RESUMO
Identifying non-annotated peaks may have a significant impact on the understanding of biological systems. In silico methodologies have focused on ESI LC/MS/MS for identifying non-annotated MS peaks. In this study, we employed in silico methodology to develop an Isotopic Ratio Outlier Analysis (IROA) workflow using enhanced mass spectrometric data acquired with the ultra-high resolution GC-Orbitrap/MS to determine the identity of non-annotated metabolites. The higher resolution of the GC-Orbitrap/MS, together with its wide dynamic range, resulted in more IROA peak pairs detected, and increased reliability of chemical formulae generation (CFG). IROA uses two different 13C-enriched carbon sources (randomized 95% 12C and 95% 13C) to produce mirror image isotopologue pairs, whose mass difference reveals the carbon chain length (n), which aids in the identification of endogenous metabolites. Accurate m/z, n, and derivatization information are obtained from our GC/MS workflow for unknown metabolite identification, and aids in silico methodologies for identifying isomeric and non-annotated metabolites. We were able to mine more mass spectral information using the same Saccharomyces cerevisiae growth protocol (Qiu et al. Anal. Chem 2016) with the ultra-high resolution GC-Orbitrap/MS, using 10% ammonia in methane as the CI reagent gas. We identified 244 IROA peaks pairs, which significantly increased IROA detection capability compared with our previous report (126 IROA peak pairs using a GC-TOF/MS machine). For 55 selected metabolites identified from matched IROA CI and EI spectra, using the GC-Orbitrap/MS vs. GC-TOF/MS, the average mass deviation for GC-Orbitrap/MS was 1.48 ppm, however, the average mass deviation was 32.2 ppm for the GC-TOF/MS machine. In summary, the higher resolution and wider dynamic range of the GC-Orbitrap/MS enabled more accurate CFG, and the coupling of accurate mass GC/MS IROA methodology with in silico fragmentation has great potential in unknown metabolite identification, with applications for characterizing model organism networks.
RESUMO
Male common carp (Cyprinus carpio) from eastern Lake Erie, which is greatly effected by urbanization, agriculture, and industry, were analyzed for PCB and PBDE concentrations in plasma, muscle, and liver to evaluate exposure to these chemicals through habitat interactions. Additional male carp from two nearby relatively clean lakes (Bear Lake and Hemlock Lake, NY) were also sampled as controls. While PCBs were detected in muscle, liver, and plasma of Lake Erie carp, the largest concentrations were found in muscle, which also had the most number of congeners. The dominant congeners were PCB 138 and PCB 153. Concentrations of PCB 153 in the muscle were correlated with fish length, total weight, and age. Therefore, larger (and generally older) carp had the highest concentrations of PCB 153. In contrast, PBDEs were found only in muscle with the predominant congener being PBDE 47. The total PCB concentrations in muscle of male carp from eastern Lake Erie (ranging from nd to 15,000 ng g(-1) lipid) were 100-fold higher than the total PBDE observed (1.5-100 ng g(-1) lipid), indicating a higher level of contamination of PCBs in Lake Erie. The high PCB levels in carp points to PCB resistance to metabolic degradation.
