A highly sensitive one-tube nested quantitative real-time PCR assay for specific detection of Bordetella pertussis using the LNA technique

Objectives: Bordetella pertussis is a highly contagious respiratory agent and is the causative pathogen of pertussis, which primarily affects children. Current diagnostic techniques for this pathogen have a variety of limitations including a long culture time, low bacterial load, and lack of specificity. Methods: This article reports the development of a one-tube nested quantitative real-time PCR assay using the locked nucleic acid (LNA) technique (LNA-OTN-q-PCR), targeting the BP485 gene and using a simple inexpensive extraction method. A total of 130 clinical samples from patients with clinically suspected pertussis, collected from the Children’s Hospital of Hebei, China, were tested by LNA-OTN-q-PCR assay. RT-PCR and two-step semi-nested PCR assays were performed in parallel for comparison. Results: Only strains of B. pertussis were identified as positive, whereas all of the remaining strains were appropriately identified as negative by the LNA-OTN-q-PCR assay. A single copy per reaction can be detected by the LNA-OTN-q-PCR assay. Additionally, the sensitivity of this method was 100 times that of the RT-PCR assay (100 copies per reaction). Sixty-three of the 130 clinical samples were detected positive by LNA-OTN-q-PCR assay; in contrast, RT-PCR was able to detect only 41 positive samples. Following this, all 63 samples were positively identified by two-step semi-nested PCR. Compared with the two-step semi-nested PCR assay, both the specificity and sensitivity of the LNA-OTN-q-PCR assay using purified DNA and crude extract were 100%. Conclusions: This assay was able to detect B. pertussis infection with high sensitivity and specificity. This test shows great potential as a promising technique to detect B. pertussis in both clinical laboratories and public health settings. Keywords: One-tube nested quantitative real-time PCR using the LNA technique, Bordetella pertussis, Simple extraction method