With the commercial introduction of atmospheric pressure chemical ionization for gas chromatography in 2008, GC-APCI coupled to high-resolution time-of-flight mass spectrometry (GC-APCI-HRTOFMS) became an interesting addition to the metabolomics toolbox. APCI is a soft ionization technique and its application to hyphenate GC to high resolution MS opens up promising new means for the identification of unknown signals in complex matrices. The actual utility of GC-APCI-HRTOFMS in metabolic fingerprinting and profiling applications to biological matrices is the topic of this doctoral thesis.
During comparison of GC-APCI-HRTOFMS with GC×GC-EI-TOFMS, GC-EI-TOFMS, GC-CI-qMS, and GC-EI-qMS in my master thesis, it was noticed that reproducibility of APCI was affected greatly by differences in humidity in the laboratory. Therefore, the impact of humidity in the APCI source on ionization efficiency and repeatability was systematically studied in the initial project of this doctoral thesis. Water was continuously infused to ensure a constant humidity during APCI in the analysis of methylchloroformate (MCF)- and methoxime-trimethylsilyl (MeOx-TMS) derivatized metabolites. These two different derivatization strategies are most commonly pursued in GC-MS based metabolome analyses. Several infusion rates were tested and a rate of 0.4 mL/h yielded an average 16.6-fold increase in intensity of the protonated molecules ([M+H]+) of 20 MCF-derivatized metabolites through suppression of in-source fragmentation. Water infusion, however, did not improve efficiency and repeatability of APCI of methoxime-trimethylsilyl (MeOx-TMS) derivatives of metabolite standards. Then, the impact of water infusion on metabolic fingerprinting of biological specimens was investigated. Water infusion led to a marked increase in the number of metabolites identified in MCF-derivatized cancer cell extracts via their [M+H]+ ions and improved repeatability of peak areas, almost doubling the number (N=23) of identified, significantly regulated metabolites (false discovery rate <0.05) between controls and cancer cells treated with the heat-shock protein 90 (Hsp90) inhibitor 17-DMAG.
Next, matrix effects caused by co-eluting compounds were investigated that might influence ionization. Strikingly, recovery of three out of seven internal standards used in a spike-in experiment was below 75% in one or several of the three biological matrices tested, namely Escherichia coli extract, serum, and urine. This was due to suppression by their respective endogenous metabolite that was present at a high concentration. Ion suppression caused by a co-eluting compound was further shown for three pairs of co-eluting standards employing standard mixtures with increasing concentrations of the co-eluting compounds. Overall these experiments demonstrated that matrix effects have to be taken into consideration in GC-APCI-MS.
In the course of my doctoral thesis, Bruker Daltonics (Bremen, Germany) introduced a redesigned APCI source. To test the capabilities of this source, MeOx-TMS derivatized supernatants of untreated cancer cells were analyzed by GC-APCI-HRTOFMS using both the original APCI I and the redesigned APCI II source. The latter source almost doubled the number of spectral features with signal-to-noise ratios greater than 20 that could be extracted from metabolite fingerprints and increased the absolute number of identified metabolites by 33% from 36 to 48. In addition, the median area RSDs of extracted features decreased from 33% to 24%. These improvements further resulted in a more than fourfold median decrease in lower limits of quantification to 0.002 - 3.91 µM as evidenced for 20 MeOx-TMS derivatized metabolite standards and a concomitant increase in the linear range by 0.5 to almost three orders of magnitude.
Finally, GC-APCI(II)-HRTOFMS was applied to the enantioselective quantitative profil-ing of the oncometabolite D-2-hydroxyglutarate (D-2-HG). MCF derivatization and GC analysis on a chiral gamma-cyclodextrin (Rt-rDEXsa) column were used to separate the D from the L enantiomer of 2-HG. Separation was optimized to avoid co-elution of D-2-HG with a highly abundant matrix compound present in cell culture media supplemented with bovine serum albumin. The use of APCI-HRTOFMS yielded highly specific quantifier ions and the infusion of water enhanced lower limits of quantification and repeatability by factors of ten and two, respectively. Analysis of a racemic 2-HG standard after MCF derivatization yielded a total of four peaks instead of the expected two signals for the D- and L-enantiomer. It was then shown that in addition to an open-chain three-fold derivative of 2-HG the methyl ester of the D/L-2-HG lactone is formed during derivatization. Since lactone of D/L-2-HG was found to be naturally present in biological specimens, the developed method was eventually based on the open-chain three-fold derivative of 2-HG yielding LLOQ values of 0.49 µM (D-2-HG) and 0.24 µM (L-2-HG). The GC-APCI(II)-HRTOFMS approach was successfully applied to the determination of D/L-2-HG concentration levels in urine specimens of 23 acute myeloid leukemia (AML) patients and 6 healthy controls, which were validated by HPLC-MS/MS. The yet to be discovered source of 2-HG lactone in sera of AML patients carrying neomorphic isocitrate dehydrogenase mutations promises to shed new light on the pathogenesis and progression of AML.
In summary this doctoral thesis demonstrates that GC-APCI-HRTOFMS is a useful addition to the established GC-MS approaches in metabolomics. Studies on factors potentially influencing the ionization, namely water infusion, matrix effects and source type, distinctly widened the applicability of GC-APCI-HRTOFMS for qualitative and quantitative analysis of MeOx-TMS and MCF derivatized metabolites. The ability of APCI along with water infusion to efficiently ionize a broad range of MCF metabolites was proven and in the following applied to comparative metabolic fingerprinting in extracts of treated cancer cells. Finally, the outstanding quantitative capabilities of GC-APCI(II)-HRTOFMS were used in a first enantioselective profiling application for quantitative determination of the oncometabolite D-2-HG. Altogether, this doctoral thesis contributed significantly to the excellent progress GC-APCI-MS has made towards becoming a routine tool in metabolomics
