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

The recent Beijing Olympic Games reminded us of the value of international sport competition for fostering peace and mutual understanding worldwide. Unfortunately, we are also reminded that there are those athletes who will sacrifice their careers and violate the trust of their countrymen by using performance-enhancing drugs to give them a competitive edge, and cheating is as old as the Olympic Games.  

The use of performance-enhancing drugs in sporting events, either in the form of supplements or highly purified and potent compounds, eventually resulted in the establishment of systematic screening protocols to detect and prevent the use of such substances. This practice of chemical enhancement of athletic performance is commonly referred to as "doping." The death of British cyclist Tommy Simpson in 1967 from an amphetamine-induced heart attack sparked the introduction of routine, in-competition drug testing by most international sports federations, and in 1972 it made its debut at the Olympic Games in Munich. After the formation of the medical committee of the International Olympic Committee (IOC) in 1967, a list of prohibited substances was established. The list is updated frequently and supervised by the World Anti-Doping Agency (WADA), which was formed in 2000. The list currently includes five categories of prohibited substances (anabolic agents, hormones and related substances, beta-agonists, anti-estrogenic agents, and diuretics and other masking agents); three prohibited methods (enhancement of oxygen transfer, chemical or physical manipulation of samples, and gene doping); and four categories of substances prohibited only during competition (stimulants, narcotics, cannabinoids, and glucocorticosteroids). A minimum required performance limit (MRPL) is established for each prohibited compound, examples of which are shown in Table I. 

Table I: Minimum required performance limits			

WADA-accredited laboratories are required to demonstrate that they can routinely perform screening and confirmatory analyses at the MRPL established for each prohibited compound, following general guidelines prescribed by WADA. Procedures to account for the integrity of each specimen and preserve the chain of custody are in place to track handling and storage from the point of collection to final disposal of the specimen. These laboratories are responsible for assuring chain of custody by recording receipt of the samples, assuring proper handling and storage through intralaboratory identification and tracking, and ensuring confidentiality. The testing is then performed, the data archived, and results communicated observing the same strict protocols governing chain of custody. Ongoing original research and method refinement activities are also required of WADA-accredited laboratories to optimize performance and develop even more effective methods to identify new prohibited substances. Consequently, the methods and analytical technologies of these laboratories are constantly evolving. 

GC–MS and LC–MS Are the Testing Platforms of Choice

WADA-accredited laboratories use methodologies that have been optimized to screen large numbers of athlete samples (usually urine) for the presence of prohibited substances, then confirm any presumptive positive result with an orthogonal method that is both highly selective and unequivocally confirmatory. The majority of standard protocols used in doping control laboratories are based on an initial chromatographic separation of the complex urine extract using either gas chromatography (GC) or high performance liquid chromatography (HPLC), followed generally by mass spectrometry (MS) analysis of the chromatographic eluent to detect and quantify the vast range of prohibited substances. GC is suitable for compounds that can be vaporized easily without degrading or decomposing the compound, and was the first chromatographic method to be used extensively in doping control laboratories. HPLC is more suitable for thermolabile and highly polar compounds that cannot be readily vaporized, and for separation of large biomolecules such as proteins and peptides. 

The combination of GC or HPLC with MS provides a highly sensitive, selective, and versatile tool for the detection of WADA-prohibited compounds. A wide range of MS analyzers is available, each having advantages for particular applications. The most common type of MS analyzer used in doping analysis is the single-quadrupole MS system, which can be used in either the full-scan or selected ion monitoring (SIM) mode in screening protocols. Mass spectrometers with more than one mass analyzer (tandem MS or MS-MS systems) provide the next higher level of confidence in the identification of banned substances. These instruments first isolate the precursor ion or other intense fragment ion present in the full-scan MS spectrum and then fragment this precursor target ion into smaller product ions. The resulting product ion mass spectrum can be compared with that obtained from an authentic standard (or interpreted 

 if no standard is available) as part of the identity confirmation process. The ion trap MS-MS system (single analyzer, tandem-in-time operation) has found utility in many doping control laboratoriess for screening due to its ability to provide both MS spectral and MS-MS product ion spectral data, and in particular its sensitivity for acquiring product ion spectra. This performance feature means that the ion-trap mass analyzer can be used for analyte confirmation in selected circumstances, but co-eluted substances with isobaric precursor masses can result in a complex product ion spectrum of questionable value for confirmation. The tandem quadrupole mass spectrometer (sometimes called a "triple quadrupole" or "QQQ" system) is the definitive tool for high-confidence screening of target analytes, their confirmation, and quantification of these prohibited compounds in a single GC–MS-MS analysis.  

GC was the first analytical technique used to detect prohibited substances in athletes, and GC–MS has become the workhorse of doping control laboratories worldwide. It is routinely used to test for anabolic agents as well as beta-2 agonists, anti-estrogens, diuretics, stimulants, narcotics, cannabinoids, and beta-blockers (1). Screening for these compounds is performed using either the full-scan mode or the selected ion monitoring (SIM) mode with a single quadrupole mass analyzer. SIM is also used for confirmation of a suspect positive by determining the relative ratios of multiple ions being monitored for each target compound and comparing these to ratios obtained for authentic standards. GC–MS-MS with an ion trap mass analyzer is used in a number of doping control laboratories as well, to provide added sensitivity and specificity. The recent availability of GC–QQQ systems promises to extend the capability of drug doping laboratories by providing the ability to screen, confirm, and quantify prohibited compounds in one run, even in complex matrices. 

Doping control efforts focus to a significant extent on anabolic steroids, as they are probably the most widely abused category of prohibited substances. The earliest drug doping test methods developed were for steroid detection, resulting for example in the confirmation of stanozolol in a urine sample from sprinter Ben Johnson in the1988 Olympic Games, with the subsequent forfeiture of his gold medal and two world records. More recently, the detection of an elevated testosterone/epitestosterone (T/E) ratio led to the stripping of the 2006 Tour de France title from Floyd Landis, and the imposition of a two-year ban from sanctioned competition. The analysis of this group of compounds also receives close attention in the laboratory, as they must be detected at such low levels (Table I), requiring ongoing development of more highly selective and sensitive testing methods. 

Many doping control laboratories have traditionally used high resolution mass spectrometry (HRMS) or GC–ion trap MS-MS to meet the challenge of identifying and quantifying very low levels of very similar steroid compounds. However, HRMS is a technology that is expensive to acquire and requires a great deal of training and expertise to operate. Ion-trap MS-MS is a more economical option and somewhat easier to operate, but for some analytes, it may require the use of MS-MS-MS to achieve the requisite specificity, potentially resulting in a failure to achieve required sensitivity. On the other hand, the steroid detection and quantification requirements of the doping control laboratory are an excellent fit for the capabilities of the GC–QQQ platform. Selected reaction monitoring (SRM) with a QQQ system provides detection of trace amounts of target compounds in complex matrices, providing screening, confirmation, and quantification in one analysis. The precursor ion of interest generated by the source is selected and isolated in the first (Q1) quadrupole. A hexapole collision cell (Q2) fragments the selected ion, and the product ions are selected in Q3. By choosing product ions from this transition that are characteristic for the steroids of interest, chemical noise is separated from the signal, providing very high sensitivity and selectivity, even in very dirty matrices. With careful selection of a unique precursor to product ion transition for each steroid, it is practical to quickly and easily create SRM assay methods that can be used to identify and quantify simultaneously many of the prohibited steroids in a sample. 

Table II: GCâMS conditions used routinely for steroid analysis are similarly adopted for analysis by GCâQQQ			

Doping control laboratories must be able to detect 2 ppb or less of each of the following steroids: clenbuterol, 19-norandrosterone, 17α-methyl-5β-androstane-3α, 17β-diol, epimetendiol (methandienone), and 3'-hydroxystanozolol (stanozolol). Methods have been developed previously in certain doping laboratories, utilizing the GC–ion trap MS-MS platform, that have demonstrated the potential to screen and confirm less than 2 ppb each of these compounds in a low-level quality control (LQC) standard. This is generally accomplished by examining the extracted ion current profiles of the target ions present in MS spectra or in MS-MS (or MS-MS-MS) product ion spectra. However, many laboratories conduct routine screening analysis of steroids in urine using GC–MS operating in the SIM mode. These laboratories can use the same chromatographic separation protocols to detect and confirm as many as 120 analytes in one run using SRM on a GC–QQQ system (Table II). This includes the components of the LQC standard, which can have the same GC retention times on a GC–QQQ system as they do on a GC–MS system. 

Table III: Reconstructed SRM spectrum SRM product ion ratios of the 3-hydroxyl and 4-hydroxyl metabolites of stanozolol, as purified standards, components of the LQC standard, or in urine samples (previously confirmed positive specimens 1, 2, 3, and 5)			

Positive Identification — Anabolic Steroids

Using SRM on the GC–QQQ system, steroids can be reliably separated, detected, identified, and quantified. Figure 1 demonstrates separation and identification of the components in the LQC standard, all present at only 2 ppb. Very similar compounds such as the 3-hydroxystanozolol and 4-hydroxystanozolol metabolites of stanozolol can be identified and quantified, using the same four ion transitions with SRM, even though they have very similar retention times (Figure 2). The two derivatives give very different relative comparative abundances of the four selected product ions. The data demonstrate that peak height ratios of the product ions, versus a reference product ion, are characteristic of each metabolite, allowing positive identification of both. These ratios are very reproducible, whether using a standard containing only the 3-OH or 4-OH metabolite, the LQC standard, or positive urine samples containing various levels of the metabolites (Table III), allowing reliable identification. 

Doping control laboratories must be able to detect prohibited steroids against a background of several endogenous steroids whose levels must be accurately quantified. For this purpose, an endogenous quality control standard (EQC) with known quantities of endogenous steroids can be used to validate detection limits and screening efficacy. Two of the most significant components of this standard are testosterone and epitestosterone. Epitestosterone is an inactive stereoisomer of testosterone, and in an average adult male the ratio of the quantities of the two is about 1:1. If exogenous testosterone is being taken as a performance-enhancing drug, the T/E ratio increases. WADA has set a ratio of 4:1 as the threshold above which further investigation is required to confirm that the elevated level is the result of exogenous testosterone administration by the athlete. Accurate estimation of this ratio is dependent upon the ability to accurately identify and quantify each of these two steroids. Identification is accomplished by GC–QQQ SRM analysis of the two stereoisomers, providing nine transitions with which to quantify testosterone and epitestosterone. The peak height ratios of the extracted product ion profiles for three of the principal product ions from these transitions (for example, SRM transition 432 > 209; 432 > 301; 432 > 196) provide essentially the same ratios, giving accurate and reliable estimation of the T/E ratio (Figure 3). 

Other endogenous steroid metabolites of testosterone including androsterone, etiocholanolone, dehydroepiandrosterone (DHEA), and 5α- and 5β-androstanediols may be quantified in a similar approach using various transitions for the quantification of these analytes. 

The sports community is moving toward the establishment of a "passport" for each athlete, based on the principle that biological monitoring throughout an athlete's career should make any illegal preparation harder to implement. Such monitoring will ensure that routine quantification of endogenous steroids becomes even more important. Basing this quantification on SIM acquisition techniques may result in inaccurate determinations of these levels, as SIM may be more prone to interferences from the matrix. The seven aforementioned endogenous steroids can indeed be reliably and reproducibly analyzed by SRM on a GC–QQQ instrument, paving the way to realizing the goal of closer scrutiny for athletes both during competition as well as out of competition. This athlete's passport then becomes a historical record of endogenous steroid levels, permitting any anomalies that may result from doping to be recognized quickly. 

As long as athletes look to performance-enhancing drugs to get an edge on their competition, there will be a need for doping control laboratories that have an ever-growing arsenal of technologies and methodologies with which to detect current prohibited substances, as well as substances that may be developed in the future. The demand for sensitivity, specificity, and accurate quantification will only increase, and technologies must continue to evolve to meet the challenge. GC–QQQ is well-suited to meet this challenge because it provides doping control laboratories with the ability to increase sensitivity and specificity in complex matrices, with a modest investment in new equipment, and without the need to change their current extraction and GC separation methods. 

 is Director of the Doping Control Center in Penang, Malaysia. 

 is an Applications Chemist at Agilent Technologies, Santa Clara, California. 

The authors discuss the use of GC-MS in drug doping testing.

The Role of Triple Quadrupole GC–MS in Steroid Analysis

LC–MS-MS fractionation experiments or direct electrospray infusion can generate information-dependent MS-MS data triggered from a suite of triple-quadrupole selective scans or linear ion trap (LIT) scans. As shown in Figure 1, precursor ion (PIS), neutral loss (NL), multiple reaction monitoring (MRM), or enhanced MS LIT scanning can trigger an information-dependent enhanced product ion scan for MS-MS characterization of lipid structures.  

Faster quadrupole scanning and LIT scanning (up to 20,000 Da/s) combined with faster polarity switching and sensitivity improvements in enhanced product ion and MS

  scanning in LIT mode provide qualitative and quantitative strategies simultaneously. Figure 2 shows the coupling of scans for global lipid profiling on the AB SCIEX QTRAP 5500 system. Methods consisting of a suite of survey scans triggering multiple MS-MS scans yield in-depth lipid coverage in samples of wide dynamic range. 

Targeted Multiple Precursor Ion Scanning by Direct Electrospray Infusion

A total of 60 combinations of PIS and NL multiplexed experiments can be acquired simultaneously for comprehensive quantitative analysis of lipid species by direct infusion. An example of data collected with negative mode multiple ion method consisting of multiplexed scanning of fatty acid acyl ions of varying saturation and carbon chain length, and diagnostic fragments for selected lipid classes, is shown in Figure 3. These data can be used directly to determine the abundance of lipids in a particular class from class-specific precursor ion experiments or to design subsequent MRM methods to quantify a subset of lipids of interest. 

Measuring the Quantitative Response of Lipids to Class-Specific Internal Standards

Lipid class internal standards are essential to confirm, normalize, and quantitate corresponding lipid species that were detected with the MS approaches mentioned earlier (1). To study the linear dynamic range, a series of samples (three replicates for each concentration) consisting of the internal lipid class standards (held constant at 0.15 μM) and an increasing amount of total lipid extract from 10

  μg were prepared from brain tissue. LIT enabled enhanced MS information-dependent acquisitions (IDA) triggered MS-MS methods were carried out and data were processed by LipidView software to evaluate the accuracy and precision of the quantitation. Figure 4 illustrates a linear response of representative lipids once corrected for their corresponding lipid-class specific internal standards across the calibration line over five orders of magnitude. Specifically for phosphatidyl choline (PC) and phosphatidyl ethanolamine (PE) lipids, the limits of detection are well in sub pmol level. 

Post-Acquisition Data Processing for Lipid Identification and Quantitation

LipidView software is data processing software that identifies and quantifies lipid species from ESI-MS data. The software enables identification and characterization of lipid species through searching masses of parent and fragment ions in a database of characteristic fragments and neutral losses corresponding to parts of lipid molecules, and reports a numerical and graphical output for profiling various lipid molecular species, lipid classes, fatty acids, and long-chain bases (3). The software streamlines various steps, such as automated data processing method selection, lipid species identification, comprehensive isotope contribution removal, multiple internal standards-based quantification, visualization, and reporting of the results. A view of the user interface is shown in Figure 5 demonstrating the results workspace for reviewing the lipid profile data from a processed raw data file. 

Improvements in Speed and Sensitivity for Lipidomics Applications

The AB Sciex QTRAP 5500 System's speed, selectivity, and sensitivity enable high multiplexing of QqQ scanning, and whole lipid extracts can be analyzed by either direct infusion of LC methods for in-depth lipid profiling — achieving both qualitative and quantitative data (with the use of synthetic lipid internal standards) in very short acquisition times. In addition to sensitivity gain, the MS system provides a polarity switching time of 50 ms, a linear accelerator trap scanning rate of 20,000 Da/s, and an LIT fill time of 50 μs. Lastly, Analyst 1.5 Software using the Scheduled MRM algorithm enables up to 2500 MRM transitions monitored in a single experiment for lipid quantitation in LC-based workflows. 

Scientists require versatility, sensitivity, specificity, and speed for high-throughput lipidome profiling of complex biological extracts by either direct infusion electrospray or LC–MS methods. For optimal results, data acquisition strategies should be coupled with automated data processing for lipid species identification and quantitation. 

 ar are with Applied Biosystems|MDS Analytical Technologies, Toronto, Ontario, Canada. 

(1)  M. Stahlman, C.S. Ejsing, K. Tarasov, J. Perman, J. Boren, and K. Ekroos, 

(2)  D. Schwudke, J. Oegema, L Burton, E. Entchev, J.T. Hannich, C.S. Ejsing, T. Kurzchalia, and A. Shevchenko, 

(3)  C.S. Ejsing, E. Duchoslav, J. Sampaio, K. Simons, R. Bonner, C. Thiele, K. Ekroos, and A. Shevchenko, 

The authors discuss analytical methods for lipidomics.

Accelerated Discovery and Quantitation of Lipids in Complex Extracts

Hydrophilic interaction chromatography (HILIC) is a unique mode of chromatography in which polar compounds are well retained and resolved using mobile phases containing high concentrations of organic solvent. Because many drug metabolites are polar, quantification using reversed-phase liquid chromatography (LC) can be compromised by poor retention and the resulting ion suppression with mass spectrometry (MS) detection. HILIC provides good retention of polar metabolites outside the suppression region and thus allows sensitive and accurate quantification. This combination of retention of polar compounds and high organic in the mobile phase makes this mode of chromatography uniquely suited to high sensitivity, quantitative bioanalytical LC–MS-MS applications.  

Despite these advantages, the use of HILIC mode separations has grown relatively slowly since its inception over a decade ago. Several possible explanations for the slow acceptance and implementation of HILIC methods include the perception that HILIC methods lack robustness. This misperception may stem from the use of conditions common in reversed-phase LC with HILIC methods. For example, the use of an acid such as formic acid to control pH is common in reversed-phase LC but in general does not provide good performance in the majority of HILIC applications (1). Another possible contributing factor may be inattention to the pronounced effect high acetonitrile concentration has on buffer and analyte p

. This is also commonly overlooked in reversed-phase LC methods but must be considered when using HILIC. When HILIC conditions are chosen carefully, robust methods can be routinely obtained. To provide a framework for HILIC users, a rationally designed, structured approach to HILIC method development is described. The conditions proposed have shown good general purpose performance with a wide variety of compound classes. This approach is specifically targeted for optimizing bioanalytical applications by evaluating analyte selectivity, overall separation performance, and MS signal suppression simultaneously using a variety of robust separation conditions. Optimum conditions can then be chosen based on both separation performance and signal suppression.  

The chromatographic system consisted of an Agilent 1100 series binary pump (Palo Alto, California), on-line solvent degasser, autosampler, and an Applied Biosystems API3000 tandem mass spectrometer with TurboIonSpray ESI interface (Foster City, California). The chromatographic system was controlled using Analyst 1.41 software. 

Chromatographic separations were performed on a 100 mm × 2.0 mm, 3-μm Phenomenex Luna HILIC, column and a 100 mm × 2.0 mm, 3-μm Phenomenex Luna Si (2) column (Torrance, California). 

Heroin, morphine, normorphine, morphine-3-B-glucuronide, codeine, and norcodeine (1 mg/mL in methanol) were obtained from Cerilliant (Round Rock, Texas). Acetonitrile was obtained from Honeywell Burdick and Jackson (Muskegon, Michigan), formic acid from EMD (Gibbstown, New Jersey), and ammonium hydroxide from Fisher Scientific (Pittsburgh, Pennsylvania). Ammonium acetate and ammonium formate were obtained from Sigma Aldrich (St. Louis, Missouri). The ammonium acetate buffer was prepared by dissolving 7.7 g ammonium acetate salt in 1 L of Milli-Q water. Acetic acid (5.4 mL) was added to obtain a pH of 5.8. The ammonium formate buffer was prepared by dissolving 6.3 g ammonium formate salt in 1 L of Milli-Q water. Formic acid (10.4 mL) was added to obtain a pH of 3.2. Neat standards (1000 ng/mL each) were prepared by adding 20 μL of each 1 mg/mL stock solution to 19.9 mL 90:10 acetonitrile–100 mM ammonium formate (pH 3.2). Human plasma disodium EDTA was obtained from Valley Biomedical (Winchester, Virginia). 

Protein precipitation was performed using the following procedure. A 1-mL volume of human plasma was added to 5 mL acetonitrile, vortexed, then centrifuged at 10,000 rpm for 5 min. The supernatant was removed and analyzed without further treatment.  

All separations were performed using the conditions shown in Table I. The initial and final gradient mobile phase compositions were premixed and placed on the "B Channel" and "A Channel" of the binary pump, respectively. Channel B was the high organic or initial mobile phase and consisted of a mixture containing 90:5:5 (v/v/v) acetonitrile, water, and buffer, where buffer is 100 mM ammonium acetate or formate. Channel A was the low organic or final mobile phase and consisted of a mixture containing 50:45:5 (v/v/v) acetonitrile, water, and buffer, where buffer is 100 mM ammonium acetate or formate. All analytes were detected using tandem MS in positive ion mode with the mass transitions and source conditions shown in Table I. 

Table I: Chromatographic and detector conditions			

The primary chromatographic parameters available to adjust retention and selectivity in HILIC are sorbent chemistry, type and concentration of organic modifier, pH, ionic strength, and temperature. The first three are generally the most influential, and therefore only these are varied during method development. The other parameters are generally less influential and can be varied during optimization. The method development strategy employed was to quickly determine if an analyte is a good candidate for HILIC and to get a good approximation of the best separation conditions by using a rationally chosen set of conditions that provide the most information in the least time. These experiments also provide the basis for further optimization. The proposed method development approach utilizes an acetonitrile gradient with three different column chemistries at two buffer pH values. All separations are performed at room temperature. Gradient elution is used because it is the most efficient starting point for method development. The 100 mm × 2.0 mm column format was chosen because it provides good resolving power at flow rates compatible with most MS sources. The buffer pH values chosen span the p

 range of many weak acids and bases and also are available with MS-compatible buffers. Evaluating selectivity and MS suppression using this variety of conditions allows selection of the best overall analysis conditions. 

Three opiate drugs and their metabolites were chosen as probe compounds to illustrate the method development approach. These compounds contain a variety of functionalities as well as a wide range of p

 (7 units) and log P values (2.5 units). The probe compounds are shown in Figure 1 and illustrate the similarities in structure. The primary differences among the majority of the compounds are the addition or subtraction of one or two methyl or acyl groups. The glucuronide metabolite of morphine is the most chemically dissimilar compound, containing a carboxylic acid and a sugar group. Removal of a methyl or acyl group produces an aromatic hydroxy or converts a tertiary amine to a secondary. These changes affect the p

, hydrogen bonding, and hydrophobicity of the compounds, which will affect their retention and selectivity. 

Figure 1: Structure, MRM transitions, and physical properties of the basic test probes heroin, morphine, normorphine, morphine-3-B-glucuronide, codeine, and norcodeine.			

Evaluation of Chromatographic Performance

As shown in Table I, an inverse acetonitrile gradient is used since acetonitrile is the weak solvent and water is the strong solvent in HILIC. The gradient profile includes a 1.7-min isocratic hold at 90% acetonitrile to determine if a compound is weakly retained in HILIC mode. A final 1.7-min isocratic hold at 50% acetonitrile is included to determine if a compound is strongly retained. The gradient portion of the elution profile is the ideal elution region. A compound eluting during the gradient will allow the maximum flexibility in adjusting selectivity. A few general recommendations regarding gradient elution in HILIC mode: three injections per column per set of conditions should be made to test reproducibility and column equilibration. Column equilibration typically requires at least 10 column volumes at 90% acetonitrile, but this varies significantly with column chemistry. Bare silica, for example, requires 15–20 column volumes for equilibration while Luna HILIC requires ~10 column volumes. Complete equilibration generally is not required for routine methods but is required in method development to allow estimation of appropriate isocratic conditions. 

The second parameter varied is column chemistry. The three sorbent chemistries tested were Luna 3-μm HILIC, Luna 3-μm Si (2), and SeQuant ZIC-HILIC 3-μm (zwitterion). These sorbents were chosen because they have been shown to give the largest differences in selectivity. As shown in Figure 2, the Luna HILIC column gives good resolution and peak shape for all compounds at pH 5.8. All compounds are resolved on the zwitterion column but the peak shapes are generally a bit poorer. On the silica column, peaks 2 and 4 and peaks 3 and 5 are coeluted. Analyte coelution can cause ion suppression so it should be avoided. The elution orders between the Luna HILIC and zwitterion columns are the same although the peak spacing is different. On the Luna Si column, the elution order of peaks 3 and 4 is reversed from the other columns. The resolution value for a pair of closely eluted peaks that share a transition is also shown in the figure. Because these compounds share a transition, they must be resolved chromatographically. These chromatograms illustrate the important role sorbent chemistry plays with selectivity in HILIC. 

Figure 2: Effect of sorbent chemistry on retention and selectivity.			

The third parameter varied in method development is buffer pH. The recommended pH values of 3.2 and 5.8 are aqueous pH values. The mobile phase pH is quite different from the aqueous pH due to the effect of organic solvent on buffer component p

 of weak acids increases with increasing organic concentration and the p

 of weak bases decreases with increasing organic concentration (2). Familiarity with these trends is typically sufficient to understand pH effects in HILIC. As shown in Figure 3, pH has a significant effect on the retention and selectivity of many compounds. With the Luna HILIC sorbent, peaks 3 and 4 are resolved with an aqueous buffer pH of 5.8 but are coeluted at pH 3.2. Also, the retention for some compounds decreases while others increase at pH 3.2. With the Luna Si (2) sorbent, significant selectivity changes are observed with pH changes. At pH 3.2, peaks 2 and 4 are resolved and their retention times shifted in opposite directions. These examples demonstrate that buffer pH is an important tool for manipulating the retention and selectivity of ionizable compounds in HILIC. 

Figure 3: Effect of pH on selectivity and retention.			

Once the three primary parameters (sorbent chemistry, percent organic, and buffer pH) have been explored, the selectivity results can be evaluated. The best results obtained with each column are compared and, as shown in Figure 4, all columns give acceptable chromatographic performance. The next consideration in method development is matrix effects. 

Figure 4: Optimum chromatographic performance obtained with each sorbent.			

The experiments to assess matrix effects can be run along with the selectivity experiments to maximize productivity. This allows evaluation of matrix effects at different pH values on each sorbent. The approach used is similar to that described by others (3). A syringe pump is used to infuse a standard solution containing all analytes of interest into the column effluent through a tee just before the MS source. This infusion experiment sets up a high, stable background signal on all analyte transitions. An extracted blank sample of protein-precipitated plasma is then injected and eluted from the column. Any changes in the analyte signals during elution indicate possible matrix effects. This approach allows for a qualititative, visual assessment of matrix effects. The profiles for the three columns tested at pH 3.2 are shown in Figure 5, and significant column-to-column differences are apparent. This result further reinforces the importance of testing several sorbents during bioanalytical method development and that matrix effects are highly compound specific. Any changes in analyte signal coming from changes in mobile phase composition are reproducible and will not affect quantitative performance. While not shown here, mobile phase pH can also have a major effect on ion suppression and should be evaluated. A useful way to combine the selectivity and suppression data is to overlay the selectivity standard and the suppression chromatograms at the same pH. The Luna HILIC column showed its best selectivity at pH 5.8, so these chromatograms are overlaid. As shown in Figure 6, the suppression early in the chromatogram doesn't directly interfere with any analyte but some robustness testing should be performed to ensure that analyte retention times and the suppression region do not change with minor changes in conditions. No significant matrix effects are apparent for the other analytes since there is no overlap between suppression or enhancement with the retention time of the analytes. This testing is designed to give a qualitative overall picture of matrix effects and to determine if the analytes are eluted near or within affected regions. After promising conditions have been identified, further quantitative testing of matrix effects should be performed. 

Figure 5: MS matrix effects profiles for each chromatographic sorbent with protein precipitated blank human plasma.			

This research shows the utility of a rationally designed, structured approach to HILIC method development. The conditions outlined have shown good general purpose performance with a wide variety of compound classes. This approach is specifically targeted for optimizing bioanalytical applications by evaluating analyte selectivity, overall separation performance, and MS signal suppression simultaneously using a variety of robust separation conditions. Optimum overall conditions can then be chosen based on both separation performance and matrix effects. 

Figure 6: Comparison of chromatographic performance and matrix effects.			

 are with Phenomenex, Inc., Torrance, California. 

(3) R. King, R. Bonfiglio, C. Fernandez-Metzler, C. Miller-Stein, and T. Olah, 

A structured, general purpose approach to method development for bioanalytical hydrophilic interaction chromatography–tandem mass spectrometry (HILIC–MS-MS) applications is described.

Structured Approach to Method Development for Bioanalytical HILIC–MS-MS Applications

For many years, and after several notable failures, many researchers were convinced that it was impossible to design a quadrupole time-of-flight (qTOF) mass spectrometer that was able to retain its ability to perform the high resolution measurements necessary for definitive molecular formula determination of unknowns. Conventional wisdom indicated that there were many reasons (such as temperature stability, ion diffusion, and ion loss on grids of reflectrons) that would make it impossible to improve resolution of these types of instruments. Figure 1 shows the internal layout of a TOF instrument designed to overcome the limitations of mass spectrometry (MS) with fast chromatography. The diagram shows improvements such as the inclusion of an ion chiller, the use of a series of ion refocusing operations, the presence of a single reflectron to minimize ion losses, and temperature control of the instrument's overall flight tube to minimize diffusion of ions. 

Figure 1: Schematic of the internal design of the maXis UHR-TOF mass spectrometer (Bruker Daltonics).			

Initial reports of the instrument's performance in both MS and MS-MS mode indicate that it is able to maintain resolution beyond 40,000 at speeds of up to 20 Hz. The mass accuracy is reported to be < 1 ppm. The mass range is 50–20,000 

 It is designed to provide a dynamic range of nearly five orders of magnitude dynamic range.  

The following section describes a series of experiments for small molecule and protein analysis that were designed to test MS performance.  

MS with Fast Chromatography and Small Molecules

A series of five unrelated drug compounds were chromatographed using a reversed-phase column and a 30-s elution gradient. The results of the initial studies are presented in Figure 2. As can be seen, the method was able to achieve baseline separation of the five compounds in 30 s. In addition, the peak widths, when measured at half height, were all less than 1 s. 

Figure 2: Separation and measurement of drug compounds with fast chromatography. Peaks:  1 - norharmane, 2 - sulfamethazine, 3 - sulfamethazole, 4 - oxybutynin, 5 - terfenadine.			

Figure 3 is a closer examination of the fourth peak in the compound series, oxybutynin. The left half of the figure shows the extracted ion chromatogram showing that more than 20 data points were collected fora 1-s peak. This leads to the high levels of both mass accuracy (0.8 ppm) and resolution (> 40,000) shown in the right half of the figure. Other peaks showed similar results. 

Figure 3: Close examination of a single fast chromatography peak.			

As many groups are focusing more and more on protein and peptide analysis, effective analysis of intact proteins has become increasingly important. Figure 4 illustrates the data obtained when measuring a sample of intact IgG antibody. 

Figure 4: MS measurement of intact IgG.			

The data shown here indicate that with intact proteins as large as IgG (148 kDa), high resolution data can be obtained to further analyze large, commercially important molecules that generate high 

 species, such as antibodies. With this resolution, it becomes possible to directly analyze the glycoforms of intact proteins such as IgG (Figure 5). 

Figure 5: MS analysis of the glycoforms of intact IgG.			

This study yielded high resolution data for intact proteins and specific information about the minute differences in proteins found in different glycosylation patterns. The high resolution capability demonstrated here would be extremely useful for rapid profiling of a series of proteins or peptides in a biotherapeutics environment, for instance. 

Today's analytical chemistry environment demands the deployment of more sophisticated methods and instrumentation to keep pace with the profound changes in separation techniques being adopted by many laboratories. Two of the most important tools for the future will be fast chromatography and mass spectrometry. 

is Marketing Manager, Bruker Daltonics, Billerica, Massachusetts. 

The author discusses the use of high-performance mass spectrometry for small molecule and protein applications.

High Performance Mass Spectrometry for Small Molecule and Protein Applications

Consider the mass spectrum of hexacosane shown in Figure 1. It is easy to understand that the peaks separated sequentially by 14 

 units represent ions formed by the loss of successively larger alkyl radicals of the form C

 from different molecular ions. Different molecular ions fragment with the loss of different-sized radicals to produce correspondingly different-sized fragment ions. Clusters of peaks with lower intensities are observed near the peak representing each of these fragment ions. Careful examination of the spectrum reveals that each of the peaks representing fragment ions (which are primary carbenium ions) in the mass spectrum (at odd 

 unit higher, which is the carbon-13 isotope peak. Moreover, as the 

 value of the fragment ion decreases, peaks one, two, and in some cases three or four 

 units less begin to become obvious (see Figures 2 and 3 for an expanded view of the spectrum). 

 values of these primary carbenium ions become smaller, the intensities of adjacent peaks representing the ions at lower 

 values become greater relative to the intensity of the principal peak representing the primary carbenium ion. Also, the intensity of the peaks representing these primary carbenium ions at lower 

 values increases. It has been shown that the ion current for all the primary carbenium ions with an 

 is the total number of carbon atoms) is due only to fragmentation of molecular ions (1). The ion current for all the primary carbenium ions with an 

 is due to secondary fragmentation of the higher-mass fragment ions as well as fragmentation of molecular ions. Evidence for this is available from tandem mass spectrometry (MS-MS) studies such as the results shown in Figure 4. For example, some of the ion current at 

 57 results from the loss of a molecule of ethene (H

 85, a hexyl ion. Some of the ion current at 

 43 is a result of the loss of a molecule of propene (H

) from other primary carbenium ions with 

 85, these same hexyl ions. These other primary carbenium ions with 

 69 (not seen in the product-ion mass spectrum shown in Figure 4). Some of the ion current at 

 69 does result from the loss of a molecule of hydrogen from the primary carbenium ion with 

 71; however, the intensity of the peak at 

 69 cannot be rationalized by this fragmentation alone. Some of these proposed fragmentations of the ion with 

 85 are supported by the product-ion mass spectrum of 

 85 shown in Figure 4. Most of the ion current at one 

 unit less than that of the primary carbenium ion with 

 43 is the result of the loss of a hydrogen radical from the primary carbenium ion. 

The cluster of peaks immediately preceding a peak that represents a primary carbenium ion often are said to be signature peaks representing an alkyl ion as opposed to an acylium ion, which would have the same integer 

 both have a nominal mass of 57 Da). The presence of these peaks usually indicates that the ion is an aliphatic ion or that aliphatic ions are present in the mass spectrum. The absence of these peaks does not necessarily indicate that the 

 value peak represents an ion other than an aliphatic ion (such as an acylium ion RC≡O

The above etiological diatribe regarding the meaning of some of the peaks in the mass spectrum of a straight-chain aliphatic hydrocarbon should be helpful in understanding how to extract structural information from a mass spectrum of an unknown compound. 

In the evaluation of an electron ionization (EI) mass spectrum, the first step involves determining whether an M

 peak is determined, the nitrogen rule must be applied to determine if the unknown contains an odd number of nitrogen atoms. 

The next step should be to try to identify any odd-electron (OE

) fragment-ion peaks that may be in the mass spectrum. These peaks will be nonisotope peaks at even 

 values in the mass spectrum where the odd-electron fragment ion does not contain an odd number of nitrogen atoms. 

The presence of more than one odd-electron fragment-ion peak may indicate more than one set of γ hydrogens. Often an OE

 fragment ion will be formed by the expulsion of a molecule from the molecular ion, and this odd-electron ion will then lose a molecule to form another odd-electron ion. The presence of these odd-electron ion peaks also indicates that the analyte has nonhalogen heteroatoms present. If one of these odd-electron ion peaks has an 

 value of 58, there is a good probability that the analyte is an aliphatic ketone. A peak at 

 58 is considered to be diagnostic for aliphatic ketones. 

The next step is to determine which peaks in the mass spectrum represent logical losses from the molecular ion. A peak at [M – 15]

 indicates that there is a methyl group present on the analyte and that it is a special methyl such as that found in a methyl ketone. Peaks at [M – 29]

 values that represent ions that have masses of multiples of 14 

[14] + 1), can represent losses of larger carbonyl or aliphatic radicals (such as C

 ion formed by heterolytic cleavage of the molecular ion of an aliphatic ketone with a C

 chain on one side of the carbonyl or the heterolytic loss of CO from an acylium ion with 

 127 formed by homolytic cleavage with the loss of the moiety on the other side of another molecular ion of the same compound. This peak could also represent an ion formed by γ cleavage from molecular ions of the same aliphatic ketone where the carbonyl is in the number four position (Figure 5) (2). 

The authors discuss the use of electron ionization to determine a compound's structure.

Special Issues-05-01-2009 | LCGC Supplements

Using High-Resolution LC–MS to Analyze Complex Sample

The Role of Triple Quadrupole GC–MS in Steroid Analysis

Accelerated Discovery and Quantitation of Lipids in Complex Extracts

Structured Approach to Method Development for Bioanalytical HILIC–MS-MS Applications

High Performance Mass Spectrometry for Small Molecule and Protein Applications

Anatomy of an Ion's Fragmentation After Electron Ionization, Part I

From the Editor