## 3 Results and Discussion
Figure 3b displays, as a representative example, the mean Raman spectra of one subset of each data set (all mean and standard deviation spectra are shown in Figure S2 of the Supporting Information), where each set of data consists of 49 to 138 single spectra per sample type, measured with an acquisition time of 60 s. The spectra of the different sample types (SARS-CoV-2, Influenza A virus, negative control) are virtually undistinguishable. The subtracted spectra in Figures 3b and S2) expose even more clearly the absence of significant differences in the average spectra of the investigated sample types. The variations observed at \(\sim\) 1001, 1345 and 1602 cm\({}^{-1}\) are all approximately within the standard deviation, making any deeper analysis of the spectral differences based on those data highly arbitrary. It needs to be pointed out that, even when these spectral changes were significant, one still needs to interpret these results with great caution as many bands occur for almost all proteins and are not necessarily characteristic for the SARS-CoV-2 proteins. The Raman signal for all sample types is mainly dominated by the magnetic bead substrate (see Figure S3 of the supporting information, where a reference spectrum acquired from the non-functionalized streptavidin magnetic beads can be found, along with a spectrum of the ACE2). The beads themselves consist of a polystyrene-divinylbenzene (PS-DVB) matrix [41] with magnetite [42] and magnetite as magnetic material and are functionalized with streptavidin and the ACE2, which are both proteins. We originally hypothesized that differentiating between the SARS-CoV-2 and Influenza samples would be enabled by an enhanced protein signature in the Raman spectra of the beads incubated with the SARS-CoV-2 particles. However, the qRT-PCR results (Table S1) indicate that, to some minor extent, Influenza A viruses also unspecifically adsorb onto the surface of the ACE2 functionalized beads. It is noteworthy that the differences between the SARS-CoV-2 and Influenza A virus with the negative control are not more pronounced, illustrating that the protein contribution to the signal must be minor, if at all detectable. This is likely due to the small amount of virus attached to the beads in combination with the low sensitivity of the Raman signal. Increasing the acquisition time or the power at the sample for signal optimization (or noise reduction) unfortunately leads to observable damage, most likely due to the absorption of the 808 nm wavelength by the beads (data not shown). Our attempts to use 532 nm, and even 785 nm, incident wavelengths (to have access to a higher signal-to-noise ratio) have failed due to the strong fluorescence background arising from the magnetic beads. An alternative way for detecting SARS-CoV-2 using our proposed sample preparation scheme is to detach the isolated virus particles from the magnetic beads before performing the Raman measurements. Thereby, the influence of the magnetic bead material and the protein modification (streptavidin and ACE2 receptor) can be minimized, and the spectra will be dominated by the contributions of the virus particles themselves. In contrast to our proposed method, this could enable identifying the virus particles according to their characteristic Raman signature. However, this approach requires additional working steps, and it needs to be ensured that enough viruses are retrieved for a Raman spectrum to be recorded. In cases of a highly purified sample, detailed information on the protein structure can be obtained and allows for discrimination between SARS-CoV-2 strains, as was demonstrated by [PERSON] et al. [43]. Correlation coefficients enable quantifying similarities/dissimilarities between data sets. The Pearson coefficient, for example, is a measure for linear correlation. It can attain values between \(-1\) and \(+1\).