title: Accuracy, precision, and method detection limits of quantitative PCR for airborne bacteria and fungi.
abstract: Real-time quantitative PCR (qPCR) for rapid and specific enumeration of microbial agents is finding increased use in aerosol science. The goal of this study was to determine qPCR accuracy, precision, and method detection limits (MDLs) within the context of indoor and ambient aerosol samples. Escherichia coli and Bacillus atrophaeus vegetative bacterial cells and Aspergillus fumigatus fungal spores loaded onto aerosol filters were considered. Efficiencies associated with recovery of DNA from aerosol filters were low, and excluding these efficiencies in quantitative analysis led to underestimating the true aerosol concentration by 10 to 24 times. Precision near detection limits ranged from a 28% to 79% coefficient of variation (COV) for the three test organisms, and the majority of this variation was due to instrument repeatability. Depending on the organism and sampling filter material, precision results suggest that qPCR is useful for determining dissimilarity between two samples only if the true differences are greater than 1.3 to 3.2 times (95% confidence level at n = 7 replicates). For MDLs, qPCR was able to produce a positive response with 99% confidence from the DNA of five B. atrophaeus cells and less than one A. fumigatus spore. Overall MDL values that included sample processing efficiencies ranged from 2,000 to 3,000 B. atrophaeus cells per filter and 10 to 25 A. fumigatus spores per filter. Applying the concepts of accuracy, precision, and MDL to qPCR aerosol measurements demonstrates that sample processing efficiencies must be accounted for in order to accurately estimate bioaerosol exposure, provides guidance on the necessary statistical rigor required to understand significant differences among separate aerosol samples, and prevents undetected (i.e., nonquantifiable) values for true aerosol concentrations that may be significant.
authors.affiliation: Department of Chemical Engineering, Environmental Engineering Program, 9 Hillhouse Avenue, Yale University, New Haven, CT 06520, USA.
authors.forename: Denina
authors.initials: D
authors.lastname: Hospodsky
authors.forename: Naomichi
authors.initials: N
authors.lastname: Yamamoto
authors.forename: Jordan
authors.initials: J
authors.lastname: Peccia
mesh_terms: D000391:Air Microbiology; D001232:Aspergillus fumigatus / Q000235:genetics / Q000378:metabolism; D001407:Bacillus / Q000235:genetics / Q000378:metabolism; D001419:Bacteria / Q000235:genetics / Q000378:metabolism*; D004269:DNA, Bacterial / Q000235:genetics; D004271:DNA, Fungal / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D005658:Fungi / Q000235:genetics / Q000378:metabolism*; D016133:Polymerase Chain Reaction / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013172:Spores, Fungal / Q000235:genetics / Q000378:metabolism
chemical_list: D004269:DNA, Bacterial; D004271:DNA, Fungal
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