Fast detection of volatile organic compounds from bacterial cultures by secondary electrospray ionization-mass spectrometry

Detection of several volatile organic compounds through Ar+ induced chemical ionisation using inductively coupled plasma-tandem mass spectrometry (ICP-MS/MS)

A new analytical technique for detection of organic compounds using inductively coupled plasma-tandem mass spectrometry (ICP-MS/MS) is described. Volatile organic compounds (VOCs) were introduced into the collision/reaction cell (CRC), instead of through the ICP ion source, and the molecules were ionised through an ion reaction, induced by collision with the primary ions (Ar+) produced in the ICP. The ionisation characteristics of this new approach were investigated by mass spectrometric analysis of eight VOCs (i.e., benzene, toluene, ethyl acetate, methyl butyrate, ethyl butyrate, pentyl acetate, pyridine, and 2-methylfuran). These molecules were detected as molecular ions (M+), protonated ions ([M + H]+), or deprotonated ions ([M - H]+), demonstrating that soft ionisation was achieved by the present ionisation protocol using ICP-MS/MS. In addition, a volatile selenium-containing organic compound, dimethyl diselenide (Se2(CH3)2), was also analysed to investigate the feasibility of this ionisation protocol to achieve soft and hard ionisation simultaneously. Several Se-related ions such as Se+, SeH+, Se2+, [SeCH3]+, and [Se2CH3]+, together with [Se2(CH3)2]+, were observed, suggesting that while soft ionisation was possible, ion reaction-induced-fragmentation and hard ionisation also occurred. To demonstrate the analytical capability of the present technique, volatile components released from coffee beans were subjected to the present mass spectrometric analysis. Many ion peaks originating from VOCs were detected from the coffee beans. The data obtained here demonstrated that ICP-MS equipped with a CRC can become an effective tool for analyzing both elements and molecules.

Metrisor: A novel diagnostic method for metritis detection in cattle based on machine learning and sensors

The Metrisor device has been developed using gas sensors for rapid, highly accurate and effective diagnosis of metritis. 513 cattle uteri were collected from abattoirs and swabs were taken for microbiological testing. The Metrisor device was used to measure intrauterine gases. The results showed a bacterial growth rate of 75.75 % in uteri with clinical metritis. In uteri positive for clinical metritis, the most commonly isolated and identified bacteria were Trueperella pyogenes, Fusobacterium necrophorum and Escherichia coli. Measurements taken with Metrisor to determine the presence of metritis in the uterus yielded the most successful results in evaluations of relevant machine learning algorithms. The ICO (Iterative Classifier Optimizer) algorithm achieved 71.22 % accuracy, 64.40 % precision and 71.20 % recall. Experiments were conducted to examine bacterial growth in the uterus and the random forest algorithm produced the most successful results with accuracy, precision and recall values of 78.16 %, 75.30 % and 78.20 % respectively. ICO also showed high performance in experiments to determine bacterial growth in metritis-positive uteri, with accuracy, precision and recall values of 78.97 %, 77.20 % and 79.00 %, respectively. In conclusion, the Metrisor device demonstrated high accuracy in detecting metritis and bacterial growth in uteri and could identify bacteria such as E. coli, S. aureus, coagulase-negative staphylococci, T. pyogenes, Bacillus spp., Clostridium spp. and F. necrophorum with rates up to 80 %. It provides a reliable, rapid and effective means of detecting metritis in animals in the field without the need for laboratory facilities.

Comparison of Cu+, Ag+, and Au+ Ions as Ionization Agents of Volatile Organic Compounds at Subatmospheric Pressure

Ionization of volatile organic compounds (VOCs) by coinage metal ions (Cu+, Ag+, and Au+) generated by laser desorption and ionization (LDI) of a metal nanolayer in subatmospheric conditions is explored. The study was performed in a commercial subatmospheric dual MALDI/ESI ion source. Five compounds representing different VOC classes were chosen for a detailed study of the metal ionization mechanism: ethanol, acetone, acetic acid, xylene, and cyclohexane. In the gas phase, ion molecular complexes of all three metal ions were formed, typically with two ligand molecules. The successful detection of the metal complexes with VOCs strongly depended on the applied voltages across the ion source, minimizing the in-source fragmentation. The employed orbital trap with ultrahigh resolving power and sub-parts-per-million mass accuracy allowed unambiguous identification of the formed complexes based on their molecular formulas. The detection limits of the studied compounds in the gas were in the range 0.1-1.4 nmol/L. Compared to Cu+ and Ag+ ions, Au+ ions exhibited the highest reactivity, often complicating spectra by side products of reactions. On the other hand, they also allowed detecting saturated hydrocarbons, which did not produce any signals with Ag+ and Cu+.

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.

Elucidating the Role of Ion Suppression in Secondary Electrospray Ionization

Ion suppression is a known matrix effect in electrospray ionization (ESI), ambient pressure chemical ionization (APCI), and desorption electrospray ionization (DESI), but its characterization in secondary electrospray ionization (SESI) is lacking. A thorough understanding of this effect is crucial for quantitative applications of SESI, such as breath analysis. In this study, gas standards were generated by using an evaporation-based system to assess the susceptibility and suppression potential of acetone, deuterated acetone, deuterated acetic acid, and pyridine. Gas-phase effects were found to dominate ion suppression, with pyridine exhibiting the most significant suppressive effect, which is potentially linked to its gas-phase basicity. The impact of increased acetone levels on the volatiles from exhaled breath condensate was also examined. In humid conditions, a noticeable decrease in intensity of approximately 30% was observed for several features at an acetone concentration of 1 ppm. Considering that this concentration is expected for breath analysis, it becomes crucial to account for this effect when SESI is utilized to quantitatively determine specific compounds.

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

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

Combination of the electronic nose with microbiology as a tool for rapid detection of Salmonella

Salmonella is one of the most important foodborne pathogens and its analysis in raw and processed products is mandatory in the food industry. Although microbiological analysis is the standard practice for Salmonella determination, these assays are commonly laborious and time-consuming, thus, alternative techniques based on easy operation, few manipulation steps, low cost, and reduced time are desirable. In this paper, we demonstrate the use of an e-nose based on ionogel composites (ionic liquid + gelatine + Fe3O4 particles) as a complementary tool for the conventional microbiological detection of Salmonella. We used the proposed methodology for differentiating Salmonella from Escherichia coli, Pseudomonas fluorescens, Pseudomonas aeruginosa, and Staphylococcus aureus in nonselective medium: pre-enrichment in brain heart infusion (BHI) (incubation at 35 °C, 24 h) and enrichment in tryptone soy agar (TSA) (incubation at 35 °C, 24 h), whereas Salmonella differentiation from E. coli and P. fluorescens was also evaluated in selective media, bismuth sulfite agar (BSA), xylose lysine deoxycholate agar (XLD), and brilliant green agar (BGA) (incubation at 35 °C, 24 h). The obtained data were compared by principal component analysis (PCA) and different machine learning algorithms: multilayer perceptron (MLP), linear discriminant analysis (LDA), instance-based (IBk), and Logistic Model Trees (LMT). For the nonselective media, under optimized conditions, taking merged data of BHI + TSA (total incubation time of 48 h), an accuracy of 85% was obtained with MLP, LDA, and LMT, while five separated clusters were presented in PCA, each cluster corresponding to a bacterium. In addition, for evaluation of the e-nose for discrimination of Salmonella using selective media, considering the combination of BSA + XLD and total incubation of 72 h, the PCA showed three separated and well-defined clusters corresponding to Salmonella, E. coli, and P. fluorescens, and an accuracy of 100% was obtained for all classifiers.

A Mass Spectrometry-Machine Learning Approach for Detecting Volatile Organic Compound Emissions for Early Fire Detection

Mass spectrometry in parallel with real-time machine learning techniques were paired in a novel application to detect and identify chemically specific, early indicators of fires and near-fire events involving a set of selected materials: Mylar, Teflon, and poly(methyl methacrylate) (PMMA). The volatile organic compounds emitted during the thermal decomposition of each of the three materials were characterized using a quadrupole mass spectrometer which scanned the 1-200 m/z range. CO2, CH3CHO, and C6H6 were the main volatiles detected during Mylar thermal decomposition, while Teflon's thermal decomposition yielded CO2 and a set of fluorocarbon compounds including CF4, C2F4, C2F6, C3F6, CF2O, and CF3O. PMMA produced CO2 and methyl methacrylate (MMA, C5H8O2). The mass spectral peak patterns observed during the thermal decomposition of each material were unique to that material and were therefore useful as chemical signatures. It was also observed that the chemical signatures remained consistent and detectable when multiple materials were heated together. Mass spectra data sets containing the chemical signatures for each material and mixtures were collected and analyzed using a random forest panel machine learning classification. The classification was tested and demonstrated 100% accuracy for single material spectra and an average of 92.3% accuracy for mixed material spectra. This investigation presents a novel technique for the real-time, chemically specific detection of fire related VOCs through mass spectrometry which shows promise as a more rapid and accurate method for detecting fires or near-fire events.

The development and application of matrix assisted laser desorption electrospray ionization: The teenage years

In the past 15 years, ambient ionization techniques have witnessed a significant incursion into the field of mass spectrometry imaging, demonstrating their ability to provide complementary information to matrix-assisted laser desorption ionization. Matrix-assisted laser desorption electrospray ionization is one such technique that has evolved since its first demonstrations with ultraviolet lasers coupled to Fourier transform-ion cyclotron resonance mass spectrometers to extensive use with infrared lasers coupled to orbitrap-based mass spectrometers. Concurrently, there have been transformative developments of this imaging platform due to the high level of control the principal group has retained over the laser technology, data acquisition software (RastirX), instrument communication, and image processing software (MSiReader). This review will discuss the developments of MALDESI since its first laboratory demonstration in 2005 to the most recent advances in 2021.

Rapid detection of Escherichia coli in dairy milk using static headspace-comprehensive two-dimensional gas chromatography

A new approach is introduced for rapid and reliable bacteria detection in food. Namely, static headspace-comprehensive two-dimensional gas chromatography (HS-GC × GC) with backflushing. The introduced approach provides fast detection of Escherichia coli (E. coli) in enriched ultra-high-temperature processed (UHT) dairy milk. The presence of E. coli may be indicated by detecting microbial volatile organic compounds emanating from test solutions inoculated with E. coli. In the present investigation, HS-GC × GC analysis is preceded by conventional enrichment in nutrient broth and inoculated samples are clearly discernable from controls following as little as 15 h sample enrichment. Headspace equilibration for 28 min followed by an 8 min GC × GC analysis of enriched test solutions reduces time-to-response by approximately one full day compared to conventional culture-based methods. The presence of ethanol, 1-propanol, and acetaldehyde may be used as a putative marker of E. coli contamination in milk and the introduced approach is able to detect single-cell initial bacterial load. Faster, reliable detection of pathogens and/or spoilage microbes in food products is desirable for the food industry. The described approach has great potential to complement the conventional workflow and be utilised for rapid microbial screening of foodstuff.

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

Early detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization–high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient’s tailored treatment.

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Real-time mass spectrometry shows potential as a tool for microbiological diagnosis

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Bacterial volatile metabolites from 1 × 10³ CFUs are detected within minutes

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S. aureus and S. pneumoniae can be distinguished on species and even strain level

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Complex clinical samples cluster according to presence or absence of viable bacteria

Taking leads out of nature, can nano deliver us from COVID-like pandemics?

The COVID-19 crisis has alerted the research community to re-purpose scientific tools that can effectively manage emergency pandemic situations. Researchers were never so desperate to discover a 'magic bullet' that has significant clinical benefits with minimal or no side effects. At the beginning of the pandemic, due to restricted access to traditional laboratory techniques, many research groups delved into computational screening of thousands of lead molecules that could inhibit SARS-CoV-2 at one or more stages of its infectious cycle. Several in silico studies on natural derivatives point out their potency against SARS-CoV-2 proteins. However, theoretical predictions and existing knowledge on related molecules reflect their poor oral bioavailability due to biotransformation in the gut and liver. Nanotechnology has evolved into a key field for precise and controlled delivery of various drugs that lack aqueous solubility, have low oral bioavailability and possess pronounced toxicity in their native form. In this review, we discuss various nanoformulations of natural products with favorable ADME properties, and also briefly explore nano-drug delivery to lungs, the primary site of SARS-CoV-2 infection. Natural products are also envisioned to augment nanotechnology-based 1) personnel protective equipment for ex vivo viral inactivation and 2) wearable sensors that perform rapid and non-invasive analysis of volatile organic compounds in exhaled breath of the infected person after therapeutic food consumption.

Volatolomics in healthcare and its advanced detection technology

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

Volatile atmospheric pressure chemical ionisation mass spectrometry headspace analysis of E. coli and S. aureus

Identifying the characteristics of bacterial species can improve treatment outcomes and mass spectrometry methods have been shown to be capable of identifying biomarkers of bacterial species. This study is the first to use volatile atmospheric pressure chemical ionisation mass spectrometry to directly and non-invasively analyse the headspace of E. coli and S. aureus bacterial cultures, enabling major biological classification at species level (Gram negative/positive respectively). Four different protocols were used to collect data, three utilising discrete 5 min samples taken between 2 and 96 h after inoculation and one method employing 24 h continuous sampling. Characteristic marker ions were found for both E. coli and S. aureus. A model to distinguish between sample types was able to correctly identify the bacteria samples after sufficient growth (24-48 h), with similar results obtained across different sampling methods. This demonstrates that this is a robust method to analyse and classify bacterial cultures accurately and within a relevant time frame, offering a promising technique for both clinical and research applications.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Detection of Bacterial Metabolic Volatile Indole Using a Graphene-Based Field-Effect Transistor Biosensor

The existence of bacteria is a great threat to food safety. Volatile compounds secreted by bacteria during their metabolic process can be dissected to evaluate bacterial contamination. Indole, as a major volatile molecule released by Escherichia coli (E. coli), was chosen to examine the presence of E. coli in this research. In this work, a graphene field-effect transistor (G-FET) was employed to detect the volatile molecule-indole based on a π-π stacking interaction between the indole and the graphene. The exposure of G-FET devices to the indole provokes a change in electrical signal, which is ascribed to the adsorption of the indole molecule onto the graphene surface via π-π stacking. The adsorption of the indole causes a charge rearrangement of the graphene-indole complex, which leads to changes in the electrical signal of G-FET biosensors with a different indole concentration. Currently, the indole biosensor can detect indole from 10 ppb to 250 ppb and reach a limit of detection of 10 ppb for indole solution detection. We believe that our detection strategy for detecting bacterial metabolic gas molecules will pave a way to developing an effective platform for bacteria detection in food safety monitoring.

A hybrid electronic nose system for discrimination of pathogenic bacterial volatile compounds

A hybrid electronic nose comprising an array of three organic-inorganic nanocomposite gas sensors [zinc tetra tert-butyl phthalocyanine (ZnTTBPc), zinc tetra-phenyl porphyrin (ZnTPP), and cobalt tetraphenyl-porphyrin (CoTPP)] coupled with three commercial metal-oxide semiconductor gas sensors (TGS 2444, TGS 2603 and TGS 2620) was developed to discriminate bacterial volatile compounds. Each type of gas sensor had its own strengths and weaknesses in terms of its capability to detect complex odors from the five different bacterial species tested. Bacterial samples were controlled at a fixed initial bacterial concentration by measuring the optical density at 600 nm of the culture suspensions. A comparative evaluation of the volatile compound fingerprints from five bacterial species grown in Luria-Bertani medium was conducted to identify the optimal incubation time for detection of volatile biomarkers to discriminate among bacteria. The results suggest that the hybrid electronic nose was indeed able to discriminate among the bacterial species and culture media, with a variance based on contributions of 92.4% from PC1 and 7.2% from PC2, at an incubation time of 6 hours. Furthermore, the results of hierarchical cluster analysis showed that bacterial odor data formed two major bacterial groups, with the maximum cluster distance close to 25. Intra-group similarity was demonstrated as the two bacterial species (E. cloacae and P. aeruginosa) from among the Gram-negative bacteria had a greater similarity with a cluster distance close to 4. Finally, the minimum distance between E. cloacae and S. Typhi was approximately 1, at an equal distance from E. coli and S. aureus.

Identification of Genetic Variants via Bacterial Respiration Gas Analysis

Indole is a signal molecule derived from the conversion of tryptophan, and it is present in bacterial respiratory gas. Besides influencing bacterial growth, indole exhibits effects on human health, including a positive effect on inflammation and protection against pathogens. However, a high fecal indole concentration (FIC) can suggest an unbalanced gut flora or the presence of certain pathogens. To analyze the indole produced by bacteria, its collection and detection is required. Traditional methods usually require centrifugation of liquid bacterial culture medium and subsequent extraction of indole from the medium or partial purification of indole from fecal samples (e.g., by distillation or extraction). In this study, we demonstrate the possibility of identifying gas contents directly from bacteria, and we distinguish the difference in species and their genetics without the need to centrifuge or extract. Using an absorbent sheet placed above a liquid culture, we were able to collect gas content directly from bacteria. Gas chromatography-mass spectrometry (GC-MS) was used for the analysis. The GC-MS results showed a clear peak attributed to indole for wild-type Escherichia coli cells (MG1655 and MC4100 strains), whereas the indole peak was absent in the chromatograms of cells where proteins, part of the indole production pathway from tryptophan (TnaA and TnaB), were not expressed (by using tnaAB-deleted cells). The indole observed was measured to be present in a low nmol-range. This method can distinguish whether the bacterial genome contains the tnaAB gene or not and can be used to collect gas compounds from bacterial cultures quickly and easily. This method is useful for other goals and future research, such as for measurements in restrooms, for food-handling facilities, and for various applications in medical settings.

Circadian Metabolomics from Breath

Metabolites like melatonin are essential in determining circadian phase. In the recent years, comprehensive metabolome analyses have unveiled entire panels of small biomolecules fluctuating in a circadian fashion, thus enabling a more precise determination of inner time and understanding of how circadian clock operates at the molecular level. Emerging analytical techniques allowing for the determination of exhaled metabolites in breath show promise to gain further insights noninvasively and in vivo into circadian metabolism.

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

Towards the Identification of Antibiotic-Resistant Bacteria Causing Urinary Tract Infections Using Volatile Organic Compounds Analysis-A Pilot Study

Antibiotic resistance is an unprecedented threat to modern medicine. The analysis of volatile organic compounds (VOCs) from bacteria potentially offers a rapid way to determine antibiotic susceptibility in bacteria. This study aimed to find the optimal conditions to obtain the maximum number of VOCs detected which next allowed the assessment of differences in VOC profiles between susceptible and resistant isolates of Escherichia coli causing urinary tract infections. The analysis of VOCs in the headspace above the bacterial cultures allowed the distinguishing of resistant and susceptible bacteria based on the abundance of six VOCs with 85.7% overall accuracy. The results of this preliminary study are promising, and with development could lead to a practical, faster diagnostic method for use in routine microbiology.

Performances and Biosensing Mechanisms of Interdigitated Capacitive Sensors Based on the Hetero-mixture of SnO2 and In2O3

This study aims to discuss the synthesis and fabrication of SnO₂-In₂O₃-based thick-films and their biosensing applications. The structural characterization of SnO₂-In₂O₃ nanocomposites was performed using X-ray diffraction, Raman spectroscopy and transmission electron microscopy. Furthermore, the screen-printing technology was used in the fabrication of conductive electrodes to form an interdigitated capacitive structure, and the sensor layer based on the mixture of SnO₂ and In₂O₃. Moreover, the sensing performance of the developed structure was tested using Pseudomonas aeruginosa (P. aeruginosa) and Staphylococcus aureus (S. aureus) bacteria. In addition, the validation of sensing characteristics was performed by electrochemical impedance spectroscopic and self-resonant frequency analysis. Finally, the sensing properties were analyzed for two consecutive days, and changes in both P. aeruginosa and S. aureus pathogens growing media were also studied.

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.

Ultrasensitive Label-Free Detection of Unamplified Multidrug-Resistance Bacteria Genes with a Bimodal Waveguide Interferometric Biosensor

Infections by multidrug-resistant bacteria are becoming a major healthcare emergence with millions of reported cases every year and an increasing incidence of deaths. An advanced diagnostic platform able to directly detect and identify antimicrobial resistance in a faster way than conventional techniques could help in the adoption of early and accurate therapeutic interventions, limiting the actual negative impact on patient outcomes. With this objective, we have developed a new biosensor methodology using an ultrasensitive nanophotonic bimodal waveguide interferometer (BiMW), which allows a rapid and direct detection, without amplification, of two prevalent and clinically relevant Gram-negative antimicrobial resistance encoding sequences: the extended-spectrum betalactamase-encoding gene blaCTX-M-15 and the carbapenemase-encoding gene blaNDM-5 We demonstrate the extreme sensitivity and specificity of our biosensor methodology for the detection of both gene sequences. Our results show that the BiMW biosensor can be employed as an ultrasensitive (attomolar level) and specific diagnostic tool for rapidly (less than 30 min) identifying drug resistance. The BiMW nanobiosensor holds great promise as a powerful tool for the control and management of healthcare-associated infections by multidrug-resistant bacteria.

Sniffing Out Urinary Tract Infection-Diagnosis Based on Volatile Organic Compounds and Smell Profile

Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1-2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24-72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography-mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent's resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

Detection of the effects of triclosan (TCS) on the metabolism of VOCs in HepG2 cells by SPI-TOFMS

Volatile organic compounds (VOCs) emitted by organisms and cell metabolism have demonstrated great physiological and pathological values. At present, there is a great interest in the study of volatile metabolome to determine whether VOCs can serve as potential diagnostic biomarkers. In view of the sensitivity of VOCs to physiological changes, the aim of this study was to investigate alterations in VOC profiles in the in vitro headspace of HepG2 cells after exposure to triclosan (TCS). Since the in vivo biological effects of TCS are clearly defined, several TCS-related VOCs may potentially be traced back to common cellular processes. In this study, HepG2 cells were cultured in TCS-containing medium for 2 h, and the emitted VOCs in the headspace of the culture flask were detected using a single photon ionization time-of-flight mass spectrometry instrument. The control group and the TCS-treated group could be well separated by differential VOC profiles, which were related to the physiological states of the HepG2 cells. Compared to the control group, eleven and ten specific VOCs were identified in the 20 μm and 50 μm TCS-treated groups, respectively. Among them, five specific VOCs (m/z 62, 64, 70, 121 and 146) were commonly observed in these two TCS-treated groups. These results indicate that TCS can cause changes in cellular metabolic VOCs, and different concentrations of TCS lead to different VOCs profiles. Based on the findings of the study, the detection of VOCs in cell metabolism can be used as an auxiliary tool to explore the mechanism of drug action, and also as an exploratory method to determine whether drugs play a role in disease treatment.

VOC fingerprints: metabolomic signatures of biothreat agents with and without antibiotic resistance

Category A and B biothreat agents are deemed to be of great concern by the US Centers for Disease Control and Prevention (CDC) and include the bacteria Francisella tularensis, Yersinia pestis, Burkholderia mallei, and Brucella species. Underscored by the impact of the 2020 SARS-CoV-2 outbreak, 2016 Zika pandemic, 2014 Ebola outbreak, 2001 anthrax letter attacks, and 1984 Rajneeshee Salmonella attacks, the threat of future epidemics/pandemics and/or terrorist/criminal use of pathogenic organisms warrants continued exploration and development of both classic and alternative methods of detecting biothreat agents. Volatile organic compounds (VOCs) comprise a large and highly diverse group of carbon-based molecules, generally related by their volatility at ambient temperature. Recently, the diagnostic potential of VOCs has been realized, as correlations between the microbial VOC metabolome and specific bacterial pathogens have been identified. Herein, we describe the use of microbial VOC profiles as fingerprints for the identification of biothreat-relevant microbes, and for differentiating between a kanamycin susceptible and resistant strain. Additionally, we demonstrate microbial VOC profiling using a rapid-throughput VOC metabolomics method we refer to as ‘simultaneous multifiber headspace solid-phase microextraction’ (simulti-hSPME). Finally, through VOC analysis, we illustrate a rapid non-invasive approach to the diagnosis of BALB/c mice infected with either F. tularensis SCHU S4 or Y. pestis CO92.

Detection of Volatile Organic Compounds with Secondary Electrospray Ionization and Proton Transfer Reaction High-Resolution Mass Spectrometry: A Feature Comparison

The analysis of volatiles is of high relevance for a wide range of applications from environmental air sampling and security screening to potential medical applications. High-resolution mass spectrometry methods offer a particularly wide compound coverage, sensitivity, and selectivity. Online approaches allow direct analysis in real time without the need for sample preparation. For the first time, we systematically compared the analysis of volatile organic compounds with secondary electrospray ionization (SESI) and proton transfer reaction (PTR) high-resolution mass spectrometry. The selected instruments had comparable mass resolving powers with m/Δm ≥ 15000, which is particularly suitable for nontargeted analysis, for example, of exhaled breath. Exhalations from 14 healthy adults were analyzed simultaneously on both instruments. In addition, 97 reference standards from nine chemical classes were analyzed with a liquid evaporation system. Surprisingly, in breath, we found more complementary than overlapping features. A clear mass dependence was observed for each method with the highest number of detected m/z features for SESI in the high mass region (m/z = 150-250) and for PTR in the low mass region (m/z = 50-150). SESI yielded a significantly higher numbers of peaks (828) compared to PTR (491) among a total of 1304 unique breath m/z features. The number of signals observed by both methods was lower than expected (133 features) with 797 unique SESI features and 374 unique PTR features. Hypotheses to explain the observed mass-dependent differences are proposed.

Malodorous gases production from food wastes decomposition by indigenous microorganisms

Volatile organic compounds (VOCs) produced during the degradation of food wastes may harm to the health of people and create annoyance in adjacent communities. In this work, the VOCs emitted from the decomposition food wastes including fruit, meat and vegetable, and their microbial communities were measured in three individual 57-L reactors for 61 days. Total of 232.8, 373.5, and 191.1 μg·kg^-1·h^-1 VOCs with oxygenated VOCs (57.6%), volatile organic sulfur compounds (VOSCs, 58.6%) and VOSCs (54.9%) as the main group were detected during fruit, meat and vegetable fermentation, respectively. 2-Butanone (55.1%) and ethyl acetate (13.8%) were the two most abundant VOCs from fruit wastes, while dimethyl sulfide (68.0 and 26.6%) and dimethyl disulfide (89.2 and 10.1%) were in vegetable and meat wastes. The predominant Firmicutes represented 93.0-99.9% of the bacterial communities of meat decomposition, while Firmicutes and Proteobacteria were the dominant phyla throughout the fruit digestion process. Proteobacteria (16.9%-83.6%) was the dominant phylum in vegetable wastes, followed by Bacteroidetes, Firmicutes, and Actinobacteria. Malodorous VOCs emissions were highly affected by microbial activity, the abundant Weissella, Leuconostoc and Enterobacteriaceae in vegetable wastes showed correlation with carbon disulfide and dimethyl sulfide, while dominant Peptococcus, Bacteroides, Lactobacillales and Peptoniphilus in meat wastes was related to dimethyl disulfide. Overall, significant differences and correlation between VOCs emission profiles and bacterial communities among different food wastes decomposition were observed. These data contribute to a more comprehensive understanding the relationship between microbial community dynamics and malodorous VOCs emission.

A Filter Supported Surface-Enhanced Raman Scattering "Nose" for Point-of-Care Monitoring of Gaseous Metabolites of Bacteria

This work designs a convenient method for fabrication of surface-enhanced Raman scattering (SERS) devices by loading gold nanostars (AuNSs) on a flat filter support with vacuum filtration. The dense accumulation of AuNSs results in a strong sensitization to SERS signal and shows sensitive response to gaseous metabolites of bacteria, which produces a SERS "nose" for rapid point-of-care monitoring of these metabolites. The "nose" shows good reproducibility and stability and can be used for SERS quantitation of a gaseous target with Raman signal. The impressive performance of the proposed SERS "nose" for detecting gaseous metabolites of common foodborne bacteria like Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa from inoculated samples demonstrates its much higher sensitivity than that of human sense and application in distinguishing spoiled food at an early stage and real-time tracing of food spoilage degree. The strong point-of-care testing ability of the designed SERS "nose" and the miniaturization of whole equipment extend greatly the analytical application of SERS technology in food safety and public health.

Exploiting the native inspiratory ability of a mass spectrometer to improve analysis efficiency

In this study, a new approach to perform self-aspirating sampling in mass spectrometry (MS) analysis was developed by using the native inspiratory ability of a mass spectrometer. Specifically, the inspiratory channel and sampling inlet of the MS instrument were integrated into a single pathway through a sealed ionization chamber to facilitate analyte delivery and improve sample utilization. Based on this approach, combined with structural simplification and optimization, a versatile electrospray ionization (ESI) source has been constructed and characterized using different mass spectrometers. In addition to the self-aspirating ability, this source configuration can provide sub-ambient pressure (SAP) conditions for ionization, which were conducive to suppressing the background ions generated from some air-involved reactions. Moreover, it can also be used directly for electrospray-driven extraction ionization. With the SAP-ESI source, a conventional mass spectrometer enables rapid analysis of both volatiles and solutions via secondary electrospray ionization and coaxial electrospray ionization, respectively. As the compact gas pathway of the source will promote the efficient transfer and ionization of the sampled substances, the total consumption of the analyte for each analysis can be reduced to subnanogram level and a subppbv limit detection is achieved. Other demonstrated features such as the versatility, easy operation as well as simple assembly will likely contribute to the prevalence of the proposed sampling and ionization strategy.

Comparison of Stir Bar Sorptive Extraction and Solid Phase Microextraction of Volatile and Semi-Volatile Metabolite Profile of Staphylococcus Aureus

For the analysis of volatile bacterial compounds, solid phase microextraction (SPME) is currently the most widely used metabolite concentration technique. Recently, the potential of stir bar sorptive extraction (SBSE) for this use has been demonstrated. These two approaches were therefore used in combination with gas-chromatography coupled with mass-spectrometry (GC–MS) for the analysis of volatile and semi-volatile bacterial compounds produced by Staphylococcus aureus. In both cases, SPME and SBSE/headspace sorptive extraction (HSSE) enrichment was carried out in two coating phases. A whole analytical and statistical process was developed to differentiate the metabolites produced from the metabolites consumed. The results obtained with SBSE/HSSE and SPME were compared and showed the recovery of 90% of the compounds by SBSE/HSSE. In addition, we were able to detect the production of 12 volatile/semi-volatile compounds by S. aureus, six of which had never been reported before. The extraction by SBSE/HSSE showed higher concentration capacities and greater sensitivity than SPME concerning bacterial compounds, suggesting that this technique may therefore become the new preferred option for bacterial volatile and semi-volatile compound analysis.

Sniffing animals as a diagnostic tool in infectious diseases

BACKGROUND

Scents and odours characterize some microbes when grown in the laboratory, and experienced clinicians can diagnose patients with some infectious diseases based on their smell. Animal sniffing is an innate behaviour, and animals' olfactory acuity is used for detecting people, weapons, bombs, narcotics and food.

OBJECTIVES

We briefly summarized current knowledge regarding the use of sniffing animals to diagnose some infectious diseases and the potential use of scent-based diagnostic instruments in microbiology.

SOURCES

Information was sought through PubMed and extracted from peer-reviewed literature published between January 2000 and September 2019 and from reliable online news. The search terms 'odour', 'scent', 'bacteria', 'diagnostics', 'tuberculosis', 'malaria' and 'volatile compounds' were used.

CONTENT

Four major areas of using sniffing animals are summarized. Dogs have been used to reliably detect stool associated with toxigenic Clostridioides difficile and for surveillance. Dogs showed high sensitivity and moderate specificity for detecting urinary tract infections in comparison to culture, especially for Escherichia coli. African giant pouched rats showed superiority for diagnosing tuberculosis over microscopy, but inferiority to culture/molecular methods. Several approaches for detecting malaria by analysing host skin odour or exhaled breath have been explored successfully. Some microbial infections produce specific volatile organic compounds (VOCs), which can be analysed by spectrometry, metabolomics or other analytical approaches to replace animal sniffing.

IMPLICATIONS

The results of sniffing animal studies are fascinating, and animal sniffing can provide intermediate diagnostic solutions for some infectious diseases. Lack of reproducibility, and cost of animal training and housing are major drawbacks for wider implementation of sniffing animals. The ultimate goal is to understand the biological background of this animal ability and to characterize the specific VOCs that animals are recognizing. VOC identification, improvement of odour sampling methods and development of point-of-care instruments could allow implementation of scent-based tests for major human pathogens.

NMR-Metabolomics Shows That BolA Is an Important Modulator of Salmonella Typhimurium Metabolic Processes under Virulence Conditions

BolA is a ubiquitous global transcription factor. Despite its clear role in the induction of important stress-resistant physiological changes and its recent implication in the virulence of Salmonella, further research is required to shed light on the pathways modulated by BolA. In this study, we resorted to untargeted ¹H-NMR metabolomics to understand the impact of BolA on the metabolic profile of Salmonella Typhimurium, under virulence conditions. Three strains of S. Typhimurium SL1344 were studied: An SL1344 strain transformed with an empty plasmid (control), a bolA knockout mutant (ΔbolA), and a strain overexpressing bolA (bolA⁺). These strains were grown in a minimal virulence-inducing medium and cells were collected at the end of the exponential and stationary phases. The extracts were analyzed by NMR, and multivariate and univariate statistical analysis were performed to identify significant alterations. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of ¹H-NMR data allowed the discrimination between the metabolic profiles of these strains, revealing increased levels of acetate, valine, alanine, NAD⁺, succinate, coenzyme A, glutathione, and putrescine in bolA⁺. These results indicate that BolA regulates pathways related to stress resistance and virulence, being an important modulator of the metabolic processes needed for S. Typhimurium infection.

An Optimistic Vision of Future: Diagnosis of Bacterial Infections by Sensing Their Associated Volatile Organic Compounds

Simple tests using sniff analysis that have the ability of diagnosing and rapidly distinguishing between infections due to different bacteria are urgently required by medical community worldwide. Professionals interested in this topic wish for these tests to be simultaneously cheap, fast, easily applicable, non-invasive, robust, reliable, and sensitive. Current analytical instrumentation has already the ability for performing real time (minutes or a few dozens of minutes) analysis of volatile bacterial biomarkers (the VOCs emitted by bacteria). Although many articles are available, a review displaying an objective evaluation of the current status in the field is still needed. This review tries to present an overview regarding the bacterial biomarkers released from in vitro cultivation of various bacterial strains and also from different biological matrices investigated, over the last 10 years. We have described results of relevant studies, which used modern analytical techniques to evaluate specific biomarker profiles associated with bacterial infections. Our purpose was to present a comprehensive view of available possibilities for detection of emitted bacterial VOCs from different matrices. We intend that this review to be of general interest for both medical doctors and for all researchers preoccupied with bacterial infectious diseases and their rapid diagnosis using analytical instrumentation.

Profiles of volatile indole emitted by Escherichia coli based on CDI-MS

Escherichia coli is an important pathogen of nosocomial infection in clinical research, Thus, exploring new methods for the rapid detection of this pathogen is urgent. We reported the early release of molecular volatile indole vapour of E. coli cultures and blood cultures analyzed by direct atmospheric corona discharge ionization mass spectrometry (CDI-MS). The concentration of indole in E. coli cultures remarkably increases during the early log and lag phases of bacterial growth, thereby enabling early detection. Technical replicates were cultivated for 3 days for reference diagnosis using current conventional bacteraemia detection. A reference MS screen of common microbes from other genera confirmed that the peaks at m/z 116 signal corresponded to indole were specifically present in E. coli. Our results indicated that volatile indole based on CDI-MS without the need for any sample pretreatment is highly suitable for the reliable and cost-efficient differentiation of E. coli, especially for bacteraemia in humans.

In-situ headspace analysis of metabolic carbon dioxide of aerobic bacteria for assessing antimicrobial activity of natural products

Headspace analysis of the volatile metabolites has been used as a good strategy for monitoring the microbial growth in several applications, but never been established for the evaluation of the activity of microbial inhibitor in the field of drug screening from natural products. We report on a new method for the determination of antimicrobial activity of drug compounds or crude extracts from natural products by measuring the amount of metabolic carbon dioxide produced in the drug-bacteria incubation system. 2 mL of medium containing bacteria and drug of interest was incubated at 37 °C for 24 h. The amount of metabolic carbon dioxide partitioned in the headspace was measured to evaluate the drug antimicrobial activity using headspace gas chromatography (HS-GC) coupled with thermal conductive detector (TCD). The principle and the standard procedure of the present method have been developed and verified. As a result, the precision of the present method was less than 4% (expressed as relative standard deviation), and an excellent agreement was found on both inhibition rate (R² = 0.935) and the half inhibition concentration (R² = 0.994) between the present method and a reference method (optical density method). By comparison, the present method is simpler and safer regarding the microorganism contamination due to the in-situ incubation and detection in the closed system, and suitable for the routine analysis of antimicrobial activity of natural products with high flexibility in both bacterial strains and sample properties.

Sensors' array of aspiration ion mobility spectrometer as a tool for bacteria discrimination

The possibility of achieving bacterial discrimination using a miniaturized aspiration ion mobility spectrometer model ChemPro-100i (Environics Oy) has been tested by interrogating the headspace air samples above in vitro bacterial cultures of three species - Escherichia coli, Bacillus subtilis and Staphylococcus aureus, respectively. The ChemPro-100i highly integrated seven sensor array, composed of one a-IMS cell, three MOS (metal oxide sensors), one FET (field effect transistor) sensor and two SC (semiconductor) sensors, provided enough analytical information to discriminate between the three bacterial species. Statistical data processing using either principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) was accomplished. We concluded that although the data from the aspiration-type ion mobility sensor, with its 16 ion detectors, is absolutely sufficient to discriminate between various bacteria using their volatile compounds' chemical profile, the other six sensors deliver additional, valuable information.

Standardization procedures for real-time breath analysis by secondary electrospray ionization high-resolution mass spectrometry

Despite the attractiveness of breath analysis as a non-invasive means to retrieve relevant metabolic information, its introduction into routine clinical practice remains a challenge. Among all the different analytical techniques available to interrogate exhaled breath, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) offers a number of advantages (e.g., real-time, yet wide, metabolome coverage) that makes it ideal for untargeted and targeted studies. However, so far, SESI-HRMS has relied mostly on lab-built prototypes, making it difficult to standardize breath sampling and subsequent analysis, hence preventing further developments such as multi-center clinical studies. To address this issue, we present here a number of new developments. In particular, we have characterized a new SESI interface featuring real-time readout of critical exhalation parameters such as CO₂, exhalation flow rate, and exhaled volume. Four healthy subjects provided breath specimens over a period of 1 month to characterize the stability of the SESI-HRMS system. A first assessment of the repeatability of the system using a gas standard revealed a coefficient of variation (CV) of 2.9%. Three classes of aldehydes, namely 4-hydroxy-2-alkenals, 2-alkenals and 4-hydroxy-2,6-alkedienals―hypothesized to be markers of oxidative stress―were chosen as representative metabolites of interest to evaluate the repeatability and reproducibility of this breath analysis analytical platform. Median and interquartile ranges (IQRs) of CVs for CO₂, exhalation flow rate, and exhaled volume were 3.2% (1.5%), 3.1% (1.9%), and 5.0% (4.6%), respectively. Despite the high repeatability observed for these parameters, we observed a systematic decay in the signal during repeated measurements for the shorter fatty aldehydes, which eventually reached a steady state after three/four repeated exhalations. In contrast, longer fatty aldehydes showed a steady behavior, independent of the number of repeated exhalation maneuvers. We hypothesize that this highly molecule-specific and individual-independent behavior may be explained by the fact that shorter aldehydes (with higher estimated blood-to-air partition coefficients; approaching 100) mainly get exchanged in the airways of the respiratory system, whereas the longer aldehydes (with smaller estimated blood-to-air partition coefficients; approaching 10) are thought to exchange mostly in the alveoli. Exclusion of the first three exhalations from the analysis led to a median CV (IQR) of 6.7 % (5.5 %) for the said classes of aldehydes. We found that such intra-subject variability is in general much lower than inter-subject variability (median relative differences between subjects 48.2%), suggesting that the system is suitable to capture such differences. No batch effect due to sampling date was observed, overall suggesting that the intra-subject variability measured for these series of aldehydes was biological rather than technical. High correlations found among the series of aldehydes support this notion. Finally, recommendations for breath sampling and analysis for SESI-HRMS users are provided with the aim of harmonizing procedures and improving future inter-laboratory comparisons.

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.

Profiling of headspace volatiles from Escherichia coli cultures using silicone-based sorptive media and thermal desorption GC-MS

Headspace sorptive extraction technique using silicone based sorptive media coated stir bars is used for the first time here to extract, identify, and quantify heavy volatile organic compounds present in Escherichia coli culture headspace. Detection of infection presence is largely accomplished in laboratories through physical sampling and subsequent growth of cultures for biochemical testing. The use of volatile biomarkers released from pathogens as indicators for pathogenic presence can vastly reduce the time needed whilst improving the success rates for infection detection. To validate this, by using a contactless headspace sorptive extraction technique, the volatile compounds released from E. coli, grown in vitro, have been extracted and identified. Two different sorptive media for extracting these headspace volatiles were compared in this study and the identified volatiles were quantified. The large phase volume and wider retention of this sorptive technique compared to traditional sampling approach enabled preconcentration and collection of wider range of volatiles towards developing an extensive database of such heavy volatiles associated with E. coli. This supplements the existing data of potential bacterial markers and use of internal standards in these tests allows semi-quantitative estimation of these compounds towards the development and optimization of novel pathogen sensing devices.

Application of Electronic-Nose Technologies and VOC-Biomarkers for the Noninvasive Early Diagnosis of Gastrointestinal Diseases †

Conventional methods utilized for clinical diagnosis of gastrointestinal (GI) diseases have employed invasive medical procedures that cause stress, anxiety and pain to patients. These methods are often expensive, time-consuming, and require sophisticated chemical-analysis instruments and advanced modeling procedures to achieve diagnostic interpretations. This paper reviews recent applications of simpler, electronic-nose (e-nose) devices for the noninvasive early diagnosis of a wide range of GI diseases by collective analysis of headspace volatile organic compound (VOC)-metabolites from clinical samples to produce disease-specific aroma signatures (VOC profiles). A different "metabolomics" approach to GI disease diagnostics, involving identifications and quantifications of disease VOC-metabolites, are compared to the electronic-nose approach based on diagnostic costs, accuracy, advantages and disadvantages. The importance of changes in gut microbiome composition that result from disease are discussed relative to effects on disease detection. A new diagnostic approach, which combines the use of e-nose instruments for early rapid prophylactic disease-screenings with targeted identification of known disease biomarkers, is proposed to yield cheaper, quicker and more dependable diagnostic results. Some priority future research needs and coordination for bringing e-nose instruments into routine clinical practice are summarized.

Validation of biofilm formation on human skin wound models and demonstration of clinically translatable bacteria-specific volatile signatures

Biofilms are major contributors to delayed wound healing and there is a need for clinically relevant experimental models to assess theranostics. Microorganisms release volatile organic compounds (VOCs) and the ability to identify these in infected cutaneous wounds could lead to efficient non-invasive diagnosis. The aims here were to develop and assess bacterial biofilm formation and identify their VOC profiles in an in vitro model and validate in human ex vivo incisional and excisional cutaneous wound models. Biofilm development was assessed using multiple microscopy techniques with biofilm-forming deficient controls and quantified using metabolic and biomass assays; and VOC production measured by gas chromatography-mass spectrometry. The production of most VOCs was affected by biofilm development and model used. Some VOCs were specific either for planktonic or biofilm growth. The relative abundance of some VOCs was significantly increased or decreased by biofilm growth phase (P < 0.05). Some Staphylococcus aureus and Pseudomonas aeruginosa VOCs correlated with biofilm metabolic activity and biomass (R ≤ −0.5; ≥0.5). We present for the first time bacterial biofilm formation in human ex vivo cutaneous wound models and their specific VOC profiles. These models provide a vehicle for human skin-relevant biofilm studies and VOC detection has potential clinical translatability in efficient non-invasive diagnosis of wound infection.