RESUMEN
Background & objectives: Bacillus anthracis, Yersinia pestis, Burkholderia pseudomallei and Brucella species are potential biowarfare agents. Classical bacteriological methods for their identification are cumbersome, time consuming and of potential risk to the handler. Methods: We describe a sensitive and specific multiplex polymerase chain reaction (mPCR) assay involving novel primers sets for the simultaneous detection of B. anthracis, Y. pestis, B. pseudomallei and Brucella species. An additional non-competitive internal amplification control (IAC) was also included. Results: The mPCR was found to be specific when tested against closely related organisms. The sensitivity of the assay in spiked blood samples was 50 colony forming units (cfus)/25 μl reaction, for the detection of B. anthracis, Y. pestis and Brucella species; and 150 cfus/25 μl reaction, for B. pseudomallei. The assay proved useful in correctly and promptly identifing the clinical isolates of the targeted agents recovered from patients, compared to the gold standard culture methods. Interpretation & conclusion: The assay described in this study showed promise to be useful in application as a routine detection cum diagnostic method for these pathogens.
RESUMEN
An internal amplification control, which could be co-amplified with the invA target gene of Salmonella in the PCR system, was constructed in order to indicate possible PCR inhibitors derived from food samples. Specificity of this PCR system was tested with 9 Salmonella strains and 15 non-Salmonella strains, and the results showed that there was a 374 bp amplicon resulted from all Salmonella strains, while only a 513 bp IAC amplicon appeared after the amplification for all non-Salmonella strains. The detection sensitivity of this PCR system was 12.8 fg/?L for purified target DNA, and the detection limit for artificially inoculated milks was 8 cfu /25g if they were enriched for 8h in buffered peptone water. Salmonella in 80 samples of seriously contaminated milks was detected by the PCR method developed in this study, and the experiments demonstrated that it could successfully eliminate false-negative results.