PARAFAC modeling of three-way hyperspectral images: Endogenous fluorophores as health biomarkers in aquatic species

Abstract

Demand for a renewable liquid-phase fuel has reinvigorated interest in the development of novel biofuels from algae. The effects of fluctuating nutrients, temperature, and predation which arise in algal aquaculture necessitate novel analytical methods to assess and optimize the health of these cultures. In this article we describe the use of trilinear modeling to these ends, using imaging data of endogenous fluorescence from the marine diatom, Thalassiosira pseudonana, collected on a hyperspectral fluorescence confocal microscope (HSF-CM). By combining the spatial and spectral data with the additional physical parameter introduced by the varying photobleach rates of endogenous fluorophores, we obtain a means for employing trilinear analysis in this system. In this case, analysis was implemented using the method of parallel factors analysis (PARAFAC) which alleviates the rotational ambiguities involved in multivariate analysis of 2-way data. By imposing a nutrient limitation in our diatom culture, and collecting single cell microscopy data at various time points during the nutritional stress, PARAFAC results reveal evolution of the spectral emission characteristics of six components and a background as a result of incremental photobleaching. Although the underlying mechanisms for these observations are not addressed, the differences observed between nutritively normal and nutritively stressed cells provide signatures for early detection of health deterioration in the algal culture. Finally, the combination of hyperspectral fluorescence microscopy with PARAFAC is generally applicable for the study of complex biological systems with endogenous fluorescence.