Breath testing for SARS-CoV-2 infection.

BACKGROUND: From a public health perspective, the identification of individuals with mild respiratory symptoms due to SARS-CoV-2 infection is important to contain the spread of the disease. The objective of this study was to identify volatile organic compounds (VOCs) in exhaled breath common to infection with different variants of the SARS-CoV-2 virus to inform the development of a point-of-care breath test to detect infected individuals with mild symptoms. METHODS: A prospective, real-world, observational study was conducted on mildly symptomatic out-patients presenting to community test-sites for RT-qPCR SARS-CoV-2 testing when the Alpha, Beta, and Delta variants were driving the COVID-19 pandemic. VOCs in exhaled breath were compared between PCR-positive and negative individuals using TD-GC-ToF-MS. Candidate VOCs were tested in an independent set of samples collected during the Omicron phase of the pandemic. FINDINGS: Fifty breath samples from symptomatic RT-qPCR positive and 58 breath samples from test-negative, but symptomatic participants were compared. Of the 50 RT-qPCR-positive participants, 22 had breath sampling repeated 8-12 weeks later. PCA-X model yielded 12 distinct VOCs that discriminated SARS-CoV-2 active infection compared to recovery/convalescence period, with an area under the receiver operator characteristic curve (AUROC), of 0.862 (0.747-0.977), sensitivity, and specificity of 82% and 86%, respectively. PCA-X model from 50 RT-qPCR positive and 58 negative symptomatic participants, yielded 11 VOCs, with AUROC of 0.72 (0.604-0.803) and sensitivity of 72%, specificity 65.5%. The 11 VOCs were validated in a separate group of SARS-CoV-2 Omicron positive patients' vs healthy controls demonstrating an AUROC of 0.96 (95% CI 0.827-0.993) with sensitivity of 80% specificity of 90%. INTERPRETATION: Exhaled breath analysis is a promising non-invasive, point-of-care method to detect mild COVID-19 infection. FUNDING: Funding for this study was a competitive grant awarded from the Vancouver Coastal Research Institute as well as funding from the BC Cancer Foundation.

Peppermint protocol: first results for gas chromatography-ion mobility spectrometry.

ThePeppermint Initiativeseeks to inform the standardisation of breath analysis methods. FivePeppermint Experimentswith gas chromatography-ion mobility spectrometry (GC-IMS), operating in the positive mode with a tritium3H 5.68 keV, 370 MBq ionisation source, were undertaken to provide benchmarkPeppermint Washoutdata for this technique, to support its use in breath-testing, analysis, and research. Headspace analysis of a peppermint-oil capsule by GC-IMS with on-column injection (0.5 cm3) identified 12 IMS responsive compounds, of which the four most abundant were: eucalyptol;ß-pinene;α-pinene; and limonene. Elevated concentrations of these four compounds were identified in exhaled-breath following ingestion of a peppermint-oil capsule. An unidentified compound attributed as a volatile catabolite of peppermint-oil was also observed. The most intense exhaled peppermint-oil component was eucalyptol, which was selected as a peppermint marker for benchmarking GC-IMS. Twenty-five washout experiments monitored levels of exhaled eucalyptol, by GC-IMS with on-column injection (0.5 cm3), att= 0 min, and then att+ 60,t+ 90,t+ 165,t+ 285 andt+ 360 min from ingestion of a peppermint capsule resulting in 148 peppermint breath analyses. Additionally, thePeppermint Washoutdata was used to evaluate clinical deployments with a further five washout tests run in clinical settings generating an additional 35 breath samples. Regression analysis yielded an average extrapolated time taken for exhaled eucalyptol levels to return to baseline values to be 429 ± 62 min (±95% confidence-interval). The benchmark value was assigned to the lower 95% confidence-interval, 367 min. Further evaluation of the data indicated that the maximum number of volatile organic compounds discernible from a 0.5 cm3breath sample was 69, while the use of an in-line biofilter appeared to reduce this to 34.

Diagnosis of COVID-19 by analysis of breath with gas chromatography-ion mobility spectrometry - a feasibility study.

BACKGROUND: There is an urgent need to rapidly distinguish COVID-19 from other respiratory conditions, including influenza, at first-presentation. Point-of-care tests not requiring laboratory- support will speed diagnosis and protect health-care staff. We studied the feasibility of using breath-analysis to distinguish these conditions with near-patient gas chromatography-ion mobility spectrometry (GC-IMS). METHODS: Independent observational prevalence studies at Edinburgh, UK, and Dortmund, Germany, recruited adult patients with possible COVID-19 at hospital presentation. Participants gave a single breath-sample for VOC analysis by GC-IMS. COVID-19 infection was identified by transcription polymerase chain reaction (RT- qPCR) of oral/nasal swabs together with clinical-review. Following correction for environmental contaminants, potential COVID-19 breath-biomarkers were identified by multi-variate analysis and comparison to GC-IMS databases. A COVID-19 breath-score based on the relative abundance of a panel of volatile organic compounds was proposed and tested against the cohort data. FINDINGS: Ninety-eight patients were recruited, of whom 21/33 (63.6%) and 10/65 (15.4%) had COVID-19 in Edinburgh and Dortmund, respectively. Other diagnoses included asthma, COPD, bacterial pneumonia, and cardiac conditions. Multivariate analysis identified aldehydes (ethanal, octanal), ketones (acetone, butanone), and methanol that discriminated COVID-19 from other conditions. An unidentified-feature with significant predictive power for severity/death was isolated in Edinburgh, while heptanal was identified in Dortmund. Differentiation of patients with definite diagnosis (25 and 65) of COVID-19 from non-COVID-19 was possible with 80% and 81.5% accuracy in Edinburgh and Dortmund respectively (sensitivity/specificity 82.4%/75%; area-under-the-receiver- operator-characteristic [AUROC] 0.87 95% CI 0.67 to 1) and Dortmund (sensitivity / specificity 90%/80%; AUROC 0.91 95% CI 0.87 to 1). INTERPRETATION: These two studies independently indicate that patients with COVID-19 can be rapidly distinguished from patients with other conditions at first healthcare contact. The identity of the marker compounds is consistent with COVID-19 derangement of breath-biochemistry by ketosis, gastrointestinal effects, and inflammatory processes. Development and validation of this approach may allow rapid diagnosis of COVID-19 in the coming endemic flu seasons. FUNDING: MR was supported by an NHS Research Scotland Career Researcher Clinician award. DMR was supported by the University of Edinburgh ref COV_29.

Breath markers for therapeutic radiation.

Radiation dose is important in radiotherapy. Too little, and the treatment is not effective, too much causes radiation toxicity. A biochemical measurement of the effect of radiotherapy would be useful in personalisation of this treatment. This study evaluated changes in exhaled breath volatile organic compounds (VOC) associated with radiotherapy with thermal desorption gas chromatography mass-spectrometry followed by data processing and multivariate statistical analysis. Further the feasibility of adopting gas chromatography ion mobility spectrometry for radiotherapy point-of-care breath was assessed. A total of 62 participants provided 240 end-tidal 1 dm3 breath samples before radiotherapy and at 1, 3, and 6 h post-exposure, that were analysed by thermal-desorption/gas-chromatography/quadrupole mass-spectrometry. Data were registered by retention-index and mass-spectra before multivariate statistical analyses identified candidate markers. A panel of sulfur containing compounds (thio-VOC) were observed to increase in concentration over the 6 h following irradiation. 3-methylthiophene (80 ng.m-3 to 790 ng.m-3) had the lowest abundance while 2-thiophenecarbaldehyde(380 ng.m-3 to 3.85 µg.m-3) the highest; note, exhaled 2-thiophenecarbaldehyde has not been observed previously. The putative tumour metabolite 2,4-dimethyl-1-heptene concentration reduced by an average of 73% over the same time. Statistical scoring based on the signal intensities thio-VOC and 3-methylthiophene appears to reflect individuals' responses to radiation exposure from radiotherapy. The thio-VOC are hypothesised to derive from glutathione and Maillard-based reactions and these are of interest as they are associated with radio-sensitivity. Further studies with continuous monitoring are needed to define the development of the breath biochemistry response to irradiation and to determine the optimum time to monitor breath for radiotherapy markers. Consequently, a single 0.5 cm3 breath-sample gas chromatography-ion mobility approach was evaluated. The calibrated limit of detection for 3-methylthiophene was 10 µg.m-3 with a lower limit of the detector's response estimated to be 210 fg.s-1; the potential for a point-of-care radiation exposure study exists.

VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography/Mass Spectrometry Data.

Metabolic profiling of breath analysis involves processing, alignment, scaling, and clustering of thousands of features extracted from gas chromatography/mass spectrometry (GC/MS) data from hundreds of participants. The multistep data processing is complicated, operator error-prone, and time-consuming. Automated algorithmic clustering methods that are able to cluster features in a fast and reliable way are necessary. These accelerate metabolic profiling and discovery platforms for next-generation medical diagnostic tools. Our unsupervised clustering technique, VOCCluster, prototyped in Python, handles features of deconvolved GC/MS breath data. VOCCluster was created from a heuristic ontology based on the observation of experts undertaking data processing with a suite of software packages. VOCCluster identifies and clusters groups of volatile organic compounds (VOCs) from deconvolved GC/MS breath with similar mass spectra and retention index profiles. VOCCluster was used to cluster more than 15 000 features extracted from 74 GC/MS clinical breath samples obtained from participants with cancer before and after a radiation therapy. Results were evaluated against a panel of ground truth compounds and compared to other clustering methods (DBSCAN and OPTICS) that were used in previous metabolomics studies. VOCCluster was able to cluster those features into 1081 groups (including endogenous and exogenous compounds and instrumental artifacts) with an accuracy rate of 96% (±0.04 at 95% confidence interval).

Breath analysis by two-dimensional gas chromatography with dual flame ionisation and mass spectrometric detection - Method optimisation and integration within a large-scale clinical study.

Precision medicine has spurred new innovations in molecular pathology leading to recent advances in the analysis of exhaled breath as a non-invasive diagnostic tool. Volatile organic compounds (VOCs) detected in exhaled breath have the potential to reveal a wealth of chemical and metabolomic information. This study describes the development of a method for the analysis of breath, based on automated thermal desorption (TD) combined with flow modulated comprehensive two-dimensional gas chromatography (GC×GC) with dual flame ionisation and quadrupole mass spectrometric detection (FID and qMS). The constrained optimisation and analytical protocol was designed to meet the practical demands of a large-scale multi-site clinical study, while maintaining analytical rigour to produce high fidelity data. The results demonstrate a comprehensive method optimisation for the collection and analysis of breath VOCs by GC×GC, integral to the standardisation and integration of breath analysis within large clinical studies.

Discrimination of bacteria by rapid sensing their metabolic volatiles using an aspiration-type ion mobility spectrometer (a-IMS) and gas chromatography-mass spectrometry GC-MS.

The objective of our study was to investigate whether one may quickly and reliably discriminate different microorganism strains by direct monitoring of the headspace atmosphere above their cultures. Headspace samples above a series of in vitro bacterial cultures were directly interrogated using an aspiration type ion mobility spectrometer (a-IMS), which produced distinct profiles ("fingerprints") of ion currents generated simultaneously by the detectors present inside the ion mobility cell. Data processing and analysis using principal component analysis showed net differences in the responses produced by volatiles emitted by various bacterial strains. Fingerprint assignments were conferred on the basis of product ion mobilities; ions of differing size and mass were deflected in a different degree upon their introduction of a transverse electric field, impacting finally on a series of capacitors (denominated as detectors, or channels) placed in a manner analogous to sensor arrays. Three microorganism strains were investigated - Escherichia coli, Bacillus subtilis and Staphylococcus aureus; all strains possess a relatively low pathogenic character. Samples of air with a 5 cm3 volume from the headspace above the bacterial cultures in agar growth medium were collected using a gas-tight chromatographic syringe and injected inside the closed-loop pneumatic circuit of the breadboard a-IMS instrument model ChemPro-100i (Environics Oy, Finland), at a distance of about 1 cm from the ionization source. The resulting chemical fingerprints were produced within two seconds from the moment of injection. The sampling protocol involved to taking three replicate samples from each of 10 different cultures for a specific strain, during a total period of 72 h after the initial incubation - at 24, 48 and 72 h, respectively. Principal component analysis (PCA) was used to discriminate between the IMS fingerprints. PCA was found to successfully discriminate between bacteria at three levels in the experimental campaign: 1) between blank samples from growth medium and samples from bacterial cultures, 2) between samples from different bacterial strains, and 3) between time evolutions of headspace samples from the same bacterial strain over the 3-day sampling period. Consistent classification between growth medium samples and growth medium inoculated with bacteria was observed in both positive and negative detection/ionization modes. In parallel, headspace air samples of 1 dm3 were collected from each bacterial culture and loaded onto Tenax™-Carbograph desorption tubes, using a custom built sampling unit based on a portable sampling pump. One sample was taken for each of 10 different cultures of a strain, at 24, 48 and 72 h after the initial incubation. These adsorption tubes were subsequently analyzed using thermal desorption - gas chromatography - mass spectrometry (TD-GC-MS). This second dataset was intended to produce a qualitative analysis of the volatiles present in the headspace above the bacterial cultures.

Detection of metabolites of trapped humans using ion mobility spectrometry coupled with gas chromatography.

For the first time, ion mobility spectrometry coupled with rapid gas chromatography, using multicapillary columns, was applied for the development of a pattern of signs of life for the localization of entrapped victims after disaster events (e.g., earthquake, terroristic attack). During a simulation experiment with entrapped volunteers, 12 human metabolites could be detected in the air of the void with sufficient sensitivity to enable a valid decision on the presence of a living person. Using a basic normalized summation of the measured concentrations, all volunteers involved in the particular experiments could be recognized only few minutes after they entered the simulation void and after less than 3 min of analysis time. An additional independent validation experiment enabled the recognition of a person in a room of ∼25 m(3) after ∼30 min with sufficiently high sensitivity to detect even a person briefly leaving the room. Undoubtedly, additional work must be done on analysis time and weight of the equipment, as well as on validation during real disaster events. However, the enormous potential of the method as a significantly helpful tool for search-and-rescue operations, in addition to trained canines, could be demonstrated.

Gas-phase and solution studies of three resorcin[4]arene derivatives using electrospray time-of-flight mass spectrometry.

Electrospray ionisation mass spectrometry (ESI-MS) has been used to study the relative gas-phase proton and alkali metal (Li, Na, K and Cs) binding affinities of three different resorcin[4]arenes using the kinetic method. Collision-induced dissociation (CID) was used to study the fragmentation of resorcin[4]arene heterodimer sandwich complexes, allowing the relative binding affinity order to be established. All the alkali metal cations have the same gas-phase binding affinity order with the resorcin[4]arene host molecules. At collision energies of > or = 13eV, one of the [resorcin[4]arene+Metal]+, (Metal = Li, Na, K) ions fragmented through break-up of the resorcin[4]arene, whilst the other host resorcin[4]arene remained intact, causing an apparent change in binding affinity at high collision energy. This effect was not observed with caesium, since all complex ions dissociated readily under CID by displacement of the caesium cation. The binding affinity for the protonated resorcin[4]arenes was found to be different from the alkali metal cation binding affinity because of the higher proton affinity of the nitrogen-containing resorcin[4]arenes. It is shown that resorcin[4]arenes containing an oxazine ring can be converted into a ring-opened derivative via an Eschweiler-CLarke reaction in the presence of formic acid. A second ring-opening process also occurs, including a hydrolysis reaction that results in apparent Losses of 12 mass units from the intact resorcin[4]arene. Both these reactions occur in solution before mass spectrometric investigation and cannot be achieved by CID. This observation was confirmed by inducing the Eschweiter-CLarke reaction in a model benzoxazine compound.

Optimisation of secondary electrospray ionisation (SESI) for the trace determination of gas-phase volatile organic compounds.

An electrospray ionisation triple quadrupole mass spectrometer (Varian 1200 L) was modified to accept nitrogen samples containing low concentrations of volatile organic compounds. Six candidate probe compounds, methyl decanoate, octan-3-one, 2-ethylhexanoic acid, 1,4-diaminobutane, dimethyl methylphosphonate, and 2,3-butanediol, at concentrations below 50 ppb(v) were generated with permeation tubes in a test atmosphere generator. The concept of using a set of molecular probes to evaluate gas-phase electrospray ionisation of volatile analytes was assessed and the feasibility of adopting a unified ionisation approach for gas and liquid contamination of exobiotic environments established. 450 experiments were run in a five-replicate, fifteen-level, three-factor, central-composite-design with exponential dilution for each of the six probe compounds studied. The three factors studied were ionisation voltage, drying-gas flow and nebulising-gas flow. Parametric modelling by regression analysis enabled the differences in the ionisation behaviours of the probe compounds to be described by the optimisation models. Regression coefficients were in the range 0.91 to 0.99, indicating satisfactory levels of precision in the optimisation models. A wide range in ionisation efficiency was observed, with different optimised conditions required for the probe compounds. It was evident that no one factor appeared to dominate the response and the different factors produced different effects on the responses for the different molecules. 1,4-Butanediamine and dimethyl methylphosphonate required significantly lower ionisation voltages (1.2 kV) than the other four, which achieved optimised sensitivity towards the maximum voltage used in this design (5 to 6 kV). Drying-gas flow rates were found to be more important than nebulising-gas flow rates. However, variations in the constant term B(0) in the optimisation models indicated that other factors, not included in this study, were also likely to be involved in the ionisation process. Electrolyte-flow rate and ionisation temperature were proposed for follow up studies. Exponential dilution data indicated sensitive and analytically useful responses in the target range of 5 to 50 ppb(v) for all six compounds. Significantly, responses were seen at concentrations significantly below 5 ppb(v), with sub ppt(v) responses observed for 1,4-butanediamine, 2-ethylhexanoic acid, dimethylmethylphosphonate, and 1,3-butanediol. Responses in the ppt(v) to ppb(v) range were observed for the remaining two compounds. The observations from this study demonstrated the utility of adopting a set of probe compounds to evaluate electrospray ionisation performance for volatile organic compound based assays; indicated the existence of multiple ionisation mechanisms; and revealed potential sensitivity at the parts per quadrillion level ppq(v).

Non-invasive metabolomic analysis of breath using differential mobility spectrometry in patients with chronic obstructive pulmonary disease and healthy smokers.

The rapid, accurate and non-invasive diagnosis of respiratory disease represents a challenge to clinicians, and the development of new treatments can be confounded by insufficient knowledge of lung disease phenotypes. Exhaled breath contains a complex mixture of volatile organic compounds (VOCs), some of which could potentially represent biomarkers for lung diseases. We have developed an adaptive sampling methodology for collecting concentrated samples of exhaled air from participants with impaired respiratory function, against which we employed two-stage thermal desorption gas chromatography-differential mobility spectrometry (GC-DMS) analysis, and showed that it was possible to discriminate between participants with and without chronic obstructive pulmonary disease (COPD). A 2.5 dm(3) volume of end tidal breath was collected onto adsorbent traps (Tenax TA/Carbotrap), from participants with severe COPD and healthy volunteers. Samples were thermally desorbed and analysed by GC-DMS, and the chromatograms analysed by univariate and multivariate analyses. Kruskal-Wallis ANOVA indicated several discriminatory (p < 0.01) signals, with good classification performance (receiver operator characteristic area up to 0.82). Partial least squares discriminant analysis using the full DMS chromatograms also gave excellent discrimination between groups (alpha = 19% and beta = 12.4%).

Discrimination of bacteria using pyrolysis-gas chromatography-differential mobility spectrometry (Py-GC-DMS) and chemometrics.

Discrimination of bacteria was investigated using pyrolysis-gas chromatography-differential mobility spectrometry (Py-GC-DMS). Three strains belonging to the genus Bacillus were investigated and these included two strains of Bacillus subtilis and a single Bacillus megaterium. These were chosen so as to evaluate the possibility of bacterial strain discrimination using Py-GC-DMS. The instrument was constructed in-house and the long-term reproducibility of the instrument was evaluated over a period of 60 days using a Scotch whisky quality control. To assess the reproducibility further each bacterium was cultured six times and each culture was analysed in replicate to give three analytical replicates. The DMS data were generated in both positive and negative modes, and the data in each mode were analysed independently of each other. The Py-GC-DMS data were pre-processed via correlation optimised warping (COW) and asymmetric least square (ALS) to align the DMS chromatograms and to remove any unavoidable baseline shifts, prior to normalisation. Processed chromatograms were analysed using principal component analysis (PCA) followed by supervised learning methodology using partial least squares for discriminant analysis (PLS-DA). It was found that the separations between B. subtilis and B. megaterium can be readily observed by PCA; however, strain discrimination within the two B. subtilis was only possible using supervised learning. As multiple biological replicates were analysed an exhaustive splitting of the training and test sets was undertaken and this allowed correct classification rates (CCRs) to be assessed for the 3375 test sets. It was found that with PLS-DA the negative ion mode DMS data were more discriminatory than the positive mode data.

Optimising cell temperature and dispersion field strength for the screening for putrescine and cadaverine with thermal desorption-gas chromatography-differential mobility spectrometry.

Biogenic amines, and putrescine and cadaverine in particular, have significant importance in the area of food quality monitoring, and are also potentially important markers of infection, for cancer, diabetes, arthritis and cystic fibrosis. A thermal desorption-gas chromatograph-heated differential mobility spectrometer was constructed and the significant effect of interactions between cell temperature and dispersion field strength on the observed responses studied. The experiment design was a Box-Wilson central composite design (CCD) over the levels of 10-24 kVcm(-1) for dispersion field strength and 100-130 degrees C for cell temperature. The optimum values were estimated to be 16.22 kVcm(-1) and 116 degrees C for putrescine and 14.78 kVcm(-1) and 112 degrees C for cadaverine, respectively with an ammonia dopant at 19 mgm(-3). An amine test atmosphere generator was constructed and produced stable concentrations of putrescine (7 mgm(-3)) and cadaverine (4 mgm(-3)) vapours at 50+/-0.5 degrees C. Tenax TA-Carbotrap adsorbent tubes were used to sample putrescine and cadaverine vapour standards and a linear response function over the range of sample masses 5-20 ng was obtained at 15.0 kVcm(-1) 115 degrees C, with a R(2) of 0.99 for both putrescine and cadaverine. The sample mass at the limit of detection was estimated to be 3 ng for putrescine and cadaverine. Preliminary data from sampling the headspace of chicken meat revealed a 62% increase in the recovered masses of putrescine from 0.84 to 1.36 ng in the sampled air.

The presumptive detection of benzene in water in the presence of phenol with an active membrane-UV photo-ionisation differential mobility spectrometer.

Studies with a new technique, active membrane-differential mobility spectrometry, with aqueous standards of benzene and phenol are described. The atmospheric pressure photo-ionisation chemistries of benzene and phenol in the presence of oxygen are similar in that benzene forms phenol radicals that subsequently react to yield diphenylether and 4-phenoxyphenol products. Further phenol sequesters charge from benzene ions leading to a significant loss of sensitivity. This is an important consideration in the development of screening techniques for the presence of benzene in environmental water samples. This challenge was addressed by including a pre-separation stage prior to photo-ionisation, and a 10 cm long polydimethylsiloxane active membrane inlet using nitrogen as a carrier gas was used to sample, concentrate and deliver low resolution separations to the 10.6 eV UV-ionisation region of a differential mobility spectrometer. Acetone was also proposed as a charge carrier for the UV photo-ionisation source; to promote phenol protonation and inhibit charge sequestration from benzene. The responses of the system to aqueous standards of benzene and phenol with and without acetone doping at 10.2 mg m(-3) were evaluated and four to five-fold increases in sensitivity were obtained with acetone doping. With a sampling time of 60 s and a total measurement cycle of 180 s it was possible to obtain quantitative responses to single standards over the concentration range 6 to 177 microg cm(-3) with linear correlations with R(2) values ranging from 0.97 to 0.99. The effects of the heating rate of the membrane and the dispersion field strength of the differential mobility spectrometer on sensitivity and the differentiation of benzene from phenol responses were optimised, leading to a configuration where a voltage heating programme of 4.75 V s(-1) was applied to a 124 microm stainless steel wire heating element within the active membrane, and a dispersion field strength of 22 kV cm(-1) was used to test a mixture of benzene (14 microg cm(-3)) and phenol (6 microg cm(-3)) in water. The presence of benzene was identified through the presence of a peak corresponding to a benzene response, V(C) = -9 V FWHM = 1 V, that followed the thermal desorption profile of benzene.

Programmable gate delayed ion mobility spectrometry-mass spectrometry: a study with low concentrations of dipropylene-glycol-monomethyl-ether in air.

The concept of using a short ionisation event, in this case a pulsed corona discharge, in conjunction with programmed gate delay is described. This technique is proposed for the selective study of different ionisation processes within the reaction region of an ion mobility spectrometer. The utility of such an approach was tested in a study of the ionisation of dipropylene-glycol-monomethyl-ether (DPM); a compound commonly used to test the operation of ion mobility spectrometers. Dipropylene-glycol-monomethyl-ether at a concentration of 113 microg m(-3) in air, with a water level of 75 mg m(-3) in air, was analysed using a switchable, high resolution ion mobility spectrometer, operating in the positive mode at 40 degrees C at ambient pressure. The ion mobility spectrometer was fitted with a pulsed corona discharge ionisation source, doped with ammonia at a concentration of 1.3 mg m(-3) in the reaction region, and interfaced to a mass spectrometer. Synchronisation of the ionisation event to the operation of the shutter grids for the drift region enabled different parts of the product ion population to be injected into the drift tube, and programming the gate delays produced a map of the gate delay verses drift time response surface. Ammonium bound dipropylene-glycol-monomethyl-ether was observed, [(DPM)NH4]+ (m/z 166) as well as the ammonium bound dimer [(DPM)2NH4]+ (m/z 314), the same as those observed with a 63Ni source. Two other species were also observed, but their molecular identity was not elucidated. One of them m/z 146, also observed with 63Ni, formed ammonium bound ions [(m/z 146)NH4]+ (K0= 1.49 cm2 V(-1) s(-1)), ammonium bound dimer ions [(m/z 146)2NH4]+(K0= 1.18 cm2 V(-1) s(-1)) and a mixed cluster ion with DPM [(m/z 146)(DPM)NH4]+(K0= 1.18 cm2 V(-1) s(-1)); while the other, m/z 88 a decomposition product, formed ammonium bound monomer [(m/z 88)NH4]+(K0= 1.68 cm2 V(-1) s(-1)), dimer ions [(m/z 88)2NH4]+(K0= 1.40 cm2 V(-1) s(-1)) and a mixed cluster ion containing DPM and ammonium, [(DPM)(m/z 88)2NH4]+(K0= 1.40 cm2 V(-1) s(-1)). The assignment of responses to these ions required the additional dimensionality in the data provided from the gate delay studies. The relationships evident in the programmable gate delay data enabled these ions to be differentiated from alternative assignments of possible nitrogen clusters, formed at the interface of the mass spectrometer.