Three-dimensional enhanced lipidomics analysis combining UPLC, differential ion mobility spectrometry, and mass spectrometric separation strategies.

identify Abstract Phospholipids serve as central structural components in cellular membranes and as potent mediators in nu-merous signaling pathways. There are six main classes of naturally occurring phospholipids distinguished by their distinct polar head groups that contain many unique molecular species with distinct fatty acid composition. Phospholipid molecular species are often expressed as isobaric species that are denoted by the phospholipid class and the total number of carbon atoms and formation-dependent MRM, multiple reaction neutral loss PA, phos- phatidic phosphatidylcholine; phosphatidylethanolamine; PG, phosphatidylglycerol; phosphatidylinositol; ion phosphatidylserine; of (cid:2) and to isolate

clustering with added volatile molecules (termed modifiers), which are related to the chemical environment surrounding the molecule's charge site ( 24,25 ). DMS was used with and without LC separation to select ionized membrane phospholipid classes prior to mass analysis by a hybrid quadrupole-linear ion trap mass spectrometer. The strengths and weaknesses of different analytical strategies are compared, and the effects DMS contributes to the analysis are discussed. This additional degree of freedom provided by DMS in the analysis of lipids enables "clean" product ion spectra by eliminating interclass isobaric interference during precursor ion selection and dramatically improves the quality of acquired lipidomic data.

Chemicals
Methylene chloride, methanol, n -propanol, acetonitrile, and isopropanol (HPLC grade or better) were obtained from Thermo Fisher Scientifi c (Pittsburgh, PA). Ammonium acetate and human serum were obtained from Sigma Chemical Co.

Sample preparation
Purifi ed phospholipid extract stock was prepared by mixing the individual phospholipid classes to a fi nal concentration of 10 µg/ ml each in methanol-methylene chloride (50:50; v/v) containing 5 mM ammonium acetate. For LC and DMS analysis, the stock was further diluted to 1 µg/ml in appropriate analysis buffer. Pooled human serum was extracted using the method of Bligh and Dyer ( 26 ). Dried lipid extracts were redissolved in the same solvent as the purifi ed lipid extracts. For HPLC ESI-MS/MS analysis of lipids, samples were dissolved in 100% HPLC solvent A.

ESI-MS/MS analyses
Lipid samples were analyzed using a QTRAP ® 6500 LC/MS/ MS system (AB SCIEX, Redwood Shores, CA), which is a hybrid quadrupole-linear ion trap mass spectrometer. Source parameters (e.g., temperatures, gas fl ows, etc.) were optimized using a mixture of phospholipid standards that were tee-infused with a syringe pump into the fl ow of an Acquity UPLC (ultra performance liquid chromatography) system (Waters, Milford, MA) delivering the sample at a fi nal fl ow rate of 500 µl/min. Nontargeted analysis was carried out using the enhanced MS (EMS) mode, which uses the linear ion trap functionality of the instrument to perform the equivalent of an MS scan with higher resolution and better sensitivity. In other experiments, semitargeted scans were used to focus on the different phospholipid classes including precursor ion scan (PIS) and neutral loss scan (NLS ) modes (i.e., "shotgun" lipidomics). For phospholipid analyses, different scan modes and ion polarities were used to monitor all six classes optimally in a multiplexed fashion: PC, PIS m/z 184 Da (+); PE, NLS individual lipids in cells ( 10 ) and plasma ( 11 ) and to quantify molecular species relevant to health and disease ( 12 ).
The evolution of lipidomics has closely coincided with the development of new technology, which has allowed for this complex array of molecules to be mined at the category, class, and molecular species levels. For example, early lipid studies relied on basic chromatographic techniques including TLC, HPLC, and GC to characterize the categories and classes of lipids in biological extracts ( 13,14 ). Unfortunately, detailed analyses of fatty acid composition of complex lipids were limited to percentage composition, and the separation process itself often resulted in alteration of the lipid profi le ( 15 ). As the analytical techniques used for lipidomics have improved, the staggering complexity of the lipidome has emerged ( 16,17 ). Although the actual number of structurally distinct lipids is not known, there may be hundreds of thousands of different lipid molecular species in a given biological extract, all found in a narrow mass range ( ‫ف‬ 700 Da). This all but ensures isobaric interferences (i.e., multiple species will present as ions with the same integer m/z value) to be the rule rather than the exception. This complex mix of isobars and structural isomers presents signifi cant diffi culties in data acquisition and analysis.
The development of two analytical techniques has attempted to address the challenges of isobaric/isomeric lipid populations: 1 ) HPLC separation and 2 ) high-resolution, accurate mass MS. However, these techniques have their own inherent analytical problems. Considering the diversity of lipid chemical structures, it has proved impossible to develop LC methods that effectively resolve all lipid categories, classes, and molecular species in a single run, and the time required to develop LC methods is not trivial. High-resolution MS offers the impressive ability to resolve lipids far beyond the capabilities of a triple quadrupole instrument ( 18 ), but there are many different lipid species that are iso-elemental and cannot be resolved by high-resolution MS alone. Additionally, no instrument currently available provides high-resolution isolation of target precursor ions. As a consequence, multiple nearisobaric precursor ions are selected for subsequent MS/ MS analysis, which makes accurate interpretation of product ion spectra very diffi cult, especially for low-abundant species. What has been lacking in the fi eld of lipidomics is an orthogonal means of selection that does not necessarily require extensive chromatographic separation or MS with high resolving power or mass accuracy to separate and clearly identify individual lipid molecular species.
Herein we report the use of differential mobility spectrometry (DMS) to enable accurate lipid molecular species identifi cation and quantitation ( 19,20 ). To date, several examples of DMS separation power have been applied to mixtures of tautomers ( 21 ), stereoisomers ( 22 ), and structural isomers ( 23 ); however, this is the fi rst report to apply the technique to lipid profi ling. DMS separates ions based on differences in their mobilities during the high-and lowfi eld portions of an applied asymmetric waveform ( 24 ). DMS can also separate ions based on chemical effects such as differences in the ions' dipole moments and the ions phospholipid classes were separated by ramping the compensation voltage (COV). The COV is a direct current voltage that stabilizes the path of selected molecules through the DMS cell. The molecular ions were recorded by EMS scan with a duty cycle of 0.15 s.

Infusion-DMS method
The mass spectrometer was equipped with SelexION TM DMS technology. The DMS-based experiments were carried out using 1.5% 1-propanol as the DMS chemical modifi er. Operating conditions were optimized using fl ow injection of lipid extract mixture and were determined as follows: DMS cell temperature = 150°C, chemical modifi er = 1-propanol, separation voltage (SV) = 4,000 V (+) or 3,750 ( Ϫ ), DMS offset = 3.0 V, and nitrogen resolving gas = 37 psi. The lipids were dissolved in methanol-methylene chloride (50:50; v/v) containing 5 mM ammonium acetate and infused at a rate of 10 l per minute for 4 min. The individual  ( Fig. 1B ) was developed based on the traditional shotgun lipidomic methodology to identify lipid classes based on specifi c precursor fragment ions and neutral losses associated with the different lipid classes.
The top panel of Fig. 1 shows HILIC chromatographic separation and mass spectrometric detection of phospholipid classes in a standard mixture of purifi ed phospholipids (left) or human serum (right) by either PISs for m/z 184, 241, and 264 or NLSs for m/z 141, 172, 185, and 98, which collectively correspond to PC, PI, and Cer and PE, PG, PS, and PA, respectively, in the positive ion mode. The middle set of panels shows the results for the phospholipid class PE using an NLS of 141 Da in the positive ion mode.
The bottom set of panels shows the extracted spectrum for PE and LPE for the standard mixture (left) and human serum (right), with a magnifi ed view of a subset of individual PE lipids within all detectable molecular species.

DMS MS
To assess the ability of DMS to resolve lipid classes within a complex lipid mixture, a phospholipid lipid standard mixture was infused and resolved by DMS and analyzed by EMS in the positive ion mode ( Fig. 2A ) and the negative ion mode ( Fig. 2B ). Ramping the COV during an EMS experiment resulted in the separation of lipids by class that can be visualized by extracting the spectrum at the appropriate COV value that is specifi c for each phospholipid class and Cer ( Fig. 2C, D ). Supplementary Table I shows the optimal COV values for each phospholipid class, as determined using lipid standards. These data show that DMS is capable of resolving a mixture of lipid standards; however, the demonstration of effective resolution using a complex lipid extract is needed to establish the technique for biologically derived samples with complex matrices. Figure 2E-H demonstrates the resolving power of DMS on human serum lipid extracts. Like the defi ned standard samples, DMS resolves the phospholipid and sphingolipid classes in human serum extract, demonstrating the resolution power of DMS even in samples with complex matrices. The resolution is dependent on the polarity of the experiment, with better separation between phospholipid classes achieved in the negative ion mode, whereas the positive ion mode is better suited for the separation of the lipid classes Cer, SM, and PC.
The addition of the DMS to the HILIC LC/MS separation strategy shows improved sensitivity and selectivity for some of the phospholipids as evidenced in the improved signal-to-noise ratio in the HILIC chromatograms ( Fig. 3A , B ). While the overall multiple reaction monitoring (MRM) signal levels decreased upon application of the DMS to this workfl ow, the ultimate outcome is the reduction of chemical The gradient ran from 0% to 9% B for 6 min, increasing to 30% for 5.5 min. After each chromatographic run, the LC column was reequilibrated prior to the next injection.

LC method II: RP-UPLC
Chromatography was performed with an Acquity UPLC system operating at a fl ow rate of 0.3 ml/min, a column oven temperature maintained at 40°C, an autosampler maintained at 4°C, and 10 µl sample injections. A CSH C18 column (1.7 um, 2.1 mm × 100 mm) (Waters Corporation) was used using a binary solvent gradient consisting of water-acetonitrile (60:40; v/v) with 10 mM ammonium acetate (buffer A) and isopropanol-acetonitrile (50:50; v/v) with 10 mM ammonium acetate (buffer B). An isocratic gradient was run at 30% B for 9 min. After each chromatographic run, the LC column was reequilibrated prior to the next injection.

LC-DMS method
For the LC-DMS experiments, the analytes within each lipid class were monitored using EMS scans with predetermined optimal COV settings. The COV values were optimized for each phospholipid class during infusion-DMS by ramping the COV at increments of 0.1 V once the other parameters were set (e.g., COV for PC in positive mode is 0.3V). The optimal COV values for the 14 phospholipid classes are listed in supplementary Table I. To generate a total ion current (TIC), the MS experiment consisted of 14 EMS scans using the optimal COV values. Each duty cycle was 1.9 s, and the EMS scans were repeated over the 10 min chromatography period. For information-dependent acquisition (IDA) experiments, the analytes within each lipid class were monitored using their optimal scan types [e.g., (+) NLS 141 for PE] with predetermined COV settings.

HILIC-UPLC MS
The resolution of lipids prior to MS analysis minimizes the isobaric interference among different lipid categories and classes. Because the MS/MS spectra for lipids are information poor (as compared with the information-rich spectra obtained from product ion analysis of peptides), it is diffi cult to identify lipids in a complex mixture qualitatively without some type of separation. HPLC has long been the preferred method to resolve lipid molecular species. Thus, initial experiments were aimed at establishing a baseline set of results to demonstrate the ability of UPLC-ESI-MS/MS to resolve and identify phospholipids and Cers ( Fig. 1 ) and to provide a data set that can be used to compare the separation effi cacy of conventional LC methods with the performance of the DMS. Using LC method I, phospholipid classes and Cer were separated with good resolution. The MS method used to analyze the lipid mixture in untargeted discovery experiments such as data-dependent and data-independent acquisitions ( 27,28 ).
In order to determine whether the application of DMS causes any loss of detectable lipid species or leads to any changes in phospholipid lipid profi les, we compared the mass spectra of serum phospholipids recorded using either HILIC separation alone with those obtained with the combination of HILIC and DMS (supplementary Fig. I). While the mass spectra for several phospholipid classes look very similar, some differences related to relative intensities between molecular species were noted. The cause of this needs to be further investigated, and additional work will be needed to fully evaluate the quantitative potential of DMS.

RP-UPLC and enhancement with DMS
The SelexION TM unit can function equally well either with infusion or with LC-based sample input strategies. Considering the huge diversity of lipid molecular species present in a biological sample, neither strategy alone is suffi cient to resolve isobaric interference during MS analysis. To test the concept of DMS as an orthogonal separation noise levels from endogenous interferences ( 27,28 ); MRMs are traditionally blind to the presence of such closely related species. In biological samples such as serum, there is increased background noise that contributes to a loss in sensitivity and selectivity for HILIC LC/MS. However, by including DMS as a fi lter to reduce background noise, the net sensitivity may be increased as shown in Fig. 3 .

Application of DMS to reduce background interference
Initial experiments to evaluate the use of DMS and UPLC together focused on reducing the general noise level in the spectrum obtained during PIS and NLS analyses. Appropriate precursor ion and neutral loss experiments were combined in a single MS experiment, and human serum extract was resolved using LC method I. Figure 3A shows the TIC in the positive and negative ion modes using LC-MS alone. When the same experiment was performed using the DMS, there was a dramatic reduction in background noise ( Fig. 3B ). These results suggest that concomitant product ion analysis could be greatly improved using DMS in addition to LC by the reduction of interfering isobars, especially can improve the quality of product ion spectra generated during an IDA discovery experiment, human serum extract was separated using LC method II, and lipids were analyzed by MS without DMS ( Fig. 5A ) and with DMS ( Fig. 5B ). For the IDA experiment, the survey scan was set to a neutral loss of 141 Da ( Fig. 5 , top panel), wherein eluting PE molecular species triggered a product ion scan. Although the survey scan is specifi c for PE, when the instrument switches to MS/MS mode, any molecule with the same nominal mass will fragment and appear in the product ion spectrum. By setting the DMS to a COV value specifi c for PE, only PE will pass through the DMS, effectively improving the clarity of the product ion spectrum. Figure 5A , top panel shows the survey scan using the semitargeted NLS 141 Da experiment specifi c for PE without DMS. The LC strategy used a RP column, so PE molecular species elute from the column based on their acyl chain lengths. Figure 5A (middle panel) shows the extracted ion chromatogram for m/z 744.5 from the NLS 141 Da (+), which is the appropriate mass for PE (36:2). In the absence of DMS, the RP-UPLC separation based on hydrophobicity is incomplete and cannot be further resolved. The eventtriggered MS/MS scan results in a mass spectrum that indicates the presence of interfering molecules, presumably derived from other chromatographically overlapping lipid categories. Figure 5A (bottom panel) shows multiple fragments associated with fatty acids (i.e., m/z 255, palmitic acid; m/z 281, oleic acid; m/z 279, linoleic acid; m/z 283, stearic acid; and m/z 307, eicosadienoic acid). Thus, the mass spectrum shows a fragmentation pattern that does not allow unequivocal identifi cation of the molecular species and undermines accuracy in quantitation. However, the application of DMS to the chromatographically resolved sample maintains the specifi city of the semitargeted scan during MS/MS that is defi ned by the COV. As shown in Fig. 5B , bottom panel, when DMS is used with a COV specifi c for PE (COV = Ϫ 4.2), only two fatty acid peaks are observed, stearic acid (18:0) and linoleic acid (18:2), as well as fragment for LPE (18:0). Note, the MS/MS spectra were acquired in the negative ion mode versus the survey scan (i.e., NLS 141), which was run in the positive ion mode. During the IDA run, masses are adjusted to refl ect different polarities; thus, in the middle panels, the extracted ion chromatograms (XICs) refl ect the positive ion mass ( m/z 744.5), and in the bottom panels, the product ion spectra were acquired from the appropriate negative ion mass, m/z 742.4. Thus, the product ion spectrum is clarifi ed, and the fragment ions fully support the identifi cation of the molecule as PE (18:0/18:2) and can be used to accurately quantitate the molecule.

DISCUSSION
A major diffi culty encountered in the analysis of lipids by MS is related to the extensive isobaric or near-isobaric overlap of different lipid molecular species within a sample. For example, at a nominal mass of m/ z 762.4 with a mass tolerance of ± 0.1, there are at least 25 different lipid molecular species, some of which are iso-elemental, meaning strategy to LC resolution, experiments were designed to separate phospholipid mixtures based on the fatty acid composition and fatty acid chain length using reversed phase (RP) chromatography (method II) and concomitantly resolve eluting lipids based on lipid class using DMS ( Fig. 4 ). It was anticipated that combining both methods would increase the resolution of the lipidomics experiment to better identify the nature of individual molecular species in complex biological samples. In the fi rst set of experiments, human serum lipid extracts were analyzed by ESI-MS in the positive and negative polarities using the nonspecifi c EMS scan mode ( Fig. 4A , upper  panels). Because RP chromatography resolves lipids based on their hydrophobicity, which is a quality that is directly related to the fatty acyl chain lengths of each complex lipid, lipids are not resolved by class based on their defi ning polar head groups as is the case with normal phase chromatography. The TIC data in Fig. 4A demonstrate reasonable resolution in a relatively short chromatographic run ( ‫ف‬ 10 min). The bottom panels of Fig. 4A display the mass spectra (0-10 min) for the corresponding TIC panels. Note that there is no class identifi cation among the many peaks in the spectrum. Figure 4B shows data from experiments designed identically to those in Fig. 4A except that the DMS was active and COV values for each lipid class and subclass of interest were used (supplementary Table I) to identify the lipid category and class of lipids eluting from the column.
The TIC panels in Fig. 4B differ from those in Fig. 4A because the DMS only allows certain lipid classes to enter the mass spectrometer, selecting only those lipids with the appropriate COV values. Figure 4B (lower panels) shows the respective extracted spectra for PC, SM, and Cer (positive ion mode) and for PC, PS, and PA (negative ion mode) from human serum extract using COV values specifi c for each lipid class. Because a nonspecifi c scan mode was used (i.e., EMS), the results show the ability of this analytical strategy to separate lipid classes by DMS while concomitantly separating the molecules based on their hydrophobicity by LC. Thus, DMS acts as an orthogonal, mass-independent means of lipid class identifi cation, greatly simplifying interpretation of the mass spectra. Data acquired in the positive ion mode used COV values of +0.3, +2.5, and Ϫ 5.0, specifi c for PC, SM, and Cer, respectively, and in the negative ion mode used COV values of Ϫ 3.0, Ϫ 2.9, and +3.0 to isolate PC, PA, and PI, respectively.

Improved qualitative analysis using DMS
Characterization of lipid molecular species is dependent on clear, high-quality product ion spectra to identify the individual fatty acids esterifi ed to the glycerol backbone of complex lipids. Due to the extensive isobaric overlap of lipid species within the lipidome and the relatively low resolution of precursor ion selection prior to MS/MS (by either triple quadrupole instruments or high resolution instruments), it is commonplace for multiple lipid species sharing the same nominal mass to be isolated for MS/MS analysis even when LC is used. To determine whether DMS Various strategies have been devised to address lipid isobaric interference. The most common method is online separation by HPLC. Using chromatography columns to separate lipids by category, class, and/or fatty acyl chain length greatly simplifi es acquired mass spectra to improve identifi cation and quantitation ( 11 ). However, due to the wide diversity in chemical structures and physical properties among lipids, it is challenging to develop a single HPLC method to resolve all lipids in a complex, biological lipid extract. The introduction of UPLC and the use of tightly packed columns have greatly improved the resolution of complex lipid mixtures. In these studies, UPLC resolved lipids into their respective categories and classes using an HILIC column in a short chromatographic time frame ( Figs. 1 and 3 ), and the use of an RP column resolved the same lipids by their respective they have the same molecular formula but are different chemical species, each with its own biological function. 4 The problem of isobaric and near-isobaric interference is magnifi ed during product ion analysis wherein a precursor ion is selected for fragmentation. The isolation window is much wider than the instrument tolerance (isolation widths vary between instrument types but range between 0.4 and 1.2 amu), so the number of molecules that are funneled to the collision cell can be dramatically higher ( ‫ف‬ 250 3 ). This issue is the fundamental challenge in the identifi cation and quantifi cation of lipids by MS. among all complex lipids, multiple different precursor ions can generate some of the same fatty acid fragments. This not only confounds identifi cation but can signifi cantly affect quantitative rigor due to isobaric MRM transitions. Figure 5 demonstrates that even with reasonable chromatography, lipid isobars from different lipid classes do coelute. The clarity of the product ion spectrum in Fig. 5B obtained using the DMS to isolate PE molecular species makes identifi cation of the molecule straightforward. The PE-specifi c COV setting ensures that only PE molecules enter the MS, and, thus, the issue of low resolution precursor isolation is no longer relevant. The diagnostic fatty acid anions can be directly attributed to a single precursor with a defi ned total number of carbons and double bonds, which enables facile determination of the fatty acid distribution among the positional isobars and simultaneously provides quantitative insight into their relative concentrations. For example, PC 36:2 ( m/z 786.6) may have multiple isomers, including PC (18:1/18:1) or (18:0/18:2); these molecules can be identifi ed in a sample based on the presence of the specifi c fatty acid fragments, and their relative concentrations can be assessed by integrating the area under the peak for these fragments only if interfering isobaric peaks are eliminated from the spectrum. These results demonstrate the power of including DMS in lipid separation strategies: DMS enables facile class identifi cation and, in combination with RP chromatography, which resolves the lipids based on their chain lengths, results in the identifi cation of lipids at the level of molecular species in a single analytical run.
The ability of DMS to resolve lipid mixtures can be applied to shotgun lipidomics via infusion as well. Indeed, one of the major criticisms of the shotgun approach has been the diffi culty to deconvolute the mass spectra at the precursor ion and product ion levels. With DMS, however, lipids can be isolated with category-and class-specifi c COV values (supplementary Table I) prior to MS analysis, thereby greatly reducing the complexity of the sample and analysis. Figure 2 demonstrates the ability of DMS to resolve lipids during an infusion experiment. Although not the central focus of this study, the possibility of DMS to improve shotgun lipidomic analysis is intriguing. The resolution of human serum extract using RP-UPLC in conjunction with DMS demonstrates the orthogonality of the method. RP separation and product ion analysis in the negative ion mode does not allow for class identifi cation. However, concomitantly using lipid class-specifi c COV values enables class identifi cation, fatty acid composition, and baseline noise reduction to improve quantitative rigor by effectively increasing the signal-to-noise ratio of analytes ( Fig. 4 ).
The COV values given in supplementary Table I remain constant over time provided conditions within the DMS cell are not changed. A test of the stability of the COV voltages over an extended time period showed no signifi cant fl uctuation over 4 days (not shown). 5 Another consideration fatty acyl chain lengths ( Figs. 4 and 5 ). These methods provide reasonable resolution, but even with chromatographic separation, lipid isobars still coelute, as demonstrated in Fig.  5A , making qualitative identifi cation problematic. The balance between resolving lipid classes based on the polarity of their head groups versus resolving lipids based on their hydrophobicity contributed by the fatty acyl chains inherently diminishes lipid coverage in a profi ling experiment. An orthogonal approach using DMS to separate lipids by category and class while simultaneously resolving lipids by chromatography offers one solution to this diffi cult problem.
The chromatographic separation of lipid extracts was enhanced with the use of DMS coupled with MS to allow orthogonal separation of components in the analyzed mixtures without a signifi cant increase in the analysis time, yielding a set of more specifi c, less convolved data resulting in confi dent species identifi cation and improved detection of low-level components within a matrix. This new workfl ow adds a new dimension to the collected data and, thus, improves the quality of the results and confi dence in the identifi cation of lipid species.
The ability of DMS to resolve lipid isobars lies in its ability to separate molecules based on their chemical properties ( 24,25,29 ) rather than size and shape alone, factors that are the basis for separation by ion mobility in drift tubes ( 19 ). The length of the DMS cell is short (3 cm) compared with more traditional ion mobility drift tubes, as the resolution lies in the separation of molecules based on their differential mobilities under oscillating high and low electrical fi elds. The chemical effects are enhanced in the presence of chemical modifi ers, such as the 1-propanol used in these studies. Under low electrical fi elds, the chemical modifi er clusters around the ions, affecting their shape, size, and chemical properties, resulting in a specifi c mobility through the cell. Under high electrical fi elds, the modifi er declusters from the ion. Hence, the net effect of the modifi er is enhancement of the differential mobility under the oscillating electrical fi eld ( 25,29 ). This technique differs from traditional ion mobility spectrometry wherein molecules are separated by their crosssectional area, which is related to their shape and size (and hence molecular weight), rather than chemical effects ( 30 ).
The power of DMS to resolve lipid categories and classes is most prominently exemplifi ed during multiplexed NLS analysis ( Fig. 5 ). Triple quadrupole instruments, by the nature of their design and confi guration, are capable of semitargeted scans that isolate specifi c classes of lipids, depending on its specifi c structural motifs. For example, PS can be isolated by looking for neutral losses of 185 Da in the positive ion mode. This transition is specifi c to the loss of the phosphoserine head group, and the resultant spectrum displays only PS molecular species. However, during product ion analysis of precursor ions identifi ed in the NLS, the specifi city is lost, and any molecule with the same nominal mass as the target precursor will fragment and contribute to the product ion spectrum. As a consequence, it can be a challenge to determine which fragments are associated with a specifi c precursor ion. Furthermore, considering that there are a limited number of common fatty acids, and hence a limited number of unique fragments, regarding COV values is the in-source formation of adducts. PA, an anionic lipid, readily forms chloride and acetate adducts. Care should be taken to select a mobile phase or infusion solvent that favors the formation of one adduct, if any, because each adduct has its own unique COV value.
The use of DMS as an independent, orthogonal separation tool during LC ESI-MS/MS analysis of lipids significantly improves lipidomic analyses. Specifi cally, DMS in combination with RP-UPLC enhances the qualitative aspects of lipid analysis by providing an additional separation element that complements the separation physics underlying the hydrophobic interactions of RP chromatography. As exemplifi ed in Fig. 5 , in combination with RP-UPLC, DMS enhances the qualitative aspects of lipid analysis and enables the resolution of isobaric species into individual molecular species that would not be possible with chromatography alone. In this report, we have not addressed the quantitative aspects of DMS but show its resolution potential as a supplementary technique to LC to resolve targets of interest in case of ambiguity. Lipid classes can be readily identifi ed owing to each class having a unique COV value among the two different instrument polarities; the instrument baseline noise is reduced, thereby increasing the signal-to-noise ratio; and the resolution of lipids provided by the column remains unchanged. The cost of additional resolution, as is the case for all mass spectrometric measurement, is a decrease of three to fi ve times in the base sensitivity of the instrument. However, because the chemical noise is reduced, the effects on sensitivity appear to be lipid class-specifi c and must be tested with authentic standards during assay development and validation. Of note, because DMS dramatically reduces background noise interferences, especially when working with biological samples, the overall detection limits generally improve. Overall, DMS signifi cantly enhances the resolution power of lipids compared with HPLC alone. The clarity it provides to qualitative analyses makes DMS an attractive technology to MS-based studies in lipidomics.