Contrasting Gene Expression Profiles of Monocytes and Lymphocytes From Peste-Des-Petits-Ruminants Virus Infected Goats

Abstract

In this study, transcriptome analysis of PPRV infected PBMC subsets—T helper cells, T cytotoxic cells, monocytes, and B lymphocytes was done to delineate their role in host response. PPRV was found to infect lymphocytes and not monocytes. The established receptor for PPRV—SLAM was found downregulated in lymphocytes and non-differentially expressed in monocytes. A profound deviation in the global gene expression profile with a large number of unique upregulated genes (851) and downregulated genes (605) was observed in monocytes in comparison to lymphocytes. ISGs—ISG15, Mx1, Mx2, RSAD2, IFIT3, and IFIT5 that play a role in antiviral response and the genes for viral sensors—MDA5, LGP2, and RIG1, were found to be upregulated in lymphocytes and downregulated in monocytes. The transcription factors—IRF-7 and STAT-1 that regulate expression of most of the ISGs were found activated in lymphocytes and not in monocytes. Interferon signaling pathway and RIG1 like receptor signaling pathway were found activated in lymphocytes and not in monocytes. This contrast in gene expression profiles and signaling pathways indicated the predominant role of lymphocytes in generating the antiviral response against PPRV in goats, thus, giving us new insights into host response to PPRV.

RNAseq Reveals the Contribution of Interferon Stimulated Genes to the Increased Host Defense and Decreased PPR Viral Replication in Cattle

“…In experiments with the Sungri/96 PPRV vaccine virus, IFN-α/β mRNA were not detected after the infection of PBMC [31] and evasion of IFN-induced antiviral effects by PPRV have been shown to occur through miRNA mediated regulation of IRF3 and IRF7 [32]. In contrast, studies with a virulent PPRV strain demonstrated that genes within the interferon and RIG-1 like receptor signaling pathway, IRF-7 and STAT-1 that regulate the expression of ISGs, were active in lymphocytes [33]. Our previous report also indicates the contribution of TLR7 mediated higher IFN alpha induction as a factor for the lower replication of PPRV in cattle PBMC [17].…”

“…Viral infection-induced interferons induce an exclusive and moderately overlapping set of interferon stimulated genes (ISG) and studies have identified 50 to 1000 ISGs (using microarrays) that are typical to some cells types with effector functions limited to the classical ISGs, namely protein kinase (PKR; also known as eukaryotic translational initiation factor 2-alphase kinase -EIF2AK2), Myxovirus Resistance Protein 1 (MX1), 2 -5 -oligoadenylate synthetase 1 (OAS1), Tripartite Motif Containing 5 (TRIM5), Interferon-stimulated gene 15 (ISG15), adenosine deaminase acting on RNA (ADAR), interferon-induced transmembrane protein 1/2/3 (IFITM1/2/3 also called CD225), Tetherin (also known as BST2 or CD17), Viperin (also known as Radical S-Adenosyl Methionine Domain Containing 2 -RSAD2) [34,35] and ATP-dependent dsRNA helicase DHX58 also known as RIG-I-like receptor LGP2 (RLR) [36]. Up-regulation of the ISGs (ISG15, Mx1, Mx2, RSAD2, IFIT3 and IFIT5) that play a role in antiviral response and the viral sensors MDA5, LGP2 and RIG1 were found to up-regulated in lymphocytes upon exposure to a virulent strain of PPRV [33]. Our RNAseq data also reveal that the IFN type I responses are highly up-regulated in cattle.…”

Systems Biology under heat stress in Indian Cattle

“…Transcriptome profiling by RNA-seq is the most common methodology to study the changes in systems biology. RNA profiling based on next-generation sequencing enables to measure and compare gene expression patterns [16]. The global transcriptome of Tharparkar and Crossbred indicated differential response to heat stress as evident from the DEGs, that are either distinct to both or have a difference in expression.…”

“…The systems biology behind a phenotype is most commonly studied by transcriptome profiling [14,15]. RNA-seq is a high throughput approach to measure relative global changes in the transcripts under specific condition(s) [14,16,17]. RNA -seq allows for analysis of transcriptome in an unbiased way, with, a tremendous dynamic detection range (>8,000 fold), and low background signals [18].…”

Systems Biology behind immunoprotection of both Sheep and Goats after Sungri/96 PPRV vaccination

“…The counts were used for calculating differentially expressed genes (DEGs) by use of R packages -EBSeq, DESeq2, edgeR. The common DEGs from the three packages were used for downstream analysis while fold changes for the corresponding genes were taken from DESeq2 [24].…”