Variability in the concentrations of volatile metabolites emitted by genotypically different strains of Pseudomonas aeruginosa

The Potential of Fecal Volatile Organic Compound Analysis for the Early Diagnosis of Late-Onset Sepsis in Preterm Infants: A Narrative Review

Early diagnosis and treatment of late-onset sepsis (LOS) is crucial for survival, but challenging. Intestinal microbiota and metabolome alterations precede the clinical onset of LOS, and the preterm gut is considered an important source of bacterial pathogens. Fecal volatile organic compounds (VOCs), formed by physiologic and pathophysiologic metabolic processes in the preterm gut, reflect a complex interplay between the human host, the environment, and microbiota. Disease-associated fecal VOCs can be detected with an array of devices with various potential for the development of a point-of-care test (POCT) for preclinical LOS detection. While characteristic VOCs for common LOS pathogens have been described, their VOC profiles often overlap with other pathogens due to similarities in metabolic pathways, hampering the construction of species-specific profiles. Clinical studies have, however, successfully discriminated LOS patients from healthy individuals using fecal VOC analysis with the highest predictive value for Gram-negative pathogens. This review discusses the current advancements in the development of a non-invasive fecal VOC-based POCT for early diagnosis of LOS, which may potentially provide opportunities for early intervention and targeted treatment and could improve clinical neonatal outcomes. Identification of confounding variables impacting VOC synthesis, selection of an optimal detection device, and development of standardized sampling protocols will allow for the development of a novel POCT in the near future.

Modern approaches for detection of volatile organic compounds in metabolic studies focusing on pathogenic bacteria: Current state of the art

Pathogenic microorganisms produce numerous metabolites, including volatile organic compounds (VOCs). Monitoring these metabolites in biological matrices (e.g., urine, blood, or breath) can reveal the presence of specific microorganisms, enabling the early diagnosis of infections and the timely implementation of targeted therapy. However, complex matrices only contain trace levels of VOCs, and their constituent components can hinder determination of these compounds. Therefore, modern analytical techniques enabling the non-invasive identification and precise quantification of microbial VOCs are needed. In this paper, we discuss bacterial VOC analysis under in vitro conditions, in animal models and disease diagnosis in humans, including techniques for offline and online analysis in clinical settings. We also consider the advantages and limitations of novel microextraction techniques used to prepare biological samples for VOC analysis, in addition to reviewing current clinical studies on bacterial volatilomes that address inter-species interactions, the kinetics of VOC metabolism, and species- and drug-resistance specificity.

Volatilomic signatures of different strains of Helicobacter pylori

BACKGROUND

Helicobacter pylori (H. pylori) infection is the most extensively studied risk factor for gastric cancer. As with any bacteria, H. pylori will release distinctive odors that result from an emission of volatile metabolic byproducts in unique combinations and proportions. Effectively capturing and identifying these volatiles can pave the way for the development of innovative and non-invasive diagnostic methods for determining infection. Here we characterize the H. pylori volatilomic signature, pinpoint potential biomarkers of its presence, and evaluate the variability of volatilomic signatures between different H. pylori isolates.

MATERIALS AND METHODS

Using needle trap extraction, volatiles in the headspace above H. pylori cultures were collected and, following thermal desorption at 290°C in a splitless mode, were analyzed using gas chromatography-mass spectrometry. The resulting volatilomic signatures of H. pylori cultures were compared to those obtained from an analysis of the volatiles in the headspace above the cultivating medium only.

RESULTS

Amongst the volatiles detected, 21 showed consistent differences between the bacteria cultures and the cultivation medium, with 11 compounds being elevated and 10 showing decreased levels in the culture's headspace. The 11 elevated volatiles are four ketones (2-pentanone, 5-methyl-3-heptanone, 2-heptanone, and 2-nonanone), three alcohols (2-methyl-1-propanol, 3-methyl-1-butanol, and 1 butanol), one aromatic (styrene), one aldehyde (2-ethyl-hexanal), one hydrocarbon (n-octane), and one sulfur compound (dimethyl disulfide). The 10 volatiles with lower levels in the headspace of the cultures are four aldehydes (2-methylpropanal, benzaldehyde, 3-methylbutanal, and butanal), two heterocyclic compounds (2-ethylfuran and 2-pentylfuran), one ketone (2-butanone), one aromatic (benzene), one alcohol (2-butanol) and bromodichloromethane. Of the volatile species showing increased levels, the highest emissions are found to be for 3-methyl-1-butanol, 1-butanol and dimethyl disulfide. Qualitative variations in their emissions from the different isolates was observed.

CONCLUSIONS

The volatiles emitted by H. pylori provide a characteristic volatilome signature that has the potential of being developed as a tool for monitoring infections caused by this pathogen. Furthermore, using the volatilome signature, we are able to differentiate different isolates of H. pylori. However, the volatiles also represent potential confounders for the recognition of gastric cancer volatile markers.

Volatilomes of human infection

The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.

Microbial volatile organic compounds as novel indicators of anaerobic digestion instability: Potential and challenges

The wide application of anaerobic digestion (AD) technology is limited by process fluctuations. Thus, process monitoring based on screening state parameters as early warning indicators (EWI) is a top priority for AD facilities. However, predicting anaerobic digester stability based on such indicators is difficult, and their threshold values are uncertain, case-specific, and sometimes produce conflicting results. Thus, new EWI should be proposed to integrate microbial and metabolic information. These microbial volatile organic compounds (mVOCs) including alkanes, alkenes, alkynes, aromatic compounds are produced by microorganisms (bacteria, archaea and fungi), which might serve as a promising diagnostic tool for environmental monitoring. Moreover, mVOCs diffuse in both gas and liquid phases and are considered the language of intra kingdom microbial interactions. Herein, we highlight the potential of mVOCs as EWI for AD process instability, including discussions regarding characteristics and sources of mVOCs as well as sampling and determination methods. Furthermore, existing challenges must be addressed, before mVOCs profiling can be used as an early warning system for diagnosing AD process instability, such as mVOCs sampling, analysis and identification. Finally, we discuss the potential biotechnology applications of mVOCs and approaches to overcome the challenges regarding their application.

Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota?

It has been shown that the gut microbiota plays a central role in human health and disease. A wide range of volatile metabolites present in exhaled breath have been linked with gut microbiota and proposed as a non-invasive marker for monitoring pathological conditions. The aim of this study was to examine the possible correlation between volatile organic compounds (VOCs) in exhaled breath and the fecal microbiome by multivariate statistical analysis in gastric cancer patients (n = 16) and healthy controls (n = 33). Shotgun metagenomic sequencing was used to characterize the fecal microbiota. Breath-VOC profiles in the same participants were identified by an untargeted gas chromatography-mass spectrometry (GC-MS) technique. A multivariate statistical approach involving a canonical correlation analysis (CCA) and sparse principal component analysis identified the significant relationship between the breath VOCs and fecal microbiota. This relation was found to differ between gastric cancer patients and healthy controls. In 16 cancer cases, 14 distinct metabolites identified from the breath belonging to hydrocarbons, alcohols, aromatics, ketones, ethers, and organosulfur compounds were highly correlated with 33 fecal bacterial taxa (correlation of 0.891, p-value 0.045), whereas in 33 healthy controls, 7 volatile metabolites belonging to alcohols, aldehydes, esters, phenols, and benzamide derivatives correlated with 17 bacterial taxa (correlation of 0.871, p-value 0.0007). This study suggested that the correlation between fecal microbiota and breath VOCs was effective in identifying exhaled volatile metabolites and the functional effects of microbiome, thus helping to understand cancer-related changes and improving the survival and life expectancy in gastric cancer patients.

Analytical methods for assessing antimicrobial activity of nanomaterials in complex media: advances, challenges, and perspectives

Assessing the antimicrobial activity of engineered nanomaterials (ENMs), especially in realistic scenarios, is of great significance for both basic research and applications. Multiple analytical methods are available for analysis via off-line or on-line measurements. Real-world samples are often complex with inorganic and organic components, which complicates the measurements of microbial viability and/or metabolic activity. This article highlights the recent advances achieved in analytical methods including typical applications and specifics regarding their accuracy, cost, efficiency, and user-friendliness. Methodological drawbacks, technique gaps, and future perspectives are also discussed. This review aims to help researchers select suitable methods for gaining insight into antimicrobial activities of targeted ENMs in artificial and natural complex matrices.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

An Investigation of Stability and Species and Strain-Level Specificity in Bacterial Volatilomes

Microbial volatilomics is a rapidly growing field of study and has shown great potential for applications in food, farming, and clinical sectors in the future. Due to the varying experimental methods and growth conditions employed in microbial volatilomic studies as well as strain-dependent volatilomic differences, there is limited knowledge regarding the stability of microbial volatilomes. Consequently, cross-study comparisons and validation of results and data can be challenging. In this study, we investigated the stability of the volatilomes of multiple strains of Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli across three frequently used nutrient-rich growth media. Volatilomic stability was assessed based on media-, time- and strain-dependent variation across the examined bacterial volatilomes. Strain-level specificity of the observed volatilomes of E. coli and P. aeruginosa strains was further investigated by comparing the emission of selected compounds at varying stages of cell growth. Headspace solid phase microextraction (HS-SPME) sampling coupled with gas chromatography mass spectrometry (GC-MS) was used to analyze the volatilome of each strain. The whole volatilomes of the examined strains demonstrate a high degree of stability across the three examined growth media. At the compound-level, media dependent differences were observed particularly when comparing the volatilomes obtained in glucose-containing brain heart infusion (BHI) and tryptone soy broth (TSB) growth media with the volatilomes obtained in glucose-free Lysogeny broth (LB) media. These glucose-dependent volatilomic differences were primarily seen in the emission of primary metabolites such as alcohols, ketones, and acids. Strain-level differences in the emission of specific compounds in E. coli and P. aeruginosa samples were also observed across the media. These strain-level volatilomic differences were also observed across varying phases of growth of each strain, therefore confirming that these strains had varying core and accessory volatilomes. Our results demonstrate that, at the species-level, the examined bacteria have a core volatilome that exhibits a high-degree of stability across frequently-used growth media. Media-dependent differences in microbial volatilomes offer valuable insights into identifying the cellular origin of individual metabolites. The observed differences in the core and accessory volatilomes of the examined strains illustrate the complexity of microbial volatilomics as a study while also highlighting the need for more strain-level investigations to ultimately elucidate the whole volatilomic capabilities of microbial species in the future.

Real-time detection of volatile metabolites enabling species-level discrimination of bacterial biofilms associated with wound infection

Aims

The main aim of this study was to investigate the real‐time detection of volatile metabolites for the species‐level discrimination of pathogens associated with clinically relevant wound infection, when grown in a collagen wound biofilm model.

Methods and Results

This work shows that Staphylococcus aureus, Pseudomonas aeruginosa and Streptococcus pyogenes produce a multitude of volatile compounds when grown as biofilms in a collagen‐based biofilm model. The real‐time detection of these complex volatile profiles using selected ion flow tube mass spectrometry and the use of multivariate statistical analysis on the resulting data can be used to successfully differentiate between the pathogens studied.

Conclusions

The range of bacterial volatile compounds detected between the species studied vary and are distinct. Discrimination between bacterial species using real‐time detection of volatile metabolites and multivariate statistical analysis was successfully demonstrated.

Significance and Impact of the Study

Development of rapid point‐of‐care diagnostics for wound infection would improve diagnosis and patient care. Such technological approaches would also facilitate the appropriate use of antimicrobials, minimizing the emergence of antimicrobial resistance. This study further develops the use of volatile metabolite detection as a new diagnostic approach for wound infection.

Thriving Under Stress: Pseudomonas aeruginosa Outcompetes the Background Polymicrobial Community Under Treatment Conditions in a Novel Chronic Wound Model

In vitro infection models are important for studying the effects of antimicrobials on microbial growth and metabolism. However, many models lack important biological components that resemble the polymicrobial nature of chronic wounds or infections. In this study, we developed a perfused meat model that supports the growth of the human pathogen Pseudomonas aeruginosa in a native meat microbial background to investigate the impact of antibiotics and hydrogen peroxide on polymicrobial community growth and metabolism. P. aeruginosa plays an important role as an etiological agent involved in chronic infections and is a common opportunistic pathogen. Chemical stressors in the form of hydrogen peroxide, carbenicillin, and gentamicin were perfused through the meat with polymicrobial growth on the surface. The relative abundances of P. aeruginosa and the background microbial community were analyzed by cell viability assays, and metabolic changes of the entire community in response to different antimicrobial treatments were characterized by GC-MS analysis of volatile organic compounds. The meat background community was characterized by amplicon sequencing. Relative densities of P. aeruginosa and background microbiota were similar under control conditions. Antimicrobial stressors, even at sub-inhibitory, physiologically relevant concentrations, spurred P. aeruginosa dominance of the meat surface community. Volatile metabolite ion intensity levels showed that antibacterial treatments drive changes in microbial metabolism. The abundance of the P. aeruginosa-derived metabolite, acetophenone, remained stable with treatment, whereas the relative abundances of 2-butanone, 2-nonanone, and 2-aminoacetophenone changed in response to treatment, suggesting these could serve as biomarkers of infection. Our model recapitulates some of the physiological conditions of chronic wounds and facilitates high throughput experiments without the high cost of in vivo models. Expanded use of this perfusion model will contribute to the understanding of polymicrobial growth and metabolism in the context of chronic wounds and infections.

Multi-strain volatile profiling of pathogenic and commensal cutaneous bacteria

The detection of volatile organic compounds (VOC) emitted by pathogenic bacteria has been proposed as a potential non-invasive approach for characterising various infectious diseases as well as wound infections. Studying microbial VOC profiles in vitro allows the mechanisms governing VOC production and the cellular origin of VOCs to be deduced. However, inter-study comparisons of microbial VOC data remains a challenge due to the variation in instrumental and growth parameters across studies. In this work, multiple strains of pathogenic and commensal cutaneous bacteria were analysed using headspace solid phase micro-extraction coupled with gas chromatography-mass spectrometry. A kinetic study was also carried out to assess the relationship between bacterial VOC profiles and the growth phase of cells. Comprehensive bacterial VOC profiles were successfully discriminated at the species-level, while strain-level variation was only observed in specific species and to a small degree. Temporal emission kinetics showed that the emission of particular compound groups were proportional to the respective growth phase for individual S. aureus and P. aeruginosa samples. Standardised experimental workflows are needed to improve comparability across studies and ultimately elevate the field of microbial VOC profiling. Our results build on and support previous literature and demonstrate that comprehensive discriminative results can be achieved using simple experimental and data analysis workflows.

Pseudomonas aeruginosa Volatilome Characteristics and Adaptations in Chronic Cystic Fibrosis Lung Infections

Pseudomonas aeruginosa is a leading cause of chronic lung infections in cystic fibrosis (CF), which are correlated with lung function decline. Significant clinical efforts are therefore aimed at detecting infections and tracking them for phenotypic changes, such as mucoidy and antibiotic resistance. Both the detection and tracking of lung infections rely on sputum cultures, but due to improvements in CF therapies, sputum production is declining, although risks for lung infections persist. Therefore, we are working toward the development of breath-based diagnostics for CF lung infections. In this study, we characterized of the volatile metabolomes of 81 P. aeruginosa clinical isolates collected from 17 CF patients over a duration of at least 5 years of a chronic lung infection. We found that the volatilome of P. aeruginosa adapts over time and is correlated with infection phenotype changes, suggesting that it may be possible to track chronic CF lung infections with a breath test.

Pseudomonas aeruginosa chronic lung infections in individuals with cystic fibrosis (CF) significantly reduce quality of life and increase morbidity and mortality. Tracking these infections is critical for monitoring patient health and informing treatments. We are working toward the development of novel breath-based biomarkers to track chronic P. aeruginosa lung infections in situ. Using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC–TOF-MS), we characterized the in vitro volatile metabolomes (“volatilomes”) of 81 P. aeruginosa isolates collected from 17 CF patients over at least a 5-year period of their chronic lung infections. We detected 539 volatiles produced by the P. aeruginosa isolates, 69 of which were core volatiles that were highly conserved. We found that each early infection isolate has a unique volatilome, and as infection progresses, the volatilomes of isolates from the same patient become increasingly dissimilar, to the point that these intrapatient isolates are no more similar to one another than to isolates from other patients. We observed that the size and chemical diversity of P. aeruginosa volatilomes do not change over the course of chronic infections; however, the relative abundances of core hydrocarbons, alcohols, and aldehydes do change and are correlated with changes in phenotypes associated with chronic infections. This study indicates that it may be feasible to track P. aeruginosa chronic lung infections by measuring changes to the infection volatilome and lays the groundwork for exploring the translatability of this approach to direct measurement using patient breath.

IMPORTANCEPseudomonas aeruginosa is a leading cause of chronic lung infections in cystic fibrosis (CF), which are correlated with lung function decline. Significant clinical efforts are therefore aimed at detecting infections and tracking them for phenotypic changes, such as mucoidy and antibiotic resistance. Both the detection and tracking of lung infections rely on sputum cultures, but due to improvements in CF therapies, sputum production is declining, although risks for lung infections persist. Therefore, we are working toward the development of breath-based diagnostics for CF lung infections. In this study, we characterized of the volatile metabolomes of 81 P. aeruginosa clinical isolates collected from 17 CF patients over a duration of at least 5 years of a chronic lung infection. We found that the volatilome of P. aeruginosa adapts over time and is correlated with infection phenotype changes, suggesting that it may be possible to track chronic CF lung infections with a breath test.

Aspergillus Is Inhibited by Pseudomonas aeruginosa Volatiles

Background: Pseudomonas aeruginosa (Pa) and Aspergillus fumigatus (Af) compete with each other for nutrients and survival in natural environments, and have been extensively studied because of their intermicrobial interactions in the human microbiome. These are the principal microbes infecting immunocompromised patients and persons with cystic fibrosis, particularly the airways. These intermicrobial studies have largely been conducted in liquid medium or on agar, and thus focus on soluble or diffusible microbial products. Several key inhibitory molecules were defined in such studies. Methods: in the present report, we examine several methodologies which can be conveniently used to study the interaction of microbial volatiles, including capture methods and kinetics. Results: Pa volatiles inhibit Af, and the inhibitory mechanism appears to be the incorporation of the inhibitory molecules into the substrate nourishing the Af, rather than directly onto Af structures. We define by mass spectroscopy some specific volatile Pa products that can inhibit Af. Some of these molecules are selected for interest by the study of gene deletion mutants, producing a few Pa strains that were impaired in inhibition. We presumed the volatiles of these latter strains could be excluded from the search for inhibitors. Conclusion: the Pa inhibition of Af via a gaseous phase could be critical components in their competition, particularly in airways, where more direct contact may not be extensive.

Review of Potential Pseudomonas Weaponry, Relevant to the Pseudomonas-Aspergillus Interplay, for the Mycology Community

Pseudomonas aeruginosa is one of the most prominent opportunistic bacteria in airways of cystic fibrosis patients and in immunocompromised patients. These bacteria share the same polymicrobial niche with other microbes, such as the opportunistic fungus Aspergillus fumigatus. Their inter-kingdom interactions and diverse exchange of secreted metabolites are responsible for how they both fare in competition for ecological niches. The outcomes of their contests likely determine persistent damage and degeneration of lung function. With a myriad of virulence factors and metabolites of promising antifungal activity, P. aeruginosa products or their derivatives may prove useful in prophylaxis and therapy against A. fumigatus. Quorum sensing underlies the primary virulence strategy of P. aeruginosa, which serves as cell–cell communication and ultimately leads to the production of multiple virulence factors. Understanding the quorum-sensing-related pathogenic mechanisms of P. aeruginosa is a first step for understanding intermicrobial competition. In this review, we provide a basic overview of some of the central virulence factors of P. aeruginosa that are regulated by quorum-sensing response pathways and briefly discuss the hitherto known antifungal properties of these virulence factors. This review also addresses the role of the bacterial secretion machinery regarding virulence factor secretion and maintenance of cell–cell communication.

A Phylogenetic and Functional Perspective on Volatile Organic Compound Production by Actinobacteria

Soil microbes produce a diverse array of natural products, including volatile organic compounds (VOCs). Volatile compounds are important molecules in soil habitats, where they mediate interactions between bacteria, fungi, insects, plants, and animals. We measured the VOCs produced by a broad diversity of soil- and dust-dwelling Actinobacteria in vitro. We detected a total of 126 unique volatile compounds, and each strain produced a unique combination of VOCs. While some of the compounds were produced by many strains, most were strain specific. Importantly, VOC profiles were more similar between closely related strains, indicating that evolutionary and ecological processes generate predictable patterns of VOC production. Finally, we observed that actinobacterial VOCs had both stimulatory and inhibitory effects on the growth of bacteria that represent a plant-beneficial symbiont and a plant-pathogenic strain, information that may lead to the development of novel strategies for plant disease prevention.

Soil microbes produce an immense diversity of metabolites, including volatile organic compounds (VOCs), which can shape the structure and function of microbial communities. VOCs mediate a multitude of microbe-microbe interactions, including antagonism. Despite their importance, the diversity and functional relevance of most microbial volatiles remain uncharacterized. We assembled a taxonomically diverse collection of 48 Actinobacteria isolated from soil and airborne dust and surveyed the VOCs produced by these strains on two different medium types in vitro using gas chromatography-mass spectrometry (GC-MS). We detected 126 distinct VOCs and structurally identified approximately 20% of these compounds, which were predominately C₁ to C₅ hetero-VOCs, including (oxygenated) alcohols, ketones, esters, and nitrogen- and sulfur-containing compounds. Each strain produced a unique VOC profile. While the most common VOCs were likely by-products of primary metabolism, most of the VOCs were strain specific. We observed a strong taxonomic and phylogenetic signal for VOC profiles, suggesting their role in finer-scale patterns of ecological diversity. Finally, we investigated the functional potential of these VOCs by assessing their effects on growth rates of both pathogenic and nonpathogenic pseudomonad strains. We identified sets of VOCs that correlated with growth inhibition and stimulation, information that may facilitate the development of microbial VOC-based pathogen control strategies.

IMPORTANCE Soil microbes produce a diverse array of natural products, including volatile organic compounds (VOCs). Volatile compounds are important molecules in soil habitats, where they mediate interactions between bacteria, fungi, insects, plants, and animals. We measured the VOCs produced by a broad diversity of soil- and dust-dwelling Actinobacteria in vitro. We detected a total of 126 unique volatile compounds, and each strain produced a unique combination of VOCs. While some of the compounds were produced by many strains, most were strain specific. Importantly, VOC profiles were more similar between closely related strains, indicating that evolutionary and ecological processes generate predictable patterns of VOC production. Finally, we observed that actinobacterial VOCs had both stimulatory and inhibitory effects on the growth of bacteria that represent a plant-beneficial symbiont and a plant-pathogenic strain, information that may lead to the development of novel strategies for plant disease prevention.

Breath metabolome of mice infected with Pseudomonas aeruginosa

INTRODUCTION

The measurement of specific volatile organic compounds in breath has been proposed as a potential diagnostic for a variety of diseases. The most well-studied bacterial lung infection in the breath field is that caused by Pseudomonas aeruginosa.

OBJECTIVES

To determine a discriminatory core of molecules in the "breath-print" of mice during a lung infection with four strains of P. aeruginosa (PAO1, PA14, PAK, PA7). Furthermore, we attempted to extrapolate a strain-specific "breath-print" signature to investigate the possibility of recapitulating the genetic phylogenetic groups (Stewart et al. Pathog Dis 71(1), 20-25, 2014. https://doi.org/10.1111/2049-632X.12107 ).

METHODS

Breath was collected into a Tedlar bag and shortly after drawn into a thermal desorption tube. The latter was then analyzed into a comprehensive multidimensional gas chromatography coupled with a time-of-flight mass spectrometer. Random forest algorithm was used for selecting the most discriminatory features and creating a prediction model.

RESULTS

Three hundred and one molecules were significantly different between animals infected with P. aeruginosa, and those given a sham infection (PBS) or inoculated with UV-killed P. aeruginosa. Of those, nine metabolites could be used to discriminate between the three groups with an accuracy of 81%. Hierarchical clustering showed that the signature from breath was due to a specific response to live bacteria instead of a generic infection response. Furthermore, we identified ten additional volatile metabolites that could differentiate mice infected with different strains of P. aeruginosa. A phylogram generated from the ten metabolites showed that PAO1 and PA7 were the most distinct group, while PAK and PA14 were interspersed between the former two groups.

CONCLUSIONS

To the best of our knowledge, this is the first study to report on a 'core' murine breath print, as well as, strain level differences between the compounds in breath. We provide identifications (by running commercially available analytical standards) to five breath compounds that are predictive of P. aeruginosa infection.

Ex vivo emission of volatile organic compounds from gastric cancer and non-cancerous tissue

The presence of certain volatile organic compounds (VOCs) in the breath of patients with gastric cancer has been reported by a number of research groups; however, the source of these compounds remains controversial. Comparison of VOCs emitted from gastric cancer tissue to those emitted from non-cancerous tissue would help in understanding which of the VOCs are associated with gastric cancer and provide a deeper knowledge on their generation. Gas chromatography with mass spectrometric detection (GC-MS) coupled with head-space needle trap extraction (HS-NTE) as the pre-concentration technique, was used to identify and quantify VOCs released by gastric cancer and non-cancerous tissue samples collected from 41 patients during surgery. Excluding contaminants, a total of 32 VOCs were liberated by the tissue samples. The emission of four of them (carbon disulfide, pyridine, 3-methyl-2-butanone and 2-pentanone) was significantly higher from cancer tissue, whereas three compounds (isoprene, γ-butyrolactone and dimethyl sulfide) were in greater concentration from the non-cancerous tissues (Wilcoxon signed-rank test, p < 0.05). Furthermore, the levels of three VOCs (2-methyl-1-propene, 2-propenenitrile and pyrrole) were correlated with the occurrence of H. pylori; and four compounds (acetonitrile, pyridine, toluene and 3-methylpyridine) were associated with tobacco smoking. Ex vivo analysis of VOCs emitted by human tissue samples provides a unique opportunity to identify chemical patterns associated with a cancerous state and can be considered as a complementary source of information on volatile biomarkers found in breath, blood or urine.

Volatile fingerprinting of Pseudomonas aeruginosa and respiratory syncytial virus infection in an in vitro cystic fibrosis co-infection model

Volatile molecules in exhaled breath represent potential biomarkers in the setting of infectious diseases, particularly those affecting the respiratory tract. In particular, Pseudomonas aeruginosa is a critically important respiratory pathogen in specific subsets of the population, such as those with cystic fibrosis (CF). Infections caused by P. aeruginosa can be particularly problematic when co-infection with respiratory syncytial virus (RSV) occurs, as this is correlated with the establishment of chronic P. aeruginosa infection. In the present study, we evaluate the volatile metabolites produced by P. aeruginosa (PAO1)-infected, RSV-infected, co-infected, or uninfected CF bronchial epithelial (CFBE) cells, in vitro. We identified a volatile metabolic signature that could discriminate between P. aeruginosa-infected and non-P. aeruginosa-infected CFBE with an area under the receiver operating characteristic curve (AUROC) of 0.850, using the machine learning algorithm random forest (RF). Although we could not discriminate between RSV-infected and non-RSV-infected CFBE (AUROC = 0.431), we note that sample classification probabilities for RSV-infected cell, generated using RF, were between those of uninfected CFBE and P. aeruginosa-infected CFBE, suggesting that RSV infection may result in a volatile metabolic profile that shares attributes with both of these groups. To more precisely elucidate the biological origins of the volatile metabolites that were discriminatory between P. aeruginosa-infected and non-P. aeruginosa-infected CFBE, we measured the volatile metabolites produced by P. aeruginosa grown in the absence of CFBE. Our findings suggest that the discriminatory metabolites produced likely result from the interaction of P. aeruginosa with the CFBE cells, rather than the metabolism of media components by the bacterium. Taken together, our findings support the notion that P. aeruginosa interacting with CFBE yields a particular volatile metabolic signature. Such a signature may have clinical utility in the monitoring of individuals with CF.

Evaluation of lipid peroxidation by the analysis of volatile aldehydes in the headspace of synthetic membranes using Selected Ion Flow Tube Mass Spectrometry, SIFT-MS

RATIONALE

Oxidative stress of cell membranes leads to a number of pathological processes associated with some diseases and is accompanied by the release of volatile aldehydes, which, potentially, can be used as biomarkers. Thus, the aim was to investigate peroxidation of defined synthetic membranes by direct quantitative analysis of volatile aldehydes.

METHODS

The concentration spectra of volatile compounds present in the headspace of synthetic membranes under peroxidation stress and following mechanical stress due to sonication were obtained using solid phase microextraction (SPME) in combination with Gas Chromatography Mass Spectrometry (SPME/GC/MS) and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS). The focus was on the direct, real time quantification of volatile aldehydes. In addition, the total aldehydes in the aqueous membrane suspensions were quantified using the TBARS method.

RESULTS

Propanal, butanal, pentanal, hexanal, heptanal and malondialdehyde were detected and quantified in the humid headspace of the media containing the synthetic membranes following peroxidation. The composition and concentration of these saturated aldehydes strongly depend on the unsaturated fatty acids representation in the liposomes. Some protective effect of cholesterol was observed especially for membranes peroxidised by Fenton reagents and after application of a mechanical stress.

CONCLUSIONS

This study demonstrates that peroxidation of model synthetic membranes in vitro can be tracked in real time using direct quantification by SIFT-MS of several specific aldehydes in the headspace of the membrane suspensions. Cholesterol plays an important role in retaining membrane structure and can indirectly protect membranes from lipid peroxidation.

Efficacy of Various Preservatives on Extending Shelf Life of Vacuum-Packaged Raw Pork during 4°C Storage

Uncontrolled bacterial growth and metabolic activities are responsible for the short shelf life of raw pork. Culture-independent analysis by 16S ribosome cDNA could reveal viable bacteria in raw pork. This study investigated microbial growth and volatile organic compounds of raw pork supplemented with various preservatives. Vacuum-packaged raw pork was stored at 4°C, after soaking in solutions of potassium sorbate, ε-poly-l-lysine, kojic acid (KA), or sodium diacetate, individually. Spoilage of raw pork was monitored by determining pH and total volatile basic nitrogen, whereas bacterial growth was determined by culture-dependent and culture-independent analyses. Data indicated that all the preservatives were able to inhibit bacterial growth and extend the shelf life of pork. High-throughput sequencing of 16S ribosome cDNA indicated that Pseudomonas was inhibited under vacuum conditions, whereas facultative anaerobes ( Acinetobacter, Photobacterium, Brochothrix, and Myroides) were the most active genera in the spoiled pork. Photobacterium was further inhibited by each preservative. The inhibition of Acinetobacter, Photobacterium, and Myroides could be responsible for the extended shelf life of vacuum-packaged pork; they were effectively inhibited by KA, which also induced the longest shelf life. Moreover, 19 types of volatile organic compounds were detected. 3-Methylbutanol, 3-methylbutanol acetate, 2-butanone, toluene, benzeneacetaldehyde, dimethyl trisulfide, and acetoin were associated with spoilage. Furthermore, KA is a potential preservative in raw pork; because no phenol was detectable within 35 days, excessive intake of phenol induced by preservatives was avoided.

Volatile molecules from bronchoalveolar lavage fluid can 'rule-in' Pseudomonas aeruginosa and 'rule-out' Staphylococcus aureus infections in cystic fibrosis patients

Respiratory infections caused by Pseudomonas aeruginosa and Staphylococcus aureus are the leading cause of morbidity and mortality in cystic fibrosis (CF) patients. The authors aimed to identify volatile biomarkers from bronchoalveolar lavage (BAL) samples that can guide breath biomarker development for pathogen identification. BAL samples (n = 154) from CF patients were analyzed using two-dimensional gas chromatography time-of-flight mass spectrometry. Random Forest was used to select suites of volatiles for identifying P. aeruginosa-positive and S. aureus-positive samples using multiple infection scenarios and validated using test sets. Using nine volatile molecules, we differentiated P. aeruginosa-positive (n = 7) from P. aeruginosa-negative (n = 53) samples with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.71–1.00) and with positive and negative predictive values of 0.67 (95% CI 0.38–0.75) and 0.92 (95% CI 0.88–1.00), respectively. We were also able to discriminate S. aureus-positive (n = 15) from S. aureus-negative (n = 45) samples with an AUROC of 0.88 (95% CI 0.79-1.00) using eight volatiles and with positive and negative predictive values of 0.86 (95% CI 0.61–0.96) and 0.70 (95% CI 0.61–0.75), respectively. Prospective validation of identified biomarkers as screening tools in patient breath may lead to clinical application.

On the importance of accurate quantification of individual volatile metabolites in exhaled breath

It is argued that shortcomings of certain approaches to breath analysis research based on superficial interpretation of non-quantitative data are inadvertently inhibiting the progression of non-invasive breath analysis into clinical practice. The objective of this perspective is to suggest more clinically profitable approaches to breath research. Thus, following a discourse on the challenges and expectations in breath research, a brief indication is given of the analytical techniques currently used for the analysis of very humid exhaled breath. The seminal work that has been carried out using GC-MS revealed that exhaled breath comprises large numbers of trace volatile organic compounds, VOCs. Unfortunately, analysis of these valuable GC-MS data is mostly performed using chemometrics to distinguish the VOC content of breath samples collected from patients and healthy controls, and reliable quantification of the VOCs is rarely deemed necessary. This limited approach ignores the requirements of clinically acceptable biomarkers and misses the opportunity to identify relationships between the concentrations of individual VOCs and certain related physiological or metabolic parameters. Therefore, a plea is made for more effort to be directed towards the positive identification and accurate quantification of individual VOCs in exhaled breath, which are more physiologically meaningful as best exemplified by the quantification of breath nitric oxide, NO. Support for the value of individual VOC quantification is illustrated by the SIFT-MS studies of breath hydrogen cyanide, HCN, a biomarker of Pseudomonas aeruginosa infection, breath acetic acid as an indicator of airways acidification in cystic fibrosis patients, and n-pentane as a breath biomarker of inflammation in idiopathic bowel disease patients. These single VOCs could be used as non-invasive monitors of the efficacy of therapeutic intervention. The increase of breath methanol following the ingestion of a known amount of the sweetener aspartame impressively shows that accurate breath analysis is a reliable indicator of blood concentrations. However, using individual VOCs for specific disease diagnosis does have its problems and it is, perhaps, more appropriate to see their concentrations as proxy markers of general underlying physiological change. We dedicate this perspective to Lars Gustafsson for his seminal work on breath research and especially for his pioneering work on nitric oxide measurements in exhaled breath in asthma, which best shows the utility and value of the quantification of individual breath biomarkers on which this perspective focuses.

Evaluation of peroxidative stress of cancer cells in vitro by real-time quantification of volatile aldehydes in culture headspace

RATIONALE

Peroxidation of lipids in cellular membranes results in the release of volatile organic compounds (VOCs), including saturated aldehydes. The real-time quantification of trace VOCs produced by cancer cells during peroxidative stress presents a new challenge to non-invasive clinical diagnostics, which as described here, we have met with some success.

METHODS

A combination of selected ion flow tube mass spectrometry (SIFT-MS), a technique that allows rapid, reliable quantification of VOCs in humid air and liquid headspace, and electrochemistry to generate reactive oxygen species (ROS) in vitro has been used. Thus, VOCs present in the headspace of CALU-1 cancer cell line cultures exposed to ROS have been monitored and quantified in real time using SIFT-MS.

RESULTS

The CALU-1 lung cancer cells were cultured in 3D collagen to mimic in vivo tissue. Real-time SIFT-MS analyses focused on the volatile aldehydes: propanal, butanal, pentanal, hexanal, heptanal and malondialdehyde (propanedial), that are expected to be products of cellular membrane peroxidation. All six aldehydes were identified in the culture headspace, each reaching peak concentrations during the time of exposure to ROS and eventually reducing as the reactants were depleted in the culture. Pentanal and hexanal were the most abundant, reaching concentrations of a few hundred parts-per-billion by volume, ppbv, in the culture headspace.

CONCLUSIONS

The results of these experiments demonstrate that peroxidation of cancer cells in vitro can be monitored and evaluated by direct real-time analysis of the volatile aldehydes produced. The combination of adopted methodology potentially has value for the study of other types of VOCs that may be produced by cellular damage.

Mining the Volatilomes of Plant-Associated Microbiota for New Biocontrol Solutions

Microbial lifeforms associated with land plants represent a rich source for crop growth- and health-promoting microorganisms and biocontrol agents. Volatile organic compounds (VOCs) produced by the plant microbiota have been demonstrated to elicit plant defenses and inhibit the growth and development of numerous plant pathogens. Therefore, these molecules are prospective alternatives to synthetic pesticides and the determination of their bioactivities against plant threats could contribute to the development of control strategies for sustainable agriculture. In our previous study we investigated the inhibitory impact of volatiles emitted by Pseudomonas species isolated from a potato field against the late blight-causing agent Phytophthora infestans. Besides the well-documented emission of hydrogen cyanide, other Pseudomonas VOCs impeded P. infestans mycelial growth and sporangia germination. Current advances in the field support the emerging concept that the microbial volatilome contains unexploited, eco-friendly chemical resources that could help select for efficient biocontrol strategies and lead to a greener chemical disease management in the field.

Mass spectrometric techniques for the analysis of volatile organic compounds emitted from bacteria

Bacteria are the main cause of many human diseases. Typical bacterial identification methods, for example culture-based, serological and genetic methods, are time-consuming, delaying the potential for an early and accurate diagnosis and the appropriate subsequent treatment. Nevertheless, there is a stringent need for in situ tests that are rapid, noninvasive and sensitive, which will greatly facilitate timely treatment of the patients. This review article presents volatile organic metabolites emitted from various micro-organism strains responsible for common bacterial infections in humans. Additionally, the manuscript shows the application of different analytical techniques for fast bacterial identification. Details of these techniques are given, which focuses on their advantages and drawbacks in using for volatile organic components analysis.

Exhaled Breath Metabolomics for the Diagnosis of Pneumonia in Intubated and Mechanically-Ventilated Intensive Care Unit (ICU)-Patients

The diagnosis of hospital-acquired pneumonia remains challenging. We hypothesized that analysis of volatile organic compounds (VOCs) in exhaled breath could be used to diagnose pneumonia or the presence of pathogens in the respiratory tract in intubated and mechanically-ventilated intensive care unit patients. In this prospective, single-centre, cross-sectional cohort study breath from mechanically ventilated patients was analysed using gas chromatography-mass spectrometry. Potentially relevant VOCs were selected with a p-value < 0.05 and an area under the receiver operating characteristics curve (AUROC) above 0.7. These VOCs were used for principal component analysis and partial least square discriminant analysis (PLS-DA). AUROC was used as a measure of accuracy. Ninety-three patients were included in the study. Twelve of 145 identified VOCs were significantly altered in patients with pneumonia compared to controls. In colonized patients, 52 VOCs were significantly different. Partial least square discriminant analysis classified patients with modest accuracy (AUROC: 0.73 (95% confidence interval (CI): 0.57–0.88) after leave-one-out cross-validation). For determining the colonization status of patients, the model had an AUROC of 0.69 (95% CI: 0.57–0.82) after leave-one-out cross-validation. To conclude, exhaled breath analysis can be used to discriminate pneumonia from controls with a modest to good accuracy. Furthermore breath profiling could be used to predict the presence and absence of pathogens in the respiratory tract. These findings need to be validated externally.

Variations and heredity in bacterial colonies

Spontaneous variation in appearance was studied in bacterial colonies of Serratia marcescens F morphotype¹: (i) A defined array of non-heritable phenotype variations does appear repeatedly; (ii) The presence of colonies of different bacterial species will narrow the variability toward the typical F appearance, as if such an added environmental factor curtailed the capacity of colony morphospace; (iii) Similarly the morphospace becomes reduced by random mutations leading to new, heritable morphotypes—at the same time opening a new array of variations typical for the mutant but not accessible directly from the original F morphospace. Results are discussed in context with biphasic model of early morphogenesis applicable to all multicellular bodies.

Comparative analysis of the volatile metabolomes of Pseudomonas aeruginosa clinical isolates

Pseudomonas aeruginosa is a nearly ubiquitous Gram-negative organism, well known to occupy a multitude of environmental niches and cause human infections at a variety of bodily sites, due to its metabolic flexibility, secondary to extensive genetic heterogeneity at the species level. Because of its dynamic metabolism and clinical importance, we sought to perform a comparative analysis on the volatile metabolome (the 'volatilome') produced by P. aeruginosa clinical isolates. In this study, we analyzed the headspace volatile molecules of 24 P. aeruginosa clinical isolates grown in vitro, using 2D gas chromatography time-of-flight mass spectrometry (GC  ×  GC-TOFMS). We identified 391 non-redundant compounds that we associate with the growth and metabolism of P. aeruginosa (the 'pan-volatilome'). Of these, 70 were produced by all 24 isolates (the 'core volatilome'), 52 by only a single isolate, and the remaining 269 volatile molecules by a subset. Sixty-five of the detected compounds could be assigned putative compound identifications, of which 43 had not previously been associated with P. aeruginosa. Using the accessory volatile molecules, we determined the inter-strain variation in the metabolomes of these isolates, clustering strains by their metabotypes. Assessing the extent of metabolomic diversity in P. aeruginosa through an analysis of the volatile molecules that it produces is a critical next step in the identification of novel diagnostic or prognostic biomarkers.

Differentiation of pulmonary bacterial pathogens in cystic fibrosis by volatile metabolites emitted by their in vitro cultures: Pseudomonas aeruginosa, Staphylococcus aureus, Stenotrophomonas maltophilia and the Burkholderia cepacia complex

As a contribution to the continuing search for breath biomarkers of lung and airways infection in patients with cystic fibrosis, CF, we have analysed the volatile metabolites released in vitro by Pseudomonas aeruginosa and other bacteria involved in respiratory infections in these patients, i.e. those belonging to the Burkholderia cepacia complex, Staphylococcus aureus or Stenotrophomonas maltophilia. These opportunistic pathogens are generally harmless to healthy people but they may cause serious infections in patients with severe underlying disease or impaired immunity such as CF patients. Volatile organic compounds emitted from the cultures of strains belonging to the above-mentioned four taxa were analysed by selected ion flow tube mass spectrometry. In order to minimize the effect of differences in media composition all strains were cultured in three different liquid media. Multivariate statistical analysis reveals that the four taxa can be well discriminated by the differences in the headspace VOC concentration profiles. The compounds that should be targeted in breath as potential biomarkers of airway infection were identified for each of these taxa of CF pathogens.

Status of selected ion flow tube MS: accomplishments and challenges in breath analysis and other areas

This article reflects our observations of recent accomplishments made using selected ion flow tube MS (SIFT-MS). Only brief descriptions are given of SIFT-MS as an analytical method and of the recent extensions to the underpinning analytical ion chemistry required to realize more robust analyses. The challenge of breath analysis is given special attention because, when achieved, it renders analysis of other air media relatively straightforward. Brief overviews are given of recent SIFT-MS breath analyses by leading research groups, noting the desirability of detection and quantification of single volatile biomarkers rather than reliance on statistical analyses, if breath analysis is to be accepted into clinical practice. A 'strengths, weaknesses, opportunities and threats' analysis of SIFT-MS is made, which should help to increase its utility for trace gas analysis.

Direct detection and quantification of malondialdehyde vapour in humid air using selected ion flow tube mass spectrometry supported by gas chromatography/mass spectrometry

RATIONALE

It has been proposed that malondialdehyde (MDA) reflects free oxygen-radical lipid peroxidation and can be useful as a biomarker to track this process. For the analysis of MDA molecules in humid air by selected ion flow tube mass spectrometry (SIFT-MS), the rate coefficients and the ion product distributions for the reactions of the SIFT-MS reagent ions with volatile MDA in the presence of water vapour are required.

METHODS

The SIFT technique has been used to determine the rate coefficients and ion product distributions for the reactions of H3O(+), NO(+) and O2 (+•) with gas-phase MDA. In support of the SIFT-MS analysis of MDA, solid-phase microextraction, SPME, coupled with gas chromatography/mass spectrometry, GC/MS, has been used to confirm the identification of MDA.

RESULTS

The primary product ions have been identified for the reactions of H3O(+), NO(+) and O2 (+•) with MDA and the formation of their hydrates formed in humid samples is described. The following combinations of reagent and the analyte ions (given as m/z values) have been adopted for SIFT-MS analyses of MDA in the gas phase: H3O(+): 109; NO(+): 89, 102; O2 (+•): 72, 90, 108, 126. The detection and quantification of MDA released by a cell culture by SIFT-MS are demonstrated.

CONCLUSIONS

This detailed study has provided the kinetics data required for the SIFT-MS analysis of MDA in humid air, including exhaled breath and the headspace of liquid-phase biogenic media. The detection and quantification by SIFT-MS of MDA released by a cell culture are demonstrated.

Pitfalls in the analysis of volatile breath biomarkers: suggested solutions and SIFT-MS quantification of single metabolites

The experimental challenges presented by the analysis of trace volatile organic compounds (VOCs) in exhaled breath with the objective of identifying reliable biomarkers are brought into focus. It is stressed that positive identification and accurate quantification of the VOCs are imperative if they are to be considered as discreet biomarkers. Breath sampling procedures are discussed and it is suggested that for accurate quantification on-line real time sampling and analysis is desirable. Whilst recognizing such real time analysis is not always possible and sample collection is often required, objective recognition of the pitfalls involved in this is essential. It is also emphasized that mouth-exhaled breath is always contaminated to some degree by orally generated compounds and so, when possible, analysis of nose-exhaled breath should be performed. Some difficulties in breath analysis are mitigated by the choice of analytical instrumentation used, but no single instrument can provide solutions to all the analytical challenges. Analysis and interpretation of breath analysis data, however acquired, needs to be treated circumspectly. In particular, the excessive use of statistics to treat imperfect mass spectrometry/mobility spectra should be avoided, since it can result in unjustifiable conclusions. It is should be understood that recognition of combinations of VOCs in breath that, for example, apparently describe particular cancer states, will not be taken seriously until they are replicated in other laboratories and clinics. Finally, the inhibiting notion that single biomarkers of infection and disease will not be identified and utilized clinically should be dispelled by the exemplary and widely used single biomarkers NO and H2 and now, as indicated by recent selected ion flow tube mass spectroscopy (SIFT-MS) results, triatomic hydrogen cyanide and perhaps pentane and acetic acid. Hopefully, these discoveries will provide encouragement to research workers to be more open-minded on this important and desirable issue.

Selected ion flow tube-mass spectrometry for online monitoring of submerged fermentations: a case study of sourdough fermentation

Selected ion flow tube-mass spectrometry (SIFT-MS) has recently gained interest as an alternative method to traditional GC-MS for the detection of targeted volatile sample compounds, due to its ease of use, its speed and sensitivity, and its potential for real-time quantification. The feasibility of this technique was demonstrated using the case of the production of ethanol during sourdough fermentation. The potential of SIFT-MS as an online monitoring device for food fermentations was further demonstrated by the detection of acetoin in certain sourdough fermentations. This allowed discrimination between sourdough fermentation processes and illustrated the importance of real-time monitoring of food fermentations.

SIFT-MS and FA-MS methods for ambient gas phase analysis: developments and applications in the UK

The origins of SIFT created to study interstellar chemistry and SIFT-MS developed for ambient gas and exhaled breath analysis and the UK centres in which these techniques are being exploited.

Volatile emanations from in vitro airway cells infected with human rhinovirus

Respiratory viral infections such as human rhinovirus (HRV) can lead to substantial morbidity and mortality, especially in people with underlying lung diseases such as asthma and COPD. One proposed strategy to detect viral infections non-invasively is by volatile organic compound (VOC) assessment via analysis of exhaled breath. The epithelial cells are one of the most important cell lines affected during respiratory infections as they are the first line of pathogen defense. Efforts to discover infection-specific biomarkers can be significantly aided by understanding the VOC emanations of respiratory epithelial cells. Here we test the hypothesis that VOCs obtained from the headspace of respiratory cell culture will differentiate healthy cells from those infected with HRV. Primary human tracheobronchial cells were cultured and placed in a system designed to trap headspace VOCs. HRV-infected cells were compared to uninfected control cells. In addition, cells treated with heat-killed HRV and poly(I:C), a TLR3 agonist, were compared to controls. The headspace was sampled with solid-phase microextraction fibers and VOCs were analyzed by gas chromatography/mass spectrometry. We determined differential expression of compounds such as aliphatic alcohols, branched hydrocarbons, and dimethyl sulfide by the infected cells, VOCs previously associated with oxidative stress and bacterial infection. We saw no major differences between the killed-HRV, poly(I:C), and control cell VOCs. We postulate that these compounds may serve as biomarkers of HRV infection, and that the production of VOCs is not due to TLR3 stimulation but does require active viral replication. Our novel approach may be used for the in vitro study of other important respiratory viruses, and ultimately it may aid in identifying VOC biomarkers of viral infection for point-of-care diagnostics.

The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva

Breath analysis is a young field of research with its roots in antiquity. Antoine Lavoisier discovered carbon dioxide in exhaled breath during the period 1777-1783, Wilhelm (Vilém) Petters discovered acetone in breath in 1857 and Johannes Müller reported the first quantitative measurements of acetone in 1898. A recent review reported 1765 volatile compounds appearing in exhaled breath, skin emanations, urine, saliva, human breast milk, blood and feces. For a large number of compounds, real-time analysis of exhaled breath or skin emanations has been performed, e.g., during exertion of effort on a stationary bicycle or during sleep. Volatile compounds in exhaled breath, which record historical exposure, are called the 'exposome'. Changes in biogenic volatile organic compound concentrations can be used to mirror metabolic or (patho)physiological processes in the whole body or blood concentrations of drugs (e.g. propofol) in clinical settings-even during artificial ventilation or during surgery. Also compounds released by bacterial strains like Pseudomonas aeruginosa or Streptococcus pneumonia could be very interesting. Methyl methacrylate (CAS 80-62-6), for example, was observed in the headspace of Streptococcus pneumonia in concentrations up to 1420 ppb. Fecal volatiles have been implicated in differentiating certain infectious bowel diseases such as Clostridium difficile, Campylobacter, Salmonella and Cholera. They have also been used to differentiate other non-infectious conditions such as irritable bowel syndrome and inflammatory bowel disease. In addition, alterations in urine volatiles have been used to detect urinary tract infections, bladder, prostate and other cancers. Peroxidation of lipids and other biomolecules by reactive oxygen species produce volatile compounds like ethane and 1-pentane. Noninvasive detection and therapeutic monitoring of oxidative stress would be highly desirable in autoimmunological, neurological, inflammatory diseases and cancer, but also during surgery and in intensive care units. The investigation of cell cultures opens up new possibilities for elucidation of the biochemical background of volatile compounds. In future studies, combined investigations of a particular compound with regard to human matrices such as breath, urine, saliva and cell culture investigations will lead to novel scientific progress in the field.