Dipanker Ghosh is with Thermo Electron Corporation, San Jose, California.

Dipankar Ghosh

Identifying and quantifying analytes in highly complex samples, such as extracts from food, animal feed, pesticides, mycotoxins, and veterinary drugs, is a major analytical challenge for mass spectrometry. Accurate screening of these samples is critical in regulated environments such as food and animal-feed analysis.

Triple-quadrupole mass spectrometers have been used for identifying and quantifying analytes in complex samples, though that approach comes with a number of limitations, including the inability to re-interrogate the data postacquisition, as well as the inability to interrogate unknowns and the limited number of compounds per analysis. Time-of-flight (TOF) instruments have also been used for this application, but the technology's low resolution (15,000) has led to inaccurate mass measurements caused by unresolved background matrix interferences. 

A growing record of successful experiments has shown that the ability to perform high-resolution liquid chromatography–tandem mass spectrometry (LC–MS

) analyses is the key to measuring accurate mass, determining elemental compositions, and performing highly specific quantification on highly complex samples.  

While the advantages of high resolution have been demonstrated, there remains significant confusion in the scientific community about what constitutes a high-resolution approach to MS. This article will attempt to clarify the terms, technology, and methods used in high-resolution MS and then present a brief case study that shows the application of a high-resolution LC–MS

The application of high-resolution technology in MS is fundamentally the same as in photography: a high-resolution photograph shows great detail; a low-resolution photograph is blurry. However, the terms 

 are often (incorrectly) used interchangeably. High resolution is necessary to separate peaks from one another and to ensure that ions of only one kind contribute to a particular measurement. The measurement may be an accurate mass determination or a highly specific quantification.  

High resolution is particularly important for experiments involving complex mixtures, such as samples generated from a matrix (for example, biological, environmental), because these will often contain a significant number of background ions. In such cases, high resolving power will make the difference between detecting analytes at low concentration or not detecting these analytes due to the masking effect of isobaric matrix interferences. 

, are used to characterize mass spectrometers, it is useful to look at their definitions. 

The International Union of Pure and Applied Chemistry (IUPAC) defines resolving power in MS as

 "The ability to distinguish between ions differing in the quotient mass/charge by a small increment. It may be characterized by giving the peak width — measured in mass units, expressed as a function of mass — for at least two points on the peak, specifically at 50% and at 5% of the maximum peak height."

 "10% valley definition: Let two peaks of equal height in a mass spectrum at masses 

 be separated by a valley, which at its lowest point is just 10% of the height of either peak. For similar peaks at a mass exceeding 

, let the height of the valley at its lowest point be more (by any amount) than 10% of either peak height."

 "Peak-width definition: For a single peak made up of singly charged ions at mass 

 in a mass spectrum, the resolution may be expressed as 

 is the width of the peak at a height that is a specified fraction of the maximum peak height." It is recommended that one of three values — 50%, 5% or 0.5% — always be used. For an isolated symmetrical peak recorded with a system that is linear in the range between 5% and 10% of the peak, the 5% peak-width definition is technically equivalent to the 10% valley definition. A common standard is the definition of resolution based upon Δ

 being full width of the peak at half its maximum height, sometimes abbreviated FWHM. Preferably, this abbreviation should be defined the first time it is used. 

 are basically interchangeable. In fact, both resolution and resolving power are defined as 

Resolution of magnetic-sector instruments is normally given according to the 10% valley definition, which defines Δ

 as the mass difference between two resolved peaks, with a 10% valley between them.  

All other definitions for resolution are measured on a single peak. Because there are several ways to do this, one should always look at the definition actually used before comparing numerical values. For example, the 10% valley definition, where Δ

 is based on a real peak separation, is equivalent to a single peak measurement, where Δ

 is defined by the peak width at 5% peak height, as can be seen below.  

The most commonly used method to measure the resolution of quadrupole MS, Fourier transform ion cyclotron resonance (FTICR), Orbitrap, and TOF MS follows the FWHM definition, which uses the width of a peak at 50% of its height as a measure for Δ

The numerical value arrived at using the FWHM definition is naturally always larger than the value one would arrive at using the "width at 5% peak height" (10% valley) definition. In fact, the numerical FWHM resolution necessary to achieve mass separation to 10% valley is about twice the value, according to the 10% valley definition. This means that a resolution of 20,000 (FWHM) is equivalent to a resolution of 10,000 (10% valley).  

An instrument that has a resolution of 10,000 (FWHM) will separate ions at 

In the above example, where resolution values are given according to the FWHM definition, the baseline separation of CO from N

 is shown (right-hand panel), which would require a resolution of 2300 following the 10% valley definition. However, at an instrumental resolution of 2300 (FWHM), the individual CO and N

 peaks (green and blue) merge to give the signal outlined by the thick black line. The instrumental resolution must be increased to about 5000 (FWHM) to separate and accurately measure the mass of each peak. 

In all following examples, "resolution" and "resolving power" will be used synonymously and numerical values will follow the FWHM definition. 

In the case of quadrupole ion trap instruments (such as the Thermo Scientific LTQ mass spectrometers) and transmission quadrupole instruments (such as the Thermo Scientific TSQ Quantum mass spectrometers), the instrumental resolution increases linearly with mass — that is, if the instrument is set to separate one integer from its neighbor (for example 100 from 101), then the resolution will be increased from 200 at 

 1000. This resolution setting is called "unit mass resolution."  

TOF and double-focusing mass spectrometers (for example, Thermo Scientific DFS) operate at constant resolving power. This means that the set resolution will be the same for the entire mass range.  

Thermo Fisher Scientific FTICR and Orbitrap series mass spectrometers operate at varying resolving power. In the case of FTICR, the resolution decreases linearly with mass; for Orbitraps, the resolution decreases with the square root of mass. For example:  

The Importance of High Resolution: A Case Study

High-resolution MS is generally used either to measure accurate masses (and thereby enable the determination of elemental compositions) or to enable highly specific quantification. In either case the mass centroid of a peak profile is measured. For a quantification experiment, unambiguous results can be obtained only if sufficient resolving power is used to separate the target analyte from any possible interference. If the resolving power of the instrument is insufficient, it will result in false-positive or false-negative signal responses.  

To demonstrate the utility of high-resolution MS and clarify how this analysis works in practice, a horse-feed extract spiked with a mixture of 116 pesticides was analyzed as an example of an extremely complex matrix. The work demonstrates a full-scan screening approach utilizing resolutions of up to 100,000. The experiment reveals the advantages of high resolution in resolving coeluted, isobaric target compounds and determining their elemental composition.  

A dilution series ranging from 2 to 250 ppb (for each compound) was measured in duplicates at two different resolution settings. In addition a 100-ppb sample of the same mixture was analyzed at a resolution of 50,000 to determine the maximum number of detectable substances for this method. 

A non-hybrid single stage Orbitrap mass spectrometer (Exactive, Thermo Fisher Scientific, Bremen, Germany) coupled to a ultrahigh-pressure liquid chromatography (UHPLC) system (Thermo Scientific Accela, Thermo Fisher Scientific, San Jose, California) was used to evaluate a highly complex mixture of 116 pesticides, mycotoxins, and plant toxins in different concentrations. A 12-min gradient was applied to a 50 mm × 2 mm RP C18 column (Thermo Scientific Hypersil GOLD with 1.9-μm particles, Thermo Fisher Scientific, Madison, Wisconsin) with water–acetonitrile eluents. 

The method developed was evaluated with respect to sensitivity, selectivity, and linearity in standard solutions and extracts from animal feed. Mass measurements were performed at different resolution settings (

 = 50,000) to enable comparisons to data acquired by TOF instruments and to demonstrate the advantage of ultrahigh resolution. Orbitrap detection was carried out using automatic control of the number of ions entering the detector (AGC, target value = 10

Figure 1: Separation of isobaric peaks at different resolution settings. 

In cases where isobaric compounds are coeluted, erroneous mass accuracy and elemental composition assignment will occur if the resolving power of the mass spectrometer is insufficient to separate these compounds. Figure 2 shows two pesticides, thiamethoxam (C

PS), which have protonated molecular ions (MH

) at 292.02656 and 292.04031, respectively. A resolution higher than 40,000 is needed to resolve the protonated molecular ion of these two compounds completely. This is a prerequisite for analysis of low concentration compounds in the presence of higher abundant ones. The example in Figure 2 shows an approximate 1:3 mixture of both pesticides measured and simulated. 

Figure 2: Mass chromatogram of two isobaric pesticides measured at a resolution of 20,000 (top) and 50,000 (bottom). Superimposed is the simulated mass trace at each resolution setting. 

Influence on Elemental Composition Determination

A limited resolution of 15,000 results in two major limitations. First, the detection of unresolved doublets may result in significant mass errors that are outside the characteristic accuracy specification of the Exactive instrument. As a consequence, at lower resolution settings the mass windows for elemental composition determination have to be increased, resulting in much larger numbers of elemental composition proposals for the unknown or targeted compounds.  

This can be seen in the example (Figure 3) of pirimicarb at 

 239.1503. Due to the presence of an isobaric interference, the peak at 239 shows a mass error of 6.5 ppm. At a resolution of 15,000, the underlying interference causes an apparent shift to higher mass, whereas at higher resolution (here 80,000), the doublet is clearly resolved and the mass accuracy is well within instrument specifications. 

Figure 3: Improved mass accuracy simply by increasing the resolution in order to resolve the doublet. The peak at 15,000 resolution splits up into two by increasing the resolution to 80,000. 

To limit the number of candidate elemental compositions to a single confident assignment, a sophisticated software algorithm is used. It takes into account the peak height and mass accuracy of the monoisotopic peak and its isotopes. However, to function correctly, all of the accurate mass values for the isotopic peaks must be within specified limits. The absence of interference peaks can only be ensured by use of high resolution (as can be seen in Figure 4). Here the fungicide azoxystrobin is shown at resolutions of 15,000 and 80,000. The medium resolution spectrum shows very good mass accuracy for the monoisotopic peak but gives unusually high mass errors for the A+1 and A+2 ions. 

Figure 4: The importance of resolution for the molecular ion and its isotopes. At high resolution, the complete molecular ion cluster is detected correctly. 

 405.1452, which cannot be resolved at medium resolution. The high resolution spectrum shows excellent mass accuracy for all three measured isotopes. Determining elemental compositions using data acquired at ~15,000 resolution will result in misleading or incorrect data. Only sufficient high resolution allows the determination of the accurate mass of the complete molecular ion cluster and therefore allows automated assignment of an elemental formula with a high degree of confidence. 

LC–MS analysis of the extracted spiked samples showed the presence of 95 out of 116 compounds at 100 ppb in matrix. Figure 5 shows the overlaid ion chromatograms for all 116 compounds (3 ppm window) at 50 ppb (in matrix). The number of recovered pesticides in different concentrations is shown in Figure 5. The data illustrate a greater number of detected compounds (higher sensitivity) with an extraction window of 3 ppm at a higher resolution setting. This is exemplified in Figure 6, where extracted ion chromatograms of sulcotrion at 50 ppb for 

 = 50,000 are shown. The higher resolved spectrum displays two peaks, of which the smaller one is sulcotrion. 

Figure 5: Overlaid extracted ion chromatograms from a mixture of 116 pesticides and mycotoxins at a 100 ppb level. Extraction was done with 3 ppm mass window. The inset chart shows the number of detected compounds at different concentrations (in matrix) at two different resolution settings. 

Articles

The authors discuss the use of high-resolution LC-MS to analyze complex samples in regulated environments such as food and animal-feed analysis.

Using High-Resolution LC–MS to Analyze Complex Sample

Analysis of Mycotoxins in Various Cattle Forages and Food Matrices with the TSQ Quantum Discovery MAX

In vitro pharmacokinetic data, such as metabolic stability and the identification of formed metabolites have become important tools in early drug discovery (1,2). This information can help medicinal chemists improve on a compound's metabolic stability and also enables them to make predictions for in vivo clearances.  

The routes by which drugs can be metabolized or biotransformed include oxidation, reduction, hydrolysis, and conjugation reactions. It is important for medicinal chemists to understand these pathways, as the rate of metabolism of a drug can impact the ultimate pharmacological, pharmacokinetic, and toxicological activities.  

The most commonly applied model in the pharmaceutical industry to determine metabolic stability utilizes NADPH-supplemented liver microsomes from various species. However, only certain biotransformations, mainly mediated by the cytochrome P450 enzymes, are characterized by this method. It is well known that certain compounds are not prone to cytochrome P450–mediated metabolism, but to direct conjugation with a sugar, sulfate, or other hydrophilicity-enhancing moieties.  

Hepatocytes offer an excellent tool to elucidate metabolic pathways, as they comprise an intact cell system with both cytochrome P450 (Phase I) and conjugation (Phase II) enzymes and their required cofactors. In Johnson & Johnson Pharmaceutical Research and Development, rat hepatocytes are applied in early drug discovery for studying both compound metabolic stability and metabolite formation. The analytical procedure utilizes LC–MS-MS for the study of compound turnover (in vitro half-life and subsequent calculation of physiological relevant hepatic clearance data) and the identification of Phase I and II metabolites. 

This report demonstrates the role of a triple-quadrupole mass spectrometer (Finnigan TSQ Quantum Discovery, Thermo Electron Corporation) in performing in vitro studies of compound metabolic stability and identification of Phase I and II metabolites. For the determination of compound metabolic stability, samples were quantified using SIM and from the metabolic turnover an in vitro half-life was calculated. Full-scan MS-MS data dependent scans were carried out for the identification of Phase I metabolites. For Phase II metabolites, constant neutral loss (CNL) scans followed by data dependent triggered MS-MS analysis were performed for identification and structural elucidation.  

 Test compounds (exemplified here with verapamil) were incubated in rat hepatocyte suspension cultures using 24-well high recovery plates, purchased from BD-Gentest (Woburn, Massachusetts). Per well, 1 million viable cells were used in 0.5 mL of incubation medium. For in vitro half-life calculations, incubates contained 5 μM verapamil. Time points were 0, 15, 30, 60, and 120 min and assayed in triplicate. The reactions were stopped with two volumes of dimethyl sulfoxide (DMSO). For metabolite identification, incubations were performed using 50 μM verapamil. The reaction was stopped with two volumes of DMSO after 60 min. For sample preparation, the incubates were centrifuged for 10 min at 4 °C in glass vials (3000

) and the supernatants were transferred to 96-well plates for analysis by LC–MS-MS.  

Column:  Hypersil BDS C18, 50 mm X 4.6 mm, 5 μm (Thermo Electron) 

Flow rate: 1.2 mL/min (from which 0.1 μL was split off and infused into the source) 

Mobile phase A: 10 mM ammonium acetate (95%), acetonitrile (5%) pH 7.5 

Gradient I: Quantitation using SIM, starting with 100% A to 5% A at 2.5 min, hold for 2 min, and return to 100% A in 0.5 min. Total time was 6 min. 

Gradient II: Qualitative metabolite i.d., starting with 100% A, hold for 2 min, to 5% A in 4 min, hold for 5 min, return to 95% A in 1 min. Total time was 12 min. 

 A Finnigan TSQ Quantum Discovery MS system from Thermo Electron Corporation (San Jose, California) was used to perform the analyses. All analyses were carried out in positive electrospray mode.  

ESI conditions: flow inlet, 0.1 mL; spray voltage, 3800 V; sheath gas pressure, 30 l; auxiliary gas pressure, 10; capillary temperature, 370 °C. 

Single ion monitoring (SIM): scan time, 0.5 s; scan width, 1 Da; unit resolution (0.7 FWHM). 

Full-scan MS-MS data-dependent scans: 320–800 Da in 1 s. Data-dependent scan (MS-MS) of most intense ions above threshold of 105 cps. Collision energy of 35 V and collision gas (Ar) pressure of 1.5 mTorr was used.  

 129 (glutathione adducts). Scan time was 1 s. The collision energy was 35 V, and the collision gas (Ar) pressure was 1.5 mTorr. 

Determination of in vitro metabolic turnover and calculation of metabolic half-life:

 The percentage compound remaining at a certain time, point 

, was determined by comparing the peak areas (measured in SIM) of the parent compound at 

 min and was calculated as follows:  					

 minute triplicates are used for calculation).  			

) were calculated using the slope of the log-linear regression from the concentration remaining parent compound versus time relationship (

) as reported by Obach and colleagues (3).  

Determination of the verapamil in vitro half-life:

 The determination of the metabolic in vitro half-life of verapamil from the log-linear curve of the verapamil turnover is graphically outlined in Figure 1. The calculated in vitro 

 Figure 1: Log-linear curve of verapamil turnover with rat hepatocytes.			

 Several metabolites were detected in full-scan mode, however we exemplify with a major M-14 and a minor M-28 metabolite. The extracted ion chromatogram of verapamil and the corresponding M-14 and M-28 metabolites are illustrated in Figures 2a–c. 

Figure 2: Extracted ion chromatograms of (a) verapamil, (b) a M-14 metabolite, (c) a M-28 metabolite and the corresponding full-scan spectra of (d) verapamil, (e) the M-14 metabolite, and (f) the M-28 metabolite, respectively, formed with rat hepatocytes.			

Verapamil is observed to be eluted at 7.57 min, with the major M-14 metabolite at 7.15 min, and the minor M-28 at 6.76 min. The corresponding full-scan mass spectra of these three components are illustrated in Figures 2d–f. As is evident from these full-scan mass spectra, it is possible to determine the molecular weight but not a great deal of structural information. However, the data dependent full-scan MS-MS spectra shown in Figures 3a and b are more information rich, allowing a prediction of the structure for the M-14 metabolite. 

Figure 3: MS-MS spectra of (a) verapamil and (b) a major M-14 metabolite obtained by data-dependent full-scan MS-MS for proposal of Phase I metabolite structure.			

 Phase II reactions in drug metabolism are classified as conjugation reactions and give products that in most cases account for the majority of the inactive, excreted products of a drug. Examples include glucuronidation, glycosidation, and sulfation.  

Figures 4a and b show the full-scan extracted ion chromatograms of the M-14 metabolite glucuronic acid conjugate (at 5.49 min) and the M-28 metabolite glucuronic acid conjugate (at 5.25 min), with their respective mass spectra in Figures 4c and d. 

Figure 4: Confirmation of glucuronide formation in full-scan mode: Full-scan ion chromatogram of (a) the M-14 metabolite glucuronic acid conjugate and (b) the M-28 metabolite glucuronic acid conjugate and corresponding full-scan spectra of (c) the M-14 metabolite glucuronic acid conjugate, and (d) the M-28 metabolite glucuronic acid conjugate.			

In comparison with Figure 4, the CNL chromatograms (Figures 5a and b) for the same M-14 and M-28 metabolite conjugates are more specific (due to the characteristic loss of 176 mass units), and provide much cleaner mass spectral data (Figures 5c and d). This clearly demonstrates the advantages of using CNL scanning when looking for specific Phase II metabolites such as glucuronide conjugates. The MS-MS spectra of these two particular metabolic conjugates are shown in Figure 6 for structure elucidation. In Figure 6a, the presence of the diagnostic fragments at 

 260 (which are characteristic of nor-verapamil, see fragmentation schematics in Figure 3), indicate nor-verapamil glucuronide as the major Phase II metabolite. Added confirmation comes from the 

 441, which can be assigned to the free M-14 metabolite fragment. Following this rationale, it is suggested that the minor Phase II metabolite eluted at 5.25 min is a bi-demethyl-verapamil glucuronide. 

Figure 5: CNL ion chromatograms of (a) the M-14 metabolite glucuronic acid conjugate and (b) the M-28 metabolite glucuronic acid conjugate and CNL spectra of (c) the M-14 metabolite glucuronic acid conjugate, and (d) the M-28 metabolite glucuronic acid conjugate.			

A further example of the advantage of CNL scanning over full-scan mode is illustrated by the detection of another Phase II metabolite in Figure 7. This shows the glutathione conjugate of a proprietary drug discovery compound (MW 421 amu, structure not disclosed). Figure 7a shows the ion chromatogram obtained using CNL, and Figure 7b shows the same chromatogram but obtained in full-scan mode. The respective mass spectra, in Figures 7c and d, again clearly highlight the benefit of CNL data for structural elucidation: while the signal-to-noise ratio (S/N) was 2.5 in full-scan, in CNL the S/N was greater than 50. 

Figure 6: MSâMS spectra of Phase II metabolites for structure elucidation: (a) the M-14 metabolite glucuronic acid conjugate and (b) the M-28 metabolite glucuronic acid conjugate.			

The utility of the Finnigan TSQ Quantum Discovery system in early drug discovery for the measurement of a compound's metabolic stability with rat hepatocytes and for the identification of its Phase I and II metabolites has been illustrated. 

Figure 7: Detection of a glutathion adduct using CNL (129) scan and confirmation with MS full-scan mode: ion chromatogram of the GSH adduct in (a) CNL mode and (b) full-scan mode and the corresponding mass spectra, (c) from CNL mode, and (d) measured in full-scan +4752.			

In this article, the role of a triple-quadrupole mass spectrometer in performing in vitro studies of compound metabolic stability and identification of Phase I and II metabolites is demonstrated.

Dipankar Ghosh

Articles

Using High-Resolution LC–MS to Analyze Complex Sample

Analysis of Mycotoxins in Various Cattle Forages and Food Matrices with the TSQ Quantum Discovery MAX

Measurement of Metabolic Stability Using SIM and Identification of Metabolites by Data-Dependent full-Scan MS-MS and CNL Scanning