Direct Visualization of Structurally Similar Polysaccharides in Single Yeast Cells in Vivo by Multivariate Analysis Assisted Raman Microspectroscopy

Abstract

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.

Discernable machine learning methods for Raman micro‐spectroscopic stratification of mitoxantrone‐induced drug‐resistant cells in acute myeloid leukemia

“…It has been largely explored in disease diagnosis as it offers several advantages such as being a real-time, objective, and minimally invasive technique. RS has also been employed successfully to study single cells [6][7][8] and for the detection of several cancers like leukemia, 9 breast, 10 colorectal, 11 head and neck cancer, 12,13 cervix, nasopharyngeal, and glioblastoma. 6,14 Furthermore, it finds applications in biomedical sciences, forensic sciences, therapeutic monitoring, and investigating chemo or radiation resistance.…”