Identification and functional analysis of circular RNAs during mitochondrial damage induced by infectious bovine rhinotracheitis virus infection in Madin–Darby bovine kidney cells

Identification and functional analysis of circular RNAs during mitochondrial damage induced by infectious bovine rhinotracheitis virus infection in Madin–Darby bovine kidney cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification and functional analysis of circular RNAs during mitochondrial damage induced by infectious bovine rhinotracheitis virus infection in Madin–Darby bovine kidney cells Yingcai Ma, Jiaxin Liu, Lianping Xu, Qin He, Heqi Lv, Zelong Li, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6754910/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Oct, 2025 Read the published version in BMC Genomics → Version 1 posted 10 You are reading this latest preprint version Abstract Background : Infectious bovine rhinotracheitis virus (IBRV), a member of the Herpesviridae family, causes infectious bovine rhinotracheitis (IBR) and induces mitochondrial dysfunction in host cells. Circular RNAs (circRNAs)—a novel class of non-coding RNAs—have been implicated in various biological processes and pathologies related to mitochondrial damage. However, their role in IBRV-induced mitochondrial damage in Madin-Darby bovine kidney (MDBK) cells remains unclear. Results : Transmission electron microscopy(TEM), laser confocal microscopy, and flow cytometry confirmed that IBRV infection causes mitochondrial damage in MDBK cells. High-throughput sequencing revealed 144 differentially expressed (DE) circRNAs, 725 messenger RNAs (mRNAs), and 160 microRNAs (miRNAs) in IBRV-infected cells. We predicted that DE circRNAs regulate mitochondrial damage via source genes, circRNA-miRNA-mRNA networks, and RNA-binding proteins (RBPs). Source genes were enriched in mitochondria-related pathways like the mammalian target of rapamycin (mTOR), thyroid hormone, and Hippo signalling; 11 genes were localized to mitochondria. CircRNA-miRNA-mRNA network target genes were associated with cellular senescence, mitophagy, and ubiquitin-mediated proteolysis; 471 genes were linked to mitochondria. Additionally, 961 RBPs were enriched in pathways like nucleocytoplasmic transport and RNA degradation; 107 RBPs were localized to mitochondria. Functional validation revealed knockdown of circ_002584 reduced reactive oxygen species (ROS) accumulation ( p < 0.05) and mitochondrial membrane potential depolarization ( p < 0.05). Knockdown of circ_004326 increased both ( p < 0.01). Conclusions : CircRNAs play a regulatory role in IBRV-induced mitochondrial damage within MDBK cells. This finding is significant for virus-associated mitochondrial damage research, forming a theoretical foundation for utilizing circRNAs as diagnostic biomarkers and potential therapeutic targets for IBR. Infectious bovine rhinotracheitis virus (IBRV) Circular RNAs (circRNAs) MicroRNA (miRNA) RNA binding proteins of circRNA (circRNA-RBP) circ_002584 circ_004326 mitochondrial damage Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Background Infectious bovine rhinotracheitis virus (IBRV) can cause a highly contagious respiratory disease called bovine herpesvirus 1 (BoHV-1). In the subfamily Alphaherpesvirinae of the Herpesviridae family, IBRV infection can cause various clinical manifestations, including rhinotracheitis, vulvovaginitis, and conjunctivitis, in cattle ( 1 , 2 ). Like other alphaherpesviruses, IBRV establishes lifelong latent infection in the trigeminal ganglia of infected hosts following acute infection, from which it can be periodically reactivated and transmitted ( 3 – 5 ). Current efforts for elimination of IBRV infections are focused on vaccine development ( 6 – 8 ), and relatively few studies have focused on the pathogenicity mechanisms of IBRV. The mitochondrion is an energy factory and key regulator of cell death signalling that provides approximately 95% of the energy required for the basic activities of the cell ( 9 , 10 ). Virus-induced cytopathic effects are associated with mitochondrial dysfunction ( 11 , 12 ). Influenza A virus (IAV) infection induces mitophagy, and the IAV PB1-F2 protein translocates to mitochondria by interacting and colocalising with mitochondrial Tu translation elongation factor to accelerate mitochondrial fragmentation ( 13 ). The classical swine fever virus is one of the most harmful pathogens in swine, and the expression of classical swine fever virus NS5A protein can induce membrane potential loss and mitochondrial fission, as well as increase the expression level of reactive oxygen species (ROS) to promote mitochondrial damage ( 14 ). Duck Tembusu virus is a pathogenic flavivirus. A previous study reported that duck Tembusu virus infection causes the release of mitochondrial cytochrome C and downregulation of the apoptosis-inhibiting protein BCL−2, which reduces mitochondrial membrane potential (MMP) and results in the accumulation of intracellular ROS to regulate mitochondrial-mediated apoptosis ( 15 ). Furthermore, study have confirmed that IBRV-induced oxidative stress can contribute to mitochondrial dysfunction in MDBK cells ( 16 ). IBRV infection can also promote intracellular mitochondrial damage ( 17 ). Our previous study confirmed that IBRV infection of MDBK cells induces mitochondrial damage ( 18 ). Nevertheless, the underlying molecular mechanisms have not been clarified. CircRNAs are a newly recognised class of special noncoding RNA molecules that mainly consist of endogenous RNA molecules formed by exon transcripts and nonlinear reverse splicing, as well as circRNA molecules containing introns ( 19 ). Most of the circRNAs are covalently connected with each other by the 3', 5'-phosphodiester bond without a polyadenylated tail ( 20 ). CircRNAs function in several ways, including serving as competing endogenous RNA (ceRNA) ( 21 ), regulating transcription and splicing of their source genes ( 22 ), interacting with RNA binding proteins ( 23 ), and being translated into proteins ( 24 ). Because circRNAs are insensitive to nuclease, and thus more stable than linear RNA, they have an obvious advantage in the development and application of new clinical diagnostic markers ( 25 ). Accumulating evidence indicates that some circRNAs play an important role in the process of mitochondrial damage ( 26 , 27 ). For example, circSamd4 was reported to be involved in antioxidant response during cardiac regeneration, reducing oxidative stress generation by inducing the mitochondrial translocation of the Vcp protein, as well as downregulating Vdac1 expression and preventing the mitochondrial permeability transition pore (mPTP) from opening ( 20 ). In the pathological process of osteoarthritis (OA), circFAM160A2 was reported to target miR−505−3p and SIRT3, which can reduce mitochondrial stabilisation and apoptosis via the circFAM160A2-miR−505−3p-SIRT3 axis ( 28 ). In recent years, an increasing number of studies have found that circRNAs can participate in the regulation of host cell immune response and virus replication during viral infection ( 29 – 31 ). Coxsackievirus B5 (CVB5) infection can change the expression profiles of circRNAs in SH-SY5Y cells, among which hsa_circ_0008378 and novel_circ_0014617 can upregulate the key factors in the Activation of the type I interferon (IFN-I) signalling pathway, hampering viral replication ( 32 ). Bovine viral diarrhoea virus (BVDV) infection can change the expression profiles of circRNAs in MDBK cells, and the host genes of DE circRNAs have been reported to be involved in the regulation of cell proliferation, apoptosis, and viral infection-related signalling pathways ( 33 ). Additionally, senecavirus A (SVA) infection has been reported to change the expression profiles of circRNAs in porcine kidney 15 (PK−15) cells, among which circ_8521 was significantly upregulated in SVA-infected PK−15 cells, which promoted the expression of LC3A by binding to miR−324, thereby promoting SVA infection ( 34 ). Transmissible gastroenteritis coronavirus (TGEV) infection has been reported to provoke circEZH2 downregulation in the porcine intestinal epithelial cell line (IPEC-J2), which can target miR−22 to provoke mitochondrial damage in IPEC-J2 via the circEZH2/miR-22/HK2 axis and circEZH2/miR−22/IL−6/NF-κB axis ( 35 ). In our previous study, we demonstrated that IBRV infection can provoke mitochondrial damage in MDBK cells ( 18 ). However, it remains unclear whether circRNAs participate in the IBRV-induced process of mitochondrial damage in MDBK cells. In the current study, we performed high-throughput sequencing at 24 h of IBRV infection of MDBK cells and screened for circRNA associated with mitochondrial damage by predicting and analysing circRNA source genes as well as circRNA-RBP and circRNA-miRNA-mRNA networks. Additionally, we performed mitochondrial damage functional validation on two circRNAs (circ_002584 and circ_004326) that were indicated by screening to be associated with mitochondria. The current findings provide novel insight to inform further exploration of the mechanisms of circRNA in the process of virus infection-induced mitochondrial damage. Results IBRV infection induced mitochondrial damage in MDBK cells To test whether IBRV infection caused mitochondrial damage in MDBK cells, we examined morphological changes in the mitochondria of MDBK cells upon infection with IBRV. The electron microscopy results showed that the mitochondria in infected MDBK cells swelled and became deformed, mitochondrial cristae fragmentation (Fig. 1a). In addition, we used a DCFH-DA probe to assess the accumulation of ROS in MDBK cells. The fluorescence intensity of the DCFH-DA, as measured by laser confocal microscopy and flow cytometry, significantly increased after IBRV infection (Figs. 1b, c), suggesting that IBRV increased the accumulation of ROS. Next, to investigate the impact of IBRV on MMP, the level of MMP depolarisation was tested using the JC-1 probe. The results revealed that IBRV infection reduced the red/green signal ratio, suggesting that IBRV increased the depolarisation of MMP (Figs. 1d, e). Overview of high-throughput sequencing data To determine whether IBRV infection could alter the expression profiles of mRNA, circRNA, and miRNA, high-throughput sequencing was performed. MDBK cells were infected with 1.5 Multiplicity of infection (MOI) IBRV for 24 h (IBRV), and normal MDBK cells were used as a control (Mock). In the Mock group and the IBRV group, a total of 4,367 circRNAs were identified. Annotations for all circRNAs identified in this study are shown in additional file 1: Table S1. We classified these circRNAs into six categories: annot_exons circRNAs (3011, 64.52%), one_exon circRNAs (324, 64.52%), exon_intron circRNAs (498, 64.52%), intronic circRNAs (157, 64.52%), intergenic circRNAs (223, 64.52%), and antisense circRNAs (154, 64.52%). Among these types, exonic circRNAs predominated (Fig. 2a). The size of these circRNA candidates ranged from less than 85 nt to greater than 3,000 nt, with most ranging from 200 nt to 800 nt. The majority of circRNAs contained 1-5 exons (Figs. 2b, c). The analysis of circRNA origin across chromosomes indicated that chromosomes 1, 3, 5, and 11 generated more circRNAs compared with other chromosomes (Fig. 2d). Moreover, the analysis of mRNA expression profiles identified 21,730 mRNAs, 78 of which were newly discovered miRNAs (novel_mRNAs) (Fig. 2e, Additional file 2: Table S2). The analysis of mRNA and miRNA expression profiles revealed that 2,022 miRNAs were identified, the length of which was concentrated at 21 nt-24 nts (Fig. 2f); among these miRNAs, 602 were extant miRNAs (exist_miRNA), 749 were known miRNAs (known_miRNA), and 671 were newly discovered miRNAs (novel_miRNA) (Fig. 2g, Additional file 3: Table S3). Screening for DE circRNAs, mRNAs, and miRNAs in MDBK cells during IBRV infection To screen the DE circRNAs, mRNAs, and miRNAs, we performed expression profiling to show circRNA, mRNA, and miRNA variations in MDBK cells during IBRV infection. The results revealed that 144 DE circRNAs in the IBRV group were differentially regulated compared with the Mock group ( p < 0.05); of these, 83 circRNAs were upregulated and 61 circRNAs were downregulated (Figs. 3a, b. Additional file 4: Table S4). Compared with the Mock group, 725 differentially expressed mRNAs (DE mRNAs) in the IBRV group were identified as being differentially regulated by a false discovery rate 1. Among these, 528 DE mRNAs (518 known mRNA, 10 novel mRNA) were upregulated and 197 DE mRNAs (196 known mRNA, 1 novel mRNA) were downregulated (Figs. 3c, d. Additional file 5: Table S5). Compared with the Mock group, 160 differentially expressed miRNAs (DE miRNAs) in the IBRV group were found to be differentially regulated ( p < 0.05). Among these, 93 DE miRNAs (83 existing and known miRNAs, 10 novel miRNAs) were upregulated while 67 DE miRNAs (48 known miRNAs, 19 novel miRNAs) were downregulated (Figs. 3e, f. Additional file 6: Table S6). Functional enrichment analysis of the source genes of DE circRNAs To further explore whether the source genes of DE circRNAs are associated with mitochondrial damage, we obtained 137 source genes of DE circRNAs (Additional file 7: Table S7), which were searched for enrichment analysis in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. GO enrichment analysis revealed that 11 source genes of DE circRNAs were enriched in the mitochondria (Fig. 4a, Additional file 7: Table S8). KEGG pathway analysis revealed that the source genes of DE circRNAs were involved in mitochondria-related signalling pathways including the mTOR, thyroid hormone, spinocerebellar ataxia, sphingolipid metabolism, neurotrophin, and Hippo signalling pathways (Fig. 4b, Additional file 9: Table S9). Functional enrichment analysis of the target genes of DE miRNAs To further screen for mitochondrial damage-associated DE miRNAs, 6,658 mRNAs (count ³ 500) were screened (Additional file 10: Table S10); 12,574 target genes of DE miRNAs were predicted (Additional file 11: Table S11) and intersected with 6,658 mRNAs (count ³ 500). Subsequently, 5,256 candidate target genes of DE miRNAs were obtained (Fig. 5a, Additional file 12: Table S12). These candidate target genes of DE miRNAs were searched for enrichment analysis via the GO and KEGG databases. GO enrichment analysis revealed that 471 candidate target genes of DE miRNAs were enriched in the mitochondria (Fig. 5b, Additional file 13: Table S13). KEGG pathway analysis revealed that the candidate target genes of DE miRNAs were primarily involved in mitochondria-related signalling pathways, including the cellular senescence, cell cycle, mitophagy, Kaposi sarcoma-associated herpesvirus infection, ubiquitin-mediated proteolysis, and thyroid hormone pathways (Fig. 5c, Additional file 14: Table S14). Construction and analysis of the circRNA-miRNA-mitochondrial-related mRNA network To screen for circRNAs involved in the regulation of mitochondrial damage as ceRNA during IBRV infection, we predicted a targeting relationship between 144 DE circRNAs and 160 DE miRNAs. Among these, 106 circRNAs were negatively correlated with 59 miRNAs. On the basis of the previous prediction regarding the target genes of 160 DE miRNAs, the 59 negatively correlated miRNAs targeted 4,611 mRNAs (Additional file 15: Table S15). GO enrichment analysis revealed that 389 mRNAs were enriched in the mitochondria (Additional file 16: Table S16). A total of 2,563 negatively regulated targeting relationship pairs of circRNA-miRNA (involving 106 circRNAs and 56 miRNAs) and 2,178 targeting relationship pairs of miRNA–mitochondria-related mRNA (involving 56 miRNAs and 389 mitochondria-related mRNAs) were identified in the bioinformatics analysis (Fig 6, Additional file 17: Table S17 and Additional file 18: Table S18). In summary, the results indicated that these DE circRNAs may participate in the IBRV-induced process of mitochondrial damage by serving as miRNA sponges in MDBK cells. CircRNA-RBP interactions Recent studies have reported that circRNA-RBP interactions play important roles in circRNA formation, the regulation of transcription, and viral replication ( 36-38 ). To screen for RBP involved in the regulation of mitochondrial damage as ceRNA during IBRV infection, we predicted the binding relationships between 144 DE circRNAs and 3,982 proteins using the catRAPID algorithm. The predicted results indicated that 141 circRNAs could bind to 961 RBPs (ranking > 0.5) (Additional file 19: Table S19). We then used the genes of 961 RBPs for the GO and KEGG enrichment analyses. GO enrichment analysis revealed that 107 RBPs were enriched in the mitochondria (Fig. 7a, Additional file 20: Table S20). KEGG pathway analysis indicated that 961 RBPs were mainly involved in mitochondria-related signalling pathways, including nucleocytoplasmic transport, the mRNA monitoring pathway, RNA degradation, RNA degradation, endoplasmic reticulum protein processing, and the citric acid cycle (Fig. 7b, Additional file 21: Table S21). Utilising 141 DE circRNAs and 107 RBPs, we constructed a circRNA-RBP network (Fig. 7c, Additional file 22: Table S22). In summary, the results suggest that these DE circRNAs may interact with RBPs to regulate mitochondrial damage in MDBK cells. Identification and localisation of circRNAs To determine the cyclisation of circRNA, according to circRNA sequencing and bioinformatic analysis, two DE circRNAs (circ_002584 and circ_004326) were selected for identification, revealing that a single and distinct product of expected size was amplified using circRNA divergent primers from only cDNA, while there was no target amplification product from gDNA (Figs. 8a, b). Sanger sequencing confirmed the head-to-tail splicing of circ_002584 and circ_004326 (Figs. 8c, d). Meanwhile, we observed significantly reduced glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and unchanged circRNA levels after digestion by RNase R, demonstrating that circ_002584 and circ_004326 were resistant to RNase R and were structurally stable (Fig. 8e). To validate the reliability of high-throughput sequencing, the expression levels of circ_002584 and circ_004326 were measured with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using divergent primers. The results were consistent with those of high-throughput sequencing (Fig. 8f). To further explore the potential function of circRNA in MDBK cells, a fluorescence in situ hybridisation (FISH) assay of circ_002584 and circ_004326 was performed in MDBK cells. The fluorescent signals of circ_002584 and circ_004326 were amplified by the SA-Cy3-Biotin system. The FISH assay results demonstrated that circ_002584 and circ_004326 were mainly localised in the cytoplasm, and small amounts were localised in the nucleus in MDBK cells (Fig. 8g). Thus, circ_002584 and circ_004326 may play important roles in the cytoplasm or nucleus. Functional validation of circ_002584 and circ_004326 To verify whether circ_002584 and circ_004326 play a role in IBRV-induced mitochondrial damage, we silenced circ_002584 and circ_004326 in MDBK cells by specific siRNA transfection, then tested the intracellular levels of ROS and the degree of depolarisation of the MMP. The results revealed that circ_002584 ( p < 0.05) and circ_004326 expression ( p < 0.01) were significantly decreased in MDBK cells post-transfection with the siRNA of circ_002584 and circ_004326 (Figs. 9a, b). Compared with the siRNA negative control group, si-circ_002584 reduced the accumulation of ROS ( p < 0.05) and si-circ_004326 increased the accumulation of ROS ( p < 0.01) (Figs. 9c, d). Meanwhile, compared with the siRNA negative control group, si-circ_002584 reduced the depolarisation of the MMP ( p < 0.05) and si-circ_004326 increased the depolarisation of the MMP ( p < 0.01) (Figs. 9e, f). In summary, these results demonstrate that circ_002584 can promote IBRV-induced mitochondrial damage in MDBK cells and circ_004326 can inhibit IBRV-induced mitochondrial damage in MDBK cells. Discussion IBRV is an animal pathogen with an important impact on the cattle industry. IBRV causes various degrees of clinical signs in cattle, including hyperpyrexia, dyspnoea, nasitis, conjunctivitis, and abortion of pregnancy ( 5 ). In many cases, IBRV establishes a latent infection in the trigeminal ganglia, and the virus is carried throughout life. Eradicating viral diseases is difficult, resulting in severe economic losses for cattle industries worldwide ( 39 ). However, few studies have investigated the pathogenic mechanisms of the virus. Mitochondria are the main source of cellular energy, and mitochondrial biogenesis is critical for mitochondrial homeostasis and intracellular physiological demands ( 40 ). Recently, viral infection was reported to cause damage to mitochondrial macromolecules, affecting mitochondrial function ( 41 ). Impaired mitochondria typically undergo structural changes and exhibit clear mitochondrial dysfunction ( 42 ), such as circEZH2 co-regulating TGEV-induced mPTP opening through both circEZH2/miR−22/HK2 and circEZH2/miR−22/IL−6/NF-κB pathways by targeting miR−22, which in turn protects mitochondrial function ( 35 ). Pathogenicity of porcine deltacoronavirus infection stimulates mitochondrial outer membrane permeabilisation through Bax recruitment or mPTP opening, leading to the release of apoptotic cytochrome c into the cytoplasm, which activates the caspase-dependent intrinsic apoptotic pathway and promotes viral replication in vitro ( 43 ). Hantavirus can inhibit apoptosis by preventing MMP loss through upregulation of the pro-survival factor BCL−2 ( 44 ). In addition, IBRV infection of MDBK cells can cause changes in intracellular miRNA expression profiles, where miR−10a and miR−182 affect mitochondrial function by altering mPTP and MMP levels ( 45 ). In the present study, we observed mitochondrial swelling and cristae rupturing in IBRV-infected MDBK cells via transmission electron microscopy (TEM) and detected the ROS level and the depolarisation of MMP in IBRV-infected MDBK cells via flow cytometry and confocal microscopy after infecting MDBK cells with IBRV. The findings confirm that IBRV infection can induce mitochondrial damage in MDBK cells. The current findings suggest new possibilities for studying the mechanisms of pathogenicity of IBRV-induced mitochondrial damage. Viral infection usually causes changes in the expression profile of non-coding RNA ( 46 ). For example, a total of 123 circRNAs, 523 mRNAs, and 65 miRNAs were identified in TGEV infected-intestinal porcine epithelial cell-jejunum 2 (IPEC-J2) cells, and these DE mRNAs were mainly enriched in the Nucleotide oligomerization domain (NOD)-like receptor, Janus kinase/signal transducer and activator of transcription (Jak-STAT), Tumor necrosis factor (TNF), and Retinoic Acid-inducible Gene-I (RIG-I)-like receptor pathways ( 47 ). In another study, 636 circRNAs were identified in the brains of mice that were infected with the rabies virus (RABV), of which 426 were significantly upregulated and 210 were significantly downregulated; these source genes of circRNA were enriched in the cGMP-PKG and MAPK signalling pathways ( 48 ). A total of 19,118 circRNAs were identified in BVDV-infected MDBK cells, and these DE circRNAs were mainly enriched in the cell proliferation, apoptosis, cycle, and viral infection-related pathways ( 49 ). To investigate the role of circRNAs in the process of IBRV-induced mitochondrial damage in MDBK cells, we obtained and analysed mRNA, circRNA, and miRNA expression profiles that were differentially expressed before and after IBRV infection via high-throughput sequencing data, and 725 DE mRNAs, 144 DE circRNAs, and 160 DE miRNAs were screened. GO enrichment analysis of DE mRNA, source genes of circRNA, and target genes of miRNA were point to mitochondrion. KEGG enrichment results indicated that enriched pathways were mainly mitochondrial function-related, including the mTOR, Hippo, nucleocytoplasmic transport, endoplasmic reticulum protein processing, and citric acid cycle signalling pathways. Additionally, using a bioinformatics approach, the circRNA-miRNA-mRNA network and circRNA-RBP network were constructed and the coding ability of circRNA was predicted. The results indicated that these DE circRNAs may have the potential to act as an miRNA sponge or binding RBP or translating protein in the IBRV-induced process of mitochondrial damage. A previous study reported that the function of circRNAs is closely associated with their localisation in the cells ( 50 ). CircRNAs localised in the nucleus can function as modulators of transcription of their host genes to regulate the transcription of genes ( 51 ). For example, circERBB2 has been reported to regulate nucleolar localisation of PA2G4, thereby, via the circERBB2-PA2G4-TIFIA regulatory axis, to regulate ribosomal DNA transcription ( 52 ). Another study reported that circ-DONSON was co-localised with SOX4 promoter in the nucleus and that circ-DONSON regulated SOX4 transcription to promote cell apoptosis to influence the progression of gastric carcinogenesis ( 53 ). Circ-CTNNB1 has been reported to exist in the nucleus, and Circ-CTNNB1 has been found to bind DEAD-box polypeptide 3 (DDX3) to promote its binding with transcription factor Yin Yang 1 (YY1), leading to the transcriptional alteration of downstream genes associated with key proteins ( 54 ). In addition, circRNA localised to the cytoplasm has been found to be involved in numerous physiological and pathological processes by acting as an miRNA molecular sponge, binding to RBP and pathways such as translation proteins ( 55 ). For example, circIgfbp2 has been found to sponge miR−370−3p and regulate mitochondrial dysfunction after traumatic brain injury via the miR−370−3p/BACH1/HO−1 axis ( 56 ). Circ−0088300 has been reported to be capable of physically interacting with RBP BOLL to regulate mitochondrial metabolic reprogramming, thereby promoting gastric cancer growth and metastasis ( 57 ). During spermatogenesis, rsrc1−161aa encoded by circRsrc1 interacted with mitochondrial protein C1qbp and enhanced its binding activity to mitochondrial mRNAs, thereby affecting the translation of oxidative phosphorylation (OXPHOS) proteins to prevent the accumulation of ROS and promote cell-cycle progression ( 58 ). In the current study, we first verified the ring-forming status of the selected circ_002584 and circ_004326. We then used PCR, gel electrophoresis, and Sanger sequencing to confirm the characteristics of the backspaced site and subsequently verified its stability with RNase R. Compared with linear RNA molecules, circ_002584 and circ_004326 were more stable and less prone to degradation in MDBK cells. The expressions of circ_002584 and circ_004326 were significantly elevated in IBRV-infected MDBK cells, consistent with the high-throughput sequencing results. The cellular localisation results showed that circ_002584 and circ_004326 were distributed in the cytoplasm and nucleus. These findings suggest that circRNAs may play important roles in regulating viral replication and mitochondrial function by interacting with miRNAs or RBPs. CircRNAs are involved in regulating the relationship between the virus and the host. Previous studies have reported that BVDV infection can cause changes in circRNA expression profiles, and the host genes of DE circRNAs have been found to be involved in the regulation of viral infection-related signalling pathways ( 33 ). CircMerTK has been reported to exhibit significantly altered expression levels following IAV infection, and overexpression and silencing have been found to accelerate and impede IAV virus replication, respectively ( 50 ). CircEZH2 has been found to exhibit significant downregulation during TGEV infection, regulating the mPTP opening via the circEZH2/miR−22/HK2 axis and circEZH2/miR−22/IL−6/NF-κB axis ( 35 ). In the current study, our prediction results indicated that the source genes, miRNAs, mRNAs, and the RBPs of DE circRNAs are associated with mitochondria. Meanwhile, we constructed circRNA-miRNA-mRNA and circRNA-RBP interaction networks using bioinformatics analysis. The results indicate that circ_002584 and circ_004326 are localised in the cytoplasm and nucleus. Functional studies of circ_002584 and circ_004326 have shown that interfering with the expression of circ_002584 significantly reduces ROS accumulation and MMP depolarisation, whereas interfering with the expression of circ_004326 significantly increases ROS accumulation and MMP depolarisation. These results provide preliminary evidence that circ_002584 can promote IBRV-induced mitochondrial damage, whereas circ_004326 can inhibit IBRV-induced mitochondrial damage. Thus, circ_002584 and circ_004326 may be involved in the process of IBRV-induced mitochondrial damage in MDBK cells. Our study provides novel insight into the molecular mechanisms of IBRV-induced mitochondrial damage, including the source genes of circRNAs, miRNA sponges, and the circRNA combination with RBPs. However, further investigation is needed to elucidate the specific mechanisms underlying the involvement of circ_002584 and circ_004326 in IBRV-induced mitochondrial damage. Conclusions The results indicate that DE circRNAs might be involved in mitochondrial damage induced by IBRV through the source genes of the circRNAs, ceRNAs, and circRNA-RBP networks. circ_002584 can promote IBRV-induced mitochondrial damage, and circ_004326 can inhibit IBRV-induced mitochondrial damage. The current findings provide evidence for circ_002584/circ_004326 as a new molecular target for the clinical diagnosis of and therapy for IBR. Methods Cells, virus, and primers In the present study, MDBK (NBL-1) cells purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China) were cultured in Dulbecco’s Modified Eagle Medium (Biological Industries, Beit Haemek, Israel) supplemented with 100 IU of penicillin and 100 mg of streptomycin per millilitre at 37°C in an incubator with 5% CO 2 . All experiments were performed with cells between passages 4 and 8. The IBRV AV21 strain was purchased from the China Institute of Veterinary Drug Control (Beijing, China). Primers of circRNAs were synthesised by the Shanghai Sangon Biological Engineering Technology Company Limited (Shanghai, China). The siRNAs of circRNAs were synthesised by GenePharma (Shanghai, China). The sequences are shown in additional file 23: Table S23 . Detection of mitochondrial damage indicators after IBRV infection of MDBK cells First, mitochondrial structural changes were observed using TEM before and after IBRV infection of MDBK cells. Briefly, the monolayer of MDBK cells infected with IBRV or Mock were fixed in situ for 24 h with a mixture of 2.5% glutaraldehyde and 2% formaldehyde in PBS (pH 7.2) for 6 h at room temperature and postfixed with 1% osmic acid for 4 h at 4°C. After dehydration and infiltration, embedding, ultrathin sectioning, and staining were performed. All sections were observed and photographed using a transmission electron microscope (HITACHI, Japan). Second, ROS generation was determined according to the manufacturer’s instructions using an ROS assay kit (Beyotime, Shanghai, China). Briefly, each sample was treated with 1 µl of DCFH-DA probe (10 µM) for 20 min at 37°C and the samples were mixed at 5 min intervals. Fluorescence was measured with laser confocal microscopy and flow cytometry, collecting 10,000 events. Additionally, MMP was determined using an MMP assay kit (Beyotime, Shanghai, China). Briefly, MDBK cells were washed with serum-free Dulbecco’s Modified Eagle Medium and incubated in JC-I working solution for 20 min in the dark at 37°C. After washing, the cells were re-suspended with JC-1 dying buffer and JC-1 monomer fluorescence distribution and j-aggregates were measured. The fluorescence was measured using laser confocal microscopy and flow cytometry, collecting 10,000 events. Total RNA extraction, library construction, and sequencing of circRNA and miRNA The MDBK cells were infected with IBRV at 1.5 MOI for 24 h. Meanwhile, mock infection was carried out. Total RNA was extracted with Trizol reagent (Invitrogen, Carlsbad, CA, US). The rRNAs were then removed to retain mRNAs and ncRNAs. The mRNAs and ncRNAs were fragmented into short fragments using fragmentation buffer and reverse transcribed into cDNA using random hexamer primers. The second-strand cDNA was synthesised using buffer, dNTPs, RNase H, and DNA polymerase I. The cDNA fragments were then purified with a QiaQuick PCR extraction kit and end repaired, poly(A) was added, and fragments were ligated to Illumina sequencing adapters. Uracil-N-Glycosylase was used to digest the second-strand cDNA. The digested products were separated using agarose gel electrophoresis, amplified through PCR, and sequenced using Illumina Novaseq 6000 (Guangzhou, China). To acquire high-quality clean reads, reads containing adapters, low-quality reads, and rRNA reads were removed and mapped to a reference genome (ARS-UCD 1.2) using HISAT2 and Bowtie (version 1.1.2) with default options. The data were then subjected to find_circ to identify circRNAs. The identified circRNAs were subjected to statistical analysis of type, exon number, chromosome distribution, and length distribution. To quantify circRNAs, back-spliced junction reads were scaled to reads per kilobase of transcript per million mapped reads. The formula is shown below: $$\:\text{R}\text{P}\text{K}\text{M}=\frac{{10}^{6}\text{C}{10}^{3}}{\text{N}\text{L}}$$ C represents the number of reads that were mapped to transcripts, N represents the total number of reads that were mapped to reference genes, and L represents the number of base pairs of transcripts. To obtain miRNA, the low-quality reads, rRNA, scRNA, snoRNA, snRNA, and tRNA were removed. The rest of the clean tags were aligned with the ARS-UCD1.2 reference genome and searched against the miRBase database to identify existing miRNAs and novel miRNAs. The miRNA expression level was calculated and normalised to transcripts per million (TPM). The formula is shown below: $$\:\text{T}\text{P}\text{M}=\frac{{\text{T}10}^{6}}{\text{N}}$$ T represents the actual miRNA count. N represents the total counts of clean tags (existing, known, and novel miRNA). Significance analysis of the circRNAs, mRNAs, and miRNAs The edgeR package ( http://www.r-project.org/ ) was used to identify DE circRNAs, mRNAs, and miRNAs; mRNAs with a |log2FC| >1 plus a false discovery rate < 0.05 were identified as significant DE mRNAs. A p -value < 0.05 was set as the threshold for significant DE miRNAs and DE circRNAs. GO and KEGG enrichment analysis of DE circRNAs, mRNAs, and miRNAs To clarify the potential biological functions associated with DE circRNAs, enrichment analyses of the source genes for DE circRNAs, target genes of DE miRNAs, and RBPs of circRNA were conducted using GO ( http://www.geneontology.org/ ) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) ( http://www.genome.jp/kegg/ ). A significance threshold of p < 0.05 was applied to identify pathways showing significant enrichment. Construction of the circRNA-miRNA-mitochondria-related target gene network Miranda (v3.3a), TargetScan (v7.0), and RNAhybrid (v2.1.2) + svm_light (v6.01) were used to predict circRNA-miRNA and miRNA-mRNA interactions. The intersections of the target genes of the DE miRNAs and DE circRNAs were chosen as candidate targets of miRNAs. The circRNA-miRNA-mRNA regulatory networks were constructed using a combination of circRNA-miRNA pairs and miRNA-mRNA pairs. The circRNA-miRNA-mitochondria-related target gene interaction network, among miRNAs, circRNAs, and mRNAs, was built and visualised using Cytoscape (v3.7.0) ( http://www.cytoscape.org/ ). Construction of the circRNA-RBP network The CatRAPID databases ( http://service.tartaglialab.com/page/catrapid_group ) was used to predict the target RBPs for the 144 different circRNAs. The RBPs were screened using a ranking > 0.5. The predicted RBPs were compared in the UniProt database ( http://www.uniprot.org/ ). The reviewed proteins were selected, and the intersection was chosen with the mRNAs obtained by high-throughput sequencing. CircRNA-RBP networks were constructed with the circRNAs, and the predicted RBPs were enriched into the mitochondria after screening. The circRNA-RBP interactions were visualised using Cytoscape (v3.7.0) ( http://www.cytoscape.org/ ). Identification and quantification of circRNAs Both divergent primers and convergent primers were designed using Primer Premier 5.0 software (Premier Biosoft, USA) to identify the circular form. Head-to-tail splicing was validated with PCR and sequencing after reverse transcription. The MDBK cells were treated with RNase R (abm, Canada). For mock infection, 2 µg RNAs were mixed with RNase-free ddH 2 O; for RNase R digestion, 2 µg RNAs were mixed with RNase R. The two groups were then incubated for 2 h at 37°C and transcribed into cDNA. The treated RNAs were detected with RT-qPCR using divergent primers. GAPDH was used as an internal control. Circ_002584 and circ_004326 were chosen using a simple random sampling method generated using Microsoft Office Excel. Trizol was used to extract total RNA from the Mock and IBRV groups. RNA was reverse-transcribed using the Hifair® III 1st Strand cDNA Synthesis Kit (gDNA digester plus) (Yeasen, China), in accordance with the manufacturer’s protocol. cDNA was amplified using a 7500 Fast Real-Time PCR System (Applied Biosystems, USA) using 2× RealStar Green Fast Mixture with ROX II (Genstar, China). All data were calculated using the 2 −ΔΔCT method, and the circRNA level of each sample was normalised according to GAPDH expression. Each group comprised three duplicate wells. Fluorescence in situ hybridisation (FISH) A CircRNA FISH assay was performed in MDBK cells. The fluorescent signals of circ_002584 and circ_004326 were amplified using the SA-Cy3-Biotin system (GenePharma, Shanghai, China). The circ_002584 and circ_004326 probes were designed and synthesised by GenePharma (Shanghai, China) (Additional file 24: Table S24 ). The cell nucleus was labelled with 4', 6-diamidino-2-phenylindole (DAPI) (GenePharma, Shanghai, China). The images were captured with a laser confocal microscope (Nikon, Japan). Functional verification of circRNAs The siRNAs of the circRNAs were transfected into the MDBK cells to inhibit or overexpress circ_002584 and circ_004326. The transfection efficiency of circ_002584 and circ_004326 was verified by RT-qPCR, and the biological functions of circ_002584 and circ_004326 were verified by flow cytometry. ROS generation was determined according to the manufacturer’s instructions using a ROS assay kit (Beyotime, Shanghai, China). MMP was determined using a mitochondrial membrane potential assay kit with JC-1 (Beyotime, Shanghai, China). SiRNA and negative control oligonucleotides of circ_002584 and circ_004326 were purchased from GenePharma (Shanghai, China). MDBK cells were cultured to 60–70% confluence after being seeded onto six-well plates. Transfection of cells with oligonucleotides was performed using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) at a final concentration of 100 nM in accord with the manufacturer’s instructions. Then, 12 h later, the transfected cells were inoculated with 1.5 MOI IBRV. After 24 h of inoculation, the cells were harvested for further study. Statistical analysis The data are presented as mean ± standard error of the mean (SEM). Statistical comparisons were performed using unpaired Student’s t-tests. Statistical significance was evaluated using Graphpad Prism 8.0 software. Relative to the control, * p < 0.05 indicated a significant difference and ** p < 0.01 indicated a highly significant difference. Abbreviations BoHV-1: bovine herpesvirus 1; CircRNA: Circular RNA; CeRNA: competing endogenous RNA; CVB5: Coxsackievirus B5; DAPI: 4', 6-diamidino-2-phenylindole; DE: Diferential expression; FISH: Fluorescence in situ hybridization; GAPDH: Glyceraldehyde 3-phosphate dehydrogenase; GO: Gene ontology; IAV: Influenza A virus; IBRV: Infectious bovine rhinotracheitis virus; IFN-I: Activation of the type I interferon; KEGG: Kyoto Encyclopedia of Genes and Genomes; miRNA: MicroRNA; MMP: Mitochondrial membrane potential; mPTP: Mitochondrial permeability transition pore; mRNA: Messenger RNA; mTOR: Mammalian target of rapamycin; NF-κB: Nuclear factor κ-light-chain-enhancer of activated B cells; RBP: RNA binding proteins; ROS: Reactive oxygen species; RT-qPCR: Reverse transcription-quantitative polymerase chain reaction; TEM: Transmission electron microscopy. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession numbers can be found below: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA941037. Data generated during analysis are included in the manuscript as supplementary information. Competing interests 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. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 32460870), the Autonomous Region’s Major Science and Technology Projects (Grant No. 2023A02007-2) and the Autonomous Region’s Postgraduate Research Innovation Project (Grant No. XJ2025G120). Funding body had no contribution in the conception and the design of the study, analysis and interpretation of data and in the writing of the manuscript. Author contributions YM and XM designed the study, supervised the laboratory analyses and drafting of the manuscript. YM, JL and QH participated in the experiment. YM, LX, HL, and NL participated in the method ological discussion. ZL, YS, PY participated in the analysis of the data. YM and XM wrote the manuscript. XZ, QZ, GY and LX participated in the revision and review. XM participated in the management and fnancial support of the project. All authors read and approved the final manuscript. 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Supplementary Files Additionalfile4TableS4DifferentiallyexpressedcircRNAs.xlsx Additionalfile6TableS6DifferentiallyexpressedmiRNAs.xlsx Additionalfile5TableS5DifferentiallyexpressedmRNAs.xls Additionalfile1TableS1IdentificationresultsofcircRNAs.xlsx Additionalfile3TableS3IdentificationresultsofmiRNAs.xls Additionalfile2TableS2IdentificationresultsofmRNAs.xls Additionalfile7TableS7SourcegenesofdifferentiallyexpressedcircRNAs.xlsx Additionalfile8TableS8GOenrichmentanalysisofsourcegenesofdifferentiallyexpressedcircRNAs.xlsx Additionalfile9TableS9KEGGenrichmentanalysisofsourcegenesofdifferentiallyexpressedcircRNAs.xlsx Additionalfile12TableS12CandidatetargetgenesofdifferentiallyexpressedmiRNAs.xls Additionalfile10TableS10ScreeningresultsfrommRNAscount500.xls Additionalfile11TableS11TargetgenepredictionresultsofdifferentiallyexpressedmiRNAs.xlsx Additionalfile14TableS14KEGGenrichmentanalysisofcandidatetargetgenesofdifferentiallyexpressedmiRNAs.xlsx Additionalfile13TableS13GOenrichmentanalysisofcandidatetargetgenesofdifferentiallyexpressedmiRNAs.xlsx Additionalfile20TableS20GOenrichmentanalysisofRBPs.xlsx Additionalfile18TableS18MiRNAmitochondriarelatedtargetgeneregulatorynetworks.xlsx Additionalfile17TableS17CircRNAmiRNAregulatorynetworks.xlsx Additionalfile16TableS16GOenrichmentanalysisof4611mRNAs.xlsx Additionalfile15TableS15Targetgenesof59negativelycorrelatedmiRNAs.xlsx Additionalfile19TableS19PredictedresultsforRBPsofcircRNAs.xlsx Additionalfile21TableS21KEGGenrichmentanalysisofRBPs.xlsx Additionalfile23TableS23PrimerandsiRNAofcircRNAs.xlsx Additionalfile24TableS24CircRNAFISHprobesequences.xlsx Additionalfile22TableS22CircRNARBPnetwork.xlsx Supplementaryfilelegends.docx Cite Share Download PDF Status: Published Journal Publication published 24 Oct, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 22 Jul, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers invited by journal 18 Jun, 2025 Editor invited by journal 30 May, 2025 Editor assigned by journal 29 May, 2025 Submission checks completed at journal 29 May, 2025 First submitted to journal 26 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Black arrows indicate mitochondrion (scale bar = 500 nm). \u003cstrong\u003e(b)\u003c/strong\u003e The ROS level was measured in MDBK cells (scale bar = 500 μm). \u003cstrong\u003e(c)\u003c/strong\u003e Changes in ROS levels after MDBK cells were infected with IBRV. \u003cstrong\u003e(d)\u003c/strong\u003e The ROS level was measured in MDBK cells (scale bar = 500 μm).\u003cstrong\u003e (e)\u003c/strong\u003e Changes in MMP depolarisation after MDBK cells were infected with IBRV. ROS levels and MMP depolarisation were measured using flow cytometric analysis. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figures1.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/2cb306ab1a5c2d0122f095d0.png"},{"id":85055602,"identity":"c447309a-728b-483f-99e5-05ad2b21f02c","added_by":"auto","created_at":"2025-06-20 12:50:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3750836,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the high-throughput sequencing data.\u003cstrong\u003e (a)\u003c/strong\u003e CircRNA type. \u003cstrong\u003e(b) \u003c/strong\u003eThe length of the circRNA. \u003cstrong\u003e(c) \u003c/strong\u003eThe exon number of circRNA. \u003cstrong\u003e(d)\u003c/strong\u003e CircRNA distribution on the chromosome. \u003cstrong\u003e(e)\u003c/strong\u003e The mRNA type. \u003cstrong\u003e(f)\u003c/strong\u003e The length of the miRNA. \u003cstrong\u003e(g)\u003c/strong\u003e miRNA type.\u003c/p\u003e","description":"","filename":"figures2.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/3f2a2cc566920c576fdc5d6a.png"},{"id":85056359,"identity":"17eb73d3-8b65-4f33-a6cc-590196cfd461","added_by":"auto","created_at":"2025-06-20 12:58:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2929343,"visible":true,"origin":"","legend":"\u003cp\u003eClustering and heatmap analysis of differentially expressed mRNAs, circRNAs, and miRNAs.\u003cstrong\u003e (a)\u003c/strong\u003e Clustering and heatmap analysis of differentially expressed circRNAs, \u003cstrong\u003e(b)\u003c/strong\u003e including 83 upregulated circRNAs and 61 downregulated circRNAs. \u003cstrong\u003e(c)\u003c/strong\u003e Clustering and heatmap analysis of differentially expressed mRNAs, \u003cstrong\u003e(d)\u003c/strong\u003e including 528 upregulated mRNAs and 197 downregulated mRNAs. \u003cstrong\u003e(e)\u003c/strong\u003e Clustering and heatmap analysis of differentially expressed miRNAs, \u003cstrong\u003e(f)\u003c/strong\u003e including 93 upregulated miRNAs and 67 downregulated miRNAs. Red represents upregulation, and green represents downregulation.\u003c/p\u003e","description":"","filename":"figures3.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/44094b32a53d3c5aa33fed44.png"},{"id":85056362,"identity":"5b64a55e-4d4c-4c0f-be84-b7853fc320fa","added_by":"auto","created_at":"2025-06-20 12:58:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3068963,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG enrichment analyses of source genes of DE circRNAs. \u003cstrong\u003e(a)\u003c/strong\u003e GO enrichment analysis of the source genes of DE circRNAs. \u003cstrong\u003e(b)\u003c/strong\u003e Top 20 items in the KEGG pathway analysis of the source genes of DE circRNAs. The degree of KEGG enrichment was assessed by the Rich Factor, p-value, and Gene Number. The closer the\u003cem\u003e \u003c/em\u003ep-value is to zero, the greater the Rich Factor. The greater the Gene Number, the more significant the enrichment.\u003c/p\u003e","description":"","filename":"figures4.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/ad2a5822b2839f3a67d2a69e.png"},{"id":85056780,"identity":"98c299c0-e510-49f1-b196-d0d36b3b9b39","added_by":"auto","created_at":"2025-06-20 13:06:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3782222,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG enrichment analyses of target genes of DE miRNAs. \u003cstrong\u003e(a)\u003c/strong\u003e Venn diagram of candidate target genes showing the intersection of target genes of differentially expressed miRNAs and identified mRNAs (count ³ 500). \u003cstrong\u003e(b)\u003c/strong\u003e GO enrichment analysis of candidate target genes. \u003cstrong\u003e(c)\u003c/strong\u003e Top 20 items in the KEGG pathway analysis of candidate target genes. The degree of KEGG enrichment was assessed by the Rich Factor, p-value, and Gene Number. The closer the\u003cem\u003e \u003c/em\u003ep-value is to zero, the greater the Rich Factor. The greater the Gene Number, the more significant the enrichment.\u003c/p\u003e","description":"","filename":"figures5.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/dbf7ff7036dc4086fb8d5d59.png"},{"id":85055610,"identity":"8784b7d4-afde-4b25-a31d-c5f1cc33e17d","added_by":"auto","created_at":"2025-06-20 12:50:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":28534337,"visible":true,"origin":"","legend":"\u003cp\u003ecircRNA–miRNA–mRNA regulatory networks.\u003cstrong\u003e \u003c/strong\u003eCircles represent circRNA, triangles represent miRNA, and squares represent mRNA. Red represents upregulation, and green represents downregulation.\u003c/p\u003e","description":"","filename":"figures6.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/f4dff1d72cb740cd32e41123.png"},{"id":85055626,"identity":"5caf50b0-08fc-4b14-a114-f0dc5230ea31","added_by":"auto","created_at":"2025-06-20 12:50:17","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":8771514,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG enrichment analyses of RBPs.\u003cstrong\u003e (a)\u003c/strong\u003e GO enrichment analysis of 961 RBPs. \u003cstrong\u003e(b) \u003c/strong\u003eTop 20 items in the KEGG pathway analysis of 961 RBPs. The degree of KEGG enrichment was assessed by the Rich Factor, p-value, and Gene Number. The closer the\u003cem\u003e p\u003c/em\u003e-value is to zero, the greater the Rich Factor. The greater the Gene Number, the more significant the enrichment.\u003cstrong\u003e (c)\u003c/strong\u003e The circRNA–RBP networks. Circles represent circRNA and squares represent RBP, including 141 DE circRNAs and 107 RBPs.\u003c/p\u003e","description":"","filename":"figures7.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/6b5d37cdc289f0f860f91d94.png"},{"id":85055608,"identity":"1cb58408-dc51-4374-bb39-9c4b95984631","added_by":"auto","created_at":"2025-06-20 12:50:17","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":13389719,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification and quantification of circRNAs. \u003cstrong\u003e(a)\u003c/strong\u003e Gel electrophoresis verified the circular characteristic of circ-002584, which was amplified by divergent primers only in cDNA.\u003cstrong\u003e (b) \u003c/strong\u003eSanger sequencing verified the spliced joint position of circ-002584. \u003cstrong\u003e(c)\u003c/strong\u003e Gel electrophoresis verified the circular characteristic of circ-004326, which was amplified by divergent primers only in cDNA.\u003cstrong\u003e (d) \u003c/strong\u003eSanger sequencing verified the spliced joint position of circ-004326.\u003cstrong\u003e (e) \u003c/strong\u003eRT-qPCR analysis of the expression of circ_0002584 and circ_0004326 and GAPDH after treatment with RNase R in MDBK cells. \u003cstrong\u003e(f) \u003c/strong\u003eRT-qPCR verified the expression of circ_0002584 and circ_0004326 in MDBK cells. This was consistent with the high-throughput sequencing results. \u003cstrong\u003e(g) \u003c/strong\u003eFISH assay to detect the subcellular localisation of circ_002584 and circ_004326 in MDBK cells (scale bar = 5 μm). All data were calculated using the 2\u003csup\u003e−ΔΔCt\u003c/sup\u003e method, and the circRNA level of each sample was normalised according to GAPDH expression, * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figures8.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/c0e937d89597a3ae9451bf4b.png"},{"id":85056376,"identity":"4b0432e0-2671-499b-ac6c-1aa1e7841997","added_by":"auto","created_at":"2025-06-20 12:58:19","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":11786340,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional validation of circ_002584 and circ_004326.\u003cstrong\u003e (a) \u003c/strong\u003eExpression levels of circ_002584 after MDBK cells were transfected with si_circ_002584. \u003cstrong\u003e(b)\u003c/strong\u003e Expression levels of circ_004326 after MDBK cells were transfected with si_circ_004326. \u003cstrong\u003e(c)\u003c/strong\u003e Changes in ROS levels after MDBK cells were transfected with si_circ_002584. Images were acquired using a confocal microscope (scale bar = 500 μm). \u003cstrong\u003e(d)\u003c/strong\u003e Changes in ROS levels after MDBK cells were transfected with si_circ_002584; ROS accumulation was measured using flow cytometric analysis. \u003cstrong\u003e(e)\u003c/strong\u003e Changes in MMP after MDBK cells were transfected with si_circ_004326. Images were acquired by confocal microscope (scale bar = 500 μm). \u003cstrong\u003e(f)\u003c/strong\u003e Changes in MMP depolarisation after MDBK cells were transfected with si_circ_002584. MMP depolarisation was measured using flow cytometric analysis. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figures9.png","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/db601e6724cfe4066f5c5482.png"},{"id":94505884,"identity":"20b62251-723d-49c7-a7c5-7fc0b815ac0e","added_by":"auto","created_at":"2025-10-28 16:24:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":89580613,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/c639d773-1d05-4aa4-b0fd-54c3c4e20a51.pdf"},{"id":85056366,"identity":"26f0efdf-0485-4d61-8448-76ef9a6d106c","added_by":"auto","created_at":"2025-06-20 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12:50:19","extension":"xlsx","order_by":23,"title":"","display":"","copyAsset":false,"role":"supplement","size":9468,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile24TableS24CircRNAFISHprobesequences.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/b3947ed61d00873c00553d11.xlsx"},{"id":85055648,"identity":"58e262e0-a8d3-4db3-ab3a-1c397cc07faf","added_by":"auto","created_at":"2025-06-20 12:50:18","extension":"xlsx","order_by":24,"title":"","display":"","copyAsset":false,"role":"supplement","size":69678,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile22TableS22CircRNARBPnetwork.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/823ee2c8b7aae3ca1c3601cc.xlsx"},{"id":85055633,"identity":"0ba49c84-2f05-4191-8f47-cc768d1d64f8","added_by":"auto","created_at":"2025-06-20 12:50:18","extension":"docx","order_by":25,"title":"","display":"","copyAsset":false,"role":"supplement","size":14369,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfilelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-6754910/v1/128bf2f4122991cc7ec945c0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification and functional analysis of circular RNAs during mitochondrial damage induced by infectious bovine rhinotracheitis virus infection in Madin–Darby bovine kidney cells","fulltext":[{"header":"Background","content":"\u003cp\u003eInfectious bovine rhinotracheitis virus (IBRV) can cause a highly contagious respiratory disease called bovine herpesvirus 1 (BoHV-1). In the subfamily Alphaherpesvirinae of the Herpesviridae family, IBRV infection can cause various clinical manifestations, including rhinotracheitis, vulvovaginitis, and conjunctivitis, in cattle (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Like other alphaherpesviruses, IBRV establishes lifelong latent infection in the trigeminal ganglia of infected hosts following acute infection, from which it can be periodically reactivated and transmitted (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Current efforts for elimination of IBRV infections are focused on vaccine development (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), and relatively few studies have focused on the pathogenicity mechanisms of IBRV.\u003c/p\u003e \u003cp\u003eThe mitochondrion is an energy factory and key regulator of cell death signalling that provides approximately 95% of the energy required for the basic activities of the cell (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Virus-induced cytopathic effects are associated with mitochondrial dysfunction (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Influenza A virus (IAV) infection induces mitophagy, and the IAV PB1-F2 protein translocates to mitochondria by interacting and colocalising with mitochondrial Tu translation elongation factor to accelerate mitochondrial fragmentation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The classical swine fever virus is one of the most harmful pathogens in swine, and the expression of classical swine fever virus NS5A protein can induce membrane potential loss and mitochondrial fission, as well as increase the expression level of reactive oxygen species (ROS) to promote mitochondrial damage (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Duck Tembusu virus is a pathogenic flavivirus. A previous study reported that duck Tembusu virus infection causes the release of mitochondrial cytochrome C and downregulation of the apoptosis-inhibiting protein BCL\u0026minus;2, which reduces mitochondrial membrane potential (MMP) and results in the accumulation of intracellular ROS to regulate mitochondrial-mediated apoptosis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, study have confirmed that IBRV-induced oxidative stress can contribute to mitochondrial dysfunction in MDBK cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). IBRV infection can also promote intracellular mitochondrial damage (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Our previous study confirmed that IBRV infection of MDBK cells induces mitochondrial damage (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Nevertheless, the underlying molecular mechanisms have not been clarified.\u003c/p\u003e \u003cp\u003eCircRNAs are a newly recognised class of special noncoding RNA molecules that mainly consist of endogenous RNA molecules formed by exon transcripts and nonlinear reverse splicing, as well as circRNA molecules containing introns (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Most of the circRNAs are covalently connected with each other by the 3', 5'-phosphodiester bond without a polyadenylated tail (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). CircRNAs function in several ways, including serving as competing endogenous RNA (ceRNA) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), regulating transcription and splicing of their source genes (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), interacting with RNA binding proteins (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), and being translated into proteins (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Because circRNAs are insensitive to nuclease, and thus more stable than linear RNA, they have an obvious advantage in the development and application of new clinical diagnostic markers (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Accumulating evidence indicates that some circRNAs play an important role in the process of mitochondrial damage (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). For example, circSamd4 was reported to be involved in antioxidant response during cardiac regeneration, reducing oxidative stress generation by inducing the mitochondrial translocation of the Vcp protein, as well as downregulating Vdac1 expression and preventing the mitochondrial permeability transition pore (mPTP) from opening (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In the pathological process of osteoarthritis (OA), circFAM160A2 was reported to target miR\u0026minus;505\u0026minus;3p and SIRT3, which can reduce mitochondrial stabilisation and apoptosis via the circFAM160A2-miR\u0026minus;505\u0026minus;3p-SIRT3 axis (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In recent years, an increasing number of studies have found that circRNAs can participate in the regulation of host cell immune response and virus replication during viral infection (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Coxsackievirus B5 (CVB5) infection can change the expression profiles of circRNAs in SH-SY5Y cells, among which hsa_circ_0008378 and novel_circ_0014617 can upregulate the key factors in the Activation of the type I interferon (IFN-I) signalling pathway, hampering viral replication (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Bovine viral diarrhoea virus (BVDV) infection can change the expression profiles of circRNAs in MDBK cells, and the host genes of DE circRNAs have been reported to be involved in the regulation of cell proliferation, apoptosis, and viral infection-related signalling pathways (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Additionally, senecavirus A (SVA) infection has been reported to change the expression profiles of circRNAs in porcine kidney 15 (PK\u0026minus;15) cells, among which circ_8521 was significantly upregulated in SVA-infected PK\u0026minus;15 cells, which promoted the expression of LC3A by binding to miR\u0026minus;324, thereby promoting SVA infection (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Transmissible gastroenteritis coronavirus (TGEV) infection has been reported to provoke circEZH2 downregulation in the porcine intestinal epithelial cell line (IPEC-J2), which can target miR\u0026minus;22 to provoke mitochondrial damage in IPEC-J2 via the circEZH2/miR-22/HK2 axis and circEZH2/miR\u0026minus;22/IL\u0026minus;6/NF-κB axis (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In our previous study, we demonstrated that IBRV infection can provoke mitochondrial damage in MDBK cells (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, it remains unclear whether circRNAs participate in the IBRV-induced process of mitochondrial damage in MDBK cells.\u003c/p\u003e \u003cp\u003eIn the current study, we performed high-throughput sequencing at 24 h of IBRV infection of MDBK cells and screened for circRNA associated with mitochondrial damage by predicting and analysing circRNA source genes as well as circRNA-RBP and circRNA-miRNA-mRNA networks. Additionally, we performed mitochondrial damage functional validation on two circRNAs (circ_002584 and circ_004326) that were indicated by screening to be associated with mitochondria. The current findings provide novel insight to inform further exploration of the mechanisms of circRNA in the process of virus infection-induced mitochondrial damage.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eIBRV infection induced mitochondrial damage in MDBK cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo test whether IBRV infection caused mitochondrial damage in MDBK cells, we examined morphological changes in the mitochondria of MDBK cells upon infection with IBRV. The electron microscopy results showed that the mitochondria in infected MDBK cells swelled and became deformed, mitochondrial cristae fragmentation (Fig. 1a). In addition, we used a DCFH-DA probe to assess the accumulation of ROS in MDBK cells. The fluorescence intensity of the DCFH-DA, as measured by laser confocal microscopy and flow cytometry, significantly increased after IBRV infection (Figs. 1b, c), suggesting that IBRV increased the accumulation of ROS. Next, to investigate the impact of IBRV on MMP, the level of MMP depolarisation was tested using the JC-1 probe. The results revealed that IBRV infection reduced the red/green signal ratio, suggesting that IBRV increased the depolarisation of MMP (Figs. 1d, e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverview of high-throughput sequencing data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine whether IBRV infection could alter the expression profiles of mRNA, circRNA, and miRNA, high-throughput sequencing was performed. MDBK cells were infected with 1.5 Multiplicity of infection (MOI) IBRV for 24 h (IBRV), and normal MDBK cells were used as a control (Mock). In the Mock group and the IBRV group, a total of 4,367 circRNAs were identified. Annotations for all circRNAs identified in this study are shown in additional file 1: Table S1. We classified these circRNAs into six categories: annot_exons circRNAs (3011, 64.52%), one_exon circRNAs (324, 64.52%), exon_intron circRNAs (498, 64.52%), intronic circRNAs (157, 64.52%), intergenic circRNAs (223, 64.52%), and antisense circRNAs (154, 64.52%). Among these types, exonic circRNAs predominated (Fig. 2a). The size of these circRNA candidates ranged from less than 85 nt to greater than 3,000 nt, with most ranging from 200 nt to 800 nt. The majority of circRNAs contained 1-5 exons (Figs. 2b, c). The analysis of circRNA origin across chromosomes indicated that chromosomes 1, 3, 5, and 11 generated more circRNAs compared with other chromosomes (Fig. 2d). Moreover, the analysis of mRNA expression profiles identified 21,730 mRNAs, 78 of which were newly discovered miRNAs (novel_mRNAs) (Fig. 2e, Additional file 2: Table S2). The analysis of mRNA and miRNA expression profiles revealed that 2,022 miRNAs were identified, the length of which was concentrated at 21 nt-24 nts (Fig. 2f); among these miRNAs, 602 were extant miRNAs (exist_miRNA), 749 were known miRNAs (known_miRNA), and 671 were newly discovered miRNAs (novel_miRNA) (Fig. 2g, Additional file 3: Table S3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening for DE circRNAs, mRNAs, and miRNAs in MDBK cells during IBRV infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo screen the DE circRNAs, mRNAs, and miRNAs, we performed expression profiling to show circRNA, mRNA, and miRNA variations in MDBK cells during IBRV infection. The results revealed that 144 DE circRNAs in the IBRV group were differentially regulated compared with the Mock group (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05); of these, 83 circRNAs were upregulated and 61 circRNAs were downregulated (Figs. 3a, b. Additional file 4: Table S4). Compared with the Mock group, 725 differentially expressed mRNAs (DE mRNAs) in the IBRV group were identified as being differentially regulated by a false discovery rate \u0026lt; 0.05 and |log2FC| \u0026gt; 1. Among these, 528 DE mRNAs (518 known mRNA, 10 novel mRNA) were upregulated and 197 DE mRNAs (196 known mRNA, 1 novel mRNA) were downregulated (Figs. 3c, d. Additional file 5: Table S5). Compared with the Mock group, 160 differentially expressed miRNAs (DE miRNAs) in the IBRV group were found to be differentially regulated (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Among these, 93 DE miRNAs (83 existing and known miRNAs, 10 novel miRNAs) were upregulated while 67 DE miRNAs (48 known miRNAs, 19 novel miRNAs) were downregulated (Figs. 3e, f. Additional file 6: Table S6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional enrichment analysis of the source genes of DE circRNAs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore whether the source genes of DE circRNAs are associated with mitochondrial damage, we obtained 137 source genes of DE circRNAs (Additional file 7: Table S7), which were searched for enrichment analysis in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. GO enrichment analysis revealed that 11 source genes of DE circRNAs were enriched in the mitochondria (Fig. 4a, Additional file 7: Table S8). KEGG pathway analysis revealed that the source genes of DE circRNAs were involved in mitochondria-related signalling pathways including the mTOR, thyroid hormone, spinocerebellar ataxia, sphingolipid metabolism, neurotrophin, and Hippo signalling pathways (Fig. 4b, Additional file 9: Table S9).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional enrichment analysis of the target genes of DE miRNAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further screen for mitochondrial damage-associated DE miRNAs, 6,658 mRNAs (count\u0026nbsp;\u0026sup3;\u0026nbsp;500) were screened (Additional file 10: Table S10); 12,574 target genes of DE miRNAs were predicted (Additional file 11: Table S11) and intersected with 6,658 mRNAs (count\u0026nbsp;\u0026sup3;\u0026nbsp;500). Subsequently, 5,256 candidate target genes of DE miRNAs were obtained (Fig.\u0026nbsp;5a, Additional file\u0026nbsp;12: Table S12). These candidate target genes of DE miRNAs were searched for enrichment analysis via the GO and KEGG databases. GO enrichment analysis revealed that 471 candidate target genes of DE miRNAs were enriched in the mitochondria (Fig.\u0026nbsp;5b, Additional file\u0026nbsp;13: Table S13). KEGG pathway analysis revealed that the candidate target genes of DE miRNAs were primarily involved in mitochondria-related signalling pathways, including the cellular senescence, cell cycle, mitophagy, Kaposi sarcoma-associated herpesvirus infection, ubiquitin-mediated proteolysis, and thyroid hormone pathways (Fig.\u0026nbsp;5c, Additional file\u0026nbsp;14: Table S14).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction and analysis of the circRNA-miRNA-mitochondrial-related mRNA network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo screen for circRNAs involved in the regulation of mitochondrial damage as ceRNA during IBRV infection, we predicted a targeting relationship between 144 DE circRNAs and 160 DE miRNAs. Among these, 106 circRNAs were negatively correlated with 59 miRNAs. On the basis of the previous prediction regarding the target genes of 160 DE miRNAs, the 59 negatively correlated miRNAs targeted 4,611 mRNAs (Additional file 15: Table S15). GO enrichment analysis revealed that 389 mRNAs were enriched in the mitochondria (Additional file 16: Table S16). A total of 2,563 negatively regulated targeting relationship pairs of circRNA-miRNA (involving 106 circRNAs and 56 miRNAs) and 2,178 targeting relationship pairs of miRNA\u0026ndash;mitochondria-related mRNA (involving 56 miRNAs and 389 mitochondria-related mRNAs) were identified in the bioinformatics analysis (Fig 6, Additional file 17: Table S17 and Additional file 18: Table S18). In summary, the results indicated that these DE circRNAs may participate in the IBRV-induced process of mitochondrial damage by serving as miRNA sponges in MDBK cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCircRNA-RBP interactions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecent studies have reported that circRNA-RBP interactions play important roles in circRNA formation, the regulation of transcription, and viral replication\u0026nbsp;(\u003ca href=\"#_ENREF_36\" title=\"Okholm, 2020 #47\"\u003e36-38\u003c/a\u003e). To screen for RBP involved in the regulation of mitochondrial damage as ceRNA during IBRV infection, we predicted the binding relationships between 144 DE circRNAs and 3,982 proteins using the catRAPID algorithm. The predicted results indicated that 141 circRNAs could bind to 961 RBPs (ranking \u0026gt; 0.5) (Additional file 19: Table S19). We then used the genes of 961 RBPs for the GO and KEGG enrichment analyses. GO enrichment analysis revealed that 107 RBPs were enriched in the mitochondria (Fig. 7a, Additional file 20: Table S20). KEGG pathway analysis indicated that 961 RBPs were mainly involved in mitochondria-related signalling pathways, including nucleocytoplasmic transport, the mRNA monitoring pathway, RNA degradation, RNA degradation, endoplasmic reticulum protein processing, and the citric acid cycle (Fig. 7b, Additional file 21: Table S21). Utilising 141 DE circRNAs and 107 RBPs, we constructed a circRNA-RBP network (Fig. 7c, Additional file 22: Table S22). In summary, the results suggest that these DE circRNAs may interact with RBPs to regulate mitochondrial damage in MDBK cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification and localisation of circRNAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine the cyclisation of circRNA, according to circRNA sequencing and bioinformatic analysis, two DE circRNAs (circ_002584 and circ_004326) were selected for identification, revealing that a single and distinct product of expected size was amplified using circRNA divergent primers from only cDNA, while there was no target amplification product from gDNA (Figs. 8a, b). Sanger sequencing confirmed the head-to-tail splicing of circ_002584 and circ_004326 (Figs. 8c, d). Meanwhile, we observed significantly reduced glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and unchanged circRNA levels after digestion by RNase R, demonstrating that circ_002584 and circ_004326 were resistant to RNase R and were structurally stable (Fig. 8e). To validate the reliability of high-throughput sequencing, the expression levels of circ_002584 and circ_004326 were measured with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using divergent primers. The results were consistent with those of high-throughput sequencing (Fig. 8f). To further explore the potential function of circRNA in MDBK cells, a fluorescence in situ hybridisation (FISH) assay of circ_002584 and circ_004326 was performed in MDBK cells. The fluorescent signals of circ_002584 and circ_004326 were amplified by the SA-Cy3-Biotin system. The FISH assay results demonstrated that circ_002584 and circ_004326 were mainly localised in the cytoplasm, and small amounts were localised in the nucleus in MDBK cells (Fig. 8g). Thus, circ_002584 and circ_004326 may play important roles in the cytoplasm or nucleus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional validation of circ_002584 and circ_004326\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo verify whether circ_002584 and circ_004326 play a role in IBRV-induced mitochondrial damage, we silenced circ_002584 and circ_004326 in MDBK cells by specific siRNA transfection, then tested the intracellular levels of ROS and the degree of depolarisation of the MMP.\u0026nbsp;The results revealed that circ_002584 (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and circ_004326 expression (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01) were significantly decreased in MDBK cells post-transfection with the siRNA of circ_002584 and circ_004326 (Figs. 9a, b). Compared with the siRNA negative control group, si-circ_002584 reduced the accumulation of ROS (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and si-circ_004326 increased the accumulation of ROS (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01) (Figs. 9c, d). Meanwhile, compared with the siRNA negative control group, si-circ_002584 reduced the depolarisation of the MMP (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and si-circ_004326 increased the depolarisation of the MMP (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) (Figs. 9e, f). In summary, these results demonstrate that circ_002584 can promote IBRV-induced mitochondrial damage in MDBK cells and circ_004326 can inhibit IBRV-induced mitochondrial damage in MDBK cells.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIBRV is an animal pathogen with an important impact on the cattle industry. IBRV causes various degrees of clinical signs in cattle, including hyperpyrexia, dyspnoea, nasitis, conjunctivitis, and abortion of pregnancy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In many cases, IBRV establishes a latent infection in the trigeminal ganglia, and the virus is carried throughout life. Eradicating viral diseases is difficult, resulting in severe economic losses for cattle industries worldwide (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, few studies have investigated the pathogenic mechanisms of the virus. Mitochondria are the main source of cellular energy, and mitochondrial biogenesis is critical for mitochondrial homeostasis and intracellular physiological demands (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Recently, viral infection was reported to cause damage to mitochondrial macromolecules, affecting mitochondrial function (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Impaired mitochondria typically undergo structural changes and exhibit clear mitochondrial dysfunction (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), such as circEZH2 co-regulating TGEV-induced mPTP opening through both circEZH2/miR\u0026minus;22/HK2 and circEZH2/miR\u0026minus;22/IL\u0026minus;6/NF-κB pathways by targeting miR\u0026minus;22, which in turn protects mitochondrial function (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Pathogenicity of porcine deltacoronavirus infection stimulates mitochondrial outer membrane permeabilisation through Bax recruitment or mPTP opening, leading to the release of apoptotic cytochrome c into the cytoplasm, which activates the caspase-dependent intrinsic apoptotic pathway and promotes viral replication in vitro (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Hantavirus can inhibit apoptosis by preventing MMP loss through upregulation of the pro-survival factor BCL\u0026minus;2 (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). In addition, IBRV infection of MDBK cells can cause changes in intracellular miRNA expression profiles, where miR\u0026minus;10a and miR\u0026minus;182 affect mitochondrial function by altering mPTP and MMP levels (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). In the present study, we observed mitochondrial swelling and cristae rupturing in IBRV-infected MDBK cells via transmission electron microscopy (TEM) and detected the ROS level and the depolarisation of MMP in IBRV-infected MDBK cells via flow cytometry and confocal microscopy after infecting MDBK cells with IBRV. The findings confirm that IBRV infection can induce mitochondrial damage in MDBK cells. The current findings suggest new possibilities for studying the mechanisms of pathogenicity of IBRV-induced mitochondrial damage.\u003c/p\u003e \u003cp\u003eViral infection usually causes changes in the expression profile of non-coding RNA (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). For example, a total of 123 circRNAs, 523 mRNAs, and 65 miRNAs were identified in TGEV infected-intestinal porcine epithelial cell-jejunum 2 (IPEC-J2) cells, and these DE mRNAs were mainly enriched in the Nucleotide oligomerization domain (NOD)-like receptor, Janus kinase/signal transducer and activator of transcription (Jak-STAT), Tumor necrosis factor (TNF), and Retinoic Acid-inducible Gene-I (RIG-I)-like receptor pathways (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). In another study, 636 circRNAs were identified in the brains of mice that were infected with the rabies virus (RABV), of which 426 were significantly upregulated and 210 were significantly downregulated; these source genes of circRNA were enriched in the cGMP-PKG and MAPK signalling pathways (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). A total of 19,118 circRNAs were identified in BVDV-infected MDBK cells, and these DE circRNAs were mainly enriched in the cell proliferation, apoptosis, cycle, and viral infection-related pathways (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). To investigate the role of circRNAs in the process of IBRV-induced mitochondrial damage in MDBK cells, we obtained and analysed mRNA, circRNA, and miRNA expression profiles that were differentially expressed before and after IBRV infection via high-throughput sequencing data, and 725 DE mRNAs, 144 DE circRNAs, and 160 DE miRNAs were screened. GO enrichment analysis of DE mRNA, source genes of circRNA, and target genes of miRNA were point to mitochondrion. KEGG enrichment results indicated that enriched pathways were mainly mitochondrial function-related, including the mTOR, Hippo, nucleocytoplasmic transport, endoplasmic reticulum protein processing, and citric acid cycle signalling pathways. Additionally, using a bioinformatics approach, the circRNA-miRNA-mRNA network and circRNA-RBP network were constructed and the coding ability of circRNA was predicted. The results indicated that these DE circRNAs may have the potential to act as an miRNA sponge or binding RBP or translating protein in the IBRV-induced process of mitochondrial damage.\u003c/p\u003e \u003cp\u003eA previous study reported that the function of circRNAs is closely associated with their localisation in the cells (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). CircRNAs localised in the nucleus can function as modulators of transcription of their host genes to regulate the transcription of genes (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). For example, circERBB2 has been reported to regulate nucleolar localisation of PA2G4, thereby, via the circERBB2-PA2G4-TIFIA regulatory axis, to regulate ribosomal DNA transcription (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Another study reported that circ-DONSON was co-localised with SOX4 promoter in the nucleus and that circ-DONSON regulated SOX4 transcription to promote cell apoptosis to influence the progression of gastric carcinogenesis (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Circ-CTNNB1 has been reported to exist in the nucleus, and Circ-CTNNB1 has been found to bind DEAD-box polypeptide 3 (DDX3) to promote its binding with transcription factor Yin Yang 1 (YY1), leading to the transcriptional alteration of downstream genes associated with key proteins (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). In addition, circRNA localised to the cytoplasm has been found to be involved in numerous physiological and pathological processes by acting as an miRNA molecular sponge, binding to RBP and pathways such as translation proteins (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). For example, circIgfbp2 has been found to sponge miR\u0026minus;370\u0026minus;3p and regulate mitochondrial dysfunction after traumatic brain injury via the miR\u0026minus;370\u0026minus;3p/BACH1/HO\u0026minus;1 axis (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Circ\u0026minus;0088300 has been reported to be capable of physically interacting with RBP BOLL to regulate mitochondrial metabolic reprogramming, thereby promoting gastric cancer growth and metastasis (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). During spermatogenesis, rsrc1\u0026minus;161aa encoded by circRsrc1 interacted with mitochondrial protein C1qbp and enhanced its binding activity to mitochondrial mRNAs, thereby affecting the translation of oxidative phosphorylation (OXPHOS) proteins to prevent the accumulation of ROS and promote cell-cycle progression (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). In the current study, we first verified the ring-forming status of the selected circ_002584 and circ_004326. We then used PCR, gel electrophoresis, and Sanger sequencing to confirm the characteristics of the backspaced site and subsequently verified its stability with RNase R. Compared with linear RNA molecules, circ_002584 and circ_004326 were more stable and less prone to degradation in MDBK cells. The expressions of circ_002584 and circ_004326 were significantly elevated in IBRV-infected MDBK cells, consistent with the high-throughput sequencing results. The cellular localisation results showed that circ_002584 and circ_004326 were distributed in the cytoplasm and nucleus. These findings suggest that circRNAs may play important roles in regulating viral replication and mitochondrial function by interacting with miRNAs or RBPs.\u003c/p\u003e \u003cp\u003eCircRNAs are involved in regulating the relationship between the virus and the host. Previous studies have reported that BVDV infection can cause changes in circRNA expression profiles, and the host genes of DE circRNAs have been found to be involved in the regulation of viral infection-related signalling pathways (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). CircMerTK has been reported to exhibit significantly altered expression levels following IAV infection, and overexpression and silencing have been found to accelerate and impede IAV virus replication, respectively (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). CircEZH2 has been found to exhibit significant downregulation during TGEV infection, regulating the mPTP opening via the circEZH2/miR\u0026minus;22/HK2 axis and circEZH2/miR\u0026minus;22/IL\u0026minus;6/NF-κB axis (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In the current study, our prediction results indicated that the source genes, miRNAs, mRNAs, and the RBPs of DE circRNAs are associated with mitochondria. Meanwhile, we constructed circRNA-miRNA-mRNA and circRNA-RBP interaction networks using bioinformatics analysis. The results indicate that circ_002584 and circ_004326 are localised in the cytoplasm and nucleus. Functional studies of circ_002584 and circ_004326 have shown that interfering with the expression of circ_002584 significantly reduces ROS accumulation and MMP depolarisation, whereas interfering with the expression of circ_004326 significantly increases ROS accumulation and MMP depolarisation. These results provide preliminary evidence that circ_002584 can promote IBRV-induced mitochondrial damage, whereas circ_004326 can inhibit IBRV-induced mitochondrial damage. Thus, circ_002584 and circ_004326 may be involved in the process of IBRV-induced mitochondrial damage in MDBK cells. Our study provides novel insight into the molecular mechanisms of IBRV-induced mitochondrial damage, including the source genes of circRNAs, miRNA sponges, and the circRNA combination with RBPs. However, further investigation is needed to elucidate the specific mechanisms underlying the involvement of circ_002584 and circ_004326 in IBRV-induced mitochondrial damage.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results indicate that DE circRNAs might be involved in mitochondrial damage induced by IBRV through the source genes of the circRNAs, ceRNAs, and circRNA-RBP networks. circ_002584 can promote IBRV-induced mitochondrial damage, and circ_004326 can inhibit IBRV-induced mitochondrial damage. The current findings provide evidence for circ_002584/circ_004326 as a new molecular target for the clinical diagnosis of and therapy for IBR.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003eCells, virus, and primers\u003c/h2\u003e\n \u003cp\u003eIn the present study, MDBK (NBL-1) cells purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China) were cultured in Dulbecco\u0026rsquo;s Modified Eagle Medium (Biological Industries, Beit Haemek, Israel) supplemented with 100 IU of penicillin and 100 mg of streptomycin per millilitre at 37\u0026deg;C in an incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e. All experiments were performed with cells between passages 4 and 8. The IBRV AV21 strain was purchased from the China Institute of Veterinary Drug Control (Beijing, China). Primers of circRNAs were synthesised by the Shanghai Sangon Biological Engineering Technology Company Limited (Shanghai, China). The siRNAs of circRNAs were synthesised by GenePharma (Shanghai, China). The sequences are shown in additional file 23: Table \u003cspan class=\"InternalRef\"\u003eS23\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eDetection of mitochondrial damage indicators after IBRV infection of MDBK cells\u003c/h2\u003e\n \u003cp\u003eFirst, mitochondrial structural changes were observed using TEM before and after IBRV infection of MDBK cells. Briefly, the monolayer of MDBK cells infected with IBRV or Mock were fixed in situ for 24 h with a mixture of 2.5% glutaraldehyde and 2% formaldehyde in PBS (pH 7.2) for 6 h at room temperature and postfixed with 1% osmic acid for 4 h at 4\u0026deg;C. After dehydration and infiltration, embedding, ultrathin sectioning, and staining were performed. All sections were observed and photographed using a transmission electron microscope (HITACHI, Japan). Second, ROS generation was determined according to the manufacturer\u0026rsquo;s instructions using an ROS assay kit (Beyotime, Shanghai, China). Briefly, each sample was treated with 1 \u0026micro;l of DCFH-DA probe (10 \u0026micro;M) for 20 min at 37\u0026deg;C and the samples were mixed at 5 min intervals. Fluorescence was measured with laser confocal microscopy and flow cytometry, collecting 10,000 events. Additionally, MMP was determined using an MMP assay kit (Beyotime, Shanghai, China). Briefly, MDBK cells were washed with serum-free Dulbecco\u0026rsquo;s Modified Eagle Medium and incubated in JC-I working solution for 20 min in the dark at 37\u0026deg;C. After washing, the cells were re-suspended with JC-1 dying buffer and JC-1 monomer fluorescence distribution and j-aggregates were measured. The fluorescence was measured using laser confocal microscopy and flow cytometry, collecting 10,000 events.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eTotal RNA extraction, library construction, and sequencing of circRNA and miRNA\u003c/h2\u003e\n \u003cp\u003eThe MDBK cells were infected with IBRV at 1.5 MOI for 24 h. Meanwhile, mock infection was carried out. Total RNA was extracted with Trizol reagent (Invitrogen, Carlsbad, CA, US). The rRNAs were then removed to retain mRNAs and ncRNAs. The mRNAs and ncRNAs were fragmented into short fragments using fragmentation buffer and reverse transcribed into cDNA using random hexamer primers. The second-strand cDNA was synthesised using buffer, dNTPs, RNase H, and DNA polymerase I. The cDNA fragments were then purified with a QiaQuick PCR extraction kit and end repaired, poly(A) was added, and fragments were ligated to Illumina sequencing adapters. Uracil-N-Glycosylase was used to digest the second-strand cDNA. The digested products were separated using agarose gel electrophoresis, amplified through PCR, and sequenced using Illumina Novaseq 6000 (Guangzhou, China).\u003c/p\u003e\n \u003cp\u003eTo acquire high-quality clean reads, reads containing adapters, low-quality reads, and rRNA reads were removed and mapped to a reference genome (ARS-UCD 1.2) using HISAT2 and Bowtie (version 1.1.2) with default options. The data were then subjected to find_circ to identify circRNAs. The identified circRNAs were subjected to statistical analysis of type, exon number, chromosome distribution, and length distribution. To quantify circRNAs, back-spliced junction reads were scaled to reads per kilobase of transcript per million mapped reads. The formula is shown below:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:\\text{R}\\text{P}\\text{K}\\text{M}=\\frac{{10}^{6}\\text{C}{10}^{3}}{\\text{N}\\text{L}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eC represents the number of reads that were mapped to transcripts, N represents the total number of reads that were mapped to reference genes, and L represents the number of base pairs of transcripts.\u003c/p\u003e\n \u003cp\u003eTo obtain miRNA, the low-quality reads, rRNA, scRNA, snoRNA, snRNA, and tRNA were removed. The rest of the clean tags were aligned with the ARS-UCD1.2 reference genome and searched against the miRBase database to identify existing miRNAs and novel miRNAs. The miRNA expression level was calculated and normalised to transcripts per million (TPM). The formula is shown below:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:\\text{T}\\text{P}\\text{M}=\\frac{{\\text{T}10}^{6}}{\\text{N}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eT represents the actual miRNA count. N represents the total counts of clean tags (existing, known, and novel miRNA).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eSignificance analysis of the circRNAs, mRNAs, and miRNAs\u003c/h2\u003e\n \u003cp\u003eThe edgeR package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org/\u003c/span\u003e\u003c/span\u003e) was used to identify DE circRNAs, mRNAs, and miRNAs; mRNAs with a |log2FC| \u0026gt;1 plus a false discovery rate\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were identified as significant DE mRNAs. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was set as the threshold for significant DE miRNAs and DE circRNAs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eGO and KEGG enrichment analysis of DE circRNAs, mRNAs, and miRNAs\u003c/h2\u003e\n \u003cp\u003eTo clarify the potential biological functions associated with DE circRNAs, enrichment analyses of the source genes for DE circRNAs, target genes of DE miRNAs, and RBPs of circRNA were conducted using GO (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.geneontology.org/\u003c/span\u003e\u003c/span\u003e) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genome.jp/kegg/\u003c/span\u003e\u003c/span\u003e). A significance threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was applied to identify pathways showing significant enrichment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eConstruction of the circRNA-miRNA-mitochondria-related target gene network\u003c/h2\u003e\n \u003cp\u003eMiranda (v3.3a), TargetScan (v7.0), and RNAhybrid (v2.1.2)\u0026thinsp;+\u0026thinsp;svm_light (v6.01) were used to predict circRNA-miRNA and miRNA-mRNA interactions. The intersections of the target genes of the DE miRNAs and DE circRNAs were chosen as candidate targets of miRNAs. The circRNA-miRNA-mRNA regulatory networks were constructed using a combination of circRNA-miRNA pairs and miRNA-mRNA pairs. The circRNA-miRNA-mitochondria-related target gene interaction network, among miRNAs, circRNAs, and mRNAs, was built and visualised using Cytoscape (v3.7.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cytoscape.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003eConstruction of the circRNA-RBP network\u003c/h2\u003e\n \u003cp\u003eThe CatRAPID databases (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://service.tartaglialab.com/page/catrapid_group\u003c/span\u003e\u003c/span\u003e) was used to predict the target RBPs for the 144 different circRNAs. The RBPs were screened using a ranking\u0026thinsp;\u0026gt;\u0026thinsp;0.5. The predicted RBPs were compared in the UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.uniprot.org/\u003c/span\u003e\u003c/span\u003e). The reviewed proteins were selected, and the intersection was chosen with the mRNAs obtained by high-throughput sequencing. CircRNA-RBP networks were constructed with the circRNAs, and the predicted RBPs were enriched into the mitochondria after screening. The circRNA-RBP interactions were visualised using Cytoscape (v3.7.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cytoscape.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n \u003ch2\u003eIdentification and quantification of circRNAs\u003c/h2\u003e\n \u003cp\u003eBoth divergent primers and convergent primers were designed using Primer Premier 5.0 software (Premier Biosoft, USA) to identify the circular form. Head-to-tail splicing was validated with PCR and sequencing after reverse transcription. The MDBK cells were treated with RNase R (abm, Canada). For mock infection, 2 \u0026micro;g RNAs were mixed with RNase-free ddH\u003csub\u003e2\u003c/sub\u003eO; for RNase R digestion, 2 \u0026micro;g RNAs were mixed with RNase R. The two groups were then incubated for 2 h at 37\u0026deg;C and transcribed into cDNA. The treated RNAs were detected with RT-qPCR using divergent primers. GAPDH was used as an internal control.\u003c/p\u003e\n \u003cp\u003eCirc_002584 and circ_004326 were chosen using a simple random sampling method generated using Microsoft Office Excel. Trizol was used to extract total RNA from the Mock and IBRV groups. RNA was reverse-transcribed using the Hifair\u0026reg; III 1st Strand cDNA Synthesis Kit (gDNA digester plus) (Yeasen, China), in accordance with the manufacturer\u0026rsquo;s protocol. cDNA was amplified using a 7500 Fast Real-Time PCR System (Applied Biosystems, USA) using 2\u0026times; RealStar Green Fast Mixture with ROX II (Genstar, China). All data were calculated using the 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method, and the circRNA level of each sample was normalised according to GAPDH expression. Each group comprised three duplicate wells.\u003c/p\u003e\n \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n \u003ch2\u003eFluorescence in situ hybridisation (FISH)\u003c/h2\u003e\n \u003cp\u003eA CircRNA FISH assay was performed in MDBK cells. The fluorescent signals of circ_002584 and circ_004326 were amplified using the SA-Cy3-Biotin system (GenePharma, Shanghai, China). The circ_002584 and circ_004326 probes were designed and synthesised by GenePharma (Shanghai, China) (Additional file 24: Table \u003cspan class=\"InternalRef\"\u003eS24\u003c/span\u003e). The cell nucleus was labelled with 4\u0026apos;, 6-diamidino-2-phenylindole (DAPI) (GenePharma, Shanghai, China). The images were captured with a laser confocal microscope (Nikon, Japan).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n \u003ch2\u003eFunctional verification of circRNAs\u003c/h2\u003e\n \u003cp\u003eThe siRNAs of the circRNAs were transfected into the MDBK cells to inhibit or overexpress circ_002584 and circ_004326. The transfection efficiency of circ_002584 and circ_004326 was verified by RT-qPCR, and the biological functions of circ_002584 and circ_004326 were verified by flow cytometry. ROS generation was determined according to the manufacturer\u0026rsquo;s instructions using a ROS assay kit (Beyotime, Shanghai, China). MMP was determined using a mitochondrial membrane potential assay kit with JC-1 (Beyotime, Shanghai, China). SiRNA and negative control oligonucleotides of circ_002584 and circ_004326 were purchased from GenePharma (Shanghai, China). MDBK cells were cultured to 60\u0026ndash;70% confluence after being seeded onto six-well plates. Transfection of cells with oligonucleotides was performed using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) at a final concentration of 100 nM in accord with the manufacturer\u0026rsquo;s instructions. Then, 12 h later, the transfected cells were inoculated with 1.5 MOI IBRV. After 24 h of inoculation, the cells were harvested for further study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). Statistical comparisons were performed using unpaired Student\u0026rsquo;s t-tests. Statistical significance was evaluated using Graphpad Prism 8.0 software. Relative to the control, * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated a significant difference and ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 indicated a highly significant difference.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBoHV-1: bovine herpesvirus 1; CircRNA: Circular RNA; CeRNA: competing endogenous RNA; CVB5: Coxsackievirus B5; DAPI: 4\u0026apos;, 6-diamidino-2-phenylindole; DE: Diferential expression; FISH: Fluorescence in situ hybridization; GAPDH: Glyceraldehyde 3-phosphate dehydrogenase; GO: Gene ontology; IAV: Influenza A virus; IBRV: Infectious bovine rhinotracheitis virus; IFN-I: Activation of the type I interferon; KEGG: Kyoto Encyclopedia of Genes and Genomes; miRNA: MicroRNA; MMP: Mitochondrial membrane potential; mPTP: Mitochondrial permeability transition pore; mRNA: Messenger RNA; mTOR: Mammalian target of rapamycin; NF-\u0026kappa;B: Nuclear factor \u0026kappa;-light-chain-enhancer of activated B cells; RBP: RNA binding proteins; ROS: Reactive oxygen species; RT-qPCR: Reverse transcription-quantitative polymerase chain reaction; TEM: Transmission electron microscopy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession numbers can be found below: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA941037. Data generated during analysis are included in the manuscript as supplementary information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 32460870), the Autonomous Region\u0026rsquo;s Major Science and Technology Projects (Grant No. 2023A02007-2) and the Autonomous Region\u0026rsquo;s Postgraduate Research Innovation Project (Grant No. XJ2025G120). Funding body had no contribution in the conception and the design of the study, analysis and interpretation of data and in the writing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYM and XM designed the study, supervised the laboratory analyses and drafting of the manuscript. YM, JL and QH participated in the experiment. YM, LX, HL, and NL participated in the method ological discussion. ZL, YS, PY participated in the analysis of the data. YM and XM wrote the manuscript. XZ, QZ, GY and LX participated in the revision and review. XM participated in the management and fnancial support of the project. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eCollege of Veterinary Medicine, Xinjiang Agricultural University, Urumqi 830052, China.\u0026nbsp;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eXinjiang Key Laboratory of New Drug Research and Development for Herbivores, Urumqi 830052,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eChina.\u0026nbsp;\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eAnimal Disease Control and Diagnosis Center of Bayingolin Mongol Autonomous Prefecture, Korla 841000, China, \u003csup\u003e4\u0026nbsp;\u003c/sup\u003eCollege of Veterinary Medicine, Northwest A \u0026amp; F University, Yangling 712100, China.\u0026nbsp;\u003csup\u003e5\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eInstitute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi 830011, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMuylkens B, Thiry J, Kirten P, Schynts F, Thiry E. 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A novel circular RNA, circIgfbp2, links neural plasticity and anxiety through targeting mitochondrial dysfunction and oxidative stress-induced synapse dysfunction after traumatic brain injury. Mol Psychiatry 2022, 27(11):4575-4589.\u003c/li\u003e\n\u003cli\u003eChu S, Fei B, Yu M. Molecular Mechanism of Circ_0088300-BOLL Interaction Regulating Mitochondrial Metabolic Reprogramming and Involved in Gastric Cancer Growth and Metastasis. J Proteome Res 2023, 22(12):3793-3810.\u003c/li\u003e\n\u003cli\u003eZhang S, Wang C, Wang Y, Zhang H, Xu C, Cheng Y, Yuan Y, Sha J, Guo X, Cui Y. A novel protein encoded by circRsrc1 regulates mitochondrial ribosome assembly and translation during spermatogenesis. BMC Biol 2023, 21(1):94.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Infectious bovine rhinotracheitis virus (IBRV), Circular RNAs (circRNAs), MicroRNA (miRNA), RNA binding proteins of circRNA (circRNA-RBP), circ_002584, circ_004326, mitochondrial damage","lastPublishedDoi":"10.21203/rs.3.rs-6754910/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6754910/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Infectious bovine rhinotracheitis virus (IBRV), a member of the Herpesviridae family, causes infectious bovine rhinotracheitis (IBR) and induces mitochondrial dysfunction in host cells. Circular RNAs (circRNAs)—a novel class of non-coding RNAs—have been implicated in various biological processes and pathologies related to mitochondrial damage. However, their role in IBRV-induced mitochondrial damage in Madin-Darby bovine kidney (MDBK) cells remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Transmission electron microscopy(TEM), laser confocal microscopy, and flow cytometry confirmed that IBRV infection causes mitochondrial damage in MDBK cells. High-throughput sequencing revealed 144 differentially expressed (DE) circRNAs, 725 messenger RNAs (mRNAs), and 160 microRNAs (miRNAs) in IBRV-infected cells. We predicted that DE circRNAs regulate mitochondrial damage via source genes, circRNA-miRNA-mRNA networks, and RNA-binding proteins (RBPs). Source genes were enriched in mitochondria-related pathways like the mammalian target of rapamycin (mTOR), thyroid hormone, and Hippo signalling; 11 genes were localized to mitochondria. CircRNA-miRNA-mRNA network target genes were associated with cellular senescence, mitophagy, and ubiquitin-mediated proteolysis; 471 genes were linked to mitochondria. Additionally, 961 RBPs were enriched in pathways like nucleocytoplasmic transport and RNA degradation; 107 RBPs were localized to mitochondria. Functional validation revealed knockdown of circ_002584 reduced reactive oxygen species (ROS) accumulation (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and mitochondrial membrane potential depolarization (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05). Knockdown of circ_004326 increased both (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: CircRNAs play a regulatory role in IBRV-induced mitochondrial damage within MDBK cells. This finding is significant for virus-associated mitochondrial damage research, forming a theoretical foundation for utilizing circRNAs as diagnostic biomarkers and potential therapeutic targets for IBR.\u003c/p\u003e","manuscriptTitle":"Identification and functional analysis of circular RNAs during mitochondrial damage induced by infectious bovine rhinotracheitis virus infection in Madin–Darby bovine kidney cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-20 12:50:11","doi":"10.21203/rs.3.rs-6754910/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-22T07:26:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T06:55:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221750954499246537248263256986227991307","date":"2025-07-08T19:32:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-02T08:44:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300112687580527997868685954973800061743","date":"2025-06-18T14:15:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-18T09:42:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-30T14:31:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-29T07:28:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-29T07:24:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-05-27T03:07:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"01fcbc7e-19d9-4f23-a620-5db1ef31ebae","owner":[],"postedDate":"June 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:27:14+00:00","versionOfRecord":{"articleIdentity":"rs-6754910","link":"https://doi.org/10.1186/s12864-025-12158-9","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-10-24 16:17:08","publishedOnDateReadable":"October 24th, 2025"},"versionCreatedAt":"2025-06-20 12:50:11","video":"","vorDoi":"10.1186/s12864-025-12158-9","vorDoiUrl":"https://doi.org/10.1186/s12864-025-12158-9","workflowStages":[]},"version":"v1","identity":"rs-6754910","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6754910","identity":"rs-6754910","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}