Abstract Coronaviruses are important viral pathogens across a range of animal species including humans. They have a high potential for cross-species transmission as evidenced by the emergence of COVID-19 and may be the origin of future pandemics. There is therefore an urgent need to study coronaviruses in depth and to identify new therapeutic targets. This study shows that distant coronaviruses such as Alpha-, Beta-, and Deltacoronaviruses can share common host immune associated pathways and genes. Differentially expressed genes (DEGs) in the transcription profile of epithelial cell lines infected with swine acute diarrhea syndrome, severe acute respiratory syndrome coronavirus 2, or porcine deltacoronavirus, showed that DEGs within 10 common immune associated pathways were upregulated upon infection. Twenty Three pathways and 21 DEGs across 10 immune response associated pathways were shared by these viruses. These 21 DEGs can serve as focused targets for therapeutics against newly emerging coronaviruses. We were able to show that even though there is a positive correlation between PDCoV and SARS-CoV-2 infections, these viruses could be using different strategies for efficient replication in their cells from their natural hosts. To the best of our knowledge, this is the first report of comparative host transcriptome analysis across distant coronavirus genres. Subject terms: Computational biology and bioinformatics, Cellular signalling networks, Gene ontology, Genome informatics, SARS-CoV-2, Viral host response, Virus-host interactions Introduction Coronaviruses (CoV) are the cause of respiratory and intestinal infections in animals and humans^[28]1. For a relatively long period of time, coronaviruses were not considered a major human concern. This however changed with the outbreak of severe acute respiratory syndrome (SARS) in 2002 and 2003 in Guangdong, China^[29]1,[30]2. SARS which emerged from the bat vector through intermediate animal hosts made it into a human transmission chain, infected at least 8096 people in 29 countries and killed 774 individuals^[31]3,[32]4. A decade later, the Middle East respiratory syndrome coronavirus (MERS-CoV)—a highly pathogenic coronavirus—appeared on the Arabian peninsula^[33]1,[34]5 As a result, more than 2578 people in 27 countries were infected, and at least 888 people killed by October 2021 (WHO)^[35]3. On December 8, 2019, the latest outbreak of a new coronavirus called sudden acute respiratory coronavirus 2 (SARS-CoV-2) was detected in Wuhan, China^[36]6. SARS-CoV-2 causes the coronavirus disease 2019 (COVID-19). This outbreak—the third major human coronavirus outbreak in the last two decades—has resulted in a significant societal impact and the first in the twenty-first century to reach every continent on the planet^[37]3. As of January 2022, over 367 million confirmed cases with more than 5.6 million deaths have occurred worldwide and continues to grow^[38]7. Coronaviruses are positive-stranded RNA viruses whose genome size is about 30 kilobases^[39]8,[40]9. Their genome contains genes encoding 4 structural proteins: membrane (M), nucleocapsid (N), Spike (S), and envelope (E)^[41]3. Coronaviruses belong to the order Nidovirales, Coronaviridae family, subfamily Orthocoronavirinae^[42]1,[43]3,[44]10. Four genera are found in the Orthocoronavirinae subfamily: Alphacoronavirus, Betacoronavirus, Deltacoronavirus, and Gammacoronavirus (ICTV, 2011)^[45]1,[46]3. The alphacoronaviruses and betacoronaviruses are known to exclusively infect mammals, typically causing respiratory illness and gastroenteritis. Of the betacoronaviruses, there are three that cause severe respiratory disease in humans: SARS-CoV, MERS-CoV and SARS-CoV-2. The other four human coronaviruses, HCoV-NL63(alpha), HCoV-229E(alpha), HCoV-OC43(beta) and HKU1(beta), typically induce mild upper respiratory diseases in immunocompetent hosts, but can cause severe infections in elderly people, infants, and young children^[47]1. SARS-CoV-1, HCoV-NL63 and SARS-CoV-2 use angiotensin—converting enzyme 2 (ACE2) as a receptor and primarily infect ciliated bronchial epithelial cells^[48]1,[49]3; while MERS-CoV infects unciliated bronchial epithelial cells, by employing the use of dipeptidyl peptidase 4 (DPP4) as a receptor^[50]1,[51]11. SARS-CoV is thought to have been transmitted to humans from market civets, while MERS-CoV from dromedary camels^[52]1. Presently, the origins of SARS-CoV-2 are unclear. However, the 2002 SARS-CoV-1 outbreak—and the entry of SARS-CoV-2 into the human population—has been implicated on the wild animal handling practices common in Southern China^[53]3. Gamma- and delta- coronaviruses primarily infect birds, but cases of mammalian infections have been documented^[54]1,[55]12–[56]15. CoVs can also have devastating effects in livestock populations, particularly pigs. CoVs with swine health implications include transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome virus (SADS-CoV), among others^[57]1,[58]16,[59]17. The Deltacoronavirus genus comprises mostly avian CoV pathogens of songbirds including HKU11 (bulbul coronavirus), HKU12 (thrush coronavirus), and HKU13 (munia coronavirus)^[60]18. PDCoV is an emerging viral disease of swine circulating globally with mortality in up to 40% of infected neonatal pigs^[61]19. PDCoV’s usage of an interspecies conserved amino acid domain within aminopeptidase N (APN) (also known as CD13) as a binding receptor allows infection of a diverse range of species^[62]13,[63]20. Lednicky et al., identified PDCoV strains in plasma samples of three Haitian children with acute undifferentiated febrile illness^[64]12 confirming the ability of PDCoV to cause disease in humans. SADS-CoV, a swine enteric alphacoronavirus, is a recent spillover from bats to pigs^[65]1. SADS is a highly pathogenic enteric CoV first reported in a fatal diarrhea outbreak in Guangdong province, China, in January 2017, causing the deaths of 24,693 newborn piglets^[66]21. This disease is caused by a novel strain of Rhinolophus bat coronavirus HKU2^[67]1,[68]17. Zhou et al., provided significant evidence that the causative agent of SADS-CoV is a novel HKU2-related coronavirus that has 98.48% identity in genome sequence to HKU2^[69]17. Transcriptomic analysis is a powerful application of Next Generation Sequencing (NGS) technology that allows the identification of pivotal genes and/or signaling pathways as well as biomarker and drug discovery for various diseases and novel therapeutics^[70]22. During the last 10 years, several studies have been focused on host cell transcriptome changes related to coronavirus infections. As an illustration of the alphacoronaviruses, Zhang et al. provided the first report of the transcriptional expression of host cells during SADS-CoV infection^[71]21. Hu et al. implemented a transcriptomic analysis describing the host genetic response to porcine epidemic diarrhea (PEDV) in IPEC-J2 cells^[72]23. Song et al. provided a transcriptomic analysis of coinfection of porcine IPEC-J2 cells with PEDV and transmissible gastroenteritis virus (TGEV)^[73]24. Additional transcriptome analyses have been generated in Vero E6 cells infected with PEDV^[74]25 and SADS-CoV^[75]26. Similarly, Friedman et al. used NGS for identifying the transcriptomic changes in human MRC-5 cells infected with human coronavirus (HCoV)-229E^[76]27. For betacoronaviruses, Blanco-Melo et al. provided a comparison of the transcriptional response of SARS-CoV-2 with other respiratory viruses to identify transcriptional factors that can determine COVID-19 biology^[77]28. Sun et al. established the host response patterns for SARS-CoV-2 at different time points of infection and performed a comprehensive analysis of their transcriptomic profile with SARS-CoV and MERS-CoV^[78]29. Yuan et.al. were able to generate the transcriptomic profile of human bronchial epithelial Calu-3 cells infected with MERS-CoV in order to investigate the importance of lipid metabolism in human viral infections^[79]30. Yoshikawa et al. analyzed the global genes responses of 2B4 cells infected with SARS-CoV at different time points by microarray analysis^[80]31. For deltacoronavirus, Cruz-Pulido et al. performed the first transcriptome analysis of human intestinal cell lines infected by PDCoV^[81]32. Liu et al. provided a transcriptomic profiling of long non-coding RNAs (lncRNAs) in swine testicular (ST) cells infected with PDCoV^[82]33. Finally, for gammacoronaviruses, Lee et al. investigated changes in chicken embryonic kidney (CEK) cells infected with infectious bronchitis virus (IBV) by transcriptome analysis^[83]34. As a result of the increasing availability of transcriptomic data, it is possible to identify different transcriptomic datasets under similar disease and control conditions that can help to elucidate novel pathways and genes with remarkable accuracy^[84]22. Therefore, transcriptomic analyses using different datasets are becoming increasingly useful. Krishnamoorthy et al. conducted a transcriptome meta-analysis of SARS-CoV-2, SARS-CoV, and MERS-CoV at different time points of infection in order to identify potential drugs for COVID-19 treatment^[85]22. Coden, et al. implemented a comparative study of epithelial expression of SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-229E and Influenza in patients with asthma^[86]35. Alsamman et al., compared the transcriptomic data of SARS-CoV-2 to MERS-CoV, SARS-CoV, H1N1 and Ebola virus (EBOV) in order to provide valid targets for potential therapy against SARS-CoV-2^[87]36. Feng et al., investigated the role of hypergraph models of biological networks that are inferred from transcriptomic data (Ebola Virus, Influenza Virus, MERS-CoV, SARS-CoV and West Nile Virus) for the identification of critical genes in viral infection^[88]37. There are also other transcriptomic studies in blood samples of patients infected with EBOV^[89]38, and microarray analyses in children^[90]39 and patients with influenza H1N1/2009^[91]40. This study compares the transcriptomic profiles of epithelial cells infected with distant CoV such as: human intestinal epithelial cells (HIECs) infected with PDCoV^[92]21, normal human bronchial epithelial (NHBE) cells infected with SARS-CoV-2^[93]41, and porcine intestinal epithelial cells (IPEC-J2) infected with SADS-CoV^[94]22. We hypothesized that similar and unique aspects in the immune-associated response to coronavirus infection in epithelial cell lines exist. Comparison of the host response to highly pathogenic coronaviruses versus potential emerging human pathogen PDCoV will provide key knowledge in understanding and developing therapeutic targets for these diseases. To explore and compare the transcriptome profiles of epithelial cell lines infected by PDCoV, SARS-CoV-2, and SADS-CoV infection, this study was able to identify common differentially expressed genes (DEGs) and signaling pathways among phylogenetically distant CoV. To our knowledge, this is a novel comparative transcriptomic analysis of epithelial cells lines infected by coronaviruses differing at the genus level. Results Alpha-, beta-, and deltacoronavirus infections result in more differentially upregulated genes across 10 common immune response associated pathways This study was able to utilize publicly available RNA-seq libraries to compare transcriptomic profiles of HIEC cells infected with PDCoV (PRJNA690955), NHBE cells infected with SARS-CoV-2 ([95]GSE147507), and IPEC-J2 cells infected with SADS-CoV (PRJNA622652). Using the pipeline described in the Methods section, differential expression analysis of these epithelial cell lines resulted in identification of DEGs. First, 7486 DEGs (40.97%) were identified in HIEC cells infected with PDCoV, where 4011 were upregulated and 3475 were downregulated. Second, 4982 DEGs (39.75%) were identified in NHBE cells infected with SARS-CoV-2 where 2381 were upregulated and 2601 were downregulated. Third, 8686 DEGs (61.27%) were identified in IPEC-J2 cells infected with SAD-CoV where 4455 were upregulated and 4231 were downregulated (Table [96]1). Table 1. DEGs in HIEC cells infected with PDCoV, NHBE cells infected with SARS-CoV-2 and IPEC cells infected with SADS-CoV at 24 hpi vs no infected cells. Cell line Up Down Not Sig Total genes Total DEs genes HIEC 4011 3475 10,784 18,270 7486 (40.97%)* NHBE 2381 2601 7551 12,533 4982 (39.75%)* IPEC 4455 4231 5491 14,177 8686 (61.27%)* [97]Open in a new tab Up, upregulated genes; Down, downregulated genes; Not Sig, genes detected with no significant differences. *Percentages of total genes that are differentially expressed. We found that the DEGs are associated with 10 common immune response associated pathways. The apoptosis signaling-, interferon signaling-, interleukin signaling-, T-cell activation-, TGF-β signaling-, and Ras signaling- pathways were mostly upregulated upon viral infection. Within these pathways, more genes were affected in the inflammation/cytokine signaling pathway in all CoVs in comparison to the other 9 pathways (Fig. [98]1, Fig. [99]S1–[100]S2). In the same way, more genes were affected in HIEC cells infected with PDCoV in this pathway and a small number of genes were affected in the Interferon and Jak-Stat signaling pathway in a majority of the cell lines (Fig. [101]1, Fig. [102]S8). Figure 1. [103]Figure 1 [104]Open in a new tab DEGs from 10 common immune-response associated pathways in HIEC (HI) cells infected with PDCoV, NHBE (NH) cells infected with SARS-CoV-2, and IPEC (IP) cells infected with SADS-CoV. Results from 10 pathways are shown: apoptosis signaling pathway, B-cell activation, inflammation/cytokine signaling pathway, interferon, interleukin signaling pathway, JAK-STAT signaling pathway, Ras signaling pathway, T-cell activation, TGF-β signaling pathway, and toll- like receptor signaling pathway. Blue is down-regulated, red is up-regulated. DEGs of each dataset were submitted to a gene set enrichment analysis (GSEA) using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to identify pathways that were common upon viral infection, and then, manually represented using CorelDRAW2019 (Fig. [105]2). A total of 23 pathways were common and enriched in human and porcine cell lines at 24 hpi (Fig. [106]2). These included Cytokine—Cytokine Receptor interaction pathway (Fig. [107]S1), Viral protein interaction pathway with cytokine and cytokine receptor (Fig. [108]S2), NF-Kappa B signaling pathway (Fig. [109]S3), Toll like receptor signaling pathway (Fig. [110]S4), NOD like receptor signaling pathway (Fig. [111]S5), RIG -I like receptor signaling pathway (Fig. [112]S6), Cytosolic DNA signaling pathway (Fig. [113]S7), JAK-STAT signaling pathway (Fig. [114]S8), IL-17 signaling pathway (Fig. [115]S9), TNF signaling pathway (Fig. [116]S10), Malaria signaling pathway (Fig. [117]S11), Influenza A (Fig. [118]S12), Coronavirus Disease (Fig. [119]S13) among others (Fig. [120]2). Figure 2. Figure 2 [121]Open in a new tab Kyoto Encyclopedia of Genes and Genomes (KEGG) gene set enrichment analysis of DEGs shared in SARS-CoV-2, PDCoV, and SADS-CoV infection in human and porcine cell lines, respectively. S = SARS-CoV-2 in NHBE cells, P = PDCoV in HIEC cells D = SADS-CoV in IPEC-J2 cells. Purple is closer to p = 0.05, red is closer to p = 0.01. Small circles = 20 counts, big circles = 40 counts. Asterisk = DEG pathways also in gamma CoV infection in avian cells. DEGs in human and pig cells also led to identification of common up-regulated and down-regulated genes between species. 826 genes were upregulated and 1,010 were downregulated among PDCoV, SARS-CoV-2, and SADS-CoV infections (Fig. [122]S14). From these genes, 21 DEGs were common across the 10 common immune response associated pathways identified in Fig. [123]1 (Table [124]2, Fig. [125]S15–[126]S16). These 21 DEGs include: MAPK Activated Protein Kinase 2 (MAPKAPK2), Integrin Subunit Alpha 4 (ITGA4), Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha (PIK3CA), Mitogen-Activated Protein Kinase 10 (MAPK10), Nuclear Factor Kappa B Subunit 1 (NFKB1), Cyclin Dependent Kinase Inhibitor 1A (CDKN1A), NF-Kappa-B Inhibitor Epsilon (NFKBIE), Inhibin Subunit Beta A (INHBA), TNF Receptor Associated Factor 2 (TRAF2), RELA Proto-Oncogene, NF-KB Subunit (RELA), P21 (RAC1) Activated Kinase 1 (PAK1), Baculoviral IAP Repeat Containing 3 (BIRC3), Mitogen-Activated Protein Kinase Kinase Kinase 8 (MAP3K8), Nuclear Factor Kappa B Subunit 2 (NFKB2), Interleukin 1 Receptor Associated Kinase 4 (IRAK4), Signal Transducer and Activator of Transcription 2 (STAT2), SOS Ras/Rho Guanine Nucleotide Exchange Factor 2 (SOS2), Signal Transducer and Activator of Transcription 5A (STAT5A), Suppressor of Cytokine Signaling 3 (SOCS3), Toll Like Receptor Adaptor Molecule 1 (TICAM1), and RELB Proto-Oncogene, NF-KB Subunit (RELB) (Table [127]2). Table 2. Orthologs of upregulated and downregulated DEGs among HIEC cells infected with PDCoV, NHBE cells infected with SARS-CoV-2, and IPEC cells infected with SADS-CoV. ID Gene Pathway/s Function References