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ments. Data processing was done using Metabolite ID application software for sample and control comparison as well as fragment comparison.
Results and Discussion
A variety of survey scan modes, all available on the 4000 Q TRAP System, identified a number of unique metabolites. Once identified as a potential metabolite, both the product ion spectrum and the isotope pattern were used to characterize and confirm the metabolites presence.
The ion trap single MS data shown in Figure 2 provided an excellent survey scan for the detection of eight high-level metabolites (Table 1). Unfortunately, the low abundance metabolites are missed due to high background encountered in single MS. To alleviate part of this problem, an inclusion list of expected metabolites can be included in the IDA method. The inclusion list approach however, will not identify low-level unexpected metabolites or compound rearrangements. Even though the full scan ion trap MS survey scan approach is not highly specific, this method is an excellent screen for abundant metabolites. In order to identify and characterize low abundance metabolites, a more selective approach is required. On the 4000 Q TRAP System, using a precursor ion scan of 169, the dominant low mass fragment for the chlorinated ring portion of the molecule allowed for determination of ten metabolites (Table 1). These metabolites are, of course, only species in which no change was made to the chlorinated ring. Three low-level di-oxidation species and two interesting ring loss N-dealkylations were found by performing this scan.
Due to the selectivity of the precursor ion survey scan, the IDA software program was easily able to identify metabolites of interest and generate excellent quality MS/MS characterization data. Figure 3 shows an example of the 412 ring loss metabolite data acquired using the precursor ion scan. The neutral loss
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