The absolute PCR quantification of microbial target genes in soils using internal gene as standards

Abstract:

[Objective] Fluorescence quantitative PCR can absolutely or relatively quantify the target genes in soil samples. However, the accuracies of absolute quantification of target genes are influenced by DNA yields during DNA extraction and inhibition caused by co-extracted humic acids. [Methods] Using prepared mutated plasmid DNA, this paper quantified the 16S rRNA gene from one paddy soil by the methods of adding such plasmid containing mutated internal gene before DNA extraction. Two-way primers amplification showed that the added internal gene inserted in this mutated plasmid DNA was specific to studied soils when used as internal standards. [Results] The results showed that DNA yields varied greatly among these paddy soil samples, leading to incorrect results from absolute quantification. Using the mutated plasmid DNA, the precision of resulted data points has been improved significantly. It showed that the coefficient of variation for absolute 16S rRNA gene copies of these samples was 17.8, which was 66.7% lower than the values calculated for soil samples without internal gene correction. It indicates that added internal gene can correct the effects of varied DNA yields. Such tested methods were further used to quantify 16S rRNA gene from 6 wetland soils with great spatial and physic-chemical differences in soil organic matter contents and water moisture. The total bacterial abundance indicated by absolute 16S rRNA gene copies was linearly correlated (R2=0.694, p<0.001) with soil microbial biomass carbon, demonstrating that after addition of internal standards, the quantified 16S rRNA gene copies can accurately reflect the absolute microbial abundance in soil samples. [Conclusion] The added internal gene can correct for DNA yields and the effects of inhibition of humic acids on PCR amplification. Using plasmid containing mutated internal gene as internal standards, this method, as a nucleic acid assay can be applied in soil ecology to quantify soil microbial biomass and absolute abundance of microbial functional genes.