UCLA

Background

Brucellosis, a zoonotic infection caused by one of the Gram-negative intracellular bacteria of the Brucella genus, is an ongoing public health problem in Perú. While most patients who receive standard antibiotic treatment recover, 5-40% suffer a brucellosis relapse. In this study, we examined the ex vivo immune cytokine profiles of recovered patients with a history of acute and relapsing brucellosis.

Methodology/principal findings

Blood was taken from healthy control donors, patients with a history of acute brucellosis, or patients with a history of relapsing brucellosis. Peripheral blood mononuclear cells were isolated and remained in culture without stimulation or were stimulated with a panel of toll-like receptor agonists or heat-killed Brucella melitensis (HKBM) isolates. Innate immune cytokine gene expression and protein secretion were measured by quantitative real-time polymerase chain reaction and a multiplex bead-based immunoassay, respectively. Acute and relapse patients demonstrated consistently elevated cytokine gene expression and secretion levels compared to controls. Notably, these include: basal and stimulus-induced expression of GM-CSF, TNF-α, and IFN-γ in response to LPS and HKBM; basal secretion of IL-6, IL-8, and TNF-α; and HKBM or Rev1-induced secretion of IL-1β, IL-2, GM-CSF, IFN-Υ, and TNF-α. Although acute and relapse patients were largely indistinguishable by their cytokine gene expression profiles, we identified a robust cytokine secretion signature that accurately discriminates acute from relapse patients. This signature consists of basal IL-6 secretion, IL-1β, IL-2, and TNF-α secretion in response to LPS and HKBM, and IFN-γ secretion in response to HKBM.

Conclusions/significance

This work demonstrates that informative cytokine variations in brucellosis patients can be detected using an ex vivo assay system and used to identify patients with differing infection histories. Targeted diagnosis of this signature may allow for better follow-up care of brucellosis patients through improved identification of patients at risk for relapse.