Detection of Pseudomonas aeruginosa in sputum headspace through volatile organic compound analysis

Progress and challenges of developing volatile metabolites from exhaled breath as a biomarker platform

BACKGROUND

The multitude of metabolites generated by physiological processes in the body can serve as valuable biomarkers for many clinical purposes. They can provide a window into relevant metabolic pathways for health and disease, as well as be candidate therapeutic targets. A subset of these metabolites generated in the human body are volatile, known as volatile organic compounds (VOCs), which can be detected in exhaled breath. These can diffuse from their point of origin throughout the body into the bloodstream and exchange into the air in the lungs. For this reason, breath VOC analysis has become a focus of biomedical research hoping to translate new useful biomarkers by taking advantage of the non-invasive nature of breath sampling, as well as the rapid rate of collection over short periods of time that can occur. Despite the promise of breath analysis as an additional platform for metabolomic analysis, no VOC breath biomarkers have successfully been implemented into a clinical setting as of the time of this review.

AIM OF REVIEW

This review aims to summarize the progress made to address the major methodological challenges, including standardization, that have historically limited the translation of breath VOC biomarkers into the clinic. We highlight what steps can be taken to improve these issues within new and ongoing breath research to promote the successful development of the VOCs in breath as a robust source of candidate biomarkers. We also highlight key recent papers across select fields, critically reviewing the progress made in the past few years to advance breath research.

KEY SCIENTIFIC CONCEPTS OF REVIEW

VOCs are a set of metabolites that can be sampled in exhaled breath to act as advantageous biomarkers in a variety of clinical contexts.

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.

A Pilot Study for Legionella pneumophila Volatilome Characterization Using a Gas Sensor Array and GC/MS Techniques

Legionellosis is a generic term describing the pneumonic (Legionnaires' disease, LD) and non-pneumonic (Pontiac fever, PF) forms of infection with bacteria belonging to the genus Legionella. Currently, the techniques used to detect Legionella spp. in water samples have certain limitations and drawbacks, and thus, there is a need to identify new tools to carry out low-cost and rapid analysis. In this regard, several studies demonstrated that a volatolomics approach rapidly detects and discriminates different species of microorganisms via their volatile signature. In this paper, the volatile organic compounds (VOCs) pattern emitted in vitro by Legionella pneumophila cultures is characterized and compared to those produced by other Legionella species and by Pseudomonas aeruginosa, using a gas sensor array and gas chromatograph mass spectrometer (GC-MS). Bacterial cultures were measured at the 3rd and 7th day after the incubation. Sensor array data analyzed via the K-nearest neighbours (k-NN) algorithm showed a sensitivity to Legionella pneumophila identification at around 89%. On the other hand, GC-MS identified a bouquet of VOCs, mainly alcohols and ketones, that enable the differentiation of Legionella pneumophila in respect to other waterborne microorganisms.

Pseudomonas aeruginosa Production of Hydrogen Cyanide Leads to Airborne Control of Staphylococcus aureus Growth in Biofilm and In Vivo Lung Environments

Diverse bacterial volatile compounds alter bacterial stress responses and physiology, but their contribution to population dynamics in polymicrobial communities is not well known. In this study, we showed that airborne volatile hydrogen cyanide (HCN) produced by a wide range of Pseudomonas aeruginosa clinical strains leads to at-a-distance in vitro inhibition of the growth of a wide array of Staphylococcus aureus strains. We determined that low-oxygen environments not only enhance P. aeruginosa HCN production but also increase S. aureus sensitivity to HCN, which impacts P. aeruginosa-S. aureus competition in microaerobic in vitro mixed biofilms as well as in an in vitro cystic fibrosis lung sputum medium. Consistently, we demonstrated that production of HCN by P. aeruginosa controls S. aureus growth in a mouse model of airways coinfected by P. aeruginosa and S. aureus. Our study therefore demonstrates that P. aeruginosa HCN contributes to local and distant airborne competition against S. aureus and potentially other HCN-sensitive bacteria in contexts relevant to cystic fibrosis and other polymicrobial infectious diseases. IMPORTANCE Airborne volatile compounds produced by bacteria are often only considered attractive or repulsive scents, but they also directly contribute to bacterial physiology. Here, we showed that volatile hydrogen cyanide (HCN) released by a wide range of Pseudomonas aeruginosa strains controls Staphylococcus aureus growth in low-oxygen in vitro biofilms or aggregates and in vivo lung environments. These results are of pathophysiological relevance, since lungs of cystic fibrosis patients are known to present microaerobic areas and to be commonly associated with the presence of S. aureus and P. aeruginosa in polymicrobial communities. Our study therefore provides insights into how a bacterial volatile compound can contribute to the exclusion of S. aureus and other HCN-sensitive competitors from P. aeruginosa ecological niches. It opens new perspectives for the management or monitoring of P. aeruginosa infections in lower-lung airway infections and other polymicrobial disease contexts.

The potential of volatile organic compound analysis for pathogen detection and disease monitoring in patients with cystic fibrosis

INTRODUCTION

Airway infection with pathogens and its associated pulmonary exacerbations (PEX) are the major causes of morbidity and premature death in cystic fibrosis (CF). Preventing or postponing chronic infections requires early diagnosis. However, limitations of conventional microbiology-based methods can hamper identification of exacerbations and specific pathogen detection. Analyzing volatile organic compounds (VOCs) in breath samples may be an interesting tool in this regard, as VOC-biomarkers can characterize specific airway infections in CF.

AREAS COVERED

We address the current achievements in VOC-analysis and discuss studies assessing VOC-biomarkers and fingerprints, i.e. a combination of multiple VOCs, in breath samples aiming at pathogen and PEX detection in people with CF (pwCF). We aim to provide bases for further research in this interesting field.

EXPERT OPINION

Overall, VOC-based analysis is a promising tool for diagnosis of infection and inflammation with potential to monitor disease progression in pwCF. Advantages over conventional diagnostic methods, including easy and non-invasive sampling procedures, may help to drive prompt, suitable therapeutic approaches in the future. Our review shall encourage further research, including validation of VOC-based methods. Specifically, longitudinal validation under standardized conditions is of interest in order to ensure repeatability and enable inclusion in CF diagnostic routine.

Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives

Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. KEY POINTS: • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future.

Volatile Organic Compounds to Identify Infectious (Bacteria/Viruses) Diseases of the Central Nervous System: A Pilot Study

BACKGROUND

Central nervous system (CNS) infectious diseases are common diseases in emergency rooms and neurology departments. CNS pathogen identification methods are time consuming and expensive and have low sensitivity and poor specificity. Some studies have shown that bacteria and viruses can produce specific volatile organic compounds (VOCs). The aim of this study is to find potential biomarkers by VOC analysis of cerebrospinal fluid (CSF) in patients with bacterial and viral meningitis/encephalitis (ME).

METHODS

CSF samples from 16 patients with bacterial ME and 42 patients with viral ME were collected, and solid-phase microextraction combined with gas chromatography-mass spectrometry was used to analyze the metabolites in the CSF.

RESULTS

There are 2 substances (ethylene oxide and phenol) that were found to be different between the 2 groups. Ethylene oxide was significantly greater in the group of bacterial ME patients than in the viral ME group of patients (p < 0.05). In addition, phenol was remarkably increased in the group of ME patients compared with the bacterial ME patients (p < 0.05).

CONCLUSIONS

Ethylene oxide and phenol may be potential biomarkers to distinguish bacterial ME and viral ME. VOC analysis of CSF may be used as a supporting tool for clinical diagnosis.

1-Undecene from Pseudomonas aeruginosa is an olfactory signal for flight-or-fight response in Caenorhabditis elegans

Animals possess conserved mechanisms to detect pathogens and to improve survival in their presence by altering their own behavior and physiology. Here, we utilize Caenorhabditis elegans as a model host to ask whether bacterial volatiles constitute microbe-associated molecular patterns. Using gas chromatography-mass spectrometry, we identify six prominent volatiles released by the bacterium Pseudomonas aeruginosa. We show that a specific volatile, 1-undecene, activates nematode odor sensory neurons inducing both flight and fight responses in worms. Using behavioral assays, we show that worms are repelled by 1-undecene and that this aversion response is driven by the detection of this volatile through AWB odor sensory neurons. Furthermore, we find that 1-undecene odor can induce immune effectors specific to P. aeruginosa via AWB neurons and that brief pre-exposure of worms to the odor enhances their survival upon subsequent bacterial infection. These results show that 1-undecene derived from P. aeruginosa serves as a pathogen-associated molecular pattern for the induction of protective responses in C. elegans.

Targeted exhaled breath analysis for detection of Pseudomonas aeruginosa in cystic fibrosis patients

BACKGROUND

Pseudomonas aeruginosa (PA) is an important respiratory pathogen for cystic fibrosis (CF) patients. Routine microbiology surveillance is time-consuming, and is best performed on expectorated sputum. As alternative, volatile organic compounds (VOCs) may be indicative of PA colonisation. In this study, we aimed to identify VOCs associated with PA in literature and perform targeted exhaled breath analysis to recognize PA positive CF patients non-invasively.

METHODS

This study consisted of 1) a literature review to select VOCs of interest, and 2) a cross-sectional CF study. Definitions used: A) PA positive, PA culture at visit/chronically; B) PA free, no PA culture in ≥12 months. Exhaled VOCs were identified via quadrupole MS. The primary endpoint was the area under the receiver operating characteristics curve (AUROCC) of individual VOCs as well as combined VOCs against PA culture.

RESULTS

241 VOCs were identified in literature, of which 56 were further evaluated, and 13 could be detected in exhaled breath in our cohort. Exhaled breath of 25 pediatric and 28 adult CF patients, PA positive (n=16) and free (n=28) was available. 3/13 VOCs were significantly (p<0.05) different between PA groups in children; none were in adults. Notably, a composite model based on 5 or 1 VOC(s) showed an AUROCC of 0.86 (CI 0.71-1.0) and 0.87 (CI 0.72-1.0) for adults and children, respectively.

CONCLUSIONS

Targeted VOC analysis appears to discriminate children and adults with and without PA positive cultures with clinically acceptable sensitivity values.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples

Background:The headspace of a biological sample contains exogenous VOCs present within the sampling environment which represent the background signal.Study aims:This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics.Methods:The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on thirteen of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK.Results:The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias of z-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background.Conclusion:Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

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.

Volatilomes of Bacterial Infections in Humans

Sense of smell in humans has the capacity to detect certain volatiles from bacterial infections. Our olfactory senses were used in ancient medicine to diagnose diseases in patients. As humans are considered holobionts, each person's unique odor consists of volatile organic compounds (VOCs, volatilome) produced not only by the humans themselves but also by their beneficial and pathogenic micro-habitants. In the past decade it has been well documented that microorganisms (fungi and bacteria) are able to emit a broad range of olfactory active VOCs [summarized in the mVOC database (http://bioinformatics.charite.de/mvoc/)]. During microbial infection, the equilibrium between the human and its microbiome is altered, followed by a change in the volatilome. For several decades, physicians have been trying to utilize these changes in smell composition to develop fast and efficient diagnostic tools, particularly because volatiles detection is non-invasive and non-destructive, which would be a breakthrough in many therapies. Within this review, we discuss bacterial infections including gastrointestinal, respiratory or lung, and blood infections, focusing on the pathogens and their known corresponding volatile biomarkers. Furthermore, we cover the potential role of the human microbiota and their volatilome in certain diseases such as neurodegenerative diseases. We also report on discrete mVOCs that affect humans.

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.

Interaction between Pseudomonas aeruginosa and Aspergillus fumigatus in cystic fibrosis

Background

Cystic fibrosis (CF) is a disease characterized by chronic airway infection with a high incidence and poor prognosis. Pseudomonas aeruginosa and Aspergillus fumigatus are pathogens commonly found in CF patients. Clinically, these two microorganisms often coexist in the airway of CF patients. Combined infection with P. aeruginosa and A. fumigatus results in worsening lung function and clinical condition.

Methods

In this review, we focus on the mutual inhibition and promotion mechanisms of P. aeruginosa and A. fumigatus in CF patients. We also summarized the mechanisms of the interaction between these pathogenic microorganisms.

Results

P. aeruginosa inhibits A. fumigatus growth through the effects of phenazines, the quorum sensing system, iron competition, bacteriophages, and small colony variants. P. aeruginosa induces A. fumigatus growth through volatile organic compounds and subbacteriostatic concentrations of phenazines. A. fumigatus interferes with P. aeruginosa, affecting its metabolic growth via phenazine metabolic transformation, gliotoxin production, and reduced antibiotic sensitivity.

Discussion

Coexistence of P. aeruginosa and A. fumigatus can lead to both mutual inhibition and promotion. In different stages of CF disease, the interaction between these two pathogenic microorganisms may shift between promotion and inhibition. A discussion of the mechanisms of P. aeruginosa and A. fumigatus interaction can be beneficial for further treatment of CF patients and for improving the prognosis of the disease.

Developments to monitor the exhalome in organ failure in critically ill patients-a look into the future

Critically ill patients typically need some kind of functional organ support or replacement. Cardiopulmonary and renal replacement therapies are well established measures in intensive care units. However, there are also inherent risks associated with these treatments. The appropriate and timely commencement, maintenance and termination of organ replacement procedures currently use weak surrogates as decision support in clinical practice. A more reasonable application of extracorporeal organ support can be expected to potentially lower adverse events and save costs in healthcare systems, if a precise online monitoring was available. The analysis of the exhalome offers great opportunities to detect circulatory, pulmonary, and renal failure in critically ill patients. Volatile organic compounds and exhalation patterns are associated with a series of metabolic disorders and may be key to indicate the appropriate time point for initiation, maintenance and termination of organ support technologies. It may thus be expected that mortality, infection risk, replacement therapy days, and medical costs of intensive care treatment may possibly be reduced using exhalome analysis for control of organ replacement therapies in the distant future.

Identification of Pseudomonas aeruginosa and airway bacterial colonization by an electronic nose in bronchiectasis

RATIONALE

Airway colonization by Potentially Pathogenic Microorganisms (PPM) in bronchiectasis is associated with worse clinical outcomes. The electronic nose is a non-invasive technology capable of distinguishing volatile organic compounds (VOC) in exhaled breath. We aim to explore if an electronic nose can reliably discriminate airway bacterial colonization in patients with bronchiectasis.

METHODS

Seventy-three clinically stable bronchiectasis patients were included. PPM presence was determined using sputum culture. Exhaled breath was collected in Tedlar bags and VOC breath-prints were detected by the electronic nose Cyranose 320^®. Raw data was reduced to three factors with principal component analysis. Univariate ANOVA followed by post-hoc least significant difference test was performed with these factors. Patients were then classified using linear canonical discriminant analysis. Cross-validation accuracy values were defined by the percentage of correctly classified patients.

RESULTS

Forty-one (56%) patients were colonized with PPM. Pseudomonas aeruginosa (n = 27, 66%) and Haemophilus influenzae (n = 7, 17%) were the most common PPM. VOC breath-prints from colonized and non-colonized patients were significantly different (accuracy of 72%, AUROC 0.75, p < 0.001). VOC breath-prints from Pseudomonas aeruginosa colonized patients were significantly different from those of patients colonized with other PPM (accuracy of 89%, AUROC 0.97, p < 0.001) and non-colonized patients (accuracy 73%, AUROC 0.83, p = 0.007).

CONCLUSIONS

An electronic nose can accurately identify VOC breath-prints of clinically stable bronchiectasis patients with airway bacterial colonization, especially in those with Pseudomonas aeruginosa.

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.

Headspace volatile organic compounds from bacteria implicated in ventilator-associated pneumonia analysed by TD-GC/MS

Ventilator-associated pneumonia (VAP) is a healthcare-acquired infection arising from the invasion of the lower respiratory tract by opportunistic pathogens in ventilated patients. The current method of diagnosis requires the culture of an airway sample such as bronchoalveolar lavage, which is invasive to obtain and may take up to seven days to identify a causal pathogen, or indeed rule out infection. While awaiting results, patients are administered empirical antibiotics; risks of this approach include lack of effect on the causal pathogen, contribution to the development of antibiotic resistance and downstream effects such as increased length of intensive care stay, cost, morbidity and mortality. Specific biomarkers which could identify causal pathogens in a timely manner are needed as they would allow judicious use of the most appropriate antimicrobial therapy. Volatile organic compound (VOC) analysis in exhaled breath is proposed as an alternative due to its non-invasive nature and its potential to provide rapid diagnosis at the patient's bedside. VOCs in exhaled breath originate from exogenous, endogenous, as well as microbial sources. To identify potential markers, VAP-associated pathogens Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus were cultured in both artificial sputum medium and nutrient broth, and their headspaces were sampled and analysed for VOCs. Previously reported volatile markers were identified in this study, including indole and 1-undecene, alongside compounds that are novel to this investigation, cyclopentanone and 1-hexanol. We further investigated media components (substrates) to identify those that are essential for indole and cyclopentanone production, with potential implications for understanding microbial metabolism in the lung.

Smelling Pseudomonas aeruginosa infections using a whole-cell biosensor - An alternative for the gold-standard culturing assay

Improved easy-to-use diagnostic tools for infections are in strong demand worldwide. Yet, despite dramatic advances in diagnostic technologies, the gold-standard remains culturing. Here we offer an alternative tool demonstrating that a bacterial biosensor can efficiently detect Pseudomonas aeruginosa infections in patients suffering from otitis externa. Detection was based on specific binding between the biosensor and 2-aminoacetophenone (2-AA), a volatile produced by P. aeruginosa in high amounts. We collected pus samples from ears of 26 subjects exhibiting symptoms of otitis externa. Detection of P. aeruginosa using the biosensor was compared to detection using gold-standard culturing assay and to gas-chromatograph-mass-spectrometry (GC-MS) analyses of 2-AA. The biosensor strain test matched the culture assay in 24 samples (92%) and the GC-MS analyses in 25 samples (96%). With this result in hand, we designed a device containing a whole-cell luminescent biosensor combined with a photo-multiplier tube. This device allowed detection of 2-AA at levels as low as 2 nmol, on par with detection level of GC-MS. The results of the described study demonstrate that the volatile 2-AA serves as an effective biomarker for P. aeruginosa in ear infections, and that activation of the biosensor strain by 2-AA provides a unique opportunity to design an easy-to-use device that can specifically detect P. aeruginosa infections.

Breath analysis for noninvasively differentiating Acinetobacter baumannii ventilator-associated pneumonia from its respiratory tract colonization of ventilated patients

A number of multiresistant pathogens including Acinetobacter baumannii (A. baumannii) place a heavy burden on ventilator-associated pneumonia (VAP) patients in intensive care units (ICU). It is critically important to differentiate between bacterial infection and colonization to avoid prescribing unnecessary antibiotics. Quantitative culture of lower respiratory tract (LRT) specimens, however, requires invasive procedures. Nowadays, volatile organic compounds (VOCs) have been studied in vitro and in vivo to identify pathogen-derived biomarkers. Therefore, an exploratory pilot study was conceived for a proof of concept that the appearance and level of A. baumannii-derived metabolites might be correlated with the presence of the pathogen and its ecological niche (i.e. the infection and colonization states) in ICU ventilated patients. Twenty patients with A. baumannii VAP (infection group), 20 ventilated patients with LRT A. baumannii colonization (colonization group) and 20 ventilated patients with neurological disorders, but without pneumonia or A. baumannii colonization (control group) were enrolled in the in vivo pilot study. A clinical isolate of A. baumannii strains was used for the in vitro culture experiment. The adsorptive preconcentration (solid-phase microextraction fiber and Tenax(®) TA) and analysis technique of gas chromatography-mass spectrometry were applied in the studies. Breath profiles could be visually differentiated between A. baumannii cultivation in vitro and culture medium, and among in vivo groups. In the in vitro experiment, nine compounds of interest (2,5-dimethyl-pyrazine, 1-undecene, isopentyl 3-methylbutanoate, decanal, 1,3-naphthalenediol, longifolene, tetradecane, iminodibenzyl and 3-methyl-indene) in the headspace were found to be possible A. baumannii derivations. While there were eight target VOCs (1-undecene, nonanal, decanal, 2,6,10-trimethyl-dodecane, 5-methyl-5-propyl-nonane, longifolene, tetradecane and 2-butyl-1-octanol) exhibiting characteristics of A. baumannii VAP derivations. The selected VOC profile in vivo could be adopted to efficiently differentiate the presence of LRT A. baumannii from its absence, and LRT A. baumannii infection from its colonization (AUC  =  0.89 and 0.88, respectively). It is not feasible to simply transfer the metabolic biomarkers from the in vitro condition to in vivo. The direct detection of exhaled A. baumannii-derived VOCs may be adopted for an early alert of the LRT bacterial presence in ventilated ICU patients, and even in different parasitic states of A. baumannii (i.e. infection and colonization). However, further refinement and validation are required before its clinical use.

In vitro volatile organic compound profiling using GC×GC-TOFMS to differentiate bacteria associated with lung infections: a proof-of-concept study

Chronic pulmonary infections are the principal cause of morbidity and mortality in individuals with cystic fibrosis (CF). Due to the polymicrobial nature of these infections, the identification of the particular bacterial species responsible is an essential step in diagnosis and treatment. Current diagnostic procedures are time-consuming, and can also be expensive, invasive and unpleasant in the absence of spontaneously expectorated sputum. The development of a rapid, non-invasive methodology capable of diagnosing and monitoring early bacterial infection is desired. Future visions of real-time, in situ diagnosis via exhaled breath testing rely on the differentiation of bacteria based on their volatile metabolites. The objective of this proof-of-concept study was to investigate whether a range of CF-associated bacterial species (i.e. Pseudomonas aeruginosa, Burkholderia cenocepacia, Haemophilus influenzae, Stenotrophomonas maltophilia, Streptococcus pneumoniae and Streptococcus milleri) could be differentiated based on their in vitro volatile metabolomic profiles. Headspace samples were collected using solid phase microextraction (SPME), analyzed using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) and evaluated using principal component analysis (PCA) in order to assess the multivariate structure of the data. Although it was not possible to effectively differentiate all six bacteria using this method, the results revealed that the presence of a particular pattern of VOCs (rather than a single VOC biomarker) is necessary for bacterial species identification. The particular pattern of VOCs was found to be dependent upon the bacterial growth phase (e.g. logarithmic versus stationary) and sample storage conditions (e.g. short-term versus long-term storage at  -18 °C). Future studies of CF-associated bacteria and exhaled breath condensate will benefit from the approaches presented in this study and further facilitate the production of diagnostic tools for the early detection of bacterial lung infections.

Volatile Compounds Emitted by Pseudomonas aeruginosa Stimulate Growth of the Fungal Pathogen Aspergillus fumigatus

Chronic lung infections with opportunistic bacterial and fungal pathogens are a major cause of morbidity and mortality especially in patients with cystic fibrosis. Pseudomonas aeruginosa is the most frequently colonizing bacterium in these patients, and it is often found in association with the filamentous fungus Aspergillus fumigatus. P. aeruginosa is known to inhibit the growth of A. fumigatus in situations of direct contact, suggesting the existence of interspecies communication that may influence disease outcome. Our study shows that the lung pathogens P. aeruginosa and A. fumigatus can interact at a distance via volatile-mediated communication and expands our understanding of interspecific signaling in microbial communities.

Microbiota studies have shown that pathogens cannot be studied individually anymore and that the establishment and progression of a specific disease are due not to a single microbial species but are the result of the activity of many species living together. To date, the interaction between members of the human microbiota has been analyzed in situations of direct contact or liquid-mediated contact between organisms. This study showed unexpectedly that human opportunistic pathogens can interact at a distance after sensing volatiles emitted by another microbial species. This finding will open a new research avenue for the understanding of microbial communities.

Establishing the volatile profile of pig carcasses as analogues for human decomposition during the early postmortem period

Following a mass disaster, it is important that victims are rapidly located as the chances of survival decrease greatly after approximately 48 h. Urban search and rescue (USAR) teams may use a range of tools to assist their efforts but detector dogs still remain one of the most effective search tools to locate victims of mass disasters. USAR teams can choose to deploy human scent dogs (trained to locate living victims) or human remains detection (HRD) dogs (trained to locate deceased victims). However, little is known about the variation between live human scent and postmortem human remains scent and the timeframe during which one type of scent transitions to the other. The aim of the current study was to measure the change in the scent profile of human decomposition analogues during the first 72 h postmortem by measuring the volatile organic compounds (VOCs) that comprise the odour. Three pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface and allowed to decompose under natural conditions. Decomposition odour was sampled frequently up to 75 h postmortem and analysed using comprehensive two-dimensional gas chromatography - time-of-flight mass spectrometry (GC×GC-TOFMS). A total of 105 postmortem VOCs were identified during the early postmortem period. The VOC profile during the early postmortem period was highly dynamic, changing both hourly and daily. A transition period was observed after 43 h postmortem, where the VOC profile appeared to shift from a distinct antemortem odour to a more generalised postmortem odour. These findings are important in informing USAR teams and their use of detector dogs for disaster victim recovery.

Early release of 1-pyrroline by Pseudomonas aeruginosa cultures discovered using ambient corona discharge ionization mass spectrometry

1-Pyrroline detected by ambient mass spectrometry is suggested as a potential volatile biomarker for early identification of Pseudomonas aeruginosa infections.

Spanish consensus on the prevention and treatment of Pseudomonas aeruginosa bronchial infections in cystic fibrosis patients

Pseudomonas aeruginosa is the main pathogen in bronchopulmonary infections in cystic fibrosis (CF) patients. It can only be eradicated at early infection stages while reduction of its bacterial load is the therapeutic goal during chronic infection or exacerbations. Neonatal screening and pharmacokinetic/pharmacodynamic knowledge has modified the management of CF-patients. A culture based microbiological follow-up should be performed in patients with no infection with P.aeruginosa. At initial infection, inhaled colistin (0,5-2MU/tid), tobramycin (300mg/bid) or aztreonam (75mg/tid) with or without oral ciprofloxacin (15-20mg/kg/bid, 2-3weeks) are recommended. In chronic infections, treatment is based on continuous administration of colistin or with a 28-day on-off regimen with tobramycin or aztreonam. During mild-moderate exacerbations oral ciprofloxacin (2-3weeks) can be administered while serious exacerbations must be treated with intravenous combination therapy (beta-lactam with an aminoglycoside or a fluoroquinolone). Future studies will support antibiotic rotation and/or new combination therapies. Epidemiological measures are also recommended to avoid new P.aeruginosa infections and "patient-to-patient transmission" of this pathogen.

Rapid recognition of bacteremia in humans using atmospheric pressure chemical ionization mass spectrometry of volatiles emitted by blood cultures

Human bacteremia is rapidly diagnosed by direct atmospheric pressure chemical ionization mass spectrometry analysis of blood culture volatiles.

A rapid method for breath analysis in cystic fibrosis patients

For easy handling and speed of lung diseases diagnostics, approaches based on volatile organic compounds (VOCs), including those emitted by pathogenic microorganisms, are considered but currently require considerable sampling efforts. We tested whether easy-to-handle and fast detection of lung infections is possible using solid-phase microextraction (SPME) of 100 ml of exhaled breath. An analytical procedure for the detection of VOCs from the headspace of epithelial lung cells infected with four human pathogens was developed. The feasibility of this method was tested in a cystic fibrosis (CF) outpatient clinic in vivo. Exhaled breath was extracted by SPME and analyzed by gas chromatography-mass spectrometry (GC-MS). The compositions of VOCs released in the infection model were characteristic for all individual pathogens tested. Exhaled breath of CF patients allowed clear distinction of CF patients and controls by their VOC compositions using multivariate analyses. Interestingly, the major specific VOCs detected in the exhaled breath of infected CF patients in vivo differed from those monitored during bacterial in vitro growth. SPME extraction of VOCs from 100 ml of human breath allowed the distinction between CF patients and healthy probands. Our results highlight the importance of assessing the entire pattern of VOCs instead of selected biomarkers for diagnostic purposes, as well as the need to use clinical samples to identify reliable biomarkers. This study provides the proof-of-concept for the approach using the composition of exhaled VOCs in human breath for the rapid identification of infectious agents in patients with lower respiratory tract infections.

Antifungal activity of volatile compounds-producing Pseudomonas P2 strain against Rhizoctonia solani

Several volatile organic compounds (VOCs) producing endophyte bacteria were isolated from the leaves of olive trees and tested for their antifungal activity against several pathogenic fungi. An antagonistic strain called P2 showed 97 % of homology with Pseudomonas sp. strains on the basis of its 16S rDNA sequence and biochemical properties. P2 strain drastically inhibited the growth of Rhizoctonia solani mycelia (86 %) at 5 day-post-confrontation (dpc) and strongly reduced fungi infection on potato slices at 10(7) bacteria ml(-1) for 3 and 7 dpc. P2 strain was also positive for protease activity as well as siderophore production. Light microscopy analysis showed that treatment of R. solani mycelia with P2 strain induced thickening of the cell-wall, vesiculation of protoplasm and blockage of fungal hyphae branching. VOCs analysis using GC-MS allowed the detection of two major products with m/z of 93.9910 and 125.9630 corresponding to dimethyl disulfide and dimethyl trisulfide respectively. VOCs-producing P2 strain could be a promising agent in the protection of tuber crops against fungal diseases.

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 volatome of Aspergillus fumigatus

Early detection of invasive aspergillosis is absolutely required for efficient therapy of this fungal infection. The identification of fungal volatiles in patient breath can be an alternative for the detection of Aspergillus fumigatus that still remains problematic. In this work, we investigated the production of volatile organic compounds (VOCs) by A. fumigatus in vitro, and we show that volatile production depends on the nutritional environment. A. fumigatus produces a multiplicity of VOCs, predominantly terpenes and related compounds. The production of sesquiterpenoid compounds was found to be strongly induced by increased iron concentrations and certain drugs, i.e., pravastatin. Terpenes that were always detectable in large amounts were α-pinene, camphene, and limonene, as well as sesquiterpenes, identified as α-bergamotene and β-trans-bergamotene. Other substance classes that were found to be present in the volatome, such as 1-octen-3-ol, 3-octanone, and pyrazines, were found only under specific growth conditions. Drugs that interfere with the terpene biosynthesis pathway influenced the composition of the fungal volatome, and most notably, a block of sesquiterpene biosynthesis by the bisphosphonate alendronate fundamentally changed the VOC composition. Using deletion mutants, we also show that a terpene cyclase and a putative kaurene synthase are essential for the synthesis of volatile terpenes by A. fumigatus. The present analysis of in vitro volatile production by A. fumigatus suggests that VOCs may be used in the diagnosis of infections caused by this fungus.

Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis

We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.