Ion mobility spectrometry: arriving on site and moving beyond a low profile

Laser Desorption of Explosives from the Surface of Different Real-World Materials Studied Using C2Cl6-Dopant-Assisted Ion Mobility Spectrometry

A highly efficient and sensitive ion mobility spectrometry (IMS) system with laser desorption sampling was applied for rapid explosive detection using different surface materials. This portable IMS detector, powered by a battery, offers mobility and is suitable for use in the field or combat zones. The laser desorption (LD) sampling of common explosives (Trinitrotoluene-TNT; Dinitrotoluenes-DNTs; Hexogene-RDX; pentaerythritol tetranitrate-PETN; plastic explosives-Compound 4 (C-4) and Semtex) on a wide range of common surface materials, such as metal, ceramic, plastic, glass, drywall, paper, wood, and textiles, was studied. Successful detection was achieved on nearly all surfaces except flammable materials (paper, wood, and textiles). The limit of detection (LOD) was determined for each explosive and specific surface, demonstrating an impressive LOD of 7 ng/mm2 for TNT. RDX, C-4, PETN, and Semtex achieved LOD values of 15 ng/mm2, while DNTs showed an LOD of approximately 50 ng/mm2.

A novel coupling technique based on thermal desorption gas chromatography with mass spectrometry and ion mobility spectrometry for breath analysis

Exhaled breath analysis is evolving into an increasingly important non-invasive diagnostic tool. Volatile organic compounds (VOCs) in breath contain information about health status and are promising biomarkers for several diseases, including respiratory infections caused by bacteria. To monitor the composition of VOCs in breath or the emission of VOCs from bacteria, sensitive analytical techniques are required. Next to mass spectrometry, ion mobility spectrometry (IMS) is considered a promising analytical tool for detecting gaseous analytes in the parts per billion by volume to parts per trillion by volume range. This work presents a new, dual coupling of thermal desorption gas chromatography to a quadrupole mass spectrometer (MS) and an IMS by operating a simple splitter. Nearly identical retention times can be reached in the range of up to 30 min with slight deviations of 0.06 min-0.24 min. This enables the identification of unknown compounds in the IMS chromatogram using unambiguous mass spectral identification, as there are still no commercially available databases for IMS. It is also possible to discriminate one of the detectors using the splitter to improve detection limits. Using a test liquid mixture of seven ketones, namely 2-butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-octanone, 2-nonanone, and 2-decanone with a concentration of 0.01 g l-1reproducibilities ranging from 3.0% to 7.6% for MS and 2.2%-5.3%, for IMS were obtained, respectively. In order to test the system optimized here for the field of breath analysis, characteristic VOCs such as ethanol, isoprene, acetone, 2-propanol, and 1-propanol were successfully identified in exhaled air using the dual detector system due to the match of the corresponding IMS, and MS spectra. The presented results may be considered to be a starting point for the greater use of IMS in combination with MS within the medical field.

Ultrafast Sulfur Mustard Simulant Gas Fluorescent Chemosensors Based on Triazole AIEE Material with High Selectivity and Sensitivity at Room Temperature

Herein, a novel blue aggregation-induced enhanced emission (AIEE) material 4-N-(naphthalen-l-yl)-3,5-bis(4-N-phenyl-1-naphthylamine)phenyl-4H-1,2,4-triazole (NDTAZ) is developed and used as a fluorescent chemosensor for sulfur mustard (SM) simulant 2-chloroethyl ethyl sulfide (2-CEES) vapor. The NDTAZ chemosensor is designed by introducing an electron-donating N-phenyl-1-naphthylamine group at 3 and 5 position of 4H-1,2,4-triazole (TAZ) to enhance the nucleophilicity of the TAZ group, and a naphthalene ring is connected to 4 position of the TAZ group to construct an AIEE molecule. The NDTAZ films show extraordinary stability and then are further used as reliable and portable fluorescent chemosensors. Upon exposure to 2-CEES vapor, the NDTAZ chemosensor exhibits an instantaneous fluorescence response (not more than 1 s). What should be noted is that this fluorescent chemosensor realizes the visualized detection of fluorescent color change from blue to green at "room temperature", which is rarely reported. The limit of detection is estimated to be 0.55 ppm, which is below the AEGL-1 (0.6 ppm for 1 min) safety ceiling level to SM exposure. Moreover, the NDTAZ chemosensor shows high selectivity toward 2-CEES vapor over closely related substances, including alkylating agents, aryl halide compounds, sulphur-containing compounds, and nerve agent mimics. More impressively, the NDTAZ chemosensor demonstrates good recyclability by water treatment. Also, the sensing mechanism is adequately proved by using multiple experimental methods and theoretical calculation. In addition, the NDTAZ-based facile filter paper-constructed test strips are fabricated for real-time and on-spot detection of leaked 2-CEES gas specifically. Therefore, this fluorescent chemosensor with excellent sensing performance greatly advances the practical detection of SM species at room temperature.

Detecting the Subtle Photo-Responsive Conformational Bistability of Monomeric Azobenzene Functionalized Keggin Polyoxometalates by Using Ion-Mobility Mass Spectrometry

Accurately characterizing the conformational variation of novel molecular assemblies is important but often ignored due to limited characterization methods. Herein, we reported the use of ion-mobility mass spectrometry (IMS/MS) to investigate the conformational changes of four azobenzene covalently functionalized Keggin hybrids (azo-Keggins, compounds 1–4). The as-prepared azo-Keggins showed the general molecular formula of [C₁₆H₃₆N]₄[SiW₁₁O₄₀(Si(CH₂)₃NH–CO(CH₂)_nO–C₆H₄N=NC₆H₄–R)₂] (R = H, n = 0 (1); R = NO₂, n = 0 (2); R = H, n = 5 (3); R = H, n = 10 (4)). The resultant azo-Keggins maintained stable monomeric states in the gas phase with intact molecular structures. Furthermore, the subtle photo-responsive trans-cis conformational variations of azo-Keggins were clearly revealed by the molecular shape-related collision cross-section value difference ranging from 2.44 Ų to 6.91 Ų. The longer the alkyl chains linkers were, the larger the conformational variation was. Moreover, for compounds 1 and 2, higher stability in trans-conformation can be observed, while for compounds 3 and 4, bistability can be achieved for both of them.

Application of gas chromatography-ion mobility spectrometry in the analysis of food volatile components

Gas chromatography-ion mobility spectrometry (GC-IMS) is an emerging analytical technique that has the advantages of fast response, high sensitivity, simple operation, and low cost. The combination of the fast speed and resolution of GC with the high sensitivity of IMS makes GC-IMS play an important role in the detection of food volatile substances. This paper focuses on the basic principles and future development trend, and the comparative analysis of the functions, similarities and differences of GC-IMS, GC-MS and electronic nose in the detection of common volatile compounds. A comprehensive introduction to the main application of GC-IMS in food volatile components: fingerprint identification of sample differences and detection of characteristic compounds. On the basis of perfecting the spectral library, GC-IMS will have broad development prospects in food authentication, origin identification, process optimization and product classification, especially in the analysis and identification of trace volatile food flavor substances.

Detection of Volatile Toxic Industrial Chemicals with Classical Ion Mobility Spectrometry and High-Kinetic Energy Ion Mobility Spectrometry

Due to their high sensitivity and compact design, ion mobility spectrometers are widely used to detect toxic industrial chemicals (TICs) in air. However, when analyzing complex gas mixtures, classical ion mobility spectrometry (IMS) suffers from false-positive rates due to limited resolving power or false-negative rates caused by competitive ion-molecule reactions and the resulting suppression of certain analyte ions. To overcome these limitations, high-kinetic energy IMS (HiKE-IMS) was introduced some years ago. In contrast to classical IMS, HiKE-IMS is operated at decreased pressures of 20···60 mbar and high reduced electric field strengths E/N of up to 120 Td. Under these conditions, the influence of competitive ion-molecule reactions on the prevailing ion population should be less pronounced, thus reducing false negatives. Additionally, effects such as fragmentation and field-dependent ion mobility may help to reduce false positives. In this work, the capabilities and limitations of HiKE-IMS in the field of on-site detection of the volatile TICs NH₃, HCN, H₂S, HCl, NO₂, Cl₂, and SO₂ are evaluated for the first time. Based on the limits of detection and the extent of spectral and chemical cross-sensitivities in gas mixtures, the results obtained for HiKE-IMS are compared with those obtained for classical IMS. It is shown that HiKE-IMS is less sensitive in comparison to classical IMS. However, when used for TIC detection, the reduced sensitivity of HiKE-IMS is not a major drawback. With values around 1 ppm_v, the achievable limits of detection for almost all TICs are below the AEGL-2 (4h) levels. Furthermore, in comparison to classical IMS, it is still striking that HiKE-IMS shows significantly less spectral and chemical cross-sensitivities and thus exhibits considerably lower false-positive and false-negative rates. Overall, it thus turns out that HiKE-IMS is a promising alternative to classical IMS in the field of on-site detection of TICs.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

Breath-Based Diagnosis of Infectious Diseases: A Review of the Current Landscape

Various analytical methods can be applied to concentrate, separate, and examine trace volatile organic metabolites in the breath, with the potential for noninvasive, rapid, real-time identification of various disease processes, including an array of microbial infections. Although biomarker discovery and validation in microbial infections can be technically challenging, it is an approach that has shown great promise, especially for infections that are particularly difficult to identify with standard culture and molecular amplification-based approaches. This article discusses the current state of breath analysis for the diagnosis of infectious diseases.

Dopant for detection of methamphetamine in the presence of nicotine with ion mobility spectrometry

Methamphetamine (MA) is a highly addictive and illegal psychostimulant drug and is currently one of the most commonly abused illicit drugs in the world. The on-site rapid detection of trace amounts of MA and screening illicit drugs in clandestine laboratories is important for drug enforcement agencies and the forensic community in general. However, detecting methamphetamine in the presence of nicotine and cigarette smoke by ion mobility spectrometry faces difficulty due to the overlapped spectral peaks of methamphetamine and nicotine. In this work, a new method was developed to detect MA using pyridine as a dopant in the presence of nicotine by a homemade ion mobility spectrometry. The reduced mobilities of MA and nicotine were measured under the temperatures of the drift tube from 40 to 120 °C and doping with pyridine. The result shows that the temperature of 100 °C is beneficial to resolve the two substances. The concentration of doped pyridine is optimized to be 18 ppm. In this doped experiment, the reaction rate of nicotine is higher than that of MA by measuring the instrumental responses of MA and nicotine. No matter how high the nicotine content is, the interference of nicotine can be eliminated in the detection of MA doped with pyridine. This method is also successfully applied for the determination of MA and nicotine simultaneously in real saliva samples. The limit of detection of MA was measured to be about 0.5 ng/μL. The promising results in this work provide an effective method for on-site detection of MA.

Ion Mobility Shift of Isotopologues in a High Kinetic Energy Ion Mobility Spectrometer (HiKE-IMS) at Elevated Effective Temperatures

Ion mobility spectrometers (IMS) separate ions mainly by ion-neutral collision cross section and to a lesser extent by ion mass and effective temperature. When investigating isotopologues, the difference in collision cross section can be assumed negligible. Since the mobility shift of isotopologues is thus mainly caused by their difference in mass and effective temperature, the investigation of isotopologues can provide important insights into the theory of ion mobility. However, in classical IMS operated at ambient pressure, cluster formation with neutral molecules occurs, which significantly influences the mobility shift of isotopologues and thus makes a sound investigation of the effect of ion mass and effective temperature on the ion mobility difficult. In this work, the relative ion mobility of several organic compounds and their ¹³C-labeled isotopologues is studied in a High Kinetic Energy Ion Mobility Spectrometer (HiKE-IMS) at high reduced electric fields up to 120 Td, which allows the investigation of nonclustered ion species and thus enables a sound investigation of the mobility shift of isotopologues. The results show that the measured relative ion mobilities of isotopologues having the same effective temperature and, thus, their ion mass dominating the relative ion mobility agree well with theoretical relative ion mobilities predicted by the theory of ion mobility.

BALSAM-An Interactive Online Platform for Breath Analysis, Visualization and Classification

The field of breath analysis lacks a fully automated analysis platform that enforces machine learning good practice and enables clinicians and clinical researchers to rapidly and reproducibly discover metabolite patterns in diseases. We present BALSAM-a comprehensive web-platform to simplify and automate this process, offering features for preprocessing, peak detection, feature extraction, visualization and pattern discovery. Our main focus is on data from multi-capillary-column ion-mobility-spectrometry. While not limited to breath data, BALSAM was developed to increase consistency and robustness in the data analysis process of breath samples, aiming to expand the array of low cost molecular diagnostics in clinics. Our platform is freely available as a web-service and in form of a publicly available docker container.

Multi-capillary Column Ion Mobility Spectrometry of Volatile Metabolites for Phenotyping of Microorganisms

Rational strain engineering requires solid testing of phenotypes including productivity and ideally contributes thereby directly to our understanding of the genotype-phenotype relationship. Actually, the test step of the strain engineering cycle becomes the limiting step, as ever advancing tools for generating genetic diversity exist. Here, we briefly define the challenge one faces in quantifying phenotypes and summarize existing analytical techniques that partially overcome this challenge. We argue that the evolution of volatile metabolites can be used as proxy for cellular metabolism. In the simplest case, the product of interest is a volatile (e.g., from bulk alcohols to special fragrances) that is directly quantified over time. But also nonvolatile products (e.g., from bulk long-chain fatty acids to natural products) require major flux rerouting that result potentially in altered volatile production. While alternative techniques for volatile determination exist, rather few can be envisaged for medium to high-throughput analysis required for phenotype testing. Here, we contribute a detailed protocol for an ion mobility spectrometry (IMS) analysis that allows volatile metabolite quantification down to the ppb range. The sensitivity can be exploited for small-scale fermentation monitoring. The insights shared might contribute to a more frequent use of IMS in biotechnology, while the experimental aspects are of general use for researchers interested in volatile monitoring.

Thermoelectric Array Sensors with Selective Combustion Catalysts for Breath Gas Monitoring

Inflammable breath gases such as H₂ and CH₄ are used as bio markers for monitoring the condition of the colon. However, their typical concentrations of below 100 ppm pose sensitivity and selectivity challenges to current gas sensing systems without the use of chromatography. We fabricated a compact, gas-selective thermoelectric array sensor (TAS) that uses micro-machined sensor devices with three different combustion catalysts to detect gases such as H₂, CO, and CH₄ in breath. Using Pt/Pt-W thin-film micro-heater meanders, Pd/Al₂O₃, Pt,Pd,Au/Co₃O₄, and Pt/Al₂O₃ catalysts were heated to 320, 200, and 125 °C, respectively, and the gas sensing performances of the TAS for each gas and for a model breath gas mixture of 100 ppm H₂, 25 ppm CO, 50 ppm CH₄, and 199 ppm CO₂ in air were investigated. Owing to its high catalyst temperature, the Pd/Al₂O₃ catalyst burned all three gases, while the Pt,Pd,Au/Co₃O₄ burned CO and H₂ and the Pt/Al₂O₃ burned H₂ selectively. To calibrate the gas concentration of the mixture gas without the use of a gas separation tool, linear discriminant analysis was applied to measure the sensing performance of TAS. To enhance the gas selectivity against H₂, a double catalyst structure was integrated into the TAS sensor.

Instrumental sensing of trace volatiles-a new promising tool for detecting the presence of entrapped or hidden people

There is a growing demand for rapid analytical systems to detect the presence of humans who are either entrapped as a result of a disaster or, in particular, hidden, as in the case of smuggling or trafficking. The trafficking and smuggling of people to Europe have reached epidemic proportions in recent years. This does not only put a major strain on European resources, but puts at risk the health and lives of the people being trafficked or smuggled. In this context, the early detection and interception of smuggled/trafficked people is of particular importance in terms of saving migrants from life-threatening situations. Similarly, the early and rapid location of entrapped people is crucial for urban search and rescue (USaR) operations organized after natural or man-made disasters. Since the duration of entrapment determines the survivability of victims, each novel detecting tool could considerably improve the effectiveness of the rescue operations and hence potentially save lives. Chemical analysis aiming at using a volatile chemical fingerprint typical for the presence of hidden humans has a huge potential to become an extremely powerful technology in this context. Interestingly, until now this approach has received little attention, despite the fact that trained dogs have been used for decades to detect the presence of buried people through scent. In this article we review the current status of using analytical techniques for chemical analysis for search and rescue operations, and discuss the challenges and future directions. As a practical implementation of this idea, we describe a prototype portable device for use in the rapid location of hidden or entrapped people that employs ion mobility spectrometry and a sensor array for the recognition of the chemical signature of the presence of humans.

Obstructive sleep apnea patients can be identified by ion mobility spectrometry-derived smell prints of different biological materials

BACKGROUND

The analysis of obstructive sleep apnoea syndrome (OSAS) is time- and cost-intensive. A number of studies demonstrated that the non-invasive analysis of exhaled breath (EB) may be suitable to distinguish between OSAS patients and healthy subjects (HS). Methods/Population: We included OSAS patients (n = 15) and HS (n = 15) in this diagnostic proof-of-concept-study. All participants underwent polygraphy to verify or exclude OSAS and performed spirometry to exclude pulmonary ventilatory diseases. The volatile organic compound profile of EB and of the headspaces over EB condensate, pharyngeal washing fluid, and serum was measured using ion mobility spectrometry (IMS) (BioScout^®) and an e-nose (Cyranose^® 320). For the statistical analysis, we fitted classification tree models using recursive partitioning, followed by a leave-one-out cross-validation. For the cross-validated predictions we calculated descriptive classification statistics, p-values from a [Formula: see text]-test with continuity correction, as well as ROC curves.

RESULTS

Using IMS, OSAS patients and HS could be distinguished with high accuracy (values ranged from 79% to 97%). The results of the e-nose-derived analyses (with the exception of EB) were less accurate. However, the cross-validated accuracy for EB was very good (0.9), reflecting a positive predictive value of 100% and a negative predictive value of 83%. For each material, we identified the best five substances that may be used for diagnostic purposes. 2-Methylfluran was found in three different biological materials to be discriminative between OSAS and HS.

CONCLUSION

The results strengthen the hypothesis that substances detectable in headspace measurements of different airway and blood materials may undergo a transition from blood into the alveoli (and EB) or vice versa. This means that substances from different compartments could be used to distinguish patients with airway diseases (in this case OSAS) from healthy controls.

Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles

Computational breath analysis is a growing research area aiming at identifying volatile organic compounds (VOCs) in human breath to assist medical diagnostics of the next generation. While inexpensive and non-invasive bioanalytical technologies for metabolite detection in exhaled air and bacterial/fungal vapor exist and the first studies on the power of supervised machine learning methods for profiling of the resulting data were conducted, we lack methods to extract hidden data features emerging from confounding factors. Here, we present Carotta, a new cluster analysis framework dedicated to uncovering such hidden substructures by sophisticated unsupervised statistical learning methods. We study the power of transitivity clustering and hierarchical clustering to identify groups of VOCs with similar expression behavior over most patient breath samples and/or groups of patients with a similar VOC intensity pattern. This enables the discovery of dependencies between metabolites. On the one hand, this allows us to eliminate the effect of potential confounding factors hindering disease classification, such as smoking. On the other hand, we may also identify VOCs associated with disease subtypes or concomitant diseases. Carotta is an open source software with an intuitive graphical user interface promoting data handling, analysis and visualization. The back-end is designed to be modular, allowing for easy extensions with plugins in the future, such as new clustering methods and statistics. It does not require much prior knowledge or technical skills to operate. We demonstrate its power and applicability by means of one artificial dataset. We also apply Carotta exemplarily to a real-world example dataset on chronic obstructive pulmonary disease (COPD). While the artificial data are utilized as a proof of concept, we will demonstrate how Carotta finds candidate markers in our real dataset associated with confounders rather than the primary disease (COPD) and bronchial carcinoma (BC). Carotta is publicly available at http://carotta.compbio.sdu.dk [1].

Exhaled volatile organic compounds discriminate patients with chronic obstructive pulmonary disease from healthy subjects

Chronic obstructive pulmonary disease (COPD) is a chronic airway inflammatory disease characterized by incompletely reversible airway obstruction. This clinically heterogeneous group of patients is characterized by different phenotypes. Spirometry and clinical parameters, such as severity of dyspnea and exacerbation frequency, are used to diagnose and assess the severity of COPD. The purpose of this study was to investigate whether volatile organic compounds (VOCs) could be detected in the exhaled breath of patients with COPD and whether these VOCs could distinguish COPD patients from healthy subjects. Moreover, we aimed to investigate whether VOCs could be used as biomarkers for classifying patients into different subgroups of the disease. Ion mobility spectrometry was used to detect VOCs in the exhaled breath of COPD patients. One hundred and thirty-seven peaks were found to have a statistically significant difference between the COPD group and the combined healthy smokers and nonsmoker group. Six of these VOCs were found to correctly discriminate COPD patients from healthy controls with an accuracy of 70%. Only 15 peaks were found to be statistically different between healthy smokers and healthy nonsmokers. Furthermore, by determining the cutoff levels for each VOC peak, it was possible to classify the COPD patients into breathprint subgroups. Forced expiratory volume in 1 second, body mass index, and C-reactive protein seem to play a role in the discrepancies observed in the different breathprint subgroups.

Volatile Organic Compounds during Inflammation and Sepsis in Rats

Background:

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.

Methods:

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).

Results:

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.

Conclusions:

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.

Selective and sensitive chromogenic and fluorogenic detection of sulfur mustard in organic, aqueous and gaseous medium

A chromogenic and fluorogenic system based on a squaraine dye (SQ) was used for the highly selective and sensitive detection of the chemical warfare agent sulfur mustard.

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.

Ion mobility spectrometry for pharmacokinetic studies--exemplary application

Breath analysis is an attractive non-invasive method for diagnosis and therapeutic monitoring. It uses endogenously produced compounds and metabolites of isotopically labeled precursors. In order to make such tests clinically useful, it is important to have relatively small portable instruments detecting volatile compounds within short time. A particularly promising analytical technique is ion mobility spectrometry (IMS) coupled to a multi capillary column (MCC). This paper focuses on demonstrating the suitability of breath analysis for pharmacokinetic applications using MCC-IMS with respect to practicability and reproducibility testing the model substrate eucalyptol. Validation of the MCC-IMS measurements were performed using proton transfer reaction mass spectrometry (PTR-MS) and resulted in an excellent correspondence of the time-dependent concentrations presented by the two different analytical techniques. Moreover, the good accordance in variance of kinetic parameters with repeated measures, and the determined inter-subject differences indicate the eligibility of the analysis method.

Ion mobility spectrometry for detection of skin volatiles

Volatile organic compounds (VOCs) released by humans through their skin were investigated in near real time using ion mobility spectrometry after gas chromatographic separation with a short multi-capillary column. VOCs typically found in a small nitrogen flow covering the skin are 3-methyl-2-butenal, 6-methylhept-5-en-2-one, sec-butyl acetate, benzaldehyde, octanal, 2-ethylhexanol, nonanal and decanal at volume fractions in the low part per billion-(ppb) range. The technique presented here may contribute to elucidating some physiological processes occurring in the human skin.

Ionization, transport, separation, and detection of ions in non-electrolyte containing liquids

Liquid phase ion mobility spectrometry (LPIMS) has the potential to be miniaturized such that it can be incorporated into chip based technology, providing higher performance in terms of both detection sensitivity and resolving power than is currently available by other separation technologies such as gas phase IMS, chromatography, or electrophoresis. This work presents modeling, simulation, and experimental investigations to characterize the mobility of ions in a liquid phase. This study included the ionization, transfer, separation, and detection of ions in non-electrolyte liquids. Using a resistive glass tube, mobility spectra were obtained by pulsed ionization for several different analytes, namely, tetramethylammonium chloride, tetrabutylammonium chloride, and dimethyl methylphosphonate (DMMP). Ion separation was demonstrated by separating solvent ions from the ions generated from the test compounds. Simulation and theoretical resolving power calculations were made to validate the experimental mobility measurements. A parametric study on the dependence of IMS resolving power on drift length, voltage across drift cell, and pulse width determined the requirements for designing a miniaturized IMS system, approximately the centimeter scale, with high performance, resolving power approaching 100 or higher. Mobility spectra are used for the first time to determine the diffusion coefficients of ions in a liquid.

Integrating mass spectrometry of intact protein complexes into structural proteomics

MS analysis of intact protein complexes has emerged as an established technology for assessing the composition and connectivity within dynamic, heterogeneous multiprotein complexes at low concentrations and in the context of mixtures. As this technology continues to move forward, one of the main challenges is to integrate the information content of such intact protein complex measurements with other MS approaches in structural biology. Methods such as H/D exchange, oxidative foot-printing, chemical cross-linking, affinity purification, and ion mobility separation add complementary information that allows access to every level of protein structure and organization. Here, we survey the structural information that can be retrieved by such experiments, demonstrate the applicability of integrative MS approaches in structural proteomics, and look to the future to explore upcoming innovations in this rapidly advancing area.

Computational methods for metabolomic data analysis of ion mobility spectrometry data-reviewing the state of the art

Ion mobility spectrometry combined with multi-capillary columns (MCC/IMS) is a well known technology for detecting volatile organic compounds (VOCs). We may utilize MCC/IMS for scanning human exhaled air, bacterial colonies or cell lines, for example. Thereby we gain information about the human health status or infection threats. We may further study the metabolic response of living cells to external perturbations. The instrument is comparably cheap, robust and easy to use in every day practice. However, the potential of the MCC/IMS methodology depends on the successful application of computational approaches for analyzing the huge amount of emerging data sets. Here, we will review the state of the art and highlight existing challenges. First, we address methods for raw data handling, data storage and visualization. Afterwards we will introduce de-noising, peak picking and other pre-processing approaches. We will discuss statistical methods for analyzing correlations between peaks and diseases or medical treatment. Finally, we study up-to-date machine learning techniques for identifying robust biomarker molecules that allow classifying patients into healthy and diseased groups. We conclude that MCC/IMS coupled with sophisticated computational methods has the potential to successfully address a broad range of biomedical questions. While we can solve most of the data pre-processing steps satisfactorily, some computational challenges with statistical learning and model validation remain.

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.