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

The role of Staphylococcus aureus in cystic fibrosis pathogenesis and clinico-microbiological interactions

Cystic fibrosis (CF) is a progressive and inherited disease that affects approximately 70000 individuals all over the world annually. A mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene serves as its defining feature. Bacterial infections have a significant impact on the occurrence and development of CF. In this manuscript, we discuss the role and virulence factors of Staphylococcus aureus as an important human pathogen with the ability to induce respiratory tract infections. Recent studies have reported S. aureus as the first isolated bacteria in CF patients. Methicillin-resistant Staphylococcus aureus (MRSA) pathogens are approximately resistant to all β-lactams. CF patients are colonized by MRSA expressing various virulence factors including toxins, and Staphylococcal Cassette Chromosome mec (SCCmec) types, and have the potential for biofilm formation. Therefore, variations in clinical outcomes will be manifested. SCCmec type II has been reported in CF patients more than in other SCCmec types from different countries. The small-colony variants (SCVs) as specific morphologic subtypes of S. aureus with slow growth and unusual properties can also contribute to persistent and difficult-to-treat infections in CF patients. The pathophysiology of SCVs is complicated and not fully understood. Patients with cystic fibrosis should be aware of the intrinsic risk factors for complex S. aureus infections, including recurring infections, physiological issues, or coinfection with P. aeruginosa.

A feasibility study of sample re-collection in the analysis of selected volatile compounds in breath samples using GC×GC-TOFMS

In this study, we aimed to assess the feasibility of re-collecting breath samples using the Centri® (Markes International, Bridgend, UK) followed by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) analysis. The work was conducted in two main phases. In the first phase, we evaluated the re-collection performance by analyzing two sets of standards, including a Grob mix primary solution and a standard mixture of 20 selected volatile compounds (VCs) covering different classes of organic species commonly found in breath samples. The intra-day and inter-day precision (reported as relative standard deviation (RSD),%) for the re-collection of the Grob mix primary solution were in the range of 1 % to14 % and 3 % to12 %, respectively. The re-collection accuracy ranged from 78 % to 97 %. The intra-day RSD for the re-collection of the standard mixture of selected VCs was within 20 % for all compounds, except for acetone and nonane. The precision was within 25 % for all compounds, except for nonane, n-hexane, 1,4-dichlorobenzene, and decane, which exhibited less than 36 % RSD. The re-collection accuracy was in the range of 67 % to 129 %. In the second phase of the study, the re-collection performance in breath analysis was evaluated via five repetitive splitting and re-collection of six breath samples obtained from healthy adults, realizing a total of 30 breath analyses. Initially, we evaluated the re-collection performance by considering all features obtained from breath analysis and then focused on the 20 VCs commonly found in breath samples. The re-collection accuracy for total breath features ranged from 86 to 103 %, and the RSDs were in the range of 1.0 % to 10.4 %. For the selected VCs, the re-collection accuracy of all compounds, except for undecane and benzene, was in the range of 71 % to 132 %.

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.

Volatile biomarkers of Gram-positive bacteria of clinical relevance as a tool for infection diagnosis

AIM

Volatile organic compounds (VOCs) are being studied as potential biomarkers in many infections. Therefore, this study aimed to analyze the volatile profile of three Gram-positive bacteria of clinical relevance to identify potential volatile biomarkers that allow their differentiation.

METHODS AND RESULTS

L. monocytogenes, S. aureus, and E. faecalis clinical isolates were inoculated in a thioglycollate medium until grown. Then, VOCs were extracted by solid-phase microextraction, and the data obtained were subjected to multivariate analysis. According to our results, there was a high production of aldehydes in E. faecalis. In the case of alcohols, they only increased in L. monocytogenes, while ketones were produced significantly in all three bacteria, mainly due to acetoin. Acids were produced significantly in E. faecalis and L. monocytogenes.

CONCLUSIONS

Potential biomarkers of L. monocytogenes could be 1-butanol and 2-methylbutanoic acid. In the case of E. faecalis, the VOC most related to its presence was nonanal. Lastly, potential biomarkers of S. aureus could be isoamyl butanoate and methionol, although some pyrazines have also been associated with this bacterium.

SIGNIFICANCE AND IMPACT OF THE STUDY

The identification of potential biomarkers of these clinically relevant bacteria could open the way for the diagnosis of these infections through the analysis of volatile compounds.

The Respiratory Microbiome in Paediatric Chronic Wet Cough: What Is Known and Future Directions

Chronic wet cough for longer than 4 weeks is a hallmark of chronic suppurative lung diseases (CSLD), including protracted bacterial bronchitis (PBB), and bronchiectasis in children. Severe lower respiratory infection early in life is a major risk factor of PBB and paediatric bronchiectasis. In these conditions, failure to clear an underlying endobronchial infection is hypothesised to drive ongoing inflammation and progressive tissue damage that culminates in irreversible bronchiectasis. Historically, the microbiology of paediatric chronic wet cough has been defined by culture-based studies focused on the detection and eradication of specific bacterial pathogens. Various 'omics technologies now allow for a more nuanced investigation of respiratory pathobiology and are enabling development of endotype-based models of care. Recent years have seen substantial advances in defining respiratory endotypes among adults with CSLD; however, less is understood about diseases affecting children. In this review, we explore the current understanding of the airway microbiome among children with chronic wet cough related to the PBB-bronchiectasis diagnostic continuum. We explore concepts emerging from the gut-lung axis and multi-omic studies that are expected to influence PBB and bronchiectasis endotyping efforts. We also consider how our evolving understanding of the airway microbiome is translating to new approaches in chronic wet cough diagnostics and treatments.

Current Limitations of Staph Infection Diagnostics, and the Role for VOCs in Achieving Culture-Independent Detection

Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.

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.

Volatile organic compound profiling to explore primary graft dysfunction after lung transplantation

Primary graft dysfunction (PGD) is a major determinant of morbidity and mortality following lung transplantation. Delineating basic mechanisms and molecular signatures of PGD remain a fundamental challenge. This pilot study examines if the pulmonary volatile organic compound (VOC) spectrum relate to PGD and postoperative outcomes. The VOC profiles of 58 bronchoalveolar lavage fluid (BALF) and blind bronchial aspirate samples from 35 transplant patients were extracted using solid-phase-microextraction and analyzed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. The support vector machine algorithm was used to identify VOCs that could differentiate patients with severe from lower grade PGD. Using 20 statistically significant VOCs from the sample headspace collected immediately after transplantation (< 6 h), severe PGD was differentiable from low PGD with an AUROC of 0.90 and an accuracy of 0.83 on test set samples. The model was somewhat effective for later time points with an AUROC of 0.80. Three major chemical classes in the model were dominated by alkylated hydrocarbons, linear hydrocarbons, and aldehydes in severe PGD samples. These VOCs may have important clinical and mechanistic implications, therefore large-scale study and potential translation to breath analysis is recommended.

Molecular Mechanisms of Staphylococcus and Pseudomonas Interactions in Cystic Fibrosis

Cystic fibrosis (CF) is an autosomal recessive genetic disorder that is characterized by recurrent and chronic infections of the lung predominantly by the opportunistic pathogens, Gram-positive Staphylococcus aureus and Gram-negative Pseudomonas aeruginosa. While S. aureus is the main colonizing bacteria of the CF lungs during infancy and early childhood, its incidence declines thereafter and infections by P. aeruginosa become more prominent with increasing age. The competitive and cooperative interactions exhibited by these two pathogens influence their survival, antibiotic susceptibility, persistence and, consequently the disease progression. For instance, P. aeruginosa secretes small respiratory inhibitors like hydrogen cyanide, pyocyanin and quinoline N-oxides that block the electron transport pathway and suppress the growth of S. aureus. However, S. aureus survives this respiratory attack by adapting to respiration-defective small colony variant (SCV) phenotype. SCVs cause persistent and recurrent infections and are also resistant to antibiotics, especially aminoglycosides, antifolate antibiotics, and to host antimicrobial peptides such as LL-37, human β-defensin (HBD) 2 and HBD3; and lactoferricin B. The interaction between P. aeruginosa and S. aureus is multifaceted. In mucoid P. aeruginosa strains, siderophores and rhamnolipids are downregulated thus enhancing the survival of S. aureus. Conversely, protein A from S. aureus inhibits P. aeruginosa biofilm formation while protecting both P. aeruginosa and S. aureus from phagocytosis by neutrophils. This review attempts to summarize the current understanding of the molecular mechanisms that drive the competitive and cooperative interactions between S. aureus and P. aeruginosa in the CF lungs that could influence the disease outcome.

NMR spectroscopy spotlighting immunogenicity induced by COVID-19 vaccination to mitigate future health concerns

In this review, the disease and immunogenicity affected by COVID-19 vaccination at the metabolic level are described considering the use of nuclear magnetic resonance (NMR) spectroscopy for the analysis of different biological samples. Consistently, we explain how different biomarkers can be examined in the saliva, blood plasma/serum, bronchoalveolar-lavage fluid (BALF), semen, feces, urine, cerebrospinal fluid (CSF) and breast milk. For example, the proposed approach for the given samples can allow one to detect molecular biomarkers that can be relevant to disease and/or vaccine interference in a system metabolome. The analysis of the given biomaterials by NMR often produces complex chemical data which can be elucidated by multivariate statistical tools, such as PCA and PLS-DA/OPLS-DA methods. Moreover, this approach may aid to improve strategies that can be helpful in disease control and treatment management in the future.

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NMR analysis of various bio-samples can explore disease course and vaccine interaction.

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Immunogenicity and reactogenicity caused by COVID-19 vaccination can be studied by NMR.

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Vaccine interaction alters metabolic pathway(s) at a certain stage, and this mechanism can be probed at the metabolic level.

Identification of Volatile Organic Compounds in Extremophilic Bacteria and Their Effective Use in Biocontrol of Postharvest Fungal Phytopathogens

Phytopathogenic fungal growth in postharvest fruits and vegetables is responsible for 20-25% of production losses. Volatile organic compounds (VOCs) have been gaining importance in the food industry as a safe and ecofriendly alternative to pesticides for combating these phytopathogenic fungi. In this study, we analysed the ability of some VOCs produced by strains of the genera Bacillus, Peribacillus, Pseudomonas, Psychrobacillus and Staphylococcus to inhibit the growth of Alternaria alternata, Botrytis cinerea, Fusarium oxysporum, Fusarium solani, Monilinia fructicola, Monilinia laxa and Sclerotinia sclerotiorum, in vitro and in vivo. We analysed bacterial VOCs by using GC/MS and 87 volatile compounds were identified, in particular acetoin, acetic acid, 2,3-butanediol, isopentanol, dimethyl disulphide and isopentyl isobutanoate. In vitro growth inhibition assays and in vivo experiments using cherry fruits showed that the best producers of VOCs, Bacillus atrophaeus L193, Bacillus velezensis XT1 and Psychrobacillus vulpis Z8, exhibited the highest antifungal activity against B. cinerea, M. fructicola and M. laxa, which highlights the potential of these strains to control postharvest diseases. Transmission electron microscopy micrographs of bacterial VOC-treated fungi clearly showed antifungal activity which led to an intense degeneration of cellular components of mycelium and cell death.

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.

Bacterial Long-Range Warfare: Aerial Killing of Legionella pneumophila by Pseudomonas fluorescens

Legionella pneumophila, the causative agent of Legionnaires’ disease, is mostly found in man-made water systems and is one of the most closely monitored waterborne pathogens. With the aim of finding natural ways to control waterborne pathogens and thus further reduce the impact of disinfection by-products on human health, some studies have demonstrated the ability of bacteria to kill Legionella through the production of secondary metabolites or antimicrobial compounds. Here, we describe an unexpected growth inhibition of L. pneumophila when exposed to a physically separated strain of Pseudomonas fluorescens, designated as MFE01. Most of the members of the Legionellaceae family are sensitive to the volatile substances emitted by MFE01, unlike other bacteria tested. Using headspace solid-phase microextraction GC-MS strategy, a volatilome comparison revealed that emission of 1-undecene, 2-undecanone, and 2-tridecanone were mainly reduced in a Tn5-transposon mutant unable to inhibit at distance the growth of L. pneumophila strain Lens. We showed that 1-undecene was mainly responsible for the inhibition at distance in vitro, and led to cell lysis in small amounts, as determined by gas chromatography-mass spectrometry (GC-MS). Collectively, our results provide new insights into the mode of action of bacterial volatiles and highlight them as potent anti-Legionella agents to focus research on novel strategies to fight legionellosis.

IMPORTANCE Microbial volatile compounds are molecules whose activities are increasingly attracting the attention of researchers. Indeed, they can act as key compounds in long-distance intrakingdom and interkingdom communication, but also as antimicrobials in competition and predation. In fact, most studies to date have focused on their antifungal activities and only a few have reported on their antibacterial properties. Here, we describe that 1-undecene, naturally produced by P. fluorescens, is a volatile with potent activity against bacteria of the genus Legionella. In small amounts, it is capable of inducing cell lysis even when the producing strain is physically separated from the target. This is the first time that such activity is described. This molecule could therefore constitute an efficient compound to counter bacterial pathogens whose treatment may fail, particularly in pulmonary diseases. Indeed, inhalation of these volatiles should be considered as a possible route of therapy in addition to antibiotic treatment.

Recognition of pathogens in food matrixes based on the untargeted in vivo microbial metabolite profiling via a novel SPME/GC × GC-QTOFMS approach

Foodborne diseases incurred by pathogenic bacteria are one of the major threats in food safety, and thus it is important to develop facile and effective recognition methodology of pathogens in food. Herein, a new automatic approach for detection of in vivo volatile metabolites emitted from foodborne pathogens was proposed by coupling solid phase microextraction (SPME) technique with a comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A novel polymer composite based SPME probe which possessed high-coverage of microbial metabolites was utilized in this contribution to realize the sensitive extraction of untargeted metabolites. As a result, a total of 126 in vivo metabolites generated by the investigated pathogens were detected and identified, with 33, 29, 25, 21 and 18 volatile metabolites belonging to Shigella sonnei, Escherichia coli, Salmonella typhimurium, Vibrio parahaemolyticus and Staphylococcus aureus, respectively. Multivariate statistical analyses were applied for further analysis of metabolic data and separation of responsive metabolic features among different microbial systems were found, which were also successfully verified in foodstuffs contaminated by microorganisms. The growth trend of the potential volatile markers of each pathogen in food samples kept consistent with that of the pure strain incubated in medium during the whole incubation time. This study promotes the application of SPME technology in microbial volatile metabolomics and contributes to the development of new approaches for foodborne pathogens recognition.

Bacterial Interactions with Aspergillus fumigatus in the Immunocompromised Lung

The immunocompromised airways are susceptible to infections caused by a range of pathogens which increases the opportunity for polymicrobial interactions to occur. Pseudomonas aeruginosa and Staphylococcus aureus are the predominant causes of pulmonary infection for individuals with respiratory disorders such as cystic fibrosis (CF). The spore-forming fungus Aspergillus fumigatus, is most frequently isolated with P. aeruginosa, and co-infection results in poor outcomes for patients. It is therefore clinically important to understand how these pathogens interact with each other and how such interactions may contribute to disease progression so that appropriate therapeutic strategies may be developed. Despite its persistence in the airways throughout the life of a patient, A. fumigatus rarely becomes the dominant pathogen. In vitro interaction studies have revealed remarkable insights into the molecular mechanisms that drive agonistic and antagonistic interactions that occur between A. fumigatus and pulmonary bacterial pathogens such as P. aeruginosa. Crucially, these studies demonstrate that although bacteria may predominate in a competitive environment, A. fumigatus has the capacity to persist and contribute to disease.

Potential of the Electronic Nose for the Detection of Respiratory Diseases with and without Infection

Respiratory tract infections are common, and when affecting the lower airways and lungs, can result in significant morbidity and mortality. There is an unfilled need for simple, non-invasive tools that can be used to screen for such infections at the clinical point of care. The electronic nose (eNose) is a novel technology that detects volatile organic compounds (VOCs). Early studies have shown that certain diseases and infections can result in characteristic changes in VOC profiles in the exhaled breath. This review summarizes current knowledge on breath analysis by the electronic nose and its potential for the detection of respiratory diseases with and without infection.

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.

Dependence of the Staphylococcal Volatilome Composition on Microbial Nutrition

In vitro cultivation of staphylococci is fundamental to both clinical and research microbiology, but few studies, to-date, have investigated how the differences in rich media can influence the volatilome of cultivated bacteria. The objective of this study was to determine the influence of rich media composition on the chemical characteristics of the volatilomes of Staphylococcus aureus and Staphylococcus epidermidis. S. aureus (ATCC 12600) and S. epidermidis (ATCC 12228) were cultured in triplicate in four rich complex media (brain heart infusion (BHI), lysogeny broth (LB), Mueller Hinton broth (MHB), and tryptic soy broth (TSB)), and the volatile metabolites produced by each culture were analyzed using headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). When comparing the chemical compositions of the staph volatilomes by the presence versus absence of volatiles produced in each medium, we observed few differences. However, when the relative abundances of volatiles were included in the analyses, we observed that culturing staph in media containing free glucose (BHI and TSB) resulted in volatilomes dominated by acids and esters (67%). The low-glucose media (LB and MHB) produced ketones in greatest relative abundances, but the volatilome compositions in these two media were highly dissimilar. We conclude that the staphylococcal volatilome is strongly influenced by the nutritional composition of the growth medium, especially the availability of free glucose, which is much more evident when the relative abundances of the volatiles are analyzed, compared to the presence versus absence.

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.

Longitudinal Associations of the Cystic Fibrosis Airway Microbiome and Volatile Metabolites: A Case Study

The identification of 16S rDNA biomarkers from respiratory samples to describe the continuum of clinical disease states within persons having cystic fibrosis (CF) has remained elusive. We sought to combine 16S, metagenomics, and metabolomics data to describe multiple transitions between clinical disease states in 14 samples collected over a 12-month period in a single person with CF. We hypothesized that each clinical disease state would have a unique combination of bacterial genera and volatile metabolites as a potential signature that could be utilized as a biomarker of clinical disease state. Taxonomy identified by 16S sequencing corroborated clinical culture results, with the majority of the 109 PCR amplicons belonging to the bacteria grown in clinical cultures (Escherichia coli and Staphylococcus aureus). While alpha diversity measures fluctuated across disease states, no significant trends were present. Principle coordinates analysis showed that treatment samples trended toward a different community composition than baseline and exacerbation samples. This was driven by the phylum Bacteroidetes (less abundant in treatment, log₂ fold difference -3.29, p = 0.015) and the genus Stenotrophomonas (more abundant in treatment, log₂ fold difference 6.26, p = 0.003). Across all sputum samples, 466 distinct volatile metabolites were identified with total intensity varying across clinical disease state. Baseline and exacerbation samples were rather uniform in chemical composition and similar to one another, while treatment samples were highly variable and differed from the other two disease states. When utilizing a combination of the microbiome and metabolome data, we observed associations between samples dominated Staphylococcus and Escherichia and higher relative abundances of alcohols, while samples dominated by Achromobacter correlated with a metabolomics shift toward more oxidized volatiles. However, the microbiome and metabolome data were not tightly correlated; examining both the metagenomics and metabolomics allows for more context to examine changes across clinical disease states. In our study, combining the sputum microbiome and metabolome data revealed stability in the sputum composition through the first exacerbation and treatment episode, and into the second exacerbation. However, the second treatment ushered in a prolonged period of instability, which after three additional exacerbations and treatments culminated in a new lung microbiome and metabolome.

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 analysis for respiratory infections

One of the most logical applications of modern breath analysis techniques is to provide information on respiratory infections. Ongoing work in various types of pulmonary infections has begun to denote candidate breath biomarkers of bacterial, viral, and fungal lung infections. Groundbreaking studies have been performed in naturally occurring cases with humans and with animal models of the disease. This has been coupled with cell culture work to understand the nature of the origins of breath biomarkers generated from the pathogen itself as it proliferates. Much work remains to be done, and the published studies described in this chapter are helping to set a foundation for this research area.

Influence of media on the differentiation of Staphylococcus spp. by volatile compounds

Staphylococcus aureus asymptomatically colonizes a third of the world's population, and it is an opportunistic pathogen that can cause life threatening diseases. To diagnose S. aureus infections, it is necessary to differentiate S. aureus from the ubiquitous human commensal Staphylococcus epidermidis, which beneficially colonizes the skin of all humans. Efforts are underway to identify volatile biomarkers for diagnosing S. aureus infections, but to date no studies have investigated whether S. aureus and S. epidermidis can be reliably differentiated under a variety of growth conditions. The overall goal of this study was to evaluate the influence of growth medium on the ability to differentiate S. aureus and S. epidermidis based on their volatile profiles. We used headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) to examine the headspace volatiles of S. aureus and S. epidermidis when aerobically grown in four different complex media. We detected 337 volatile features when culturing S. aureus and S. epidermidis in four complex media, termed the staph volatiles, and found only 20%-40% concurrence in the volatiles produced by these two species in any single medium. Using principal components analysis and hierarchical clustering analysis on the staph volatiles, we observed that S. aureus and S. epidermidis clustered independently from each other, and distinctly clustered by growth medium within species. Removing volatiles that are species and/or media-specific from the analysis reduced the resolution between species clusters, but in all models clustering by species overrode clustering by media type. These analyses suggest that, while volatile profiles are media-specific, species differences dominate the staph volatilome. These data enable future investigations into the identification of volatile biomarkers to discriminate staphylococcal pathogens versus commensals, which will improve staph diagnoses and provide insights into the biochemistry of staph infections and immunity.

Improving outcomes of infections in cystic fibrosis in the era of CFTR modulator therapy

Currently, available single and dual-combination cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies have favorably altered the life course of individuals with cystic fibrosis (CF) by decreasing morbidities and increasing survival. However, even with CFTR modulator use, questions and challenges remain to optimize the management of lung infections. This review (a) identifies these ongoing challenges and discusses the current understanding of the potential impact of CFTR modulator therapy on infections; (b) describes ongoing research to optimize detection, diagnosis, and treatment of CF microorganisms; and (c) discusses strategies to develop new anti-infective therapies. The CF Foundation has launched the Infection Research Initiative to fund research that will improve our understanding of the complex microbial ecology within the CF lung, improve detection of CF pathogens, optimize current treatment, including long-term chronic therapies, and develop new anti-infective therapies. Ongoing clinical trials to determine the optimal duration of treatment of pulmonary exacerbations and to diagnose and treat nontuberculous mycobacteria represent clinical research paradigms that could be used to answer other complex treatment questions. The anti-infective pipeline includes both existing anti-infective and non-anti-infective agents, many of which are proposed to have unique mechanisms of action in CF. Future studies plan to evaluate short- and long-term clinical effectiveness and impact on infections, of the next generation of CFTR modulator therapy, the highly effective triple-combination therapy, for individuals with CF, homozygous or heterozygous for F508del.

Pseudomonas aeruginosa-Derived Volatile Sulfur Compounds Promote Distal Aspergillus fumigatus Growth and a Synergistic Pathogen-Pathogen Interaction That Increases Pathogenicity in Co-infection

Pathogen-pathogen interactions in polymicrobial infections are known to directly impact, often to worsen, disease outcomes. For example, co-infection with Pseudomonas aeruginosa and Aspergillus fumigatus, respectively the most common bacterial and fungal pathogens isolated from cystic fibrosis (CF) airways, leads to a worsened prognosis. Recent studies of in vitro microbial cross-talk demonstrated that P. aeruginosa-derived volatile sulfur compounds (VSCs) can promote A. fumigatus growth in vitro. However, the mechanistic basis of such cross-talk and its physiological relevance during co-infection remains unknown. In this study we combine genetic approaches and GC-MS-mediated volatile analysis to show that A. fumigatus assimilates VSCs via cysteine (CysB)- or homocysteine (CysD)-synthase. This process is essential for utilization of VSCs as sulfur sources, since P. aeruginosa-derived VSCs trigger growth of A. fumigatus wild-type, but not of a ΔcysBΔcysD mutant, on sulfur-limiting media. P. aeruginosa produces VSCs when infecting Galleria mellonella and co-infection with A. fumigatus in this model results in a synergistic increase in mortality and of fungal and bacterial burdens. Interestingly, the increment in mortality is much greater with the A. fumigatus wild-type than with the ΔcysBΔcysD mutant. Therefore, A. fumigatus' ability to assimilate P. aeruginosa derived VSCs significantly triggers a synergistic association that increases the pathobiology of infection. Finally, we show that P. aeruginosa can promote fungal growth when growing on substrates that resemble the lung environment, which suggests that this volatile based synergism is likely to occur during co-infection of the human respiratory airways.

Detection of Volatile Compounds Emitted by Bacteria in Wounds Using Gas Sensors

In this paper we analyze an experiment for the use of low-cost gas sensors intended to detect bacteria in wounds using a non-intrusive technique. Seven different genera/species of microbes tend to be present in most wound infections. Detection of these bacteria usually requires sample and laboratory testing which is costly, inconvenient and time-consuming. The validation processes for these sensors with nineteen types of microbes (1 Candida, 2 Enterococcus, 6 Staphylococcus, 1 Aeromonas, 1 Micrococcus, 2 E. coli and 6 Pseudomonas) are presented here, in which four sensors were evaluated: TGS-826 used for ammonia and amines, MQ-3 used for alcohol detection, MQ-135 for CO₂ and MQ-138 for acetone detection. Validation was undertaken by studying the behavior of the sensors at different distances and gas concentrations. Preliminary results with liquid cultures of 10⁸ CFU/mL and solid cultures of 10⁸ CFU/cm² of the 6 Pseudomonas aeruginosa strains revealed that the four gas sensors showed a response at a height of 5 mm. The ammonia detection response of the TGS-826 to Pseudomonas showed the highest responses for the experimental samples over the background signals, with a difference between the values of up to 60 units in the solid samples and the most consistent and constant values. This could suggest that this sensor is a good detector of Pseudomonas aeruginosa, and the recording made of its values could be indicative of the detection of this species. All the species revealed similar CO₂ emission and a high response rate with acetone for Micrococcus, Aeromonas and Staphylococcus.

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.