SERS-Based Heavy Metal Sensing Protocol

Spectral data of lysate samples are acquired by placing a droplet with a volume of 25 µL of lysate from E. coli cells untreated (control) or exposed to heavy metal ion solutions at various concentrations on SERS surfaces. The measured concentration range for NaAsO₂ was 0.65 pg/L to 650 mg/L (13 concentrations) and for K₂Cr₂O₇ was 0.1 ng/L to 10 mg/L (nine concentrations) spaced by one order of magnitude as shown in Table 1. The corresponding concentrations in molarity of As³⁺ and Cr⁶⁺ are shown in Table 1.
For each exposure concentration, a dataset of 1,200 SERS spectra is acquired using a Renishaw InVia™ micro Raman system with an integration time of 0.5 s, 146 µW laser power at 785 nm excitation wavelength, and a 60× water immersion lens with 1.2 NA (beam diameter of 292 nm). Raman maps were acquired in an array of 20 × 20 with 3 µm steps between measurement points, resulting in 400 spectra per map. Three maps were acquired over different regions of the sample surface resulting in a total of 1,200 spectra per concentration for each metal ion defining a class for initial training of machine learning algorithms (61 (link)). The dataset acquisition takes 10 min, and the droplet does not evaporate during this period of time. In order to ensure that the algorithm is not being trained to detect batch-to-batch variations of SERS surfaces, concentration classes between two and six, including control samples, were acquired on different regions of the same SERS surface (droplets exposed to isolated regions), indicated by superscripts in Table 1. Furthermore, the control group, prepared under the same conditions in the absence of Cr⁶⁺ or As³⁺ exposure, was measured from lysate samples prepared in biological duplicates on different days, from the eight different SERS surfaces, also fabricated on different days, used for the other metal concentrations exposure conditions to train algorithms to not identify differences based on normal variability of experimental conditions such as culture growth, device fabrication, and processing steps.