Oxidative stress pathway gene transcription after bovine respiratory syncytial virus infection in vitro and ex vivo

Modeling Human Respiratory Syncytial Virus (RSV) Infection: Recent Contributions and Future Directions Using the Calf Model of Bovine RSV Disease

The human orthopneumovirus (human respiratory syncytial virus [RSV]) is a leading cause of respiratory disease in children worldwide and a significant cause of infant mortality in low- and middle-income countries. The natural immune response to the virus has a preponderant role in disease progression, with a rapid neutrophil infiltration and dysbalanced T cell response in the lungs associated with severe disease in infants. The development of preventive interventions against human RSV has been difficult partly due to the need to use animal models that only partially recapitulate the immune response as well as the disease progression seen in human infants. In this brief review, we discuss the contributions of the calf model of RSV infection to understanding immunity to RSV and in developing vaccine and drug candidates, focusing on recent research areas. We propose that the bovine model of RSV infection is a valuable alternative for assessing the translational potential of interventions aimed at the human population.

Bovine Airway Models: Approaches for Investigating Bovine Respiratory Disease

Bovine respiratory disease (BRD) is a multifactorial condition where different genera of bacteria, such as Mannheimia haemolytica, Histophilus somni, Pasteurella multocida, and Mycoplasma bovis, and viruses, like bovine respiratory syncytial virus, bovine viral diarrhea virus, and bovine herpes virus-1, infect the lower respiratory tract of cattle. These pathogens can co-infect cells in the respiratory system, thereby making specific treatment very difficult. Currently, the most common models for studying BRD include a submerged tissue culture (STC), where monolayers of epithelial cells are typically covered either in cellular or spent biofilm culture medium. Another model is an air-liquid interface (ALI), where epithelial cells are exposed on their apical side and allowed to differentiate. However, limited work has been reported on the study of three-dimensional (3D) bovine models that incorporate multiple cell types to represent the architecture of the respiratory tract. The roles of different defense mechanisms in an infected bovine respiratory system, such as mucin production, tight junction barriers, and the production of antimicrobial peptides in in vitro cultures require further investigation in order to provide a comprehensive understanding of the disease pathogenesis. In this report, we describe the different aspects of BRD, including the most implicated pathogens and the respiratory tract, which are important to incorporate in disease models assembled in vitro. Although current advancements of bovine respiratory cultures have led to knowledge of the disease, 3D multicellular organoids that better recapitulate the in vivo environment exhibit potential for future investigations.

Integrated Network Analysis to Identify Key Modules and Potential Hub Genes Involved in Bovine Respiratory Disease: A Systems Biology Approach

Background: Bovine respiratory disease (BRD) is the most common disease in the beef and dairy cattle industry. BRD is a multifactorial disease resulting from the interaction between environmental stressors and infectious agents. However, the molecular mechanisms underlying BRD are not fully understood yet. Therefore, this study aimed to use a systems biology approach to systematically evaluate this disorder to better understand the molecular mechanisms responsible for BRD. Methods: Previously published RNA-seq data from whole blood of 18 healthy and 25 BRD samples were downloaded from the Gene Expression Omnibus (GEO) and then analyzed. Next, two distinct methods of weighted gene coexpression network analysis (WGCNA), i.e., module-trait relationships (MTRs) and module preservation (MP) analysis were used to identify significant highly correlated modules with clinical traits of BRD and non-preserved modules between healthy and BRD samples, respectively. After identifying respective modules by the two mentioned methods of WGCNA, functional enrichment analysis was performed to extract the modules that are biologically related to BRD. Gene coexpression networks based on the hub genes from the candidate modules were then integrated with protein-protein interaction (PPI) networks to identify hub-hub genes and potential transcription factors (TFs). Results: Four significant highly correlated modules with clinical traits of BRD as well as 29 non-preserved modules were identified by MTRs and MP methods, respectively. Among them, two significant highly correlated modules (identified by MTRs) and six nonpreserved modules (identified by MP) were biologically associated with immune response, pulmonary inflammation, and pathogenesis of BRD. After aggregation of gene coexpression networks based on the hub genes with PPI networks, a total of 307 hub-hub genes were identified in the eight candidate modules. Interestingly, most of these hub-hub genes were reported to play an important role in the immune response and BRD pathogenesis. Among the eight candidate modules, the turquoise (identified by MTRs) and purple (identified by MP) modules were highly biologically enriched in BRD. Moreover, STAT1, STAT2, STAT3, IRF7, and IRF9 TFs were suggested to play an important role in the immune system during BRD by regulating the coexpressed genes of these modules. Additionally, a gene set containing several hub-hub genes was identified in the eight candidate modules, such as TLR2, TLR4, IL10, SOCS3, GZMB, ANXA1, ANXA5, PTEN, SGK1, IFI6, ISG15, MX1, MX2, OAS2, IFIH1, DDX58, DHX58, RSAD2, IFI44, IFI44L, EIF2AK2, ISG20, IFIT5, IFITM3, OAS1Y, HERC5, and PRF1, which are potentially critical during infection with agents of bovine respiratory disease complex (BRDC). Conclusion: This study not only helps us to better understand the molecular mechanisms responsible for BRD but also suggested eight candidate modules along with several promising hub-hub genes as diagnosis biomarkers and therapeutic targets for BRD.

Melatonin is a potential adjuvant to improve clinical outcomes in individuals with obesity and diabetes with coexistence of Covid-19

Coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a newly discovered highly pathogenic virus that was declared pandemic in March 2020 by the World Health Organization. The virus affects the respiratory system, produces an inflammatory storm that causes lung damage and respiratory dysfunction. It infects humans of all ages. The Covid-19 takes a more severe course in individuals with chronic metabolic diseases such as obesity, diabetes mellitus, and hypertension. This category of persons exhibits weak immune activity and decreased levels of endogenous antioxidants. Melatonin is a multifunctional signaling hormone synthesized and secreted primarily by the pineal gland. It is a potent antioxidant with immunomodulatory action and has remarkable anti-inflammatory effects under a variety of circumstances. Regarding Covid-19 and metabolic syndrome, adequate information about the relationship between these two comorbidities is required for better management of these patients. Since Covid-19 infection and complications involve severe inflammation and oxidative stress in people with obesity and diabetes, we anticipated the inclusion of melatonin, as powerful antioxidant, within proposed treatment protocols. In this context, melatonin is a potential and promising agent to help overcome Covid-19 infection and boost the immune system in healthy persons and obese and diabetic patients. This review summarizes some evidence from recently published reports on the utility of melatonin as a potential adjuvant in Covid-19-infected individuals with diabetes and obesity.