Reverse transcription-PCR-electrospray ionization mass spectrometry for rapid detection of biothreat and common respiratory pathogens

用于快速检测生物威胁和常见呼吸道病原体的逆转录-PCR-电喷雾电离质谱法

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Abstract

Electrospray ionization mass spectrometry (ESI-MS) analysis of reverse transcription (RT)-PCR amplicons from human respiratory samples allows for broad pathogen identification approximately 8 h after collection. We investigated the performance characteristics of a high-throughput RT-PCR-coupled ESI-MS assay for distinguishing biothreat (BT) agents from common bacterial, fungal, and viral respiratory pathogens in bronchoalveolar lavage (BAL) fluid specimens from subjects with suspected respiratory infections. In a retrospective case series, 202 BAL fluid specimens were collected at the Johns Hopkins Hospital between August 2010 and February 2011 from patients with suspected acute respiratory infections. Samples were processed using standard bacterial, viral, and fungal testing in the clinical microbiology laboratory as part of routine care and then were blindly spiked with either water or nucleic acids from BT organisms (Bacillus anthracis, Yersinia pestis, Francisella tularensis, Brucella spp., Burkholderia spp., and Rickettsia prowazekii) and tested by RT-PCR-ESI-MS. The sensitivities and specificities of RT-PCR-ESI-MS versus standard clinical methods were as follows: for mock BT DNA, 98.5% sensitivity (95% confidence interval [CI], 94.2 to 99.7%) and 100% specificity (95% CI, 93.1 to 100.0%); for bacterial pathogens, 81.8% sensitivity (95% CI, 74.3 to 87.6%) and 73.6% specificity (95% CI, 64.2 to 81.4%); for viral pathogens, 93.3% sensitivity (95% CI, 66.0 to 99.7%) and 97.3% specificity (95% CI, 89.7 to 99.5%); for fungal pathogens, 42.6% sensitivity (95% CI, 29.5 to 56.7%) and 97.8% specificity (95% CI, 91.8 to 99.6%). Our data suggest that RT-PCR-ESI-MS is a useful adjunct to standard culture protocols for rapid detection of both BT and common respiratory pathogens; further study is required for assay validation, especially for fungal detection, and potential implementation.

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