Transcriptome analysis of primary chicken cells infected with infectious bronchitis virus strain K047-12 isolated in Korea

Host Immune Response Modulation in Avian Coronavirus Infection: Tracheal Transcriptome Profiling In Vitro and In Vivo

Infectious bronchitis virus (IBV) is a highly contagious Gammacoronavirus causing moderate to severe respiratory infection in chickens. Understanding the initial antiviral response in the respiratory mucosa is crucial for controlling viral spread. We aimed to characterize the impact of IBV Delmarva (DMV)/1639 and IBV Massachusetts (Mass) 41 at the primary site of infection, namely, in chicken tracheal epithelial cells (cTECs) in vitro and the trachea in vivo. We hypothesized that some elements of the induced antiviral responses are distinct in both infection models. We inoculated cTECs and infected young specific pathogen-free (SPF) chickens with IBV DMV/1639 or IBV Mass41, along with mock-inoculated controls, and studied the transcriptome using RNA-sequencing (RNA-seq) at 3 and 18 h post-infection (hpi) for cTECs and at 4 and 11 days post-infection (dpi) in the trachea. We showed that IBV DMV/1639 and IBV Mass41 replicate in cTECs in vitro and the trachea in vivo, inducing host mRNA expression profiles that are strain- and time-dependent. We demonstrated the different gene expression patterns between in vitro and in vivo tracheal IBV infection. Ultimately, characterizing host-pathogen interactions with various IBV strains reveals potential mechanisms for inducing and modulating the immune response during IBV infection in the chicken trachea.

Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection

INTRODUCTION

Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early.

OBJECTIVE

The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells.

METHODS

Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis.

RESULTS

Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1).

CONCLUSIONS

The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.

Molecular characterization and transcriptomic analysis of a novel polymycovirus in the fungus Talaromyces amestolkiae

Talaromyces amestolkiae is an important fungal species owing to its ubiquity in soils, plants, air, and food. In this study, we identified a novel six-segmented polymycovirus, Talaromyces amestolkiae polymycovirus 1 (TaPmV-1). Each of the double-stranded (ds) RNA segments of TaPmV-1 contained a single open reading frame, and the proteins encoded by dsRNA1, dsRNA2, dsRNA3, and dsRNA 5 shared significant amino acid identities of 56, 40, 47, and 43%, respectively, with the corresponding proteins of Aspergillus fumigatus polymycovirus-1(AfuPmV-1). DsRNA1, dsRNA3, and dsRNA5 of TaPmV-1 encoded an RNA-dependent RNA polymerase (RdRp), a viral methyltransferase, and a PAS-rich protein, respectively. The functions of the proteins encoded by dsRNA2, dsRNA4, and dsRNA6 have not been elucidated. Comparison of the virus-infected strain LSH3 with virus-cured strain LSHVF revealed that infection with TaPmV-l may reduce the production of red pigments and induce the clustering of fungal sclerotia. Furthermore, transcriptomic analyses demonstrated that infection with TaPmV-l downregulated the expression of transcripts related to metabolism, and may correlate with the reduced production of red pigments and clustering of sclerotia in T. amestolkiae. These results of this study provide novel insights into the mechanism of fungal gene regulation by polymycovirus infections at the transcriptome level, and this study is the first to report a novel polymycovirus of T. amestolkiae.

Transcriptomic analysis reveals crucial regulatory roles of immediate-early response genes and related signaling pathways in coronavirus infectious bronchitis virus infection

Coronavirus infection of cells differentially regulates the expression of host genes and their related pathways. In this study, we present the transcriptomic profile of cells infected with gammacoronavirus infectious bronchitis virus (IBV). In IBV-infected human non-small cell lung carcinoma cells (H1299 cells), a total of 1162 differentially expressed genes (DEGs), including 984 upregulated and 178 downregulated genes, was identified. These DEGs were mainly enriched in MAPK and Wnt signaling pathways, and 5 out of the 10 top upregulated genes in all transcripts were immediate-early response genes (IEGs). In addition, the induction of 11 transcripts was validated in IBV-infected H1299 and Vero cells by RT-qPCR. The accuracy, reliability and genericity of the transcriptomic data were demonstrated by functional characterization of these IEGs in cells infected with different coronaviruses in our previous publications. This study provides a reliable transcriptomic profile of host genes and pathways regulated by coronavirus infection.

Differing coronavirus genres alter shared host signaling pathways upon viral infection

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.