Analytical scientists are searching for methods that allow the detection, mapping, and identification of a wide range of molecules in complex biological samples. Ion mobility spectrometry (IMS) separates molecules by their shape and size, offering an additional layer of analysis. The next generation of the technique, known as high performance ion mobility spectrometry (HPIMS), provides the ability to separate isomers faster and with less effort than chromatography‐based methods. Liquid chromatography–mass spectrometry (LC–MS) frequently requires a complex setup and long run times to distinguish isomers. In contrast, ion mobility filters for a set of isomers can be applied on a similar timescale to individual mass spectra acquisition. This article reviews using atmospheric pressure drift tube ion mobility with an HPIMS–MS instrument to separate isomers of eight pairs of metabolites and gangliosides. The data demonstrates the potential benefits of being able to quickly optimize the drift gas composition to selectively maximize the mobility difference for isomer separation.

The study of metabolites and gangliosides is increasingly important in drug discovery (1) and immunology (2). Accurate analysis of biologically relevant isomers is important because their structure affects their molecular properties. Typically, the isomers are separated using chromatography prior to mass spectrometry (MS) analysis. However, specialized chromatographic methods that distinguish isomers frequently require a complex setup and long runs. Techniques that allow accurate results to be acquired quickly and efficiently would be beneficial.

Ion mobility spectrometry (IMS) offers a potential solution. It is faster than liquid chromatography (LC) and requires less effort because it separates molecules by their shape and size without needing complex sample preparation or setup protocols (3–12). Ion mobility filters for a set of isomers can be applied in a similar time frame to MS alone.

Several different IMS systems are available that can be coupled to mass spectrometers. Examples include drift tube ion mobility (DTIMS), (8) traveling wave IMS (TWIMS), (5,6) trapped ion mobility spectrometry (TIMS), differential mobility spectrometry (DMS) (13), and field asymmetric wave form IMS (FAIMS) (9,10).

Most IMS systems are combined with time-of-flight (TOF) mass analyzers. IMS-TOF techniques employ ion mobility at a reduced pressure to satisfy the vacuum regime of the TOF instrument, but the high resolving power of the IMS system is lost.

These hybrid quadrupole mass spectrometers and ion trap MS instruments offer an alternative. These analyzers feature ultrahigh resolution and high mass accuracy, but their longer acquisition times mean that they present challenges when coupling with IMS.

DMS and FAIMS are more compact IMS devices. Both forms of mobility analysis are based on nonlinear IMS and cannot be directly correlated to the collisional cross-section of a molecule (9), which limits their applicability for modeling molecular structures or analyzing conformation states because of the reliance on comparisons between collisional cross-sections.

Clearly, a range of IMS techniques can be coupled with mass analyzers to cover the majority of an analytical workflow. However, the missing component is a compact IMS device that does not sacrifice performance for size and can be coupled with a benchtop mass spectrometer for easy integration into the workflow.

High Performance IMS (HPIMS) Featuring Atmospheric Pressure Drift Tube

High performance ion mobility spectrometry (HPIMS) deploys atmospheric pressure short drift tube technology, enabling it to be coupled as a practical front-end to an MS device without breaking vacuum. High pressure is used to increase the number of ion collisions in a smaller space, boosting performance in a smaller footprint device. It offers a high degree of flexibility for separating isomers and other compounds (14).

This study analyzed eight pairs of samples: a pair of gangliosides, GD1a and GD1b (Biovalley Nanterre), and seven metabolite pairs: corticosterone and 21-deoxycortisol; prednisolone and cortisone; dexamethasone and betamethasone; citric acid and isocitric acid; ursodeoxycholic acid and deoxycholic acid; and etiocholan-3-α-glucuronide and dihydrotestosterone-glucuronide (Sigma Aldrich). All samples were analyzed using an MA3100 Drift Tube High Performance IMS ion mobility spectrometer (Excellims) mounted on a Thermo Scientific Q Exactive Focus hybrid quadrupole Orbitrap MS instrument.

The MA3100 consisted of a 10.55 cm dual-gate linear drift tube operating at atmospheric pressure. It replaced the standard electrospray ionization (ESI) source on the front of most MS instruments (figure 1), enabling quick and easy transitioning between regular and IMS–MS use without breaking the vacuum. The ion mobility stage contained two Bradbury Nielsen-type ion gates that enabled operation in various IMS–MS modes.

Drift gas flow and temperature were under full software control. A manual mixing station consisting of two flow meters was used to apply different drift gases to study the potential improvement in mobility resolution.

A Directspray ESI source (Excellims) was used for ion generation. The ESI voltage ranged from 1400 V to 2400 V and optimized for each compound pair at a sample flow rate of 1.5 µL/min. The inlet gate of the IMS analyzer was pulsed open for 100 µs to start the ion mobility separation. The electric field applied across the mobility analyzer’s 10.55 cm drift region was set to 5530 V, resulting in a field strength of 524 V/cm. The drift gas temperature was controlled at 180 °C for all experiments, and the drift gas flow was set to 2.00–2.75 L/min, depending on the compound. The MS instrument was set to a mass range of 150–2000 

, with mass spectrometer resolution set to 35,000 or 70,000.

For each pair of samples, both instrument polarities were initially tried, with most compounds showing a clear preference for one polarity, typically yielding two to three orders of magnitude more signal than for the opposite polarity. The gangliosides ionized primarily in negative ion mode. For the metabolites, three pairs were found to ionize primarily in positive mode, and three others in negative mode. The prostaglandins showed good intensity in either ionization mode. For positive ion mode, both protonated and sodiated ions were initially considered, and the best species were chosen based on the intensity and separation. For negative ion mode, all experiments were carried out on the deprotonated [M − H]

 ion except for the gangliosides, which showed the highest peaks on the doubly deprotonated species [M − 2H]

. Because drift times for the isomers were initially unknown, the MA3100 was run in scan mode with total acquisition times of 45–300 s, which were dictated by the length of drift time needed to see all ions of interest. This analysis time can be significantly shortened when setting only individual IMS windows to confirm or quantify isomers with previously determined drift times. For each sample, the extracted mass spectra (Thermo Xcalibur 4.0.27.19 Qual Browser) for the relevant masses were overlaid, and the retention time (

) was converted to drift time. A 25 ppm sucrose solution was used for drift time calibration in both polarities to eliminate the influence of changes in atmospheric pressure. Resolving power was calculated as drift time divided by peak width (full width at half maximum).

Initially, all samples were analyzed with air as standard drift gas. If the separation with air was below 50%, carbon dioxide (CO

) was attempted next, followed by mixtures of CO

 and air using the flow meter apparatus described above, with a length of tubing for continuous flow blending. The percentage of CO

 in the air was increased until maximum improvement was achieved. Percentages of gases were determined based on the readings of the flow meters. Residual CO

 traces in the purified air were low enough to be ignored.



Half of the isomer pairs achieved sufficient separation (from 50% to baseline) using air as the drift gas (see figures 2, 3, and 4a).

Changing to a more polar drift gas is expected to affect the drift separation of molecules that could be polarized (15). Because this may impact the mobility of two molecules differently, the net separation can be increased or decreased (or remain unchanged) when introducing a more polar drift gas, which is shown for corticosterone and 21-deoxycortisol in figure 5. Comparing the spectra in 100% air and in a 45:55 mixture of air and CO

-rich drift gas shows longer drift times. More importantly, the minor separation of the two isomers in 100% air increased significantly in the gas mixture, most notably for the protonated species, but the effect is also visible for the sodiated species, which reflects a relatively stronger influence of CO

 on the mobility of one isomer over the other.

The same approach was taken for the remaining isomer pairs. Prednisolone and cortisone increased in separation to 10% in the protonated species and 20% in the sodiated species for 25% CO

. Dexamethasone and betamethasone could be separated 15% in their polymer state ([2M + Na]+, 807.403 

. Although these pairs benefited from a mix with CO

 yielded almost no benefit compared to air. The increased separation of the epimeric isomers by observing the sodiated dimer (as compared to protonated or sodiated monomer) has been shown for many biologically relevant pairs with a variety of drift gases, but until now has not been explored for gas mixtures.

Out of the eight isomer pairs analyzed by high-resolution atmospheric drift tube IMS, only the citric acid and isocitric acid pair remained unresolved, which is not surprising, given the minimal structural change between the two. A secondary peak was observed in CO

, potentially pointing to different tautomers, but again with near identical drift times. The addition of a chemical modifier in the drift gas could be explored in the future (16).

 mixtures were generally not tried if air alone gave good results. GD1a and GD1b were measured in 100% CO

 to study the effect on resolution and separation. Although both molecules had a major change in drift time in CO

, separation was only minimally improved (figure 4a). The resolving powers observed for the doubly charged gangliosides in CO

 were 102 and 87, respectively, yielding a similar average resolving power to pure air.


The results show that high performance ion mobility–orbital trap mass spectrometry (HPIM–OT-MS) is a powerful combination for the separation and analysis of biologically relevant isomers. The resolutions were generally found to exceed 70 and reach as high as 100, enabling the differentiation of comparatively small differences.

Although HPIM–OT-MS was capable of separating half of the isomers using air as drift gas, adding gas mixtures with CO

 increased the number of at least partially separated isomer pairs to seven out of eight.

As neither pumping speed nor gas-specific pressure sensor calibration need to be considered, it is easy to switch between different drift gases, enabling optimization of compound separation based on polarity differences (17). The ability to adjust the gas mixture is more practical with HPIMS-orbital ion trap MS because of the ease of changing the drift gas. Other studies have shown biological epimeric isomers change their separation in different drift gases on a low-pressure DTIMS–MS instrument (18). For the epimeric isomer pair in this study, the increase in separation with gas mixing gives another dimension of the drift gas variable that is not necessarily available at low pressure, where changing the drift gas is a more involved process.

The HPIMS coupled with Thermo’s MS instrument offers other variables that might be useful in studying conformation. It has flexibility in temperature ranges and liquid gas modifiers, such as methanol (19) or propanol (20), can give further separation improvement. Alternatively, gas samples, solids, and swab samples can be introduced via an optional gas inlet or thermal desorber ion source.

In practice, HPIM–OT-MS lends itself to targeted studies, allowing the presence and relative abundance of multiple isomers to be determined through a quick series of mobility windows. Although complete 2D IMS–MS maps typically require acquisition times in minutes, individual confirmatory IM–MS scans can be acquired in a fraction of a second, thus making the application of several IM–MS windows per compound feasible.

HPIM–OT-MS is an interesting alternative for isomer separation compared to complex chromatographic methods or relying solely on MS2 fragmentation, especially for targeted applications. Once the drift time of potentially occurring isomers has been identified using standards, quick application of targeted drift time windows in gated mode enables different isomers to be distinguished.

Compared with multicolumn chromatographic setups, variables including drift gas composition, flow and temperature can be quickly optimized, giving flexibility and experimental convenience.

Employing ion mobility at atmospheric pressure without vacuum enables coupling to high resolution benchtop mass analyzers. The addition of the HPIMS to the mass analyzer, rather than the integration of IMS, allows existing MS users to expand their capability.

Drift gas variation also has potential in the analysis of other biomolecules, for example saccharide isomers. Combined with drift gas temperature variation and the addition of liquid modifiers, HPIMS on the orbital trap MS instrument offers a powerful addition to the toolbox in the investigation of a wide variety of samples (liquid, thermal desorption, or headspace [21]) and applications, including molecular characterization, isomer identification, analysis of protein conformation states, and characterization of complex mixtures like polymers and petrochemical samples (22).

The authors would like to thank Service de Pharmacologie et d’Immunoanalyse and Laboratoire d’Etude du Métabolisme des Médicaments for their contributions to this paper.

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are with Thermo Fisher Scientific. Direct correspondence to: 

Articles

Employing ion mobility at atmospheric pressure without vacuum enables coupling to high-resolution mass analyzers. High performance ion mobility–orbital trap mass spectrometry (HPIM-OT-MS) is a useful alternative for separating isomers, such as isomeric metabolites seen in drug discovery.

Separation of Isomeric Metabolites and Gangliosides with High Performance (Drift Tube) Ion Mobility–Mass Spectrometry 

The widespread wildfires in northern California’s wine country in 2020 posed a multitude of issues for winemakers, even for those whose vineyards were lucky to survive. One of the primary challenges of harvesting a vintage exposed to wildfires is smoke taint, which at high levels can make the taste of a wine akin to an ashtray. Smoke taint is caused by aroma compounds called volatile phenols that are released by burning wood. These odorants are absorbed and stored as nonvolatile glycosylated precursors in grapes, but they may be released during winemaking, resulting in a loss of wine quality. Currently, gas chromatography–mass spectrometry (GC–MS)-based approaches are used to measure volatile phenols with sufficient sensitivity. However, GC–MS suffers from low throughput, which can cause backlogs when there are demand surges, which were experienced in 2020. In this article, solid phase mesh enhanced sorption from headspace (SPMESH) was modified for direct immersion (DI) conditions and coupled to direct analysis in real time–mass spectrometry (DART-MS), creating a new method for analyzing volatile phenols referred to as DI-SPMESH-DART-MS. The DI-SPMESH-DART-MS technique was performed on volatile phenols, including guaiacol (G), a common marker for smoke taint. This approach enabled increased throughput of a sample every 2 min, offering an effective method for rapid screening of volatile phenols.

The wildfires that hit northern California in 2020 caused extensive damage to numerous vineyards; however, in many cases, the vines themselves remained intact. Exposed to smoke for prolonged periods throughout the month of September, the 2020 harvest was written off by winemakers who were unwilling to risk producing wine with a smoky, ashy taint (1). This concern resulted in a major economic hit for an industry struggling to rebuild. Therefore, rapid and reliable methods for detecting compounds associated with smoke taint in unfermented grape juice or newly fermented wines are needed to help winemakers navigate this problem.

Grapes absorb volatile phenols, such as guaiacol (G) and 4-methylguaiacol (4-MG), from burning wood, storing them as nonvolatile glycosylated precursors prior to release during winemaking. Gas chromatography–mass spectrometry (GC–MS) techniques, utilizing solid-phase microextraction (SPME) fibers for phenol extraction, offer sensitive detection for such phenols but run times are in the order of 30–60 min per sample (2,3). This observation is an important limitation—for this application and more generally in the production of seasonal products—when analyses are required quickly and in large numbers, to support decisions around how best to manage the harvest at key points in the year. In 2020, winemakers needed reliable data to decide whether to discard fruit ahead of beginning the winemaking process but analytical demand rapidly outstripped supply as thousands of wineries sought smoke taint analysis via commercial laboratories with limited throughput. Inherently faster analytical techniques are needed to deliver higher throughput and ease this problem.

Direct analysis in real-time mass spectrometry (DART-MS) has a proven track record in the detection of food and drink contaminants (4) and the speed to deliver significant throughput gains to address analytical bottlenecks. However, off-aromas can result from odorants present at levels of just a few parts per billion or even less (5). Effective extraction and preconcentration of the odorants from the juice is therefore critical to capitalize on the inherent capabilities of DART-MS to provide rapid, sensitive detection.

Thin-film microextraction (TFME) coupled to ambient ionization (AI)-MS has already been successfully used to rapidly preconcentrate and quantify trace analytes present in complex matrices (2). TFME devices can be fabricated from adsorbent materials coated on solid substrates or absorbent polydimethylsiloxane (PDMS) mesh sheets—solid phase mesh enhanced sorption from headspace (SPMESH) sheets—with the latter exhibiting better performance for the concentration of volatile headspace compounds (6). Simple to prepare by laser etching, SPMESH sheets enable the simultaneous extraction of volatiles from multiple samples and have been successfully coupled with DART-MS to quantify µg/L to ng/L levels of odorant volatiles such as 3-isobutylmethoxypyrazine (IBMP, “green pepper”), linalool (“floral”), and methyl anthranilate (“Concord purple grape juice”), with speed and efficiency (7).

A direct immersion (DI)-SPMESH technique for the volatile phenols associated with smoke taint was developed and combined with DART-MS to provide a rapid, effective screening solution for assessing grape juice. A pragmatic alternative to the use of multipolymer SPMESH sheets, which are not commercially available, this technique removes any requirement for headspace partitioning and builds on previously reported success using DI for volatile phenols (8,9). Experiments were carried out to determine the selectivity of the resulting DI-SPMESH-DART-MS technique for the target phenols. The results show that this innovative approach offers advantages in regard to both speed and sensitivity compared with a headspace DART-MS technique and could be used to support winemaking decisions.

Developing a TFME Device for High Throughput Phenol Extraction

SPMESH sheets were made from PDMS sheets (Grace Bio-Labs) using laser etching to apply a 0.5 by 0.5 mm mesh pattern (Cornell NanoScale Facility) in accordance with a previously developed method (7). These were baked for 30 min at 250 °C prior to use.

For headspace (HS) extraction, samples were loaded into a 24 deep well plate (VWR), which was then covered with: a Teflon gasket; stainless-steel spacer; SPMESH sheet; second spacer; and stainless-steel top cover. Once secured, the assembly was shaken at 200 rpm at 50 °C for 30 min (C24KC Refrigerated Incubator Shaker).

For DI extraction, the previously described assembly was modified to include a second Teflon gasket between the spacer and top cover and secured using a standard woodworking vice clamp (Grainger). This complete assembly was then inverted and agitated at 200 rpm at 22.5 °C. Post-extraction the SPMESH sheets were rinsed with water to remove interfering analytes prior to DART-MS analysis (see Figure 1).

With both extraction methods SPMESH sheets are soaked in a water:methanol solution to remove residual non-volatiles prior to re-use.

Establishing a DART-MS Method for Fast and Reliable Analysis

In DART-MS, the analyte is volatilized and ionized at the inlet to a mass spectrometer by a heated gas flow, allowing analysis of a wide range of sample types without preparation under ambient conditions in an open environment. Here, the SPMESH sheets were placed on an automated positioning stage and scanned at a rate of 0.5 mm/s. Figure 2 shows a schematic of the standardized voltage and pressure (SVP) ion source used (DART, Ionsense Inc.). The high voltage needle applies an electrical discharge converting the inert gas, in this case helium, into a plasma. Ions and electrons are then filtered out, leaving only longer-lived excited atoms and molecules in the exiting stream. The grid electrode prevents ion-electron recombination and provides electrons for the negative-ion formation while the heater increases the temperature of the exiting gas, thereby promoting the desorption of molecules from the sample surface. The net result is a heated gas stream containing neutral, highly energetic atoms and molecules that interact with the sample to produce ions for analysis in a coupled atmospheric pressure ionization mass spectrometer.


In this study the ion source was coupled to a triple quadrupole mass spectrometer (Finnigan TSQ Discovery Max, Thermo) via an interface (Vapur, IonSense) to maximize ion collection. Tests were carried out using two different ceramic caps—0.5 mm and 2.5 mm—at the outlet of the ion source to control the diameter of the gas stream, and both the ion source and mass spectrometer were operated in negative ion mode. The temperature of the exiting gas was 300 °C.

A range of baseline experiments and scans were carried out to identify precursors and products for each compound of interest and to establish a method for analyte quantitation. These included full scans of DI-SPMESH extractions of 10 mg/L aqueous solutions for each of the individual phenols of interest: guaiacol (G) (>99% purity), 4-methylguaiacol (4-MG) (99% purity) (Acros Organics), 4-ethylphenol (4-EP) (>99% purity, FCC, FG), and 4-ethylguaiacol (4-EG) (>99% purity, FCC, FG) (MilliporeSigma). To assess interferences between the compounds, DI-SPMESH extractions were also performed for 1 mg/L aqueous solutions of each the phenols of interest, for two deuterated internal standards—d4-4-ethylphenol (d4-EP) (> 98% purity, 99% D, Neta Scientific) and d3-guaiacol (d3-G) (>99% D, C/D/N Isotopes, Pointe-Claire)—and for syringol, a component of wood smoke. All measurements were made in triplicate.

A series of tests were carried out to assess the integrity of the TFME device and to progressively optimize the method:

• To determine how watertight each of the two devices were, 5 mL of water was added to every other well (12 out of 24 wells in total). The device was then sealed, inverted, and visually checked for signs of leakage. Crosstalk, which is the extent of leakage of volatiles between the headspace of adjacent wells, was assessed by adding 5 mL of 10 µg/L IBMP in water solution to every other well and carrying out the HS-SPMESH-DART-MS technique as previously described (7).

• The stability of the analytes on the SPMESH sheets were assessed by carrying out HS-SPMESH extractions and leaving the sheets in air at room temperature for varying lengths of time—0, 20, 40 or 60 min—prior to DART-MS analysis.

• Desorption efficiency was assessed by carrying out HS-SPMESH extractions and then analyzing the same sheet by DART-MS three times in succession with no repeat extraction.

• Extraction kinetics were assessed by varying the incubation times used in both HS-SPMESH and DI-SPMESH extractions (six wells). Data were collected at incubation times of 5, 15, 30, 60, and 120 min.

• Sheet rinsing and sample dilution protocols were optimized by assessing the impact of rinse volume by immersing the SPMESH in 0, 1, 2, or 5 mL of water for 30 s following DI extraction of an undiluted spiked sample (standard solution of 4-EP, 4-EG, 4-MG and G (1 mg/L) in white grape juice (Welch’s)). Rinse time was also tested using a 5 mL water volume and a shaking time of 0, 10, 20, and 30 s and repeated with a diluted, spiked samples (1:1 with water).

The developed DI-SPMESH-DART-MS technique was used to measure a range of commercial juice samples including white grape juice (Welch’s) and samples from local vineyards: Cabernet franc (

). Comparative analyses were also carried out using the HS-SPMESH-DART-MS technique.

Limits of detection (LODs) were determined for the DI-SPMESH-DART-MS techniques in water and model juice. Well plates were pretreated with a 1 g/L bovine serum albumin solution to reduce active site binding for all measurements. Accuracy measurements were carried out using real juice samples spiked with target phenols.

Assessing Performance: Demonstrating an Effective High Throughput Technique for Volatile Phenol Detection

The experiments carried out enabled the progressive optimization of the DI-SPMESH-DART-MS method, ultimately resulting in a method with the sensitivity, accuracy, and throughput required to provide value for the application.

The design of the DI-SPMESH device was shown to be superior to that of the preceding HS-SPMESH assembly with respect to leakage and crosstalk. In leakage testing, the DI assembly remained watertight for 2 hr when inverted, whereas the HS design leaked, demonstrating its unsuitability for the DI technique. Crosstalk was an order of magnitude lower in the DI-SPMESH design (Figure 3b) relative to the original HS-SPMESH design which has levels ranging from 0.1 to 0.5% (Figure 3a). These results confirm the suitability of the new TFME device design for full utilization of the well plate and for the parallel extraction of volatiles onto spatially resolved locations on the sheet.

Each of the phenols was observed to form a series of oxygenated adducts of the form [M+nO-H]- (for example, [4-EP+O-H]-). These have potential to give rise to isobaric interferences among the analytes and steps were taken to refine the method for maximum selectivity with optimal 

 values selected for each of the phenols. Analytes were found to be highly stable on the SPMESH (no loss of volatile phenol signal after one hour in air), and the ion source was shown to be highly effective in achieving thermal desorption of the sample. An 80% reduction in signal was observed with each repeat measurement test in desorption studies. Taken together, these results demonstrate the potential utility of the DART-MS technique for extracted phenols.

Initial studies with the HS-SPMESH device showed poor LODs for the target phenols in water and grape juice. Figure 4 shows the impact of longer extraction times and indicates that even after 2 hr, there is little, if any, evidence of a plateau in HS extraction (red line). DI extraction, in contrast, was found to be far more effective (see Figure 4—blue line). After 5 min, signal levels with DI match those achieved with HS after 120 min and equilibrium levels are reached within 60 min at most; the equilibrium signal intensities were far higher than those achieved with HS. These results provide further evidence of the superiority of DI for a high throughput technique.

One final step with respect to optimizing the technique was to address the potential for fouling and associated interference from nonvolatiles associated with the repeated use of SPMESH sheets. No evidence of fouling was observed in the DI-SPMESH experiments. However, in initial experiments with phenol-spiked real juice samples, the volatile phenols proved undetectable, which was a result attributed to the adsorption of sugars, acids, and other juice components onto the surface of the SPMESH and the consequent competitive inhibition of volatile phenol ionization. Figure 5 shows how rinsing removes these polar compounds, thereby improving the signal. Following rinsing for 30 s in 5 mL of water, peaks associated with acid and sugar interference are no longer observed, and signal intensity for all the volatile phenols increases. Diluting the juice sample with water has an even more dramatic effect (see Figure 5b). Using a saturated sodium chloride solution for dilution also increased the signal, which was an effect attributable to the salting out phenomenon associated with this type of TFME device.

Based on these results, the optimized method included a two-fold brine dilution pre-extraction and a 30 s, 5 mL water rinse post-extraction. Table I summarizes the figures of merit for the fully optimized DI-SPMESH-DART-MS method and shows that the LODs for the four phenols in water lie between 0.5 and 1.7 µg/L; in model juice, the corresponding range is 0.9 and 2.8 µg/L. These compare well to quoted thresholds for sensory detection of the phenols which are in the range of 9.5–440 µg/L (4).

Table II summarizes the accuracy data for the method in different cultivars. 4-MG was not included in this analysis because of poor MS selectivity attributable to interferences from other compounds. With 4-EP and 4-EG, acceptable accuracy is observed with all grape cultivars (values in the range 72–137% of expected), but with G, accuracy is cultivar-dependent. Acceptable accuracy is observed with Cabernet franc and Chardonnay but not with Pinot Noir and Lemberger (>300%). G is also observed in unspiked samples of these cultivars, indicating a likely problem with isobaric interferences. Going forward, there is the potential to address this issue using alternative MS technologies (high-resolution MS), thereby expanding the range of cultivars for which the technique could be used.

In terms of throughput, the technique is significantly better than SPME-GC–MS alternatives with the capability to handle 24 samples in 45 min (that is, one sample per 2 min).

The method presented here provides a good example of the potential of DART-MS to provide practical and effective analysis for industrially relevant problems. A valuable technique for detecting volatile phenols associated with smoke taint in grape juice samples was developed by exploiting the inherent speed and flexibility of DART-MS. Using a DI-SPMESH extraction device, phenols can be simultaneously extracted with high spatial resolution to enable the full analysis of all 24 samples in just 45 min, which represents an order of magnitude improvement in throughput relative to established SPME-GC–MS techniques that typically take approximately 60 min for a single sample.

The limits of detection of the developed DI-SPMESH-DART-MS technique are in the low µg/L, below the sensory thresholds for the phenols of interest and good accuracy levels were achieved with multiple wine cultivars for the majority of the target phenols. These results suggest that the technique has considerable promise as a complement to GC–MS methods for rapid grape juice screening at periods of high demand. Specifically, commercial laboratories could use DART-MS as an initial high-throughput screening approach during periods of high demand, with GC–MS used for confirmatory analyses.

The figures and data were originally published in a paper in 

Journal of Agricultural and Food Chemistry

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are with Cornell University in Ithaca, New York. 

 is with IonSense in Saugus, Massachusetts. Direct correspondence to: 

Measuring volatile phenols in wine is essential in ensuring superior wine quality. A new analytical technique, called solid-phase mesh-enhanced sorption from headspace (SPMESH), was modified with direct immersion (DI) conditions and coupled to direct analysis in real time–mass spectrometry (DART–MS) to be used to detect smoke taint in winemaking.

Quantifying Smoke Taint in California Wines by Immersive Sorbent Sheet Extraction Prior to Direct Analysis in Real-Time Mass Spectrometry (DART-MS)

Household dust is an important indicator of chemical exposure. Humans are regularly exposed to a wide variety of harmful substances in dust, such as pesticides, flame-retardants, and persistent organic pollutants (POPs). The occurrence of POPs in homes is potentially high because of the presence of harmful chemicals in household goods, such as carpet, furniture, paint, textiles, and electronic devices. Unfortunately, the characterization of pollutants in dust samples is complicated because of component chemical diversity and trace concentrations in this complex matrix. Many POPs are present in different forms (congeners, structural isomers, and stereoisomers). For example, there are 209 possible congeners for polychlorinated biphenyls. Furthermore, analysis by conventional gas chromatography–mass spectrometry (GC–MS) is hampered by overlapping chromatographic peaks and isobaric interferences. In this study, we implemented the use of high resolution time-of-flight mass spectrometry (HR-TOF-MS) with a novel multimode ionization source together with enhanced chromatographic resolution to successfully detect and identify pollutants in household dust samples. The implementation of this methodology resulted in the identification of a variety of POPs including PCBs, PBDEs, and pesticides in the dust.

Individuals spend a good portion of their lives indoors and are regularly exposed to a variety of harmful substances. Hazardous chemicals are ubiquitous, and chronic exposure via inhalation, dermal uptake, or ingestion can be detrimental to human health.The sources of pollutants in homes and places of employment include, but are not limited to, textiles, electronic devices, and building materials. Dust is a repository of a wide array of substances; therefore, it is an important indicator of chronic chemical exposure (1). 

Unfortunately, analyzing dust samples is challenging because of the enormous number of chemical constituents, variety of chemical classes with different physiochemical properties, and wide concentration ranges. Analysis by conventional gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) techniques is hampered by overlapping chromatographic peaks and potential isobaric interferences in their mass spectra. Researchers have attempted to circumvent these problems by combining different instrumental techniques for analyzing targeted compounds in complex dust samples (2–4). More recent untargeted approaches have been conducted through multi-institutional collaborations and the utilization of numerous analytical techniques (5).

The focus of this study was to develop a methodology for the untargeted characterization of compounds in a dust standard reference material (SRM), office dust, and household dust. The instrumental technique used for the analysis combined comprehensive two-dimensional gas chromatography and high resolution time-of-flight mass spectrometry (GCxGC-HR-TOF-MS) using a novel ion source. The enhanced chromatographic resolution of GCxGC minimized coelutions, and isobaric interferences were reduced because of the high resolving power of the mass spectrometer. The technology resulted in data with exceptional peak alignment between ionization modes, better signal to noise (S/N), and an increase in the total number of compounds identified. Electron ionization (EI) data were utilized to identify compounds through spectral similarity searches of large databases and formula determinations for molecular, adduct, and fragment ions. Positive chemical ionization (PCI) and electron capture negative ionization (ECNI) spectra provided complementary molecular formula information to increase confidence in compound identification. Advanced software tools allowed for both untargeted data processing as well as retrospective targeted analysis of the comprehensive data. Instrument software afforded complete control over the autosampler, chromatograph, and mass spectrometer, in addition to automated instrument optimization for a seamless transition between the three ionization modes.

Office and house dust samples were obtained from vacuum cleaner bags used over multiple weeks at a local home and place of business. A National Institute of Standards and Technology (NIST) SRM 2585 was purchased directly from the NIST website and used for method development (6).

Dust samples were weighed (0.14 ± 0.01g) and transferred to 10 mL glass centrifuge tubes. Then, 3 mL of extraction solvent (3:1 dichloromethane/hexane) were added, and the tube was capped. The heterogeneous mixture was vortexed for 10 s and then extracted for 20 min via sonication. The supernatant was removed, and the residue was extracted again with an additional 3 mL of solvent. The combined extracts were filtered using a syringe filter and placed under N

 gas to evaporate the solvents. The resulting residue was reconstituted in 400 μL of dichloromethane and transferred to 2 mL vials for analysis. The instrument used for data collection was a Pegasus HRT+ 4D. (LECO Corporation) equipped with a novel multimode source (MMS). The mass spectrometer was operated in EI, PCI, and ECNI modes with source temperatures of 250 °C for EI and 165 °C for both PCI and ECNI. The spectrometer was tuned with perfluorotributylamine (PFTBA) to give a resolving power of 25,000 for 

 218.98514 and a mass accuracy less than or equal to 1 PPM. Data were collected at 200 spectra per second, and methane was used as a reagent gas for chemical ionization. The gas chromatograph was equipped with a LECO Dual Stage QuadJet Thermal Modulator and two different columns. The column set consisted of an Agilent DB-5MS UI (30 m x 0.25 mm i.d. x 0.25 μm film thickness) first dimension (1D) column, and a Trajan BPX-50 (0.60 m x 0.10 mm i.d. x 0.10 μm film thickness) second dimension (2D) column. The carrier gas was helium (1.0 mL/min constant flow), the injection was 2 μL splitless, and the inlet was programmed to start at 70 °C and increase to 300 °C at 500 °C/min. The oven temperature program started at 80 °C (1 min) before it increased to 140 °C at 20 °C/min (30 min hold). It then ramped up to 200 °C at 10 °C/ min and finally increased to 300 °C at 1.5 °C/min (5 min hold). The secondary oven was maintained at +5 °C relative to the primary oven. The modulation period was 8 s, and the temperature offset of +15 °C was relative to the secondary oven.

GCxGC-HR-TOF-MS data were processed using ChromaTOF brand software. Peak Find (untargeted) processing included automated mass calibration (PFTBA calibrant), peak finding with deconvolution, spectral similarity comparisons to large, well-established databases (NIST 20, Wiley 12), and formula determinations for high resolution, accurate mass (HRAM) molecular and fragment ions. The target analyte finding (TAF) processing feature of ChromaTOF was used to target trace compounds in the dust samples.

The EI data collected was relatively rich and intense because of the universal ionization capabilities and efficiency of the ionization method. PCI and ECNI are selective ionization modes for electron-rich and deficient compounds, respectively. ECNI mode exhibits not only selectivity but exceptional sensitivity for electron-deficient compounds. The utilization of all modes, together with the HRAM capabilities of the mass spectrometer, facilitated the identification of the compounds, thereby increasing the total number of annotated substances in the dust. Careful inspection of the EI data contour plot for the NIST SRM (Figure 1) clearly illustrated the enhanced separation of GCxGC, leading to better S/N, cleaner spectra, and improved spectral data- base similarity scores. Furthermore, the plot exhibited group clustering (or positioning) for easy visualization and quick identification of the compound groups of interest and the removal of undesirable column and septa bleed. Dust components highlighted in the plot include branched and linear alkanes, dibenzothiophenes, phthalates, parent and substituted pyrene, and chrysene polyaromatic hydrocarbons (PAHs). Group clustering directly correlated to compound physiochemical properties; thus, their ability to interact with column stationary phase was impacted. Increased efficiency in compound separation was accomplished through careful primary and secondary column selection. The two columns were coated with different stationary phases leading to dissimilar or orthogonal compound separation mechanisms. For a nonpolar primary column (100% dimethyl polysiloxane), there were stronger London dispersion force interactions between the stationary phase and compounds with greater molecular weights and increased surface area. For example, higher molecular weight linear alkanes were retained longer than smaller, branched alkanes. In the case of the secondary column with an increased percentage of aromatic groups (50% dimethyl/50% diphenyl polysiloxane), saturated hydrocarbons interacted less with the phase and are located at the bottom of the contour plot (

-axis) while unsaturated compounds such as PAHs are located at towards the top of the plot because they were retained more through stronger pi–pi interactions. The assigned bubble colors in the contour plot are related to compound classification, and their size is proportional to their relative areas.

After automated data processing, a large number of organic compounds were identified in the SRM including hydrocarbons, acids, amines, alcohols, aldehydes, ketones, esters, phenols, terpenes, fatty acids, sterols, and phosphates. Classes of substances identified included illicit and over-the-counter drugs, food and flavor substances, sunscreen components, tobacco-related alkaloids, and cannabinoids. Two examples are cotinine, the predominant nicotine metabolite in humans, and cocaine, a powerful tropane alkaloid obtained from coca leaves native to South America. The comparison of their deconvoluted mass spectra to databases resulted in spectral similarity match values of 895 and 936, respectively, out of a potential perfect score of 1000. Greater confidence in compound identification was achieved by examining the mass accuracy values (PPM = 106 x (

calc) for these compounds (-0.23 and 0.28 PPM respectively).

Substances of major environmental and human health concerns included halogenated organic compounds, pesticides, and persistent organic pollutants (POPs). These compounds were present in trace quantities, but they were easily characterized through analysis with a combination of EI and PCI or ECNI. The names, database similarity values, and molecular ion mass accuracies of selected hazardous substances are listed in Table I. Spectral similarity values for all compounds in Table I averaged 862/1000. Mass accuracy values ranged from -0.80 to 1.93 PPM for compounds with molecular ions in their mass spectra. The endocrine-disrupting, brominated flame retardant, 2,2’,4,4’,5,-pentabromodiphenyl ether (BDE-99), exhibited a similarity value of 892/1000 and mass accuracy of 0.34 PPM for its molecular ion. Mass accuracy values for major fragments were used to help characterize compounds when molecular ions were absent in their spectra. For example, tris-dichloropropylphosphate (TDCPP), a phosphorus flame retardant used widely in the 1970s in children’s pajamas has a strong fragment ion at 

,-0.03 PPM). Spectra for BDE-209 and TDCPP are shown in Figure 2.

The pesticides identified in the SRM included organochlorines, organophosphates, carbamates, and pyrethroids. One example is sumithrin, a general insecticide of the pyrethroid family used for agricultural and household applications. Sumithrin, also known as D-phenothrin, is a neurotoxin used to kill mosquitoes, fleas, ticks, and head lice. Technical mixtures can be comprised of up to four stereoisomers because their structure contains two asymmetric carbon atoms. The EI Peak True and database mass spectra for the sumithrin isomer 2 are displayed in Figure 3 (similarity = 935/1000). The spectrum shows a small molecular ion with a mass accuracy of 0.20 PPM. The complementary PCI data displays excellent mass accuracy for the [MH]+, [M+C2H5]+, and [M+C3H5]+ adducts (

 391.22624, -1.36 PPM). In addition, a comparison of the actual molecular ion cluster in the PCI spectrum for sumithrin and the theoretically generated cluster resulted in an excellent match (isotopic fidelity = 990/1000). The EI and ECNI for the electron-deficient pesticide, trans-chlordane, are displayed in Figure 4. The EI spectral similarity and mass accuracy values were 788/1000 and -0.22 PPM ([M-Cl]+). As expected, a significant increase in sensitivity (>10x), and production of an intense molecular anion (-0.05 PPM, Fidelity = 982/1000) was apparent when using ECNI.

After analyzing the results of the untargeted data processing of comprehensive NIST SRM data, trace compounds of interest were identified and targeted in the comprehensive GCxGC data. Targeted processing is fast and ideal for trace analysis, quantitative analysis, or both. In this study, 40 halogenated pollutants were targeted on ECNI contour plots with pinpoint accuracy with two retention time (

) values and two abundant HRAM masses. For example, the [M+2]-• (407.79539) and [M+4]-• (409.79247) ions were used to target trans-chlordane (C10H6Cl8) in comprehensive data files. The list of target pollutants included hexachlorobenzene, polychlorinated naphthalenes (PCNs), heptachlor isomers, chlordane isomers, polychlorinated biphenyls (PCBs), nonachlor isomers, and BDE-71. TAF processing results for the NIST SRM, household, and office samples are listed in Table II. These results demonstrated that NIST 2585 SRM contained more pollutants than either the office or household samples, which was expected because the NIST SRM consists of a large collection of dust samples from different sources, whereas the office and household samples were limited to specific locations.

Household and office dust are good indicators of human exposure to hazardous substances. In this study, an improved analytical approach using GCxGC with high resolution mass spectrometry (HRMS) was utilized for the untargeted characterization of dust samples. Compounds were identified using a combination of database searches and formula determinations for molecular and fragment ions. Complementary PCI and ECNI modes of ionization produced data that improved confidence in compound identification. Dust analysis result comparisons demonstrated that there were more POPs in the SRM as compared to the household and office samples. The total number of compounds characterized in this study was much greater than the number reported in the certificate of analysis for SRM. For example, chlorinated naphthalenes and large numbers of polychlorinated paraffins were not listed in the SRM certificate; however, they were identified during this study.


C. Moschet, T. Anumol, B.M. Lew, D.H. Bennett, and T.M. Young, 

H.M. Stapleton, T. Harner, M. Shoeib, J.M. Keller, M.M. Schantz, S.D. Leigh, and S.A. Wise, 

T.P. Whitehead, C. Metayer, M. Pe- treas, M. Does, P.A. Buffler, and S.M. Rappaport, 

C. Bergh, G. Luongo, S. Wise, and C. Ostman, 

P. Rostkowski, P. Haglund, R. Aaliza- delh, N. Alyglzakis, N. Thomaidis, J.B. Arandes, et al, 

NIST, SRM 2585 - Organic Contaminants in House Dust.

 https://www-s.nist. gov/srmors/view_detail.cfm?srm=2585

David E. Alonso, Todd Richards, and Joe Binkley 

are with LECO Corporation, in St. Joseph, MI. Direct Correspondence to: 

High resolution time-of-flight mass spectrometry (HR-TOF-MS) with a novel multimode ionization source together with enhanced chromatographic resolution can successfully detect and identify pollutants in household dust samples. Here’s how.

Current Trends in Mass Spectrometry | LCGC Supplements

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Quantifying Smoke Taint in California Wines by Immersive Sorbent Sheet Extraction Prior to Direct Analysis in Real-Time Mass Spectrometry (DART-MS)

Comprehensive Screening of Pollutants in Household Dust Using High-Resolution Mass Spectrometry with Enhanced Chromatographic Resolution