title: Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering.
abstract: Identification and quantification of analytes in complex solution-state mixtures are critical procedures in many areas of chemistry, biology, and molecular medicine. Nuclear magnetic resonance (NMR) is a unique tool for this purpose providing a wealth of atomic-detail information without requiring extensive fractionation of the samples. We present three new multidimensional-NMR based approaches that are geared toward the analysis of mixtures with high complexity at natural (13)C abundance, including approaches that are encountered in metabolomics. Common to all three approaches is the concept of the extraction of one-dimensional (1D) consensus spectral traces or 2D consensus planes followed by clustering, which significantly improves the capability to identify mixture components that are affected by strong spectral overlap. The methods are demonstrated for covariance (1)H-(1)H TOCSY and (13)C-(1)H HSQC-TOCSY spectra and triple-rank correlation spectra constructed from pairs of (13)C-(1)H HSQC and (13)C-(1)H HSQC-TOCSY spectra. All methods are first demonstrated for an eight-compound metabolite model mixture before being applied to an extract from E. coli cell lysate.
authors.affiliation: Institute of Molecular Biophysics, Department of Chemistry & Biochemistry and National High Magnetic Field Laboratory, Florida State University, Tallahassee, Florida 32306, USA.
authors.forename: Kerem
authors.initials: K
authors.lastname: Bingol
authors.forename: Rafael
authors.initials: R
authors.lastname: Brüschweiler
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000032:analysis*; D003198:Computer Simulation; D004926:Escherichia coli / Q000737:chemistry / Q000166:cytology / Q000378:metabolism; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D009696:Nucleic Acids / Q000032:analysis*
chemical_list: D000596:Amino Acids; D009696:Nucleic Acids