## 3 Results and Discussion
### The Effects of Antimicrobials on Changes in the Diversity of Methanogenic Microorganisms
The number of the _MSC_ gene copies in 1 g of CS digestate samples was lower by one order of magnitude (2.14 \(\times\)\(10^{6}\)) in comparison with the control sample. Despite the observed decrease in the number of copies of the _MST_ and _MSC_ genes, both gene copies in CS digestate samples remained constantly high (in the order of \(10^{7}\) in 1 g of digestate). The persistently high number of copies of the _MST_ and _MSC_ genes in CS digestate proves that _Methanosarcinaceae_ and _Methanosataceae_ have adapted to the antibiotics and products of their metabolism present in the digestate. The results of our study are convergent with the reports by other researchers, who applied molecular methods to monitor the composition of microbial communities in manure digestate, and also noted the most numerous presence of _Methanosarcinaceae_[60, 61, 62]. A possible underlying cause of the dominance of _Methanosarcinaceae_ in CS digestate could be the degree of dilution of the substrate, characteristic of cattle slurry and beneficial for the microorganisms in question. The prevalence of _Methanosarcinaceae_ could also result in the decreasing abundance of _Methanosataceae_ in the substrate fed to a bioreactor, as these two families of microorganisms compete for such products as acetate [36]. The influence of antibiotics on changes in the methanogenic community in the samples is well illustrated by the Ward method based on gene concentrations determined in the qPCR assay (Figure 4). Three main clusters were identified. In the case of SS, the heatmap shows that the highest differences compared to the control (SSC) were observed in MET SS and AMO SS, which formed clusters IIIa and IIIb, respectively. Moreover, cluster II included MET SC and AMO SC. Exposure of CS and SS to MET and AMO caused the greatest changes in the concentrations of genes that are characteristic of the methanogenic community. In Figure 1 discussed above, among others the distinctness of MET SS and AMO CS is visible. However, the present analysis clearly distinguishes four process bioreactors, both SS and CS exposed to MET and AMO. This may indicate that both MET and AMO had the greatest impact on the disturbance of the AD efficiency in both substrates by its characteristic microbiota, although the production of methane itself would indicate a distinct inhibition of the process by MET in the case of SS, and by AMO in the case of CS. Interestingly, SS OXY and SSC were in a common cluster (IIIc), as were CS OXY and CSC (cluster I). However, the exposure of both SS and CS to OXY was manifested by a significant reduction in the efficiency of methane production, in comparison to the proper control (Table 2). It is noticeable once again that the concentrations of the genes that are characteristic of methanogenic microorganisms, do not reflect the actual production of methane in bioreactors. In conclusion, while evaluating the effectiveness of methane fermentation, it is important to supplement the analysis of the process parameters with an additional analysis using molecular methods. Furthermore, the dominance of the SS digestate samples by the MST genes, and the CS digestate samples by MSC genes can be seen on the heatmap, as reflected also in Figure 2C-F. Considering the above, perhaps _Methanosataceae_ dominant in SS is more sensitive to MET, while _Methanosarcinaceae_ dominant in CS is more susceptible to inhibition by exposure to AMO. These assays of the number of copies of the _MSC_ and _MST_ genes in CS and SS digestate samples revealed the biodiversity of microorganisms between the analyzed substrates. Sewage sludge which has trace quantities of drugs and products of their metabolism also contains microorganisms adapted somewhat to the present concentrations of drugs, which may explain differences in the number of gene copies between the SS and CS digestate samples.