Front Microbiol. 2026 Feb 17;17:1751544. doi: 10.3389/fmicb.2026.1751544. eCollection 2026.
ABSTRACT
INTRODUCTION: Q fever, caused by Coxiella burnetii, is a zoonotic disease of global relevance with domestic ruminants as the main reservoirs. Serological diagnosis, especially enzyme-linked immunosorbent assay (ELISA), often suffers from limited sensitivity and specificity due to antigenic variability and cross-reactivity.
SCIENTIFIC GOAL: In this study, a combined proteomic and literature research approach was used to identify immunoreactive proteins and predict linear B-cell epitopes as alternative diagnostic targets.
METHODS: Total protein extracts of a C. burnetii field isolate from sheep were separated by two-dimensional gel electrophoresis, and immunoreactive proteins were detected by Western blotting using pooled sheep sera obtained from various flocks with known Q fever status. Immunoreactive proteins were identified by LC-MS/MS and used for linear B-cell epitope prediction for peptide synthesis. Peptides (n = 30) were initially screened by fluorescent ELISA against nine field serum pools (90 individual sera), and the most promising peptides (n = 15) were individually tested with 79 single sera. Diagnostic performance was assessed by receiver operating characteristic (ROC) analysis and by a multi-peptide rule ("positive if ≥1 peptide reactive").
RESULTS: A total of 156 seroreactive proteins, including 51 previously reported antigens, were detected, among others, Com1, CBU_0482, and Mip. Although the selected 15 peptides showed a specific reaction with pooled sera, they showed limited diagnostic performance with an area under the curve (AUC) of 0.5-0.7 when using single serum samples (n = 79). Multi-peptide combinations (6-8 peptides) increased sensitivity (Se) to 80% and specificity (Sp) to 75%.
DISCUSSION: Although single peptides lacked discriminatory power, multi-epitope combinations reached acceptable accuracy and may be used as a complementary tool for commercial ELISAs. However, larger bioinformatic approaches and validation studies are required to identify specific peptides of high diagnostic accuracy.
PMID:41783493 | PMC:PMC12953093 | DOI:10.3389/fmicb.2026.1751544