DNA extraction leads to bias in bacterial quantification by qPCR

Abstract

Quantitative PCR (qPCR) has become a widely used technique for bacterial quantification. The affordability, ease of experimental design, reproducibility, and robustness of qPCR experiments contribute to its success. The establishment of guidelines for minimum information for publication of qPCR experiments, now more than 10 years ago, aimed to mitigate the publication of contradictory data. Unfortunately, there are still a significant number of recent research articles that do not consider the main pitfalls of qPCR for quantification of biological samples, which undoubtedly leads to biased experimental conclusions. qPCR experiments have two main issues that need to be properly tackled: those related to the extraction and purification of genomic DNA and those related to the thermal amplification process. This mini-review provides an updated literature survey that critically analyzes the following key aspects of bacterial quantification by qPCR: (i) the normalization of qPCR results by using exogenous controls, (ii) the construction of adequate calibration curves, and (iii) the determination of qPCR reaction efficiency. It is primarily focused on original papers published last year, where qPCR was applied to quantify bacterial species in different types of biological samples, including multi-species biofilms, human fluids, and water and soil samples. KEY POINTS: • qPCR is a widely used technique used for absolute bacterial quantification. • Recently published papers lack proper qPCR methodologies. • Not including proper qPCR controls significantly affect experimental conclusions.

Keywords: Bacterial load quantification; Calibration curve; Exogenous control; gDNA extraction efficiency; gDNA yield; qPCR; qPCR reaction efficiency.

Fig. 1

General concept and pitfalls behind bacterial load quantification by qPCR. Bacterial quantification by qPCR requires the preparation of a calibration curve, which includes gDNA isolated from samples with different concentrations of the bacterial species under study (A). However, due to the variable efficiency of the gDNA extraction procedure, each extraction, even from technical replicates, has inherent variability that can lead to biased bacterial load quantification (B). When the starting bacterial amount is known, gDNA loss, due to technical issues, can be easily detected. However, when the initial quantity of bacteria is unknown, it cannot be differentiated whether the variation detected was introduced by technical issues or if it was due to the initial bacterial load (C). As such, the addition of an exogenous control is imperative

Fig. 2

Graphical representation of the percentage (%) of studies presented in Table 1 that considered the three critical aspects for bacterial quantification by qPCR. The caption is the same as described in the Table 1 footer section

Fig. 3

Common flaws when quantifying bacterial load using qPCR. In most of the studies surveyed, (A) DNA extraction normalization was not performed (or described) or was normalized by total gDNA concentration, which can bias the results. Often (B), the qPCR/bacterial load calibration curve is performed by diluting a known gDNA sample, but this fails to consider the different extraction efficiencies at different bacterial concentrations. Also (C) some studies failed to consider the qPCR reaction efficiency that needs to be determined for each primer set and varies according to reagent and equipment used

Fig. 4

Flowchart highlighting the “do’s” and “don’ts” of procedures in bacterial quantification by qPCR. This scheme represents our recommended actions to perform a proper bacterial quantification by qPCR (green lines). It also includes common errors that are generally made (red lines) and should be avoided