Monitoring the volatile language of fungi using gas chromatography-ion mobility spectrometry.

Fusarium oxysporum is a plant pathogenic fungus leading to severe crop losses in agriculture every year. A sustainable way of combating this pathogen is the application of mycoparasites-fungi parasitizing other fungi. The filamentous fungus Trichoderma atroviride is such a mycoparasite that is able to antagonize phytopathogenic fungi. It is therefore frequently applied as a biological pest control agent in agriculture. Given that volatile metabolites play a crucial role in organismic interactions, the major aim of this study was to establish a method for on-line analysis of headspace microbial volatile organic compounds (MVOCs) during cultivation of different fungi. An ion mobility spectrometer with gas chromatographic pre-separation (GC-IMS) enables almost real-time information of volatile emissions with good selectivity. Here we illustrate the successful use of GC-IMS for monitoring the time- and light-dependent release of MVOCs by F. oxysporum and T. atroviride during axenic and co-cultivation. More than 50 spectral peaks were detected, which could be assigned to 14 volatile compounds with the help of parallel gas chromatography-mass spectrometric (GC-MS) measurements. The majority of identified compounds are alcohols, such as ethanol, 1-propanol, 2-methyl propanol, 2-methyl butanol, 3-methyl-1-butanol and 1-octen-3-ol. In addition to four ketones, namely acetone, 2-pentanone, 2-heptanone, 3-octanone, and 2-octanone; two esters, ethyl acetate and 1-butanol-3-methylacetate; and one aldehyde, 3-methyl butanal, showed characteristic profiles during cultivation depending on axenic or co-cultivation, exposure to light, and fungal species. Interestingly, 2-octanone was produced only in co-cultures of F. oxysporum and T. atroviride, but it was not detected in the headspace of their axenic cultures. The concentrations of the measured volatiles were predominantly in the low ppbv range; however, values above 100 ppbv were detected for several alcohols, including ethanol, 2-methylpropanol, 2-methyl butanol, 1- and 3-methyl butanol, and for the ketone 2-heptanone, depending on the cultivation conditions. Our results highlight that GC-IMS analysis can be used as a valuable analytical tool for identifying specific metabolite patterns for chemotaxonomic and metabolomic applications in near-to-real time and hence easily monitor temporal changes in volatile concentrations that take place in minutes.

Sniffing Entrapped Humans with Sensor Arrays.

Earthquakes are lethal natural disasters frequently burying people alive under collapsed buildings. Tracking entrapped humans from their unique volatile chemical signature with hand-held devices would accelerate urban search and rescue (USaR) efforts. Here, a pilot study is presented with compact and orthogonal sensor arrays to detect the breath- and skin-emitted metabolic tracers acetone, ammonia, isoprene, CO2, and relative humidity (RH), all together serving as sign of life. It consists of three nanostructured metal-oxide sensors (Si-doped WO3, Si-doped MoO3, and Ti-doped ZnO), each specifically tailored at the nanoscale for highly sensitive and selective tracer detection along with commercial CO2 and humidity sensors. When tested on humans enclosed in plethysmography chambers to simulate entrapment, this sensor array rapidly detected sub-ppm acetone, ammonia, and isoprene concentrations with high accuracies (19, 21, and 3 ppb, respectively) and precision, unprecedented by portable sensors but required for USaR. These results were in good agreement (Pearson's correlation coefficients ≥0.9) with benchtop selective reagent ionization time-of-flight mass spectrometry (SRI-TOF-MS). As a result, an inexpensive sensor array is presented that can be integrated readily into hand-held or even drone-carried detectors for first responders to rapidly screen affected terrain.

Monitoring of selected skin- and breath-borne volatile organic compounds emitted from the human body using gas chromatography ion mobility spectrometry (GC-IMS).

Human smuggling and associated cross-border crimes have evolved as a major challenge for the European Union in recent years. Of particular concern is the increasing trend of smuggling migrants hidden inside shipping containers or trucks. Therefore, there is a growing demand for portable security devices for the non-intrusive and rapid monitoring of containers to detect people hiding inside. In this context, chemical analysis of volatiles organic compounds (VOCs) emitted from the human body is proposed as a locating tool. In the present study, an in-house made ion mobility spectrometer coupled with gas chromatography (GC-IMS) was used to monitor the volatile moieties released from the human body under conditions that mimic entrapment. A total of 17 omnipresent volatile compounds were identified and quantified from 35 ion mobility peaks corresponding to human presence. These are 7 aldehydes (acrolein, 2-methylpropanal, 3-methylbutanal, 2-ethacrolein, n-hexanal, n-heptanal, benzaldehyde), 3 ketones (acetone, 2-pentanone, 4-methyl-2-pentanone), 5 esters (ethyl formate, ethyl propionate, vinyl butyrate, butyl acetate, ethyl isovalerate), one alcohol (2-methyl-1-propanol) and one organic acid (acetic acid). The limits of detection (0.05-7.2 ppb) and relative standard deviations (0.6-11%) should be sufficient for detecting these markers of human presence in field conditions. This study shows that GC-IMS can be used as a portable field detector of hidden or entrapped people.

Analysis of volatile organic compounds in the breath of patients with stable or acute exacerbation of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a major cause of death worldwide. Acute exacerbations COPD (AECOPD), caused by infectious and non-infectious agents, contribute to an increase in mortality. The diagnostic procedure of AECOPD is mainly based on clinical features. The aim of this pilot study was to identify whether volatile organic compounds (VOCs) in breath could be used to discriminate for acute exacerbated COPD. Three patient groups were included in this controlled study: AECOPD patients (n = 14, age mean ± SD: 71.4 ± 7.46), stable COPD patients (n = 16, age mean ± SD: 66.9 ± 9.05) and healthy volunteers (n = 24, age mean ± SD: 28 ± 6.08). Breath samples were collected by optimizing a sampling strategy developed by us. These samples were then analyzed using a thermal desorption-gas chromatography-time of flight-mass spectrometer (TD-GC-ToF-MS). A total of 105 VOCs were identified in the breath samples. Relevant substances were subsequently selected by overall occurrence rate, the frequency of positive alveolar gradient (AG) (i.e. the difference in exhaled and inhaled VOCs concentration), exclusion of 'smoking related' VOCs and significant differences in AGs between the three groups. These steps dramatically reduced the number of relevant analytes and resulted in 12 key VOCs having discriminative values. The performance of patients' classification described by the Receiver Operating Characteristic (ROC) curve using all 12 substances delineates an area under the curve (AUC) of 0.97. A further reduction to four VOCs (AGs only different between AECOPD and COPD) delineates an AUC of 0.92. These results indicate that breath analysis with TD-GC-ToF-MS holds promise for an accurate and easy to perform differential diagnosis between AECOPD and COPD. In this regard, ketones were observed at the highest levels in exhaled breath of AECOPD, some of which are also related to potential bacterial pathogens. Using a set of VOCs that can discriminate for AECOPD, the calculated AUCs in ROC curve analysis show far superior results in comparison to serum AECOPD biomarkers, such as C-reactive protein. The identified VOCs should be further investigated in translational studies addressing their potential for developing highly specific nanosensors for breath gas analysis which would give clinicians a tool for non-invasive diagnosis of AECOPD at the point of care.

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.

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.

Characterization of volatile metabolites taken up by or released from Streptococcus pneumoniae and Haemophilus influenzae by using GC-MS.

Volatile organic compounds (VOCs) released from or taken up by Streptococcus pneumoniae and Haemophilus influenzae cultures were analysed by means of GC-MS after adsorption of headspace samples on multi-bed sorption tubes. Sampling was performed at different time points during cultivation of bacteria to follow the dynamics of VOC metabolism. VOCs were identified not only by spectral library match but also based on retention times of native standards. As many as 34 volatile metabolites were released from S. pneumoniae and 28 from H. influenzae, comprising alcohols, aldehydes, esters, hydrocarbons, ketones and sulfur-containing compounds. For both species, acetic acid, acetaldehyde, methyl methacrylate, 2,3-butanedione and methanethiol were found in strongly elevated concentrations and 1-butanol and butanal in moderately elevated concentrations. In addition, characteristic volatile biomarkers were detected for both bacterial species and exclusively for S. pneumoniae, also catabolism of aldehydes (3-methylbutanal and hexanal) was found. The results obtained provide important input into the knowledge about volatile bacterial biomarkers, which may become particularly important for detection of pathogens in upper airways by breath-gas analysis in the future.

Molecular analysis of volatile metabolites released specifically by Staphylococcus aureus and Pseudomonas aeruginosa.

BACKGROUND: The routinely used microbiological diagnosis of ventilator associated pneumonia (VAP) is time consuming and often requires invasive methods for collection of human specimens (e.g. bronchoscopy). Therefore, it is of utmost interest to develop a non-invasive method for the early detection of bacterial infection in ventilated patients, preferably allowing the identification of the specific pathogens. The present work is an attempt to identify pathogen-derived volatile biomarkers in breath that can be used for early and non- invasive diagnosis of ventilator associated pneumonia (VAP). For this purpose, in vitro experiments with bacteria most frequently found in VAP patients, i.e. Staphylococcus aureus and Pseudomonas aeruginosa, were performed to investigate the release or consumption of volatile organic compounds (VOCs). RESULTS: Headspace samples were collected and preconcentrated on multibed sorption tubes at different time points and subsequently analyzed with gas chromatography mass spectrometry (GC-MS). As many as 32 and 37 volatile metabolites were released by S. aureus and P. aeruginosa, respectively. Distinct differences in the bacteria-specific VOC profiles were found, especially with regard to aldehydes (e.g. acetaldehyde, 3-methylbutanal), which were taken up only by P. aeruginosa but released by S. aureus. Differences in concentration profiles were also found for acids (e.g. isovaleric acid), ketones (e.g. acetoin, 2-nonanone), hydrocarbons (e.g. 2-butene, 1,10-undecadiene), alcohols (e.g. 2-methyl-1-propanol, 2-butanol), esters (e.g. ethyl formate, methyl 2-methylbutyrate), volatile sulfur compounds (VSCs, e.g. dimethylsulfide) and volatile nitrogen compounds (VNCs, e.g. 3-methylpyrrole).Importantly, a significant VOC release was found already 1.5 hours after culture start, corresponding to cell numbers of ~8*106 [CFUs/ml]. CONCLUSIONS: The results obtained provide strong evidence that the detection and perhaps even identification of bacteria could be achieved by determination of characteristic volatile metabolites, supporting the clinical use of breath-gas analysis as non-invasive method for early detection of bacterial lung infections.

Optimization of sampling parameters for collection and preconcentration of alveolar air by needle traps.

The approach for breath-VOCs' collection and preconcentration by applying needle traps was developed and optimized. The alveolar air was collected from only a few exhalations under visual control of expired CO(2) into a large gas-tight glass syringe and then warmed up to 45 °C for a short time to avoid condensation. Subsequently, a specially constructed sampling device equipped with Bronkhorst® electronic flow controllers was used for automated adsorption. This sampling device allows time-saving collection of expired/inspired air in parallel onto three different needle traps as well as improvement of sensitivity and reproducibility of NT-GC-MS analysis by collection of relatively large (up to 150 ml) volume of exhaled breath. It was shown that the collection of alveolar air derived from only a few exhalations into a large syringe followed by automated adsorption on needle traps yields better results than manual sorption by up/down cycles with a 1 ml syringe, mostly due to avoided condensation and electronically controlled stable sample flow rate. The optimal profile and composition of needle traps consists of 2 cm Carbopack X and 1 cm Carboxen 1000, allowing highly efficient VOCs' enrichment, while injection by a fast expansive flow technique requires no modifications in instrumentation and fully automated GC-MS analysis can be performed with a commercially available autosampler. This optimized analytical procedure considerably facilitates the collection and enrichment of alveolar air, and is therefore suitable for application at the bedside of critically ill patients in an intensive care unit. Due to its simplicity it can replace the time-consuming sampling of sufficient breath volume by numerous up/down cycles with a 1 ml syringe.

Temporal profiling of human urine VOCs and its potential role under the ruins of collapsed buildings.

CONTEXT: The scent profile of human urine was investigated as potential source of chemical markers of human presence in collapsed buildings after natural or man-made disasters. OBJECTIVE: The main goals of this study were to build a library of potential biomarkers of human urine to be used for the detection of entrapped victims and to further examine their evolution profile in time. MATERIALS AND METHODS: Headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) was used to detect and identify the volatile organic compounds (VOCs) spontaneously released from urine of 20 healthy volunteers. Additionally, the evolution of human urine headspace during four days storage at room temperature was investigated. RESULTS: 33 omnipresent species with incidence higher than 80% were selected as potential urine markers. The most represented chemical classes were ketones with 10 representatives, aldehydes (7 species) and sulfur compounds (7 species). The monitoring of the evolution of the urine scent demonstrated an increase in the emission of 26 omnipresent urinary volatiles (rise from 36% to 526%). The highest increase was noted for dimethyldisulfide and dimethyltrisulfide (fivefold increase) and 3-methyl-2-butanone, 4-methyl-2-pentanone and 3-hexanone (fourfold rise). Only three compounds exhibited decreasing trend; dimethylsulfone, octanal and propanal. CONCLUSION: The ubiquitous urine VOCs identified within this study create a library of potential markers of human urine to be verified in further field studies, involving portable and sensitive instruments, directly applied in the field.