Comparison of droplet digital PCR and quantitative real-time PCR for examining population dynamics of bacteria in soil

Abstract

The newly developed droplet digital PCR (DD-PCR) has shown promise as a DNA quantification technology in medical diagnostic fields. This study evaluated the applicability of DD-PCR as a quantitative tool for soil DNA using quantitative real-time PCR (qRT-PCR) as a reference technology. Cupriavidus sp. MBT14 and Sphingopyxis sp. MD2 were used, and a primer/TaqMan probe set was designed for each (CupMBT and SphMD2, respectively). Standard curve analyses on tenfold dilution series showed that both qRT-PCR and DD-PCR exhibited excellent linearity (R (2) = 1.00) and PCR efficiency (≥92 %) across their detectable ranges. However, DD-PCR showed a tenfold greater sensitivity than qRT-PCR. MBT14 and MD2 were added to non-sterile soil at 0 ~ 5 × 10(8) and 0 ~ 5 × 10(7) cells per gram of soil, respectively (n = 5). This bacterial load test indicated that DD-PCR was more sensitive and discriminating than qRT-PCR. For instance, DD-PCR showed a gradual DNA increase from 14 to 141,160 MBT14 rDNA copies μL DNA extract(-1) as the bacterial load increased, while qRT-PCR could quantify the DNA (6,432 copies μL DNA(-1)) at ≥5 × 10(5) MBT14 per gram of soil. When temporal DNA changes were monitored for 3 weeks in the amended soils, the two technologies exhibited nearly identical changes over time. Linearity tests (y = a · x) revealed excellent quantitative agreement between the two technologies (a = 0.98, R (2) = 0.97 in the CupMBT set and a = 0.90, R (2) = 0.94 in the SphMD2 set). These results suggest that DD-PCR is a promising tool to examine temporal dynamics of microorganisms in complex environments.

Sensitive detection of Porcine circovirus-2 by droplet digital polymerase chain reaction

“…After the reaction endpoint, Poisson statistics are used to measure the initial template concentration by determining the fraction of positive (containing an amplified target) and negative (no amplified target) droplets. 4 Compared with TaqMan real-time PCR, ddPCR has been confirmed to have some of the following advantages: it is more sensitive for low copy number quantification, 6 is better at identifying single nucleotide polymorphisms, 10 is less susceptible to PCR inhibitors, and can detect target DNA in complex environments. 5 All of these features make ddPCR a promising detection technique and a practical method for clinical diagnosis.…”

Comparison of next-generation droplet digital PCR (ddPCR) with quantitative PCR (qPCR) for enumeration of Cryptosporidium oocysts in faecal samples

“…ddPCR has also shown its potential utility in the char-142 acterisation of the temporal dynamics of microbial populations in 143 complex soil environments (Kim et al, 2014) and in the accurate 144 quantification of DNA (Dong et al, 2014 The oocysts were purified using a Ficoll density gradient extraction 187 as previously described (Meloni and Thompson, 1996). Purified (10,000g) in a bench-top microcentrifuge (500,000 oocysts total).…”

Development of a Droplet Digital Polymerase Chain Reaction for Rapid and Simultaneous Identification of Common Foodborne Pathogens in Soft Cheese

“…This procedure represents an important advantage in comparison with an assay based on qPCR because construction of a standard curve requires accurate quantification of the template DNA, which might be difficult to obtain (especially if working with food samples) (Kim et al, 2014). qPCR remains the most popular choice for the detection and quantification of a wide variety of microorganisms in food samples due to quantification of real samples, the shorter time required to obtain results, and lower costs (Hudecova, 2015).…”

“…These droplets are monitored for positive amplification after endpoint PCR amplification using fluorescent target-specific hydrolysis probes (Floren et al, 2015). Until now, this method has been adopted for: routine analyses of genetically modified organisms in food and animal feed (Morisset et al, 2013; Gerdes et al, 2016); detection and quantification of pathogenic bacteria such as Salmonella spp., Campylobacter jejuni and Listeria monocytogenes in environmental water (Rothrock et al, 2013); exact quantification of different species in meat and processed meat products (Floren et al, 2015); monitoring the dynamics of microbial populations in soils with different population levels (Kim et al, 2014). …”