New 1D and 2D NMR approaches for studying known and unknown complex metabolomics mixtures

New 1D and 2D NMR Approaches for Quantitative Studies of Known and Unknown Complex Metabolite Mixtures

Rafael Brüschweiler

Department of Chemistry & Biochemistry and Department of Biological Chemistry & Pharmacology, The Ohio State University, Columbus, Ohio 43210, USA

The characterization of complex chemical mixtures by NMR encountered in metabolomics poses a wide range of opportunities and challenges in terms of metabolite coverage, identification accuracy, reproducibility, quantitation, speed, and automation. I will discuss new approaches toward these goals that include NOAH supersequences, machine-learning methods for automated spectral processing and analysis, new metabolite data bases, a new chemical shift predictor for resonance assignment and the characterization of unknown metabolites. These methods will be demonstrated for periprosthetic joint infection studies caused by opportunistic pathogens such as Pseudomonas aeruginosa and Staphylococcus aureus that tend to form biofilms with high antibiotic resistance.