title: Correlation coefficients between different methods of expressing bacterial quantification using real time PCR.
abstract: The applications of conventional culture-dependent assays to quantify bacteria populations are limited by their dependence on the inconsistent success of the different culture-steps involved. In addition, some bacteria can be pathogenic or a source of endotoxins and pose a health risk to the researchers. Bacterial quantification based on the real-time PCR method can overcome the above-mentioned problems. However, the quantification of bacteria using this approach is commonly expressed as absolute quantities even though the composition of samples (like those of digesta) can vary widely; thus, the final results may be affected if the samples are not properly homogenized, especially when multiple samples are to be pooled together before DNA extraction. The objective of this study was to determine the correlation coefficients between four different methods of expressing the output data of real-time PCR-based bacterial quantification. The four methods were: (i) the common absolute method expressed as the cell number of specific bacteria per gram of digesta; (ii) the Livak and Schmittgen, ΔΔCt method; (iii) the Pfaffl equation; and (iv) a simple relative method based on the ratio of cell number of specific bacteria to the total bacterial cells. Because of the effect on total bacteria population in the results obtained using ΔCt-based methods (ΔΔCt and Pfaffl), these methods lack the acceptable consistency to be used as valid and reliable methods in real-time PCR-based bacterial quantification studies. On the other hand, because of the variable compositions of digesta samples, a simple ratio of cell number of specific bacteria to the corresponding total bacterial cells of the same sample can be a more accurate method to quantify the population.
authors.affiliation: Department of Animal Science, University of Mohaghegh Ardabili, 56199-11367, Ardabil, Iran.|Institute of Tropical Agriculture, University Putra Malaysia, 43400 UPM Serdang, Malaysia.
authors.forename: Bahman
authors.initials: B
authors.lastname: Navidshad
authors.affiliation: Institute of Tropical Agriculture, University Putra Malaysia, 43400 UPM Serdang, Malaysia.
authors.forename: Juan Boo
authors.initials: JB
authors.lastname: Liang
authors.affiliation: Laboratory of Industrial Biotechnology, Institute of Bioscience, University Putra Malaysia, 43400 UPM Serdang, Malaysia.
authors.forename: Mohammad Faseleh
authors.initials: MF
authors.lastname: Jahromi
mesh_terms: D001419:Bacteria / Q000187:drug effects / Q000235:genetics / Q000254:growth & development; D058491:Bacterial Load / Q000379:methods* / Q000706:statistics & numerical data; D015169:Colony Count, Microbial / Q000706:statistics & numerical data; D003470:Culture Media / Q000494:pharmacology; D004269:DNA, Bacterial / Q000032:analysis*; D003627:Data Interpretation, Statistical; D004755:Enterobacteriaceae / Q000187:drug effects / Q000235:genetics / Q000254:growth & development; D016983:Enterococcus / Q000187:drug effects / Q000235:genetics / Q000254:growth & development; D004926:Escherichia coli / Q000187:drug effects / Q000235:genetics / Q000254:growth & development; D007777:Lactobacillaceae / Q000187:drug effects / Q000235:genetics / Q000254:growth & development; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods*
chemical_list: D003470:Culture Media; D004269:DNA, Bacterial