Abstract
A CE-MS method was developed and validated for the quantitative analysis of negatively charged metabolites by making use of the high mass accuracy and the quantitation capabilities of a TOF mass analyzer in combination with automated feature extraction and database search. Metabolites of the central carbon metabolism were quantified with an LOD and lower LOQ (LLOQ) of 0.2-2 and 1-4 mu M, ...
Abstract
A CE-MS method was developed and validated for the quantitative analysis of negatively charged metabolites by making use of the high mass accuracy and the quantitation capabilities of a TOF mass analyzer in combination with automated feature extraction and database search. Metabolites of the central carbon metabolism were quantified with an LOD and lower LOQ (LLOQ) of 0.2-2 and 1-4 mu M, respectively. The method was used to elucidate metabolic changes in the Escherichia coli deletion mutant PntAB-UdhA that lacks nicotinamide nucleotide transhydrogenase function, under both stationary and exponential growth conditions. The reproducibility of metabolite extraction and CE-TOF-MS analysis ranged from 3.7 to 22.7 and 7.9 to 22.6%, respectively, while the biological variance was 3.4-31.3%. We observed significant differences in metabolite abundance, particularly in the citrate cycle, between wild-type and mutant E. coli. Overall, more than 600 features were found by automated feature detection, which resulted in similar to 150 high-confidence metabolite identifications. Concomitant analyses with two different GC-MS methods allowed not only crossvalidation of the quantitative results obtained by the various methods, but also led to a more comprehensive coverage of the E. coli metabolome.
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