Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Rapid differentiation of cystic fibrosis-related bacteria via reagentless atmospheric pressure photoionisation mass spectrometry

Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person's lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein, we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified, including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry

BACKGROUND

Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).

OBJECTIVE

To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.

METHODS

102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z).

RESULTS

PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing.

CONCLUSION

PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

Combining Thermal Desorption with Selected Ion Flow Tube Mass Spectrometry for Analyses of Breath Volatile Organic Compounds

An instrument integrating thermal desorption (TD) to selected ion flow tube mass spectrometry (SIFT-MS) is presented, and its application to analyze volatile organic compounds (VOCs) in human breath is demonstrated for the first time. The rationale behind this development is the need to analyze breath samples in large-scale multicenter clinical projects involving thousands of patients recruited in different hospitals. Following adapted guidelines for validating analytical techniques, we developed and validated a targeted analytical method for 21 compounds of diverse chemical class, chosen for their clinical and biological relevance. Validation has been carried out by two independent laboratories, using calibration standards and real breath samples from healthy volunteers. The merging of SIFT-MS and TD integrates the rapid analytical capabilities of SIFT-MS with the capacity to collect breath samples across multiple hospitals. Thanks to these features, the novel instrument has the potential to be easily employed in clinical practice.

Real-time breath analysis towards a healthy human breath profile

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant (p< 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

Breath biomarkers in Non-Carcinogenic diseases

The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.

Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma

Introduction: There is a need to improve the diagnosis and management of pediatric asthma. Breath analysis aims to address this by non-invasively assessing altered metabolism and disease-associated processes. Our goal was to identify exhaled metabolic signatures that distinguish children with allergic asthma from healthy controls using secondary electrospray ionization high-resolution mass spectrometry (SESI/HRMS) in a cross-sectional observational study. Methods: Breath analysis was performed with SESI/HRMS. Significant differentially expressed mass-to-charge features in breath were extracted using the empirical Bayes moderated t-statistics test. Corresponding molecules were putatively annotated by tandem mass spectrometry database matching and pathway analysis. Results: 48 allergic asthmatics and 56 healthy controls were included in the study. Among 375 significant mass-to-charge features, 134 were putatively identified. Many of these could be grouped to metabolites of common pathways or chemical families. We found several pathways that are well-represented by the significant metabolites, for example, lysine degradation elevated and two arginine pathways downregulated in the asthmatic group. Assessing the ability of breath profiles to classify samples as asthmatic or healthy with supervised machine learning in a 10 times repeated 10-fold cross-validation revealed an area under the receiver operating characteristic curve of 0.83. Discussion: For the first time, a large number of breath-derived metabolites that discriminate children with allergic asthma from healthy controls were identified by online breath analysis. Many are linked to well-described metabolic pathways and chemical families involved in pathophysiological processes of asthma. Furthermore, a subset of these volatile organic compounds showed high potential for clinical diagnostic applications.

A gas-phase standard delivery system for direct breath analysis

Applications for direct breath analysis by mass spectrometry (MS) are rapidly expanding. One of the more recent mass spectrometry-based approaches is secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). Despite increasing usage, the SESI methodology still lacks standardization procedures for quality control and absolute quantification. In this study, we designed and evaluated a custom-built standard delivery system tailored for direct breath analysis. The system enables the simultaneous introduction of multiple gas-phase standard compounds into ambient MS setups in the lower parts-per-million (ppm) to parts-per-billion (ppb) range. To best mimic exhaled breath, the gas flow can be heated (37 °C-40 °C) and humidified (up to 98% relative humidity). Inter-laboratory comparison of the system included various SESI-HRMS setups, i.e. an Orbitrap and a quadrupole time-of-flight mass spectrometer (QTOF), and using both single- as well as multi-component standards. This revealed highly stable and reproducible performances with between-run variation <19% and within-run variation <20%. Independent calibration runs demonstrated high accuracy (96%-111%) and precision (>95%) for the single-compound standard acetone, while compound-specific performances were obtained for the multi-component standard. Similarly, the sensitivity varied for different compounds within the multi-component standard across all SESI-Orbitrap and -QTOF setups, yielding limits of detections from 3.1 ppb (forp-xylene) to 0.05 ppb (for 1,8-cineol). Routinely applying the standard system throughout several weeks, allowed us to monitor instrument stability and to identify technical outliers in exhaled breath measurements. Such routine deployment of standards would significantly improve data quality and comparability, which is especially important in longitudinal and multi-center studies. Furthermore, performance validation of the system demonstrated its suitability for reliable absolute quantification while it illustrated compound-dependent behavior for SESI.

Effects of a Volatile Organic Compound Filter on Breath Profiles Measured by Secondary Electrospray High-Resolution Mass Spectrometry

Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland−Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.

Identification of Exhaled Metabolites in Children with Cystic Fibrosis

The early detection of inflammation and infection is important to prevent irreversible lung damage in cystic fibrosis. Novel and non-invasive monitoring tools would be of high benefit for the quality of life of patients. Our group previously detected over 100 exhaled mass-to-charge (m/z) features, using on-line secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), which distinguish children with cystic fibrosis from healthy controls. The aim of this study was to annotate as many m/z features as possible with putative chemical structures. Compound identification was performed by applying a rigorous workflow, which included the analysis of on-line MS2 spectra and a literature comparison. A total of 49 discriminatory exhaled compounds were putatively identified. A group of compounds including glycolic acid, glyceric acid and xanthine were elevated in the cystic fibrosis group. A large group of acylcarnitines and aldehydes were found to be decreased in cystic fibrosis. The proposed compound identification workflow was used to identify signatures of volatile organic compounds that discriminate children with cystic fibrosis from healthy controls, which is the first step for future non-invasive and personalized applications.

Membrane inlet mass spectrometry method for food intake impact assessment on specific volatile organic compounds in exhaled breath

This research work describes the development of a novel bioanalytical method for the assessment of food impact on selected exhaled breath volatile organic compounds (VOCs) using a fast and portable screening VOC prototype sensor based on membrane inlet mass spectrometry (MIMS). Method and sensor prototype functionality was verified by obtaining good response times, linearity in the examined concentration ranges, and sensitivity and repeatability for several breath VOCs—acetone, ethanol, n-pentane, and isoprene. A new VOC sensor prototype was also proven to be sensitive enough for selected breath VOC quantification with limits of detection at low part per billion (ppb) levels—5 ppb for n-pentane, 10 ppb for acetone and ethanol, and 25 ppb for isoprene. Food impact assessment was accomplished by tracking the levels of acetone, ethanol, n-pentane, and isoprene in exhaled breath samples collected from 50 healthy participants before the meal and 60 min and 120 min after the meal. For acetone, isoprene, and n-pentane, a larger impact was noticed 120 min after the meal, while for ethanol, it was after 60 min. Obtained VOC levels were in the expected concentration ranges. Mean values at all time points were ~ 500–900 ppb for acetone and ~ 400–600 ppb for ethanol. Most of the results for n-pentane were below 5 ppb, but the mean value for those which were detected was ~ 30 ppb. Along with samples, data about participants’ lifestyle were collected via a short questionnaire, which were compared against obtained VOC levels in order to reveal some significant correlations between habits of participants and their breath VOC levels.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review

Introduction

An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.

Methods

The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.

Results

Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.

Discussion

Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Breathing new life into clinical testing and diagnostics: perspectives on volatile biomarkers from breath

Human breath offers several benefits for diagnostic applications, including simple, noninvasive collection. Breath is a rich source of clinically-relevant biological information; this includes a volatile fraction, where greater than 1,000 volatile organic compounds (VOCs) have been described so far, and breath aerosols that carry nucleic acids, proteins, signaling molecules, and pathogens. Many of these factors, especially VOCs, are delivered to the lung by the systemic circulation, and diffusion of candidate biomarkers from blood into breath allows systematic profiling of organismal health. Biomarkers on breath offer the capability to advance early detection and precision medicine in areas of global clinical need. Breath tests are noninvasive and can be performed at home or in a primary care setting, which makes them well-suited for the kind of public screening program that could dramatically improve the early detection of conditions such as lung cancer. Since measurements of VOCs on breath largely report on metabolic changes, this too aids in the early detection of a broader range of illnesses and can be used to detect metabolic shifts that could be targeted through precision medicine. Furthermore, the ability to perform frequent sampling has envisioned applications in monitoring treatment responses. Breath has been investigated in respiratory, liver, gut, and neurological diseases and in contexts as diverse as infectious diseases and cancer. Preclinical research studies using breath have been ongoing for some time, yet only a few breath-based diagnostics tests are currently available and in widespread clinical use. Most recently, tests assessing the gut microbiome using hydrogen and methane on breath, in addition to tests using urea to detect Helicobacter pylori infections have been released, yet there are many more applications of breath tests still to be realized. Here, we discuss the strengths of breath as a clinical sampling matrix and the technical challenges to be addressed in developing it for clinical use. Historically, a lack of standardized methodologies has delayed the discovery and validation of biomarker candidates, resulting in a proliferation of early-stage pilot studies. We will explore how advancements in breath collection and analysis are in the process of driving renewed progress in the field, particularly in the context of gastrointestinal and chronic liver disease. Finally, we will provide a forward-looking outlook for developing the next generation of clinically relevant breath tests and how they may emerge into clinical practice.

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) fingerprinting enabled treatment monitoring of pulmonary carcinoma cells in real time

Lung cancer is one of the leading causes of cancer related deaths in the United States. A novel volatile analysis platform is needed to complement current diagnostic techniques and better elucidate chemical signatures of lung cancer and subsequent treatments. A systems biology bottom-up approach using cell culture volatilomics was employed to identify pathological volatile fingerprints of lung cancer in real time. An advanced secondary electrospray ionization (SESI) source, named SuperSESI was used in this study and directly attached to a Thermo Q-Exactive high-resolution mass spectrometer (HRMS). We performed a series of experiments to determine if our optimized SESI-HRMS platform can distinguish between cancer types by sampling their in vitro volatilome profiles. We detected 60 significant volatile organic compound (VOC) features in positive mode that were deemed of cancer cell origin. The cell derived features were used for subsequent analyses to distinguish between our two studied lung cancer types, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Partial least squares-discriminant analysis (PLS-DA) model revealed a good separation of the two cancer types, suggesting unique chemical composition of their headspace profiles. A receiver operating characteristic (ROC) curve using 10 prominent features was used to predict disease type, with an area under the curve (AUC) of 0.811. Cultures were also treated with cisplatin to determine the feasibility of classifying drug treatment from expelled gases. A PLS-DA model revealed independent clustering based on their headspace profiles. An ROC curve using the top features driving separation of PLS-DA model suggested good accuracy with an AUC of 1. It is thus possible to benefit from the advantages of this platform to distinguish the unique volatile fingerprints of cancers to uncover potential biomarkers for cancer type differentiation and treatment monitoring.

Hyphenated Mass Spectrometry versus Real-Time Mass Spectrometry Techniques for the Detection of Volatile Compounds from the Human Body

Mass spectrometry (MS) is an analytical technique that can be used for various applications in a number of scientific areas including environmental, security, forensic science, space exploration, agri-food, and numerous others. MS is also continuing to offer new insights into the proteomic and metabolomic fields. MS techniques are frequently used for the analysis of volatile compounds (VCs). The detection of VCs from human samples has the potential to aid in the diagnosis of diseases, in monitoring drug metabolites, and in providing insight into metabolic processes. The broad usage of MS has resulted in numerous variations of the technique being developed over the years, which can be divided into hyphenated and real-time MS techniques. Hyphenated chromatographic techniques coupled with MS offer unparalleled qualitative analysis and high accuracy and sensitivity, even when analysing complex matrices (breath, urine, stool, etc.). However, these benefits are traded for a significantly longer analysis time and a greater need for sample preparation and method development. On the other hand, real-time MS techniques offer highly sensitive quantitative data. Additionally, real-time techniques can provide results in a matter of minutes or even seconds, without altering the sample in any way. However, real-time MS can only offer tentative qualitative data and suffers from molecular weight overlap in complex matrices. This review compares hyphenated and real-time MS methods and provides examples of applications for each technique for the detection of VCs from humans.

Breath-Taking Perspectives and Preliminary Data toward Early Detection of Chronic Liver Diseases

The gold standard method for chronic liver diseases diagnosis and staging remains liver biopsy, despite the spread of less invasive surrogate modalities based on imaging and blood biomarkers. Still, more than 50% of chronic liver disease cases are detected at later stages when patients exhibit episodes of liver decompensation. Breath analysis represents an attractive means for the development of non-invasive tests for several pathologies, including chronic liver diseases. In this perspective review, we summarize the main findings of studies that compared the breath of patients with chronic liver diseases against that of control subjects and found candidate biomarkers for a potential breath test. Interestingly, identified compounds with best classification performance are of exogenous origin and used as flavoring agents in food. Therefore, random dietary exposure of the general population to these compounds prevents the establishment of threshold levels for the identification of disease subjects. To overcome this limitation, we propose the exogenous volatile organic compounds (EVOCs) probe approach, where one or multiple of these flavoring agent(s) are administered at a standard dose and liver dysfunction associated with chronic liver diseases is evaluated as a washout of ingested compound(s). We report preliminary results in healthy subjects in support of the potential of the EVOC Probe approach.

Optimizing Secondary Electrospray Ionization High-Resolution Mass Spectrometry (SESI-HRMS) for the Analysis of Volatile Fatty Acids from Gut Microbiome

Gut microbiota plays essential roles in maintaining gut homeostasis. The composition of gut microbes and their metabolites are altered in response to diet and remedial agents such as antibiotics. However, little is known about the effect of antibiotics on the gut microbiota and their volatile metabolites. In this study, we evaluated the impact of a moderate level of ampicillin treatment on volatile fatty acids (VFAs) of gut microbial cultures using an optimized real-time secondary electrospray ionization coupled with high-resolution mass spectrometry (SESI-HRMS). To evaluate the ionization efficiency, different types of electrospray solvents and concentrations of formic acid as an additive (0.01, 0.05, and 0.1%, v/v) were tested using VFAs standard mixture (C2-C7). As a result, the maximum SESI-HRMS signals of all studied m/z values were observed from water with 0.01% formic acid than those from the aqueous methanolic solutions. Optimal temperatures of sample inlet and ion chamber were set at 130 °C and 85 °C, respectively. SESI spray pressure at 0.5 bar generated the maximum intensity than other tested values. The optimized SESI-HRMS was then used for the analysis of VFAs in gut microbial cultures. We detected that the significantly elevated C4 and C7 VFAs in the headspace of gut microbial cultures six hours after ampicillin treatment (1 mg/L). In conclusion, our results suggested that the optimized SESI-HRMS method can be suitable for the analysis of VFAs from gut microbes in a rapid, sensitive, and non-invasive manner.

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.