These results indicate that dd-PCR is more sensitive for the detection and quantification of DNA from digester samples, which is consistent with a observation by Kim et al. 
that dd-PCR was more sensitive for quantifying DNA from soil than qPCR. PCR inhibitors co-extracted with nucleic acids from environmental samples can adversely affect qPCR quantification . dd-PCR may be less sensitive to PCR inhibitors than the qPCR because the post-PCR quantification regime after 40 cycles can tolerate wide variations in PCR amplification efficiencies  and . The technologies detected five groups: msar, msa, GSK-3 inhibitor mcp, msp, and mcr7 ( Figs. 1a–e), and therefore, they were compared based on these groups. T-test revealed that the technologies identically indicated the digesters in which the target groups were most abundant at p < 0.05. Both technologies also showed the same order among the digesters in order of abundance of msa, mcp, msp, and mcr7 (p < 0.05). In the case of msar, both technologies showed that it was much greater in digester C than in digesters A and B, and dd-PCR showed it was greater in digester A than in digester B, while qPCR showed the opposite (p < 0.05). The linear regression (y = ax + b) was conducted in order to determine whether or not there were quantitative agreements between the dd-PCR and qPCR measurements. Similar to previous observations
showing quantitative agreements between both technologies  and , there were R2 values ranging from 0.59–0.98 in all of the groups ( Protein Tyrosine Kinase inhibitor Fig. 1). However, slope values substantially varied between the groups. Both technologies quantitatively agreed, although their quantitative differences were quite varied. In order to determine whether or not both datasets represent similar relationships among the digester communities, principal component analysis (PCA), a multivariate approach to compare microbial communities, was performed using CANOCO version 4.5 . The PCA plot of dd-PCR shows click here that the first and second principal component axes account for 88.3 and 11.1% of the compositional variance in the data,
respectively (Fig. 2a), whereas that of qPCR shows that the first and second axes account for 98.1 and 1.9% (Fig. 2b). Both plots indicate a substantial difference in the community composition among the digesters, and exhibit similar levels of differentiation among the communities. Both plots also indicate that operational temperature (from 38 to 52.5 °C) coincides with the score of the first axis (from approximately −0.5 to 1.0). Both plots indicate that the community of the thermophilic digester C was distinct from those of the mesophilic digesters A and B, primarily because msar dominated the C community. The msar (Methanosarcina) abundance increased along with the temperature, since Methanosarcina is better established in thermophilic regimes than in mesophilic regimes .