Multi-capillary Column-ion Mobility Spectrometry Research Articles

Metabolism of 3-pentanone under inflammatory conditions**Institution to which the work should be attributed: Center of Breath Research, Department of Anaesthesiology, Intensive Care and Pain Therapy, Saarland University Medical Center, Homburg (Saar), Germany.

Breath analysis of rats using multi-capillary column ion-mobility spectrometry (MCC-IMS) revealed alterations in acetone and other ketones, including 3-pentanone, during inflammation. The alterations seem likely to result from oxidative branched-chain keto acid (BCKA) catabolism. We therefore tested the hypothesis that 3-pentanone arises during inflammation from increased BCKA oxidation in the liver with consequent accumulation of propionyl-CoA and its condensation products.Male Sprague-Dawley rats were anaesthetised and ventilated for 24 h or until death. Exhaled breath was analysed by MCC-IMS while rats were injected with low and high doses of lipopolysaccharide (LPS), tumour necrosis factor α (TNFα), or vehicle. The exhaled 3-pentanone peak was identified by pure substance measurements. Blood was collected 12 h after treatment for the determination of cytokine concentrations; transcription enzymes for BCKA catabolism and the activity of the BCKA dehydrogenase were analysed in liver tissue by quantitative real-time PCR and western blotting.Exhaled 3-pentanone decreased in all groups, but minimum concentrations with high-dose LPS (0.24 ± 0.31 volts; mean ± SD), low-dose TNFα (0.17 ± 0.10 volts) and high-dose TNFα (0.13 ± 0.04 volts) were lower than in vehicle animals (0.27 ± 0.12 volts). At 60% and 85% survival times (svt) concentrations of exhaled 3-pentanone increased significantly in all animals treated with low-dose LPS, (svt60% 0.38 ± 0.18 volts, svt85% 0.62 ± 0.15 volts) and high-dose LPS (0.26 ± 0.28 volts, 0.40 ± 0.22 volts), as well as low-dose TNFα, (0.20 ± 0.09 volts, 0.39 ± 0.17 volts) and high-dose TNFα (0.18 ± 0.06 volts, 0.34 ± 0.08 volts), but not in vehicle rats (0.27 ± 0.12 volts, 0.30 ± 0.09 volts). BCKA catabolism was seen in the liver, with increased expression and activity of the branched-chain alpha-keto acid dehydrogenase (BCKD), lower expression of the propionyl-CoA carboxylase (PCC) subunits, and altered expression levels of BCKD regulating enzymes.Exhaled 3-pentanone may arise from altered BCKA catabolism. Our results suggest that excessive propionyl-CoA is possibly generated from BCKAs via increased activity of BCKD, but may undergo unusual condensation reactions rather than being physiologically processed to methylmalonyl-CoA by PCC. The pattern of 3-pentanone during early and prolonged inflammation suggests that reuse of BCKAs for the synthesis of new proteins might be initially favoured. As inflammatory conditions persist, substrates for cellular energy supply are required which activate irreversible degradation of excessive BCKA to propionyl-CoA yielding increased levels of exhaled 3-pentanone.

Detection of malignant pleural mesothelioma in exhaled breath by multicapillary column/ion mobility spectrometry (MCC/IMS)

Malignant pleural mesothelioma (MPM) is predominantly caused by previous asbestos exposure. Diagnosis often happens in advanced stages restricting any therapeutic perspectives. Early stage detection via breath analysis was explored using multicapillary column/ion mobility spectrometry (MCC/IMS) to detect volatile organic compounds (VOCs) in the exhaled breath of MPM patients in comparison to former occupational asbestos-exposed and non-exposed controls.Breath and background samples of 23 MPM patients, 22 asymptomatic former asbestos (AEx) workers and 21 healthy non-asbestos exposed persons were taken for analysis. After background correction, we performed a logistic least absolute shrinkage and selection operator (lasso) regression to select the most important VOCs, followed by receiver operating characteristic (ROC) analysis.MPM patients were discriminated from both controls with 87% sensitivity, 70% specificity and respective positive and negative predictive values of 61% and 91%. The overall accuracy was 76% and the area under the ROC-curve was 0.81. AEx individuals could be discriminated from MPM patients with 87% sensitivity, 86% specificity and respective positive and negative predictive values of 87% and 86%. The overall accuracy was 87% with an area under the ROC-curve of 0.86.Breath analysis by MCC/IMS allows MPM patients to be discriminated from controls and holds promise for further investigation as a screening tool for former asbestos-exposed persons at risk of developing MPM.

Exhalation of volatile organic compounds during hemorrhagic shock and reperfusion in rats: an exploratory trial

Ischemia and reperfusion alter metabolism. Multi-capillary column ion-mobility spectrometry (MCC-IMS) can identify volatile organic compounds (VOCs) in exhaled gas. We therefore used MCC-IMS to evaluate exhaled gas in a rat model of hemorrhagic shock with reperfusion. Adult male Sprague-Dawley rats (n = 10 in control group, n = 15 in intervention group) were anaesthetized and ventilated via tracheostomy for 14 h or until death. Hemorrhagic shock was maintained for 90 min by removing blood from the femoral artery to a target of MAP 35 ± 5 mmHg, and then retransfusing the blood over 60 min in 15 rats; 10 control rats were evaluated without shock and reperfusion. Exhaled gas was analyzed with MCC-IMS, VOCs were identified using the BS-MCC/IMS analytes database (Version 1209). VOC intensities were analyzed at the end of shock, end of reperfusion, and after 9 h. All normotensive animals survived the observation period, whereas mean survival time was 11.2 h in shock and reperfusion animals. 16 VOCs differed significantly for at least one of the three analysis periods. Peak intensities of butanone, 2-ethyl-1-hexanol, nonanal, and an unknown compound were higher in shocked than normotensive rats, and another unknown compound increased over the time. 1-butanol increased only during reperfusion. Acetone, butanal, 1.2-butandiol, isoprene, 3-methylbutanal, 3-pentanone, 2-propanol, and two unknown compounds were lower and decreased during shock and reperfusion. 1-pentanol and 1-propanol were significant greater in the hypotensive animals during shock, were comparable during reperfusion, and then decreased after resuscitation. VOCs differ during hemorrhagic shock, reperfusion, and after reperfusion. MCC-IMS of exhaled breath deserves additional study as a non-invasive approach for monitoring changes in metabolism during ischemia and reperfusion.

Increasing conclusiveness of clinical breath analysis by improved baseline correction of multi capillary column – ion mobility spectrometry (MCC-IMS) data

Current challenges of clinical breath analysis include large data size and non-clinically relevant variations observed in exhaled breath measurements, which should be urgently addressed with competent scientific data tools. In this study, three different baseline correction methods are evaluated within a previously developed data size reduction strategy for multi capillary column – ion mobility spectrometry (MCC-IMS) datasets. Introduced for the first time in breath data analysis, the Top-hat method is presented as the optimum baseline correction method. A refined data size reduction strategy is employed in the analysis of a large breathomic dataset on a healthy and respiratory disease population. New insights into MCC-IMS spectra differences associated with respiratory diseases are provided, demonstrating the additional value of the refined data analysis strategy in clinical breath analysis.

Determination of volatile compounds by GC–IMS to assign the quality of virgin olive oil

The characterisation of different olive oil categories (extra virgin, virgin and lampante) using Ion Mobility Spectrometry (IMS) was improved by replacing the multicapillary column (MCC) with a capillary column (CC). The data obtained with MCC–IMS and CC–IMS were evaluated, studying both the global and the specific information obtained after the analysis of the volatile fraction of olive oils. A better differentiation of the oil categories was obtained employing CC vs MCC, since the classification percentage obtained with the CC–IMS was 92% as opposed to 87% obtained with MCC–IMS; although in productivity analytical terms, MCC offer a faster analysis than GC. The specific information obtained was also used to build a database, with a view to facilitating the characterization of specific attributes of olive oils. A total of 26 volatile metabolites (aldehydes, ketones, alcohols and esters) were identified. Finally, as revealed by an ANOVA test, some volatiles differed markedly in content among the different categories of oil. The data obtained confirms the potential of IMS as a reliable analytical screening technique, which can be used to assign the correct category to an olive oil sample.

Multi-capillary column-ion mobility spectrometry (MCC-IMS) as a new method for the quantification of occupational exposure to sevoflurane in anaesthesia workplaces: an observational feasibility study.

BackgroundOccupational exposure to sevoflurane has the potential to cause health damage in hospital personnel. Workplace contamination with the substance mostly is assessed by using photoacoustic infrared spectrometry with detection limits of 10 ppbv. Multi-capillary column-ion mobility spectrometry (MCC-IMS) could be an alternative technology for the quantification of sevoflurane in the room air and could be even more accurate because of potentially lower detection limits. The aim of this study was to test the hypothesis that MCC-IMS is able to detect and monitor very low concentrations of sevoflurane (<10 ppbv) and to evaluate the exposure of hospital personnel to sevoflurane during paediatric anaesthesia and in the post anaesthesia care unit (PACU).MethodsA MCC-IMS device was calibrated to several concentrations of sevoflurane and limits of detection (LOD) and quantification (LOQ) were calculated. Sevoflurane exposure of hospital personnel was measured at two anaesthesia workplaces and time-weighted average (TWA) values were calculated.ResultsThe LOD was 0.0068 ppbv and the LOQ was 0.0189 ppbv. During paediatric anaesthesia the mean sevoflurane concentration was 46.9 ppbv (8.0 - 314.7 ppbv) with TWA values between 5.8 and 45.7 ppbv. In the PACU the mean sevoflurane concentration was 27.9 ppbv (8.0 – 170.2 ppbv) and TWA values reached from 8.3 to 45.1 ppbv.ConclusionsMCC-IMS shows a significantly lower LOD and LOQ than comparable methods. It is a reliable technology for monitoring sevoflurane concentrations at anaesthesia workplaces and has a particular strength in quantifying low-level contaminations of sevoflurane. The exposure of the personnel working in these areas did not exceed recommended limits and therefore adverse health effects are unlikely.

Exhalation pattern changes during fasting and low dose glucose treatment in rats

The analysis of exhaled metabolites has become a promising field of research in recent decades. Several volatile organic compounds reflecting metabolic disturbance and nutrition status have even been reported. These are particularly important for long-term measurements, as needed in medical research for detection of disease progression and therapeutic efficacy. In this context, it has become urgent to investigate the effect of fasting and glucose treatment for breath analysis. In the present study, we used a model of ventilated rats that fasted for 12h prior to the experiment. Ten rats per group were randomly assigned for continuous intravenous infusion without glucose or an infusion including 25mg glucose per 100g per hour during an observation period of 12h. Exhaled gas was analysed using multicapillary column ion-mobility spectrometry. Analytes were identified by the BS-MCC/IMS database (version 1209; B & S Analytik, Dortmund, Germany). Glucose infusion led to a significant increase in blood glucose levels (p < 0.05 at 4h and thereafter) and cardiac output (p < 0.05 at 4h and thereafter). During the observation period, 39 peaks were found collectively. There were significant differences between groups in the concentration of ten volatile organic compounds: p < 0.001 at 4h and thereafter for isoprene, cyclohexanone, acetone, p-cymol, 2-hexanone, phenylacetylene, and one unknown compound, and p < 0.001 at 8h and thereafter for 1-pentanol, 1-propanol, and 2-heptanol. Our results indicate that for long-term measurement, fasting and the withholding of glucose could contribute to changes of volatile metabolites in exhaled air.

Data size reduction strategy for the classification of breath and air samples using multicapillary column-ion mobility spectrometry.

Ion mobility spectrometry combined with multicapillary column separation (MCC-IMS) is a well-known technology for detecting volatile organic compounds (VOCs) in gaseous samples. Due to their large data size, processing of MCC-IMS spectra is still the main bottleneck of data analysis, and there is an increasing need for data analysis strategies in which the size of MCC-IMS data is reduced to enable further analysis. In our study, the first untargeted chemometric strategy is developed and employed in the analysis of MCC-IMS spectra from 264 breath and ambient air samples. This strategy does not comprise identification of compounds as a primary step but includes several preprocessing steps and a discriminant analysis. Data size is significantly reduced in three steps. Wavelet transform, mask construction, and sparse-partial least squares-discriminant analysis (s-PLS-DA) allow data size reduction with down to 50 variables relevant to the goal of analysis. The influence and compatibility of the data reduction tools are studied by applying different settings of the developed strategy. Loss of information after preprocessing is evaluated, e.g., by comparing the performance of classification models for different classes of samples. Finally, the interpretability of the classification models is evaluated, and regions of spectra that are related to the identification of potential analytical biomarkers are successfully determined. This work will greatly enable the standardization of analytical procedures across different instrumentation types promoting the adoption of MCC-IMS technology in a wide range of diverse application fields.

Volatile organic compounds during inflammation and sepsis in rats: a potential breath test using ion-mobility spectrometry.

Multicapillary column ion-mobility spectrometry (MCC-IMS) may identify volatile components in exhaled gas. The authors therefore used MCC-IMS to evaluate exhaled gas in a rat model of sepsis, inflammation, and hemorrhagic shock. Male Sprague-Dawley rats were anesthetized and ventilated via tracheostomy for 10 h or until death. Sepsis was induced by cecal ligation and incision in 10 rats; a sham operation was performed in 10 others. In 10 other rats, endotoxemia was induced by intravenous administration of 10 mg/kg lipopolysaccharide. In a final 10 rats, hemorrhagic shock was induced to a mean arterial pressure of 35 ± 5 mmHg. Exhaled gas was analyzed with MCC-IMS, and volatile compounds were identified using the BS-MCC/IMS-analytes database (Version 1209; B&S Analytik, Dortmund, Germany). All sham animals survived the observation period, whereas mean survival time was 7.9 h in the septic animals, 9.1 h in endotoxemic animals, and 2.5 h in hemorrhagic shock. Volatile compounds showed statistically significant differences in septic and endotoxemic rats compared with sham rats for 3-pentanone and acetone. Endotoxic rats differed significantly from sham for 1-propanol, butanal, acetophenone, 1,2-butandiol, and 2-hexanone. Statistically significant differences were observed between septic and endotoxemic rats for butanal, 3-pentanone, and 2-hexanone. 2-Hexanone differed from all other groups in the rats with shock. Breath analysis of expired organic compounds differed significantly in septic, inflammation, and sham rats. MCC-IMS of exhaled breath deserves additional study as a noninvasive approach for distinguishing sepsis from inflammation.

Volatile Metabolites of Goat Cheeses Determined by Ion Mobility Spectrometry. Potential Applications in Quality Control

Headspace sampling coupled with multi-capillary column-ion mobility spectrometry (HS-MCC-IMS) has been used for extraction and identification of some volatile metabolites from different types of goat cheese samples. The only manual operation carried out in this method was the introduction of samples into vials; the following steps (headspace generation, injection of the volatiles compounds into MCC and IMS detection) were fully automated. The analysis by MCC-IMS allowed rapid and simple differentiation of goat cheeses made with raw and pasteurized milk. MCC-IMS produced multidimensional ion mobility spectra with different retention times and intensity information different for some individual metabolites. A total of six metabolites were identified in goat cheeses including 1 alcohol (1-hexanol), 1 ketone (2-nonanone), 2 aldehydes (octanal, trans-2-heptanal) and 2 esters (ethyl butanoate and propyl butanoate). Furthermore, the evolution of one targeted metabolite (ethyl butanoate) was monitored through different ripening times (60, 150, 180, 210, 240, 270 days). These preliminary results showed that this volatile compound increased during cheese ageing according to biochemical and microbial dynamic of the matrix, and therefore ethyl butanoate could be a potential marker of ripening time in these kinds of cheese samples. Therefore, the method could be used for quality control purposes in goat cheese producers.

Multi-capillary column-ion mobility spectrometry of volatile metabolites emitted by Saccharomyces cerevisiae.

Volatile organic compounds (VOCs) produced during microbial fermentations determine the flavor of fermented food and are of interest for the production of fragrances or food additives. However, the microbial synthesis of these compounds from simple carbon sources has not been well investigated so far. Here, we analyzed the headspace over glucose minimal salt medium cultures of Saccharomyces cerevisiae using multi-capillary column-ion mobility spectrometry (MCC-IMS). The high sensitivity and fast data acquisition of the MCC-IMS enabled online analysis of the fermentation off-gas and 19 specific signals were determined. To four of these volatile compounds, we could assign the metabolites ethanol, 2-pentanone, isobutyric acid, and 2,3-hexanedione by MCC-IMS measurements of pure standards and cross validation with thermal desorption–gas chromatography-mass spectrometry measurements. Despite the huge biochemical knowledge of the biochemistry of the model organism S. cerevisiae, only the biosynthetic pathways for ethanol and isobutyric acid are fully understood, demonstrating the considerable lack of research of volatile metabolites. As monitoring of VOCs produced during microbial fermentations can give valuable insight into the metabolic state of the organism, fast and non-invasive MCC-IMS analyses provide valuable data for process control.

Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)

Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species.

Headspace–multicapillary column–ion mobility spectrometry for the direct analysis of 2,4,6-trichloroanisole in wine and cork samples

Headspace–multicapillary column–ion mobility spectrometry coupling has been evaluated for the direct analysis of wine and cork stopper samples for the determination of 2,4,6-trichloroanisole (2,4,6-TCA). The instrumental configuration permits the sample to be introduced in headspace vials which are placed into the autosampler oven in order to facilitate the transference of the volatile compounds from the sample to its headspace. Further, an aliquot of 200μL of the homogenized gaseous phase is injected into the multicapillary column in order to separate the target compounds from potential interferents. The detection of 2,4,6-TCA was carried out in an ion mobility spectrometer with a radioactive source and working under negative mode. All the system was computer controlled, including data acquisition and treatment. The limits of detection achieved were 0.012ngL−1 for wine and 0.28ngg−1 for the cork stopper. The procedure was applied to the analysis of commercial wine samples in different packages and 2,4,6-TCA was found in all of those closed with a cork stopper. The excellent recovery values obtained testify for the goodness of the method as no interference from the sample matrix exits.

Evaluation of fast volatile analysis for detection of Botrytis cinerea infections in strawberry

Grey mold (Botrytis cinerea) is one of the major phytopathogens causing serious losses during strawberry postharvest and storage. B. cinerea–host interaction affect emissions of volatile compounds during infection resulting in a characteristic earthy, mushroom odor. Therefore, the objective of this study was to evaluate two analytical techniques based on fast volatile analysis on their performance for monitoring evolution and early detection of B. cinerea infections in strawberry. In a first experiment headspace multi-capillary column–ion mobility spectrometry (HS MCC–IMS) has been successfully used to evaluate development of strawberry aroma during shelflife. In a second experiment the same technique has been used to detect the degree of B. cinerea infection through changes in the volatile profile. Additionally, these samples were analyzed with headspace solid-phase-microextraction fast GC–MS (HS SPME fast GC–MS). Both HS MCC–IMS and HS SPME fast GC–MS could determine the changes in volatile composition as a function of the degree of B. cinerea infection as determined by an enzyme-linked immunosorbent assay (ELISA) and could be used to follow the evolution of infection. According to the ELISA data, some fruit were infected even without any symptoms and volatiles produced by the fungus may be overshadowed by the fruit volatiles. Therefore, both analytical techniques could not be used for early detection of B. cinerea infections. After identification of the volatile compounds and multivariate data analysis, potential biomarkers specific for B. cinerea were highlighted, being 3-methylbutanal, cis-4-decenal, 2-methyl-1-butanol, 2-methyl-1-propanol, 1-octen-3-one and 1-octen-3-ol.

Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria

Presently, 2 to 4 days elapse between sampling at infection suspicion and result of microbial diagnostics. This delay for the identification of pathogens causes quite often a late and/or inappropriate initiation of therapy for patients suffering from infections. Bad outcome and high hospitalization costs are the consequences of these currently existing limited pathogen identification possibilities. For this reason, we aimed to apply the innovative method multi-capillary column–ion mobility spectrometry (MCC-IMS) for a fast identification of human pathogenic bacteria by determination of their characteristic volatile metabolomes. We determined volatile organic compound (VOC) patterns in headspace of 15 human pathogenic bacteria, which were grown for 24 h on Columbia blood agar plates. Besides MCC-IMS determination, we also used thermal desorption–gas chromatography–mass spectrometry measurements to confirm and evaluate obtained MCC-IMS data and if possible to assign volatile compounds to unknown MCC-IMS signals. Up to 21 specific signals have been determined by MCC-IMS for Proteus mirabilis possessing the most VOCs of all investigated strains. Of particular importance is the result that all investigated strains showed different VOC patterns by MCC-IMS using positive and negative ion mode for every single strain. Thus, the discrimination of investigated bacteria is possible by detection of their volatile organic compounds in the chosen experimental setup with the fast and cost-effective method MCC-IMS. In a hospital routine, this method could enable the identification of pathogens already after 24 h with the consequence that a specific therapy could be initiated significantly earlier.

Multi-capillary column-ion mobility spectrometry: a potential screening system to differentiate virgin olive oils

The potential of a headspace device coupled to multi-capillary column-ion mobility spectrometry has been studied as a screening system to differentiate virgin olive oils ("lampante," "virgin," and "extra virgin" olive oil). The last two types are virgin olive oil samples of very similar characteristics, which were very difficult to distinguish with the existing analytical method. The procedure involves the direct introduction of the virgin olive oil sample into a vial, headspace generation, and automatic injection of the volatiles into a gas chromatograph-ion mobility spectrometer. The data obtained after the analysis by duplicate of 98 samples of three different categories of virgin olive oils, were preprocessed and submitted to a detailed chemometric treatment to classify the virgin olive oil samples according to their sensory quality. The same virgin olive oil samples were also analyzed by an expert's panel to establish their category and use these data as reference values to check the potential of this new screening system. This comparison confirms the potential of the results presented here. The model was able to classify 97% of virgin olive oil samples in their corresponding group. Finally, the chemometric method was validated obtaining a percentage of prediction of 87%. These results provide promising perspectives for the use of ion mobility spectrometry to differentiate virgin olive oil samples according to their quality instead of using the classical analytical procedure.

Breath sampling control for medical application

Sampling of breath under human control or automated control with sensors was combined with chemical determination of a synthetic sample using multi-capillary column ion mobility spectrometry to measure quantitative variability. Variation was 19% with an automated inlet and 33% with human control. Sensors to operate an automated inlet were also evaluated with human subjects and included carbon dioxide (CO2), flow (direction and velocity), volume (integrated from the flow rate) and humidity, all operating in the mainstream of exhaled air. The flow sensor provided a measure of sampling of breath from the upper airways and other sensors gauged exclusive sampling of the end-tidal volume as well. Sensors for volume and CO2 exhibited identical profiles, using appropriate threshold values, in reference to inspiration and expiration. A sensor for humidity lagged inspiration and expiration with a delay of 300 ms and therefore is diminished in value. The sensors recommended for an automated inlet for breath sampling are CO2 and the exhaled or tidal volume though tidal volume varies significantly with personal physiognomy. This necessitates an evaluation of a subject to establish a threshold setting and CO2 is the single best parameter providing the availability of sensor signal within 50 ms.

Peak assignment in multi-capillary column–ion mobility spectrometry using comparative studies with gas chromatography–mass spectrometry for VOC analysis

Over the past years, ion mobility spectrometry (IMS) as a well established method within the fields of military and security has gained more and more interest for biological and medical applications. This highly sensitive and rapid separation technique was crucially enhanced by a multi-capillary column (MCC), pre-separation for complex samples. In order to unambiguously identify compounds in a complex sample, like breath, by IMS, a reference database is mandatory. To obtain a first set of reference data, 16 selected volatile organic substances were examined by MCC-IMS and comparatively analyzed by the standard technique for breath research, thermal desorption-gas chromatography-mass spectrometry. Experimentally determined MCC and GC retention times of these 16 compounds were aligned and their relation was expressed in a mathematical function. Using this function, a prognosis of the GC retention time can be given very precisely according to a recorded MCC retention time and vice versa. Thus, unknown MCC-IMS peaks from biological samples can be assigned-after alignment via the estimated GC retention time-to analytes identified by GC/MS from equivalent accomplished data. One example of applying the peak assignment strategy to a real breath sample is shown in detail.

Exemplar application of multi-capillary column ion mobility spectrometry for biological and medical purpose

In recent years, ion mobility spectrometry is increasingly in demand for new applications especially on biological samples (cells, bacteria, fungi), in medicine (diagnosis, therapy and medication control e.g. from breath analyses), for food quality control, safety monitoring and characterisation or process control in chemical and pharmaceutical industry. For this purpose instruments based on gas phase separation of ions in weak electric fields were developed at ISAS–Institute for Analytical Sciences, focussing on the particular challenges such as humid and rather complex samples, specific sampling procedures adapted to the application, fast pre-separation techniques like multi-capillary columns and suitable data processing including data bases for relevant analytes and automatic characterisation of IMS-chromatograms. Feasibility studies were carried out successfully for biological and medical purpose at ISAS, including the detection of bacteria, fungi and metabolites of cells and in human breath. For all those samples characteristic pattern of analytes were found and could be used for the identification of cell lines, fungi and bacteria as well as of numerous diseases. Furthermore, the quantification of those analytes could be used to obtain information about the state of the process or person (e.g. growth of cultures, development of diseases, level of medication, grade of cancer). Those examples shall demonstrate the potential of ion mobility spectrometry for the selected applications. However, a general and reliable data bases of reference analytes is required in the near future to enable an exploitation of the metabolic pathways and to confirm the relevance of the detected signals for the investigated topic.

RADIOLOGICAL QUIZ

Current challenges of clinical breath analysis include large data size and non-clinically relevant variations observed in exhaled breath measurements, which should be urgently addressed with competent scientific data tools. In this study, three different baseline correction methods are evaluated within a previously developed data size reduction strategy for multi capillary column – ion mobility spectrometry (MCC-IMS) datasets. Introduced for the first time in breath data analysis, the Top-hat method is presented as the optimum baseline correction method. A refined data size reduction strategy is employed in the analysis of a large breathomic dataset on a healthy and respiratory disease population. New insights into MCC-IMS spectra differences associated with respiratory diseases are provided, demonstrating the additional value of the refined data analysis strategy in clinical breath analysis.