Characterisation of chemical damage on tissue structures by multispectral imaging and machine learning procedures: Alkaline hypochlorite effect in C. elegans

Abstract

[EN] Multispectral imaging represents a powerful technique to maximise data collection and analysis for biological materials. It improves the exploitation and understanding of in vivo/vitro experiments. This work focused on testing the capability of multispectral imaging to characterise the tissue damage produced by alkaline hypochlorite on the body and eggs of the biological model C. elegans. To that end, three synchronisation processes with different final bleach and sodium hydroxide concentrations were performed. The impact of treatments was characterised by measuring egg viability and morphology, besides capturing multispectral images of both nematode bodies and eggs. Multispectral images consisted of seven slices captured from different wavelengths within the visible/infrared spectrum by different light-pass filters. The results showed dependence between increased alkaline hypochlorite concentration and loss of egg viability/morphology. This relation was also observed for the imaging data, which showed alterations to tissue transmittance for all the tested wavelengths for both bodies and eggs. Localised alterations related to alkaline hypochlorite diffusion through anatomical nematode orifices were recognised. Applying multivariate methods to imaging data successfully characterised tissue alterations, from which treatment type was predicted for both nematodes and eggs. Moreover, the alterations recorded by imaging data were also used to predict egg viability regardless of treatment type (0.94). The high correlation between the imaging data from nematodes and eggs with egg viability evidenced multispectral imaging's ability to characterise tissue damage and its possible practical application to study alterations to the tissues of this biological model.