## 3 Results and Discussion
### Quantification of mcrA Gene
Figure 1: Heatmap with the logged values of methane production (L kg\({}^{-1}\) VS) and VFAs concentrations (g L\({}^{-1}\)) in process and control bioreactors with sewage sludge (SS) and cattle slurry (CS). (SSC) control samples of sewage sludge, (CSC) control samples of cattle slurry. Figure 2: Average concentrations of \(mcr\)A, \(MSC\) and \(MST\) genes in 1 g\({}_{\mathrm{D}}\)\({}^{-1}\) of sewage sludge samples (**A**,**C**,**E**, respectively) from the process and control bioreactors and cattle slurry samples (**B**,**D**,**F**, respectively) from the process and control bioreactors. (SSC) control samples of sewage sludge, (CSC) control samples of cattle slurry, (*) indicates statistically significant differences compared to the proper control (\(p<0.05\)). Furthermore, an analysis was made of the presence of statistically significant differences in concentrations of the _mcr_A gene between appropriate samples of SS and CS digestates (exposed to the same antimicrobial substance) and control samples SSC and CSC. Statistically significant differences (\(p<0.05\)) were noted in each case (Figure 3). Importantly, the number of the _mcr_A gene copies in the CSC control sample ranged around \(5.0\times 10^{8}\) in 1 g of digestate (Figure 2B), whereas, in the SSC sample, this concentration was just \(1.34\times 10^{7}\) copies per gram of analyzed sample (Figure 2A), which was 37-fold lower. With these data, one might expect that the concentration and activity of methanogens in the CSC samples would be higher, which should result in a higher efficiency of the process. However, the results of an analysis of AD parameters (Table 2) demonstrated that the CH\({}_{4}\) yield was higher by 72 L kg\({}^{-1}\) VS in the SSC samples, not exposed to the presence of antimicrobial substances. [PERSON] et al. [52] demonstrated in their study that the number of _mcr_A gene copies in substrates undergoing AD may significantly differ from the concentration of transcripts of this gene. In their investigation of the soil from rice fields, these authors showed that the number of _mcr_A gene transcripts changed in different environmental conditions while the number of copies of this gene remained virtually unchanged [52]. These results suggest that only some of the methanogenic _Archaea_ were metabolically active and responsible for CH\({}_{4}\) production. It can be suspected that the underlying reason is that the AD reaction environment presented conditions unfavorable for methanogens, causing the inhibition of the _mcr_A gene transcription processes. In the experiment reported in this article, first  
Figure 3: Principal component analysis (PCA) based on the distribution of the analyzed genes characteristic of methanogens and parameters of methane fermentation in bioreactors with sewage sludge (SS) and cattle slurry (CS). (SSC) control samples of sewage sludge, (CSC) control samples of cattle slurry. and foremost such unfavorable conditions meant exposure to high doses of antimicrobial substances, in addition to the resulting accumulation of VFAs in the selected process bioreactor chambers. Our experiment proved that an evident decrease in the production of CH4, caused by the presence of each of the tested drugs, may not correlate with the abundance of the _mcr_A gene, characteristic of methanogens [53]. Considering the above information, it can be concluded that the abundance of both the _mcr_A gene and its transcripts should be analyzed as part of an evaluation of the metabolic activity of methanogenic microorganisms. The experiment reported herein has shown that an assessment based solely on the presence of a functional gene of methanogens can lead to unreliable data. As the transcription of genes is more closely connected with the activity of microorganisms, determination of the number of _mcr_A gene transcripts seems to be a more adequate measure than just the number of copies of this gene [54; 55; 56; 57].