Correlation coefficients between different methods of expressing bacterial quantification using real time PCR

Area of Science:

• Microbiology
• Molecular Biology
• Bioinformatics

Background:

• Conventional culture-dependent assays for bacterial quantification are inconsistent and pose health risks.
• Real-time PCR (qPCR) offers a more reliable method for bacterial enumeration.
• Quantifying bacteria in complex matrices like digesta using qPCR presents challenges due to sample variability.

Purpose of the Study:

• To evaluate the correlation between four distinct methods for expressing qPCR-based bacterial quantification data.
• To identify the most accurate and reliable method for bacterial quantification in variable samples.

Main Methods:

• Comparison of four qPCR data expression methods: absolute quantification (cells/gram), ΔΔCt (Livak and Schmittgen), Pfaffl equation, and a relative ratio (specific bacteria/total bacteria).
• Analysis of bacterial populations in digesta samples.

Main Results:

• ΔCt-based methods (ΔΔCt and Pfaffl) demonstrated inconsistency due to their sensitivity to total bacterial population changes.
• The simple relative method, using the ratio of specific to total bacterial cells within the same sample, showed higher accuracy.
• Absolute quantification, while common, is sensitive to sample homogenization and pooling.

Conclusions:

• Relative quantification methods (ΔΔCt and Pfaffl) are not recommended for reliable bacterial enumeration in qPCR studies with variable sample compositions.
• A simple relative method comparing specific bacterial counts to total bacterial counts within a sample is a more accurate approach for qPCR-based bacterial quantification.
• Accurate bacterial quantification in complex samples requires careful consideration of data expression methods to account for sample variability.