## 2 Results and Discussion
### Unsupervised Inspection of Bacterial VOC Profiles  
The distribution of profiles and correlation between bacterial species were inferred by using principal component analysis (PCA). Considering solely the VOC profiles emitted by unstressed cultures (Figure 2a), the patterns of replicates belonging to the same species tend to be grouped together, indicating that VOC patterns are characteristic for each examined species. In addition, the set of volatile metabolites produced by _E. coli_ and _E. faecalis_ displayed more related patterns, while variances of _K. pneumoniae_ and _P. mirabilis_ were  
Figure 1: Phyloproteomic tree of the isolated bacterial strains, identified by MALDI Biotyper Compass platform.  
negatively correlated to the aforementioned species. When considering also VOC profiles from headspace of cultures supplemented with bio-AgNPs (Figure 2b), these appeared to be clustered according with the applied concentration of nanoparticles. This observation suggests that different levels of bio-AgNPs may induce metabolic shifts common among the studied species. Besides that, the patterns of variance in detected volatiles appeared to be more similar for the concentrations 25 and 50 \(\upmu\)g mL\({}^{-1}\), indicating the preservation of a similar basic metabolism at greater levels of the agent.  
At this step, a preliminary inspection of the data's general trend was aimed at observing if differentiation between species could be obtained spontaneously, considering the acquired global VOC profiles. In both cases, the first two principal components were able to describe only around 34% of the total variance observed within the data. This is possibly due to the fact that the studied bacteria share most of their VOC composition. This common fraction of the composition can be ascribed as belonging to bacterial fundamental metabolism at the given conditions. Such an explanation can be extended to the samples after bio-AgNPs treatment. In this sense, only a smaller portion of these profiles appear to be responsible for such simultaneous discriminations observed in the score plots.  
Hierarchical cluster analysis (HCA; Figure 3) displays average VOC profiles obtained for each assay ordered according to their similarity. Such approaches reinforce that profile composition tends to be governed by the added concentration of nanoparticles. With basis on the dendrograms presented at the top of the heatmap, the performed experiments can be divided into two main groups: unstressed cultures together with those supplemented with the lower concentration of bio-AgNPs (12.5 \(\upmu\)g mL\({}^{-1}\)--C1) and the cultures treated with greater concentrations of the agent (25 and 50 \(\upmu\)g mL\({}^{-1}\)--C2 and C3, respectively). These groups can be discriminated due to the differential response of compounds organized in the clusters A to E. The compounds contained in the cluster A, which are mostly hydrocarbons, presented increased responses in assays using greater concentrations of nanoparticles (C2 and C3). However, for clusters B, C, D and E, the opposite trend is observed.  
Figure 2: PCA score plots performed by using data regarding profiles obtained from (**a**) solely untreated cultures and (**b**) average of all performed assays (untreated + bio-AgNPs-treated cultures). C0 = assay without the addition of bio-AgNPs; C1, C2 and C3 = supplementation with bio-AgNPs at 12.5, 25 and 50 \(\upmu\)g mL\({}^{-1}\), respectively. EC = _E. coli_, EF = _E. faecalis_, KP = _K. pneumoniae_, PM = _P. mirabilis_.