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Prediction of Johne’s disease state based on quantification of T cell markers and their interaction with macrophages in the bovine intestine

Authors :
Judith R. Stabel
Elsa Obando Marrero
Caitlin J. Jenvey
Adrienne L. Shircliff
National Animal Disease Center
United States Department of Agriculture (USDA)
Source :
Veterinary Research, Veterinary Research, BioMed Central, 2021, 52 (1), pp.55. ⟨10.1186/s13567-021-00925-x⟩, Veterinary Research, Vol 52, Iss 1, Pp 1-9 (2021)
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

Cell-mediated immune responses to Mycobacterium avium subsp. paratuberculosis (MAP) are regulated by various types of T lymphocytes. The aim of this study was to quantitate T cell subsets in the mid-ileum of cows naturally infected with MAP to identify differences during different stages of infection, and to determine whether these subsets could be used as predictors of disease state. Immunofluorescent labeling of T cell subsets and macrophages was performed on frozen mid-ileal tissue sections archived from naturally infected dairy cows in either subclinical or clinical disease status, and noninfected control cows. Comprehensive IF staining for CD4, CD8α, TcR1-N24 (gamma delta), FoxP3, CXCR3 and CCR9 served to define T cell subsets and was correlated with macrophages present. Clinically affected cows demonstrated significantly higher numbers of CXCR3+ (Th1-type) and CCR9+ (total small intestinal lymphocytes) cells at the site of infection compared to the subclinical cows and noninfected controls. Further, predictive modeling indicated a significant interaction between CXCR3+ and AM3K+ (macrophages) cells, suggesting that progression to clinical disease state aligns with increased numbers of these cell types at the site of infection. The ability to predict disease state with this model was improved from previous modeling using immunofluorescent macrophage data. Predictive modelling indicated an interaction between CXCR3+ and AM3K+ cells, which could more sensitively detect subclinical cows compared to clinical cows. It may be possible to use this knowledge to improve and develop an assay to detect subclinically infected animals with more confidence during the early stages of the disease.

Details

Language :
English
ISSN :
09284249 and 12979716
Database :
OpenAIRE
Journal :
Veterinary Research, Veterinary Research, BioMed Central, 2021, 52 (1), pp.55. ⟨10.1186/s13567-021-00925-x⟩, Veterinary Research, Vol 52, Iss 1, Pp 1-9 (2021)
Accession number :
edsair.doi.dedup.....52f56a2d68be7e804a282665d8ddd289
Full Text :
https://doi.org/10.1186/s13567-021-00925-x⟩