in the main effect model. Each interaction was assessed according to its 2.4.p-value < 0.05 indicated statistical significance.All statistical analyses were conducted using Stata, version 15.0 . A two-tailed 3.3.1.n = 503, 49.1%) of the respondents earned between CNY 110,000 and CNY 250,000  of the respondents were 18–39 years old, 545 (53.2%) were men, and 818 (79.9%) were married. A total of 827 (80.8%) respondents were university-educated, and 761 (74.3%) had employee medical insurance. Regarding annual income distribution, most , marital status , number of years of residence , educational level , industry type , annual income , number of physician visits in the past 12 months , number of physical examinations in the past 12 months , number of “disease І” , and number of “disease II”   .3.3.According to the results of the multicollinearity test, the variance inflation factor index score of each significant independent variable in the multivariate logistic regression model was found to be between 1.06 and 1.29, indicating no multicollinearity.p < 0.001) (p < 0.001). Therefore, regarding SRH, internal migrants who had lived in Shanghai for <10 years were 1.891 times more likely to report favorable health compared with locals. However, the OR of SRH for internal migrants who had lived in Shanghai for ≥10 years was not significant. Additionally, among the statistically significant covariates, the OR of favorable SRH among those aged 40–60 years was 0.642 (p < 0.05), which indicated that the OR of favorable SRH in internal migrants decreases with age. Further, internal migrants in Shanghai who were married were 2.103 times more likely to report favorable SRH than unmarried migrants (p < 0.001). The ORs of obtaining an undergraduate or a postgraduate (or higher) degree were 2.283 (p < 0.01) and 2.797 (p < 0.01), respectively, which indicated that better-educated internal migrants in Shanghai were more likely to report favorable health. Similarly, those with an annual income between CNY 110,000 and CNY 250,000 were 1.989 times (p < 0.001) more likely to report favorable health compared with those with an annual income of CNY 100,000 or less.According to the results of the unadjusted model 1, the OR of <10 years of residency was 3.884 (< 0.001) . Similarp < 0.001), indicating that internal migrants who had lived in Shanghai for <10 years were 1.684 times more likely to report favorable health than Shanghai locals. Similar to the case in model 1, the OR of living in Shanghai for ≥10 years was not significant. Furthermore, the ORs of favorable SRH were 1.971 (p < 0.001), 2.092 (p < 0.01), and 2.514 (p < 0.05) for internal migrants who had undergone one, two, and three physical examinations, respectively, in the past 12 months. These results indicate that favorable SRH increases with the number of physical examinations undergone by the internal migrants.In model 3, when the demographic and socioeconomic covariates, and health-care use were controlled, the OR of living in Shanghai for <10 years was 2.684 (p < 0.001), indicating that internal migrants who had lived in Shanghai for <10 years were 1.418 times more likely to report favorable health than Shanghai locals. However, the OR of living in Shanghai for ≥10 years was not statistically significant (p > 0.10). Additionally, the OR of favorable SRH among the respondents with one or more critical diseases was 82.4% lower than that of those with no critical diseases . Regarding the adjusted covariates in models 2 and 3, marital status, education at graduate level or above, annual income between CNY 110,000 and CNY 250,000, and number of physical examinations in the past 12 months were all significantly associated with a favorable SRH.In model 4, as in model 3, when the covariate of the number of diseases was controlled, the OR of <10 years of residency was 2.418 (p < 0.012), indicating that blue-collar internal migrants were 7.068 times more likely to report favorable SRH compared with locals. Conversely, no HIE was observed among white-collar migrant workers, which indicated that such workers did not benefit from Shanghai residency in a similar manner , followed by model 3 (AUC = 0.7070), model 2 (AUC = 0.6948), and model 1 (AUC = 0.5891). Further, data fitting revealed that the Akaike information criterions of models 1, 2, 3, and 4 were 929.285, 844.247, 846.8031, and 814.554, respectively . Therefo4.This study analyzed the HIE theory for internal migrants in a megacity and found that migrants had a health advantage over native locals. However, this health advantage did not apply to those who had lived in Shanghai for >10 years. Additionally, marital status, educated with a graduate degree or above, an annual income of CNY 110,000–250,000, number of physical examinations undergone in the past 12 months, and number of critical diseases they were suffering from, had significant effects on SRH.The results of this study showed that when confounding variables were controlled, internal migrants who had lived in Shanghai for 5–10 years were 2.418 times more likely to report good health than Shanghai locals; this finding supported the HIE theory and was consistent with that of other studies . For exaFurther, in this study, the OR of SRH for internal migrants who had lived in Shanghai for >10 years was not significant; this finding suggests that the health advantages of the HIE among internal migrants gradually decline over time. This decline may be caused by acculturation and the persistent effect of the local environment as well as a cumulative exposure to it , 41. TheTherefore, the government should enact measures that consider the length of residency, for example, by attaching more importance to number of years of residency and employment in the point-based hukou household registration system, promoting the urbanization of migrants, and providing more public services and social security to permanent residents of Shanghai. Moreover, popularizing the Shanghainese dialect among migrants, promoting the integration of their hometown dialects with the local dialect, and providing regular mental health counseling are also necessary.Furthermore, other covariates were significantly associated with SRH among internal migrants, including being married, having a graduate degree or above, having an annual income between CNY 110,000 and CNY 250,000, receiving more than one physical examination in a year, and having one or more critical diseases. These findings are consistent with those of other studies regarding SRH , 45, 46.Finally, according to the findings of this study, the HIE is not applicable to white-collar migrants. White-collar workers in megacities like Shanghai may face more workplace competition and daily stress compared with workers in other industries, which ultimately affects their physical and mental health. According to a report published in 2020, 94% of a sample of white-collar workers suffered from chronic diseases . A whiteThis study had some limitations. Firstly, data for the study were collected from a specific manufacturing industry; thus, the results might not be extendable to other industries. Secondly, only SRH was used to verify the HIE; although SRH is undeniably a well-validated health measure  that hasIn conclusion, this study analyzed the HIE theory and applied it to evaluate SRH. Compared with Shanghai locals, internal migrants initially had more favorable SRH; however, these health advantages gradually diminished as the duration of residency increased. Thus, the Chinese government should carefully consider the heterogeneity of SRH among internal migrants and their length of residency to formulate appropriate policies and health promotion programs. In particular, the government should factor in the less favorable SRH of migrants who have lived in Shanghai for >10 years. Improvements to physical screening technology, promotion of healthy habits, and facilitation of integration should also be considered. Finally, some community-based psychological interventions may be necessary to address mental health, alleviate cumulative exposure to the local environment, and improve socioeconomic and working conditions for internal migrants, especially white-collar workers.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Shanghai University of Medicine and Health Sciences Institutional Review Board for the Protection of Human Subjects. The patients/participants provided their written informed consent to participate in this study.ED, TX, ZL, and CH designed the study and acquired the data and developed the statistical plan. JS and DB carried out the survey. ED and TX performed the statistical analysis. ED, TX, ZL, HZ, and CH interpreted the analysis. ED, TX, ZL, and CH drafted and revised the manuscript. All authors contributed to the article and approved the submitted version.This research was funded by National Social Science Foundation of China General Project (Grant No. 19BGL246) and National Social Science Foundation of China Major Project (Grant No. 18ZDA088).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.