Personal tools
You are here: The Britz-McKibbin Laboratory > Publications > Integrative metabolomics for characterizing unknown low-abundance metabolites by capillary electrophoresis-mass spectrometry with computer simulations.

Richard Lee, Adam S Ptolemy, Liliana Niewczas, and Philip Britz-McKibbin (2007)

Integrative metabolomics for characterizing unknown low-abundance metabolites by capillary electrophoresis-mass spectrometry with computer simulations.

Anal Chem, 79(2):403-15.

Characterization of unknown low-abundance metabolites in biological samples is one the most significant challenges in metabolomic research. In this report, an integrative strategy based on capillary electrophoresis-electrospray ionization-ion trap mass spectrometry (CE-ESI-ITMS) with computer simulations isexamined as a multiplexed approach for studying the selective nutrient uptake behavior of E. coli within a complex broth medium. On-line sample preconcentration with desalting by CE-ESI-ITMS was performed directly without off-line sample pretreatment in order to improve detector sensitivity over 50-fold for cationic metabolites with nanomolar detection limits. The migration behavior of charged metabolites were also modeled in CE as a qualitative tool tosupport MS characterization based on two fundamental analyte physicochemical properties, namely, absolute mobility (muo) and acid dissociation constant (pKa). Computer simulations using Simul 5.0 were used to better understand the dynamicsof analyte electromigration, as well as aiding de novo identification of unknownnutrients. There was excellent agreement between computer-simulated and experimental electropherograms for several classes of cationic metabolites as reflected by their relative migration times with an average error of <2.0%. Our studies revealed differential uptake of specific amino acids and nucleoside nutrients associated with distinct stages of bacterial growth. Herein, we demonstrate that CE can serve as an effective preconcentrator, desalter, and separator prior to ESI-MS, while providing additional qualitative information for unambiguous identification among isobaric and isomeric metabolites. The proposedstrategy is particularly relevant for characterizing unknown yet biologically relevant metabolites that are not readily synthesized or commercially available.

automatic medline import
 

Document Actions