( Purpose In this ...)Strategies to Identify and Confirm Phase I Metabolites of Glyburide Using the 4000 Q TRAP System

Purpose

In this application note, several different metabolite identification approaches are evaluated for their merits. A comprehensive examination of four Information Dependent Acquisition (IDA) survey modes was performed to illustrate data quality and types of metabolites found. A significant number of metabolites were found with each mode of operation to create a thorough investigation of the metabolites derived from glyburide.

Overview

A common strategy for metabolite analysis consists of using two mass spectrometry (MS) systemsa triple quadrupole MS system to identify metabolites, and a separate ion trap MS system to characterize the metabolites. The sample is split and run on the separate instruments in a sequential manner with the metabolite identification information from the triple quadrupole used to drive the characterization analysis on the 3D ion trap. Alternatively, methods have been proposed that split the HPLC flow into the two separate MS systems in an effort to get the information at the same time. Either way, the two separate systems approaches are not ideal. Triple quadrupole scan modes such as precursor ion and neutral loss provide a very selective method for the identification of structurally similar metabolites even in the presence of major background contaminants from complex biological matrices. With these selective scan modes, conventional triple quadrupoles can effectively identify metabolite candidates for further characterization analysis. Unfortunately, due to their inherent poor MS/MS full scan sensitivity, triple quadrupoles are not ideal tools to acquire MS/MS characterization data on critical low-level metabolites.

Also 3D ion trap systems alone cannot provide complete metabolite investigation. In this single-system approach, a single MS survey scan is commonly followed by a dependent MS/MS scan for structural characterization. Unfortunately, there are serious drawbacks to this mode of operation. They include poor selectivity due to the wide number of extraneous background ions that generate a lot of unnecessary data; poor and incomplete fragmentation related to limited fragmentation pathways; and missing low mass ion data due to the low mass cut-off experienced in 3D ion traps.

With the advent of the hybrid triple quadrupole-linear ion trap (LIT) instrumentation, both triple quadrupole and ion trap scans can now be performed on the same instrument in a single experiment. In our studies, we used a 4000 Q TRAP System, a hybrid triple quadrupole-linear ion trap mass spectrometer with superior MS and MS/MS full scan sensitivity and no low mass cut-off, to provide a broad range of informative fragment ions. Furthermore, the coupling of highly selective precursor and neutral loss scans with an efficient linear ion trap MS/MS experiment allows for a significant improvement in metabolite identification over traditional 3D and non-hybrid linear ion traps. In a separate approach, a Multiple Reaction Monitoring (MRM) experiment with 50 theoretical metabolites was used as an ultra-high sensitivity survey scan to generate MS/MS data. A comparison of these different modes of operation was performed to demonstrate the unique features of each IDA combination for exploring the complete metabolism of the glyburide molecule (Figure 1).

Key Features

Automated metabolite identification and confirmation allows you to rapidly identify, characterize and confirm Phase I and Phase II metabolites in a single LC/MS/MS run.

Unequalled triple quad and ion trap sensitivity enables you to identify more low abundance metabolites with a high degree of confidence.

LINAC collision cell permits monitoring of up to 100 MRM transitions in a single experiment.

Targeted MRM analysis significantly increases the number of identified and confirmed metabolites compared to traditional full scan MS analysis.

Eliminate erroneous metabolite identifications with high-sensitivity MS/MS and MS3 spectra to confirm the presence and structure of the metabolite.

Analyst software and Metabolite ID application software give you more useful information per sample.

Experimental Conditions

Researchers prepared microsomal incubations of glyburide using S9 derived P450 enzymes. Glyburide was incubated at 30 C for two hours at a final concentration of 20 μM. The reaction was quenched by addition of acetonitrile at a 2 to 1 volume ratio. The solution was dried under vacuum to complete dryness and samples were reconstituted in 20% acetronitrile/0.1% formic acid (FA) to the original volume. All LC/MS analysis was performed on a Keystone 1 x 150 mm C18 column running at 70 μL/min. Solvent A was water with 0.1% FA, solvent B was acetonitrile with 0.1% FA. A gradient of 5% B for three minutes ramped to 70% B over 40 minutes was utilized. A wash and equilibration of five minutes each were used to prepare the column for the subsequent run. A CTC PAL autosampler (LEAP Technologies) with 10 μL loop was coupled to a Shimadzu 10 ADvp binary pump. An Applied Biosystems/MDS SCIEX 4000 Q TRAP System was used for all experiments. Enhanced MS (EMS), a single MS linear ion trap scan, neutral loss, MRM, and precursor ion scans were used as IDA survey scans. Dynamic Fill Time (DFT) was used for trap scans to ensure optimal ion trap fill times. All tune values were derived from a standard. Time zero quenched controls were performed in all modes to eliminate matrix and sample background signals. An IDAbased linear ion trap enhanced resolution scan was also used to confirm isotope pattern and obtain mass assignment along with dependent MS/MS linear ion trap experiments. 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 of 125 survey scan, corresponding to the right ring loss, provides clear detection of five different metabolites. Two of these, m/z 476 and 414, were totally unique to this mode of detection. Figure 4 shows the enhanced resolution and product ion spectra that provided excellent confirmation and assignment of these unique species. The targeted MRM IDA experiment delivered the best possible detection limit due to the excellent duty cycle. Figure 5 contains data for one of the oxidation species detected in this experiment along with its corresponding MS/MS. The 50 MRM transitions used in this mode were predicted with the MRM Method Builder in Analyst software. A number of the truly lowlevel di-oxidations and other species (Table 1) were found using this mode. The total metabolites detected using MRM-directed IDA were ten. As with the other approaches, product ion spectra provided characterization and confirmation of the metabolites. This step is critical in eliminating erroneous results based on chance. With its excellent sensitivity and selectivity, this approach is best suited for Phase I and II metabolite screening where the lists of expected metabolites are easily compiled.

Conclusions

With the advent of the hybrid triple quadrupole-linear ion trap (LIT) instrumentation, both triple quadrupole and ion trap scans functions can be performed on the same system to identify, confirm, and fully characterize low abundance metabolites in a single experiment. The LIT system setup fragments ions in a LINAC triple quadrupole collision cell, resulting in a diverse set of informative fragment ions that allows full metabolite characterization. Furthermore, traditional 3D and nonhybrid linear ion traps limitations, such as the loss of informative low mass ions, are eliminated.

The superior sensitivity of 4000 Q TRAP System provides ultralow- level detection of metabolites. This sensitivity, combined with the variety of scan modes (precursor, neutral loss, and MRM), facilitates metabolite identification capabilities. The precursor and neutral loss scans allow for determination of both trace level expected and unexpected metabolites from a complex matrix. Enhanced MS provides information on expected and unexpected metabolites that are present at relatively high levels. MRM provides the best detection limits for expected metabolites and is best suited for fast screening. Table 1 shows the large number of unique metabolites found by the various scan modes available on the 4000 Q TRAP System. In combination, these approaches provide a more comprehensive view of the metabolites of glyburide.