Identification and Design of Synthetic B Cell Epitopes for Carbohydrate-Based Vaccines

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates

Organic synthesis methodology enables the synthesis of complex molecules and materials used in all fields of science and technology and represents a vast body of accumulated knowledge optimally suited for deep learning. While most organic reactions involve distinct functional groups and can readily be learned by deep learning models and chemists alike, regio- and stereoselective transformations are more challenging because their outcome also depends on functional group surroundings. Here, we challenge the Molecular Transformer model to predict reactions on carbohydrates where regio- and stereoselectivity are notoriously difficult to predict. We show that transfer learning of the general patent reaction model with a small set of carbohydrate reactions produces a specialized model returning predictions for carbohydrate reactions with remarkable accuracy. We validate these predictions experimentally with the synthesis of a lipid-linked oligosaccharide involving regioselective protections and stereoselective glycosylations. The transfer learning approach should be applicable to any reaction class of interest.

Evaluation of Biomass and Chitin Production of Morchella Mushrooms Grown on Starch-Based Substrates

Morchella sp. is one of the most expensive mushrooms with a high nutritional profile. In this study, the polysaccharide content of Morchella species was investigated. Specifically, mycelium growth rate, biomass production, sclerotia formation, and glucosamine and total polysaccharides content of six Morchella species grown on a starch-based media were evaluated. Submerged fermentations in potato dextrose broth resulted in a glucosamine content of around 3.0%. In solid-state fermentations (SSF), using potato dextrose agar, a high linear growth rate (20.6 mm/day) was determined. Increased glucosamine and total polysaccharides content were observed after the formation of sclerotia. Biomass and glucosamine content were correlated, and the equations were used for the indirect estimation of biomass in SSF with agro-industrial starch-based materials. Wheat grains (WG), potato peels (PP), and a mixture of 1:1 of them (WG-PP) were evaluated as substrates. Results showed that the highest growth rate of 9.05 mm/day was determined on WG and the maximum biomass yield (407 mg/g) on WG-PP. The total polysaccharide content reached up to 18.4% of dried biomass in WG-PP. The results of the present study proved encouraging for the efficient bioconversion of potato and other starch-based agro-industrial waste streams to morel biomass and sclerotia eliciting nutritional and bioactive value.