Targeting the F17-A Fimbrial gene: An efficient method for the quantitative detection of Escherichia coli F17

Escherichia coli (E. coli) F17 is one of the leading bacterial causes of diarrhea in farm livestock, which cause huge economic losses and could also pose potential risks to public health. Generally, the monitoring the E. coli F17 is based on the polymerase chain reaction (PCR) and bacteria plate counting method, which were largely limited by the time-consuming nature and susceptibility to detection errors. Hence, there is an urgent need to develop a rapid and quantitative detection method for E. coli F17. In the present study, an E. coli F17 challenge experiment in ovine intestinal epithelial cells (IECs) was employed as an in vitro model. At different post-challenge time points (1 h, 2 h, and 3 h), two conventional methods (bacteria plate counting and microplate method) were conducted as benchmarks to estimate the number of E. coli F17 adhering to the IECs. Additionally, total genomic DNA was extracted and quantitative Real-time PCR (qPCR) was performed to detect the relative abundance of E. coli F17 fimbrial pilin (F17-A) and adhesion (F17-G) genes. Subsequently, statistical analyses, including Pearson's correlation coefficient (PCC) method and linear curve-fitting, were performed to evaluate the correlation between the abundance of F17-A/G genes and the results of the benchmark methods. The results showed that the relative abundances of both genes were highly correlated with the number of E. coli F17 that adhered to the IECs, among them, the F17-A gene showed a stronger correlation with the bacterial counts, exhibiting a correlation coefficient > 0.85. Furthermore, standard curves analyses further confirmed the out-performed quantitative performance of F17-A gene and a significantly stronger correlation with bacterial counts which exhibited an outstanding linear correlation (r = -0.9534, R² = 0.9252) with amplification efficiency of 101.4%, The results of the present study indicate that targeting fimbrial genetic hallmarks via qPCR is an effective and promising method for E. coli F17 quantification, which could potentially contribute to epidemiological studies and pathogen monitoring in the livestock industry.