The complete assignment of the proton chemical shifts obtained by nuclear magnetic resonance (NMR) spectroscopy of de-O-acetylated glucuronoxylomannans (GXMs) from Cryptococcus neoformanspermitted the high-resolution determination of the total structure of any GXM. Six structural motifs based on an α-(1→3)-mannotriose substituted with variable quantities of 2-O-β- and 4-O-β-xylopyranosyl and 2-O-β-glucopyranosyluronic acid were identified. The chemical shifts of only the anomeric protons of the mannosyl residues served as structure reporter groups (SRG) for the identification and quantitation of the six triads present in any GXM. The assigned protons for the mannosyl residues resonated at clearly distinguishable positions in the spectrum and supplied all the information essential for the assignment of the complete GXM structure. This technique for assigning structure is referred to as the SRG concept. The SRG concept was used to analyze the distribution of the six mannosyl triads of GXMs obtained from 106 isolates of C. neoformans. The six mannosyl triads occurred singularly or in combination with one or more of the other triads. The identification and quantitation of the SRG were simplified by using a computer-simulated artificial neural network (ANN) to automatically analyze the SRG region of the one-dimensional proton NMR spectra. The occurrence and relative distribution of the six mannosyl triads were used to chemotype C. neoformans on the basis of subtle variations in GXM structure determined by analysis of the SRG region of the proton NMR spectrum by the ANN. The data for the distribution of the six SRGs from GXMs of 106 isolates of C. neoformansyielded eight chemotypes, Chem1 through Chem8.
Published in Clinical and Vaccine Immunology, Volume 5, Issue 2, 1998, pages 146-159.
Copyright American Society for Microbiology, 1998.
Cherniak R, Valafar H, et al., (1998). Cryptococcus neoformans chemotyping by quantitative analysis of H-1 nuclear magnetic resonance spectra of glucuronoxylomannans with a computer-simulated artificial neural network. Clinical and Vaccine Immunology, 5(2): 146-159.