Rapid discrimination of glycogen particles originated from different eukaryotic organisms.

There are many commercially available glycogen particles in the market due to their bioactive functions as food additive, drug carrier and natural moisturizer, etc. It would be beneficial to rapidly determine the origins of commercially-available glycogen particles, which could facilitate the establishment of quality control methodology for glycogen-containing products. With its non-destructive, label-free and low-cost features, surface enhanced Raman spectroscopy (SERS) is an attractive technique with high potential to discriminate chemical compounds in a rapid mode. In this study, we applied the combination of SERS technique and machine leaning algorithms on glycogen analysis, which successfully predicted the origins of glycogen particles from a variety of organisms with convolutional neural network (CNN) algorithm plus attention mechanism having the best computational performance (5-fold cross validation accuracy = 96.97 %). In sum, this is the first study focusing on the discrimination of commercial glycogen particles originated from different organisms, which holds the application potential in quality control of glycogen-containing products.

A Non-Degradative Extraction Method for Molecular Structure Characterization of Bacterial Glycogen Particles.

Currently, there exist a variety of glycogen extraction methods, which either damage glycogen spatial structure or only partially extract glycogen, leading to the biased characterization of glycogen fine molecular structure. To understand the dynamic changes of glycogen structures and the versatile functions of glycogen particles in bacteria, it is essential to isolate glycogen with minimal degradation. In this study, a mild glycogen isolation method is demonstrated by using cold-water (CW) precipitation via sugar density gradient ultra-centrifugation (SDGU-CW). The traditional trichloroacetic acid (TCA) method and potassium hydroxide (KOH) method were also performed for comparison. A commonly used lab strain, Escherichia coli BL21(DE3), was used as a model organism in this study for demonstration purposes. After extracting glycogen particles using different methods, their structures were analyzed and compared through size exclusion chromatography (SEC) for particle size distribution and fluorophore-assisted capillary electrophoresis (FACE) for linear chain length distributions. The analysis confirmed that glycogen extracted via SDGU-CW had minimal degradation.