Volatile metabolic diversity of Klebsiella pneumoniae in nutrient-replete conditions

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.

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.

Electronic nose versus VITEK 2 system for the rapid diagnosis of bloodstream infections

Infectious diseases that spread through the bloodstream, known as bloodstream infections (BSIs), are a major global health problem. Positive outcomes for patients with sepsis are typically the result of prompt treatment started after an early diagnosis of BSIs. In this study, we evaluated the capabilities of a portable electronic nose (E-Nose) to detect BSIs with two commonly isolated Gram-negative bacterial species, E. coli and K. pneumonia. One hundred and five blood samples were randomly collected for blood culture examinations using BACTEC and VITEK 2 system, and headspace analysis by an E-Nose from June to December 2021. Classification accuracy of E. coli, K. pneumonia, and negative controls was measured using principal component analysis, area under the receiver operating characteristic curve, sensitivity, and specificity analysis. After incubation for 24 h, cluster plots generated using principal component analysis demonstrated that E-Nose could accurately diagnose the presence of E. coli and K. pneumonia in BACTEC blood culture bottles with a sensitivity and specificity of 100% in just 120 s. The E-Nose method has been shown to be an immediate, precise, and cost-effective alternative to automated blood culture BACTEC and VITEK 2 systems for the fast detection of the causative bacterial pathogens of BSIs in clinical practice. Thus, patients with such Gram-negative bacteremia can have guided empirical antimicrobial therapy on the same day of BSIs diagnosis, which can be lifesaving.

β-Lactamase Sensitive Probe for Rapid Detection of Antibiotic-Resistant Bacteria with Gas Chromatography–Tandem Mass Spectrometry

β-Lactamase (Bla) produced by bacteria to resist β-lactam antibiotics is a serious public health threat. Developing efficient diagnostic protocols for drug-resistant bacteria is of great significance. In this work, based on gas molecules in bacteria, a novel research strategy was proposed to develop a gas molecule-based probe by grafting 2-methyl-3-mercaptofuran (MF) onto cephalosporin intermediates via a nucleophilic substitution reaction. The probe can release the corresponding MF by reacting with Bla. The released MF, as a marker of drug-resistant bacteria, was analyzed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The Bla concentration as low as 0.2 nM can be easily observed, providing an efficient method for detecting enzyme activity and screening drug-resistant strains in vivo. Importantly, the method is universal, and probes with different properties can be prepared by changing different substrates to further identify different types of bacteria, thereby broadening the research methods and ideas for monitoring physiological processes.

Untargeted Metabolomics Analysis of Gentamicin-Induced Tolerant Colonies of Klebsiella pneumoniae

PURPOSE

Antibiotic resistance development in pathogenic bacteria like Klebsiella pneumoniae seriously threatens humankind. Therefore, it is important to understand the interaction of bacteria with antibiotic agents and how it acquires resistance at the molecular level. The current study describes metabolomics analysis of K. pneumoniae sensitive strains and its gentamicin-tolerant (resistant) strains.

METHODS

K. pneumoniae strains were treated at five different concentrations of gentamicin, increasing from a low dose (16.2 µg/mL) to the highest dose (250 µg/mL) at three incubation time periods (24h, 48h, and 72h). Colonies obtained at various concentrations and time intervals were subjected to metabolomic analysis using GC-MS.

RESULTS

A drastic change was observed in the morphology of K. pneumoniae colonies with the increasing gentamicin concentration. Moreover, K. pneumoniae strains grown at the highest concentration (250 µg/mL) were found tolerant to 1 mg/mL gentamicin (4-folds) and considered resistant strains. A total of 459 metabolites were identified. A sequential down/up-regulation in 4, 3, and 4 metabolites were observed in association with the increasing gentamicin concentration at 24h, 48h, and 72h, respectively. While with the comparative analysis of resistant and sensitive strains, a total of seven down- and sixteen up-regulated metabolites were observed. The concentration of some fatty acids and sugars have been found to increase while, a few metabolites like inosine, tyrosine, 1-propionylproline, and 2-hydroxyacetic acid have been found down-regulated in resistant samples.

CONCLUSION

These regulator metabolites might be associated with resistance development in K. pneumoniae against gentamicin and might be helpful in the rapid detection of gentamicin-resistant clinical strains.

GC-MS profiling of volatile metabolites produced by Klebsiella pneumoniae

Currently used methods for diagnosing ventilator-associated pneumonia (VAP) are complex, time-consuming and require invasive procedures while empirical antibacterial therapy applies broad spectrum antibiotics that may promote antimicrobial resistance. Hence, novel and fast methods based on alternative markers are needed for VAP detection and differentiation of causative pathogens. Pathogenic bacteria produce a broad range of volatile organic compounds (VOCs), some of which may potentially serve as biomarkers for microorganism identification. Additionally, monitoring of dynamically changing VOCs concentration profiles may indicate emerging pneumonia and allow timely implementation of appropriate antimicrobial treatment. This study substantially extends the knowledge on bacterial metabolites providing the unambiguous identification of volatile metabolites produced by carbapenem-resistant and susceptible strains of Klebsiella pneumoniae (confirmed with pure standards in addition to mass spectra match) but also revealing their temporary concentration profiles (along the course of pathogen proliferation) and dependence on the addition of antibiotic (imipenem) to bacteria. Furthermore, the clinical strains of K. pneumoniae isolated from bronchoalveolar lavage specimens collected from mechanically ventilated patients were investigated to reveal, whether bacterial metabolites observed in model experiments with reference strains could be relevant for wild pathogens as well. In all experiments, the headspace samples from bacteria cultures were collected on multibed sorption tubes and analyzed by GC-MS. Sampling was done under strictly controlled conditions at seven time points (up to 24 h after bacteria inoculation) to follow the dynamic changes in VOC concentrations, revealing three profiles: release proportional to bacteria load, temporary maximum and uptake. Altogether 32 VOCs were released by susceptible and 25 VOCs by resistant strain, amongst which 2-pentanone, 2-heptanone, and 2-nonanone were significantly higher for carbapenem-resistant KPN. Considerably more metabolites (n = 64) were produced by clinical isolates and in higher diversity compared to reference KPN strains.

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.

Multi-Strain and -Species Investigation of Volatile Metabolites Emitted from Planktonic and Biofilm Candida Cultures

Candida parapsiliosis is a prevalent neonatal pathogen that attains its virulence through its strain-specific ability to form biofilms. The use of volatilomics, the profiling of volatile metabolites from microbes is a non-invasive, simple way to identify and classify microbes; it has shown great potential for pathogen identification. Although C. parapsiliosis is one of the most common clinical fungal pathogens, its volatilome has never been characterised. In this study, planktonic volatilomes of ten clinical strains of C. parapsilosis were analysed, along with a single strain of Candida albicans. Headspace-solid-phase microextraction coupled with gas chromatography-mass spectrometry were employed to analyse the samples. Species-, strain-, and media- influences on the fungal volatilomes were investigated. Twenty-four unique metabolites from the examined Candida spp. (22 from C. albicans; 18 from C. parapsilosis) were included in this study. Chemical classes detected across the samples included alcohols, fatty acid esters, acetates, thiols, sesquiterpenes, and nitrogen-containing compounds. C. albicans volatilomes were most clearly discriminated from C. parapsilosis based on the detection of unique sesquiterpene compounds. The effect of biofilm formation on the C. parapsilosis volatilomes was investigated for the first time by comparing volatilomes of a biofilm-positive strain and a biofilm-negative strain over time (0–48 h) using a novel sampling approach. Volatilomic shifts in the profiles of alcohols, ketones, acids, and acetates were observed specifically in the biofilm-forming samples and attributed to biofilm maturation. This study highlights species-specificity of Candida volatilomes, and also marks the clinical potential for volatilomics for non-invasively detecting fungal pathogens. Additionally, the range of biofilm-specificity across microbial volatilomes is potentially far-reaching, and therefore characterising these volatilomic changes in pathogenic fungal and bacterial biofilms could lead to novel opportunities for detecting severe infections early.

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.

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.

Multi-Omic Analysis of Symbiotic Bacteria Associated With Aedes aegypti Breeding Sites

Mosquito breeding sites are complex aquatic environments with wide microbial diversity and physicochemical parameters that can change over time during the development of immature insect stages. Changes in biotic and abiotic conditions in water can alter life-history traits of adult mosquitos but this area remains understudied. Here, using microbial genomic and metabolomics analyses, we explored the metabolites associated with Aedes aegypti breeding sites as well as the potential contribution of Klebsiella sp., symbiotic bacteria highly associated with mosquitoes. We sought to address whether breeding sites have a signature metabolic profile and understand the metabolite contribution of the bacteria in the aquatic niches where Ae. aegypti larvae develop. An analysis of 32 mosquito-associated bacterial genomes, including Klebsiella, allowed us to identify gene clusters involved in primary metabolic pathways. From them, we inferred metabolites that could impact larval development (e.g., spermidine), as well as influence the quality assessment of a breeding site by a gravid female (e.g., putrescine), if produced by bacteria in the water. We also detected significant variance in metabolite presence profiles between water samples representing a decoupled oviposition event (oviposition by single females and manually deposited eggs) versus a control where no mosquito interactions occurred (PERMANOVA: p < 0.05; R² = 24.64% and R² = 30.07%). Five Klebsiella metabolites were exclusively linked to water samples where oviposition and development occurred. These data suggest metabolomics can be applied to identify compounds potentially used by female Ae. aegypti to evaluate the quality of a breeding site. Elucidating the physiological mechanisms by which the females could integrate these sensory cues while ovipositing constitutes a growing field of interest, which could benefit from a more depurated list of candidate molecules.

Volatile Compounds From Bacillus, Serratia, and Pseudomonas Promote Growth and Alter the Transcriptional Landscape of Solanum tuberosum in a Passively Ventilated Growth System

The interaction of an array of volatile organic compounds (VOCs) termed bacterial volatile compounds (BVCs) with plants is now a major area of study under the umbrella of plant-microbe interactions. Many growth systems have been developed to determine the nature of these interactions in vitro. However, each of these systems have their benefits and drawbacks with respect to one another and can greatly influence the end-point interpretation of the BVC effect on plant physiology. To address the need for novel growth systems in BVC-plant interactions, our study investigated the use of a passively ventilated growth system, made possible via Microbox^® growth chambers, to determine the effect of BVCs emitted by six bacterial isolates from the genera Bacillus, Serratia, and Pseudomonas. Solid-phase microextraction GC/MS was utilized to determine the BVC profile of each bacterial isolate when cultured in three different growth media each with varying carbon content. 66 BVCs were identified in total, with alcohols and alkanes being the most abundant. When cultured in tryptic soy broth, all six isolates were capable of producing 2,5-dimethylpyrazine, however BVC emission associated with this media were deemed to have negative effects on plant growth. The two remaining media types, namely Methyl Red-Voges Proskeur (MR-VP) and Murashige and Skoog (M + S), were selected for bacterial growth in co-cultivation experiments with Solanum tuberosum L. cv. ‘Golden Wonder.’ The BVC emissions of Bacillus and Serratia isolates cultured on MR-VP induced alterations in the transcriptional landscape of potato across all treatments with 956 significantly differentially expressed genes. This study has yielded interesting results which indicate that BVCs may not always broadly upregulate expression of defense genes and this may be due to choice of plant-bacteria co-cultivation apparatus, bacterial growth media and/or strain, or likely, a complex interaction between these factors. The multifactorial complexities of observed effects of BVCs on target organisms, while intensely studied in recent years, need to be further elucidated before the translation of lab to open-field applications can be fully realized.

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.

Metabolic Profiling of Volatile Organic Compounds (VOCs) Emitted by the Pathogens Francisella tularensis and Bacillus anthracis in Liquid Culture

We conducted comprehensive (untargeted) metabolic profiling of volatile organic compounds (VOCs) emitted in culture by bacterial taxa Francisella tularensis (F. tularensis) subspecies novicida and Bacillus anthracis (B. anthracis) Sterne, surrogates for potential bacterial bioterrorism agents, as well as selective measurements of VOCs from their fully virulent counterparts, F. tularensis subspecies tularensis strain SCHU S4 and B. anthracis Ames. F. tularensis and B. anthracis were grown in liquid broth for time periods that covered logarithmic growth, stationary, and decline phases. VOCs emitted over the course of the growth phases were collected from the headspace above the cultures using solid phase microextraction (SPME) and were analyzed using gas chromatography-mass spectrometry (GC-MS). We developed criteria for distinguishing VOCs originating from bacteria versus background VOCs (originating from growth media only controls or sampling devices). Analyses of collected VOCs revealed methyl ketones, alcohols, esters, carboxylic acids, and nitrogen- and sulfur-containing compounds that were present in the bacterial cultures and absent (or present at only low abundance) in control samples indicating that these compounds originated from the bacteria. Distinct VOC profiles where observed for F. tularensis when compared with B. anthracis while the observed profiles of each of the two F. tularensis and B. anthracis strains exhibited some similarities. Furthermore, the relative abundance of VOCs was influenced by bacterial growth phase. These data illustrate the potential for VOC profiles to distinguish pathogens at the genus and species-level and to discriminate bacterial growth phases. The determination of VOC profiles lays the groundwork for non-invasive probes of bacterial metabolism and offers prospects for detection of microbe-specific VOC biomarkers from two potential biowarfare agents.

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.

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.

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.

SPME-GC×GC-TOF MS fingerprint of virally-infected cell culture: Sample preparation optimization and data processing evaluation

Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated.

Comprehensive volatile metabolic fingerprinting of bacterial and fungal pathogen groups

The identification of pathogen-specific volatile metabolic 'fingerprints' could lead to the rapid identification of disease-causing organisms either directly from ex vivo patient bio-specimens or from in vitro cultures. In the present study, we have evaluated the volatile metabolites produced by 100 clinical isolates belonging to ten distinct pathogen groups that, in aggregate, account for 90% of bloodstream infections, 90% of urinary tract infections, and 80% of infections encountered in the intensive care unit setting. Headspace volatile metabolites produced in vitro were concentrated using headspace solid-phase microextraction and analyzed via two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). A total of 811 volatile metabolites were detected across all samples, of which 203 were: (1) detected in 9 or 10 (of 10) isolates belonging to one or more pathogen groups, and (2) significantly more abundant in cultures relative to sterile media. Network analysis revealed a distinct metabolic fingerprint associated with each pathogen group, and analysis via Random Forest using leave-one-out cross-validation resulted in a 95% accuracy for the differentiation between groups. The present findings support the results of prior studies that have reported on the differential production of volatile metabolites across pathogenic bacteria and fungi, and provide additional insight through the inclusion of pathogen groups that have seldom been studied previously, including Acinetobacter spp., coagulase-negative Staphylococcus, and Proteus mirabilis, as well as the utilization of HS-SPME-GC×GC-TOFMS for improved sensitivity and resolution relative to traditional gas chromatography-based techniques.