Abstract
Mycobacterium bovis (M. bovis) causes bovine tuberculosis (bTB). The challenges in controlling and eradicating this zoonotic disease are compounded by our incomplete understanding of the host immune response. In this study, we used high-throughput bulk RNA sequencing (RNA-seq) to characterise the response profiles of γδ T cells to antigenic stimulation using purified protein derivate from M. bovis (PPDb). γδ T cells are a subgroup of T cells that bridge innate and adaptive immunity and have known anti-mycobacterial response mechanisms. These cells are usually classified based on the expression of a pathogen-recognition receptor, Workshop Cluster 1 (WC1), into two main subsets: WC1.1+ and WC1.2+. Previous studies have identified a preferential transcriptomic response in WC1.1+ cells during natural bTB infection, suggesting a subset-specific response to mycobacterial antigens. This follow on study tested the hypothesis that a subset specific response would also be apparent from γδ T cells from infected cattle after repeat stimulation. Peripheral blood was collected from Holstein-Friesian cattle naturally infected with M. bovis, confirmed by a single intradermal comparative tuberculin test (SICTT) and IFN-γ ELISA and stimulated with 10 μg/ml PPDb for 6 hours. After whole blood stimulation, WC1.1+ and WC1.2+ γδ T cell subsets were isolated using magnetic cell sorting (n = 5 per group). High-quality RNA was extracted from each purified lymphocyte subset (WC1.1+ and WC1.2+) to generate transcriptomes using bulk RNA sequencing, resulting in 20 RNA-seq libraries. Transcriptomic analysis revealed 111 differentially expressed genes (DEGs) common to both WC1.1+ and WC1.2+ γδ T cell compartments, including upregulation of IL1A, IL1B, IL6, IL17A, IL17F, and IFNG genes (FDR-Padj. < 0.1). Interestingly, the WC1.2+ cells showed upregulation of IL10, CCL22, and GZMA (log2FC ≥ 1.5, and FDR-Padj. < 0.1). In conclusion, while WC1.1+ and WC1.2+ γδ T cells exhibit a conserved inflammatory response to PPDb, differences in anti-inflammatory and antimicrobial gene expression between these cell subsets provide new insights into their effector functions in response to mycobacterial antigens.