The demand for functional food ingredients like β-glucan
has risen enormously in recent times owing to its use in many fields
including the food and beverage, cosmetics, pharmaceuticals, and biotechnology
industries. Among the many natural sources of glucans such as oats,
barley, mushrooms, and seaweeds, yeast has a special advantage in
the industrial production of glucans. However, characterizing glucans
is not straightforward as there are many different structural variations
such as α- or β-glucans with various configurations which
vary in their physical and chemical properties. Currently, microscopy,
chemical or genetic approaches are followed to study glucan synthesis
and accumulation in single yeast cells. However, they are time-consuming,
lack molecular specificity, or are practically not feasible for real
applications. Therefore, we developed a Raman microspectroscopy based
method to identify, distinguish, and visualize structurally similar
glucan polysaccharides. By employing multivariate curve resolution
analysis, we successfully separated Raman spectra of α- and
β-glucans from mixtures with high specificity and visualized
heterogeneous molecular distributions during the sporulation of yeasts
at the single-cell level in a label-free manner. We believe such an
approach when combined with a flow cell can achieve the sorting of
yeast cells based on the accumulation of glucans for various applications.
Further, such an approach can also be extended to various other biological
systems to investigate structurally similar carbohydrate polymers
in a fast and reliable manner.