## 3 Results
### Bacterial Abundance Results  
The previously created OTU tables were used to create a potential metabolomics profiling with the iVikodak workflow [29]. Although this type of inference should be performed from the metatranscriptomics datasets, they can give us insights into their potential roles in specific KEGG pathways. According to species abundance level, we can assume the influence of metabolites produced by the bacteria and their impact on the cellular mechanisms. The most abundant genus has been found to be the _Faecalibacterium_ genus which could influence the development and support CRC development. This genus is less abundant in the non-resistant microbiome samples, and the concentration increases in resistant samples. Furthermore, the correlation between _Faecalibacterium_ and CRC is enhanced with the evidence of the highest abundance of this genus in the not-treated CRC microbiome samples. The bacterial abundance is shown in Figure 5. \begin{table}
\begin{tabular}{c c} \hline \hline
**Aggregated Bacteria** & **“Not Resistance’ Contribution** \\ \hline _[’Weissella’_, _’Eisenbergiella’_, _’[Eubacterium] ruminantitium group’_, _’Denitrobacterium’_ & 0.006 \\ _[’Escherichia-Shigella’_, _’Lachmogiraceae_ _UCG-010’_, _'Family XIII UCG-001’_]_ & 0.00568889 \\ _[’Entreococcus’_, _'Lachmogiraceae_ _NC2004 group’_, _'Lachmogiraceae_ _NC2004 group’_, _’Lachmogiraceae_ _NC2004 group’_ & 0.00533109 \\ _[’Runinococcus’_, _’[Eubacterium] elegans group’_, _’Coproacillus’_]_ & 0.004474074 \\ _[’Streprococcus’_, _’Phascaloricbacterium’_, _’Paraprevoltella’_]_ & 0.0043956 \\ _[’Phascaloricbacterium’_, _’Eisenbergiella’_, _’Olsenella’_]_ & 0.00394872 \\ _[’Escherichia-Shigella’_, _’Negativibacillus’_]_ & 0.00385632 \\ _[’Weissella’_, _’Eubacterium] ruminantium group’_, _’Dentirobacterium’_ & 0.00378355 \\ _[’Phascaloricbacterium’_, _’Eisenbergiella’_, _’Parasutterella’_, _’Olsenella’_]_ & 0.00334066 \\ _[’Bacteroides’_, _'Megasphera’_, _’Coproacillus’_]_ & 0.00314286 \\ _[’Eubacterium] ruminantium group’_, _’Slackia’_, _’Eubacterium’_ & 0.003 \\ _[’Clostridium sensu stride’_, _’Weissella’_, _’Slackia’_]_ & 0.00283414 \\ _[’Subdoligranulum’_, _’Ruminococcus’_, _’NKA214 group’_, _’Family XIII UCG-001’_]_ & 0.00242424 \\ _[’Clostridium sensu stride’_, _’Blautia’_, _’TM’x’_]_ & 0.00238235 \\ _[’Streprococcus’_, _’UICG-002’_, _'Negativibacillus’_]_ & 0.00227273 \\ _[’Ruminococcus’_, _’Turichieter’_, _’Leuconosloc’_]_ & 0.00226263 \\ _[’Phascaloricbacterium’_, _’Lachmogiraceae_ _NC2004 group’_, _'Barnesiella’_]_ & 0.00222222 \\ _[’Haemiophilus’_, _’Terrisprobacher’_, _’Weissella’_, _’Slackia’_]_ & 0.00215385 \\ _[’Alistye’_, _’Lachmogiraceae_ _NC2004 group’_]_ & 0.002 \\ _[’Eubacterium] ruminantium group’_, _’Parasutterella’_, _’Slackia’_, _’Eubacterium’_]_ & 0.0019222 \\ _[’Eubacterium] eligens group’_, _’Moryla’_]_ & 0.00189076 \\ _[’Eisenbergiella’_, _’Olsenella’_]_ & 0.00181319 \\ _[’Escherichia-Shigella’_, _’Subdoligranulum’_, _’Megasphera’_, _’Veillonella’_]_ & 0.00166667 \\ _[’Weissella’_, _’Slackia’_]_ & 0.00153515 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Aggregated bacteria significance contributions to the not resistant class. The second significant correlation was observed in correspondence to the _Bifidobacterium_ genus. The inflammatory effect of the _Bifidobacterium_ biofilm is supported by our results, as we observed the highest abundance in resistant samples. These cases are most prone to high immune response due to inflammations. Moreover, we observed a significant abundance of two beneficial genera, _Ruminococcus_ and _Bacteroides_. The first one, _Ruminococcus_, has the highest abundance in the non-resistant group and partially decreases its abundance in the resistant group. The bacterial abundance is shown on Figure 6.  
Figure 5: Bacterial abundance in CRC-prior treatment group. Figure 6: Bacterial abundance in the non-resistant group. The abundance frequency pattern is slightly different in correspondence to the _Bacteroides_.