significant Raman vibrational bands were identified as: esters at 1731 cm-1 (C=O, stretching), amide I at 1651 cm-1 (C=O, stretching), lipids and nucleic acids at 1484 cm-1 deformation), proteins at 1375 cm-1, tyrosine (ring breathing) and/or nucleic acids stretching) at 826 cm-1, and a combination cytosine and uracil at 782 cm-1 (C=O, C-N and ring deformations)., The HCA dendogram (Figure 5B) of the Raman PC-DFA scores also exhibited this clear separation. Validation of the PLS-DA classification models (Figure 6B), generated using Raman spectral data confirmed the accuracy and validity of the model (between 95.3 – 99.9%) with an average prediction accuracy of 97.8% (Table S2). SERS fingerprints Unlike Raman, SERS spectra of S. cerevisiae provided detailed features (Figure 3C) showing that the nanoparticles had caused an enhancement and had quenched fluorescence. By contrast, SERS spectra obtained from P. putida samples contained high background fluorescence, possibly due to the presence of an exopolysaccharide capsule surrounding the cell, and were therefore excluded from further analysis. PC-DFA scores plot of the SERS spectral data displayed clear separation of all samples (Figure 4E, F), the two Bacillus spp. were separated from all other samples based on DF1. Although S. cerevisiae are yeast cells with different biochemical composition compared to that of bacterial cells, and despite any prior assumptions, these samples clustered closely with S. lividans. It was clear that in comparison to FT-IR and Raman data (Figure 4) that the clustering of the biological replicates was not so tight and this suggests that these data have
significant Raman vibrational bands were identified as: esters at 1731 cm-1 (C=O, stretching), amide I at 1651 cm-1 (C=O, stretching), lipids and nucleic acids at 1484 cm-1 deformation), proteins at 1375 cm-1, tyrosine (ring breathing) and/or nucleic acids stretching) at 826 cm-1, and a combination cytosine and uracil at 782 cm-1 (C=O, C-N and ring deformations)., The HCA dendogram (Figure 5B) of the Raman PC-DFA scores also exhibited this clear separation. Validation of the PLS-DA classification models (Figure 6B), generated using Raman spectral data confirmed the accuracy and validity of the model (between 95.3 – 99.9%) with an average prediction accuracy of 97.8% (Table S2). SERS fingerprints Unlike Raman, SERS spectra of S. cerevisiae provided detailed features (Figure 3C) showing that the nanoparticles had caused an enhancement and had quenched fluorescence. By contrast, SERS spectra obtained from P. putida samples contained high background fluorescence, possibly due to the presence of an exopolysaccharide capsule surrounding the cell, and were therefore excluded from further analysis. PC-DFA scores plot of the SERS spectral data displayed clear separation of all samples (Figure 4E, F), the two Bacillus spp. were separated from all other samples based on DF1. Although S. cerevisiae are yeast cells with different biochemical composition compared to that of bacterial cells, and despite any prior assumptions, these samples clustered closely with S. lividans. It was clear that in comparison to FT-IR and Raman data (Figure 4) that the clustering of the biological replicates was not so tight and this suggests that these data have
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