In the field of toxicological bioassays, the latest progress in Raman spectroscopy opens new research perspectives on a fast method of observing metabolic responses against toxic agents. This technique offers a multiparametric approach, providing an overview of the physiological changes that are caused by pollutants. However, physiological spectral fingerprints require complex chemometric methods for proper analysis. In this study, particular attention has been given to the elaboration of an "aberrant spectra" detection strategy to highlight the effects of arsenic on the bacteria Escherichia coli. This strategy significantly improved spectra classification, consistent with a dose-response effect of the four tested concentrations of the metal. Indeed, the correct classification score of the spectra increased from 88 to more than 99%. The exposure time effect has also been investigated. The fine analysis of Raman spectroscopy fingerprints enabled the design of different "spectral signatures", highlighting early and late effects of arsenic on bacteria. The observed variations are in agreement with the expected toxicity and encourage the use of Raman spectroscopy for toxic element detection.

Water quality monitoring requires a rapid and sensitive method that can detect multiple hazardous pollutants at trace levels. This study aims to develop a new generation of biosensors using a low-cost fiber-optic Raman device. An automatic measurement system was thus conceived, built and successfully tested with toxic substances of three different types: antibiotics, heavy metals and herbicides. Raman spectroscopy provides a multiparametric view of metabolic responses of biological organisms to these toxic agents through their spectral fingerprints. Spectral analysis identified the most susceptible macromolecules in an E. coli model strain, providing a way to determine specific toxic effects in microorganisms. The automation of Raman analysis reduces the number of spectra required per sample and the measurement time: for four samples, time was cut from 3 h to 35 min by using a multi-well sample holder without intervention from an operator. The correct classifications were, respectively, 99%, 82% and 93% for the different concentrations of norfloxacin, while the results were 85%, 93% and 81% for copper and 92%, 90% and 96% for 3,5-dichlorophenol at the three tested concentrations. The work initiated here advances the technology needed to use Raman spectroscopy coupled with bioassays so that together, they can advance field toxicological testing.

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