Kevin Siek

The analysis of persistent organic pollutants (POPs) in complex matrices is challenging because of their broad concentration ranges and the presence of interfering substances with similar physicochemical properties. In addition, there is a lack of instrument technology for widespread analyses of targeted and nontargeted compounds in minimally processed environmental samples. POPs in complex matrices such as sediment and fish samples were analyzed using gas chromatography (GC) with high-performance time-of-flight mass spectrometry (TOF-MS). High-performance TOF-MS offers the benefits of classical TOF (for example, a nonscanning mass analyzer, high acquisition rates, and spectral continuity) with the added advantages of increased mass accuracy and resolving power (

 = 50,000 at FWHM in ultrahigh resolution mode). Different classes of POPs were screened in single sample analyses. The power of high-resolution MS coupled with the ability to extract specific ions from full-range mass spectral data makes high-performance TOF-MS valuable for analyses of POPs in complex matrices.

Persistent organic pollutants (POPs) are halogenated organic compounds produced industrially for a wide variety of commercial applications. Examples of POPs include dioxins (polychlorinated dibenzodioxins [PCDDs] and polychlorinated dibenzofurans [PCDFs]), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs) (Figure 1). PCBs, marketed under trade names such as Aroclor, Sovol, and Clophen, were used for many years as dielectric fluids in electrical transformers and capacitors, heat transfer fluids, hydraulic fluids, lubricating and cutting oils, and additives in many commercial products (1). PBDEs have been used as fire retardants in household goods, construction material, and various plastics for the aviation and automotive industry (2). Dioxins are by-products formed during combustion processes. POPs are relatively inert and lipophilic, and tend to bioaccumulate in the environment. Their adverse health and environmental effects have led to their regulation in many industrialized countries (3,4). Detection of POPs is complicated by their broad range of concentrations and the presence of interfering substances with similar physicochemical properties (5–7). Furthermore, there has been a lack of appropriate instrumental technology for exhaustive analyses of targeted and nontargeted POPs in minimally processed environmental samples. Analysis of environmental samples typically requires costly equipment and highly specialized personnel. Analysts can spend significant time isolating, purifying, and characterizing the materials only to find that their efforts have resulted in partial loss, chemical modification, or complete elimination of targeted substances. 

Comprehensive analysis of POPs should involve the study of all classes of POPs and their metabolites. Metabolites of POPs are emerging as regular contaminants in wildlife and are critical for the risk assessment of human exposure to pollutants such as PCBs (8). Detection of POPs can be improved by reducing the amount of sample processing or enhancing instrument selectivity. High-resolution mass spectrometry (MS) has been the method of choice for the analysis of POPs; however, time-of-flight (TOF) mass spectrometers have emerged as an attractive alternative to their more costly counterparts (9,10). TOF-MS instruments were commercially available in the 1950s, and recent advances such as orthogonal acceleration, extended pathlengths, and improvements in data acquisition and processing have led to a renaissance of TOF mass analyzers as modern tools for biological and chemical research (9). The attractive features of TOF-MS, such as an unlimited mass range, fast acquisition rates, and spectral acquisition over a wide mass range without sacrifice of sensitivity, have been advantageous for the analysis of both small and large molecules. The fast acquisition rates of TOF-MS result in nonskewed mass spectral data that can be easily deconvoluted. Unfortunately, the low-resolution capabilities of classical TOF instruments made them unsuitable for the analysis of POPs. The emergence of high performance TOF-MS with extended flight paths, improved detection systems, and resolving powers greater than 50,000 (FWHM), has only increased the utility of these instruments for both targeted and nontargeted analysis of complex samples (7,11). 

Gas chromatography (GC)–TOF-MS analyses of fish and sediment samples containing PCBs and other POPs were performed using a Pegasus GC-HRT MS system (LECO Corporation, St. Joseph, Michigan) equipped with an Agilent Technologies (Palo Alto, California) 7890A GC system. PCB-containing sediment and fish samples were analyzed using an Rxi-5 Sil MS column (Restek, Bellefonte, Pennsylvania) and data were collected in high-resolution mode. Samples were previously prepared and not processed further before analysis (12). GC and MS parameters for PCB sample analyses are listed in Table I.  

Table I: GCâMS parameters for PCB sample analysis 

Figure 2: TOF-MS system operational modes (Pegasus GC-HRT). A = accelerator, D = detector. 

At the heart of the MS system is a folded flight path (FFP) mass analyzer with three operational modes (Figure 2): nominal (resolving power, 

 = 25,000, FWHM at 218.985080), and ultrahigh resolution (

 = 50,000, FWHM at 218.985080). Ions are introduced via orthogonal acceleration and then travel between a parallel set of gridless mirrors and through a set of periodic ion lenses (Figure 3). The flight path can be adjusted to 2 m (nominal), 20 m (high resolution), or 40 m (ultrahigh resolution). Most routine analyses can be performed in high-resolution mode; however, nominal mode can be used for quick inspection of samples, chromatographic method development, or NIST library searches. Ultrahigh-resolution mode can be used for samples requiring a high level of selectivity. 

Figure 4: (a) TIC of sediment containing elevated PCB levels. (b) XIC of sediment sample showing three different PCBs. 

The utility of high-performance TOF-MS is clearly evident from the analysis of sediment sample containing elevated levels of PCBs (>90 congeners). The total ion chromatogram (TIC) and extracted ion chromatogram (XIC) are shown in Figure 4. The average mass accuracy for 26 PCBs present in the sediment is -0.71 ppm with a standard deviation of 0.81 (Table II). Mass spectral data for PCBs 47, 162, and 209 are shown in Figure 5. 

Table II: Mass accuracy values for PCBs in sediment 

Figure 5: Mass spectra for PCBs (a) 47, (b) 162, and (c) 209.  

Comprehensive mass spectral analysis of trace levels of PCBs and other POPs was accomplished using high-performance TOF-MS. The analysis of fish tissue resulted in the identification of 15 PCBs (for example, tri-, penta-, hexa-, hepta, octa-, nona-, and deca-PCB congeners) and other classes of POPs such as dichlorodiphenyldichloroethene (

-DDE is the major metabolite of dichlorodiphenyltrichloroethane (DDT). 

-DDE has been linked to cancer and reproductive deficiencies in humans (13,14). TIC and XIC data (

-DDE, several hexachloro-PCBs including PCB 153 and decachlorobiphenyl) for fish tissue are shown in Figure 6. The molecular ion region in the corresponding mass spectral data is shown in Figure 7. A comparison of the calculated and observed ion ratios in the molecular ion region of the data is shown in Table III. The TOF-MS system with its high resolving power provided good mass accuracies for the three analytes: –0.10 ppm (

-DDE), 0.79 ppm (PCB 153), and –0.08 (PCB 209). 

Figure 6: (a) TIC of fish samples containing low levels of PCBs. (b) XIC of sediment sample showing two different PCBs and p,p’-DDE. 

Sector mass analyzers have traditionally been used for the analysis of POPs. However, TOF-MS systems are the ideal detectors for comprehensive POP analysis. Their fast acquisition rates, broad mass spectral range, and inherent sensitivity have made them an attractive option over conventional scanning mass spectrometers (12). With TOF-MS a complete data set can be acquired in a single run. Selection of desired analytes is performed after the acquisition using accompanying software that allows users to extract specific ions from the total ion set. This is in contrast to sector instruments that are operated in multiple ion detection (MID) mode to perform quantitative high-resolution spectrometry and quadrupole analyzers that are scanned across a given mass range or more typically set to acquire in selective ion monitoring (SIM) mode. The ability to simultaneously extract ions for different classes of POPs and possible metabolites would clearly facilitate analysis of complex environmental samples. One problem that has plagued TOF-MS instruments in the past is their relatively low resolving power caused by varying kinetic energy distributions in the ion source and mass analyzer. These energy or time aberrations have been reduced through the use of orthogonal acceleration, delayed extraction, and reflectrons (10). The high-performance mass analyzer minimizes these time aberrations and provides a flight path of up to 40 m, resulting in high mass accuracy and resolving power. 

Figure 7: Calculated and observed molecular ion region of the mass spectrum: (a) p,p’-DDE,  (b) PCB 153, and (c) PCB 209. 

Analysis of POPs is challenging due to the similar chemical and physical properties of these compounds. They are aromatic, lipophilic, and usually coextracted with numerous organic compounds when nonpolar solvents (for example, hexanes) are used during sample preparation. High-performance TOF-MS is capable of performing exact mass measurements and allows for selection and extraction of targeted analytes for elemental composition confirmation. High-performance TOF-MS provides a comprehensive profile of the sample in a single run, making it a powerful tool for the analysis of POPs in complex matrices. 

Table III: Isotope ratio values for p,p’-DDE, PCB 153, and PCB 209 

The authors would like to thank Dr. Eric Reiner from the Ontario Ministry of the Environment (Toronto, ON) for providing samples.  

 (3) P.O. Darnerud, G.S. Eriksen, T. Johannesson, P.B. Larsen, and M. Viluksela, 

 (4) E.J. Reiner, A.R. Boden, T. Chen , K.A. MacPherson, and A.M. Muscalu,

 (5) T.M. Kolic, L. Shen, K. MacPherson, L. Fayez, T. Gobran, P.A. Helm, C.H. Marvin, G. Arsenault, and E. Reiner, 

 (7) T. Cajka, J. Hajslova, R. Kazda, and J. Poustka, 

 (8) J. Maervoet, A. Covaci, P. Schepens, C.D. Sandau, and R.J. Letcher, 

Mass Spectrometry — Principles and Applications

 (John Wiley & Sons, Hoboken, New Jersey, 3rd ed., 2007), pp. 126–142. 

, R. Marsili, Ed. (Marcel Dekker, Inc., 2002), pp. 107–138.   

 (12) T.M. Kolic, L. Shen, K. MacPherson, L. Fayez, T. Gobran, P.A. Helm, C.H. Marvin, G. Arsenault, and E.J. Reiner, 

 are with LECO Corporation Life Science & Chemical Analysis Center in St. Joseph, Michigan. 

 is an applications chemist at LECO Corporation Life Science & Chemical Analysis Center in St. Joseph, Michigan.  

Articles

The combination of GC with time-of-flight (TOF)-MS proves to be a successful approach for the challenging analysis of persistent organic pollutants in complex matrices such as sediment and fish samples.

Comprehensive Analysis of Persistent Organic Pollutants in Complex Matrices 48 Using GC with High-Performance TOF-MS

High performance time-of-flight mass spectrometry (TOF-MS) is applied to the analysis and characterization of complex biological samples. High mass accuracy, high resolution, and accurate relative isotope abundance are all applied to the determination of analytes covering a range of concentrations in complex matrices including plasma and urine. Qualitative and quantitative evaluations are provided and include demonstrations of the impact of high-performance MS on sensitivity and selectivity. The ability to leverage high-performance MS in conjunction with a broad dynamic range in rapid ultrahigh-pressure liquid chromatography (UHPLC) analyses to identify unknowns and to propose putative metabolic biomarkers is demonstrated. The impact of speed of analysis and selectivity to the depth of coverage and accuracy of the analyses are discussed.

Demands on modern analytical chemistry are driven by enhanced information content, faster analyses, faster data processing, and higher throughput. Tools in separation science continue to increase the speed and information content of traditional analyses as demonstrated by the growing popularity of ultrahigh-pressure liquid chromatography (UHPLC) (1), fast gas chromatography (GC) (2), and GC×GC (3). This creates demands for faster data acquisition and higher fidelity data, which in mass spectrometry (MS) translate to mass accuracy and resolution. To address these demands, the mass resolution, mass accuracy, and data acquisition speeds of mass spectrometry have been pushed to improve instrument capabilities. A historical overview of mass analyzers is provided in Table I with the representative performance attributes provided.  

Table I: Overview of high-performance mass spectrometers 

The utility and value of high-resolution, high mass accuracy MS has been emphasized in numerous recently reported applications of the technology (4–9). High-resolution MS has been the domain of Fourier-transform (FT) MS and magnetic-sector instruments for decades. The paradigm is shifting away from just high-resolution MS to high-performance MS that includes mass resolving power, mass accuracy, isotope abundance, and acquisition speed in its considerations. New developments in high-performance mass spectrometers have shown significant impact. Time-of-flight (TOF) instruments with higher resolution and enhanced performance are a significant portion of the efforts. Recent advances in TOF mass spectrometers have enabled these instruments to provide high resolution and mass accuracy with speed, simplicity, and convenience. The measurement of mass-to-charge ratio (

) in a TOF analyzer is described by the following equation: 

 is the charge on the ion. This provides the fundamental relationship that 

. This has been one of the challenges to TOF — to achieve long flight paths in reasonable physical space and provide high performance. A number of key advances have occurred over the past two decades that have improved the performance of TOF mass analyzers and have included orthogonal acceleration (10), high-speed electronics, delayed extraction (10), and pulsed ionization (11), which permit the most effective utilization of the flight path available. In spite of these advances, TOF mass analyzers are highly sensitive to the initial conditions of the ions as they enter the mass analyzer. This includes distributions in velocity, time, and space during ion generation and at entry to the mass analyzer. To provide an extended flight path and address initial ion dispersion, electrostatic time-focusing elements such as reflectrons (12) have been implemented, improving resolution significantly.  

However, these approaches are limited by dispersions and higher order aberrations, as well as flight lengths on the order of a few meters. Other efforts have attempted to extend the flight path using cyclotron and torroidal analyzers (13). Duty cycle and effective mass range are typical compromises to high levels of mass measurement performance. With these advances, TOF has achieved a position in the realm of mass analyzers in which it provides sensitivity, mass accuracy and resolution that surpass some magnetic sector systems and encroach on the analyses historically reserved for FTMS systems. The principle advantage of a TOF system is the absence of scanning. This provides a mass measurement system well suited to analyte surveys rich in information content and high in duty cycle. These advances have opened the world of high resolution accurate mass analysis, historically the domain of FTMS and magnetic sectors, to TOF mass analyzers with the added benefit of simplicity and speed. The significant advances of TOF mass analyzers toward high-performance mass spectrometers continue in the approach discussed below. 

In one of the most recent advances in TOF-MS, Verentchikov and colleagues (14,15) have introduced the multireflecting time-of-flight analyzer that uses a Folded Flight Path (FFP). This is depicted in Figure 1, which shows how the ions effectively pass between each of two planar ion mirrors and through an Einzel lens array. A major challenge in the multireflecting systems is poor transmission because of defocusing of ion trajectories. In the FFP configuration, transmission is improved by using nonlinear electrostatic fields in the gridless mirrors. The ions are constantly refocused as they traverse the flight path and create the extended flight path needed to enhance the resolution. The gridless design minimizes ion loss during the flight. The mass analyzer offers three effective flight paths of approximately 2-, 20-, and 40- m lengths with operations in the same planar flight "tube." These operational options are depicted in Figure 2. The number of passes or reflections determines the effective pathlength, and by inference, the available resolving power. The performance capabilities of this system are provided in Table I.  

Figure 1: Depiction of multireflecting TOF or folded flight path design. 

This design is applied to the analysis of analytes in complex matrices in the form of UHPLC coupled to atmospheric pressure ionization with TOF-MS. The matrices include plasma and urine, and the analytes include compounds of pharmaceutical interest and naturally occurring biological analytes associated with disease states. The applications discussed include the identification and relative quantitation of metabolites in plasma from three strains of Zucker rats, an example of the study of animal models of disease (16), and the analysis for metabolites of common cold medications in human urine.

Figure 2: The three modes of operation of the MRT/HRT system. The FFP design facilitates multiple flight distances for ions, and as such, the potential for multiple levels of resolving power. Ions pass between electrostatic mirrors and are refocused by central lenses for the length of the analyzer. Two full passes across the analyzer provide a 40-m flight path (ultrahigh resolution) and 100,00 resolving power, one pass through the entire analyzer provides a 20-m flight path (high resolution) and 50,000 resolving power, and a partial pass through the analyzer provides a 2-m path (nominal resolution) and 2500 resolving power. (Note: A = accelerator and D = detector.) 

The following represent the basic conditions used in the analyses described in the results and discussion which follow. Chromatographic separation was achieved using an Agilent Technologies (Santa Clara, California) 1290 UHPLC system with mobile phases consisting of water with 0.1% (v/v) formic acid (A) and acetonitrile with 0.1% (v/v) formic acid (B). Mobile phase was delivered at 0.1–0.2 mL/min and with gradients covering 0–80% B between 3 and 30 min. Injection volumes varied between 1 and 5 μL. The column used was a 50 mm × 1 mm Hypersil Gold C18 AQ (Thermo Fisher Scientific, West Palm Beach, Florida). MS was achieved on a LECO Citius LC-HRT system equipped with a LECO electrospray ionization (ESI) source (LECO Corporation, St. Joseph, Michigan) and operated in high resolution mode (

 = 50,000 [FWHM]). Data were processed using ChromaTOF-HRT software (LECO). Acquisition rates of 2–40 spectra/s were used both with and without in-source collision-induced dissociation. Calibration was achieved using external calibration with Agilent Tune Mix.  

Figure 3: Relative response ratios for select analytes in plasma from Zucker lean, fatty, and obese rats. (a) Full-scale plot; (b) zoomed plot. 

Rat plasma samples were obtained from Bioreclamation (Hicksville, New York) and were from lean, fatty, and obese Zucker animals. The plasma was from terminal bleeds with the rats being 7–9 weeks of age. The plasma samples were deproteinated using Microcon (Billerica, Massachusetts) centrifugal devices with a 5K cutoff. After protein removal, samples were diluted 5× into aqueous 0.2% heptafluorobutyric acid before UHPLC analysis.  

Figure 4: Extracted ion chromatogram of 232.1554 Â± 0.01 from selected rat samples. 

Urine was obtained from a healthy male volunteer before and after a single dose of cold medicine containing 6.5 mg doxylamine, 15 mg dextromethorphan, and unspecified amounts of polyethyleneglycol (PEG) and other excipients. To remove salt and protein from each sample, a 0.15-mL aliquot was diluted with 1.05 mL methanol and centrifuged. A 1.0-mL aliquot of the clear supernatant was evaporated, reconstituted with 0.025 mL methanol and 0.10 mL water with 0.1% formic acid, and analyzed by UHPLC–TOF-MS under high resolution conditions. All other chemicals used were obtained from Fisher Scientific (Fairlawn, New Jersey) or Sigma-Aldrich (St. Louis, Missouri).  

Table II: Mass accuracy in the assignment of identities to doxylamine metabolites 

 = 10) Zucker rats were analyzed by LC–MS using high-performance TOF-MS. The analysis of the data was achieved by means of two mechanisms. In one, a list of established analytes was used to search the data for these analytes using an accurate mass targeted approach. In these instances, the exact 

 value was searched against the existing data to within 0.001 

 values obtained from the analyses were used to determine molecular formulas, and the formulas or the accurate 

 values were searched in ChemSpider (17) or KEGG (18) or other similar metabolite databases to facilitate the identification of the analyte in question. In both of these instances, the ratio of area responses in the samples from the different phenotypes were then averaged and compared to each other for differences as three ratios. Specifically, the Lean:Fatty, Lean:Obese, and Fatty:Obese response ratios were generated, and the averages for each phenotype are provided graphically in Figure 3 for representative analytes. The plot shows several selected or readily identified analytes that show positive changes in the Lean:Fatty and Lean:Obese ratios relative to the Fatty:Obese ratio. These include leucine/isoleucine, hippurate, dimethylarginine, kynurenine, and urate. The nearly sixfold change in leucine/isoleucine is the most striking and largest proportional positive change for the "fatty" phenotype, while the change in kynurenine is the highest magnitude change negatively correlated with the "fatty" state. Both kynurenine and leucine/isoleucine have been previously associated with diabetes and obesity (19–23).  

Figure 5: Comparison of relative isotope abundance measurements for the analyte at m/z 232.1554. The percent of the theoretical abundance is provided versus the expected values for each option and is shown as Option 1/Option 2. The options are the two highest hits in the formula match. Isotope abundance was calculated using the ChromaTOF-HRT tool. Signals were considered from each of five samples, which covered a range of response intensities, and all three phenotypes. 

At the beginning of this study, standards were not available for confirmation of identity. As such, experiments including the fragmentation of "precursor" ions before the mass analyzer (so-called in source CID) with accurate mass measurement of fragment ions and the use of relative isotope abundance were used to clarify or support identification. One analyte identified in these studies was butyryl carnitine. In this case, an ion at 

 = 232.1554 was observed to change in intensity between lean and fatty/obese states. The formula search for this 

 provided two formulas within 5 ppm of the target 

 (1.3 ppm error). To provide additional information on the structures of the analyte, the fragment ions were extracted into a separate data channel and evaluated. Figure 4 shows an extracted ion chromatogram for both low (lean) and high (obese/fatty) samples along with the fragment ion spectrum from a lean sample. The two prominent fragment ions at 

 173.082 and 85.03 match the loss of trimethylamine from 232 and the loss of butyric acid group and a trimethylamino group from 232, respectively. These are consistent with the identification of 232.1554 as butyryl carnitine. To provide yet another piece of supporting evidence, the relative isotope abundance was generated for the two formula above and these were compared to what was observed in high (fatty/obese) and low (lean) intensity samples. These findings are provided in Table II. For the monoisotopic peak and first isotope the agreement with the theoretical distribution is better than ±5% (relative) in all cases versus Option 1 (butyryl carnitine). For the second isotope (2 

C), the agreement is still better than ±17% (relative) for four of the five samples, with the fifth being of very low signal intensity. In all cases, the relative isotope abundance defines which of the two formula options best fits the data. This is most clearly seen in the first isotope data shown in Figure 5. This combination of accurate mass precursor analysis, accurate mass fragment ion analysis, and high integrity relative isotope evaluation is a clear demonstration of the impact that high-performance MS can have in metabolomic analysis and the characterization of analytes.  

Figure 6: Standard curve of butyryl carnitine from single injections: (a) 0.16â500 nM, (b) zoomed region of 0.16â20 nM. 

Of additional importance in metabolomic analysis is the dynamic range of the instrument. To effectively interrogate both abundant and trace level analytes simultaneously, the linearity of response across several orders of magnitude is necessary. To explore this and the limit of detection of the accurate mass system, a standard curve of butyryl carnitine was created that covered the range of 0.16 through >500 nM. The plots of response versus concentration are shown in Figure 6 (Figure 6a: 0.16–500 nM; Figure 6b: 0.16–20 nM) and demonstrate that the dynamic range achievable here is clearly in excess of the 500 nM point shown (2500 nM not shown). This is equivalent to a linear dynamic range greater than 3000-fold (15,000-fold at 2500 nM). The experiment has its lowest detectable level at 0.16 nM or approximately 200 fg of butyrylcarnitine on-column. This translates to the ability to examine either dramatic differences in concentrations of a single analyte or a range of analytes at substantially different concentrations in the same analysis.  

Figure 7: (a) Base peak signal and extracted ion chromatograms of active ingredients and potential metabolites in urine. The signal for PEGs is clear between 50â100 s. (b) Precursor (low energy) and product (high energy) spectra from m/z 271 showing key fragment ions. The extraction window is at Â±2 ppm for each analyte. 

Analysis and Characterization of Drug Metabolites in Urine:

 One of the most complex, but also most readily available, biological fluids is urine. It is difficult to standardize and is affected by diet, physiological state, disease, and other hard-to-control factors (24). With all of this said, urine is still able to indicate the health of individuals and to provide insights into what the body has been exposed to, as it does give up its metabolites easily through renal clearance mechanisms. Here, urine from a healthy donor was analyzed by UHPLC with high-performance detection. A minimal level of cleanup was performed with the objective of providing a global survey for metabolites of doxylamine and dextromethorphan. Figure 7 shows a representative set of chromatograms for actives and metabolites detected in urine. The extraction window of ±2 ppm shows the necessary stability of the mass accuracy across the entire peak. This facilitates accurate integration of signal with high resolution and accuracy relative to other peaks. Although there are known compounds which should be present from the dosing, urine is a complex matrix, and as such, the identity of the analytes was confirmed by accurate mass analysis (Table II), which showed less than 0.5 ppm mass errors for the proposed doxylamine-related peaks. Similar to what was achieved with the butyryl carnitine peak, relative isotope abundance for the doxylamine provided highly accurate agreement with the theoretical isotope abundance. This is shown in the top of Table III. In addition, the application of "in-source CID" to generate fragment ions provided both accurate mass fragment identification and accurate relative isotope abundance of the fragment ions. These findings are shown in the bottom of Table III. All but the lowest of signals provide better than 5% relative difference versus the theoretical isotope abundance. Furthermore, the measured resolving power was in excess of 40,000 at 

 90, the resolving power was a robust 35,000.  

Table III: Mass accuracy and relative isotope abundance for doxylamine using "in source CID." Parent ion data are provided at the top of the table and product ion data at the bottom. 

The above applications of high-performance MS to the analysis of physiological analytes and metabolites in complex biological matrices provide a representative overview of the impact that this type of experimentation can have on analyte identification and quantitation. High mass accuracy, mass resolving power, and relative isotope abundance prove to be invaluable tools for analyte identification in the experiments discussed and facilitated the identification of analytes as potential biomarkers for obesity and as metabolic byproducts of pharmaceutical agents. Having high mass accuracy, resolving power, and isotope measures available in both precursor and fragment ions make the confidence an analyst might have in the identification of analytes extremely high. As this can be achieved on femtogram amounts of material using high acquisition rates with analysis times of a few minutes and provide high performance under all acquisition conditions, high-performance MS is both fast and of high information content. These findings clearly define the ability of high-performance MS to provide a positive impact in the advancement of metabolomic and metabanomic analyses. 

The authors wish to thank Celine Aguer and Mary-Ellen Harper from the University of Ottawa (Ottawa, Canada), Oliver Fiehn from UC Davis (Davis, California), and Sean Adams from the Western Human Nutrition Research Center (WHNRC) at UC Davis for butyryl carnitine standards through work funded by the National Institute of Health (DK 078328, Bethesda, Maryland).

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The impact of speed of analysis and selectivity to the depth of coverage and accuracy of the analyses are discussed.

A New Path to High-Resolution HPLC–TOF-MS — Survey, Targeted, and Trace Analysis Applications of TOF-MS in the Analysis of Complex Biochemical Matrices