High host specificity of alphacoronaviruses in Nearctic, insectivorous bats

High host specificity of alphacoronaviruses in Nearctic, insectivorous bats | 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 Article High host specificity of alphacoronaviruses in Nearctic, insectivorous bats Jonathon Kotwa, Arkadeb Bhuinya, Winfield Yim, Giulia Gallo, Pahul Singh, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5633972/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Bats are reservoir hosts for a number of coronaviruses, some of which may pose spillover risks for humans and other animals. Surveillance for bat coronaviruses in temperate regions remains limited and represents an important blind spot for emerging pathogen preparedness and bat conservation. We detected two alphacoronaviruses in big brown bats ( Eptesicus fuscus ) and little brown myotis ( Myotis lucifugus ) in the province of Ontario, Canada. These viruses are closely related to other coronaviruses circulating in bats in North America and Asia and also related to human and swine coronaviruses. We found unexpected diversity in the spike gene of these highly similar coronaviruses. High homology in the receptor-binding domain (RBD) was maintained in viruses derived from the same species of bat, but markedly lower in those derived from other species. RBD in silico structural analysis of closely related coronaviruses suggests that the viruses we detected are less likely to use bat APN (30 bat species) or ACE2 (20 bat species), or human DPP4 or TMPRSS2 as putative receptors or attachment factors. To gain early insights into interferon antagonism, we also functionally characterized the accessory protein ORF3 from both bat viruses and discovered that ORF3 inhibited both IFNβ production and signaling. Taken together, our study provides insights into coronavirus diversity in Nearctic, insectivorous bats in a previously under-sampled region. This work provides a baseline for more in-depth surveillance to better characterize the transmission dynamics of endemic coronaviruses in free-ranging wildlife, and for exploring the evolutionary relationships between coronaviruses and their hosts. Biological sciences/Microbiology/Virology/Viral epidemiology Biological sciences/Microbiology/Virology/Virus host interactions Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Bats represent over 1470 species in the order Chiroptera and perform critical ecosystem services including pollination, seed dispersal, and pest control (Beilke and O’Keefe, 2023 ; Ripperger et al., 2015 ). Bats are hosts to an exceptional diversity of coronaviruses; a recent estimate suggests that more than 4,800 coronaviruses have been detected in just 543 of known bat species (Ruiz-Aravena et al., 2022 ). Most of these are not associated with current human or livestock disease, but bat-derived coronaviruses also include close relatives of several coronaviruses that are of high consequence to public health and bear devastating impacts on livestock health and the global economy. Well-known examples include severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, Middle East respiratory syndrome coronavirus (MERS-CoV), porcine epidemic diarrhea virus (PEDV), and swine acute diarrhea syndrome coronavirus (SADS-CoV) (Banerjee et al., 2019 ; Plowright et al., 2015 ). Most research on bat-borne coronaviruses has focused on bat species in Asia, Europe and Africa, and far fewer studies have investigated viral diversity in North American bats (Hernández-Aguilar et al., 2021 ; Ruiz-Aravena et al., 2022 ), particularly in Canada. Moreover, full genomes are only available for two bat coronaviruses in North America: the Myotis lucifugus coronavirus (MylCoV) from Manitoba, Canada (Subudhi et al., 2017 ) and Colorado, USA (NC_022103.1), and Eptesicus bat coronavirus (EbCoV) from South Dakota, USA (Schaeffer et al., 2022 ). A more complete characterization of viral diversity in temperate, North American bats is critical to assessing potential zoonotic risk (Letko et al., 2020 ). Furthermore, surveillance programs can help us monitor the impacts of identified coronaviruses on the transmission between and health of host bat populations. As many of Canada’s bat species are assessed as Endangered (Canada, 2013 , 2023 ), understanding the effects of coronaviruses on bat hosts is vital for informing species’ recovery strategies. Coronaviruses’ structural, non-structural, and accessory proteins shape their pathogenesis and host-virus interactions, particularly with bat hosts that exhibit some down-regulated immunological responses during hibernation. Non-structural and structural proteins are essential for virus replication and progeny virion production. Importantly, the structural spike protein is responsible for binding the host receptor thereby governing species specificity (Li, 2016 , 2014 ; Lu et al., 2015 ). Accessory proteins are not required for virus replication but are critical for host antiviral response modulation and pathogenesis. For example, human and porcine alphacoronaviruses (alpha-CoVs) have evolved accessory proteins to suppress the antiviral type I interferon (IFN) response in humans and pigs, respectively (Kaewborisuth et al., 2020 ; Zheng et al., 2023 ). Similarly, PEDV open reading frame 3 (ORF3) protein can suppress the type I interferon (IFN) response in host cell, and inhibit polyinosinic:polycytidylic acid (poly(i:c)) induced type I IFN production and downstream signaling in human embryonic kidney (HEK) cells (Kaewborisuth et al., 2020 ). Reporter assays and VSV-GFP bioassays in HeLa cells also demonstrated that PEDV ORF3 functions as an IFN antagonist (Zhang et al., 2016 ). Understanding viral immune evasion strategies of bat-derived coronaviruses can contribute to risk assessments through the potential determinants of viral pathogenesis as well as aid in the development of targeted antiviral therapeutics. To improve our understanding of bat coronavirus diversity in North American bats, we sought to identify and characterize coronaviruses in five bat species in eastern Ontario, Canada with similar ecological roles: Eptesicus fuscus, Myotis lucifugus , Myotis leibii , Perimyotis subflavus , and Myotis septentrionalis . All five species are insectivorous, undertake regional migrations between their summer and over-wintering habitats, and survive the winter by hibernating, usually in caves and abandoned mines (Fenton, 1969 ). We sampled free-ranging bats and used nested real-time polymerase chain reaction (RT-PCR) to identify coronavirus-positive bat samples, followed by whole genome sequencing to determine the genome sequence of two bat-derived alpha-CoVs. We performed phylogenetic analyses to characterize the relatedness of these viruses to other coronaviruses, focusing on bat, human and other animal alpha-CoVs. Finally, we focused on two key host-pathogen interactions, including exploration of spike diversity and candidate host cell receptors, and functional characterization of ORF3 from both viruses to determine their abilities to inhibit innate antiviral IFN-dependent responses. Taken together, our study reports the discovery of two alpha-CoVs in insectivorous Nearctic bats found in Canada. These viruses are closely related to other circulating coronaviruses in bats in North America and Asia. Our study further highlights the diversity of genome structure and function among bat-borne coronaviruses in a previously under sampled region. Results Two alpha-CoVs detected in bats in Eastern Ontario, Canada We collected oral swabs from 390 individuals across five species of Vespertilionid bats. We collected these samples from five roosting sites in Ontario between 2020–2023 (Fig. 1 A), and tested 131 pools of samples using a pan-coronavirus RT-PCR. Viral RNA was detected from 8 pools (Fig. 1 B). These included one Myotis leibii pool and two Myotis septentrionalis pools, for which original individual material was not available for repeat testing, and which were therefore considered inconclusive. However, individual samples were tested from the other pools, yielding positive coronavirus detections from two Eptesicus fuscus (1.9%; 2/107) and three Myotis lucifugus (2.0%; 3/150) samples (Fig. 1 C). The five bats that yielded positive samples included a female M. lucifugus and female E. fuscus sampled during swarming at two distinct hibernacula in July and August, 2021, a female E. fuscus sampled at a maternity colony in late July 2022, and two M. lucifugus of unknown sex sampled during late hibernation at a third hibernaculum in March 2023. Overall, two alpha-CoVs were detected between four of the five sampling locations. Partial RNA-dependent RNA-polymerase (RdRp) amplicon sequencing (556 bp) resulted in five partial RdRp consensus sequences (average 61,000x depth of coverage); product from three pooled samples (one Myotis leibii pool and two Myotis septentrionalis pools) could not be sequenced due to low viral RNA quantity. Eptesicus fuscus- derived partial RdRp sequences were highly similar (95–97%) to Eptesicus bat coronavirus (EbCoV) sequences from recently sampled E. fuscus in South Dakota, USA (Schaeffer et al., 2022 ). The E. fuscus partial RdRp sequences were also highly similar to Eptesicus serotinus- derived alphacoronavirus HCQD-2020 (97%) (HCQD-2020; South Korea) (Do et al., 2021 ) and Bat Coronavirus EsJX20 (97%) (EsJX20; China), and Pipistrellus bat coronaviruses (97%) (Pakistan) from Pipistrellus spp.. Myotis lucifugus- derived partial RdRp sequences in this study were highly similar (95–97%) to Myotis lucifugus coronavirus (MylCoV) and Bat coronavirus CDPHE15/USA/2006 (CDPHE15) reported in M. lucifugus in Manitoba, Canada and Colorado, USA, respectively, as well as partial alpha-CoV sequences from Myotis occultus from Colorado, USA (EF544565.1). Whole-genome sequencing for the positive samples generated near-complete and partial genomes from all samples, with genome completeness ranging from 63–97% (Table 1 ). Individual, gene-level completeness was inferred using MylCoV (KY799179.1) and EbCoV (OL415262.1) as reference genomes (Table 1 ). Similar to the partial RdRp results, the E. fuscus- derived sequences (EfONCAN) were highly similar to EbCoV, HCQD-2020, and Pipistrellus bat coronavirus whole genomes (Fig. 2 A). The Myotis lucifugus- derived sequences (MlONCAN), were highly similar to MylCoV and CDPHE15 whole genomes (Fig. 2 B). Similarity was high for all genes except for the region corresponding to the spike gene for both M. lucifugus- and E. fuscus- derived sequences, with a particular divergence within the S1 subunit (Fig. 2 A, B). Table 1 Whole genome and gene completeness (%) of ≥ 10x coverage for coronaviruses sampled from big brown bats ( Eptesicus fuscus) and little brown bats ( Myotis lucifugus) in Ontario, Canada. Whole genome ORF1ab Spike ORF3 Envelope Membrane Nucleocapsid ORF7 EfONCAN21.4185 63.48 59.09* 65.95* 100* 97.97 99.85 77.17 70.01 EfONCAN22.320328 93.70 92.47* 96.75* 100* 100 98.83 98.03 99.28 MlONCAN21.3592 67.08 70.83 35.75 59.58 100 100 95.54 NA MlONCAN23.320388 97.16 97.01* 99.37* 100* 100 99.56 98.67 NA MlONCAN23.320392 85.41 86.49 80.75* 100* 100 99.41 99.68 NA * Gaps filled in with partial RdRp sequencing or targeted sequencing Genomic characterization of Ontario Eptesicus bat coronavirus and Myotis lucifugus coronaviruses The two Eptesicus- derived coronavirus genomes shared 98% nucleotide identity with each other. Open reading frame (ORF) and BLASTp analysis of EfONCAN22.320328 identified genes that encode the replicase polyprotein ORF1ab (partial), spike glycoprotein (S), envelope protein (E), membrane protein (M), and nucleocapsid protein (N). Accessory genes ORF3 and ORF7 were located between S and E and after N, respectively. All proteins were most similar to EbCoV identified in bats in South Dakota, USA, (Schaeffer et al. 2022 ) with the exception of E, which was closely related to Eptesicus serotinus- derived HCQD-2020 (Do. et al. 2020). All proteins shared a 97% or greater identity with EbCoV and HCQD-2020 with the exception of S, which ranged from 91–95% identity. Apart from bat coronaviruses, BLASTp analysis revealed relatedness of EfONCAN22.320328 proteins with proteins from a wider group of alpha-CoVs including: human coronaviruses (HCoV)-229E (35–76%) and NL63 (33–76%), feline infectious peritonitis virus (30–71%), canine coronavirus (28–48%), swine acute diarrhea syndrome coronavirus (36–76%), and PEDV (35–76%). Notably, ORF7 appears to be unique to alpha-CoVs identified in E. fuscus , E. serotinus , Pipistrellus spp. and Tadarida brasiliensis . The Myotis lucifugus -derived coronavirus genomes shared 98% nucleotide identity with each other. Open reading frame and BLASTp analysis of MlONCAN23.320388 identified genes that encode for ORF1ab, S glycoprotein, ORF3 accessory protein, E protein, M protein, and N protein, but not ORF7. With the exception of the S glycoprotein, all proteins shared a > 97% homology with MylCoV from Manitoba and CDPHE15; the S glycoprotein was 94% identical to MylCoV and 74% identical to CDPHE15. BLASTp further revealed more distant relatedness of MlONCAN23.320388 proteins to HCoV-229E (39–75%) and NL63 (42–76%), feline infectious peritonitis virus (31–71%), canine coronavirus (33–45%), and PEDV (44–82%). MlONCAN23.320388 was more closely related to PEDV compared to EfONCAN22.320328, including the ORF3 (MlONCAN23.320388 [52%] vs EfONCAN22.320328 [36%]). Phylogenetic analysis Based on the whole-genome phylogeny, the Eptesicus bat coronaviruses from Ontario clustered in a well-supported, monophyletic clade with other North American Eptesicus bat coronavirus sequences, Asian coronaviruses sampled from E. serotinus , including HCQD-2020 (South Korea), EsJX20 (China), and with a Pipistrellus bat coronavirus (Pakistan) (Fig. 2 C); we will herein refer to this clade as EbCoV (Fig. 2 C). This clade is most closely related to bat coronavirus McGD16 from a Myotis chinensis sampled in China. The Ontario Myotis lucifugus coronaviruses clustered in a well-supported, monophyletic clade with other Myotis lucifugus coronavirus sequences (Fig. 2 C); we will refer to this group of viruses as MylCoV (Fig. 2 C). This clade is sister to a clade including BtCoV/512/2005 from a Scotophilus kuhlii sampled in China, bat coronavirus MrGD17 from a Myotis ricketti bat in China, and PEDV. These Eptesicus bat and Myotis bat coronavirus sequences cluster together in a larger, monophyletic clade that also includes HCoV-229E and NL63, and Bat coronaviruses 1A and 1B (sampled from Miniopterus magnater and Miniopterus pusillus , respectively, in Hong Kong). Falling outside this larger group is a well-supported sister clade containing bat coronavirus HKU2 (from a Rhinolophid bat sampled in Hong Kong), and swine acute diarrhea syndrome coronavirus (SADS-CoV). Highly similar tree topology was observed with the ORF1ab phylogeny (Fig. 3 A). Analysis of the S gene sequences also indicated the Ontario Eptesicus bat coronaviruses clustered in a well-supported monophyletic clade with other EbCoV sequences including HCQD-2020 (South Korea) and Pipistrellus bat coronavirus (Pakistan) apart from EsJX20 (China) (Fig. 3 B); EsJX20 clustered with BtCoV/512/2005 (China), MrGD17 (China), and PEDV (Fig. 3 B). Notably, the S gene within the Eptesicus bat clade is more closely related to companion and livestock animal coronaviruses (e.g., canine coronavirus, feline infectious peritonitis virus, transmissible gastroenteritis virus) than McGD16 (China) as seen in the whole genome phylogeny (Fig. 3 B). The Ontario Myotis lucifugus coronaviruses clustered in a well-supported monophyletic clade with other MylCoV sequences. Similar to the whole-genome phylogeny, the Myotis bat clade is most closely related to a sister clade comprising BtCoV/512/2005, bat coronavirus MrGD17, PEDV, as well as EsJX20 (Fig. 3 B). Genomic characterization of the spike gene Pairwise amino acid identity of S1 and S2 subunits of the S glycoprotein of EfONCAN22.320328 and MlONCAN23.320388 were compared to alpha-CoVs from the phylogenetic analysis. In general, there was a greater homology for the S2 subunit (68%) compared to the S1 subunit (52%) across alpha-CoV sequences for both Ontario EbCoV and MylCoV (Fig. 4 A). Our observations were consistent when comparing amino acid sequences derived from similar species; EbCoV related amino acid sequences had a higher average percent identity in the S2 subunit (97%) compared to the S1 subunit (90%) and MylCoV related amino acid sequences had a higher average percent identity in the S2 subunit (95%) compared to the S1 subunit (76%) (Fig. 4 A). For EbCoV, despite variation in S1, receptor binding domain (RBD) homology remained high (95–98%) when compared to all but one South Dakota origin EbCoV sequence (72%) but was lower compared to HCQD-2020 (64%) and Pipistrellus bat coronavirus (63%) (Fig. 4 B). Receptor binding domain homology was greatest between Ontario and Manitoba derived sequences (92%) and substantially lower when compared to CDPHE15 (75%) (Fig. 4 B). No correlation was found between sampling times and root-to-tip genetic distances for whole genomes (Corr = 0.2347, R 2 = 0.0551), ORF1ab (Corr = 0.3566, R 2 = 0.1272), or S genes (Corr=-0.0693, R 2 = 0.0048), thereby precluding molecular clock analysis. Several significant recombination events were detected involving EbCoV sensu sequences (Supplementary Table 1). Four events involved regions corresponding to the spike gene were detected, all of which included EbCoV sequences from South Dakota (Schaeffer et al., 2022 ) as the recombinant, and major and minor parents. To characterize signatures of selection within EbCoV and MylCoV, we generated codon-alignment phylogenies for S gene sequences and applied selection methods from HyPhy (Kosakovsky Pond et al., 2020 ). Evidence of positive selection (P ≤ 0.05) was found at eight sites for the EbCoV clade (291S, 372N, 532G, 565V, 607I, 703V, 681N, 797T) and three sites (1121D, 1185P, 1292D) for the MylCoV clade. Sites are relative to the S protein of EfONCAN22.320328 and MlONCAN23.320388 for EbCoV and MylCoV, respectively. Notably, all but one site (797T) under positive selective pressure in the EbCoV clade were located in the S1 subunit of which two (328G, 361V) were in the RBD. Relative to other EbCoVs, evidence of a different dN/dS ratio (q threshold 0.2) in EfONCAN22.320328 was detected at one site (1179Q) using constrast-FEL; no significant results were found with aBSREL or RELAX. No significant difference in for MlONCAN23.320388 relative to the rest of the MylCoV clade were detected. To gain better insight in the structural properties, we predicted the RBD structure of EfONCAN22.320328 (Fig. 4 C) and MlONCAN23.320388 (Fig. 4 D) using AlphaFold. While the prediction score is high for the core of the RBDs, whose folding resembles those of other alpha-CoVs, the loops at the interface of interaction with yet-to-identify receptors (highlighted in light grey) possess a lower score, as the spatial location in absence of the interactor(s) is difficult to predict (Fig. 4 C, D). Additionally, no furin cleavage site motif was identified at the S1/S2 boundary for either the EbCoV or MylCoV clades. A predicted propeptide S2’ cleavage site (KR 858 ↓S) was identified (prediction score = 0.542) in EfONCAN22.320328. This S2’ cleavage site was found to occur in the viruses comprising the EbCoV clade, with the exception of the Pipistrellus bat coronavirus (MZ293738.1) and EsJX20 (OQ175260.1). Bat alpha-CoV ORF3 inhibits antiviral type I interferon response To test whether EbCoV (EfONCAN22.320328) and MylCoV (MlONCAN23.320388) ORF3 accessory protein can inhibit the human IFN response, we assessed the modulation of the human IFNβ promoter and interferon stimulated gene (ISG) promoter activity by EbCoV and MylCoV ORF3 proteins. HEK293T cells that expressed PEDV, MylCoV, and EbCoV ORF3 proteins exhibited significantly reduced IFNβ promoter-driven luciferase expression upon poly (I:C) stimulation, relative to pcDNA transfected controls. Among the three alpha-CoV ORF3 proteins tested, EbCoV ORF3 demonstrated the most potent inhibitory effect, reducing luciferase activity by 2.5-fold. MylCoV ORF3 suppressed luciferase activity by two-fold, while PEDV ORF3 demonstrated a 1.5-fold inhibition in luciferase expression (Fig. 5 A). We also screened these viral proteins for their ability to suppress human type I IFN signaling using a plasmid containing a luciferase reporter driven by an interferon-stimulated response element (ISRE) promoter. ORF3 proteins from all three alpha-CoVs significantly suppressed ISRE promoter driven luciferase expression (Fig. 5 B). PEDV ORF3 exhibited the strongest inhibition of ISRE promoter activity, and EbCoV and MylCoV ORF3 proteins inhibited ISRE promoter activity by six- and seven-fold, respectively (Fig. 5 B). We confirmed ORF3 protein and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression by immunoblot analysis (Fig. 5 C). Discussion This is the first survey for coronaviruses in bats in Ontario, Canada, and resulted in the detection of two different alpha-CoVs. We did not find evidence of cross-species transmission despite sampling five species at sites where they co-occur and share hibernacula. The E. fuscus- derived coronaviruses we detected were most closely related to EbCoVs from E. fuscus in South Dakota, USA (Schaeffer et al., 2022 ), and the coronaviruses we sampled from M. lucifugus were most closely related to coronaviruses from M. lucifugus in Manitoba, Canada (Subudhi et al., 2017 ) and Colorado, USA (NC_022103.1). We observed remarkable similarity between Eptesicus coronaviruses detected in this study, and coronaviruses sampled from E. serotinus from South Korea (Do et al., 2021 )and Pipistrellus sp. from Pakistan. The detection of highly related coronaviruses in geographically distant bats suggests long-term evolutionary interactions within bat-coronavirus assemblages (Cui et al., 2007 ; Leopardi et al., 2018 ; Vijaykrishna et al., 2007 ). The observed phylogeny implies infrequent spillover events interspersed with periods of high host specificity, possibly mediated by high interspecific variation in spike proteins. Our finding that EbCoV and MylCoV ORF3 accessory proteins can inhibit human interferon responses in vitro requires further consideration. This result cannot directly predict spillover risk but has potential implications for risk assessments where bats cohabit with humans and livestock. Neither evolutionary host relationships nor geographic distance can fully explain the observed phylogeny, which is probably a product of both factors. The phylogeny generally resolved two groups consistent with the bat Suborders Yinpterochiroptera and Yangochiroptera (Teeling et al., 2002 ). However, our phylogeny included only a single sequence sampled from a Yinpterochiropteran host (Bat Coronavirus HKU2, EF2030065.1, sampled from a Rhinolophid bat). Our analysis placed HCoV-NL63 and 229E as a sister clade to viruses sampled from Yangochiropteran hosts, but HCoV-NL63 was previously shown to be closely related to coronaviruses isolated from the Yinpterochiropteran genera Hipposideros and Triaenops (Tao et al., 2017 ). The evolutionary relationships estimated for viruses sampled from members of the family Miniopteridae, and the Vespertilionid subfamilies Myotinae and Vespertilioninae were also incongruent with host phylogeny. For example, coronavirus sampled from M. chinensis fell into a clade comprised mostly of EbCoVs, although the relationship between these viruses was not close (Fig. 2 C). These exceptions, and the interspersion of swine and human coronaviruses across the phylogeny, imply ongoing, occasional viral transmission among species. The direction of transmission is unclear, and coronaviruses can move between hosts by the respiratory route after contact with excreta (Plowright et al., 2015 ). Therefore, plausible scenarios include bat-to-human, bat-to-livestock, human-to-bat and livestock-to-bat transmission, and transmission through one or more intermediate hosts. The current data do not allow us to assess the relative likelihood of these scenarios, nor are they evidence that the EbCoV or MylCoV we detected are likely to spill over to human hosts. However, these viruses merit further research, including explorations of the role of host ecology in the evolution of bat coronaviruses and broader host-pathogen interactions. The apparent host-specificity of MylCoV and the North American EbCoV in this study contrasts with the frequent roost-sharing exhibited by these two relatively common species, which often form maternity colonies in buildings, and hibernate in the same underground features. The well-supported, distantly related MylCoV and EbCoV clades (Figs. 2 and 3 ) suggest high host specificity of EbCoV and MylCoV in their North American hosts. In contrast, EbCoV isolated from E. fuscus is closely related to EbCoV from Asian E. serotinus (Fig. 2 C; Schaeffer et al., 2022 ), which seems surprising given the substantial geographic distance between the sampling locations. We can only speculate as to the mechanisms maintaining this similarity, but we note that E. fuscus is frequently involved in accidental translocations that can move individuals kilometers across a continent, or even an ocean (Constantine, 2003 ), potentially facilitating viral transmission. Spike glycoprotein is an important coronavirus structural protein charged with binding the host receptor, and the S1 subunit is critical in determining species specificity; mutations within this region, particularly within the RBD, likely play a critical role in cross-species transmission and emergence (Li, 2016 , 2014 ; Menachery et al., 2017 ). In this study, we found that genes of closely related coronaviruses were highly similar, except for the region corresponding to the spike gene of EfONCAN and MlONCAN, with higher divergence within the S1 subunit (Fig. 2 A, B). This variation was surprising given the role of the S1 subunit in host specificity, and we did not find evidence of recombination that could explain it. Evidence of positive selection was detected for the EbCoV clade at several sites in the S1 subunit with two sites included in the RBD. High homology in the RBD was maintained in viruses derived from the same species of bat, but markedly lower in those derived from other species with the exception of the MylCoV from Colorado, USA (CDPHE15) (Fig. 4 B) which further supports our hypothesis of high host specificity. Understanding host receptors is a key step in assessing the risk of viral transmission across species. To our knowledge, the receptors used for EbCoV and MylCoV are unknown. In the present study, we generated near complete S gene sequences for EfONCAN22.320328 and MlONCAN23.320388 and predicted the structure of the RBDs (Fig. 4 C, D). An entry assay using the S protein of closely related bat alpha-CoV showed that these viruses do not use APN (25 bat species), ACE2 (35 bat species), human TMPRSS2 or human DPP4 (G. Gallo, unpub. data). Structural analysis of the predicted RBD of EfONCAN22.320328 and MlONCAN23.320388 supports the hypothesis that these viruses are likely to use an unknown receptor(s) to enter cells (Fig. 4 ). Further experimental characterization of cell receptor affinity of these viruses are warranted. The type I IFN response is the first line of cellular defense against invading viruses in mammals. Coronaviruses, including alpha-CoVs, have evolved accessory proteins that can efficiently block the human IFNβ response (Kaewborisuth et al., 2020 ; Zheng et al., 2023 ). PEDV has evolved mechanisms to suppress the type I IFN response, with ORF3 identified as a potent inhibitor. Pairwise amino acid identity analysis showed that EfONCAN and MlONCAN ORF3 were related, albeit distantly, to PEDV ORF3 with MlONCAN having a closer relatedness (52%) than EfONCAN (36%). In this study, we investigated the inhibitory effects of ORF3 proteins from our bat-derived alpha-CoVs, both related to PEDV, a swine-restricted virus, on the human type-I interferon response. Our findings revealed that while EbCoV ORF3 exhibited a potent inhibitory effect on IFNβ production, MylCoV ORF3 demonstrated greater potency in suppressing IFNβ signaling. These findings highlight the differential impacts of bat-derived alpha-CoV ORF3 proteins on host IFN-mediated antiviral responses (Fig. 5 D). The sampling methods we employed in this study impose certain limitations, but also provide a framework for future studies of viral diversity, prevalence, and impact in free-ranging, threatened populations. The populations we studied are recovering from drastic, recent declines caused by mortality from bat white-nose syndrome (WNS; Hooton et al., 2023 ), and four of the five species we sampled are listed as Endangered in Ontario. Therefore, we considered lethal or potentially harmful sampling unacceptable and unnecessary. Four of our study species are particularly small (body mass for M. leibii is typically 3–5 g), and only oral swab samples could be collected with minimal risk or stress to the bats. As coronavirus infections are often concentrated in the gastro-intestinal tract, our detections from oral swab samples represent a conservative, minimum estimate of true prevalence. We also collected guano samples, but individual guano samples did not provide sufficient material for testing, and pooled guano samples cannot be re-tested at the individual level to characterize pathogen diversity among individual hosts. Our study demonstrates that near-complete viral genomes can be obtained from non-harmful, oral swab samples and compared among individual bat hosts, enabling future, longitudinal studies of viral prevalence and transmission in our study system. Further work can hopefully achieve similar results from guano samples, to further explore drivers of coronavirus prevalence in endangered bats. We provide preliminary insights into coronavirus diversity in bats in a previously undersampled region. In this work, we detected two alpha-CoVs in two Ontario bat species; Eptesicus bat coronavirus (EbCoV) and Myotis lucifugus coronavirus (MylCoV). This report represents the first detection of bat coronaviruses in Ontario and the first report of EbCoV in Canada. Ebcov and MylCoV were most closely related to other bat alpha-CoVs from host species within the same respective subfamily. Both viruses were also related to porcine epidemic diarrhea syndrome virus, swine acute diarrhea syndrome coronavirus and HCoV-229e and NL63. Additionally, we found that the ORF3 accessory protein of EbCoV and MylCoV demonstrate inhibition of human type I interferon response. This work provides a baseline for more rigorous surveillance to understand transmission dynamics of endemic coronaviruses in a natural setting, and for exploring the evolutionary relationships between bat, human, and swine coronaviruses in our study area. Further experimental characterization (e.g., cell receptor affinity) of these viruses are required for a fulsome risk assessment. Materials and Methods Sample collection Bat capture, handling, and sample collection were approved under permits No. 1039395, 1045694, and 1050823 from the Ontario Ministry of Natural Resources and Forestry. All captures were approved by Animal Care protocols from Trent University (No. 25253 and 26117), Carleton University (No. 117298), and the Ontario Ministry of Natural Resources and Forestry (No. 394). Survey gear was cleaned following current WNS decontamination protocols (CWHC-RCSF 2017), and for work performed after 2020, we took precautions to ensure that we would not inadvertently expose bats to SARS-CoV-2. We sampled at two abandoned mines, one cave, and three human-built structures in Eastern Ontario, Canada. Sampling occurred during swarming and hibernation from 2020–2023. Bats were captured at the entrances of mines and caves using a harp trap (Tuttle, 1974 ). Bats were captured outside building roosts using a triple-high mist net system (Bat Conservation and Management Inc.,Carlisle, Pennsylvania). Sex, age (based on ossification of phalangeal joints [Kunz and Anthony, 1982 ]), body mass, and forearm length were recorded for each bat. We used nasopharyngeal FLOQSwabs® (Typenex Medical) to gently collect oral samples and stored each swab in 1 mL of in-house transport media. Samples were placed on dry ice in the field and were subsequently stored at -80°C prior to analysis. All bats were released after sample collection. Nucleic acid extraction and nested SYBR Green pancoronavirus RT-PCR All samples were extracted at the containment level 3 at the University of Toronto. Samples were extracted in pooled groups of 2–4. Pools were prepared by mixing 140 uL of each individual sample and 140 uL of the pool material was used for RNA extraction via QIAmp viral RNA mini kit (QIAGEN, https://ww.qiagen.com ) according to manufacturer’s instructions; samples were eluted into 40 uL buffer AVE. Individual samples from PCR-positive pools were then extracted individually for follow-up analysis. We analyzed RNA via a nested SYBR Green pancoronavirus RT-PCR targeting the highly conserved, RNA-dependent RNA-polymerase (RdRp) of the coronavirus genome. The following primers were used for round 1 RT-PCR: outer forward 5’-CCAARTTYTAYGGHGGNTGG-3’ (Xiu et al., 2020 ) and outer reverse 5’-GCATWGTRTGYTGNGARCARAATTC-3’(Escutenaire et al., 2007 ). Reactions were performed using the Qiagen One-Step RT-PCR kit (QIAGEN, https://ww.qiagen.com ) with 5 uL 5x buffer, 1 uL dNTP mix, 1 uL enzyme mix, 0.4uL of each of the primers (25 uM stock; 0.4 uM final concentration), 12.2 uL RNase-free water, and 5 uL of RNA template. Reverse transcription was carried out at 50°C for 30 minutes, followed by the polymerase activation at 95°C for 15 minutes and by 40 cycles of 3 steps: 94°C for 15 seconds, 53.4°C for 30 seconds, and 68°C for 1 minute with a final extension step of 68°C for 5 minutes; cycling conditions were conducted under standard conditions. For round 2 PCR, the following primers were used: inner forward 5’-TGATGATGSNGTTGTNTGYTAYAA-3’ (Escutenaire et al., 2007 ) and inner reverse 5’-TGTTGNGARCARAAYTCATGNGG-3’ (Xiu et al., 2020 ). Reactions were performed using the PowerTrack SYBR Green PCR Master Mix (Applied Biosystems™; https://www.thermofisher.com ) with 10 uL of the SYBR Green master mix, 0.32 uL of each of the the primers (25 uM stock; 0.4 uM final concentration), 8.36 uL RNase-free water, and 1 uL of cDNA product from round 1 PCR. Polymerase activation was carried out at 95°C for 2 minutes followed by 40 cycles of 3 steps: 94°C for 5 seconds, 50°C for 40 seconds, and 72°C for 40 seconds. First-derivative melting curve analysis was performed as follows: 95°C for 1 minute, 55°C for 45 seconds, 0.1°C/second continuous increase to 95°C, 95°C for 1 second; cycling conditions were conducted under fast conditions. Each round of PCR included a non-template (negative) control with RNase-free water, and a coronavirus positive control. We considered samples positive if we observed both an exponential increase in fluorescence and a coronavirus-specific melt peak. Partial RNA-dependent RNA-polymerase Sequencing Round 1 cDNA product from positive samples were amplified using the following primers: inner seq forward 5’-GGTTGGGAYTAYCCHAARTGTGA-3’ and inner reverse 5’-TGTTGNGARCARAAYTCATGNGG-3’ (Xiu et al., 2020 ). PCR reactions were performed using Platinum™ Taq DNA Polymerase (Invitrogen) with 2.5 uL 10x PCR buffer, 0.75 uL 50 nM MgCl2, 0.5 uL 10 nM dNTP, 0.25 uL Taq, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 19.2 uL RNase-free water, and 1 uL of cDNA product from round 1 PCR. Polymerase activation was carried out at 94°C for 2 minutes followed by 35 cycles of 3 steps: 94°C for 15 seconds, 54.5°C for 30 seconds, and 72°C for 1 minute with a final extension step of 72°C for 10 minutes. Amplified material was quantified using Qubit 4 with the dsDNA HS kit. Libraries were prepared using the Native Barcoding Amplicons (SQK-LSK109 with EXP-NBD104) protocol (version NBA_9093_v109_revJ_12Nov2019) and loaded on R.9.4.1 flow cells and sequenced on the MinION Mk1B nanopore sequencer. Basecalling and barcode and adapter trimming was performed using ONT guppy (v6.5.7 + ca6d6af) (gpu). Fastq reads were also filtered to remove reads < 450 bp using filtlong (v0.2.1) (Wick, 2021 , p. 20) and then aligned to a multi reference containing 37 coronavirus partial RdRp sequences using Minimap2 (v2.24) (Li, 2018 ). Consensus sequences were generated based on the best hit from alignment using samtools (v1.6) (Danecek et al., 2021 ), bcftools (v1.5) (Danecek et al., 2021 ) and seqtk (v1.3) (github.com/lh3/ seqtk) ; quality check reports were generated from bam files using qualimap (v2.2.2a)(Okonechnikov et al., 2016 ). Finally, resultant consensus sequences were identified by BLASTn against NCBI’s core nucleotide database. Whole genome sequencing RNA from pooled and individual bat oral samples were used for cDNA synthesis using 4 uL of LunaScript RT Mix (NEB, E3010), 8 uL of RNase free water, and 8 uL of RNA. This reaction was incubated at 25°C for 2 minutes, 55°C for 20 minutes, 95°C for 1 minute, followed by a 4°C hold. Whole genome sequencing used amplicon-based sequencing using EbCoV or MylCoV specific primer schemes and enrichment-based sequencing with the Illumina Pan-Coronavirus Panel (Illumina, USA) if sufficient material was available. Primer schemes for MylCoV (KY799179.1) and EbCoV (OL415262.1) were designed using primalscheme (Quick et al., 2017 ) with an amplicon size of 400 bp. For amplicon-based sequencing, lyophilized EbCoV and MylCoV primer pools (IDT), were resuspended in Tris-EDTA (TE) according to the oligonucleotide synthesis reports to achieve a stock concentration of 100 uM for each odd (primer pool 1) and even (primer pool 2) region primer pool. Working stocks were prepared by diluting stock primer pools with nuclease-free water to achieve a concentration of 10 uM. Amplification occurred in two reactions per sample (one for each primer pool) with 12.5 uL of Q5® Hot Start High-Fidelity 2X Master Mix (NEB, M0494), 3.5 uL of nuclease-free water, 4 uL of primer pool, and 5 uL of cDNA. Thermocycling conditions were as follows: 98°C for 30 seconds, followed by 35 cycles of 98°C for 15 seconds and 65°C for 5 minutes, followed by a 4°C hold. After PCR products were combined, a clean-up was performed using AMPure XP beads (Beckman Coulter, USA) at 1:1 bead to sample ratio. The quantity of the amplicons was measured with the Quibut 4.0 fluorometer using the 1X dsDNA HS Assay Kit (Thermo Fisher Scientific, USA). The sequencing libraries were prepared using the Nextera DNA Flex Prep kit (Illumina, USA) as per manufacturer’s instructions. Paired-end (2x150 bp) sequencing was performed on a MiniSeq with a 300-cycle Mid output reagent kit (Illumina, USA). A negative control library with nuclease-free water as input was included in each sequencing run. Paired-end illumina reads were analyzed using the following workflow that employed: FASTQC (v0.11.9) (Andrews, 2010 ) read-level quality control, Trim Galore (v0.6.10) (Krueger et al., 2023 ) quality filtering and adapter trimming, Minimap2 (v2.24) (Li, 2018 ) read mapping to MylCoV (KY799179.1) and EbCoV (OL415262.1) reference genomes, Samtools (v1.17) (Danecek et al., 2021 )/ iVar (v1.4.2) (Grubaugh et al., 2019 )/Seqtk (v1.3) (github.com/lh3/ seqtk) read mapping statistics, primer trimming and consensus generation, and bedtools (v2.30.0) (Quinlan and Hall, 2010 ) genome depth of coverage. For the enrichment-based sequencing, cDNA was prepared using Illumina RNA Prep with Enrichment (Illumina, USA) and the Pan-Coronavirus Panel (Illumina, USA) as per manufacturer’s instructions. Paired-end (2x150 bp) sequencing was performed on a Miniseq with a 300-cycle high Output reagent kit (Illumina, USA). A negative control library with nuclease-free water as input was included in each sequencing run. Paired-end illumina reads were analyzed using the following workflow that employed: FASTQC (v0.11.9) (Andrews, 2010 ) read-level quality control, Trim Galore (v0.6.10) (Krueger et al., 2023 ) quality filtering and adapter trimming, Megahit (v1.2.9) (Li et al., 2015 ) de-novo assembly, Minimap2 (v2.24) (Li, 2018 ) contig mapping to a multi-reference fasta, Samtools (v1.17) (Danecek et al., 2021 )/Seqtk (v1.3) (github.com/lh3/ seqtk) read mapping statistics and consensus generation, and bedtools (v2.30.0) (Quinlan and Hall, 2010 ) genome depth of coverage. One sample (EfONCAN22.320328) produced sufficient reads via the enrichment-based sequencing; reads from both amplicon-based and enrichment-based sequencing were combined to generate the EfONCAN22.320328 consensus. Targeted sequencing of the spike and ORF3 genes Spike gene sequences with an additional 200 flanking nucleotides for MylCoV (KY799179.1) and EbCoV (OL415262.1) were downloaded from NCBI. Primers located in the 200 nucleotide flanking regions were designed using PrimerQuest Tool (Integrated DNA Technologies, Coralville, IA, USA) resulting in the following primers: EbCoV spike forward 5’-TAGTGCGAAGTAACGCCAAG-3’ and EbCoV spike reverse 5’-GAACAAGAAGAGTCCTCCAATCA-3´ and MylCoV spike forward 5’-GGGTTCAGGGCCATTAGTT-3’ and MylCoV spike reverse 5’-CTGGTCAACAACAACAGCATC-3’. cDNA from pools and individual bat oral samples as described above were amplified with the following PCR reactions using the Q5® Hot Start High-Fidelity DNA Polymerase (New England Biolabs) : with 12.5 uL 2x PCR buffer, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 9.2 uL RNase-free water, and 2.5 uL of cDNA. Polymerase activation was carried out at 98°C for 30 seconds followed by 40 cycles of 2 steps: 98°C for 15 seconds and 65°C for 5 minutes + 10 seconds per cycle, with a final extension step of 72°C for 5 minutes and 4°C infinite hold. Amplified material was quantified using Qubit 4 with the dsDNA HS kit. Primers for MylCoV (KY799179.1) and EbCoV (OL415262.1) ORF3 genes, were generated using MacVector (Version 18.6.1), resulting in the following primers: EbCoV ORF3 forward 5’-ATGATTGGAGGACTCTTCTTGTTCTCAGTTG-3’ and EbCoV ORF3 reverse 5’-TTAAACAGCATCTTCGTAAAGTTTTTCATT-3´ and MylCoV ORF3 forward 5’-ATGTTTCTTGGACTTTTCCAGTAYACAATT-3’ and MylCoV ORF3 reverse 5’-TCAACTAGCTGAAGCATATTCAAGTTCGTC-3’. cDNA from pools and individual bat oral samples as described above were amplified in triplicate with the following PCR reactions using the Q5® Hot Start High-Fidelity DNA Polymerase (New England Biolabs): with 12.5 uL 2x PCR buffer, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 9.2 uL RNase-free water, and 2.5 uL of cDNA. Polymerase activation was carried out at 98°C for 30 seconds followed by 40 cycles of 3 steps: 98°C for 15 seconds, 59°C, 61°C or 65°C for 30 seconds, and 72°C for 1 minute, with a final extension step of 72°C for 5 minutes and 4°C infinite hold. Amplified material was quantified using Qubit 4 with the dsDNA HS kit. Libraries for both spike and ORF3 libraries were prepared using the Ligation Sequencing Kit SQK-LSK114.24) according to manufacturer’s protocol (version NBA_9168_v114_revM_15sep2022) and loaded on R.10.4 Flongle flow cells according to manufacturer’s protocol (version NBE_9169_v114_revR_15Sep2022) and sequenced on the MinION Mk1B nanopore sequencer. Basecalling and barcode and adapter trimming was performed using ONT guppy (v6.5.7 + ca6d6af) (gpu). Fastq reads were also filtered to remove reads < 450 bp using filtlong (v0.2.1) (Wick, 2021 ) and then aligned to a ORF3 or spike reference (MylCoV [KY799179.1] and EbCoV [OL415262.1]) using Minimap2 (v2.24) (Li, 2018 ). Consensus sequences were generated based on the best hit from alignment using samtools (v1.6) (Danecek et al., 2021 ), bcftools (v1.5) (Danecek et al., 2021 ) and seqtk (v1.3) (github.com/lh3/ seqtk) ; quality check reports were generated from bam files using qualimap (v2.2.2a) (Okonechnikov et al., 2016 ). Genomic and phylogenetic analyses Gaps in sequences generated from whole genome sequencing were filled in using targeted sequencing; sequences were manually combined in AliView (Larsson, 2014 ). Whole genome and gene level completeness for all sequences were calculated using R 4.2.3 with Biostrings package (2.66.0) against MylCoV (KY799179.1) and EbCoV (OL415262.1) reference genomes. Similarity analysis was conducted using SimPlot (Lole et al., 1999 ) .Whole genomes were identified using BLASTn against the core nucleotide database. Putative structural and non-structural proteins were investigated using NCBI ORF Finder ( https://www.ncbi.nlm.nih.gov/orffinder/ ) and were identified using BLASTp against the non-redundant protein sequences and UniProtKB/Swiss-Prot databases. Phylogenetic analysis was performed for whole genomes, ORF1ab, and S gene. Phylogenies included species in the genus Alphacoronavirus , with SARS-CoV-2 included as an outgroup representing Betacoronavirus . Nucleotide sequences were aligned in MAFFT (Katoh et al., 2019 ). Phylogenies were inferred using the Maximum Likelihood method using the GTR + G model in RaxML (Stamatakis, 2014 ). Bootstrap support values for each tree were estimated with 500 replicates. Phylogenies were visualized using R 4.2.3 with ggtree (v3.6.2), ggimage (v0.3.3), ggplot2 (v3.5.1), rphylopic (v1.4.0), treeio (v1.22.0), phylotools (v0.2.2), phytools (2.3-0), treetools (1.11.1), dplyr (1.1.4), and phangorn (2.11.1). Recombination analysis was performed with alpha-CoV sequences from the phylogenetic analysis including EfONCAN22.320328 and MlONCAN23.320388 using RDP4 (Martin et al., 2015 ) with seven analyses (RDP, GENECONV, Bootscan, Maxchi, Chimera. SiScan, 3Seq). We only considered recombination events of ≥ 1000 bp detected by at least five of the above-mentioned analyses (p < 0.05). Events with undetermined breakpoints were not considered. The degree of temporal signal for whole genome, ORF1ab, and S gene phylogenies were explored by plotting root-to-tip distances on the maximum likelihood phylogenies against sampling date via TempEst (Rambaut et al., 2016 ). Spike sequence analyses Amino acid sequences for alpha-CoVs included in the abovementioned phylogenetic analysis for S glycoprotein S1 and S2 subunits were downloaded from NCBI. Pairwise amino acid identity analysis were carried out for EfONCAN22.320328 and MlONCAN23.320388 as they represented the most complete sequences generated in this study; nucleotide sequences were translated to amino acid in AliView (Larsson, 2014 ). All S1 and S2 sequences were aligned via MAFFT (Katoh et al., 2019 ). Pairwise amino acid identity of EfONCAN22.320328 and MlONCAN23.320388 against all alpha-CoV S1 and S2 subunit sequences were calculated using R 4.2.3 with Biostrings package (2.66.0). A heatmap of resultant pairwise identities was generated using R 4.2.3 using packages ggplot2 (v3.5.1) and tidyr (v1.3.1). A phylogenetic approach employing HyPhy (Kosakovsky Pond et al., 2020 ) was used to assess for signatures of selection for EfONCAN22.320328 and MlONCAN23.320388 relative to the wider EbCoV and MylCoV clades, respectively. Spike genes in EfONCAN22.320328 and MlONCAN23.320388 were identified using VADR (v1.6.4) with the pan-coronaviridae v1.3.3 library. Aligning sections of related genomes were identified and extracted using NCBI BLAST+ (v2.16) with the nucleotide core database and biopython (v1.84). Sequences were then translated into amino acids using transeq from EMBOSS v6.6.0 and alignments were generated using MAFFT. The codon alignments were generated using PAL2NAL (v14). Codon-alignment for EbCoV included: EfONCAN22.320328, OL410608.1, OL410607.1, OL415262.1, OL415261.1, OL410610.1, OL410609.1, MW924112.1, MZ293737.1, MZ293738.1, and OP715781.1. The codon-alignment for MylCoV included: KY799179.1, NC_022103.1, and MZ081396.1. Few complete sequences related to MlONCAN23.320388 were available which precluded analysis of the S1 subunit. Signatures of positive selection were evaluated using HyPhy’s mixed-effects model of evolution (MEME) (Murrell et al., 2012 ), Contrast Fixed-Effects Likelihood (Contrast-FEL) (Kosakovsky Pond and Frost, 2005 ), adaptive branch-site random effects likelihood (aBSREL) method (Smith et al., 2015 ), and RELAX (Wertheim et al., 2015 ). Predicted RBD were obtained from S1 subunit amino acid alignment of EfONCAN22.320328 and MlONCAN23.320388 with other alpha-CoV species, including: Ebcov (UNE74476.1), HCQD-2020 (UED13287.1), Mylcov (ASL23654.1), CDPHE15 (YP_008439202.1), HCoV-NL63 (AGT51331.1), HCoV-229E (APT69883.1), and PEDV (NP_598310.1). RBD sequences of EfONCAN22.320328 and MlONCAN23.320388 were submitted to Alphafold 3 (AlphaFold Server; https://alphafoldserver.com ) to obtain a prediction of the tertiary structures. Figures of the predicted structures were obtained using Pymol (Schrodinger; https://www.schrodinger.com/ ). Additionally, we investigated for the presence of Furin cleavage sites for viruses within the EbCoV and MylCoV clades using ProP (Duckert et al., 2004 ). ORF3 characterization - luciferase reporter assays The ORF3 gene from MlONCAN23.320388 and EfONCAN22.320328 were synthesized through GenScript, and the expression plasmids (pcDNA3.1 (+) - MylORF3 and pcDNA3.1(+) - EbORF3) were subsequently scaled up in E. coli Stabl3 cells. For the IFNβ promoter assay, HEK293T cells (.75 x 10 5 cells per well in a 24-well plate) were co-transfected with 20 ng of IFNβ promoter reporter plasmid, 10 ng of Renilla luciferase plasmid, and 200 ng of ORF3 expression plasmid using Lipofectamine™ 3000 transfection reagent (Invitrogen). At 24 hours post-transfection, cells were treated with 2µg/well high molecular weight polyI:C (InvivoGen). Sixteen hours post-treatment, cells were lysed and analyzed using dual-luciferase reporter assays according to the manufacturer’s instructions (Promega). For the ISRE promoter assay, HEK293T cells (.75 x 10 5 cells per well in a 24-well plate) were co-transfected with 250 ng of ISRE promoter reporter plasmid, 10 ng of Renilla luciferase plasmid, and 200 ng of viral ORF3 expression plasmid. At 24 hours post-transfection, cells were exposed to 100 units per well of human IFNβ for 16 hours, followed by analysis using the dual-luciferase reporter assay which was performed as per manufacturer’s instructions (Promega). Luciferase levels were measured by GloMax® 20/20 Luminometer (Promega). Immunoblot Cells were harvested in Passive Lysis 5X Buffer (Promega). Protein samples were resolved on a 12% SDS-polyacrylamide gel and transferred onto a polyvinylidene difluoride (PVDF) membrane using the Trans-Blot Turbo Transfer System (Bio-Rad). The membrane was blocked for 1 hour and then probed with anti-FLAG (mouse, 1:2000 dilution) (Millipore sigma) and anti-GAPDH (rabbit, 1:2000 dilution) (Millipore sigma) primary antibodies. After incubation with respective secondary antibodies (1:10,000 dilution), the proteins were visualized using an Odyssey CLx imager (Licor Bio). Declarations Acknowledgements: This project was supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (RGPIN-2020-06199), Canadian Institutes of Health Research (CIHR) operating grant (MM1174925) and project grant (PJT186217). Sample collection from wild bats was supported by the Government of Ontario, the Canadian Wildlife Service, and the Canadian Safety and Security Program. J.D.K. was supported by an AMMI Canada/BioMérieux Fellowship in Microbial Diagnostics. Research within A.B.’s lab is supported by an NSERC Discovery Grant (RGPIN-2022-03010), Canadian Institutes of Health Research (CIHR) – Institute for Infection and Immunity Early Career Research grant (PTT-192089), CIHR - Pandemic Preparedness and Health Emergencies Early Career Investigator grant (PEE-183995), and CIHR-Institute for Infection and Immunity, Project grant (PJT-195787). VIDO receives operational funding from the Government of Saskatchewan through Innovation Saskatchewan and the Ministry of Agriculture and from the Canada Foundation for Innovation through the Major Science Initiatives Fund. Thanks to E. Allen, T. Ambeau, A. Anderson, L. Crawshaw, S. Davison, R. Dillon, E. Elizondo, L. Hooton, A. Kowalchuk-Reid, S. Laursen, C. Menzies, C. Pearson, E. Maquignaz, E. Nkwonta, L. Scott, E. Stukenholtz, T. Thorne, C. Turenne, K. Vanderwolf, and D. White for assistance collecting samples in the field. Inclusion and diversity: We support inclusive, diverse, and equitable conduct of research. Author contributions: Conceptualization: JDK, SM, CD, AB, VM; Sample collection: CD, VVZ, JDK, SM, KAW; Laboratory analysis: JDK, AH, HYC, JBS, EC, LY, WY, AB, PS; Data analysis/investigation: JDK, FM, AB, GG, DB; Resources: QL, AK; Writing – original draft: JDK, CD; Writing – review & editing: all authors; Visualization: JDK, AB, CD; Supervision: SM, CD, FM, AB; Funding acquisition: SM, CD, AB Data availability: Partial genome sequences generated in this study have been deposited on NCBI GenBank under accession numbers PQ554521-PQ554525. Code availability: Code for analysis and visualization is available through https://github.com/jkotwa/bat-alphacov-analyses. References Andrews, S., 2010. FastQC: a quality control tool for high throughput sequence data. 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Sci. 159, 146–159. https://doi.org/10.1016/j.rvsc.2023.03.022 Additional Declarations No competing interests reported. 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(A) \u003c/strong\u003eMap of the southwestern and eastern regions of Ontario, Canada. Bat sampling location types are indicated, and a breakdown of species sampled at each location is shown via pie chart. Location of study region within Canada is shown in inset. Pan-coronavirus RT-PCR detection in (B) oral swab RNA pools and (C) individual oral swab samples. Proportion of positives (%) are shown at the end of each bar.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/6b354fe5459e43bcec504319.png"},{"id":73883534,"identity":"3fed2a88-5ccd-4e27-87d9-057d8fc33a7c","added_by":"auto","created_at":"2025-01-15 14:16:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62867,"visible":true,"origin":"","legend":"\u003cp\u003eSimilarity analysis of (A) EfONCAN22.320328 with EfONCAN21.4185, OL415262.1, OL410608.1, OL415261.1, MZ293738.1, and MW924112.1 and (B) MlONCAN23.320388 with MlONCAN21.3592, MlONCAN23.320392, KY799179.1, and NC_022103.1. Genome organization for MylCoV (KY799179.1) and EbCoV (OL415262.1) are on the bottom of each plot. (C) Phylogenetic analysis of complete genome sequences was performed in RAxML using maximum likelihood method along with a GTR + G substitution model. Support calculated with bootstrap analysis (500 replicates) for common ancestors above the specified outgroup are indicated with pie charts (purple); bootstrap support \u0026lt;75 are not shown. Sequences derived from this study are highlighted. Scale bar represents nucleotide substitutions. Green boxes indicate the continental origins of bat-derived coronaviruses (light green: North America; dark green: East and South Asia).\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/7f0bfa7ee46a95ddc645f835.png"},{"id":73883540,"identity":"0b2af07f-a5bf-4d58-adcf-e5be6e66780b","added_by":"auto","created_at":"2025-01-15 14:16:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":148044,"visible":true,"origin":"","legend":"\u003cp\u003eTanglegram showing maximum-likelihood trees estimated with RAxML from select alpha-CoV between whole genomes and (A) ORF1ab (B) spike genes with SARS-CoV-2 as an outgroup. Support calculated with bootstrap analysis (500 replicates) are indicated with pie charts (black). Links between the phylogenies link tips belonging to the same sequence to compare tree topologies. Blue and purple linkages represent Myotis bat coronaviruses and Eptesicus bat coronaviruses, respectively. Sequences from this study are highlighted in grey.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/53d2cdc032e5ec7f9dfc673c.png"},{"id":73883539,"identity":"2ba34e2e-da70-415c-8762-9f5a61b6fdb0","added_by":"auto","created_at":"2025-01-15 14:16:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":177825,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003eA) Heatmap of pairwise amino acid identity for S1 and S2 subunits of the S glycoprotein of EfONCAN22.320328 and MlONCAN23.320388 compared to alpha-CoVs included in the phylogenetic analysis. (B) Amino acid sequence alignment of receptor-binding domains (RBDs) of EfONCAN22.320328 and closely related sequences (purple), MlONCAN23.320388 and closely related sequences (blue), HCoV-NL63, HCoV-299E, and PEDV. Bolded residues highlight differences between the Ontario-derived sequences and closely related sequences. Residues highlighted in grey are predicted receptor-binding motifs (RBMs) or known RBMs of HCoV-NL63 and HCoV-229E. Key receptor binding residues for HCoV-NL63 (human ACE2) and HCoV-29E (human aminopeptidase N) are underlined. Predicted structures of EfONCAN22.320328 RBD (C) and MlONCAN23.320388 RBD (D); in the surface model on the left, loops predicted to interact with unknown receptors are shown in grey. On the right, ribbon diagrams of predicted RBDs show the reliability of modeling prediction per residue.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/b44539b77ee2c9a631195123.png"},{"id":73883538,"identity":"d6fae302-b155-4dab-8fcf-0b44ea63c078","added_by":"auto","created_at":"2025-01-15 14:16:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBat alpha-CoV ORF3 inhibits Type I interferon (IFN) response\u003c/strong\u003e. (A) IFNβ promoter luciferase assay. HEK293T cells were co-transfected with Firefly luciferase reporter plasmid, Renilla luciferase control plasmid and viral protein expressing plasmid. Empty vector and PEDV ORF3 were used as controls. At 24 hours post-transfection, cells were treated with 2µg/well poly IC for 16 h, followed by dual-luciferase reporter assays. The data were analyzed by normalizing the Firefly luciferase activity to the Renilla luciferase (Rluc) activity and then normalized by IFNβ promoter only samples to obtain fold induction. IFNβ control was set to 100%. Statistics were determined by comparing with empty vector control and one-way ANOVA with Šídák's multiple comparisons test, ****p \u0026lt; 0.0001. (B) ISRE promoter luciferase assay. HEK293T cells were co-transfected with an ISRE promoter-driven Firefly luciferase reporter plasmid, Renilla luciferase control plasmid, and viral protein expressing plasmid. At 24 hpt, cells were treated with 100 U/well IFNβ for 16 h, followed by dual-luciferase reporter assays. Data processing was the same as described in panel A. Statistical values were determined by comparing with empty vector control and one-way ANOVA with Šídák's multiple comparisons test, **p \u0026lt; 0.01, *p \u0026lt; 0.05. (C) ORF3 and GAPDH protein expression were confirmed by immunoblot analysis using anti-FLAG antibody. (D) Schematic representation of ORF3 mediated inhibition of IFNβ production and signaling.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/b285ddd73108cf90dddceb3b.png"},{"id":73884721,"identity":"75b36307-a156-460e-9461-ce778c51e6a7","added_by":"auto","created_at":"2025-01-15 14:24:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1780126,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/5fd4d67f-9c6e-49e7-9f27-faba8600250d.pdf"},{"id":73883536,"identity":"44f19263-2b62-49c3-bc92-f25667ab4e06","added_by":"auto","created_at":"2025-01-15 14:16:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":39745,"visible":true,"origin":"","legend":"","description":"","filename":"npjvirusSupplementaryinformation12122024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5633972/v1/6fcb57cfda1d487e6f263936.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High host specificity of alphacoronaviruses in Nearctic, insectivorous bats","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBats represent over 1470 species in the order Chiroptera and perform critical ecosystem services including pollination, seed dispersal, and pest control (Beilke and O\u0026rsquo;Keefe, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ripperger et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Bats are hosts to an exceptional diversity of coronaviruses; a recent estimate suggests that more than 4,800 coronaviruses have been detected in just 543 of known bat species (Ruiz-Aravena et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Most of these are not associated with current human or livestock disease, but bat-derived coronaviruses also include close relatives of several coronaviruses that are of high consequence to public health and bear devastating impacts on livestock health and the global economy. Well-known examples include severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, Middle East respiratory syndrome coronavirus (MERS-CoV), porcine epidemic diarrhea virus (PEDV), and swine acute diarrhea syndrome coronavirus (SADS-CoV) (Banerjee et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Plowright et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost research on bat-borne coronaviruses has focused on bat species in Asia, Europe and Africa, and far fewer studies have investigated viral diversity in North American bats (Hern\u0026aacute;ndez-Aguilar et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ruiz-Aravena et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), particularly in Canada. Moreover, full genomes are only available for two bat coronaviruses in North America: the Myotis lucifugus coronavirus (MylCoV) from Manitoba, Canada (Subudhi et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Colorado, USA (NC_022103.1), and Eptesicus bat coronavirus (EbCoV) from South Dakota, USA (Schaeffer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A more complete characterization of viral diversity in temperate, North American bats is critical to assessing potential zoonotic risk (Letko et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, surveillance programs can help us monitor the impacts of identified coronaviruses on the transmission between and health of host bat populations. As many of Canada\u0026rsquo;s bat species are assessed as Endangered (Canada, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), understanding the effects of coronaviruses on bat hosts is vital for informing species\u0026rsquo; recovery strategies.\u003c/p\u003e \u003cp\u003eCoronaviruses\u0026rsquo; structural, non-structural, and accessory proteins shape their pathogenesis and host-virus interactions, particularly with bat hosts that exhibit some down-regulated immunological responses during hibernation. Non-structural and structural proteins are essential for virus replication and progeny virion production. Importantly, the structural spike protein is responsible for binding the host receptor thereby governing species specificity (Li, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Accessory proteins are not required for virus replication but are critical for host antiviral response modulation and pathogenesis. For example, human and porcine alphacoronaviruses (alpha-CoVs) have evolved accessory proteins to suppress the antiviral type I interferon (IFN) response in humans and pigs, respectively (Kaewborisuth et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, PEDV open reading frame 3 (ORF3) protein can suppress the type I interferon (IFN) response in host cell, and inhibit polyinosinic:polycytidylic acid (poly(i:c)) induced type I IFN production and downstream signaling in human embryonic kidney (HEK) cells (Kaewborisuth et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Reporter assays and VSV-GFP bioassays in HeLa cells also demonstrated that PEDV ORF3 functions as an IFN antagonist (Zhang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Understanding viral immune evasion strategies of bat-derived coronaviruses can contribute to risk assessments through the potential determinants of viral pathogenesis as well as aid in the development of targeted antiviral therapeutics.\u003c/p\u003e \u003cp\u003eTo improve our understanding of bat coronavirus diversity in North American bats, we sought to identify and characterize coronaviruses in five bat species in eastern Ontario, Canada with similar ecological roles: \u003cem\u003eEptesicus fuscus, Myotis lucifugus\u003c/em\u003e, \u003cem\u003eMyotis leibii\u003c/em\u003e, \u003cem\u003ePerimyotis subflavus\u003c/em\u003e, and \u003cem\u003eMyotis septentrionalis\u003c/em\u003e. All five species are insectivorous, undertake regional migrations between their summer and over-wintering habitats, and survive the winter by hibernating, usually in caves and abandoned mines (Fenton, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). We sampled free-ranging bats and used nested real-time polymerase chain reaction (RT-PCR) to identify coronavirus-positive bat samples, followed by whole genome sequencing to determine the genome sequence of two bat-derived alpha-CoVs. We performed phylogenetic analyses to characterize the relatedness of these viruses to other coronaviruses, focusing on bat, human and other animal alpha-CoVs. Finally, we focused on two key host-pathogen interactions, including exploration of spike diversity and candidate host cell receptors, and functional characterization of ORF3 from both viruses to determine their abilities to inhibit innate antiviral IFN-dependent responses. Taken together, our study reports the discovery of two alpha-CoVs in insectivorous Nearctic bats found in Canada. These viruses are closely related to other circulating coronaviruses in bats in North America and Asia. Our study further highlights the diversity of genome structure and function among bat-borne coronaviruses in a previously under sampled region.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTwo alpha-CoVs detected in bats in Eastern Ontario, Canada\u003c/h2\u003e \u003cp\u003eWe collected oral swabs from 390 individuals across five species of Vespertilionid bats. We collected these samples from five roosting sites in Ontario between 2020\u0026ndash;2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), and tested 131 pools of samples using a pan-coronavirus RT-PCR. Viral RNA was detected from 8 pools (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). These included one \u003cem\u003eMyotis leibii\u003c/em\u003e pool and two \u003cem\u003eMyotis septentrionalis\u003c/em\u003e pools, for which original individual material was not available for repeat testing, and which were therefore considered inconclusive. However, individual samples were tested from the other pools, yielding positive coronavirus detections from two \u003cem\u003eEptesicus fuscus\u003c/em\u003e (1.9%; 2/107) and three \u003cem\u003eMyotis lucifugus\u003c/em\u003e (2.0%; 3/150) samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThe five bats that yielded positive samples included a female \u003cem\u003eM. lucifugus\u003c/em\u003e and female \u003cem\u003eE. fuscus\u003c/em\u003e sampled during swarming at two distinct hibernacula in July and August, 2021, a female \u003cem\u003eE. fuscus\u003c/em\u003e sampled at a maternity colony in late July 2022, and two \u003cem\u003eM. lucifugus\u003c/em\u003e of unknown sex sampled during late hibernation at a third hibernaculum in March 2023. Overall, two alpha-CoVs were detected between four of the five sampling locations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePartial RNA-dependent RNA-polymerase (RdRp) amplicon sequencing (556 bp) resulted in five partial RdRp consensus sequences (average 61,000x depth of coverage); product from three pooled samples (one \u003cem\u003eMyotis leibii\u003c/em\u003e pool and two \u003cem\u003eMyotis septentrionalis\u003c/em\u003e pools) could not be sequenced due to low viral RNA quantity.\u003c/p\u003e \u003cp\u003e \u003cem\u003eEptesicus fuscus-\u003c/em\u003ederived partial RdRp sequences were highly similar (95\u0026ndash;97%) to Eptesicus bat coronavirus (EbCoV) sequences from recently sampled \u003cem\u003eE. fuscus\u003c/em\u003e in South Dakota, USA (Schaeffer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The \u003cem\u003eE. fuscus\u003c/em\u003e partial RdRp sequences were also highly similar to \u003cem\u003eEptesicus serotinus-\u003c/em\u003ederived alphacoronavirus HCQD-2020 (97%) (HCQD-2020; South Korea) (Do et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Bat Coronavirus EsJX20 (97%) (EsJX20; China), and Pipistrellus bat coronaviruses (97%) (Pakistan) from \u003cem\u003ePipistrellus\u003c/em\u003e spp.. \u003cem\u003eMyotis lucifugus-\u003c/em\u003ederived partial RdRp sequences in this study were highly similar (95\u0026ndash;97%) to Myotis lucifugus coronavirus (MylCoV) and Bat coronavirus CDPHE15/USA/2006 (CDPHE15) reported in \u003cem\u003eM. lucifugus\u003c/em\u003e in Manitoba, Canada and Colorado, USA, respectively, as well as partial alpha-CoV sequences from \u003cem\u003eMyotis occultus\u003c/em\u003e from Colorado, USA (EF544565.1).\u003c/p\u003e \u003cp\u003eWhole-genome sequencing for the positive samples generated near-complete and partial genomes from all samples, with genome completeness ranging from 63\u0026ndash;97% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Individual, gene-level completeness was inferred using MylCoV (KY799179.1) and EbCoV (OL415262.1) as reference genomes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similar to the partial RdRp results, the \u003cem\u003eE. fuscus-\u003c/em\u003ederived sequences (EfONCAN) were highly similar to EbCoV, HCQD-2020, and Pipistrellus bat coronavirus whole genomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The \u003cem\u003eMyotis lucifugus-\u003c/em\u003ederived sequences (MlONCAN), were highly similar to MylCoV and CDPHE15 whole genomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Similarity was high for all genes except for the region corresponding to the spike gene for both \u003cem\u003eM. lucifugus-\u003c/em\u003e and \u003cem\u003eE. fuscus-\u003c/em\u003ederived sequences, with a particular divergence within the S1 subunit (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWhole genome and gene completeness (%) of \u0026ge;\u0026thinsp;10x coverage for coronaviruses sampled from big brown bats (\u003cem\u003eEptesicus fuscus)\u003c/em\u003e and little brown bats (\u003cem\u003eMyotis lucifugus)\u003c/em\u003e in Ontario, Canada.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhole genome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eORF1ab\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpike\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eORF3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEnvelope\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMembrane\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNucleocapsid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eORF7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEfONCAN21.4185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.09*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.95*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e77.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEfONCAN22.320328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92.47*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96.75*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e98.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMlONCAN21.3592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e95.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMlONCAN23.320388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97.01*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.37*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e98.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMlONCAN23.320392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.75*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e* Gaps filled in with partial RdRp sequencing or targeted sequencing\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenomic characterization of Ontario Eptesicus bat coronavirus and Myotis lucifugus coronaviruses\u003c/h3\u003e\n\u003cp\u003eThe two \u003cem\u003eEptesicus-\u003c/em\u003ederived coronavirus genomes shared 98% nucleotide identity with each other. Open reading frame (ORF) and BLASTp analysis of EfONCAN22.320328 identified genes that encode the replicase polyprotein ORF1ab (partial), spike glycoprotein (S), envelope protein (E), membrane protein (M), and nucleocapsid protein (N). Accessory genes ORF3 and ORF7 were located between S and E and after N, respectively. All proteins were most similar to EbCoV identified in bats in South Dakota, USA, (Schaeffer et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) with the exception of E, which was closely related to \u003cem\u003eEptesicus serotinus-\u003c/em\u003ederived HCQD-2020 (Do. et al. 2020). All proteins shared a 97% or greater identity with EbCoV and HCQD-2020 with the exception of S, which ranged from 91\u0026ndash;95% identity. Apart from bat coronaviruses, BLASTp analysis revealed relatedness of EfONCAN22.320328 proteins with proteins from a wider group of alpha-CoVs including: human coronaviruses (HCoV)-229E (35\u0026ndash;76%) and NL63 (33\u0026ndash;76%), feline infectious peritonitis virus (30\u0026ndash;71%), canine coronavirus (28\u0026ndash;48%), swine acute diarrhea syndrome coronavirus (36\u0026ndash;76%), and PEDV (35\u0026ndash;76%). Notably, ORF7 appears to be unique to alpha-CoVs identified in \u003cem\u003eE. fuscus\u003c/em\u003e, \u003cem\u003eE. serotinus\u003c/em\u003e, Pipistrellus spp. and \u003cem\u003eTadarida brasiliensis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eMyotis lucifugus\u003c/em\u003e-derived coronavirus genomes shared 98% nucleotide identity with each other. Open reading frame and BLASTp analysis of MlONCAN23.320388 identified genes that encode for ORF1ab, S glycoprotein, ORF3 accessory protein, E protein, M protein, and N protein, but not ORF7. With the exception of the S glycoprotein, all proteins shared a\u0026thinsp;\u0026gt;\u0026thinsp;97% homology with MylCoV from Manitoba and CDPHE15; the S glycoprotein was 94% identical to MylCoV and 74% identical to CDPHE15. BLASTp further revealed more distant relatedness of MlONCAN23.320388 proteins to HCoV-229E (39\u0026ndash;75%) and NL63 (42\u0026ndash;76%), feline infectious peritonitis virus (31\u0026ndash;71%), canine coronavirus (33\u0026ndash;45%), and PEDV (44\u0026ndash;82%). MlONCAN23.320388 was more closely related to PEDV compared to EfONCAN22.320328, including the ORF3 (MlONCAN23.320388 [52%] vs EfONCAN22.320328 [36%]).\u003c/p\u003e\n\u003ch3\u003ePhylogenetic analysis\u003c/h3\u003e\n\u003cp\u003eBased on the whole-genome phylogeny, the Eptesicus bat coronaviruses from Ontario clustered in a well-supported, monophyletic clade with other North American Eptesicus bat coronavirus sequences, Asian coronaviruses sampled from \u003cem\u003eE. serotinus\u003c/em\u003e, including HCQD-2020 (South Korea), EsJX20 (China), and with a Pipistrellus bat coronavirus (Pakistan) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC); we will herein refer to this clade as EbCoV (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). This clade is most closely related to bat coronavirus McGD16 from a \u003cem\u003eMyotis chinensis\u003c/em\u003e sampled in China. The Ontario Myotis lucifugus coronaviruses clustered in a well-supported, monophyletic clade with other Myotis lucifugus coronavirus sequences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC); we will refer to this group of viruses as MylCoV (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). This clade is sister to a clade including BtCoV/512/2005 from a \u003cem\u003eScotophilus kuhlii\u003c/em\u003e sampled in China, bat coronavirus MrGD17 from a \u003cem\u003eMyotis ricketti\u003c/em\u003e bat in China, and PEDV.\u003c/p\u003e \u003cp\u003eThese Eptesicus bat and Myotis bat coronavirus sequences cluster together in a larger, monophyletic clade that also includes HCoV-229E and NL63, and Bat coronaviruses 1A and 1B (sampled from \u003cem\u003eMiniopterus magnater\u003c/em\u003e and \u003cem\u003eMiniopterus pusillus\u003c/em\u003e, respectively, in Hong Kong). Falling outside this larger group is a well-supported sister clade containing bat coronavirus HKU2 (from a Rhinolophid bat sampled in Hong Kong), and swine acute diarrhea syndrome coronavirus (SADS-CoV). Highly similar tree topology was observed with the ORF1ab phylogeny (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis of the S gene sequences also indicated the Ontario Eptesicus bat coronaviruses clustered in a well-supported monophyletic clade with other EbCoV sequences including HCQD-2020 (South Korea) and Pipistrellus bat coronavirus (Pakistan) apart from EsJX20 (China) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB); EsJX20 clustered with BtCoV/512/2005 (China), MrGD17 (China), and PEDV (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Notably, the S gene within the Eptesicus bat clade is more closely related to companion and livestock animal coronaviruses (e.g., canine coronavirus, feline infectious peritonitis virus, transmissible gastroenteritis virus) than McGD16 (China) as seen in the whole genome phylogeny (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The Ontario Myotis lucifugus coronaviruses clustered in a well-supported monophyletic clade with other MylCoV sequences. Similar to the whole-genome phylogeny, the \u003cem\u003eMyotis\u003c/em\u003e bat clade is most closely related to a sister clade comprising BtCoV/512/2005, bat coronavirus MrGD17, PEDV, as well as EsJX20 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\n\u003ch3\u003eGenomic characterization of the spike gene\u003c/h3\u003e\n\u003cp\u003ePairwise amino acid identity of S1 and S2 subunits of the S glycoprotein of EfONCAN22.320328 and MlONCAN23.320388 were compared to alpha-CoVs from the phylogenetic analysis. In general, there was a greater homology for the S2 subunit (68%) compared to the S1 subunit (52%) across alpha-CoV sequences for both Ontario EbCoV and MylCoV (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Our observations were consistent when comparing amino acid sequences derived from similar species; EbCoV related amino acid sequences had a higher average percent identity in the S2 subunit (97%) compared to the S1 subunit (90%) and MylCoV related amino acid sequences had a higher average percent identity in the S2 subunit (95%) compared to the S1 subunit (76%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). For EbCoV, despite variation in S1, receptor binding domain (RBD) homology remained high (95\u0026ndash;98%) when compared to all but one South Dakota origin EbCoV sequence (72%) but was lower compared to HCQD-2020 (64%) and Pipistrellus bat coronavirus (63%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Receptor binding domain homology was greatest between Ontario and Manitoba derived sequences (92%) and substantially lower when compared to CDPHE15 (75%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). No correlation was found between sampling times and root-to-tip genetic distances for whole genomes (Corr\u0026thinsp;=\u0026thinsp;0.2347, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0551), ORF1ab (Corr\u0026thinsp;=\u0026thinsp;0.3566, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.1272), or S genes (Corr=-0.0693, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0048), thereby precluding molecular clock analysis. Several significant recombination events were detected involving EbCoV sensu sequences (Supplementary Table\u0026nbsp;1). Four events involved regions corresponding to the spike gene were detected, all of which included EbCoV sequences from South Dakota (Schaeffer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) as the recombinant, and major and minor parents.\u003c/p\u003e \u003cp\u003eTo characterize signatures of selection within EbCoV and MylCoV, we generated codon-alignment phylogenies for S gene sequences and applied selection methods from HyPhy (Kosakovsky Pond et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Evidence of positive selection (P\u0026thinsp;\u0026le;\u0026thinsp;0.05) was found at eight sites for the EbCoV clade (291S, 372N, 532G, 565V, 607I, 703V, 681N, 797T) and three sites (1121D, 1185P, 1292D) for the MylCoV clade. Sites are relative to the S protein of EfONCAN22.320328 and MlONCAN23.320388 for EbCoV and MylCoV, respectively. Notably, all but one site (797T) under positive selective pressure in the EbCoV clade were located in the S1 subunit of which two (328G, 361V) were in the RBD. Relative to other EbCoVs, evidence of a different dN/dS ratio (q threshold 0.2) in EfONCAN22.320328 was detected at one site (1179Q) using constrast-FEL; no significant results were found with aBSREL or RELAX. No significant difference in for MlONCAN23.320388 relative to the rest of the MylCoV clade were detected.\u003c/p\u003e \u003cp\u003eTo gain better insight in the structural properties, we predicted the RBD structure of EfONCAN22.320328 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and MlONCAN23.320388 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) using AlphaFold. While the prediction score is high for the core of the RBDs, whose folding resembles those of other alpha-CoVs, the loops at the interface of interaction with yet-to-identify receptors (highlighted in light grey) possess a lower score, as the spatial location in absence of the interactor(s) is difficult to predict (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, D). Additionally, no furin cleavage site motif was identified at the S1/S2 boundary for either the EbCoV or MylCoV clades. A predicted propeptide S2\u0026rsquo; cleavage site (KR\u003csub\u003e858\u003c/sub\u003e\u0026darr;S) was identified (prediction score\u0026thinsp;=\u0026thinsp;0.542) in EfONCAN22.320328. This S2\u0026rsquo; cleavage site was found to occur in the viruses comprising the EbCoV clade, with the exception of the Pipistrellus bat coronavirus (MZ293738.1) and EsJX20 (OQ175260.1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eBat alpha-CoV ORF3 inhibits antiviral type I interferon response\u003c/h3\u003e\n\u003cp\u003eTo test whether EbCoV (EfONCAN22.320328) and MylCoV (MlONCAN23.320388) ORF3 accessory protein can inhibit the human IFN response, we assessed the modulation of the human IFNβ promoter and interferon stimulated gene (ISG) promoter activity by EbCoV and MylCoV ORF3 proteins. HEK293T cells that expressed PEDV, MylCoV, and EbCoV ORF3 proteins exhibited significantly reduced IFNβ promoter-driven luciferase expression upon poly (I:C) stimulation, relative to pcDNA transfected controls. Among the three alpha-CoV ORF3 proteins tested, EbCoV ORF3 demonstrated the most potent inhibitory effect, reducing luciferase activity by 2.5-fold. MylCoV ORF3 suppressed luciferase activity by two-fold, while PEDV ORF3 demonstrated a 1.5-fold inhibition in luciferase expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). We also screened these viral proteins for their ability to suppress human type I IFN signaling using a plasmid containing a luciferase reporter driven by an interferon-stimulated response element (ISRE) promoter. ORF3 proteins from all three alpha-CoVs significantly suppressed ISRE promoter driven luciferase expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). PEDV ORF3 exhibited the strongest inhibition of ISRE promoter activity, and EbCoV and MylCoV ORF3 proteins inhibited ISRE promoter activity by six- and seven-fold, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We confirmed ORF3 protein and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression by immunoblot analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first survey for coronaviruses in bats in Ontario, Canada, and resulted in the detection of two different alpha-CoVs. We did not find evidence of cross-species transmission despite sampling five species at sites where they co-occur and share hibernacula. The \u003cem\u003eE. fuscus-\u003c/em\u003ederived coronaviruses we detected were most closely related to EbCoVs from \u003cem\u003eE. fuscus\u003c/em\u003e in South Dakota, USA (Schaeffer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and the coronaviruses we sampled from \u003cem\u003eM. lucifugus\u003c/em\u003e were most closely related to coronaviruses from \u003cem\u003eM. lucifugus\u003c/em\u003e in Manitoba, Canada (Subudhi et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Colorado, USA (NC_022103.1). We observed remarkable similarity between Eptesicus coronaviruses detected in this study, and coronaviruses sampled from \u003cem\u003eE. serotinus\u003c/em\u003e from South Korea (Do et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)and \u003cem\u003ePipistrellus\u003c/em\u003e sp. from Pakistan. The detection of highly related coronaviruses in geographically distant bats suggests long-term evolutionary interactions within bat-coronavirus assemblages (Cui et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Leopardi et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vijaykrishna et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The observed phylogeny implies infrequent spillover events interspersed with periods of high host specificity, possibly mediated by high interspecific variation in spike proteins. Our finding that EbCoV and MylCoV ORF3 accessory proteins can inhibit human interferon responses \u003cem\u003ein vitro\u003c/em\u003e requires further consideration. This result cannot directly predict spillover risk but has potential implications for risk assessments where bats cohabit with humans and livestock.\u003c/p\u003e \u003cp\u003eNeither evolutionary host relationships nor geographic distance can fully explain the observed phylogeny, which is probably a product of both factors. The phylogeny generally resolved two groups consistent with the bat Suborders Yinpterochiroptera and Yangochiroptera (Teeling et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, our phylogeny included only a single sequence sampled from a Yinpterochiropteran host (Bat Coronavirus HKU2, EF2030065.1, sampled from a Rhinolophid bat). Our analysis placed HCoV-NL63 and 229E as a sister clade to viruses sampled from Yangochiropteran hosts, but HCoV-NL63 was previously shown to be closely related to coronaviruses isolated from the Yinpterochiropteran genera \u003cem\u003eHipposideros\u003c/em\u003e and \u003cem\u003eTriaenops\u003c/em\u003e (Tao et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The evolutionary relationships estimated for viruses sampled from members of the family Miniopteridae, and the Vespertilionid subfamilies Myotinae and Vespertilioninae were also incongruent with host phylogeny. For example, coronavirus sampled from \u003cem\u003eM. chinensis\u003c/em\u003e fell into a clade comprised mostly of EbCoVs, although the relationship between these viruses was not close (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThese exceptions, and the interspersion of swine and human coronaviruses across the phylogeny, imply ongoing, occasional viral transmission among species. The direction of transmission is unclear, and coronaviruses can move between hosts by the respiratory route after contact with excreta (Plowright et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, plausible scenarios include bat-to-human, bat-to-livestock, human-to-bat and livestock-to-bat transmission, and transmission through one or more intermediate hosts. The current data do not allow us to assess the relative likelihood of these scenarios, nor are they evidence that the EbCoV or MylCoV we detected are likely to spill over to human hosts. However, these viruses merit further research, including explorations of the role of host ecology in the evolution of bat coronaviruses and broader host-pathogen interactions.\u003c/p\u003e \u003cp\u003eThe apparent host-specificity of MylCoV and the North American EbCoV in this study contrasts with the frequent roost-sharing exhibited by these two relatively common species, which often form maternity colonies in buildings, and hibernate in the same underground features. The well-supported, distantly related MylCoV and EbCoV clades (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) suggest high host specificity of EbCoV and MylCoV in their North American hosts. In contrast, EbCoV isolated from \u003cem\u003eE. fuscus\u003c/em\u003e is closely related to EbCoV from Asian \u003cem\u003eE. serotinus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; Schaeffer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which seems surprising given the substantial geographic distance between the sampling locations. We can only speculate as to the mechanisms maintaining this similarity, but we note that \u003cem\u003eE. fuscus\u003c/em\u003e is frequently involved in accidental translocations that can move individuals kilometers across a continent, or even an ocean (Constantine, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), potentially facilitating viral transmission.\u003c/p\u003e \u003cp\u003eSpike glycoprotein is an important coronavirus structural protein charged with binding the host receptor, and the S1 subunit is critical in determining species specificity; mutations within this region, particularly within the RBD, likely play a critical role in cross-species transmission and emergence (Li, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Menachery et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this study, we found that genes of closely related coronaviruses were highly similar, except for the region corresponding to the spike gene of EfONCAN and MlONCAN, with higher divergence within the S1 subunit (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). This variation was surprising given the role of the S1 subunit in host specificity, and we did not find evidence of recombination that could explain it. Evidence of positive selection was detected for the EbCoV clade at several sites in the S1 subunit with two sites included in the RBD. High homology in the RBD was maintained in viruses derived from the same species of bat, but markedly lower in those derived from other species with the exception of the MylCoV from Colorado, USA (CDPHE15) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) which further supports our hypothesis of high host specificity.\u003c/p\u003e \u003cp\u003eUnderstanding host receptors is a key step in assessing the risk of viral transmission across species. To our knowledge, the receptors used for EbCoV and MylCoV are unknown. In the present study, we generated near complete S gene sequences for EfONCAN22.320328 and MlONCAN23.320388 and predicted the structure of the RBDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, D). An entry assay using the S protein of closely related bat alpha-CoV showed that these viruses do not use APN (25 bat species), ACE2 (35 bat species), human TMPRSS2 or human DPP4 (G. Gallo, unpub. data). Structural analysis of the predicted RBD of EfONCAN22.320328 and MlONCAN23.320388 supports the hypothesis that these viruses are likely to use an unknown receptor(s) to enter cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Further experimental characterization of cell receptor affinity of these viruses are warranted.\u003c/p\u003e \u003cp\u003eThe type I IFN response is the first line of cellular defense against invading viruses in mammals. Coronaviruses, including alpha-CoVs, have evolved accessory proteins that can efficiently block the human IFNβ response (Kaewborisuth et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). PEDV has evolved mechanisms to suppress the type I IFN response, with ORF3 identified as a potent inhibitor. Pairwise amino acid identity analysis showed that EfONCAN and MlONCAN ORF3 were related, albeit distantly, to PEDV ORF3 with MlONCAN having a closer relatedness (52%) than EfONCAN (36%). In this study, we investigated the inhibitory effects of ORF3 proteins from our bat-derived alpha-CoVs, both related to PEDV, a swine-restricted virus, on the human type-I interferon response. Our findings revealed that while EbCoV ORF3 exhibited a potent inhibitory effect on IFNβ production, MylCoV ORF3 demonstrated greater potency in suppressing IFNβ signaling. These findings highlight the differential impacts of bat-derived alpha-CoV ORF3 proteins on host IFN-mediated antiviral responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eThe sampling methods we employed in this study impose certain limitations, but also provide a framework for future studies of viral diversity, prevalence, and impact in free-ranging, threatened populations. The populations we studied are recovering from drastic, recent declines caused by mortality from bat white-nose syndrome (WNS; Hooton et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and four of the five species we sampled are listed as Endangered in Ontario. Therefore, we considered lethal or potentially harmful sampling unacceptable and unnecessary. Four of our study species are particularly small (body mass for \u003cem\u003eM. leibii\u003c/em\u003e is typically 3\u0026ndash;5 g), and only oral swab samples could be collected with minimal risk or stress to the bats. As coronavirus infections are often concentrated in the gastro-intestinal tract, our detections from oral swab samples represent a conservative, minimum estimate of true prevalence. We also collected guano samples, but individual guano samples did not provide sufficient material for testing, and pooled guano samples cannot be re-tested at the individual level to characterize pathogen diversity among individual hosts. Our study demonstrates that near-complete viral genomes can be obtained from non-harmful, oral swab samples and compared among individual bat hosts, enabling future, longitudinal studies of viral prevalence and transmission in our study system. Further work can hopefully achieve similar results from guano samples, to further explore drivers of coronavirus prevalence in endangered bats.\u003c/p\u003e \u003cp\u003eWe provide preliminary insights into coronavirus diversity in bats in a previously undersampled region. In this work, we detected two alpha-CoVs in two Ontario bat species; Eptesicus bat coronavirus (EbCoV) and Myotis lucifugus coronavirus (MylCoV). This report represents the first detection of bat coronaviruses in Ontario and the first report of EbCoV in Canada. Ebcov and MylCoV were most closely related to other bat alpha-CoVs from host species within the same respective subfamily. Both viruses were also related to porcine epidemic diarrhea syndrome virus, swine acute diarrhea syndrome coronavirus and HCoV-229e and NL63. Additionally, we found that the ORF3 accessory protein of EbCoV and MylCoV demonstrate inhibition of human type I interferon response. This work provides a baseline for more rigorous surveillance to understand transmission dynamics of endemic coronaviruses in a natural setting, and for exploring the evolutionary relationships between bat, human, and swine coronaviruses in our study area. Further experimental characterization (e.g., cell receptor affinity) of these viruses are required for a fulsome risk assessment.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSample collection\u003c/h2\u003e \u003cp\u003eBat capture, handling, and sample collection were approved under permits No. 1039395, 1045694, and 1050823 from the Ontario Ministry of Natural Resources and Forestry. All captures were approved by Animal Care protocols from Trent University (No. 25253 and 26117), Carleton University (No. 117298), and the Ontario Ministry of Natural Resources and Forestry (No. 394). Survey gear was cleaned following current WNS decontamination protocols (CWHC-RCSF 2017), and for work performed after 2020, we took precautions to ensure that we would not inadvertently expose bats to SARS-CoV-2.\u003c/p\u003e \u003cp\u003eWe sampled at two abandoned mines, one cave, and three human-built structures in Eastern Ontario, Canada. Sampling occurred during swarming and hibernation from 2020\u0026ndash;2023. Bats were captured at the entrances of mines and caves using a harp trap (Tuttle, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Bats were captured outside building roosts using a triple-high mist net system (Bat Conservation and Management Inc.,Carlisle, Pennsylvania). Sex, age (based on ossification of phalangeal joints [Kunz and Anthony, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1982\u003c/span\u003e]), body mass, and forearm length were recorded for each bat. We used nasopharyngeal FLOQSwabs\u0026reg; (Typenex Medical) to gently collect oral samples and stored each swab in 1 mL of in-house transport media. Samples were placed on dry ice in the field and were subsequently stored at -80\u0026deg;C prior to analysis. All bats were released after sample collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNucleic acid extraction and nested SYBR Green pancoronavirus RT-PCR\u003c/h2\u003e \u003cp\u003eAll samples were extracted at the containment level 3 at the University of Toronto. Samples were extracted in pooled groups of 2\u0026ndash;4. Pools were prepared by mixing 140 uL of each individual sample and 140 uL of the pool material was used for RNA extraction via QIAmp viral RNA mini kit (QIAGEN, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ww.qiagen.com\u003c/span\u003e\u003cspan address=\"https://ww.qiagen.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e according to manufacturer\u0026rsquo;s instructions; samples were eluted into 40 uL buffer AVE. Individual samples from PCR-positive pools were then extracted individually for follow-up analysis.\u003c/p\u003e \u003cp\u003eWe analyzed RNA via a nested SYBR Green pancoronavirus RT-PCR targeting the highly conserved, RNA-dependent RNA-polymerase (RdRp) of the coronavirus genome. The following primers were used for round 1 RT-PCR: outer forward 5\u0026rsquo;-CCAARTTYTAYGGHGGNTGG-3\u0026rsquo; (Xiu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and outer reverse 5\u0026rsquo;-GCATWGTRTGYTGNGARCARAATTC-3\u0026rsquo;(Escutenaire et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Reactions were performed using the Qiagen One-Step RT-PCR kit (QIAGEN, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ww.qiagen.com\u003c/span\u003e\u003cspan address=\"https://ww.qiagen.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e with 5 uL 5x buffer, 1 uL dNTP mix, 1 uL enzyme mix, 0.4uL of each of the primers (25 uM stock; 0.4 uM final concentration), 12.2 uL RNase-free water, and 5 uL of RNA template. Reverse transcription was carried out at 50\u0026deg;C for 30 minutes, followed by the polymerase activation at 95\u0026deg;C for 15 minutes and by 40 cycles of 3 steps: 94\u0026deg;C for 15 seconds, 53.4\u0026deg;C for 30 seconds, and 68\u0026deg;C for 1 minute with a final extension step of 68\u0026deg;C for 5 minutes; cycling conditions were conducted under standard conditions. For round 2 PCR, the following primers were used: inner forward 5\u0026rsquo;-TGATGATGSNGTTGTNTGYTAYAA-3\u0026rsquo; (Escutenaire et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and inner reverse 5\u0026rsquo;-TGTTGNGARCARAAYTCATGNGG-3\u0026rsquo; (Xiu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Reactions were performed using the PowerTrack SYBR Green PCR Master Mix (Applied Biosystems\u0026trade;; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thermofisher.com\u003c/span\u003e\u003cspan address=\"https://www.thermofisher.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e with 10 uL of the SYBR Green master mix, 0.32 uL of each of the the primers (25 uM stock; 0.4 uM final concentration), 8.36 uL RNase-free water, and 1 uL of cDNA product from round 1 PCR. Polymerase activation was carried out at 95\u0026deg;C for 2 minutes followed by 40 cycles of 3 steps: 94\u0026deg;C for 5 seconds, 50\u0026deg;C for 40 seconds, and 72\u0026deg;C for 40 seconds. First-derivative melting curve analysis was performed as follows: 95\u0026deg;C for 1 minute, 55\u0026deg;C for 45 seconds, 0.1\u0026deg;C/second continuous increase to 95\u0026deg;C, 95\u0026deg;C for 1 second; cycling conditions were conducted under fast conditions. Each round of PCR included a non-template (negative) control with RNase-free water, and a coronavirus positive control. We considered samples positive if we observed both an exponential increase in fluorescence and a coronavirus-specific melt peak.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePartial RNA-dependent RNA-polymerase Sequencing\u003c/h2\u003e \u003cp\u003eRound 1 cDNA product from positive samples were amplified using the following primers: inner seq forward 5\u0026rsquo;-GGTTGGGAYTAYCCHAARTGTGA-3\u0026rsquo; and inner reverse 5\u0026rsquo;-TGTTGNGARCARAAYTCATGNGG-3\u0026rsquo; (Xiu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). PCR reactions were performed using Platinum\u0026trade; Taq DNA Polymerase (Invitrogen) with 2.5 uL 10x PCR buffer, 0.75 uL 50 nM MgCl2, 0.5 uL 10 nM dNTP, 0.25 uL Taq, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 19.2 uL RNase-free water, and 1 uL of cDNA product from round 1 PCR. Polymerase activation was carried out at 94\u0026deg;C for 2 minutes followed by 35 cycles of 3 steps: 94\u0026deg;C for 15 seconds, 54.5\u0026deg;C for 30 seconds, and 72\u0026deg;C for 1 minute with a final extension step of 72\u0026deg;C for 10 minutes. Amplified material was quantified using Qubit 4 with the dsDNA HS kit. Libraries were prepared using the Native Barcoding Amplicons (SQK-LSK109 with EXP-NBD104) protocol (version NBA_9093_v109_revJ_12Nov2019) and loaded on R.9.4.1 flow cells and sequenced on the MinION Mk1B nanopore sequencer.\u003c/p\u003e \u003cp\u003eBasecalling and barcode and adapter trimming was performed using ONT guppy (v6.5.7\u0026thinsp;+\u0026thinsp;ca6d6af) (gpu). Fastq reads were also filtered to remove reads\u0026thinsp;\u0026lt;\u0026thinsp;450 bp using filtlong (v0.2.1) (Wick, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, p. 20) and then aligned to a multi reference containing 37 coronavirus partial RdRp sequences using Minimap2 (v2.24) (Li, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Consensus sequences were generated based on the best hit from alignment using samtools (v1.6) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), bcftools (v1.5) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and seqtk (v1.3) (github.com/lh3/\u003cb\u003eseqtk)\u003c/b\u003e; quality check reports were generated from bam files using qualimap (v2.2.2a)(Okonechnikov et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Finally, resultant consensus sequences were identified by BLASTn against NCBI\u0026rsquo;s core nucleotide database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWhole genome sequencing\u003c/h2\u003e \u003cp\u003eRNA from pooled and individual bat oral samples were used for cDNA synthesis using 4 uL of LunaScript RT Mix (NEB, E3010), 8 uL of RNase free water, and 8 uL of RNA. This reaction was incubated at 25\u0026deg;C for 2 minutes, 55\u0026deg;C for 20 minutes, 95\u0026deg;C for 1 minute, followed by a 4\u0026deg;C hold. Whole genome sequencing used amplicon-based sequencing using EbCoV or MylCoV specific primer schemes and enrichment-based sequencing with the Illumina Pan-Coronavirus Panel (Illumina, USA) if sufficient material was available.\u003c/p\u003e \u003cp\u003ePrimer schemes for MylCoV (KY799179.1) and EbCoV (OL415262.1) were designed using primalscheme (Quick et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) with an amplicon size of 400 bp. For amplicon-based sequencing, lyophilized EbCoV and MylCoV primer pools (IDT), were resuspended in Tris-EDTA (TE) according to the oligonucleotide synthesis reports to achieve a stock concentration of 100 uM for each odd (primer pool 1) and even (primer pool 2) region primer pool. Working stocks were prepared by diluting stock primer pools with nuclease-free water to achieve a concentration of 10 uM. Amplification occurred in two reactions per sample (one for each primer pool) with 12.5 uL of Q5\u0026reg; Hot Start High-Fidelity 2X Master Mix (NEB, M0494), 3.5 uL of nuclease-free water, 4 uL of primer pool, and 5 uL of cDNA. Thermocycling conditions were as follows: 98\u0026deg;C for 30 seconds, followed by 35 cycles of 98\u0026deg;C for 15 seconds and 65\u0026deg;C for 5 minutes, followed by a 4\u0026deg;C hold. After PCR products were combined, a clean-up was performed using AMPure XP beads (Beckman Coulter, USA) at 1:1 bead to sample ratio. The quantity of the amplicons was measured with the Quibut 4.0 fluorometer using the 1X dsDNA HS Assay Kit (Thermo Fisher Scientific, USA). The sequencing libraries were prepared using the Nextera DNA Flex Prep kit (Illumina, USA) as per manufacturer\u0026rsquo;s instructions. Paired-end (2x150 bp) sequencing was performed on a MiniSeq with a 300-cycle Mid output reagent kit (Illumina, USA). A negative control library with nuclease-free water as input was included in each sequencing run. Paired-end illumina reads were analyzed using the following workflow that employed: FASTQC (v0.11.9) (Andrews, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) read-level quality control, Trim Galore (v0.6.10) (Krueger et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) quality filtering and adapter trimming, Minimap2 (v2.24) (Li, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) read mapping to MylCoV (KY799179.1) and EbCoV (OL415262.1) reference genomes, Samtools (v1.17) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)/ iVar (v1.4.2) (Grubaugh et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)/Seqtk (v1.3) (github.com/lh3/\u003cb\u003eseqtk)\u003c/b\u003e read mapping statistics, primer trimming and consensus generation, and bedtools (v2.30.0) (Quinlan and Hall, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) genome depth of coverage.\u003c/p\u003e \u003cp\u003eFor the enrichment-based sequencing, cDNA was prepared using Illumina RNA Prep with Enrichment (Illumina, USA) and the Pan-Coronavirus Panel (Illumina, USA) as per manufacturer\u0026rsquo;s instructions. Paired-end (2x150 bp) sequencing was performed on a Miniseq with a 300-cycle high Output reagent kit (Illumina, USA). A negative control library with nuclease-free water as input was included in each sequencing run. Paired-end illumina reads were analyzed using the following workflow that employed: FASTQC (v0.11.9) (Andrews, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) read-level quality control, Trim Galore (v0.6.10) (Krueger et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) quality filtering and adapter trimming, Megahit (v1.2.9) (Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) de-novo assembly, Minimap2 (v2.24) (Li, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) contig mapping to a multi-reference fasta, Samtools (v1.17) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)/Seqtk (v1.3) (github.com/lh3/\u003cb\u003eseqtk)\u003c/b\u003e read mapping statistics and consensus generation, and bedtools (v2.30.0) (Quinlan and Hall, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) genome depth of coverage. One sample (EfONCAN22.320328) produced sufficient reads via the enrichment-based sequencing; reads from both amplicon-based and enrichment-based sequencing were combined to generate the EfONCAN22.320328 consensus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTargeted sequencing of the spike and ORF3 genes\u003c/h2\u003e \u003cp\u003eSpike gene sequences with an additional 200 flanking nucleotides for MylCoV (KY799179.1) and EbCoV (OL415262.1) were downloaded from NCBI. Primers located in the 200 nucleotide flanking regions were designed using PrimerQuest Tool (Integrated DNA Technologies, Coralville, IA, USA) resulting in the following primers: EbCoV spike forward 5\u0026rsquo;-TAGTGCGAAGTAACGCCAAG-3\u0026rsquo; and EbCoV spike reverse 5\u0026rsquo;-GAACAAGAAGAGTCCTCCAATCA-3\u0026acute; and MylCoV spike forward 5\u0026rsquo;-GGGTTCAGGGCCATTAGTT-3\u0026rsquo; and MylCoV spike reverse 5\u0026rsquo;-CTGGTCAACAACAACAGCATC-3\u0026rsquo;. cDNA from pools and individual bat oral samples as described above were amplified with the following PCR reactions using the Q5\u0026reg; Hot Start High-Fidelity DNA Polymerase (New England Biolabs) : with 12.5 uL 2x PCR buffer, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 9.2 uL RNase-free water, and 2.5 uL of cDNA. Polymerase activation was carried out at 98\u0026deg;C for 30 seconds followed by 40 cycles of 2 steps: 98\u0026deg;C for 15 seconds and 65\u0026deg;C for 5 minutes\u0026thinsp;+\u0026thinsp;10 seconds per cycle, with a final extension step of 72\u0026deg;C for 5 minutes and 4\u0026deg;C infinite hold. Amplified material was quantified using Qubit 4 with the dsDNA HS kit.\u003c/p\u003e \u003cp\u003ePrimers for MylCoV (KY799179.1) and EbCoV (OL415262.1) ORF3 genes, were generated using MacVector (Version 18.6.1), resulting in the following primers: EbCoV ORF3 forward 5\u0026rsquo;-ATGATTGGAGGACTCTTCTTGTTCTCAGTTG-3\u0026rsquo; and EbCoV ORF3 reverse 5\u0026rsquo;-TTAAACAGCATCTTCGTAAAGTTTTTCATT-3\u0026acute; and MylCoV ORF3 forward 5\u0026rsquo;-ATGTTTCTTGGACTTTTCCAGTAYACAATT-3\u0026rsquo; and MylCoV ORF3 reverse 5\u0026rsquo;-TCAACTAGCTGAAGCATATTCAAGTTCGTC-3\u0026rsquo;. cDNA from pools and individual bat oral samples as described above were amplified in triplicate with the following PCR reactions using the Q5\u0026reg; Hot Start High-Fidelity DNA Polymerase (New England Biolabs): with 12.5 uL 2x PCR buffer, 0.4 uL of each of the primers (25 uM stock; 0.4 uM final concentration), 9.2 uL RNase-free water, and 2.5 uL of cDNA. Polymerase activation was carried out at 98\u0026deg;C for 30 seconds followed by 40 cycles of 3 steps: 98\u0026deg;C for 15 seconds, 59\u0026deg;C, 61\u0026deg;C or 65\u0026deg;C for 30 seconds, and 72\u0026deg;C for 1 minute, with a final extension step of 72\u0026deg;C for 5 minutes and 4\u0026deg;C infinite hold. Amplified material was quantified using Qubit 4 with the dsDNA HS kit.\u003c/p\u003e \u003cp\u003eLibraries for both spike and ORF3 libraries were prepared using the Ligation Sequencing Kit SQK-LSK114.24) according to manufacturer\u0026rsquo;s protocol (version NBA_9168_v114_revM_15sep2022) and loaded on R.10.4 Flongle flow cells according to manufacturer\u0026rsquo;s protocol (version NBE_9169_v114_revR_15Sep2022) and sequenced on the MinION Mk1B nanopore sequencer.\u003c/p\u003e \u003cp\u003eBasecalling and barcode and adapter trimming was performed using ONT guppy (v6.5.7\u0026thinsp;+\u0026thinsp;ca6d6af) (gpu). Fastq reads were also filtered to remove reads\u0026thinsp;\u0026lt;\u0026thinsp;450 bp using filtlong (v0.2.1) (Wick, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and then aligned to a ORF3 or spike reference (MylCoV [KY799179.1] and EbCoV [OL415262.1]) using Minimap2 (v2.24) (Li, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Consensus sequences were generated based on the best hit from alignment using samtools (v1.6) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), bcftools (v1.5) (Danecek et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and seqtk (v1.3) (github.com/lh3/\u003cb\u003eseqtk)\u003c/b\u003e; quality check reports were generated from bam files using qualimap (v2.2.2a) (Okonechnikov et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eGenomic and phylogenetic analyses\u003c/h2\u003e \u003cp\u003eGaps in sequences generated from whole genome sequencing were filled in using targeted sequencing; sequences were manually combined in AliView (Larsson, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Whole genome and gene level completeness for all sequences were calculated using R 4.2.3 with Biostrings package (2.66.0) against MylCoV (KY799179.1) and EbCoV (OL415262.1) reference genomes. Similarity analysis was conducted using SimPlot (Lole et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) .Whole genomes were identified using BLASTn against the core nucleotide database. Putative structural and non-structural proteins were investigated using NCBI ORF Finder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/orffinder/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/orffinder/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and were identified using BLASTp against the non-redundant protein sequences and UniProtKB/Swiss-Prot databases.\u003c/p\u003e \u003cp\u003ePhylogenetic analysis was performed for whole genomes, ORF1ab, and S gene. Phylogenies included species in the genus \u003cem\u003eAlphacoronavirus\u003c/em\u003e, with SARS-CoV-2 included as an outgroup representing \u003cem\u003eBetacoronavirus\u003c/em\u003e. Nucleotide sequences were aligned in MAFFT (Katoh et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Phylogenies were inferred using the Maximum Likelihood method using the GTR\u0026thinsp;+\u0026thinsp;G model in RaxML (Stamatakis, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Bootstrap support values for each tree were estimated with 500 replicates. Phylogenies were visualized using R 4.2.3 with ggtree (v3.6.2), ggimage (v0.3.3), ggplot2 (v3.5.1), rphylopic (v1.4.0), treeio (v1.22.0), phylotools (v0.2.2), phytools (2.3-0), treetools (1.11.1), dplyr (1.1.4), and phangorn (2.11.1).\u003c/p\u003e \u003cp\u003eRecombination analysis was performed with alpha-CoV sequences from the phylogenetic analysis including EfONCAN22.320328 and MlONCAN23.320388 using RDP4 (Martin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) with seven analyses (RDP, GENECONV, Bootscan, Maxchi, Chimera. SiScan, 3Seq). We only considered recombination events of \u0026ge;\u0026thinsp;1000 bp detected by at least five of the above-mentioned analyses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Events with undetermined breakpoints were not considered.\u003c/p\u003e \u003cp\u003eThe degree of temporal signal for whole genome, ORF1ab, and S gene phylogenies were explored by plotting root-to-tip distances on the maximum likelihood phylogenies against sampling date via TempEst (Rambaut et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSpike sequence analyses\u003c/h2\u003e \u003cp\u003eAmino acid sequences for alpha-CoVs included in the abovementioned phylogenetic analysis for S glycoprotein S1 and S2 subunits were downloaded from NCBI. Pairwise amino acid identity analysis were carried out for EfONCAN22.320328 and MlONCAN23.320388 as they represented the most complete sequences generated in this study; nucleotide sequences were translated to amino acid in AliView (Larsson, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). All S1 and S2 sequences were aligned via MAFFT (Katoh et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Pairwise amino acid identity of EfONCAN22.320328 and MlONCAN23.320388 against all alpha-CoV S1 and S2 subunit sequences were calculated using R 4.2.3 with Biostrings package (2.66.0). A heatmap of resultant pairwise identities was generated using R 4.2.3 using packages ggplot2 (v3.5.1) and tidyr (v1.3.1).\u003c/p\u003e \u003cp\u003eA phylogenetic approach employing HyPhy (Kosakovsky Pond et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) was used to assess for signatures of selection for EfONCAN22.320328 and MlONCAN23.320388 relative to the wider EbCoV and MylCoV clades, respectively. Spike genes in EfONCAN22.320328 and MlONCAN23.320388 were identified using VADR (v1.6.4) with the pan-coronaviridae v1.3.3 library. Aligning sections of related genomes were identified and extracted using NCBI BLAST+ (v2.16) with the nucleotide core database and biopython (v1.84). Sequences were then translated into amino acids using transeq from EMBOSS v6.6.0 and alignments were generated using MAFFT. The codon alignments were generated using PAL2NAL (v14). Codon-alignment for EbCoV included: EfONCAN22.320328, OL410608.1, OL410607.1, OL415262.1, OL415261.1, OL410610.1, OL410609.1, MW924112.1, MZ293737.1, MZ293738.1, and OP715781.1. The codon-alignment for MylCoV included: KY799179.1, NC_022103.1, and MZ081396.1. Few complete sequences related to MlONCAN23.320388 were available which precluded analysis of the S1 subunit. Signatures of positive selection were evaluated using HyPhy\u0026rsquo;s mixed-effects model of evolution (MEME) (Murrell et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Contrast Fixed-Effects Likelihood (Contrast-FEL) (Kosakovsky Pond and Frost, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), adaptive branch-site random effects likelihood (aBSREL) method (Smith et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and RELAX (Wertheim et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePredicted RBD were obtained from S1 subunit amino acid alignment of EfONCAN22.320328 and MlONCAN23.320388 with other alpha-CoV species, including: Ebcov (UNE74476.1), HCQD-2020 (UED13287.1), Mylcov (ASL23654.1), CDPHE15 (YP_008439202.1), HCoV-NL63 (AGT51331.1), HCoV-229E (APT69883.1), and PEDV (NP_598310.1). RBD sequences of EfONCAN22.320328 and MlONCAN23.320388 were submitted to Alphafold 3 (AlphaFold Server; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://alphafoldserver.com\u003c/span\u003e\u003cspan address=\"https://alphafoldserver.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to obtain a prediction of the tertiary structures. Figures of the predicted structures were obtained using Pymol (Schrodinger; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.schrodinger.com/\u003c/span\u003e\u003cspan address=\"https://www.schrodinger.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Additionally, we investigated for the presence of Furin cleavage sites for viruses within the EbCoV and MylCoV clades using ProP (Duckert et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eORF3 characterization - luciferase reporter assays\u003c/h2\u003e \u003cp\u003eThe ORF3 gene from MlONCAN23.320388 and EfONCAN22.320328 were synthesized through GenScript, and the expression plasmids (pcDNA3.1 (+) - MylORF3 and pcDNA3.1(+) - EbORF3) were subsequently scaled up in \u003cem\u003eE. coli\u003c/em\u003e Stabl3 cells. For the IFNβ promoter assay, HEK293T cells (.75 x 10\u003csup\u003e5\u003c/sup\u003e cells per well in a 24-well plate) were co-transfected with 20 ng of IFNβ promoter reporter plasmid, 10 ng of Renilla luciferase plasmid, and 200 ng of ORF3 expression plasmid using Lipofectamine\u0026trade; 3000 transfection reagent (Invitrogen). At 24 hours post-transfection, cells were treated with 2\u0026micro;g/well high molecular weight polyI:C (InvivoGen). Sixteen hours post-treatment, cells were lysed and analyzed using dual-luciferase reporter assays according to the manufacturer\u0026rsquo;s instructions (Promega). For the ISRE promoter assay, HEK293T cells (.75 x 10\u003csup\u003e5\u003c/sup\u003e cells per well in a 24-well plate) were co-transfected with 250 ng of ISRE promoter reporter plasmid, 10 ng of Renilla luciferase plasmid, and 200 ng of viral ORF3 expression plasmid. At 24 hours post-transfection, cells were exposed to 100 units per well of human IFNβ for 16 hours, followed by analysis using the dual-luciferase reporter assay which was performed as per manufacturer\u0026rsquo;s instructions (Promega). Luciferase levels were measured by GloMax\u0026reg; 20/20 Luminometer (Promega).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eImmunoblot\u003c/h2\u003e \u003cp\u003eCells were harvested in Passive Lysis 5X Buffer (Promega). Protein samples were resolved on a 12% SDS-polyacrylamide gel and transferred onto a polyvinylidene difluoride (PVDF) membrane using the Trans-Blot Turbo Transfer System (Bio-Rad). The membrane was blocked for 1 hour and then probed with anti-FLAG (mouse, 1:2000 dilution) (Millipore sigma) and anti-GAPDH (rabbit, 1:2000 dilution) (Millipore sigma) primary antibodies. After incubation with respective secondary antibodies (1:10,000 dilution), the proteins were visualized using an Odyssey CLx imager (Licor Bio).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (RGPIN-2020-06199), Canadian Institutes of Health Research (CIHR) operating grant (MM1174925) and project grant (PJT186217). Sample collection from wild bats was supported by the Government of Ontario, the Canadian Wildlife Service, and the Canadian Safety and Security Program. J.D.K. was supported by an AMMI Canada/BioM\u0026eacute;rieux Fellowship in Microbial Diagnostics. Research within A.B.\u0026rsquo;s lab is supported by an NSERC Discovery Grant (RGPIN-2022-03010), Canadian Institutes of Health Research (CIHR) \u0026ndash; Institute for Infection and Immunity Early Career Research grant (PTT-192089), CIHR - Pandemic Preparedness and Health Emergencies Early Career Investigator grant (PEE-183995), and CIHR-Institute for Infection and Immunity, Project grant (PJT-195787). VIDO receives operational funding from the Government of Saskatchewan through Innovation Saskatchewan and the Ministry of Agriculture and from the Canada Foundation for Innovation through the Major Science Initiatives Fund. Thanks to E. Allen, T. Ambeau, A. Anderson, L. Crawshaw, S. Davison, R. Dillon, E. Elizondo, L. Hooton, A. Kowalchuk-Reid, S. Laursen, C. Menzies, C. Pearson, E. Maquignaz, E. Nkwonta, L. Scott, E. Stukenholtz, T. Thorne, C. Turenne, K. Vanderwolf, and D. White for assistance collecting samples in the field.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and diversity:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe support inclusive, diverse, and equitable conduct of research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: JDK, SM, CD, AB, VM; Sample collection: CD, VVZ, JDK, SM, KAW; Laboratory analysis: JDK, AH, HYC, JBS, EC, LY, WY, AB, PS; Data analysis/investigation: JDK, FM, AB, GG, DB; Resources: QL, AK; Writing \u0026ndash; original draft: JDK, CD; Writing \u0026ndash; review \u0026amp; editing: all authors; Visualization: JDK, AB, CD; Supervision: SM, CD, FM, AB; Funding acquisition: SM, CD, AB\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePartial genome sequences generated in this study have been deposited on NCBI GenBank under accession numbers PQ554521-PQ554525.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCode for analysis and visualization is available through https://github.com/jkotwa/bat-alphacov-analyses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndrews, S., 2010. 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Sci. 159, 146\u0026ndash;159. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.rvsc.2023.03.022\u003c/span\u003e\u003cspan address=\"10.1016/j.rvsc.2023.03.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\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":"npj-viruses","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Viruses](https://www.nature.com/npjviruses)","snPcode":"44298","submissionUrl":"https://submission.springernature.com/new-submission/44298/3","title":"npj Viruses","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5633972/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5633972/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBats are reservoir hosts for a number of coronaviruses, some of which may pose spillover risks for humans and other animals. Surveillance for bat coronaviruses in temperate regions remains limited and represents an important blind spot for emerging pathogen preparedness and bat conservation. We detected two alphacoronaviruses in big brown bats (\u003cem\u003eEptesicus fuscus\u003c/em\u003e) and little brown myotis (\u003cem\u003eMyotis lucifugus\u003c/em\u003e) in the province of Ontario, Canada. These viruses are closely related to other coronaviruses circulating in bats in North America and Asia and also related to human and swine coronaviruses. We found unexpected diversity in the spike gene of these highly similar coronaviruses. High homology in the receptor-binding domain (RBD) was maintained in viruses derived from the same species of bat, but markedly lower in those derived from other species. RBD \u003cem\u003ein silico\u003c/em\u003e structural analysis of closely related coronaviruses suggests that the viruses we detected are less likely to use bat APN (30 bat species) or ACE2 (20 bat species), or human DPP4 or TMPRSS2 as putative receptors or attachment factors. To gain early insights into interferon antagonism, we also functionally characterized the accessory protein ORF3 from both bat viruses and discovered that ORF3 inhibited both IFNβ production and signaling. Taken together, our study provides insights into coronavirus diversity in Nearctic, insectivorous bats in a previously under-sampled region. This work provides a baseline for more in-depth surveillance to better characterize the transmission dynamics of endemic coronaviruses in free-ranging wildlife, and for exploring the evolutionary relationships between coronaviruses and their hosts.\u003c/p\u003e","manuscriptTitle":"High host specificity of alphacoronaviruses in Nearctic, insectivorous bats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-15 14:16:13","doi":"10.21203/rs.3.rs-5633972/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-27T08:13:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-21T02:08:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-19T17:49:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-18T12:49:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179259620992282387257549172588667571078","date":"2025-01-12T10:14:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272968656753475755133033861118451743319","date":"2025-01-08T14:30:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172599490782398612796639322498812004342","date":"2025-01-07T05:26:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103405931133561103216548398685136325022","date":"2025-01-06T19:55:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157999154785117668982654548113139152923","date":"2025-01-06T10:10:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"340236566135024913906176461674446328011","date":"2025-01-06T10:00:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-06T09:08:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-24T11:52:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-12-19T05:41:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Viruses","date":"2024-12-12T20:00:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-viruses","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Viruses](https://www.nature.com/npjviruses)","snPcode":"44298","submissionUrl":"https://submission.springernature.com/new-submission/44298/3","title":"npj Viruses","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"80d419ff-b077-4994-9ac1-7921323d8b06","owner":[],"postedDate":"January 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":42768260,"name":"Biological sciences/Microbiology/Virology/Viral epidemiology"},{"id":42768261,"name":"Biological sciences/Microbiology/Virology/Virus host interactions"}],"tags":[],"updatedAt":"2025-04-04T08:23:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-15 14:16:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5633972","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5633972","identity":"rs-5633972","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}