NMR spectroscopic studies of chitin oligomers - Resolution of individual residues and characterization of minor amide cis conformations.

Chitin is the second most abundant biopolymer in nature after cellulose and is composed of N-acetylglucosamine (GlcNAc) connected via β(1 → 4)-glycosidic bonds. Despite its prominence in nature and diverse roles in pharmaceutical and food technological applications, there is still a need to develop methods to study structure and function of chitin and its corresponding oligomers. Efforts have been made to analyse chitin oligomers by NMR spectroscopy, but spectral overlap has prevented any differentiation between the interior residues.

Impact of mutations in starch synthesis genes on morphological, compositional, molecular structure, and functional properties of potato starch.

Morphology, composition and molecular structure of starch directly affect the functional properties. This study investigated the morphological, compositional, and molecular structure properties of starch from starch branching enzyme gene (SBE) and granule-bound starch synthase gene (GBSS) mutated potato, and their associations with thermal, pasting, and film-making properties. SBE mutations were induced in native variety Desiree while GBSS mutations were herestacked to a selected SBE mutated parental line.

H, C and N backbone resonance assignment of Cel45A from Phanerochaete chrysosporium.

A glycoside hydrolase family 45 (GH45) enzyme from the white-rot basidiomycete fungus Phanerochaete chrysosporium (PcCel45A) was expressed in Pichia pastoris with C and N labelling. A nearly complete assignment of H, C and N backbone resonances was obtained, as well as the secondary structure prediction based on the assigned chemical shifts using the TALOS-N software. The predicted secondary structure was almost identical to previously published crystal structures of the same enzyme, except for differences in the termini of the sequence.

Extended automated quantification algorithm (AQuA) for targeted H NMR metabolomics of highly complex samples: application to plant root exudates.

Introduction: The Automated Quantification Algorithm (AQuA) is a rapid and efficient method for targeted NMR-based metabolomics, currently optimised for blood plasma. AQuA quantifies metabolites from 1D-H NMR spectra based on the height of only one signal per metabolite, which minimises the computational time and workload of the method without compromising the quantification accuracy.

Objectives: To develop a fast and computationally efficient extension of AQuA for quantification of selected metabolites in highly complex samples, with minimal prior sample preparation.