Abstract
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.
Highlights
Bovine respiratory disease (BRD) is the most common and costly infectious disease in the beef and dairy cattle industry
The use of SGK inhibitors may be a suitable strategy to reduce BoHV-1 and HSV-1 replication (Kook and Jones, 2016). These findings demonstrate the relevance of the mentioned modules as well as their genes, especially hub–hub genes and transcription factor (TF) as important candidates in the development of BRD, helping us to better understand the molecular mechanisms responsible for the immune response to BRD
Given that BRD is the main cause of morbidity and mortality in beef and dairy cattle and has a potential impact on economic losses in the livestock industry, a systems biology approach was used to further investigate the molecular mechanisms of BRD as well as to identify diagnosis biomarkers and therapeutic targets for BRD
Summary
Bovine respiratory disease (BRD) is the most common and costly infectious disease in the beef and dairy cattle industry. BRD is a multifactorial disease, and its onset is usually associated with stress factors (nutritional or environmental risk factors) and the presence of infectious agents (Gagea et al, 2006; Grissett et al, 2015) Stress factors such as weaning, shipping distance, and commingling that negatively affect the immune system, can predispose cattle to a primary infection (Snowder et al, 2006; Timsit et al, 2016b). Clinical diagnosis of BRD is made by visual observations and is usually based on clinical signs such as high rectal temperature, depression/lethargy, nasal or ocular discharge, increased respiration rate, reduced feed intake, and reduced average daily gain (Amrine et al, 2013; Behura et al, 2017) This method has low detection sensitivity and specificity, and the diagnosis is often made without identifying the cause of the disease (White and Renter, 2009; Timsit et al, 2016a).
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