Comparative analysis of the volatile metabolomes of Pseudomonas aeruginosa clinical isolates

Defining a core breath profile for healthy, non-human primates

Non-human primates remain the most useful and reliable pre-clinical model for many human diseases. Primate breath profiles have previously distinguished healthy animals from diseased, including non-human primates. Breath collection is relatively non-invasive, so this motivated us to define a healthy baseline breath profile that could be used in studies evaluating disease, therapies, and vaccines in non-human primates. A pilot study, which enrolled 30 healthy macaques, was conducted. Macaque breath molecules were sampled into a Tedlar bag, concentrated onto a thermal desorption tube, then desorbed and analyzed by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry. These breath samples contained 2,017 features, of which 113 molecules were present in all breath samples. The core breathprint was dominated by aliphatic hydrocarbons, aromatic compounds, and carbonyl compounds. The data were internally validated with additional breath samples from a subset of 19 of these non-human primates. A critical core consisting of 23 highly abundant and invariant molecules was identified as a pragmatic breathprint set, useful for future validation studies in healthy primates.

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.

Olfaction regulates peripheral mitophagy and mitochondrial function

The central nervous system coordinates peripheral cellular stress responses, including the unfolded protein response of the mitochondria (UPRMT); however, the contexts for which this regulatory capability evolved are unknown. UPRMT is up-regulated upon pathogenic infection and in metabolic flux, and the olfactory nervous system has been shown to regulate pathogen resistance and peripheral metabolic activity. Therefore, we asked whether the olfactory nervous system in Caenorhabditis elegans controls the UPRMT cell nonautonomously. We found that silencing a single inhibitory olfactory neuron pair, AWC, led to robust induction of UPRMT and reduction of oxidative phosphorylation dependent on serotonin signaling and parkin-mediated mitophagy. Further, AWC ablation confers resistance to the pathogenic bacteria Pseudomonas aeruginosa partially dependent on the UPRMT transcription factor atfs-1 and fully dependent on mitophagy machinery. These data illustrate a role for the olfactory nervous system in regulating whole-organism mitochondrial dynamics, perhaps in preparation for postprandial metabolic stress or pathogenic infection.

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.

Dogs can detect an odor profile associated with Staphylococcus aureus biofilms in cultures and biological samples

Introduction

The study investigated the utilization of odor detection dogs to identify the odor profile of Staphylococcus aureus (S. aureus) biofilms in pure in vitro samples and in in vivo biosamples from animals and humans with S. aureus periprosthetic joint infection (PJI). Biofilms form when bacterial communities aggregate on orthopedic implants leading to recalcitrant infections that are difficult to treat. Identifying PJI biofilm infections is challenging, and traditional microbiological cultures may yield negative results even in the presence of clinical signs.

Methods

Dogs were trained on pure in vitro S. aureus biofilms and tested on lacrimal fluid samples from an in vivo animal model (rabbits) and human patients with confirmed S. aureus PJI.

Results

The results demonstrated that dogs achieved a high degree of sensitivity and specificity in detecting the odor profile associated with S. aureus biofilms in rabbit samples. Preliminary results suggest that dogs can recognize S. aureus volatile organic compounds (VOCs) in human lacrimal fluid samples.

Discussion

Training odor detection dogs on in vitro S. aureus, may provide an alternative to obtaining clinical samples for training and mitigates biosecurity hazards. The findings hold promise for culture-independent diagnostics, enabling early disease detection, and improved antimicrobial stewardship. In conclusion, this research demonstrates that dogs trained on in vitro S. aureus samples can identify the consistent VOC profile of PJI S. aureus biofilm infections. The study opens avenues for further investigations into a retained VOC profile of S. aureus biofilm infection. These advancements could revolutionize infectious disease diagnosis and treatment, leading to better patient outcomes and addressing the global challenge of antimicrobial resistance.

Genomic and metabolic versatility of Pseudomonas aeruginosa contributes to its inter-kingdom transmission and survival

Pseudomonas aeruginosa is one of the most versatile bacteria with renowned pathogenicity and extensive drug resistance. The diverse habitats of this bacterium include fresh, saline and drainage waters, soil, moist surfaces, taps, showerheads, pipelines, medical implants, nematodes, insects, plants, animals, birds and humans. The arsenal of virulence factors produced by P. aeruginosa includes pyocyanin, rhamnolipids, siderophores, lytic enzymes, toxins and polysaccharides. All these virulent elements coupled with intrinsic, adaptive and acquired antibiotic resistance facilitate persistent colonization and lethal infections in different hosts. To date, treating pulmonary diseases remains complicated due to the chronic secondary infections triggered by hospital-acquired P. aeruginosa. On the contrary, this bacterium can improve plant growth by suppressing phytopathogens and insects. Notably, P. aeruginosa is one of the very few bacteria capable of trans-kingdom transmission and infection. Transfer of P. aeruginosa strains from plant materials to hospital wards, animals to humans, and humans to their pets occurs relatively often. Recently, we have identified that plant-associated P. aeruginosa strains could be pathologically similar to clinical isolates. In this review, we have highlighted the genomic and metabolic factors that facilitate the dominance of P. aeruginosa across different biological kingdoms and the varying roles of this bacterium in plant and human health.

Volatilomes of human infection

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

Toward Comprehensive Analysis of the 3D Chemistry of Pseudomonas aeruginosa Biofilms

Bacterial biofilms are structured communities consisting of cells enmeshed in a self-generated extracellular matrix usually attached to a surface. They contain diverse classes of molecules including polysaccharides, lipids, proteins, nucleic acids, and diverse small organic molecules (primary and secondary metabolites) which are organized to optimize survival and facilitate dispersal to new colonization sites. In situ characterization of the chemical composition and structure of bacterial biofilms is necessary to fully understand their development on surfaces relevant to biofouling in health, industry, and the environment. Biofilm development has been extensively studied using confocal microscopy using targeted fluorescent labels providing important insights into the architecture of biofilms. Recently, cryopreparation has been used to undertake targeted in situ chemical characterization using Orbitrap secondary ion mass spectrometry (OrbiSIMS), providing a label-free method for imaging biofilms in their native state. Although the high mass resolution of OrbiSIMS enables more confident peak assignments, it is still very challenging to assign most of the peaks in the spectra due to complexity of SIMS spectra and lack of automatic peak assignment methods. Here, we analyze the same OrbiSIMS depth profile data generated from the frozen-hydrated biofilm, but employ a new untargeted chemical filtering process utilizing mass spectral databases to assign secondary ions to decipher the large number of fragments present in the SIMS spectra. To move towards comprehensive analysis of different chemistries in the sample, we apply a molecular formula prediction approach which putatively assigns 81% of peaks in the 3D OrbiSIMS depth profile analysis. This enables us to catalog over 1000 lipids and their fragments, 3500 protein fragments, 71 quorum sensing-related molecules (2-alkyl-4-quinolones and N-acylhomoserine lactones), 150 polysaccharide fragments, and glycolipids simultaneously from one data set and map these separated molecular classes spatially through a Pseudomonas aeruginosa biofilm. Assignment of different chemistries in this sample facilitates identification of differences between biofilms grown on biofilm-promoting and biofilm-resistant polymers.

Microbial Volatiles as Diagnostic Biomarkers of Bacterial Lung Infection in Mechanically Ventilated Patients

BACKGROUND

Early and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as noninvasive biomarkers of infection to support clinical diagnosis.

METHODS

In this study, we investigated the diagnostic potential of in vitro-confirmed mVOCs in the exhaled breath of patients under mechanical ventilation from the BreathDx study. Samples were analyzed by thermal desorption-gas chromatography-mass spectrometry.

RESULTS

Pathogens from bronchoalveolar lavage (BAL) cultures were identified in 45 of 89 patients and Staphylococcus aureus was the most commonly identified pathogen (n = 15). Of 19 mVOCs detected in the in vitro culture headspace of 4 common respiratory pathogens (S. aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of 2 mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal: P < .01, area under the receiver operating characteristic curve [AUROC] = 0.81-0.87; and 3-methylbutanoic acid: P = .01, AUROC = 0.79-0.80). In addition, bacteria identified from BAL cultures that are known to metabolize tryptophan (E. coli, Klebsiella oxytoca, and Haemophilus influenzae) were grouped and found to produce higher concentrations of indole compared to breath samples with culture-negative (P = .034) and other pathogen-positive (P = .049) samples.

CONCLUSIONS

This study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multicenter clinical studies.

Volatiles of the Apicomplexan Alga Chromera velia and Associated Bacteria

Volatiles released by the apicomplexan alga Chromera velia CCAP1602/1 and their associated bacteria have been investigated. A metagenome analysis allowed the identification of the most abundant heterotrophic bacteria of the phycosphere, but the isolation of additional strains showed that metagenomics underestimated the complexity of the algal microbiome, However, a culture-independent approach revealed the presence of a planctomycete that likely represents a novel bacterial family. We analysed algal and bacterial volatiles by open-system-stripping analysis (OSSA) on Tenax TA desorption tubes, followed by thermodesorption, cryofocusing and GC-MS-analysis. The analyses of the alga and the abundant bacterial strains Sphingopyxis litoris A01A-101, Algihabitans albus A01A-324, "Coraliitalea coralii" A01A-333 and Litoreibacter sp. A01A-347 revealed sulfur- and nitrogen-containing compounds, ketones, alcohols, aldehydes, aromatic compounds, amides and one lactone, as well as the typical algal products, apocarotenoids. The compounds were identified by gas chromatographic retention indices, comparison of mass spectra and syntheses of reference compounds. A major algal metabolite was 3,4,4-trimethylcyclopent-2-en-1-one, an apocarotenoid indicating the presence of carotenoids related to capsanthin, not reported from algae so far. A low overlap in volatiles bouquets between C. velia and the bacteria was found, and the xenic algal culture almost exclusively released algal components.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Addressing Missing Data in GC × GC Metabolomics: Identifying Missingness Type and Evaluating the Impact of Imputation Methods on Experimental Replication

Missing data is a significant issue in metabolomics that is often neglected when conducting data preprocessing, particularly when it comes to imputation. This can have serious implications for downstream statistical analyses and lead to misleading or uninterpretable inferences. In this study, we aim to identify the primary types of missingness that affect untargeted metabolomics data and compare strategies for imputation using two real-world comprehensive two-dimensional gas chromatography (GC × GC) data sets. We also present these goals in the context of experimental replication whereby imputation is conducted in a within-replicate-based fashion─the first description and evaluation of this strategy─and introduce an R package MetabImpute to carry out these analyses. Our results conclude that, in these two GC × GC data sets, missingness was most likely of the missing at-random (MAR) and missing not-at-random (MNAR) types as opposed to missing completely at-random (MCAR). Gibbs sampler imputation and Random Forest gave the best results when imputing MAR and MNAR compared against single-value imputation (zero, minimum, mean, median, and half-minimum) and other more sophisticated approaches (Bayesian principal component analysis and quantile regression imputation for left-censored data). When samples are replicated, within-replicate imputation approaches led to an increase in the reproducibility of peak quantification compared to imputation that ignores replication, suggesting that imputing with respect to replication may preserve potentially important features in downstream analyses for biomarker discovery.

Subtle relationships between Pseudomonas aeruginosa and fungi in patients with cystic fibrosis

Cystic fibrosis (CF) is one of the most common hereditary lung diseases. Pseudomonas aeruginosa (PA), Aspergillus fumigatus (AF) and Candida albicans (CA) are the principal bacterial and fungal pathogens in the airways of CF patients. The interactions of coexisting bacterial-fungal pathogens are of great interest. In the present work, we reviewed the literature of available in vitro and in vivo studies, whereas most of the reports have shown that PA inhibits the growth of fungi through restriction of iron uptake and secretion of toxic substances. Fungi may also affect the growth or virulence of PA through their secreted molecules. To clarify the bacterial-fungal interaction, more in-depth and detailed studies are still needed, which will provide a better understanding of species, microbial population dynamics, and related mechanisms in CF patients.

Application of a Target-Guided Data Processing Approach in Saturated Peak Correction of GC×GC Analysis

Detector and column saturations are problematic in comprehensive two-dimensional gas chromatography (GC×GC) data analysis. This limits the application of GC×GC in metabolomics research. To address the problems caused by detector and column saturations, we propose a two-stage data processing strategy that will incorporate a targeted data processing and cleaning approach upstream of the “standard” untargeted analysis. By using the retention time and mass spectrometry (MS) data stored in a library, the annotation and quantification of the targeted saturated peaks have been significantly improved. After subtracting the nonperfected signals caused by saturation, peaks of coelutes can be annotated more accurately. Our research shows that the target-guided method has broad application prospects in the data analysis of GC×GC chromatograms of complex samples.

Differentiation of Cystic Fibrosis-Related Pathogens by Volatile Organic Compound Analysis with Secondary Electrospray Ionization Mass Spectrometry

Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.

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

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

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.

Life Cycle Dominates the Volatilome Character of Dimorphic Fungus Coccidioides spp

Valley fever (coccidioidomycosis) is an endemic fungal pneumonia of the North and South American deserts. The causative agents of Valley fever are the dimorphic fungi Coccidioides immitis and C. posadasii, which grow as mycelia in the environment and as spherules within the lungs of vulnerable hosts. Current diagnostics for Valley fever are severely lacking due to poor sensitivity and invasiveness, contributing to a 23-day median time to diagnosis, and therefore, new diagnostic tools are needed. We are working toward the development of a breath-based diagnostic for coccidioidomycosis, and in this initial study, we characterized the volatile metabolomes (or volatilomes) of in vitro cultures of Coccidioides. Using solid-phase microextraction (SPME) and comprehensive two-dimensional gas chromatography coupled to time of flight mass spectrometry (GC×GC-TOFMS), we characterized the volatile organic compounds (VOCs) produced by six strains of each species during mycelial or spherule growth. We detected a total of 353 VOCs that were at least 2-fold more abundant in a Coccidioides culture than in medium controls and found that the volatile metabolome of Coccidioides is more dependent on the growth phase (spherules versus mycelia) than on the species. The volatile profiles of C. immitis and C. posadasii have strong similarities, indicating that a single suite of Valley fever breath biomarkers can be developed to detect both species.

IMPORTANCE Coccidioidomycosis, or Valley fever, causes up to 30% of community-acquired pneumonias in highly populated areas of the U.S. desert southwest where the disease is endemic. The infection is difficult to diagnose by standard serological and histopathological methods, which delays appropriate treatment. Therefore, we are working toward the development of breath-based diagnostics for Valley fever. In this study, we characterized the volatile metabolomes (or volatilomes) of six strains each of Coccidioides immitis and C. posadasii, the dimorphic fungal species that cause Valley fever. By analyzing the volatilomes during the two modes of growth of the fungus—mycelia and spherules—we observed that the life cycle plays a significant role in the volatiles produced by Coccidioides. In contrast, we observed no significant differences in the C. immitis versus C. posadasii volatilomes. These data suggest that life cycle, rather than species, should guide the selection of putative biomarkers for a Valley fever breath test.

Learning about microbial language: possible interactions mediated by microbial volatile organic compounds (VOCs) and relevance to understanding Malassezia spp. metabolism

BACKGROUND

Microorganisms synthesize and release a large diversity of small molecules like volatile compounds, which allow them to relate and interact with their environment. Volatile organic compounds (VOCs) are carbon-based compounds with low molecular weight and generally, high vapor pressure; because of their nature, they spread easily in the environment. Little is known about the role of VOCs in the interaction processes, and less is known about VOCs produced by Malassezia, a genus of yeasts that belongs to the human skin mycobiota. These yeasts have been associated with several dermatological diseases and currently, they are considered as emerging opportunistic yeasts. Research about secondary metabolites of these yeasts is limited. The pathogenic role and the molecular mechanisms involved in the infection processes of this genus are yet to be clarified. VOCs produced by Malassezia yeasts could play an important function in their metabolism; in addition, they might be involved in either beneficial or pathogenic host-interaction processes. Since these yeasts present differences in their nutritional requirements, like lipids to grow, it is possible that these variations of growth requirements also define differences in the volatile organic compounds produced in Malassezia species.

AIM OF REVIEW

We present a mini review about VOCs produced by microorganisms and Malassezia species, and hypothesize about their role in its metabolism, which would reveal clues about host-pathogen interaction.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Since living organisms inhabit a similar environment, the interaction processes occur naturally; as a result, a signal and a response from participants of these processes become important in understanding several biological behaviors. The efforts to elucidate how living organisms interact has been studied from several perspectives. An important issue is that VOCs released by the microbiota plays a key role in the setup of relationships between living micro and macro organisms. The challenge is to determine what is the role of these VOCs produced by human microbiota in commensal/pathogenic scenarios, and how these allow understanding the species metabolism. Malassezia is part of the human mycobiota, and it is implicated in commensal and pathogenic processes. It is possible that their VOCs are involved in these behavioral changes, but the knowledge about this remains overlocked. For this reason, VOCs produced by microorganisms and Malassezia spp. and their role in several biological processes are the main topic in this review.

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

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

Multi-strain volatile profiling of pathogenic and commensal cutaneous bacteria

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

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

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

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

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

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.

Comparative Genomic and Metabolomic Analyses of Two Pseudomonas aeruginosa Strains With Different Antifungal Activities

Pseudomonas aeruginosa isolated from the plant rhizosphere has been widely used as an effective strain in biological control against plant disease. This bacterium promotes plant growth and protect plants against various phytopathogens through the production of phenazine metabolites. In this study, the strain P. aeruginosa Y12 with anti-Beauveria bassiana activity was isolated from the gut of housefly larvae. It was comparatively analyzed with the strain P. aeruginosa P18, which showed no anti-B. bassiana activity. Genomic and metabolomic methods were used to obtain a comprehensive understanding of the antimicrobial mechanism of Y12. After whole-genome resequencing of the two strains, a total of 7,087 non-synonymous single-nucleotide polymorphisms (nsSNPs), 1079 insertions and deletions (InDels), 62 copy-number variations (CNVs) and 42 structural variations (SV) were found in both strains. We analyzed the differentially abundant metabolites between Y12 and P18, and identified six bioactive compounds that could be associated with the antimicrobial activity of Y12. Additionally, we found that, unlike other previously reported rhizospheric P. aeruginosa strains, Y12 could produce both phenazine-1,6-dicarboxylic acid (PDC) and pyocyanin (PYO) at significantly higher concentrations than P18. As B. bassiana is an effective biological insecticide that can cause high mortality in adult houseflies but has little effect on housefly larvae, we believe that P. aeruginosa Y12, identified in housefly larvae but not in adults, were beneficial for the development of housefly larvae and could protect them from B. bassiana infection through the production of toxic metabolites.

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.

Untargeted LC-MS Metabolomics Differentiates Between Virulent and Avirulent Clinical Strains of Pseudomonas aeruginosa

Pseudomonas aeruginosa is a facultative pathogen that can cause, inter alia, acute or chronic pneumonia in predisposed individuals. The gram-negative bacterium displays considerable genomic and phenotypic diversity that is also shaped by small molecule secondary metabolites. The discrimination of virulence phenotypes is highly relevant to the diagnosis and prognosis of P. aeruginosa infections. In order to discover small molecule metabolites that distinguish different virulence phenotypes of P. aeruginosa, 35 clinical strains were cultivated under standard conditions, characterized in terms of virulence and biofilm phenotype, and their metabolomes were investigated by untargeted liquid chromatography-mass spectrometry. The data was both mined for individual candidate markers as well as used to construct statistical models to infer the virulence phenotype from metabolomics data. We found that clinical strains that differed in their virulence and biofilm phenotype also had pronounced divergence in their metabolomes, as underlined by 332 features that were significantly differentially abundant with fold changes greater than 1.5 in both directions. Important virulence-associated secondary metabolites like rhamnolipids, alkyl quinolones or phenazines were found to be strongly upregulated in virulent strains. In contrast, we observed little change in primary metabolism. A hitherto novel cationic metabolite with a sum formula of C₁₂H₁₅N₂ could be identified as a candidate biomarker. A random forest model was able to classify strains according to their virulence and biofilm phenotype with an area under the Receiver Operation Characteristics curve of 0.84. These findings demonstrate that untargeted metabolomics is a valuable tool to characterize P. aeruginosa virulence, and to explore interrelations between clinically important phenotypic traits and the bacterial metabolome.

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.

Inhibition of Fungal Growth and Induction of a Novel Volatilome in Response to Chromobacterium vaccinii Volatile Organic Compounds

The study of chemical bioactivity in the rhizosphere has recently broadened to include microbial metabolites, and their roles in niche construction and competition via growth promotion, growth inhibition, and toxicity. Several prior studies have identified bacteria that produce volatile organic compounds (VOCs) with antifungal activities, indicating their potential use as biocontrol organisms to suppress phytopathogenic fungi and reduce agricultural losses. We sought to expand the roster of soil bacteria with known antifungal VOCs by testing bacterial isolates from wild and cultivated cranberry bog soils for VOCs that inhibit the growth of four common fungal and oomycete plant pathogens, and Trichoderma sp. Twenty one of the screened isolates inhibited the growth of at least one fungus by the production of VOCs, and isolates of Chromobacterium vaccinii had broad antifungal VOC activity, with growth inhibition over 90% for some fungi. Fungi exposed to C. vaccinii VOCs had extensive morphological abnormalities such as swollen hyphal cells, vacuolar depositions, and cell wall alterations. Quorum-insensitive cviR⁻ mutants of C. vaccinii were significantly less fungistatic, indicating a role for quorum regulation in the production of antifungal VOCs. We collected and characterized VOCs from co-cultivation assays of Phoma sp. exposed to wild-type C. vaccinii MWU328, and its cviR⁻ mutant using stir bar sorptive extraction and comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (SBSE-GC × GC-TOFMS). We detected 53 VOCs that differ significantly in abundance between microbial cultures and media controls, including four candidate quorum-regulated fungistatic VOCs produced by C. vaccinii. Importantly, the metabolomes of the bacterial-fungal co-cultures were not the sum of the monoculture VOCs, an emergent property of their VOC-mediated interactions. These data suggest semiochemical feedback loops between microbes that have co-evolved for sensing and responding to exogenous VOCs.

Defining Critical Genes During Spherule Remodeling and Endospore Development in the Fungal Pathogen, Coccidioides posadasii

Coccidioides immitis and C. posadasii are soil dwelling dimorphic fungi found in North and South America. Inhalation of aerosolized asexual conidia can result in asymptomatic, acute, or chronic respiratory infection. In the United States there are approximately 350,000 new infections per year. The Coccidioides genus is the only known fungal pathogen to make specialized parasitic spherules, which contain endospores that are released into the host upon spherule rupture. The molecular determinants involved in this key step of infection remain largely elusive as 49% of genes are hypothetical with unknown function. An attenuated mutant strain C. posadasii Δcts2/Δard1/Δcts3 in which chitinase genes 2 and 3 were deleted was previously created for vaccine development. This strain does not complete endospore development, which prevents completion of the parasitic lifecycle. We sought to identify pathways active in the wild-type strain during spherule remodeling and endospore formation that have been affected by gene deletion in the mutant. We compared the transcriptome and volatile metabolome of the mutant Δcts2/Δard1/Δcts3 to the wild-type C735. First, the global transcriptome was compared for both isolates using RNA sequencing. The raw reads were aligned to the reference genome using TOPHAT2 and analyzed using the Cufflinks package. Genes of interest were screened in an in vivo model using NanoString technology. Using solid phase microextraction (SPME) and comprehensive two-dimensional gas chromatography - time-of-flight mass spectrometry (GC × GC-TOFMS) volatile organic compounds (VOCs) were collected and analyzed. Our RNA-Seq analyses reveal approximately 280 significantly differentially regulated transcripts that are either absent or show opposite expression patterns in the mutant compared to the parent strain. This suggests that these genes are tied to networks impacted by deletion and may be critical for endospore development and/or spherule rupture in the wild-type strain. Of these genes, 14 were specific to the Coccidioides genus. We also found that the wild-type and mutant strains differed significantly in their production versus consumption of metabolites, with the mutant displaying increased nutrient scavenging. Overall, our results provide the first targeted list of key genes that are active during endospore formation and demonstrate that this approach can define targets for functional assays in future studies.

A Metabolomic Approach for Predicting Diurnal Changes in Cortisol

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.

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.

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.

Targeting LOX-1 Inhibits Colorectal Cancer Metastasis in an Animal Model

Recurrence and metastasis are the primary causes of mortality in patients with colorectal cancer (CRC), and therefore effective tools to reduce morbidity and mortality of CRC patients are necessary. LOX-1, the ox-LDL receptor, is strongly involved in inflammation, obesity, and atherosclerosis, and several studies have assessed its role in the carcinogenesis process linking ROS, metabolic disorders and cancer. We have already demonstrated in vitro that LOX-1 expression correlates to the aggressiveness of human colon cancer and its downregulation weakens the tumoral phenotype, indicating its potential function as a biomarker and a target in CRC therapy. Here we further investigate in vivo the role of LOX-1 in colon tumorigenesis by xenografting procedures, injecting nude mice both subcutaneously and intravenously with human high grade metastatic colorectal cancer cells, DLD-1, in which LOX-1 expression has been downregulated by shRNA (LOX-1RNAi cells). Histopathological and immunohistochemical evaluations have been performed on xenograft tumors. The experiments have been complemented by the analysis of the volatile compounds (VOCs) collected from the cages of injected mice and analyzed by gas-chromatography and gas sensors. After intravenous injection of LOX-1RNAi cells, we found that LOX-1 silencing influences both the engraftment of the tumor and the metastasis development, acting by angiogenesis. For the first time, we have observed that LOX-1 inhibition significantly prevents metastasis formation in injected mice and, at the same time, induces a downregulation of VEGF-A165, HIF-1α, and β-catenin whose expression is involved in cell migration and metastasis, and a variation of histone H4 acetylation pattern suggesting also a role of LOX-1 in regulating gene transcription. The analysis of the volatile compounds (VOCs) collected from the cages of injected mice has evidenced a specific profile in those xenograft mice in which metastasis originates. These findings underline the role of LOX-1 as a potential target for inhibition of tumor progression and metastasis, enhancing current therapeutic strategies against colorectal cancer.

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.

In vitro Interactions of Pseudomonas aeruginosa With Scedosporium Species Frequently Associated With Cystic Fibrosis

Members of the Scedosporium apiospermum species complex are the second most frequently isolated pathogens after Aspergillus fumigatus from cystic fibrosis (CF) patients with fungal pulmonary infections. Even so, the main risk factors for the infection are unrevealed. According to previous studies, bacterial infections might reduce the risk of a fungal infection, but an antibacterial therapy may contribute to the airway colonization by several fungal pathogens. Furthermore, corticosteroids, which are often used to reduce lung inflammation in children and adults with CF, are also proved to enhance the growth of A. fumigatus in vitro. Considering all the above discussed points, we aimed to test how Pseudomonas aeruginosa influences the growth of scedosporia and to investigate the potential effect of commonly applied antibacterial agents and corticosteroids on Scedosporium species. Direct interactions between fungal and bacterial strains were tested using the disk inhibition method. Indirect interactions via volatile compounds were investigated by the plate-in-plate method, while the effect of bacterial media-soluble molecules was tested using a modified cellophane assay and also in liquid culture media conditioned by P. aeruginosa. To test the effect of bacterial signal molecules, antibacterial agents and corticosteroids on the fungal growth, the broth microdilution method was used. We also investigated the germination ability of Scedosporium conidia in the presence of pyocyanin and diffusible signal factor by microscopy. According to our results, P. aeruginosa either inhibited or enhanced the growth of scedosporia depending on the culture conditions and the mode of interactions. When the two pathogens were cultured physically separately from each other in the plate-in-plate tests, the presence of the bacteria was able to stimulate the growth of several fungal isolates. While in direct physical contact, bacterial strains inhibited the fungal growth. This effect might be attributed to bacterial signal molecules, which also proved to inhibit the germination and growth of scedosporia. In addition, antibacterial agents showed growth-promoting, while corticosteroids exhibited growth inhibitory effect on several Scedosporium isolates. These data raise the possibility that a P. aeruginosa infection or a previously administered antibacterial therapy might be able to increase the chance of a Scedosporium colonization in a CF lung.

Metabolomic richness and fingerprints of deep-sea coral species and populations

INTRODUCTION

From shallow water to the deep sea, corals form the basis of diverse communities with significant ecological and economic value. These communities face many anthropogenic stressors including energy and mineral extraction activities, ocean acidification and rising sea temperatures. Corals and their symbionts produce a diverse assemblage of compounds that may help provide resilience to some of these stressors.

OBJECTIVES

We aim to characterize the metabolomic diversity of deep-sea corals in an ecological context by investigating patterns across space and phylogeny.

METHODS

We applied untargeted Liquid Chromatography-Mass Spectrometry to examine the metabolomic diversity of the deep-sea coral, Callogorgia delta, across three sites in the Northern Gulf of Mexico as well as three other deep-sea corals, Stichopathes sp., Leiopathes glaberrima, and Lophelia pertusa, and a shallow-water species, Acropora palmata.

RESULTS

Different coral species exhibited distinct metabolomic fingerprints and differences in metabolomic richness including core ions unique to each species. C. delta was generally least diverse while Lophelia pertusa was most diverse. C. delta from different sites had different metabolomic fingerprints and metabolomic richness at individual and population levels, although no sites exhibited unique core ions. Two core ions unique to C. delta were putatively identified as diterpenes and thus may possess a biologically important function.

CONCLUSION

Deep-sea coral species have distinct metabolomic fingerprints and exhibit high metabolomic diversity at multiple scales which may contribute to their capabilities to respond to both natural and anthropogenic stressors, including climate change.

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.

Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics

Due to excellent separation capacity for complex mixtures of chemicals, comprehensive two-dimensional gas chromatography (GC × GC) is being utilized with increasing frequency for metabolomics analyses. This review describes recent advances in GC × GC method development for metabolomics, organismal sampling techniques compatible with GC × GC, metabolomic discoveries made using GC × GC, and recommendations and best practices for collecting and reporting GC × GC metabolomics data.

Sampling Dynamics for Volatile Organic Compounds Using Headspace Solid-Phase Microextraction Arrow for Microbiological Samples

Volatile organic compounds (VOCs) are monitored in numerous fields using several commercially-available sampling options. Sorbent-based sampling techniques, such as solid-phase microextraction (SPME), provide pre-concentration and focusing of VOCs prior to gas chromatography–mass spectrometry (GC–MS) analysis. This study investigated the dynamics of SPME Arrow, which exhibits an increased sorbent phase volume and improved durability compared to traditional SPME fibers. A volatile reference mixture (VRM) and saturated alkanes mix (SAM) were used to investigate optimal parameters for microbiological VOC profiling in combination with GC–MS analysis. Fiber type, extraction time, desorption time, carryover, and reproducibility were characterized, in addition to a comparison with traditional SPME fibers. The developed method was then applied to longitudinal monitoring of Bacillus subtilis cultures, which represents a ubiquitous microbe in medical, forensic, and agricultural applications. The carbon wide range/polydimethylsiloxane (CWR/PDMS) fiber was found to be optimal for the range of expected VOCs in microbiological profiling, and a statistically significant increase in the majority of VOCs monitored was observed. B. subtilis cultures released a total of 25 VOCs of interest, across three different temporal trend categories (produced, consumed, and equilibrated). This work will assist in providing foundational data for the use of SPME Arrow in future microbiological applications.

Detection of high-risk carbapenem-resistant Klebsiella pneumoniae and Enterobacter cloacae isolates using volatile molecular profiles

Infections caused by carbapenem-resistant Enterobacteriaceae (CRE) are alarming in the clinical setting, as CRE isolates often exhibit resistance to most clinically-available antibiotics. Klebsiella pneumoniae carbapenemase (KPC) is the most common carbapenemase carried by CRE in North America and Europe, frequently detected in isolates of K. pneumoniae, Escherichia coli, and Enterobacter cloacae. Notably, KPC-expressing strains often arise from clonal lineages, with sequence type 258 (ST258) representing the dominant lineage in K. pneumoniae, ST131 in E. coli, and ST78 and ST171 in E. cloacae. Prior studies have demonstrated that carbapenem-resistant K. pneumoniae differs from carbapenem-susceptible K. pneumoniae at both the transcriptomic and soluble metabolomic levels. In the present study, we sought to determine whether carbapenem-resistant and carbapenem-susceptible isolates of K. pneumoniae, E. coli, and E. cloacae produce distinct volatile metabolic profiles. We were able to identify a volatile metabolic fingerprint that could discriminate between CRE and non-CRE with an area under the receiver operating characteristic curve (AUROC) as high as 0.912. Species-specific AUROCs were as high as 0.988 for K. pneumoniae and 1.000 for E. cloacae. Paradoxically, curing of KPC-expressing plasmids from a subset of K. pneumoniae isolates further accentuated the metabolic differences observed between ST258 and non-ST258.

Volatile compounds emission from teratogenic human pluripotent stem cells observed during their differentiation in vivo

Several investigations point out that the volatile fraction of metabolites, often called volatilome, might signal the difference processes occurring in living beings, both in vitro and in vivo. These studies have been recently applied to stem cells biology, and preliminary results show that the composition of the volatilome of stem cells in vitro changes along the differentiation processes leading from pluripotency to full differentiation. The identification of pluripotent stem cells is of great importance to improve safety in regenerative medicine avoiding the formation of teratomas. In this paper, we applied gas chromatography and gas sensor array to the study of the volatilome released by mice transplanted with human induced pluripotent stem cells (hiPSCs) or embryoid bodies (EBs) derived from hiPSCs at 5 days and spontaneously differentiated cells at 27 day. Gas chromatography analysis finds that, in mice transplanted with hiPSCs, the abundance of 13 volatile compounds increases four weeks after the implant and immediately before the formation of malignant teratomas (grade 3) become observable. The same behaviour is also followed by the signals of the gas sensors. Besides this event, the gas-chromatograms and the sensors signals do not show any appreciable variation related neither among the groups of transplanted mice nor respect to a placebo population. This is the first in vivo observation of the change of volatile metabolites released by human induced pluripotent stem cells and hiPSCs-derived cells during the differentiation process. These results shed further light on the differentiation mechanisms of stem cells and suggest possible applications for diagnostic purposes for an early detection of tumor relapse after surgery.

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

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

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.